From 60bfbe2671ed2bbd327e6a84cf8c504b0aeadc82 Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Thu, 10 Jul 2025 12:06:55 +0100
Subject: [PATCH 1/9] test(python_api): add Python API test suite

- Add `tests/test_python_api.hjson` manifest listing model specs for models from ML Zoo
- Implement test script `tests/test_python_api.py` with full test suite for testing the Python API

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 tests/test_python_api.hjson |  62 +++++++
 tests/test_python_api.py    | 333 ++++++++++++++++++++++++++++++++++++
 2 files changed, 395 insertions(+)
 create mode 100644 tests/test_python_api.hjson
 create mode 100644 tests/test_python_api.py

diff --git a/tests/test_python_api.hjson b/tests/test_python_api.hjson
new file mode 100644
index 0000000..2111485
--- /dev/null
+++ b/tests/test_python_api.hjson
@@ -0,0 +1,62 @@
+#
+# SPDX-FileCopyrightText: Copyright 2025 Arm Limited and/or its affiliates <open-source-office@arm.com>
+#
+# SPDX-License-Identifier: Apache-2.0
+#
+
+# Model manifest for Python API tests.
+# Each entry must include:
+#   - name: a unique identifier for the model spec
+#   - path: the relative model path in the ML Zoo repository
+
+[
+  {
+    "name": "ad_small_int8",
+    "path": "models/anomaly_detection/micronet_small/tflite_int8/ad_small_int8.tflite"
+  },
+  {
+    "name": "ds_cnn_s_quantized_int16",
+    "path": "models/keyword_spotting/ds_cnn_small/model_package_tf/model_archive/TFLite/tflite_int16/ds_cnn_s_quantized_int16.tflite"
+  },
+  {
+    "name": "kws_micronet_s",
+    "path": "models/keyword_spotting/micronet_small/tflite_int8/kws_micronet_s.tflite"
+  },
+  {
+    "name": "tiny_wav2letter_pruned_int8",
+    "path": "models/speech_recognition/tiny_wav2letter/tflite_pruned_int8/tiny_wav2letter_pruned_int8.tflite"
+  },
+  {
+    "name": "yolov3_tiny_int8_pruned_backbone_only",
+    "path": "models/experimental/yolov3_tiny_int8_pruned_backbone_only/yolov3_tiny_int8_pruned_backbone_only.tflite"
+  },
+  {
+    "name": "cnn_s_quantized",
+    "path": "models/keyword_spotting/cnn_small/model_package_tf/model_archive/TFLite/tflite_int8/cnn_s_quantized.tflite"
+  },
+  {
+    "name": "efficientnet_lite0_224",
+    "path": "models/experimental/efficientnet_lite0_224/efficientnet_lite0_224.tflite"
+  },
+  {
+    "name": "mobilenet_v2_1.0_224_quantized_1_default_1",
+    "path": "models/image_classification/mobilenet_v2_1.0_224/tflite_uint8/mobilenet_v2_1.0_224_quantized_1_default_1.tflite"
+  },
+  {
+    "name": "vww4_128_128_INT8",
+    "path": "models/visual_wake_words/micronet_vww4/tflite_int8/vww4_128_128_INT8.tflite"
+  },
+  {
+    "name": "dnn_s_quantized",
+    "path": "models/keyword_spotting/dnn_small/model_package_tf/model_archive/TFLite/tflite_int8/dnn_s_quantized.tflite"
+  },
+  {
+    "name": "har_int8",
+    "path": "models/experimental/har_cnn/har_int8.tflite"
+  },
+  {
+    "name": "ssd_mobilenet_v3_int8",
+    "path": "models/experimental/ssd_mobilenet_v3_int8/ssd_mobilenet_v3_int8.tflite"
+  },
+
+]
diff --git a/tests/test_python_api.py b/tests/test_python_api.py
new file mode 100644
index 0000000..a2fce6a
--- /dev/null
+++ b/tests/test_python_api.py
@@ -0,0 +1,333 @@
+#
+# SPDX-FileCopyrightText: Copyright 2025 Arm Limited and/or its affiliates <open-source-office@arm.com>
+#
+# SPDX-License-Identifier: Apache-2.0
+#
+"""
+Test suite for the `tosa-converter-for-tflite` Python API.
+
+To run tests with logging:
+    TOSA_TEST_ELIDE=1 pytest tests/test_python_api.py -v --log-cli-level=DEBUG
+
+To add a new model spec:
+  1. Edit `tests/test_python_api.hjson`, adding an entry with:
+       - name (str): unique spec identifier
+       - path (str): relative model path in Arm ML Zoo repo
+  2. Place the corresponding golden MLIR file under `tests/gold/test_python_api/<name>.mlir`, normalised for whitespace.
+
+Tests cover:
+  - File based & stream based conversion
+  - Bytecode vs text output via `TosaConverterOutputFormat`
+  - MLIR text regression
+  - Error cases: invalid sink types, truncated inputs, invalid format args
+  - Pre-commit sanity checks
+"""
+import io
+import logging
+import os
+import shutil
+import subprocess
+from functools import lru_cache
+from pathlib import Path
+from typing import Any
+from typing import Dict
+from typing import List
+
+import hjson
+import pytest
+from tosa_converter_for_tflite import tflite_flatbuffer_to_tosa_mlir
+from tosa_converter_for_tflite import TosaConverterOutputFormat
+
+# -----------------------------------------------------------------------------
+# Logger configuration
+# -----------------------------------------------------------------------------
+logger = logging.getLogger(__name__)
+
+# -----------------------------------------------------------------------------
+# Constants & paths
+# -----------------------------------------------------------------------------
+TEST_ROOT: Path = Path(__file__).parent
+MANIFEST_FILE: Path = TEST_ROOT / "test_python_api.hjson"
+GOLDEN_DIR: Path = TEST_ROOT / "gold" / "test_python_api"
+GENERATED_DIR: Path = TEST_ROOT / "generated" / "test_python_api"
+# Model-Zoo repo details
+MODEL_ZOO_REPO_DIR_PATH: str = os.environ.get("MODEL_ZOO_REPO_DIR_PATH")
+MODEL_ZOO_REPO_URL: str = "https://github.com/Arm-Examples/ML-zoo.git"
+MODEL_ZOO_BRANCH: str = "master"
+MODEL_ZOO_REPO_DIR_NAME: str = "ml_zoo_repo"
+
+
+# -----------------------------------------------------------------------------
+# Helper functions
+# -----------------------------------------------------------------------------
+@lru_cache
+def load_manifest() -> List[Dict[str, Any]]:
+    """Parse the model manifest file into a list of dictionaries."""
+    text = MANIFEST_FILE.read_text(encoding="utf-8")
+    specs = hjson.loads(text)
+    logger.debug(f"Loaded {len(specs)} specs from manifest")
+    return specs
+
+
+def normalise_lines(lines: List[str]) -> List[str]:
+    """Strip trailing whitespace, drop blank lines."""
+    normalised = []
+    for ln in lines:
+        # Strip trailing whitespace
+        ln = ln.rstrip()
+        # Skip blank lines
+        if ln:
+            normalised.append(ln)
+    return normalised
+
+
+def assert_mlir_matches_golden(name: str, gen_path: Path) -> None:
+    """
+    Compare generated MLIR file to golden, after normalization.
+    Always copy generated MLIR to GENERATED_DIR for missing or mismatched cases.
+    """
+    golden_path = GOLDEN_DIR / f"{name}.mlir"
+    dump_path = GENERATED_DIR / f"{name}.mlir"
+
+    # If golden missing or content mismatched, dump and report
+    if not golden_path.exists():
+        shutil.copy(gen_path, dump_path)
+        pytest.fail(
+            f"Golden MLIR missing for '{name}'; generated file dumped to {dump_path}"
+        )
+
+    gold_lines = normalise_lines(golden_path.read_text().splitlines())
+    gen_lines = normalise_lines(gen_path.read_text().splitlines())
+    if gen_lines != gold_lines:
+        shutil.copy(gen_path, dump_path)
+        logger.error(f"MLIR regression detected for '{name}'")
+        pytest.fail(f"MLIR regression for '{name}'; see dumped file {dump_path}")
+
+    logger.debug(f"MLIR matches golden for '{name}'")
+    # Clean up any leftover dump
+    dump_path.unlink(missing_ok=True)
+
+
+# -----------------------------------------------------------------------------
+# Parametrise specs dynamically
+# -----------------------------------------------------------------------------
+def pytest_generate_tests(metafunc: pytest.Metafunc) -> None:
+    """Parametrise all tests that accept 'spec' with entries from the manifest."""
+    if "spec" in metafunc.fixturenames:
+        if not MANIFEST_FILE.is_file():
+            pytest.skip(f"Manifest not found at {MANIFEST_FILE}")
+        specs = load_manifest()
+        ids = [s.get("name", "<unknown>") for s in specs]
+        metafunc.parametrize("spec", specs, ids=ids)
+
+
+# -----------------------------------------------------------------------------
+# Session scoped fixtures
+# -----------------------------------------------------------------------------
+@pytest.fixture(scope="session")
+def manifest() -> List[Dict[str, Any]]:
+    """Session scoped fixture: parsed list of model specs."""
+    return load_manifest()
+
+
+@pytest.fixture(scope="session")
+def tflite_files(
+    tmp_path_factory: pytest.TempPathFactory,
+    manifest: List[Dict[str, Any]],
+) -> Dict[str, Path]:
+    """
+    Get .tflite model files from Model Zoo repo or from MODEL_ZOO_DIR env if provided.
+    Returns mapping spec_name to .tflite Path.
+    """
+    # Use existing repo if provided
+    if MODEL_ZOO_REPO_DIR_PATH:
+        repo_dir = Path(MODEL_ZOO_REPO_DIR_PATH)
+        if not repo_dir.is_dir():
+            pytest.skip(
+                f"MODEL_ZOO_DIR set to '{MODEL_ZOO_REPO_DIR_PATH}', but it is not a directory"
+            )
+        logger.info(f"Using existing Model Zoo at {repo_dir}")
+    else:
+        # Clone into a fresh temp dir
+        repo_dir = tmp_path_factory.mktemp(MODEL_ZOO_REPO_DIR_NAME)
+        subprocess.run(
+            [
+                "git",
+                "clone",
+                f"--branch={MODEL_ZOO_BRANCH}",
+                "--depth=1",
+                MODEL_ZOO_REPO_URL,
+                str(repo_dir),
+            ],
+            check=True,
+        )
+        subprocess.run(
+            ["git", "-C", str(repo_dir), "sparse-checkout", "init", "--cone"],
+            check=True,
+        )
+        dirs_to_include = sorted({Path(spec["path"]).parent for spec in manifest})
+        subprocess.run(
+            ["git", "-C", str(repo_dir), "sparse-checkout", "set", *dirs_to_include],
+            check=True,
+        )
+
+    # Build index of available models
+    models = {p.stem: p for p in repo_dir.rglob("*.tflite")}
+    mapping: Dict[str, Path] = {}
+    missing: List[str] = []
+    for spec in manifest:
+        name = spec["name"]
+        model_path = models.get(name)
+        if not model_path:
+            missing.append(name)
+        else:
+            mapping[name] = model_path
+            logger.debug("Selected model %s at %s", name, model_path)
+    if missing:
+        logger.warning("Skipping missing models: %s", missing)
+    return mapping
+
+
+@pytest.fixture(autouse=True, scope="session")
+def clear_generated_dir() -> None:
+    """Clean or create the generated_mlir directory once before any tests run."""
+    if GENERATED_DIR.exists():
+        shutil.rmtree(GENERATED_DIR)
+    GENERATED_DIR.mkdir(parents=True, exist_ok=True)
+    logger.debug(f"Prepared clean generated directory at {GENERATED_DIR}")
+
+
+# -----------------------------------------------------------------------------
+# Module scoped fixtures
+# -----------------------------------------------------------------------------
+@pytest.fixture(scope="module")
+def sample_tflite_file(
+    manifest: List[Dict[str, Any]], tflite_files: Dict[str, Path]
+) -> Path:
+    """
+    Pick one model from the manifest (the first) and return its .tflite path.
+    """
+    name = manifest[0]["name"]
+    return tflite_files[name]
+
+
+# -----------------------------------------------------------------------------
+# Function scoped fixtures
+# -----------------------------------------------------------------------------
+@pytest.fixture
+def tflite_file(spec: Dict[str, Any], tflite_files: Dict[str, Path]) -> Path:
+    """Lookup the prebuilt .tflite for this spec, skip tests if missing."""
+    name = spec["name"]
+    if name not in tflite_files:
+        pytest.skip(f"Skipping '{name}': model not available")
+    return tflite_files[name]
+
+
+# -----------------------------------------------------------------------------
+# Tests
+# -----------------------------------------------------------------------------
+@pytest.mark.python_api
+def test_bytecode_filesystem(
+    tmp_path: Path, spec: Dict[str, Any], tflite_file: Path
+) -> None:
+    """Ensure that file based bytecode conversion creates a non empty .tosa.mlirbc file."""
+    out_file = tmp_path / f"{spec['name']}.tosa.mlirbc"
+    logger.info(f"Testing filesystem bytecode output for '{spec['name']}'")
+    tflite_flatbuffer_to_tosa_mlir(str(tflite_file), str(out_file))
+    assert out_file.exists(), "Output file not created"
+    assert out_file.stat().st_size > 0, "Output file is empty"
+    logger.debug(f"Created bytecode file {out_file} ({out_file.stat().st_size} bytes)")
+
+
+@pytest.mark.slow
+@pytest.mark.python_api
+def test_mlir_text_regression(
+    tmp_path: Path, spec: Dict[str, Any], tflite_file: Path
+) -> None:
+    """Generate MLIR text and compare against golden MLIR text files."""
+    name = spec["name"]
+    gen_tmp = tmp_path / f"{name}.mlir"
+    logger.info(f"Testing MLIR text regression for '{name}'")
+    tflite_flatbuffer_to_tosa_mlir(
+        str(tflite_file), str(gen_tmp), TosaConverterOutputFormat.Text
+    )
+    assert gen_tmp.exists(), f"Generated MLIR missing: {gen_tmp}"
+    assert_mlir_matches_golden(name, gen_tmp)
+
+
+@pytest.mark.python_api
+def test_bytecode_stream_vs_filesystem(
+    tmp_path: Path, sample_tflite_file: Path
+) -> None:
+    """Verify that in memory bytecode == file based bytecode and flush() was called."""
+    buf = io.BytesIO()
+    called = False
+
+    def _flush() -> None:
+        nonlocal called
+        called = True
+
+    buf.flush = _flush
+
+    tflite_flatbuffer_to_tosa_mlir(
+        str(sample_tflite_file), buf, TosaConverterOutputFormat.Bytecode
+    )
+    data_stream = buf.getvalue()
+    assert data_stream, "In memory bytecode is empty"
+    assert called, "flush() was not called on the stream"
+
+    fs_path = tmp_path / "sample_fs.tosa.mlirbc"
+    tflite_flatbuffer_to_tosa_mlir(
+        str(sample_tflite_file), str(fs_path), TosaConverterOutputFormat.Bytecode
+    )
+    data_file = fs_path.read_bytes()
+
+    assert data_stream == data_file, "Bytecode mismatch between stream and file"
+
+
+@pytest.mark.python_api
+def test_missing_input_file(tmp_path: Path):
+    """Missing Input file."""
+    bad = tmp_path / "does_not_exist.tflite"
+    with pytest.raises(RuntimeError):
+        tflite_flatbuffer_to_tosa_mlir(str(bad), "missing_input.tosa")
+
+
+@pytest.mark.python_api
+@pytest.mark.parametrize("sink", [123, None, 5.6])
+def test_invalid_sink(sample_tflite_file: Path, sink: Any) -> None:
+    """Passing a non path, non stream sink should raise TypeError."""
+    with pytest.raises(TypeError):
+        tflite_flatbuffer_to_tosa_mlir(str(sample_tflite_file), sink)
+
+
+@pytest.mark.python_api
+def test_truncated_tflite(tmp_path: Path, sample_tflite_file: Path) -> None:
+    """A truncated .tflite input should cause a RuntimeError."""
+    data = sample_tflite_file.read_bytes()
+    trunc = data[: len(data) // 2]
+    trunc_path = tmp_path / "trunc.tflite"
+    trunc_path.write_bytes(trunc)
+    with pytest.raises(RuntimeError):
+        tflite_flatbuffer_to_tosa_mlir(
+            str(trunc_path), str(tmp_path / "truncated_input.tosa.mlirbc")
+        )
+
+
+@pytest.mark.python_api
+@pytest.mark.parametrize("fmt", [123, "bogus", None])
+def test_invalid_format(tmp_path: Path, sample_tflite_file: Path, fmt: Any) -> None:
+    """Passing an invalid format argument should raise TypeError or ValueError."""
+    with pytest.raises((TypeError, ValueError)):
+        tflite_flatbuffer_to_tosa_mlir(
+            str(sample_tflite_file), str(tmp_path / "invalid_format.tosa.mlirbc"), fmt
+        )
+
+
+@pytest.mark.python_api
+@pytest.mark.pre_commit
+def test_precommit_sanity(manifest: List[Dict[str, Any]]) -> None:
+    """Sanity check for pre-commit: manifest must not be empty and API callable."""
+    logger.info("Running pre-commit sanity checks")
+    assert manifest, "Manifest is empty"
+    assert callable(tflite_flatbuffer_to_tosa_mlir), "API function missing"
-- 
GitLab


From 85d35f15c3df44cfe23dcf493bc188e5e7b7e7cf Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Thu, 10 Jul 2025 12:16:49 +0100
Subject: [PATCH 2/9]     test(python_api): add generated textual MLIR gold
 files

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 tests/gold/test_python_api/ad_small_int8.mlir |  84 ++
 .../gold/test_python_api/cnn_s_quantized.mlir | 120 +++
 .../gold/test_python_api/dnn_s_quantized.mlir | 114 ++
 .../ds_cnn_s_quantized_int16.mlir             | 125 +++
 .../efficientnet_lite0_224.mlir               | 528 ++++++++++
 tests/gold/test_python_api/har_int8.mlir      | 117 +++
 .../gold/test_python_api/kws_micronet_s.mlir  | 103 ++
 ...enet_v2_1.0_224_quantized_1_default_1.mlir | 427 ++++++++
 .../ssd_mobilenet_v3_int8.mlir                | 993 ++++++++++++++++++
 .../tiny_wav2letter_pruned_int8.mlir          | 128 +++
 .../test_python_api/vww4_128_128_INT8.mlir    | 514 +++++++++
 ...yolov3_tiny_int8_pruned_backbone_only.mlir | 197 ++++
 12 files changed, 3450 insertions(+)
 create mode 100644 tests/gold/test_python_api/ad_small_int8.mlir
 create mode 100644 tests/gold/test_python_api/cnn_s_quantized.mlir
 create mode 100644 tests/gold/test_python_api/dnn_s_quantized.mlir
 create mode 100644 tests/gold/test_python_api/ds_cnn_s_quantized_int16.mlir
 create mode 100644 tests/gold/test_python_api/efficientnet_lite0_224.mlir
 create mode 100644 tests/gold/test_python_api/har_int8.mlir
 create mode 100644 tests/gold/test_python_api/kws_micronet_s.mlir
 create mode 100644 tests/gold/test_python_api/mobilenet_v2_1.0_224_quantized_1_default_1.mlir
 create mode 100644 tests/gold/test_python_api/ssd_mobilenet_v3_int8.mlir
 create mode 100644 tests/gold/test_python_api/tiny_wav2letter_pruned_int8.mlir
 create mode 100644 tests/gold/test_python_api/vww4_128_128_INT8.mlir
 create mode 100644 tests/gold/test_python_api/yolov3_tiny_int8_pruned_backbone_only.mlir

