| """Create GenomeQA 3_species_cls subsets grouped by target organism.""" |
|
|
| import argparse |
| import json |
| from pathlib import Path |
|
|
| from datasets import load_dataset |
|
|
|
|
| DATASET_ID = "HuggingFaceBio/genomeqa" |
| SOURCE_REVISION = "d2213306c6cf5b4568a504f87f86ea50b03eeced" |
| SOURCE_CONFIGS = ("binary", "mcq") |
| ORGANISMS = ("eukaryote", "prokaryote") |
| SUBTASK = "3_species_cls" |
| ORGANISM_KEY_BY_DIMENSION = { |
| "1_identity": "true", |
| "basic_class": "true", |
| "reverse_search": "target", |
| "odd_one_out": "minority", |
| } |
|
|
|
|
| def get_organism(metadata: str) -> str: |
| metadata_dict = json.loads(metadata) |
| dimension = metadata_dict["dim"] |
| return metadata_dict[ORGANISM_KEY_BY_DIMENSION[dimension]] |
|
|
|
|
| def create_subsets(config: str, output_dir: Path) -> None: |
| dataset = load_dataset(DATASET_ID, config, split="train", revision=SOURCE_REVISION) |
| species_dataset = dataset.filter(lambda example: example["subtask"] == SUBTASK) |
|
|
| for organism in ORGANISMS: |
| subset = species_dataset.filter( |
| lambda example, organism=organism: get_organism(example["metadata"]) == organism |
| ) |
| if not subset: |
| raise RuntimeError(f"No {organism} rows found in {config}") |
| if any(get_organism(metadata) != organism for metadata in subset["metadata"]): |
| raise RuntimeError(f"Generated {config}_{organism} subset contains another organism") |
|
|
| config_dir = output_dir / f"{config}_{organism}" |
| config_dir.mkdir(parents=True, exist_ok=True) |
| subset.to_parquet(config_dir / "train-00000-of-00001.parquet") |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--output-dir", type=Path, default=Path.cwd()) |
| args = parser.parse_args() |
|
|
| for config in SOURCE_CONFIGS: |
| create_subsets(config, args.output_dir) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
