1ffca8673f
### What this PR does / why we need it?
Add basic 310p support. Only dense models work with eager mode now.
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
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Signed-off-by: Tflowers-0129 <2906339855@qq.com>
Signed-off-by: Shaoxu Cheng <2906339855@qq.com>
31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
#
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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
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import torch.nn.functional as F
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from vllm_ascend.ops.activation import AscendSiluAndMul as _Base
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class AscendSiluAndMul310(_Base):
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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torch.ops.vllm.maybe_prefetch_mlp_down_proj(x)
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h = x.shape[-1] // 2
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out = (F.silu(x[..., :h].to(torch.float32)) * x[..., h:].to(torch.float32)).to(torch.float16)
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torch.ops.vllm.maybe_wait_prefetch_done(out)
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return out
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