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Summary

  1. Support weight sharing with compile spec
  2. Support weight sharing feature to llama export script and runner
  3. Optimize llama performance

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pytorch-bot bot commented Sep 4, 2025

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/13941

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❌ 3 New Failures

As of commit 6b30094 with merge base b02db12 (image):

NEW FAILURES - The following jobs have failed:

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@meta-cla meta-cla 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 Sep 4, 2025
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cccclai commented Sep 4, 2025

@neuropilot-captain I think the PR needs to rebase

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cccclai commented Sep 5, 2025

There is still lint error...can you fix it?

@cccclai cccclai merged commit a90e907 into pytorch:main Sep 8, 2025
113 of 116 checks passed
Comment on lines +156 to +157
mPlannedBuffers.push_back(std::make_unique<uint8_t[]>(buffer_size));
mPlannedSpans.push_back({mPlannedBuffers.back().get(), buffer_size});
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nit: use emplace_back

ET_LOG(Debug, "Setting up planned buffer %zu, size %zu.", id, buffer_size);
planned_buffers.push_back(std::make_unique<uint8_t[]>(buffer_size));
planned_spans.push_back({planned_buffers.back().get(), buffer_size});
auto modelInstance = new ModelInstance(modelPath);
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use unique_ptr; this will leak if anything in here throws

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3 participants