torchvision0.11.2是高于torchvision0.3.0吗
时间: 2024-05-02 12:11:08 浏览: 7
不是,torchvision0.3.0是比torchvision0.11.2更新的版本。版本号中的第一个数字表示主要版本号,第二个数字表示次要版本号,第三个数字表示修订版本号。因此,0.11.2是torchvision的主要版本号为0,次要版本号为11,修订版本号为2的版本。而0.3.0是torchvision的主要版本号为0,次要版本号为3,修订版本号为0的版本,所以它比0.11.2要早。
相关问题
No matching distribution found for torchvision==0.11.2+cu111
As an AI language model, I don't have access to your exact environment and setup, but it seems like the error message is indicating that the version of the `torchvision` library you are trying to install (`0.11.2`) is not compatible with your CUDA version (`cu111`).
You may want to try installing a different version of `torchvision` that is compatible with CUDA 11.1 or update your CUDA version to 11.1 if possible. You can check the compatibility of different `torchvision` versions with CUDA on the PyTorch website.
Alternatively, you can try to install `torchvision` without specifying a version and let pip install the latest compatible version for your environment:
```
pip install torchvision
```
If the issue persists, you may want to seek assistance from the PyTorch or torchvision community forums.
pytorch和torchvision版本
根据引用\[1\]和引用\[2\]的内容,安装torchvision的方法有两种。一种是根据下载的pytorch版本,去相应的whl文件下载地址下载合适的torchvision版本,然后使用pip install命令进行安装。另一种是先安装torch,然后使用pip install torchvision命令自动安装torchvision。如果无法找到对应的torch版本,可以先安装torch,再使用pip install torchvision命令进行安装。根据引用\[3\]的内容,还可以根据不同的操作系统和CUDA版本进行安装。例如,如果使用的是CUDA 11.1,可以使用pip install torch==1.10.1+cu111 torchvision==0.11.2+cu111命令进行安装。
#### 引用[.reference_title]
- *1* *2* [pytorch、torchvision历史版本的whl文件下载地址、版本对应关系与离线安装方法](https://blog.csdn.net/weixin_39833897/article/details/123072353)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control_2,239^v3^insert_chatgpt"}} ] [.reference_item]
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