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import json |
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import jsonlines |
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import argparse |
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import pandas as pd |
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import pprint |
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def main(args): |
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mainDict = {} |
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with jsonlines.open(args.input_file) as reader: |
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for obj in reader: |
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neutral = "" |
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entailment = "" |
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contradiction = "" |
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prompt = "" |
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if mainDict.get(obj['promptID'], None): |
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prompt = obj['sentence1'] |
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entailment = mainDict[obj['promptID']].get('entailment','') |
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contradiction = mainDict[obj['promptID']].get('contradiction','') |
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neutral = mainDict[obj['promptID']].get('neutral','') |
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if obj['gold_label'] == "neutral": |
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neutral = obj['sentence2'] |
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elif obj['gold_label'] == "contradiction": |
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contradiction = obj['sentence2'] |
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elif obj['gold_label'] == "entailment": |
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entailment = obj['sentence2'] |
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mainDict[obj['promptID']] = {'prompt': prompt, 'entailment' : entailment, 'neutral' : neutral, 'contradiction' : contradiction} |
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myList = [] |
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for promptID in mainDict: |
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myList.append({'sent0':mainDict[promptID]['prompt'], 'sent1':mainDict[promptID]['entailment'], 'hard_neg':mainDict[promptID]['contradiction']}) |
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df = pd.DataFrame.from_records(myList) |
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df.replace("", float("NaN"), inplace=True) |
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df.dropna(subset = ["sent0","sent1","hard_neg"], inplace=True) |
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df.to_csv(args.output_file, index=False) |
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if __name__ == '__main__': |
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parser = argparse.ArgumentParser() |
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parser.add_argument('--input_file', help="Input file.", required=True) |
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parser.add_argument('--output_file', help="Output file.", required=True) |
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args = parser.parse_args() |
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main(args) |
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