# 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. # ============================================================================== """ Testing Spectrogram Python API """ import numpy as np import mindspore.dataset as ds import mindspore.dataset.audio.transforms as audio from mindspore import log as logger from mindspore.dataset.audio.utils import WindowType, BorderType def count_unequal_element(data_expected, data_me, rtol, atol): """ Precision calculation func """ 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_spectrogram_pipeline(): """ Feature: mindspore pipeline mode normal testcase: spectrogram op. Description: input audio signal to test pipeline. Expectation: success. """ logger.info("test_spectrogram_pipeline") wav = [[[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]] dataset = ds.NumpySlicesDataset(wav, column_names=["audio"], shuffle=False) out = audio.Spectrogram(n_fft=8) dataset = dataset.map(operations=out, input_columns=["audio"], output_columns=["Spectrogram"], column_order=['Spectrogram']) result = np.array([[[2.8015e+01, 1.2100e+02, 3.1354e+02, 1.6900e+02, 2.5000e+01, 1.0843e+01, 1.2100e+02, 3.3150e+02], [3.2145e+00, 3.3914e+01, 9.4728e+01, 4.5914e+01, 9.9142e+00, 4.5858e+00, 3.3914e+01, 9.5685e+01], [1.0000e+00, 1.7157e-01, 1.5000e+00, 1.7157e-01, 1.7157e-01, 5.0000e-01, 1.7157e-01, 7.5000e-01], [4.2893e-02, 2.5736e-01, 5.8579e-01, 2.5736e-01, 2.5736e-01, 5.8579e-01, 2.5736e-01, 1.2868e-01], [5.0000e-01, 1.0000e+00, 8.5787e-02, 1.0000e+00, 1.0000e+00, 5.0000e-01, 1.0000e+00, 6.2868e-01]]]) for data1 in dataset.create_dict_iterator(num_epochs=1, output_numpy=True): count_unequal_element(data1["Spectrogram"], result, 0.0001, 0.0001) def test_spectrogram_eager(): """ Feature: mindspore eager mode normal testcase: spectrogram op. Description: input audio signal to test eager. Expectation: success. """ logger.info("test_spectrogram_eager") wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) out = audio.Spectrogram(n_fft=8, win_length=8, window=WindowType.HANN, pad_mode=BorderType.REFLECT)(np.array(wav, dtype="float")) result = np.array([[[2.8015e+01, 1.2100e+02, 3.1354e+02, 1.6900e+02, 2.5000e+01, 1.0843e+01, 1.2100e+02, 3.3150e+02], [3.2145e+00, 3.3914e+01, 9.4728e+01, 4.5914e+01, 9.9142e+00, 4.5858e+00, 3.3914e+01, 9.5685e+01], [1.0000e+00, 1.7157e-01, 1.5000e+00, 1.7157e-01, 1.7157e-01, 5.0000e-01, 1.7157e-01, 7.5000e-01], [4.2893e-02, 2.5736e-01, 5.8579e-01, 2.5736e-01, 2.5736e-01, 5.8579e-01, 2.5736e-01, 1.2868e-01], [5.0000e-01, 1.0000e+00, 8.5787e-02, 1.0000e+00, 1.0000e+00, 5.0000e-01, 1.0000e+00, 6.2868e-01]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_window_hamming_padmode_constant(): """ Feature: test spectrogram parameter: window, pad_mode. Description: test parameter. Expectation: success. """ logger.info("test_spectrogram_window_hamming_padmode_constant") wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) out = audio.Spectrogram(n_fft=8, window=WindowType.HAMMING, pad_mode=BorderType.CONSTANT)(np.array(wav, dtype="float")) result = np.array([[[1.1389e+01, 1.3736e+02, 3.5534e+02, 2.0164e+02, 3.0914e+01, 1.3465e+01, 1.3736e+02, 2.5064e+02], [5.6934e+00, 3.1860e+01, 8.5291e+01, 3.8484e+01, 9.1907e+00, 4.5576e+00, 3.1860e+01, 1.0027e+02], [1.9633e-01, 7.4475e-02, 1.2696e+00, 7.4475e-02, 7.4475e-02, 4.2320e-01, 7.4475e-02, 1.1765e+01], [5.0570e-01, 3.8456e-01, 6.8326e-01, 3.8456e-01, 3.8456e-01, 6.8326e-01, 3.8456e-01, 5.4501e+00], [6.1665e-01, 8.4640e-01, 7.2610e-02, 8.4640e-01, 8.4640e-01, 4.2320e-01, 8.4640e-01, 1.0642e+00]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_nfft_10_window_bartlett_padmode_edge(): """ Feature: test spectrogram parameter: n_fft, window, pad_mode. Description: test parameter. Expectation: success. """ logger.info("test_spectrogram_nfft_10_window_bartlett_padmode_edge") wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) out = audio.Spectrogram(n_fft=10, window=WindowType.BARTLETT, pad_mode=BorderType.EDGE)(np.array(wav, dtype="float")) result = np.array([[[4.0960e+01, 2.6244e+02, 4.0000e+02, 7.7440e+01, 2.5000e+01, 2.6244e+02, 5.9536e+02], [4.7655e+00, 5.6721e+01, 9.4681e+01, 2.3822e+01, 5.9597e+00, 5.6721e+01, 1.1597e+02], [5.3889e-01, 5.8360e-03, 9.2361e-01, 5.8359e-03, 9.2361e-01, 5.8360e-03, 2.4944e-01], [1.1449e-01, 9.9859e-01, 3.1897e-01, 2.9828e-01, 1.0403e+00, 9.9859e-01, 1.3072e+00], [1.8111e-01, 2.7416e-01, 4.7639e-01, 2.7416e-01, 4.7639e-01, 2.7416e-01, 7.0557e-02], [6.4000e-01, 3.6000e-01, 0.0000e+00, 2.5600e+00, 1.0000e+00, 3.6000e-01, 1.4400e+00]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_onsided_false(): """ Feature: test spectrogram parameter: onesided. Description: test parameter. Expectation: success. """ logger.info("test_spectrogram_onsided_false") wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) out = audio.Spectrogram(n_fft=10, window=WindowType.BARTLETT, pad_mode=BorderType.EDGE, onesided=False)(np.array(wav, dtype="float")) result = np.array([[[4.0960e+01, 2.6244e+02, 4.0000e+02, 7.7440e+01, 2.5000e+01, 2.6244e+02, 5.9536e+02], [4.7655e+00, 5.6721e+01, 9.4681e+01, 2.3822e+01, 5.9597e+00, 5.6721e+01, 1.1597e+02], [5.3889e-01, 5.8360e-03, 9.2361e-01, 5.8359e-03, 9.2361e-01, 5.8360e-03, 2.4944e-01], [1.1449e-01, 9.9859e-01, 3.1897e-01, 2.9828e-01, 1.0403e+00, 9.9859e-01, 1.3072e+00], [1.8111e-01, 2.7416e-01, 4.7639e-01, 2.7416e-01, 4.7639e-01, 2.7416e-01, 7.0557e-02], [6.4000e-01, 3.6000e-01, 0.0000e+00, 2.5600e+00, 1.0000e+00, 3.6000e-01, 1.4400e+00], [1.8111e-01, 2.7416e-01, 4.7639e-01, 2.7416e-01, 4.7639e-01, 2.7416e-01, 7.0557e-02], [1.1449e-01, 9.9859e-01, 3.1897e-01, 2.9828e-01, 1.0403e+00, 9.9859e-01, 1.3072e+00], [5.3889e-01, 5.8360e-03, 9.2361e-01, 5.8359e-03, 9.2361e-01, 5.8360e-03, 2.4944e-01], [4.7655e+00, 5.6721e+01, 9.4681e+01, 2.3822e+01, 5.9597e+00, 5.6721e+01, 1.1597e+02]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_power_0(): """ Feature: test spectrogram parameter: power. Description: test parameter. Expectation: success. """ logger.info("test_spectrogram_power_0") wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) out = audio.Spectrogram(n_fft=8, window=WindowType.HANN, pad_mode=BorderType.REFLECT, power=0)(np.array(wav, dtype="float")) result = np.array([[[[5.2929e+00, 0.0000e+00], [1.1000e+01, 0.0000e+00], [1.7707e+01, 0.0000e+00], [1.3000e+01, 0.0000e+00], [5.0000e+00, 0.0000e+00], [3.2929e+00, 0.0000e+00], [1.1000e+01, 0.0000e+00], [1.8207e+01, 0.0000e+00]], [[-1.7929e+00, -2.5288e-07], [-5.5000e+00, 1.9142e+00], [-9.7071e+00, 7.0711e-01], [-6.5000e+00, -1.9142e+00], [-2.5000e+00, -1.9142e+00], [-1.2929e+00, 1.7071e+00], [-5.5000e+00, 1.9142e+00], [-9.7071e+00, 1.2071e+00]], [[-1.0000e+00, 0.0000e+00], [0.0000e+00, -4.1421e-01], [1.0000e+00, -7.0711e-01], [0.0000e+00, 4.1421e-01], [0.0000e+00, 4.1421e-01], [0.0000e+00, -7.0711e-01], [0.0000e+00, -4.1421e-01], [5.0000e-01, -7.0711e-01]], [[-2.0711e-01, -2.5288e-07], [-5.0000e-01, -8.5787e-02], [-2.9289e-01, 7.0711e-01], [5.0000e-01, 8.5786e-02], [5.0000e-01, 8.5786e-02], [-7.0711e-01, -2.9289e-01], [-5.0000e-01, -8.5787e-02], [-2.9289e-01, 2.0711e-01]], [[7.0711e-01, 0.0000e+00], [1.0000e+00, 0.0000e+00], [2.9289e-01, 0.0000e+00], [-1.0000e+00, 0.0000e+00], [-1.0000e+00, 0.0000e+00], [7.0711e-01, 0.0000e+00], [1.0000e+00, 0.0000e+00], [7.9289e-01, 0.0000e+00]]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_center_false(): """ Feature: test spectrogram parameter: center. Description: test parameter. Expectation: success. """ logger.info("test_spectrogram_center_false") wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) out = audio.Spectrogram(n_fft=8, window=WindowType.HANN, center=False, pad_mode=BorderType.REFLECT)(np.array(wav, dtype="float")) result = np.array([[[1.2100e+02, 3.1354e+02, 1.6900e+02, 2.5000e+01, 1.0843e+01, 1.2100e+02], [3.3914e+01, 9.4728e+01, 4.5914e+01, 9.9142e+00, 4.5858e+00, 3.3914e+01], [1.7157e-01, 1.5000e+00, 1.7157e-01, 1.7157e-01, 5.0000e-01, 1.7157e-01], [2.5736e-01, 5.8579e-01, 2.5736e-01, 2.5736e-01, 5.8579e-01, 2.5736e-01], [1.0000e+00, 8.5787e-02, 1.0000e+00, 1.0000e+00, 5.0000e-01, 1.0000e+00]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_normalized_true(): """ Feature: test spectrogram parameter: normalized. Description: test parameter. Expectation: success. """ logger.info("test_spectrogram_normalized_true") wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) out = audio.Spectrogram(n_fft=8, window=WindowType.HANN, center=False, normalized=True, pad_mode=BorderType.REFLECT)(np.array(wav, dtype="float")) result = np.array([[[4.0333e+01, 1.0451e+02, 5.6333e+01, 8.3333e+00, 3.6144e+00, 4.0333e+01], [1.1305e+01, 3.1576e+01, 1.5305e+01, 3.3047e+00, 1.5286e+00, 1.1305e+01], [5.7191e-02, 5.0000e-01, 5.7191e-02, 5.7191e-02, 1.6667e-01, 5.7191e-02], [8.5786e-02, 1.9526e-01, 8.5786e-02, 8.5786e-02, 1.9526e-01, 8.5786e-02], [3.3333e-01, 2.8596e-02, 3.3333e-01, 3.3333e-01, 1.6667e-01, 3.3333e-01]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_inputrank_3(): """ Feature: test spectrogram parameter: input rank. Description: test input rank. Expectation: success. """ logger.info("test_spectrogram_inputrank_3") wav = np.array([[[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1]], [[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1]]]) out = audio.Spectrogram(n_fft=8, window=WindowType.HANN, pad_mode=BorderType.REFLECT)(np.array(wav, dtype="float")) result = np.array([[[[2.8015e+01, 1.2100e+02, 3.1354e+02, 1.6900e+02, 3.3558e+01], [3.2145e+00, 3.3914e+01, 9.4728e+01, 4.5914e+01, 6.7145e+00], [1.0000e+00, 1.7157e-01, 1.5000e+00, 1.7157e-01, 7.5000e-01], [4.2893e-02, 2.5736e-01, 5.8579e-01, 2.5736e-01, 1.2868e-01], [5.0000e-01, 1.0000e+00, 8.5787e-02, 1.0000e+00, 6.2868e-01]]], [[[2.8015e+01, 1.2100e+02, 3.1354e+02, 1.6900e+02, 3.3558e+01], [3.2145e+00, 3.3914e+01, 9.4728e+01, 4.5914e+01, 6.7145e+00], [1.0000e+00, 1.7157e-01, 1.5000e+00, 1.7157e-01, 7.5000e-01], [4.2893e-02, 2.5736e-01, 5.8579e-01, 2.5736e-01, 1.2868e-01], [5.0000e-01, 1.0000e+00, 8.5787e-02, 1.0000e+00, 6.2868e-01]]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_winlength_7(): """ Feature: test spectrogram parameter: win_length. Description: test parameter. Expectation: success. """ logger.info("test_spectrogram_winlength_7") wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) out = audio.Spectrogram(n_fft=8, win_length=7, window=WindowType.HANN,)(np.array(wav, dtype="float")) result = np.array([[[2.0140e+01, 4.9000e+01, 1.5006e+02, 2.5284e+02, 1.5006e+02, 4.9000e+01, 4.5220e+00, 1.2250e+01, 7.6562e+01, 1.9600e+02, 2.7265e+02], [5.0272e+00, 1.9488e+01, 5.5103e+01, 1.0153e+02, 5.5103e+01, 1.9488e+01, 2.0179e+00, 6.5089e+00, 2.9144e+01, 7.1406e+01, 1.0662e+02], [4.2200e-01, 5.4020e-01, 1.0554e+00, 4.8321e+00, 1.0554e+00, 5.4020e-01, 9.6867e-01, 4.0345e-01, 7.8188e-01, 1.0872e+00, 3.3055e+00], [1.2817e-01, 3.8618e-01, 2.1917e-01, 2.6102e-01, 2.1917e-01, 3.8618e-01, 4.3028e-01, 3.7738e-01, 2.0158e-01, 4.2135e-01, 5.7616e-02], [3.7364e-01, 7.1574e-01, 8.1719e-01, 9.0949e-13, 8.1720e-01, 7.1573e-01, 2.7823e-01, 7.1573e-01, 8.1719e-01, 7.1574e-01, 3.7364e-01]]]) count_unequal_element(out, result, 0.0001, 0.0001) def test_spectrogram_param(): """ Feature: test spectrogram invalid parameter. Description: test some invalid parameters. Expectation: success. """ try: _ = audio.Spectrogram(n_fft=-1) except ValueError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Input n_fft is not within the required