test_save.py 12.2 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
13
import itertools

from torchaudio.backend import sox_io_backend
from parameterized import parameterized

from ..common_utils import (
    TempDirMixin,
    PytorchTestCase,
    skipIfNoExec,
    skipIfNoExtension,
    get_wav_data,
    load_wav,
    save_wav,
moto's avatar
moto committed
14
15
16
17
    sox_utils,
)
from .common import (
    name_func,
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
)


class SaveTestBase(TempDirMixin, PytorchTestCase):
    def assert_wav(self, dtype, sample_rate, num_channels, num_frames):
        """`sox_io_backend.save` can save wav format."""
        path = self.get_temp_path('data.wav')
        expected = get_wav_data(dtype, num_channels, num_frames=num_frames)
        sox_io_backend.save(path, expected, sample_rate)
        found, sr = load_wav(path)
        assert sample_rate == sr
        self.assertEqual(found, expected)

    def assert_mp3(self, sample_rate, num_channels, bit_rate, duration):
        """`sox_io_backend.save` can save mp3 format.

        mp3 encoding introduces delay and boundary effects so
        we convert the resulting mp3 to wav and compare the results there

                          |
                          | 1. Generate original wav file with SciPy
                          |
                          v
          -------------- wav ----------------
         |                                   |
         | 2.1. load with scipy              | 3.1. Convert to mp3 with Sox
         | then save with torchaudio         |
         v                                   v
        mp3                                 mp3
         |                                   |
         | 2.2. Convert to wav with Sox      | 3.2. Convert to wav with Sox
         |                                   |
         v                                   v
        wav                                 wav
         |                                   |
         | 2.3. load with scipy              | 3.3. load with scipy
         |                                   |
         v                                   v
        tensor -------> compare <--------- tensor

        """
        src_path = self.get_temp_path('1.reference.wav')
        mp3_path = self.get_temp_path('2.1.torchaudio.mp3')
        wav_path = self.get_temp_path('2.2.torchaudio.wav')
        mp3_path_sox = self.get_temp_path('3.1.sox.mp3')
        wav_path_sox = self.get_temp_path('3.2.sox.wav')

        # 1. Generate original wav
        data = get_wav_data('float32', num_channels, normalize=True, num_frames=duration * sample_rate)
        save_wav(src_path, data, sample_rate)
        # 2.1. Convert the original wav to mp3 with torchaudio
        sox_io_backend.save(
            mp3_path, load_wav(src_path)[0], sample_rate, compression=bit_rate)
        # 2.2. Convert the mp3 to wav with Sox
        sox_utils.convert_audio_file(mp3_path, wav_path)
        # 2.3. Load
        found = load_wav(wav_path)[0]

        # 3.1. Convert the original wav to mp3 with SoX
        sox_utils.convert_audio_file(src_path, mp3_path_sox, compression=bit_rate)
        # 3.2. Convert the mp3 to wav with Sox
        sox_utils.convert_audio_file(mp3_path_sox, wav_path_sox)
        # 3.3. Load
        expected = load_wav(wav_path_sox)[0]

        self.assertEqual(found, expected)

    def assert_flac(self, sample_rate, num_channels, compression_level, duration):
        """`sox_io_backend.save` can save flac format.

        This test takes the same strategy as mp3 to compare the result
        """
        src_path = self.get_temp_path('1.reference.wav')
        flc_path = self.get_temp_path('2.1.torchaudio.flac')
        wav_path = self.get_temp_path('2.2.torchaudio.wav')
        flc_path_sox = self.get_temp_path('3.1.sox.flac')
        wav_path_sox = self.get_temp_path('3.2.sox.wav')

        # 1. Generate original wav
        data = get_wav_data('float32', num_channels, normalize=True, num_frames=duration * sample_rate)
        save_wav(src_path, data, sample_rate)
        # 2.1. Convert the original wav to flac with torchaudio
        sox_io_backend.save(
            flc_path, load_wav(src_path)[0], sample_rate, compression=compression_level)
        # 2.2. Convert the flac to wav with Sox
        # converting to 32 bit because flac file has 24 bit depth which scipy cannot handle.
        sox_utils.convert_audio_file(flc_path, wav_path, bit_depth=32)
        # 2.3. Load
        found = load_wav(wav_path)[0]

        # 3.1. Convert the original wav to flac with SoX
        sox_utils.convert_audio_file(src_path, flc_path_sox, compression=compression_level)
        # 3.2. Convert the flac to wav with Sox
        # converting to 32 bit because flac file has 24 bit depth which scipy cannot handle.
        sox_utils.convert_audio_file(flc_path_sox, wav_path_sox, bit_depth=32)
        # 3.3. Load
        expected = load_wav(wav_path_sox)[0]

        self.assertEqual(found, expected)

    def _assert_vorbis(self, sample_rate, num_channels, quality_level, duration):
        """`sox_io_backend.save` can save vorbis format.

