9935d45728
### What this PR does / why we need it? Add model basic accuracy test(Qwen2.5-0.5B-Instruct) Signed-off-by: hfadzxy <starmoon_zhang@163.com>
41 lines
1.3 KiB
Python
41 lines
1.3 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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from typing import Optional, Tuple, Union
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import torch
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from vllm.model_executor.layers.layernorm import RMSNorm
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def forward_oot(
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self,
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x: torch.Tensor,
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residual: Optional[torch.Tensor] = None,
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) -> Union[torch.Tensor, Tuple[torch.Tensor, torch.Tensor]]:
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import torch_npu
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if residual is not None:
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x, _, residual = torch_npu.npu_add_rms_norm(x, residual, self.weight,
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self.variance_epsilon)
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return x, residual
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x, residual = torch_npu.npu_rms_norm(x, self.weight, self.variance_epsilon)
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return x
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RMSNorm.forward_oot = forward_oot
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