How can you implement ACT in a large language model to control per-token computation

Question

Can you tell me How can you implement ACT in a large language model to control per-token computation?

Answer 1

You can implement Adaptive Computation Time (ACT) in a large language model by adjusting the number of computation steps per token based on its complexity, allowing for dynamic computation based on token difficulty.

Here is the code snippet below:

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

• The ACTLayer predicts the number of computation steps needed for each token based on its complexity using a linear layer.

• The forward() method applies these computed steps for token processing.

Hence, this adaptive approach optimizes computational efficiency by performing more computation for complex tokens and less for simpler ones.