329961b375
### What this PR does / why we need it?
**Scope of Changes**:
| File Path |
| :--- |
| `vllm_ascend/attention/attention_mask.py` |
| `vllm_ascend/attention/attention_v1.py` |
| `vllm_ascend/attention/context_parallel/attention_cp.py` |
| `vllm_ascend/attention/context_parallel/common_cp.py` |
| `vllm_ascend/attention/context_parallel/mla_cp.py` |
| `vllm_ascend/attention/utils.py` |
| `vllm_ascend/batch_invariant.py` |
| `vllm_ascend/device/device_op.py` |
| `vllm_ascend/device_allocator/camem.py` |
| `vllm_ascend/envs.py` |
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
---------
Signed-off-by: MrZ20 <2609716663@qq.com>
48 lines
1.7 KiB
Python
48 lines
1.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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#
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import torch_npu
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from vllm_ascend.utils import AscendDeviceType, get_ascend_device_type
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class BaseDeviceAdaptor:
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@classmethod
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def reshape_and_cache(cls, key, value, key_cache, value_cache, slot_mapping):
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torch_npu._npu_reshape_and_cache(
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key=key, value=value, key_cache=key_cache, value_cache=value_cache, slot_indices=slot_mapping
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)
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class A5DeviceAdaptor(BaseDeviceAdaptor):
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@classmethod
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def reshape_and_cache(cls, key, value, key_cache, value_cache, slot_mapping):
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torch_npu.npu_scatter_pa_kv_cache(
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key=key, value=value.contiguous(), key_cache=key_cache, value_cache=value_cache, slot_mapping=slot_mapping
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)
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def get_device_adaptor():
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ascend_device_type = get_ascend_device_type()
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if ascend_device_type == AscendDeviceType.A5:
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return A5DeviceAdaptor
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return BaseDeviceAdaptor
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DeviceOperator: type["BaseDeviceAdaptor"] | None = get_device_adaptor()
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