安装老版本的Pytorch

2022-09-02 19:57:57 浏览数 (1)

Installing previous versions of PyTorch

We’d prefer you install the latest version, but old binaries and installation instructions are provided below for your convenience.

Commands for Versions >= 1.0.0

v1.6.0

Conda

OSX

代码语言：javascript复制
# conda
conda install pytorch==1.6.0 torchvision==0.7.0 -c pytorch

Linux and Windows

代码语言：javascript复制
# CUDA 9.2
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1 -c pytorch

# CUDA 10.2
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.2 -c pytorch

# CPU Only
conda install pytorch==1.6.0 torchvision==0.7.0 cpuonly -c pytorch

Wheel

OSX

代码语言：javascript复制
pip install torch==1.6.0 torchvision==0.7.0

Linux and Windows

代码语言：javascript复制
# CUDA 10.2
pip install torch==1.6.0 torchvision==0.7.0

# CUDA 10.1
pip install torch==1.6.0 cu101 torchvision==0.7.0 cu101 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 9.2
pip install torch==1.6.0 cu92 torchvision==0.7.0 cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.6.0 cpu torchvision==0.7.0 cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.5.1

Conda

OSX

代码语言：javascript复制
# conda
conda install pytorch==1.5.1 torchvision==0.6.1 -c pytorch

Linux and Windows

代码语言：javascript复制
# CUDA 9.2
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=10.1 -c pytorch

# CUDA 10.2
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=10.2 -c pytorch

# CPU Only
conda install pytorch==1.5.1 torchvision==0.6.1 cpuonly -c pytorch

Wheel

OSX

代码语言：javascript复制
pip install torch==1.5.1 torchvision==0.6.1

Linux and Windows

代码语言：javascript复制
# CUDA 10.2
pip install torch==1.5.1 torchvision==0.6.1

# CUDA 10.1
pip install torch==1.5.1 cu101 torchvision==0.6.1 cu101 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 9.2
pip install torch==1.5.1 cu92 torchvision==0.6.1 cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.5.1 cpu torchvision==0.6.1 cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.5.0

Conda

OSX

代码语言：javascript复制
# conda
conda install pytorch==1.5.0 torchvision==0.6.0 -c pytorch

Linux and Windows

代码语言：javascript复制
# CUDA 9.2
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=10.1 -c pytorch

# CUDA 10.2
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=10.2 -c pytorch

# CPU Only
conda install pytorch==1.5.0 torchvision==0.6.0 cpuonly -c pytorch

Wheel

OSX

代码语言：javascript复制
pip install torch==1.5.0 torchvision==0.6.0

Linux and Windows

代码语言：javascript复制
# CUDA 10.2
pip install torch==1.5.0 torchvision==0.6.0

# CUDA 10.1
pip install torch==1.5.0 cu101 torchvision==0.6.0 cu101 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 9.2
pip install torch==1.5.0 cu92 torchvision==0.6.0 cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.5.0 cpu torchvision==0.6.0 cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.4.0

Conda

OSX

代码语言：javascript复制
# conda
conda install pytorch==1.4.0 torchvision==0.5.0 -c pytorch

Linux and Windows

代码语言：javascript复制
# CUDA 9.2
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=10.1 -c pytorch

# CPU Only
conda install pytorch==1.4.0 torchvision==0.5.0 cpuonly -c pytorch

Wheel

OSX

代码语言：javascript复制
pip install torch==1.4.0 torchvision==0.5.0

Linux and Windows

代码语言：javascript复制
# CUDA 10.1
pip install torch==1.4.0 torchvision==0.5.0

# CUDA 9.2
pip install torch==1.4.0 cu92 torchvision==0.5.0 cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.4.0 cpu torchvision==0.5.0 cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.2.0

Conda

OSX

代码语言：javascript复制
# conda
conda install pytorch==1.2.0 torchvision==0.4.0 -c pytorch

Linux and Windows

代码语言：javascript复制
# CUDA 9.2
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=9.2 -c pytorch

