RNN implementation incorrect in PyTorch Tutorials?

The RNN implementation in https://pytorch.org/tutorials/intermediate/char_rnn_classification_tutorial.html does not pass the hidden into the output but computes the output entirely separately. Isn’t this the equation of RNNs: 42%20PM
As described in http://blog.echen.me ?

Agree. When you check out simple RNN code result, it makes us wonder why the code in the RNN tutorial is different from the definition of RNN.

import torch.nn as nn
rnn = nn.RNN(10, 10, batch_first=True)

inp = torch.randn((1,3,10))

result = rnn(inp)

print(result[0].shape)
print(result[1].shape)
print(result[0][0])
print(result[1])

Same result of :
tensor([[[-0.0253, 0.5289, -0.2582, -0.5125, -0.4577, 0.5456, -0.4042,
-0.6476, -0.4210, -0.5473]]], grad_fn=)