chore: import upstream snapshot with attribution

2026-07-13 13:36:55 +08:00
commit c8a779b1bb
1887 changed files with 3245738 additions and 0 deletions
@@ -0,0 +1,158 @@
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+
+import sys
+import tensorflow as tf
+from tensorflow_quantization import QuantizationSpec
+from tensorflow_quantization.custom_qdq_cases import ResNetV1QDQCase
+from network_pool import frodo_32_32
+from onnx_graph_qdq_validator import validate_quantized_model
+from tensorflow_quantization.utils import CreateAssetsFolders
+import pytest
+
+test_assets = CreateAssetsFolders("test_quantize_qdq_insertion")
+
+# ############################################
+# ######### Full Quantize Test ###############
+# ############################################
+
+
+def test_quantize_full():
+    this_function_name = sys._getframe().f_code.co_name
+
+    nn_model_original = frodo_32_32()
+    q_model, vr = validate_quantized_model(
+        test_assets, nn_model_original, test_name=this_function_name
+    )
+
+    assert vr, "ONNX QDQ Validation for full network quantization failed!"
+    # Necessary to clear model layer names from the memory
+    tf.keras.backend.clear_session()
+
+
+def test_quantize_full_residual():
+    this_function_name = sys._getframe().f_code.co_name
+
+    nn_model_original = frodo_32_32()
+    q_model, vr = validate_quantized_model(
+        test_assets, nn_model_original, custom_qdq_cases=[ResNetV1QDQCase()], test_name=this_function_name
+    )
+
+    assert vr, "ONNX QDQ Validation for quantizing full network with special residual failed!"
+    tf.keras.backend.clear_session()
+
+
+# ############################################
+# ######### Full Special Quantize Test #######
+# ############################################
+
+
+def test_quantize_full_special_layer():
+    this_function_name = sys._getframe().f_code.co_name
+
+    nn_model_original = frodo_32_32()
+
+    # Create a Quantization Spec (dictionary telling how `add` layer should be treated differently).
+    qspec = QuantizationSpec()
+    qspec.add(name="add", quantization_index=[0])
+    q_model, vr = validate_quantized_model(
+        test_assets, nn_model_original, qspec=qspec, test_name=this_function_name
+    )
+
+    assert vr, "QDQ Validation for full network but one special layer quantization failed!"
+    tf.keras.backend.clear_session()
+
+
+# ##########################################
+# ######### Partial Quantize Test ##########
+# ##########################################
+
+
+def test_quantize_partial():
+    this_function_name = sys._getframe().f_code.co_name
+
+    nn_model_original = frodo_32_32()
+
+    # Create a qspec dictionary to quantize only two layers named 'conv2d_2' and 'dense'
+    qspec = QuantizationSpec()
+    qspec.add(name="conv2d_2")
+    qspec.add(name="dense")
+    q_model, vr = validate_quantized_model(
+        test_assets, nn_model_original, quantization_mode="partial", qspec=qspec, test_name=this_function_name
+    )
+
+    assert vr, "ONNX QDQ Validation for partial network quantization failed!"
+    tf.keras.backend.clear_session()
+
+
+# ####################################################
+# ######### Subset layers Test - Full quantize #######
+# ####################################################
+
+
+def test_quantize_specific_class_maxpool():
+    this_function_name = sys._getframe().f_code.co_name
+
+    nn_model_original = frodo_32_32()
+
+    # Create a list with keras layer classes to quantize
+    qspec = QuantizationSpec()
+    qspec.add(name="MaxPooling2D", is_keras_class=True)
+    q_model, vr = validate_quantized_model(
+        test_assets, nn_model_original, qspec=qspec, test_name=this_function_name
+    )
+
+    assert vr, "ONNX QDQ Validation for specific class `Dense` quantization failed!"
+    tf.keras.backend.clear_session()
+
+
+def test_quantize_specific_class_add():
+    this_function_name = sys._getframe().f_code.co_name
+
+    nn_model_original = frodo_32_32()
+
+    # Create a list with keras layer classes to quantize
+    qspec = QuantizationSpec()
+    qspec.add(name="Add", is_keras_class=True)
+    q_model, vr = validate_quantized_model(
+        test_assets, nn_model_original, qspec=qspec, test_name=this_function_name
+    )
+
+    assert vr, "ONNX QDQ Validation for quantizing specific class `Add` failed!"
+    tf.keras.backend.clear_session()
+
+
+# ####################################################
+# ####### Subset layers Test - Partial quantize ######
+# ####################################################
+
+
+def test_quantize_specific_class_conv2d_partial():
+    this_function_name = sys._getframe().f_code.co_name
+
+    nn_model_original = frodo_32_32()
+
+    # Create a list with keras layer classes to quantize
+    qspec = QuantizationSpec()
+    qspec.add(name="Conv2D", is_keras_class=True)
+    q_model, vr = validate_quantized_model(
+        test_assets, nn_model_original, quantization_mode="partial", qspec=qspec, test_name=this_function_name
+    )
+
+    assert vr, "ONNX QDQ Validation for quantizing specific class `Conv2D` and `conv2d_1` layer failed!"
+    tf.keras.backend.clear_session()