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import os |
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from collections import Counter |
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import pandas as pd |
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dfs = [] |
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base_path = "dataframes" |
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for file_path in os.listdir(base_path): |
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dfs.append(pd.read_json(os.path.join(base_path, file_path), lines=True)) |
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raw_df = pd.concat(dfs, ignore_index=True) |
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print(f"{raw_df=}") |
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clue_counts = Counter(clue for clues in raw_df['clues'] for clue in clues) |
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unique_stories = set(c for c in raw_df['story']) |
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test_stories = set(x for i, x in enumerate(unique_stories) if i % 5 == 0) |
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test_df0 = raw_df[raw_df['story'].apply(lambda story: story in test_stories)] |
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test_df = test_df0[test_df0['clues'].apply(lambda clues: sum(clue_counts[clue] > 1 for clue in clues) <= 1)] |
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test_df.to_json("test.jsonl", orient='records', lines=True) |
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print(f"{test_df=}") |
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train_val_df = raw_df[raw_df['story'].apply(lambda story: story not in test_stories)] |
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val_df = train_val_df[train_val_df.index % 5 == 0] |
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val_df.to_json("validation.jsonl", orient='records', lines=True) |
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print(f"{val_df=}") |
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train_df = train_val_df[train_val_df.index % 5 != 0] |
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train_df.to_json("train.jsonl", orient='records', lines=True) |
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print(f"{train_df=}") |
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