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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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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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