[Relax][Onnx] Support Multi Input Ops with Multidirectional Broadcasting

[locnd182644]

This PR support Multi Input Ops with Multidirectional Broadcasting

Description

• Support Multi Input Ops with Multidirectional Broadcasting (Min, Max, Mean, Sum)
• Edit handle workflow for MultiInputBase:
  • Compute target shape for Multidirectional Broadcasting
  • Broadcast_to with target shape
  • Stack op
  • Reduce ops with axis same stack op

Expected

• Example target shape:

Reference

• Multidirectional Broadcasting: https://onnx.ai/onnx/repo-docs/Broadcasting.html
• Fixed: [Bug] Importing ONNX Min with broadcasting fails #18592

[gemini-code-assist]

Summary of Changes

Hello @locnd182644, 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 significantly enhances the ONNX frontend for Relax by introducing robust support for multidirectional broadcasting in multi-input operators. This ensures that models leveraging operations like Min, Max, Sum, and Mean with inputs of different but broadcast-compatible shapes are correctly translated and executed within the Relax framework, improving compatibility and functionality for a wider range of ONNX models.

Highlights

• Multidirectional Broadcasting Support: Implemented support for multidirectional broadcasting in ONNX multi-input operators such as Min, Max, Sum, and Mean, allowing these operations to correctly handle inputs with varying shapes that require broadcasting.
• New Broadcasting Utility: Added a new utility function, compute_broadcast_shape, to determine the target shape for multidirectional broadcasting between two input shapes.
• Updated MultiInputBase Conversion: Modified the MultiInputBase conversion logic to first compute the target broadcast shape for all inputs, then apply relax.op.broadcast_to to each input before stacking them, and finally performing the reduction operation.
• Comprehensive Test Cases: Introduced new parameterized test cases (test_multi_input_broadcasting) to validate the correct behavior of multidirectional broadcasting for multi-input operators across various complex input shape combinations.

🧠 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 Assist

The 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 /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.

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 .gemini/ folder in the base of the repository. Detailed instructions can be found here.

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

1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩

[gemini-code-assist]

Code Review

This pull request adds support for multi-input ops (Min, Max, Mean, Sum) with multidirectional broadcasting in the ONNX frontend. The changes include a new helper function to compute the broadcast shape and an update to the MultiInputBase operator converter to handle broadcasting before stacking and reducing the inputs. The accompanying tests have been updated to cover various broadcasting scenarios, ensuring the correctness of the implementation. The changes look good and correctly implement the desired functionality. I have one minor suggestion to improve code conciseness.

[locnd182644]

@tvm-bot rerun