pytorch版本官网命令

本文提供了不同版本PyTorch的安装指令,包括使用Conda及pip安装含不同CUDA版本的PyTorch、torchvision和torchaudio。适用于Linux、Windows及OSX系统。
部署运行你感兴趣的模型镜像

COMMANDS FOR VERSIONS >= 1.0.0

v1.8.0

Conda

OSX

# conda
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 -c pytorch

Linux and Windows

# CUDA 10.2
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=10.2 -c pytorch

# CUDA 11.1
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge

# CPU Only
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cpuonly -c pytorch

Wheel

OSX

pip install torch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0

Linux and Windows

# RocM 4.0.1 (Linux only)
pip install torch -f https://download.pytorch.org/whl/rocm4.0.1/torch_stable.html
pip install ninja
pip install 'git+https://github.com/pytorch/vision.git@v0.9.0'

# CUDA 11.0
pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 torchaudio==0.8.0 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 10.2
pip install torch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0

# CPU only
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

v1.7.1

Conda

OSX

# conda
conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 -c pytorch

Linux and Windows

# CUDA 9.2
conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=10.1 -c pytorch

# CUDA 10.2
conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=10.2 -c pytorch

# CUDA 11.0
conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=11.0 -c pytorch

# CPU Only
conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cpuonly -c pytorch

Wheel

OSX

pip install torch==1.7.1 torchvision==0.8.2 torchaudio=0.7.2

Linux and Windows

# CUDA 11.0
pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 10.2
pip install torch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2

# CUDA 10.1
pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 9.2
pip install torch==1.7.1+cu92 torchvision==0.8.2+cu92 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.7.1+cpu torchvision==0.8.2+cpu torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html

v1.7.0

Conda

OSX

# conda
conda install pytorch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 -c pytorch

Linux and Windows

# CUDA 9.2
conda install pytorch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 cudatoolkit=10.1 -c pytorch

# CUDA 10.2
conda install pytorch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 cudatoolkit=10.2 -c pytorch

# CUDA 11.0
conda install pytorch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 cudatoolkit=11.0 -c pytorch

# CPU Only
conda install pytorch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 cpuonly -c pytorch

Wheel

OSX

pip install torch==1.7.0 torchvision==0.8.0 torchaudio=0.7.0

Linux and Windows

# CUDA 11.0
pip install torch==1.7.0+cu110 torchvision==0.8.0+cu110 torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 10.2
pip install torch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0

# CUDA 10.1
pip install torch==1.7.0+cu101 torchvision==0.8.0+cu101 torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 9.2
pip install torch==1.7.0+cu92 torchvision==0.8.0+cu92 torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.7.0+cpu torchvision==0.8.0+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html

v1.6.0

Conda

OSX

# conda
conda install pytorch==1.6.0 torchvision==0.7.0 -c pytorch

Linux and Windows

# 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

pip install torch==1.6.0 torchvision==0.7.0

Linux and Windows

# 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

# conda
conda install pytorch==1.5.1 torchvision==0.6.1 -c pytorch

Linux and Windows

# 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

pip install torch==1.5.1 torchvision==0.6.1

Linux and Windows

# 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

# conda
conda install pytorch==1.5.0 torchvision==0.6.0 -c pytorch

Linux and Windows

# 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

pip install torch==1.5.0 torchvision==0.6.0

Linux and Windows

# 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

# conda
conda install pytorch==1.4.0 torchvision==0.5.0 -c pytorch

Linux and Windows

# 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

pip install torch==1.4.0 torchvision==0.5.0

Linux and Windows

# 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

# conda
conda install pytorch==1.2.0 torchvision==0.4.0 -c pytorch

Linux and Windows

# 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

pip install torch==1.2.0 torchvision==0.4.0

Linux and Windows

# 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

# conda
conda install pytorch==1.1.0 torchvision==0.3.0 -c pytorch

Linux and Windows

# 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

pip install torch==1.1.0 torchvision==0.3.0

Linux and Windows

# 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

# conda
conda install pytorch==1.0.1 torchvision==0.2.2 -c pytorch

Linux and Windows

# 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

pip install torch==1.0.1 torchvision==0.2.2

Linux and Windows

# 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

# conda
conda install pytorch==1.0.0 torchvision==0.2.1 -c pytorch

Linux and Windows

# 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

pip install torch==1.0.0 torchvision==0.2.1

Linux and Windows

# 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

 

您可能感兴趣的与本文相关的镜像

PyTorch 2.9

PyTorch 2.9

PyTorch
Cuda

PyTorch 是一个开源的 Python 机器学习库,基于 Torch 库,底层由 C++ 实现,应用于人工智能领域,如计算机视觉和自然语言处理

可以使用以下几种方法来查看已安装的 PyTorch 版本信息: 在 Python 脚本或交互式环境中,可以通过导入 `torch` 模块并打印其版本信息来实现: ```python import torch print(torch.__version__) ``` 这种方法直接利用了 PyTorch 自身提供的版本信息查询功能,是最直接有效的方式之一[^2]。 如果希望在不启动 Python 解释器的情况下快速检查版本,可以通过命令行执行单行 Python 命令来达到目的: ```bash python -c "import torch; print(torch.__version__)" ``` 此命令会在命令行环境下运行一个小型的 Python 脚本,输出 PyTorch版本信息[^2]。 此外,还可以通过查看 PyTorch 的 CUDA 支持情况来间接确认版本,尽管这主要用于确认是否支持 GPU 加速,但也能反映出部分版本相关的信息: ```python import torch if torch.cuda.is_available(): print("CUDA 版本:", torch.version.cuda) else: print("CUDA 不可用") ``` 这段代码不仅检查了 CUDA 是否可用,还能够显示与当前安装的 PyTorch 版本兼容的 CUDA 版本[^5]。 对于希望进一步验证安装或者需要特定版本的情况,了解如何查看当前安装的 PyTorch 版本是非常有帮助的。如果确实需要安装特定版本PyTorch,可以考虑使用 `conda` 或 `pip` 安装指定版本,具体命令如下: - 使用 `conda` 安装指定版本: ```bash conda install pytorch=0.1.10 -c soumith ``` - 使用 `pip` 安装指定版本: ```bash pip install pytorch==0.1.10 ``` 这些方法确保了用户可以根据自己的需求选择合适的安装方式[^3]。 最后,对于那些需要安装带有 GPU 支持的 PyTorch 版本的用户,可以通过特定的下载链接和安装命令来完成安装,例如安装带有 CUDA 10.1 支持的 PyTorch 1.7.1 版本: ```bash pip install torch1.7.1+cu101 torchvision0.8.2+cu101 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html ``` 这种方式允许用户精确地控制所安装的 PyTorch 及其依赖库的版本[^4]。
评论 1
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值