import torch

class Rnn(torch.nn.Module):
    def __init__(self, vocab_size):
        super(Rnn, self).__init__()
        self.embedding = torch.nn.Embedding(vocab_size, 128)
        self.lstm1 = torch.nn.LSTM(128, 128, batch_first=True, dropout=0.5)
        self.lstm2 = torch.nn.LSTM(128, 128, batch_first=True, dropout=0.5)
        self.fc = torch.nn.Linear(128, vocab_size)
        
    def forward(self, x):
        x = self.embedding(x)
        x, _ = self.lstm1(x)
        x, _ = self.lstm2(x)
        x = self.fc(x)
        return x