pretrained resnet34 on tiny-imagenet about kesi HOT 6 CLOSED

parser.add_argument('--data_root', default='data')
parser.add_argument('--model', default='resnet34_imagenet')
parser.add_argument('--dataset', default='tiny_imagenet')
parser.add_argument('--epochs', default=100, type=int, metavar='N',
                    help='number of total epochs to run')
parser.add_argument('-b', '--batch-size', default=128, type=int,
                    metavar='N',
                    help='mini-batch size (default: 256), this is the total '
                         'batch size of all GPUs on the current node when '
                         'using Data Parallel or Distributed Data Parallel')
parser.add_argument('--warm_up_epoches', default=10, type=int,
                    metavar='WPI', help='warm up epoches')
parser.add_argument('--warm_up_lr', default=0.01, type=int,
                    metavar='WPI', help='warm up learning rate')
parser.add_argument('--lr', '--learning-rate', default=0.1, type=float,
                    metavar='LR', help='initial learning rate', dest='lr')
parser.add_argument('--lr_decay_milestones', default="50,75", type=str,
                    help='milestones for learning rate decay')
parser.add_argument('--evaluate_only', action='store_true',
                    help='evaluate model on validation set')
parser.add_argument('--resume', default='', type=str, metavar='PATH',
                    help='path to latest checkpoint (default: none)')
parser.add_argument('--gpu', default=0, type=int,
                    help='GPU id to use.')