fix: update tuning code samples to improve readability

[yishan-pu]

Description

Fixes #

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Checklist

• I have followed Sample Guidelines from AUTHORING_GUIDE.MD
• README is updated to include all relevant information
• Tests pass: nox -s py-3.9 (see Test Environment Setup)
• Lint pass: nox -s lint (see Test Environment Setup)
• These samples need a new API enabled in testing projects to pass (let us know which ones)
• These samples need a new/updated env vars in testing projects set to pass (let us know which ones)
• This sample adds a new sample directory, and I updated the CODEOWNERS file with the codeowners for this sample
• This sample adds a new Product API, and I updated the Blunderbuss issue/PR auto-assigner with the codeowners for this sample
• Please merge this PR for me once it is approved

[gemini-code-assist]

Hello @yishan-pu, 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!

Summary of Changes

Hello! Gemini here, providing a summary of this pull request to help everyone get up to speed quickly.

This PR aims to improve the readability of the tuning code samples within the genai/tuning directory. The primary changes involve renaming functions and variables to be more descriptive and adding clarifying comments, including example outputs.

Highlights

• Improved Readability: The main goal is to make the tuning code samples easier to understand by using clearer names for functions and variables.
• Function and Variable Renames: Several functions and variables across multiple tuning sample files have been renamed to better reflect their purpose (e.g., test_tuned_endpoint to predict_with_tuned_endpoint, name to tuning_job_name).
• Added Example Comments: Example response comments have been added to the prediction samples to show users the expected output format.

Changelog

Click here to see the changelog

• genai/tuning/test_tuning_examples.py
  • Renamed test function test_tuned_endpoint to predict_with_tuned_endpoint.
  • Renamed test function test_checkpoint to predict_with_checkpoints.
• genai/tuning/tuning_job_get.py
  • Renamed function parameter name to tuning_job_name in get_tuning_job.
  • Renamed local variable tuning_job_name to input_tuning_job_name in the if __name__ == "__main__": block.
  • Updated comments to reflect the parameter name change.
• genai/tuning/tuning_textgen_with_txt.py
  • Renamed function test_tuned_endpoint to predict_with_tuned_endpoint.
  • Renamed function parameter name to tuning_job_name.
  • Updated comments and the if __name__ == "__main__": block to use the new function and parameter names.
  • Added example response comments.
• genai/tuning/tuning_with_checkpoints_get_model.py
  • Renamed function parameter name to tuning_job_name in get_tuned_model_with_checkpoints.
  • Renamed local variable tuning_job_name to input_tuning_job_name in the if __name__ == "__main__": block.
  • Updated comments to reflect the parameter name change.
• genai/tuning/tuning_with_checkpoints_list_checkpoints.py
  • Renamed function parameter name to tuning_job_name in list_checkpoints.
  • Renamed local variable tuning_job_name to input_tuning_job_name in the if __name__ == "__main__": block.
  • Updated comments to reflect the parameter name change.
• genai/tuning/tuning_with_checkpoints_set_default_checkpoint.py
  • Renamed function parameter name to tuning_job_name in set_default_checkpoint.
  • Renamed local variable tuning_job_name to input_tuning_job_name in the if __name__ == "__main__": block.
  • Updated comments to reflect the parameter name change.
• genai/tuning/tuning_with_checkpoints_textgen_with_txt.py
  • Renamed function test_checkpoint to predict_with_checkpoints.
  • Renamed function parameter name to tuning_job_name.
  • Updated comments and the if __name__ == "__main__": block to use the new function and parameter names.
  • Added example response comments.

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---

A name change, small and neat,
Makes the code sample sweet.
Readability's key,
For all eyes to see,
A developer's treat.

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[gemini-code-assist]

Code Review

This pull request significantly improves the readability of the tuning code samples. The renaming of functions (e.g., from test_... to predict_...) clarifies their purpose within the context of example code. Parameter names have been made more specific (e.g., name to tuning_job_name), and variables in if __name__ == "__main__": blocks are now more distinct (e.g., input_tuning_job_name). Additionally, comments have been updated for accuracy, and the inclusion of example responses is a helpful touch for users.

These changes are well-executed and consistently applied across all relevant files, including the test file updates. Overall, this is a good enhancement to the samples.

One point to consider from the PR checklist: the item [ ] README is updated to include [all relevant information] is currently unchecked. Please ensure that any README files referencing these sample functions are updated with the new names to maintain documentation accuracy.

Summary of Findings

• Improved Function Naming: Functions previously named with a test_ prefix (e.g., test_tuned_endpoint, test_checkpoint) have been renamed to use a predict_ prefix (e.g., predict_with_tuned_endpoint, predict_with_checkpoints). This change more accurately reflects their role in the sample code, which is to demonstrate prediction capabilities rather than to serve as unit tests.
• Enhanced Parameter Clarity: Generic parameter names like name have been replaced with more descriptive names such as tuning_job_name. This improves code comprehension by making the expected input clearer.
• Clearer Variable Scoping in __main__: In if __name__ == "__main__": blocks, variables used to store user input (e.g., tuning_job_name) have been renamed (e.g., to input_tuning_job_name) to better distinguish them from function parameters, enhancing readability.
• Updated and Added Code Comments: Code comments have been updated to align with the new function names (e.g., changing "Tests the default checkpoint" to "Predicts with the tuned endpoint"). Additionally, new comments providing example responses have been added, which is beneficial for users running these samples.
• Consistent Test File Updates: The test file (test_tuning_examples.py) has been correctly updated to call the renamed functions, ensuring that tests remain aligned with the sample code changes.

Merge Readiness

The code changes are well-implemented and significantly improve readability. I recommend merging this pull request once the author has confirmed that any relevant README files are updated to reflect the new function names, as indicated by the unchecked item in the PR checklist. I am not authorized to approve pull requests, so please ensure it undergoes the standard approval process.

[msampathkumar]

LGTM. Nice work @yishan-pu 👍