Created
August 28, 2020 08:33
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Information on available GPU by PyTorch
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| import torch | |
| #Check availability of GPU: | |
| print(f"Pytorch version: {torch.__version__}") | |
| print(f"Current device: {torch.cuda.current_device()}") | |
| print(f"Device count: {torch.cuda.device_count()}") | |
| print(f"Device name: {torch.cuda.get_device_name(0)}") | |
| print(f"Is CUDA available?: {torch.cuda.is_available()}") | |
| # Set device on GPU if available, else CPU | |
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') | |
| print('\nUsing device:', device) | |
| #A dditional info on memory | |
| if device.type == 'cuda': | |
| print(torch.cuda.get_device_name(0)) | |
| print('\nMemory Usage:') | |
| print('Allocated:', round(torch.cuda.memory_allocated(0)/1024**3,1), 'GB') | |
| print('Cached: ', round(torch.cuda.memory_cached(0)/1024**3,1), 'GB') |
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