[Fix] Delete redundant variable (#4903)

### What this PR does / why we need it?
The variable ’is_deepseek_v3_r1‘ now is useless in the repository, so
delete it now. And the funciton 'get_fused_moe_state' is used only for
torchair, so it need to be deleted along with torchair

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?

- vLLM version: v0.12.0
- vLLM main:
vllm-project/vllm@ad32e3e

Signed-off-by: hust17yixuan <[email protected]>

Author: hust17yixuan

vllm_ascend/ascend_forward_context.py

@@ -5,8 +5,7 @@
 
 import torch
 from vllm.config import CUDAGraphMode, VllmConfig
-from vllm.distributed import (get_dp_group, get_ep_group,
-                              get_tensor_model_parallel_world_size)
+from vllm.distributed import get_dp_group, get_tensor_model_parallel_world_size
 from vllm.forward_context import (BatchDescriptor, get_forward_context,
                                   set_forward_context)
 
@@ -29,25 +28,6 @@ class FusedMoEState(Enum):
     All2AllSeq = 5
 
 
-def get_fused_moe_state(ep_size: int, with_prefill: bool,
-                        is_deepseek_v3_r1: bool):
-    # the fusion operator torch_npu.npu_grouped_matmul_finalize_routing called by allgather ep
-    # only supports deepseek v3/r1
-    if (envs_ascend.VLLM_ENABLE_FUSED_EXPERTS_ALLGATHER_EP and ep_size > 1
-            and is_deepseek_v3_r1):
-        return FusedMoEState.AllGatherEP
-    elif ep_size == 1:
-        if with_prefill:
-            return FusedMoEState.NaiveMulticast
-        else:
-            return FusedMoEState.AllGather
-    # NOTE: mc2 need ep_size >= 16 & all2all can't use in torchair graph.
-    elif ep_size < 16 or with_prefill:
-        return FusedMoEState.All2All
-    else:
-        return FusedMoEState.MC2
-
-
 class MoECommType(Enum):
     ALLGATHER = 0
     MC2 = 1
@@ -95,16 +75,7 @@ def set_ascend_forward_context(
 
         forward_context.with_prefill = with_prefill
         tp_world_size = get_tensor_model_parallel_world_size()
-        ep_size = (get_ep_group().world_size if
-                   vllm_config.parallel_config.enable_expert_parallel else 1)
-
-        # fused_moe_state is used in torchair, it will be deleted along with torchair
-        is_deepseek_v3_r1 = hasattr(
-            vllm_config.model_config.hf_config, 'n_routed_experts'
-        ) and vllm_config.model_config.hf_config.n_routed_experts == 256
-        fused_moe_state = get_fused_moe_state(ep_size, with_prefill,
-                                              is_deepseek_v3_r1)
-        forward_context.fused_moe_state = fused_moe_state
+
         forward_context.in_profile_run = in_profile_run
 
         # NOTE: This cannot be set using set_forward_context