PyTorch - Calculate one step of gradient

import torch

# create initial tensor with floats
w = torch.tensor( [[1.,2.,3.],[5.,6.,7.],[8.,9.,0.]], requires_grad=True)

# or it is possible to specify type of data directly
#w = torch.tensor( [[1,2,3],[5,6,7],[8,9,0]], requires_grad=True, dtype=torch.float)

a = 5
function = a * torch.log(w + 3.).sum()

# another way to write functions for torch:
#function = a * (w + 3.).log().sum()

function.backward()
print(w-w.grad)

#tensor([[-0.2500,  1.0000,  2.1667],
#        [ 4.3750,  5.4444,  6.5000],
#        [ 7.5455,  8.5833, -1.6667]], grad_fn=)