init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>

vllm_ascend/_310p/fused_moe/moe_comm_method.py

@@ -0,0 +1,50 @@
+# Copyright (c) 2026 Huawei Technologies Co., Ltd. All Rights Reserved.
+# Copyright 2023 The vLLM team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# This file is a part of the vllm-ascend project.
+from __future__ import annotations
+
+from typing import Any
+
+from vllm_ascend.ops.fused_moe.moe_comm_method import AllGatherCommImpl
+from vllm_ascend.ops.fused_moe.moe_runtime_args import MoEMlpComputeInput
+
+from .moe_mlp import unified_apply_mlp
+from .token_dispatcher import TokenDispatcherWithAllGather310
+
+
+class AllGatherCommImpl310(AllGatherCommImpl):
+    """This implementation is the same as NativeAllGatherCommImpl,
+    but uses NPU-specific ops for better performance.
+
+    This implementation should be compatible with all scenarios, and
+    thus it is the default implementation for MoE communication methods.
+    It uses `torch_npu.npu_moe_init_routing_v2` for pre-processing
+    and `torch_npu.npu_moe_token_unpermute` for post-processing
+    to handle the token-to-expert mapping and communication efficiently.
+    """
+
+    def __init__(self, moe_config):
+        super().__init__(moe_config)
+        self.use_fusion_ops = False
+
+    def _apply_mlp(self, mlp_compute_input: MoEMlpComputeInput) -> Any:
+        return unified_apply_mlp(mlp_compute_input=mlp_compute_input), None
+
+    def _get_token_dispatcher(self):
+        return TokenDispatcherWithAllGather310(
+            top_k=self.moe_config.experts_per_token,
+            num_experts=self.moe_config.num_experts,
+            num_local_experts=self.moe_config.num_local_experts,
+        )