        This test takes the same strategy as mp3 to compare the result
        """
        src_path = self.get_temp_path('1.reference.wav')
        vbs_path = self.get_temp_path('2.1.torchaudio.vorbis')
        wav_path = self.get_temp_path('2.2.torchaudio.wav')
        vbs_path_sox = self.get_temp_path('3.1.sox.vorbis')
        wav_path_sox = self.get_temp_path('3.2.sox.wav')

        # 1. Generate original wav
        data = get_wav_data('int16', num_channels, normalize=False, num_frames=duration * sample_rate)
        save_wav(src_path, data, sample_rate)
        # 2.1. Convert the original wav to vorbis with torchaudio
        sox_io_backend.save(
            vbs_path, load_wav(src_path)[0], sample_rate, compression=quality_level)
        # 2.2. Convert the vorbis to wav with Sox
        sox_utils.convert_audio_file(vbs_path, wav_path)
        # 2.3. Load
        found = load_wav(wav_path)[0]

        # 3.1. Convert the original wav to vorbis with SoX
        sox_utils.convert_audio_file(src_path, vbs_path_sox, compression=quality_level)
        # 3.2. Convert the vorbis to wav with Sox
        sox_utils.convert_audio_file(vbs_path_sox, wav_path_sox)
        # 3.3. Load
        expected = load_wav(wav_path_sox)[0]

        # sox's vorbis encoding has some random boundary effect, which cause small number of
        # samples yields higher descrepency than the others.
        # so we allow small portions of data to be outside of absolute torelance.
        # make sure to pass somewhat long duration
        atol = 1.0e-4
        max_failure_allowed = 0.01  # this percent of samples are allowed to outside of atol.
        failure_ratio = ((found - expected).abs() > atol).sum().item() / found.numel()
        if failure_ratio > max_failure_allowed:
            # it's failed and this will give a better error message.
            self.assertEqual(found, expected, atol=atol, rtol=1.3e-6)

    def assert_vorbis(self, *args, **kwargs):
        # sox's vorbis encoding has some randomness, so we run tests multiple time
        max_retry = 5
        error = None
        for _ in range(max_retry):
            try:
                self._assert_vorbis(*args, **kwargs)
                break
            except AssertionError as e:
                error = e
        else:
            raise error


@skipIfNoExec('sox')
@skipIfNoExtension
class TestSave(SaveTestBase):
    @parameterized.expand(list(itertools.product(
        ['float32', 'int32', 'int16', 'uint8'],
        [8000, 16000],
        [1, 2],
moto's avatar
moto committed
179
    )), name_func=name_func)
180
181
182
183
184
185
186
187
    def test_wav(self, dtype, sample_rate, num_channels):
        """`sox_io_backend.save` can save wav format."""
        self.assert_wav(dtype, sample_rate, num_channels, num_frames=None)

    @parameterized.expand(list(itertools.product(
        ['float32'],
        [16000],
        [2],
moto's avatar
moto committed
188
    )), name_func=name_func)
189
190
191
192
193
194
195
196
    def test_wav_large(self, dtype, sample_rate, num_channels):
        """`sox_io_backend.save` can save large wav file."""
        two_hours = 2 * 60 * 60 * sample_rate
        self.assert_wav(dtype, sample_rate, num_channels, num_frames=two_hours)

    @parameterized.expand(list(itertools.product(
        ['float32', 'int32', 'int16', 'uint8'],
        [4, 8, 16, 32],
moto's avatar
moto committed
197
    )), name_func=name_func)
198
199
200
201
202
203
204
205
206
    def test_multiple_channels(self, dtype, num_channels):
        """`sox_io_backend.save` can save wav with more than 2 channels."""
        sample_rate = 8000
        self.assert_wav(dtype, sample_rate, num_channels, num_frames=None)

