forked from mindspore-Ecosystem/mindspore
124 lines
4.9 KiB
Python
124 lines
4.9 KiB
Python
# Copyright 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 pytest
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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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from util import diff_mse
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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_filtfilt_eager():
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"""
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Feature: Filtfilt
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Description: Test Filtfilt op in eager mode under normal test case
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Expectation: Output is equal to the expected output
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"""
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logger.info("test_filtfilt_eager")
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# construct input
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waveform = np.array([[0.1, 0.2, 0.3], [0.3, 0.4, 0.5]], dtype=np.float64)
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a_coeffs = [0.1, 0.2, 0.3]
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b_coeffs = [0.4, 0.5, 0.6]
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clanmp_input = True
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filtfilt_op = audio.Filtfilt(a_coeffs, b_coeffs, clamp=clanmp_input)
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our_waveform = filtfilt_op(waveform)
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# use np flip
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forward_filtered_op = audio.LFilter(a_coeffs, b_coeffs, clamp=False)
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backward_filtered_op = audio.LFilter(a_coeffs, b_coeffs, clamp=clanmp_input)
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# use np flip
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forward_filtered_waveform = forward_filtered_op(waveform)
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backward_filtered_waveform = backward_filtered_op(np.flip(forward_filtered_waveform, -1))
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expect_waveform = np.flip(backward_filtered_waveform, -1)
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mse = diff_mse(our_waveform, expect_waveform)
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assert mse == 0
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logger.info("test_filtfilt_eager Success")
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def test_filtfilt_pipeline():
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"""
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Feature: Filtfilt
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Description: Test Filtfilt op in pipeline mode under normal test case
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Expectation: Output is equal to the expected output
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"""
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logger.info("test_filtfilt_pipeline")
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# construct input
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waveform = np.array([[0.1, 0.2, 0.3, 0.4], [0.4, 0.5, 0.6, 0.7]], dtype=np.float64)
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a_coeffs = [0.1, 0.2, 0.3]
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b_coeffs = [0.4, 0.5, 0.6]
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expect_waveform = np.array([[1, 0.2, -1, 1], [1, 0.5, -1, 1]], dtype=np.float64)
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data = (waveform, waveform.shape)
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dataset = ds.NumpySlicesDataset(data, ["channel", "sample"], shuffle=False)
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filtfilt_op = audio.Filtfilt(a_coeffs, b_coeffs, clamp=True)
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# Filtered waveform by lfilter
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dataset = dataset.map(input_columns=["channel"], operations=filtfilt_op, num_parallel_workers=8)
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i = 0
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for data in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
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count_unequal_element(expect_waveform[i, :], data['channel'], 0.0001, 0.0001)
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i += 1
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def test_filtfilt_invalid_input_all():
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"""
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Feature: Filtfilt
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Description: Test Filtfilt op with invalid input
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Expectation: Correct error is raised as expected
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"""
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waveform = np.random.rand(2, 1000)
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def test_invalid_input(test_name, a_coeffs, b_coeffs, clamp, error, error_msg):
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logger.info("Test Filtfilt with bad input: {0}".format(test_name))
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with pytest.raises(error) as error_info:
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audio.Filtfilt(a_coeffs, b_coeffs, clamp)(waveform)
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assert error_msg in str(error_info.value)
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a_coeffs = ['0.1', '0.2', '0.3']
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b_coeffs = [0.1, 0.2, 0.3]
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test_invalid_input("invalid a_coeffs parameter type as a string", a_coeffs, b_coeffs, True, TypeError,
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"Argument a_coeffs[0] with value 0.1 is not of type [<class 'float'>, <class 'int'>], "
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+ "but got <class 'str'>.")
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a_coeffs = [234322354352353453651, 0.2, 0.3]
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b_coeffs = [0.1, 0.2, 0.3]
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test_invalid_input("invalid a_coeffs parameter value", a_coeffs, b_coeffs, True, ValueError,
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"Input a_coeffs[0] is not within the required interval of [-16777216, 16777216].")
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a_coeffs = [0.1, 0.2, 0.3]
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b_coeffs = [0.1, 0.2, 0.3]
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test_invalid_input("invalid clamp parameter type as a String", a_coeffs, b_coeffs, "True", TypeError,
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"Argument clamp with value True 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_filtfilt_eager()
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test_filtfilt_pipeline()
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test_filtfilt_invalid_input_all()
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