1、、Tensors are similar to NumPy’s ndarrays, with the addition being that Tensors can also be used on a GPU to accelerate computing.
2、、Any operation that mutates a tensor in-place is post-fixed with an ``_``.
# For example: ``x.copy_(y)``, ``x.t_()``, will change ``x``.
3、、You need to clear the existing gradients though, else gradients will be accumulated to existing gradients.
# # zeroes the gradient buffers of all parameters
4、、
print(loss.grad_fn.next_functions[0][0].next_functions[0][0])
5、、