How do you implement sequence masking in RNN-based generative models to handle varying sequence lengths

Question

Can you implement sequence masking in RNN based generative models to handle varying sequence lengths?

Answer 1

You can implement sequence masking in RNN-based generative models to handle varying sequence lengths by implementing  sequence masking in an RNN-based generative model using PyTorch, here is code you can refer to:

The code above handles varying sequence lengths, and the mask can be used further for attention or loss calculations.

Hence, by referring to the above, you can implement sequence masking in RNN-based generative models to handle varying sequence lengths