import argparse

'''
training settings

metavar参数，用来控制部分命令行参数的显示
'''
parser = argparse.ArgumentParser(description='PyTorch Example for all')
'''
train
'''
parser.add_argument('--train-batch-size', type=int, default=16, metavar='N',
                    help='input batch size for training (default: 32)')
parser.add_argument('--test-batch-size', type=int, default=16, metavar='N',
                    help='input batch size for testing (default: 64)')
parser.add_argument('--epochs', type=int, default=500, metavar='N',
                    help='number of epochs to train (default: 10)')
parser.add_argument('--lr', type=float, default=0.0001, metavar='LR',
                    help='learning rate (default: 0.0001)')
parser.add_argument('--momentum', type=float, default=0.5, metavar='M',
                    help='SGD momentum (default: 0.5)')
parser.add_argument('--seed', type=int, default=123, metavar='S',
                    help='random seed 设置种子的用意是一旦固定种子，后面依次生成的随机数其实都是固定的,有利于实验结果的产生与比较')
parser.add_argument('--use_cuda', type=bool, default=True,
                    help='whether to use cuda to acclerate')
parser.add_argument('--base_data_path', type=str, default='E:/Datasets2/',
                    help="total base data path for training")
parser.add_argument('--resume', type=bool, default=True, metavar='R',
                    help="whether to use the pretrained model to start the train")
parser.add_argument('--saved_model', type=str, default="E:/完成工作/trained_model/",
                    help="the path to store the weight")
parser.add_argument('--val_num', type=float, default=0.3,
                    help="percentage of validate data")
parser.add_argument('--save', type=bool, default=True,
                    help="whether to save the model weight")
parser.add_argument('--project_name', type=str, default='dogs 10 classification',
                    help="该项目的工程名称")
parser.add_argument('--use_aug', type=bool, default=True,
                    help='使用数据增广,增加数据多样性')
'''
inference
'''
parser.add_argument('--pretrained_weight', type=str, default="E:/完成工作/trained_model/",
                    help="the path to load the pytorch weight")