[Relax][Frontend][Torch] Fix parsing error when input dimension of unbind is 1

[eaten-cake]

fix issue #18338
When the input dimension of unbind is 1, we should directly apply squeeze instead of performing split followed by squeeze. This issue has been fixed, and a corresponding regression test has been added.
Previously, the error occurred because when the output of split contains only a single tensor, the struct_info of the expression is TensorStructInfo rather than TupleStructInfo. As a result, the TupleGetItem node generated at

tvm/python/tvm/relax/frontend/torch/base_fx_graph_translator.py

Lines 1279 to 1280 in f68651f

	for i in range(selections):
	ret.append(self.block_builder.emit(relax.op.squeeze(split[i], axis=dim)))

would fail.

[gemini-code-assist]

Summary of Changes

Hello @eaten-cake, 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 addresses a specific parsing error within the TVM Relax frontend for Torch, which occurred when processing torch.unbind operations on tensors with a dimension of size one. The fix streamlines the translation of this edge case by directly applying a squeeze operation, avoiding an incorrect split behavior that led to TupleGetItem failures. A new test case has been included to validate this correction and maintain stability.

Highlights

• Bug Fix: Resolved a parsing error in the Relax frontend for Torch when the unbind operation is applied to an input tensor where the target dimension has a size of 1.
• Optimized unbind handling: Modified the _unbind method to directly apply a squeeze operation when the input dimension for unbinding is 1, instead of performing a split followed by squeeze.
• Regression Test: Added a new regression test case to ensure the correct behavior of unbind when the input dimension is 1, preventing future regressions.

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 fixes a parsing error in the PyTorch frontend for the unbind operator when the input dimension size is 1. The fix correctly handles this edge case by using squeeze directly, avoiding an incorrect split operation. A regression test is added to cover this specific scenario. The changes are correct and well-tested. I have one suggestion to improve the readability of the newly added test case.

[eaten-cake]

resolve #18338

[tlopex]

LGTM! Thanks @eaten-cake