diff --git a/tests/gold/test_python_api/ad_small_int8.mlir b/tests/gold/test_python_api/ad_small_int8.mlir
new file mode 100644
index 0000000..8794d9e
--- /dev/null
+++ b/tests/gold/test_python_api/ad_small_int8.mlir
@@ -0,0 +1,84 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<1x32x32x1xi8>) -> tensor<1x8xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
+    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %5 = "tosa.const"() <{values = dense<41> : tensor<8xi8>}> : () -> tensor<8xi8>
+    %6 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
+    %7 = "tosa.const"() <{values = dense<29> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %8 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
+    %9 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8x1x1x276xi8>}> : () -> tensor<8x1x1x276xi8>
+    %10 = "tosa.const"() <{values = dense<42> : tensor<276xi8>}> : () -> tensor<276xi8>
+    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi32>}> : () -> tensor<276xi32>
+    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276x1x1x276xi8>}> : () -> tensor<276x1x1x276xi8>
+    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi8>}> : () -> tensor<276xi8>
+    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi32>}> : () -> tensor<276xi32>
+    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x276xi8>}> : () -> tensor<1x3x3x276xi8>
+    %16 = "tosa.const"() <{values = dense<41> : tensor<276xi8>}> : () -> tensor<276xi8>
+    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi32>}> : () -> tensor<276xi32>
+    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi32>}> : () -> tensor<276xi32>
+    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276x1x1x220xi8>}> : () -> tensor<276x1x1x220xi8>
+    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220xi8>}> : () -> tensor<220xi8>
+    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220xi32>}> : () -> tensor<220xi32>
+    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x220xi8>}> : () -> tensor<1x3x3x220xi8>
+    %23 = "tosa.const"() <{values = dense<39> : tensor<220xi8>}> : () -> tensor<220xi8>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220xi32>}> : () -> tensor<220xi32>
+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220xi32>}> : () -> tensor<220xi32>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220x1x1x164xi8>}> : () -> tensor<220x1x1x164xi8>
+    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<164xi32>}> : () -> tensor<164xi32>
+    %28 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x164xi8>}> : () -> tensor<1x3x3x164xi8>
+    %29 = "tosa.const"() <{values = dense<39> : tensor<164xi8>}> : () -> tensor<164xi8>
+    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<164xi32>}> : () -> tensor<164xi32>
+    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<164xi32>}> : () -> tensor<164xi32>
+    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<164x1x1x72xi8>}> : () -> tensor<164x1x1x72xi8>
+    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi8>}> : () -> tensor<72xi8>
+    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
+    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x72xi8>}> : () -> tensor<1x3x3x72xi8>
+    %36 = "tosa.const"() <{values = dense<38> : tensor<72xi8>}> : () -> tensor<72xi8>
+    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
+    %38 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %39 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72x3x3x1xi8>}> : () -> tensor<72x3x3x1xi8>
+    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
+    %42 = "tosa.const"() <{values = dense<11> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %43 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %44 = tosa.conv2d %arg0, %40, %41, %42, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x32x32x1xi8>, tensor<72x3x3x1xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x72xi32>
+    %45 = tosa.rescale %44, %37, %36, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x72xi8>
+    %46 = tosa.clamp %45 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x72xi8>) -> tensor<1x32x32x72xi8>
+    %47 = tosa.reshape %35, %3 : (tensor<1x3x3x72xi8>, !tosa.shape<4>) -> tensor<3x3x72x1xi8>
+    %48 = tosa.depthwise_conv2d %46, %47, %41, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x32x32x72xi8>, tensor<3x3x72x1xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x72xi32>
+    %49 = tosa.rescale %48, %34, %33, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x72xi8>
+    %50 = tosa.clamp %49 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x72xi8>) -> tensor<1x16x16x72xi8>
+    %51 = tosa.conv2d %50, %32, %31, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x72xi8>, tensor<164x1x1x72xi8>, tensor<164xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x164xi32>
+    %52 = tosa.rescale %51, %30, %29, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x164xi32>, tensor<164xi32>, tensor<164xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x164xi8>
+    %53 = tosa.clamp %52 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x164xi8>) -> tensor<1x16x16x164xi8>
+    %54 = tosa.reshape %28, %2 : (tensor<1x3x3x164xi8>, !tosa.shape<4>) -> tensor<3x3x164x1xi8>
+    %55 = tosa.depthwise_conv2d %53, %54, %31, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x16x16x164xi8>, tensor<3x3x164x1xi8>, tensor<164xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x164xi32>
+    %56 = tosa.rescale %55, %27, %29, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x164xi32>, tensor<164xi32>, tensor<164xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x164xi8>
+    %57 = tosa.clamp %56 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x164xi8>) -> tensor<1x16x16x164xi8>
+    %58 = tosa.conv2d %57, %26, %25, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x164xi8>, tensor<220x1x1x164xi8>, tensor<220xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x220xi32>
+    %59 = tosa.rescale %58, %24, %23, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x220xi32>, tensor<220xi32>, tensor<220xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x220xi8>
+    %60 = tosa.clamp %59 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x220xi8>) -> tensor<1x16x16x220xi8>
+    %61 = tosa.reshape %22, %1 : (tensor<1x3x3x220xi8>, !tosa.shape<4>) -> tensor<3x3x220x1xi8>
+    %62 = tosa.depthwise_conv2d %60, %61, %25, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x16x16x220xi8>, tensor<3x3x220x1xi8>, tensor<220xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x220xi32>
+    %63 = tosa.rescale %62, %21, %20, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x220xi32>, tensor<220xi32>, tensor<220xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x220xi8>
+    %64 = tosa.clamp %63 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x220xi8>) -> tensor<1x8x8x220xi8>
+    %65 = tosa.conv2d %64, %19, %18, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x220xi8>, tensor<276x1x1x220xi8>, tensor<276xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x276xi32>
+    %66 = tosa.rescale %65, %17, %16, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x276xi32>, tensor<276xi32>, tensor<276xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x276xi8>
+    %67 = tosa.clamp %66 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x276xi8>) -> tensor<1x8x8x276xi8>
+    %68 = tosa.reshape %15, %0 : (tensor<1x3x3x276xi8>, !tosa.shape<4>) -> tensor<3x3x276x1xi8>
+    %69 = tosa.depthwise_conv2d %67, %68, %18, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x8x8x276xi8>, tensor<3x3x276x1xi8>, tensor<276xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x276xi32>
+    %70 = tosa.rescale %69, %14, %13, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x276xi32>, tensor<276xi32>, tensor<276xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x276xi8>
+    %71 = tosa.clamp %70 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x276xi8>) -> tensor<1x4x4x276xi8>
+    %72 = tosa.conv2d %71, %12, %18, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x276xi8>, tensor<276x1x1x276xi8>, tensor<276xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x276xi32>
+    %73 = tosa.rescale %72, %11, %10, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x276xi32>, tensor<276xi32>, tensor<276xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x276xi8>
+    %74 = tosa.clamp %73 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x276xi8>) -> tensor<1x4x4x276xi8>
+    %75 = tosa.avg_pool2d %74, %43, %43 {acc_type = i32, kernel = array<i64: 4, 4>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x276xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x276xi8>
+    %76 = tosa.conv2d %75, %9, %8, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x276xi8>, tensor<8x1x1x276xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x8xi32>
+    %77 = tosa.rescale %76, %6, %5, %39, %7 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x8xi8>
+    %78 = tosa.reshape %77, %4 : (tensor<1x1x1x8xi8>, !tosa.shape<2>) -> tensor<1x8xi8>
+    return %78 : tensor<1x8xi8>
+  }
+}
diff --git a/tests/gold/test_python_api/cnn_s_quantized.mlir b/tests/gold/test_python_api/cnn_s_quantized.mlir
new file mode 100644
index 0000000..dd1148f
--- /dev/null
+++ b/tests/gold/test_python_api/cnn_s_quantized.mlir
@@ -0,0 +1,120 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.14.0\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<?x490xi8>) -> tensor<?x12xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
+    %0 = "tosa.const"() <{values = dense<35> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %1 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %2 = "tosa.const"() <{values = dense<-1010580540> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %3 = "tosa.const"() <{values = dense<1515870810> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %4 = "tosa.const"() <{values = dense<536870912> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %5 = "tosa.const"() <{values = dense<4> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %6 = "tosa.const"() <{values = dense<12> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %7 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %8 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %9 = "tosa.const"() <{values = dense<9> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %10 = "tosa.const"() <{values = dense<17> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %11 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
+    %12 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %17 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %18 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %19 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %20 = "tosa.const"() <{values = dense<41> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %21 = "tosa.const"() <{values = dense<1201210766> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %22 = "tosa.const"() <{values = dense<34> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %23 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %24 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi32>}> : () -> tensor<12xi32>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12x128xi8>}> : () -> tensor<12x128xi8>
+    %27 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %28 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %29 = "tosa.const"() <{values = dense<1937167208> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %30 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x16xi8>}> : () -> tensor<128x16xi8>
+    %33 = "tosa.const"() <{values = dense<39> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %34 = "tosa.const"() <{values = dense<1331195725> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %35 = "tosa.const"() <{values = dense<-9> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %36 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %37 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1920xi8>}> : () -> tensor<16x1920xi8>
+    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<30xi8>}> : () -> tensor<30xi8>
+    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<30xi32>}> : () -> tensor<30xi32>
+    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<30xi32>}> : () -> tensor<30xi32>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<30x10x4x28xi8>}> : () -> tensor<30x10x4x28xi8>
+    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<28xi8>}> : () -> tensor<28xi8>
+    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<28xi32>}> : () -> tensor<28xi32>
+    %46 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %47 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %48 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %49 = "tosa.const"() <{values = dense<102> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %50 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<28xi32>}> : () -> tensor<28xi32>
+    %51 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<28x10x4x1xi8>}> : () -> tensor<28x10x4x1xi8>
+    %52 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %53 = tosa.reshape %arg0, %52 : (tensor<?x490xi8>, !tosa.shape<4>) -> tensor<?x49x10x1xi8>
+    %54 = tosa.conv2d %53, %51, %50, %49, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x49x10x1xi8>, tensor<28x10x4x1xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x40x7x28xi32>
+    %55 = tosa.rescale %54, %45, %44, %47, %46 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x40x7x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x40x7x28xi8>
+    %56 = tosa.clamp %55 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x40x7x28xi8>) -> tensor<?x40x7x28xi8>
+    %57 = tosa.conv2d %56, %43, %42, %46, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 1>} : (tensor<?x40x7x28xi8>, tensor<30x10x4x28xi8>, tensor<30xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x16x4x30xi32>
+    %58 = tosa.rescale %57, %41, %40, %47, %46 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x16x4x30xi32>, tensor<30xi32>, tensor<30xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x16x4x30xi8>
+    %59 = tosa.clamp %58 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x16x4x30xi8>) -> tensor<?x16x4x30xi8>
+    %60 = tosa.reshape %59, %37 : (tensor<?x16x4x30xi8>, !tosa.shape<4>) -> tensor<?x1x1x1920xi8>
+    %61 = tosa.reshape %39, %36 : (tensor<16x1920xi8>, !tosa.shape<4>) -> tensor<16x1x1x1920xi8>
+    %62 = tosa.conv2d %60, %61, %38, %46, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x1920xi8>, tensor<16x1x1x1920xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x16xi32>
+    %63 = tosa.rescale %62, %34, %33, %47, %35 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x16xi8>
+    %64 = tosa.reshape %32, %30 : (tensor<128x16xi8>, !tosa.shape<4>) -> tensor<128x1x1x16xi8>
+    %65 = tosa.conv2d %63, %64, %31, %35, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x16xi8>, tensor<128x1x1x16xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x128xi32>
+    %66 = tosa.rescale %65, %29, %28, %47, %46 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x128xi8>
+    %67 = tosa.reshape %66, %27 : (tensor<?x1x1x128xi8>, !tosa.shape<2>) -> tensor<?x128xi8>
+    %68 = tosa.clamp %67 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x128xi8>) -> tensor<?x128xi8>
+    %69 = tosa.reshape %68, %24 : (tensor<?x128xi8>, !tosa.shape<4>) -> tensor<?x1x1x128xi8>
+    %70 = tosa.reshape %26, %23 : (tensor<12x128xi8>, !tosa.shape<4>) -> tensor<12x1x1x128xi8>
+    %71 = tosa.conv2d %69, %70, %25, %46, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x128xi8>, tensor<12x1x1x128xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x12xi32>
+    %72 = tosa.rescale %71, %21, %20, %47, %22 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x12xi8>
+    %73 = tosa.reshape %72, %19 : (tensor<?x1x1x12xi8>, !tosa.shape<2>) -> tensor<?x12xi8>
+    %74 = tosa.rescale %73, %18, %17, %22, %47 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x12xi32>
+    %75 = tosa.reduce_max %74 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
+    %76 = tosa.sub %74, %75 : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
+    %77 = tosa.rescale %76, %18, %12, %47, %11 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<?x12xi16>
+    %78 = tosa.table %77, %16 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %79 = tosa.table %77, %15 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %80 = tosa.table %77, %14 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %81 = tosa.table %77, %13 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %82 = tosa.logical_left_shift %78, %10 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %83 = tosa.logical_left_shift %79, %9 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %84 = tosa.logical_left_shift %80, %8 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %85 = tosa.arithmetic_right_shift %81, %7 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %86 = tosa.add %82, %83 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
+    %87 = tosa.add %86, %84 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
+    %88 = tosa.add %87, %85 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
+    %89 = tosa.arithmetic_right_shift %88, %6 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %90 = tosa.reduce_sum %89 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
+    %91 = tosa.clz %90 : (tensor<?x1xi32>) -> tensor<?x1xi32>
+    %92 = tosa.sub %91, %8 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %93 = tosa.logical_left_shift %90, %92 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %94 = tosa.mul %93, %2, %1 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %95 = tosa.add %94, %3 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %96 = tosa.mul %95, %93, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %97 = tosa.sub %4, %96 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %98 = tosa.mul %95, %97, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %99 = tosa.mul %98, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %100 = tosa.add %95, %99 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %101 = tosa.mul %100, %93, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %102 = tosa.sub %4, %101 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %103 = tosa.mul %100, %102, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %104 = tosa.mul %103, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %105 = tosa.add %100, %104 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %106 = tosa.mul %105, %93, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %107 = tosa.sub %4, %106 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %108 = tosa.mul %105, %107, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %109 = tosa.mul %108, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %110 = tosa.add %105, %109 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %111 = tosa.mul %88, %110, %17 : (tensor<?x12xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x12xi32>
+    %112 = tosa.sub %0, %91 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %113 = tosa.arithmetic_right_shift %111, %112 {round = true} : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
+    %114 = tosa.rescale %113, %18, %17, %47, %46 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x12xi8>
+    return %114 : tensor<?x12xi8>
+  }
+}
diff --git a/tests/gold/test_python_api/dnn_s_quantized.mlir b/tests/gold/test_python_api/dnn_s_quantized.mlir
new file mode 100644
index 0000000..44e67fd
--- /dev/null
+++ b/tests/gold/test_python_api/dnn_s_quantized.mlir
@@ -0,0 +1,114 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.14.0\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<?x250xi8>) -> tensor<?x12xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
+    %0 = "tosa.const"() <{values = dense<35> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %1 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %2 = "tosa.const"() <{values = dense<-1010580540> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %3 = "tosa.const"() <{values = dense<1515870810> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %4 = "tosa.const"() <{values = dense<536870912> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %5 = "tosa.const"() <{values = dense<4> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %6 = "tosa.const"() <{values = dense<12> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %7 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %8 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %9 = "tosa.const"() <{values = dense<9> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %10 = "tosa.const"() <{values = dense<17> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %11 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
+    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %16 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %17 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %18 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %19 = "tosa.const"() <{values = dense<40> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %20 = "tosa.const"() <{values = dense<1374243659> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %21 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %22 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi32>}> : () -> tensor<12xi32>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12x144xi8>}> : () -> tensor<12x144xi8>
+    %25 = "tosa.const"() <{values = dense<1143565917> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x144xi8>}> : () -> tensor<144x144xi8>
+    %28 = "tosa.const"() <{values = dense<39> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %29 = "tosa.const"() <{values = dense<1857097977> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %30 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %31 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x144xi8>}> : () -> tensor<144x144xi8>
+    %34 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %35 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %36 = "tosa.const"() <{values = dense<1901577989> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %37 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %38 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %39 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %40 = "tosa.const"() <{values = dense<100> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %41 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x250xi8>}> : () -> tensor<144x250xi8>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %44 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %45 = tosa.reshape %arg0, %44 : (tensor<?x250xi8>, !tosa.shape<4>) -> tensor<?x1x1x250xi8>
+    %46 = tosa.reshape %42, %41 : (tensor<144x250xi8>, !tosa.shape<4>) -> tensor<144x1x1x250xi8>
+    %47 = tosa.conv2d %45, %46, %43, %40, %39 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x250xi8>, tensor<144x1x1x250xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x144xi32>
+    %48 = tosa.rescale %47, %36, %35, %38, %37 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x144xi8>
+    %49 = tosa.reshape %48, %34 : (tensor<?x1x1x144xi8>, !tosa.shape<2>) -> tensor<?x144xi8>
+    %50 = tosa.clamp %49 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x144xi8>) -> tensor<?x144xi8>
+    %51 = tosa.reshape %50, %31 : (tensor<?x144xi8>, !tosa.shape<4>) -> tensor<?x1x1x144xi8>
+    %52 = tosa.reshape %33, %30 : (tensor<144x144xi8>, !tosa.shape<4>) -> tensor<144x1x1x144xi8>
+    %53 = tosa.conv2d %51, %52, %32, %37, %39 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x144xi8>, tensor<144x1x1x144xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x144xi32>
+    %54 = tosa.rescale %53, %29, %28, %38, %37 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x144xi8>
+    %55 = tosa.reshape %54, %34 : (tensor<?x1x1x144xi8>, !tosa.shape<2>) -> tensor<?x144xi8>
+    %56 = tosa.clamp %55 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x144xi8>) -> tensor<?x144xi8>
+    %57 = tosa.reshape %56, %31 : (tensor<?x144xi8>, !tosa.shape<4>) -> tensor<?x1x1x144xi8>
+    %58 = tosa.reshape %27, %30 : (tensor<144x144xi8>, !tosa.shape<4>) -> tensor<144x1x1x144xi8>
+    %59 = tosa.conv2d %57, %58, %26, %37, %39 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x144xi8>, tensor<144x1x1x144xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x144xi32>
+    %60 = tosa.rescale %59, %25, %35, %38, %37 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x144xi8>
+    %61 = tosa.reshape %60, %34 : (tensor<?x1x1x144xi8>, !tosa.shape<2>) -> tensor<?x144xi8>
+    %62 = tosa.clamp %61 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x144xi8>) -> tensor<?x144xi8>
+    %63 = tosa.reshape %62, %31 : (tensor<?x144xi8>, !tosa.shape<4>) -> tensor<?x1x1x144xi8>
+    %64 = tosa.reshape %24, %22 : (tensor<12x144xi8>, !tosa.shape<4>) -> tensor<12x1x1x144xi8>
+    %65 = tosa.conv2d %63, %64, %23, %37, %39 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x144xi8>, tensor<12x1x1x144xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x12xi32>
+    %66 = tosa.rescale %65, %20, %19, %38, %21 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x12xi8>
+    %67 = tosa.reshape %66, %18 : (tensor<?x1x1x12xi8>, !tosa.shape<2>) -> tensor<?x12xi8>
+    %68 = tosa.rescale %67, %17, %16, %21, %38 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x12xi32>
+    %69 = tosa.reduce_max %68 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
+    %70 = tosa.sub %68, %69 : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
+    %71 = tosa.rescale %70, %17, %21, %38, %11 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<?x12xi16>
+    %72 = tosa.table %71, %15 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %73 = tosa.table %71, %14 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %74 = tosa.table %71, %13 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %75 = tosa.table %71, %12 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %76 = tosa.logical_left_shift %72, %10 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %77 = tosa.logical_left_shift %73, %9 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %78 = tosa.logical_left_shift %74, %8 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %79 = tosa.arithmetic_right_shift %75, %7 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %80 = tosa.add %76, %77 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
+    %81 = tosa.add %80, %78 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
+    %82 = tosa.add %81, %79 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
+    %83 = tosa.arithmetic_right_shift %82, %6 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %84 = tosa.reduce_sum %83 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
+    %85 = tosa.clz %84 : (tensor<?x1xi32>) -> tensor<?x1xi32>
+    %86 = tosa.sub %85, %8 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %87 = tosa.logical_left_shift %84, %86 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %88 = tosa.mul %87, %2, %1 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %89 = tosa.add %88, %3 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %90 = tosa.mul %89, %87, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %91 = tosa.sub %4, %90 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %92 = tosa.mul %89, %91, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %93 = tosa.mul %92, %5, %39 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %94 = tosa.add %89, %93 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %95 = tosa.mul %94, %87, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %96 = tosa.sub %4, %95 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %97 = tosa.mul %94, %96, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %98 = tosa.mul %97, %5, %39 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %99 = tosa.add %94, %98 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %100 = tosa.mul %99, %87, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %101 = tosa.sub %4, %100 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %102 = tosa.mul %99, %101, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %103 = tosa.mul %102, %5, %39 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %104 = tosa.add %99, %103 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %105 = tosa.mul %82, %104, %16 : (tensor<?x12xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x12xi32>
+    %106 = tosa.sub %0, %85 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %107 = tosa.arithmetic_right_shift %105, %106 {round = true} : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
+    %108 = tosa.rescale %107, %17, %16, %38, %37 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x12xi8>
+    return %108 : tensor<?x12xi8>
+  }
+}
diff --git a/tests/gold/test_python_api/ds_cnn_s_quantized_int16.mlir b/tests/gold/test_python_api/ds_cnn_s_quantized_int16.mlir
new file mode 100644
index 0000000..4b0d719
--- /dev/null
+++ b/tests/gold/test_python_api/ds_cnn_s_quantized_int16.mlir
@@ -0,0 +1,125 @@
+module attributes {tf_saved_model.semantics, tfl.description = "MLIR Converted.", tfl.metadata = {CONVERSION_METADATA = "\0C\00\00\00\08\00\0E\00\08\00\04\00\08\00\00\00\10\00\00\00(\00\00\00\00\00\06\00\08\00\04\00\06\00\00\00\04\00\00\00\01\00\00\00\EC\03\00\00\00\00\0A\00\10\00\0C\00\08\00\04\00\0A\00\00\00\02\00\00\00\02\00\00\00\04\00\00\00\05\00\00\002.9.1\00\00\00", min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<?x490xi16> {tf_saved_model.index_path = ["input"]}) -> (tensor<?x12xi16> {tf_saved_model.index_path = ["dense"]}) attributes {tf.entry_function = {inputs = "serving_default_input:0", outputs = "StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {
+    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %1 = "tosa.const"() <{values = dense<31> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %2 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %3 = "tosa.const"() <{values = dense<32768> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %4 = "tosa.const"() <{values = dense<14> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %5 = "tosa.const"() <{values = dense<1073741824> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %6 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %7 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %8 = "tosa.const"() <{values = dense<32767> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %9 = "tosa.const"() <{values = dense<27> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %10 = "tosa.const"() <{values = dense<1564587505> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %12 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %13 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %14 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %15 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %16 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %17 = "tosa.const"() <{values = dense<23137> : tensor<1xi16>}> : () -> tensor<1xi16>
+    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi48>}> : () -> tensor<12xi48>
+    %19 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12x64xi8>}> : () -> tensor<12x64xi8>
+    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x64xi8>}> : () -> tensor<64x1x1x64xi8>
+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %28 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x64xi8>}> : () -> tensor<1x3x3x64xi8>
+    %29 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x64xi8>}> : () -> tensor<64x1x1x64xi8>
+    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x64xi8>}> : () -> tensor<1x3x3x64xi8>
+    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x64xi8>}> : () -> tensor<64x1x1x64xi8>
+    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x64xi8>}> : () -> tensor<1x3x3x64xi8>
+    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x64xi8>}> : () -> tensor<64x1x1x64xi8>
+    %49 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %50 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %51 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x64xi8>}> : () -> tensor<1x3x3x64xi8>
+    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %54 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
+    %55 = "tosa.const"() <{values = dense<0> : tensor<1xi48>}> : () -> tensor<1xi48>
+    %56 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %57 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
+    %58 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
+    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x10x4x1xi8>}> : () -> tensor<64x10x4x1xi8>
+    %60 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %61 = tosa.reshape %arg0, %60 : (tensor<?x490xi16>, !tosa.shape<4>) -> tensor<?x49x10x1xi16>
+    %62 = tosa.conv2d %61, %59, %58, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 4, 5, 1, 1>, stride = array<i64: 2, 2>} : (tensor<?x49x10x1xi16>, tensor<64x10x4x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %63 = tosa.rescale %62, %54, %53, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %64 = tosa.clamp %63 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %65 = tosa.reshape %52, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
+    %66 = tosa.depthwise_conv2d %64, %65, %51, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<3x3x64x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %67 = tosa.rescale %66, %50, %49, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %68 = tosa.clamp %67 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %69 = tosa.conv2d %68, %48, %47, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<64x1x1x64xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %70 = tosa.rescale %69, %46, %45, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %71 = tosa.clamp %70 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %72 = tosa.reshape %44, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
+    %73 = tosa.depthwise_conv2d %71, %72, %43, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<3x3x64x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %74 = tosa.rescale %73, %42, %41, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %75 = tosa.clamp %74 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %76 = tosa.conv2d %75, %40, %39, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<64x1x1x64xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %77 = tosa.rescale %76, %38, %37, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %78 = tosa.clamp %77 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %79 = tosa.reshape %36, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
+    %80 = tosa.depthwise_conv2d %78, %79, %35, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<3x3x64x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %81 = tosa.rescale %80, %34, %33, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %82 = tosa.clamp %81 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %83 = tosa.conv2d %82, %32, %31, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<64x1x1x64xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %84 = tosa.rescale %83, %30, %29, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %85 = tosa.clamp %84 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %86 = tosa.reshape %28, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
+    %87 = tosa.depthwise_conv2d %85, %86, %27, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<3x3x64x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %88 = tosa.rescale %87, %26, %25, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %89 = tosa.clamp %88 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %90 = tosa.conv2d %89, %24, %23, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<64x1x1x64xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
+    %91 = tosa.rescale %90, %22, %21, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
+    %92 = tosa.clamp %91 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
+    %93 = tosa.avg_pool2d %92, %57, %57 {acc_type = i32, kernel = array<i64: 25, 5>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<1xi16>, tensor<1xi16>) -> tensor<?x1x1x64xi16>
+    %94 = tosa.reshape %20, %19 : (tensor<12x64xi8>, !tosa.shape<4>) -> tensor<12x1x1x64xi8>
+    %95 = tosa.conv2d %93, %94, %18, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x64xi16>, tensor<12x1x1x64xi8>, tensor<12xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x1x1x12xi48>
+    %96 = tosa.rescale %95, %17, %16, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x1x1x12xi48>, tensor<1xi16>, tensor<1xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x1x1x12xi16>
+    %97 = tosa.reshape %96, %15 : (tensor<?x1x1x12xi16>, !tosa.shape<2>) -> tensor<?x12xi16>
+    %98 = tosa.rescale %97, %14, %13, %57, %12 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi16>, tensor<1xi32>, tensor<1xi8>, tensor<1xi16>, tensor<1xi32>) -> tensor<?x12xi32>
+    %99 = tosa.reduce_max %98 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
+    %100 = tosa.sub %98, %99 : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
+    %101 = tosa.rescale %100, %10, %9, %12, %12 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<?x12xi32>
+    %102 = tosa.add %101, %8 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %103 = tosa.cast %102 : (tensor<?x12xi32>) -> tensor<?x12xi16>
+    %104 = tosa.table %103, %11 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
+    %105 = tosa.arithmetic_right_shift %104, %7 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
+    %106 = tosa.reduce_sum %105 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
+    %107 = tosa.clz %106 : (tensor<?x1xi32>) -> tensor<?x1xi32>
+    %108 = tosa.sub %107, %6 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %109 = tosa.logical_left_shift %106, %108 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %110 = tosa.sub %109, %5 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %111 = tosa.arithmetic_right_shift %110, %4 {round = true} : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %112 = tosa.sub %111, %3 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %113 = tosa.cast %112 : (tensor<?x1xi32>) -> tensor<?x1xi16>
+    %114 = tosa.table %113, %2 : (tensor<?x1xi16>, tensor<513xi16>) -> tensor<?x1xi32>
+    %115 = tosa.arithmetic_right_shift %114, %7 {round = true} : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %116 = tosa.mul %115, %105, %56 : (tensor<?x1xi32>, tensor<?x12xi32>, tensor<1xi8>) -> tensor<?x12xi32>
+    %117 = tosa.sub %1, %107 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %118 = tosa.arithmetic_right_shift %116, %117 {round = true} : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
+    %119 = tosa.rescale %118, %14, %13, %12, %57 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<?x12xi16>
+    return %119 : tensor<?x12xi16>
+  }
+}
diff --git a/tests/gold/test_python_api/efficientnet_lite0_224.mlir b/tests/gold/test_python_api/efficientnet_lite0_224.mlir
new file mode 100644
index 0000000..77ae940
--- /dev/null
+++ b/tests/gold/test_python_api/efficientnet_lite0_224.mlir
@@ -0,0 +1,528 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<1x224x224x3xui8>) -> tensor<1x1000xui8> attributes {tf.entry_function = {inputs = "images", outputs = "Softmax"}} {
+    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
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+    %182 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
+    %183 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x480xi8>}> : () -> tensor<1x3x3x480xi8>
+    %184 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi8>}> : () -> tensor<480xi8>
+    %185 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
+    %186 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
+    %187 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480x1x1x80xi8>}> : () -> tensor<480x1x1x80xi8>
+    %188 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi8>}> : () -> tensor<80xi8>
+    %189 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi32>}> : () -> tensor<80xi32>
+    %190 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi32>}> : () -> tensor<80xi32>
+    %191 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80x1x1x240xi8>}> : () -> tensor<80x1x1x240xi8>
+    %192 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
+    %193 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %194 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %195 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x240xi8>}> : () -> tensor<1x3x3x240xi8>
+    %196 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
+    %197 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %198 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %199 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240x1x1x40xi8>}> : () -> tensor<240x1x1x40xi8>
+    %200 = "tosa.const"() <{values = dense<-4> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %201 = "tosa.const"() <{values = dense<1934301239> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %202 = "tosa.const"() <{values = dense<1676171725> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %203 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi8>}> : () -> tensor<40xi8>
+    %204 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
+    %205 = "tosa.const"() <{values = dense<-7> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %206 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
+    %207 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40x1x1x240xi8>}> : () -> tensor<40x1x1x240xi8>
+    %208 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
+    %209 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %210 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %211 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x240xi8>}> : () -> tensor<1x5x5x240xi8>
+    %212 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
+    %213 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %214 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %215 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240x1x1x40xi8>}> : () -> tensor<240x1x1x40xi8>
+    %216 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi8>}> : () -> tensor<40xi8>
+    %217 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
+    %218 = "tosa.const"() <{values = dense<-6> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %219 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
+    %220 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40x1x1x144xi8>}> : () -> tensor<40x1x1x144xi8>
+    %221 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi8>}> : () -> tensor<144xi8>
+    %222 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %223 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %224 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x144xi8>}> : () -> tensor<1x5x5x144xi8>
+    %225 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi8>}> : () -> tensor<144xi8>
+    %226 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %227 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %228 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x1x1x24xi8>}> : () -> tensor<144x1x1x24xi8>
+    %229 = "tosa.const"() <{values = dense<-11> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %230 = "tosa.const"() <{values = dense<50> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %231 = "tosa.const"() <{values = dense<1867833568> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %232 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %233 = "tosa.const"() <{values = dense<2065654195> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %234 = "tosa.const"() <{values = dense<10> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %235 = "tosa.const"() <{values = dense<11> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %236 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
+    %237 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %238 = "tosa.const"() <{values = dense<-9> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %239 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %240 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x144xi8>}> : () -> tensor<24x1x1x144xi8>
+    %241 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi8>}> : () -> tensor<144xi8>
+    %242 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %243 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %244 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x144xi8>}> : () -> tensor<1x3x3x144xi8>
+    %245 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi8>}> : () -> tensor<144xi8>
+    %246 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %247 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %248 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x1x1x24xi8>}> : () -> tensor<144x1x1x24xi8>
+    %249 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
+    %250 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %251 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %252 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x96xi8>}> : () -> tensor<24x1x1x96xi8>
+    %253 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %254 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %255 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %256 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
+    %257 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %258 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %259 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %260 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x16xi8>}> : () -> tensor<96x1x1x16xi8>
+    %261 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
+    %262 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %263 = "tosa.const"() <{values = dense<1> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %264 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %265 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x32xi8>}> : () -> tensor<16x1x1x32xi8>
+    %266 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
+    %267 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %268 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %269 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x32xi8>}> : () -> tensor<1x3x3x32xi8>
+    %270 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
+    %271 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %272 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %273 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %274 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x3x3x3xi8>}> : () -> tensor<32x3x3x3xi8>
+    %275 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %276 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %277 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %278 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %279 = "tosa.const"() <{values = dense<-125> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %280 = "tosa.const"() <{values = dense<3> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %281 = tosa.rescale %arg0, %277, %278, %279, %280 {input_unsigned = true, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x224x224x3xui8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x224x224x3xi8>
+    %282 = tosa.rescale %281, %277, %278, %280, %280 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x224x224x3xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x224x224x3xi8>
+    %283 = tosa.conv2d %282, %274, %273, %280, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x224x224x3xi8>, tensor<32x3x3x3xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x32xi32>
+    %284 = tosa.rescale %283, %271, %270, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x32xi8>
+    %285 = tosa.clamp %284 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x112x112x32xi8>) -> tensor<1x112x112x32xi8>
+    %286 = tosa.reshape %269, %10 : (tensor<1x3x3x32xi8>, !tosa.shape<4>) -> tensor<3x3x32x1xi8>
+    %287 = tosa.depthwise_conv2d %285, %286, %268, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x112x112x32xi8>, tensor<3x3x32x1xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x32xi32>
+    %288 = tosa.rescale %287, %267, %266, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x32xi8>
+    %289 = tosa.clamp %288 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x112x112x32xi8>) -> tensor<1x112x112x32xi8>
+    %290 = tosa.conv2d %289, %265, %264, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x112x112x32xi8>, tensor<16x1x1x32xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x16xi32>
+    %291 = tosa.rescale %290, %262, %261, %272, %263 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x16xi8>
+    %292 = tosa.conv2d %291, %260, %259, %263, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x112x112x16xi8>, tensor<96x1x1x16xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x96xi32>
+    %293 = tosa.rescale %292, %258, %257, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x96xi8>
+    %294 = tosa.clamp %293 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x112x112x96xi8>) -> tensor<1x112x112x96xi8>
+    %295 = tosa.reshape %256, %9 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
+    %296 = tosa.depthwise_conv2d %294, %295, %255, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x112x112x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x96xi32>
+    %297 = tosa.rescale %296, %254, %253, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x96xi8>
+    %298 = tosa.clamp %297 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x56x56x96xi8>) -> tensor<1x56x56x96xi8>
+    %299 = tosa.conv2d %298, %252, %251, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x96xi8>, tensor<24x1x1x96xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x24xi32>
+    %300 = tosa.rescale %299, %250, %249, %272, %276 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
+    %301 = tosa.conv2d %300, %248, %247, %276, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x24xi8>, tensor<144x1x1x24xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
+    %302 = tosa.rescale %301, %246, %245, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
+    %303 = tosa.clamp %302 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x56x56x144xi8>) -> tensor<1x56x56x144xi8>
+    %304 = tosa.reshape %244, %8 : (tensor<1x3x3x144xi8>, !tosa.shape<4>) -> tensor<3x3x144x1xi8>
+    %305 = tosa.depthwise_conv2d %303, %304, %243, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x56x56x144xi8>, tensor<3x3x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
+    %306 = tosa.rescale %305, %242, %241, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
+    %307 = tosa.clamp %306 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x56x56x144xi8>) -> tensor<1x56x56x144xi8>
+    %308 = tosa.conv2d %307, %240, %239, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x144xi8>, tensor<24x1x1x144xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x24xi32>
+    %309 = tosa.rescale %308, %237, %236, %272, %238 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
+    %310 = tosa.rescale %309, %277, %235, %238, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
+    %311 = tosa.rescale %300, %277, %234, %276, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
+    %312 = tosa.rescale %311, %233, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
+    %313 = tosa.add %310, %312 : (tensor<1x56x56x24xi32>, tensor<1x56x56x24xi32>) -> tensor<1x56x56x24xi32>
+    %314 = tosa.rescale %313, %231, %230, %272, %229 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
+    %315 = tosa.conv2d %314, %228, %227, %229, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x24xi8>, tensor<144x1x1x24xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
+    %316 = tosa.rescale %315, %226, %225, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
+    %317 = tosa.clamp %316 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x56x56x144xi8>) -> tensor<1x56x56x144xi8>
+    %318 = tosa.reshape %224, %7 : (tensor<1x5x5x144xi8>, !tosa.shape<4>) -> tensor<5x5x144x1xi8>
+    %319 = tosa.depthwise_conv2d %317, %318, %223, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 2, 1, 2>, stride = array<i64: 2, 2>} : (tensor<1x56x56x144xi8>, tensor<5x5x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x144xi32>
+    %320 = tosa.rescale %319, %222, %221, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x144xi8>
+    %321 = tosa.clamp %320 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x28x28x144xi8>) -> tensor<1x28x28x144xi8>
+    %322 = tosa.conv2d %321, %220, %219, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x144xi8>, tensor<40x1x1x144xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x40xi32>
+    %323 = tosa.rescale %322, %217, %216, %272, %218 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x40xi8>
+    %324 = tosa.conv2d %323, %215, %214, %218, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x40xi8>, tensor<240x1x1x40xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x240xi32>
+    %325 = tosa.rescale %324, %213, %212, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x240xi8>
+    %326 = tosa.clamp %325 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x28x28x240xi8>) -> tensor<1x28x28x240xi8>
+    %327 = tosa.reshape %211, %6 : (tensor<1x5x5x240xi8>, !tosa.shape<4>) -> tensor<5x5x240x1xi8>
+    %328 = tosa.depthwise_conv2d %326, %327, %210, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x28x28x240xi8>, tensor<5x5x240x1xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x240xi32>
+    %329 = tosa.rescale %328, %209, %208, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x240xi8>
+    %330 = tosa.clamp %329 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x28x28x240xi8>) -> tensor<1x28x28x240xi8>
+    %331 = tosa.conv2d %330, %207, %206, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x240xi8>, tensor<40x1x1x240xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x40xi32>
+    %332 = tosa.rescale %331, %204, %203, %272, %205 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x40xi8>
+    %333 = tosa.rescale %332, %277, %234, %205, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x40xi32>
+    %334 = tosa.rescale %333, %202, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x28x28x40xi32>
+    %335 = tosa.rescale %323, %277, %235, %218, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x40xi32>
+    %336 = tosa.add %334, %335 : (tensor<1x28x28x40xi32>, tensor<1x28x28x40xi32>) -> tensor<1x28x28x40xi32>
+    %337 = tosa.rescale %336, %201, %230, %272, %200 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x40xi8>
+    %338 = tosa.conv2d %337, %199, %198, %200, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x40xi8>, tensor<240x1x1x40xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x240xi32>
+    %339 = tosa.rescale %338, %197, %196, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x240xi8>
+    %340 = tosa.clamp %339 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x28x28x240xi8>) -> tensor<1x28x28x240xi8>
+    %341 = tosa.reshape %195, %5 : (tensor<1x3x3x240xi8>, !tosa.shape<4>) -> tensor<3x3x240x1xi8>
+    %342 = tosa.depthwise_conv2d %340, %341, %194, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x28x28x240xi8>, tensor<3x3x240x1xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x240xi32>
+    %343 = tosa.rescale %342, %193, %192, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x240xi8>
+    %344 = tosa.clamp %343 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x240xi8>) -> tensor<1x14x14x240xi8>
+    %345 = tosa.conv2d %344, %191, %190, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x240xi8>, tensor<80x1x1x240xi8>, tensor<80xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x80xi32>
+    %346 = tosa.rescale %345, %189, %188, %272, %276 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<80xi32>, tensor<80xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
+    %347 = tosa.conv2d %346, %187, %186, %276, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x80xi8>, tensor<480x1x1x80xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
+    %348 = tosa.rescale %347, %185, %184, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
+    %349 = tosa.clamp %348 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
+    %350 = tosa.reshape %183, %4 : (tensor<1x3x3x480xi8>, !tosa.shape<4>) -> tensor<3x3x480x1xi8>
+    %351 = tosa.depthwise_conv2d %349, %350, %182, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<3x3x480x1xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
+    %352 = tosa.rescale %351, %181, %180, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
+    %353 = tosa.clamp %352 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
+    %354 = tosa.conv2d %353, %179, %178, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<80x1x1x480xi8>, tensor<80xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x80xi32>
+    %355 = tosa.rescale %354, %176, %175, %272, %177 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<80xi32>, tensor<80xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
+    %356 = tosa.rescale %355, %277, %234, %177, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
+    %357 = tosa.rescale %356, %174, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
+    %358 = tosa.rescale %346, %277, %235, %276, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
+    %359 = tosa.add %357, %358 : (tensor<1x14x14x80xi32>, tensor<1x14x14x80xi32>) -> tensor<1x14x14x80xi32>
+    %360 = tosa.rescale %359, %173, %230, %272, %172 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
+    %361 = tosa.conv2d %360, %171, %170, %172, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x80xi8>, tensor<480x1x1x80xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
+    %362 = tosa.rescale %361, %169, %168, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
+    %363 = tosa.clamp %362 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
+    %364 = tosa.reshape %167, %4 : (tensor<1x3x3x480xi8>, !tosa.shape<4>) -> tensor<3x3x480x1xi8>
+    %365 = tosa.depthwise_conv2d %363, %364, %166, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<3x3x480x1xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
+    %366 = tosa.rescale %365, %165, %164, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
+    %367 = tosa.clamp %366 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
+    %368 = tosa.conv2d %367, %163, %162, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<80x1x1x480xi8>, tensor<80xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x80xi32>
+    %369 = tosa.rescale %368, %161, %160, %272, %200 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<80xi32>, tensor<80xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
+    %370 = tosa.rescale %369, %277, %234, %200, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
+    %371 = tosa.rescale %370, %159, %158, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
+    %372 = tosa.rescale %360, %277, %235, %172, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
+    %373 = tosa.add %371, %372 : (tensor<1x14x14x80xi32>, tensor<1x14x14x80xi32>) -> tensor<1x14x14x80xi32>
+    %374 = tosa.rescale %373, %157, %156, %272, %280 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
+    %375 = tosa.conv2d %374, %155, %154, %280, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x80xi8>, tensor<480x1x1x80xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
+    %376 = tosa.rescale %375, %153, %152, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
+    %377 = tosa.clamp %376 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
+    %378 = tosa.reshape %151, %3 : (tensor<1x5x5x480xi8>, !tosa.shape<4>) -> tensor<5x5x480x1xi8>
+    %379 = tosa.depthwise_conv2d %377, %378, %150, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<5x5x480x1xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
+    %380 = tosa.rescale %379, %149, %148, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
+    %381 = tosa.clamp %380 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
+    %382 = tosa.conv2d %381, %147, %146, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<112x1x1x480xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x112xi32>
+    %383 = tosa.rescale %382, %145, %144, %272, %235 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
+    %384 = tosa.conv2d %383, %143, %142, %235, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x112xi8>, tensor<672x1x1x112xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
+    %385 = tosa.rescale %384, %141, %140, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
+    %386 = tosa.clamp %385 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
+    %387 = tosa.reshape %139, %2 : (tensor<1x5x5x672xi8>, !tosa.shape<4>) -> tensor<5x5x672x1xi8>
+    %388 = tosa.depthwise_conv2d %386, %387, %138, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x14x14x672xi8>, tensor<5x5x672x1xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
+    %389 = tosa.rescale %388, %137, %136, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
+    %390 = tosa.clamp %389 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
+    %391 = tosa.conv2d %390, %135, %134, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x672xi8>, tensor<112x1x1x672xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x112xi32>
+    %392 = tosa.rescale %391, %132, %131, %272, %133 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
+    %393 = tosa.rescale %392, %277, %234, %133, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
+    %394 = tosa.rescale %393, %130, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
+    %395 = tosa.rescale %383, %277, %235, %235, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
+    %396 = tosa.add %394, %395 : (tensor<1x14x14x112xi32>, tensor<1x14x14x112xi32>) -> tensor<1x14x14x112xi32>
+    %397 = tosa.rescale %396, %129, %230, %272, %128 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
+    %398 = tosa.conv2d %397, %127, %126, %128, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x112xi8>, tensor<672x1x1x112xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
+    %399 = tosa.rescale %398, %125, %124, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
+    %400 = tosa.clamp %399 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
+    %401 = tosa.reshape %123, %2 : (tensor<1x5x5x672xi8>, !tosa.shape<4>) -> tensor<5x5x672x1xi8>
+    %402 = tosa.depthwise_conv2d %400, %401, %122, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x14x14x672xi8>, tensor<5x5x672x1xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
+    %403 = tosa.rescale %402, %121, %120, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
+    %404 = tosa.clamp %403 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
+    %405 = tosa.conv2d %404, %119, %118, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x672xi8>, tensor<112x1x1x672xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x112xi32>
+    %406 = tosa.rescale %405, %116, %115, %272, %117 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
+    %407 = tosa.rescale %406, %277, %234, %117, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
+    %408 = tosa.rescale %407, %114, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
+    %409 = tosa.rescale %397, %277, %235, %128, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
+    %410 = tosa.add %408, %409 : (tensor<1x14x14x112xi32>, tensor<1x14x14x112xi32>) -> tensor<1x14x14x112xi32>
+    %411 = tosa.rescale %410, %113, %230, %272, %112 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
+    %412 = tosa.conv2d %411, %111, %110, %112, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x112xi8>, tensor<672x1x1x112xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
+    %413 = tosa.rescale %412, %109, %108, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
+    %414 = tosa.clamp %413 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
+    %415 = tosa.reshape %107, %2 : (tensor<1x5x5x672xi8>, !tosa.shape<4>) -> tensor<5x5x672x1xi8>
+    %416 = tosa.depthwise_conv2d %414, %415, %106, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 2, 1, 2>, stride = array<i64: 2, 2>} : (tensor<1x14x14x672xi8>, tensor<5x5x672x1xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x672xi32>
+    %417 = tosa.rescale %416, %105, %104, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x672xi8>
+    %418 = tosa.clamp %417 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x672xi8>) -> tensor<1x7x7x672xi8>
+    %419 = tosa.conv2d %418, %103, %102, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x672xi8>, tensor<192x1x1x672xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x192xi32>
+    %420 = tosa.rescale %419, %100, %99, %272, %101 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
+    %421 = tosa.conv2d %420, %98, %97, %101, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x192xi8>, tensor<1152x1x1x192xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
+    %422 = tosa.rescale %421, %96, %95, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
+    %423 = tosa.clamp %422 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
+    %424 = tosa.reshape %94, %1 : (tensor<1x5x5x1152xi8>, !tosa.shape<4>) -> tensor<5x5x1152x1xi8>
+    %425 = tosa.depthwise_conv2d %423, %424, %93, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<5x5x1152x1xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
+    %426 = tosa.rescale %425, %92, %91, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
+    %427 = tosa.clamp %426 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
+    %428 = tosa.conv2d %427, %90, %89, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<192x1x1x1152xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x192xi32>
+    %429 = tosa.rescale %428, %87, %86, %272, %88 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
+    %430 = tosa.rescale %429, %277, %234, %88, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %431 = tosa.rescale %430, %85, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %432 = tosa.rescale %420, %277, %235, %101, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %433 = tosa.add %431, %432 : (tensor<1x7x7x192xi32>, tensor<1x7x7x192xi32>) -> tensor<1x7x7x192xi32>
+    %434 = tosa.rescale %433, %84, %230, %272, %83 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
+    %435 = tosa.conv2d %434, %82, %81, %83, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x192xi8>, tensor<1152x1x1x192xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
+    %436 = tosa.rescale %435, %80, %79, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
+    %437 = tosa.clamp %436 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
+    %438 = tosa.reshape %78, %1 : (tensor<1x5x5x1152xi8>, !tosa.shape<4>) -> tensor<5x5x1152x1xi8>
+    %439 = tosa.depthwise_conv2d %437, %438, %77, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<5x5x1152x1xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
+    %440 = tosa.rescale %439, %76, %75, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
+    %441 = tosa.clamp %440 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
+    %442 = tosa.conv2d %441, %74, %73, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<192x1x1x1152xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x192xi32>
+    %443 = tosa.rescale %442, %71, %70, %272, %72 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
+    %444 = tosa.rescale %443, %277, %234, %72, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %445 = tosa.rescale %444, %69, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %446 = tosa.rescale %434, %277, %235, %83, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %447 = tosa.add %445, %446 : (tensor<1x7x7x192xi32>, tensor<1x7x7x192xi32>) -> tensor<1x7x7x192xi32>
+    %448 = tosa.rescale %447, %68, %230, %272, %67 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
+    %449 = tosa.conv2d %448, %66, %65, %67, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x192xi8>, tensor<1152x1x1x192xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
+    %450 = tosa.rescale %449, %64, %63, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
+    %451 = tosa.clamp %450 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
+    %452 = tosa.reshape %62, %1 : (tensor<1x5x5x1152xi8>, !tosa.shape<4>) -> tensor<5x5x1152x1xi8>
+    %453 = tosa.depthwise_conv2d %451, %452, %61, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<5x5x1152x1xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
+    %454 = tosa.rescale %453, %60, %59, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
+    %455 = tosa.clamp %454 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
+    %456 = tosa.conv2d %455, %58, %57, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<192x1x1x1152xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x192xi32>
+    %457 = tosa.rescale %456, %55, %54, %272, %56 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
+    %458 = tosa.rescale %457, %277, %234, %56, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %459 = tosa.rescale %458, %53, %158, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %460 = tosa.rescale %448, %277, %235, %67, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
+    %461 = tosa.add %459, %460 : (tensor<1x7x7x192xi32>, tensor<1x7x7x192xi32>) -> tensor<1x7x7x192xi32>
+    %462 = tosa.rescale %461, %52, %230, %272, %51 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
+    %463 = tosa.conv2d %462, %50, %49, %51, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x192xi8>, tensor<1152x1x1x192xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
+    %464 = tosa.rescale %463, %48, %47, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
+    %465 = tosa.clamp %464 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
+    %466 = tosa.reshape %46, %0 : (tensor<1x3x3x1152xi8>, !tosa.shape<4>) -> tensor<3x3x1152x1xi8>
+    %467 = tosa.depthwise_conv2d %465, %466, %45, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<3x3x1152x1xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
+    %468 = tosa.rescale %467, %44, %43, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
+    %469 = tosa.clamp %468 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
+    %470 = tosa.conv2d %469, %42, %41, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<320x1x1x1152xi8>, tensor<320xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x320xi32>
+    %471 = tosa.rescale %470, %39, %38, %272, %40 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x320xi32>, tensor<320xi32>, tensor<320xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x320xi8>
+    %472 = tosa.conv2d %471, %37, %36, %40, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x320xi8>, tensor<1280x1x1x320xi8>, tensor<1280xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1280xi32>
+    %473 = tosa.rescale %472, %35, %34, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1280xi32>, tensor<1280xi32>, tensor<1280xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1280xi8>
+    %474 = tosa.clamp %473 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1280xi8>) -> tensor<1x7x7x1280xi8>
+    %475 = tosa.avg_pool2d %474, %276, %276 {acc_type = i32, kernel = array<i64: 7, 7>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1280xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x1280xi8>
+    %476 = tosa.reshape %33, %31 : (tensor<1000x1280xi8>, !tosa.shape<4>) -> tensor<1000x1x1x1280xi8>
+    %477 = tosa.conv2d %475, %476, %32, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x1280xi8>, tensor<1000x1x1x1280xi8>, tensor<1000xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x1000xi32>
+    %478 = tosa.rescale %477, %29, %28, %272, %30 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x1000xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x1000xi8>
+    %479 = tosa.reshape %478, %27 : (tensor<1x1x1x1000xi8>, !tosa.shape<2>) -> tensor<1x1000xi8>
+    %480 = tosa.rescale %479, %277, %278, %30, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1000xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1000xi32>
+    %481 = tosa.reduce_max %480 {axis = 1 : i32} : (tensor<1x1000xi32>) -> tensor<1x1xi32>
+    %482 = tosa.sub %480, %481 : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
+    %483 = tosa.rescale %482, %277, %22, %272, %21 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1000xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<1x1000xi16>
+    %484 = tosa.table %483, %26 : (tensor<1x1000xi16>, tensor<513xi16>) -> tensor<1x1000xi32>
+    %485 = tosa.table %483, %25 : (tensor<1x1000xi16>, tensor<513xi16>) -> tensor<1x1000xi32>
+    %486 = tosa.table %483, %24 : (tensor<1x1000xi16>, tensor<513xi16>) -> tensor<1x1000xi32>
+    %487 = tosa.table %483, %23 : (tensor<1x1000xi16>, tensor<513xi16>) -> tensor<1x1000xi32>
+    %488 = tosa.logical_left_shift %484, %20 : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
+    %489 = tosa.logical_left_shift %485, %19 : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
+    %490 = tosa.logical_left_shift %486, %18 : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
+    %491 = tosa.arithmetic_right_shift %487, %17 {round = true} : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
+    %492 = tosa.add %488, %489 : (tensor<1x1000xi32>, tensor<1x1000xi32>) -> tensor<1x1000xi32>
+    %493 = tosa.add %492, %490 : (tensor<1x1000xi32>, tensor<1x1000xi32>) -> tensor<1x1000xi32>
+    %494 = tosa.add %493, %491 : (tensor<1x1000xi32>, tensor<1x1000xi32>) -> tensor<1x1000xi32>
+    %495 = tosa.arithmetic_right_shift %494, %16 {round = true} : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
+    %496 = tosa.reduce_sum %495 {axis = 1 : i32} : (tensor<1x1000xi32>) -> tensor<1x1xi32>
+    %497 = tosa.clz %496 : (tensor<1x1xi32>) -> tensor<1x1xi32>
+    %498 = tosa.sub %497, %18 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %499 = tosa.logical_left_shift %496, %498 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %500 = tosa.mul %499, %12, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %501 = tosa.add %500, %13 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %502 = tosa.mul %501, %499, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %503 = tosa.sub %14, %502 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %504 = tosa.mul %501, %503, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %505 = tosa.mul %504, %15, %276 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %506 = tosa.add %501, %505 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %507 = tosa.mul %506, %499, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %508 = tosa.sub %14, %507 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %509 = tosa.mul %506, %508, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %510 = tosa.mul %509, %15, %276 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %511 = tosa.add %506, %510 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %512 = tosa.mul %511, %499, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %513 = tosa.sub %14, %512 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %514 = tosa.mul %511, %513, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %515 = tosa.mul %514, %15, %276 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
+    %516 = tosa.add %511, %515 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %517 = tosa.mul %494, %516, %278 : (tensor<1x1000xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1000xi32>
+    %518 = tosa.sub %11, %497 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
+    %519 = tosa.arithmetic_right_shift %517, %518 {round = true} : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
+    %520 = tosa.rescale %519, %277, %278, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1000xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1000xi8>
+    %521 = tosa.rescale %520, %277, %278, %275, %275 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1000xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1000xi8>
+    %522 = tosa.rescale %521, %277, %278, %275, %276 {input_unsigned = false, output_unsigned = true, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1000xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1000xui8>
+    return %522 : tensor<1x1000xui8>
+  }
+}
diff --git a/tests/gold/test_python_api/har_int8.mlir b/tests/gold/test_python_api/har_int8.mlir
new file mode 100644
index 0000000..e66ed22
--- /dev/null
+++ b/tests/gold/test_python_api/har_int8.mlir
@@ -0,0 +1,117 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<?x90x3x1xi8>) -> tensor<?x6xi8> attributes {tf.entry_function = {inputs = "conv2d_input", outputs = "Identity"}} {
+    %0 = "tosa.const"() <{values = dense<35> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %1 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %2 = "tosa.const"() <{values = dense<-1010580540> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %3 = "tosa.const"() <{values = dense<1515870810> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %4 = "tosa.const"() <{values = dense<536870912> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %5 = "tosa.const"() <{values = dense<4> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %6 = "tosa.const"() <{values = dense<12> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %7 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %8 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %9 = "tosa.const"() <{values = dense<9> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %10 = "tosa.const"() <{values = dense<17> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
+    %11 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
+    %12 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
+    %17 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %18 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %19 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %20 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %21 = "tosa.const"() <{values = dense<1078364279> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %22 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %23 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<6xi32>}> : () -> tensor<6xi32>
+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<6x128xi8>}> : () -> tensor<6x128xi8>
+    %26 = "tosa.const"() <{values = dense<36> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %27 = "tosa.const"() <{values = dense<1596441372> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %28 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %29 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x128xi8>}> : () -> tensor<128x128xi8>
+    %32 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %33 = "tosa.const"() <{values = dense<41> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %34 = "tosa.const"() <{values = dense<1440829658> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %35 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %36 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x5632xi8>}> : () -> tensor<128x5632xi8>
+    %39 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %40 = tosa.const_shape  {values = dense<0> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
+    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %43 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %44 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x2x2x1xi8>}> : () -> tensor<128x2x2x1xi8>
+    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %47 = "tosa.const"() <{values = dense<-45> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %48 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %49 = tosa.conv2d %arg0, %45, %46, %47, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x90x3x1xi8>, tensor<128x2x2x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x89x2x128xi32>
+    %50 = tosa.rescale %49, %42, %41, %44, %43 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x89x2x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x89x2x128xi8>
+    %51 = tosa.clamp %50 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x89x2x128xi8>) -> tensor<?x89x2x128xi8>
+    %52 = tosa.slice %51, %40, %39 : (tensor<?x89x2x128xi8>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x88x2x128xi8>
+    %53 = tosa.max_pool2d %52 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x88x2x128xi8>) -> tensor<?x44x1x128xi8>
+    %54 = tosa.reshape %53, %36 : (tensor<?x44x1x128xi8>, !tosa.shape<4>) -> tensor<?x1x1x5632xi8>
+    %55 = tosa.reshape %38, %35 : (tensor<128x5632xi8>, !tosa.shape<4>) -> tensor<128x1x1x5632xi8>
+    %56 = tosa.conv2d %54, %55, %37, %43, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x5632xi8>, tensor<128x1x1x5632xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x128xi32>
+    %57 = tosa.rescale %56, %34, %33, %44, %43 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x128xi8>
+    %58 = tosa.reshape %57, %32 : (tensor<?x1x1x128xi8>, !tosa.shape<2>) -> tensor<?x128xi8>
+    %59 = tosa.clamp %58 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x128xi8>) -> tensor<?x128xi8>
+    %60 = tosa.reshape %59, %29 : (tensor<?x128xi8>, !tosa.shape<4>) -> tensor<?x1x1x128xi8>
+    %61 = tosa.reshape %31, %28 : (tensor<128x128xi8>, !tosa.shape<4>) -> tensor<128x1x1x128xi8>
+    %62 = tosa.conv2d %60, %61, %30, %43, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x128xi8>, tensor<128x1x1x128xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x128xi32>
+    %63 = tosa.rescale %62, %27, %26, %44, %43 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x128xi8>
+    %64 = tosa.reshape %63, %32 : (tensor<?x1x1x128xi8>, !tosa.shape<2>) -> tensor<?x128xi8>
+    %65 = tosa.clamp %64 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x128xi8>) -> tensor<?x128xi8>
+    %66 = tosa.reshape %65, %29 : (tensor<?x128xi8>, !tosa.shape<4>) -> tensor<?x1x1x128xi8>
+    %67 = tosa.reshape %25, %23 : (tensor<6x128xi8>, !tosa.shape<4>) -> tensor<6x1x1x128xi8>
+    %68 = tosa.conv2d %66, %67, %24, %43, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x128xi8>, tensor<6x1x1x128xi8>, tensor<6xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x6xi32>
+    %69 = tosa.rescale %68, %21, %20, %44, %22 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x6xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x6xi8>
+    %70 = tosa.reshape %69, %19 : (tensor<?x1x1x6xi8>, !tosa.shape<2>) -> tensor<?x6xi8>
+    %71 = tosa.rescale %70, %18, %17, %22, %44 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x6xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x6xi32>
+    %72 = tosa.reduce_max %71 {axis = 1 : i32} : (tensor<?x6xi32>) -> tensor<?x1xi32>
+    %73 = tosa.sub %71, %72 : (tensor<?x6xi32>, tensor<?x1xi32>) -> tensor<?x6xi32>
+    %74 = tosa.rescale %73, %18, %12, %44, %11 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x6xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<?x6xi16>
+    %75 = tosa.table %74, %16 : (tensor<?x6xi16>, tensor<513xi16>) -> tensor<?x6xi32>
+    %76 = tosa.table %74, %15 : (tensor<?x6xi16>, tensor<513xi16>) -> tensor<?x6xi32>
+    %77 = tosa.table %74, %14 : (tensor<?x6xi16>, tensor<513xi16>) -> tensor<?x6xi32>
+    %78 = tosa.table %74, %13 : (tensor<?x6xi16>, tensor<513xi16>) -> tensor<?x6xi32>
+    %79 = tosa.logical_left_shift %75, %10 : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
+    %80 = tosa.logical_left_shift %76, %9 : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
+    %81 = tosa.logical_left_shift %77, %8 : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
+    %82 = tosa.arithmetic_right_shift %78, %7 {round = true} : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
+    %83 = tosa.add %79, %80 : (tensor<?x6xi32>, tensor<?x6xi32>) -> tensor<?x6xi32>
+    %84 = tosa.add %83, %81 : (tensor<?x6xi32>, tensor<?x6xi32>) -> tensor<?x6xi32>
+    %85 = tosa.add %84, %82 : (tensor<?x6xi32>, tensor<?x6xi32>) -> tensor<?x6xi32>
+    %86 = tosa.arithmetic_right_shift %85, %6 {round = true} : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
+    %87 = tosa.reduce_sum %86 {axis = 1 : i32} : (tensor<?x6xi32>) -> tensor<?x1xi32>
+    %88 = tosa.clz %87 : (tensor<?x1xi32>) -> tensor<?x1xi32>
+    %89 = tosa.sub %88, %8 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %90 = tosa.logical_left_shift %87, %89 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %91 = tosa.mul %90, %2, %1 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %92 = tosa.add %91, %3 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
+    %93 = tosa.mul %92, %90, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %94 = tosa.sub %4, %93 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %95 = tosa.mul %92, %94, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %96 = tosa.mul %95, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %97 = tosa.add %92, %96 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %98 = tosa.mul %97, %90, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %99 = tosa.sub %4, %98 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %100 = tosa.mul %97, %99, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %101 = tosa.mul %100, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %102 = tosa.add %97, %101 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %103 = tosa.mul %102, %90, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %104 = tosa.sub %4, %103 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %105 = tosa.mul %102, %104, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %106 = tosa.mul %105, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
+    %107 = tosa.add %102, %106 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %108 = tosa.mul %85, %107, %17 : (tensor<?x6xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x6xi32>
+    %109 = tosa.sub %0, %88 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
+    %110 = tosa.arithmetic_right_shift %108, %109 {round = true} : (tensor<?x6xi32>, tensor<?x1xi32>) -> tensor<?x6xi32>
+    %111 = tosa.rescale %110, %18, %17, %44, %43 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x6xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x6xi8>
+    return %111 : tensor<?x6xi8>
+  }
+}
diff --git a/tests/gold/test_python_api/kws_micronet_s.mlir b/tests/gold/test_python_api/kws_micronet_s.mlir
new file mode 100644
index 0000000..f9cf330
--- /dev/null
+++ b/tests/gold/test_python_api/kws_micronet_s.mlir
@@ -0,0 +1,103 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<1x49x10x1xi8>) -> tensor<1x12xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
+    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %3 = "tosa.const"() <{values = dense<41> : tensor<12xi8>}> : () -> tensor<12xi8>
+    %4 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi32>}> : () -> tensor<12xi32>
+    %5 = "tosa.const"() <{values = dense<-49> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %6 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi32>}> : () -> tensor<12xi32>
+    %7 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12x1x1x196xi8>}> : () -> tensor<12x1x1x196xi8>
+    %8 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<196xi8>}> : () -> tensor<196xi8>
+    %9 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<196xi32>}> : () -> tensor<196xi32>
+    %10 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<196xi32>}> : () -> tensor<196xi32>
+    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<196x1x1x84xi8>}> : () -> tensor<196x1x1x84xi8>
+    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
+    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x84xi8>}> : () -> tensor<1x3x3x84xi8>
+    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
+    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84x1x1x84xi8>}> : () -> tensor<84x1x1x84xi8>
+    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
+    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x84xi8>}> : () -> tensor<1x3x3x84xi8>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84x1x1x84xi8>}> : () -> tensor<84x1x1x84xi8>
+    %28 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
+    %29 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x84xi8>}> : () -> tensor<1x3x3x84xi8>
+    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
+    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84x1x1x112xi8>}> : () -> tensor<84x1x1x112xi8>
+    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi8>}> : () -> tensor<112xi8>
+    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
+    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x112xi8>}> : () -> tensor<1x3x3x112xi8>
+    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi8>}> : () -> tensor<112xi8>
+    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
+    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112x1x1x84xi8>}> : () -> tensor<112x1x1x84xi8>
+    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
+    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x84xi8>}> : () -> tensor<1x3x3x84xi8>
+    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
+    %49 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %50 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %51 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84x10x4x1xi8>}> : () -> tensor<84x10x4x1xi8>
+    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
+    %54 = "tosa.const"() <{values = dense<-5> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %55 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %56 = tosa.conv2d %arg0, %52, %53, %54, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 4, 5, 1, 2>, stride = array<i64: 1, 1>} : (tensor<1x49x10x1xi8>, tensor<84x10x4x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x49x10x84xi32>
+    %57 = tosa.rescale %56, %49, %48, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x49x10x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x49x10x84xi8>
+    %58 = tosa.clamp %57 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x49x10x84xi8>) -> tensor<1x49x10x84xi8>
+    %59 = tosa.reshape %47, %1 : (tensor<1x3x3x84xi8>, !tosa.shape<4>) -> tensor<3x3x84x1xi8>
+    %60 = tosa.depthwise_conv2d %58, %59, %46, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x49x10x84xi8>, tensor<3x3x84x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
+    %61 = tosa.rescale %60, %45, %44, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
+    %62 = tosa.clamp %61 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
+    %63 = tosa.conv2d %62, %43, %42, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<112x1x1x84xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x112xi32>
+    %64 = tosa.rescale %63, %41, %40, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x112xi8>
+    %65 = tosa.clamp %64 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x112xi8>) -> tensor<1x25x5x112xi8>
+    %66 = tosa.reshape %39, %0 : (tensor<1x3x3x112xi8>, !tosa.shape<4>) -> tensor<3x3x112x1xi8>
+    %67 = tosa.depthwise_conv2d %65, %66, %38, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x25x5x112xi8>, tensor<3x3x112x1xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x112xi32>
+    %68 = tosa.rescale %67, %37, %36, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x112xi8>
+    %69 = tosa.clamp %68 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x112xi8>) -> tensor<1x25x5x112xi8>
+    %70 = tosa.conv2d %69, %35, %34, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x112xi8>, tensor<84x1x1x112xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
+    %71 = tosa.rescale %70, %33, %32, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
+    %72 = tosa.clamp %71 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
+    %73 = tosa.reshape %31, %1 : (tensor<1x3x3x84xi8>, !tosa.shape<4>) -> tensor<3x3x84x1xi8>
+    %74 = tosa.depthwise_conv2d %72, %73, %30, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<3x3x84x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
+    %75 = tosa.rescale %74, %29, %28, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
+    %76 = tosa.clamp %75 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
+    %77 = tosa.conv2d %76, %27, %26, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<84x1x1x84xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
+    %78 = tosa.rescale %77, %25, %24, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
+    %79 = tosa.clamp %78 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
+    %80 = tosa.reshape %23, %1 : (tensor<1x3x3x84xi8>, !tosa.shape<4>) -> tensor<3x3x84x1xi8>
+    %81 = tosa.depthwise_conv2d %79, %80, %22, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<3x3x84x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
+    %82 = tosa.rescale %81, %21, %20, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
+    %83 = tosa.clamp %82 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
+    %84 = tosa.conv2d %83, %19, %18, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<84x1x1x84xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
+    %85 = tosa.rescale %84, %17, %16, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
+    %86 = tosa.clamp %85 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
+    %87 = tosa.reshape %15, %1 : (tensor<1x3x3x84xi8>, !tosa.shape<4>) -> tensor<3x3x84x1xi8>
+    %88 = tosa.depthwise_conv2d %86, %87, %14, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<3x3x84x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
+    %89 = tosa.rescale %88, %13, %12, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
+    %90 = tosa.clamp %89 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
+    %91 = tosa.conv2d %90, %11, %10, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<196x1x1x84xi8>, tensor<196xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x196xi32>
+    %92 = tosa.rescale %91, %9, %8, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x196xi32>, tensor<196xi32>, tensor<196xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x196xi8>
+    %93 = tosa.clamp %92 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x196xi8>) -> tensor<1x25x5x196xi8>
+    %94 = tosa.avg_pool2d %93, %55, %55 {acc_type = i32, kernel = array<i64: 25, 5>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x196xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x196xi8>
+    %95 = tosa.conv2d %94, %7, %6, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x196xi8>, tensor<12x1x1x196xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x12xi32>
+    %96 = tosa.rescale %95, %4, %3, %51, %5 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x12xi32>, tensor<12xi32>, tensor<12xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x12xi8>
+    %97 = tosa.reshape %96, %2 : (tensor<1x1x1x12xi8>, !tosa.shape<2>) -> tensor<1x12xi8>
+    return %97 : tensor<1x12xi8>
+  }
+}
diff --git a/tests/gold/test_python_api/mobilenet_v2_1.0_224_quantized_1_default_1.mlir b/tests/gold/test_python_api/mobilenet_v2_1.0_224_quantized_1_default_1.mlir
new file mode 100644
index 0000000..4db4c11
--- /dev/null
+++ b/tests/gold/test_python_api/mobilenet_v2_1.0_224_quantized_1_default_1.mlir
@@ -0,0 +1,427 @@
+module attributes {tfl.description = "TOCO Converted.", tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<1x224x224x3xui8>) -> tensor<1x1001xui8> attributes {tf.entry_function = {inputs = "input", outputs = "output"}} {
+    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %5 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %6 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %7 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %8 = "tosa.const"() <{values = dense<42> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %9 = "tosa.const"() <{values = dense<1769517290> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %10 = "tosa.const"() <{values = dense<-15> : tensor<1xi8>}> : () -> tensor<1xi8>
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+    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1280x1x1x320xi8>}> : () -> tensor<1280x1x1x320xi8>
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+    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<320xi32>}> : () -> tensor<320xi32>
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+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960x1x1x160xi8>}> : () -> tensor<960x1x1x160xi8>
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+    %27 = "tosa.const"() <{values = dense<1908224859> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %28 = "tosa.const"() <{values = dense<38> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %29 = "tosa.const"() <{values = dense<1409905126> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160xi32>}> : () -> tensor<160xi32>
+    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160x1x1x960xi8>}> : () -> tensor<160x1x1x960xi8>
+    %32 = "tosa.const"() <{values = dense<1471261696> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %33 = "tosa.const"() <{values = dense<-26> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
+    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x960xi8>}> : () -> tensor<1x3x3x960xi8>
+    %36 = "tosa.const"() <{values = dense<1403672173> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960x1x1x160xi8>}> : () -> tensor<960x1x1x160xi8>
+    %39 = "tosa.const"() <{values = dense<1886271458> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %40 = "tosa.const"() <{values = dense<1629649814> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %41 = "tosa.const"() <{values = dense<2034086883> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160xi32>}> : () -> tensor<160xi32>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160x1x1x960xi8>}> : () -> tensor<160x1x1x960xi8>
+    %44 = "tosa.const"() <{values = dense<1431685120> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
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+    %47 = "tosa.const"() <{values = dense<1563714083> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
+    %49 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960x1x1x160xi8>}> : () -> tensor<960x1x1x160xi8>
+    %50 = "tosa.const"() <{values = dense<1846357403> : tensor<1xi32>}> : () -> tensor<1xi32>
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+    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160xi32>}> : () -> tensor<160xi32>
+    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160x1x1x576xi8>}> : () -> tensor<160x1x1x576xi8>
+    %54 = "tosa.const"() <{values = dense<2097034112> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %55 = "tosa.const"() <{values = dense<-36> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %56 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
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+    %58 = "tosa.const"() <{values = dense<1885290042> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
+    %60 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576x1x1x96xi8>}> : () -> tensor<576x1x1x96xi8>
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+    %62 = "tosa.const"() <{values = dense<2031709950> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %63 = "tosa.const"() <{values = dense<1666054802> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %64 = "tosa.const"() <{values = dense<26> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %65 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %66 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x576xi8>}> : () -> tensor<96x1x1x576xi8>
+    %67 = "tosa.const"() <{values = dense<1279693056> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %68 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %69 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
+    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x576xi8>}> : () -> tensor<1x3x3x576xi8>
+    %71 = "tosa.const"() <{values = dense<1878841398> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %72 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
+    %73 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576x1x1x96xi8>}> : () -> tensor<576x1x1x96xi8>
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+    %75 = "tosa.const"() <{values = dense<1552338772> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %76 = "tosa.const"() <{values = dense<1758291557> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %77 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %78 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x576xi8>}> : () -> tensor<96x1x1x576xi8>
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+    %81 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
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+    %84 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
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+    %87 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
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+    %89 = "tosa.const"() <{values = dense<2137714944> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %90 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
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+    %93 = "tosa.const"() <{values = dense<3> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %94 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
+    %95 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384x1x1x64xi8>}> : () -> tensor<384x1x1x64xi8>
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+    %97 = "tosa.const"() <{values = dense<1946727039> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %98 = "tosa.const"() <{values = dense<1680680778> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %99 = "tosa.const"() <{values = dense<1619097955> : tensor<1xi32>}> : () -> tensor<1xi32>
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+    %104 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
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+    %116 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
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+    %119 = "tosa.const"() <{values = dense<6> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %120 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
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+    %123 = "tosa.const"() <{values = dense<1999568813> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %124 = "tosa.const"() <{values = dense<1257485775> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %125 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
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+    %136 = "tosa.const"() <{values = dense<-2> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %137 = "tosa.const"() <{values = dense<19> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %138 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
+    %139 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x192xi8>}> : () -> tensor<64x1x1x192xi8>
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+    %141 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
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+    %154 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
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+    %158 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
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+    %163 = "tosa.const"() <{values = dense<1081754833> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %164 = "tosa.const"() <{values = dense<-7> : tensor<1xi8>}> : () -> tensor<1xi8>
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+    %169 = "tosa.const"() <{values = dense<1120997760> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %170 = "tosa.const"() <{values = dense<-10> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %171 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
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+    %174 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
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+    %178 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
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+    %181 = "tosa.const"() <{values = dense<15> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %182 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
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+    %184 = "tosa.const"() <{values = dense<1892639773> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %185 = "tosa.const"() <{values = dense<-24> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %186 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %187 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x1x1x24xi8>}> : () -> tensor<144x1x1x24xi8>
+    %188 = "tosa.const"() <{values = dense<5> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %189 = "tosa.const"() <{values = dense<50> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %190 = "tosa.const"() <{values = dense<1995052007> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %191 = "tosa.const"() <{values = dense<1475367762> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %192 = "tosa.const"() <{values = dense<10> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %193 = "tosa.const"() <{values = dense<11> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %194 = "tosa.const"() <{values = dense<1766066391> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %195 = "tosa.const"() <{values = dense<8> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %196 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %197 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x144xi8>}> : () -> tensor<24x1x1x144xi8>
+    %198 = "tosa.const"() <{values = dense<1458735232> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %199 = "tosa.const"() <{values = dense<-76> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %200 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %201 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x144xi8>}> : () -> tensor<1x3x3x144xi8>
+    %202 = "tosa.const"() <{values = dense<35> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %203 = "tosa.const"() <{values = dense<1472565610> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %204 = "tosa.const"() <{values = dense<16> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %205 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
+    %206 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x1x1x24xi8>}> : () -> tensor<144x1x1x24xi8>
+    %207 = "tosa.const"() <{values = dense<40> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %208 = "tosa.const"() <{values = dense<2113598676> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %209 = "tosa.const"() <{values = dense<-9> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %210 = "tosa.const"() <{values = dense<28> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %211 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %212 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x96xi8>}> : () -> tensor<24x1x1x96xi8>
+    %213 = "tosa.const"() <{values = dense<36> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %214 = "tosa.const"() <{values = dense<1440987008> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %215 = "tosa.const"() <{values = dense<-19> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %216 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %217 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
+    %218 = "tosa.const"() <{values = dense<33> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %219 = "tosa.const"() <{values = dense<1262668951> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %220 = "tosa.const"() <{values = dense<-1> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %221 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %222 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x16xi8>}> : () -> tensor<96x1x1x16xi8>
+    %223 = "tosa.const"() <{values = dense<39> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %224 = "tosa.const"() <{values = dense<1363945730> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %225 = "tosa.const"() <{values = dense<1> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %226 = "tosa.const"() <{values = dense<12> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %227 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %228 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x32xi8>}> : () -> tensor<16x1x1x32xi8>
+    %229 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %230 = "tosa.const"() <{values = dense<1476161024> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %231 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %232 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x32xi8>}> : () -> tensor<1x3x3x32xi8>
+    %233 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %234 = "tosa.const"() <{values = dense<1550200454> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %235 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %236 = "tosa.const"() <{values = dense<-6> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %237 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %238 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x3x3x3xi8>}> : () -> tensor<32x3x3x3xi8>
+    %239 = "tosa.const"() <{values = dense<-70> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %240 = "tosa.const"() <{values = dense<58> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %241 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %242 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %243 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %244 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %245 = tosa.rescale %arg0, %241, %242, %243, %244 {input_unsigned = true, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x224x224x3xui8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x224x224x3xi8>
+    %246 = tosa.conv2d %245, %238, %237, %244, %236 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x224x224x3xi8>, tensor<32x3x3x3xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x32xi32>
+    %247 = tosa.rescale %246, %234, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x32xi8>
+    %248 = tosa.reshape %232, %6 : (tensor<1x3x3x32xi8>, !tosa.shape<4>) -> tensor<3x3x32x1xi8>
+    %249 = tosa.depthwise_conv2d %247, %248, %231, %243, %233 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x112x112x32xi8>, tensor<3x3x32x1xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x32xi32>
+    %250 = tosa.rescale %249, %230, %229, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x32xi8>
+    %251 = tosa.conv2d %250, %228, %227, %243, %226 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x112x112x32xi8>, tensor<16x1x1x32xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x16xi32>
+    %252 = tosa.rescale %251, %224, %223, %235, %225 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x16xi8>
+    %253 = tosa.conv2d %252, %222, %221, %225, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x112x112x16xi8>, tensor<96x1x1x16xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x96xi32>
+    %254 = tosa.rescale %253, %219, %218, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x96xi8>
+    %255 = tosa.reshape %217, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
+    %256 = tosa.depthwise_conv2d %254, %255, %216, %243, %215 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x112x112x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x96xi32>
+    %257 = tosa.rescale %256, %214, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x96xi8>
+    %258 = tosa.conv2d %257, %212, %211, %243, %210 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x96xi8>, tensor<24x1x1x96xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x24xi32>
+    %259 = tosa.rescale %258, %208, %207, %235, %209 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
+    %260 = tosa.conv2d %259, %206, %205, %209, %204 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x24xi8>, tensor<144x1x1x24xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
+    %261 = tosa.rescale %260, %203, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
+    %262 = tosa.reshape %201, %4 : (tensor<1x3x3x144xi8>, !tosa.shape<4>) -> tensor<3x3x144x1xi8>
+    %263 = tosa.depthwise_conv2d %261, %262, %200, %243, %199 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x56x56x144xi8>, tensor<3x3x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
+    %264 = tosa.rescale %263, %198, %218, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
+    %265 = tosa.conv2d %264, %197, %196, %243, %236 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x144xi8>, tensor<24x1x1x144xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x24xi32>
+    %266 = tosa.rescale %265, %194, %207, %235, %195 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
+    %267 = tosa.rescale %266, %241, %193, %195, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
+    %268 = tosa.rescale %259, %241, %192, %209, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
+    %269 = tosa.rescale %268, %191, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
+    %270 = tosa.add %267, %269 : (tensor<1x56x56x24xi32>, tensor<1x56x56x24xi32>) -> tensor<1x56x56x24xi32>
+    %271 = tosa.rescale %270, %190, %189, %235, %188 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
+    %272 = tosa.conv2d %271, %187, %186, %188, %185 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x24xi8>, tensor<144x1x1x24xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
+    %273 = tosa.rescale %272, %184, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
+    %274 = tosa.reshape %183, %4 : (tensor<1x3x3x144xi8>, !tosa.shape<4>) -> tensor<3x3x144x1xi8>
+    %275 = tosa.depthwise_conv2d %273, %274, %182, %243, %181 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x56x56x144xi8>, tensor<3x3x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x144xi32>
+    %276 = tosa.rescale %275, %180, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x144xi8>
+    %277 = tosa.conv2d %276, %179, %178, %243, %177 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x144xi8>, tensor<32x1x1x144xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x32xi32>
+    %278 = tosa.rescale %277, %176, %207, %235, %220 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
+    %279 = tosa.conv2d %278, %175, %174, %220, %244 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x32xi8>, tensor<192x1x1x32xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
+    %280 = tosa.rescale %279, %173, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
+    %281 = tosa.reshape %172, %3 : (tensor<1x3x3x192xi8>, !tosa.shape<4>) -> tensor<3x3x192x1xi8>
+    %282 = tosa.depthwise_conv2d %280, %281, %171, %243, %170 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x28x28x192xi8>, tensor<3x3x192x1xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
+    %283 = tosa.rescale %282, %169, %168, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
+    %284 = tosa.conv2d %283, %167, %166, %243, %165 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x192xi8>, tensor<32x1x1x192xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x32xi32>
+    %285 = tosa.rescale %284, %163, %223, %235, %164 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
+    %286 = tosa.rescale %285, %241, %193, %164, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
+    %287 = tosa.rescale %278, %241, %192, %220, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
+    %288 = tosa.rescale %287, %162, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
+    %289 = tosa.add %286, %288 : (tensor<1x28x28x32xi32>, tensor<1x28x28x32xi32>) -> tensor<1x28x28x32xi32>
+    %290 = tosa.rescale %289, %161, %189, %235, %160 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
+    %291 = tosa.conv2d %290, %159, %158, %160, %157 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x32xi8>, tensor<192x1x1x32xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
+    %292 = tosa.rescale %291, %156, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
+    %293 = tosa.reshape %155, %3 : (tensor<1x3x3x192xi8>, !tosa.shape<4>) -> tensor<3x3x192x1xi8>
+    %294 = tosa.depthwise_conv2d %292, %293, %154, %243, %153 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x28x28x192xi8>, tensor<3x3x192x1xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
+    %295 = tosa.rescale %294, %152, %168, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
+    %296 = tosa.conv2d %295, %151, %150, %243, %244 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x192xi8>, tensor<32x1x1x192xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x32xi32>
+    %297 = tosa.rescale %296, %148, %207, %235, %149 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
+    %298 = tosa.rescale %297, %241, %192, %149, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
+    %299 = tosa.rescale %298, %147, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
+    %300 = tosa.rescale %290, %241, %193, %160, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
+    %301 = tosa.add %299, %300 : (tensor<1x28x28x32xi32>, tensor<1x28x28x32xi32>) -> tensor<1x28x28x32xi32>
+    %302 = tosa.rescale %301, %146, %189, %235, %149 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
+    %303 = tosa.conv2d %302, %145, %144, %149, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x32xi8>, tensor<192x1x1x32xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
+    %304 = tosa.rescale %303, %143, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
+    %305 = tosa.reshape %142, %3 : (tensor<1x3x3x192xi8>, !tosa.shape<4>) -> tensor<3x3x192x1xi8>
+    %306 = tosa.depthwise_conv2d %304, %305, %141, %243, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x28x28x192xi8>, tensor<3x3x192x1xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x192xi32>
+    %307 = tosa.rescale %306, %140, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x192xi8>
+    %308 = tosa.conv2d %307, %139, %138, %243, %137 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x192xi8>, tensor<64x1x1x192xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x64xi32>
+    %309 = tosa.rescale %308, %135, %207, %235, %136 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
+    %310 = tosa.conv2d %309, %134, %133, %136, %132 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x64xi8>, tensor<384x1x1x64xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
+    %311 = tosa.rescale %310, %131, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
+    %312 = tosa.reshape %130, %2 : (tensor<1x3x3x384xi8>, !tosa.shape<4>) -> tensor<3x3x384x1xi8>
+    %313 = tosa.depthwise_conv2d %311, %312, %129, %243, %128 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<3x3x384x1xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
+    %314 = tosa.rescale %313, %127, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
+    %315 = tosa.conv2d %314, %126, %125, %243, %149 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<64x1x1x384xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x64xi32>
+    %316 = tosa.rescale %315, %124, %223, %235, %215 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
+    %317 = tosa.rescale %316, %241, %192, %215, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %318 = tosa.rescale %317, %123, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %319 = tosa.rescale %309, %241, %193, %136, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %320 = tosa.add %318, %319 : (tensor<1x14x14x64xi32>, tensor<1x14x14x64xi32>) -> tensor<1x14x14x64xi32>
+    %321 = tosa.rescale %320, %122, %189, %235, %236 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
+    %322 = tosa.conv2d %321, %121, %120, %236, %119 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x64xi8>, tensor<384x1x1x64xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
+    %323 = tosa.rescale %322, %118, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
+    %324 = tosa.reshape %117, %2 : (tensor<1x3x3x384xi8>, !tosa.shape<4>) -> tensor<3x3x384x1xi8>
+    %325 = tosa.depthwise_conv2d %323, %324, %116, %243, %188 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<3x3x384x1xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
+    %326 = tosa.rescale %325, %115, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
+    %327 = tosa.conv2d %326, %114, %113, %243, %132 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<64x1x1x384xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x64xi32>
+    %328 = tosa.rescale %327, %111, %223, %235, %112 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
+    %329 = tosa.rescale %328, %241, %192, %112, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %330 = tosa.rescale %329, %110, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %331 = tosa.rescale %321, %241, %193, %236, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %332 = tosa.add %330, %331 : (tensor<1x14x14x64xi32>, tensor<1x14x14x64xi32>) -> tensor<1x14x14x64xi32>
+    %333 = tosa.rescale %332, %109, %189, %235, %149 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
+    %334 = tosa.conv2d %333, %108, %107, %149, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x64xi8>, tensor<384x1x1x64xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
+    %335 = tosa.rescale %334, %106, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
+    %336 = tosa.reshape %105, %2 : (tensor<1x3x3x384xi8>, !tosa.shape<4>) -> tensor<3x3x384x1xi8>
+    %337 = tosa.depthwise_conv2d %335, %336, %104, %243, %103 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<3x3x384x1xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
+    %338 = tosa.rescale %337, %102, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
+    %339 = tosa.conv2d %338, %101, %100, %243, %204 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<64x1x1x384xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x64xi32>
+    %340 = tosa.rescale %339, %99, %223, %235, %236 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
+    %341 = tosa.rescale %340, %241, %192, %236, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %342 = tosa.rescale %341, %98, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %343 = tosa.rescale %333, %241, %193, %149, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
+    %344 = tosa.add %342, %343 : (tensor<1x14x14x64xi32>, tensor<1x14x14x64xi32>) -> tensor<1x14x14x64xi32>
+    %345 = tosa.rescale %344, %97, %189, %235, %96 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
+    %346 = tosa.conv2d %345, %95, %94, %96, %93 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x64xi8>, tensor<384x1x1x64xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
+    %347 = tosa.rescale %346, %92, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
+    %348 = tosa.reshape %91, %2 : (tensor<1x3x3x384xi8>, !tosa.shape<4>) -> tensor<3x3x384x1xi8>
+    %349 = tosa.depthwise_conv2d %347, %348, %90, %243, %181 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<3x3x384x1xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
+    %350 = tosa.rescale %349, %89, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
+    %351 = tosa.conv2d %350, %88, %87, %243, %225 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<96x1x1x384xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x96xi32>
+    %352 = tosa.rescale %351, %86, %207, %235, %225 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
+    %353 = tosa.conv2d %352, %85, %84, %225, %119 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x96xi8>, tensor<576x1x1x96xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
+    %354 = tosa.rescale %353, %83, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
+    %355 = tosa.reshape %82, %1 : (tensor<1x3x3x576xi8>, !tosa.shape<4>) -> tensor<3x3x576x1xi8>
+    %356 = tosa.depthwise_conv2d %354, %355, %81, %243, %80 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x576xi8>, tensor<3x3x576x1xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
+    %357 = tosa.rescale %356, %79, %168, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
+    %358 = tosa.conv2d %357, %78, %77, %243, %195 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x576xi8>, tensor<96x1x1x576xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x96xi32>
+    %359 = tosa.rescale %358, %76, %207, %235, %220 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
+    %360 = tosa.rescale %359, %241, %192, %220, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
+    %361 = tosa.rescale %360, %75, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
+    %362 = tosa.rescale %352, %241, %193, %225, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
+    %363 = tosa.add %361, %362 : (tensor<1x14x14x96xi32>, tensor<1x14x14x96xi32>) -> tensor<1x14x14x96xi32>
+    %364 = tosa.rescale %363, %74, %189, %235, %220 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
+    %365 = tosa.conv2d %364, %73, %72, %220, %192 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x96xi8>, tensor<576x1x1x96xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
+    %366 = tosa.rescale %365, %71, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
+    %367 = tosa.reshape %70, %1 : (tensor<1x3x3x576xi8>, !tosa.shape<4>) -> tensor<3x3x576x1xi8>
+    %368 = tosa.depthwise_conv2d %366, %367, %69, %243, %68 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x576xi8>, tensor<3x3x576x1xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
+    %369 = tosa.rescale %368, %67, %168, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
+    %370 = tosa.conv2d %369, %66, %65, %243, %64 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x576xi8>, tensor<96x1x1x576xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x96xi32>
+    %371 = tosa.rescale %370, %63, %223, %235, %220 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
+    %372 = tosa.rescale %371, %241, %193, %220, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
+    %373 = tosa.rescale %364, %241, %192, %220, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
+    %374 = tosa.rescale %373, %62, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
+    %375 = tosa.add %372, %374 : (tensor<1x14x14x96xi32>, tensor<1x14x14x96xi32>) -> tensor<1x14x14x96xi32>
+    %376 = tosa.rescale %375, %61, %189, %235, %136 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
+    %377 = tosa.conv2d %376, %60, %59, %136, %112 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x96xi8>, tensor<576x1x1x96xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
+    %378 = tosa.rescale %377, %58, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
+    %379 = tosa.reshape %57, %1 : (tensor<1x3x3x576xi8>, !tosa.shape<4>) -> tensor<3x3x576x1xi8>
+    %380 = tosa.depthwise_conv2d %378, %379, %56, %243, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x14x14x576xi8>, tensor<3x3x576x1xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x576xi32>
+    %381 = tosa.rescale %380, %54, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x576xi8>
+    %382 = tosa.conv2d %381, %53, %52, %243, %226 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x576xi8>, tensor<160x1x1x576xi8>, tensor<160xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x160xi32>
+    %383 = tosa.rescale %382, %50, %207, %235, %51 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
+    %384 = tosa.conv2d %383, %49, %48, %51, %157 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x160xi8>, tensor<960x1x1x160xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
+    %385 = tosa.rescale %384, %47, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
+    %386 = tosa.reshape %46, %0 : (tensor<1x3x3x960xi8>, !tosa.shape<4>) -> tensor<3x3x960x1xi8>
+    %387 = tosa.depthwise_conv2d %385, %386, %45, %243, %137 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<3x3x960x1xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
+    %388 = tosa.rescale %387, %44, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
+    %389 = tosa.conv2d %388, %43, %42, %243, %193 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<160x1x1x960xi8>, tensor<160xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x160xi32>
+    %390 = tosa.rescale %389, %41, %207, %235, %225 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
+    %391 = tosa.rescale %390, %241, %192, %225, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
+    %392 = tosa.rescale %391, %40, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
+    %393 = tosa.rescale %383, %241, %193, %51, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
+    %394 = tosa.add %392, %393 : (tensor<1x7x7x160xi32>, tensor<1x7x7x160xi32>) -> tensor<1x7x7x160xi32>
+    %395 = tosa.rescale %394, %39, %189, %235, %119 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
+    %396 = tosa.conv2d %395, %38, %37, %119, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x160xi8>, tensor<960x1x1x160xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
+    %397 = tosa.rescale %396, %36, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
+    %398 = tosa.reshape %35, %0 : (tensor<1x3x3x960xi8>, !tosa.shape<4>) -> tensor<3x3x960x1xi8>
+    %399 = tosa.depthwise_conv2d %397, %398, %34, %243, %33 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<3x3x960x1xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
+    %400 = tosa.rescale %399, %32, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
+    %401 = tosa.conv2d %400, %31, %30, %243, %93 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<160x1x1x960xi8>, tensor<160xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x160xi32>
+    %402 = tosa.rescale %401, %29, %28, %235, %188 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
+    %403 = tosa.rescale %402, %241, %193, %188, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
+    %404 = tosa.rescale %395, %241, %192, %119, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
+    %405 = tosa.rescale %404, %27, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
+    %406 = tosa.add %403, %405 : (tensor<1x7x7x160xi32>, tensor<1x7x7x160xi32>) -> tensor<1x7x7x160xi32>
+    %407 = tosa.rescale %406, %26, %189, %235, %93 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
+    %408 = tosa.conv2d %407, %25, %24, %93, %157 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x160xi8>, tensor<960x1x1x160xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
+    %409 = tosa.rescale %408, %23, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
+    %410 = tosa.reshape %22, %0 : (tensor<1x3x3x960xi8>, !tosa.shape<4>) -> tensor<3x3x960x1xi8>
+    %411 = tosa.depthwise_conv2d %409, %410, %21, %243, %20 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<3x3x960x1xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
+    %412 = tosa.rescale %411, %19, %218, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
+    %413 = tosa.conv2d %412, %18, %17, %243, %177 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<320x1x1x960xi8>, tensor<320xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x320xi32>
+    %414 = tosa.rescale %413, %16, %207, %235, %160 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x320xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x320xi8>
+    %415 = tosa.conv2d %414, %15, %14, %160, %132 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x320xi8>, tensor<1280x1x1x320xi8>, tensor<1280xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1280xi32>
+    %416 = tosa.rescale %415, %13, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1280xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1280xi8>
+    %417 = tosa.avg_pool2d %416, %244, %244 {acc_type = i32, kernel = array<i64: 7, 7>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1280xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x1280xi8>
+    %418 = tosa.conv2d %417, %12, %11, %243, %10 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x1280xi8>, tensor<1001x1x1x1280xi8>, tensor<1001xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x1001xi32>
+    %419 = tosa.rescale %418, %9, %8, %235, %239 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x1001xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x1001xi8>
+    %420 = tosa.reshape %419, %7 : (tensor<1x1x1x1001xi8>, !tosa.shape<2>) -> tensor<1x1001xi8>
+    %421 = tosa.rescale %420, %241, %242, %239, %240 {input_unsigned = false, output_unsigned = true, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1001xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1001xui8>
+    return %421 : tensor<1x1001xui8>
+  }
+}
diff --git a/tests/gold/test_python_api/ssd_mobilenet_v3_int8.mlir b/tests/gold/test_python_api/ssd_mobilenet_v3_int8.mlir
new file mode 100644
index 0000000..e230308
--- /dev/null
+++ b/tests/gold/test_python_api/ssd_mobilenet_v3_int8.mlir
@@ -0,0 +1,993 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.15.0\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<1x320x320x3xi8>) -> (tensor<1x2034x91xi8>, tensor<1x2034x4xi8>) attributes {tf.entry_function = {inputs = "normalized_input_image_tensor", outputs = "raw_outputs/class_predictions,raw_outputs/box_encodings"}} {
+    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %5 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %6 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %7 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %8 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %9 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %10 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %11 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %12 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
+    %14 = "tosa.const"() <{values = dense<1862935214> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %15 = "tosa.const"() <{values = dense<1553028373> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %16 = "tosa.const"() <{values = dense<1582603170> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %17 = "tosa.const"() <{values = dense<1187055602> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %18 = "tosa.const"() <{values = dense<1118715085> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %19 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<3xindex>} : () -> !tosa.shape<3>
+    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<546xi8>}> : () -> tensor<546xi8>
+    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<546xi32>}> : () -> tensor<546xi32>
+    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<546xi32>}> : () -> tensor<546xi32>
+    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<546x1x1x128xi8>}> : () -> tensor<546x1x1x128xi8>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x128xi8>}> : () -> tensor<1x3x3x128xi8>
+    %28 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<3xindex>} : () -> !tosa.shape<3>
+    %29 = "tosa.const"() <{values = dense<1835346993> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %30 = "tosa.const"() <{values = dense<1415988625> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %31 = "tosa.const"() <{values = dense<1183143852> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %32 = "tosa.const"() <{values = dense<1124158657> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %33 = "tosa.const"() <{values = dense<1214666873> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %34 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
+    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %37 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x128xi8>}> : () -> tensor<24x1x1x128xi8>
+    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
+    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x128xi8>}> : () -> tensor<1x3x3x128xi8>
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+    %404 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %405 = "tosa.const"() <{values = dense<-119> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %406 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %407 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x240xi8>}> : () -> tensor<1x5x5x240xi8>
