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Creating a RNN model for text generation

At PyBooks, you've been tasked to develop an algorithm that can perform text generation. The project involves auto-completion of book names. To kickstart this project, you decide to experiment with a Recurrent Neural Network (RNN). This way, you can understand the nuances of RNNs before moving to more complex models.

The following has been imported for you: torch, torch.nn as nn.

The data variable has been initialized with an excerpt from Alice's Adventures in Wonderland by Lewis Carroll.

This exercise is part of the course

Deep Learning for Text with PyTorch

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Exercise instructions

  • Include an RNN layer and linear layer in RNNmodel class
  • Instantiate the RNN model with input size as length of chars, hidden size of 16, and output size as length of chars.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Include an RNN layer and linear layer in RNNmodel class
class RNNmodel(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super(RNNmodel, self).__init__()
        self.hidden_size = hidden_size
        self.rnn = nn.____(input_size, hidden_size, batch_first=True)
        self.fc = nn.____(hidden_size, output_size)

    def forward(self, x):
      h0 = torch.zeros(1, x.size(0), self.hidden_size)
      out, _ = self.rnn(x, h0)  
      out = self.fc(out[:, -1, :])  
      return out

# Instantiate the RNN model
model = RNNmodel(____, ____, ____)
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