init v0.23.0

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

vllm_ascend/compilation/graph_fusion_pass_manager.py

@@ -0,0 +1,79 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# This file is a part of the vllm-ascend project.
+#
+#
+# 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.
+#
+
+from torch import fx as fx
+from vllm.compilation.passes.inductor_pass import get_pass_context
+from vllm.compilation.passes.vllm_inductor_pass import VllmInductorPass
+from vllm.config import VllmConfig
+
+
+class GraphFusionPassManager:
+    """
+    A pass manager for graph fusion passes.
+    It handles the configuration and execution of passes.
+    The counterpart in vllm is PostGradPassManager. Since torch_npu
+    does not support triton for now, we define our own pass manager.
+    """
+
+    def __init__(self):
+        self.passes: list[VllmInductorPass] = []
+
+    def __call__(self, graph: fx.Graph) -> fx.Graph:
+        compile_range = get_pass_context().compile_range
+
+        for pass_ in self.passes:
+            if pass_.is_applicable_for_range(compile_range):
+                pass_(graph)
+        graph.recompile()
+        return graph
+
+    def add(self, pass_: VllmInductorPass):
+        assert isinstance(pass_, VllmInductorPass)
+        self.passes.append(pass_)
+
+    def configure(self, config: VllmConfig):
+        from vllm_ascend.utils import is_310p
+
+        # By default, we enable the graph fusion and quantization fusion pass.
+        self.ascend_compilation_config: dict = config.additional_config.get("ascend_compilation_config", {})
+        if self.ascend_compilation_config.get("fuse_norm_quant", True) and not is_310p():
+            from .passes.norm_quant_fusion_pass import AddRMSNormQuantFusionPass
+
+            self.passes.append(AddRMSNormQuantFusionPass(config))
+
+        if self.ascend_compilation_config.get("fuse_qknorm_rope", True):
+            from .passes.qknorm_rope_fusion_pass import QKNormRopeFusionPass
+
+            self.passes.append(QKNormRopeFusionPass(config))
+
+        if self.ascend_compilation_config.get("fuse_allreduce_rms", True):
+            from .passes.allreduce_rmsnorm_fusion_pass import MatmulAllReduceAddRMSNormPass
+
+            self.passes.append(MatmulAllReduceAddRMSNormPass(config))
+
+        if self.ascend_compilation_config.get("fuse_muls_add", True) and not is_310p():
+            from .passes.muls_add_pass import MulsAddFusionPass
+
+            self.passes.append(MulsAddFusionPass(config))
+
+        if config.compilation_config.pass_config.enable_sp:
+            from .passes.sequence_parallelism import SequenceParallelismPass
+            from .passes.sequence_parallelism_moe import SequenceParallelismMoePass
+
+            self.passes.append(SequenceParallelismPass(config))
+            self.passes.append(SequenceParallelismMoePass(config))