anaconda配置pytorch环境

# CUDA 10.2
conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cudatoolkit=10.2 -c pytorch


# CUDA 11.3
conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cudatoolkit=11.3 -c pytorch


# CPU Only
conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cpuonly -c pytorch

# ROCM 4.5.2 (Linux only)
pip install torch==1.11.0+rocm4.5.2 torchvision==0.12.0+rocm4.5.2 torchaudio==0.11.0 --extra-index-url  https://download.pytorch.org/whl/rocm4.5.2


# CUDA 11.3
pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113


# CUDA 10.2
pip install torch==1.11.0+cu102 torchvision==0.12.0+cu102 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu102


# CPU only
pip install torch==1.11.0+cpu torchvision==0.12.0+cpu torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cpu

import torch
x = torch.arange(12)
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terminal: tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])

print(torch.cuda.is_available())
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terminal: False

conda install cudnn=7.6.5

再次测试torch是否可以调取GPU

print(torch.cuda.is_available())
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terminal: False

经测试依旧无法调取gpu,经查询CUDA与pytorch匹配关系如下

# 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

print(torch.cuda.is_available())
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terminal: True