1# Copyright 2021 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15 16import numpy as np 17import pytest 18 19import mindspore.dataset as ds 20import mindspore.dataset.audio.transforms as audio 21from mindspore import log as logger 22 23 24def count_unequal_element(data_expected, data_me, rtol, atol): 25 assert data_expected.shape == data_me.shape 26 total_count = len(data_expected.flatten()) 27 error = np.abs(data_expected - data_me) 28 greater = np.greater(error, atol + np.abs(data_expected) * rtol) 29 loss_count = np.count_nonzero(greater) 30 assert (loss_count / total_count) < rtol, "\ndata_expected_std:{0}\ndata_me_error:{1}\nloss:{2}".format( 31 data_expected[greater], data_me[greater], error[greater]) 32 33 34def test_func_contrast_eager(): 35 """ mindspore eager mode normal testcase:contrast op""" 36 # Original waveform 37 waveform = np.array([[1, 2], [3, 4]], dtype=np.float32) 38 # Expect waveform 39 expect_waveform = np.array([[1., -8.742277e-08], 40 [-1., 1.748455e-07]], 41 dtype=np.float32) 42 contrast_op = audio.Contrast(75.0) 43 # Filtered waveform by contrast 44 output = contrast_op(waveform) 45 count_unequal_element(expect_waveform, output, 0.0001, 0.0001) 46 47 48def test_func_contrast_pipeline(): 49 """ mindspore pipeline mode normal testcase:contrast op""" 50 # Original waveform 51 waveform = np.array([[0.4941969, 0.53911686, 0.4846254], [0.10841596, 0.029320478, 0.52353495], 52 [0.23657, 0.087965, 0.43579]], dtype=np.float64) 53 # Expect waveform 54 expect_waveform = np.array([[7.032282948493957520e-01, 7.328570485115051270e-01, 6.967759728431701660e-01], 55 [2.311619222164154053e-01, 6.433061510324478149e-02, 7.226532697677612305e-01], 56 [4.539981484413146973e-01, 1.895205676555633545e-01, 6.622338891029357910e-01]], 57 dtype=np.float64) 58 dataset = ds.NumpySlicesDataset(waveform, ["audio"], shuffle=False) 59 contrast_op = audio.Contrast() 60 # Filtered waveform by contrast 61 dataset = dataset.map(input_columns=["audio"], operations=contrast_op, num_parallel_workers=8) 62 i = 0 63 for item in dataset.create_dict_iterator(output_numpy=True): 64 count_unequal_element(expect_waveform[i, :], item['audio'], 0.0001, 0.0001) 65 i += 1 66 67 68def test_contrast_invalid_input(): 69 def test_invalid_input(test_name, enhancement_amount, error, error_msg): 70 logger.info("Test Contrast with bad input: {0}".format(test_name)) 71 with pytest.raises(error) as error_info: 72 audio.Contrast(enhancement_amount) 73 assert error_msg in str(error_info.value) 74 75 test_invalid_input("invalid enhancement_amount parameter type as a String", "75.0", TypeError, 76 "Argument enhancement_amount with value 75.0 is not of type [<class 'float'>, <class 'int'>]," 77 + " but got <class 'str'>.") 78 test_invalid_input("invalid enhancement_amount parameter value", -1, ValueError, 79 "Input enhancement_amount is not within the required interval of [0, 100].") 80 test_invalid_input("invalid enhancement_amount parameter value", 101, ValueError, 81 "Input enhancement_amount is not within the required interval of [0, 100].") 82 83 84if __name__ == "__main__": 85 test_func_contrast_eager() 86 test_func_contrast_pipeline() 87 test_contrast_invalid_input() 88