+    %408 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
+    %409 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
+    %410 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %411 = "tosa.const"() <{values = dense<-5> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %412 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
+    %413 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240x1x1x40xi8>}> : () -> tensor<240x1x1x40xi8>
+    %414 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi8>}> : () -> tensor<40xi8>
+    %415 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
+    %416 = "tosa.const"() <{values = dense<-12> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %417 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
+    %418 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40x1x1x96xi8>}> : () -> tensor<40x1x1x96xi8>
+    %419 = "tosa.const"() <{values = dense<-110> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %420 = "tosa.const"() <{values = dense<36> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %421 = "tosa.const"() <{values = dense<1770674688> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %422 = "tosa.const"() <{values = dense<1982666603> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %423 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %424 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %425 = "tosa.const"() <{values = dense<-16> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %426 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %427 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x24xi8>}> : () -> tensor<96x1x1x24xi8>
+    %428 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
+    %429 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %430 = "tosa.const"() <{values = dense<-125> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %431 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %432 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x96xi8>}> : () -> tensor<24x1x1x96xi8>
+    %433 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
+    %434 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %435 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %436 = "tosa.const"() <{values = dense<-11> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %437 = "tosa.const"() <{values = dense<-120> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %438 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %439 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x96xi8>}> : () -> tensor<1x5x5x96xi8>
+    %440 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
+    %441 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %442 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %443 = "tosa.const"() <{values = dense<12> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %444 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %445 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x24xi8>}> : () -> tensor<96x1x1x24xi8>
+    %446 = "tosa.const"() <{values = dense<1> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %447 = "tosa.const"() <{values = dense<1085834602> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %448 = "tosa.const"() <{values = dense<1899624818> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %449 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
+    %450 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %451 = "tosa.const"() <{values = dense<14> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %452 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %453 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x88xi8>}> : () -> tensor<24x1x1x88xi8>
+    %454 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi8>}> : () -> tensor<88xi8>
+    %455 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi32>}> : () -> tensor<88xi32>
+    %456 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi32>}> : () -> tensor<88xi32>
+    %457 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x88xi8>}> : () -> tensor<1x3x3x88xi8>
+    %458 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi8>}> : () -> tensor<88xi8>
+    %459 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi32>}> : () -> tensor<88xi32>
+    %460 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi32>}> : () -> tensor<88xi32>
+    %461 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88x1x1x24xi8>}> : () -> tensor<88x1x1x24xi8>
+    %462 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
+    %463 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %464 = "tosa.const"() <{values = dense<-3> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %465 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
+    %466 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x72xi8>}> : () -> tensor<24x1x1x72xi8>
+    %467 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi8>}> : () -> tensor<72xi8>
+    %468 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
+    %469 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
+    %470 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x72xi8>}> : () -> tensor<1x3x3x72xi8>
+    %471 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi8>}> : () -> tensor<72xi8>
+    %472 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
+    %473 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
+    %474 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72x1x1x16xi8>}> : () -> tensor<72x1x1x16xi8>
+    %475 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
+    %476 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %477 = "tosa.const"() <{values = dense<-22> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %478 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %479 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x16xi8>}> : () -> tensor<16x1x1x16xi8>
+    %480 = "tosa.const"() <{values = dense<38> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %481 = "tosa.const"() <{values = dense<1082344576> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %482 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %483 = "tosa.const"() <{values = dense<1082196480> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %484 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %485 = "tosa.const"() <{values = dense<127> : tensor<i8>}> : () -> tensor<i8>
+    %486 = "tosa.const"() <{values = dense<127> : tensor<i8>}> : () -> tensor<i8>
+    %487 = "tosa.const"() <{values = dense<49> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %488 = "tosa.const"() <{values = dense<1077969129> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %489 = tosa.const_shape  {values = dense<1> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %490 = "tosa.const"() <{values = dense<11> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %491 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %492 = "tosa.const"() <{values = dense<1529543979> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %493 = "tosa.const"() <{values = dense<10> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %494 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %495 = "tosa.const"() <{values = dense<127> : tensor<i8>}> : () -> tensor<i8>
+    %496 = "tosa.const"() <{values = dense<127> : tensor<i8>}> : () -> tensor<i8>
+    %497 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
+    %498 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %499 = "tosa.const"() <{values = dense<-51> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %500 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %501 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x8xi8>}> : () -> tensor<16x1x1x8xi8>
+    %502 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi8>}> : () -> tensor<8xi8>
+    %503 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
+    %504 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
+    %505 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8x1x1x16xi8>}> : () -> tensor<8x1x1x16xi8>
+    %506 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
+    %507 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %508 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %509 = "tosa.const"() <{values = dense<-127> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %510 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %511 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x16xi8>}> : () -> tensor<1x3x3x16xi8>
+    %512 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
+    %513 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
+    %514 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %515 = "tosa.const"() <{values = dense<-45> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %516 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %517 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x3x3x3xi8>}> : () -> tensor<16x3x3x3xi8>
+    %518 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %519 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %520 = tosa.conv2d %arg0, %517, %518, %519, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x320x320x3xi8>, tensor<16x3x3x3xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x160x160x16xi32>
+    %521 = tosa.rescale %520, %514, %513, %516, %515 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x160x160x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x160x160x16xi8>
+    %522 = tosa.table %521, %512 : (tensor<1x160x160x16xi8>, tensor<256xi8>) -> tensor<1x160x160x16xi8>
+    %523 = tosa.reshape %511, %12 : (tensor<1x3x3x16xi8>, !tosa.shape<4>) -> tensor<3x3x16x1xi8>
+    %524 = tosa.depthwise_conv2d %522, %523, %510, %509, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x160x160x16xi8>, tensor<3x3x16x1xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x80x80x16xi32>
+    %525 = tosa.rescale %524, %507, %506, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x80x80x16xi8>
+    %526 = tosa.clamp %525 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x80x80x16xi8>) -> tensor<1x80x80x16xi8>
+    %527 = tosa.avg_pool2d %526, %519, %519 {acc_type = i32, kernel = array<i64: 80, 80>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x80x80x16xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x16xi8>
+    %528 = tosa.conv2d %527, %505, %504, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x16xi8>, tensor<8x1x1x16xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x8xi32>
+    %529 = tosa.rescale %528, %503, %502, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x8xi8>
+    %530 = tosa.clamp %529 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x8xi8>) -> tensor<1x1x1x8xi8>
+    %531 = tosa.conv2d %530, %501, %500, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x8xi8>, tensor<16x1x1x8xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x16xi32>
+    %532 = tosa.rescale %531, %498, %497, %516, %499 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x16xi8>
+    %533 = tosa.rescale %532, %494, %493, %499, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x16xi32>
+    %534 = tosa.rescale %533, %492, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x16xi32>
+    %535 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %536 = tosa.reshape %535, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %537 = tosa.add %534, %536 : (tensor<1x1x1x16xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x16xi32>
+    %538 = tosa.rescale %537, %488, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x16xi8>
+    %539 = tosa.clamp %538 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x16xi8>) -> tensor<1x1x1x16xi8>
+    %540 = tosa.rescale %539, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x16xi32>
+    %541 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %542 = tosa.reshape %541, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %543 = tosa.mul %540, %542, %519 : (tensor<1x1x1x16xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x16xi32>
+    %544 = tosa.rescale %543, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x16xi8>
+    %545 = tosa.rescale %526, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x80x80x16xi32>
+    %546 = tosa.rescale %544, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x16xi32>
+    %547 = tosa.mul %545, %546, %519 : (tensor<1x80x80x16xi32>, tensor<1x1x1x16xi32>, tensor<1xi8>) -> tensor<1x80x80x16xi32>
+    %548 = tosa.rescale %547, %481, %480, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x80x80x16xi8>
+    %549 = tosa.conv2d %548, %479, %478, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x80x80x16xi8>, tensor<16x1x1x16xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x80x80x16xi32>
+    %550 = tosa.rescale %549, %476, %475, %516, %477 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x80x80x16xi8>
+    %551 = tosa.conv2d %550, %474, %473, %477, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x80x80x16xi8>, tensor<72x1x1x16xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x80x80x72xi32>
+    %552 = tosa.rescale %551, %472, %471, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x80x80x72xi8>
+    %553 = tosa.clamp %552 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x80x80x72xi8>) -> tensor<1x80x80x72xi8>
+    %554 = tosa.reshape %470, %11 : (tensor<1x3x3x72xi8>, !tosa.shape<4>) -> tensor<3x3x72x1xi8>
+    %555 = tosa.depthwise_conv2d %553, %554, %469, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x80x80x72xi8>, tensor<3x3x72x1xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x72xi32>
+    %556 = tosa.rescale %555, %468, %467, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x72xi8>
+    %557 = tosa.clamp %556 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x40x40x72xi8>) -> tensor<1x40x40x72xi8>
+    %558 = tosa.conv2d %557, %466, %465, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x40x40x72xi8>, tensor<24x1x1x72xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x24xi32>
+    %559 = tosa.rescale %558, %463, %462, %516, %464 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x24xi8>
+    %560 = tosa.conv2d %559, %461, %460, %464, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x40x40x24xi8>, tensor<88x1x1x24xi8>, tensor<88xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x88xi32>
+    %561 = tosa.rescale %560, %459, %458, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x88xi32>, tensor<88xi32>, tensor<88xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x88xi8>
+    %562 = tosa.clamp %561 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x40x40x88xi8>) -> tensor<1x40x40x88xi8>
+    %563 = tosa.reshape %457, %10 : (tensor<1x3x3x88xi8>, !tosa.shape<4>) -> tensor<3x3x88x1xi8>
+    %564 = tosa.depthwise_conv2d %562, %563, %456, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x40x40x88xi8>, tensor<3x3x88x1xi8>, tensor<88xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x88xi32>
+    %565 = tosa.rescale %564, %455, %454, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x88xi32>, tensor<88xi32>, tensor<88xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x88xi8>
+    %566 = tosa.clamp %565 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x40x40x88xi8>) -> tensor<1x40x40x88xi8>
+    %567 = tosa.conv2d %566, %453, %452, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x40x40x88xi8>, tensor<24x1x1x88xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x24xi32>
+    %568 = tosa.rescale %567, %450, %449, %516, %451 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x24xi8>
+    %569 = tosa.rescale %568, %494, %490, %451, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x40x40x24xi32>
+    %570 = tosa.rescale %559, %494, %493, %464, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x40x40x24xi32>
+    %571 = tosa.rescale %570, %448, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x40x40x24xi32>
+    %572 = tosa.add %569, %571 : (tensor<1x40x40x24xi32>, tensor<1x40x40x24xi32>) -> tensor<1x40x40x24xi32>
+    %573 = tosa.rescale %572, %447, %487, %516, %446 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x24xi8>
+    %574 = tosa.conv2d %573, %445, %444, %446, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x40x40x24xi8>, tensor<96x1x1x24xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x96xi32>
+    %575 = tosa.rescale %574, %442, %441, %516, %443 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x96xi8>
+    %576 = tosa.table %575, %440 : (tensor<1x40x40x96xi8>, tensor<256xi8>) -> tensor<1x40x40x96xi8>
+    %577 = tosa.reshape %439, %9 : (tensor<1x5x5x96xi8>, !tosa.shape<4>) -> tensor<5x5x96x1xi8>
+    %578 = tosa.depthwise_conv2d %576, %577, %438, %437, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 2, 1, 2>, stride = array<i64: 2, 2>} : (tensor<1x40x40x96xi8>, tensor<5x5x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x96xi32>
+    %579 = tosa.rescale %578, %435, %434, %516, %436 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x96xi8>
+    %580 = tosa.table %579, %433 : (tensor<1x20x20x96xi8>, tensor<256xi8>) -> tensor<1x20x20x96xi8>
+    %581 = tosa.avg_pool2d %580, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x96xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x96xi8>
+    %582 = tosa.conv2d %581, %432, %431, %430, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x96xi8>, tensor<24x1x1x96xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x24xi32>
+    %583 = tosa.rescale %582, %429, %428, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x24xi8>
+    %584 = tosa.clamp %583 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x24xi8>) -> tensor<1x1x1x24xi8>
+    %585 = tosa.conv2d %584, %427, %426, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x24xi8>, tensor<96x1x1x24xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x96xi32>
+    %586 = tosa.rescale %585, %424, %423, %516, %425 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x96xi8>
+    %587 = tosa.rescale %586, %494, %493, %425, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x96xi32>
+    %588 = tosa.rescale %587, %422, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x96xi32>
+    %589 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %590 = tosa.reshape %589, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %591 = tosa.add %588, %590 : (tensor<1x1x1x96xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x96xi32>
+    %592 = tosa.rescale %591, %488, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x96xi8>
+    %593 = tosa.clamp %592 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x96xi8>) -> tensor<1x1x1x96xi8>
+    %594 = tosa.rescale %593, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x96xi32>
+    %595 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %596 = tosa.reshape %595, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %597 = tosa.mul %594, %596, %519 : (tensor<1x1x1x96xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x96xi32>
+    %598 = tosa.rescale %597, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x96xi8>
+    %599 = tosa.rescale %580, %494, %484, %430, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x96xi32>
+    %600 = tosa.rescale %598, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x96xi32>
+    %601 = tosa.mul %599, %600, %519 : (tensor<1x20x20x96xi32>, tensor<1x1x1x96xi32>, tensor<1xi8>) -> tensor<1x20x20x96xi32>
+    %602 = tosa.rescale %601, %421, %420, %516, %419 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x96xi8>
+    %603 = tosa.conv2d %602, %418, %417, %419, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x96xi8>, tensor<40x1x1x96xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x40xi32>
+    %604 = tosa.rescale %603, %415, %414, %516, %416 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
+    %605 = tosa.conv2d %604, %413, %412, %416, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x40xi8>, tensor<240x1x1x40xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
+    %606 = tosa.rescale %605, %410, %409, %516, %411 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
+    %607 = tosa.table %606, %408 : (tensor<1x20x20x240xi8>, tensor<256xi8>) -> tensor<1x20x20x240xi8>
+    %608 = tosa.reshape %407, %8 : (tensor<1x5x5x240xi8>, !tosa.shape<4>) -> tensor<5x5x240x1xi8>
+    %609 = tosa.depthwise_conv2d %607, %608, %406, %405, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<5x5x240x1xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
+    %610 = tosa.rescale %609, %404, %403, %516, %436 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
+    %611 = tosa.table %610, %402 : (tensor<1x20x20x240xi8>, tensor<256xi8>) -> tensor<1x20x20x240xi8>
+    %612 = tosa.avg_pool2d %611, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
+    %613 = tosa.conv2d %612, %401, %400, %399, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x240xi8>, tensor<64x1x1x240xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x64xi32>
+    %614 = tosa.rescale %613, %398, %397, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x64xi8>
+    %615 = tosa.clamp %614 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x64xi8>) -> tensor<1x1x1x64xi8>
+    %616 = tosa.conv2d %615, %396, %395, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x64xi8>, tensor<240x1x1x64xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x240xi32>
+    %617 = tosa.rescale %616, %393, %392, %516, %394 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
+    %618 = tosa.rescale %617, %494, %493, %394, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
+    %619 = tosa.rescale %618, %391, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
+    %620 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %621 = tosa.reshape %620, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %622 = tosa.add %619, %621 : (tensor<1x1x1x240xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x240xi32>
+    %623 = tosa.rescale %622, %390, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
+    %624 = tosa.clamp %623 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x240xi8>) -> tensor<1x1x1x240xi8>
+    %625 = tosa.rescale %624, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
+    %626 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %627 = tosa.reshape %626, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %628 = tosa.mul %625, %627, %519 : (tensor<1x1x1x240xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi32>
+    %629 = tosa.rescale %628, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
+    %630 = tosa.rescale %611, %494, %484, %399, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x240xi32>
+    %631 = tosa.rescale %629, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
+    %632 = tosa.mul %630, %631, %519 : (tensor<1x20x20x240xi32>, tensor<1x1x1x240xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
+    %633 = tosa.rescale %632, %389, %388, %516, %387 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
+    %634 = tosa.conv2d %633, %386, %385, %387, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<40x1x1x240xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x40xi32>
+    %635 = tosa.rescale %634, %383, %382, %516, %384 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
+    %636 = tosa.rescale %635, %494, %490, %384, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
+    %637 = tosa.rescale %604, %494, %493, %416, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
+    %638 = tosa.rescale %637, %381, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
+    %639 = tosa.add %636, %638 : (tensor<1x20x20x40xi32>, tensor<1x20x20x40xi32>) -> tensor<1x20x20x40xi32>
+    %640 = tosa.rescale %639, %380, %379, %516, %519 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
+    %641 = tosa.conv2d %640, %378, %377, %519, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x40xi8>, tensor<240x1x1x40xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
+    %642 = tosa.rescale %641, %376, %375, %516, %491 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
+    %643 = tosa.table %642, %374 : (tensor<1x20x20x240xi8>, tensor<256xi8>) -> tensor<1x20x20x240xi8>
+    %644 = tosa.reshape %373, %8 : (tensor<1x5x5x240xi8>, !tosa.shape<4>) -> tensor<5x5x240x1xi8>
+    %645 = tosa.depthwise_conv2d %643, %644, %372, %405, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<5x5x240x1xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
+    %646 = tosa.rescale %645, %370, %369, %516, %371 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
+    %647 = tosa.table %646, %368 : (tensor<1x20x20x240xi8>, tensor<256xi8>) -> tensor<1x20x20x240xi8>
+    %648 = tosa.avg_pool2d %647, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
+    %649 = tosa.conv2d %648, %367, %366, %365, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x240xi8>, tensor<64x1x1x240xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x64xi32>
+    %650 = tosa.rescale %649, %364, %363, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x64xi8>
+    %651 = tosa.clamp %650 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x64xi8>) -> tensor<1x1x1x64xi8>
+    %652 = tosa.conv2d %651, %362, %361, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x64xi8>, tensor<240x1x1x64xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x240xi32>
+    %653 = tosa.rescale %652, %359, %358, %516, %360 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
+    %654 = tosa.rescale %653, %494, %493, %360, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
+    %655 = tosa.rescale %654, %357, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
+    %656 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %657 = tosa.reshape %656, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %658 = tosa.add %655, %657 : (tensor<1x1x1x240xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x240xi32>
+    %659 = tosa.rescale %658, %356, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
+    %660 = tosa.clamp %659 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x240xi8>) -> tensor<1x1x1x240xi8>
+    %661 = tosa.rescale %660, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
+    %662 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %663 = tosa.reshape %662, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %664 = tosa.mul %661, %663, %519 : (tensor<1x1x1x240xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi32>
+    %665 = tosa.rescale %664, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
+    %666 = tosa.rescale %647, %494, %484, %365, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x240xi32>
+    %667 = tosa.rescale %665, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
+    %668 = tosa.mul %666, %667, %519 : (tensor<1x20x20x240xi32>, tensor<1x1x1x240xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
+    %669 = tosa.rescale %668, %355, %388, %516, %354 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
+    %670 = tosa.conv2d %669, %353, %352, %354, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<40x1x1x240xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x40xi32>
+    %671 = tosa.rescale %670, %350, %349, %516, %351 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
+    %672 = tosa.rescale %671, %494, %490, %351, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
+    %673 = tosa.rescale %640, %494, %493, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
+    %674 = tosa.rescale %673, %348, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
+    %675 = tosa.add %672, %674 : (tensor<1x20x20x40xi32>, tensor<1x20x20x40xi32>) -> tensor<1x20x20x40xi32>
+    %676 = tosa.rescale %675, %347, %379, %516, %354 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
+    %677 = tosa.conv2d %676, %346, %345, %354, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x40xi8>, tensor<120x1x1x40xi8>, tensor<120xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x120xi32>
+    %678 = tosa.rescale %677, %343, %342, %516, %344 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x120xi32>, tensor<120xi32>, tensor<120xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x120xi8>
+    %679 = tosa.table %678, %341 : (tensor<1x20x20x120xi8>, tensor<256xi8>) -> tensor<1x20x20x120xi8>
+    %680 = tosa.reshape %340, %7 : (tensor<1x5x5x120xi8>, !tosa.shape<4>) -> tensor<5x5x120x1xi8>
+    %681 = tosa.depthwise_conv2d %679, %680, %339, %338, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x20x20x120xi8>, tensor<5x5x120x1xi8>, tensor<120xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x120xi32>
+    %682 = tosa.rescale %681, %336, %335, %516, %337 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x120xi32>, tensor<120xi32>, tensor<120xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x120xi8>
+    %683 = tosa.table %682, %334 : (tensor<1x20x20x120xi8>, tensor<256xi8>) -> tensor<1x20x20x120xi8>
+    %684 = tosa.avg_pool2d %683, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x120xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x120xi8>
+    %685 = tosa.conv2d %684, %333, %332, %331, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x120xi8>, tensor<32x1x1x120xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x32xi32>
+    %686 = tosa.rescale %685, %330, %329, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x32xi8>
+    %687 = tosa.clamp %686 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x32xi8>) -> tensor<1x1x1x32xi8>
+    %688 = tosa.conv2d %687, %328, %327, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x32xi8>, tensor<120x1x1x32xi8>, tensor<120xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x120xi32>
+    %689 = tosa.rescale %688, %325, %324, %516, %326 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi32>, tensor<120xi32>, tensor<120xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x120xi8>
+    %690 = tosa.rescale %689, %494, %490, %326, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x120xi32>
+    %691 = tosa.rescale %496, %494, %493, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %692 = tosa.rescale %691, %323, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<i32>
+    %693 = tosa.reshape %692, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %694 = tosa.add %690, %693 : (tensor<1x1x1x120xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x120xi32>
+    %695 = tosa.rescale %694, %322, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x120xi8>
+    %696 = tosa.clamp %695 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x120xi8>) -> tensor<1x1x1x120xi8>
+    %697 = tosa.rescale %696, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x120xi32>
+    %698 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %699 = tosa.reshape %698, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %700 = tosa.mul %697, %699, %519 : (tensor<1x1x1x120xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x120xi32>
+    %701 = tosa.rescale %700, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x120xi8>
+    %702 = tosa.rescale %683, %494, %484, %331, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x120xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x120xi32>
+    %703 = tosa.rescale %701, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x120xi32>
+    %704 = tosa.mul %702, %703, %519 : (tensor<1x20x20x120xi32>, tensor<1x1x1x120xi32>, tensor<1xi8>) -> tensor<1x20x20x120xi32>
+    %705 = tosa.rescale %704, %321, %388, %516, %337 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x120xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x120xi8>
+    %706 = tosa.conv2d %705, %320, %319, %337, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x120xi8>, tensor<48x1x1x120xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x48xi32>
+    %707 = tosa.rescale %706, %317, %316, %516, %318 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x48xi8>
+    %708 = tosa.conv2d %707, %315, %314, %318, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x48xi8>, tensor<144x1x1x48xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x144xi32>
+    %709 = tosa.rescale %708, %313, %312, %516, %416 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x144xi8>
+    %710 = tosa.table %709, %311 : (tensor<1x20x20x144xi8>, tensor<256xi8>) -> tensor<1x20x20x144xi8>
+    %711 = tosa.reshape %310, %6 : (tensor<1x5x5x144xi8>, !tosa.shape<4>) -> tensor<5x5x144x1xi8>
+    %712 = tosa.depthwise_conv2d %710, %711, %309, %365, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x20x20x144xi8>, tensor<5x5x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x144xi32>
+    %713 = tosa.rescale %712, %308, %307, %516, %451 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x144xi8>
+    %714 = tosa.table %713, %306 : (tensor<1x20x20x144xi8>, tensor<256xi8>) -> tensor<1x20x20x144xi8>
+    %715 = tosa.avg_pool2d %714, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x144xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x144xi8>
+    %716 = tosa.conv2d %715, %305, %304, %303, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x144xi8>, tensor<40x1x1x144xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x40xi32>
+    %717 = tosa.rescale %716, %302, %301, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x40xi8>
+    %718 = tosa.clamp %717 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x40xi8>) -> tensor<1x1x1x40xi8>
+    %719 = tosa.conv2d %718, %300, %299, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x40xi8>, tensor<144x1x1x40xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x144xi32>
+    %720 = tosa.rescale %719, %297, %296, %516, %298 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x144xi8>
+    %721 = tosa.rescale %720, %494, %493, %298, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x144xi32>
+    %722 = tosa.rescale %721, %295, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x144xi32>
+    %723 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %724 = tosa.reshape %723, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %725 = tosa.add %722, %724 : (tensor<1x1x1x144xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x144xi32>
+    %726 = tosa.rescale %725, %294, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x144xi8>
+    %727 = tosa.clamp %726 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x144xi8>) -> tensor<1x1x1x144xi8>
+    %728 = tosa.rescale %727, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x144xi32>
+    %729 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %730 = tosa.reshape %729, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %731 = tosa.mul %728, %730, %519 : (tensor<1x1x1x144xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x144xi32>
+    %732 = tosa.rescale %731, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x144xi8>
+    %733 = tosa.rescale %714, %494, %484, %303, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x144xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x144xi32>
+    %734 = tosa.rescale %732, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x144xi32>
+    %735 = tosa.mul %733, %734, %519 : (tensor<1x20x20x144xi32>, tensor<1x1x1x144xi32>, tensor<1xi8>) -> tensor<1x20x20x144xi32>
+    %736 = tosa.rescale %735, %293, %388, %516, %477 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x144xi8>
+    %737 = tosa.conv2d %736, %292, %291, %477, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x144xi8>, tensor<48x1x1x144xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x48xi32>
+    %738 = tosa.rescale %737, %290, %289, %516, %411 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x48xi8>
+    %739 = tosa.rescale %738, %494, %493, %411, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x48xi32>
+    %740 = tosa.rescale %739, %288, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x20x20x48xi32>
+    %741 = tosa.rescale %707, %494, %490, %318, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x48xi32>
+    %742 = tosa.add %740, %741 : (tensor<1x20x20x48xi32>, tensor<1x20x20x48xi32>) -> tensor<1x20x20x48xi32>
+    %743 = tosa.rescale %742, %287, %379, %516, %286 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x48xi8>
+    %744 = tosa.conv2d %743, %285, %284, %286, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x48xi8>, tensor<288x1x1x48xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x288xi32>
+    %745 = tosa.rescale %744, %283, %282, %516, %344 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x288xi8>
+    %746 = tosa.table %745, %281 : (tensor<1x20x20x288xi8>, tensor<256xi8>) -> tensor<1x20x20x288xi8>
+    %747 = tosa.reshape %280, %5 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
+    %748 = tosa.depthwise_conv2d %746, %747, %279, %278, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x20x20x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x288xi32>
+    %749 = tosa.rescale %748, %277, %276, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x288xi8>
+    %750 = tosa.clamp %749 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x20x20x288xi8>) -> tensor<1x20x20x288xi8>
+    %751 = tosa.conv2d %750, %275, %274, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x288xi8>, tensor<12x1x1x288xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x12xi32>
+    %752 = tosa.rescale %751, %272, %271, %516, %273 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x12xi32>, tensor<12xi32>, tensor<12xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x12xi8>
+    %753 = tosa.reshape %752, %270 : (tensor<1x20x20x12xi8>, !tosa.shape<4>) -> tensor<1x1200x1x4xi8>
+    %754 = tosa.reshape %269, %5 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
+    %755 = tosa.depthwise_conv2d %746, %754, %268, %278, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x20x20x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x288xi32>
+    %756 = tosa.rescale %755, %267, %266, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x288xi8>
+    %757 = tosa.clamp %756 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x20x20x288xi8>) -> tensor<1x20x20x288xi8>
+    %758 = tosa.conv2d %757, %265, %264, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x288xi8>, tensor<273x1x1x288xi8>, tensor<273xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x273xi32>
+    %759 = tosa.rescale %758, %262, %261, %516, %263 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x273xi32>, tensor<273xi32>, tensor<273xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x273xi8>
+    %760 = tosa.reshape %759, %260 : (tensor<1x20x20x273xi8>, !tosa.shape<3>) -> tensor<1x1200x91xi8>
+    %761 = tosa.reshape %259, %4 : (tensor<1x5x5x288xi8>, !tosa.shape<4>) -> tensor<5x5x288x1xi8>
+    %762 = tosa.depthwise_conv2d %746, %761, %258, %278, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 2, 1, 2>, stride = array<i64: 2, 2>} : (tensor<1x20x20x288xi8>, tensor<5x5x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %763 = tosa.rescale %762, %256, %255, %516, %257 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %764 = tosa.table %763, %254 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
+    %765 = tosa.avg_pool2d %764, %519, %519 {acc_type = i32, kernel = array<i64: 10, 10>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %766 = tosa.conv2d %765, %253, %252, %303, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x288xi8>, tensor<72x1x1x288xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x72xi32>
+    %767 = tosa.rescale %766, %251, %250, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x72xi8>
+    %768 = tosa.clamp %767 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x72xi8>) -> tensor<1x1x1x72xi8>
+    %769 = tosa.conv2d %768, %249, %248, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x72xi8>, tensor<288x1x1x72xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
+    %770 = tosa.rescale %769, %247, %246, %516, %490 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %771 = tosa.rescale %770, %494, %493, %490, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %772 = tosa.rescale %771, %245, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %773 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %774 = tosa.reshape %773, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %775 = tosa.add %772, %774 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x288xi32>
+    %776 = tosa.rescale %775, %244, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %777 = tosa.clamp %776 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x288xi8>) -> tensor<1x1x1x288xi8>
+    %778 = tosa.rescale %777, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %779 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %780 = tosa.reshape %779, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %781 = tosa.mul %778, %780, %519 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
+    %782 = tosa.rescale %781, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %783 = tosa.rescale %764, %494, %484, %303, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x288xi32>
+    %784 = tosa.rescale %782, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %785 = tosa.mul %783, %784, %519 : (tensor<1x10x10x288xi32>, tensor<1x1x1x288xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %786 = tosa.rescale %785, %243, %242, %516, %337 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %787 = tosa.conv2d %786, %241, %240, %337, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<48x1x1x288xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x48xi32>
+    %788 = tosa.rescale %787, %239, %238, %516, %351 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
+    %789 = tosa.conv2d %788, %237, %236, %351, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x48xi8>, tensor<288x1x1x48xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %790 = tosa.rescale %789, %234, %233, %516, %235 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %791 = tosa.table %790, %232 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
+    %792 = tosa.reshape %231, %4 : (tensor<1x5x5x288xi8>, !tosa.shape<4>) -> tensor<5x5x288x1xi8>
+    %793 = tosa.depthwise_conv2d %791, %792, %230, %229, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<5x5x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %794 = tosa.rescale %793, %227, %226, %516, %228 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %795 = tosa.table %794, %225 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
+    %796 = tosa.avg_pool2d %795, %519, %519 {acc_type = i32, kernel = array<i64: 10, 10>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %797 = tosa.conv2d %796, %224, %223, %399, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x288xi8>, tensor<72x1x1x288xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x72xi32>
+    %798 = tosa.rescale %797, %222, %221, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x72xi8>
+    %799 = tosa.clamp %798 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x72xi8>) -> tensor<1x1x1x72xi8>
+    %800 = tosa.conv2d %799, %220, %219, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x72xi8>, tensor<288x1x1x72xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
+    %801 = tosa.rescale %800, %218, %217, %516, %326 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %802 = tosa.rescale %801, %494, %493, %326, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %803 = tosa.rescale %802, %216, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %804 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %805 = tosa.reshape %804, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %806 = tosa.add %803, %805 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x288xi32>
+    %807 = tosa.rescale %806, %215, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %808 = tosa.clamp %807 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x288xi8>) -> tensor<1x1x1x288xi8>
+    %809 = tosa.rescale %808, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %810 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %811 = tosa.reshape %810, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %812 = tosa.mul %809, %811, %519 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
+    %813 = tosa.rescale %812, %214, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %814 = tosa.rescale %795, %494, %484, %399, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x288xi32>
+    %815 = tosa.rescale %813, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %816 = tosa.mul %814, %815, %519 : (tensor<1x10x10x288xi32>, tensor<1x1x1x288xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %817 = tosa.rescale %816, %213, %242, %516, %212 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %818 = tosa.conv2d %817, %211, %210, %212, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<48x1x1x288xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x48xi32>
+    %819 = tosa.rescale %818, %208, %207, %516, %209 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
+    %820 = tosa.rescale %819, %494, %490, %209, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
+    %821 = tosa.rescale %788, %494, %493, %351, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
+    %822 = tosa.rescale %821, %206, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
+    %823 = tosa.add %820, %822 : (tensor<1x10x10x48xi32>, tensor<1x10x10x48xi32>) -> tensor<1x10x10x48xi32>
+    %824 = tosa.rescale %823, %205, %487, %516, %204 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
+    %825 = tosa.conv2d %824, %203, %202, %204, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x48xi8>, tensor<288x1x1x48xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %826 = tosa.rescale %825, %201, %200, %516, %354 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %827 = tosa.table %826, %199 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
+    %828 = tosa.reshape %198, %4 : (tensor<1x5x5x288xi8>, !tosa.shape<4>) -> tensor<5x5x288x1xi8>
+    %829 = tosa.depthwise_conv2d %827, %828, %197, %278, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<5x5x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %830 = tosa.rescale %829, %195, %194, %516, %196 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %831 = tosa.table %830, %193 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
+    %832 = tosa.avg_pool2d %831, %519, %519 {acc_type = i32, kernel = array<i64: 10, 10>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %833 = tosa.conv2d %832, %192, %191, %399, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x288xi8>, tensor<72x1x1x288xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x72xi32>
+    %834 = tosa.rescale %833, %190, %189, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x72xi8>
+    %835 = tosa.clamp %834 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x72xi8>) -> tensor<1x1x1x72xi8>
+    %836 = tosa.conv2d %835, %188, %187, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x72xi8>, tensor<288x1x1x72xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
+    %837 = tosa.rescale %836, %186, %185, %516, %326 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %838 = tosa.rescale %837, %494, %493, %326, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %839 = tosa.rescale %838, %184, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %840 = tosa.rescale %495, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %841 = tosa.reshape %840, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %842 = tosa.add %839, %841 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x288xi32>
+    %843 = tosa.rescale %842, %183, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %844 = tosa.clamp %843 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x288xi8>) -> tensor<1x1x1x288xi8>
+    %845 = tosa.rescale %844, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %846 = tosa.rescale %485, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
+    %847 = tosa.reshape %846, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
+    %848 = tosa.mul %845, %847, %519 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
+    %849 = tosa.rescale %848, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
+    %850 = tosa.rescale %831, %494, %484, %399, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x288xi32>
+    %851 = tosa.rescale %849, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
+    %852 = tosa.mul %850, %851, %519 : (tensor<1x10x10x288xi32>, tensor<1x1x1x288xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %853 = tosa.rescale %852, %182, %242, %516, %181 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %854 = tosa.conv2d %853, %180, %179, %181, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<48x1x1x288xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x48xi32>
+    %855 = tosa.rescale %854, %178, %177, %516, %425 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
+    %856 = tosa.rescale %855, %494, %490, %425, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
+    %857 = tosa.rescale %824, %494, %493, %204, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
+    %858 = tosa.rescale %857, %176, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
+    %859 = tosa.add %856, %858 : (tensor<1x10x10x48xi32>, tensor<1x10x10x48xi32>) -> tensor<1x10x10x48xi32>
+    %860 = tosa.rescale %859, %175, %379, %516, %436 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
+    %861 = tosa.conv2d %860, %174, %173, %436, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x48xi8>, tensor<288x1x1x48xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %862 = tosa.rescale %861, %171, %170, %516, %172 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %863 = tosa.table %862, %169 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
+    %864 = tosa.reshape %168, %5 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
+    %865 = tosa.depthwise_conv2d %863, %864, %167, %166, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %866 = tosa.rescale %865, %165, %164, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %867 = tosa.clamp %866 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x10x10x288xi8>) -> tensor<1x10x10x288xi8>
+    %868 = tosa.conv2d %867, %163, %162, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<24x1x1x288xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x24xi32>
+    %869 = tosa.rescale %868, %160, %159, %516, %161 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x24xi8>
+    %870 = tosa.reshape %869, %158 : (tensor<1x10x10x24xi8>, !tosa.shape<4>) -> tensor<1x600x1x4xi8>
+    %871 = tosa.reshape %157, %5 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
+    %872 = tosa.depthwise_conv2d %863, %871, %156, %166, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
+    %873 = tosa.rescale %872, %155, %154, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
+    %874 = tosa.clamp %873 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x10x10x288xi8>) -> tensor<1x10x10x288xi8>
+    %875 = tosa.conv2d %874, %153, %152, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<546x1x1x288xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x546xi32>
+    %876 = tosa.rescale %875, %150, %149, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x546xi8>
+    %877 = tosa.reshape %876, %148 : (tensor<1x10x10x546xi8>, !tosa.shape<3>) -> tensor<1x600x91xi8>
+    %878 = tosa.conv2d %863, %147, %146, %166, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<256x1x1x288xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x256xi32>
+    %879 = tosa.rescale %878, %145, %144, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x256xi8>
+    %880 = tosa.clamp %879 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x10x10x256xi8>) -> tensor<1x10x10x256xi8>
+    %881 = tosa.reshape %143, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
+    %882 = tosa.depthwise_conv2d %880, %881, %142, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x10x10x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x256xi32>
+    %883 = tosa.rescale %882, %141, %140, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x256xi8>
+    %884 = tosa.clamp %883 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x256xi8>) -> tensor<1x5x5x256xi8>
+    %885 = tosa.conv2d %884, %139, %138, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x5x5x256xi8>, tensor<512x1x1x256xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x512xi32>
+    %886 = tosa.rescale %885, %137, %136, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x512xi8>
+    %887 = tosa.clamp %886 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x512xi8>) -> tensor<1x5x5x512xi8>
+    %888 = tosa.reshape %135, %2 : (tensor<1x3x3x512xi8>, !tosa.shape<4>) -> tensor<3x3x512x1xi8>
+    %889 = tosa.depthwise_conv2d %887, %888, %134, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<3x3x512x1xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x512xi32>
+    %890 = tosa.rescale %889, %133, %132, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x512xi8>
+    %891 = tosa.clamp %890 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x512xi8>) -> tensor<1x5x5x512xi8>
+    %892 = tosa.conv2d %891, %131, %130, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<24x1x1x512xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x24xi32>
+    %893 = tosa.rescale %892, %128, %127, %516, %129 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x24xi8>
+    %894 = tosa.reshape %893, %126 : (tensor<1x5x5x24xi8>, !tosa.shape<4>) -> tensor<1x150x1x4xi8>
+    %895 = tosa.reshape %125, %2 : (tensor<1x3x3x512xi8>, !tosa.shape<4>) -> tensor<3x3x512x1xi8>
+    %896 = tosa.depthwise_conv2d %887, %895, %124, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<3x3x512x1xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x512xi32>
+    %897 = tosa.rescale %896, %123, %122, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x512xi8>
+    %898 = tosa.clamp %897 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x512xi8>) -> tensor<1x5x5x512xi8>
+    %899 = tosa.conv2d %898, %121, %120, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<546x1x1x512xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x546xi32>
+    %900 = tosa.rescale %899, %119, %118, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x546xi8>
+    %901 = tosa.reshape %900, %117 : (tensor<1x5x5x546xi8>, !tosa.shape<3>) -> tensor<1x150x91xi8>
+    %902 = tosa.conv2d %887, %116, %115, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<128x1x1x512xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x128xi32>
+    %903 = tosa.rescale %902, %114, %113, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x128xi8>
+    %904 = tosa.clamp %903 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x128xi8>) -> tensor<1x5x5x128xi8>
+    %905 = tosa.reshape %112, %1 : (tensor<1x3x3x128xi8>, !tosa.shape<4>) -> tensor<3x3x128x1xi8>
+    %906 = tosa.depthwise_conv2d %904, %905, %111, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 2, 2>} : (tensor<1x5x5x128xi8>, tensor<3x3x128x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x128xi32>
+    %907 = tosa.rescale %906, %110, %109, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x128xi8>
+    %908 = tosa.clamp %907 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x128xi8>) -> tensor<1x3x3x128xi8>
+    %909 = tosa.conv2d %908, %108, %107, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x3x3x128xi8>, tensor<256x1x1x128xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x256xi32>
+    %910 = tosa.rescale %909, %106, %105, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x256xi8>
+    %911 = tosa.clamp %910 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x256xi8>) -> tensor<1x3x3x256xi8>
+    %912 = tosa.reshape %104, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
+    %913 = tosa.depthwise_conv2d %911, %912, %103, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x256xi32>
+    %914 = tosa.rescale %913, %102, %101, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x256xi8>
+    %915 = tosa.clamp %914 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x256xi8>) -> tensor<1x3x3x256xi8>
+    %916 = tosa.conv2d %915, %100, %99, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<24x1x1x256xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x24xi32>
+    %917 = tosa.rescale %916, %97, %96, %516, %98 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x24xi8>
+    %918 = tosa.reshape %917, %95 : (tensor<1x3x3x24xi8>, !tosa.shape<4>) -> tensor<1x54x1x4xi8>
+    %919 = tosa.reshape %94, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
+    %920 = tosa.depthwise_conv2d %911, %919, %93, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x256xi32>
+    %921 = tosa.rescale %920, %92, %91, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x256xi8>
+    %922 = tosa.clamp %921 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x256xi8>) -> tensor<1x3x3x256xi8>
+    %923 = tosa.conv2d %922, %90, %89, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<546x1x1x256xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x546xi32>
+    %924 = tosa.rescale %923, %88, %87, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x546xi8>
+    %925 = tosa.reshape %924, %86 : (tensor<1x3x3x546xi8>, !tosa.shape<3>) -> tensor<1x54x91xi8>
+    %926 = tosa.conv2d %911, %85, %84, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<128x1x1x256xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x128xi32>
+    %927 = tosa.rescale %926, %83, %82, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x128xi8>
+    %928 = tosa.clamp %927 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x128xi8>) -> tensor<1x3x3x128xi8>
+    %929 = tosa.reshape %81, %1 : (tensor<1x3x3x128xi8>, !tosa.shape<4>) -> tensor<3x3x128x1xi8>
+    %930 = tosa.depthwise_conv2d %928, %929, %80, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 2, 2>} : (tensor<1x3x3x128xi8>, tensor<3x3x128x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x128xi32>
+    %931 = tosa.rescale %930, %79, %78, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x128xi8>
+    %932 = tosa.clamp %931 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x128xi8>) -> tensor<1x2x2x128xi8>
+    %933 = tosa.conv2d %932, %77, %76, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x2x2x128xi8>, tensor<256x1x1x128xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x256xi32>
+    %934 = tosa.rescale %933, %75, %74, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x256xi8>
+    %935 = tosa.clamp %934 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x256xi8>) -> tensor<1x2x2x256xi8>
+    %936 = tosa.reshape %73, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
+    %937 = tosa.depthwise_conv2d %935, %936, %72, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x256xi32>
+    %938 = tosa.rescale %937, %71, %70, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x256xi8>
+    %939 = tosa.clamp %938 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x256xi8>) -> tensor<1x2x2x256xi8>
+    %940 = tosa.conv2d %939, %69, %68, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<24x1x1x256xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x24xi32>
+    %941 = tosa.rescale %940, %67, %66, %516, %298 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x24xi8>
+    %942 = tosa.reshape %941, %65 : (tensor<1x2x2x24xi8>, !tosa.shape<4>) -> tensor<1x24x1x4xi8>
+    %943 = tosa.reshape %64, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
+    %944 = tosa.depthwise_conv2d %935, %943, %63, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x256xi32>
+    %945 = tosa.rescale %944, %62, %61, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x256xi8>
+    %946 = tosa.clamp %945 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x256xi8>) -> tensor<1x2x2x256xi8>
+    %947 = tosa.conv2d %946, %60, %59, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<546x1x1x256xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x546xi32>
+    %948 = tosa.rescale %947, %58, %57, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x546xi8>
+    %949 = tosa.reshape %948, %56 : (tensor<1x2x2x546xi8>, !tosa.shape<3>) -> tensor<1x24x91xi8>
+    %950 = tosa.conv2d %935, %55, %54, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<64x1x1x256xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x64xi32>
+    %951 = tosa.rescale %950, %53, %52, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x64xi8>
+    %952 = tosa.clamp %951 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x64xi8>) -> tensor<1x2x2x64xi8>
+    %953 = tosa.reshape %51, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
+    %954 = tosa.depthwise_conv2d %952, %953, %50, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x2x2x64xi8>, tensor<3x3x64x1xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x64xi32>
+    %955 = tosa.rescale %954, %49, %48, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x64xi8>
+    %956 = tosa.clamp %955 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x64xi8>) -> tensor<1x1x1x64xi8>
+    %957 = tosa.conv2d %956, %47, %46, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x64xi8>, tensor<128x1x1x64xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x128xi32>
+    %958 = tosa.rescale %957, %45, %44, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x128xi8>
+    %959 = tosa.clamp %958 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x128xi8>) -> tensor<1x1x1x128xi8>
+    %960 = tosa.reshape %43, %1 : (tensor<1x3x3x128xi8>, !tosa.shape<4>) -> tensor<3x3x128x1xi8>
+    %961 = tosa.depthwise_conv2d %959, %960, %42, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<3x3x128x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x128xi32>
+    %962 = tosa.rescale %961, %41, %40, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x128xi8>
+    %963 = tosa.clamp %962 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x128xi8>) -> tensor<1x1x1x128xi8>
+    %964 = tosa.conv2d %963, %39, %38, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<24x1x1x128xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x24xi32>
+    %965 = tosa.rescale %964, %36, %35, %516, %37 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x24xi8>
+    %966 = tosa.reshape %965, %34 : (tensor<1x1x1x24xi8>, !tosa.shape<4>) -> tensor<1x6x1x4xi8>
+    %967 = tosa.rescale %966, %33, %491, %37, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x6x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x6x1x4xi8>
+    %968 = tosa.rescale %942, %32, %491, %298, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x24x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x24x1x4xi8>
+    %969 = tosa.rescale %918, %31, %491, %98, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x54x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x54x1x4xi8>
+    %970 = tosa.rescale %894, %30, %491, %129, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x150x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x150x1x4xi8>
+    %971 = tosa.rescale %870, %29, %491, %161, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x600x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x600x1x4xi8>
+    %972 = tosa.concat %753, %971, %970, %969, %968, %967 {axis = 1 : i32} : (tensor<1x1200x1x4xi8>, tensor<1x600x1x4xi8>, tensor<1x150x1x4xi8>, tensor<1x54x1x4xi8>, tensor<1x24x1x4xi8>, tensor<1x6x1x4xi8>) -> tensor<1x2034x1x4xi8>
+    %973 = tosa.reshape %972, %28 : (tensor<1x2034x1x4xi8>, !tosa.shape<3>) -> tensor<1x2034x4xi8>
+    %974 = tosa.reshape %27, %1 : (tensor<1x3x3x128xi8>, !tosa.shape<4>) -> tensor<3x3x128x1xi8>
+    %975 = tosa.depthwise_conv2d %959, %974, %26, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<3x3x128x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x128xi32>
+    %976 = tosa.rescale %975, %25, %24, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x128xi8>
+    %977 = tosa.clamp %976 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x128xi8>) -> tensor<1x1x1x128xi8>
+    %978 = tosa.conv2d %977, %23, %22, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<546x1x1x128xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x546xi32>
+    %979 = tosa.rescale %978, %21, %20, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x546xi8>
+    %980 = tosa.reshape %979, %19 : (tensor<1x1x1x546xi8>, !tosa.shape<3>) -> tensor<1x6x91xi8>
+    %981 = tosa.rescale %980, %18, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x6x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x6x91xi8>
+    %982 = tosa.rescale %949, %17, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x24x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x24x91xi8>
+    %983 = tosa.rescale %925, %16, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x54x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x54x91xi8>
+    %984 = tosa.rescale %901, %15, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x150x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x150x91xi8>
+    %985 = tosa.rescale %877, %14, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x600x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x600x91xi8>
+    %986 = tosa.concat %760, %985, %984, %983, %982, %981 {axis = 1 : i32} : (tensor<1x1200x91xi8>, tensor<1x600x91xi8>, tensor<1x150x91xi8>, tensor<1x54x91xi8>, tensor<1x24x91xi8>, tensor<1x6x91xi8>) -> tensor<1x2034x91xi8>
+    %987 = tosa.table %986, %13 : (tensor<1x2034x91xi8>, tensor<256xi8>) -> tensor<1x2034x91xi8>
+    return %987, %973 : tensor<1x2034x91xi8>, tensor<1x2034x4xi8>
+  }
+}
diff --git a/tests/gold/test_python_api/tiny_wav2letter_pruned_int8.mlir b/tests/gold/test_python_api/tiny_wav2letter_pruned_int8.mlir
new file mode 100644
index 0000000..199e562
--- /dev/null
+++ b/tests/gold/test_python_api/tiny_wav2letter_pruned_int8.mlir
@@ -0,0 +1,128 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.13.1\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<1x296x39xi8>) -> tensor<1x1x148x29xi8> attributes {tf.entry_function = {inputs = "input_1_int8", outputs = "Identity_int8"}} {
+    %0 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<29xi8>}> : () -> tensor<29xi8>
+    %1 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<29xi32>}> : () -> tensor<29xi32>
+    %2 = "tosa.const"() <{values = dense<5> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %3 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<29xi32>}> : () -> tensor<29xi32>
+    %4 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<29x1x1x750xi8>}> : () -> tensor<29x1x1x750xi8>
+    %5 = "tosa.const"() <{values = dense<-77> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %6 = "tosa.const"() <{values = dense<1925690389> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %7 = "tosa.const"() <{values = dense<1540552334> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %8 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi8>}> : () -> tensor<750xi8>
+    %9 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi32>}> : () -> tensor<750xi32>
+    %10 = "tosa.const"() <{values = dense<13> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi32>}> : () -> tensor<750xi32>
+    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750x1x1x750xi8>}> : () -> tensor<750x1x1x750xi8>
+    %13 = "tosa.const"() <{values = dense<-76> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %14 = "tosa.const"() <{values = dense<1949381878> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %15 = "tosa.const"() <{values = dense<1559505526> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi8>}> : () -> tensor<750xi8>
+    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi32>}> : () -> tensor<750xi32>
+    %18 = "tosa.const"() <{values = dense<15> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi32>}> : () -> tensor<750xi32>
+    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750x1x32x100xi8>}> : () -> tensor<750x1x32x100xi8>
+    %21 = "tosa.const"() <{values = dense<-84> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %22 = "tosa.const"() <{values = dense<1819150077> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %23 = "tosa.const"() <{values = dense<1455320083> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x100xi8>}> : () -> tensor<100x1x7x100xi8>
+    %28 = "tosa.const"() <{values = dense<1833421420> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %29 = "tosa.const"() <{values = dense<1466737158> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
+    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x100xi8>}> : () -> tensor<100x1x7x100xi8>
+    %34 = "tosa.const"() <{values = dense<1981257558> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %35 = "tosa.const"() <{values = dense<1585006070> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
+    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x100xi8>}> : () -> tensor<100x1x7x100xi8>
+    %40 = "tosa.const"() <{values = dense<-74> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %41 = "tosa.const"() <{values = dense<1976102450> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %42 = "tosa.const"() <{values = dense<1580881984> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
+    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %45 = "tosa.const"() <{values = dense<18> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x100xi8>}> : () -> tensor<100x1x7x100xi8>
+    %48 = "tosa.const"() <{values = dense<-56> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %49 = "tosa.const"() <{values = dense<29> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %50 = "tosa.const"() <{values = dense<1139114841> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %51 = "tosa.const"() <{values = dense<1822583773> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
+    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %54 = "tosa.const"() <{values = dense<41> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %55 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
+    %56 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x250xi8>}> : () -> tensor<100x1x7x250xi8>
+    %57 = "tosa.const"() <{values = dense<-83> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %58 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %59 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %60 = "tosa.const"() <{values = dense<1827101553> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %61 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %62 = "tosa.const"() <{values = dense<1461681264> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %63 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<250xi8>}> : () -> tensor<250xi8>
+    %64 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<250xi32>}> : () -> tensor<250xi32>
+    %65 = "tosa.const"() <{values = dense<3> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %66 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %67 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %68 = "tosa.const"() <{values = dense<4> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %69 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<250xi32>}> : () -> tensor<250xi32>
+    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<250x1x48x39xi8>}> : () -> tensor<250x1x48x39xi8>
+    %71 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %72 = tosa.reshape %arg0, %71 : (tensor<1x296x39xi8>, !tosa.shape<4>) -> tensor<1x1x296x39xi8>
+    %73 = tosa.conv2d %72, %70, %69, %68, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 23, 23>, stride = array<i64: 1, 2>} : (tensor<1x1x296x39xi8>, tensor<250x1x48x39xi8>, tensor<250xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x250xi32>
+    %74 = tosa.rescale %73, %64, %63, %66, %65 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x250xi32>, tensor<250xi32>, tensor<250xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x250xi8>
+    %75 = tosa.rescale %74, %62, %61, %65, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x250xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x250xi32>
+    %76 = tosa.rescale %74, %60, %59, %65, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x250xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x250xi32>
+    %77 = tosa.maximum %76, %75 : (tensor<1x1x148x250xi32>, tensor<1x1x148x250xi32>) -> tensor<1x1x148x250xi32>
+    %78 = tosa.rescale %77, %58, %59, %66, %57 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x250xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x250xi8>
+    %79 = tosa.conv2d %78, %56, %55, %57, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x250xi8>, tensor<100x1x7x250xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
+    %80 = tosa.rescale %79, %53, %52, %66, %54 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %81 = tosa.rescale %80, %51, %61, %54, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %82 = tosa.rescale %80, %50, %49, %54, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %83 = tosa.maximum %82, %81 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
+    %84 = tosa.rescale %83, %58, %59, %66, %48 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %85 = tosa.conv2d %84, %47, %46, %48, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<100x1x7x100xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
+    %86 = tosa.rescale %85, %44, %43, %66, %45 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %87 = tosa.rescale %86, %42, %61, %45, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %88 = tosa.rescale %86, %41, %59, %45, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %89 = tosa.maximum %88, %87 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
+    %90 = tosa.rescale %89, %58, %59, %66, %40 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %91 = tosa.conv2d %90, %39, %38, %40, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<100x1x7x100xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
+    %92 = tosa.rescale %91, %37, %36, %66, %45 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %93 = tosa.rescale %92, %35, %61, %45, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %94 = tosa.rescale %92, %34, %59, %45, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %95 = tosa.maximum %94, %93 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
+    %96 = tosa.rescale %95, %58, %59, %66, %40 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %97 = tosa.conv2d %96, %33, %32, %40, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<100x1x7x100xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
+    %98 = tosa.rescale %97, %31, %30, %66, %68 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %99 = tosa.rescale %98, %29, %61, %68, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %100 = tosa.rescale %98, %28, %59, %68, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %101 = tosa.maximum %100, %99 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
+    %102 = tosa.rescale %101, %58, %59, %66, %57 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %103 = tosa.conv2d %102, %27, %26, %57, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<100x1x7x100xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
+    %104 = tosa.rescale %103, %25, %24, %66, %65 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %105 = tosa.rescale %104, %23, %61, %65, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %106 = tosa.rescale %104, %22, %59, %65, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
+    %107 = tosa.maximum %106, %105 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
+    %108 = tosa.rescale %107, %58, %59, %66, %21 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
+    %109 = tosa.conv2d %108, %20, %19, %21, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 15, 16>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<750x1x32x100xi8>, tensor<750xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x750xi32>
+    %110 = tosa.rescale %109, %17, %16, %66, %18 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi32>, tensor<750xi32>, tensor<750xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x750xi8>
+    %111 = tosa.rescale %110, %15, %61, %18, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x750xi32>
+    %112 = tosa.rescale %110, %14, %59, %18, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x750xi32>
+    %113 = tosa.maximum %112, %111 : (tensor<1x1x148x750xi32>, tensor<1x1x148x750xi32>) -> tensor<1x1x148x750xi32>
+    %114 = tosa.rescale %113, %58, %59, %66, %13 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x750xi8>
+    %115 = tosa.conv2d %114, %12, %11, %13, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x148x750xi8>, tensor<750x1x1x750xi8>, tensor<750xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x750xi32>
+    %116 = tosa.rescale %115, %9, %8, %66, %10 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi32>, tensor<750xi32>, tensor<750xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x750xi8>
+    %117 = tosa.rescale %116, %7, %61, %10, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x750xi32>
+    %118 = tosa.rescale %116, %6, %59, %10, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x750xi32>
+    %119 = tosa.maximum %118, %117 : (tensor<1x1x148x750xi32>, tensor<1x1x148x750xi32>) -> tensor<1x1x148x750xi32>
+    %120 = tosa.rescale %119, %58, %59, %66, %5 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x750xi8>
+    %121 = tosa.conv2d %120, %4, %3, %5, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x148x750xi8>, tensor<29x1x1x750xi8>, tensor<29xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x29xi32>
+    %122 = tosa.rescale %121, %1, %0, %66, %2 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x29xi32>, tensor<29xi32>, tensor<29xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x29xi8>
+    return %122 : tensor<1x1x148x29xi8>
+  }
+}
diff --git a/tests/gold/test_python_api/vww4_128_128_INT8.mlir b/tests/gold/test_python_api/vww4_128_128_INT8.mlir
new file mode 100644
index 0000000..0991a35
--- /dev/null
+++ b/tests/gold/test_python_api/vww4_128_128_INT8.mlir
@@ -0,0 +1,514 @@
+module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<1x128x128x1xi8>) -> tensor<1x2xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
+    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %5 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %6 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %7 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %8 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %9 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %10 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %11 = "tosa.const"() <{values = dense<41> : tensor<2xi8>}> : () -> tensor<2xi8>
+    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<2xi32>}> : () -> tensor<2xi32>
+    %13 = "tosa.const"() <{values = dense<-17> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<2xi32>}> : () -> tensor<2xi32>
+    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<2x1x1x128xi8>}> : () -> tensor<2x1x1x128xi8>
+    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
+    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x1x1x32xi8>}> : () -> tensor<128x1x1x32xi8>
+    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
+    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x1x1x96xi8>}> : () -> tensor<32x1x1x96xi8>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
+    %28 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %29 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x32xi8>}> : () -> tensor<96x1x1x32xi8>
+    %32 = "tosa.const"() <{values = dense<20> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %33 = "tosa.const"() <{values = dense<1867675366> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %34 = "tosa.const"() <{values = dense<1869358422> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %35 = "tosa.const"() <{values = dense<-23> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %36 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<8xindex>} : () -> !tosa.shape<8>
+    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x1x1x96xi8>}> : () -> tensor<32x1x1x96xi8>
+    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
+    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x16xi8>}> : () -> tensor<96x1x1x16xi8>
+    %49 = "tosa.const"() <{values = dense<-23> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %50 = "tosa.const"() <{values = dense<1356240683> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %51 = "tosa.const"() <{values = dense<2017076441> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
+    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %54 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %55 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x96xi8>}> : () -> tensor<16x1x1x96xi8>
+    %56 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %57 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %58 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
+    %60 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
+    %61 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %62 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
+    %63 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x16xi8>}> : () -> tensor<96x1x1x16xi8>
+    %64 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
+    %65 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %66 = "tosa.const"() <{values = dense<-21> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %67 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %68 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x288xi8>}> : () -> tensor<16x1x1x288xi8>
+    %69 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi8>}> : () -> tensor<288xi8>
+    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi32>}> : () -> tensor<288xi32>
+    %71 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi32>}> : () -> tensor<288xi32>
+    %72 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x288xi8>}> : () -> tensor<1x3x3x288xi8>
+    %73 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi8>}> : () -> tensor<288xi8>
+    %74 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi32>}> : () -> tensor<288xi32>
+    %75 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi32>}> : () -> tensor<288xi32>
+    %76 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288x1x1x68xi8>}> : () -> tensor<288x1x1x68xi8>
+    %77 = "tosa.const"() <{values = dense<-8> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %78 = "tosa.const"() <{values = dense<2052730416> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %79 = "tosa.const"() <{values = dense<1366556772> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %80 = "tosa.const"() <{values = dense<18> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %81 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<8xindex>} : () -> !tosa.shape<8>
+    %82 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<48xi8>}> : () -> tensor<48xi8>
+    %83 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<48xi32>}> : () -> tensor<48xi32>
+    %84 = "tosa.const"() <{values = dense<18> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %85 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<48xi32>}> : () -> tensor<48xi32>
+    %86 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<48x1x1x172xi8>}> : () -> tensor<48x1x1x172xi8>
+    %87 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi8>}> : () -> tensor<172xi8>
+    %88 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi32>}> : () -> tensor<172xi32>
+    %89 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi32>}> : () -> tensor<172xi32>
+    %90 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x172xi8>}> : () -> tensor<1x3x3x172xi8>
+    %91 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi8>}> : () -> tensor<172xi8>
+    %92 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi32>}> : () -> tensor<172xi32>
+    %93 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi32>}> : () -> tensor<172xi32>
+    %94 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172x1x1x68xi8>}> : () -> tensor<172x1x1x68xi8>
+    %95 = "tosa.const"() <{values = dense<-10> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %96 = "tosa.const"() <{values = dense<1372189797> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %97 = "tosa.const"() <{values = dense<1887351030> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %98 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<68xi8>}> : () -> tensor<68xi8>
+    %99 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<68xi32>}> : () -> tensor<68xi32>
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+    %278 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<4xi32>}> : () -> tensor<4xi32>
+    %279 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<4x1x1x8xi8>}> : () -> tensor<4x1x1x8xi8>
+    %280 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi8>}> : () -> tensor<8xi8>
+    %281 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
+    %282 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %283 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %284 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8x3x3x1xi8>}> : () -> tensor<8x3x3x1xi8>
+    %285 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
+    %286 = "tosa.const"() <{values = dense<-70> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %287 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %288 = tosa.conv2d %arg0, %284, %285, %286, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x128x128x1xi8>, tensor<8x3x3x1xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x8xi32>
+    %289 = tosa.rescale %288, %281, %280, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x8xi8>
+    %290 = tosa.clamp %289 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x64x64x8xi8>) -> tensor<1x64x64x8xi8>
+    %291 = tosa.conv2d %290, %279, %278, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x64x64x8xi8>, tensor<4x1x1x8xi8>, tensor<4xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x4xi32>
+    %292 = tosa.rescale %291, %277, %276, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x4xi32>, tensor<4xi32>, tensor<4xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x4xi8>
+    %293 = tosa.clamp %292 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x64x64x4xi8>) -> tensor<1x64x64x4xi8>
+    %294 = tosa.reshape %275, %9 : (tensor<1x3x3x4xi8>, !tosa.shape<4>) -> tensor<3x3x4x1xi8>
+    %295 = tosa.depthwise_conv2d %293, %294, %274, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x64x64x4xi8>, tensor<3x3x4x1xi8>, tensor<4xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x4xi32>
+    %296 = tosa.rescale %295, %273, %272, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x4xi32>, tensor<4xi32>, tensor<4xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x4xi8>
+    %297 = tosa.clamp %296 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x64x64x4xi8>) -> tensor<1x64x64x4xi8>
+    %298 = tosa.conv2d %297, %271, %270, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x64x64x4xi8>, tensor<4x1x1x4xi8>, tensor<4xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x4xi32>
+    %299 = tosa.rescale %298, %269, %268, %283, %287 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x4xi32>, tensor<4xi32>, tensor<4xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x4xi8>
+    %300 = tosa.conv2d %299, %267, %266, %287, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x64x64x4xi8>, tensor<8x1x1x4xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x8xi32>
+    %301 = tosa.rescale %300, %265, %264, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x8xi8>
+    %302 = tosa.clamp %301 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x64x64x8xi8>) -> tensor<1x64x64x8xi8>
+    %303 = tosa.reshape %263, %8 : (tensor<1x3x3x8xi8>, !tosa.shape<4>) -> tensor<3x3x8x1xi8>
+    %304 = tosa.depthwise_conv2d %302, %303, %262, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x64x64x8xi8>, tensor<3x3x8x1xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x8xi32>
+    %305 = tosa.rescale %304, %261, %260, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x8xi8>
+    %306 = tosa.clamp %305 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x8xi8>) -> tensor<1x32x32x8xi8>
+    %307 = tosa.conv2d %306, %259, %258, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xi8>, tensor<12x1x1x8xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x12xi32>
+    %308 = tosa.rescale %307, %256, %255, %283, %257 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x12xi32>, tensor<12xi32>, tensor<12xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x12xi8>
+    %309 = tosa.conv2d %308, %254, %253, %257, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x12xi8>, tensor<14x1x1x12xi8>, tensor<14xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x14xi32>
+    %310 = tosa.rescale %309, %252, %251, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x14xi32>, tensor<14xi32>, tensor<14xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x14xi8>
+    %311 = tosa.clamp %310 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x14xi8>) -> tensor<1x32x32x14xi8>
+    %312 = tosa.reshape %250, %7 : (tensor<1x3x3x14xi8>, !tosa.shape<4>) -> tensor<3x3x14x1xi8>
+    %313 = tosa.depthwise_conv2d %311, %312, %249, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x32x32x14xi8>, tensor<3x3x14x1xi8>, tensor<14xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x14xi32>
+    %314 = tosa.rescale %313, %248, %247, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x14xi32>, tensor<14xi32>, tensor<14xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x14xi8>
+    %315 = tosa.clamp %314 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x14xi8>) -> tensor<1x32x32x14xi8>
+    %316 = tosa.conv2d %315, %246, %245, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x14xi8>, tensor<16x1x1x14xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x16xi32>
+    %317 = tosa.rescale %316, %243, %242, %283, %244 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x16xi8>
+    %318 = tosa.pad %308, %241, %240 : (tensor<1x32x32x12xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x32x32x16xi8>
+    %319 = tosa.rescale %318, %239, %238, %257, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x32x32x16xi32>
+    %320 = tosa.rescale %317, %239, %237, %244, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x32x32x16xi32>
+    %321 = tosa.rescale %320, %236, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x32x32x16xi32>
+    %322 = tosa.add %319, %321 : (tensor<1x32x32x16xi32>, tensor<1x32x32x16xi32>) -> tensor<1x32x32x16xi32>
+    %323 = tosa.rescale %322, %234, %233, %283, %232 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x16xi8>
+    %324 = tosa.conv2d %323, %231, %230, %232, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x16xi8>, tensor<28x1x1x16xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x28xi32>
+    %325 = tosa.rescale %324, %229, %228, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x28xi8>
+    %326 = tosa.clamp %325 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x28xi8>) -> tensor<1x32x32x28xi8>
+    %327 = tosa.reshape %227, %6 : (tensor<1x3x3x28xi8>, !tosa.shape<4>) -> tensor<3x3x28x1xi8>
+    %328 = tosa.depthwise_conv2d %326, %327, %226, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x32x32x28xi8>, tensor<3x3x28x1xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x28xi32>
+    %329 = tosa.rescale %328, %225, %224, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x28xi8>
+    %330 = tosa.clamp %329 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x28xi8>) -> tensor<1x16x16x28xi8>
+    %331 = tosa.conv2d %330, %223, %222, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x28xi8>, tensor<32x1x1x28xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x32xi32>
+    %332 = tosa.rescale %331, %220, %219, %283, %221 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
+    %333 = tosa.conv2d %332, %218, %217, %221, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x32xi8>, tensor<96x1x1x32xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x96xi32>
+    %334 = tosa.rescale %333, %216, %215, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x96xi8>
+    %335 = tosa.clamp %334 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x96xi8>) -> tensor<1x16x16x96xi8>
+    %336 = tosa.reshape %214, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
+    %337 = tosa.depthwise_conv2d %335, %336, %213, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x16x16x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x96xi32>
+    %338 = tosa.rescale %337, %212, %211, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x96xi8>
+    %339 = tosa.clamp %338 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x96xi8>) -> tensor<1x16x16x96xi8>
+    %340 = tosa.conv2d %339, %210, %209, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x96xi8>, tensor<28x1x1x96xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x28xi32>
+    %341 = tosa.rescale %340, %207, %206, %283, %208 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x28xi8>
+    %342 = tosa.pad %341, %241, %205 : (tensor<1x16x16x28xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
+    %343 = tosa.rescale %332, %239, %238, %221, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
+    %344 = tosa.rescale %342, %239, %237, %208, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
+    %345 = tosa.rescale %344, %204, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
+    %346 = tosa.add %343, %345 : (tensor<1x16x16x32xi32>, tensor<1x16x16x32xi32>) -> tensor<1x16x16x32xi32>
+    %347 = tosa.rescale %346, %203, %233, %283, %202 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
+    %348 = tosa.conv2d %347, %201, %200, %202, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x32xi8>, tensor<96x1x1x32xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x96xi32>
+    %349 = tosa.rescale %348, %199, %198, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x96xi8>
+    %350 = tosa.clamp %349 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x96xi8>) -> tensor<1x16x16x96xi8>
+    %351 = tosa.reshape %197, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
+    %352 = tosa.depthwise_conv2d %350, %351, %196, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x16x16x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x96xi32>
+    %353 = tosa.rescale %352, %195, %194, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x96xi8>
+    %354 = tosa.clamp %353 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x96xi8>) -> tensor<1x16x16x96xi8>
+    %355 = tosa.conv2d %354, %193, %192, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x96xi8>, tensor<28x1x1x96xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x28xi32>
+    %356 = tosa.rescale %355, %191, %190, %283, %208 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x28xi8>
+    %357 = tosa.pad %356, %241, %189 : (tensor<1x16x16x28xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
+    %358 = tosa.rescale %347, %239, %238, %202, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
+    %359 = tosa.rescale %357, %239, %237, %208, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
+    %360 = tosa.rescale %359, %188, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
+    %361 = tosa.add %358, %360 : (tensor<1x16x16x32xi32>, tensor<1x16x16x32xi32>) -> tensor<1x16x16x32xi32>
+    %362 = tosa.rescale %361, %187, %186, %283, %185 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
+    %363 = tosa.conv2d %362, %184, %183, %185, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x32xi8>, tensor<152x1x1x32xi8>, tensor<152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x152xi32>
+    %364 = tosa.rescale %363, %182, %181, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x152xi32>, tensor<152xi32>, tensor<152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x152xi8>
+    %365 = tosa.clamp %364 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x152xi8>) -> tensor<1x16x16x152xi8>
+    %366 = tosa.reshape %180, %4 : (tensor<1x3x3x152xi8>, !tosa.shape<4>) -> tensor<3x3x152x1xi8>
+    %367 = tosa.depthwise_conv2d %365, %366, %179, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x16x16x152xi8>, tensor<3x3x152x1xi8>, tensor<152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x152xi32>
+    %368 = tosa.rescale %367, %178, %177, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x152xi32>, tensor<152xi32>, tensor<152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x152xi8>
+    %369 = tosa.clamp %368 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x152xi8>) -> tensor<1x8x8x152xi8>
+    %370 = tosa.conv2d %369, %176, %175, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x152xi8>, tensor<44x1x1x152xi8>, tensor<44xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x44xi32>
+    %371 = tosa.rescale %370, %174, %173, %283, %232 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi32>, tensor<44xi32>, tensor<44xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x44xi8>
+    %372 = tosa.conv2d %371, %172, %171, %232, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x44xi8>, tensor<268x1x1x44xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
+    %373 = tosa.rescale %372, %170, %169, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
+    %374 = tosa.clamp %373 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
+    %375 = tosa.reshape %168, %3 : (tensor<1x3x3x268xi8>, !tosa.shape<4>) -> tensor<3x3x268x1xi8>
+    %376 = tosa.depthwise_conv2d %374, %375, %167, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<3x3x268x1xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
+    %377 = tosa.rescale %376, %166, %165, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
+    %378 = tosa.clamp %377 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
+    %379 = tosa.conv2d %378, %164, %163, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<40x1x1x268xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x40xi32>
+    %380 = tosa.rescale %379, %161, %160, %283, %162 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x40xi8>
+    %381 = tosa.pad %380, %241, %159 : (tensor<1x8x8x40xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x8x8x44xi8>
+    %382 = tosa.rescale %371, %239, %238, %232, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x44xi32>
+    %383 = tosa.rescale %381, %239, %237, %162, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x44xi32>
+    %384 = tosa.rescale %383, %158, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x44xi32>
+    %385 = tosa.add %382, %384 : (tensor<1x8x8x44xi32>, tensor<1x8x8x44xi32>) -> tensor<1x8x8x44xi32>
+    %386 = tosa.rescale %385, %157, %186, %283, %156 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x44xi8>
+    %387 = tosa.conv2d %386, %155, %154, %156, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x44xi8>, tensor<268x1x1x44xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
+    %388 = tosa.rescale %387, %153, %152, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
+    %389 = tosa.clamp %388 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
+    %390 = tosa.reshape %151, %3 : (tensor<1x3x3x268xi8>, !tosa.shape<4>) -> tensor<3x3x268x1xi8>
+    %391 = tosa.depthwise_conv2d %389, %390, %150, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<3x3x268x1xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
+    %392 = tosa.rescale %391, %149, %148, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
+    %393 = tosa.clamp %392 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
+    %394 = tosa.conv2d %393, %147, %146, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<52x1x1x268xi8>, tensor<52xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x52xi32>
+    %395 = tosa.rescale %394, %144, %143, %283, %145 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<52xi32>, tensor<52xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
+    %396 = tosa.pad %386, %142, %141 : (tensor<1x8x8x44xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
+    %397 = tosa.rescale %396, %239, %238, %156, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
+    %398 = tosa.rescale %395, %239, %237, %145, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
+    %399 = tosa.rescale %398, %140, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
+    %400 = tosa.add %397, %399 : (tensor<1x8x8x52xi32>, tensor<1x8x8x52xi32>) -> tensor<1x8x8x52xi32>
+    %401 = tosa.rescale %400, %139, %186, %283, %232 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
+    %402 = tosa.conv2d %401, %138, %137, %232, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x52xi8>, tensor<268x1x1x52xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
+    %403 = tosa.rescale %402, %136, %135, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
+    %404 = tosa.clamp %403 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
+    %405 = tosa.reshape %134, %3 : (tensor<1x3x3x268xi8>, !tosa.shape<4>) -> tensor<3x3x268x1xi8>
+    %406 = tosa.depthwise_conv2d %404, %405, %133, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<3x3x268x1xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
+    %407 = tosa.rescale %406, %132, %131, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
+    %408 = tosa.clamp %407 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
+    %409 = tosa.conv2d %408, %130, %129, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<44x1x1x268xi8>, tensor<44xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x44xi32>
+    %410 = tosa.rescale %409, %128, %127, %283, %145 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi32>, tensor<44xi32>, tensor<44xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x44xi8>
+    %411 = tosa.pad %410, %142, %126 : (tensor<1x8x8x44xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
+    %412 = tosa.rescale %401, %239, %238, %232, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
+    %413 = tosa.rescale %411, %239, %237, %145, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
+    %414 = tosa.rescale %413, %125, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
+    %415 = tosa.add %412, %414 : (tensor<1x8x8x52xi32>, tensor<1x8x8x52xi32>) -> tensor<1x8x8x52xi32>
+    %416 = tosa.rescale %415, %124, %186, %283, %123 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
+    %417 = tosa.conv2d %416, %122, %121, %123, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x52xi8>, tensor<192x1x1x52xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x192xi32>
+    %418 = tosa.rescale %417, %120, %119, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x192xi8>
+    %419 = tosa.clamp %418 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x192xi8>) -> tensor<1x8x8x192xi8>
+    %420 = tosa.reshape %118, %2 : (tensor<1x3x3x192xi8>, !tosa.shape<4>) -> tensor<3x3x192x1xi8>
+    %421 = tosa.depthwise_conv2d %419, %420, %117, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x192xi8>, tensor<3x3x192x1xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x192xi32>
+    %422 = tosa.rescale %421, %116, %115, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x192xi8>
+    %423 = tosa.clamp %422 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x192xi8>) -> tensor<1x8x8x192xi8>
+    %424 = tosa.conv2d %423, %114, %113, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x192xi8>, tensor<68x1x1x192xi8>, tensor<68xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x68xi32>
+    %425 = tosa.rescale %424, %112, %111, %283, %287 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<68xi32>, tensor<68xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
+    %426 = tosa.conv2d %425, %110, %109, %287, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x68xi8>, tensor<172x1x1x68xi8>, tensor<172xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x172xi32>
+    %427 = tosa.rescale %426, %108, %107, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x172xi32>, tensor<172xi32>, tensor<172xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x172xi8>
+    %428 = tosa.clamp %427 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x172xi8>) -> tensor<1x8x8x172xi8>
+    %429 = tosa.reshape %106, %1 : (tensor<1x3x3x172xi8>, !tosa.shape<4>) -> tensor<3x3x172x1xi8>
+    %430 = tosa.depthwise_conv2d %428, %429, %105, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x172xi8>, tensor<3x3x172x1xi8>, tensor<172xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x172xi32>
+    %431 = tosa.rescale %430, %104, %103, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x172xi32>, tensor<172xi32>, tensor<172xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x172xi8>
+    %432 = tosa.clamp %431 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x172xi8>) -> tensor<1x8x8x172xi8>
+    %433 = tosa.conv2d %432, %102, %101, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x172xi8>, tensor<68x1x1x172xi8>, tensor<68xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x68xi32>
+    %434 = tosa.rescale %433, %99, %98, %283, %100 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<68xi32>, tensor<68xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
+    %435 = tosa.rescale %425, %239, %237, %287, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
+    %436 = tosa.rescale %435, %97, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
+    %437 = tosa.rescale %434, %239, %238, %100, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
+    %438 = tosa.add %436, %437 : (tensor<1x8x8x68xi32>, tensor<1x8x8x68xi32>) -> tensor<1x8x8x68xi32>
+    %439 = tosa.rescale %438, %96, %186, %283, %95 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
+    %440 = tosa.conv2d %439, %94, %93, %95, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x68xi8>, tensor<172x1x1x68xi8>, tensor<172xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x172xi32>
+    %441 = tosa.rescale %440, %92, %91, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x172xi32>, tensor<172xi32>, tensor<172xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x172xi8>
+    %442 = tosa.clamp %441 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x172xi8>) -> tensor<1x8x8x172xi8>
+    %443 = tosa.reshape %90, %1 : (tensor<1x3x3x172xi8>, !tosa.shape<4>) -> tensor<3x3x172x1xi8>
+    %444 = tosa.depthwise_conv2d %442, %443, %89, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x172xi8>, tensor<3x3x172x1xi8>, tensor<172xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x172xi32>
+    %445 = tosa.rescale %444, %88, %87, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x172xi32>, tensor<172xi32>, tensor<172xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x172xi8>
+    %446 = tosa.clamp %445 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x172xi8>) -> tensor<1x8x8x172xi8>
+    %447 = tosa.conv2d %446, %86, %85, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x172xi8>, tensor<48x1x1x172xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x48xi32>
+    %448 = tosa.rescale %447, %83, %82, %283, %84 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x48xi8>
+    %449 = tosa.pad %448, %81, %80 : (tensor<1x8x8x48xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
+    %450 = tosa.rescale %439, %239, %238, %95, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
+    %451 = tosa.rescale %449, %239, %237, %84, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
+    %452 = tosa.rescale %451, %79, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
+    %453 = tosa.add %450, %452 : (tensor<1x8x8x68xi32>, tensor<1x8x8x68xi32>) -> tensor<1x8x8x68xi32>
+    %454 = tosa.rescale %453, %78, %186, %283, %77 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
+    %455 = tosa.conv2d %454, %76, %75, %77, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x68xi8>, tensor<288x1x1x68xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x288xi32>
+    %456 = tosa.rescale %455, %74, %73, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x288xi8>
+    %457 = tosa.clamp %456 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x288xi8>) -> tensor<1x8x8x288xi8>
+    %458 = tosa.reshape %72, %0 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
+    %459 = tosa.depthwise_conv2d %457, %458, %71, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x8x8x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x288xi32>
+    %460 = tosa.rescale %459, %70, %69, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x288xi8>
+    %461 = tosa.clamp %460 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x288xi8>) -> tensor<1x4x4x288xi8>
+    %462 = tosa.conv2d %461, %68, %67, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x288xi8>, tensor<16x1x1x288xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x16xi32>
+    %463 = tosa.rescale %462, %65, %64, %283, %66 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x16xi8>
+    %464 = tosa.conv2d %463, %63, %62, %66, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x16xi8>, tensor<96x1x1x16xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
+    %465 = tosa.rescale %464, %61, %60, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
+    %466 = tosa.clamp %465 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
+    %467 = tosa.reshape %59, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
+    %468 = tosa.depthwise_conv2d %466, %467, %58, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
+    %469 = tosa.rescale %468, %57, %56, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
+    %470 = tosa.clamp %469 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
+    %471 = tosa.conv2d %470, %55, %54, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<16x1x1x96xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x16xi32>
+    %472 = tosa.rescale %471, %53, %52, %283, %95 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x16xi8>
+    %473 = tosa.rescale %463, %239, %237, %66, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x4x4x16xi32>
+    %474 = tosa.rescale %473, %51, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x4x4x16xi32>
+    %475 = tosa.rescale %472, %239, %238, %95, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x4x4x16xi32>
+    %476 = tosa.add %474, %475 : (tensor<1x4x4x16xi32>, tensor<1x4x4x16xi32>) -> tensor<1x4x4x16xi32>
+    %477 = tosa.rescale %476, %50, %186, %283, %49 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x16xi8>
+    %478 = tosa.conv2d %477, %48, %47, %49, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x16xi8>, tensor<96x1x1x16xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
+    %479 = tosa.rescale %478, %46, %45, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
+    %480 = tosa.clamp %479 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
+    %481 = tosa.reshape %44, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
+    %482 = tosa.depthwise_conv2d %480, %481, %43, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
+    %483 = tosa.rescale %482, %42, %41, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
+    %484 = tosa.clamp %483 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
+    %485 = tosa.conv2d %484, %40, %39, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<32x1x1x96xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x32xi32>
+    %486 = tosa.rescale %485, %38, %37, %283, %287 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x32xi8>
+    %487 = tosa.pad %477, %36, %35 : (tensor<1x4x4x16xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x4x4x32xi8>
+    %488 = tosa.rescale %487, %239, %238, %49, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x4x4x32xi32>
+    %489 = tosa.rescale %486, %239, %237, %287, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x4x4x32xi32>
+    %490 = tosa.rescale %489, %34, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x4x4x32xi32>
+    %491 = tosa.add %488, %490 : (tensor<1x4x4x32xi32>, tensor<1x4x4x32xi32>) -> tensor<1x4x4x32xi32>
+    %492 = tosa.rescale %491, %33, %186, %283, %32 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x32xi8>
+    %493 = tosa.conv2d %492, %31, %30, %32, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x32xi8>, tensor<96x1x1x32xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
+    %494 = tosa.rescale %493, %29, %28, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
+    %495 = tosa.clamp %494 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
+    %496 = tosa.reshape %27, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
+    %497 = tosa.depthwise_conv2d %495, %496, %26, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
+    %498 = tosa.rescale %497, %25, %24, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
+    %499 = tosa.clamp %498 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
+    %500 = tosa.conv2d %499, %23, %22, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<32x1x1x96xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x32xi32>
+    %501 = tosa.rescale %500, %21, %20, %283, %202 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x32xi8>
+    %502 = tosa.conv2d %501, %19, %18, %202, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x32xi8>, tensor<128x1x1x32xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x128xi32>
+    %503 = tosa.rescale %502, %17, %16, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x128xi8>
+    %504 = tosa.clamp %503 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x128xi8>) -> tensor<1x4x4x128xi8>
+    %505 = tosa.avg_pool2d %504, %287, %287 {acc_type = i32, kernel = array<i64: 4, 4>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 4, 4>} : (tensor<1x4x4x128xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x128xi8>
+    %506 = tosa.conv2d %505, %15, %14, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<2x1x1x128xi8>, tensor<2xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x2xi32>
+    %507 = tosa.rescale %506, %12, %11, %283, %13 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x2xi32>, tensor<2xi32>, tensor<2xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x2xi8>
+    %508 = tosa.reshape %507, %10 : (tensor<1x1x1x2xi8>, !tosa.shape<2>) -> tensor<1x2xi8>
+    return %508 : tensor<1x2xi8>
+  }
+}
diff --git a/tests/gold/test_python_api/yolov3_tiny_int8_pruned_backbone_only.mlir b/tests/gold/test_python_api/yolov3_tiny_int8_pruned_backbone_only.mlir
new file mode 100644
index 0000000..6457b20
--- /dev/null
+++ b/tests/gold/test_python_api/yolov3_tiny_int8_pruned_backbone_only.mlir
@@ -0,0 +1,197 @@
+module attributes {tf_saved_model.semantics, tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "2.3.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
+  func.func @main(%arg0: tensor<?x416x416x3xi8> {tf_saved_model.index_path = ["input"]}) -> (tensor<?x26x26x3x85xi8> {tf_saved_model.index_path = ["yolo_output_1"]}, tensor<?x13x13x3x85xi8> {tf_saved_model.index_path = ["yolo_output_0"]}) attributes {tf.entry_function = {inputs = "serving_default_input:0", outputs = "StatefulPartitionedCall:1,StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {
+    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<5xindex>} : () -> !tosa.shape<5>
+    %1 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi8>}> : () -> tensor<255xi8>
+    %2 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi32>}> : () -> tensor<255xi32>
+    %3 = "tosa.const"() <{values = dense<67> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %4 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi32>}> : () -> tensor<255xi32>
+    %5 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255x1x1x256xi8>}> : () -> tensor<255x1x1x256xi8>
+    %6 = "tosa.const"() <{values = dense<-100> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %7 = "tosa.const"() <{values = dense<2146540981> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %8 = "tosa.const"() <{values = dense<1717232810> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %9 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
+    %10 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
+    %11 = "tosa.const"() <{values = dense<14> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
+    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256x3x3x384xi8>}> : () -> tensor<256x3x3x384xi8>
+    %14 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<5xindex>} : () -> !tosa.shape<5>
+    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi8>}> : () -> tensor<255xi8>
+    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi32>}> : () -> tensor<255xi32>
+    %17 = "tosa.const"() <{values = dense<57> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi32>}> : () -> tensor<255xi32>
+    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255x1x1x512xi8>}> : () -> tensor<255x1x1x512xi8>
+    %20 = "tosa.const"() <{values = dense<-102> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %21 = "tosa.const"() <{values = dense<2045027926> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %22 = "tosa.const"() <{values = dense<1636022365> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi8>}> : () -> tensor<512xi8>
+    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi32>}> : () -> tensor<512xi32>
+    %25 = "tosa.const"() <{values = dense<7> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi32>}> : () -> tensor<512xi32>
+    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512x3x3x256xi8>}> : () -> tensor<512x3x3x256xi8>
+    %28 = tosa.const_shape  {values = dense<3> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %29 = tosa.const_shape  {values = dense<1> : tensor<2xindex>} : () -> !tosa.shape<2>
+    %30 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
+    %31 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %32 = "tosa.const"() <{values = dense<1867790575> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %33 = "tosa.const"() <{values = dense<34> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %34 = "tosa.const"() <{values = dense<1494232483> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
+    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %37 = "tosa.const"() <{values = dense<-16> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x1x1x256xi8>}> : () -> tensor<128x1x1x256xi8>
+    %40 = "tosa.const"() <{values = dense<-95> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %41 = "tosa.const"() <{values = dense<1153990886> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %42 = "tosa.const"() <{values = dense<1846385445> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
+    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
+    %45 = "tosa.const"() <{values = dense<24> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
+    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256x1x1x1024xi8>}> : () -> tensor<256x1x1x1024xi8>
+    %48 = "tosa.const"() <{values = dense<-98> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %49 = "tosa.const"() <{values = dense<1112539429> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %50 = "tosa.const"() <{values = dense<1780063113> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %51 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1024xi8>}> : () -> tensor<1024xi8>
+    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1024xi32>}> : () -> tensor<1024xi32>
+    %53 = "tosa.const"() <{values = dense<19> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %54 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1024xi32>}> : () -> tensor<1024xi32>
+    %55 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1024x3x3x512xi8>}> : () -> tensor<1024x3x3x512xi8>
+    %56 = "tosa.const"() <{values = dense<-99> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %57 = "tosa.const"() <{values = dense<1090607686> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %58 = "tosa.const"() <{values = dense<1744972324> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi8>}> : () -> tensor<512xi8>
+    %60 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi32>}> : () -> tensor<512xi32>
+    %61 = "tosa.const"() <{values = dense<16> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %62 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi32>}> : () -> tensor<512xi32>
+    %63 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512x3x3x256xi8>}> : () -> tensor<512x3x3x256xi8>
+    %64 = "tosa.const"() <{values = dense<-108> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %65 = "tosa.const"() <{values = dense<1827454564> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %66 = "tosa.const"() <{values = dense<1461963673> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %67 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
+    %68 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
+    %69 = "tosa.const"() <{values = dense<-11> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
+    %71 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256x3x3x128xi8>}> : () -> tensor<256x3x3x128xi8>
+    %72 = "tosa.const"() <{values = dense<-93> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %73 = "tosa.const"() <{values = dense<1199308892> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %74 = "tosa.const"() <{values = dense<1918894256> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %75 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
+    %76 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %77 = "tosa.const"() <{values = dense<28> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %78 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
+    %79 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x3x3x64xi8>}> : () -> tensor<128x3x3x64xi8>
+    %80 = "tosa.const"() <{values = dense<-85> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %81 = "tosa.const"() <{values = dense<1360529732> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %82 = "tosa.const"() <{values = dense<1088423802> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %83 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
+    %84 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
+    %85 = "tosa.const"() <{values = dense<44> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %86 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
+    %87 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x3x3x32xi8>}> : () -> tensor<64x3x3x32xi8>
+    %88 = "tosa.const"() <{values = dense<-74> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %89 = "tosa.const"() <{values = dense<29> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %90 = "tosa.const"() <{values = dense<1564368468> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %91 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %92 = "tosa.const"() <{values = dense<1251494793> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %93 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
+    %94 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %95 = "tosa.const"() <{values = dense<58> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %96 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
+    %97 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x3x3x16xi8>}> : () -> tensor<32x3x3x16xi8>
+    %98 = "tosa.const"() <{values = dense<-106> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %99 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %100 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %101 = "tosa.const"() <{values = dense<1905935579> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %102 = "tosa.const"() <{values = dense<33> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %103 = "tosa.const"() <{values = dense<1524748486> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %104 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
+    %105 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %106 = "tosa.const"() <{values = dense<-4> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %107 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
+    %108 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x3x3x3xi8>}> : () -> tensor<16x3x3x3xi8>
+    %109 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
+    %110 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %111 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
+    %112 = tosa.conv2d %arg0, %108, %109, %110, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x416x416x3xi8>, tensor<16x3x3x3xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x416x416x16xi32>
+    %113 = tosa.rescale %112, %105, %104, %107, %106 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x416x416x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x416x416x16xi8>
+    %114 = tosa.rescale %113, %103, %102, %106, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x416x416x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x416x416x16xi32>
+    %115 = tosa.rescale %113, %101, %100, %106, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x416x416x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x416x416x16xi32>
+    %116 = tosa.maximum %115, %114 : (tensor<?x416x416x16xi32>, tensor<?x416x416x16xi32>) -> tensor<?x416x416x16xi32>
+    %117 = tosa.rescale %116, %99, %100, %107, %98 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x416x416x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x416x416x16xi8>
+    %118 = tosa.max_pool2d %117 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x416x416x16xi8>) -> tensor<?x208x208x16xi8>
+    %119 = tosa.conv2d %118, %97, %96, %98, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x208x208x16xi8>, tensor<32x3x3x16xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x208x208x32xi32>
+    %120 = tosa.rescale %119, %94, %93, %107, %95 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x208x208x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x208x208x32xi8>
+    %121 = tosa.rescale %120, %92, %91, %95, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x208x208x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x208x208x32xi32>
+    %122 = tosa.rescale %120, %90, %89, %95, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x208x208x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x208x208x32xi32>
+    %123 = tosa.maximum %122, %121 : (tensor<?x208x208x32xi32>, tensor<?x208x208x32xi32>) -> tensor<?x208x208x32xi32>
+    %124 = tosa.rescale %123, %99, %100, %107, %88 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x208x208x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x208x208x32xi8>
+    %125 = tosa.max_pool2d %124 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x208x208x32xi8>) -> tensor<?x104x104x32xi8>
+    %126 = tosa.conv2d %125, %87, %86, %88, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x104x104x32xi8>, tensor<64x3x3x32xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x104x104x64xi32>
+    %127 = tosa.rescale %126, %84, %83, %107, %85 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x104x104x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x104x104x64xi8>
+    %128 = tosa.rescale %127, %82, %91, %85, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x104x104x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x104x104x64xi32>
+    %129 = tosa.rescale %127, %81, %89, %85, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x104x104x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x104x104x64xi32>
+    %130 = tosa.maximum %129, %128 : (tensor<?x104x104x64xi32>, tensor<?x104x104x64xi32>) -> tensor<?x104x104x64xi32>
+    %131 = tosa.rescale %130, %99, %100, %107, %80 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x104x104x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x104x104x64xi8>
+    %132 = tosa.max_pool2d %131 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x104x104x64xi8>) -> tensor<?x52x52x64xi8>
+    %133 = tosa.conv2d %132, %79, %78, %80, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x52x52x64xi8>, tensor<128x3x3x64xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x52x52x128xi32>
+    %134 = tosa.rescale %133, %76, %75, %107, %77 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x52x52x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x52x52x128xi8>
+    %135 = tosa.rescale %134, %74, %102, %77, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x52x52x128xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x52x52x128xi32>
+    %136 = tosa.rescale %134, %73, %89, %77, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x52x52x128xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x52x52x128xi32>
+    %137 = tosa.maximum %136, %135 : (tensor<?x52x52x128xi32>, tensor<?x52x52x128xi32>) -> tensor<?x52x52x128xi32>
+    %138 = tosa.rescale %137, %99, %100, %107, %72 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x52x52x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x52x52x128xi8>
+    %139 = tosa.max_pool2d %138 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x52x52x128xi8>) -> tensor<?x26x26x128xi8>
+    %140 = tosa.conv2d %139, %71, %70, %72, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x26x26x128xi8>, tensor<256x3x3x128xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x26x26x256xi32>
+    %141 = tosa.rescale %140, %68, %67, %107, %69 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x256xi8>
+    %142 = tosa.rescale %141, %66, %102, %69, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x26x26x256xi32>
+    %143 = tosa.rescale %141, %65, %100, %69, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x26x26x256xi32>
+    %144 = tosa.maximum %143, %142 : (tensor<?x26x26x256xi32>, tensor<?x26x26x256xi32>) -> tensor<?x26x26x256xi32>
+    %145 = tosa.rescale %144, %99, %100, %107, %64 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x256xi8>
+    %146 = tosa.max_pool2d %145 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x26x26x256xi8>) -> tensor<?x13x13x256xi8>
+    %147 = tosa.conv2d %146, %63, %62, %64, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x13x13x256xi8>, tensor<512x3x3x256xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x512xi32>
+    %148 = tosa.rescale %147, %60, %59, %107, %61 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x512xi8>
+    %149 = tosa.rescale %148, %58, %102, %61, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x512xi32>
+    %150 = tosa.rescale %148, %57, %89, %61, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x512xi32>
+    %151 = tosa.maximum %150, %149 : (tensor<?x13x13x512xi32>, tensor<?x13x13x512xi32>) -> tensor<?x13x13x512xi32>
+    %152 = tosa.rescale %151, %99, %100, %107, %56 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x512xi8>
+    %153 = tosa.max_pool2d %152 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} : (tensor<?x13x13x512xi8>) -> tensor<?x13x13x512xi8>
+    %154 = tosa.conv2d %153, %55, %54, %56, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x13x13x512xi8>, tensor<1024x3x3x512xi8>, tensor<1024xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x1024xi32>
+    %155 = tosa.rescale %154, %52, %51, %107, %53 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x1024xi32>, tensor<1024xi32>, tensor<1024xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x1024xi8>
+    %156 = tosa.rescale %155, %50, %102, %53, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x1024xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x1024xi32>
+    %157 = tosa.rescale %155, %49, %89, %53, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x1024xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x1024xi32>
+    %158 = tosa.maximum %157, %156 : (tensor<?x13x13x1024xi32>, tensor<?x13x13x1024xi32>) -> tensor<?x13x13x1024xi32>
+    %159 = tosa.rescale %158, %99, %100, %107, %48 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x1024xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x1024xi8>
+    %160 = tosa.conv2d %159, %47, %46, %48, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x13x13x1024xi8>, tensor<256x1x1x1024xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x256xi32>
+    %161 = tosa.rescale %160, %44, %43, %107, %45 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x256xi8>
+    %162 = tosa.rescale %161, %42, %102, %45, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x256xi32>
+    %163 = tosa.rescale %161, %41, %89, %45, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x256xi32>
+    %164 = tosa.maximum %163, %162 : (tensor<?x13x13x256xi32>, tensor<?x13x13x256xi32>) -> tensor<?x13x13x256xi32>
+    %165 = tosa.rescale %164, %99, %100, %107, %40 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x256xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x256xi8>
+    %166 = tosa.conv2d %165, %39, %38, %40, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x13x13x256xi8>, tensor<128x1x1x256xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x128xi32>
+    %167 = tosa.rescale %166, %36, %35, %107, %37 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x128xi8>
+    %168 = tosa.rescale %167, %34, %33, %37, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x128xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x128xi32>
+    %169 = tosa.rescale %167, %32, %31, %37, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x128xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x128xi32>
+    %170 = tosa.maximum %169, %168 : (tensor<?x13x13x128xi32>, tensor<?x13x13x128xi32>) -> tensor<?x13x13x128xi32>
+    %171 = tosa.rescale %170, %99, %100, %107, %64 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x128xi8>
+    %172 = tosa.resize %171, %30, %29, %28 {mode = "NEAREST_NEIGHBOR"} : (tensor<?x13x13x128xi8>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<?x26x26x128xi8>
+    %173 = tosa.concat %172, %145 {axis = 3 : i32} : (tensor<?x26x26x128xi8>, tensor<?x26x26x256xi8>) -> tensor<?x26x26x384xi8>
+    %174 = tosa.conv2d %165, %27, %26, %40, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x13x13x256xi8>, tensor<512x3x3x256xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x512xi32>
+    %175 = tosa.rescale %174, %24, %23, %107, %25 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x512xi8>
+    %176 = tosa.rescale %175, %22, %102, %25, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x512xi32>
+    %177 = tosa.rescale %175, %21, %100, %25, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x512xi32>
+    %178 = tosa.maximum %177, %176 : (tensor<?x13x13x512xi32>, tensor<?x13x13x512xi32>) -> tensor<?x13x13x512xi32>
+    %179 = tosa.rescale %178, %99, %100, %107, %20 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x512xi8>
+    %180 = tosa.conv2d %179, %19, %18, %20, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x13x13x512xi8>, tensor<255x1x1x512xi8>, tensor<255xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x255xi32>
+    %181 = tosa.rescale %180, %16, %15, %107, %17 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x255xi32>, tensor<255xi32>, tensor<255xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x255xi8>
+    %182 = tosa.reshape %181, %14 : (tensor<?x13x13x255xi8>, !tosa.shape<5>) -> tensor<?x13x13x3x85xi8>
+    %183 = tosa.conv2d %173, %13, %12, %64, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x26x26x384xi8>, tensor<256x3x3x384xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x26x26x256xi32>
+    %184 = tosa.rescale %183, %10, %9, %107, %11 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x256xi8>
+    %185 = tosa.rescale %184, %8, %102, %11, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x26x26x256xi32>
+    %186 = tosa.rescale %184, %7, %100, %11, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x26x26x256xi32>
+    %187 = tosa.maximum %186, %185 : (tensor<?x26x26x256xi32>, tensor<?x26x26x256xi32>) -> tensor<?x26x26x256xi32>
+    %188 = tosa.rescale %187, %99, %100, %107, %6 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x256xi8>
+    %189 = tosa.conv2d %188, %5, %4, %6, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x26x26x256xi8>, tensor<255x1x1x256xi8>, tensor<255xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x26x26x255xi32>
+    %190 = tosa.rescale %189, %2, %1, %107, %3 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x255xi32>, tensor<255xi32>, tensor<255xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x255xi8>
+    %191 = tosa.reshape %190, %0 : (tensor<?x26x26x255xi8>, !tosa.shape<5>) -> tensor<?x26x26x3x85xi8>
+    return %191, %182 : tensor<?x26x26x3x85xi8>, tensor<?x13x13x3x85xi8>
+  }
+}
-- 
GitLab


