[Oneshot] Add validation for empty dataset and enhance oneshot function parameters

[ArkaSanka]

Fix argument handling in oneshot function #1850

Issue Description

The oneshot function signature in oneshot.py was missing several parameters that exist in the underlying dataclasses (DatasetArguments, ModelArguments, RecipeArguments). This caused issues when users tried to use these parameters directly, particularly with:

• sequential_targets: Conflicts occurred between recipe modifiers and direct parameters
• preprocessing_func: Returns an error when the dataset is empty
• pipeline: Not properly validated against sequential_targets

Changes Made

Parameter Alignment:

• Updated the oneshot function signature to include all missing parameters from the argument dataclasses
• Ensured type hints and default values match those defined in the dataclasses
• Added missing parameters: preprocessing_func, data_collator, raw_kwargs, max_train_samples, pipeline, tracing_ignore, sequential_targets

Validation Logic:

• Added validation to detect conflicting sequential_targets between recipe modifiers and direct parameters
• Added validation to prevent incompatible pipeline settings with sequential_targets
• Fixed error message formatting to comply with style guidelines

Test Improvements:

• Updated the test fixture in test_api_inputs.py to handle all parameters correctly
• Added detection for potential parameter conflicts to make tests more robust

Impact

These changes ensure that all parameters defined in the argument dataclasses can be used directly with the oneshot function without unexpected behavior. Users can now pass parameters like sequential_targets and preprocessing_func directly to oneshot without running into cryptic errors or unexpected behavior. The API is now more consistent with its underlying implementation, making it more intuitive to use.

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[gemini-code-assist]

Summary of Changes

Hello @ArkaSanka, 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 improves the oneshot function's usability and robustness by aligning its parameter signature with its internal dataclasses and introducing critical validation checks. It ensures that users can pass a wider range of configuration options directly to oneshot without encountering unexpected behavior or cryptic errors, while also preventing operations on empty datasets and incompatible pipeline settings.

Highlights

• Enhanced oneshot Function Signature: The oneshot function now includes previously missing parameters like preprocessing_func, pipeline, and sequential_targets, aligning its signature with underlying dataclasses for improved usability.
• Improved Parameter Validation: New validation checks prevent conflicting configurations, specifically disallowing sequential_targets when the pipeline is set to 'independent', ensuring more robust function calls.
• Empty Dataset Safeguard: A new check has been added to prevent calibration from proceeding with an empty dataset, raising a ValueError for clarity and preventing potential issues.
• Robust Test Coverage: The test suite has been updated to correctly handle the expanded oneshot parameters and gracefully manage empty dataset scenarios during testing, making tests more reliable.

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[gemini-code-assist]

Code Review

This pull request enhances the oneshot function by aligning its parameters with the underlying argument dataclasses, which makes the API more complete and intuitive. It also introduces valuable validation for empty datasets and incompatible parameter combinations, such as sequential_targets with an independent pipeline. The tests have been updated accordingly to cover these new parameters and handle potential data-related issues more gracefully. My review focuses on a potential issue in the test suite where preprocessing_func is wrapped in a tuple, which seems to contradict its type hint and the stated goal of the pull request. I have also included a minor style suggestion to improve code maintainability.

[ArkaSanka]

Hi @kylesayrs, @dsikka, let me know if there are any additional/missing changes to be made.