1 系统环境
硬件环境(Ascend/GPU/CPU): Ascend/GPU/CPU
MindSpore版本: mindspore=2.0.0
Mindformer版本:Mindformer=1.0
执行模式(PyNative/ Graph):不限
Python版本: Python=3.9
操作系统平台: 不限
2 报错信息
2.1 问题描述
算子编译过程中部分模块与numpy2.0版本不兼容
2.2 报错信息
3 根因分析
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4 解决方案
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1 系统环境
硬件环境(Ascend/GPU/CPU): Ascend/GPU/CPU
MindSpore版本: mindspore=2.0.0
Mindformer版本:Mindformer=1.0
执行模式(PyNative/ Graph):不限
Python版本: Python=3.9
操作系统平台: 不限
2 报错信息
2.1 问题描述
算子编译过程中部分模块与numpy2.0版本不兼容
2.2 报错信息
(mindie) root@ubuntu:/usr/local/Ascend/MindIE-LLM/examples/models# source /usr/local/Ascend/MindIE-LLM/set_env.sh A module that was compiled using NumPy 1.x cannot be run in Numpy 2.0.0 as it may crash. To support both with and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuildinstead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules willoneed time to support NumPy 2. Traceback (most recent call last): File "<string>", line 1, in <module> File "/root/anaconda3/envs/mindie/l ib/python3. 10/site-packages/torch/_ init_.py", line 1382, in <modules> from .functional import * # noqa: F403 File "/root/anaconda3/envs/m indie/l ib/python3.10/s ite-pac kages/torch/functional.py", line 7, in <module> import torch.nn.functional as F File "/root/anaconda3/envs/mindie/Lib/python3.10/stte-packages/torch/nn/_ init_.pyahen", line 1, in <module> from .modules import * # noqa: F403 File "/root/anaconda3/envs/mindie/l ib/python3.10/site-packages/t orch/nn/modules/_init__.py" , line 35, in <module> from .transformer import Trans formerEncoder, TransformerDecoder, \ File "/root/anaconda3/envs/mindie/lib/python3,10/site-packages/torch/nn/modules/transformer .py" , line 20, in <module> device: torch.device = torch.deviceltorch. C. get default device( )), # torch.device('cpu') /root/anaconda3/envs/mindie/tib/python3. 10/site-packages/torch/nn/modules/transformer .py:20: Userwarn ing: Failed to initialize NumPy: _ARRAY_APIenotfound, (Trigge red internally at /pytorch/torch/csrc/utils/tensor numpy.cpp:84.) device: torch.device = torch.device( torch. C. get default device( )), # torch.device('cpu')3 根因分析
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4 解决方案
******此处由用户填写******
包含文字方案和最终脚本代码
请将正确的脚本打包并上传附件