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import sys
import tensorflow as tf
from tensorflow_quantization.custom_qdq_cases import EfficientNetQDQCase
from utils import create_efficientnet_model
from tests.onnx_graph_qdq_validator import validate_quantized_model
from tensorflow_quantization.utils import CreateAssetsFolders
import pytest

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


def test_efficientnet_b0_quantize_full():
    """
    EfficientNet-B0: Full model quantization.

    Contains special patterns connected to Add layer:
        1. (Conv->BatchNorm->Activation)->Add
        2. (Conv->BatchNorm->Activation->Dropout)->Add
    Previously, only (Conv)->Add and (Conv->BatchNorm)->Add checks were done when checking for quantizable Residual
        connections (branches to `Add` layer). The new EfficientNet patterns have now also been added to the
        ResidualCustomQDQCases check.
    """
    this_function_name = sys._getframe().f_code.co_name

    # Instantiate Baseline model
    nn_model_original = create_efficientnet_model()

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


def test_efficientnet_b3_quantize_full():
    """
    EfficientNet-B3: Full model quantization.
    Contains the same special patterns as EfficientNet-B0.
    """
    this_function_name = sys._getframe().f_code.co_name

    # Instantiate Baseline model
    nn_model_original = create_efficientnet_model(model_version="b3")

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