Thanks for the quick reply @albanD. Does this mean that if I have a cuda tensor I can just pass it as an argument to a pyCuda kernel and it would just behave as a PyCuda DeviceAllocation object? Or do I have to do something else?
e.g

a = torch.LongTensor(10).fill_(3).cuda
myCudaFunc(a,
block=BLOCK_DIMS,
grid=GRID_DIMS)