101 lines
4.1 KiB
Python
101 lines
4.1 KiB
Python
# Copyright 2021-2022 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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import numpy as np
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import pytest
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import mindspore.dataset as ds
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import mindspore.dataset.audio as audio
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from mindspore import log as logger
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def count_unequal_element(data_expected, data_me, rtol, atol):
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assert data_expected.shape == data_me.shape
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total_count = len(data_expected.flatten())
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error = np.abs(data_expected - data_me)
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greater = np.greater(error, atol + np.abs(data_expected) * rtol)
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loss_count = np.count_nonzero(greater)
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assert (loss_count / total_count) < rtol, "\ndata_expected_std:{0}\ndata_me_error:{1}\nloss:{2}".format(
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data_expected[greater], data_me[greater], error[greater])
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def test_overdrive_eager():
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"""
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Feature: Overdrive
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Description: Test Overdrive in eager mode
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Expectation: The results are as expected
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"""
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# Original waveform
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waveform = np.array([[1.47, 4.722, 5.863], [0.492, 0.235, 0.56]], dtype=np.float32)
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# Expect waveform
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expect_waveform = np.array([[1., 1., 1.],
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[0.74600005, 0.615, 0.77501255]], dtype=np.float32)
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overdrive_op = audio.Overdrive()
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# Filtered waveform by overdrive
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output = overdrive_op(waveform)
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count_unequal_element(expect_waveform, output, 0.0001, 0.0001)
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def test_overdrive_pipeline():
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"""
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Feature: Overdrive
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Description: Test Overdrive in pipeline mode
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Expectation: The results are as expected
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"""
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# Original waveform
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waveform = np.array([[0.1, 0.2], [0.4, 2.6]], dtype=np.float32)
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# Expect waveform
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expect_waveform = np.array([[0.29598799, 0.52081579],
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[0.7, 1.]], dtype=np.float32)
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dataset = ds.NumpySlicesDataset(waveform, ["waveform"], shuffle=False)
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overdrive_op = audio.Overdrive(10.0, 5.0)
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# Filtered waveform by overdrive
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dataset = dataset.map(
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input_columns=["waveform"], operations=overdrive_op)
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i = 0
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for item in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
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count_unequal_element(expect_waveform[i, :],
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item['waveform'], 0.0001, 0.0001)
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i += 1
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def test_overdrive_invalid_input():
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"""
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Feature: Overdrive
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Description: Test invalid parameter of Overdrive
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Expectation: Catch exceptions correctly
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"""
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def test_invalid_input(test_name, gain, color, error, error_msg):
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logger.info("Test Overdrive with bad input: {0}".format(test_name))
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with pytest.raises(error) as error_info:
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audio.Overdrive(gain, color)
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assert error_msg in str(error_info.value)
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test_invalid_input("invalid gain parameter type as a str", "20", 20, TypeError,
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"Argument gain with value 20 is not of type [<class 'float'>, <class 'int'>],"
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+ " but got <class 'str'>.")
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test_invalid_input("invalid color parameter type as a str", 10, "5", TypeError,
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"Argument color with value 5 is not of type [<class 'float'>, <class 'int'>],"
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+ " but got <class 'str'>.")
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test_invalid_input("invalid gain out of range [0, 100]", 100.23, 5.0, ValueError,
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"Input gain is not within the required interval of [0, 100].")
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test_invalid_input("invalid color out of range [0, 100]", 30, -0.333, ValueError,
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"Input color is not within the required interval of [0, 100].")
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if __name__ == "__main__":
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test_overdrive_eager()
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test_overdrive_pipeline()
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test_overdrive_invalid_input()
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