ubantu18.04 RTX2070使用anaconda3安裝pytorch

pytorch安裝參考https://blog.csdn.net/sinat_41563673/article/details/97402059

https://blog.csdn.net/excellent_sun/article/details/88830687

1、anaconda3安裝方法見https://blog.csdn.net/qq_42412214/article/details/94917609

2、創建名爲torch的anaconda虛擬環境：

conda create -n torch python=3.6.5

3、安裝pytorch

1）添加anaconda國內源，使anaconda安裝環境更快

將以下配置文件寫在~/.condarc中（初始爲空文件）
sudo gedit ~/.condarc

channels:
  - https://mirrors.ustc.edu.cn/anaconda/pkgs/main/
  - https://mirrors.ustc.edu.cn/anaconda/cloud/conda-forge/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
  - defaults
show_channel_urls: true

2）在pytorch官網找到對應版本安裝命令https://pytorch.org/get-started/locally/

選擇本機CUDA10.0  conda安裝的版本

# CUDA 10.0
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=10.0 -c pytorch

3）進入conda虛擬環境torch，使用上述命令安裝

4）安裝成功後import torch，沒有報錯

5）繼續測試

python tor.py
python torgpu.py

tor.py代碼：

# -*- coding: utf-8 -*-
"""
Created on Sun Feb  4 14:26:59 2018

@author: admin
"""

import torch #引用torch包

x = torch.Tensor(2,3)
print(x)

torgpu.py代碼：

# CUDA TEST
import torch
x = torch.Tensor([1.0])
xx = x.cuda()
print(xx)

# CUDNN TEST
from torch.backends import cudnn
print(cudnn.is_acceptable(xx))