24 lines
1.7 KiB
Python
24 lines
1.7 KiB
Python
import random, argparse
|
|
from .share_args import add_shared_args
|
|
|
|
def obtain_cls_kd_args():
|
|
parser = argparse.ArgumentParser(description='Train a classification model on typical image classification datasets.', formatter_class=argparse.ArgumentDefaultsHelpFormatter)
|
|
parser.add_argument('--resume' , type=str, help='Resume path.')
|
|
parser.add_argument('--init_model' , type=str, help='The initialization model path.')
|
|
parser.add_argument('--model_config', type=str, help='The path to the model configuration')
|
|
parser.add_argument('--optim_config', type=str, help='The path to the optimizer configuration')
|
|
parser.add_argument('--procedure' , type=str, help='The procedure basic prefix.')
|
|
parser.add_argument('--KD_checkpoint', type=str, help='The teacher checkpoint in knowledge distillation.')
|
|
parser.add_argument('--KD_alpha' , type=float, help='The alpha parameter in knowledge distillation.')
|
|
parser.add_argument('--KD_temperature', type=float, help='The temperature parameter in knowledge distillation.')
|
|
#parser.add_argument('--KD_feature', type=float, help='Knowledge distillation at the feature level.')
|
|
add_shared_args( parser )
|
|
# Optimization options
|
|
parser.add_argument('--batch_size', type=int, default=2, help='Batch size for training.')
|
|
args = parser.parse_args()
|
|
|
|
if args.rand_seed is None or args.rand_seed < 0:
|
|
args.rand_seed = random.randint(1, 100000)
|
|
assert args.save_dir is not None, 'save-path argument can not be None'
|
|
return args
|