import torch.nn as nn
import torch.nn.functional as F

class CharRNN([nn.Module](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module "torch.nn.Module")):
    def __init__(self, input_size, hidden_size, output_size):
        super([CharRNN](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module "torch.nn.Module"), self).__init__()

        self.rnn = [nn.RNN](https://docs.pytorch.org/docs/stable/generated/torch.nn.RNN.html#torch.nn.RNN "torch.nn.RNN")(input_size, hidden_size)
        self.h2o = [nn.Linear](https://docs.pytorch.org/docs/stable/generated/torch.nn.Linear.html#torch.nn.Linear "torch.nn.Linear")(hidden_size, output_size)
        self.softmax = [nn.LogSoftmax](https://docs.pytorch.org/docs/stable/generated/torch.nn.LogSoftmax.html#torch.nn.LogSoftmax "torch.nn.LogSoftmax")(dim=1)

    def forward(self, line_tensor):
        rnn_out, hidden = self.rnn(line_tensor)
        [output](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = self.h2o(hidden[0])
        [output](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = self.softmax([output](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"))

        return [output](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor")