Hi,
Is there a way to use Cuda through numpy arrays inside the forward() and backward() functions in custom Modules? For example, if I want to compute fft2 in GPU in the example in https://github.com/pytorch/tutorials/blob/master/Creating%20extensions%20using%20numpy%20and%20scipy.ipynb 9 how should I go about that?
Just converting the model and input to cuda results in “RuntimeError: numpy conversion for FloatTensor is not supported” error at “result = abs(rfft2(numpy_input)) line”.
class BadFFTFunction(Function):
    
    def forward(self, input):
        numpy_input = input.numpy()
        result = abs(rfft2(numpy_input))
        return torch.FloatTensor(result)
    
    def backward(self, grad_output):
        numpy_go = grad_output.numpy()
        result = irfft2(numpy_go)
        return torch.FloatTensor(result)