I think the simplest is going for you to print the objects. And check whether you have a Tensor (if not specified, it’s on the cpu, otherwise it will tell your it’s a cuda Tensor) or a np.array.
You need to give a Tensor to your model, torch operations and np.array to everything else.
To go from np.array to cpu Tensor, use torch.from_numpy().
To go from cpu Tensor to gpu Tensor, use .cuda().
To go from a Tensor that requires_grad to one that does not, use .detach() (in your case, your net output will most likely requires gradients and so it’s output will need to be detached).
To go from a gpu Tensor to cpu Tensor, use .cpu().
Tp gp from a cpu Tensor to np.array, use .numpy().