No matching distribution found for torch==1.9.0+cu111
时间: 2024-01-13 19:13:10 浏览: 43
这个错误通常是由于找不到与你的CUDA版本匹配的PyTorch版本所致。 `cu111` 表示你正在使用CUDA 11.1版本,因此你需要安装与之兼容的PyTorch版本。
你可以尝试安装以下命令来获取与CUDA 11.1兼容的PyTorch版本:
```
pip install torch==1.9.0+cu111 -f https://download.pytorch.org/whl/cu111/torch_stable.html
```
如果你使用的是conda,则可以使用以下命令:
```
conda install pytorch==1.9.0 torchvision==0.10.0 torchaudio==0.9.0 cudatoolkit=11.1 -c pytorch -c nvidia
```
注意,你需要确保你的系统上已经安装了CUDA 11.1。
相关问题
No matching distribution found for torch==1.10.0+cu111
As an AI language model, I do not have access to your system specifications, but it is possible that the error message "No matching distribution found for torch==1.10.0 cu111" may occur due to one of the following reasons:
1. CUDA version: The "cu111" in the error message refers to CUDA version 11.1. If your system does not have this version of CUDA installed, you will not be able to install the corresponding version of PyTorch (torch==1.10.0 cu111). You may need to install the correct version of CUDA before installing PyTorch.
2. Python version: PyTorch 1.10.0 requires Python 3.7 or higher. Ensure that you are running Python 3.7 or a later version.
3. Pip version: Ensure that you are using the latest version of pip. You can upgrade pip by running the command "pip install --upgrade pip".
4. Internet connectivity: Ensure that your system has an active internet connection and that your firewall is not blocking the installation of PyTorch.
5. Operating system: Ensure that you are using a supported operating system. PyTorch 1.10.0 supports Linux, Windows, and macOS.
If none of the above solutions work, you can try installing an earlier version of PyTorch or seek help from the PyTorch community.
No matching distribution found for torch==1.10.0+cu111怎么办
如果你遇到了 "No matching distribution found for torch==1.10.0 cu111" 的错误,可能是因为你的系统环境与 torch==1.10.0 cu111 不兼容。
你可以尝试以下解决方法:
1. 确认你的CUDA版本是否为11.1,如果不是,可以尝试安装匹配的版本。
2. 确认你的操作系统是否为64位,如果不是,需要安装匹配的32位版本。
3. 尝试安装最新版本的pip,然后再次尝试安装torch。
4. 如果以上方法都不行,可以尝试安装其他版本的torch,或者使用conda进行安装。
5. 如果还是无法解决问题,可以尝试在社区或者论坛上寻求帮助。