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40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
import os
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import json
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import argparse
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import pathlib
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from collections import Counter
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from load_aokvqa import load_aokvqa
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parser = argparse.ArgumentParser()
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parser.add_argument('--aokvqa-dir', type=pathlib.Path, required=True, dest='aokvqa_dir')
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parser.add_argument('--split', type=str, choices=['train', 'val', 'test'], required=True)
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parser.add_argument('--mc', action='store_true', dest='multiple_choice')
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parser.add_argument('--out', type=argparse.FileType('w'), required=True, dest='output_file')
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args = parser.parse_args()
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train_set = load_aokvqa(args.aokvqa_dir, 'train')
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train_freq = dict(Counter(
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[d['choices'][d['correct_choice_idx']] for d in train_set]
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))
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most_common_answer = max(train_freq.keys(), key=train_freq.get)
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##
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eval_set = load_aokvqa(args.aokvqa_dir, args.split)
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predictions = {}
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for d in eval_set:
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q = d['question_id']
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predictions[q] = most_common_answer
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if args.multiple_choice:
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choices = [c for c in d['choices'] if c in train_freq.keys()]
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if len(choices) > 0:
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predictions[q] = max(choices, key=train_freq.get)
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json.dump(predictions, args.output_file)
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