如何在没有冲突的情况下使用 conda 将 CUDA 降级到 10.0.10？

Question

我想转到兼容的CUDA（cudatoolkit）版本 Nvidie-430 驱动程序，即 Nvidias site 推荐的 10.0.130。

基于 this answer 我做了，

conda install -c pytorch cudatoolkit=10.0.130

然后我得到这个错误（pastebin link)。（下面是非常简短的版本）：

(fastaiclean) eghx@eghx-nitro:~$ conda install -c pytorch cudatoolkit=10.0.130
...  
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: | 
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed   
UnsatisfiableError: The following specifications were found to be incompatible with each other:

Output in format: Requested package -> Available versions

Package _libgcc_mutex conflicts for:
pyzmq -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex=[build=main]
libgcc-ng -> _libgcc_mutex=[build=main]
lcms2 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex=[build=main]
...  
The following specifications were found to be incompatible with your system:

  - feature:/linux-64::__cuda==10.1=0
  - feature:|@/linux-64::__cuda==10.1=0

Your installed version is: 10.1

为什么我会遇到冲突？ cuda工具包为什么显示10.1 是 10.2.89 (conda list)？如何处理冲突？我能做什么有这个错误？矛盾太大，不知从何说起

其他

Nvidia 驱动程序430
当前 cudatoolkit: 10.2.89

Answer 1

使用

检查当前版本

torch.version.cuda

我有 10.2。但我需要 10.1，根据：table 1 here 和我安装的 430 NVIDIA 驱动程序。

卸载并安装

conda remove pytorch torchvision cudatoolkit

conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1.168 -c pytorch

对上述命令的所有内容都说“是”。

如何在没有冲突的情况下使用 conda 将 CUDA 降级到 10.0.10？

How to downgrade CUDA to 10.0.10 with conda, without conflicts?

python

conda

pytorch