From 7c54c60e9c7d199a6a3e632ab6b014e89acf6218 Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Thu, 10 Jul 2025 12:23:47 +0100
Subject: [PATCH 3/9] docs(tests): document CLI and Python API test suites

- Add overview of test coverage and installation requirements
- Details of CLI test definitions, execution commands, and how to add new CLI tests
- Details of Python API test definitions, golden file locations, execution commands, and how to add new API tests

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 tests/README.md | 99 +++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 99 insertions(+)
 create mode 100644 tests/README.md

diff --git a/tests/README.md b/tests/README.md
new file mode 100644
index 0000000..09ebd5b
--- /dev/null
+++ b/tests/README.md
@@ -0,0 +1,99 @@
+<!--
+    SPDX-FileCopyrightText: Copyright 2025 Arm Limited and/or its affiliates <open-source-office@arm.com>
+
+    SPDX-License-Identifier: Apache-2.0
+-->
+
+# TOSA Converter for TFLite Test Suite
+
+This document summarises the test coverage for the tosa-converter-for-tflite project.
+
+## Requirements to run Tests
+
+- Python >= 3.9
+- pytest >= 7.0
+- hjson >= 3.0
+
+Install dependencies with:
+
+```bash
+pip install pytest==8.4.1 hjson==3.1.0 tensorflow==2.19.0
+```
+
+---
+
+## CLI Tests
+
+The CLI test suite verifies that TFLite models provided as files or through stdin are correctly converted to TOSA MLIR, respecting both output formats (`--bytecode` and `--text`).
+
+### CLI Test Definition
+
+CLI tests are defined in `tests/test_cli.hjson` and consumed by `tests/test_cli.py`.
+
+### Run CLI Tests
+
+```bash
+pytest -v tests/test_cli.py --log-cli-level=DEBUG
+```
+
+### Adding a CLI Test
+
+To add a new CLI test, append an object to `tests/test_cli.hjson`. For example, to verify that `--text` without `-o` writes MLIR text to `stdout`:
+
+```hjson
+{
+  name: text_to_stdout
+  description: "Emit MLIR textual form to stdout when --text is given"
+  args: [
+    "--text"
+    "{model}"
+  ]
+  stdin: null
+  expect_success: true
+  out_fname: null
+}
+```
+
+---
+
+## Python API Tests
+
+The Python API test suite exercises the `tflite_flatbuffer_to_tosa_mlir` wrapper and tests:
+
+- **File based** and **stream based** conversions
+- **Bytecode** and **text** output format generation options
+- **Regression** of MLIR textual output against golden files
+
+### Python API Test Definition
+
+- **Model specs** live in `tests/test_python_api_models.hjson`
+- **Test script** is `tests/test_python_api.py`
+- **Golden textual MLIR files** for text regression are under `tests/gold/test_python_api/*.mlir`
+
+### Run Python API Tests
+
+```bash
+TOSA_TEST_ELIDE=1 pytest tests/test_python_api.py -v --log-cli-level=DEBUG
+```
+
+### Adding a Python API Test
+
+1. **Add a new model spec** to `tests/test_python_api_models.hjson`:
+
+   ```hjson
+   {
+     name: "my_new_model"
+     class: "MyModelClass"
+     input_shape: [128, 128, 3]
+   }
+   ```
+
+2. **Provide a golden MLIR** for text regression:
+   Place `my_new_model.mlir` under `tests/gold/test_python_api/`, which is the expected textual output.
+
+3. **(Optional)** Extend `tests/test_python_api.py` with additional tests:
+
+   ```python
+   def test_some_new_behavior(...):
+       ...
+   ```
-- 
GitLab


From 2ab7794e9a8658ab44aaf450a605e04b2cc1fafb Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Thu, 10 Jul 2025 12:38:05 +0100
Subject: [PATCH 4/9] chore(gitignore): update ignore patterns for generated
 MLIR directory

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 .gitignore | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.gitignore b/.gitignore
index 0bc4134..2a47e77 100644
--- a/.gitignore
+++ b/.gitignore
@@ -9,3 +9,4 @@
 /build
 __pycache__
 *.egg-info
+/tests/generated/
-- 
GitLab


From 0d933acdd5946134e9f62222642e14f64ab62032 Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Thu, 10 Jul 2025 12:40:17 +0100
Subject: [PATCH 5/9] chore(pytest): add `python_api` and `slow` markers in
 setup.cfg

- Register `python_api` marker for Python API tests
- Register `slow` marker for longer-running tests

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 setup.cfg | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/setup.cfg b/setup.cfg
index 5d3e858..98e793f 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -21,4 +21,6 @@ python_files = test_*.py
 norecursedirs = external
 markers =
     cli: marks tests of the command-line interface
+    python_api: marks tests of the Python API
     pre_commit: marks tests to be run in pre-commit
+    slow: marks tests that take more time to run
-- 
GitLab


From e1e62663d4519eacd74f124e2bf21b74275f3949 Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Tue, 15 Jul 2025 16:07:08 +0100
Subject: [PATCH 6/9] cleanup: removing regression tests

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 .gitignore                                    |   1 -
 tests/README.md                               |   9 +-
 tests/gold/test_python_api/ad_small_int8.mlir |  84 --
 .../gold/test_python_api/cnn_s_quantized.mlir | 120 ---
 .../gold/test_python_api/dnn_s_quantized.mlir | 114 --
 .../ds_cnn_s_quantized_int16.mlir             | 125 ---
 .../efficientnet_lite0_224.mlir               | 528 ----------
 tests/gold/test_python_api/har_int8.mlir      | 117 ---
 .../gold/test_python_api/kws_micronet_s.mlir  | 103 --
 ...enet_v2_1.0_224_quantized_1_default_1.mlir | 427 --------
 .../ssd_mobilenet_v3_int8.mlir                | 993 ------------------
 .../tiny_wav2letter_pruned_int8.mlir          | 128 ---
 .../test_python_api/vww4_128_128_INT8.mlir    | 514 ---------
 ...yolov3_tiny_int8_pruned_backbone_only.mlir | 197 ----
 tests/test_python_api.py                      |  59 +-
 15 files changed, 3 insertions(+), 3516 deletions(-)
 delete mode 100644 tests/gold/test_python_api/ad_small_int8.mlir
 delete mode 100644 tests/gold/test_python_api/cnn_s_quantized.mlir
 delete mode 100644 tests/gold/test_python_api/dnn_s_quantized.mlir
 delete mode 100644 tests/gold/test_python_api/ds_cnn_s_quantized_int16.mlir
 delete mode 100644 tests/gold/test_python_api/efficientnet_lite0_224.mlir
 delete mode 100644 tests/gold/test_python_api/har_int8.mlir
 delete mode 100644 tests/gold/test_python_api/kws_micronet_s.mlir
 delete mode 100644 tests/gold/test_python_api/mobilenet_v2_1.0_224_quantized_1_default_1.mlir
 delete mode 100644 tests/gold/test_python_api/ssd_mobilenet_v3_int8.mlir
 delete mode 100644 tests/gold/test_python_api/tiny_wav2letter_pruned_int8.mlir
 delete mode 100644 tests/gold/test_python_api/vww4_128_128_INT8.mlir
 delete mode 100644 tests/gold/test_python_api/yolov3_tiny_int8_pruned_backbone_only.mlir

diff --git a/.gitignore b/.gitignore
index 2a47e77..0bc4134 100644
--- a/.gitignore
+++ b/.gitignore
@@ -9,4 +9,3 @@
 /build
 __pycache__
 *.egg-info
-/tests/generated/
diff --git a/tests/README.md b/tests/README.md
index 09ebd5b..099dc15 100644
--- a/tests/README.md
+++ b/tests/README.md
@@ -62,18 +62,16 @@ The Python API test suite exercises the `tflite_flatbuffer_to_tosa_mlir` wrapper
 
 - **File based** and **stream based** conversions
 - **Bytecode** and **text** output format generation options
-- **Regression** of MLIR textual output against golden files
 
 ### Python API Test Definition
 
 - **Model specs** live in `tests/test_python_api_models.hjson`
 - **Test script** is `tests/test_python_api.py`
-- **Golden textual MLIR files** for text regression are under `tests/gold/test_python_api/*.mlir`
 
 ### Run Python API Tests
 
 ```bash
-TOSA_TEST_ELIDE=1 pytest tests/test_python_api.py -v --log-cli-level=DEBUG
+pytest tests/test_python_api.py -v --log-cli-level=DEBUG
 ```
 
 ### Adding a Python API Test
@@ -88,10 +86,7 @@ TOSA_TEST_ELIDE=1 pytest tests/test_python_api.py -v --log-cli-level=DEBUG
    }
    ```
 
-2. **Provide a golden MLIR** for text regression:
-   Place `my_new_model.mlir` under `tests/gold/test_python_api/`, which is the expected textual output.
-
-3. **(Optional)** Extend `tests/test_python_api.py` with additional tests:
+2. **(Optional)** Extend `tests/test_python_api.py` with additional tests:
 
