文章目录
- conda 安装pytorch with cuda 失败问题
- 使用pip安装
- 使用conda安装pytorch with cuda
- 安装完cuda依然无法调用:错误的版本搭配
- 正确的安装组合
- 清华源
conda 安装pytorch with cuda 失败问题
- 激活环境(本例假设环境为
pytorch_ser)
PS D:\repos\PythonLearn> conda activate pytorch_ser
- 尝试直接运行pytorch官网给出的conda安装命令,发现解析操作迟迟无法结束
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
....
Solving environment: ....
- 原因可能是:
- 我将默认的源换成清华源,而清华源的镜像没有能够满足要安装的配套组件
- 网络环境问题,更换网络重试
- 服务器问题,更改时段再试
使用pip安装
(d:\condaPythonEnvs\pytorch_ser) PS D:\repos\blogs> pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu117
Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu117
Requirement already satisfied: torch in d:\condapythonenvs\pytorch_ser\lib\site-packages (1.13.1)
Requirement already satisfied: torchvision in d:\condapythonenvs\pytorch_ser\lib\site-packages (0.14.1)
Requirement already satisfied: torchaudio in d:\condapythonenvs\pytorch_ser\lib\site-packages (0.13.1)
Requirement already satisfied: typing_extensions in d:\condapythonenvs\pytorch_ser\lib\site-packages (from torch) (4.4.0)
Requirement already satisfied: numpy in d:\condapythonenvs\pytorch_ser\lib\site-packages (from torchvision) (1.23.5)
Requirement already satisfied: requests in d:\condapythonenvs\pytorch_ser\lib\site-packages (from torchvision) (2.28.1)
Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in d:\condapythonenvs\pytorch_ser\lib\site-packages (from torchvision) (9.3.0)
Requirement already satisfied: certifi>=2017.4.17 in d:\condapythonenvs\pytorch_ser\lib\site-packages (from requests->torchvision) (2022.12.7)
Requirement already satisfied: charset-normalizer<3,>=2 in d:\condapythonenvs\pytorch_ser\lib\site-packages (from requests->torchvision) (2.0.4)
Requirement already satisfied: idna<4,>=2.5 in d:\condapythonenvs\pytorch_ser\lib\site-packages (from requests->torchvision) (3.4)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in d:\condapythonenvs\pytorch_ser\lib\site-packages (from requests->torchvision) (1.26.13)
- 从上面的输出上看,pip似乎无法完成cuda组件的安装
使用conda安装pytorch with cuda
安装完cuda依然无法调用:错误的版本搭配
- 最初我尝试安装pytorch with cuda,发现无法安装(不停的解析,而无法顺利结束)
- 我安装一遍pytorch cpu only,发现可以顺利安装
- 过来若干天,重试,发现可以安装pytorch with cuda
- 遗憾的是,当我检查cuda可用性时,发现不可用!
(d:\condaPythonEnvs\pytorch_ser) PS D:\repos\blogs> conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: done
## Package Plan ##
environment location: d:\condaPythonEnvs\pytorch_ser
added / updated specs:
- pytorch
- pytorch-cuda=11.7
- torchaudio
- torchvision
The following packages will be downloaded:
package | build
---------------------------|-----------------
cuda-11.7.1 | 0 1 KB nvidia
cuda-cccl-11.7.91 | 0 1.2 MB nvidia
cuda-command-line-tools-11.7.1| 0 1 KB nvidia
cuda-compiler-11.7.1 | 0 1 KB nvidia
cuda-cudart-11.7.99 | 0 1.4 MB nvidia
cuda-cudart-dev-11.7.99 | 0 711 KB nvidia
cuda-cuobjdump-11.7.91 | 0 2.5 MB nvidia
cuda-cupti-11.7.101 | 0 10.2 MB nvidia
cuda-cuxxfilt-11.7.91 | 0 165 KB nvidia
....
