[ET-VK] Miscellaneous fixes #14803
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[ET-VK] Miscellaneous fixes #14803
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Collecting fixes for various models/ops in this diff/PR. They have all been squashed into this single change to make it easier to cherry pick. # Fixes ## Wav2Letter Type: Output correctness failure This is caused by a bug in swiftshader, and not reproducible on any other platform. Specifically, the issue is in the softmax shader; the exact cause of the issue is unknown, but it is related to using shared memory within shaders. The workaround for this issue is to use separate shared memory arrays for the shared max and shared sum. ## ConvNeXT Type: Exception during runtime This is caused by an incompatible memory layout being used for mean2d. More technically, the packed dimension of the tensor cannot be one of the dims being reduced. The current operator registry system did not have a way to select valid tensor representations based on the actual arguments of an op. To fix, we have to introduce a mechanism for ops to specify valid representations once a node's arguments are known. Once the model is exported with supported memory layout, the model test passes. ## Inception_V3/ViT Type: Exception during runtime The root cause of this was an interaction betwen the fuse batch norm pass and how `vulkan_preprocess.py` was applying passes. Essentially, the fuse batch norm pass creates a new param node for the fused weight, but after the pass is applied `_copy_module` is used to copy the transformed graph back into the ExportedProgram. However, it seems that _copy_module lowercases the node names without updating the exported program's graph signature. Therefore, subsequent passes couldn't recognize the weight tensor of convolution tensors as a constant/parameter node. The solution was to migrate vulkan_preprocess.py to use the _transform() API instead of using _copy_module. ## DenseNet 161 (w/ dynamic shapes) Type: Output Mismatch Cause: the native_batch_norm op doesn't support dynamic shapes. However, the backend test runner doesn't set the correct compile option to filter ops without dynamic shape support. Differential Revision: [D83703496](https://our.internmc.facebook.com/intern/diff/D83703496/) [ghstack-poisoned] (cherry picked from commit 3f0896a)
This was referenced Oct 4, 2025
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14803
Note: Links to docs will display an error until the docs builds have been completed. ❌ 5 New Failures, 2 Cancelled Jobs, 1 Unrelated FailureAs of commit 98d5969 with merge base e0dda90 ( NEW FAILURES - The following jobs have failed:
CANCELLED JOBS - The following jobs were cancelled. Please retry:
FLAKY - The following job failed but was likely due to flakiness present on trunk:
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This PR was created by the merge bot to help merge the original PR into the main branch.
ghstack PR number: #14732 by @SS-JIA
^ Please use this as the source of truth for the PR details, comments, and reviews
ghstack PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/335/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/335/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/main
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/335/orig
Differential Revision: D83703496
@diff-train-skip-merge