Visual Studio
安裝 Python
Update nvidia driver
打開(kāi) cmd - 運(yùn)行 nvidia-smi (若運(yùn)行不成功需添加系統(tǒng)變量) - 查看 Driver Version - 確定支持的CUDA版本?
CUDA
cuDNN (需要注冊(cè)nvidia)
解壓，將bin, include, lib三個(gè)文件夾復(fù)制到?C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0
在系統(tǒng)變量的path中添加
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\extras\CUPTI\libx64
Anaconda安裝
點(diǎn)擊 Anaconda Prompt, 輸入
conda create -n pytorch_gpu pip python=3.7
conda activate pytorch_gpu
PyTorch
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=10.0 -c pytorch
驗(yàn)證安裝是否成功
運(yùn)行 python
import torch
x = torch.rand(5,3)
print(x)
torch.cuda.is_available()? ?（如果返回false，很可能網(wǎng)絡(luò)安裝pytorch的版本不對(duì)，可以下載相應(yīng)版本pytorch，用pip安裝）
安裝Spyder
打開(kāi) Anaconda Navigator - Home - Application on pytorch_gpu - Spyder install
run Spyder(pytorch_gpu)
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There are multiple different Pytorch versions for 1.1.0 if you want to use a GPU or want to be CPU only.
For Cuda10.0: https://download.pytorch.org/whl/cu100/torch_stable.html
For Cuda9.0: https://download.pytorch.org/whl/cu90/torch_stable.html
For CPU only: https://download.pytorch.org/whl/cpu/torch_stable.html
Then use?ctrl+f?to search for:
torch-1.1.0-cp{CPython version}-cp{CPython version}m-win_AMD64.whl
Replace?{Cpython version}?with your python version, for example 37 for 3.7.
Then download that file. Install using:
pip install <path to wheel file>
