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authorDiego Russo <diego.russo@arm.com>2022-05-30 13:34:14 +0100
committerDiego Russo <diego.russo@arm.com>2022-05-30 13:34:14 +0100
commit0efca3cadbad5517a59884576ddb90cfe7ac30f8 (patch)
treeabed6cb6fbf3c439fc8d947f505b6a53d5daeb1e /tests/mlia/test_nn_tensorflow_utils.py
parent0777092695c143c3a54680b5748287d40c914c35 (diff)
downloadmlia-0efca3cadbad5517a59884576ddb90cfe7ac30f8.tar.gz
Add MLIA codebase0.3.0-rc.1
Add MLIA codebase including sources and tests. Change-Id: Id41707559bd721edd114793618d12ccd188d8dbd
Diffstat (limited to 'tests/mlia/test_nn_tensorflow_utils.py')
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diff --git a/tests/mlia/test_nn_tensorflow_utils.py b/tests/mlia/test_nn_tensorflow_utils.py
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+# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
+# SPDX-License-Identifier: Apache-2.0
+"""Test for module utils/test_utils."""
+from pathlib import Path
+
+import pytest
+import tensorflow as tf
+
+from mlia.nn.tensorflow.utils import convert_to_tflite
+from mlia.nn.tensorflow.utils import get_tf_tensor_shape
+from mlia.nn.tensorflow.utils import is_keras_model
+from mlia.nn.tensorflow.utils import is_tflite_model
+from mlia.nn.tensorflow.utils import save_keras_model
+from mlia.nn.tensorflow.utils import save_tflite_model
+
+
+def test_convert_to_tflite(test_keras_model: Path) -> None:
+ """Test converting Keras model to TFLite."""
+ keras_model = tf.keras.models.load_model(str(test_keras_model))
+ tflite_model = convert_to_tflite(keras_model)
+
+ assert tflite_model
+
+
+def test_save_keras_model(tmp_path: Path, test_keras_model: Path) -> None:
+ """Test saving Keras model."""
+ keras_model = tf.keras.models.load_model(str(test_keras_model))
+
+ temp_file = tmp_path / "test_model_saving.h5"
+ save_keras_model(keras_model, temp_file)
+ loaded_model = tf.keras.models.load_model(temp_file)
+
+ assert loaded_model.summary() == keras_model.summary()
+
+
+def test_save_tflite_model(tmp_path: Path, test_keras_model: Path) -> None:
+ """Test saving TFLite model."""
+ keras_model = tf.keras.models.load_model(str(test_keras_model))
+
+ tflite_model = convert_to_tflite(keras_model)
+
+ temp_file = tmp_path / "test_model_saving.tflite"
+ save_tflite_model(tflite_model, temp_file)
+
+ interpreter = tf.lite.Interpreter(model_path=str(temp_file))
+ assert interpreter
+
+
+@pytest.mark.parametrize(
+ "model_path, expected_result",
+ [
+ [Path("sample_model.tflite"), True],
+ [Path("strange_model.tflite.tfl"), False],
+ [Path("sample_model.h5"), False],
+ [Path("sample_model"), False],
+ ],
+)
+def test_is_tflite_model(model_path: Path, expected_result: bool) -> None:
+ """Test function is_tflite_model."""
+ result = is_tflite_model(model_path)
+ assert result == expected_result
+
+
+@pytest.mark.parametrize(
+ "model_path, expected_result",
+ [
+ [Path("sample_model.h5"), True],
+ [Path("strange_model.h5.keras"), False],
+ [Path("sample_model.tflite"), False],
+ [Path("sample_model"), False],
+ ],
+)
+def test_is_keras_model(model_path: Path, expected_result: bool) -> None:
+ """Test function is_keras_model."""
+ result = is_keras_model(model_path)
+ assert result == expected_result
+
+
+def test_get_tf_tensor_shape(test_tf_model: Path) -> None:
+ """Test get_tf_tensor_shape with test model."""
+ assert get_tf_tensor_shape(str(test_tf_model)) == [1, 28, 28, 1]