GPU-based vectorized Specaug Version 2 #9155
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Signed-off-by: Piotr Żelasko <petezor@gmail.com>
Signed-off-by: Piotr Żelasko <petezor@gmail.com>
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I visually inspected that the masks look correct on random spectrograms. I also ran a training with this variant in Nsight profiler and noticed the specaug computation mostly disappeared from the profile. It is estimated to be about 4-5x faster than the variant proposed in #9041 which would make it 8-10x faster than the original version (still available as the "legacy" setting).
LGTM!
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pzelasko
dismissed
their stale review
requested update to another version with some extra fixes
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After this I think that we may also have to add the flag in the audio processing module: And also we may have to add a test, adding the pytest run_only_on('GPU') flag the same it is done for the numba code: |
Signed-off-by: Alessandro Morari <amorari@nvidia.com>
Signed-off-by: Alessandro Morari <amorari@nvidia.com>
Signed-off-by: Alessandro Morari <amorari@nvidia.com>
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@amorari-nvidia As a last thing, could you remove the numba specaug implementation altogether in this PR? IIRC it will automatically kick in with numba 0.58 (or when numba+cuda versions are compatible for earlier versions), overriding the implementation here. CC @titu1994 pls double check if I'm right about this. |
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Waiting for confirmation from @titu1994 |
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You can remove it entirely, or set the default flag of numba cuda to false. I think that's sufficient for the time being. If you can remove it cleanly, then that's fine too |
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I will just set the Numba version default flag to false for now |
Signed-off-by: pzelasko <pzelasko@users.noreply.github.com>
The Numba SpecAugment version is already set to false, while the vectorized version is set to true and is the default code. |
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great, re-triggered tests, LGTM as soon as it's green |
CI passed |
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Congrats @amorari-nvidia on the first contribution! |
What does this PR do ?
This PR proposes a faster version of the Spectrogram Augmentation module for time and frequency masking.