NVIDIA / NVIDIA/TensorRT-LLM

Consider using pre-built Flash Attention kernels via `kernels`

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Customized kernels
Dominant language
Python
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Description

Hey,

I am Sayak from the Kernels team at Hugging Face. I noticed that this project uses Flash Attention which includes a long build time. We ship pre-built binaries (which provide bit-exact outputs as the upstream) and thereby, we make it easy to use.

Using FA3 on a supported machine is as easy as:

# make sure `kernels` is installed: `pip install -U kernels`
from kernels import get_kernel

kernel_module = get_kernel("kernels-community/flash-attn3")
flash_attn_func = kernel_module.flash_attn_func

flash_attn_func(...)

Let us know if you'd be interested in this and and we'd be happy to provide a draft of how it would look in your repo.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

The issue names no files or tests. Start by locating the existing Flash Attention integration and its build path, then compare it with the proposed kernels installation and get_kernel API. Done would require an agreed integration scope plus validation that supported inference paths preserve behavior and improve or avoid the current build cost.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
performance
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
38/100

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