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[Bugfix] Fix passing of activation_type to trtllm fused MoE NVFP4 and FP8 (#36017)

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Signed-off-by: amitz-nv <203509407+amitz-nv@users.noreply.github.com>
(cherry picked from commit d7adcadb9b)
This commit is contained in:
amitz-nv
2026-03-05 00:23:51 +02:00
committed by khluu
parent b31e9326a7
commit 244b922088
2 changed files with 2 additions and 2 deletions
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3
vllm/model_executor/layers/fused_moe/experts/trtllm_fp8_moe.py
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@@ -240,12 +240,11 @@ class TrtLlmFp8Experts(mk.FusedMoEExpertsMonolithic):
) -> torch.Tensor: ) -> torch.Tensor:
# Delay import for non-CUDA. # Delay import for non-CUDA.
import flashinfer import flashinfer
from flashinfer.fused_moe.core import ActivationType
# Confirm supported activation function. # Confirm supported activation function.
assert activation in [MoEActivation.SILU, MoEActivation.RELU2_NO_MUL] assert activation in [MoEActivation.SILU, MoEActivation.RELU2_NO_MUL]
activation_type = ActivationType(activation_to_flashinfer_int(activation)) activation_type = activation_to_flashinfer_int(activation)
# Confirm Llama-4 routing is proper. # Confirm Llama-4 routing is proper.
if self.routing_method_type == RoutingMethodType.Llama4: if self.routing_method_type == RoutingMethodType.Llama4:

1
vllm/model_executor/layers/fused_moe/experts/trtllm_nvfp4_moe.py
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@@ -323,4 +323,5 @@ class TrtLlmNvFp4ExpertsMonolithic(
routed_scaling_factor=routed_scaling_factor, routed_scaling_factor=routed_scaling_factor,
routing_method_type=self.routing_method_type, routing_method_type=self.routing_method_type,
do_finalize=True, do_finalize=True,
activation_type=activation_to_flashinfer_int(activation),
)[0] )[0]