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tests_pytest/keras_tests/e2e_tests/wrapper/test_mct_wrapper_keras_e2e.py

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The tests use a simple CNN model and random data for representative
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dataset generation for quantization testing.
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"""
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import pytest
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import tensorflow as tf
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import keras

tests_pytest/keras_tests/integration_tests/wrapper/test_mct_wrapper_keras_integ.py

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"""
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Test cases for MCTWrapper class from model_compression_toolkit.wrapper.mct_wrapper
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"""
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import pytest
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from unittest.mock import Mock, patch
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from typing import Any, List, Tuple
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from model_compression_toolkit.wrapper.mct_wrapper import MCTWrapper
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tests_pytest/keras_tests/unit_tests/wrapper/test_mct_wrapper_keras_unit.py

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"""
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Test cases for MCTWrapper class from model_compression_toolkit.wrapper.mct_wrapper
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"""
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import pytest
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from unittest.mock import Mock, patch
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from typing import Any, List, Tuple
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from model_compression_toolkit.core import QuantizationErrorMethod
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from model_compression_toolkit.wrapper.mct_wrapper import MCTWrapper
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tests_pytest/pytorch_tests/e2e_tests/wrapper/test_mct_wrapper_pytorch_e2e.py

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dataset generation for quantization testing. All quantized models are
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exported to ONNX format for cross-platform deployment.
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"""
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# Import required libraries
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import pytest
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import torch
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import torch.nn as nn

tests_pytest/pytorch_tests/integration_tests/wrapper/test_mct_wrapper_pytorch_integ.py

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"""
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Test cases for MCTWrapper class from model_compression_toolkit.wrapper.mct_wrapper
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"""
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import pytest
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from unittest.mock import Mock, patch
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from typing import Any, List, Tuple
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from model_compression_toolkit.core import QuantizationErrorMethod
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from model_compression_toolkit.wrapper.mct_wrapper import MCTWrapper
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tests_pytest/pytorch_tests/unit_tests/wrapper/test_mct_wrapper_pytorch_unit.py

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"""
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Test cases for MCTWrapper class from model_compression_toolkit.wrapper.mct_wrapper
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"""
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import pytest
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from unittest.mock import Mock, patch
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from typing import Any, List, Tuple
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from model_compression_toolkit.core import QuantizationErrorMethod
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from model_compression_toolkit.wrapper.mct_wrapper import MCTWrapper
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