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Merge dbd4d76c0580ab64f7b30c3ef94227d960cee188 into 254f6b986720c92ddf97fbb1a6a6465da8e87e29

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ゆり 2025-12-25 00:07:05 +00:00 committed by GitHub
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1 changed files with 18 additions and 3 deletions
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21
vllm/model_executor/layers/fused_moe/unquantized_fused_moe_method.py
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@ -10,6 +10,7 @@ import vllm.model_executor.layers.fused_moe.modular_kernel as mk
from vllm._aiter_ops import rocm_aiter_ops from vllm._aiter_ops import rocm_aiter_ops
from vllm.logger import init_logger from vllm.logger import init_logger
from vllm.model_executor.custom_op import CustomOp from vllm.model_executor.custom_op import CustomOp
from vllm.model_executor.layers.batch_invariant import vllm_is_batch_invariant
from vllm.model_executor.layers.fused_moe.config import ( from vllm.model_executor.layers.fused_moe.config import (
FUSED_MOE_UNQUANTIZED_CONFIG, FUSED_MOE_UNQUANTIZED_CONFIG,
FusedMoEConfig, FusedMoEConfig,
@ -62,16 +63,21 @@ class UnquantizedFusedMoEMethod(FusedMoEMethodBase, CustomOp):
self.rocm_aiter_fused_experts = None # type: ignore self.rocm_aiter_fused_experts = None # type: ignore
# FlashInfer CUTLASS MoE is only supported on Hopper and later GPUS # FlashInfer CUTLASS MoE is only supported on Hopper and later GPUS
# Note: FlashInfer MoE is non-deterministic, so disable it when
# batch invariant mode is enabled for deterministic inference.
self.flashinfer_cutlass_moe_enabled = ( self.flashinfer_cutlass_moe_enabled = (
has_flashinfer_cutlass_fused_moe() has_flashinfer_cutlass_fused_moe()
and envs.VLLM_USE_FLASHINFER_MOE_FP16 and envs.VLLM_USE_FLASHINFER_MOE_FP16
and self.moe.moe_parallel_config.use_ep and self.moe.moe_parallel_config.use_ep
and self.moe.moe_parallel_config.dp_size == 1 and self.moe.moe_parallel_config.dp_size == 1
and current_platform.get_device_capability()[0] >= 9 and current_platform.get_device_capability()[0] >= 9
and not vllm_is_batch_invariant()
) )
if self.flashinfer_cutlass_moe_enabled: if self.flashinfer_cutlass_moe_enabled:
logger.info_once( logger.info_once(
"Enabling FlashInfer CUTLASS MoE for UnquantizedFusedMoEMethod" "Enabling FlashInfer CUTLASS MoE for UnquantizedFusedMoEMethod. "
"Note: This kernel may produce non-deterministic results. "
"Use VLLM_BATCH_INVARIANT=1 for deterministic inference."
) )
from functools import partial from functools import partial
@ -86,14 +92,23 @@ class UnquantizedFusedMoEMethod(FusedMoEMethodBase, CustomOp):
ep_size=self.moe.moe_parallel_config.ep_size, ep_size=self.moe.moe_parallel_config.ep_size,
) )
else: else:
if ( if vllm_is_batch_invariant() and envs.VLLM_USE_FLASHINFER_MOE_FP16:
logger.info_once(
"FlashInfer CUTLASS MoE is disabled in batch invariant mode "
"because it produces non-deterministic results. "
"Using the default MoE implementation for deterministic "
"inference.",
scope="local",
)
elif (
self.moe.moe_parallel_config.use_ep self.moe.moe_parallel_config.use_ep
and self.moe.moe_parallel_config.dp_size == 1 and self.moe.moe_parallel_config.dp_size == 1
): ):
logger.info_once( logger.info_once(
"FlashInfer CUTLASS MoE is available for EP" "FlashInfer CUTLASS MoE is available for EP"
" but not enabled, consider setting" " but not enabled, consider setting"
" VLLM_USE_FLASHINFER_MOE_FP16=1 to enable it.", " VLLM_USE_FLASHINFER_MOE_FP16=1 to enable it."
" Note: FlashInfer MoE produces non-deterministic results.",
scope="local", scope="local",
) )
elif self.moe.moe_parallel_config.dp_size > 1: elif self.moe.moe_parallel_config.dp_size > 1: