TheLazy.Dev
Portfolio GitHub

Blog

python |pytorch |version |device

Check PyTorch version, CPU and GPU(CUDA) in PyTorch

hyperkai

Super Kai (Kazuya Ito)

Posted on May 26, 2024

Check PyTorch version, CPU and GPU(CUDA) in PyTorch

Buy Me a Coffee☕

*My post explains how to create and acceess a tensor.

__version__ can check PyTorch version as shown below. *__version__ can be used with torch but not with a tensor:

import torch

torch.__version__ # 2.2.1+cu121
Enter fullscreen mode Exit fullscreen mode

cpu.is_available(), cpu.device_count() or cpu.current_device() can check if CPU is available, getting a scalar as shown below:

*Memos:

  • cpu.is_available(), cpu.device_count() or cpu.current_device() can be used with torch but not with a tensor.
  • cpu.device_count() can get the number of CPUs. *It always gets 1:
  • cpu.current_device() can get the index of a currently selected CPU. *It always gets cpu: 
import torch

torch.cpu.is_available() # True

torch.cpu.device_count() # 1

torch.cpu.current_device() # cpu
Enter fullscreen mode Exit fullscreen mode

cuda.is_available() or cuda.device_count() can check if GPU(CUDA) is available, getting a scalar as shown below:

*Memos:

  • cuda.is_available() or cuda.device_count() can be used with torch but not with a tensor.
  • cuda.device_count() can get the number of GPUs. 
import torch

torch.cuda.is_available() # True

torch.cuda.device_count() # 1
Enter fullscreen mode Exit fullscreen mode

In addition, you can use cuda.current_device(), cuda.get_device_name() or cuda.get_device_properties(), getting a scalar as shown below:

*Memos:

  • cuda.current_device(), cuda.get_device_name() or cuda.get_device_properties() can be used with torch but not with a tensor.
  • cuda.current_device() can get the index of a currently selected GPU.
  • cuda.get_device_name() can get the name of a GPU. *Memos:
    • The 1st argument with torch is device(Optional-Default:None-Type:(str, int or device().
    • If it's None, cuda.current_device() is used.
    • The number must be zero or positive.
    • Only cuda can be set to device.
    • My post explains device().
  • cuda.get_device_properties() can get the properties of a GPU. *Memos:
    • The 1st argument with torch is device(Required-Type:str, int or device()).
    • The number must be zero or positive.
    • Only cuda can be set to device.
    • My post explains device(). 
torch.cuda.current_device() # 0

torch.cuda.get_device_name()
torch.cuda.get_device_name(device='cuda:0')
torch.cuda.get_device_name(device='cuda')
torch.cuda.get_device_name(device=0)
torch.cuda.get_device_name(device=torch.device(device='cuda:0'))
torch.cuda.get_device_name(device=torch.device(device='cuda'))
torch.cuda.get_device_name(device=torch.device(device=0))
torch.cuda.get_device_name(device=torch.device(type='cuda'))
torch.cuda.get_device_name(device=torch.device(type='cuda', index=0))
# Tesla T4

torch.cuda.get_device_properties(device='cuda:0')
torch.cuda.get_device_properties(device='cuda')
torch.cuda.get_device_properties(device=0)
torch.cuda.get_device_properties(device=torch.device(device='cuda:0'))
torch.cuda.get_device_properties(device=torch.device(device='cuda'))
torch.cuda.get_device_properties(device=torch.device(device=0))
torch.cuda.get_device_name(device=torch.device(type='cuda'))
torch.cuda.get_device_name(device=torch.device(type='cuda', index=0))
# _CudaDeviceProperties(name='Tesla T4', major=7, minor=5, 
# total_memory=15102MB, multi_processor_count=40)
Enter fullscreen mode Exit fullscreen mode

!nvidia-smi can get the information about GPUs as shown below:

!nvidia-smi

Wed May 15 13:18:15 2024       
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  Tesla T4                       Off | 00000000:00:04.0 Off |                    0 |
| N/A   56C    P0              28W /  70W |    105MiB / 15360MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
+---------------------------------------------------------------------------------------+
Enter fullscreen mode Exit fullscreen mode
💖 💪 🙅 🚩
hyperkai
Super Kai (Kazuya Ito)

Posted on May 26, 2024

Join Our Newsletter. No Spam, Only the good stuff.

Sign up to receive the latest update from our blog.

Related

Check PyTorch version, CPU and GPU(CUDA) in PyTorch
python Check PyTorch version, CPU and GPU(CUDA) in PyTorch

May 26, 2024