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[Hardware] [HPU]add mark_step
for hpu
#10239
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👋 Hi! Thank you for contributing to the vLLM project. Once the PR is approved and ready to go, your PR reviewer(s) can run CI to test the changes comprehensively before merging. To run CI, PR reviewers can do one of these:
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Signed-off-by: Kunshang Ji <[email protected]>
Hi @jikunshang . Could the same functionality be implemented using stock PT functionalities like forward hooks (https://pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module.register_forward_hook)? I guess we only need to call mark_step() and there's no other complex logic involved. |
Signed-off-by: Kunshang Ji <[email protected]>
nice catch, addressed your comments. please take a look again, thanks! |
@madamczykhabana Please take a look. I will merge the PR once you approve it. |
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LGTM
@WoosukKwon Can we merge this now? |
Sorry for missing this! |
Signed-off-by: Kunshang Ji <[email protected]> Signed-off-by: Linkun Chen <[email protected]>
Signed-off-by: Kunshang Ji <[email protected]>
Signed-off-by: Kunshang Ji <[email protected]>
Signed-off-by: Kunshang Ji <[email protected]> Signed-off-by: Maxime Fournioux <[email protected]>
Signed-off-by: Kunshang Ji <[email protected]> Signed-off-by: rickyx <[email protected]>
Signed-off-by: Kunshang Ji <[email protected]> Signed-off-by: Tyler Michael Smith <[email protected]>
We are seeing 10% performance regression in the llama-based model due to vllm-project#10239. The mark_step() function needs to be configured differently for each model to achieve the best performance. For some models, mark_step() for every decoder step would be optimal, but for other models, it's better to run it every n-th step. We are adding a counter to only register the hook for every n-th step, which can be configured with VLLM_CONFIG_HIDDEN_LAYERS
Signed-off-by: Kunshang Ji <[email protected]>
Signed-off-by: Kunshang Ji <[email protected]>
This PR add
mark_step
after each model's decoder layer, which could benefit performance and not break origin model files.mark_step doc
cc @kzawora-intel