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[Bugfix] Added more env vars to hash (#22449)

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Signed-off-by: Julien Lin <jullin@nvidia.com>
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nvjullin 2025-08-16 04:08:37 +08:00 committed by GitHub
parent 6e670778cd
commit 79899b63f6
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1 changed files with 36 additions and 10 deletions
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46
vllm/envs.py
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@ -1199,14 +1199,6 @@ def compute_hash() -> str:
affect the choice of different kernels or attention backends should
also be included in the factors list.
"""
factors: list[Any] = []
# summarize environment variables
def factorize(name: str):
if __getattr__(name):
factors.append(__getattr__(name))
else:
factors.append("None")
# The values of envs may affects the computation graph.
# TODO(DefTruth): hash all environment variables?
@ -1221,11 +1213,45 @@ def compute_hash() -> str:
"VLLM_DP_SIZE",
"VLLM_USE_STANDALONE_COMPILE",
"VLLM_FUSED_MOE_CHUNK_SIZE",
"VLLM_FLASHINFER_MOE_BACKEND",
"VLLM_V1_USE_PREFILL_DECODE_ATTENTION",
"VLLM_USE_AITER_UNIFIED_ATTENTION",
"VLLM_ATTENTION_BACKEND",
"VLLM_USE_FLASHINFER_SAMPLER",
"VLLM_FLASHINFER_FORCE_TENSOR_CORES",
"VLLM_DISABLED_KERNELS",
"VLLM_USE_DEEP_GEMM",
"VLLM_USE_TRTLLM_FP4_GEMM",
"VLLM_USE_FLASHINFER_MOE_FP8",
"VLLM_USE_FLASHINFER_MOE_FP4",
"VLLM_USE_FLASHINFER_MOE_MXFP4_MXFP8",
"VLLM_USE_FLASHINFER_MOE_MXFP4_BF16",
"VLLM_USE_CUDNN_PREFILL",
"VLLM_USE_TRTLLM_ATTENTION",
"VLLM_ROCM_USE_AITER",
"VLLM_ROCM_USE_AITER_PAGED_ATTN",
"VLLM_ROCM_USE_AITER_LINEAR",
"VLLM_ROCM_USE_AITER_MOE",
"VLLM_ROCM_USE_AITER_RMSNORM",
"VLLM_ROCM_USE_AITER_MLA",
"VLLM_ROCM_USE_AITER_MHA",
"VLLM_ROCM_USE_SKINNY_GEMM",
"VLLM_ROCM_FP8_PADDING",
"VLLM_ROCM_MOE_PADDING",
"VLLM_ROCM_CUSTOM_PAGED_ATTN",
"VLLM_ROCM_QUICK_REDUCE_QUANTIZATION",
"VLLM_ROCM_QUICK_REDUCE_CAST_BF16_TO_FP16",
"VLLM_ROCM_QUICK_REDUCE_MAX_SIZE_BYTES_MB",
]
for key in environment_variables_to_hash:
if key in environment_variables:
factorize(key)
# if this goes out of sync with environment_variables,
# it's not a user error, it's a bug
assert key in environment_variables, \
"Please update environment_variables_to_hash in envs.py"
factors = [
environment_variables[key]() for key in environment_variables_to_hash
]
hash_str = hashlib.md5(str(factors).encode(),
usedforsecurity=False).hexdigest()