PyTorch GPU版本安装 PyTorch 检查GPU版本是否安装成功的操作

(base) PS C:\Users\chenxuqi> conda deactivate
PS C:\Users\chenxuqi> conda activate ssd
(ssd) PS C:\Users\chenxuqi> python
Python 3.6.12 |Anaconda, Inc.| (default, Sep 9 2020, 00:29:25) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.__version__)
0.4.0
>>> print(torch.cuda.is_available())
True
>>>
>>>
>>>

Microsoft Windows [版本 10.0.18363.1139]
(c) 2019 Microsoft Corporation。保留所有权利。

C:\Users\chenxuqi>nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Sep__1_21:08:32_Central_Daylight_Time_2017
Cuda compilation tools, release 9.0, V9.0.176

C:\Users\chenxuqi>
C:\Users\chenxuqi>

import time
import torch 

##################################################

for i in range(1,10):
  start = time.time()
  a = torch.FloatTensor(i*100,1000,1000)
  a = a.cuda() #a = a
  a = torch.matmul(a,a)
  end = time.time() - start
  print(end)

Windows PowerShell

尝试新的跨平台 PowerShell https://aka.ms/pscore6

PS C:\Users\chenxuqi\Desktop\新建文件夹> & 'D:\Anaconda3\envs\ssd\python.exe' 'c:\Users\chenxuqi\.vscode\extensions\ms-python.python-2020.10.332292344\pythonFiles\lib\python\debugpy\launcher' '50571' '--' 'c:\Users\chenxuqi\Desktop\新建文件夹\testGPU.py'
3.6260359287261963
0.6305170059204102
0.9055967330932617
1.3199987411499023
1.5979139804840088
2.0483360290527344
THCudaCheck FAIL file=c:\programdata\miniconda3\conda-bld\pytorch_1524549877902\work\aten\src\thc\generic/THCStorage.cu line=58 error=2 : out of memory
Traceback (most recent call last):
 File "c:\Users\chenxuqi\Desktop\新建文件夹\testGPU.py", line 10, in <module>
  a = torch.matmul(a,a)
RuntimeError: cuda runtime error (2) : out of memory at c:\programdata\miniconda3\conda-bld\pytorch_1524549877902\work\aten\src\thc\generic/THCStorage.cu:58
PS C:\Users\chenxuqi\Desktop\新建文件夹> conda activate ssd
PS C:\Users\chenxuqi\Desktop\新建文件夹>

pip install "下在的安装包的路径"

pip install "C:\Users\28614\Desktop\pytorch-nightly-cpu-1.0.0.dev20181222-py3.7_cpu_0.tar.bz2"

import torch
print(torch.cuda.is_available())