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[TRTLLM-5921][feat] Prevent serialization of entire LoRA adapters in each request #5080
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[TRTLLM-5921][feat] Prevent serialization of entire LoRA adapters in each request #5080
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/bot run --stage-list "DGX_H100-4_GPUs-PyTorch-Others-1" |
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One small last comment.
LGTM
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…apter wasn't previously loaded Signed-off-by: Amit Zuker <[email protected]>
Signed-off-by: Amit Zuker <[email protected]>
…f, load_from_nemo Signed-off-by: Amit Zuker <[email protected]>
Signed-off-by: Amit Zuker <[email protected]>
…ew uids are found Signed-off-by: Amit Zuker <[email protected]>
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…each request (NVIDIA#5080) Signed-off-by: Amit Zuker <[email protected]>
…each request (NVIDIA#5080) Signed-off-by: Amit Zuker <[email protected]>
…each request (NVIDIA#5080) Signed-off-by: Amit Zuker <[email protected]>
…each request (NVIDIA#5080) Signed-off-by: Amit Zuker <[email protected]>
…each request (NVIDIA#5080) Signed-off-by: Amit Zuker <[email protected]>
…each request (NVIDIA#5080) Signed-off-by: Amit Zuker <[email protected]>
…each request (NVIDIA#5080) Signed-off-by: Amit Zuker <[email protected]>
…each request (NVIDIA#5080) Signed-off-by: Amit Zuker <[email protected]>
Description
Make LoRA pytorch to broadcast weights & config tensors only on new LoRA adapter, so when the adapter is already loaded on rank 0 (and thus, should be loaded on other ranks as well), only the adapter ID is sent in the request.
NOTE: The changes in this PR cause requests with a LoRA adapter that were previously unloaded from LoRA CPU cache not to work, as they remain in
_cpp_lora_weights
inLoraManager
python class. It was decided that for now this flow is not supported, in favor of its significant performance boost.Test Coverage
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