Dear Chris
From what I gather, I need to code between the output -> softmax layers
class RNN(Module):
    def __init__(self, input_size, hidden_size,
                 output_size):
        super(RNN, self).__init__()
        self.hidden_size = hidden_size
        size_sum = input_size + hidden_size
        self.i2h = Linear(size_sum, hidden_size)
        self.h2o = Linear(hidden_size, output_size)
        self.o2h = Linear(output_size, hidden_size)
        self.softmax = LogSoftmax(dim=1)

    def forward(self, input_, hidden_):
        combined = cat(tensors=(input_, hidden_), dim=1)
        hidden_ = self.i2h(input=combined)
        output = self.h2o(input=hidden_)
        hidden_ = self.o2h(input=output)
        hidden_ = relu(input=hidden_)
        output = self.h2o(input=hidden_)
        return output, hidden_

    def init_hidden(self):
        return zeros(1, self.hidden_size)

When I made the network like above, it is not learning anything. (0% accuracy)
I think, I need more time to think about where I’m doing it wrong.
Thanks for the answer.