Padding
Understand how to apply padding to tokenized text sequences of varying lengths to create fixed-size inputs for LSTM language models. Learn the importance of padding tokens and how to prepare input and target sequences for training batches in NLP tasks.
We'll cover the following...
We'll cover the following...
Chapter Goals:
Learn about sequence lengths and padding
A. Varied length sequence
When dealing with most neural networks, the input data always has a fixed length. This is because most neural networks have what's known as a feed-forward structure, meaning that they utilize multiple layers of fixed sizes to compute the network's output.
However, since text ...