    ```python
    def test_some_new_behavior(...):
diff --git a/tests/gold/test_python_api/ad_small_int8.mlir b/tests/gold/test_python_api/ad_small_int8.mlir
deleted file mode 100644
index 8794d9e..0000000
--- a/tests/gold/test_python_api/ad_small_int8.mlir
+++ /dev/null
@@ -1,84 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<1x32x32x1xi8>) -> tensor<1x8xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
-    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %5 = "tosa.const"() <{values = dense<41> : tensor<8xi8>}> : () -> tensor<8xi8>
-    %6 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
-    %7 = "tosa.const"() <{values = dense<29> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %8 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
-    %9 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8x1x1x276xi8>}> : () -> tensor<8x1x1x276xi8>
-    %10 = "tosa.const"() <{values = dense<42> : tensor<276xi8>}> : () -> tensor<276xi8>
-    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi32>}> : () -> tensor<276xi32>
-    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276x1x1x276xi8>}> : () -> tensor<276x1x1x276xi8>
-    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi8>}> : () -> tensor<276xi8>
-    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi32>}> : () -> tensor<276xi32>
-    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x276xi8>}> : () -> tensor<1x3x3x276xi8>
-    %16 = "tosa.const"() <{values = dense<41> : tensor<276xi8>}> : () -> tensor<276xi8>
-    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi32>}> : () -> tensor<276xi32>
-    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276xi32>}> : () -> tensor<276xi32>
-    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<276x1x1x220xi8>}> : () -> tensor<276x1x1x220xi8>
-    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220xi8>}> : () -> tensor<220xi8>
-    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220xi32>}> : () -> tensor<220xi32>
-    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x220xi8>}> : () -> tensor<1x3x3x220xi8>
-    %23 = "tosa.const"() <{values = dense<39> : tensor<220xi8>}> : () -> tensor<220xi8>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220xi32>}> : () -> tensor<220xi32>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220xi32>}> : () -> tensor<220xi32>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<220x1x1x164xi8>}> : () -> tensor<220x1x1x164xi8>
-    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<164xi32>}> : () -> tensor<164xi32>
-    %28 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x164xi8>}> : () -> tensor<1x3x3x164xi8>
-    %29 = "tosa.const"() <{values = dense<39> : tensor<164xi8>}> : () -> tensor<164xi8>
-    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<164xi32>}> : () -> tensor<164xi32>
-    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<164xi32>}> : () -> tensor<164xi32>
-    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<164x1x1x72xi8>}> : () -> tensor<164x1x1x72xi8>
-    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi8>}> : () -> tensor<72xi8>
-    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
-    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x72xi8>}> : () -> tensor<1x3x3x72xi8>
-    %36 = "tosa.const"() <{values = dense<38> : tensor<72xi8>}> : () -> tensor<72xi8>
-    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
-    %38 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %39 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72x3x3x1xi8>}> : () -> tensor<72x3x3x1xi8>
-    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
-    %42 = "tosa.const"() <{values = dense<11> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %43 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %44 = tosa.conv2d %arg0, %40, %41, %42, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x32x32x1xi8>, tensor<72x3x3x1xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x72xi32>
-    %45 = tosa.rescale %44, %37, %36, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x72xi8>
-    %46 = tosa.clamp %45 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x72xi8>) -> tensor<1x32x32x72xi8>
-    %47 = tosa.reshape %35, %3 : (tensor<1x3x3x72xi8>, !tosa.shape<4>) -> tensor<3x3x72x1xi8>
-    %48 = tosa.depthwise_conv2d %46, %47, %41, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x32x32x72xi8>, tensor<3x3x72x1xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x72xi32>
-    %49 = tosa.rescale %48, %34, %33, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x72xi8>
-    %50 = tosa.clamp %49 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x72xi8>) -> tensor<1x16x16x72xi8>
-    %51 = tosa.conv2d %50, %32, %31, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x72xi8>, tensor<164x1x1x72xi8>, tensor<164xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x164xi32>
-    %52 = tosa.rescale %51, %30, %29, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x164xi32>, tensor<164xi32>, tensor<164xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x164xi8>
-    %53 = tosa.clamp %52 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x164xi8>) -> tensor<1x16x16x164xi8>
-    %54 = tosa.reshape %28, %2 : (tensor<1x3x3x164xi8>, !tosa.shape<4>) -> tensor<3x3x164x1xi8>
-    %55 = tosa.depthwise_conv2d %53, %54, %31, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x16x16x164xi8>, tensor<3x3x164x1xi8>, tensor<164xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x164xi32>
-    %56 = tosa.rescale %55, %27, %29, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x164xi32>, tensor<164xi32>, tensor<164xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x164xi8>
-    %57 = tosa.clamp %56 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x164xi8>) -> tensor<1x16x16x164xi8>
-    %58 = tosa.conv2d %57, %26, %25, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x164xi8>, tensor<220x1x1x164xi8>, tensor<220xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x220xi32>
-    %59 = tosa.rescale %58, %24, %23, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x220xi32>, tensor<220xi32>, tensor<220xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x220xi8>
-    %60 = tosa.clamp %59 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x220xi8>) -> tensor<1x16x16x220xi8>
-    %61 = tosa.reshape %22, %1 : (tensor<1x3x3x220xi8>, !tosa.shape<4>) -> tensor<3x3x220x1xi8>
-    %62 = tosa.depthwise_conv2d %60, %61, %25, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x16x16x220xi8>, tensor<3x3x220x1xi8>, tensor<220xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x220xi32>
-    %63 = tosa.rescale %62, %21, %20, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x220xi32>, tensor<220xi32>, tensor<220xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x220xi8>
-    %64 = tosa.clamp %63 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x220xi8>) -> tensor<1x8x8x220xi8>
-    %65 = tosa.conv2d %64, %19, %18, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x220xi8>, tensor<276x1x1x220xi8>, tensor<276xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x276xi32>
-    %66 = tosa.rescale %65, %17, %16, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x276xi32>, tensor<276xi32>, tensor<276xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x276xi8>
-    %67 = tosa.clamp %66 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x276xi8>) -> tensor<1x8x8x276xi8>
-    %68 = tosa.reshape %15, %0 : (tensor<1x3x3x276xi8>, !tosa.shape<4>) -> tensor<3x3x276x1xi8>
-    %69 = tosa.depthwise_conv2d %67, %68, %18, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x8x8x276xi8>, tensor<3x3x276x1xi8>, tensor<276xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x276xi32>
-    %70 = tosa.rescale %69, %14, %13, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x276xi32>, tensor<276xi32>, tensor<276xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x276xi8>
-    %71 = tosa.clamp %70 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x276xi8>) -> tensor<1x4x4x276xi8>
-    %72 = tosa.conv2d %71, %12, %18, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x276xi8>, tensor<276x1x1x276xi8>, tensor<276xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x276xi32>
-    %73 = tosa.rescale %72, %11, %10, %39, %38 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x276xi32>, tensor<276xi32>, tensor<276xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x276xi8>
-    %74 = tosa.clamp %73 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x276xi8>) -> tensor<1x4x4x276xi8>
-    %75 = tosa.avg_pool2d %74, %43, %43 {acc_type = i32, kernel = array<i64: 4, 4>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x276xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x276xi8>
-    %76 = tosa.conv2d %75, %9, %8, %38, %43 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x276xi8>, tensor<8x1x1x276xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x8xi32>
-    %77 = tosa.rescale %76, %6, %5, %39, %7 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x8xi8>
-    %78 = tosa.reshape %77, %4 : (tensor<1x1x1x8xi8>, !tosa.shape<2>) -> tensor<1x8xi8>
-    return %78 : tensor<1x8xi8>
-  }
-}
diff --git a/tests/gold/test_python_api/cnn_s_quantized.mlir b/tests/gold/test_python_api/cnn_s_quantized.mlir
deleted file mode 100644
index dd1148f..0000000
--- a/tests/gold/test_python_api/cnn_s_quantized.mlir
+++ /dev/null
@@ -1,120 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.14.0\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<?x490xi8>) -> tensor<?x12xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
-    %0 = "tosa.const"() <{values = dense<35> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %1 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %2 = "tosa.const"() <{values = dense<-1010580540> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %3 = "tosa.const"() <{values = dense<1515870810> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %4 = "tosa.const"() <{values = dense<536870912> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %5 = "tosa.const"() <{values = dense<4> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %6 = "tosa.const"() <{values = dense<12> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %7 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %8 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %9 = "tosa.const"() <{values = dense<9> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %10 = "tosa.const"() <{values = dense<17> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %11 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
-    %12 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %17 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %18 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %19 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %20 = "tosa.const"() <{values = dense<41> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %21 = "tosa.const"() <{values = dense<1201210766> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %22 = "tosa.const"() <{values = dense<34> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %23 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %24 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi32>}> : () -> tensor<12xi32>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12x128xi8>}> : () -> tensor<12x128xi8>
-    %27 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %28 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %29 = "tosa.const"() <{values = dense<1937167208> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %30 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x16xi8>}> : () -> tensor<128x16xi8>
-    %33 = "tosa.const"() <{values = dense<39> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %34 = "tosa.const"() <{values = dense<1331195725> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %35 = "tosa.const"() <{values = dense<-9> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %36 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %37 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1920xi8>}> : () -> tensor<16x1920xi8>
-    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<30xi8>}> : () -> tensor<30xi8>
-    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<30xi32>}> : () -> tensor<30xi32>
-    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<30xi32>}> : () -> tensor<30xi32>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<30x10x4x28xi8>}> : () -> tensor<30x10x4x28xi8>
-    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<28xi8>}> : () -> tensor<28xi8>
-    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<28xi32>}> : () -> tensor<28xi32>
-    %46 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %47 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %48 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %49 = "tosa.const"() <{values = dense<102> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %50 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<28xi32>}> : () -> tensor<28xi32>
-    %51 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<28x10x4x1xi8>}> : () -> tensor<28x10x4x1xi8>
-    %52 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %53 = tosa.reshape %arg0, %52 : (tensor<?x490xi8>, !tosa.shape<4>) -> tensor<?x49x10x1xi8>
-    %54 = tosa.conv2d %53, %51, %50, %49, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x49x10x1xi8>, tensor<28x10x4x1xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x40x7x28xi32>
-    %55 = tosa.rescale %54, %45, %44, %47, %46 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x40x7x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x40x7x28xi8>
-    %56 = tosa.clamp %55 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x40x7x28xi8>) -> tensor<?x40x7x28xi8>
-    %57 = tosa.conv2d %56, %43, %42, %46, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 1>} : (tensor<?x40x7x28xi8>, tensor<30x10x4x28xi8>, tensor<30xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x16x4x30xi32>
-    %58 = tosa.rescale %57, %41, %40, %47, %46 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x16x4x30xi32>, tensor<30xi32>, tensor<30xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x16x4x30xi8>
-    %59 = tosa.clamp %58 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x16x4x30xi8>) -> tensor<?x16x4x30xi8>
-    %60 = tosa.reshape %59, %37 : (tensor<?x16x4x30xi8>, !tosa.shape<4>) -> tensor<?x1x1x1920xi8>
-    %61 = tosa.reshape %39, %36 : (tensor<16x1920xi8>, !tosa.shape<4>) -> tensor<16x1x1x1920xi8>
-    %62 = tosa.conv2d %60, %61, %38, %46, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x1920xi8>, tensor<16x1x1x1920xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x16xi32>
-    %63 = tosa.rescale %62, %34, %33, %47, %35 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x16xi8>
-    %64 = tosa.reshape %32, %30 : (tensor<128x16xi8>, !tosa.shape<4>) -> tensor<128x1x1x16xi8>
-    %65 = tosa.conv2d %63, %64, %31, %35, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x16xi8>, tensor<128x1x1x16xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x128xi32>
-    %66 = tosa.rescale %65, %29, %28, %47, %46 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x128xi8>
-    %67 = tosa.reshape %66, %27 : (tensor<?x1x1x128xi8>, !tosa.shape<2>) -> tensor<?x128xi8>
-    %68 = tosa.clamp %67 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x128xi8>) -> tensor<?x128xi8>
-    %69 = tosa.reshape %68, %24 : (tensor<?x128xi8>, !tosa.shape<4>) -> tensor<?x1x1x128xi8>
-    %70 = tosa.reshape %26, %23 : (tensor<12x128xi8>, !tosa.shape<4>) -> tensor<12x1x1x128xi8>
-    %71 = tosa.conv2d %69, %70, %25, %46, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x128xi8>, tensor<12x1x1x128xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x12xi32>
-    %72 = tosa.rescale %71, %21, %20, %47, %22 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x12xi8>
-    %73 = tosa.reshape %72, %19 : (tensor<?x1x1x12xi8>, !tosa.shape<2>) -> tensor<?x12xi8>
-    %74 = tosa.rescale %73, %18, %17, %22, %47 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x12xi32>
-    %75 = tosa.reduce_max %74 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
-    %76 = tosa.sub %74, %75 : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
-    %77 = tosa.rescale %76, %18, %12, %47, %11 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<?x12xi16>
-    %78 = tosa.table %77, %16 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %79 = tosa.table %77, %15 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %80 = tosa.table %77, %14 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %81 = tosa.table %77, %13 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %82 = tosa.logical_left_shift %78, %10 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %83 = tosa.logical_left_shift %79, %9 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %84 = tosa.logical_left_shift %80, %8 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %85 = tosa.arithmetic_right_shift %81, %7 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %86 = tosa.add %82, %83 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
-    %87 = tosa.add %86, %84 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
-    %88 = tosa.add %87, %85 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
-    %89 = tosa.arithmetic_right_shift %88, %6 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %90 = tosa.reduce_sum %89 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
-    %91 = tosa.clz %90 : (tensor<?x1xi32>) -> tensor<?x1xi32>
-    %92 = tosa.sub %91, %8 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %93 = tosa.logical_left_shift %90, %92 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %94 = tosa.mul %93, %2, %1 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %95 = tosa.add %94, %3 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %96 = tosa.mul %95, %93, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %97 = tosa.sub %4, %96 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %98 = tosa.mul %95, %97, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %99 = tosa.mul %98, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %100 = tosa.add %95, %99 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %101 = tosa.mul %100, %93, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %102 = tosa.sub %4, %101 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %103 = tosa.mul %100, %102, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %104 = tosa.mul %103, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %105 = tosa.add %100, %104 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %106 = tosa.mul %105, %93, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %107 = tosa.sub %4, %106 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %108 = tosa.mul %105, %107, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %109 = tosa.mul %108, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %110 = tosa.add %105, %109 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %111 = tosa.mul %88, %110, %17 : (tensor<?x12xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x12xi32>
-    %112 = tosa.sub %0, %91 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %113 = tosa.arithmetic_right_shift %111, %112 {round = true} : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
-    %114 = tosa.rescale %113, %18, %17, %47, %46 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x12xi8>
-    return %114 : tensor<?x12xi8>
-  }
-}
diff --git a/tests/gold/test_python_api/dnn_s_quantized.mlir b/tests/gold/test_python_api/dnn_s_quantized.mlir
deleted file mode 100644
index 44e67fd..0000000
--- a/tests/gold/test_python_api/dnn_s_quantized.mlir
+++ /dev/null
@@ -1,114 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.14.0\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<?x250xi8>) -> tensor<?x12xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
-    %0 = "tosa.const"() <{values = dense<35> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %1 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %2 = "tosa.const"() <{values = dense<-1010580540> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %3 = "tosa.const"() <{values = dense<1515870810> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %4 = "tosa.const"() <{values = dense<536870912> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %5 = "tosa.const"() <{values = dense<4> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %6 = "tosa.const"() <{values = dense<12> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %7 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %8 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %9 = "tosa.const"() <{values = dense<9> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %10 = "tosa.const"() <{values = dense<17> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %11 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
-    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %16 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %17 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %18 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %19 = "tosa.const"() <{values = dense<40> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %20 = "tosa.const"() <{values = dense<1374243659> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %21 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %22 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi32>}> : () -> tensor<12xi32>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12x144xi8>}> : () -> tensor<12x144xi8>
-    %25 = "tosa.const"() <{values = dense<1143565917> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x144xi8>}> : () -> tensor<144x144xi8>
-    %28 = "tosa.const"() <{values = dense<39> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %29 = "tosa.const"() <{values = dense<1857097977> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %30 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %31 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x144xi8>}> : () -> tensor<144x144xi8>
-    %34 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %35 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %36 = "tosa.const"() <{values = dense<1901577989> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %37 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %38 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %39 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %40 = "tosa.const"() <{values = dense<100> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %41 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x250xi8>}> : () -> tensor<144x250xi8>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %44 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %45 = tosa.reshape %arg0, %44 : (tensor<?x250xi8>, !tosa.shape<4>) -> tensor<?x1x1x250xi8>
-    %46 = tosa.reshape %42, %41 : (tensor<144x250xi8>, !tosa.shape<4>) -> tensor<144x1x1x250xi8>
-    %47 = tosa.conv2d %45, %46, %43, %40, %39 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x250xi8>, tensor<144x1x1x250xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x144xi32>
-    %48 = tosa.rescale %47, %36, %35, %38, %37 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x144xi8>
-    %49 = tosa.reshape %48, %34 : (tensor<?x1x1x144xi8>, !tosa.shape<2>) -> tensor<?x144xi8>
-    %50 = tosa.clamp %49 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x144xi8>) -> tensor<?x144xi8>
-    %51 = tosa.reshape %50, %31 : (tensor<?x144xi8>, !tosa.shape<4>) -> tensor<?x1x1x144xi8>
-    %52 = tosa.reshape %33, %30 : (tensor<144x144xi8>, !tosa.shape<4>) -> tensor<144x1x1x144xi8>
-    %53 = tosa.conv2d %51, %52, %32, %37, %39 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x144xi8>, tensor<144x1x1x144xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x144xi32>
-    %54 = tosa.rescale %53, %29, %28, %38, %37 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x144xi8>
-    %55 = tosa.reshape %54, %34 : (tensor<?x1x1x144xi8>, !tosa.shape<2>) -> tensor<?x144xi8>
-    %56 = tosa.clamp %55 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x144xi8>) -> tensor<?x144xi8>
-    %57 = tosa.reshape %56, %31 : (tensor<?x144xi8>, !tosa.shape<4>) -> tensor<?x1x1x144xi8>
-    %58 = tosa.reshape %27, %30 : (tensor<144x144xi8>, !tosa.shape<4>) -> tensor<144x1x1x144xi8>
-    %59 = tosa.conv2d %57, %58, %26, %37, %39 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x144xi8>, tensor<144x1x1x144xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x144xi32>
-    %60 = tosa.rescale %59, %25, %35, %38, %37 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x144xi8>
-    %61 = tosa.reshape %60, %34 : (tensor<?x1x1x144xi8>, !tosa.shape<2>) -> tensor<?x144xi8>
-    %62 = tosa.clamp %61 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x144xi8>) -> tensor<?x144xi8>
-    %63 = tosa.reshape %62, %31 : (tensor<?x144xi8>, !tosa.shape<4>) -> tensor<?x1x1x144xi8>
-    %64 = tosa.reshape %24, %22 : (tensor<12x144xi8>, !tosa.shape<4>) -> tensor<12x1x1x144xi8>
-    %65 = tosa.conv2d %63, %64, %23, %37, %39 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x144xi8>, tensor<12x1x1x144xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x12xi32>
-    %66 = tosa.rescale %65, %20, %19, %38, %21 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x12xi8>
-    %67 = tosa.reshape %66, %18 : (tensor<?x1x1x12xi8>, !tosa.shape<2>) -> tensor<?x12xi8>
-    %68 = tosa.rescale %67, %17, %16, %21, %38 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x12xi32>
-    %69 = tosa.reduce_max %68 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
-    %70 = tosa.sub %68, %69 : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
-    %71 = tosa.rescale %70, %17, %21, %38, %11 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<?x12xi16>
-    %72 = tosa.table %71, %15 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %73 = tosa.table %71, %14 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %74 = tosa.table %71, %13 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %75 = tosa.table %71, %12 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %76 = tosa.logical_left_shift %72, %10 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %77 = tosa.logical_left_shift %73, %9 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %78 = tosa.logical_left_shift %74, %8 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %79 = tosa.arithmetic_right_shift %75, %7 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %80 = tosa.add %76, %77 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
-    %81 = tosa.add %80, %78 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
-    %82 = tosa.add %81, %79 : (tensor<?x12xi32>, tensor<?x12xi32>) -> tensor<?x12xi32>
-    %83 = tosa.arithmetic_right_shift %82, %6 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %84 = tosa.reduce_sum %83 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
-    %85 = tosa.clz %84 : (tensor<?x1xi32>) -> tensor<?x1xi32>
-    %86 = tosa.sub %85, %8 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %87 = tosa.logical_left_shift %84, %86 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %88 = tosa.mul %87, %2, %1 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %89 = tosa.add %88, %3 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %90 = tosa.mul %89, %87, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %91 = tosa.sub %4, %90 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %92 = tosa.mul %89, %91, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %93 = tosa.mul %92, %5, %39 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %94 = tosa.add %89, %93 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %95 = tosa.mul %94, %87, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %96 = tosa.sub %4, %95 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %97 = tosa.mul %94, %96, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %98 = tosa.mul %97, %5, %39 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %99 = tosa.add %94, %98 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %100 = tosa.mul %99, %87, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %101 = tosa.sub %4, %100 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %102 = tosa.mul %99, %101, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %103 = tosa.mul %102, %5, %39 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %104 = tosa.add %99, %103 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %105 = tosa.mul %82, %104, %16 : (tensor<?x12xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x12xi32>
-    %106 = tosa.sub %0, %85 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %107 = tosa.arithmetic_right_shift %105, %106 {round = true} : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
-    %108 = tosa.rescale %107, %17, %16, %38, %37 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x12xi8>
-    return %108 : tensor<?x12xi8>
-  }
-}
diff --git a/tests/gold/test_python_api/ds_cnn_s_quantized_int16.mlir b/tests/gold/test_python_api/ds_cnn_s_quantized_int16.mlir
deleted file mode 100644
index 4b0d719..0000000
--- a/tests/gold/test_python_api/ds_cnn_s_quantized_int16.mlir
+++ /dev/null
@@ -1,125 +0,0 @@
-module attributes {tf_saved_model.semantics, tfl.description = "MLIR Converted.", tfl.metadata = {CONVERSION_METADATA = "\0C\00\00\00\08\00\0E\00\08\00\04\00\08\00\00\00\10\00\00\00(\00\00\00\00\00\06\00\08\00\04\00\06\00\00\00\04\00\00\00\01\00\00\00\EC\03\00\00\00\00\0A\00\10\00\0C\00\08\00\04\00\0A\00\00\00\02\00\00\00\02\00\00\00\04\00\00\00\05\00\00\002.9.1\00\00\00", min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<?x490xi16> {tf_saved_model.index_path = ["input"]}) -> (tensor<?x12xi16> {tf_saved_model.index_path = ["dense"]}) attributes {tf.entry_function = {inputs = "serving_default_input:0", outputs = "StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {
-    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %1 = "tosa.const"() <{values = dense<31> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %2 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %3 = "tosa.const"() <{values = dense<32768> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %4 = "tosa.const"() <{values = dense<14> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %5 = "tosa.const"() <{values = dense<1073741824> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %6 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %7 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %8 = "tosa.const"() <{values = dense<32767> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %9 = "tosa.const"() <{values = dense<27> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %10 = "tosa.const"() <{values = dense<1564587505> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %12 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %13 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %14 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %15 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %16 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %17 = "tosa.const"() <{values = dense<23137> : tensor<1xi16>}> : () -> tensor<1xi16>
-    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi48>}> : () -> tensor<12xi48>
-    %19 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12x64xi8>}> : () -> tensor<12x64xi8>
-    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x64xi8>}> : () -> tensor<64x1x1x64xi8>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %28 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x64xi8>}> : () -> tensor<1x3x3x64xi8>
-    %29 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x64xi8>}> : () -> tensor<64x1x1x64xi8>
-    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x64xi8>}> : () -> tensor<1x3x3x64xi8>
-    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x64xi8>}> : () -> tensor<64x1x1x64xi8>
-    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x64xi8>}> : () -> tensor<1x3x3x64xi8>
-    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x64xi8>}> : () -> tensor<64x1x1x64xi8>
-    %49 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %50 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %51 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x64xi8>}> : () -> tensor<1x3x3x64xi8>
-    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %54 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi16>}> : () -> tensor<64xi16>
-    %55 = "tosa.const"() <{values = dense<0> : tensor<1xi48>}> : () -> tensor<1xi48>
-    %56 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %57 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
-    %58 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi48>}> : () -> tensor<64xi48>
-    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x10x4x1xi8>}> : () -> tensor<64x10x4x1xi8>
-    %60 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %61 = tosa.reshape %arg0, %60 : (tensor<?x490xi16>, !tosa.shape<4>) -> tensor<?x49x10x1xi16>
-    %62 = tosa.conv2d %61, %59, %58, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 4, 5, 1, 1>, stride = array<i64: 2, 2>} : (tensor<?x49x10x1xi16>, tensor<64x10x4x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %63 = tosa.rescale %62, %54, %53, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %64 = tosa.clamp %63 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %65 = tosa.reshape %52, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
-    %66 = tosa.depthwise_conv2d %64, %65, %51, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<3x3x64x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %67 = tosa.rescale %66, %50, %49, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %68 = tosa.clamp %67 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %69 = tosa.conv2d %68, %48, %47, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<64x1x1x64xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %70 = tosa.rescale %69, %46, %45, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %71 = tosa.clamp %70 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %72 = tosa.reshape %44, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
-    %73 = tosa.depthwise_conv2d %71, %72, %43, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<3x3x64x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %74 = tosa.rescale %73, %42, %41, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %75 = tosa.clamp %74 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %76 = tosa.conv2d %75, %40, %39, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<64x1x1x64xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %77 = tosa.rescale %76, %38, %37, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %78 = tosa.clamp %77 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %79 = tosa.reshape %36, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
-    %80 = tosa.depthwise_conv2d %78, %79, %35, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<3x3x64x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %81 = tosa.rescale %80, %34, %33, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %82 = tosa.clamp %81 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %83 = tosa.conv2d %82, %32, %31, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<64x1x1x64xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %84 = tosa.rescale %83, %30, %29, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %85 = tosa.clamp %84 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %86 = tosa.reshape %28, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
-    %87 = tosa.depthwise_conv2d %85, %86, %27, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<3x3x64x1xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %88 = tosa.rescale %87, %26, %25, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %89 = tosa.clamp %88 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %90 = tosa.conv2d %89, %24, %23, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<64x1x1x64xi8>, tensor<64xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x25x5x64xi48>
-    %91 = tosa.rescale %90, %22, %21, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x25x5x64xi48>, tensor<64xi16>, tensor<64xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x25x5x64xi16>
-    %92 = tosa.clamp %91 {max_val = 32767 : i16, min_val = 0 : i16} : (tensor<?x25x5x64xi16>) -> tensor<?x25x5x64xi16>
-    %93 = tosa.avg_pool2d %92, %57, %57 {acc_type = i32, kernel = array<i64: 25, 5>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x25x5x64xi16>, tensor<1xi16>, tensor<1xi16>) -> tensor<?x1x1x64xi16>
-    %94 = tosa.reshape %20, %19 : (tensor<12x64xi8>, !tosa.shape<4>) -> tensor<12x1x1x64xi8>
-    %95 = tosa.conv2d %93, %94, %18, %57, %56 {acc_type = i48, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x64xi16>, tensor<12x1x1x64xi8>, tensor<12xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<?x1x1x12xi48>
-    %96 = tosa.rescale %95, %17, %16, %55, %57 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = false} : (tensor<?x1x1x12xi48>, tensor<1xi16>, tensor<1xi8>, tensor<1xi48>, tensor<1xi16>) -> tensor<?x1x1x12xi16>
-    %97 = tosa.reshape %96, %15 : (tensor<?x1x1x12xi16>, !tosa.shape<2>) -> tensor<?x12xi16>
-    %98 = tosa.rescale %97, %14, %13, %57, %12 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi16>, tensor<1xi32>, tensor<1xi8>, tensor<1xi16>, tensor<1xi32>) -> tensor<?x12xi32>
-    %99 = tosa.reduce_max %98 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
-    %100 = tosa.sub %98, %99 : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
-    %101 = tosa.rescale %100, %10, %9, %12, %12 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<?x12xi32>
-    %102 = tosa.add %101, %8 : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %103 = tosa.cast %102 : (tensor<?x12xi32>) -> tensor<?x12xi16>
-    %104 = tosa.table %103, %11 : (tensor<?x12xi16>, tensor<513xi16>) -> tensor<?x12xi32>
-    %105 = tosa.arithmetic_right_shift %104, %7 {round = true} : (tensor<?x12xi32>, tensor<1x1xi32>) -> tensor<?x12xi32>
-    %106 = tosa.reduce_sum %105 {axis = 1 : i32} : (tensor<?x12xi32>) -> tensor<?x1xi32>
-    %107 = tosa.clz %106 : (tensor<?x1xi32>) -> tensor<?x1xi32>
-    %108 = tosa.sub %107, %6 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %109 = tosa.logical_left_shift %106, %108 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %110 = tosa.sub %109, %5 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %111 = tosa.arithmetic_right_shift %110, %4 {round = true} : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %112 = tosa.sub %111, %3 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %113 = tosa.cast %112 : (tensor<?x1xi32>) -> tensor<?x1xi16>
-    %114 = tosa.table %113, %2 : (tensor<?x1xi16>, tensor<513xi16>) -> tensor<?x1xi32>
-    %115 = tosa.arithmetic_right_shift %114, %7 {round = true} : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %116 = tosa.mul %115, %105, %56 : (tensor<?x1xi32>, tensor<?x12xi32>, tensor<1xi8>) -> tensor<?x12xi32>
-    %117 = tosa.sub %1, %107 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %118 = tosa.arithmetic_right_shift %116, %117 {round = true} : (tensor<?x12xi32>, tensor<?x1xi32>) -> tensor<?x12xi32>
-    %119 = tosa.rescale %118, %14, %13, %12, %57 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x12xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<?x12xi16>
-    return %119 : tensor<?x12xi16>
-  }
-}
diff --git a/tests/gold/test_python_api/efficientnet_lite0_224.mlir b/tests/gold/test_python_api/efficientnet_lite0_224.mlir
deleted file mode 100644
index 77ae940..0000000
--- a/tests/gold/test_python_api/efficientnet_lite0_224.mlir
+++ /dev/null
@@ -1,528 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<1x224x224x3xui8>) -> tensor<1x1000xui8> attributes {tf.entry_function = {inputs = "images", outputs = "Softmax"}} {
-    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %5 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %6 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %7 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %8 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %9 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %10 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %11 = "tosa.const"() <{values = dense<35> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %12 = "tosa.const"() <{values = dense<-1010580540> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %13 = "tosa.const"() <{values = dense<1515870810> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %14 = "tosa.const"() <{values = dense<536870912> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %15 = "tosa.const"() <{values = dense<4> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %16 = "tosa.const"() <{values = dense<12> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %17 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %18 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %19 = "tosa.const"() <{values = dense<9> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %20 = "tosa.const"() <{values = dense<17> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %21 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
-    %22 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %27 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %28 = "tosa.const"() <{values = dense<40> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %29 = "tosa.const"() <{values = dense<1076206832> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %30 = "tosa.const"() <{values = dense<-62> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %31 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1000xi32>}> : () -> tensor<1000xi32>
-    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1000x1280xi8>}> : () -> tensor<1000x1280xi8>
-    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1280xi8>}> : () -> tensor<1280xi8>
-    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1280xi32>}> : () -> tensor<1280xi32>
-    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1280xi32>}> : () -> tensor<1280xi32>
-    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1280x1x1x320xi8>}> : () -> tensor<1280x1x1x320xi8>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<320xi8>}> : () -> tensor<320xi8>
-    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<320xi32>}> : () -> tensor<320xi32>
-    %40 = "tosa.const"() <{values = dense<-5> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<320xi32>}> : () -> tensor<320xi32>
-    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<320x1x1x1152xi8>}> : () -> tensor<320x1x1x1152xi8>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi8>}> : () -> tensor<1152xi8>
-    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x1152xi8>}> : () -> tensor<1x3x3x1152xi8>
-    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi8>}> : () -> tensor<1152xi8>
-    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %49 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %50 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152x1x1x192xi8>}> : () -> tensor<1152x1x1x192xi8>
-    %51 = "tosa.const"() <{values = dense<-19> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %52 = "tosa.const"() <{values = dense<1844865123> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %53 = "tosa.const"() <{values = dense<2111135967> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %54 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi8>}> : () -> tensor<192xi8>
-    %55 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %56 = "tosa.const"() <{values = dense<-15> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %57 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %58 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192x1x1x1152xi8>}> : () -> tensor<192x1x1x1152xi8>
-    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi8>}> : () -> tensor<1152xi8>
-    %60 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %61 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %62 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x1152xi8>}> : () -> tensor<1x5x5x1152xi8>
-    %63 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi8>}> : () -> tensor<1152xi8>
-    %64 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %65 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %66 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152x1x1x192xi8>}> : () -> tensor<1152x1x1x192xi8>
-    %67 = "tosa.const"() <{values = dense<-16> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %68 = "tosa.const"() <{values = dense<1566288474> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %69 = "tosa.const"() <{values = dense<1421836328> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi8>}> : () -> tensor<192xi8>
-    %71 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %72 = "tosa.const"() <{values = dense<-27> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %73 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %74 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192x1x1x1152xi8>}> : () -> tensor<192x1x1x1152xi8>
-    %75 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi8>}> : () -> tensor<1152xi8>
-    %76 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %77 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %78 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x1152xi8>}> : () -> tensor<1x5x5x1152xi8>
-    %79 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi8>}> : () -> tensor<1152xi8>
-    %80 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %81 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %82 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152x1x1x192xi8>}> : () -> tensor<1152x1x1x192xi8>
-    %83 = "tosa.const"() <{values = dense<2> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %84 = "tosa.const"() <{values = dense<2090466540> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %85 = "tosa.const"() <{values = dense<1656099189> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %86 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi8>}> : () -> tensor<192xi8>
-    %87 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %88 = "tosa.const"() <{values = dense<-12> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %89 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %90 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192x1x1x1152xi8>}> : () -> tensor<192x1x1x1152xi8>
-    %91 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi8>}> : () -> tensor<1152xi8>
-    %92 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %93 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %94 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x1152xi8>}> : () -> tensor<1x5x5x1152xi8>
-    %95 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi8>}> : () -> tensor<1152xi8>
-    %96 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %97 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152xi32>}> : () -> tensor<1152xi32>
-    %98 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1152x1x1x192xi8>}> : () -> tensor<1152x1x1x192xi8>
-    %99 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi8>}> : () -> tensor<192xi8>
-    %100 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %101 = "tosa.const"() <{values = dense<4> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %102 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %103 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192x1x1x672xi8>}> : () -> tensor<192x1x1x672xi8>
-    %104 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi8>}> : () -> tensor<672xi8>
-    %105 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %106 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %107 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x672xi8>}> : () -> tensor<1x5x5x672xi8>
-    %108 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi8>}> : () -> tensor<672xi8>
-    %109 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %110 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %111 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672x1x1x112xi8>}> : () -> tensor<672x1x1x112xi8>
-    %112 = "tosa.const"() <{values = dense<27> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %113 = "tosa.const"() <{values = dense<1858682003> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %114 = "tosa.const"() <{values = dense<1095275027> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %115 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi8>}> : () -> tensor<112xi8>
-    %116 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %117 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %118 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %119 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112x1x1x672xi8>}> : () -> tensor<112x1x1x672xi8>
-    %120 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi8>}> : () -> tensor<672xi8>
-    %121 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %122 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %123 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x672xi8>}> : () -> tensor<1x5x5x672xi8>
-    %124 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi8>}> : () -> tensor<672xi8>
-    %125 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %126 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %127 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672x1x1x112xi8>}> : () -> tensor<672x1x1x112xi8>
-    %128 = "tosa.const"() <{values = dense<18> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %129 = "tosa.const"() <{values = dense<1874662413> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %130 = "tosa.const"() <{values = dense<1480402198> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %131 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi8>}> : () -> tensor<112xi8>
-    %132 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %133 = "tosa.const"() <{values = dense<21> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %134 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %135 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112x1x1x672xi8>}> : () -> tensor<112x1x1x672xi8>
-    %136 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi8>}> : () -> tensor<672xi8>
-    %137 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %138 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %139 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x672xi8>}> : () -> tensor<1x5x5x672xi8>
-    %140 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi8>}> : () -> tensor<672xi8>
-    %141 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %142 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672xi32>}> : () -> tensor<672xi32>
-    %143 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<672x1x1x112xi8>}> : () -> tensor<672x1x1x112xi8>
-    %144 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi8>}> : () -> tensor<112xi8>
-    %145 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %146 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %147 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112x1x1x480xi8>}> : () -> tensor<112x1x1x480xi8>
-    %148 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi8>}> : () -> tensor<480xi8>
-    %149 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %150 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %151 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x480xi8>}> : () -> tensor<1x5x5x480xi8>
-    %152 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi8>}> : () -> tensor<480xi8>
-    %153 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %154 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %155 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480x1x1x80xi8>}> : () -> tensor<480x1x1x80xi8>
-    %156 = "tosa.const"() <{values = dense<49> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %157 = "tosa.const"() <{values = dense<1077008715> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %158 = "tosa.const"() <{values = dense<33> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %159 = "tosa.const"() <{values = dense<2000085201> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %160 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi8>}> : () -> tensor<80xi8>
-    %161 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi32>}> : () -> tensor<80xi32>
-    %162 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi32>}> : () -> tensor<80xi32>
-    %163 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80x1x1x480xi8>}> : () -> tensor<80x1x1x480xi8>
-    %164 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi8>}> : () -> tensor<480xi8>
-    %165 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %166 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %167 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x480xi8>}> : () -> tensor<1x3x3x480xi8>
-    %168 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi8>}> : () -> tensor<480xi8>
-    %169 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %170 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %171 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480x1x1x80xi8>}> : () -> tensor<480x1x1x80xi8>
-    %172 = "tosa.const"() <{values = dense<-1> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %173 = "tosa.const"() <{values = dense<2135713319> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %174 = "tosa.const"() <{values = dense<1310035080> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %175 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi8>}> : () -> tensor<80xi8>
-    %176 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi32>}> : () -> tensor<80xi32>
-    %177 = "tosa.const"() <{values = dense<13> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %178 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi32>}> : () -> tensor<80xi32>
-    %179 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80x1x1x480xi8>}> : () -> tensor<80x1x1x480xi8>
-    %180 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi8>}> : () -> tensor<480xi8>
-    %181 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %182 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %183 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x480xi8>}> : () -> tensor<1x3x3x480xi8>
-    %184 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi8>}> : () -> tensor<480xi8>
-    %185 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %186 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480xi32>}> : () -> tensor<480xi32>
-    %187 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<480x1x1x80xi8>}> : () -> tensor<480x1x1x80xi8>
-    %188 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi8>}> : () -> tensor<80xi8>
-    %189 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi32>}> : () -> tensor<80xi32>
-    %190 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80xi32>}> : () -> tensor<80xi32>
-    %191 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<80x1x1x240xi8>}> : () -> tensor<80x1x1x240xi8>
-    %192 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
-    %193 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %194 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %195 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x240xi8>}> : () -> tensor<1x3x3x240xi8>
-    %196 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
-    %197 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %198 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %199 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240x1x1x40xi8>}> : () -> tensor<240x1x1x40xi8>
-    %200 = "tosa.const"() <{values = dense<-4> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %201 = "tosa.const"() <{values = dense<1934301239> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %202 = "tosa.const"() <{values = dense<1676171725> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %203 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi8>}> : () -> tensor<40xi8>
-    %204 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
-    %205 = "tosa.const"() <{values = dense<-7> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %206 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
-    %207 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40x1x1x240xi8>}> : () -> tensor<40x1x1x240xi8>
-    %208 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
-    %209 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %210 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %211 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x240xi8>}> : () -> tensor<1x5x5x240xi8>
-    %212 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
-    %213 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %214 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %215 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240x1x1x40xi8>}> : () -> tensor<240x1x1x40xi8>
-    %216 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi8>}> : () -> tensor<40xi8>
-    %217 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
-    %218 = "tosa.const"() <{values = dense<-6> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %219 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
-    %220 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40x1x1x144xi8>}> : () -> tensor<40x1x1x144xi8>
-    %221 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi8>}> : () -> tensor<144xi8>
-    %222 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %223 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %224 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x144xi8>}> : () -> tensor<1x5x5x144xi8>
-    %225 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi8>}> : () -> tensor<144xi8>
-    %226 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %227 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %228 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x1x1x24xi8>}> : () -> tensor<144x1x1x24xi8>
-    %229 = "tosa.const"() <{values = dense<-11> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %230 = "tosa.const"() <{values = dense<50> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %231 = "tosa.const"() <{values = dense<1867833568> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %232 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %233 = "tosa.const"() <{values = dense<2065654195> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %234 = "tosa.const"() <{values = dense<10> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %235 = "tosa.const"() <{values = dense<11> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %236 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
-    %237 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %238 = "tosa.const"() <{values = dense<-9> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %239 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %240 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x144xi8>}> : () -> tensor<24x1x1x144xi8>
-    %241 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi8>}> : () -> tensor<144xi8>
-    %242 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %243 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %244 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x144xi8>}> : () -> tensor<1x3x3x144xi8>
-    %245 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi8>}> : () -> tensor<144xi8>
-    %246 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %247 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %248 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x1x1x24xi8>}> : () -> tensor<144x1x1x24xi8>
-    %249 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
-    %250 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %251 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %252 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x96xi8>}> : () -> tensor<24x1x1x96xi8>
-    %253 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %254 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %255 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %256 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
-    %257 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %258 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %259 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %260 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x16xi8>}> : () -> tensor<96x1x1x16xi8>
-    %261 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
-    %262 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %263 = "tosa.const"() <{values = dense<1> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %264 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %265 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x32xi8>}> : () -> tensor<16x1x1x32xi8>
-    %266 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
-    %267 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %268 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %269 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x32xi8>}> : () -> tensor<1x3x3x32xi8>
-    %270 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
-    %271 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %272 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %273 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %274 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x3x3x3xi8>}> : () -> tensor<32x3x3x3xi8>
-    %275 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %276 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %277 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %278 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %279 = "tosa.const"() <{values = dense<-125> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %280 = "tosa.const"() <{values = dense<3> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %281 = tosa.rescale %arg0, %277, %278, %279, %280 {input_unsigned = true, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x224x224x3xui8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x224x224x3xi8>
-    %282 = tosa.rescale %281, %277, %278, %280, %280 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x224x224x3xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x224x224x3xi8>
-    %283 = tosa.conv2d %282, %274, %273, %280, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x224x224x3xi8>, tensor<32x3x3x3xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x32xi32>
-    %284 = tosa.rescale %283, %271, %270, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x32xi8>
-    %285 = tosa.clamp %284 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x112x112x32xi8>) -> tensor<1x112x112x32xi8>
-    %286 = tosa.reshape %269, %10 : (tensor<1x3x3x32xi8>, !tosa.shape<4>) -> tensor<3x3x32x1xi8>
-    %287 = tosa.depthwise_conv2d %285, %286, %268, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x112x112x32xi8>, tensor<3x3x32x1xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x32xi32>
-    %288 = tosa.rescale %287, %267, %266, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x32xi8>
-    %289 = tosa.clamp %288 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x112x112x32xi8>) -> tensor<1x112x112x32xi8>
-    %290 = tosa.conv2d %289, %265, %264, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x112x112x32xi8>, tensor<16x1x1x32xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x16xi32>
-    %291 = tosa.rescale %290, %262, %261, %272, %263 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x16xi8>
-    %292 = tosa.conv2d %291, %260, %259, %263, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x112x112x16xi8>, tensor<96x1x1x16xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x96xi32>
-    %293 = tosa.rescale %292, %258, %257, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x96xi8>
-    %294 = tosa.clamp %293 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x112x112x96xi8>) -> tensor<1x112x112x96xi8>
-    %295 = tosa.reshape %256, %9 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
-    %296 = tosa.depthwise_conv2d %294, %295, %255, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x112x112x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x96xi32>
-    %297 = tosa.rescale %296, %254, %253, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x96xi8>
-    %298 = tosa.clamp %297 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x56x56x96xi8>) -> tensor<1x56x56x96xi8>
-    %299 = tosa.conv2d %298, %252, %251, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x96xi8>, tensor<24x1x1x96xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x24xi32>
-    %300 = tosa.rescale %299, %250, %249, %272, %276 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
-    %301 = tosa.conv2d %300, %248, %247, %276, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x24xi8>, tensor<144x1x1x24xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
-    %302 = tosa.rescale %301, %246, %245, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
-    %303 = tosa.clamp %302 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x56x56x144xi8>) -> tensor<1x56x56x144xi8>
-    %304 = tosa.reshape %244, %8 : (tensor<1x3x3x144xi8>, !tosa.shape<4>) -> tensor<3x3x144x1xi8>
-    %305 = tosa.depthwise_conv2d %303, %304, %243, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x56x56x144xi8>, tensor<3x3x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
-    %306 = tosa.rescale %305, %242, %241, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
-    %307 = tosa.clamp %306 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x56x56x144xi8>) -> tensor<1x56x56x144xi8>
-    %308 = tosa.conv2d %307, %240, %239, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x144xi8>, tensor<24x1x1x144xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x24xi32>
-    %309 = tosa.rescale %308, %237, %236, %272, %238 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
-    %310 = tosa.rescale %309, %277, %235, %238, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
-    %311 = tosa.rescale %300, %277, %234, %276, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
-    %312 = tosa.rescale %311, %233, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
-    %313 = tosa.add %310, %312 : (tensor<1x56x56x24xi32>, tensor<1x56x56x24xi32>) -> tensor<1x56x56x24xi32>
-    %314 = tosa.rescale %313, %231, %230, %272, %229 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
-    %315 = tosa.conv2d %314, %228, %227, %229, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x24xi8>, tensor<144x1x1x24xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
-    %316 = tosa.rescale %315, %226, %225, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
-    %317 = tosa.clamp %316 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x56x56x144xi8>) -> tensor<1x56x56x144xi8>
-    %318 = tosa.reshape %224, %7 : (tensor<1x5x5x144xi8>, !tosa.shape<4>) -> tensor<5x5x144x1xi8>
-    %319 = tosa.depthwise_conv2d %317, %318, %223, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 2, 1, 2>, stride = array<i64: 2, 2>} : (tensor<1x56x56x144xi8>, tensor<5x5x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x144xi32>
-    %320 = tosa.rescale %319, %222, %221, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x144xi8>
-    %321 = tosa.clamp %320 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x28x28x144xi8>) -> tensor<1x28x28x144xi8>
-    %322 = tosa.conv2d %321, %220, %219, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x144xi8>, tensor<40x1x1x144xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x40xi32>
-    %323 = tosa.rescale %322, %217, %216, %272, %218 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x40xi8>
-    %324 = tosa.conv2d %323, %215, %214, %218, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x40xi8>, tensor<240x1x1x40xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x240xi32>
-    %325 = tosa.rescale %324, %213, %212, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x240xi8>
-    %326 = tosa.clamp %325 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x28x28x240xi8>) -> tensor<1x28x28x240xi8>
-    %327 = tosa.reshape %211, %6 : (tensor<1x5x5x240xi8>, !tosa.shape<4>) -> tensor<5x5x240x1xi8>
-    %328 = tosa.depthwise_conv2d %326, %327, %210, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x28x28x240xi8>, tensor<5x5x240x1xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x240xi32>
-    %329 = tosa.rescale %328, %209, %208, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x240xi8>
-    %330 = tosa.clamp %329 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x28x28x240xi8>) -> tensor<1x28x28x240xi8>
-    %331 = tosa.conv2d %330, %207, %206, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x240xi8>, tensor<40x1x1x240xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x40xi32>
-    %332 = tosa.rescale %331, %204, %203, %272, %205 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x40xi8>
-    %333 = tosa.rescale %332, %277, %234, %205, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x40xi32>
-    %334 = tosa.rescale %333, %202, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x28x28x40xi32>
-    %335 = tosa.rescale %323, %277, %235, %218, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x40xi32>
-    %336 = tosa.add %334, %335 : (tensor<1x28x28x40xi32>, tensor<1x28x28x40xi32>) -> tensor<1x28x28x40xi32>
-    %337 = tosa.rescale %336, %201, %230, %272, %200 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x40xi8>
-    %338 = tosa.conv2d %337, %199, %198, %200, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x40xi8>, tensor<240x1x1x40xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x240xi32>
-    %339 = tosa.rescale %338, %197, %196, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x240xi8>
-    %340 = tosa.clamp %339 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x28x28x240xi8>) -> tensor<1x28x28x240xi8>
-    %341 = tosa.reshape %195, %5 : (tensor<1x3x3x240xi8>, !tosa.shape<4>) -> tensor<3x3x240x1xi8>
-    %342 = tosa.depthwise_conv2d %340, %341, %194, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x28x28x240xi8>, tensor<3x3x240x1xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x240xi32>
-    %343 = tosa.rescale %342, %193, %192, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x240xi8>
-    %344 = tosa.clamp %343 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x240xi8>) -> tensor<1x14x14x240xi8>
-    %345 = tosa.conv2d %344, %191, %190, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x240xi8>, tensor<80x1x1x240xi8>, tensor<80xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x80xi32>
-    %346 = tosa.rescale %345, %189, %188, %272, %276 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<80xi32>, tensor<80xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
-    %347 = tosa.conv2d %346, %187, %186, %276, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x80xi8>, tensor<480x1x1x80xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
-    %348 = tosa.rescale %347, %185, %184, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
-    %349 = tosa.clamp %348 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
-    %350 = tosa.reshape %183, %4 : (tensor<1x3x3x480xi8>, !tosa.shape<4>) -> tensor<3x3x480x1xi8>
-    %351 = tosa.depthwise_conv2d %349, %350, %182, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<3x3x480x1xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
-    %352 = tosa.rescale %351, %181, %180, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
-    %353 = tosa.clamp %352 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
-    %354 = tosa.conv2d %353, %179, %178, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<80x1x1x480xi8>, tensor<80xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x80xi32>
-    %355 = tosa.rescale %354, %176, %175, %272, %177 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<80xi32>, tensor<80xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
-    %356 = tosa.rescale %355, %277, %234, %177, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
-    %357 = tosa.rescale %356, %174, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
-    %358 = tosa.rescale %346, %277, %235, %276, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
-    %359 = tosa.add %357, %358 : (tensor<1x14x14x80xi32>, tensor<1x14x14x80xi32>) -> tensor<1x14x14x80xi32>
-    %360 = tosa.rescale %359, %173, %230, %272, %172 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
-    %361 = tosa.conv2d %360, %171, %170, %172, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x80xi8>, tensor<480x1x1x80xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
-    %362 = tosa.rescale %361, %169, %168, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
-    %363 = tosa.clamp %362 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
-    %364 = tosa.reshape %167, %4 : (tensor<1x3x3x480xi8>, !tosa.shape<4>) -> tensor<3x3x480x1xi8>
-    %365 = tosa.depthwise_conv2d %363, %364, %166, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<3x3x480x1xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
-    %366 = tosa.rescale %365, %165, %164, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
-    %367 = tosa.clamp %366 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
-    %368 = tosa.conv2d %367, %163, %162, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<80x1x1x480xi8>, tensor<80xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x80xi32>
-    %369 = tosa.rescale %368, %161, %160, %272, %200 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<80xi32>, tensor<80xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
-    %370 = tosa.rescale %369, %277, %234, %200, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
-    %371 = tosa.rescale %370, %159, %158, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
-    %372 = tosa.rescale %360, %277, %235, %172, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x80xi32>
-    %373 = tosa.add %371, %372 : (tensor<1x14x14x80xi32>, tensor<1x14x14x80xi32>) -> tensor<1x14x14x80xi32>
-    %374 = tosa.rescale %373, %157, %156, %272, %280 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x80xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x80xi8>
-    %375 = tosa.conv2d %374, %155, %154, %280, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x80xi8>, tensor<480x1x1x80xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
-    %376 = tosa.rescale %375, %153, %152, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
-    %377 = tosa.clamp %376 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
-    %378 = tosa.reshape %151, %3 : (tensor<1x5x5x480xi8>, !tosa.shape<4>) -> tensor<5x5x480x1xi8>
-    %379 = tosa.depthwise_conv2d %377, %378, %150, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<5x5x480x1xi8>, tensor<480xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x480xi32>
-    %380 = tosa.rescale %379, %149, %148, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x480xi32>, tensor<480xi32>, tensor<480xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x480xi8>
-    %381 = tosa.clamp %380 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x480xi8>) -> tensor<1x14x14x480xi8>
-    %382 = tosa.conv2d %381, %147, %146, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x480xi8>, tensor<112x1x1x480xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x112xi32>
-    %383 = tosa.rescale %382, %145, %144, %272, %235 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
-    %384 = tosa.conv2d %383, %143, %142, %235, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x112xi8>, tensor<672x1x1x112xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
-    %385 = tosa.rescale %384, %141, %140, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
-    %386 = tosa.clamp %385 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
-    %387 = tosa.reshape %139, %2 : (tensor<1x5x5x672xi8>, !tosa.shape<4>) -> tensor<5x5x672x1xi8>
-    %388 = tosa.depthwise_conv2d %386, %387, %138, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x14x14x672xi8>, tensor<5x5x672x1xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
-    %389 = tosa.rescale %388, %137, %136, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
-    %390 = tosa.clamp %389 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
-    %391 = tosa.conv2d %390, %135, %134, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x672xi8>, tensor<112x1x1x672xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x112xi32>
-    %392 = tosa.rescale %391, %132, %131, %272, %133 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
-    %393 = tosa.rescale %392, %277, %234, %133, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
-    %394 = tosa.rescale %393, %130, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
-    %395 = tosa.rescale %383, %277, %235, %235, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
-    %396 = tosa.add %394, %395 : (tensor<1x14x14x112xi32>, tensor<1x14x14x112xi32>) -> tensor<1x14x14x112xi32>
-    %397 = tosa.rescale %396, %129, %230, %272, %128 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
-    %398 = tosa.conv2d %397, %127, %126, %128, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x112xi8>, tensor<672x1x1x112xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
-    %399 = tosa.rescale %398, %125, %124, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
-    %400 = tosa.clamp %399 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
-    %401 = tosa.reshape %123, %2 : (tensor<1x5x5x672xi8>, !tosa.shape<4>) -> tensor<5x5x672x1xi8>
-    %402 = tosa.depthwise_conv2d %400, %401, %122, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x14x14x672xi8>, tensor<5x5x672x1xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
-    %403 = tosa.rescale %402, %121, %120, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
-    %404 = tosa.clamp %403 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
-    %405 = tosa.conv2d %404, %119, %118, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x672xi8>, tensor<112x1x1x672xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x112xi32>
-    %406 = tosa.rescale %405, %116, %115, %272, %117 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
-    %407 = tosa.rescale %406, %277, %234, %117, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
-    %408 = tosa.rescale %407, %114, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
-    %409 = tosa.rescale %397, %277, %235, %128, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x112xi32>
-    %410 = tosa.add %408, %409 : (tensor<1x14x14x112xi32>, tensor<1x14x14x112xi32>) -> tensor<1x14x14x112xi32>
-    %411 = tosa.rescale %410, %113, %230, %272, %112 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x112xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x112xi8>
-    %412 = tosa.conv2d %411, %111, %110, %112, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x112xi8>, tensor<672x1x1x112xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x672xi32>
-    %413 = tosa.rescale %412, %109, %108, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x672xi8>
-    %414 = tosa.clamp %413 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x14x14x672xi8>) -> tensor<1x14x14x672xi8>
-    %415 = tosa.reshape %107, %2 : (tensor<1x5x5x672xi8>, !tosa.shape<4>) -> tensor<5x5x672x1xi8>
-    %416 = tosa.depthwise_conv2d %414, %415, %106, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 2, 1, 2>, stride = array<i64: 2, 2>} : (tensor<1x14x14x672xi8>, tensor<5x5x672x1xi8>, tensor<672xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x672xi32>
-    %417 = tosa.rescale %416, %105, %104, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x672xi32>, tensor<672xi32>, tensor<672xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x672xi8>
-    %418 = tosa.clamp %417 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x672xi8>) -> tensor<1x7x7x672xi8>
-    %419 = tosa.conv2d %418, %103, %102, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x672xi8>, tensor<192x1x1x672xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x192xi32>
-    %420 = tosa.rescale %419, %100, %99, %272, %101 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
-    %421 = tosa.conv2d %420, %98, %97, %101, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x192xi8>, tensor<1152x1x1x192xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
-    %422 = tosa.rescale %421, %96, %95, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
-    %423 = tosa.clamp %422 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
-    %424 = tosa.reshape %94, %1 : (tensor<1x5x5x1152xi8>, !tosa.shape<4>) -> tensor<5x5x1152x1xi8>
-    %425 = tosa.depthwise_conv2d %423, %424, %93, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<5x5x1152x1xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
-    %426 = tosa.rescale %425, %92, %91, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
-    %427 = tosa.clamp %426 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
-    %428 = tosa.conv2d %427, %90, %89, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<192x1x1x1152xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x192xi32>
-    %429 = tosa.rescale %428, %87, %86, %272, %88 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
-    %430 = tosa.rescale %429, %277, %234, %88, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %431 = tosa.rescale %430, %85, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %432 = tosa.rescale %420, %277, %235, %101, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %433 = tosa.add %431, %432 : (tensor<1x7x7x192xi32>, tensor<1x7x7x192xi32>) -> tensor<1x7x7x192xi32>
-    %434 = tosa.rescale %433, %84, %230, %272, %83 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
-    %435 = tosa.conv2d %434, %82, %81, %83, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x192xi8>, tensor<1152x1x1x192xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
-    %436 = tosa.rescale %435, %80, %79, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
-    %437 = tosa.clamp %436 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
-    %438 = tosa.reshape %78, %1 : (tensor<1x5x5x1152xi8>, !tosa.shape<4>) -> tensor<5x5x1152x1xi8>
-    %439 = tosa.depthwise_conv2d %437, %438, %77, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<5x5x1152x1xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
-    %440 = tosa.rescale %439, %76, %75, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
-    %441 = tosa.clamp %440 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
-    %442 = tosa.conv2d %441, %74, %73, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<192x1x1x1152xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x192xi32>
-    %443 = tosa.rescale %442, %71, %70, %272, %72 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
-    %444 = tosa.rescale %443, %277, %234, %72, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %445 = tosa.rescale %444, %69, %232, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %446 = tosa.rescale %434, %277, %235, %83, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %447 = tosa.add %445, %446 : (tensor<1x7x7x192xi32>, tensor<1x7x7x192xi32>) -> tensor<1x7x7x192xi32>
-    %448 = tosa.rescale %447, %68, %230, %272, %67 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
-    %449 = tosa.conv2d %448, %66, %65, %67, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x192xi8>, tensor<1152x1x1x192xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
-    %450 = tosa.rescale %449, %64, %63, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
-    %451 = tosa.clamp %450 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
-    %452 = tosa.reshape %62, %1 : (tensor<1x5x5x1152xi8>, !tosa.shape<4>) -> tensor<5x5x1152x1xi8>
-    %453 = tosa.depthwise_conv2d %451, %452, %61, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<5x5x1152x1xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
-    %454 = tosa.rescale %453, %60, %59, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
-    %455 = tosa.clamp %454 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
-    %456 = tosa.conv2d %455, %58, %57, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<192x1x1x1152xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x192xi32>
-    %457 = tosa.rescale %456, %55, %54, %272, %56 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
-    %458 = tosa.rescale %457, %277, %234, %56, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %459 = tosa.rescale %458, %53, %158, %272, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %460 = tosa.rescale %448, %277, %235, %67, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x192xi32>
-    %461 = tosa.add %459, %460 : (tensor<1x7x7x192xi32>, tensor<1x7x7x192xi32>) -> tensor<1x7x7x192xi32>
-    %462 = tosa.rescale %461, %52, %230, %272, %51 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x192xi8>
-    %463 = tosa.conv2d %462, %50, %49, %51, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x192xi8>, tensor<1152x1x1x192xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
-    %464 = tosa.rescale %463, %48, %47, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
-    %465 = tosa.clamp %464 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
-    %466 = tosa.reshape %46, %0 : (tensor<1x3x3x1152xi8>, !tosa.shape<4>) -> tensor<3x3x1152x1xi8>
-    %467 = tosa.depthwise_conv2d %465, %466, %45, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<3x3x1152x1xi8>, tensor<1152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1152xi32>
-    %468 = tosa.rescale %467, %44, %43, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1152xi32>, tensor<1152xi32>, tensor<1152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1152xi8>
-    %469 = tosa.clamp %468 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1152xi8>) -> tensor<1x7x7x1152xi8>
-    %470 = tosa.conv2d %469, %42, %41, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1152xi8>, tensor<320x1x1x1152xi8>, tensor<320xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x320xi32>
-    %471 = tosa.rescale %470, %39, %38, %272, %40 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x320xi32>, tensor<320xi32>, tensor<320xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x320xi8>
-    %472 = tosa.conv2d %471, %37, %36, %40, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x320xi8>, tensor<1280x1x1x320xi8>, tensor<1280xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1280xi32>
-    %473 = tosa.rescale %472, %35, %34, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1280xi32>, tensor<1280xi32>, tensor<1280xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1280xi8>
-    %474 = tosa.clamp %473 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x7x7x1280xi8>) -> tensor<1x7x7x1280xi8>
-    %475 = tosa.avg_pool2d %474, %276, %276 {acc_type = i32, kernel = array<i64: 7, 7>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1280xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x1280xi8>
-    %476 = tosa.reshape %33, %31 : (tensor<1000x1280xi8>, !tosa.shape<4>) -> tensor<1000x1x1x1280xi8>
-    %477 = tosa.conv2d %475, %476, %32, %275, %276 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x1280xi8>, tensor<1000x1x1x1280xi8>, tensor<1000xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x1000xi32>
-    %478 = tosa.rescale %477, %29, %28, %272, %30 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x1000xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x1000xi8>
-    %479 = tosa.reshape %478, %27 : (tensor<1x1x1x1000xi8>, !tosa.shape<2>) -> tensor<1x1000xi8>
-    %480 = tosa.rescale %479, %277, %278, %30, %272 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1000xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1000xi32>
-    %481 = tosa.reduce_max %480 {axis = 1 : i32} : (tensor<1x1000xi32>) -> tensor<1x1xi32>
-    %482 = tosa.sub %480, %481 : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
-    %483 = tosa.rescale %482, %277, %22, %272, %21 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1000xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<1x1000xi16>
-    %484 = tosa.table %483, %26 : (tensor<1x1000xi16>, tensor<513xi16>) -> tensor<1x1000xi32>
-    %485 = tosa.table %483, %25 : (tensor<1x1000xi16>, tensor<513xi16>) -> tensor<1x1000xi32>
-    %486 = tosa.table %483, %24 : (tensor<1x1000xi16>, tensor<513xi16>) -> tensor<1x1000xi32>
-    %487 = tosa.table %483, %23 : (tensor<1x1000xi16>, tensor<513xi16>) -> tensor<1x1000xi32>
-    %488 = tosa.logical_left_shift %484, %20 : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
-    %489 = tosa.logical_left_shift %485, %19 : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
-    %490 = tosa.logical_left_shift %486, %18 : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
-    %491 = tosa.arithmetic_right_shift %487, %17 {round = true} : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
-    %492 = tosa.add %488, %489 : (tensor<1x1000xi32>, tensor<1x1000xi32>) -> tensor<1x1000xi32>
-    %493 = tosa.add %492, %490 : (tensor<1x1000xi32>, tensor<1x1000xi32>) -> tensor<1x1000xi32>
-    %494 = tosa.add %493, %491 : (tensor<1x1000xi32>, tensor<1x1000xi32>) -> tensor<1x1000xi32>
-    %495 = tosa.arithmetic_right_shift %494, %16 {round = true} : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
-    %496 = tosa.reduce_sum %495 {axis = 1 : i32} : (tensor<1x1000xi32>) -> tensor<1x1xi32>
-    %497 = tosa.clz %496 : (tensor<1x1xi32>) -> tensor<1x1xi32>
-    %498 = tosa.sub %497, %18 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %499 = tosa.logical_left_shift %496, %498 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %500 = tosa.mul %499, %12, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %501 = tosa.add %500, %13 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %502 = tosa.mul %501, %499, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %503 = tosa.sub %14, %502 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %504 = tosa.mul %501, %503, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %505 = tosa.mul %504, %15, %276 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %506 = tosa.add %501, %505 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %507 = tosa.mul %506, %499, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %508 = tosa.sub %14, %507 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %509 = tosa.mul %506, %508, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %510 = tosa.mul %509, %15, %276 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %511 = tosa.add %506, %510 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %512 = tosa.mul %511, %499, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %513 = tosa.sub %14, %512 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %514 = tosa.mul %511, %513, %117 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %515 = tosa.mul %514, %15, %276 : (tensor<1x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1xi32>
-    %516 = tosa.add %511, %515 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %517 = tosa.mul %494, %516, %278 : (tensor<1x1000xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<1x1000xi32>
-    %518 = tosa.sub %11, %497 : (tensor<1x1xi32>, tensor<1x1xi32>) -> tensor<1x1xi32>
-    %519 = tosa.arithmetic_right_shift %517, %518 {round = true} : (tensor<1x1000xi32>, tensor<1x1xi32>) -> tensor<1x1000xi32>
-    %520 = tosa.rescale %519, %277, %278, %272, %275 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1000xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1000xi8>
-    %521 = tosa.rescale %520, %277, %278, %275, %275 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1000xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1000xi8>
-    %522 = tosa.rescale %521, %277, %278, %275, %276 {input_unsigned = false, output_unsigned = true, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1000xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1000xui8>
-    return %522 : tensor<1x1000xui8>
-  }
-}
diff --git a/tests/gold/test_python_api/har_int8.mlir b/tests/gold/test_python_api/har_int8.mlir
deleted file mode 100644
index e66ed22..0000000
--- a/tests/gold/test_python_api/har_int8.mlir
+++ /dev/null
@@ -1,117 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<?x90x3x1xi8>) -> tensor<?x6xi8> attributes {tf.entry_function = {inputs = "conv2d_input", outputs = "Identity"}} {
-    %0 = "tosa.const"() <{values = dense<35> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %1 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %2 = "tosa.const"() <{values = dense<-1010580540> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %3 = "tosa.const"() <{values = dense<1515870810> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %4 = "tosa.const"() <{values = dense<536870912> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %5 = "tosa.const"() <{values = dense<4> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %6 = "tosa.const"() <{values = dense<12> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %7 = "tosa.const"() <{values = dense<7> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %8 = "tosa.const"() <{values = dense<1> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %9 = "tosa.const"() <{values = dense<9> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %10 = "tosa.const"() <{values = dense<17> : tensor<1x1xi32>}> : () -> tensor<1x1xi32>
-    %11 = "tosa.const"() <{values = dense<0> : tensor<1xi16>}> : () -> tensor<1xi16>
-    %12 = "tosa.const"() <{values = dense<23> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<513xi16>}> : () -> tensor<513xi16>
-    %17 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %18 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %19 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %20 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %21 = "tosa.const"() <{values = dense<1078364279> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %22 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %23 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<6xi32>}> : () -> tensor<6xi32>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<6x128xi8>}> : () -> tensor<6x128xi8>
-    %26 = "tosa.const"() <{values = dense<36> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %27 = "tosa.const"() <{values = dense<1596441372> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %28 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %29 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x128xi8>}> : () -> tensor<128x128xi8>
-    %32 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %33 = "tosa.const"() <{values = dense<41> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %34 = "tosa.const"() <{values = dense<1440829658> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %35 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %36 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x5632xi8>}> : () -> tensor<128x5632xi8>
-    %39 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %40 = tosa.const_shape  {values = dense<0> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
-    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %43 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %44 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x2x2x1xi8>}> : () -> tensor<128x2x2x1xi8>
-    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %47 = "tosa.const"() <{values = dense<-45> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %48 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %49 = tosa.conv2d %arg0, %45, %46, %47, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x90x3x1xi8>, tensor<128x2x2x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x89x2x128xi32>
-    %50 = tosa.rescale %49, %42, %41, %44, %43 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x89x2x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x89x2x128xi8>
-    %51 = tosa.clamp %50 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x89x2x128xi8>) -> tensor<?x89x2x128xi8>
-    %52 = tosa.slice %51, %40, %39 : (tensor<?x89x2x128xi8>, !tosa.shape<4>, !tosa.shape<4>) -> tensor<?x88x2x128xi8>
-    %53 = tosa.max_pool2d %52 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x88x2x128xi8>) -> tensor<?x44x1x128xi8>
-    %54 = tosa.reshape %53, %36 : (tensor<?x44x1x128xi8>, !tosa.shape<4>) -> tensor<?x1x1x5632xi8>
-    %55 = tosa.reshape %38, %35 : (tensor<128x5632xi8>, !tosa.shape<4>) -> tensor<128x1x1x5632xi8>
-    %56 = tosa.conv2d %54, %55, %37, %43, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x5632xi8>, tensor<128x1x1x5632xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x128xi32>
-    %57 = tosa.rescale %56, %34, %33, %44, %43 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x128xi8>
-    %58 = tosa.reshape %57, %32 : (tensor<?x1x1x128xi8>, !tosa.shape<2>) -> tensor<?x128xi8>
-    %59 = tosa.clamp %58 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x128xi8>) -> tensor<?x128xi8>
-    %60 = tosa.reshape %59, %29 : (tensor<?x128xi8>, !tosa.shape<4>) -> tensor<?x1x1x128xi8>
-    %61 = tosa.reshape %31, %28 : (tensor<128x128xi8>, !tosa.shape<4>) -> tensor<128x1x1x128xi8>
-    %62 = tosa.conv2d %60, %61, %30, %43, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x128xi8>, tensor<128x1x1x128xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x128xi32>
-    %63 = tosa.rescale %62, %27, %26, %44, %43 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x128xi8>
-    %64 = tosa.reshape %63, %32 : (tensor<?x1x1x128xi8>, !tosa.shape<2>) -> tensor<?x128xi8>
-    %65 = tosa.clamp %64 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<?x128xi8>) -> tensor<?x128xi8>
-    %66 = tosa.reshape %65, %29 : (tensor<?x128xi8>, !tosa.shape<4>) -> tensor<?x1x1x128xi8>
-    %67 = tosa.reshape %25, %23 : (tensor<6x128xi8>, !tosa.shape<4>) -> tensor<6x1x1x128xi8>
-    %68 = tosa.conv2d %66, %67, %24, %43, %48 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x1x1x128xi8>, tensor<6x1x1x128xi8>, tensor<6xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x1x1x6xi32>
-    %69 = tosa.rescale %68, %21, %20, %44, %22 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x1x1x6xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x1x1x6xi8>
-    %70 = tosa.reshape %69, %19 : (tensor<?x1x1x6xi8>, !tosa.shape<2>) -> tensor<?x6xi8>
-    %71 = tosa.rescale %70, %18, %17, %22, %44 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x6xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x6xi32>
-    %72 = tosa.reduce_max %71 {axis = 1 : i32} : (tensor<?x6xi32>) -> tensor<?x1xi32>
-    %73 = tosa.sub %71, %72 : (tensor<?x6xi32>, tensor<?x1xi32>) -> tensor<?x6xi32>
-    %74 = tosa.rescale %73, %18, %12, %44, %11 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x6xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi16>) -> tensor<?x6xi16>
-    %75 = tosa.table %74, %16 : (tensor<?x6xi16>, tensor<513xi16>) -> tensor<?x6xi32>
-    %76 = tosa.table %74, %15 : (tensor<?x6xi16>, tensor<513xi16>) -> tensor<?x6xi32>
-    %77 = tosa.table %74, %14 : (tensor<?x6xi16>, tensor<513xi16>) -> tensor<?x6xi32>
-    %78 = tosa.table %74, %13 : (tensor<?x6xi16>, tensor<513xi16>) -> tensor<?x6xi32>
-    %79 = tosa.logical_left_shift %75, %10 : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
-    %80 = tosa.logical_left_shift %76, %9 : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
-    %81 = tosa.logical_left_shift %77, %8 : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
-    %82 = tosa.arithmetic_right_shift %78, %7 {round = true} : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
-    %83 = tosa.add %79, %80 : (tensor<?x6xi32>, tensor<?x6xi32>) -> tensor<?x6xi32>
-    %84 = tosa.add %83, %81 : (tensor<?x6xi32>, tensor<?x6xi32>) -> tensor<?x6xi32>
-    %85 = tosa.add %84, %82 : (tensor<?x6xi32>, tensor<?x6xi32>) -> tensor<?x6xi32>
-    %86 = tosa.arithmetic_right_shift %85, %6 {round = true} : (tensor<?x6xi32>, tensor<1x1xi32>) -> tensor<?x6xi32>
-    %87 = tosa.reduce_sum %86 {axis = 1 : i32} : (tensor<?x6xi32>) -> tensor<?x1xi32>
-    %88 = tosa.clz %87 : (tensor<?x1xi32>) -> tensor<?x1xi32>
-    %89 = tosa.sub %88, %8 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %90 = tosa.logical_left_shift %87, %89 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %91 = tosa.mul %90, %2, %1 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %92 = tosa.add %91, %3 : (tensor<?x1xi32>, tensor<1x1xi32>) -> tensor<?x1xi32>
-    %93 = tosa.mul %92, %90, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %94 = tosa.sub %4, %93 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %95 = tosa.mul %92, %94, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %96 = tosa.mul %95, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %97 = tosa.add %92, %96 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %98 = tosa.mul %97, %90, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %99 = tosa.sub %4, %98 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %100 = tosa.mul %97, %99, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %101 = tosa.mul %100, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %102 = tosa.add %97, %101 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %103 = tosa.mul %102, %90, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %104 = tosa.sub %4, %103 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %105 = tosa.mul %102, %104, %1 : (tensor<?x1xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %106 = tosa.mul %105, %5, %48 : (tensor<?x1xi32>, tensor<1x1xi32>, tensor<1xi8>) -> tensor<?x1xi32>
-    %107 = tosa.add %102, %106 : (tensor<?x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %108 = tosa.mul %85, %107, %17 : (tensor<?x6xi32>, tensor<?x1xi32>, tensor<1xi8>) -> tensor<?x6xi32>