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

# CPU Only
conda install pytorch==1.2.0 torchvision==0.4.0 cpuonly -c pytorch

Wheel

OSX

代码语言：javascript复制
pip install torch==1.2.0 torchvision==0.4.0

Linux and Windows

代码语言：javascript复制
# CUDA 10.0
pip install torch==1.2.0 torchvision==0.4.0

# CUDA 9.2
pip install torch==1.2.0 cu92 torchvision==0.4.0 cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.2.0 cpu torchvision==0.4.0 cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.1.0

Conda

OSX

代码语言：javascript复制
# conda
conda install pytorch==1.1.0 torchvision==0.3.0 -c pytorch

Linux and Windows

代码语言：javascript复制
# CUDA 9.0
conda install pytorch==1.1.0 torchvision==0.3.0 cudatoolkit=9.0 -c pytorch

# CUDA 10.0
conda install pytorch==1.1.0 torchvision==0.3.0 cudatoolkit=10.0 -c pytorch

# CPU Only
conda install pytorch-cpu==1.1.0 torchvision-cpu==0.3.0 cpuonly -c pytorch

Wheel

OSX

代码语言：javascript复制
pip install torch==1.1.0 torchvision==0.3.0

Linux and Windows

代码语言：javascript复制
# CUDA 10.0
Download and install wheel from https://download.pytorch.org/whl/cu100/torch_stable.html

# CUDA 9.0
Download and install wheel from https://download.pytorch.org/whl/cu90/torch_stable.html

# CPU only
Download and install wheel from https://download.pytorch.org/whl/cpu/torch_stable.html

v1.0.1

Conda

OSX

代码语言：javascript复制
# conda
conda install pytorch==1.0.1 torchvision==0.2.2 -c pytorch

Linux and Windows

代码语言：javascript复制
# CUDA 9.0
conda install pytorch==1.0.1 torchvision==0.2.2 cudatoolkit=9.0 -c pytorch

# CUDA 10.0
conda install pytorch==1.0.1 torchvision==0.2.2 cudatoolkit=10.0 -c pytorch

# CPU Only
conda install pytorch-cpu==1.0.1 torchvision-cpu==0.2.2 cpuonly -c pytorch

Wheel

OSX

代码语言：javascript复制
pip install torch==1.0.1 torchvision==0.2.2

Linux and Windows

代码语言：javascript复制
# CUDA 10.0
Download and install wheel from https://download.pytorch.org/whl/cu100/torch_stable.html

# CUDA 9.0
Download and install wheel from https://download.pytorch.org/whl/cu90/torch_stable.html

# CPU only
Download and install wheel from https://download.pytorch.org/whl/cpu/torch_stable.html

v1.0.0

Conda

OSX

代码语言：javascript复制
# conda
conda install pytorch==1.0.0 torchvision==0.2.1 -c pytorch

Linux and Windows

代码语言：javascript复制
# CUDA 10.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda100 -c pytorch

# CUDA 9.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda90 -c pytorch

# CUDA 8.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda80 -c pytorch

# CPU Only
conda install pytorch-cpu==1.0.0 torchvision-cpu==0.2.1 cpuonly -c pytorch

Wheel

OSX

代码语言：javascript复制
pip install torch==1.0.0 torchvision==0.2.1

Linux and Windows

代码语言：javascript复制
# CUDA 10.0
Download and install wheel from https://download.pytorch.org/whl/cu100/torch_stable.html

# CUDA 9.0
Download and install wheel from https://download.pytorch.org/whl/cu90/torch_stable.html

# CUDA 8.0
Download and install wheel from https://download.pytorch.org/whl/cu80/torch_stable.html

# CPU only
Download and install wheel from https://download.pytorch.org/whl/cpu/torch_stable.html

Commands for Versions < 1.0.0

Via conda

This should be used for most previous macOS version installs.

To install a previous version of PyTorch via Anaconda or Miniconda, replace “0.4.1” in the following commands with the desired version (i.e., “0.2.0”).

