While running a generation using the CLI on the student JSON grammar with the Phi-3.5-mini-4bit model, I observed that the majority of tokens were already valid without applying a mask.

As evident in the screenshot above, the green tokens were sampled without constraints and were already valid.

I implemented the following logic in the mask_logits method:

1. Compute the argmax of the logits to determine the sampled token (with temperature set to 0). This operation has negligible computational cost (approximately 1e-5 seconds).
2. Evaluate the validity of this token.
3. If valid, return this token directly.
4. If invalid, compute the entire mask.

This minor modification resulted in a significant speed increase of 3 tokens per second.

As shown in the second screenshot, the impact of the logits_processor has been substantially reduced. It's worth noting that this improvement becomes more pronounced as the vocabulary size increases.