interval of [1, 2147483647]." in str(error) try: _ = audio.Spectrogram(n_fft=0) except ValueError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Input n_fft is not within the required interval of [1, 2147483647]." in str(error) try: _ = audio.Spectrogram(win_length=-1) except ValueError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Input win_length is not within the required interval of [1, 2147483647]." in str(error) try: _ = audio.Spectrogram(win_length="s") except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument win_length with value s is not of type [], but got ." in str(error) try: _ = audio.Spectrogram(hop_length=-1) except ValueError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Input hop_length is not within the required interval of [1, 2147483647]." in str(error) try: _ = audio.Spectrogram(hop_length=-100) except ValueError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Input hop_length is not within the required interval of [1, 2147483647]." in str(error) try: _ = audio.Spectrogram(win_length=300, n_fft=200) except ValueError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Input win_length should be no more than n_fft, but got win_length: 300 and n_fft: 200." \ in str(error) try: _ = audio.Spectrogram(pad=-1) except ValueError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Input pad is not within the required interval of [0, 2147483647]." in str(error) try: _ = audio.Spectrogram(power=-1) except ValueError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Input power is not within the required interval of [0, 16777216]." in str(error) try: _ = audio.Spectrogram(n_fft=False) except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument n_fft with value False is not of type (,)" in str(error) try: _ = audio.Spectrogram(n_fft="s") except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument n_fft with value s is not of type [], but got ." \ in str(error) try: _ = audio.Spectrogram(window=False) except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument window with value False is not of type [], but got ." \ in str(error) try: _ = audio.Spectrogram(pad_mode=False) except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument pad_mode with value False is not of type [], but got ." \ in str(error) try: _ = audio.Spectrogram(onesided="s") except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument onesided with value s is not of type [], but got ." in str(error) try: _ = audio.Spectrogram(center="s") except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument center with value s is not of type [], but got ." in str(error) try: _ = audio.Spectrogram(normalized="s") except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument normalized with value s is not of type [], but got ." in str(error) try: _ = audio.Spectrogram(normalized=1) except TypeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Argument normalized with value 1 is not of type [], but got ." in str(error) try: wav = np.array([[1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 4, 4, 3, 3, 2, 2, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]]) _ = audio.Spectrogram(n_fft=100, center=False)(wav) except RuntimeError as error: logger.info("Got an exception in Spectrogram: {}".format(str(error))) assert "Unexpected error. Spectrogram: n_fft should be more than 0 and less than 30," \ " but got n_fft: 100." in str(error) if __name__ == "__main__": test_spectrogram_pipeline() test_spectrogram_eager() test_spectrogram_window_hamming_padmode_constant() test_spectrogram_nfft_10_window_bartlett_padmode_edge() test_spectrogram_onsided_false() test_spectrogram_power_0() test_spectrogram_center_false() test_spectrogram_normalized_true() test_spectrogram_inputrank_3() test_spectrogram_winlength_7() test_spectrogram_param()