How can you build a custom generative model based on a recurrent neural network using a simple RNN cell in a deep learning framework

Question

With the help of Python programming, can you explain how you can build a custom generative model based on a recurrent neural network using a simple RNN cell in a deep learning framework?

Answer 1

You can build a custom generative model using a simple RNN cell by stacking layers of RNNs and training it to generate sequential data. 

Here is the code snippet using PyTorch:

In the above code, we are using the following key points:

• RNN Cell: Use nn.RNN to build the recurrent layers.
• Hidden State Management: Initialize and pass the hidden state through time steps.
• Fully Connected Layer: Map RNN outputs to the desired output space for generation.

Hence, by referring to the above, you can build a custom generative model based on a recurrent neural network using a simple RNN cell in a deep learning framework.