A convenient utility function can be defined to return the requested $$i^{	extrm{th}}$$ GPU if it exists, or fall back to returning the CPU if the requested GPU is not available. This allows deep learning code to run smoothly regardless of the specific hardware configuration.

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The number of available GPUs on a system can be queried in PyTorch using the function torch.cuda.device_count().

Querying Available GPUs in PyTorch

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Fallback GPU Allocation Function

A utility function can be defined to return a list of all available GPUs. If no GPUs exist on the system, the function should return a list containing only the CPU device. This is useful for distributing workloads across all available hardware.

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