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Summary:
Add overwrite precision of linear op in partitioning.

When using legacy_mode, we will test we don't partition [add]mm given,
(1) We can't assume that weights are always static (non param).
(2) Alternatively, when lowering [add]mm to xnn::bmm we can't support bias.
(2)(a) Only lowering non-bias [add]mm, which is only exposed on legacy_path deemed low ROI.

Added tests to make sure we see this behavior

Differential Revision: D67011716

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pytorch-bot bot commented Dec 11, 2024

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@facebook-github-bot facebook-github-bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Dec 11, 2024
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This pull request was exported from Phabricator. Differential Revision: D67011716

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digantdesai added a commit to digantdesai/executorch-1 that referenced this pull request Dec 11, 2024
…7284)

Summary:
Pull Request resolved: pytorch#7284

Add overwrite precision of linear op in partitioning.

When using legacy_mode, we will test we don't partition [add]mm given,
(1) We can't assume that weights are always static (non param).
(2) Alternatively, when lowering [add]mm to xnn::bmm we can't support bias.
(2)(a) Only lowering non-bias [add]mm, which is only exposed on legacy_path deemed low ROI.

Added tests to make sure we see this behavior

Differential Revision: D67011716
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This pull request was exported from Phabricator. Differential Revision: D67011716

digantdesai added a commit to digantdesai/executorch-1 that referenced this pull request Dec 11, 2024
…7284)

Summary:
Pull Request resolved: pytorch#7284

Add overwrite precision of linear op in partitioning.

When using legacy_mode, we will test we don't partition [add]mm given,
(1) We can't assume that weights are always static (non param).
(2) Alternatively, when lowering [add]mm to xnn::bmm we can't support bias.
(2)(a) Only lowering non-bias [add]mm, which is only exposed on legacy_path deemed low ROI.

Added tests to make sure we see this behavior

Differential Revision: D67011716
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This pull request was exported from Phabricator. Differential Revision: D67011716

digantdesai added a commit to digantdesai/executorch-1 that referenced this pull request Dec 17, 2024
…7284)

Summary:

Add overwrite precision of linear op in partitioning.

When using legacy_mode, we will test we don't partition [add]mm given,
(1) We can't assume that weights are always static (non param).
(2) Alternatively, when lowering [add]mm to xnn::bmm we can't support bias.
(2)(a) Only lowering non-bias [add]mm, which is only exposed on legacy_path deemed low ROI.
        
Added tests to make sure we see this behavior

Reviewed By: mcr229

Differential Revision: D67011716
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This pull request was exported from Phabricator. Differential Revision: D67011716

@digantdesai digantdesai added the module: xnnpack Issues related to xnnpack delegation and the code under backends/xnnpack/ label Dec 17, 2024
digantdesai added a commit to digantdesai/executorch-1 that referenced this pull request Dec 17, 2024
…7284)

Summary:

Add overwrite precision of linear op in partitioning.

When using legacy_mode, we will test we don't partition [add]mm given,
(1) We can't assume that weights are always static (non param).
(2) Alternatively, when lowering [add]mm to xnn::bmm we can't support bias.
(2)(a) Only lowering non-bias [add]mm, which is only exposed on legacy_path deemed low ROI.
        
Added tests to make sure we see this behavior

Reviewed By: mcr229

Differential Revision: D67011716
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This pull request was exported from Phabricator. Differential Revision: D67011716

…7284)

Summary:

Add overwrite precision of linear op in partitioning.

When using legacy_mode, we will test we don't partition [add]mm given,
(1) We can't assume that weights are always static (non param).
(2) Alternatively, when lowering [add]mm to xnn::bmm we can't support bias.
(2)(a) Only lowering non-bias [add]mm, which is only exposed on legacy_path deemed low ROI.
        
Added tests to make sure we see this behavior

Reviewed By: mcr229

Differential Revision: D67011716
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This pull request was exported from Phabricator. Differential Revision: D67011716

@facebook-github-bot facebook-github-bot merged commit 884d16d into pytorch:main Dec 18, 2024
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