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Summary:
Add rowwise prune pytorch op.

This operator introduces sparsity to the 'weights' matrix with the help
of the importance indicator 'mask'.

A row is considered important and not pruned if the mask value for that
particular row is 1(True) and not important otherwise.

Test Plan:
buck test caffe2/torch/fb/sparsenn:test -- rowwise_prune
buck test caffe2/test:pruning

Differential Revision: D22849432

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This pull request was exported from Phabricator. Differential Revision: D22849432

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dr-ci bot commented Aug 7, 2020

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@radkris-git
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Addressed comments.

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This pull request was exported from Phabricator. Differential Revision: D22849432

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This pull request was exported from Phabricator. Differential Revision: D22849432

@facebook-github-bot
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This pull request was exported from Phabricator. Differential Revision: D22849432

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This pull request was exported from Phabricator. Differential Revision: D22849432

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This pull request was exported from Phabricator. Differential Revision: D22849432

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This pull request was exported from Phabricator. Differential Revision: D22849432

Summary:
Pull Request resolved: pytorch#42708

Add rowwise prune pytorch op.

This operator introduces sparsity to the 'weights' matrix with the help
of the importance indicator 'mask'.

A row is considered important and not pruned if the mask value for that
particular row is 1(True) and not important otherwise.

Test Plan:
buck test caffe2/torch/fb/sparsenn:test -- rowwise_prune
buck test caffe2/test:pruning

Reviewed By: supriyar

Differential Revision: D22849432

fbshipit-source-id: b9eaa128fd8b8d63cf1aa2270dbb23f7816bf79d
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This pull request was exported from Phabricator. Differential Revision: D22849432

albanD added a commit to albanD/pytorch that referenced this pull request Oct 9, 2020
malfet pushed a commit that referenced this pull request Oct 12, 2020
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4 participants