Installing with CUDA 9

conda install pytorch=0.4.1 cuda90 -c pytorch

or

conda install pytorch=0.4.1 cuda92 -c pytorch

Installing with CUDA 8

conda install pytorch=0.4.1 cuda80 -c pytorch

Installing with CUDA 7.5

conda install pytorch=0.4.1 cuda75 -c pytorch

Installing without CUDA

conda install pytorch=0.4.1 -c pytorch

From source

It is possible to checkout an older version of PyTorch and build it. You can list tags in PyTorch git repository with git tag and checkout a particular one (replace ‘0.1.9’ with the desired version) with

git checkout v0.1.9

Follow the install from source instructions in the README.md of the PyTorch checkout.

Via pip

Download the whl file with the desired version from the following html pages:

  • https://download.pytorch.org/whl/cpu/torch_stable.html # CPU-only build
  • https://download.pytorch.org/whl/cu80/torch_stable.html # CUDA 8.0 build
  • https://download.pytorch.org/whl/cu90/torch_stable.html # CUDA 9.0 build
  • https://download.pytorch.org/whl/cu92/torch_stable.html # CUDA 9.2 build
  • https://download.pytorch.org/whl/cu100/torch_stable.html # CUDA 10.0 build

Then, install the file with pip install [downloaded file]

Note: most pytorch versions are available only for specific CUDA versions. For example pytorch=1.0.1 is not available for CUDA 9.2

(Old) PyTorch Linux binaries compiled with CUDA 7.5

These predate the html page above and have to be manually installed by downloading the wheel file and pip install downloaded_file

  • cu75/torch-0.3.0.post4-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.3.0.post4-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.3.0.post4-cp27-cp27mu-linux_x86_64.whl
  • cu75/torch-0.3.0.post4-cp27-cp27m-linux_x86_64.whl
  • cu75/torch-0.2.0.post3-cp36-cp36m-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post3-cp35-cp35m-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post3-cp27-cp27mu-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post3-cp27-cp27m-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post2-cp36-cp36m-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post2-cp35-cp35m-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post2-cp27-cp27mu-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post2-cp27-cp27m-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post1-cp36-cp36m-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post1-cp35-cp35m-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post1-cp27-cp27mu-manylinux1_x86_64.whl
  • cu75/torch-0.2.0.post1-cp27-cp27m-manylinux1_x86_64.whl
  • cu75/torch-0.1.12.post2-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.12.post2-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.12.post2-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.12.post1-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.12.post1-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.12.post1-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.11.post5-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.11.post5-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.11.post5-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.11.post4-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.11.post4-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.11.post4-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.10.post2-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.10.post2-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.10.post2-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.10.post1-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.10.post1-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.10.post1-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.9.post2-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.9.post2-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.9.post2-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.9.post1-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.9.post1-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.9.post1-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.8.post1-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.8.post1-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.8.post1-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.7.post2-cp36-cp36m-linux_x86_64.whl
  • cu75/torch-0.1.7.post2-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.7.post2-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.6.post22-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.6.post22-cp27-none-linux_x86_64.whl
  • cu75/torch-0.1.6.post20-cp35-cp35m-linux_x86_64.whl
  • cu75/torch-0.1.6.post20-cp27-cp27mu-linux_x86_64.whl

Windows binaries

  • cpu/torch-1.0.0-cp35-cp35m-win_amd64.whl
  • cu80/torch-1.0.0-cp35-cp35m-win_amd64.whl
  • cu90/torch-1.0.0-cp35-cp35m-win_amd64.whl
  • cu100/torch-1.0.0-cp35-cp35m-win_amd64.whl
  • cpu/torch-1.0.0-cp36-cp36m-win_amd64.whl
  • cu80/torch-1.0.0-cp36-cp36m-win_amd64.whl
  • cu90/torch-1.0.0-cp36-cp36m-win_amd64.whl
  • cu100/torch-1.0.0-cp36-cp36m-win_amd64.whl
  • cpu/torch-1.0.0-cp37-cp37m-win_amd64.whl
  • cu80/torch-1.0.0-cp37-cp37m-win_amd64.whl
  • cu90/torch-1.0.0-cp37-cp37m-win_amd64.whl
  • cu100/torch-1.0.0-cp37-cp37m-win_amd64.whl
  • cpu/torch-0.4.1-cp35-cp35m-win_amd64.whl
  • cu80/torch-0.4.1-cp35-cp35m-win_amd64.whl
  • cu90/torch-0.4.1-cp35-cp35m-win_amd64.whl
  • cu92/torch-0.4.1-cp35-cp35m-win_amd64.whl
  • cpu/torch-0.4.1-cp36-cp36m-win_amd64.whl
  • cu80/torch-0.4.1-cp36-cp36m-win_amd64.whl
  • cu90/torch-0.4.1-cp36-cp36m-win_amd64.whl
  • cu92/torch-0.4.1-cp36-cp36m-win_amd64.whl
  • cpu/torch-0.4.1-cp37-cp37m-win_amd64.whl
  • cu80/torch-0.4.1-cp37-cp37m-win_amd64.whl
  • cu90/torch-0.4.1-cp37-cp37m-win_amd64.whl
  • cu92/torch-0.4.1-cp37-cp37m-win_amd64.whl