-    %109 = tosa.sub %0, %88 : (tensor<1x1xi32>, tensor<?x1xi32>) -> tensor<?x1xi32>
-    %110 = tosa.arithmetic_right_shift %108, %109 {round = true} : (tensor<?x6xi32>, tensor<?x1xi32>) -> tensor<?x6xi32>
-    %111 = tosa.rescale %110, %18, %17, %44, %43 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<?x6xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x6xi8>
-    return %111 : tensor<?x6xi8>
-  }
-}
diff --git a/tests/gold/test_python_api/kws_micronet_s.mlir b/tests/gold/test_python_api/kws_micronet_s.mlir
deleted file mode 100644
index f9cf330..0000000
--- a/tests/gold/test_python_api/kws_micronet_s.mlir
+++ /dev/null
@@ -1,103 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<1x49x10x1xi8>) -> tensor<1x12xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
-    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %3 = "tosa.const"() <{values = dense<41> : tensor<12xi8>}> : () -> tensor<12xi8>
-    %4 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi32>}> : () -> tensor<12xi32>
-    %5 = "tosa.const"() <{values = dense<-49> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %6 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12xi32>}> : () -> tensor<12xi32>
-    %7 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<12x1x1x196xi8>}> : () -> tensor<12x1x1x196xi8>
-    %8 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<196xi8>}> : () -> tensor<196xi8>
-    %9 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<196xi32>}> : () -> tensor<196xi32>
-    %10 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<196xi32>}> : () -> tensor<196xi32>
-    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<196x1x1x84xi8>}> : () -> tensor<196x1x1x84xi8>
-    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
-    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x84xi8>}> : () -> tensor<1x3x3x84xi8>
-    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
-    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84x1x1x84xi8>}> : () -> tensor<84x1x1x84xi8>
-    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
-    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x84xi8>}> : () -> tensor<1x3x3x84xi8>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84x1x1x84xi8>}> : () -> tensor<84x1x1x84xi8>
-    %28 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
-    %29 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x84xi8>}> : () -> tensor<1x3x3x84xi8>
-    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
-    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84x1x1x112xi8>}> : () -> tensor<84x1x1x112xi8>
-    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi8>}> : () -> tensor<112xi8>
-    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x112xi8>}> : () -> tensor<1x3x3x112xi8>
-    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi8>}> : () -> tensor<112xi8>
-    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112xi32>}> : () -> tensor<112xi32>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<112x1x1x84xi8>}> : () -> tensor<112x1x1x84xi8>
-    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
-    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x84xi8>}> : () -> tensor<1x3x3x84xi8>
-    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi8>}> : () -> tensor<84xi8>
-    %49 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %50 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %51 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84x10x4x1xi8>}> : () -> tensor<84x10x4x1xi8>
-    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<84xi32>}> : () -> tensor<84xi32>
-    %54 = "tosa.const"() <{values = dense<-5> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %55 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %56 = tosa.conv2d %arg0, %52, %53, %54, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 4, 5, 1, 2>, stride = array<i64: 1, 1>} : (tensor<1x49x10x1xi8>, tensor<84x10x4x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x49x10x84xi32>
-    %57 = tosa.rescale %56, %49, %48, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x49x10x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x49x10x84xi8>
-    %58 = tosa.clamp %57 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x49x10x84xi8>) -> tensor<1x49x10x84xi8>
-    %59 = tosa.reshape %47, %1 : (tensor<1x3x3x84xi8>, !tosa.shape<4>) -> tensor<3x3x84x1xi8>
-    %60 = tosa.depthwise_conv2d %58, %59, %46, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x49x10x84xi8>, tensor<3x3x84x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
-    %61 = tosa.rescale %60, %45, %44, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
-    %62 = tosa.clamp %61 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
-    %63 = tosa.conv2d %62, %43, %42, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<112x1x1x84xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x112xi32>
-    %64 = tosa.rescale %63, %41, %40, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x112xi8>
-    %65 = tosa.clamp %64 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x112xi8>) -> tensor<1x25x5x112xi8>
-    %66 = tosa.reshape %39, %0 : (tensor<1x3x3x112xi8>, !tosa.shape<4>) -> tensor<3x3x112x1xi8>
-    %67 = tosa.depthwise_conv2d %65, %66, %38, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x25x5x112xi8>, tensor<3x3x112x1xi8>, tensor<112xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x112xi32>
-    %68 = tosa.rescale %67, %37, %36, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x112xi32>, tensor<112xi32>, tensor<112xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x112xi8>
-    %69 = tosa.clamp %68 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x112xi8>) -> tensor<1x25x5x112xi8>
-    %70 = tosa.conv2d %69, %35, %34, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x112xi8>, tensor<84x1x1x112xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
-    %71 = tosa.rescale %70, %33, %32, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
-    %72 = tosa.clamp %71 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
-    %73 = tosa.reshape %31, %1 : (tensor<1x3x3x84xi8>, !tosa.shape<4>) -> tensor<3x3x84x1xi8>
-    %74 = tosa.depthwise_conv2d %72, %73, %30, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<3x3x84x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
-    %75 = tosa.rescale %74, %29, %28, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
-    %76 = tosa.clamp %75 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
-    %77 = tosa.conv2d %76, %27, %26, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<84x1x1x84xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
-    %78 = tosa.rescale %77, %25, %24, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
-    %79 = tosa.clamp %78 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
-    %80 = tosa.reshape %23, %1 : (tensor<1x3x3x84xi8>, !tosa.shape<4>) -> tensor<3x3x84x1xi8>
-    %81 = tosa.depthwise_conv2d %79, %80, %22, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<3x3x84x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
-    %82 = tosa.rescale %81, %21, %20, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
-    %83 = tosa.clamp %82 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
-    %84 = tosa.conv2d %83, %19, %18, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<84x1x1x84xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
-    %85 = tosa.rescale %84, %17, %16, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
-    %86 = tosa.clamp %85 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
-    %87 = tosa.reshape %15, %1 : (tensor<1x3x3x84xi8>, !tosa.shape<4>) -> tensor<3x3x84x1xi8>
-    %88 = tosa.depthwise_conv2d %86, %87, %14, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<3x3x84x1xi8>, tensor<84xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x84xi32>
-    %89 = tosa.rescale %88, %13, %12, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x84xi32>, tensor<84xi32>, tensor<84xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x84xi8>
-    %90 = tosa.clamp %89 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x84xi8>) -> tensor<1x25x5x84xi8>
-    %91 = tosa.conv2d %90, %11, %10, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x84xi8>, tensor<196x1x1x84xi8>, tensor<196xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x25x5x196xi32>
-    %92 = tosa.rescale %91, %9, %8, %51, %50 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x25x5x196xi32>, tensor<196xi32>, tensor<196xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x25x5x196xi8>
-    %93 = tosa.clamp %92 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x25x5x196xi8>) -> tensor<1x25x5x196xi8>
-    %94 = tosa.avg_pool2d %93, %55, %55 {acc_type = i32, kernel = array<i64: 25, 5>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x25x5x196xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x196xi8>
-    %95 = tosa.conv2d %94, %7, %6, %50, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x196xi8>, tensor<12x1x1x196xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x12xi32>
-    %96 = tosa.rescale %95, %4, %3, %51, %5 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x12xi32>, tensor<12xi32>, tensor<12xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x12xi8>
-    %97 = tosa.reshape %96, %2 : (tensor<1x1x1x12xi8>, !tosa.shape<2>) -> tensor<1x12xi8>
-    return %97 : tensor<1x12xi8>
-  }
-}
diff --git a/tests/gold/test_python_api/mobilenet_v2_1.0_224_quantized_1_default_1.mlir b/tests/gold/test_python_api/mobilenet_v2_1.0_224_quantized_1_default_1.mlir
deleted file mode 100644
index 4db4c11..0000000
--- a/tests/gold/test_python_api/mobilenet_v2_1.0_224_quantized_1_default_1.mlir
+++ /dev/null
@@ -1,427 +0,0 @@
-module attributes {tfl.description = "TOCO Converted.", tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<1x224x224x3xui8>) -> tensor<1x1001xui8> attributes {tf.entry_function = {inputs = "input", outputs = "output"}} {
-    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %5 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %6 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %7 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %8 = "tosa.const"() <{values = dense<42> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %9 = "tosa.const"() <{values = dense<1769517290> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %10 = "tosa.const"() <{values = dense<-15> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1001xi32>}> : () -> tensor<1001xi32>
-    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1001x1x1x1280xi8>}> : () -> tensor<1001x1x1x1280xi8>
-    %13 = "tosa.const"() <{values = dense<1764866200> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1280xi32>}> : () -> tensor<1280xi32>
-    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1280x1x1x320xi8>}> : () -> tensor<1280x1x1x320xi8>
-    %16 = "tosa.const"() <{values = dense<1771764546> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<320xi32>}> : () -> tensor<320xi32>
-    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<320x1x1x960xi8>}> : () -> tensor<320x1x1x960xi8>
-    %19 = "tosa.const"() <{values = dense<1413581440> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %20 = "tosa.const"() <{values = dense<73> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
-    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x960xi8>}> : () -> tensor<1x3x3x960xi8>
-    %23 = "tosa.const"() <{values = dense<1255718954> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960x1x1x160xi8>}> : () -> tensor<960x1x1x160xi8>
-    %26 = "tosa.const"() <{values = dense<1733986385> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %27 = "tosa.const"() <{values = dense<1908224859> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %28 = "tosa.const"() <{values = dense<38> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %29 = "tosa.const"() <{values = dense<1409905126> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160xi32>}> : () -> tensor<160xi32>
-    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160x1x1x960xi8>}> : () -> tensor<160x1x1x960xi8>
-    %32 = "tosa.const"() <{values = dense<1471261696> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %33 = "tosa.const"() <{values = dense<-26> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %34 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
-    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x960xi8>}> : () -> tensor<1x3x3x960xi8>
-    %36 = "tosa.const"() <{values = dense<1403672173> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960x1x1x160xi8>}> : () -> tensor<960x1x1x160xi8>
-    %39 = "tosa.const"() <{values = dense<1886271458> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %40 = "tosa.const"() <{values = dense<1629649814> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %41 = "tosa.const"() <{values = dense<2034086883> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160xi32>}> : () -> tensor<160xi32>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160x1x1x960xi8>}> : () -> tensor<160x1x1x960xi8>
-    %44 = "tosa.const"() <{values = dense<1431685120> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
-    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x960xi8>}> : () -> tensor<1x3x3x960xi8>
-    %47 = "tosa.const"() <{values = dense<1563714083> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960xi32>}> : () -> tensor<960xi32>
-    %49 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<960x1x1x160xi8>}> : () -> tensor<960x1x1x160xi8>
-    %50 = "tosa.const"() <{values = dense<1846357403> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %51 = "tosa.const"() <{values = dense<4> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160xi32>}> : () -> tensor<160xi32>
-    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<160x1x1x576xi8>}> : () -> tensor<160x1x1x576xi8>
-    %54 = "tosa.const"() <{values = dense<2097034112> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %55 = "tosa.const"() <{values = dense<-36> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %56 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
-    %57 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x576xi8>}> : () -> tensor<1x3x3x576xi8>
-    %58 = "tosa.const"() <{values = dense<1885290042> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
-    %60 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576x1x1x96xi8>}> : () -> tensor<576x1x1x96xi8>
-    %61 = "tosa.const"() <{values = dense<1713159654> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %62 = "tosa.const"() <{values = dense<2031709950> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %63 = "tosa.const"() <{values = dense<1666054802> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %64 = "tosa.const"() <{values = dense<26> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %65 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %66 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x576xi8>}> : () -> tensor<96x1x1x576xi8>
-    %67 = "tosa.const"() <{values = dense<1279693056> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %68 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %69 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
-    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x576xi8>}> : () -> tensor<1x3x3x576xi8>
-    %71 = "tosa.const"() <{values = dense<1878841398> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %72 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
-    %73 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576x1x1x96xi8>}> : () -> tensor<576x1x1x96xi8>
-    %74 = "tosa.const"() <{values = dense<2079856357> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %75 = "tosa.const"() <{values = dense<1552338772> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %76 = "tosa.const"() <{values = dense<1758291557> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %77 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %78 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x576xi8>}> : () -> tensor<96x1x1x576xi8>
-    %79 = "tosa.const"() <{values = dense<1216473984> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %80 = "tosa.const"() <{values = dense<-62> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %81 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
-    %82 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x576xi8>}> : () -> tensor<1x3x3x576xi8>
-    %83 = "tosa.const"() <{values = dense<1625450438> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %84 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576xi32>}> : () -> tensor<576xi32>
-    %85 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<576x1x1x96xi8>}> : () -> tensor<576x1x1x96xi8>
-    %86 = "tosa.const"() <{values = dense<1127574829> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %87 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %88 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x384xi8>}> : () -> tensor<96x1x1x384xi8>
-    %89 = "tosa.const"() <{values = dense<2137714944> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %90 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
-    %91 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x384xi8>}> : () -> tensor<1x3x3x384xi8>
-    %92 = "tosa.const"() <{values = dense<2095071944> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %93 = "tosa.const"() <{values = dense<3> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %94 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
-    %95 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384x1x1x64xi8>}> : () -> tensor<384x1x1x64xi8>
-    %96 = "tosa.const"() <{values = dense<-8> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %97 = "tosa.const"() <{values = dense<1946727039> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %98 = "tosa.const"() <{values = dense<1680680778> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %99 = "tosa.const"() <{values = dense<1619097955> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %100 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
-    %101 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x384xi8>}> : () -> tensor<64x1x1x384xi8>
-    %102 = "tosa.const"() <{values = dense<1401151616> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %103 = "tosa.const"() <{values = dense<27> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %104 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
-    %105 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x384xi8>}> : () -> tensor<1x3x3x384xi8>
-    %106 = "tosa.const"() <{values = dense<1601894870> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %107 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
-    %108 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384x1x1x64xi8>}> : () -> tensor<384x1x1x64xi8>
-    %109 = "tosa.const"() <{values = dense<2033798859> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %110 = "tosa.const"() <{values = dense<1671053707> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %111 = "tosa.const"() <{values = dense<1133754932> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %112 = "tosa.const"() <{values = dense<-5> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %113 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
-    %114 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x384xi8>}> : () -> tensor<64x1x1x384xi8>
-    %115 = "tosa.const"() <{values = dense<1800720000> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %116 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
-    %117 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x384xi8>}> : () -> tensor<1x3x3x384xi8>
-    %118 = "tosa.const"() <{values = dense<1624188629> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %119 = "tosa.const"() <{values = dense<6> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %120 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
-    %121 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384x1x1x64xi8>}> : () -> tensor<384x1x1x64xi8>
-    %122 = "tosa.const"() <{values = dense<2105410924> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %123 = "tosa.const"() <{values = dense<1999568813> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %124 = "tosa.const"() <{values = dense<1257485775> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %125 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
-    %126 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x384xi8>}> : () -> tensor<64x1x1x384xi8>
-    %127 = "tosa.const"() <{values = dense<2093439744> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %128 = "tosa.const"() <{values = dense<-18> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %129 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
-    %130 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x384xi8>}> : () -> tensor<1x3x3x384xi8>
-    %131 = "tosa.const"() <{values = dense<1682901674> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %132 = "tosa.const"() <{values = dense<-3> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %133 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384xi32>}> : () -> tensor<384xi32>
-    %134 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<384x1x1x64xi8>}> : () -> tensor<384x1x1x64xi8>
-    %135 = "tosa.const"() <{values = dense<2037336008> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %136 = "tosa.const"() <{values = dense<-2> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %137 = "tosa.const"() <{values = dense<19> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %138 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
-    %139 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x192xi8>}> : () -> tensor<64x1x1x192xi8>
-    %140 = "tosa.const"() <{values = dense<1386468480> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %141 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %142 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x192xi8>}> : () -> tensor<1x3x3x192xi8>
-    %143 = "tosa.const"() <{values = dense<1857304257> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %144 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %145 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192x1x1x32xi8>}> : () -> tensor<192x1x1x32xi8>
-    %146 = "tosa.const"() <{values = dense<1681202601> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %147 = "tosa.const"() <{values = dense<2131432016> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %148 = "tosa.const"() <{values = dense<1836050801> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %149 = "tosa.const"() <{values = dense<-4> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %150 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %151 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x1x1x192xi8>}> : () -> tensor<32x1x1x192xi8>
-    %152 = "tosa.const"() <{values = dense<1358890624> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %153 = "tosa.const"() <{values = dense<-33> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %154 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %155 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x192xi8>}> : () -> tensor<1x3x3x192xi8>
-    %156 = "tosa.const"() <{values = dense<2070508920> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %157 = "tosa.const"() <{values = dense<7> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %158 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %159 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192x1x1x32xi8>}> : () -> tensor<192x1x1x32xi8>
-    %160 = "tosa.const"() <{values = dense<2> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %161 = "tosa.const"() <{values = dense<1884945131> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %162 = "tosa.const"() <{values = dense<2057234100> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %163 = "tosa.const"() <{values = dense<1081754833> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %164 = "tosa.const"() <{values = dense<-7> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %165 = "tosa.const"() <{values = dense<18> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %166 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %167 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x1x1x192xi8>}> : () -> tensor<32x1x1x192xi8>
-    %168 = "tosa.const"() <{values = dense<34> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %169 = "tosa.const"() <{values = dense<1120997760> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %170 = "tosa.const"() <{values = dense<-10> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %171 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %172 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x192xi8>}> : () -> tensor<1x3x3x192xi8>
-    %173 = "tosa.const"() <{values = dense<1227338673> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %174 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192xi32>}> : () -> tensor<192xi32>
-    %175 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<192x1x1x32xi8>}> : () -> tensor<192x1x1x32xi8>
-    %176 = "tosa.const"() <{values = dense<1995624654> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %177 = "tosa.const"() <{values = dense<-17> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %178 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %179 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x1x1x144xi8>}> : () -> tensor<32x1x1x144xi8>
-    %180 = "tosa.const"() <{values = dense<1182172288> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %181 = "tosa.const"() <{values = dense<15> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %182 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %183 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x144xi8>}> : () -> tensor<1x3x3x144xi8>
-    %184 = "tosa.const"() <{values = dense<1892639773> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %185 = "tosa.const"() <{values = dense<-24> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %186 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %187 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x1x1x24xi8>}> : () -> tensor<144x1x1x24xi8>
-    %188 = "tosa.const"() <{values = dense<5> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %189 = "tosa.const"() <{values = dense<50> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %190 = "tosa.const"() <{values = dense<1995052007> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %191 = "tosa.const"() <{values = dense<1475367762> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %192 = "tosa.const"() <{values = dense<10> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %193 = "tosa.const"() <{values = dense<11> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %194 = "tosa.const"() <{values = dense<1766066391> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %195 = "tosa.const"() <{values = dense<8> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %196 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %197 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x144xi8>}> : () -> tensor<24x1x1x144xi8>
-    %198 = "tosa.const"() <{values = dense<1458735232> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %199 = "tosa.const"() <{values = dense<-76> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %200 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %201 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x144xi8>}> : () -> tensor<1x3x3x144xi8>
-    %202 = "tosa.const"() <{values = dense<35> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %203 = "tosa.const"() <{values = dense<1472565610> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %204 = "tosa.const"() <{values = dense<16> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %205 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144xi32>}> : () -> tensor<144xi32>
-    %206 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<144x1x1x24xi8>}> : () -> tensor<144x1x1x24xi8>
-    %207 = "tosa.const"() <{values = dense<40> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %208 = "tosa.const"() <{values = dense<2113598676> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %209 = "tosa.const"() <{values = dense<-9> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %210 = "tosa.const"() <{values = dense<28> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %211 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %212 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x96xi8>}> : () -> tensor<24x1x1x96xi8>
-    %213 = "tosa.const"() <{values = dense<36> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %214 = "tosa.const"() <{values = dense<1440987008> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %215 = "tosa.const"() <{values = dense<-19> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %216 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %217 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
-    %218 = "tosa.const"() <{values = dense<33> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %219 = "tosa.const"() <{values = dense<1262668951> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %220 = "tosa.const"() <{values = dense<-1> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %221 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %222 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x16xi8>}> : () -> tensor<96x1x1x16xi8>
-    %223 = "tosa.const"() <{values = dense<39> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %224 = "tosa.const"() <{values = dense<1363945730> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %225 = "tosa.const"() <{values = dense<1> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %226 = "tosa.const"() <{values = dense<12> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %227 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %228 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x32xi8>}> : () -> tensor<16x1x1x32xi8>
-    %229 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %230 = "tosa.const"() <{values = dense<1476161024> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %231 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %232 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x32xi8>}> : () -> tensor<1x3x3x32xi8>
-    %233 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %234 = "tosa.const"() <{values = dense<1550200454> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %235 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %236 = "tosa.const"() <{values = dense<-6> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %237 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %238 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x3x3x3xi8>}> : () -> tensor<32x3x3x3xi8>
-    %239 = "tosa.const"() <{values = dense<-70> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %240 = "tosa.const"() <{values = dense<58> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %241 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %242 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %243 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %244 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %245 = tosa.rescale %arg0, %241, %242, %243, %244 {input_unsigned = true, output_unsigned = false, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x224x224x3xui8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x224x224x3xi8>
-    %246 = tosa.conv2d %245, %238, %237, %244, %236 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x224x224x3xi8>, tensor<32x3x3x3xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x32xi32>
-    %247 = tosa.rescale %246, %234, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x32xi8>
-    %248 = tosa.reshape %232, %6 : (tensor<1x3x3x32xi8>, !tosa.shape<4>) -> tensor<3x3x32x1xi8>
-    %249 = tosa.depthwise_conv2d %247, %248, %231, %243, %233 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x112x112x32xi8>, tensor<3x3x32x1xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x32xi32>
-    %250 = tosa.rescale %249, %230, %229, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x32xi8>
-    %251 = tosa.conv2d %250, %228, %227, %243, %226 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x112x112x32xi8>, tensor<16x1x1x32xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x16xi32>
-    %252 = tosa.rescale %251, %224, %223, %235, %225 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x16xi8>
-    %253 = tosa.conv2d %252, %222, %221, %225, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x112x112x16xi8>, tensor<96x1x1x16xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x112x112x96xi32>
-    %254 = tosa.rescale %253, %219, %218, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x112x112x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x112x112x96xi8>
-    %255 = tosa.reshape %217, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
-    %256 = tosa.depthwise_conv2d %254, %255, %216, %243, %215 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x112x112x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x96xi32>
-    %257 = tosa.rescale %256, %214, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x96xi8>
-    %258 = tosa.conv2d %257, %212, %211, %243, %210 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x96xi8>, tensor<24x1x1x96xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x24xi32>
-    %259 = tosa.rescale %258, %208, %207, %235, %209 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
-    %260 = tosa.conv2d %259, %206, %205, %209, %204 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x24xi8>, tensor<144x1x1x24xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
-    %261 = tosa.rescale %260, %203, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
-    %262 = tosa.reshape %201, %4 : (tensor<1x3x3x144xi8>, !tosa.shape<4>) -> tensor<3x3x144x1xi8>
-    %263 = tosa.depthwise_conv2d %261, %262, %200, %243, %199 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x56x56x144xi8>, tensor<3x3x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
-    %264 = tosa.rescale %263, %198, %218, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
-    %265 = tosa.conv2d %264, %197, %196, %243, %236 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x144xi8>, tensor<24x1x1x144xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x24xi32>
-    %266 = tosa.rescale %265, %194, %207, %235, %195 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
-    %267 = tosa.rescale %266, %241, %193, %195, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
-    %268 = tosa.rescale %259, %241, %192, %209, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
-    %269 = tosa.rescale %268, %191, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x56x56x24xi32>
-    %270 = tosa.add %267, %269 : (tensor<1x56x56x24xi32>, tensor<1x56x56x24xi32>) -> tensor<1x56x56x24xi32>
-    %271 = tosa.rescale %270, %190, %189, %235, %188 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x24xi8>
-    %272 = tosa.conv2d %271, %187, %186, %188, %185 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x56x56x24xi8>, tensor<144x1x1x24xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x56x56x144xi32>
-    %273 = tosa.rescale %272, %184, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x56x56x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x56x56x144xi8>
-    %274 = tosa.reshape %183, %4 : (tensor<1x3x3x144xi8>, !tosa.shape<4>) -> tensor<3x3x144x1xi8>
-    %275 = tosa.depthwise_conv2d %273, %274, %182, %243, %181 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x56x56x144xi8>, tensor<3x3x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x144xi32>
-    %276 = tosa.rescale %275, %180, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x144xi8>
-    %277 = tosa.conv2d %276, %179, %178, %243, %177 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x144xi8>, tensor<32x1x1x144xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x32xi32>
-    %278 = tosa.rescale %277, %176, %207, %235, %220 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
-    %279 = tosa.conv2d %278, %175, %174, %220, %244 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x32xi8>, tensor<192x1x1x32xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
-    %280 = tosa.rescale %279, %173, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
-    %281 = tosa.reshape %172, %3 : (tensor<1x3x3x192xi8>, !tosa.shape<4>) -> tensor<3x3x192x1xi8>
-    %282 = tosa.depthwise_conv2d %280, %281, %171, %243, %170 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x28x28x192xi8>, tensor<3x3x192x1xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
-    %283 = tosa.rescale %282, %169, %168, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
-    %284 = tosa.conv2d %283, %167, %166, %243, %165 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x192xi8>, tensor<32x1x1x192xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x32xi32>
-    %285 = tosa.rescale %284, %163, %223, %235, %164 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
-    %286 = tosa.rescale %285, %241, %193, %164, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
-    %287 = tosa.rescale %278, %241, %192, %220, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
-    %288 = tosa.rescale %287, %162, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
-    %289 = tosa.add %286, %288 : (tensor<1x28x28x32xi32>, tensor<1x28x28x32xi32>) -> tensor<1x28x28x32xi32>
-    %290 = tosa.rescale %289, %161, %189, %235, %160 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
-    %291 = tosa.conv2d %290, %159, %158, %160, %157 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x32xi8>, tensor<192x1x1x32xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
-    %292 = tosa.rescale %291, %156, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
-    %293 = tosa.reshape %155, %3 : (tensor<1x3x3x192xi8>, !tosa.shape<4>) -> tensor<3x3x192x1xi8>
-    %294 = tosa.depthwise_conv2d %292, %293, %154, %243, %153 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x28x28x192xi8>, tensor<3x3x192x1xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
-    %295 = tosa.rescale %294, %152, %168, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
-    %296 = tosa.conv2d %295, %151, %150, %243, %244 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x192xi8>, tensor<32x1x1x192xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x32xi32>
-    %297 = tosa.rescale %296, %148, %207, %235, %149 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
-    %298 = tosa.rescale %297, %241, %192, %149, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
-    %299 = tosa.rescale %298, %147, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
-    %300 = tosa.rescale %290, %241, %193, %160, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x28x28x32xi32>
-    %301 = tosa.add %299, %300 : (tensor<1x28x28x32xi32>, tensor<1x28x28x32xi32>) -> tensor<1x28x28x32xi32>
-    %302 = tosa.rescale %301, %146, %189, %235, %149 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x32xi8>
-    %303 = tosa.conv2d %302, %145, %144, %149, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x28x28x32xi8>, tensor<192x1x1x32xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x28x28x192xi32>
-    %304 = tosa.rescale %303, %143, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x28x28x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x28x28x192xi8>
-    %305 = tosa.reshape %142, %3 : (tensor<1x3x3x192xi8>, !tosa.shape<4>) -> tensor<3x3x192x1xi8>
-    %306 = tosa.depthwise_conv2d %304, %305, %141, %243, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x28x28x192xi8>, tensor<3x3x192x1xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x192xi32>
-    %307 = tosa.rescale %306, %140, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x192xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x192xi8>
-    %308 = tosa.conv2d %307, %139, %138, %243, %137 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x192xi8>, tensor<64x1x1x192xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x64xi32>
-    %309 = tosa.rescale %308, %135, %207, %235, %136 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
-    %310 = tosa.conv2d %309, %134, %133, %136, %132 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x64xi8>, tensor<384x1x1x64xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
-    %311 = tosa.rescale %310, %131, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
-    %312 = tosa.reshape %130, %2 : (tensor<1x3x3x384xi8>, !tosa.shape<4>) -> tensor<3x3x384x1xi8>
-    %313 = tosa.depthwise_conv2d %311, %312, %129, %243, %128 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<3x3x384x1xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
-    %314 = tosa.rescale %313, %127, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
-    %315 = tosa.conv2d %314, %126, %125, %243, %149 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<64x1x1x384xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x64xi32>
-    %316 = tosa.rescale %315, %124, %223, %235, %215 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
-    %317 = tosa.rescale %316, %241, %192, %215, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %318 = tosa.rescale %317, %123, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %319 = tosa.rescale %309, %241, %193, %136, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %320 = tosa.add %318, %319 : (tensor<1x14x14x64xi32>, tensor<1x14x14x64xi32>) -> tensor<1x14x14x64xi32>
-    %321 = tosa.rescale %320, %122, %189, %235, %236 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
-    %322 = tosa.conv2d %321, %121, %120, %236, %119 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x64xi8>, tensor<384x1x1x64xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
-    %323 = tosa.rescale %322, %118, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
-    %324 = tosa.reshape %117, %2 : (tensor<1x3x3x384xi8>, !tosa.shape<4>) -> tensor<3x3x384x1xi8>
-    %325 = tosa.depthwise_conv2d %323, %324, %116, %243, %188 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<3x3x384x1xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
-    %326 = tosa.rescale %325, %115, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
-    %327 = tosa.conv2d %326, %114, %113, %243, %132 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<64x1x1x384xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x64xi32>
-    %328 = tosa.rescale %327, %111, %223, %235, %112 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
-    %329 = tosa.rescale %328, %241, %192, %112, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %330 = tosa.rescale %329, %110, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %331 = tosa.rescale %321, %241, %193, %236, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %332 = tosa.add %330, %331 : (tensor<1x14x14x64xi32>, tensor<1x14x14x64xi32>) -> tensor<1x14x14x64xi32>
-    %333 = tosa.rescale %332, %109, %189, %235, %149 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
-    %334 = tosa.conv2d %333, %108, %107, %149, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x64xi8>, tensor<384x1x1x64xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
-    %335 = tosa.rescale %334, %106, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
-    %336 = tosa.reshape %105, %2 : (tensor<1x3x3x384xi8>, !tosa.shape<4>) -> tensor<3x3x384x1xi8>
-    %337 = tosa.depthwise_conv2d %335, %336, %104, %243, %103 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<3x3x384x1xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
-    %338 = tosa.rescale %337, %102, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
-    %339 = tosa.conv2d %338, %101, %100, %243, %204 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<64x1x1x384xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x64xi32>
-    %340 = tosa.rescale %339, %99, %223, %235, %236 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
-    %341 = tosa.rescale %340, %241, %192, %236, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %342 = tosa.rescale %341, %98, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %343 = tosa.rescale %333, %241, %193, %149, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x64xi32>
-    %344 = tosa.add %342, %343 : (tensor<1x14x14x64xi32>, tensor<1x14x14x64xi32>) -> tensor<1x14x14x64xi32>
-    %345 = tosa.rescale %344, %97, %189, %235, %96 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x64xi8>
-    %346 = tosa.conv2d %345, %95, %94, %96, %93 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x64xi8>, tensor<384x1x1x64xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
-    %347 = tosa.rescale %346, %92, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
-    %348 = tosa.reshape %91, %2 : (tensor<1x3x3x384xi8>, !tosa.shape<4>) -> tensor<3x3x384x1xi8>
-    %349 = tosa.depthwise_conv2d %347, %348, %90, %243, %181 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<3x3x384x1xi8>, tensor<384xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x384xi32>
-    %350 = tosa.rescale %349, %89, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x384xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x384xi8>
-    %351 = tosa.conv2d %350, %88, %87, %243, %225 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x384xi8>, tensor<96x1x1x384xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x96xi32>
-    %352 = tosa.rescale %351, %86, %207, %235, %225 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
-    %353 = tosa.conv2d %352, %85, %84, %225, %119 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x96xi8>, tensor<576x1x1x96xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
-    %354 = tosa.rescale %353, %83, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
-    %355 = tosa.reshape %82, %1 : (tensor<1x3x3x576xi8>, !tosa.shape<4>) -> tensor<3x3x576x1xi8>
-    %356 = tosa.depthwise_conv2d %354, %355, %81, %243, %80 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x576xi8>, tensor<3x3x576x1xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
-    %357 = tosa.rescale %356, %79, %168, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
-    %358 = tosa.conv2d %357, %78, %77, %243, %195 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x576xi8>, tensor<96x1x1x576xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x96xi32>
-    %359 = tosa.rescale %358, %76, %207, %235, %220 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
-    %360 = tosa.rescale %359, %241, %192, %220, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
-    %361 = tosa.rescale %360, %75, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
-    %362 = tosa.rescale %352, %241, %193, %225, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
-    %363 = tosa.add %361, %362 : (tensor<1x14x14x96xi32>, tensor<1x14x14x96xi32>) -> tensor<1x14x14x96xi32>
-    %364 = tosa.rescale %363, %74, %189, %235, %220 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
-    %365 = tosa.conv2d %364, %73, %72, %220, %192 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x96xi8>, tensor<576x1x1x96xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
-    %366 = tosa.rescale %365, %71, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
-    %367 = tosa.reshape %70, %1 : (tensor<1x3x3x576xi8>, !tosa.shape<4>) -> tensor<3x3x576x1xi8>
-    %368 = tosa.depthwise_conv2d %366, %367, %69, %243, %68 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x14x14x576xi8>, tensor<3x3x576x1xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
-    %369 = tosa.rescale %368, %67, %168, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
-    %370 = tosa.conv2d %369, %66, %65, %243, %64 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x576xi8>, tensor<96x1x1x576xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x96xi32>
-    %371 = tosa.rescale %370, %63, %223, %235, %220 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
-    %372 = tosa.rescale %371, %241, %193, %220, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
-    %373 = tosa.rescale %364, %241, %192, %220, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
-    %374 = tosa.rescale %373, %62, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x14x14x96xi32>
-    %375 = tosa.add %372, %374 : (tensor<1x14x14x96xi32>, tensor<1x14x14x96xi32>) -> tensor<1x14x14x96xi32>
-    %376 = tosa.rescale %375, %61, %189, %235, %136 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x96xi8>
-    %377 = tosa.conv2d %376, %60, %59, %136, %112 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x14x14x96xi8>, tensor<576x1x1x96xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x14x14x576xi32>
-    %378 = tosa.rescale %377, %58, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x14x14x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x14x14x576xi8>
-    %379 = tosa.reshape %57, %1 : (tensor<1x3x3x576xi8>, !tosa.shape<4>) -> tensor<3x3x576x1xi8>
-    %380 = tosa.depthwise_conv2d %378, %379, %56, %243, %55 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x14x14x576xi8>, tensor<3x3x576x1xi8>, tensor<576xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x576xi32>
-    %381 = tosa.rescale %380, %54, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x576xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x576xi8>
-    %382 = tosa.conv2d %381, %53, %52, %243, %226 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x576xi8>, tensor<160x1x1x576xi8>, tensor<160xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x160xi32>
-    %383 = tosa.rescale %382, %50, %207, %235, %51 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
-    %384 = tosa.conv2d %383, %49, %48, %51, %157 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x160xi8>, tensor<960x1x1x160xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
-    %385 = tosa.rescale %384, %47, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
-    %386 = tosa.reshape %46, %0 : (tensor<1x3x3x960xi8>, !tosa.shape<4>) -> tensor<3x3x960x1xi8>
-    %387 = tosa.depthwise_conv2d %385, %386, %45, %243, %137 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<3x3x960x1xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
-    %388 = tosa.rescale %387, %44, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
-    %389 = tosa.conv2d %388, %43, %42, %243, %193 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<160x1x1x960xi8>, tensor<160xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x160xi32>
-    %390 = tosa.rescale %389, %41, %207, %235, %225 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
-    %391 = tosa.rescale %390, %241, %192, %225, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
-    %392 = tosa.rescale %391, %40, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
-    %393 = tosa.rescale %383, %241, %193, %51, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
-    %394 = tosa.add %392, %393 : (tensor<1x7x7x160xi32>, tensor<1x7x7x160xi32>) -> tensor<1x7x7x160xi32>
-    %395 = tosa.rescale %394, %39, %189, %235, %119 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
-    %396 = tosa.conv2d %395, %38, %37, %119, %220 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x160xi8>, tensor<960x1x1x160xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
-    %397 = tosa.rescale %396, %36, %233, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
-    %398 = tosa.reshape %35, %0 : (tensor<1x3x3x960xi8>, !tosa.shape<4>) -> tensor<3x3x960x1xi8>
-    %399 = tosa.depthwise_conv2d %397, %398, %34, %243, %33 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<3x3x960x1xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
-    %400 = tosa.rescale %399, %32, %202, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
-    %401 = tosa.conv2d %400, %31, %30, %243, %93 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<160x1x1x960xi8>, tensor<160xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x160xi32>
-    %402 = tosa.rescale %401, %29, %28, %235, %188 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
-    %403 = tosa.rescale %402, %241, %193, %188, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
-    %404 = tosa.rescale %395, %241, %192, %119, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
-    %405 = tosa.rescale %404, %27, %229, %235, %235 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x7x7x160xi32>
-    %406 = tosa.add %403, %405 : (tensor<1x7x7x160xi32>, tensor<1x7x7x160xi32>) -> tensor<1x7x7x160xi32>
-    %407 = tosa.rescale %406, %26, %189, %235, %93 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x160xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x160xi8>
-    %408 = tosa.conv2d %407, %25, %24, %93, %157 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x160xi8>, tensor<960x1x1x160xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
-    %409 = tosa.rescale %408, %23, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
-    %410 = tosa.reshape %22, %0 : (tensor<1x3x3x960xi8>, !tosa.shape<4>) -> tensor<3x3x960x1xi8>
-    %411 = tosa.depthwise_conv2d %409, %410, %21, %243, %20 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<3x3x960x1xi8>, tensor<960xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x960xi32>
-    %412 = tosa.rescale %411, %19, %218, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x960xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x960xi8>
-    %413 = tosa.conv2d %412, %18, %17, %243, %177 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x960xi8>, tensor<320x1x1x960xi8>, tensor<320xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x320xi32>
-    %414 = tosa.rescale %413, %16, %207, %235, %160 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x320xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x320xi8>
-    %415 = tosa.conv2d %414, %15, %14, %160, %132 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x320xi8>, tensor<1280x1x1x320xi8>, tensor<1280xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x7x7x1280xi32>
-    %416 = tosa.rescale %415, %13, %213, %235, %243 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x7x7x1280xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x7x7x1280xi8>
-    %417 = tosa.avg_pool2d %416, %244, %244 {acc_type = i32, kernel = array<i64: 7, 7>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x1280xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x1280xi8>
-    %418 = tosa.conv2d %417, %12, %11, %243, %10 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x1280xi8>, tensor<1001x1x1x1280xi8>, tensor<1001xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x1001xi32>
-    %419 = tosa.rescale %418, %9, %8, %235, %239 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x1001xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x1001xi8>
-    %420 = tosa.reshape %419, %7 : (tensor<1x1x1x1001xi8>, !tosa.shape<2>) -> tensor<1x1001xi8>
-    %421 = tosa.rescale %420, %241, %242, %239, %240 {input_unsigned = false, output_unsigned = true, per_channel = false, rounding_mode = "SINGLE_ROUND", scale32 = true} : (tensor<1x1001xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1001xui8>
-    return %421 : tensor<1x1001xui8>
-  }
-}
diff --git a/tests/gold/test_python_api/ssd_mobilenet_v3_int8.mlir b/tests/gold/test_python_api/ssd_mobilenet_v3_int8.mlir
deleted file mode 100644
index e230308..0000000
--- a/tests/gold/test_python_api/ssd_mobilenet_v3_int8.mlir
+++ /dev/null
@@ -1,993 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.15.0\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<1x320x320x3xi8>) -> (tensor<1x2034x91xi8>, tensor<1x2034x4xi8>) attributes {tf.entry_function = {inputs = "normalized_input_image_tensor", outputs = "raw_outputs/class_predictions,raw_outputs/box_encodings"}} {
-    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %5 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %6 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %7 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %8 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %9 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %10 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %11 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %12 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %14 = "tosa.const"() <{values = dense<1862935214> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %15 = "tosa.const"() <{values = dense<1553028373> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %16 = "tosa.const"() <{values = dense<1582603170> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %17 = "tosa.const"() <{values = dense<1187055602> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %18 = "tosa.const"() <{values = dense<1118715085> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %19 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<3xindex>} : () -> !tosa.shape<3>
-    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<546xi8>}> : () -> tensor<546xi8>
-    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<546xi32>}> : () -> tensor<546xi32>
-    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<546xi32>}> : () -> tensor<546xi32>
-    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<546x1x1x128xi8>}> : () -> tensor<546x1x1x128xi8>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x128xi8>}> : () -> tensor<1x3x3x128xi8>
-    %28 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<3xindex>} : () -> !tosa.shape<3>
-    %29 = "tosa.const"() <{values = dense<1835346993> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %30 = "tosa.const"() <{values = dense<1415988625> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %31 = "tosa.const"() <{values = dense<1183143852> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %32 = "tosa.const"() <{values = dense<1124158657> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %33 = "tosa.const"() <{values = dense<1214666873> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %34 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
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-    %395 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %396 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240x1x1x64xi8>}> : () -> tensor<240x1x1x64xi8>
-    %397 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %398 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
-    %399 = "tosa.const"() <{values = dense<-122> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %400 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
-    %401 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x1x1x240xi8>}> : () -> tensor<64x1x1x240xi8>
-    %402 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %403 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
-    %404 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %405 = "tosa.const"() <{values = dense<-119> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %406 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %407 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x240xi8>}> : () -> tensor<1x5x5x240xi8>
-    %408 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %409 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi8>}> : () -> tensor<240xi8>
-    %410 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %411 = "tosa.const"() <{values = dense<-5> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %412 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240xi32>}> : () -> tensor<240xi32>
-    %413 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<240x1x1x40xi8>}> : () -> tensor<240x1x1x40xi8>
-    %414 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi8>}> : () -> tensor<40xi8>
-    %415 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
-    %416 = "tosa.const"() <{values = dense<-12> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %417 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40xi32>}> : () -> tensor<40xi32>
-    %418 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<40x1x1x96xi8>}> : () -> tensor<40x1x1x96xi8>
-    %419 = "tosa.const"() <{values = dense<-110> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %420 = "tosa.const"() <{values = dense<36> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %421 = "tosa.const"() <{values = dense<1770674688> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %422 = "tosa.const"() <{values = dense<1982666603> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %423 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %424 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %425 = "tosa.const"() <{values = dense<-16> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %426 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %427 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x24xi8>}> : () -> tensor<96x1x1x24xi8>
-    %428 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
-    %429 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %430 = "tosa.const"() <{values = dense<-125> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %431 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %432 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x96xi8>}> : () -> tensor<24x1x1x96xi8>
-    %433 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %434 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %435 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %436 = "tosa.const"() <{values = dense<-11> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %437 = "tosa.const"() <{values = dense<-120> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %438 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %439 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x5x5x96xi8>}> : () -> tensor<1x5x5x96xi8>
-    %440 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %441 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %442 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %443 = "tosa.const"() <{values = dense<12> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %444 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %445 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x24xi8>}> : () -> tensor<96x1x1x24xi8>
-    %446 = "tosa.const"() <{values = dense<1> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %447 = "tosa.const"() <{values = dense<1085834602> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %448 = "tosa.const"() <{values = dense<1899624818> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %449 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
-    %450 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %451 = "tosa.const"() <{values = dense<14> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %452 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %453 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x88xi8>}> : () -> tensor<24x1x1x88xi8>
-    %454 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi8>}> : () -> tensor<88xi8>
-    %455 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi32>}> : () -> tensor<88xi32>
-    %456 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi32>}> : () -> tensor<88xi32>
-    %457 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x88xi8>}> : () -> tensor<1x3x3x88xi8>
-    %458 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi8>}> : () -> tensor<88xi8>
-    %459 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi32>}> : () -> tensor<88xi32>
-    %460 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88xi32>}> : () -> tensor<88xi32>
-    %461 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<88x1x1x24xi8>}> : () -> tensor<88x1x1x24xi8>
-    %462 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi8>}> : () -> tensor<24xi8>
-    %463 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %464 = "tosa.const"() <{values = dense<-3> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %465 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24xi32>}> : () -> tensor<24xi32>
-    %466 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<24x1x1x72xi8>}> : () -> tensor<24x1x1x72xi8>
-    %467 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi8>}> : () -> tensor<72xi8>
-    %468 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
-    %469 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
-    %470 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x72xi8>}> : () -> tensor<1x3x3x72xi8>
-    %471 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi8>}> : () -> tensor<72xi8>
-    %472 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
-    %473 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72xi32>}> : () -> tensor<72xi32>
-    %474 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<72x1x1x16xi8>}> : () -> tensor<72x1x1x16xi8>
-    %475 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
-    %476 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %477 = "tosa.const"() <{values = dense<-22> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %478 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %479 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x16xi8>}> : () -> tensor<16x1x1x16xi8>
-    %480 = "tosa.const"() <{values = dense<38> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %481 = "tosa.const"() <{values = dense<1082344576> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %482 = "tosa.const"() <{values = dense<37> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %483 = "tosa.const"() <{values = dense<1082196480> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %484 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %485 = "tosa.const"() <{values = dense<127> : tensor<i8>}> : () -> tensor<i8>
-    %486 = "tosa.const"() <{values = dense<127> : tensor<i8>}> : () -> tensor<i8>
-    %487 = "tosa.const"() <{values = dense<49> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %488 = "tosa.const"() <{values = dense<1077969129> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %489 = tosa.const_shape  {values = dense<1> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %490 = "tosa.const"() <{values = dense<11> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %491 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %492 = "tosa.const"() <{values = dense<1529543979> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %493 = "tosa.const"() <{values = dense<10> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %494 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %495 = "tosa.const"() <{values = dense<127> : tensor<i8>}> : () -> tensor<i8>
-    %496 = "tosa.const"() <{values = dense<127> : tensor<i8>}> : () -> tensor<i8>
-    %497 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
-    %498 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %499 = "tosa.const"() <{values = dense<-51> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %500 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %501 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x8xi8>}> : () -> tensor<16x1x1x8xi8>
-    %502 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi8>}> : () -> tensor<8xi8>
-    %503 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
-    %504 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
-    %505 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8x1x1x16xi8>}> : () -> tensor<8x1x1x16xi8>
-    %506 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
-    %507 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %508 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %509 = "tosa.const"() <{values = dense<-127> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %510 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %511 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x16xi8>}> : () -> tensor<1x3x3x16xi8>
-    %512 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %513 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
-    %514 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %515 = "tosa.const"() <{values = dense<-45> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %516 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %517 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x3x3x3xi8>}> : () -> tensor<16x3x3x3xi8>
-    %518 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %519 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %520 = tosa.conv2d %arg0, %517, %518, %519, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x320x320x3xi8>, tensor<16x3x3x3xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x160x160x16xi32>
-    %521 = tosa.rescale %520, %514, %513, %516, %515 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x160x160x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x160x160x16xi8>
-    %522 = tosa.table %521, %512 : (tensor<1x160x160x16xi8>, tensor<256xi8>) -> tensor<1x160x160x16xi8>
-    %523 = tosa.reshape %511, %12 : (tensor<1x3x3x16xi8>, !tosa.shape<4>) -> tensor<3x3x16x1xi8>
-    %524 = tosa.depthwise_conv2d %522, %523, %510, %509, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x160x160x16xi8>, tensor<3x3x16x1xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x80x80x16xi32>
-    %525 = tosa.rescale %524, %507, %506, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x80x80x16xi8>
-    %526 = tosa.clamp %525 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x80x80x16xi8>) -> tensor<1x80x80x16xi8>
-    %527 = tosa.avg_pool2d %526, %519, %519 {acc_type = i32, kernel = array<i64: 80, 80>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x80x80x16xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x16xi8>
-    %528 = tosa.conv2d %527, %505, %504, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x16xi8>, tensor<8x1x1x16xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x8xi32>
-    %529 = tosa.rescale %528, %503, %502, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x8xi8>
-    %530 = tosa.clamp %529 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x8xi8>) -> tensor<1x1x1x8xi8>
-    %531 = tosa.conv2d %530, %501, %500, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x8xi8>, tensor<16x1x1x8xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x16xi32>
-    %532 = tosa.rescale %531, %498, %497, %516, %499 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x16xi8>
-    %533 = tosa.rescale %532, %494, %493, %499, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x16xi32>
-    %534 = tosa.rescale %533, %492, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x16xi32>
-    %535 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %536 = tosa.reshape %535, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %537 = tosa.add %534, %536 : (tensor<1x1x1x16xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x16xi32>
-    %538 = tosa.rescale %537, %488, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x16xi8>
-    %539 = tosa.clamp %538 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x16xi8>) -> tensor<1x1x1x16xi8>
-    %540 = tosa.rescale %539, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x16xi32>
-    %541 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %542 = tosa.reshape %541, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %543 = tosa.mul %540, %542, %519 : (tensor<1x1x1x16xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x16xi32>
-    %544 = tosa.rescale %543, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x16xi8>
-    %545 = tosa.rescale %526, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x80x80x16xi32>
-    %546 = tosa.rescale %544, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x16xi32>
-    %547 = tosa.mul %545, %546, %519 : (tensor<1x80x80x16xi32>, tensor<1x1x1x16xi32>, tensor<1xi8>) -> tensor<1x80x80x16xi32>
-    %548 = tosa.rescale %547, %481, %480, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x80x80x16xi8>
-    %549 = tosa.conv2d %548, %479, %478, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x80x80x16xi8>, tensor<16x1x1x16xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x80x80x16xi32>
-    %550 = tosa.rescale %549, %476, %475, %516, %477 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x80x80x16xi8>
-    %551 = tosa.conv2d %550, %474, %473, %477, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x80x80x16xi8>, tensor<72x1x1x16xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x80x80x72xi32>
-    %552 = tosa.rescale %551, %472, %471, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x80x80x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x80x80x72xi8>
-    %553 = tosa.clamp %552 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x80x80x72xi8>) -> tensor<1x80x80x72xi8>
-    %554 = tosa.reshape %470, %11 : (tensor<1x3x3x72xi8>, !tosa.shape<4>) -> tensor<3x3x72x1xi8>
-    %555 = tosa.depthwise_conv2d %553, %554, %469, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x80x80x72xi8>, tensor<3x3x72x1xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x72xi32>
-    %556 = tosa.rescale %555, %468, %467, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x72xi8>
-    %557 = tosa.clamp %556 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x40x40x72xi8>) -> tensor<1x40x40x72xi8>
-    %558 = tosa.conv2d %557, %466, %465, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x40x40x72xi8>, tensor<24x1x1x72xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x24xi32>
-    %559 = tosa.rescale %558, %463, %462, %516, %464 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x24xi8>
-    %560 = tosa.conv2d %559, %461, %460, %464, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x40x40x24xi8>, tensor<88x1x1x24xi8>, tensor<88xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x88xi32>
-    %561 = tosa.rescale %560, %459, %458, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x88xi32>, tensor<88xi32>, tensor<88xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x88xi8>
-    %562 = tosa.clamp %561 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x40x40x88xi8>) -> tensor<1x40x40x88xi8>
-    %563 = tosa.reshape %457, %10 : (tensor<1x3x3x88xi8>, !tosa.shape<4>) -> tensor<3x3x88x1xi8>
-    %564 = tosa.depthwise_conv2d %562, %563, %456, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x40x40x88xi8>, tensor<3x3x88x1xi8>, tensor<88xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x88xi32>
-    %565 = tosa.rescale %564, %455, %454, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x88xi32>, tensor<88xi32>, tensor<88xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x88xi8>
-    %566 = tosa.clamp %565 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x40x40x88xi8>) -> tensor<1x40x40x88xi8>
-    %567 = tosa.conv2d %566, %453, %452, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x40x40x88xi8>, tensor<24x1x1x88xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x24xi32>
-    %568 = tosa.rescale %567, %450, %449, %516, %451 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x24xi8>
-    %569 = tosa.rescale %568, %494, %490, %451, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x40x40x24xi32>
-    %570 = tosa.rescale %559, %494, %493, %464, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x40x40x24xi32>
-    %571 = tosa.rescale %570, %448, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x40x40x24xi32>
-    %572 = tosa.add %569, %571 : (tensor<1x40x40x24xi32>, tensor<1x40x40x24xi32>) -> tensor<1x40x40x24xi32>
-    %573 = tosa.rescale %572, %447, %487, %516, %446 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x24xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x24xi8>
-    %574 = tosa.conv2d %573, %445, %444, %446, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x40x40x24xi8>, tensor<96x1x1x24xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x40x40x96xi32>
-    %575 = tosa.rescale %574, %442, %441, %516, %443 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x40x40x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x40x40x96xi8>
-    %576 = tosa.table %575, %440 : (tensor<1x40x40x96xi8>, tensor<256xi8>) -> tensor<1x40x40x96xi8>
-    %577 = tosa.reshape %439, %9 : (tensor<1x5x5x96xi8>, !tosa.shape<4>) -> tensor<5x5x96x1xi8>
-    %578 = tosa.depthwise_conv2d %576, %577, %438, %437, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 2, 1, 2>, stride = array<i64: 2, 2>} : (tensor<1x40x40x96xi8>, tensor<5x5x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x96xi32>
-    %579 = tosa.rescale %578, %435, %434, %516, %436 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x96xi8>
-    %580 = tosa.table %579, %433 : (tensor<1x20x20x96xi8>, tensor<256xi8>) -> tensor<1x20x20x96xi8>
-    %581 = tosa.avg_pool2d %580, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x96xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x96xi8>
-    %582 = tosa.conv2d %581, %432, %431, %430, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x96xi8>, tensor<24x1x1x96xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x24xi32>
-    %583 = tosa.rescale %582, %429, %428, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x24xi8>
-    %584 = tosa.clamp %583 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x24xi8>) -> tensor<1x1x1x24xi8>
-    %585 = tosa.conv2d %584, %427, %426, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x24xi8>, tensor<96x1x1x24xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x96xi32>
-    %586 = tosa.rescale %585, %424, %423, %516, %425 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x96xi8>
-    %587 = tosa.rescale %586, %494, %493, %425, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x96xi32>
-    %588 = tosa.rescale %587, %422, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x96xi32>
-    %589 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %590 = tosa.reshape %589, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %591 = tosa.add %588, %590 : (tensor<1x1x1x96xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x96xi32>
-    %592 = tosa.rescale %591, %488, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x96xi8>
-    %593 = tosa.clamp %592 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x96xi8>) -> tensor<1x1x1x96xi8>
-    %594 = tosa.rescale %593, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x96xi32>
-    %595 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %596 = tosa.reshape %595, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %597 = tosa.mul %594, %596, %519 : (tensor<1x1x1x96xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x96xi32>
-    %598 = tosa.rescale %597, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x96xi8>
-    %599 = tosa.rescale %580, %494, %484, %430, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x96xi32>
-    %600 = tosa.rescale %598, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x96xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x96xi32>
-    %601 = tosa.mul %599, %600, %519 : (tensor<1x20x20x96xi32>, tensor<1x1x1x96xi32>, tensor<1xi8>) -> tensor<1x20x20x96xi32>
-    %602 = tosa.rescale %601, %421, %420, %516, %419 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x96xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x96xi8>
-    %603 = tosa.conv2d %602, %418, %417, %419, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x96xi8>, tensor<40x1x1x96xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x40xi32>
-    %604 = tosa.rescale %603, %415, %414, %516, %416 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
-    %605 = tosa.conv2d %604, %413, %412, %416, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x40xi8>, tensor<240x1x1x40xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
-    %606 = tosa.rescale %605, %410, %409, %516, %411 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
-    %607 = tosa.table %606, %408 : (tensor<1x20x20x240xi8>, tensor<256xi8>) -> tensor<1x20x20x240xi8>
-    %608 = tosa.reshape %407, %8 : (tensor<1x5x5x240xi8>, !tosa.shape<4>) -> tensor<5x5x240x1xi8>
-    %609 = tosa.depthwise_conv2d %607, %608, %406, %405, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<5x5x240x1xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
-    %610 = tosa.rescale %609, %404, %403, %516, %436 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
-    %611 = tosa.table %610, %402 : (tensor<1x20x20x240xi8>, tensor<256xi8>) -> tensor<1x20x20x240xi8>
-    %612 = tosa.avg_pool2d %611, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
-    %613 = tosa.conv2d %612, %401, %400, %399, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x240xi8>, tensor<64x1x1x240xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x64xi32>
-    %614 = tosa.rescale %613, %398, %397, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x64xi8>
-    %615 = tosa.clamp %614 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x64xi8>) -> tensor<1x1x1x64xi8>
-    %616 = tosa.conv2d %615, %396, %395, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x64xi8>, tensor<240x1x1x64xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x240xi32>
-    %617 = tosa.rescale %616, %393, %392, %516, %394 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
-    %618 = tosa.rescale %617, %494, %493, %394, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
-    %619 = tosa.rescale %618, %391, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
-    %620 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %621 = tosa.reshape %620, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %622 = tosa.add %619, %621 : (tensor<1x1x1x240xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x240xi32>
-    %623 = tosa.rescale %622, %390, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
-    %624 = tosa.clamp %623 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x240xi8>) -> tensor<1x1x1x240xi8>
-    %625 = tosa.rescale %624, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
-    %626 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %627 = tosa.reshape %626, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %628 = tosa.mul %625, %627, %519 : (tensor<1x1x1x240xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi32>
-    %629 = tosa.rescale %628, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
-    %630 = tosa.rescale %611, %494, %484, %399, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x240xi32>
-    %631 = tosa.rescale %629, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
-    %632 = tosa.mul %630, %631, %519 : (tensor<1x20x20x240xi32>, tensor<1x1x1x240xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
-    %633 = tosa.rescale %632, %389, %388, %516, %387 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
-    %634 = tosa.conv2d %633, %386, %385, %387, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<40x1x1x240xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x40xi32>
-    %635 = tosa.rescale %634, %383, %382, %516, %384 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
-    %636 = tosa.rescale %635, %494, %490, %384, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
-    %637 = tosa.rescale %604, %494, %493, %416, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
-    %638 = tosa.rescale %637, %381, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
-    %639 = tosa.add %636, %638 : (tensor<1x20x20x40xi32>, tensor<1x20x20x40xi32>) -> tensor<1x20x20x40xi32>
-    %640 = tosa.rescale %639, %380, %379, %516, %519 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
-    %641 = tosa.conv2d %640, %378, %377, %519, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x40xi8>, tensor<240x1x1x40xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
-    %642 = tosa.rescale %641, %376, %375, %516, %491 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
-    %643 = tosa.table %642, %374 : (tensor<1x20x20x240xi8>, tensor<256xi8>) -> tensor<1x20x20x240xi8>
-    %644 = tosa.reshape %373, %8 : (tensor<1x5x5x240xi8>, !tosa.shape<4>) -> tensor<5x5x240x1xi8>
-    %645 = tosa.depthwise_conv2d %643, %644, %372, %405, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<5x5x240x1xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
-    %646 = tosa.rescale %645, %370, %369, %516, %371 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
-    %647 = tosa.table %646, %368 : (tensor<1x20x20x240xi8>, tensor<256xi8>) -> tensor<1x20x20x240xi8>
-    %648 = tosa.avg_pool2d %647, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
-    %649 = tosa.conv2d %648, %367, %366, %365, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x240xi8>, tensor<64x1x1x240xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x64xi32>
-    %650 = tosa.rescale %649, %364, %363, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x64xi8>
-    %651 = tosa.clamp %650 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x64xi8>) -> tensor<1x1x1x64xi8>
-    %652 = tosa.conv2d %651, %362, %361, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x64xi8>, tensor<240x1x1x64xi8>, tensor<240xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x240xi32>
-    %653 = tosa.rescale %652, %359, %358, %516, %360 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<240xi32>, tensor<240xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
-    %654 = tosa.rescale %653, %494, %493, %360, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
-    %655 = tosa.rescale %654, %357, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
-    %656 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %657 = tosa.reshape %656, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %658 = tosa.add %655, %657 : (tensor<1x1x1x240xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x240xi32>
-    %659 = tosa.rescale %658, %356, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
-    %660 = tosa.clamp %659 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x240xi8>) -> tensor<1x1x1x240xi8>
-    %661 = tosa.rescale %660, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
-    %662 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %663 = tosa.reshape %662, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %664 = tosa.mul %661, %663, %519 : (tensor<1x1x1x240xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi32>
-    %665 = tosa.rescale %664, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x240xi8>
-    %666 = tosa.rescale %647, %494, %484, %365, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x240xi32>
-    %667 = tosa.rescale %665, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x240xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x240xi32>
-    %668 = tosa.mul %666, %667, %519 : (tensor<1x20x20x240xi32>, tensor<1x1x1x240xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi32>
-    %669 = tosa.rescale %668, %355, %388, %516, %354 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x240xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x240xi8>
-    %670 = tosa.conv2d %669, %353, %352, %354, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x240xi8>, tensor<40x1x1x240xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x40xi32>
-    %671 = tosa.rescale %670, %350, %349, %516, %351 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
-    %672 = tosa.rescale %671, %494, %490, %351, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
-    %673 = tosa.rescale %640, %494, %493, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
-    %674 = tosa.rescale %673, %348, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x20x20x40xi32>
-    %675 = tosa.add %672, %674 : (tensor<1x20x20x40xi32>, tensor<1x20x20x40xi32>) -> tensor<1x20x20x40xi32>
-    %676 = tosa.rescale %675, %347, %379, %516, %354 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x40xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x40xi8>
-    %677 = tosa.conv2d %676, %346, %345, %354, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x40xi8>, tensor<120x1x1x40xi8>, tensor<120xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x120xi32>
-    %678 = tosa.rescale %677, %343, %342, %516, %344 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x120xi32>, tensor<120xi32>, tensor<120xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x120xi8>
-    %679 = tosa.table %678, %341 : (tensor<1x20x20x120xi8>, tensor<256xi8>) -> tensor<1x20x20x120xi8>
-    %680 = tosa.reshape %340, %7 : (tensor<1x5x5x120xi8>, !tosa.shape<4>) -> tensor<5x5x120x1xi8>
-    %681 = tosa.depthwise_conv2d %679, %680, %339, %338, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x20x20x120xi8>, tensor<5x5x120x1xi8>, tensor<120xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x120xi32>
-    %682 = tosa.rescale %681, %336, %335, %516, %337 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x120xi32>, tensor<120xi32>, tensor<120xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x120xi8>
-    %683 = tosa.table %682, %334 : (tensor<1x20x20x120xi8>, tensor<256xi8>) -> tensor<1x20x20x120xi8>
-    %684 = tosa.avg_pool2d %683, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x120xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x120xi8>
-    %685 = tosa.conv2d %684, %333, %332, %331, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x120xi8>, tensor<32x1x1x120xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x32xi32>
-    %686 = tosa.rescale %685, %330, %329, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x32xi8>
-    %687 = tosa.clamp %686 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x32xi8>) -> tensor<1x1x1x32xi8>
-    %688 = tosa.conv2d %687, %328, %327, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x32xi8>, tensor<120x1x1x32xi8>, tensor<120xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x120xi32>
-    %689 = tosa.rescale %688, %325, %324, %516, %326 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi32>, tensor<120xi32>, tensor<120xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x120xi8>
-    %690 = tosa.rescale %689, %494, %490, %326, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x120xi32>
-    %691 = tosa.rescale %496, %494, %493, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %692 = tosa.rescale %691, %323, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<i32>
-    %693 = tosa.reshape %692, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %694 = tosa.add %690, %693 : (tensor<1x1x1x120xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x120xi32>
-    %695 = tosa.rescale %694, %322, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x120xi8>
-    %696 = tosa.clamp %695 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x120xi8>) -> tensor<1x1x1x120xi8>
-    %697 = tosa.rescale %696, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x120xi32>
-    %698 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %699 = tosa.reshape %698, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %700 = tosa.mul %697, %699, %519 : (tensor<1x1x1x120xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x120xi32>
-    %701 = tosa.rescale %700, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x120xi8>
-    %702 = tosa.rescale %683, %494, %484, %331, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x120xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x120xi32>
-    %703 = tosa.rescale %701, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x120xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x120xi32>
-    %704 = tosa.mul %702, %703, %519 : (tensor<1x20x20x120xi32>, tensor<1x1x1x120xi32>, tensor<1xi8>) -> tensor<1x20x20x120xi32>
-    %705 = tosa.rescale %704, %321, %388, %516, %337 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x120xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x120xi8>
-    %706 = tosa.conv2d %705, %320, %319, %337, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x120xi8>, tensor<48x1x1x120xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x48xi32>
-    %707 = tosa.rescale %706, %317, %316, %516, %318 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x48xi8>
-    %708 = tosa.conv2d %707, %315, %314, %318, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x48xi8>, tensor<144x1x1x48xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x144xi32>
-    %709 = tosa.rescale %708, %313, %312, %516, %416 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x144xi8>
-    %710 = tosa.table %709, %311 : (tensor<1x20x20x144xi8>, tensor<256xi8>) -> tensor<1x20x20x144xi8>
-    %711 = tosa.reshape %310, %6 : (tensor<1x5x5x144xi8>, !tosa.shape<4>) -> tensor<5x5x144x1xi8>
-    %712 = tosa.depthwise_conv2d %710, %711, %309, %365, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x20x20x144xi8>, tensor<5x5x144x1xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x144xi32>
-    %713 = tosa.rescale %712, %308, %307, %516, %451 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x144xi8>
-    %714 = tosa.table %713, %306 : (tensor<1x20x20x144xi8>, tensor<256xi8>) -> tensor<1x20x20x144xi8>
-    %715 = tosa.avg_pool2d %714, %519, %519 {acc_type = i32, kernel = array<i64: 20, 20>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x144xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x144xi8>
-    %716 = tosa.conv2d %715, %305, %304, %303, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x144xi8>, tensor<40x1x1x144xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x40xi32>
-    %717 = tosa.rescale %716, %302, %301, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x40xi8>
-    %718 = tosa.clamp %717 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x40xi8>) -> tensor<1x1x1x40xi8>
-    %719 = tosa.conv2d %718, %300, %299, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x40xi8>, tensor<144x1x1x40xi8>, tensor<144xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x144xi32>
-    %720 = tosa.rescale %719, %297, %296, %516, %298 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi32>, tensor<144xi32>, tensor<144xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x144xi8>
-    %721 = tosa.rescale %720, %494, %493, %298, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x144xi32>
-    %722 = tosa.rescale %721, %295, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x144xi32>
-    %723 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %724 = tosa.reshape %723, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %725 = tosa.add %722, %724 : (tensor<1x1x1x144xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x144xi32>
-    %726 = tosa.rescale %725, %294, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x144xi8>
-    %727 = tosa.clamp %726 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x144xi8>) -> tensor<1x1x1x144xi8>
-    %728 = tosa.rescale %727, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x144xi32>
-    %729 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %730 = tosa.reshape %729, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %731 = tosa.mul %728, %730, %519 : (tensor<1x1x1x144xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x144xi32>
-    %732 = tosa.rescale %731, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x144xi8>
-    %733 = tosa.rescale %714, %494, %484, %303, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x144xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x144xi32>
-    %734 = tosa.rescale %732, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x144xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x144xi32>
-    %735 = tosa.mul %733, %734, %519 : (tensor<1x20x20x144xi32>, tensor<1x1x1x144xi32>, tensor<1xi8>) -> tensor<1x20x20x144xi32>
-    %736 = tosa.rescale %735, %293, %388, %516, %477 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x144xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x144xi8>
-    %737 = tosa.conv2d %736, %292, %291, %477, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x144xi8>, tensor<48x1x1x144xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x48xi32>
-    %738 = tosa.rescale %737, %290, %289, %516, %411 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x48xi8>
-    %739 = tosa.rescale %738, %494, %493, %411, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x48xi32>
-    %740 = tosa.rescale %739, %288, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x20x20x48xi32>
-    %741 = tosa.rescale %707, %494, %490, %318, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x20x20x48xi32>
-    %742 = tosa.add %740, %741 : (tensor<1x20x20x48xi32>, tensor<1x20x20x48xi32>) -> tensor<1x20x20x48xi32>
-    %743 = tosa.rescale %742, %287, %379, %516, %286 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x48xi8>
-    %744 = tosa.conv2d %743, %285, %284, %286, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x48xi8>, tensor<288x1x1x48xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x288xi32>
-    %745 = tosa.rescale %744, %283, %282, %516, %344 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x288xi8>
-    %746 = tosa.table %745, %281 : (tensor<1x20x20x288xi8>, tensor<256xi8>) -> tensor<1x20x20x288xi8>
-    %747 = tosa.reshape %280, %5 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
-    %748 = tosa.depthwise_conv2d %746, %747, %279, %278, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x20x20x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x288xi32>
-    %749 = tosa.rescale %748, %277, %276, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x288xi8>
-    %750 = tosa.clamp %749 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x20x20x288xi8>) -> tensor<1x20x20x288xi8>
-    %751 = tosa.conv2d %750, %275, %274, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x288xi8>, tensor<12x1x1x288xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x12xi32>
-    %752 = tosa.rescale %751, %272, %271, %516, %273 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x12xi32>, tensor<12xi32>, tensor<12xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x12xi8>
-    %753 = tosa.reshape %752, %270 : (tensor<1x20x20x12xi8>, !tosa.shape<4>) -> tensor<1x1200x1x4xi8>
-    %754 = tosa.reshape %269, %5 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
-    %755 = tosa.depthwise_conv2d %746, %754, %268, %278, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x20x20x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x288xi32>
-    %756 = tosa.rescale %755, %267, %266, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x288xi8>
-    %757 = tosa.clamp %756 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x20x20x288xi8>) -> tensor<1x20x20x288xi8>
-    %758 = tosa.conv2d %757, %265, %264, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x20x20x288xi8>, tensor<273x1x1x288xi8>, tensor<273xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x20x20x273xi32>
-    %759 = tosa.rescale %758, %262, %261, %516, %263 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x20x20x273xi32>, tensor<273xi32>, tensor<273xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x20x20x273xi8>
-    %760 = tosa.reshape %759, %260 : (tensor<1x20x20x273xi8>, !tosa.shape<3>) -> tensor<1x1200x91xi8>
-    %761 = tosa.reshape %259, %4 : (tensor<1x5x5x288xi8>, !tosa.shape<4>) -> tensor<5x5x288x1xi8>
-    %762 = tosa.depthwise_conv2d %746, %761, %258, %278, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 2, 1, 2>, stride = array<i64: 2, 2>} : (tensor<1x20x20x288xi8>, tensor<5x5x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %763 = tosa.rescale %762, %256, %255, %516, %257 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %764 = tosa.table %763, %254 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
-    %765 = tosa.avg_pool2d %764, %519, %519 {acc_type = i32, kernel = array<i64: 10, 10>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %766 = tosa.conv2d %765, %253, %252, %303, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x288xi8>, tensor<72x1x1x288xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x72xi32>
-    %767 = tosa.rescale %766, %251, %250, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x72xi8>
-    %768 = tosa.clamp %767 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x72xi8>) -> tensor<1x1x1x72xi8>
-    %769 = tosa.conv2d %768, %249, %248, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x72xi8>, tensor<288x1x1x72xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
-    %770 = tosa.rescale %769, %247, %246, %516, %490 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %771 = tosa.rescale %770, %494, %493, %490, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %772 = tosa.rescale %771, %245, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %773 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %774 = tosa.reshape %773, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %775 = tosa.add %772, %774 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x288xi32>
-    %776 = tosa.rescale %775, %244, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %777 = tosa.clamp %776 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x288xi8>) -> tensor<1x1x1x288xi8>
-    %778 = tosa.rescale %777, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %779 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %780 = tosa.reshape %779, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %781 = tosa.mul %778, %780, %519 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
-    %782 = tosa.rescale %781, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %783 = tosa.rescale %764, %494, %484, %303, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x288xi32>
-    %784 = tosa.rescale %782, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %785 = tosa.mul %783, %784, %519 : (tensor<1x10x10x288xi32>, tensor<1x1x1x288xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %786 = tosa.rescale %785, %243, %242, %516, %337 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %787 = tosa.conv2d %786, %241, %240, %337, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<48x1x1x288xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x48xi32>
-    %788 = tosa.rescale %787, %239, %238, %516, %351 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
