Does the pytorch has a tool to convert data from GPU to CPU and from CPU to GPU automatically when the GPU memory is not enough?

[ptrblck]

@clockzhong

Then I could fully utilize my GPU’s calculating performance and my CPU memory’s size.

For a potentially large performance penalty due to the additional data movement.

You could offload data to the CPU as described here or you could try to write a custom allocator with offloading capabilities using torch.cuda.CUDAPluggableAllocator.