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added finetune and test codes
1 parent bd0dd35 commit 186db89

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‎.gitignore‎

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@@ -3,3 +3,4 @@ experiments*
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model/pretrained_checkpoints*
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support_data.pth
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data_paths.yaml
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*ipynb*

‎args.py‎

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import argparse
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import yaml
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from easydict import EasyDict
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from dataset.taskonomy_constants import TASKS_GROUP_NAMES, TASKS_GROUP_TEST
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def str2bool(v):
@@ -14,109 +17,110 @@ def str2bool(v):
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# argument parser
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parser = argparse.ArgumentParser()
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# environment arguments
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parser.add_argument('--seed', type=int, default=0)
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parser.add_argument('--precision', '-prc', type=str, default='bf16', choices=['fp32', 'fp16', 'bf16'])
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parser.add_argument('--strategy', '-str', type=str, default='ddp', choices=['none', 'ddp'])
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# necessary arguments
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parser.add_argument('--debug_mode', '-debug', default=False, action='store_true')
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parser.add_argument('--continue_mode', '-cont', default=False, action='store_true')
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parser.add_argument('--skip_mode', '-skip', default=False, action='store_true')
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parser.add_argument('--no_eval', '-ne', default=False, action='store_true')
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parser.add_argument('--no_save', '-ns', default=False, action='store_true')
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parser.add_argument('--reset_mode', '-reset', default=False, action='store_true')
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parser.add_argument('--profile_mode', '-prof', default=False, action='store_true')
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parser.add_argument('--sanity_check', '-sc', default=False, action='store_true')
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# data arguments
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parser.add_argument('--dataset', type=str, default='taskonomy', choices=['taskonomy'])
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parser.add_argument('--task', type=str, default='', choices=['', 'all'])
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parser.add_argument('--task_fold', '-fold', type=int, default=0, choices=[0, 1, 2, 3, 4])
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parser.add_argument('--num_workers', '-nw', type=int, default=8)
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parser.add_argument('--global_batch_size', '-gbs', type=int, default=8)
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parser.add_argument('--max_channels', '-mc', type=int, default=5)
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parser.add_argument('--shot', type=int, default=4)
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parser.add_argument('--domains_per_batch', '-dpb', type=int, default=2)
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parser.add_argument('--eval_batch_size', '-ebs', type=int, default=8)
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parser.add_argument('--n_eval_batches', '-neb', type=int, default=10)
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parser.add_argument('--img_size', type=int, default=224, choices=[224])
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parser.add_argument('--image_augmentation', '-ia', type=str2bool, default=True)
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parser.add_argument('--unary_augmentation', '-ua', type=str2bool, default=True)
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parser.add_argument('--binary_augmentation', '-ba', type=str2bool, default=True)
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parser.add_argument('--mixed_augmentation', '-ma', type=str2bool, default=True)
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# model arguments
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parser.add_argument('--model', type=str, default='VTM', choices=['VTM'])
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parser.add_argument('--image_backbone', '-ib', type=str, default='beit_base_patch16_224_in22k')
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parser.add_argument('--label_backbone', '-lb', type=str, default='vit_base_patch16_224')
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parser.add_argument('--image_encoder_weights', '-iew', type=str, default='imagenet', choices=['none', 'imagenet'])
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parser.add_argument('--label_encoder_weights', '-lew', type=str, default='none', choices=['none', 'imagenet'])
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parser.add_argument('--n_attn_heads', '-nah', type=int, default=4)
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parser.add_argument('--n_attn_layers', '-nal', type=int, default=1)
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parser.add_argument('--attn_residual', '-ar', type=str2bool, default=True)
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parser.add_argument('--out_activation', '-oa', type=str, default='sigmoid', choices=['sigmoid', 'clip', 'none'])
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parser.add_argument('--drop_rate', '-dr', type=float, default=0.0)
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parser.add_argument('--drop_path_rate', '-dpr', type=float, default=0.1)
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parser.add_argument('--bitfit', '-bf', type=str2bool, default=True)
