# Copyright 2022 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== import numpy as np import pytest import mindspore.dataset.audio.utils as audio from mindspore import log as logger def count_unequal_element(data_expected, data_me, rtol, atol): assert data_expected.shape == data_me.shape total_count = len(data_expected.flatten()) error = np.abs(data_expected - data_me) greater = np.greater(error, atol + np.abs(data_expected) * rtol) loss_count = np.count_nonzero(greater) assert (loss_count / total_count) < rtol, \ "\ndata_expected_std:{0}\ndata_me_error:{1}\nloss:{2}". \ format(data_expected[greater], data_me[greater], error[greater]) def test_melscale_fbanks_normal(): """ Feature: melscale_fbanks. Description: Test normal operation with NormType.NONE and MelType.HTK. Expectation: The output data is the same as the result of torchaudio.functional.melscale_fbanks. """ expect = np.array([[0.0000, 0.0000, 0.0000, 0.0000], [0.5502, 0.0000, 0.0000, 0.0000], [0.6898, 0.3102, 0.0000, 0.0000], [0.0000, 0.9366, 0.0634, 0.0000], [0.0000, 0.1924, 0.8076, 0.0000], [0.0000, 0.0000, 0.4555, 0.5445], [0.0000, 0.0000, 0.0000, 0.7247], [0.0000, 0.0000, 0.0000, 0.0000]], dtype=np.float64) output = audio.melscale_fbanks(8, 2, 50, 4, 100, audio.NormType.NONE, audio.MelType.HTK) count_unequal_element(expect, output, 0.0001, 0.0001) def test_melscale_fbanks_none_slaney(): """ Feature: melscale_fbanks. Description: Test normal operation with NormType.NONE and MelType.SLANEY. Expectation: The output data is the same as the result of torchaudio.functional.melscale_fbanks. """ expect = np.array([[0.0000, 0.0000, 0.0000, 0.0000], [0.5357, 0.0000, 0.0000, 0.0000], [0.7202, 0.2798, 0.0000, 0.0000], [0.0000, 0.9762, 0.0238, 0.0000], [0.0000, 0.2321, 0.7679, 0.0000], [0.0000, 0.0000, 0.4881, 0.5119], [0.0000, 0.0000, 0.0000, 0.7440], [0.0000, 0.0000, 0.0000, 0.0000]], dtype=np.float64) output = audio.melscale_fbanks(8, 2, 50, 4, 100, audio.NormType.NONE, audio.MelType.SLANEY) count_unequal_element(expect, output, 0.0001, 0.0001) def test_melscale_fbanks_with_slaney_htk(): """ Feature: melscale_fbanks. Description: Test normal operation with NormType.SLANEY and MelType.HTK. Expectation: The output data is the same as the result of torchaudio.functional.melscale_fbanks. """ output = audio.melscale_fbanks(10, 0, 50, 5, 100, audio.NormType.SLANEY, audio.MelType.HTK) expect = np.array([[0.0000, 0.0000, 0.0000, 0.0000, 0.0000], [0.0843, 0.0000, 0.0000, 0.0000, 0.0000], [0.0776, 0.0447, 0.0000, 0.0000, 0.0000], [0.0000, 0.1158, 0.0055, 0.0000, 0.0000], [0.0000, 0.0344, 0.0860, 0.0000, 0.0000], [0.0000, 0.0000, 0.0741, 0.0454, 0.0000], [0.0000, 0.0000, 0.0000, 0.1133, 0.0053], [0.0000, 0.0000, 0.0000, 0.0355, 0.0822], [0.0000, 0.0000, 0.0000, 0.0000, 0.0760], [0.0000, 0.0000, 0.0000, 0.0000, 0.0000]], dtype=np.float64) count_unequal_element(expect, output, 0.0001, 0.0001) def test_melscale_fbanks_with_slaney_slaney(): """ Feature: melscale_fbanks. Description: Test normal operation with NormType.SLANEY and MelType.SLANEY. Expectation: The output data is the same as the result of torchaudio.functional.melscale_fbanks. """ output = audio.melscale_fbanks(8, 2, 50, 4, 100, audio.NormType.SLANEY, audio.MelType.SLANEY) expect = np.array([[0.0000, 0.0000, 0.0000, 0.0000], [0.0558, 0.0000, 0.0000, 0.0000], [0.0750, 0.0291, 0.0000, 0.0000], [0.0000, 0.1017, 0.0025, 0.0000], [0.0000, 0.0242, 0.0800, 0.0000], [0.0000, 0.0000, 0.0508, 0.0533], [0.0000, 0.0000, 0.0000, 0.0775], [0.0000, 0.0000, 0.0000, 0.0000]], dtype=np.float64) count_unequal_element(expect, output, 0.0001, 0.0001) def test_melscale_fbanks_invalid_input(): """ Feature: melscale_fbanks. Description: Test operation with invalid input. Expectation: Throw exception as expected. """ def test_invalid_input(test_name, n_freqs, f_min, f_max, n_mels, sample_rate, norm, mel_type, error, error_msg): logger.info("Test melscale_fbanks with bad input: {0}".format(test_name)) with pytest.raises(error) as error_info: audio.melscale_fbanks(n_freqs, f_min, f_max, n_mels, sample_rate, norm, mel_type) print(error_info) assert error_msg in str(error_info.value) test_invalid_input("invalid n_freqs parameter Value", 99999999999, 0, 50, 5, 100, audio.NormType.NONE, audio.MelType.HTK, ValueError, "n_freqs") test_invalid_input("invalid n_freqs parameter type", 10.5, 0, 50, 5, 100, audio.NormType.NONE, audio.MelType.HTK, TypeError, "n_freqs") test_invalid_input("invalid f_min parameter type", 10, None, 50, 5, 100, audio.NormType.NONE, audio.MelType.HTK, TypeError, "f_min") test_invalid_input("invalid f_max parameter type", 10, 0, None, 5, 100, audio.NormType.NONE, audio.MelType.HTK, TypeError, "f_max") test_invalid_input("invalid n_mels parameter type", 10, 0, 50, 10.1, 100, audio.NormType.NONE, audio.MelType.HTK, TypeError, "n_mels") test_invalid_input("invalid n_mels parameter Value", 20, 0, 50, 999999999999, 100, audio.NormType.NONE, audio.MelType.HTK, ValueError, "n_mels") test_invalid_input("invalid sample_rate parameter type", 10, 0, 50, 5, 100.1, audio.NormType.NONE, audio.MelType.HTK, TypeError, "sample_rate") test_invalid_input("invalid sample_rate parameter Value", 20, 0, 50, 5, 999999999999, audio.NormType.NONE, audio.MelType.HTK, ValueError, "sample_rate") test_invalid_input("invalid norm parameter type", 10, 0, 50, 5, 100, None, audio.MelType.HTK, TypeError, "norm") test_invalid_input("invalid norm parameter type", 10, 0, 50, 5, 100, audio.NormType.SLANEY, None, TypeError, "mel_type") if __name__ == "__main__": test_melscale_fbanks_normal() test_melscale_fbanks_none_slaney() test_melscale_fbanks_with_slaney_htk() test_melscale_fbanks_with_slaney_slaney() test_melscale_fbanks_invalid_input()