cuda-toolkit-11.7.1 | 0 1 KB nvidia
cuda-tools-11.7.1 | 0 1 KB nvidia
cuda-visual-tools-11.7.1 | 0 1 KB nvidia
libcublas-11.10.3.66 | 0 24 KB nvidia
libcublas-dev-11.10.3.66 | 0 282.4 MB nvidia
libcufft-10.7.2.124 | 0 6 KB nvidia
libcufft-dev-10.7.2.124 | 0 250.1 MB nvidia
libcurand-10.3.1.50 | 0 3 KB nvidia
libcurand-dev-10.3.1.50 | 0 50.0 MB nvidia
libcusolver-11.4.0.1 | 0 29 KB nvidia
libcusolver-dev-11.4.0.1 | 0 76.5 MB nvidia
libcusparse-11.7.4.91 | 0 13 KB nvidia
libcusparse-dev-11.7.4.91 | 0 149.6 MB nvidia
libnpp-11.7.4.75 | 0 294 KB nvidia
libnpp-dev-11.7.4.75 | 0 125.6 MB nvidia
libnvjpeg-11.8.0.2 | 0 4 KB nvidia
libnvjpeg-dev-11.8.0.2 | 0 1.7 MB nvidia
nsight-compute-2022.4.0.15 | 0 598.6 MB nvidia
pytorch-cuda-11.7 | h67b0de4_1 3 KB pytorch
------------------------------------------------------------
Total: 1.82 GB
The following NEW packages will be INSTALLED:
cuda nvidia/win-64::cuda-11.7.1-0
cuda-cccl nvidia/win-64::cuda-cccl-11.7.91-0
cuda-command-line~ nvidia/win-64::cuda-command-line-tools-11.7.1-0
cuda-compiler nvidia/win-64::cuda-compiler-11.7.1-0
cuda-cudart nvidia/win-64::cuda-cudart-11.7.99-0
cuda-cudart-dev nvidia/win-64::cuda-cudart-dev-11.7.99-0
cuda-cuobjdump nvidia/win-64::cuda-cuobjdump-11.7.91-0
cuda-cupti nvidia/win-64::cuda-cupti-11.7.101-0
...
cuda-tools nvidia/win-64::cuda-tools-11.7.1-0
cuda-visual-tools nvidia/win-64::cuda-visual-tools-11.7.1-0
libcublas nvidia/win-64::libcublas-11.10.3.66-0
libcublas-dev nvidia/win-64::libcublas-dev-11.10.3.66-0
libcufft nvidia/win-64::libcufft-10.7.2.124-0
libcufft-dev nvidia/win-64::libcufft-dev-10.7.2.124-0
libcurand nvidia/win-64::libcurand-10.3.1.50-0
libcurand-dev nvidia/win-64::libcurand-dev-10.3.1.50-0
libcusolver nvidia/win-64::libcusolver-11.4.0.1-0
libcusolver-dev nvidia/win-64::libcusolver-dev-11.4.0.1-0
libcusparse nvidia/win-64::libcusparse-11.7.4.91-0
libcusparse-dev nvidia/win-64::libcusparse-dev-11.7.4.91-0
libnpp nvidia/win-64::libnpp-11.7.4.75-0
libnpp-dev nvidia/win-64::libnpp-dev-11.7.4.75-0
libnvjpeg nvidia/win-64::libnvjpeg-11.8.0.2-0
libnvjpeg-dev nvidia/win-64::libnvjpeg-dev-11.8.0.2-0
nsight-compute nvidia/win-64::nsight-compute-2022.4.0.15-0
pytorch-cuda pytorch/noarch::pytorch-cuda-11.7-h67b0de4_1
Proceed ([y]/n)? y
Downloading and Extracting Packages
cuda-cudart-dev-11.7 | 711 KB | ############################################################################################################################################### | 100%
cuda-memcheck-11.8.8 | 183 KB | ############################################################################################################################################### | 100%
cuda-cudart-11.7.99 | 1.4 MB | ############################################################################################################################################### | 100%
libnvjpeg-11.8.0.2 | 4 KB | ############################################################################################################################################### | 100%
pytorch-cuda-11.7 | 3 KB | ############################################################################################################################################### | 100%
........
