Files
xc-llm-ascend/vllm_ascend/compilation/graph_fusion_pass_manager.py
Fager10086 77a029979e Revert "[BugFix][Fusion] Fix graph fusion failure problem (#5253)" (#5667)
### What this PR does / why we need it?

Revert PR 5253 to fix the smoking problem

### Does this PR introduce _any_ user-facing change?

Does not.

### How was this patch tested?

It was tested in the failure case.

Signed-off-by: Rifa <865071616@qq.com>
2026-01-06 21:55:47 +08:00

57 lines
2.1 KiB
Python

#
# 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.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, runtime_shape) -> fx.Graph:
for pass_ in self.passes:
if pass_.is_applicable(runtime_shape):
pass_(graph)
return graph
def add(self, pass_: VllmInductorPass):
assert isinstance(pass_, VllmInductorPass)
self.passes.append(pass_)
def configure(self, config: VllmConfig):
# 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):
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))