1ccb9acd9a
come from: https://github.com/vllm-project/vllm-ascend/issues/5463
Reason:
During the iteration process of the hardware version, there may be a
large number of iterations for the operators, which can lead to
short-term compatibility differences. Therefore, an intermediate
adaptation layer is provided to accommodate the short-term differences
in operators.
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: weijinqian_v1 <weijinqian@huawei.com>
Signed-off-by: weijinqian0 <1184188277@qq.com>
Co-authored-by: weijinqian_v1 <weijinqian@huawei.com>
57 lines
2.1 KiB
Python
57 lines
2.1 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
|
|
#
|
|
# 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 typing import Optional, Type
|
|
|
|
import torch_npu
|
|
|
|
from vllm_ascend.utils import AscendDeviceType, get_ascend_device_type
|
|
|
|
|
|
class BaseDeviceAdaptor(object):
|
|
|
|
@classmethod
|
|
def reshape_and_cache(cls, key, value, key_cache, value_cache,
|
|
slot_mapping):
|
|
torch_npu._npu_reshape_and_cache(key=key,
|
|
value=value,
|
|
key_cache=key_cache,
|
|
value_cache=value_cache,
|
|
slot_indices=slot_mapping)
|
|
|
|
|
|
class A5DeviceAdaptor(BaseDeviceAdaptor):
|
|
|
|
@classmethod
|
|
def reshape_and_cache(cls, key, value, key_cache, value_cache,
|
|
slot_mapping):
|
|
torch_npu.npu_scatter_pa_kv_cache(key=key,
|
|
value=value.contiguous(),
|
|
key_cache=key_cache,
|
|
value_cache=value_cache,
|
|
slot_mapping=slot_mapping)
|
|
|
|
|
|
def get_device_adaptor():
|
|
ascend_device_type = get_ascend_device_type()
|
|
if ascend_device_type == AscendDeviceType.A5:
|
|
return A5DeviceAdaptor
|
|
return BaseDeviceAdaptor
|
|
|
|
|
|
DeviceOperator: Optional[Type['BaseDeviceAdaptor']] = get_device_adaptor()
|