Mac and misc. binaries

For recent macOS binaries, use conda:

e.g.,

conda install pytorch=0.4.1 cuda90 -c pytorch conda install pytorch=0.4.1 cuda92 -c pytorch conda install pytorch=0.4.1 cuda80 -c pytorch conda install pytorch=0.4.1 -c pytorch # No CUDA

  • torchvision-0.1.6-py3-none-any.whl
  • torchvision-0.1.6-py2-none-any.whl
  • torch-1.0.0-cp37-none-macosx_10_7_x86_64.whl
  • torch-1.0.0-cp36-none-macosx_10_7_x86_64.whl
  • torch-1.0.0-cp35-none-macosx_10_6_x86_64.whl
  • torch-1.0.0-cp27-none-macosx_10_6_x86_64.whl
  • torch-0.4.0-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.4.0-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.4.0-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.3.1-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.3.1-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.3.1-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.3.0.post4-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.3.0.post4-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.3.0.post4-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.2.0.post3-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.2.0.post3-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.2.0.post3-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.2.0.post2-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.2.0.post2-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.2.0.post2-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.2.0.post1-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.2.0.post1-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.2.0.post1-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.12.post2-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.12.post2-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.1.12.post2-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.12.post1-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.12.post1-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.1.12.post1-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.11.post5-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.11.post5-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.1.11.post5-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.11.post4-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.11.post4-cp35-cp35m-macosx_10_7_x86_64.whl
  • torch-0.1.11.post4-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.10.post1-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.10.post1-cp35-cp35m-macosx_10_6_x86_64.whl
  • torch-0.1.10.post1-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.9.post2-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.9.post2-cp35-cp35m-macosx_10_6_x86_64.whl
  • torch-0.1.9.post2-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.9.post1-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.9.post1-cp35-cp35m-macosx_10_6_x86_64.whl
  • torch-0.1.9.post1-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.8.post1-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.8.post1-cp35-cp35m-macosx_10_6_x86_64.whl
  • torch-0.1.8.post1-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.7.post2-cp36-cp36m-macosx_10_7_x86_64.whl
  • torch-0.1.7.post2-cp35-cp35m-macosx_10_6_x86_64.whl
  • torch-0.1.7.post2-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.6.post22-cp35-cp35m-macosx_10_6_x86_64.whl
  • torch-0.1.6.post22-cp27-none-macosx_10_7_x86_64.whl
  • torch-0.1.6.post20-cp35-cp35m-linux_x86_64.whl
  • torch-0.1.6.post20-cp27-cp27mu-linux_x86_64.whl
  • torch-0.1.6.post17-cp35-cp35m-linux_x86_64.whl
  • torch-0.1.6.post17-cp27-cp27mu-linux_x86_64.whl
  • torch-0.1-cp35-cp35m-macosx_10_6_x86_64.whl
  • torch-0.1-cp27-cp27m-macosx_10_6_x86_64.whl
  • torch_cuda80-0.1.6.post20-cp35-cp35m-linux_x86_64.whl
  • torch_cuda80-0.1.6.post20-cp27-cp27mu-linux_x86_64.whl
  • torch_cuda80-0.1.6.post17-cp35-cp35m-linux_x86_64.whl
  • torch_cuda80-0.1.6.post17-cp27-cp27mu-linux_x86_64.whl
macos 对象存储 pytorch linux windows

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