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📌 Description

Hey, I had a hard time figuring out what is going on in sampling.cuh, after I figured it out I documented it.
Yes an AI helped my and yes I read the documents and they are good in my opinion.

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Summary of Changes

Hello @yonikremer, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on significantly improving the documentation within the include/flashinfer/sampling.cuh file. It introduces a comprehensive file-level overview and detailed Doxygen comments for nearly all CUDA kernels and host utilities related to softmax and token sampling. The goal is to enhance the clarity and understanding of the complex algorithms implemented, making the codebase more accessible and maintainable for current and future developers.

Highlights

  • Comprehensive File Documentation: A detailed Doxygen comment has been added to the sampling.cuh header, providing a high-level overview of its purpose, design principles, threading model, error handling, and usage for softmax and token sampling.
  • Function-Level Documentation: Extensive Doxygen comments have been introduced for numerous CUDA kernels and host utilities within sampling.cuh, including GetMinMaxValue, OnlineSoftmaxFusedKernel, SamplingFromLogitsKernel, TopKSamplingFromProbKernel, and OnlineSoftmax.
  • Algorithmic Clarity: Inline comments have been added to clarify complex algorithmic details, such as the online merge rule for softmax, Gumbel-max sampling logic, CDF search mechanisms, and iterative pivot refinement in Top-K and Top-P sampling.
  • Improved Readability: The added documentation significantly enhances the readability and maintainability of the sampling.cuh file, making it easier for developers to understand the intricate logic behind the high-performance CUDA primitives.
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Code Review

This pull request adds comprehensive Doxygen-style documentation to sampling.cuh, significantly improving the readability and maintainability of the CUDA kernels and host utilities for token sampling. The added comments are clear, detailed, and accurately describe the functionality, design, and algorithms used. I have one minor suggestion to improve the clarity of the file-level documentation.

* workspace in the map-reduce softmax path).
*
* Usage overview:
* - Call OnlineSoftmax to convert logits to probabilities in-place into an output buffer.
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medium

The term "in-place" can be ambiguous here. While it's possible for the output buffer to be the same as the logits buffer, the function signature OnlineSoftmax(DType* logits, DType* output, ...) suggests they can be separate. Using "in-place" might imply that the logits buffer is always modified directly, which isn't necessarily true. To improve clarity, I suggest removing "in-place".

 * - Call OnlineSoftmax to convert logits to probabilities into an output buffer.

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