forked from EngineX-Ascend/enginex-ascend-910-vllm
49 lines
1.9 KiB
Python
49 lines
1.9 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 typing import List, Optional
|
|
|
|
import torch
|
|
import vllm
|
|
from vllm.distributed.parallel_state import GroupCoordinator
|
|
|
|
|
|
class GroupCoordinatorPatch(GroupCoordinator):
|
|
|
|
def __init__(self, *args, **kwargs):
|
|
super().__init__(*args, **kwargs)
|
|
|
|
def all_to_all(self,
|
|
input_: torch.Tensor,
|
|
scatter_dim: int = 0,
|
|
gather_dim: int = -1,
|
|
scatter_sizes: Optional[List[int]] = None,
|
|
gather_sizes: Optional[List[int]] = None) -> torch.Tensor:
|
|
if self.world_size == 1:
|
|
return input_
|
|
assert -input_.dim() <= scatter_dim < input_.dim(), (
|
|
f"Invalid scatter dim ({scatter_dim}) for input tensor with shape {input_.size()}"
|
|
)
|
|
assert -input_.dim() <= gather_dim < input_.dim(), (
|
|
f"Invalid gather dim ({gather_dim}) for input tensor with shape {input_.size()}"
|
|
)
|
|
return self.device_communicator.all_to_all(input_, scatter_dim,
|
|
gather_dim, scatter_sizes,
|
|
gather_sizes)
|
|
|
|
|
|
vllm.distributed.parallel_state.GroupCoordinator = GroupCoordinatorPatch # Note: check the GroupCoordinator with online serving |