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import argparse |
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import numpy as np |
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from questiongenerator import QuestionGenerator |
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from questiongenerator import print_qa |
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def main(): |
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parser = argparse.ArgumentParser() |
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parser.add_argument( |
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"--text_dir", |
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default=None, |
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type=str, |
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required=True, |
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help="The text that will be used as context for question generation.", |
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) |
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parser.add_argument( |
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"--model_dir", |
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default=None, |
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type=str, |
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help="The folder that the trained model checkpoints are in.", |
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) |
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parser.add_argument( |
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"--num_questions", |
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default=10, |
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type=int, |
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help="The desired number of questions to generate.", |
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) |
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parser.add_argument( |
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"--answer_style", |
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default="all", |
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type=str, |
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help="The desired type of answers. Choose from ['all', 'sentences', 'multiple_choice']", |
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) |
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parser.add_argument( |
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"--show_answers", |
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default='True', |
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type=parse_bool_string, |
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help="Whether or not you want the answers to be visible. Choose from ['True', 'False']", |
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) |
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parser.add_argument( |
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"--use_qa_eval", |
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default='True', |
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type=parse_bool_string, |
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help="Whether or not you want the generated questions to be filtered for quality. Choose from ['True', 'False']", |
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) |
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args = parser.parse_args() |
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with open(args.text_dir, 'r') as file: |
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text_file = file.read() |
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qg = QuestionGenerator(args.model_dir) |
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qa_list = qg.generate( |
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text_file, |
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num_questions=int(args.num_questions), |
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answer_style=args.answer_style, |
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use_evaluator=args.use_qa_eval |
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) |
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print_qa(qa_list, show_answers=args.show_answers) |
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def parse_bool_string(s): |
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if isinstance(s, bool): |
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return s |
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if s.lower() in ('yes', 'true', 't', 'y', '1'): |
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return True |
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elif s.lower() in ('no', 'false', 'f', 'n', '0'): |
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return False |
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else: |
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raise argparse.ArgumentTypeError('Boolean value expected.') |
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if __name__ == "__main__": |
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main() |
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