How can you implement beam search decoding for text generation using TensorFlow

Question

Can you tell me how can you implement beam search decoding for text generation using TensorFlow?

Answer 1

To implement beam search decoding for text generation in TensorFlow, you can use a loop to iteratively expand beam candidates and select the top-k sequences based on their scores.

Here is the code snippet you can refer to:

In the above code, we are using the following:

• Initialization: The code starts with an input sequence and initializes the beam with possible candidates and their scores.
• Iteration: At each step, it expands the sequences by adding top-k tokens based on log probabilities and updates the beam.
• Final Selection: The best sequence is decoded after iterating to the maximum length, based on cumulative scores.

Hence, this implementation maintains a beam of sequences and scores, expanding them at each step and keeping the top-k sequences based on their cumulative log probabilities.