# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Pytest conf module."""
import shutil
import tarfile
from pathlib import Path
from typing import Any
from typing import Generator

import pytest
import tensorflow as tf

from mlia.core.context import ExecutionContext
from mlia.devices.ethosu.config import EthosUConfiguration
from mlia.nn.tensorflow.utils import convert_to_tflite
from mlia.nn.tensorflow.utils import save_keras_model
from mlia.nn.tensorflow.utils import save_tflite_model
from mlia.tools.vela_wrapper import optimize_model


@pytest.fixture(scope="session", name="test_resources_path")
def fixture_test_resources_path() -> Path:
    """Return test resources path."""
    return Path(__file__).parent / "test_resources"


@pytest.fixture(name="dummy_context")
def fixture_dummy_context(tmpdir: str) -> ExecutionContext:
    """Return dummy context fixture."""
    return ExecutionContext(working_dir=tmpdir)


@pytest.fixture(scope="session")
def test_systems_path(test_resources_path: Path) -> Path:
    """Return test systems path in a pytest fixture."""
    return test_resources_path / "backends" / "systems"


@pytest.fixture(scope="session")
def test_applications_path(test_resources_path: Path) -> Path:
    """Return test applications path in a pytest fixture."""
    return test_resources_path / "backends" / "applications"


@pytest.fixture(scope="session")
def non_optimised_input_model_file(test_tflite_model: Path) -> Path:
    """Provide the path to a quantized dummy model file."""
    return test_tflite_model


@pytest.fixture(scope="session")
def optimised_input_model_file(test_tflite_vela_model: Path) -> Path:
    """Provide path to Vela-optimised dummy model file."""
    return test_tflite_vela_model


@pytest.fixture(scope="session")
def invalid_input_model_file(test_tflite_invalid_model: Path) -> Path:
    """Provide the path to an invalid dummy model file."""
    return test_tflite_invalid_model


@pytest.fixture(autouse=True)
def test_resources(monkeypatch: pytest.MonkeyPatch, test_resources_path: Path) -> Any:
    """Force using test resources as middleware's repository."""

    def get_test_resources() -> Path:
        """Return path to the test resources."""
        return test_resources_path / "backends"

    monkeypatch.setattr("mlia.backend.fs.get_backend_resources", get_test_resources)
    yield


def create_archive(
    archive_name: str, source: Path, destination: Path, with_root_folder: bool = False
) -> None:
    """Create archive from directory source."""
    with tarfile.open(destination / archive_name, mode="w:gz") as tar:
        for item in source.iterdir():
            item_name = item.name
            if with_root_folder:
                item_name = f"{source.name}/{item_name}"
            tar.add(item, item_name)


def process_directory(source: Path, destination: Path) -> None:
    """Process resource directory."""
    destination.mkdir()

    for item in source.iterdir():
        if item.is_dir():
            create_archive(f"{item.name}.tar.gz", item, destination)
            create_archive(f"{item.name}_dir.tar.gz", item, destination, True)


@pytest.fixture(scope="session", autouse=True)
def add_archives(
    test_resources_path: Path, tmp_path_factory: pytest.TempPathFactory
) -> Any:
    """Generate archives of the test resources."""
    tmp_path = tmp_path_factory.mktemp("archives")

    archives_path = tmp_path / "archives"
    archives_path.mkdir()

    if (archives_path_link := test_resources_path / "archives").is_symlink():
        archives_path_link.unlink()

    archives_path_link.symlink_to(archives_path, target_is_directory=True)

    for item in ["applications", "systems"]:
        process_directory(test_resources_path / "backends" / item, archives_path / item)

    yield

    archives_path_link.unlink()
    shutil.rmtree(tmp_path)


def get_test_keras_model() -> tf.keras.Model:
    """Return test Keras model."""
    model = tf.keras.Sequential(
        [
            tf.keras.Input(shape=(28, 28, 1), batch_size=1, name="input"),
            tf.keras.layers.Reshape((28, 28, 1)),
            tf.keras.layers.Conv2D(
                filters=12, kernel_size=(3, 3), activation="relu", name="conv1"
            ),
            tf.keras.layers.Conv2D(
                filters=12, kernel_size=(3, 3), activation="relu", name="conv2"
            ),
            tf.keras.layers.MaxPool2D(2, 2),
            tf.keras.layers.Flatten(),
            tf.keras.layers.Dense(10, name="output"),
        ]
    )

    model.compile(optimizer="sgd", loss="mean_squared_error")
    return model


@pytest.fixture(scope="session", name="test_models_path")
def fixture_test_models_path(
    tmp_path_factory: pytest.TempPathFactory,
) -> Generator[Path, None, None]:
    """Provide path to the test models."""
    tmp_path = tmp_path_factory.mktemp("models")

    keras_model = get_test_keras_model()
    save_keras_model(keras_model, tmp_path / "test_model.h5")

    tflite_model = convert_to_tflite(keras_model, quantized=True)
    tflite_model_path = tmp_path / "test_model.tflite"
    save_tflite_model(tflite_model, tflite_model_path)

    tflite_vela_model = tmp_path / "test_model_vela.tflite"
    device = EthosUConfiguration("ethos-u55-256")
    optimize_model(tflite_model_path, device.compiler_options, tflite_vela_model)

    tf.saved_model.save(keras_model, str(tmp_path / "tf_model_test_model"))

    invalid_tflite_model = tmp_path / "invalid.tflite"
    invalid_tflite_model.touch()

    yield tmp_path

    shutil.rmtree(tmp_path)


@pytest.fixture(scope="session", name="test_keras_model")
def fixture_test_keras_model(test_models_path: Path) -> Path:
    """Return test Keras model."""
    return test_models_path / "test_model.h5"


@pytest.fixture(scope="session", name="test_tflite_model")
def fixture_test_tflite_model(test_models_path: Path) -> Path:
    """Return test TFLite model."""
    return test_models_path / "test_model.tflite"


@pytest.fixture(scope="session", name="test_tflite_vela_model")
def fixture_test_tflite_vela_model(test_models_path: Path) -> Path:
    """Return test Vela-optimized TFLite model."""
    return test_models_path / "test_model_vela.tflite"


@pytest.fixture(scope="session", name="test_tf_model")
def fixture_test_tf_model(test_models_path: Path) -> Path:
    """Return test TFLite model."""
    return test_models_path / "tf_model_test_model"


@pytest.fixture(scope="session", name="test_tflite_invalid_model")
def fixture_test_tflite_invalid_model(test_models_path: Path) -> Path:
    """Return test invalid TFLite model."""
    return test_models_path / "invalid.tflite"