forked from huawei/mindspore2022
115 lines
6.7 KiB
Python
115 lines
6.7 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_detect_pitch_frequency_eager():
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""" mindspore eager mode normal testcase:detect_pitch_frequency op"""
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# Original waveform
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waveform = np.array([[2.716064453125e-03, 6.34765625e-03, 9.246826171875e-03, 1.0894775390625e-02,
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1.1383056640625e-02, 1.1566162109375e-02, 1.3946533203125e-02, 1.55029296875e-02,
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1.6143798828125e-02, 1.8402099609375e-02],
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[1.7181396484375e-02, 1.59912109375e-02, 1.64794921875e-02, 1.5106201171875e-02,
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1.385498046875e-02, 1.3458251953125e-02, 1.4190673828125e-02, 1.2847900390625e-02,
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1.0528564453125e-02, 9.368896484375e-03]], dtype=np.float64)
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# Expect waveform
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expect_waveform = np.array(
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[[10., 10., 10.], [5., 5., 10.]], dtype=np.float64)
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detect_pitch_frequency_op = audio.DetectPitchFrequency(30, 0.1, 3, 5, 25)
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# Detect pitch frequence
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output = detect_pitch_frequency_op(waveform)
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count_unequal_element(expect_waveform, output, 0.0001, 0.0001)
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def test_detect_pitch_frequency_pipeline():
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""" mindspore pipeline mode normal testcase:detect_pitch_frequency op"""
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# Original waveform
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waveform = np.array([[0.716064453125e-03, 5.34765625e-03, 6.246826171875e-03, 2.0894775390625e-02,
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7.1383056640625e-02], [4.1566162109375e-02, 1.3946533203125e-02, 3.55029296875e-02,
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0.6143798828125e-02, 3.8402099609375e-02]], dtype=np.float64)
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# Expect waveform
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expect_waveform = np.array([[10.0000], [7.5000]], dtype=np.float64)
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dataset = ds.NumpySlicesDataset(waveform, ["audio"], shuffle=False)
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detect_pitch_frequency_op = audio.DetectPitchFrequency(30, 0.1, 3, 5, 25)
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# Detect pitch frequence
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dataset = dataset.map(input_columns=["audio"],
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operations=detect_pitch_frequency_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_detect_pitch_frequency_invalid_input():
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def test_invalid_input(test_name, sample_rate, frame_time, win_length, freq_low, freq_high, error, error_msg):
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logger.info(
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"Test DetectPitchFrequency with bad input: {0}".format(test_name))
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with pytest.raises(error) as error_info:
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audio.DetectPitchFrequency(
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sample_rate, frame_time, win_length, freq_low, freq_high)
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assert error_msg in str(error_info.value)
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test_invalid_input("invalid sample_rate parameter type as a float", 44100.5, 0.01, 30, 85, 3400, TypeError,
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"Argument sample_rate with value 44100.5 is not of type [<class 'int'>],"
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" but got <class 'float'>.")
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test_invalid_input("invalid sample_rate parameter type as a String", "44100", 0.01, 30, 85, 3400, TypeError,
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"Argument sample_rate with value 44100 is not of type [<class 'int'>], but got <class 'str'>.")
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test_invalid_input("invalid frame_time parameter type as a String", 44100, "0.01", 30, 85, 3400, TypeError,
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"Argument frame_time with value 0.01 is not of type [<class 'float'>, <class 'int'>],"
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" but got <class 'str'>.")
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test_invalid_input("invalid win_length parameter type as a float", 44100, 0.01, 30.1, 85, 3400, TypeError,
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"Argument win_length with value 30.1 is not of type [<class 'int'>], but got <class 'float'>.")
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test_invalid_input("invalid win_length parameter type as a String", 44100, 0.01, "30", 85, 3400, TypeError,
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"Argument win_length with value 30 is not of type [<class 'int'>], but got <class 'str'>.")
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test_invalid_input("invalid freq_low parameter type as a String", 44100, 0.01, 30, "85", 3400, TypeError,
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"Argument freq_low with value 85 is not of type [<class 'int'>, <class 'float'>],"
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" but got <class 'str'>.")
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test_invalid_input("invalid freq_high parameter type as a String", 44100, 0.01, 30, 85, "3400", TypeError,
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"Argument freq_high with value 3400 is not of type [<class 'int'>, <class 'float'>],"
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" but got <class 'str'>.")
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test_invalid_input("invalid sample_rate parameter value", 0, 0.01, 30, 85, 3400, ValueError,
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"Input sample_rate is not within the required interval of [-2147483648, 0) and (0, 2147483647].")
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test_invalid_input("invalid frame_time parameter value", 44100, 0, 30, 85, 3400, ValueError,
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"Input frame_time is not within the required interval of (0, 16777216].")
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test_invalid_input("invalid win_length parameter value", 44100, 0.01, 0, 85, 3400, ValueError,
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"Input win_length is not within the required interval of [1, 2147483647].")
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test_invalid_input("invalid freq_low parameter value", 44100, 0.01, 30, 0, 3400, ValueError,
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"Input freq_low is not within the required interval of (0, 16777216].")
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test_invalid_input("invalid freq_high parameter value", 44100, 0.01, 30, 85, 0, ValueError,
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"Input freq_high is not within the required interval of (0, 16777216].")
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if __name__ == "__main__":
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test_detect_pitch_frequency_eager()
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test_detect_pitch_frequency_pipeline()
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test_detect_pitch_frequency_invalid_input()
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