PyTorch Env¶

1.PyTorch 支持的硬件平台¶

PC

CPU

GPU

Cloud TPU(张量)

Mobile

Android

iOS

Embedded Devices

2.PyTorch 系统要求¶

Linux distributions that use glibc >= v2.17

Arch Linux, minimum version 2012-07-15

CentOS, minimum version 7.3-1611

Debian, minimum version 8.0

Fedora, minimum version 24

Mint, minimum version 14

OpenSUSE, minimum version 42.1

PCLinuxOS, minimum version 2014.7

Slackware, minimum version 14.2

Ubuntu, minimum version 13.04

macOS 10.10(Yosemite) or above

Windows

Windows 7 and greater; Windows 10 or greater recommended.

Windows Server 2008 r2 and greater

3.macOS 安装 PyTorch¶

3.1 使用 pip 安装 PyTorch¶

$ pip install numpy
$ pip install torch torchvision

3.2 使用 Anaconda 安装 PyTorch¶

$ conda install pytorch torchvision -c pytorch

3.3 使用 Docker 安装 PyTorch¶

$ test test

4.Ubuntu 安装 Pytorch¶

4.1 使用 pip 安装 PyTorch¶

$ pip install torch==1.8.0+cpu torchvision==0.9.0+cpu torchaudio==0.8.0 -f https://download.pytorch.org/whl/torch_stable.html

4.2 使用 Anaconda 安装 PyTorch¶

$ conda install pytorch torchvision torchaudio cpuonly -c pytorch

4.3 使用 Docker 安装 PyTorch¶

$ test test

5.Building from source¶

5.1 macOS¶

Prerequisites

Install Anaconda

Install CUDA, if your machine has a CUDA-enabled GPU.

Install optional dependencies:
$ export CMAKE_PREFIX_PATH=[anaconda root directory]
$ conda install numpy pyyaml mkl mkl-include setuptools cmake cffi typing
$ git clone --recursive https://github.com/pytorch/pytorch
$ cd pytorch
$ MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py install
Note

当前，仅可以通过从源码构建 PyTorch 来获得 macOS 的 CUDA 支持

5.2 Ubuntu¶

$ git clone

6.Verification¶

Torch 使用:

>>> from __future__ import print_function
>>> import torch

>>> x = torch.rand(5, 3)
>>> print(x)

tensor([[0.3380, 0.3845, 0.3217],
      [0.8337, 0.9050, 0.2650],
      [0.2979, 0.7141, 0.9069],
      [0.1449, 0.1132, 0.1375],
      [0.4675, 0.3947, 0.1426]])

GPU dirver 和 CUDA:

import torch

torch.cuda.is_available()