forked from huawei/mindspore2022
141 lines
7.4 KiB
Python
141 lines
7.4 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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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.transforms 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, \
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"\ndata_expected_std:{0}\ndata_me_error:{1}\nloss:{2}". \
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format(data_expected[greater], data_me[greater], error[greater])
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def test_sliding_window_cmn_eager():
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"""
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Feature: test the basic function in eager mode.
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Description: mindspore eager mode normal testcase:sliding_window_cmn op.
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Expectation: compile done without error.
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"""
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# Original waveform
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waveform_1 = np.array([[[0.0000, 0.1000, 0.2000],
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[0.3000, 0.4000, 0.5000]],
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[[0.6000, 0.7000, 0.8000],
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[0.9000, 1.0000, 1.1000]]], dtype=np.float64)
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# Expect waveform
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expect_waveform_1 = np.array([[[-0.1500, -0.1500, -0.1500],
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[0.1500, 0.1500, 0.1500]],
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[[-0.1500, -0.1500, -0.1500],
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[0.1500, 0.1500, 0.1500]]], dtype=np.float64)
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sliding_window_cmn_op_1 = audio.SlidingWindowCmn(500, 200, False, False)
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# Filtered waveform by sliding_window_cmn
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output_1 = sliding_window_cmn_op_1(waveform_1)
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count_unequal_element(expect_waveform_1, output_1, 0.0001, 0.0001)
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# Original waveform
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waveform_2 = np.array([[0.0050, 0.0306, 0.6146, 0.7620, 0.6369],
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[0.9525, 0.0362, 0.6721, 0.6867, 0.8466]], dtype=np.float32)
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# Expect waveform
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expect_waveform_2 = np.array([[-1.0000, -1.0000, -1.0000, 1.0000, -1.0000],
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[1.0000, 1.0000, 1.0000, -1.0000, 1.0000]], dtype=np.float32)
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sliding_window_cmn_op_2 = audio.SlidingWindowCmn(600, 100, False, True)
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# Filtered waveform by sliding_window_cmn
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output_2 = sliding_window_cmn_op_2(waveform_2)
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count_unequal_element(expect_waveform_2, output_2, 0.0001, 0.0001)
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# Original waveform
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waveform_3 = np.array([[[0.3764, 0.4168, 0.0635, 0.7082, 0.4596, 0.3457, 0.8438, 0.8860, 0.9151, 0.5746,
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0.6630, 0.0260, 0.2631, 0.7410, 0.5627, 0.6749, 0.7099, 0.1120, 0.4794, 0.2778],
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[0.4157, 0.2246, 0.2488, 0.2686, 0.0562, 0.4422, 0.9407, 0.0756, 0.5737, 0.7501,
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0.3122, 0.7982, 0.3034, 0.1880, 0.2298, 0.0961, 0.7439, 0.9947, 0.8156, 0.2907]]],
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dtype=np.float64)
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# Expect waveform
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expect_waveform_3 = np.array([[[-1.0000, 1.0000, -1.0000, 1.0000, 1.0000, -1.0000, -1.0000, 1.0000,
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1.0000, -1.0000, 1.0000, -1.0000, -1.0000, 1.0000, 1.0000, 1.0000,
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-1.0000, -1.0000, -1.0000, -1.0000],
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[1.0000, -1.0000, 1.0000, -1.0000, -1.0000, 1.0000, 1.0000, -1.0000,
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-1.0000, 1.0000, -1.0000, 1.0000, 1.0000, -1.0000, -1.0000, -1.0000,
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1.0000, 1.0000, 1.0000, 1.0000]]], dtype=np.float64)
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sliding_window_cmn_op_3 = audio.SlidingWindowCmn(3, 0, True, True)
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# Filtered waveform by sliding_window_cmn
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output_3 = sliding_window_cmn_op_3(waveform_3)
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count_unequal_element(expect_waveform_3, output_3, 0.0001, 0.0001)
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def test_sliding_window_cmn_pipeline():
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"""
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Feature: test the basic function in pipeline mode.
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Description: mindspore pipeline mode normal testcase:sliding_window_cmn op.
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Expectation: compile done without error.
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"""
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# Original waveform
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waveform = np.array([[[3.2, 2.1, 1.3], [6.2, 5.3, 6]]], dtype=np.float64)
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# Expect waveform
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expect_waveform = np.array([[[-1.0000, -1.0000, -1.0000],
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[1.0000, 1.0000, 1.0000]]], dtype=np.float64)
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dataset = ds.NumpySlicesDataset(waveform, ["audio"], shuffle=False)
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sliding_window_cmn_op = audio.SlidingWindowCmn(600, 100, False, True)
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# Filtered waveform by sliding_window_cmn
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dataset = dataset.map(input_columns=["audio"], operations=sliding_window_cmn_op, num_parallel_workers=8)
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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['audio'], 0.0001, 0.0001)
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i += 1
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def test_sliding_window_cmn_invalid_input():
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"""
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Feature: test the validate function with invalid parameters.
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Description: mindspore invalid parameters testcase:sliding_window_cmn op.
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Expectation: compile done without error.
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"""
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def test_invalid_input(test_name, cmn_window, min_cmn_window, center, norm_vars, error, error_msg):
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logger.info("Test SlidingWindowCmn with bad input: {0}".format(test_name))
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with pytest.raises(error) as error_info:
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audio.SlidingWindowCmn(cmn_window, min_cmn_window, center, norm_vars)
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assert error_msg in str(error_info.value)
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test_invalid_input("invalid cmn_window parameter type as a String", "600", 100, False, False, TypeError,
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"Argument cmn_window with value 600 is not of type [<class 'int'>],"
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" but got <class 'str'>.")
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test_invalid_input("invalid cmn_window parameter value", 441324343243242342345300, 100, False, False, ValueError,
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"Input cmn_window is not within the required interval of [0, 2147483647].")
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test_invalid_input("invalid min_cmn_window parameter type as a String", 600, "100", False, False, TypeError,
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"Argument min_cmn_window with value 100 is not of type [<class 'int'>],"
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" but got <class 'str'>.")
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test_invalid_input("invalid min_cmn_window parameter value", 600, 441324343243242342345300, False, False,
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ValueError, "Input min_cmn_window is not within the required interval of [0, 2147483647].")
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test_invalid_input("invalid center parameter type as a String", 600, 100, "False", False, TypeError,
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"Argument center with value False is not of type [<class 'bool'>],"
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" but got <class 'str'>.")
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test_invalid_input("invalid norm_vars parameter type as a String", 600, 100, False, "False", TypeError,
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"Argument norm_vars with value False is not of type [<class 'bool'>],"
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" but got <class 'str'>.")
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if __name__ == '__main__':
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test_sliding_window_cmn_eager()
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test_sliding_window_cmn_pipeline()
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test_sliding_window_cmn_invalid_input()
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