[refactor] Refactoring AscendFusedMoE (#1229)

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### What this PR does / why we need it?
This PR is used for resolved [issue
1147](https://github.com/vllm-project/vllm-ascend/issues/1147)
1. Move fused_moe code into one file `fused_moe.py`.
2. Integrate branch conditions into function `get_fused_moe_state`.
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### Does this PR introduce _any_ user-facing change?
1. This PR has removed the env `VLLM_ENABLE_MC2`, because I think this
env is useless, we can make judgments based on the current scenario
without this env, it will only increase complexity.
2. This PR has removed the env `USING_LCCL_COM`, because this env has
already expired.
3. `additional_config.expert_tensor_parallel_size` has already expired,
and now we also use parameter `enable_expert_parallel`, consistent with
the vLLM.
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Signed-off-by: zzzzwwjj <1183291235@qq.com>

vllm_ascend/utils.py

@@ -20,6 +20,7 @@
 import atexit
 import math
 from contextlib import contextmanager, nullcontext
+from enum import Enum
 from threading import Lock
 from typing import TYPE_CHECKING, List, Tuple
 
@@ -275,3 +276,21 @@ def npu_wait_tensor(self: torch.Tensor,
                     *,
                     enabled: bool = True):
     return _npu_wait_tensor(self, dependency) if enabled else self
+
+
+# TODO(zzzzwwjj): move this into forward_context
+class FusedMoEState(Enum):
+    AllGather = 0
+    All2All = 1
+    MC2 = 2
+
+
+# TODO(zzzzwwjj): add soc_version to choose branch
+def get_fused_moe_state(ep_size: int, with_prefill: bool):
+    if ep_size == 1:
+        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