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@wanchaol wanchaol commented Mar 28, 2019

Fixes the problem of #18391

The issue is that when we code gen the ATenOp, we always generated static number of outputs for each operator. E.g. If there's operator from a old model that only requires two outputs, in its createOperator it will only allocate two output blobs, while the newer version of the operator (unique in this case) requires more output blob to be allocated.

@wanchaol wanchaol force-pushed the atenop branch 2 times, most recently from 3bac07c to c76d5c7 Compare March 29, 2019 00:19
@wanchaol wanchaol marked this pull request as ready for review March 29, 2019 00:26
@wanchaol wanchaol force-pushed the atenop branch 2 times, most recently from 63236f4 to 5c3ee8a Compare March 29, 2019 22:20
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removed this since we don't have ones supported either way.

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Seems correct, thanks! Let see if this works for serialized models with a new binary

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also try only ["output"]?

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@wanchaol has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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@wanchaol merged this pull request in 56b18ea.

zhangguanheng66 pushed a commit to zhangguanheng66/pytorch that referenced this pull request May 6, 2019
Summary:
Fixes the problem of pytorch#18391

The issue is that when we code gen the ATenOp, we always generated static number of outputs for each operator. E.g. If there's operator from a old model that only requires two outputs, in its createOperator it will only allocate two output blobs, while the newer version of the operator (`unique` in this case) requires more output blob to be allocated.
Pull Request resolved: pytorch#18581

Differential Revision: D14865647

Pulled By: wanchaol

fbshipit-source-id: 85f63fe16d6fe408a09eca84798c7e8cab3070e9
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4 participants