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[Chore] Fix torch precision warning (#30428)

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Signed-off-by: yewentao256 <zhyanwentao@126.com>
This commit is contained in:
Wentao Ye 2025-12-10 23:05:56 -05:00 committed by GitHub
parent 7e24e5d4d6
commit d6464f2679
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GPG Key ID: B5690EEEBB952194
3 changed files with 9 additions and 7 deletions
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4
tests/v1/e2e/test_async_scheduling.py
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@ -152,8 +152,8 @@ def run_tests(
m.setenv("VLLM_ATTENTION_BACKEND", "ROCM_AITER_FA")
else:
m.setenv("VLLM_ATTENTION_BACKEND", "FLEX_ATTENTION")
# lock matmul precision to full FP32
m.setenv("VLLM_FLOAT32_MATMUL_PRECISION", "highest")
# lock matmul precision to full FP32 (IEEE)
m.setenv("VLLM_FLOAT32_MATMUL_PRECISION", "ieee")
# m.setenv("VLLM_BATCH_INVARIANT", "1")
outputs: list[tuple[str, list, list]] = []
for n, (

10
vllm/envs.py
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@ -74,7 +74,7 @@ if TYPE_CHECKING:
VLLM_MEDIA_CONNECTOR: str = "http"
VLLM_TARGET_DEVICE: str = "cuda"
VLLM_MAIN_CUDA_VERSION: str = "12.9"
VLLM_FLOAT32_MATMUL_PRECISION: Literal["highest", "high", "medium"] = "highest"
VLLM_FLOAT32_MATMUL_PRECISION: Literal["ieee", "tf32"] = "ieee"
MAX_JOBS: str | None = None
NVCC_THREADS: str | None = None
VLLM_USE_PRECOMPILED: bool = False
@ -456,11 +456,13 @@ environment_variables: dict[str, Callable[[], Any]] = {
"VLLM_MAIN_CUDA_VERSION": lambda: os.getenv("VLLM_MAIN_CUDA_VERSION", "").lower()
or "12.9",
# Controls PyTorch float32 matmul precision mode within vLLM workers.
# Valid options mirror torch.set_float32_matmul_precision
# Accepted values:
# - "ieee" (default): force full IEEE FP32 matmul precision.
# - "tf32": enable TensorFloat32-based fast matmul.
"VLLM_FLOAT32_MATMUL_PRECISION": env_with_choices(
"VLLM_FLOAT32_MATMUL_PRECISION",
"highest",
["highest", "high", "medium"],
"ieee",
["ieee", "tf32"],
case_sensitive=False,
),
# Maximum number of compilation jobs to run in parallel.

2
vllm/v1/worker/gpu_worker.py
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@ -81,7 +81,7 @@ class Worker(WorkerBase):
# configure float32 matmul precision according to vLLM env.
precision = envs.VLLM_FLOAT32_MATMUL_PRECISION
torch.set_float32_matmul_precision(precision)
torch.backends.cuda.matmul.fp32_precision = precision
if self.model_config.trust_remote_code:
# note: lazy import to avoid importing torch before initializing