forked from huawei/mindspore2022
123 lines
5.7 KiB
Python
123 lines
5.7 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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"""
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Testing SpectralCentroid Python API
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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 count_unequal_element(data_expected, data_me, rtol, atol):
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""" Precision calculation func """
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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_spectral_centroid_pipeline():
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"""
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Feature: mindspore pipeline mode normal testcase: spectral_centroid op.
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Description: input audio signal to test pipeline.
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Expectation: success.
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"""
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logger.info("test_spectral_centroid_pipeline")
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wav = [[[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]]
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dataset = ds.NumpySlicesDataset(wav, column_names=["audio"], shuffle=False)
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out = audio.SpectralCentroid(sample_rate=44100, n_fft=8)
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dataset = dataset.map(operations=out, input_columns=["audio"], output_columns=["SpectralCentroid"],
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column_order=['SpectralCentroid'])
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result = np.array([[[4436.1182, 3580.0718, 2902.4917, 3334.8962, 5199.8350, 6284.4814,
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3580.0718, 2895.5659]]])
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for data1 in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
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count_unequal_element(data1["SpectralCentroid"], result, 0.0001, 0.0001)
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def test_spectral_centroid_eager():
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"""
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Feature: mindspore eager mode normal testcase: spectral_centroid op.
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Description: input audio signal to test eager.
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Expectation: success.
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"""
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logger.info("test_spectral_centroid_eager")
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wav = np.array([[1.2, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5.5, 6.5]])
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spectral_centroid_op = audio.SpectralCentroid(sample_rate=48000, n_fft=8)
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out = spectral_centroid_op(wav)
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result = np.array([[[5276.65022959, 3896.67543098, 3159.17400004, 3629.81957922,
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5659.68456649, 6840.25126846, 3896.67543098, 3316.97434286]]])
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count_unequal_element(out, result, 0.0001, 0.0001)
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def test_spectral_centroid_param():
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"""
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Feature: test spectral_centroid invalid parameter.
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Description: test some invalid parameters.
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Expectation: success.
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"""
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try:
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_ = audio.SpectralCentroid(sample_rate=-1)
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except ValueError as error:
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logger.info("Got an exception in SpectralCentroid: {}".format(str(error)))
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assert "Input sample_rate is not within the required interval of [0, 2147483647]." in str(error)
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try:
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_ = audio.SpectralCentroid(sample_rate=48000, n_fft=-1)
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except ValueError as error:
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logger.info("Got an exception in SpectralCentroid: {}".format(str(error)))
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assert "Input n_fft is not within the required interval of [1, 2147483647]." in str(error)
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try:
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_ = audio.SpectralCentroid(sample_rate=48000, n_fft=0)
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except ValueError as error:
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logger.info("Got an exception in SpectralCentroid: {}".format(str(error)))
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assert "Input n_fft is not within the required interval of [1, 2147483647]." in str(error)
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try:
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_ = audio.SpectralCentroid(sample_rate=48000, win_length=-1)
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except ValueError as error:
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logger.info("Got an exception in SpectralCentroid: {}".format(str(error)))
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assert "Input win_length is not within the required interval of [1, 2147483647]." in str(error)
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try:
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_ = audio.SpectralCentroid(sample_rate=48000, win_length="s")
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except TypeError as error:
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logger.info("Got an exception in SpectralCentroid: {}".format(str(error)))
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assert "Argument win_length with value s is not of type [<class 'int'>], but got <class 'str'>." in str(error)
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try:
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_ = audio.SpectralCentroid(sample_rate=48000, hop_length=-1)
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except ValueError as error:
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logger.info("Got an exception in SpectralCentroid: {}".format(str(error)))
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assert "Input hop_length is not within the required interval of [1, 2147483647]." in str(error)
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try:
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_ = audio.SpectralCentroid(sample_rate=48000, hop_length=-100)
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except ValueError as error:
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logger.info("Got an exception in SpectralCentroid: {}".format(str(error)))
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assert "Input hop_length is not within the required interval of [1, 2147483647]." in str(error)
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try:
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_ = audio.SpectralCentroid(sample_rate=48000, win_length=300, n_fft=200)
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except ValueError as error:
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logger.info("Got an exception in SpectralCentroid: {}".format(str(error)))
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assert "Input win_length should be no more than n_fft, but got win_length: 300 and n_fft: 200." \
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in str(error)
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if __name__ == "__main__":
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test_spectral_centroid_pipeline()
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test_spectral_centroid_eager()
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test_spectral_centroid_param()
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