Package | 解决 RuntimeError: Numpy is not available. Failed to initialize NumPy against version 0xf

最新推荐文章于 2025-05-30 22:39:33 发布
最新推荐文章于 2025-05-30 22:39:33 发布
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分类专栏： Package 文章标签： numpy python 深度学习
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本文链接：https://blog.youkuaiyun.com/iLOVEJohnny/article/details/127651663
在Docker环境中配置深度学习实验时，遇到Numpy不可用的问题。通过详细错误提示，找到并解决了Numpy版本与PyTorch不兼容的故障。

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.

背景

在docker里配置实验环境，根据repo中的指令"pip install -r requirement.txt"，安装完必要的包，具体信息如下。
“
torch == 1.8.0
opencv_python == 4.5.2.52
trimesh == 3.9.8
numpy == 1.19.2
pyhocon == 0.3.57
icecream == 2.1.0
tqdm == 4.50.2
scipy == 1.7.0
PyMCubes == 0.1.2
”

运行训练时，出现报错如下，非常简略的报错信息：
“
RuntimeError: Numpy is not available
”

根据该报错信息查到几篇博客，其中的方法都不太适用。于是重看报错的信息，发现有一行User Warning，内容如下：
“
/opt/conda/lib/python3.8/site-packages/torch/_masked/__init__.py:223: UserWarning: Failed to initialize NumPy: module compiled against API version 0xf but this version of numpy is 0xd (Triggered internally at /opt/pytorch/pytorch/torch/csrc/utils/tensor_numpy.cpp:68.)
”

.

解决方案

根据User Warning的信息搜到有效解决方案，原答案链接：github-answer

该报错原因是当前numpy版本和环境不匹配，需要对其进行升级。指令如下：

pip install numpy --upgrade

问题解决~

预祝大家写代码顺利~

.

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print("PyTorch NPU支持:", torch.npu.is_available()) # 应返回True x = torch.tensor([1.0], device="npu:0") y = torch.tensor([2.0], device="npu:0") print("NPU计算验证:", x + y) # 应输出tensor([3.], ...
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解决RuntimeError: Numpy is not available
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针对于这个问题其他人的解决办法是需要安装tensorflow，但是我没有尝试，仅针对我自己问题进行理解。版本不兼容的具体错误：在numpy数据类型转变为tensor数据类型。
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重新安装numpy版本：
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