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Move str2bool to config_utils

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D-X-Y
2021-03-30 09:17:05 +00:00
parent 9fc2c991f5
commit c2270fd153
16 changed files with 519 additions and 305 deletions
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44
lib/config_utils/cls_init_args.py
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@@ -1,20 +1,32 @@
import random, argparse
from .share_args import add_shared_args
def obtain_cls_init_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('--init_checkpoint', type=str, help='The checkpoint path to the initial model.')
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
def obtain_cls_init_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(
"--init_checkpoint", type=str, help="The checkpoint path to the initial model."
)
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