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Samuel Moors
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adding easyconfigs: torchaudio-2.6.0-foss-2024a.eb and patches: torchaudio-2.6.0_fix_tests.patch, torchaudio-2.6.0_use_ffmpeg7.patch
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easyblock = 'PythonBundle'
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name = 'torchaudio'
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version = '2.6.0'
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homepage = 'https://github.com/pytorch/audio'
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description = """ Data manipulation and transformation for audio signal
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processing, powered by PyTorch """
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toolchain = {'name': 'foss', 'version': '2024a'}
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builddependencies = [
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('CMake', '3.29.3'),
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('Ninja', '1.12.1'),
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('parameterized', '0.9.0'), # for tests
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('scikit-learn', '1.5.2'), # for tests
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('librosa', '0.10.2.post1'), # for tests
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]
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dependencies = [
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('Python', '3.12.3'),
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('PyTorch', version),
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('FFmpeg', '7.0.2'),
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('SoX', '14.4.2'),
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]
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exts_list = [
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(name, version, {
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'installopts': '-v',
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'patches': [
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'torchaudio-%(version)s_use_ffmpeg7.patch',
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'torchaudio-%(version)s_fix_tests.patch',
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],
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'preinstallopts': ('unset BUILD_VERSION && rm -r third_party/{sox,ffmpeg/multi};' # runs twice when testinstall
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' USE_CUDA=0 USE_OPENMP=1 USE_FFMPEG=1 FFMPEG_ROOT="$EBROOTFFMPEG" BUILD_SOX=0'),
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'source_urls': ['https://github.com/pytorch/audio/archive'],
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'sources': [{'download_filename': 'v%(version)s.tar.gz', 'filename': '%(name)s-%(version)s.tar.gz'}],
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'runtest': (
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'export OMP_NUM_THREADS=%(parallel)s && '
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'pytest test/torchaudio_unittest/'
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' -k "not TestProcessPoolExecutor"' # hang maybe related https://github.com/pytorch/audio/issues/1021
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'" and not FilterGraphWithCudaAccel"' # requires FFmpeg with CUDA support
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'" and not kaldi_io_test"' # requires kaldi_io
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'" and not test_dup_hw_acel"' # requires special render device permissions
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'" and not test_h264_cuvid"' # requires special render device permissions
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'" and not test_hevc_cuvid"' # requires special render device permissions
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),
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'testinstall': True,
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'checksums': [
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{'torchaudio-2.6.0.tar.gz': '3335d8fcf58c26acf3c628d751103b59226e01c91847ce56efb2a4e7ae8351ef'},
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{'torchaudio-2.6.0_use_ffmpeg7.patch': '1a2f7505efee9852ef393e6f4583cef209ad302db241171bf41be8d4a88920bd'},
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{'torchaudio-2.6.0_fix_tests.patch': '3964df416b64a30eb20928c1392c588ae92def8a4a17b0b0e8b69a8a20e093b0'},
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],
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}),
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]
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moduleclass = 'ai'
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Increase the atol and rtol for tests that fail with some elements exceeding default tolerances.
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Remove failing version check for librosa-0.10.2.post1
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Author: Samuel Moors (Vrije Universiteit Brussel)
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diff -ur audio-2.6.0.orig/test/torchaudio_unittest/functional/librosa_compatibility_test_impl.py audio-2.6.0/test/torchaudio_unittest/functional/librosa_compatibility_test_impl.py
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--- audio-2.6.0.orig/test/torchaudio_unittest/functional/librosa_compatibility_test_impl.py 2025-01-29 02:11:55.000000000 +0100
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+++ audio-2.6.0/test/torchaudio_unittest/functional/librosa_compatibility_test_impl.py 2025-12-03 16:55:39.426408000 +0100
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@@ -1,5 +1,4 @@
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import unittest
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-from distutils.version import StrictVersion
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import torch
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import torchaudio.functional as F
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@@ -77,8 +76,6 @@
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def test_create_mel_fb(
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self, n_mels=40, sample_rate=22050, n_fft=2048, fmin=0.0, fmax=8000.0, norm=None, mel_scale="htk"
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):
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- if norm == "slaney" and StrictVersion(librosa.__version__) < StrictVersion("0.7.2"):
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- self.skipTest("Test is known to fail with older versions of librosa.")
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if self.device != "cpu":
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self.skipTest("No need to run this test on CUDA")
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diff -ur audio-2.6.0.orig/test/torchaudio_unittest/transforms/batch_consistency_test.py audio-2.6.0/test/torchaudio_unittest/transforms/batch_consistency_test.py
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--- audio-2.6.0.orig/test/torchaudio_unittest/transforms/batch_consistency_test.py 2025-01-29 02:11:55.000000000 +0100
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+++ audio-2.6.0/test/torchaudio_unittest/transforms/batch_consistency_test.py 2025-12-04 09:30:50.369565944 +0100
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@@ -89,7 +89,7 @@
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waveform = waveform.reshape(3, 2, -1)
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transform = T.Spectrogram()
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- self.assert_batch_consistency(transform, waveform)
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+ self.assert_batch_consistency(transform, waveform, atol=1e-7, rtol=1e-4)
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def test_batch_inverse_spectrogram(self):
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waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=6)
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specgram = specgram.reshape(3, 2, specgram.shape[-2], specgram.shape[-1])
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transform = T.InverseSpectrogram(n_fft=400)
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- self.assert_batch_consistency(transform, specgram)
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+ self.assert_batch_consistency(transform, specgram, atol=1e-7, rtol=1e-3)
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def test_batch_melspectrogram(self):
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waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=6)
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waveform = waveform.reshape(3, 2, -1)
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transform = T.PitchShift(sample_rate, n_steps, n_fft=400)
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- self.assert_batch_consistency(transform, waveform)
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+ self.assert_batch_consistency(transform, waveform, atol=1e-5, rtol=1e-2)
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def test_batch_PSD(self):
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waveform = common_utils.get_whitenoise(sample_rate=8000, duration=1, n_channels=6)

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