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jagged_dense_elementwise_mul add Meta and Autograd backend #1469

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Summary:
Add Meta and Autograd backend for jagged_dense_elementwise_mul for dynamo and AOT autograd.

A more proper way of doing Autograd to make inductor working for jagged ops. Also added Meta tensors so we're not mercy of arbitrary zero inputs fed into by default.

Differential Revision: D41383597

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This pull request was exported from Phabricator. Differential Revision: D41383597

brad-mengchi added a commit to brad-mengchi/FBGEMM that referenced this pull request Nov 21, 2022
)

Summary:
Pull Request resolved: pytorch#1469

Add Meta and Autograd backend for jagged_dense_elementwise_mul for dynamo and AOT autograd.

A more proper way of doing Autograd to make inductor working for jagged ops. Also added Meta tensors so we're not mercy of arbitrary zero inputs fed into by default.

Differential Revision: D41383597

fbshipit-source-id: e2ba6bfe7128c7f3b7557cf2b0e5bae48b69362f
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This pull request was exported from Phabricator. Differential Revision: D41383597

brad-mengchi added a commit to brad-mengchi/FBGEMM that referenced this pull request Nov 23, 2022
)

Summary:
Pull Request resolved: pytorch#1469

Add Meta and Autograd backend for jagged_dense_elementwise_mul for dynamo and AOT autograd.

A more proper way of doing Autograd to make inductor working for jagged ops. Also added Meta tensors so we're not mercy of arbitrary zero inputs fed into by default.

Differential Revision: D41383597

fbshipit-source-id: 75bd2072b9f8f47e7e3dd3e5a26bdaaf047c6672
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This pull request was exported from Phabricator. Differential Revision: D41383597

brad-mengchi added a commit to brad-mengchi/FBGEMM that referenced this pull request Nov 23, 2022
)

Summary:
Pull Request resolved: pytorch#1469

Add Meta and Autograd backend for jagged_dense_elementwise_mul for dynamo and AOT autograd.

A more proper way of doing Autograd to make inductor working for jagged ops. Also added Meta tensors so we're not mercy of arbitrary zero inputs fed into by default.

Differential Revision: D41383597

fbshipit-source-id: 9feff915dbcb59e989bafbad53ba152fd57566cb
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This pull request was exported from Phabricator. Differential Revision: D41383597

jianyuh and others added 4 commits November 22, 2022 22:43
Summary:
Pull Request resolved: pytorch#1472

As title

Reviewed By: brad-mengchi, jiawenliu64

Differential Revision: D41445777

fbshipit-source-id: 7b2ea96b41043b733db9e83f1fdec898c4ebe306
Differential Revision: https://internalfb.com/D41367064

fbshipit-source-id: 8e6d38d54ac47dcf9bd0453bc4d869810a8d03cb
Differential Revision: D41368350

fbshipit-source-id: 0423f9dc5df65f2a94bbd13c65fcc796b5905579
)

Summary:
Pull Request resolved: pytorch#1469

Add Meta and Autograd backend for jagged_dense_elementwise_mul for dynamo and AOT autograd.

A more proper way of doing Autograd to make inductor working for jagged ops. Also added Meta tensors so we're not mercy of arbitrary zero inputs fed into by default.

Differential Revision: D41383597

fbshipit-source-id: 8b696852af78d93d0abe65e549087a8f683476b9
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This pull request was exported from Phabricator. Differential Revision: D41383597

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3 participants