What are the trade-offs of using autoregressive decoding vs parallel decoding in Generative AI

Question

With the help of code can you tell me What are the trade-offs of using autoregressive decoding vs. parallel decoding in Generative AI?

Answer 1

Autoregressive decoding generates tokens sequentially, ensuring coherence, but is slower. Parallel decoding generates tokens simultaneously, improving speed but may compromise coherence.

Here is the code snippet you can refer to:

 

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

• Autoregressive Decoding: Sequentially appends tokens, maintaining strong dependencies between tokens.
• Parallel Decoding: Generates multiple tokens at once, trading quality for speed.
• Model API: Use .generate() for sequential and .generate_parallel() for parallel decoding if supported.

Hence, autoregressive decoding is ideal for coherence, while parallel decoding suits tasks prioritizing speed. Choose based on task requirements.