[ExecuTorch][llm] Add MoE source transformation with INT4 quantized packing#21121
[ExecuTorch][llm] Add MoE source transformation with INT4 quantized packing#21121digantdesai wants to merge 2 commits into
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21121
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ❌ 4 New Failures, 1 Unrelated FailureAs of commit 11b27ac with merge base bfed808 ( NEW FAILURES - The following jobs have failed:
BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Add
moe.pywith aQuantizedMoEFFNmodule wrappingllama::quantized_moe_ffn, INT4 symmetric group quantization, torchao packing, and recursive module replacement. Preserve fp32 buffers and output dtype across model casts.Dequantize a torchao-quantized gate into the custom op fp32 buffer so QAT models can be captured by
torch.exportwithout tensor-subclass dispatch failures.Differential Revision: D102381994