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Re-enable FlashInfer for Llama4 on Blackwell in e2e fusion tests (#28966)

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Signed-off-by: Luka Govedič <ProExpertProg@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: ProExpertProg <11367180+ProExpertProg@users.noreply.github.com>
Co-authored-by: Luka Govedič <ProExpertProg@users.noreply.github.com>
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Copilot 2025-11-19 13:32:19 -05:00 committed by GitHub
parent 0c80efd94f
commit 61728cd1df
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2 changed files with 6 additions and 8 deletions
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2
.buildkite/test-pipeline.yaml
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@ -930,6 +930,8 @@ steps:
- csrc/quantization/fp4/
- vllm/model_executor/layers/quantization/utils/flashinfer_utils.py
- vllm/v1/attention/backends/flashinfer.py
- vllm/v1/worker/
- vllm/v1/cudagraph_dispatcher.py
- vllm/compilation/
# can affect pattern matching
- vllm/model_executor/layers/layernorm.py

12
tests/compile/distributed/test_fusions_e2e.py
View File

@ -47,12 +47,8 @@ if current_platform.is_cuda():
ModelBackendTestCase(
# Use smaller model for L40s in CI
model_name="RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8",
# TODO while llama4 is broken, use FLASHINFER for llama3 on Blackwell
# so FI attention+fp8_quant is at least tested once
model_kwargs=dict(max_model_len=1024, kv_cache_dtype="fp8"),
backend=AttentionBackendEnum.FLASHINFER
if is_blackwell()
else AttentionBackendEnum.TRITON_ATTN,
backend=AttentionBackendEnum.TRITON_ATTN,
matches=Matches(
attention_fusion=32,
allreduce_fusion=65,
@ -65,9 +61,9 @@ if current_platform.is_cuda():
model_kwargs=dict(max_model_len=1024, kv_cache_dtype="fp8"),
# TODO FlashInfer attn broken on Hopper with kvcache=fp8:
# https://github.com/vllm-project/vllm/issues/28568
# TODO FlashInfer attn broken on Blackwell for llama4:
# https://github.com/vllm-project/vllm/issues/28604
backend=AttentionBackendEnum.TRITON_ATTN,
backend=AttentionBackendEnum.FLASHINFER
if is_blackwell()
else AttentionBackendEnum.TRITON_ATTN,
matches=Matches(
attention_fusion=48,
allreduce_fusion=96,