Support un-fused batchnorm1d/2d on XNNPACK via decomposition #16533
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/16533
Note: Links to docs will display an error until the docs builds have been completed. ❌ 3 New Failures, 1 Unrelated FailureAs of commit 1aa7400 with merge base 3dd80c1 ( NEW FAILURES - The following jobs have failed:
UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:
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module: xnnpack
…#16533) Summary: Add a new pass - DecomposeBatchNorm - which converts standalone (non-fused) batch norm operators to 1x1 depthwise convolution. This prevents delegation graph breaks when batch norm operators can't be fused. Differential Revision: D90422630
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Summary: Add a new pass - DecomposeBatchNorm - which converts standalone (non-fused) batch norm operators to 1x1 depthwise convolution. This prevents delegation graph breaks when batch norm operators can't be fused.
Differential Revision: D90422630
cc @digantdesai @cbilgin