gemini-code-assist[bot] commented on PR #431: URL: https://github.com/apache/tvm-ffi/pull/431#issuecomment-3859522809
## Summary of Changes Hello @junrushao, I'm Gemini Code Assist[^1]! 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 significantly enhances the TVM-FFI documentation by overhauling the Kernel Library Guide. The guide has been transformed into a practical, step-by-step tutorial, complete with new, concrete C++/CUDA kernel examples and helper utilities. These changes aim to provide developers with clearer instructions and best practices for integrating custom kernels, making the process more accessible and robust. ### Highlights * **Kernel Library Guide Overhaul**: The `Kernel Library Guide` has been completely rewritten to provide a more practical, example-driven tutorial for developing C++/CUDA kernels with TVM-FFI. It now covers the anatomy of a kernel function, best practices for input validation, device and stream management, dtype dispatch, and tensor handling. * **New Example Kernel and Utilities**: A new comprehensive `Scale` kernel example (`scale_kernel.cu`) has been added, demonstrating the concepts discussed in the updated guide. This is complemented by a new utility header (`tvm_ffi_utils.h`) providing reusable macros for input validation, stream handling, and tensor allocation. * **Improved Documentation Generation**: Doxygen configuration has been updated in `docs/conf.py` to refine symbol and pattern exclusions, leading to cleaner and more focused generated documentation. Minor adjustments were also made to static initialization block macros in `base_details.h`. 🧠**New Feature in Public Preview:** You can now enable **Memory** to help **Gemini Code Assist** learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. **Click [here](https://codeassist.google/code-review/login) to enable Memory in your admin console.** <details> <summary><b>Changelog</b></summary> * **docs/conf.py** * Updated `EXCLUDE_SYMBOLS` to remove specific FFI-related macros from Doxygen documentation. * Modified `EXCLUDE_PATTERNS` to target specific detail headers (`function_details.h`, `container_details.h`) for exclusion. * **docs/guides/kernel_library_guide.rst** * Rewrote the entire guide to focus on practical kernel development, including sections on input validation, device/stream management, dtype dispatch, and tensor handling. * Added `seealso` links to related documentation and example code. * Incorporated detailed code examples and best practices for `TensorView` vs `Tensor` usage and tensor allocation strategies. * Introduced a 'Further Reading' section with links to other core TVM-FFI concepts. * **examples/kernel_library/load_scale.py** * Added a new Python script demonstrating how to load a compiled kernel library and call a `Scale` function with PyTorch tensors. * **examples/kernel_library/scale_kernel.cu** * Added a new C++/CUDA file implementing a `Scale` kernel, showcasing input validation, device guard, stream acquisition, dtype dispatch, and FFI export. * **examples/kernel_library/tvm_ffi_utils.h** * Added a new utility header containing reusable macros for input validation (`CHECK_CUDA`, `CHECK_CONTIGUOUS`, `CHECK_DIM`, `CHECK_DEVICE`). * Included helper functions for CUDA stream acquisition (`get_cuda_stream`) and framework-aware tensor allocation (`alloc_tensor`). * Defined common DLPack `DLDataType` constants for convenience. * **include/tvm/ffi/base_details.h** * Refactored the `TVM_FFI_STATIC_INIT_BLOCK` macro definitions, potentially improving documentation generation or compiler compatibility. </details> <details> <summary><b>Activity</b></summary> * The pull request introduces significant documentation and example code changes. * New example files for a 'Scale' kernel and associated utilities have been added. * The core kernel library guide has been completely rewritten for improved clarity and practicality. </details> <details> <summary><b>Using Gemini Code Assist</b></summary> <br> The full guide for Gemini Code Assist can be found on our [documentation page](https://developers.google.com/gemini-code-assist/docs/review-github-code), here are some quick tips. <b>Invoking Gemini</b> You can request assistance from Gemini at any point by creating a comment using either `/gemini <command>` or `@gemini-code-assist <command>`. Below is a summary of the supported commands on the current page. Feature | Command | Description --- | --- | --- Code Review | `/gemini review` | Performs a code review for the current pull request in its current state. Pull Request Summary | `/gemini summary` | Provides a summary of the current pull request in its current state. Comment | @gemini-code-assist | Responds in comments when explicitly tagged, both in pull request comments and review comments. Help | `/gemini help` | Displays a list of available commands. <b>Customization</b> To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a `.gemini/` folder in the base of the repository. Detailed instructions can be found [here](https://developers.google.com/gemini-code-assist/docs/customize-gemini-behavior-github). <b>Limitations & Feedback</b> Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with :thumbsup: and :thumbsdown: on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up [here](https://google.qualtrics.com/jfe/form/SV_2cyuGuTWsEw84yG). <b>You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the [Gemini Code Assist IDE Extension](https://cloud.google.com/products/gemini/code-assist).</b> </details> [^1]: Review the [Privacy Notices](https://policies.google.com/privacy), [Generative AI Prohibited Use Policy](https://policies.google.com/terms/generative-ai/use-policy), [Terms of Service](https://policies.google.com/terms), and learn how to configure Gemini Code Assist in GitHub [here](https://developers.google.com/gemini-code-assist/docs/customize-gemini-behavior-github). Gemini can make mistakes, so double check it and [use code with caution](https://support.google.com/legal/answer/13505487). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
