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Previously, at::native::embedding implicitly assumed that the weight argument would be 1-D or greater. Given a 0-D tensor, it would segfault. This change makes it throw a RuntimeError instead.

Fixes #41780

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dr-ci bot commented Aug 4, 2020

💊 CI failures summary and remediations

As of commit fd7b249 (more details on the Dr. CI page):


None of the CI failures appear to be your fault 💚



🚧 1 fixed upstream failure:

These were probably caused by upstream breakages that were already fixed.

Please rebase on the viable/strict branch (expand for instructions)

Since your merge base is older than viable/strict, run these commands:

git fetch https://github.com/pytorch/pytorch viable/strict
git rebase FETCH_HEAD

Check out the recency history of this "viable master" tracking branch.


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This comment has been revised 2 times.

@ailzhang ailzhang added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label Aug 7, 2020
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LGTM
Thanks for the fix !

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

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@albanD merged this pull request in 42b4a71.

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segfault in torch.nn.functional.embedding

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