# Copyright 2021 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 as ds import mindspore.dataset.audio.transforms 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_overdrive_eager(): """ Feature: Overdrive Description: test Overdrive in eager mode Expectation: the results are as expected """ # Original waveform waveform = np.array([[1.47, 4.722, 5.863], [0.492, 0.235, 0.56]], dtype=np.float32) # Expect waveform expect_waveform = np.array([[1., 1., 1.], [0.74600005, 0.615, 0.77501255]], dtype=np.float32) overdrive_op = audio.Overdrive() # Filtered waveform by overdrive output = overdrive_op(waveform) count_unequal_element(expect_waveform, output, 0.0001, 0.0001) def test_overdrive_pipeline(): """ Feature: Overdrive Description: test Overdrive in pipeline mode Expectation: the results are as expected """ # Original waveform waveform = np.array([[0.1, 0.2], [0.4, 2.6]], dtype=np.float32) # Expect waveform expect_waveform = np.array([[0.29598799, 0.52081579], [0.7, 1.]], dtype=np.float32) dataset = ds.NumpySlicesDataset(waveform, ["waveform"], shuffle=False) overdrive_op = audio.Overdrive(10.0, 5.0) # Filtered waveform by overdrive dataset = dataset.map( input_columns=["waveform"], operations=overdrive_op) i = 0 for item in dataset.create_dict_iterator(num_epochs=1, output_numpy=True): count_unequal_element(expect_waveform[i, :], item['waveform'], 0.0001, 0.0001) i += 1 def test_overdrive_invalid_input(): """ Feature: Overdrive Description: test invalid parameter of Overdrive Expectation: catch exceptions correctly """ def test_invalid_input(test_name, gain, color, error, error_msg): logger.info("Test Overdrive with bad input: {0}".format(test_name)) with pytest.raises(error) as error_info: audio.Overdrive(gain, color) assert error_msg in str(error_info.value) test_invalid_input("invalid gain parameter type as a str", "20", 20, TypeError, "Argument gain with value 20 is not of type [, ]," + " but got .") test_invalid_input("invalid color parameter type as a str", 10, "5", TypeError, "Argument color with value 5 is not of type [, ]," + " but got .") test_invalid_input("invalid gain out of range [0, 100]", 100.23, 5.0, ValueError, "Input gain is not within the required interval of [0, 100].") test_invalid_input("invalid color out of range [0, 100]", 30, -0.333, ValueError, "Input color is not within the required interval of [0, 100].") if __name__ == "__main__": test_overdrive_eager() test_overdrive_pipeline() test_overdrive_invalid_input()