-    %789 = tosa.conv2d %788, %237, %236, %351, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x48xi8>, tensor<288x1x1x48xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %790 = tosa.rescale %789, %234, %233, %516, %235 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %791 = tosa.table %790, %232 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
-    %792 = tosa.reshape %231, %4 : (tensor<1x5x5x288xi8>, !tosa.shape<4>) -> tensor<5x5x288x1xi8>
-    %793 = tosa.depthwise_conv2d %791, %792, %230, %229, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<5x5x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %794 = tosa.rescale %793, %227, %226, %516, %228 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %795 = tosa.table %794, %225 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
-    %796 = tosa.avg_pool2d %795, %519, %519 {acc_type = i32, kernel = array<i64: 10, 10>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %797 = tosa.conv2d %796, %224, %223, %399, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x288xi8>, tensor<72x1x1x288xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x72xi32>
-    %798 = tosa.rescale %797, %222, %221, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x72xi8>
-    %799 = tosa.clamp %798 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x72xi8>) -> tensor<1x1x1x72xi8>
-    %800 = tosa.conv2d %799, %220, %219, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x72xi8>, tensor<288x1x1x72xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
-    %801 = tosa.rescale %800, %218, %217, %516, %326 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %802 = tosa.rescale %801, %494, %493, %326, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %803 = tosa.rescale %802, %216, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %804 = tosa.rescale %496, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %805 = tosa.reshape %804, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %806 = tosa.add %803, %805 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x288xi32>
-    %807 = tosa.rescale %806, %215, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %808 = tosa.clamp %807 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x288xi8>) -> tensor<1x1x1x288xi8>
-    %809 = tosa.rescale %808, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %810 = tosa.rescale %486, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %811 = tosa.reshape %810, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %812 = tosa.mul %809, %811, %519 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
-    %813 = tosa.rescale %812, %214, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %814 = tosa.rescale %795, %494, %484, %399, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x288xi32>
-    %815 = tosa.rescale %813, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %816 = tosa.mul %814, %815, %519 : (tensor<1x10x10x288xi32>, tensor<1x1x1x288xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %817 = tosa.rescale %816, %213, %242, %516, %212 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %818 = tosa.conv2d %817, %211, %210, %212, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<48x1x1x288xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x48xi32>
-    %819 = tosa.rescale %818, %208, %207, %516, %209 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
-    %820 = tosa.rescale %819, %494, %490, %209, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
-    %821 = tosa.rescale %788, %494, %493, %351, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
-    %822 = tosa.rescale %821, %206, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
-    %823 = tosa.add %820, %822 : (tensor<1x10x10x48xi32>, tensor<1x10x10x48xi32>) -> tensor<1x10x10x48xi32>
-    %824 = tosa.rescale %823, %205, %487, %516, %204 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
-    %825 = tosa.conv2d %824, %203, %202, %204, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x48xi8>, tensor<288x1x1x48xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %826 = tosa.rescale %825, %201, %200, %516, %354 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %827 = tosa.table %826, %199 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
-    %828 = tosa.reshape %198, %4 : (tensor<1x5x5x288xi8>, !tosa.shape<4>) -> tensor<5x5x288x1xi8>
-    %829 = tosa.depthwise_conv2d %827, %828, %197, %278, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 2, 2>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<5x5x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %830 = tosa.rescale %829, %195, %194, %516, %196 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %831 = tosa.table %830, %193 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
-    %832 = tosa.avg_pool2d %831, %519, %519 {acc_type = i32, kernel = array<i64: 10, 10>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %833 = tosa.conv2d %832, %192, %191, %399, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x288xi8>, tensor<72x1x1x288xi8>, tensor<72xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x72xi32>
-    %834 = tosa.rescale %833, %190, %189, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x72xi32>, tensor<72xi32>, tensor<72xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x72xi8>
-    %835 = tosa.clamp %834 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x72xi8>) -> tensor<1x1x1x72xi8>
-    %836 = tosa.conv2d %835, %188, %187, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x72xi8>, tensor<288x1x1x72xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
-    %837 = tosa.rescale %836, %186, %185, %516, %326 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %838 = tosa.rescale %837, %494, %493, %326, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %839 = tosa.rescale %838, %184, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %840 = tosa.rescale %495, %494, %490, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %841 = tosa.reshape %840, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %842 = tosa.add %839, %841 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>) -> tensor<1x1x1x288xi32>
-    %843 = tosa.rescale %842, %183, %487, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %844 = tosa.clamp %843 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x288xi8>) -> tensor<1x1x1x288xi8>
-    %845 = tosa.rescale %844, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %846 = tosa.rescale %485, %494, %484, %519, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<i8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<i32>
-    %847 = tosa.reshape %846, %489 : (tensor<i32>, !tosa.shape<4>) -> tensor<1x1x1x1xi32>
-    %848 = tosa.mul %845, %847, %519 : (tensor<1x1x1x288xi32>, tensor<1x1x1x1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi32>
-    %849 = tosa.rescale %848, %483, %482, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x288xi8>
-    %850 = tosa.rescale %831, %494, %484, %399, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x288xi32>
-    %851 = tosa.rescale %849, %494, %484, %508, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x288xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x1x288xi32>
-    %852 = tosa.mul %850, %851, %519 : (tensor<1x10x10x288xi32>, tensor<1x1x1x288xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %853 = tosa.rescale %852, %182, %242, %516, %181 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %854 = tosa.conv2d %853, %180, %179, %181, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<48x1x1x288xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x48xi32>
-    %855 = tosa.rescale %854, %178, %177, %516, %425 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
-    %856 = tosa.rescale %855, %494, %490, %425, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
-    %857 = tosa.rescale %824, %494, %493, %204, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
-    %858 = tosa.rescale %857, %176, %491, %516, %516 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x10x10x48xi32>
-    %859 = tosa.add %856, %858 : (tensor<1x10x10x48xi32>, tensor<1x10x10x48xi32>) -> tensor<1x10x10x48xi32>
-    %860 = tosa.rescale %859, %175, %379, %516, %436 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x48xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x48xi8>
-    %861 = tosa.conv2d %860, %174, %173, %436, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x48xi8>, tensor<288x1x1x48xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %862 = tosa.rescale %861, %171, %170, %516, %172 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %863 = tosa.table %862, %169 : (tensor<1x10x10x288xi8>, tensor<256xi8>) -> tensor<1x10x10x288xi8>
-    %864 = tosa.reshape %168, %5 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
-    %865 = tosa.depthwise_conv2d %863, %864, %167, %166, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %866 = tosa.rescale %865, %165, %164, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %867 = tosa.clamp %866 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x10x10x288xi8>) -> tensor<1x10x10x288xi8>
-    %868 = tosa.conv2d %867, %163, %162, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<24x1x1x288xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x24xi32>
-    %869 = tosa.rescale %868, %160, %159, %516, %161 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x24xi8>
-    %870 = tosa.reshape %869, %158 : (tensor<1x10x10x24xi8>, !tosa.shape<4>) -> tensor<1x600x1x4xi8>
-    %871 = tosa.reshape %157, %5 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
-    %872 = tosa.depthwise_conv2d %863, %871, %156, %166, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x288xi32>
-    %873 = tosa.rescale %872, %155, %154, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x288xi8>
-    %874 = tosa.clamp %873 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x10x10x288xi8>) -> tensor<1x10x10x288xi8>
-    %875 = tosa.conv2d %874, %153, %152, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<546x1x1x288xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x546xi32>
-    %876 = tosa.rescale %875, %150, %149, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x546xi8>
-    %877 = tosa.reshape %876, %148 : (tensor<1x10x10x546xi8>, !tosa.shape<3>) -> tensor<1x600x91xi8>
-    %878 = tosa.conv2d %863, %147, %146, %166, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x10x10x288xi8>, tensor<256x1x1x288xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x10x10x256xi32>
-    %879 = tosa.rescale %878, %145, %144, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x10x10x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x10x10x256xi8>
-    %880 = tosa.clamp %879 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x10x10x256xi8>) -> tensor<1x10x10x256xi8>
-    %881 = tosa.reshape %143, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
-    %882 = tosa.depthwise_conv2d %880, %881, %142, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x10x10x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x256xi32>
-    %883 = tosa.rescale %882, %141, %140, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x256xi8>
-    %884 = tosa.clamp %883 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x256xi8>) -> tensor<1x5x5x256xi8>
-    %885 = tosa.conv2d %884, %139, %138, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x5x5x256xi8>, tensor<512x1x1x256xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x512xi32>
-    %886 = tosa.rescale %885, %137, %136, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x512xi8>
-    %887 = tosa.clamp %886 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x512xi8>) -> tensor<1x5x5x512xi8>
-    %888 = tosa.reshape %135, %2 : (tensor<1x3x3x512xi8>, !tosa.shape<4>) -> tensor<3x3x512x1xi8>
-    %889 = tosa.depthwise_conv2d %887, %888, %134, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<3x3x512x1xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x512xi32>
-    %890 = tosa.rescale %889, %133, %132, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x512xi8>
-    %891 = tosa.clamp %890 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x512xi8>) -> tensor<1x5x5x512xi8>
-    %892 = tosa.conv2d %891, %131, %130, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<24x1x1x512xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x24xi32>
-    %893 = tosa.rescale %892, %128, %127, %516, %129 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x24xi8>
-    %894 = tosa.reshape %893, %126 : (tensor<1x5x5x24xi8>, !tosa.shape<4>) -> tensor<1x150x1x4xi8>
-    %895 = tosa.reshape %125, %2 : (tensor<1x3x3x512xi8>, !tosa.shape<4>) -> tensor<3x3x512x1xi8>
-    %896 = tosa.depthwise_conv2d %887, %895, %124, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<3x3x512x1xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x512xi32>
-    %897 = tosa.rescale %896, %123, %122, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x512xi8>
-    %898 = tosa.clamp %897 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x512xi8>) -> tensor<1x5x5x512xi8>
-    %899 = tosa.conv2d %898, %121, %120, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<546x1x1x512xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x546xi32>
-    %900 = tosa.rescale %899, %119, %118, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x546xi8>
-    %901 = tosa.reshape %900, %117 : (tensor<1x5x5x546xi8>, !tosa.shape<3>) -> tensor<1x150x91xi8>
-    %902 = tosa.conv2d %887, %116, %115, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x5x5x512xi8>, tensor<128x1x1x512xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x5x5x128xi32>
-    %903 = tosa.rescale %902, %114, %113, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x5x5x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x5x5x128xi8>
-    %904 = tosa.clamp %903 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x5x5x128xi8>) -> tensor<1x5x5x128xi8>
-    %905 = tosa.reshape %112, %1 : (tensor<1x3x3x128xi8>, !tosa.shape<4>) -> tensor<3x3x128x1xi8>
-    %906 = tosa.depthwise_conv2d %904, %905, %111, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 2, 2>} : (tensor<1x5x5x128xi8>, tensor<3x3x128x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x128xi32>
-    %907 = tosa.rescale %906, %110, %109, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x128xi8>
-    %908 = tosa.clamp %907 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x128xi8>) -> tensor<1x3x3x128xi8>
-    %909 = tosa.conv2d %908, %108, %107, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x3x3x128xi8>, tensor<256x1x1x128xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x256xi32>
-    %910 = tosa.rescale %909, %106, %105, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x256xi8>
-    %911 = tosa.clamp %910 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x256xi8>) -> tensor<1x3x3x256xi8>
-    %912 = tosa.reshape %104, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
-    %913 = tosa.depthwise_conv2d %911, %912, %103, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x256xi32>
-    %914 = tosa.rescale %913, %102, %101, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x256xi8>
-    %915 = tosa.clamp %914 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x256xi8>) -> tensor<1x3x3x256xi8>
-    %916 = tosa.conv2d %915, %100, %99, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<24x1x1x256xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x24xi32>
-    %917 = tosa.rescale %916, %97, %96, %516, %98 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x24xi8>
-    %918 = tosa.reshape %917, %95 : (tensor<1x3x3x24xi8>, !tosa.shape<4>) -> tensor<1x54x1x4xi8>
-    %919 = tosa.reshape %94, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
-    %920 = tosa.depthwise_conv2d %911, %919, %93, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x256xi32>
-    %921 = tosa.rescale %920, %92, %91, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x256xi8>
-    %922 = tosa.clamp %921 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x256xi8>) -> tensor<1x3x3x256xi8>
-    %923 = tosa.conv2d %922, %90, %89, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<546x1x1x256xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x546xi32>
-    %924 = tosa.rescale %923, %88, %87, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x546xi8>
-    %925 = tosa.reshape %924, %86 : (tensor<1x3x3x546xi8>, !tosa.shape<3>) -> tensor<1x54x91xi8>
-    %926 = tosa.conv2d %911, %85, %84, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x3x3x256xi8>, tensor<128x1x1x256xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x3x3x128xi32>
-    %927 = tosa.rescale %926, %83, %82, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x3x3x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x3x3x128xi8>
-    %928 = tosa.clamp %927 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x3x3x128xi8>) -> tensor<1x3x3x128xi8>
-    %929 = tosa.reshape %81, %1 : (tensor<1x3x3x128xi8>, !tosa.shape<4>) -> tensor<3x3x128x1xi8>
-    %930 = tosa.depthwise_conv2d %928, %929, %80, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 2, 2>} : (tensor<1x3x3x128xi8>, tensor<3x3x128x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x128xi32>
-    %931 = tosa.rescale %930, %79, %78, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x128xi8>
-    %932 = tosa.clamp %931 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x128xi8>) -> tensor<1x2x2x128xi8>
-    %933 = tosa.conv2d %932, %77, %76, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x2x2x128xi8>, tensor<256x1x1x128xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x256xi32>
-    %934 = tosa.rescale %933, %75, %74, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x256xi8>
-    %935 = tosa.clamp %934 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x256xi8>) -> tensor<1x2x2x256xi8>
-    %936 = tosa.reshape %73, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
-    %937 = tosa.depthwise_conv2d %935, %936, %72, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x256xi32>
-    %938 = tosa.rescale %937, %71, %70, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x256xi8>
-    %939 = tosa.clamp %938 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x256xi8>) -> tensor<1x2x2x256xi8>
-    %940 = tosa.conv2d %939, %69, %68, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<24x1x1x256xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x24xi32>
-    %941 = tosa.rescale %940, %67, %66, %516, %298 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x24xi8>
-    %942 = tosa.reshape %941, %65 : (tensor<1x2x2x24xi8>, !tosa.shape<4>) -> tensor<1x24x1x4xi8>
-    %943 = tosa.reshape %64, %3 : (tensor<1x3x3x256xi8>, !tosa.shape<4>) -> tensor<3x3x256x1xi8>
-    %944 = tosa.depthwise_conv2d %935, %943, %63, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<3x3x256x1xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x256xi32>
-    %945 = tosa.rescale %944, %62, %61, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x256xi8>
-    %946 = tosa.clamp %945 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x256xi8>) -> tensor<1x2x2x256xi8>
-    %947 = tosa.conv2d %946, %60, %59, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<546x1x1x256xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x546xi32>
-    %948 = tosa.rescale %947, %58, %57, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x546xi8>
-    %949 = tosa.reshape %948, %56 : (tensor<1x2x2x546xi8>, !tosa.shape<3>) -> tensor<1x24x91xi8>
-    %950 = tosa.conv2d %935, %55, %54, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x2x2x256xi8>, tensor<64x1x1x256xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x2x2x64xi32>
-    %951 = tosa.rescale %950, %53, %52, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x2x2x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x2x2x64xi8>
-    %952 = tosa.clamp %951 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x2x2x64xi8>) -> tensor<1x2x2x64xi8>
-    %953 = tosa.reshape %51, %0 : (tensor<1x3x3x64xi8>, !tosa.shape<4>) -> tensor<3x3x64x1xi8>
-    %954 = tosa.depthwise_conv2d %952, %953, %50, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x2x2x64xi8>, tensor<3x3x64x1xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x64xi32>
-    %955 = tosa.rescale %954, %49, %48, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x64xi8>
-    %956 = tosa.clamp %955 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x64xi8>) -> tensor<1x1x1x64xi8>
-    %957 = tosa.conv2d %956, %47, %46, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x64xi8>, tensor<128x1x1x64xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x128xi32>
-    %958 = tosa.rescale %957, %45, %44, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x128xi8>
-    %959 = tosa.clamp %958 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x128xi8>) -> tensor<1x1x1x128xi8>
-    %960 = tosa.reshape %43, %1 : (tensor<1x3x3x128xi8>, !tosa.shape<4>) -> tensor<3x3x128x1xi8>
-    %961 = tosa.depthwise_conv2d %959, %960, %42, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<3x3x128x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x128xi32>
-    %962 = tosa.rescale %961, %41, %40, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x128xi8>
-    %963 = tosa.clamp %962 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x128xi8>) -> tensor<1x1x1x128xi8>
-    %964 = tosa.conv2d %963, %39, %38, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<24x1x1x128xi8>, tensor<24xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x24xi32>
-    %965 = tosa.rescale %964, %36, %35, %516, %37 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x24xi32>, tensor<24xi32>, tensor<24xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x24xi8>
-    %966 = tosa.reshape %965, %34 : (tensor<1x1x1x24xi8>, !tosa.shape<4>) -> tensor<1x6x1x4xi8>
-    %967 = tosa.rescale %966, %33, %491, %37, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x6x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x6x1x4xi8>
-    %968 = tosa.rescale %942, %32, %491, %298, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x24x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x24x1x4xi8>
-    %969 = tosa.rescale %918, %31, %491, %98, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x54x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x54x1x4xi8>
-    %970 = tosa.rescale %894, %30, %491, %129, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x150x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x150x1x4xi8>
-    %971 = tosa.rescale %870, %29, %491, %161, %273 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x600x1x4xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x600x1x4xi8>
-    %972 = tosa.concat %753, %971, %970, %969, %968, %967 {axis = 1 : i32} : (tensor<1x1200x1x4xi8>, tensor<1x600x1x4xi8>, tensor<1x150x1x4xi8>, tensor<1x54x1x4xi8>, tensor<1x24x1x4xi8>, tensor<1x6x1x4xi8>) -> tensor<1x2034x1x4xi8>
-    %973 = tosa.reshape %972, %28 : (tensor<1x2034x1x4xi8>, !tosa.shape<3>) -> tensor<1x2034x4xi8>
-    %974 = tosa.reshape %27, %1 : (tensor<1x3x3x128xi8>, !tosa.shape<4>) -> tensor<3x3x128x1xi8>
-    %975 = tosa.depthwise_conv2d %959, %974, %26, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<3x3x128x1xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x128xi32>
-    %976 = tosa.rescale %975, %25, %24, %516, %508 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x128xi8>
-    %977 = tosa.clamp %976 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x1x1x128xi8>) -> tensor<1x1x1x128xi8>
-    %978 = tosa.conv2d %977, %23, %22, %508, %519 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<546x1x1x128xi8>, tensor<546xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x546xi32>
-    %979 = tosa.rescale %978, %21, %20, %516, %151 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x546xi32>, tensor<546xi32>, tensor<546xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x546xi8>
-    %980 = tosa.reshape %979, %19 : (tensor<1x1x1x546xi8>, !tosa.shape<3>) -> tensor<1x6x91xi8>
-    %981 = tosa.rescale %980, %18, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x6x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x6x91xi8>
-    %982 = tosa.rescale %949, %17, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x24x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x24x91xi8>
-    %983 = tosa.rescale %925, %16, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x54x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x54x91xi8>
-    %984 = tosa.rescale %901, %15, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x150x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x150x91xi8>
-    %985 = tosa.rescale %877, %14, %37, %151, %263 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x600x91xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x600x91xi8>
-    %986 = tosa.concat %760, %985, %984, %983, %982, %981 {axis = 1 : i32} : (tensor<1x1200x91xi8>, tensor<1x600x91xi8>, tensor<1x150x91xi8>, tensor<1x54x91xi8>, tensor<1x24x91xi8>, tensor<1x6x91xi8>) -> tensor<1x2034x91xi8>
-    %987 = tosa.table %986, %13 : (tensor<1x2034x91xi8>, tensor<256xi8>) -> tensor<1x2034x91xi8>
-    return %987, %973 : tensor<1x2034x91xi8>, tensor<1x2034x4xi8>
-  }
-}
diff --git a/tests/gold/test_python_api/tiny_wav2letter_pruned_int8.mlir b/tests/gold/test_python_api/tiny_wav2letter_pruned_int8.mlir
deleted file mode 100644
index 199e562..0000000
--- a/tests/gold/test_python_api/tiny_wav2letter_pruned_int8.mlir
+++ /dev/null
@@ -1,128 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.13.1\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<1x296x39xi8>) -> tensor<1x1x148x29xi8> attributes {tf.entry_function = {inputs = "input_1_int8", outputs = "Identity_int8"}} {
-    %0 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<29xi8>}> : () -> tensor<29xi8>
-    %1 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<29xi32>}> : () -> tensor<29xi32>
-    %2 = "tosa.const"() <{values = dense<5> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %3 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<29xi32>}> : () -> tensor<29xi32>
-    %4 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<29x1x1x750xi8>}> : () -> tensor<29x1x1x750xi8>
-    %5 = "tosa.const"() <{values = dense<-77> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %6 = "tosa.const"() <{values = dense<1925690389> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %7 = "tosa.const"() <{values = dense<1540552334> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %8 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi8>}> : () -> tensor<750xi8>
-    %9 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi32>}> : () -> tensor<750xi32>
-    %10 = "tosa.const"() <{values = dense<13> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %11 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi32>}> : () -> tensor<750xi32>
-    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750x1x1x750xi8>}> : () -> tensor<750x1x1x750xi8>
-    %13 = "tosa.const"() <{values = dense<-76> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %14 = "tosa.const"() <{values = dense<1949381878> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %15 = "tosa.const"() <{values = dense<1559505526> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi8>}> : () -> tensor<750xi8>
-    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi32>}> : () -> tensor<750xi32>
-    %18 = "tosa.const"() <{values = dense<15> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750xi32>}> : () -> tensor<750xi32>
-    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<750x1x32x100xi8>}> : () -> tensor<750x1x32x100xi8>
-    %21 = "tosa.const"() <{values = dense<-84> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %22 = "tosa.const"() <{values = dense<1819150077> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %23 = "tosa.const"() <{values = dense<1455320083> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x100xi8>}> : () -> tensor<100x1x7x100xi8>
-    %28 = "tosa.const"() <{values = dense<1833421420> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %29 = "tosa.const"() <{values = dense<1466737158> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
-    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %32 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %33 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x100xi8>}> : () -> tensor<100x1x7x100xi8>
-    %34 = "tosa.const"() <{values = dense<1981257558> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %35 = "tosa.const"() <{values = dense<1585006070> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
-    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x100xi8>}> : () -> tensor<100x1x7x100xi8>
-    %40 = "tosa.const"() <{values = dense<-74> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %41 = "tosa.const"() <{values = dense<1976102450> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %42 = "tosa.const"() <{values = dense<1580881984> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
-    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %45 = "tosa.const"() <{values = dense<18> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x100xi8>}> : () -> tensor<100x1x7x100xi8>
-    %48 = "tosa.const"() <{values = dense<-56> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %49 = "tosa.const"() <{values = dense<29> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %50 = "tosa.const"() <{values = dense<1139114841> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %51 = "tosa.const"() <{values = dense<1822583773> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi8>}> : () -> tensor<100xi8>
-    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %54 = "tosa.const"() <{values = dense<41> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %55 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100xi32>}> : () -> tensor<100xi32>
-    %56 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<100x1x7x250xi8>}> : () -> tensor<100x1x7x250xi8>
-    %57 = "tosa.const"() <{values = dense<-83> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %58 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %59 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %60 = "tosa.const"() <{values = dense<1827101553> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %61 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %62 = "tosa.const"() <{values = dense<1461681264> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %63 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<250xi8>}> : () -> tensor<250xi8>
-    %64 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<250xi32>}> : () -> tensor<250xi32>
-    %65 = "tosa.const"() <{values = dense<3> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %66 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %67 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %68 = "tosa.const"() <{values = dense<4> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %69 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<250xi32>}> : () -> tensor<250xi32>
-    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<250x1x48x39xi8>}> : () -> tensor<250x1x48x39xi8>
-    %71 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %72 = tosa.reshape %arg0, %71 : (tensor<1x296x39xi8>, !tosa.shape<4>) -> tensor<1x1x296x39xi8>
-    %73 = tosa.conv2d %72, %70, %69, %68, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 23, 23>, stride = array<i64: 1, 2>} : (tensor<1x1x296x39xi8>, tensor<250x1x48x39xi8>, tensor<250xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x250xi32>
-    %74 = tosa.rescale %73, %64, %63, %66, %65 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x250xi32>, tensor<250xi32>, tensor<250xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x250xi8>
-    %75 = tosa.rescale %74, %62, %61, %65, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x250xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x250xi32>
-    %76 = tosa.rescale %74, %60, %59, %65, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x250xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x250xi32>
-    %77 = tosa.maximum %76, %75 : (tensor<1x1x148x250xi32>, tensor<1x1x148x250xi32>) -> tensor<1x1x148x250xi32>
-    %78 = tosa.rescale %77, %58, %59, %66, %57 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x250xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x250xi8>
-    %79 = tosa.conv2d %78, %56, %55, %57, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x250xi8>, tensor<100x1x7x250xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
-    %80 = tosa.rescale %79, %53, %52, %66, %54 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %81 = tosa.rescale %80, %51, %61, %54, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %82 = tosa.rescale %80, %50, %49, %54, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %83 = tosa.maximum %82, %81 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
-    %84 = tosa.rescale %83, %58, %59, %66, %48 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %85 = tosa.conv2d %84, %47, %46, %48, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<100x1x7x100xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
-    %86 = tosa.rescale %85, %44, %43, %66, %45 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %87 = tosa.rescale %86, %42, %61, %45, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %88 = tosa.rescale %86, %41, %59, %45, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %89 = tosa.maximum %88, %87 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
-    %90 = tosa.rescale %89, %58, %59, %66, %40 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %91 = tosa.conv2d %90, %39, %38, %40, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<100x1x7x100xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
-    %92 = tosa.rescale %91, %37, %36, %66, %45 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %93 = tosa.rescale %92, %35, %61, %45, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %94 = tosa.rescale %92, %34, %59, %45, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %95 = tosa.maximum %94, %93 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
-    %96 = tosa.rescale %95, %58, %59, %66, %40 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %97 = tosa.conv2d %96, %33, %32, %40, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<100x1x7x100xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
-    %98 = tosa.rescale %97, %31, %30, %66, %68 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %99 = tosa.rescale %98, %29, %61, %68, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %100 = tosa.rescale %98, %28, %59, %68, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %101 = tosa.maximum %100, %99 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
-    %102 = tosa.rescale %101, %58, %59, %66, %57 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %103 = tosa.conv2d %102, %27, %26, %57, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 3, 3>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<100x1x7x100xi8>, tensor<100xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x100xi32>
-    %104 = tosa.rescale %103, %25, %24, %66, %65 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<100xi32>, tensor<100xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %105 = tosa.rescale %104, %23, %61, %65, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %106 = tosa.rescale %104, %22, %59, %65, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x100xi32>
-    %107 = tosa.maximum %106, %105 : (tensor<1x1x148x100xi32>, tensor<1x1x148x100xi32>) -> tensor<1x1x148x100xi32>
-    %108 = tosa.rescale %107, %58, %59, %66, %21 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x100xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x100xi8>
-    %109 = tosa.conv2d %108, %20, %19, %21, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 15, 16>, stride = array<i64: 1, 1>} : (tensor<1x1x148x100xi8>, tensor<750x1x32x100xi8>, tensor<750xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x750xi32>
-    %110 = tosa.rescale %109, %17, %16, %66, %18 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi32>, tensor<750xi32>, tensor<750xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x750xi8>
-    %111 = tosa.rescale %110, %15, %61, %18, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x750xi32>
-    %112 = tosa.rescale %110, %14, %59, %18, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x750xi32>
-    %113 = tosa.maximum %112, %111 : (tensor<1x1x148x750xi32>, tensor<1x1x148x750xi32>) -> tensor<1x1x148x750xi32>
-    %114 = tosa.rescale %113, %58, %59, %66, %13 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x750xi8>
-    %115 = tosa.conv2d %114, %12, %11, %13, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x148x750xi8>, tensor<750x1x1x750xi8>, tensor<750xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x750xi32>
-    %116 = tosa.rescale %115, %9, %8, %66, %10 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi32>, tensor<750xi32>, tensor<750xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x750xi8>
-    %117 = tosa.rescale %116, %7, %61, %10, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x750xi32>
-    %118 = tosa.rescale %116, %6, %59, %10, %66 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x1x148x750xi32>
-    %119 = tosa.maximum %118, %117 : (tensor<1x1x148x750xi32>, tensor<1x1x148x750xi32>) -> tensor<1x1x148x750xi32>
-    %120 = tosa.rescale %119, %58, %59, %66, %5 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x750xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x750xi8>
-    %121 = tosa.conv2d %120, %4, %3, %5, %67 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x148x750xi8>, tensor<29x1x1x750xi8>, tensor<29xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x148x29xi32>
-    %122 = tosa.rescale %121, %1, %0, %66, %2 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x148x29xi32>, tensor<29xi32>, tensor<29xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x148x29xi8>
-    return %122 : tensor<1x1x148x29xi8>
-  }
-}
diff --git a/tests/gold/test_python_api/vww4_128_128_INT8.mlir b/tests/gold/test_python_api/vww4_128_128_INT8.mlir
deleted file mode 100644
index 0991a35..0000000
--- a/tests/gold/test_python_api/vww4_128_128_INT8.mlir
+++ /dev/null
@@ -1,514 +0,0 @@
-module attributes {tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "1.5.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<1x128x128x1xi8>) -> tensor<1x2xi8> attributes {tf.entry_function = {inputs = "input", outputs = "Identity"}} {
-    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %1 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %2 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %3 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %4 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %5 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %6 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %7 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %8 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %9 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %10 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %11 = "tosa.const"() <{values = dense<41> : tensor<2xi8>}> : () -> tensor<2xi8>
-    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<2xi32>}> : () -> tensor<2xi32>
-    %13 = "tosa.const"() <{values = dense<-17> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %14 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<2xi32>}> : () -> tensor<2xi32>
-    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<2x1x1x128xi8>}> : () -> tensor<2x1x1x128xi8>
-    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
-    %17 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x1x1x32xi8>}> : () -> tensor<128x1x1x32xi8>
-    %20 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
-    %21 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %22 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x1x1x96xi8>}> : () -> tensor<32x1x1x96xi8>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %25 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
-    %28 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %29 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %30 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %31 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x32xi8>}> : () -> tensor<96x1x1x32xi8>
-    %32 = "tosa.const"() <{values = dense<20> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %33 = "tosa.const"() <{values = dense<1867675366> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %34 = "tosa.const"() <{values = dense<1869358422> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %35 = "tosa.const"() <{values = dense<-23> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %36 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<8xindex>} : () -> !tosa.shape<8>
-    %37 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %40 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x1x1x96xi8>}> : () -> tensor<32x1x1x96xi8>
-    %41 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %42 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
-    %45 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %48 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x16xi8>}> : () -> tensor<96x1x1x16xi8>
-    %49 = "tosa.const"() <{values = dense<-23> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %50 = "tosa.const"() <{values = dense<1356240683> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %51 = "tosa.const"() <{values = dense<2017076441> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
-    %53 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %54 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %55 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x96xi8>}> : () -> tensor<16x1x1x96xi8>
-    %56 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %57 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %58 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x96xi8>}> : () -> tensor<1x3x3x96xi8>
-    %60 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi8>}> : () -> tensor<96xi8>
-    %61 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %62 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96xi32>}> : () -> tensor<96xi32>
-    %63 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<96x1x1x16xi8>}> : () -> tensor<96x1x1x16xi8>
-    %64 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
-    %65 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %66 = "tosa.const"() <{values = dense<-21> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %67 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %68 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x1x1x288xi8>}> : () -> tensor<16x1x1x288xi8>
-    %69 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi8>}> : () -> tensor<288xi8>
-    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi32>}> : () -> tensor<288xi32>
-    %71 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi32>}> : () -> tensor<288xi32>
-    %72 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x288xi8>}> : () -> tensor<1x3x3x288xi8>
-    %73 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi8>}> : () -> tensor<288xi8>
-    %74 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi32>}> : () -> tensor<288xi32>
-    %75 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288xi32>}> : () -> tensor<288xi32>
-    %76 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<288x1x1x68xi8>}> : () -> tensor<288x1x1x68xi8>
-    %77 = "tosa.const"() <{values = dense<-8> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %78 = "tosa.const"() <{values = dense<2052730416> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %79 = "tosa.const"() <{values = dense<1366556772> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %80 = "tosa.const"() <{values = dense<18> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %81 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<8xindex>} : () -> !tosa.shape<8>
-    %82 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<48xi8>}> : () -> tensor<48xi8>
-    %83 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<48xi32>}> : () -> tensor<48xi32>
-    %84 = "tosa.const"() <{values = dense<18> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %85 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<48xi32>}> : () -> tensor<48xi32>
-    %86 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<48x1x1x172xi8>}> : () -> tensor<48x1x1x172xi8>
-    %87 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi8>}> : () -> tensor<172xi8>
-    %88 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi32>}> : () -> tensor<172xi32>
-    %89 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi32>}> : () -> tensor<172xi32>
-    %90 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x172xi8>}> : () -> tensor<1x3x3x172xi8>
-    %91 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi8>}> : () -> tensor<172xi8>
-    %92 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi32>}> : () -> tensor<172xi32>
-    %93 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172xi32>}> : () -> tensor<172xi32>
-    %94 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<172x1x1x68xi8>}> : () -> tensor<172x1x1x68xi8>
-    %95 = "tosa.const"() <{values = dense<-10> : tensor<1xi8>}> : () -> tensor<1xi8>
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-    %274 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<4xi32>}> : () -> tensor<4xi32>
-    %275 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1x3x3x4xi8>}> : () -> tensor<1x3x3x4xi8>
-    %276 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<4xi8>}> : () -> tensor<4xi8>
-    %277 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<4xi32>}> : () -> tensor<4xi32>
-    %278 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<4xi32>}> : () -> tensor<4xi32>
-    %279 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<4x1x1x8xi8>}> : () -> tensor<4x1x1x8xi8>
-    %280 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi8>}> : () -> tensor<8xi8>
-    %281 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
-    %282 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %283 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %284 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8x3x3x1xi8>}> : () -> tensor<8x3x3x1xi8>
-    %285 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<8xi32>}> : () -> tensor<8xi32>
-    %286 = "tosa.const"() <{values = dense<-70> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %287 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %288 = tosa.conv2d %arg0, %284, %285, %286, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x128x128x1xi8>, tensor<8x3x3x1xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x8xi32>
-    %289 = tosa.rescale %288, %281, %280, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x8xi8>
-    %290 = tosa.clamp %289 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x64x64x8xi8>) -> tensor<1x64x64x8xi8>
-    %291 = tosa.conv2d %290, %279, %278, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x64x64x8xi8>, tensor<4x1x1x8xi8>, tensor<4xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x4xi32>
-    %292 = tosa.rescale %291, %277, %276, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x4xi32>, tensor<4xi32>, tensor<4xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x4xi8>
-    %293 = tosa.clamp %292 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x64x64x4xi8>) -> tensor<1x64x64x4xi8>
-    %294 = tosa.reshape %275, %9 : (tensor<1x3x3x4xi8>, !tosa.shape<4>) -> tensor<3x3x4x1xi8>
-    %295 = tosa.depthwise_conv2d %293, %294, %274, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x64x64x4xi8>, tensor<3x3x4x1xi8>, tensor<4xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x4xi32>
-    %296 = tosa.rescale %295, %273, %272, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x4xi32>, tensor<4xi32>, tensor<4xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x4xi8>
-    %297 = tosa.clamp %296 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x64x64x4xi8>) -> tensor<1x64x64x4xi8>
-    %298 = tosa.conv2d %297, %271, %270, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x64x64x4xi8>, tensor<4x1x1x4xi8>, tensor<4xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x4xi32>
-    %299 = tosa.rescale %298, %269, %268, %283, %287 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x4xi32>, tensor<4xi32>, tensor<4xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x4xi8>
-    %300 = tosa.conv2d %299, %267, %266, %287, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x64x64x4xi8>, tensor<8x1x1x4xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x64x64x8xi32>
-    %301 = tosa.rescale %300, %265, %264, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x64x64x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x64x64x8xi8>
-    %302 = tosa.clamp %301 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x64x64x8xi8>) -> tensor<1x64x64x8xi8>
-    %303 = tosa.reshape %263, %8 : (tensor<1x3x3x8xi8>, !tosa.shape<4>) -> tensor<3x3x8x1xi8>
-    %304 = tosa.depthwise_conv2d %302, %303, %262, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x64x64x8xi8>, tensor<3x3x8x1xi8>, tensor<8xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x8xi32>
-    %305 = tosa.rescale %304, %261, %260, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x8xi32>, tensor<8xi32>, tensor<8xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x8xi8>
-    %306 = tosa.clamp %305 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x8xi8>) -> tensor<1x32x32x8xi8>
-    %307 = tosa.conv2d %306, %259, %258, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xi8>, tensor<12x1x1x8xi8>, tensor<12xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x12xi32>
-    %308 = tosa.rescale %307, %256, %255, %283, %257 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x12xi32>, tensor<12xi32>, tensor<12xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x12xi8>
-    %309 = tosa.conv2d %308, %254, %253, %257, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x12xi8>, tensor<14x1x1x12xi8>, tensor<14xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x14xi32>
-    %310 = tosa.rescale %309, %252, %251, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x14xi32>, tensor<14xi32>, tensor<14xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x14xi8>
-    %311 = tosa.clamp %310 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x14xi8>) -> tensor<1x32x32x14xi8>
-    %312 = tosa.reshape %250, %7 : (tensor<1x3x3x14xi8>, !tosa.shape<4>) -> tensor<3x3x14x1xi8>
-    %313 = tosa.depthwise_conv2d %311, %312, %249, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x32x32x14xi8>, tensor<3x3x14x1xi8>, tensor<14xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x14xi32>
-    %314 = tosa.rescale %313, %248, %247, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x14xi32>, tensor<14xi32>, tensor<14xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x14xi8>
-    %315 = tosa.clamp %314 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x14xi8>) -> tensor<1x32x32x14xi8>
-    %316 = tosa.conv2d %315, %246, %245, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x14xi8>, tensor<16x1x1x14xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x16xi32>
-    %317 = tosa.rescale %316, %243, %242, %283, %244 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x16xi8>
-    %318 = tosa.pad %308, %241, %240 : (tensor<1x32x32x12xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x32x32x16xi8>
-    %319 = tosa.rescale %318, %239, %238, %257, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x32x32x16xi32>
-    %320 = tosa.rescale %317, %239, %237, %244, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x32x32x16xi32>
-    %321 = tosa.rescale %320, %236, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x32x32x16xi32>
-    %322 = tosa.add %319, %321 : (tensor<1x32x32x16xi32>, tensor<1x32x32x16xi32>) -> tensor<1x32x32x16xi32>
-    %323 = tosa.rescale %322, %234, %233, %283, %232 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x16xi8>
-    %324 = tosa.conv2d %323, %231, %230, %232, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x16xi8>, tensor<28x1x1x16xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x28xi32>
-    %325 = tosa.rescale %324, %229, %228, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x32x32x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x32x32x28xi8>
-    %326 = tosa.clamp %325 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x32x32x28xi8>) -> tensor<1x32x32x28xi8>
-    %327 = tosa.reshape %227, %6 : (tensor<1x3x3x28xi8>, !tosa.shape<4>) -> tensor<3x3x28x1xi8>
-    %328 = tosa.depthwise_conv2d %326, %327, %226, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x32x32x28xi8>, tensor<3x3x28x1xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x28xi32>
-    %329 = tosa.rescale %328, %225, %224, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x28xi8>
-    %330 = tosa.clamp %329 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x28xi8>) -> tensor<1x16x16x28xi8>
-    %331 = tosa.conv2d %330, %223, %222, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x28xi8>, tensor<32x1x1x28xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x32xi32>
-    %332 = tosa.rescale %331, %220, %219, %283, %221 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
-    %333 = tosa.conv2d %332, %218, %217, %221, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x32xi8>, tensor<96x1x1x32xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x96xi32>
-    %334 = tosa.rescale %333, %216, %215, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x96xi8>
-    %335 = tosa.clamp %334 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x96xi8>) -> tensor<1x16x16x96xi8>
-    %336 = tosa.reshape %214, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
-    %337 = tosa.depthwise_conv2d %335, %336, %213, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x16x16x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x96xi32>
-    %338 = tosa.rescale %337, %212, %211, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x96xi8>
-    %339 = tosa.clamp %338 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x96xi8>) -> tensor<1x16x16x96xi8>
-    %340 = tosa.conv2d %339, %210, %209, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x96xi8>, tensor<28x1x1x96xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x28xi32>
-    %341 = tosa.rescale %340, %207, %206, %283, %208 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x28xi8>
-    %342 = tosa.pad %341, %241, %205 : (tensor<1x16x16x28xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
-    %343 = tosa.rescale %332, %239, %238, %221, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
-    %344 = tosa.rescale %342, %239, %237, %208, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
-    %345 = tosa.rescale %344, %204, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
-    %346 = tosa.add %343, %345 : (tensor<1x16x16x32xi32>, tensor<1x16x16x32xi32>) -> tensor<1x16x16x32xi32>
-    %347 = tosa.rescale %346, %203, %233, %283, %202 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
-    %348 = tosa.conv2d %347, %201, %200, %202, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x32xi8>, tensor<96x1x1x32xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x96xi32>
-    %349 = tosa.rescale %348, %199, %198, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x96xi8>
-    %350 = tosa.clamp %349 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x96xi8>) -> tensor<1x16x16x96xi8>
-    %351 = tosa.reshape %197, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
-    %352 = tosa.depthwise_conv2d %350, %351, %196, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x16x16x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x96xi32>
-    %353 = tosa.rescale %352, %195, %194, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x96xi8>
-    %354 = tosa.clamp %353 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x96xi8>) -> tensor<1x16x16x96xi8>
-    %355 = tosa.conv2d %354, %193, %192, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x96xi8>, tensor<28x1x1x96xi8>, tensor<28xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x28xi32>
-    %356 = tosa.rescale %355, %191, %190, %283, %208 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x28xi32>, tensor<28xi32>, tensor<28xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x28xi8>
-    %357 = tosa.pad %356, %241, %189 : (tensor<1x16x16x28xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
-    %358 = tosa.rescale %347, %239, %238, %202, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
-    %359 = tosa.rescale %357, %239, %237, %208, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
-    %360 = tosa.rescale %359, %188, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x16x16x32xi32>
-    %361 = tosa.add %358, %360 : (tensor<1x16x16x32xi32>, tensor<1x16x16x32xi32>) -> tensor<1x16x16x32xi32>
-    %362 = tosa.rescale %361, %187, %186, %283, %185 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x32xi8>
-    %363 = tosa.conv2d %362, %184, %183, %185, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x16x16x32xi8>, tensor<152x1x1x32xi8>, tensor<152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x16x16x152xi32>
-    %364 = tosa.rescale %363, %182, %181, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x16x16x152xi32>, tensor<152xi32>, tensor<152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x16x16x152xi8>
-    %365 = tosa.clamp %364 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x16x16x152xi8>) -> tensor<1x16x16x152xi8>
-    %366 = tosa.reshape %180, %4 : (tensor<1x3x3x152xi8>, !tosa.shape<4>) -> tensor<3x3x152x1xi8>
-    %367 = tosa.depthwise_conv2d %365, %366, %179, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x16x16x152xi8>, tensor<3x3x152x1xi8>, tensor<152xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x152xi32>
-    %368 = tosa.rescale %367, %178, %177, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x152xi32>, tensor<152xi32>, tensor<152xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x152xi8>
-    %369 = tosa.clamp %368 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x152xi8>) -> tensor<1x8x8x152xi8>
-    %370 = tosa.conv2d %369, %176, %175, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x152xi8>, tensor<44x1x1x152xi8>, tensor<44xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x44xi32>
-    %371 = tosa.rescale %370, %174, %173, %283, %232 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi32>, tensor<44xi32>, tensor<44xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x44xi8>
-    %372 = tosa.conv2d %371, %172, %171, %232, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x44xi8>, tensor<268x1x1x44xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
-    %373 = tosa.rescale %372, %170, %169, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
-    %374 = tosa.clamp %373 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
-    %375 = tosa.reshape %168, %3 : (tensor<1x3x3x268xi8>, !tosa.shape<4>) -> tensor<3x3x268x1xi8>
-    %376 = tosa.depthwise_conv2d %374, %375, %167, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<3x3x268x1xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
-    %377 = tosa.rescale %376, %166, %165, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
-    %378 = tosa.clamp %377 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
-    %379 = tosa.conv2d %378, %164, %163, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<40x1x1x268xi8>, tensor<40xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x40xi32>
-    %380 = tosa.rescale %379, %161, %160, %283, %162 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x40xi32>, tensor<40xi32>, tensor<40xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x40xi8>
-    %381 = tosa.pad %380, %241, %159 : (tensor<1x8x8x40xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x8x8x44xi8>
-    %382 = tosa.rescale %371, %239, %238, %232, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x44xi32>
-    %383 = tosa.rescale %381, %239, %237, %162, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x44xi32>
-    %384 = tosa.rescale %383, %158, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x44xi32>
-    %385 = tosa.add %382, %384 : (tensor<1x8x8x44xi32>, tensor<1x8x8x44xi32>) -> tensor<1x8x8x44xi32>
-    %386 = tosa.rescale %385, %157, %186, %283, %156 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x44xi8>
-    %387 = tosa.conv2d %386, %155, %154, %156, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x44xi8>, tensor<268x1x1x44xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
-    %388 = tosa.rescale %387, %153, %152, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
-    %389 = tosa.clamp %388 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
-    %390 = tosa.reshape %151, %3 : (tensor<1x3x3x268xi8>, !tosa.shape<4>) -> tensor<3x3x268x1xi8>
-    %391 = tosa.depthwise_conv2d %389, %390, %150, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<3x3x268x1xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
-    %392 = tosa.rescale %391, %149, %148, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
-    %393 = tosa.clamp %392 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
-    %394 = tosa.conv2d %393, %147, %146, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<52x1x1x268xi8>, tensor<52xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x52xi32>
-    %395 = tosa.rescale %394, %144, %143, %283, %145 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<52xi32>, tensor<52xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
-    %396 = tosa.pad %386, %142, %141 : (tensor<1x8x8x44xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
-    %397 = tosa.rescale %396, %239, %238, %156, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
-    %398 = tosa.rescale %395, %239, %237, %145, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
-    %399 = tosa.rescale %398, %140, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
-    %400 = tosa.add %397, %399 : (tensor<1x8x8x52xi32>, tensor<1x8x8x52xi32>) -> tensor<1x8x8x52xi32>
-    %401 = tosa.rescale %400, %139, %186, %283, %232 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
-    %402 = tosa.conv2d %401, %138, %137, %232, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x52xi8>, tensor<268x1x1x52xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
-    %403 = tosa.rescale %402, %136, %135, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
-    %404 = tosa.clamp %403 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
-    %405 = tosa.reshape %134, %3 : (tensor<1x3x3x268xi8>, !tosa.shape<4>) -> tensor<3x3x268x1xi8>
-    %406 = tosa.depthwise_conv2d %404, %405, %133, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<3x3x268x1xi8>, tensor<268xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x268xi32>
-    %407 = tosa.rescale %406, %132, %131, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x268xi32>, tensor<268xi32>, tensor<268xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x268xi8>
-    %408 = tosa.clamp %407 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x268xi8>) -> tensor<1x8x8x268xi8>
-    %409 = tosa.conv2d %408, %130, %129, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x268xi8>, tensor<44x1x1x268xi8>, tensor<44xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x44xi32>
-    %410 = tosa.rescale %409, %128, %127, %283, %145 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x44xi32>, tensor<44xi32>, tensor<44xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x44xi8>
-    %411 = tosa.pad %410, %142, %126 : (tensor<1x8x8x44xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
-    %412 = tosa.rescale %401, %239, %238, %232, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
-    %413 = tosa.rescale %411, %239, %237, %145, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
-    %414 = tosa.rescale %413, %125, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x52xi32>
-    %415 = tosa.add %412, %414 : (tensor<1x8x8x52xi32>, tensor<1x8x8x52xi32>) -> tensor<1x8x8x52xi32>
-    %416 = tosa.rescale %415, %124, %186, %283, %123 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x52xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x52xi8>
-    %417 = tosa.conv2d %416, %122, %121, %123, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x52xi8>, tensor<192x1x1x52xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x192xi32>
-    %418 = tosa.rescale %417, %120, %119, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x192xi8>
-    %419 = tosa.clamp %418 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x192xi8>) -> tensor<1x8x8x192xi8>
-    %420 = tosa.reshape %118, %2 : (tensor<1x3x3x192xi8>, !tosa.shape<4>) -> tensor<3x3x192x1xi8>
-    %421 = tosa.depthwise_conv2d %419, %420, %117, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x192xi8>, tensor<3x3x192x1xi8>, tensor<192xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x192xi32>
-    %422 = tosa.rescale %421, %116, %115, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x192xi32>, tensor<192xi32>, tensor<192xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x192xi8>
-    %423 = tosa.clamp %422 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x192xi8>) -> tensor<1x8x8x192xi8>
-    %424 = tosa.conv2d %423, %114, %113, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x192xi8>, tensor<68x1x1x192xi8>, tensor<68xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x68xi32>
-    %425 = tosa.rescale %424, %112, %111, %283, %287 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<68xi32>, tensor<68xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
-    %426 = tosa.conv2d %425, %110, %109, %287, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x68xi8>, tensor<172x1x1x68xi8>, tensor<172xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x172xi32>
-    %427 = tosa.rescale %426, %108, %107, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x172xi32>, tensor<172xi32>, tensor<172xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x172xi8>
-    %428 = tosa.clamp %427 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x172xi8>) -> tensor<1x8x8x172xi8>
-    %429 = tosa.reshape %106, %1 : (tensor<1x3x3x172xi8>, !tosa.shape<4>) -> tensor<3x3x172x1xi8>
-    %430 = tosa.depthwise_conv2d %428, %429, %105, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x172xi8>, tensor<3x3x172x1xi8>, tensor<172xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x172xi32>
-    %431 = tosa.rescale %430, %104, %103, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x172xi32>, tensor<172xi32>, tensor<172xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x172xi8>
-    %432 = tosa.clamp %431 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x172xi8>) -> tensor<1x8x8x172xi8>
-    %433 = tosa.conv2d %432, %102, %101, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x172xi8>, tensor<68x1x1x172xi8>, tensor<68xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x68xi32>
-    %434 = tosa.rescale %433, %99, %98, %283, %100 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<68xi32>, tensor<68xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
-    %435 = tosa.rescale %425, %239, %237, %287, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
-    %436 = tosa.rescale %435, %97, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
-    %437 = tosa.rescale %434, %239, %238, %100, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
-    %438 = tosa.add %436, %437 : (tensor<1x8x8x68xi32>, tensor<1x8x8x68xi32>) -> tensor<1x8x8x68xi32>
-    %439 = tosa.rescale %438, %96, %186, %283, %95 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
-    %440 = tosa.conv2d %439, %94, %93, %95, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x68xi8>, tensor<172x1x1x68xi8>, tensor<172xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x172xi32>
-    %441 = tosa.rescale %440, %92, %91, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x172xi32>, tensor<172xi32>, tensor<172xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x172xi8>
-    %442 = tosa.clamp %441 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x172xi8>) -> tensor<1x8x8x172xi8>
-    %443 = tosa.reshape %90, %1 : (tensor<1x3x3x172xi8>, !tosa.shape<4>) -> tensor<3x3x172x1xi8>
-    %444 = tosa.depthwise_conv2d %442, %443, %89, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x8x8x172xi8>, tensor<3x3x172x1xi8>, tensor<172xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x172xi32>
-    %445 = tosa.rescale %444, %88, %87, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x172xi32>, tensor<172xi32>, tensor<172xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x172xi8>
-    %446 = tosa.clamp %445 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x172xi8>) -> tensor<1x8x8x172xi8>
-    %447 = tosa.conv2d %446, %86, %85, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x172xi8>, tensor<48x1x1x172xi8>, tensor<48xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x48xi32>
-    %448 = tosa.rescale %447, %83, %82, %283, %84 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x48xi32>, tensor<48xi32>, tensor<48xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x48xi8>
-    %449 = tosa.pad %448, %81, %80 : (tensor<1x8x8x48xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
-    %450 = tosa.rescale %439, %239, %238, %95, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
-    %451 = tosa.rescale %449, %239, %237, %84, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
-    %452 = tosa.rescale %451, %79, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x8x8x68xi32>
-    %453 = tosa.add %450, %452 : (tensor<1x8x8x68xi32>, tensor<1x8x8x68xi32>) -> tensor<1x8x8x68xi32>
-    %454 = tosa.rescale %453, %78, %186, %283, %77 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x68xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x68xi8>
-    %455 = tosa.conv2d %454, %76, %75, %77, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x8x8x68xi8>, tensor<288x1x1x68xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x8x8x288xi32>
-    %456 = tosa.rescale %455, %74, %73, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x8x8x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x8x8x288xi8>
-    %457 = tosa.clamp %456 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x8x8x288xi8>) -> tensor<1x8x8x288xi8>
-    %458 = tosa.reshape %72, %0 : (tensor<1x3x3x288xi8>, !tosa.shape<4>) -> tensor<3x3x288x1xi8>
-    %459 = tosa.depthwise_conv2d %457, %458, %71, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 2, 2>} : (tensor<1x8x8x288xi8>, tensor<3x3x288x1xi8>, tensor<288xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x288xi32>
-    %460 = tosa.rescale %459, %70, %69, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x288xi32>, tensor<288xi32>, tensor<288xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x288xi8>
-    %461 = tosa.clamp %460 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x288xi8>) -> tensor<1x4x4x288xi8>
-    %462 = tosa.conv2d %461, %68, %67, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x288xi8>, tensor<16x1x1x288xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x16xi32>
-    %463 = tosa.rescale %462, %65, %64, %283, %66 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x16xi8>
-    %464 = tosa.conv2d %463, %63, %62, %66, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x16xi8>, tensor<96x1x1x16xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
-    %465 = tosa.rescale %464, %61, %60, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
-    %466 = tosa.clamp %465 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
-    %467 = tosa.reshape %59, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
-    %468 = tosa.depthwise_conv2d %466, %467, %58, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
-    %469 = tosa.rescale %468, %57, %56, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
-    %470 = tosa.clamp %469 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
-    %471 = tosa.conv2d %470, %55, %54, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<16x1x1x96xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x16xi32>
-    %472 = tosa.rescale %471, %53, %52, %283, %95 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x16xi8>
-    %473 = tosa.rescale %463, %239, %237, %66, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x4x4x16xi32>
-    %474 = tosa.rescale %473, %51, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x4x4x16xi32>
-    %475 = tosa.rescale %472, %239, %238, %95, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x4x4x16xi32>
-    %476 = tosa.add %474, %475 : (tensor<1x4x4x16xi32>, tensor<1x4x4x16xi32>) -> tensor<1x4x4x16xi32>
-    %477 = tosa.rescale %476, %50, %186, %283, %49 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x16xi8>
-    %478 = tosa.conv2d %477, %48, %47, %49, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x16xi8>, tensor<96x1x1x16xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
-    %479 = tosa.rescale %478, %46, %45, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
-    %480 = tosa.clamp %479 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
-    %481 = tosa.reshape %44, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
-    %482 = tosa.depthwise_conv2d %480, %481, %43, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
-    %483 = tosa.rescale %482, %42, %41, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
-    %484 = tosa.clamp %483 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
-    %485 = tosa.conv2d %484, %40, %39, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<32x1x1x96xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x32xi32>
-    %486 = tosa.rescale %485, %38, %37, %283, %287 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x32xi8>
-    %487 = tosa.pad %477, %36, %35 : (tensor<1x4x4x16xi8>, !tosa.shape<8>, tensor<1xi8>) -> tensor<1x4x4x32xi8>
-    %488 = tosa.rescale %487, %239, %238, %49, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x4x4x32xi32>
-    %489 = tosa.rescale %486, %239, %237, %287, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<1x4x4x32xi32>
-    %490 = tosa.rescale %489, %34, %235, %283, %283 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi32>) -> tensor<1x4x4x32xi32>
-    %491 = tosa.add %488, %490 : (tensor<1x4x4x32xi32>, tensor<1x4x4x32xi32>) -> tensor<1x4x4x32xi32>
-    %492 = tosa.rescale %491, %33, %186, %283, %32 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x32xi8>
-    %493 = tosa.conv2d %492, %31, %30, %32, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x32xi8>, tensor<96x1x1x32xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
-    %494 = tosa.rescale %493, %29, %28, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
-    %495 = tosa.clamp %494 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
-    %496 = tosa.reshape %27, %5 : (tensor<1x3x3x96xi8>, !tosa.shape<4>) -> tensor<3x3x96x1xi8>
-    %497 = tosa.depthwise_conv2d %495, %496, %26, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<3x3x96x1xi8>, tensor<96xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x96xi32>
-    %498 = tosa.rescale %497, %25, %24, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x96xi32>, tensor<96xi32>, tensor<96xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x96xi8>
-    %499 = tosa.clamp %498 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x96xi8>) -> tensor<1x4x4x96xi8>
-    %500 = tosa.conv2d %499, %23, %22, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x96xi8>, tensor<32x1x1x96xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x32xi32>
-    %501 = tosa.rescale %500, %21, %20, %283, %202 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x32xi8>
-    %502 = tosa.conv2d %501, %19, %18, %202, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x32xi8>, tensor<128x1x1x32xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x128xi32>
-    %503 = tosa.rescale %502, %17, %16, %283, %282 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x4x4x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x4x4x128xi8>
-    %504 = tosa.clamp %503 {max_val = 127 : i8, min_val = -128 : i8} : (tensor<1x4x4x128xi8>) -> tensor<1x4x4x128xi8>
-    %505 = tosa.avg_pool2d %504, %287, %287 {acc_type = i32, kernel = array<i64: 4, 4>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 4, 4>} : (tensor<1x4x4x128xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x128xi8>
-    %506 = tosa.conv2d %505, %15, %14, %282, %287 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x1x1x128xi8>, tensor<2x1x1x128xi8>, tensor<2xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x1x1x2xi32>
-    %507 = tosa.rescale %506, %12, %11, %283, %13 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<1x1x1x2xi32>, tensor<2xi32>, tensor<2xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<1x1x1x2xi8>
-    %508 = tosa.reshape %507, %10 : (tensor<1x1x1x2xi8>, !tosa.shape<2>) -> tensor<1x2xi8>
-    return %508 : tensor<1x2xi8>
-  }
-}
diff --git a/tests/gold/test_python_api/yolov3_tiny_int8_pruned_backbone_only.mlir b/tests/gold/test_python_api/yolov3_tiny_int8_pruned_backbone_only.mlir
deleted file mode 100644
index 6457b20..0000000
--- a/tests/gold/test_python_api/yolov3_tiny_int8_pruned_backbone_only.mlir
+++ /dev/null
@@ -1,197 +0,0 @@
-module attributes {tf_saved_model.semantics, tfl.description = "MLIR Converted.", tfl.metadata = {min_runtime_version = "2.3.0\00\00\00\00\00\00\00\00\00\00\00"}, tfl.schema_version = 3 : i32} {
-  func.func @main(%arg0: tensor<?x416x416x3xi8> {tf_saved_model.index_path = ["input"]}) -> (tensor<?x26x26x3x85xi8> {tf_saved_model.index_path = ["yolo_output_1"]}, tensor<?x13x13x3x85xi8> {tf_saved_model.index_path = ["yolo_output_0"]}) attributes {tf.entry_function = {inputs = "serving_default_input:0", outputs = "StatefulPartitionedCall:1,StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {
-    %0 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<5xindex>} : () -> !tosa.shape<5>
-    %1 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi8>}> : () -> tensor<255xi8>
-    %2 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi32>}> : () -> tensor<255xi32>
-    %3 = "tosa.const"() <{values = dense<67> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %4 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi32>}> : () -> tensor<255xi32>
-    %5 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255x1x1x256xi8>}> : () -> tensor<255x1x1x256xi8>
-    %6 = "tosa.const"() <{values = dense<-100> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %7 = "tosa.const"() <{values = dense<2146540981> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %8 = "tosa.const"() <{values = dense<1717232810> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %9 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %10 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
-    %11 = "tosa.const"() <{values = dense<14> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %12 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
-    %13 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256x3x3x384xi8>}> : () -> tensor<256x3x3x384xi8>
-    %14 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<5xindex>} : () -> !tosa.shape<5>
-    %15 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi8>}> : () -> tensor<255xi8>
-    %16 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi32>}> : () -> tensor<255xi32>
-    %17 = "tosa.const"() <{values = dense<57> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %18 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255xi32>}> : () -> tensor<255xi32>
-    %19 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<255x1x1x512xi8>}> : () -> tensor<255x1x1x512xi8>
-    %20 = "tosa.const"() <{values = dense<-102> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %21 = "tosa.const"() <{values = dense<2045027926> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %22 = "tosa.const"() <{values = dense<1636022365> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %23 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi8>}> : () -> tensor<512xi8>
-    %24 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi32>}> : () -> tensor<512xi32>
-    %25 = "tosa.const"() <{values = dense<7> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %26 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi32>}> : () -> tensor<512xi32>
-    %27 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512x3x3x256xi8>}> : () -> tensor<512x3x3x256xi8>
-    %28 = tosa.const_shape  {values = dense<3> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %29 = tosa.const_shape  {values = dense<1> : tensor<2xindex>} : () -> !tosa.shape<2>
-    %30 = tosa.const_shape  {values = dense_resource<__elided__> : tensor<4xindex>} : () -> !tosa.shape<4>
-    %31 = "tosa.const"() <{values = dense<31> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %32 = "tosa.const"() <{values = dense<1867790575> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %33 = "tosa.const"() <{values = dense<34> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %34 = "tosa.const"() <{values = dense<1494232483> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %35 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
-    %36 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %37 = "tosa.const"() <{values = dense<-16> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %38 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %39 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x1x1x256xi8>}> : () -> tensor<128x1x1x256xi8>
-    %40 = "tosa.const"() <{values = dense<-95> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %41 = "tosa.const"() <{values = dense<1153990886> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %42 = "tosa.const"() <{values = dense<1846385445> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %43 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %44 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
-    %45 = "tosa.const"() <{values = dense<24> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %46 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
-    %47 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256x1x1x1024xi8>}> : () -> tensor<256x1x1x1024xi8>
-    %48 = "tosa.const"() <{values = dense<-98> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %49 = "tosa.const"() <{values = dense<1112539429> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %50 = "tosa.const"() <{values = dense<1780063113> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %51 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1024xi8>}> : () -> tensor<1024xi8>
-    %52 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1024xi32>}> : () -> tensor<1024xi32>
-    %53 = "tosa.const"() <{values = dense<19> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %54 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1024xi32>}> : () -> tensor<1024xi32>
-    %55 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<1024x3x3x512xi8>}> : () -> tensor<1024x3x3x512xi8>
-    %56 = "tosa.const"() <{values = dense<-99> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %57 = "tosa.const"() <{values = dense<1090607686> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %58 = "tosa.const"() <{values = dense<1744972324> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %59 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi8>}> : () -> tensor<512xi8>
-    %60 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi32>}> : () -> tensor<512xi32>
-    %61 = "tosa.const"() <{values = dense<16> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %62 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512xi32>}> : () -> tensor<512xi32>
-    %63 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<512x3x3x256xi8>}> : () -> tensor<512x3x3x256xi8>
-    %64 = "tosa.const"() <{values = dense<-108> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %65 = "tosa.const"() <{values = dense<1827454564> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %66 = "tosa.const"() <{values = dense<1461963673> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %67 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi8>}> : () -> tensor<256xi8>
-    %68 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
-    %69 = "tosa.const"() <{values = dense<-11> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %70 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256xi32>}> : () -> tensor<256xi32>
-    %71 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<256x3x3x128xi8>}> : () -> tensor<256x3x3x128xi8>
-    %72 = "tosa.const"() <{values = dense<-93> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %73 = "tosa.const"() <{values = dense<1199308892> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %74 = "tosa.const"() <{values = dense<1918894256> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %75 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi8>}> : () -> tensor<128xi8>
-    %76 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %77 = "tosa.const"() <{values = dense<28> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %78 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128xi32>}> : () -> tensor<128xi32>
-    %79 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<128x3x3x64xi8>}> : () -> tensor<128x3x3x64xi8>
-    %80 = "tosa.const"() <{values = dense<-85> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %81 = "tosa.const"() <{values = dense<1360529732> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %82 = "tosa.const"() <{values = dense<1088423802> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %83 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi8>}> : () -> tensor<64xi8>
-    %84 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
-    %85 = "tosa.const"() <{values = dense<44> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %86 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64xi32>}> : () -> tensor<64xi32>
-    %87 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<64x3x3x32xi8>}> : () -> tensor<64x3x3x32xi8>
-    %88 = "tosa.const"() <{values = dense<-74> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %89 = "tosa.const"() <{values = dense<29> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %90 = "tosa.const"() <{values = dense<1564368468> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %91 = "tosa.const"() <{values = dense<32> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %92 = "tosa.const"() <{values = dense<1251494793> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %93 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi8>}> : () -> tensor<32xi8>
-    %94 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %95 = "tosa.const"() <{values = dense<58> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %96 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32xi32>}> : () -> tensor<32xi32>
-    %97 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<32x3x3x16xi8>}> : () -> tensor<32x3x3x16xi8>
-    %98 = "tosa.const"() <{values = dense<-106> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %99 = "tosa.const"() <{values = dense<1073741824> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %100 = "tosa.const"() <{values = dense<30> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %101 = "tosa.const"() <{values = dense<1905935579> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %102 = "tosa.const"() <{values = dense<33> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %103 = "tosa.const"() <{values = dense<1524748486> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %104 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi8>}> : () -> tensor<16xi8>
-    %105 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %106 = "tosa.const"() <{values = dense<-4> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %107 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
-    %108 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16x3x3x3xi8>}> : () -> tensor<16x3x3x3xi8>
-    %109 = "tosa.const"() <{values = dense_resource<__elided__> : tensor<16xi32>}> : () -> tensor<16xi32>
-    %110 = "tosa.const"() <{values = dense<-128> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %111 = "tosa.const"() <{values = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
-    %112 = tosa.conv2d %arg0, %108, %109, %110, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x416x416x3xi8>, tensor<16x3x3x3xi8>, tensor<16xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x416x416x16xi32>
-    %113 = tosa.rescale %112, %105, %104, %107, %106 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x416x416x16xi32>, tensor<16xi32>, tensor<16xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x416x416x16xi8>
-    %114 = tosa.rescale %113, %103, %102, %106, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x416x416x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x416x416x16xi32>
-    %115 = tosa.rescale %113, %101, %100, %106, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x416x416x16xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x416x416x16xi32>
-    %116 = tosa.maximum %115, %114 : (tensor<?x416x416x16xi32>, tensor<?x416x416x16xi32>) -> tensor<?x416x416x16xi32>
-    %117 = tosa.rescale %116, %99, %100, %107, %98 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x416x416x16xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x416x416x16xi8>
-    %118 = tosa.max_pool2d %117 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x416x416x16xi8>) -> tensor<?x208x208x16xi8>
-    %119 = tosa.conv2d %118, %97, %96, %98, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x208x208x16xi8>, tensor<32x3x3x16xi8>, tensor<32xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x208x208x32xi32>
-    %120 = tosa.rescale %119, %94, %93, %107, %95 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x208x208x32xi32>, tensor<32xi32>, tensor<32xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x208x208x32xi8>
-    %121 = tosa.rescale %120, %92, %91, %95, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x208x208x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x208x208x32xi32>
-    %122 = tosa.rescale %120, %90, %89, %95, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x208x208x32xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x208x208x32xi32>
-    %123 = tosa.maximum %122, %121 : (tensor<?x208x208x32xi32>, tensor<?x208x208x32xi32>) -> tensor<?x208x208x32xi32>
-    %124 = tosa.rescale %123, %99, %100, %107, %88 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x208x208x32xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x208x208x32xi8>
-    %125 = tosa.max_pool2d %124 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x208x208x32xi8>) -> tensor<?x104x104x32xi8>
-    %126 = tosa.conv2d %125, %87, %86, %88, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x104x104x32xi8>, tensor<64x3x3x32xi8>, tensor<64xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x104x104x64xi32>
-    %127 = tosa.rescale %126, %84, %83, %107, %85 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x104x104x64xi32>, tensor<64xi32>, tensor<64xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x104x104x64xi8>
-    %128 = tosa.rescale %127, %82, %91, %85, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x104x104x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x104x104x64xi32>
-    %129 = tosa.rescale %127, %81, %89, %85, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x104x104x64xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x104x104x64xi32>
-    %130 = tosa.maximum %129, %128 : (tensor<?x104x104x64xi32>, tensor<?x104x104x64xi32>) -> tensor<?x104x104x64xi32>
-    %131 = tosa.rescale %130, %99, %100, %107, %80 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x104x104x64xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x104x104x64xi8>
-    %132 = tosa.max_pool2d %131 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x104x104x64xi8>) -> tensor<?x52x52x64xi8>
-    %133 = tosa.conv2d %132, %79, %78, %80, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x52x52x64xi8>, tensor<128x3x3x64xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x52x52x128xi32>
-    %134 = tosa.rescale %133, %76, %75, %107, %77 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x52x52x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x52x52x128xi8>
-    %135 = tosa.rescale %134, %74, %102, %77, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x52x52x128xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x52x52x128xi32>
-    %136 = tosa.rescale %134, %73, %89, %77, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x52x52x128xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x52x52x128xi32>
-    %137 = tosa.maximum %136, %135 : (tensor<?x52x52x128xi32>, tensor<?x52x52x128xi32>) -> tensor<?x52x52x128xi32>
-    %138 = tosa.rescale %137, %99, %100, %107, %72 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x52x52x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x52x52x128xi8>
-    %139 = tosa.max_pool2d %138 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x52x52x128xi8>) -> tensor<?x26x26x128xi8>
-    %140 = tosa.conv2d %139, %71, %70, %72, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x26x26x128xi8>, tensor<256x3x3x128xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x26x26x256xi32>
-    %141 = tosa.rescale %140, %68, %67, %107, %69 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x256xi8>
-    %142 = tosa.rescale %141, %66, %102, %69, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x26x26x256xi32>
-    %143 = tosa.rescale %141, %65, %100, %69, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x26x26x256xi32>
-    %144 = tosa.maximum %143, %142 : (tensor<?x26x26x256xi32>, tensor<?x26x26x256xi32>) -> tensor<?x26x26x256xi32>
-    %145 = tosa.rescale %144, %99, %100, %107, %64 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x256xi8>
-    %146 = tosa.max_pool2d %145 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 2>} : (tensor<?x26x26x256xi8>) -> tensor<?x13x13x256xi8>
-    %147 = tosa.conv2d %146, %63, %62, %64, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x13x13x256xi8>, tensor<512x3x3x256xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x512xi32>
-    %148 = tosa.rescale %147, %60, %59, %107, %61 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x512xi8>
-    %149 = tosa.rescale %148, %58, %102, %61, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x512xi32>
-    %150 = tosa.rescale %148, %57, %89, %61, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x512xi32>
-    %151 = tosa.maximum %150, %149 : (tensor<?x13x13x512xi32>, tensor<?x13x13x512xi32>) -> tensor<?x13x13x512xi32>
-    %152 = tosa.rescale %151, %99, %100, %107, %56 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x512xi8>
-    %153 = tosa.max_pool2d %152 {kernel = array<i64: 2, 2>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} : (tensor<?x13x13x512xi8>) -> tensor<?x13x13x512xi8>
-    %154 = tosa.conv2d %153, %55, %54, %56, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x13x13x512xi8>, tensor<1024x3x3x512xi8>, tensor<1024xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x1024xi32>
-    %155 = tosa.rescale %154, %52, %51, %107, %53 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x1024xi32>, tensor<1024xi32>, tensor<1024xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x1024xi8>
-    %156 = tosa.rescale %155, %50, %102, %53, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x1024xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x1024xi32>
-    %157 = tosa.rescale %155, %49, %89, %53, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x1024xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x1024xi32>
-    %158 = tosa.maximum %157, %156 : (tensor<?x13x13x1024xi32>, tensor<?x13x13x1024xi32>) -> tensor<?x13x13x1024xi32>
-    %159 = tosa.rescale %158, %99, %100, %107, %48 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x1024xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x1024xi8>
-    %160 = tosa.conv2d %159, %47, %46, %48, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x13x13x1024xi8>, tensor<256x1x1x1024xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x256xi32>
-    %161 = tosa.rescale %160, %44, %43, %107, %45 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x256xi8>
-    %162 = tosa.rescale %161, %42, %102, %45, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x256xi32>
-    %163 = tosa.rescale %161, %41, %89, %45, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x256xi32>
-    %164 = tosa.maximum %163, %162 : (tensor<?x13x13x256xi32>, tensor<?x13x13x256xi32>) -> tensor<?x13x13x256xi32>
-    %165 = tosa.rescale %164, %99, %100, %107, %40 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x256xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x256xi8>
-    %166 = tosa.conv2d %165, %39, %38, %40, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x13x13x256xi8>, tensor<128x1x1x256xi8>, tensor<128xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x128xi32>
-    %167 = tosa.rescale %166, %36, %35, %107, %37 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x128xi32>, tensor<128xi32>, tensor<128xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x128xi8>
-    %168 = tosa.rescale %167, %34, %33, %37, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x128xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x128xi32>
-    %169 = tosa.rescale %167, %32, %31, %37, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x128xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x128xi32>
-    %170 = tosa.maximum %169, %168 : (tensor<?x13x13x128xi32>, tensor<?x13x13x128xi32>) -> tensor<?x13x13x128xi32>
-    %171 = tosa.rescale %170, %99, %100, %107, %64 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x128xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x128xi8>
-    %172 = tosa.resize %171, %30, %29, %28 {mode = "NEAREST_NEIGHBOR"} : (tensor<?x13x13x128xi8>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<?x26x26x128xi8>
-    %173 = tosa.concat %172, %145 {axis = 3 : i32} : (tensor<?x26x26x128xi8>, tensor<?x26x26x256xi8>) -> tensor<?x26x26x384xi8>
-    %174 = tosa.conv2d %165, %27, %26, %40, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x13x13x256xi8>, tensor<512x3x3x256xi8>, tensor<512xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x512xi32>
-    %175 = tosa.rescale %174, %24, %23, %107, %25 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi32>, tensor<512xi32>, tensor<512xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x512xi8>
-    %176 = tosa.rescale %175, %22, %102, %25, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x512xi32>
-    %177 = tosa.rescale %175, %21, %100, %25, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x13x13x512xi32>
-    %178 = tosa.maximum %177, %176 : (tensor<?x13x13x512xi32>, tensor<?x13x13x512xi32>) -> tensor<?x13x13x512xi32>
-    %179 = tosa.rescale %178, %99, %100, %107, %20 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x512xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x512xi8>
-    %180 = tosa.conv2d %179, %19, %18, %20, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x13x13x512xi8>, tensor<255x1x1x512xi8>, tensor<255xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x13x13x255xi32>
-    %181 = tosa.rescale %180, %16, %15, %107, %17 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x13x13x255xi32>, tensor<255xi32>, tensor<255xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x13x13x255xi8>
-    %182 = tosa.reshape %181, %14 : (tensor<?x13x13x255xi8>, !tosa.shape<5>) -> tensor<?x13x13x3x85xi8>
-    %183 = tosa.conv2d %173, %13, %12, %64, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 1, 1, 1, 1>, stride = array<i64: 1, 1>} : (tensor<?x26x26x384xi8>, tensor<256x3x3x384xi8>, tensor<256xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x26x26x256xi32>
-    %184 = tosa.rescale %183, %10, %9, %107, %11 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi32>, tensor<256xi32>, tensor<256xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x256xi8>
-    %185 = tosa.rescale %184, %8, %102, %11, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x26x26x256xi32>
-    %186 = tosa.rescale %184, %7, %100, %11, %107 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi32>) -> tensor<?x26x26x256xi32>
-    %187 = tosa.maximum %186, %185 : (tensor<?x26x26x256xi32>, tensor<?x26x26x256xi32>) -> tensor<?x26x26x256xi32>
-    %188 = tosa.rescale %187, %99, %100, %107, %6 {input_unsigned = false, output_unsigned = false, per_channel = false, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x256xi32>, tensor<1xi32>, tensor<1xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x256xi8>
-    %189 = tosa.conv2d %188, %5, %4, %6, %111 {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x26x26x256xi8>, tensor<255x1x1x256xi8>, tensor<255xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<?x26x26x255xi32>
-    %190 = tosa.rescale %189, %2, %1, %107, %3 {input_unsigned = false, output_unsigned = false, per_channel = true, rounding_mode = "DOUBLE_ROUND", scale32 = true} : (tensor<?x26x26x255xi32>, tensor<255xi32>, tensor<255xi8>, tensor<1xi32>, tensor<1xi8>) -> tensor<?x26x26x255xi8>
-    %191 = tosa.reshape %190, %0 : (tensor<?x26x26x255xi8>, !tosa.shape<5>) -> tensor<?x26x26x3x85xi8>
-    return %191, %182 : tensor<?x26x26x3x85xi8>, tensor<?x13x13x3x85xi8>
-  }
-}
diff --git a/tests/test_python_api.py b/tests/test_python_api.py
index a2fce6a..275d524 100644
--- a/tests/test_python_api.py
+++ b/tests/test_python_api.py
@@ -7,25 +7,22 @@
 Test suite for the `tosa-converter-for-tflite` Python API.
 