####################################################################################################################5 | 81%
cuda-cupti-11.7.101 | 10.2 MB | ############################################################################################################################################### | 100%
cuda-demo-suite-12.0 | 4.7 MB | ############################################################################################################################################### | 100%
正确的安装组合
- 我猜测如果之前安装过cpu only 版本的pytorch,导致pytorch基础组件和cuda pytorch 组件不能够配合工作
- 所以再一个新的环境中重新安装cuda版pytorch
(d:\condaPythonEnvs\pytorch_ser) PS C:\Users\cxxu\Desktop> conda activate py310
(py310) PS C:\Users\cxxu\Desktop> conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: done
## Package Plan ##
environment location: C:\Users\cxxu\miniconda3\envs\py310
added / updated specs:
- pytorch
- pytorch-cuda=11.7
- torchaudio
- torchvision
The following packages will be downloaded:
package | build
---------------------------|-----------------
pytorch-1.13.1 |py3.10_cuda11.7_cudnn8_0 1.10 GB pytorch
pytorch-mutex-1.0 | cuda 3 KB pytorch
torchaudio-0.13.1 | py310_cu117 4.7 MB pytorch
torchvision-0.14.1 | py310_cu117 7.5 MB pytorch
------------------------------------------------------------
Total: 1.11 GB
The following NEW packages will be INSTALLED:
brotlipy anaconda/pkgs/main/win-64::brotlipy-0.7.0-py310h2bbff1b_1002
cffi anaconda/pkgs/main/win-64::cffi-1.15.1-py310h2bbff1b_3
charset-normalizer anaconda/pkgs/main/noarch::charset-normalizer-2.0.4-pyhd3eb1b0_0
cryptography anaconda/pkgs/main/win-64::cryptography-38.0.1-py310h21b164f_0
cuda nvidia/win-64::cuda-11.7.1-0
cuda-cccl nvidia/win-64::cuda-cccl-11.7.91-0
cuda-command-line~ nvidia/win-64::cuda-command-line-tools-11.7.1-0
cuda-compiler nvidia/win-64::cuda-compiler-11.7.1-0
....
cuda-tools nvidia/win-64::cuda-tools-11.7.1-0
cuda-visual-tools nvidia/win-64::cuda-visual-tools-11.7.1-0
flit-core anaconda/pkgs/main/noarch::flit-core-3.6.0-pyhd3eb1b0_0
freetype anaconda/pkgs/main/win-64::freetype-2.12.1-ha860e81_0
idna anaconda/pkgs/main/win-64::idna-3.4-py310haa95532_0
jpeg anaconda/pkgs/main/win-64::jpeg-9e-h2bbff1b_0
lerc anaconda/pkgs/main/win-64::lerc-3.0-hd77b12b_0
....
pytorch-mutex pytorch/noarch::pytorch-mutex-1.0-cuda
requests anaconda/pkgs/main/win-64::requests-2.28.1-py310haa95532_0
torchaudio pytorch/win-64::torchaudio-0.13.1-py310_cu117
torchvision pytorch/win-64::torchvision-0.14.1-py310_cu117
typing_extensions anaconda/pkgs/main/win-64::typing_extensions-4.4.0-py310haa95532_0
urllib3 anaconda/pkgs/main/win-64::urllib3-1.26.13-py310haa95532_0
win_inet_pton anaconda/pkgs/main/win-64::win_inet_pton-1.1.0-py310haa95532_0
zstd anaconda/pkgs/main/win-64::zstd-1.5.2-h19a0ad4_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
torchaudio-0.13.1 | 4.7 MB | ############################################################################ | 100%
pytorch-mutex-1.0 | 3 KB | ############################################################################ | 100%
pytorch-1.13.1 | 1.10 GB | ###########################################################################9 | 100%
torchvision-0.14.1 | 7.5 MB | ############################################################################ | 100%
GB | ########################################################
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(py310) PS C:\Users\cxxu\Desktop>
- 检查cuda可用性
import torch as torch
import torch as th
print(th.__version__)
print(th.version.cuda)
print(th.cuda.is_available())
(py310) PS D:\repos\CCSER> python
Python 3.10.8 | packaged by conda-forge | (main, Nov 24 2022, 14:07:00) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch as torch
>>> import torch as th
>>> print(th.__version__)
1.13.1
>>> print(th.version.cuda)
11.7
>>> print(th.cuda.is_available())
True
- 安装的源用的清华源,宽带500M,再几分钟内(5分钟)可以完成安装
- nvidia驱动版本和cuda驱动版本(CUDA Version: 12.0 )
- cuda驱动版本要高于cuda运行时版本
- 如果驱动版本过旧,到nvidia官方下载更新
- 官方驱动 | NVIDIA
PS C:\Users\cxxu\Desktop> nvidia-smi.exe
Sun Jan 8 17:15:39 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 527.56 Driver Version: 527.56 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... WDDM | 00000000:02:00.0 Off | N/A |
| N/A 45C P0 N/A / N/A | 0MiB / 2048MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
- 配置文件样例如下:
channels:
- defaults
show_channel_urls: true
default_channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:
conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
auto_activate_base: false
清华源
- anaconda | 镜像站使用帮助 | 清华大学开源软件镜像站 | Tsinghua Open Source Mirror
- conda发行版比较@python环境管理@conda命令的基本操作@配置conda_xuchaoxin1375的博客-
