forked from huawei/mindspore2022
106 lines
3.4 KiB
Python
106 lines
3.4 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""
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Testing MuLawEncoding op in DE.
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"""
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import numpy as np
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import mindspore.dataset as ds
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import mindspore.dataset.audio.transforms as audio
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from mindspore import log as logger
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def test_mu_law_encoding():
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"""
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Feature: MuLawEncoding
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Description: test MuLawEncoding in pipeline mode
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Expectation: the data is processed successfully
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"""
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logger.info("Test MuLawEncoding.")
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def gen():
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data = np.array([[0.1, 0.2, 0.3, 0.4]])
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yield (np.array(data, dtype=np.float32),)
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dataset = ds.GeneratorDataset(source=gen, column_names=["multi_dim_data"])
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dataset = dataset.map(operations=audio.MuLawEncoding(), input_columns=["multi_dim_data"])
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for i in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
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assert i["multi_dim_data"].shape == (1, 4)
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expected = np.array([[203, 218, 228, 234]])
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assert np.array_equal(i["multi_dim_data"], expected)
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logger.info("Finish testing MuLawEncoding.")
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def test_mu_law_encoding_eager():
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"""
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Feature: MuLawEncoding
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Description: test MuLawEncoding in eager mode
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Expectation: the data is processed successfully
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"""
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logger.info("Test MuLawEncoding callable.")
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input_t = np.array([[0.1, 0.2, 0.3, 0.4]])
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output_t = audio.MuLawEncoding(128)(input_t)
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assert output_t.shape == (1, 4)
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expected = np.array([[98, 106, 111, 115]])
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assert np.array_equal(output_t, expected)
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logger.info("Finish testing MuLawEncoding.")
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def test_mu_law_encoding_uncallable():
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"""
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Feature: MuLawEncoding
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Description: test param check of MuLawEncoding
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Expectation: throw correct error and message
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"""
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logger.info("Test MuLawEncoding not callable.")
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try:
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input_t = np.random.rand(2, 4)
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output_t = audio.MuLawEncoding(-3)(input_t)
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assert output_t.shape == (2, 4)
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except ValueError as e:
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assert 'Input quantization_channels is not within the required interval of [1, 2147483647].' in str(e)
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logger.info("Finish testing MuLawEncoding.")
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def test_mu_law_encoding_and_decoding():
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"""
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Feature: MuLawEncoding and MuLawDecoding
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Description: test MuLawEncoding and MuLawDecoding in eager mode
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Expectation: the data is processed successfully
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"""
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logger.info("Test MuLawEncoding and MuLawDecoding callable.")
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input_t = np.array([[98, 106, 111, 115]])
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output_decoding = audio.MuLawDecoding(128)(input_t)
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output_encoding = audio.MuLawEncoding(128)(output_decoding)
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assert np.array_equal(input_t, output_encoding)
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logger.info("Finish testing MuLawEncoding and MuLawDecoding callable.")
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if __name__ == "__main__":
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test_mu_law_encoding()
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test_mu_law_encoding_eager()
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test_mu_law_encoding_uncallable()
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test_mu_law_encoding_and_decoding()
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