23524f2ca4
### What this PR does / why we need it?
This pull request focuses on a significant refactoring effort within the
vllm-ascend project, specifically targeting operations optimized for the
Ascend 310P hardware. The changes aim to streamline the implementation
of core components like quantization and multi-head attention, making
the codebase more maintainable and robust. Concurrently, new unit tests
have been introduced to ensure the correctness and reliability of these
refactored modules.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
E2E test with qwen3-32b w8a8
- vLLM version: v0.15.0
- vLLM main:
d7e17aaacd
---------
Signed-off-by: pu-zhe <zpuaa@outlook.com>
29 lines
1.0 KiB
Python
29 lines
1.0 KiB
Python
#
|
|
# 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.
|
|
#
|
|
|
|
import torch
|
|
import torch.nn.functional as F
|
|
|
|
from vllm_ascend.ops.activation import AscendSiluAndMul
|
|
|
|
|
|
class AscendSiluAndMul310(AscendSiluAndMul):
|
|
def forward(self, x: torch.Tensor) -> torch.Tensor:
|
|
h = x.shape[-1] // 2
|
|
out = (F.silu(x[..., :h].to(torch.float32)) * x[..., h:].to(torch.float32)).to(torch.float16)
|
|
return out
|