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Use portable lib for finetuning demo #8613
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/8613
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit cfe0472 with merge base 9c51e58 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This pull request was exported from Phabricator. Differential Revision: D69954671 |
Summary: Update the example of LLM fine-tuning on ET using portable_lib and XNNPack backend Differential Revision: D69954671
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node.op == "call_function" | ||
and node.target == torch.ops.aten.empty_permuted.out | ||
): | ||
print("find empty_permute: ", node) |
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nit: I think the past tense "found" is more typical for log output than the present tense "find"
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Makes sense. Will update it, thanks!
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Looks good to me. cc @mergennachin who had been thinking about using a different repo for examples.
Summary: Update the example of LLM fine-tuning on ET using portable_lib and XNNPack backend Reviewed By: JacobSzwejbka Differential Revision: D69954671
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This pull request was exported from Phabricator. Differential Revision: D69954671 |
Summary: Update the example of LLM fine-tuning on ET using portable_lib and XNNPack backend Reviewed By: JacobSzwejbka Differential Revision: D69954671
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This pull request was exported from Phabricator. Differential Revision: D69954671 |
Summary: Update the example of LLM fine-tuning on ET using portable_lib and XNNPack backend Reviewed By: JacobSzwejbka Differential Revision: D69954671
a9ac4be
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cfe0472
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This pull request was exported from Phabricator. Differential Revision: D69954671 |
Summary: Update the example of LLM fine-tuning on ET using portable_lib and XNNPack backend
Differential Revision: D69954671