[AMD][Hardware][Misc][Bugfix] xformer cleanup and light navi logic and CI fixes and refactoring

[hongxiayang]

This PR is
(1) to remove xformer package and patches since right now raw flash attention api is called instead of using xformers wrapper.
(2) to facilitate gfx1100/navi3x to use triton flash-attn.
(3) still make it possible for other gfx target to use flash-attn and updated the flash-attention branch.

(4) fixed the CI failure for "basic correctness" issue on cuda env

FIX #xxxx (link existing issues this PR will resolve)

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[hongxiayang]

I could not reproduce the failed "Basic Correctness Test" shown in the CI when running in my dev environment.

[hliuca]

I could not reproduce the failed "Basic Correctness Test" shown in the CI when running in my dev environment.

It looks the testing env using CUDA version Triton, not from ROCm?

pip uninstall -y triton
&& git clone https://github.com/ROCm/triton.git
&& cd triton/python
&& pip3 install .
&& cd ../

[WoosukKwon]

LGTM! Thanks for the PR!

[WoosukKwon]

@hongxiayang Could you please fix the CI error? It seems the error log is saying that there's a problem in Triton, maybe the issue @hliuca pointed out.

[hongxiayang]

@hongxiayang Could you please fix the CI error? It seems the error log is saying that there's a problem in Triton, maybe the issue @hliuca pointed out.

@WoosukKwon Checking. One difference I saw between the CI and my dev env is that python version is different:
in my dev env, triton is installed in below directory (note the python version is 3.9):

/opt/conda/envs/py_3.9/lib/python3.9/site-packages

while in CI, the error showed it used triton in python3.10:

<html>
<body>
<!--StartFragment-->
/usr/local/lib/python3.10/dist-packages/triton/runtime/autotuner.py:110: in kernel_call
--
  | self.fn.run(
  | /usr/local/lib/python3.10/dist-packages/triton/runtime/jit.py:426: in run

<!--EndFragment-->
</body>
</html>

Not sure what caused the difference yet.

[hongxiayang]

@WoosukKwon Does the CI build docker using Dockerfile instead of Dockerfile.rocm?

Maybe this is the CI setup issue?

[hongxiayang]

@WoosukKwon Inspecting more in the raw log, we can see it is build for CUDA, not ROCm:

But, later from the log, it selected ROCmFlashAttention backend.
And checking more logs showed below:

It seems that all backends were tested for a "CUDA" machine since it used cuda's nccl? Maybe the CI setup problem should be addressed in a different PR?

[hongxiayang]

@WoosukKwon This line:

vllm/.buildkite/test-pipeline.yaml

Line 18 in a37d815

- VLLM_ATTENTION_BACKEND=ROCM_FLASH pytest -v -s basic_correctness/test_basic_correctness.py

Should I remove it in this PR?

[WoosukKwon]

@hongxiayang LGTM! As you found, I think the tests were added by mistake and the CI happened to pass the tests because the ROCm Flash backend used to use naive attention for L4 (compute capability 8.9). I think we should skip these CI tests for AMD GPUs for now.

[jfactory07]

hi @hongxiayang

Did you see the performance has uplift after enabling triton flash-attn.

According to my test result on Navi31 triton's flash-attn is slower than naive-attn. I used 0.4.1+rocm603 + triton 2.1.0