| import argparse |
| import os |
|
|
| from datasets import DatasetDict, concatenate_datasets, load_from_disk |
|
|
|
|
| SOURCE_SPECS = { |
| "qqp": {"sentence1": "question1", "sentence2": "question2", "keep": lambda label: label == 1}, |
| "mrpc": {"sentence1": "sentence1", "sentence2": "sentence2", "keep": lambda label: label == 1}, |
| "stsb": {"sentence1": "sentence1", "sentence2": "sentence2", "keep": lambda label: label >= 3}, |
| "rte": {"sentence1": "sentence1", "sentence2": "sentence2", "keep": lambda label: label == 1}, |
| "anli": {"sentence1": "sentence1", "sentence2": "sentence2", "keep": lambda label: label == 0}, |
| "smf": {"sentence1": "sentence1", "sentence2": "sentence2", "keep": lambda label: label == 0}, |
| } |
|
|
|
|
| def parse_args(): |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--data_dir", default="./data") |
| parser.add_argument("--sources", default="qqp,mrpc,stsb") |
| parser.add_argument("--output", default="ling_conversion") |
| return parser.parse_args() |
|
|
|
|
| def rename_dev_split(data): |
| if "dev" not in data and "validation" in data: |
| data["dev"] = data["validation"] |
| del data["validation"] |
| return data |
|
|
|
|
| def normalize_columns(data, source_name, sentence1_name, sentence2_name): |
| for split in data.keys(): |
| split_data = data[split] |
| rename_map = {} |
| if sentence1_name in split_data.column_names and sentence1_name != "sentence1": |
| rename_map[sentence1_name] = "sentence1" |
| if sentence2_name in split_data.column_names and sentence2_name != "sentence2": |
| rename_map[sentence2_name] = "sentence2" |
| if rename_map: |
| split_data = split_data.rename_columns(rename_map) |
| if "source" not in split_data.column_names: |
| split_data = split_data.add_column("source", [source_name] * len(split_data)) |
| keep_columns = [column for column in split_data.column_names if column.startswith("sentence") or column == "source"] |
| data[split] = split_data.remove_columns(sorted(set(split_data.column_names) - set(keep_columns))) |
| return data |
|
|
|
|
| def main(): |
| args = parse_args() |
| sources = [source.strip() for source in args.sources.split(",") if source.strip()] |
|
|
| datasets = {} |
| for source_name in sources: |
| if source_name not in SOURCE_SPECS: |
| raise ValueError(f"Unsupported source dataset: {source_name}") |
|
|
| spec = SOURCE_SPECS[source_name] |
| dataset = load_from_disk(os.path.join(args.data_dir, source_name)) |
| dataset = rename_dev_split(dataset) |
| dataset = dataset.filter(lambda row: spec["keep"](row["label"])) |
| dataset = normalize_columns(dataset, source_name, spec["sentence1"], spec["sentence2"]) |
| datasets[source_name] = dataset |
|
|
| merged = DatasetDict( |
| { |
| "train": concatenate_datasets([dataset["train"] for dataset in datasets.values() if "train" in dataset]), |
| "dev": concatenate_datasets([dataset["dev"] for dataset in datasets.values() if "dev" in dataset]), |
| "test": concatenate_datasets([dataset["test"] for dataset in datasets.values() if "test" in dataset]), |
| } |
| ) |
| merged.save_to_disk(os.path.join(args.data_dir, args.output)) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
