ml-explore / ml-explore/mlx

[ENH]: Using `IndexError` instead of `ValueError` at appropriate places?

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enhancement low priority python
Dominant language
C++
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Description

☑️ I understand it is strictly prohibited to use AI to write issues.

Following the suggestion, functions like expand_dims raise ValueError when the axis is invalid, but it makes more sense for them to raise IndexError instead.

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First steps

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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the expand_dims API and trace related functions that validate axis arguments. Review existing exception behavior and tests for invalid axes, then determine which cases should use IndexError rather than ValueError. Done means the appropriate APIs consistently raise the intended exception and their existing tests reflect that behavior.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
48/100

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