    @parameterized.expand(list(itertools.product(
        [8000, 16000],
        [1, 2],
        [-4.2, -0.2, 0, 0.2, 96, 128, 160, 192, 224, 256, 320],
moto's avatar
moto committed
207
    )), name_func=name_func)
208
209
210
211
212
213
214
215
    def test_mp3(self, sample_rate, num_channels, bit_rate):
        """`sox_io_backend.save` can save mp3 format."""
        self.assert_mp3(sample_rate, num_channels, bit_rate, duration=1)

    @parameterized.expand(list(itertools.product(
        [16000],
        [2],
        [128],
moto's avatar
moto committed
216
    )), name_func=name_func)
217
218
219
220
221
222
223
224
225
    def test_mp3_large(self, sample_rate, num_channels, bit_rate):
        """`sox_io_backend.save` can save large mp3 file."""
        two_hours = 2 * 60 * 60
        self.assert_mp3(sample_rate, num_channels, bit_rate, duration=two_hours)

    @parameterized.expand(list(itertools.product(
        [8000, 16000],
        [1, 2],
        list(range(9)),
moto's avatar
moto committed
226
    )), name_func=name_func)
227
228
229
230
231
232
233
234
    def test_flac(self, sample_rate, num_channels, compression_level):
        """`sox_io_backend.save` can save flac format."""
        self.assert_flac(sample_rate, num_channels, compression_level, duration=1)

    @parameterized.expand(list(itertools.product(
        [16000],
        [2],
        [0],
moto's avatar
moto committed
235
    )), name_func=name_func)
236
237
238
239
240
241
242
243
244
    def test_flac_large(self, sample_rate, num_channels, compression_level):
        """`sox_io_backend.save` can save large flac file."""
        two_hours = 2 * 60 * 60
        self.assert_flac(sample_rate, num_channels, compression_level, duration=two_hours)

    @parameterized.expand(list(itertools.product(
        [8000, 16000],
        [1, 2],
        [-1, 0, 1, 2, 3, 3.6, 5, 10],
moto's avatar
moto committed
245
    )), name_func=name_func)
246
247
248
249
250
251
252
253
254
255
256
257
    def test_vorbis(self, sample_rate, num_channels, quality_level):
        """`sox_io_backend.save` can save vorbis format."""
        self.assert_vorbis(sample_rate, num_channels, quality_level, duration=20)

    # note: torchaudio can load large vorbis file, but cannot save large volbis file
    # the following test causes Segmentation fault
    #
    '''
    @parameterized.expand(list(itertools.product(
        [16000],
        [2],
        [10],
moto's avatar
moto committed
258
    )), name_func=name_func)
259
260
261
262
263
264
265
266
267
268
269
    def test_vorbis_large(self, sample_rate, num_channels, quality_level):
        """`sox_io_backend.save` can save large vorbis file correctly."""
        two_hours = 2 * 60 * 60
        self.assert_vorbis(sample_rate, num_channels, quality_level, two_hours)
    '''


@skipIfNoExec('sox')
@skipIfNoExtension
class TestSaveParams(TempDirMixin, PytorchTestCase):
    """Test the correctness of optional parameters of `sox_io_backend.save`"""
moto's avatar
moto committed
270
    @parameterized.expand([(True, ), (False, )], name_func=name_func)
271
272
273
274
275
276
277
278
279
280
281
282
    def test_channels_first(self, channels_first):
        """channels_first swaps axes"""
        path = self.get_temp_path('data.wav')
        data = get_wav_data('int32', 2, channels_first=channels_first)
        sox_io_backend.save(
            path, data, 8000, channels_first=channels_first)
        found = load_wav(path)[0]
        expected = data if channels_first else data.transpose(1, 0)
        self.assertEqual(found, expected)

    @parameterized.expand([
        'float32', 'int32', 'int16', 'uint8'
moto's avatar
moto committed
283
    ], name_func=name_func)
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
    def test_noncontiguous(self, dtype):
        """Noncontiguous tensors are saved correctly"""
        path = self.get_temp_path('data.wav')
        expected = get_wav_data(dtype, 4)[::2, ::2]
        assert not expected.is_contiguous()
        sox_io_backend.save(path, expected, 8000)
        found = load_wav(path)[0]
        self.assertEqual(found, expected)

    @parameterized.expand([
        'float32', 'int32', 'int16', 'uint8',
    ])
    def test_tensor_preserve(self, dtype):
        """save function should not alter Tensor"""
        path = self.get_temp_path('data.wav')
        expected = get_wav_data(dtype, 4)[::2, ::2]

        data = expected.clone()
        sox_io_backend.save(path, data, 8000)

        self.assertEqual(data, expected)