Apply torch.compile to fused_moe/grouped_topk

vllm/model_executor/layers/fused_moe/fused_moe.py

@@ -759,6 +759,7 @@ def fused_topk(
 
 
 # This is used by the Deepseek-V2 and Deepseek-V3 model
+@torch.compile(dynamic=True, backend=current_platform.simple_compile_backend)
 def grouped_topk(hidden_states: torch.Tensor,
                  gating_output: torch.Tensor,
                  topk: int,

vllm/model_executor/models/deepseek_v3.py

@@ -27,6 +27,7 @@
 from transformers import PretrainedConfig
 
 from vllm.attention import Attention, AttentionMetadata
+from vllm.compilation.decorators import support_torch_compile
 from vllm.config import CacheConfig, ModelConfig, VllmConfig
 from vllm.distributed import (get_pp_group,
                               get_tensor_model_parallel_world_size,
@@ -566,8 +567,7 @@ def forward(
         return hidden_states, residual
 
 
-# TODO(simon): check whether we support torch compile for Deepseek V3
-# @support_torch_compile
+@support_torch_compile
 class DeepseekV3Model(nn.Module):
 
     fall_back_to_pt_during_load = False