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# SPDX-FileCopyrightText: Copyright 2023, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Tests for module mlia.nn.rewrite.core.rewrite."""
from __future__ import annotations
from contextlib import ExitStack as does_not_raise
from pathlib import Path
from typing import Any
import pytest
from mlia.nn.rewrite.core.rewrite import RewriteConfiguration
from mlia.nn.rewrite.core.rewrite import Rewriter
from mlia.nn.tensorflow.config import TFLiteModel
from tests.utils.rewrite import TestTrainingParameters
@pytest.mark.parametrize(
"rewrite_name, expected_error",
[
("fully_connected", does_not_raise()),
("random", does_not_raise()),
],
)
def test_rewrite_configuration(
test_tflite_model_fp32: Path, rewrite_name: str, expected_error: Any
) -> None:
"""Test get_rewrite function only supports rewrite type fully_connected."""
with expected_error:
config_obj = RewriteConfiguration(
rewrite_name,
["sample_node_start", "sample_node_end"],
None,
)
assert config_obj.optimization_target in str(config_obj)
rewriter_obj = Rewriter(test_tflite_model_fp32, config_obj)
assert rewriter_obj.optimizer_configuration.optimization_target == rewrite_name
assert isinstance(rewriter_obj, Rewriter)
def test_rewriting_optimizer(
test_tflite_model_fp32: Path,
test_tfrecord_fp32: Path,
) -> None:
"""Test fc_layer rewrite process with rewrite type fully_connected."""
config_obj = RewriteConfiguration(
"fully_connected",
["sequential/flatten/Reshape", "StatefulPartitionedCall:0"],
test_tfrecord_fp32,
train_params=TestTrainingParameters(),
)
test_obj = Rewriter(test_tflite_model_fp32, config_obj)
test_obj.apply_optimization()
trained_model = test_obj.get_model()
assert isinstance(trained_model, TFLiteModel)
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