feat: add OneIG benchmark with subset support#508
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davidberenstein1957 wants to merge 10 commits intomainfrom
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feat: add OneIG benchmark with subset support#508davidberenstein1957 wants to merge 10 commits intomainfrom
davidberenstein1957 wants to merge 10 commits intomainfrom
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…mpts benchmark - Introduced `from_benchmark` method in `PrunaDataModule` to create instances from benchmark classes. - Added `Benchmark`, `BenchmarkEntry`, and `BenchmarkRegistry` classes for managing benchmarks. - Implemented `PartiPrompts` benchmark for text-to-image generation with various categories and challenges. - Created utility function `benchmark_to_datasets` to convert benchmarks into datasets compatible with `PrunaDataModule`. - Added integration tests for benchmark functionality and data module interactions.
…filtering - Remove heavy benchmark abstraction (Benchmark class, registry, adapter, 24 subclasses) - Extend setup_parti_prompts_dataset with category and num_samples params - Add BenchmarkInfo dataclass for metadata (metrics, description, subsets) - Switch PartiPrompts to prompt_with_auxiliaries_collate to preserve Category/Challenge - Merge tests into test_datamodule.py Reduces 964 lines to 128 lines (87% reduction) Co-authored-by: Cursor <cursoragent@cursor.com>
Document all dataclass fields per Numpydoc PR01 with summary on new line per GL01. Co-authored-by: Cursor <cursoragent@cursor.com>
- Add list_benchmarks() to filter benchmarks by task type - Add get_benchmark_info() to retrieve benchmark metadata - Add COCO, ImageNet, WikiText to benchmark_info registry Co-authored-by: Cursor <cursoragent@cursor.com>
Update benchmark metrics to match registered names: - clip -> clip_score - clip_iqa -> clipiqa - Remove unimplemented top5_accuracy Co-authored-by: Cursor <cursoragent@cursor.com>
- Add setup_oneig_text_rendering_dataset in datasets/prompt.py - Register OneIGTextRendering in base_datasets - Add BenchmarkInfo entry with clip_score, clipiqa metrics - Auxiliaries include text_content for OCR evaluation - Add test for loading and auxiliaries Co-authored-by: Cursor <cursoragent@cursor.com>
- Add setup_oneig_alignment_dataset in datasets/prompt.py - Support category filter (Anime_Stylization, Portrait, General_Object) - Register OneIGAlignment in base_datasets - Add BenchmarkInfo entry with accuracy metric, task_type text_generation - Auxiliaries include questions, dependencies, category - Add test for loading with category filter Co-authored-by: Cursor <cursoragent@cursor.com>
Combine text rendering and alignment into single OneIG benchmark: - Add setup_oneig_dataset with subset parameter - Subsets: text_rendering, anime_alignment, portrait_alignment, object_alignment - Loading without subset returns all data combined - Each record includes subset field for filtering - Update tests to use subset parameter Co-authored-by: Cursor <cursoragent@cursor.com>
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- Add subset parameter support to PrunaDataModule.from_string() - Fix task_type from text_generation to text_to_image - Unify schema between text_rendering and alignment datasets - Remove unused imports in test file Co-authored-by: Cursor <cursoragent@cursor.com>
Prevents IndexError when subset filtering returns no samples Co-authored-by: Cursor <cursoragent@cursor.com>
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Closes #515
Summary
Usage
Test plan
PrunaDataModule.from_string("OneIG")loads all subsets