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# PyTorch torch.cuda Functions * * Pytorch torch Reference Manual](#) `torch.cuda` is the module for CUDA management in PyTorch. It provides functions for CUDA device management, memory management, synchronization, and more. ### Function Definition torch.cuda The torch.cuda module contains the following commonly used functions: * `torch.cuda.is_available()` - Check if CUDA is available * `torch.cuda.device_count()` - Get the number of CUDA devices * `torch.cuda.current_device()` - Get the current device * `torch.cuda.synchronize()` - Synchronize CUDA operations * `torch.cuda.empty_cache()` - Clear cache * * * ## Usage Example ## Example import torch # Check if CUDA is Available print(f"CUDA available: {torch.cuda.is_available()}") # Get Number of CUDA Devices if torch.cuda.is_available(): print(f"CUDA device count: {torch.cuda.device_count()}") print(f"CUDA device name: {torch.cuda.get_device_name(0)}") * * Pytorch torch Reference Manual](#)