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Arm backend: Enable VGF KV-cache aliasing in LLM export - #24680
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xingguo01 merged 2 commits intoNov 9, 2026
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/24680
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zingo
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Nov 9, 2026
Expose mutable buffer aliasing through the LLM export configuration and forward it to the VGF partitioner for static quantized KV caches. Update the SmolLM2 VGF example with the supported export command, persistent runner handling, timestamp reporting, and parallel WikiText perplexity scoring. Wait for runner completion before reading logits, kill hung runners during cleanup, and let evaluation select the KV input dtype. Support tokenizers without a BOS token. AI-assisted-by: Codex Change-Id: Id001b3fde168262ed748b03498d278d594bbfa0b Signed-off-by: Xingguo Li <xingguo.li@arm.com>
Read mutated non-persistent buffers from ExportedProgram.constants when resetting static VGF KV state. Keep state_dict lookup for persistent buffers so both storage paths match the graph signature. Cover both persistence modes with StaticQuantizedKVCache, including zero initialization, retained scales, subsequent updates, and dtype validation. AI-assisted-by: Codex Change-Id: Ie8364ccb6f9ddb3ea680e2aaf8b71508a564e699 Signed-off-by: Xingguo Li <xingguo.li@arm.com>
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Expose mutable buffer aliasing through the LLM export configuration and forward it to the VGF partitioner for static quantized KV caches.
Update the SmolLM2 VGF example with the supported export command, persistent runner handling, timestamp reporting, and parallel WikiText perplexity scoring. Wait for runner completion before reading logits, kill hung runners during cleanup, and let evaluation select the KV input dtype. Support tokenizers without a BOS token.
AI-assisted-by: Codex
cc @digantdesai @freddan80 @per @zingo @oscarandersson8218 @mansnils @Sebastian-Larsson @robell @rascani