-
Notifications
You must be signed in to change notification settings - Fork 3.4k
Implement approx_tanh for ROCm using OCML tanh function #34598
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
base: main
Are you sure you want to change the base?
Conversation
Summary of ChangesHello @phambinhfin, 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 enhances the Highlights
🧠 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 to enable Memory in your admin console. Using Gemini Code AssistThe full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips. Invoking Gemini You can request assistance from Gemini at any point by creating a comment using either
Customization 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 Limitations & Feedback Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 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. 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. Footnotes
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Code Review
This pull request implements approx_tanh for ROCm using OCML's tanh function for f64 and Triton's fast tanh function for f32, f16, and bf16. It includes changes to jax/_src/pallas/triton/primitives.py to add f64 support and ROCm platform detection, adds _approx_tanh_rocm_lowering function, and adds a test case in tests/pallas/ops_test.py with f16/bf16/f32/f64 support. The review identifies a potential issue with the library path in _approx_tanh_rocm_lowering.
AMD CDNA3 (MI300X/gfx942) does not have a hardware tanh instruction like NVIDIA's PTX tanh.approx. This implements approx_tanh for ROCm using: - For f32 (and f16/bf16 via casting): Triton's __triton_hip_fast_tanhf which uses a fast exp-based formula: tanh(x) = (exp(2x) - 1) / (exp(2x) + 1) - For f64: OCML's __ocml_tanh_f64 (AMD's Open Compute Math Library) Changes: - Add f64 support to approx_tanh function - Add ROCm platform detection in _elementwise_inline_asm_lowering - Add _approx_tanh_rocm_lowering function for ROCm-specific lowering - Add test_approx_tanh test with f16/bf16/f32/f64 support See: triton-lang/triton#7780
95c6f8e to
ec6e822
Compare
AMD CDNA3 (MI300X/gfx942) does not have a hardware tanh instruction like NVIDIA's PTX tanh.approx. This implements approx_tanh for ROCm using:
which uses a fast exp-based formula: tanh(x) = (exp(2x) - 1) / (exp(2x) + 1)
Changes:
Related commit form ROCm/jax PR #614
See: triton-lang/triton#7780