 To run tests with logging:
-    TOSA_TEST_ELIDE=1 pytest tests/test_python_api.py -v --log-cli-level=DEBUG
+    pytest tests/test_python_api.py -v --log-cli-level=DEBUG
 
 To add a new model spec:
   1. Edit `tests/test_python_api.hjson`, adding an entry with:
        - name (str): unique spec identifier
        - path (str): relative model path in Arm ML Zoo repo
-  2. Place the corresponding golden MLIR file under `tests/gold/test_python_api/<name>.mlir`, normalised for whitespace.
 
 Tests cover:
   - File based & stream based conversion
   - Bytecode vs text output via `TosaConverterOutputFormat`
-  - MLIR text regression
   - Error cases: invalid sink types, truncated inputs, invalid format args
   - Pre-commit sanity checks
 """
 import io
 import logging
 import os
-import shutil
 import subprocess
 from functools import lru_cache
 from pathlib import Path
@@ -48,8 +45,6 @@ logger = logging.getLogger(__name__)
 # -----------------------------------------------------------------------------
 TEST_ROOT: Path = Path(__file__).parent
 MANIFEST_FILE: Path = TEST_ROOT / "test_python_api.hjson"
-GOLDEN_DIR: Path = TEST_ROOT / "gold" / "test_python_api"
-GENERATED_DIR: Path = TEST_ROOT / "generated" / "test_python_api"
 # Model-Zoo repo details
 MODEL_ZOO_REPO_DIR_PATH: str = os.environ.get("MODEL_ZOO_REPO_DIR_PATH")
 MODEL_ZOO_REPO_URL: str = "https://github.com/Arm-Examples/ML-zoo.git"
@@ -81,33 +76,6 @@ def normalise_lines(lines: List[str]) -> List[str]:
     return normalised
 
 
-def assert_mlir_matches_golden(name: str, gen_path: Path) -> None:
-    """
-    Compare generated MLIR file to golden, after normalization.
-    Always copy generated MLIR to GENERATED_DIR for missing or mismatched cases.
-    """
-    golden_path = GOLDEN_DIR / f"{name}.mlir"
-    dump_path = GENERATED_DIR / f"{name}.mlir"
-
-    # If golden missing or content mismatched, dump and report
-    if not golden_path.exists():
-        shutil.copy(gen_path, dump_path)
-        pytest.fail(
-            f"Golden MLIR missing for '{name}'; generated file dumped to {dump_path}"
-        )
-
-    gold_lines = normalise_lines(golden_path.read_text().splitlines())
-    gen_lines = normalise_lines(gen_path.read_text().splitlines())
-    if gen_lines != gold_lines:
-        shutil.copy(gen_path, dump_path)
-        logger.error(f"MLIR regression detected for '{name}'")
-        pytest.fail(f"MLIR regression for '{name}'; see dumped file {dump_path}")
-
-    logger.debug(f"MLIR matches golden for '{name}'")
-    # Clean up any leftover dump
-    dump_path.unlink(missing_ok=True)
-
-
 # -----------------------------------------------------------------------------
 # Parametrise specs dynamically
 # -----------------------------------------------------------------------------
@@ -188,15 +156,6 @@ def tflite_files(
     return mapping
 
 
-@pytest.fixture(autouse=True, scope="session")
-def clear_generated_dir() -> None:
-    """Clean or create the generated_mlir directory once before any tests run."""
-    if GENERATED_DIR.exists():
-        shutil.rmtree(GENERATED_DIR)
-    GENERATED_DIR.mkdir(parents=True, exist_ok=True)
-    logger.debug(f"Prepared clean generated directory at {GENERATED_DIR}")
-
-
 # -----------------------------------------------------------------------------
 # Module scoped fixtures
 # -----------------------------------------------------------------------------
@@ -239,22 +198,6 @@ def test_bytecode_filesystem(
     logger.debug(f"Created bytecode file {out_file} ({out_file.stat().st_size} bytes)")
 
 
-@pytest.mark.slow
-@pytest.mark.python_api
-def test_mlir_text_regression(
-    tmp_path: Path, spec: Dict[str, Any], tflite_file: Path
-) -> None:
-    """Generate MLIR text and compare against golden MLIR text files."""
-    name = spec["name"]
-    gen_tmp = tmp_path / f"{name}.mlir"
-    logger.info(f"Testing MLIR text regression for '{name}'")
-    tflite_flatbuffer_to_tosa_mlir(
-        str(tflite_file), str(gen_tmp), TosaConverterOutputFormat.Text
-    )
-    assert gen_tmp.exists(), f"Generated MLIR missing: {gen_tmp}"
-    assert_mlir_matches_golden(name, gen_tmp)
-
-
 @pytest.mark.python_api
 def test_bytecode_stream_vs_filesystem(
     tmp_path: Path, sample_tflite_file: Path
-- 
GitLab


From a194f5e54f30be9149b2ea8cee5d97e3e5b740d4 Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Wed, 16 Jul 2025 09:29:59 +0100
Subject: [PATCH 7/9] chore(Python API Tests): remove sanity tests for large
 models from model zoo

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 setup.cfg                   |   1 -
 tests/README.md             |  13 +--
 tests/test_python_api.hjson |  62 -----------
 tests/test_python_api.py    | 199 ++++++------------------------------
 4 files changed, 35 insertions(+), 240 deletions(-)
 delete mode 100644 tests/test_python_api.hjson

diff --git a/setup.cfg b/setup.cfg
index 98e793f..f861493 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -23,4 +23,3 @@ markers =
     cli: marks tests of the command-line interface
     python_api: marks tests of the Python API
     pre_commit: marks tests to be run in pre-commit
-    slow: marks tests that take more time to run
diff --git a/tests/README.md b/tests/README.md
index 099dc15..a5ba9ed 100644
--- a/tests/README.md
+++ b/tests/README.md
@@ -65,7 +65,6 @@ The Python API test suite exercises the `tflite_flatbuffer_to_tosa_mlir` wrapper
 
 ### Python API Test Definition
 
-- **Model specs** live in `tests/test_python_api_models.hjson`
 - **Test script** is `tests/test_python_api.py`
 
 ### Run Python API Tests
@@ -76,17 +75,7 @@ pytest tests/test_python_api.py -v --log-cli-level=DEBUG
 
 ### Adding a Python API Test
 
-1. **Add a new model spec** to `tests/test_python_api_models.hjson`:
-
-   ```hjson
-   {
-     name: "my_new_model"
-     class: "MyModelClass"
-     input_shape: [128, 128, 3]
-   }
-   ```
-
-2. **(Optional)** Extend `tests/test_python_api.py` with additional tests:
+To add a new text extend `tests/test_python_api.py` with additional tests:
 
    ```python
    def test_some_new_behavior(...):
diff --git a/tests/test_python_api.hjson b/tests/test_python_api.hjson
deleted file mode 100644
index 2111485..0000000
--- a/tests/test_python_api.hjson
+++ /dev/null
@@ -1,62 +0,0 @@
-#
-# SPDX-FileCopyrightText: Copyright 2025 Arm Limited and/or its affiliates <open-source-office@arm.com>
-#
-# SPDX-License-Identifier: Apache-2.0
-#
-
-# Model manifest for Python API tests.
-# Each entry must include:
-#   - name: a unique identifier for the model spec
-#   - path: the relative model path in the ML Zoo repository
-
-[
-  {
-    "name": "ad_small_int8",
-    "path": "models/anomaly_detection/micronet_small/tflite_int8/ad_small_int8.tflite"
-  },
-  {
-    "name": "ds_cnn_s_quantized_int16",
-    "path": "models/keyword_spotting/ds_cnn_small/model_package_tf/model_archive/TFLite/tflite_int16/ds_cnn_s_quantized_int16.tflite"
-  },
-  {
-    "name": "kws_micronet_s",
-    "path": "models/keyword_spotting/micronet_small/tflite_int8/kws_micronet_s.tflite"
-  },
-  {
-    "name": "tiny_wav2letter_pruned_int8",
-    "path": "models/speech_recognition/tiny_wav2letter/tflite_pruned_int8/tiny_wav2letter_pruned_int8.tflite"
-  },
-  {
-    "name": "yolov3_tiny_int8_pruned_backbone_only",
-    "path": "models/experimental/yolov3_tiny_int8_pruned_backbone_only/yolov3_tiny_int8_pruned_backbone_only.tflite"
-  },
-  {
-    "name": "cnn_s_quantized",
-    "path": "models/keyword_spotting/cnn_small/model_package_tf/model_archive/TFLite/tflite_int8/cnn_s_quantized.tflite"
-  },
-  {
-    "name": "efficientnet_lite0_224",
-    "path": "models/experimental/efficientnet_lite0_224/efficientnet_lite0_224.tflite"
-  },
-  {
-    "name": "mobilenet_v2_1.0_224_quantized_1_default_1",
-    "path": "models/image_classification/mobilenet_v2_1.0_224/tflite_uint8/mobilenet_v2_1.0_224_quantized_1_default_1.tflite"
-  },
-  {
-    "name": "vww4_128_128_INT8",
-    "path": "models/visual_wake_words/micronet_vww4/tflite_int8/vww4_128_128_INT8.tflite"
-  },
-  {
-    "name": "dnn_s_quantized",
-    "path": "models/keyword_spotting/dnn_small/model_package_tf/model_archive/TFLite/tflite_int8/dnn_s_quantized.tflite"
-  },
-  {
-    "name": "har_int8",
-    "path": "models/experimental/har_cnn/har_int8.tflite"
-  },
-  {
-    "name": "ssd_mobilenet_v3_int8",
-    "path": "models/experimental/ssd_mobilenet_v3_int8/ssd_mobilenet_v3_int8.tflite"
-  },
-
-]
diff --git a/tests/test_python_api.py b/tests/test_python_api.py
index 275d524..f66618b 100644
--- a/tests/test_python_api.py
+++ b/tests/test_python_api.py
@@ -9,11 +9,6 @@ Test suite for the `tosa-converter-for-tflite` Python API.
 To run tests with logging:
     pytest tests/test_python_api.py -v --log-cli-level=DEBUG
 
-To add a new model spec:
-  1. Edit `tests/test_python_api.hjson`, adding an entry with:
-       - name (str): unique spec identifier
-       - path (str): relative model path in Arm ML Zoo repo
-
 Tests cover:
   - File based & stream based conversion
   - Bytecode vs text output via `TosaConverterOutputFormat`
@@ -22,15 +17,9 @@ Tests cover:
 """
 import io
 import logging
-import os
-import subprocess
-from functools import lru_cache
 from pathlib import Path
 from typing import Any
-from typing import Dict
-from typing import List
 
-import hjson
 import pytest
 from tosa_converter_for_tflite import tflite_flatbuffer_to_tosa_mlir
 from tosa_converter_for_tflite import TosaConverterOutputFormat
@@ -40,168 +29,49 @@ from tosa_converter_for_tflite import TosaConverterOutputFormat
 # -----------------------------------------------------------------------------
 logger = logging.getLogger(__name__)
 
-# -----------------------------------------------------------------------------
-# Constants & paths
-# -----------------------------------------------------------------------------
-TEST_ROOT: Path = Path(__file__).parent
-MANIFEST_FILE: Path = TEST_ROOT / "test_python_api.hjson"
-# Model-Zoo repo details
-MODEL_ZOO_REPO_DIR_PATH: str = os.environ.get("MODEL_ZOO_REPO_DIR_PATH")
-MODEL_ZOO_REPO_URL: str = "https://github.com/Arm-Examples/ML-zoo.git"
-MODEL_ZOO_BRANCH: str = "master"
-MODEL_ZOO_REPO_DIR_NAME: str = "ml_zoo_repo"
-
-
-# -----------------------------------------------------------------------------
-# Helper functions
-# -----------------------------------------------------------------------------
-@lru_cache
-def load_manifest() -> List[Dict[str, Any]]:
-    """Parse the model manifest file into a list of dictionaries."""
-    text = MANIFEST_FILE.read_text(encoding="utf-8")
-    specs = hjson.loads(text)
-    logger.debug(f"Loaded {len(specs)} specs from manifest")
-    return specs
-
-
-def normalise_lines(lines: List[str]) -> List[str]:
-    """Strip trailing whitespace, drop blank lines."""
-    normalised = []
-    for ln in lines:
-        # Strip trailing whitespace
-        ln = ln.rstrip()
-        # Skip blank lines
-        if ln:
-            normalised.append(ln)
-    return normalised
-
-
-# -----------------------------------------------------------------------------
-# Parametrise specs dynamically
-# -----------------------------------------------------------------------------
-def pytest_generate_tests(metafunc: pytest.Metafunc) -> None:
-    """Parametrise all tests that accept 'spec' with entries from the manifest."""
-    if "spec" in metafunc.fixturenames:
-        if not MANIFEST_FILE.is_file():
-            pytest.skip(f"Manifest not found at {MANIFEST_FILE}")
-        specs = load_manifest()
-        ids = [s.get("name", "<unknown>") for s in specs]
-        metafunc.parametrize("spec", specs, ids=ids)
-
 
 # -----------------------------------------------------------------------------
 # Session scoped fixtures
 # -----------------------------------------------------------------------------
 @pytest.fixture(scope="session")
-def manifest() -> List[Dict[str, Any]]:
-    """Session scoped fixture: parsed list of model specs."""
-    return load_manifest()
-
-
-@pytest.fixture(scope="session")
-def tflite_files(
-    tmp_path_factory: pytest.TempPathFactory,
-    manifest: List[Dict[str, Any]],
-) -> Dict[str, Path]:
-    """
-    Get .tflite model files from Model Zoo repo or from MODEL_ZOO_DIR env if provided.
-    Returns mapping spec_name to .tflite Path.
-    """
-    # Use existing repo if provided
-    if MODEL_ZOO_REPO_DIR_PATH:
-        repo_dir = Path(MODEL_ZOO_REPO_DIR_PATH)
-        if not repo_dir.is_dir():
-            pytest.skip(
-                f"MODEL_ZOO_DIR set to '{MODEL_ZOO_REPO_DIR_PATH}', but it is not a directory"
-            )
-        logger.info(f"Using existing Model Zoo at {repo_dir}")
-    else:
-        # Clone into a fresh temp dir
-        repo_dir = tmp_path_factory.mktemp(MODEL_ZOO_REPO_DIR_NAME)
-        subprocess.run(
-            [
-                "git",
-                "clone",
-                f"--branch={MODEL_ZOO_BRANCH}",
-                "--depth=1",
-                MODEL_ZOO_REPO_URL,
-                str(repo_dir),
-            ],
-            check=True,
-        )
-        subprocess.run(
-            ["git", "-C", str(repo_dir), "sparse-checkout", "init", "--cone"],
-            check=True,
-        )
-        dirs_to_include = sorted({Path(spec["path"]).parent for spec in manifest})
-        subprocess.run(
-            ["git", "-C", str(repo_dir), "sparse-checkout", "set", *dirs_to_include],
-            check=True,
-        )
-
-    # Build index of available models
-    models = {p.stem: p for p in repo_dir.rglob("*.tflite")}
-    mapping: Dict[str, Path] = {}
-    missing: List[str] = []
-    for spec in manifest:
-        name = spec["name"]
-        model_path = models.get(name)
-        if not model_path:
-            missing.append(name)
-        else:
-            mapping[name] = model_path
-            logger.debug("Selected model %s at %s", name, model_path)
-    if missing:
-        logger.warning("Skipping missing models: %s", missing)
-    return mapping
-
-
-# -----------------------------------------------------------------------------
-# Module scoped fixtures
-# -----------------------------------------------------------------------------
-@pytest.fixture(scope="module")
-def sample_tflite_file(
-    manifest: List[Dict[str, Any]], tflite_files: Dict[str, Path]
-) -> Path:
-    """
-    Pick one model from the manifest (the first) and return its .tflite path.
-    """
-    name = manifest[0]["name"]
-    return tflite_files[name]
-
+def mobilenet_tflite(tmp_path_factory) -> Path:
+    """Build a MobileNetV3Small TFLite model for testing."""
+    # Skip if TensorFlow isn't available
+    tf = pytest.importorskip(
+        "tensorflow", reason="TensorFlow is required for TFLite conversion"
+    )
+    # 1) Load the pretrained Keras model
+    keras_model = tf.keras.applications.MobileNetV3Small(
+        weights="imagenet", input_shape=(224, 224, 3)
+    )
+    # 2) Convert it to TFLite
+    converter = tf.lite.TFLiteConverter.from_keras_model(keras_model)
+    tflite_bytes = converter.convert()
 
-# -----------------------------------------------------------------------------
-# Function scoped fixtures
-# -----------------------------------------------------------------------------
-@pytest.fixture
-def tflite_file(spec: Dict[str, Any], tflite_files: Dict[str, Path]) -> Path:
-    """Lookup the prebuilt .tflite for this spec, skip tests if missing."""
-    name = spec["name"]
-    if name not in tflite_files:
-        pytest.skip(f"Skipping '{name}': model not available")
-    return tflite_files[name]
+    # 3) Write it out to a temp .tflite file
+    model_dir = tmp_path_factory.mktemp("tflite_model")
+    model_path = model_dir / "mobilenet_v3_small_1.0_224.tflite"
+    model_path.write_bytes(tflite_bytes)
+    logger.info("TFLite model written to %s", model_path)
+    return model_path
 
 
 # -----------------------------------------------------------------------------
 # Tests
 # -----------------------------------------------------------------------------
 @pytest.mark.python_api
-def test_bytecode_filesystem(
-    tmp_path: Path, spec: Dict[str, Any], tflite_file: Path
-) -> None:
+def test_bytecode_filesystem(tmp_path: Path, mobilenet_tflite: Path) -> None:
     """Ensure that file based bytecode conversion creates a non empty .tosa.mlirbc file."""
-    out_file = tmp_path / f"{spec['name']}.tosa.mlirbc"
-    logger.info(f"Testing filesystem bytecode output for '{spec['name']}'")
-    tflite_flatbuffer_to_tosa_mlir(str(tflite_file), str(out_file))
+    out_file = tmp_path / f"{__name__}.tosa.mlirbc"
+    logger.info(f"Testing filesystem bytecode output for '{__name__}'")
+    tflite_flatbuffer_to_tosa_mlir(str(mobilenet_tflite), str(out_file))
     assert out_file.exists(), "Output file not created"
     assert out_file.stat().st_size > 0, "Output file is empty"
     logger.debug(f"Created bytecode file {out_file} ({out_file.stat().st_size} bytes)")
 
 
 @pytest.mark.python_api
-def test_bytecode_stream_vs_filesystem(
-    tmp_path: Path, sample_tflite_file: Path
-) -> None:
+def test_bytecode_stream_vs_filesystem(tmp_path: Path, mobilenet_tflite: Path) -> None:
     """Verify that in memory bytecode == file based bytecode and flush() was called."""
     buf = io.BytesIO()
     called = False
@@ -213,7 +83,7 @@ def test_bytecode_stream_vs_filesystem(
     buf.flush = _flush
 
     tflite_flatbuffer_to_tosa_mlir(
-        str(sample_tflite_file), buf, TosaConverterOutputFormat.Bytecode
+        str(mobilenet_tflite), buf, TosaConverterOutputFormat.Bytecode
     )
     data_stream = buf.getvalue()
     assert data_stream, "In memory bytecode is empty"
@@ -221,7 +91,7 @@ def test_bytecode_stream_vs_filesystem(
 
     fs_path = tmp_path / "sample_fs.tosa.mlirbc"
     tflite_flatbuffer_to_tosa_mlir(
-        str(sample_tflite_file), str(fs_path), TosaConverterOutputFormat.Bytecode
+        str(mobilenet_tflite), str(fs_path), TosaConverterOutputFormat.Bytecode
     )
     data_file = fs_path.read_bytes()
 
@@ -238,16 +108,16 @@ def test_missing_input_file(tmp_path: Path):
 
 @pytest.mark.python_api
 @pytest.mark.parametrize("sink", [123, None, 5.6])
-def test_invalid_sink(sample_tflite_file: Path, sink: Any) -> None:
+def test_invalid_sink(mobilenet_tflite: Path, sink: Any) -> None:
     """Passing a non path, non stream sink should raise TypeError."""
     with pytest.raises(TypeError):
-        tflite_flatbuffer_to_tosa_mlir(str(sample_tflite_file), sink)
+        tflite_flatbuffer_to_tosa_mlir(str(mobilenet_tflite), sink)
 
 
 @pytest.mark.python_api
-def test_truncated_tflite(tmp_path: Path, sample_tflite_file: Path) -> None:
+def test_truncated_tflite(tmp_path: Path, mobilenet_tflite: Path) -> None:
     """A truncated .tflite input should cause a RuntimeError."""
-    data = sample_tflite_file.read_bytes()
+    data = mobilenet_tflite.read_bytes()
     trunc = data[: len(data) // 2]
     trunc_path = tmp_path / "trunc.tflite"
     trunc_path.write_bytes(trunc)
@@ -259,18 +129,17 @@ def test_truncated_tflite(tmp_path: Path, sample_tflite_file: Path) -> None:
 
 @pytest.mark.python_api
 @pytest.mark.parametrize("fmt", [123, "bogus", None])
-def test_invalid_format(tmp_path: Path, sample_tflite_file: Path, fmt: Any) -> None:
+def test_invalid_format(tmp_path: Path, mobilenet_tflite: Path, fmt: Any) -> None:
     """Passing an invalid format argument should raise TypeError or ValueError."""
     with pytest.raises((TypeError, ValueError)):
         tflite_flatbuffer_to_tosa_mlir(
-            str(sample_tflite_file), str(tmp_path / "invalid_format.tosa.mlirbc"), fmt
+            str(mobilenet_tflite), str(tmp_path / "invalid_format.tosa.mlirbc"), fmt
         )
 
 
 @pytest.mark.python_api
 @pytest.mark.pre_commit
-def test_precommit_sanity(manifest: List[Dict[str, Any]]) -> None:
-    """Sanity check for pre-commit: manifest must not be empty and API callable."""
+def test_precommit_sanity() -> None:
+    """Sanity check for pre-commit: API should be callable."""
     logger.info("Running pre-commit sanity checks")
-    assert manifest, "Manifest is empty"
     assert callable(tflite_flatbuffer_to_tosa_mlir), "API function missing"
-- 
GitLab


From 02ad517694e280d076dc26fbcde5e0dd82257ebb Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Fri, 18 Jul 2025 12:47:20 +0100
Subject: [PATCH 8/9] docs(tests): update install instructions to use
 requirements.txt

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 tests/README.md | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/tests/README.md b/tests/README.md
index a5ba9ed..f655924 100644
--- a/tests/README.md
+++ b/tests/README.md
@@ -10,14 +10,10 @@ This document summarises the test coverage for the tosa-converter-for-tflite pro
 
 ## Requirements to run Tests
 
-- Python >= 3.9
-- pytest >= 7.0
-- hjson >= 3.0
-
-Install dependencies with:
+Install the dependencies with:
 
 ```bash
-pip install pytest==8.4.1 hjson==3.1.0 tensorflow==2.19.0
+pip install -r requirements.txt
 ```
 
 ---
-- 
GitLab


From 7ef53945304a8eec213c496b883584dc542c7a37 Mon Sep 17 00:00:00 2001
From: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
Date: Mon, 21 Jul 2025 20:37:53 +0100
Subject: [PATCH 9/9] ci: skip python_api tests in pre-commit hook

- Update pytest-pre-commit entry to ignore tests/test_python_api.py
- re-assign callable sanity test as python_api test marker

Signed-off-by: Deeptanshu Sekhri <deeptanshu.sekhri@arm.com>
---
 .pre-commit-config.yaml  |  2 +-
 tests/test_python_api.py | 15 +++++++--------
 2 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 5c9977a..a65f8bf 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -39,7 +39,7 @@ repos:
     hooks:
       - id: pytest-pre-commit
         name: Run pre-commit marked tests
-        entry: pytest -m pre_commit
+        entry: pytest -m pre_commit --ignore=tests/test_python_api.py
         language: system
         pass_filenames: false
         always_run: true
diff --git a/tests/test_python_api.py b/tests/test_python_api.py
index f66618b..d0300ba 100644
--- a/tests/test_python_api.py
+++ b/tests/test_python_api.py
@@ -59,6 +59,13 @@ def mobilenet_tflite(tmp_path_factory) -> Path:
 # -----------------------------------------------------------------------------
 # Tests
 # -----------------------------------------------------------------------------
+@pytest.mark.python_api
+def test_precommit_sanity() -> None:
+    """Sanity check: API should be callable."""
+    logger.info("Running python API callable sanity checks")
+    assert callable(tflite_flatbuffer_to_tosa_mlir), "API function missing"
+
+
 @pytest.mark.python_api
 def test_bytecode_filesystem(tmp_path: Path, mobilenet_tflite: Path) -> None:
     """Ensure that file based bytecode conversion creates a non empty .tosa.mlirbc file."""
@@ -135,11 +142,3 @@ def test_invalid_format(tmp_path: Path, mobilenet_tflite: Path, fmt: Any) -> Non
         tflite_flatbuffer_to_tosa_mlir(
             str(mobilenet_tflite), str(tmp_path / "invalid_format.tosa.mlirbc"), fmt
         )
-
-
-@pytest.mark.python_api
-@pytest.mark.pre_commit
-def test_precommit_sanity() -> None:
-    """Sanity check for pre-commit: API should be callable."""
-    logger.info("Running pre-commit sanity checks")
-    assert callable(tflite_flatbuffer_to_tosa_mlir), "API function missing"
-- 
GitLab