import argparse

def parse_args():
        parser = argparse.ArgumentParser(description="PaddlePaddle CTR example")
        parser.add_argument(
                '--train_data_path',
                type=str,
                default='./data/raw/train.txt',
                help="The path of training dataset")
        parser.add_argument(
                '--sparse_only',
                type=bool,
                default=False,
                help="Whether we use sparse features only")
        parser.add_argument(
                '--test_data_path',
                type=str,
                default='./data/raw/valid.txt',
                help="The path of testing dataset")
        parser.add_argument(
                '--batch_size',
                type=int,
                default=1000,
                help="The size of mini-batch (default:1000)")
        parser.add_argument(
                '--embedding_size',
                type=int,
                default=10,
                help="The size for embedding layer (default:10)")
        parser.add_argument(
                '--num_passes',
                type=int,
                default=10,
                help="The number of passes to train (default: 10)")
        parser.add_argument(
                '--model_output_dir',
                type=str,
                default='models',
                help='The path for model to store (default: models)')
        parser.add_argument(
                '--sparse_feature_dim',
                type=int,
                default=1000001,
                help='sparse feature hashing space for index processing')
        parser.add_argument(
                '--is_local',
                type=int,
                default=1,
                help='Local train or distributed train (default: 1)')
        parser.add_argument(
                '--cloud_train',
                type=int,
                default=0,
                help='Local train or distributed train on paddlecloud (default: 0)')
        parser.add_argument(
                '--async_mode',
                action='store_true',
                default=False,
                help='Whether start pserver in async mode to support ASGD')
        parser.add_argument(
                '--no_split_var',
                action='store_true',
                default=False,
                help='Whether split variables into blocks when update_method is pserver')
        parser.add_argument(
                '--role',
                type=str,
                default='pserver', # trainer or pserver
                help='The path for model to store (default: models)')
        parser.add_argument(
                '--endpoints',
                type=str,
                default='127.0.0.1:6000',
                help='The pserver endpoints, like: 127.0.0.1:6000,127.0.0.1:6001')
        parser.add_argument(
                '--current_endpoint',
                type=str,
                default='127.0.0.1:6000',
                help='The path for model to store (default: 127.0.0.1:6000)')
        parser.add_argument(
                '--trainer_id',
                type=int,
                default=0,
                help='The path for model to store (default: models)')
        parser.add_argument(
                '--trainers',
                type=int,
                default=1,
                help='The num of trianers, (default: 1)')
        return parser.parse_args()