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""" 16Testing AmplitudeToDB op in DE 17""" 18import numpy as np 19import pytest 20 21import mindspore.dataset as ds 22import mindspore.dataset.audio.transforms as c_audio 23from mindspore import log as logger 24from mindspore.dataset.audio.utils import ScaleType 25 26CHANNEL = 1 27FREQ = 20 28TIME = 15 29 30 31def gen(shape): 32 np.random.seed(0) 33 data = np.random.random(shape) 34 yield (np.array(data, dtype=np.float32),) 35 36 37def count_unequal_element(data_expected, data_me, rtol, atol): 38 """ Precision calculation func """ 39 assert data_expected.shape == data_me.shape 40 total_count = len(data_expected.flatten()) 41 error = np.abs(data_expected - data_me) 42 greater = np.greater(error, atol + np.abs(data_expected) * rtol) 43 loss_count = np.count_nonzero(greater) 44 assert (loss_count / total_count) < rtol, "\ndata_expected_std:{0}\ndata_me_error:{1}\nloss:{2}".format( 45 data_expected[greater], data_me[greater], error[greater]) 46 47 48def allclose_nparray(data_expected, data_me, rtol, atol, equal_nan=True): 49 """ Precision calculation formula """ 50 if np.any(np.isnan(data_expected)): 51 assert np.allclose(data_me, data_expected, rtol, atol, equal_nan=equal_nan) 52 elif not np.allclose(data_me, data_expected, rtol, atol, equal_nan=equal_nan): 53 count_unequal_element(data_expected, data_me, rtol, atol) 54 55 56def test_func_amplitude_to_db_eager(): 57 """ mindspore eager mode normal testcase:amplitude_to_db op""" 58 59 logger.info("check amplitude_to_db op output") 60 ndarr_in = np.array([[[[-0.2197528, 0.3821656]]], 61 [[[0.57418776, 0.46741104]]], 62 [[[-0.20381108, -0.9303914]]], 63 [[[0.3693608, -0.2017813]]], 64 [[[-1.727381, -1.3708513]]], 65 [[[1.259975, 0.4981323]]], 66 [[[0.76986176, -0.5793846]]]]).astype(np.float32) 67 # cal from benchmark 68 out_expect = np.array([[[[-84.17748, -4.177484]]], 69 [[[-2.4094608, -3.3030105]]], 70 [[[-100., -100.]]], 71 [[[-4.325492, -84.32549]]], 72 [[[-100., -100.]]], 73 [[[1.0036192, -3.0265532]]], 74 [[[-1.1358725, -81.13587]]]]).astype(np.float32) 75 76 amplitude_to_db_op = c_audio.AmplitudeToDB() 77 out_mindspore = amplitude_to_db_op(ndarr_in) 78 79 allclose_nparray(out_mindspore, out_expect, 0.0001, 0.0001) 80 81 82def test_func_amplitude_to_db_pipeline(): 83 """ mindspore pipeline mode normal testcase:amplitude_to_db op""" 84 85 logger.info("test AmplitudeToDB op with default value") 86 generator = gen([CHANNEL, FREQ, TIME]) 87 88 data1 = ds.GeneratorDataset(source=generator, column_names=["multi_dimensional_data"]) 89 90 transforms = [c_audio.AmplitudeToDB()] 91 data1 = data1.map(operations=transforms, input_columns=["multi_dimensional_data"]) 92 93 for item in data1.create_dict_iterator(num_epochs=1, output_numpy=True): 94 out_put = item["multi_dimensional_data"] 95 assert out_put.shape == (CHANNEL, FREQ, TIME) 96 97 98def test_amplitude_to_db_invalid_input(): 99 def test_invalid_input(test_name, stype, ref_value, amin, top_db, error, error_msg): 100 logger.info("Test AmplitudeToDB with bad input: {0}".format(test_name)) 101 with pytest.raises(error) as error_info: 102 c_audio.AmplitudeToDB(stype=stype, ref_value=ref_value, amin=amin, top_db=top_db) 103 assert error_msg in str(error_info.value) 104 105 test_invalid_input("invalid stype parameter value", "test", 1.0, 1e-10, 80.0, TypeError, 106 "Argument stype with value test is not of type [<enum 'ScaleType'>], but got <class 'str'>.") 107 test_invalid_input("invalid ref_value parameter value", ScaleType.POWER, -1.0, 1e-10, 80.0, ValueError, 108 "Input ref_value is not within the required interval of (0, 16777216]") 109 test_invalid_input("invalid amin parameter value", ScaleType.POWER, 1.0, -1e-10, 80.0, ValueError, 110 "Input amin is not within the required interval of (0, 16777216]") 111 test_invalid_input("invalid top_db parameter value", ScaleType.POWER, 1.0, 1e-10, -80.0, ValueError, 112 "Input top_db is not within the required interval of (0, 16777216]") 113 114 test_invalid_input("invalid stype parameter value", True, 1.0, 1e-10, 80.0, TypeError, 115 "Argument stype with value True is not of type [<enum 'ScaleType'>], but got <class 'bool'>.") 116 test_invalid_input("invalid ref_value parameter value", ScaleType.POWER, "value", 1e-10, 80.0, TypeError, 117 "Argument ref_value with value value is not of type [<class 'int'>, <class 'float'>], " + 118 "but got <class 'str'>") 119 test_invalid_input("invalid amin parameter value", ScaleType.POWER, 1.0, "value", -80.0, TypeError, 120 "Argument amin with value value is not of type [<class 'int'>, <class 'float'>], " + 121 "but got <class 'str'>") 122 test_invalid_input("invalid top_db parameter value", ScaleType.POWER, 1.0, 1e-10, "value", TypeError, 123 "Argument top_db with value value is not of type [<class 'int'>, <class 'float'>], " + 124 "but got <class 'str'>") 125 126 127if __name__ == "__main__": 128 test_func_amplitude_to_db_eager() 129 test_func_amplitude_to_db_pipeline() 130 test_amplitude_to_db_invalid_input() 131