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import sys
import tensorflow as tf
from tensorflow_quantization.custom_qdq_cases import InceptionQDQCase
from examples.utils import get_tfkeras_model
from tests.onnx_graph_qdq_validator import validate_quantized_model
from tensorflow_quantization.utils import CreateAssetsFolders
from tensorflow_quantization.quantize import LayerConfig
import pytest

# Create a directory to save test models
test_assets = CreateAssetsFolders("test_qdq_node_placement")

EXPECTED_QDQ_INSERTION = [
    LayerConfig(name="Conv2D", is_keras_class=True),
    LayerConfig(name="Dense", is_keras_class=True),
    LayerConfig(name="DepthwiseConv2D", is_keras_class=True),
    LayerConfig(
        name="AveragePooling2D", is_keras_class=True, quantize_weight=False
    ),
    LayerConfig(
        name="GlobalAveragePooling2D", is_keras_class=True, quantize_weight=False
    )
]


def test_inceptionv3_quantize_full():
    """
    Inception-v3: Full model quantization
    """
    this_function_name = sys._getframe().f_code.co_name

    # Instantiate Baseline model
    nn_model_original = get_tfkeras_model(model_name="inception_v3")

    custom_qdq_cases = [InceptionQDQCase()]
    q_model, validated = validate_quantized_model(
        test_assets, nn_model_original, test_name=this_function_name,
        custom_qdq_cases=custom_qdq_cases,
        expected_qdq_insertion=EXPECTED_QDQ_INSERTION
    )
    assert validated, "ONNX QDQ validation for full network quantization failed!"
    # necessary to clear model layer names from the memory
    tf.keras.backend.clear_session()
