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PyTorch documentation
https://pytorch.org/docs/master/index.html

PyTorch is an optimized tensor library for deep learning using GPUs and CPUs.

• torch.cuda.is_available (Python function, in torch.cuda.is_available)

1. torch.cuda.is_available

https://pytorch.org/docs/stable/generated/torch.cuda.is_available.html

torch.cuda.is_available()

Return a bool indicating if CUDA is currently available.

• Return type

bool

2. Example

https://github.com/karpathy/llama2.c/blob/master/sample.py

import torchdevice = 'cuda' if torch.cuda.is_available() else 'cpu'  # examples: 'cpu', 'cuda', 'cuda:0', 'cuda:1', etc.
device_type = 'cuda' if 'cuda' in device else 'cpu'  # for later use in torch.autocastprint("device =", device)
print("device_type =", device_type)

/home/yongqiang/miniconda3/bin/python /home/yongqiang/llm_work/llama2.c/yongqiang.py 
device = cpu
device_type = cpuProcess finished with exit code 0

References

[1] Yongqiang Cheng, https://yongqiang.blog.csdn.net/