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import pandas as pd |
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import os |
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from typing import Union |
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import datasets |
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from datasets import load_dataset |
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def save_and_compress(dataset: Union[datasets.Dataset, pd.DataFrame], name: str, idx=None): |
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if idx: |
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path = f"{name}_{idx}.jsonl" |
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else: |
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path = f"{name}.jsonl" |
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print("Saving to", path) |
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dataset.to_json(path, force_ascii=False, orient='records', lines=True) |
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print("Compressing...") |
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os.system(f'xz -zkf -T0 {path}') |
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def get_dataset_column_from_text_folder(folder_path): |
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return load_dataset("text", data_dir=folder_path, sample_by="document", split='train').to_pandas()['text'] |
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for split in ["train", "test"]: |
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dfs = [] |
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for dataset_name in ["IN-Abs", "UK-Abs", "IN-Ext"]: |
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if dataset_name == "IN-Ext" and split == "test": |
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continue |
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print(f"Processing {dataset_name} {split}") |
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path = f"original_dataset/{dataset_name}/{split}-data" |
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df = pd.DataFrame() |
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df['judgement'] = get_dataset_column_from_text_folder(f"{path}/judgement") |
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df['dataset_name'] = dataset_name |
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if dataset_name == "UK-Abs" and split == "test" or dataset_name == "IN-Ext": |
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summary_full_path = f"{path}/summary/full" |
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else: |
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summary_full_path = f"{path}/summary" |
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df['summary'] = get_dataset_column_from_text_folder(summary_full_path) |
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dfs.append(df) |
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df = pd.concat(dfs) |
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df = df.fillna("") |
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save_and_compress(df, f"data/{split}") |
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