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Fix for interctc test random failure #6644

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May 26, 2023
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@Kipok Kipok commented May 12, 2023

What does this PR do ?

I finally figured out the reason for random failure of this test. It turns out that sometimes our input signal is such that for some models it results in all-zeros in the output of some initial encoder layers. This is then propagated all the way through the model and so the assert that final layer output is different from middle layer fails. After changing the code to pass processed signal directly, this should not happen anymore.

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@Kipok Kipok requested a review from titu1994 May 12, 2023 00:39
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This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.

@github-actions github-actions bot added the stale label May 26, 2023
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Seems reasonable but you sure the zeros generation won't affect model padding during actual training ?

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Kipok commented May 26, 2023

Seems reasonable but you sure the zeros generation won't affect model padding during actual training ?

There is no real issue here, it's just that I test that the output of different layers is different, but when they are all zeros, this breaks. The logic in the code needs no changes.

@Kipok Kipok merged commit b50ae98 into NVIDIA:main May 26, 2023
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hsiehjackson pushed a commit to hsiehjackson/NeMo that referenced this pull request Jun 2, 2023
Signed-off-by: Igor Gitman <[email protected]>
Signed-off-by: hsiehjackson <[email protected]>
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