Hi again @ptrblck
I am trying to use some opencv functions like the following:
class opencv_torch(Function):
    @staticmethod
    def forward(ctx, im1, im2, **params,):
        numpy_im1 = im1.to('cpu').detach().numpy()
        result = cv2.FUNCTION(numpy_im1 , **params)
        return torch.FloatTensor(result)
    @staticmethod
    def backward(ctx, grad_output):
        return None, None

I want this Function to be parameter-less without any learnable parameters so it gives only the output, does this break the gradient flow?
Thank you