batched_dense_vec_jagged_2d_mul add Meta and Autograd backend #1468
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This pull request was exported from Phabricator. Differential Revision: D41387994 |
Summary: Pull Request resolved: pytorch#1472 As title Reviewed By: brad-mengchi, jiawenliu64 Differential Revision: D41445777 fbshipit-source-id: 510e30e2292b617944ebb7a7d2fe51f0a544f529
Differential Revision: https://internalfb.com/D41367064 fbshipit-source-id: 6f2a7b923dc337548d87aa2828e431dab40bc706
Differential Revision: D41368350 fbshipit-source-id: 21519b9b4017ed480217011bee74051c465f6e03
Differential Revision: D41383597 fbshipit-source-id: 7aeed19578feb3ceffbac3a28c562222123b195f
…h#1468) Summary: Pull Request resolved: pytorch#1468 Add Meta and Autograd backend for batched_dense_vec_jagged_2d_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: D41387994 fbshipit-source-id: 827d2fb26c8c173c4af9bb52b7fadf75ded1105b
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This pull request was exported from Phabricator. Differential Revision: D41387994 |
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Summary:
Add Meta and Autograd backend for batched_dense_vec_jagged_2d_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: D41387994