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parser.add_argument('--semseg_threshold', '-th', type=float, default=0.2)
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# training arguments
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parser.add_argument('--n_steps', '-nst', type=int, default=300000)
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parser.add_argument('--optimizer', '-opt', type=str, default='adam', choices=['sgd', 'adam', 'adamw', 'fadam', 'dsadam'])
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parser.add_argument('--lr', type=float, default=1e-4)
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parser.add_argument('--lr_pretrained', '-lrp', type=float, default=1e-5)
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parser.add_argument('--lr_schedule', '-lrs', type=str, default='poly', choices=['constant', 'sqroot', 'cos', 'poly'])
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parser.add_argument('--lr_warmup', '-lrw', type=int, default=5000)
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parser.add_argument('--lr_warmup_scale', '-lrws', type=float, default=0.)
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parser.add_argument('--weight_decay', '-wd', type=float, default=0.)
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parser.add_argument('--lr_decay_degree', '-ldd', type=float, default=0.9)
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parser.add_argument('--temperature', '-temp', type=float, default=-1.)
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parser.add_argument('--reg_coef', '-rgc', type=float, default=1.)
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parser.add_argument('--mask_value', '-mv', type=float, default=-1.)
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# logging arguments
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parser.add_argument('--log_dir', type=str, default='TRAIN')
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parser.add_argument('--save_dir', type=str, default='')
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parser.add_argument('--load_dir', type=str, default='')
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parser.add_argument('--stage', type=int, default=0, choices=[0, 1, 2])
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parser.add_argument('--task', type=str, default='', choices=['', 'all'] + TASKS_GROUP_NAMES)
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parser.add_argument('--task_fold', '-fold', type=int, default=None, choices=[0, 1, 2, 3, 4])
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parser.add_argument('--exp_name', type=str, default='')
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parser.add_argument('--exp_subname', type=str, default='')
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parser.add_argument('--name_postfix', '-ptf', type=str, default='')
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parser.add_argument('--log_iter', '-li', type=int, default=100)
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parser.add_argument('--val_iter', '-vi', type=int, default=10000)
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parser.add_argument('--save_iter', '-si', type=int, default=10000)
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parser.add_argument('--save_postfix', '-sptf', type=str, default='')
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parser.add_argument('--result_postfix', '-rptf', type=str, default='')
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parser.add_argument('--load_step', '-ls', type=int, default=-1)
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config = parser.parse_args()
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# optional arguments
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parser.add_argument('--model', type=str, default=None, choices=['VTM'])
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parser.add_argument('--seed', type=int, default=None)
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parser.add_argument('--strategy', '-str', type=str, default=None)
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parser.add_argument('--num_workers', '-nw', type=int, default=None)
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parser.add_argument('--global_batch_size', '-gbs', type=int, default=None)
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parser.add_argument('--eval_batch_size', '-ebs', type=int, default=None)
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parser.add_argument('--n_eval_batches', '-neb', type=int, default=None)
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parser.add_argument('--shot', type=int, default=None)
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parser.add_argument('--max_channels', '-mc', type=int, default=None)
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parser.add_argument('--support_idx', '-sid', type=int, default=None)
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parser.add_argument('--channel_idx', '-cid', type=int, default=None)
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parser.add_argument('--test_split', '-split', type=str, default=None)
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parser.add_argument('--semseg_threshold', '-sth', type=float, default=None)
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parser.add_argument('--image_augmentation', '-ia', type=str2bool, default=None)
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parser.add_argument('--unary_augmentation', '-ua', type=str2bool, default=None)
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parser.add_argument('--binary_augmentation', '-ba', type=str2bool, default=None)
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parser.add_argument('--mixed_augmentation', '-ma', type=str2bool, default=None)
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parser.add_argument('--image_backbone', '-ib', type=str, default=None)
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parser.add_argument('--label_backbone', '-lb', type=str, default=None)
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parser.add_argument('--n_attn_heads', '-nah', type=int, default=None)
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parser.add_argument('--n_steps', '-nst', type=int, default=None)
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parser.add_argument('--optimizer', '-opt', type=str, default=None, choices=['sgd', 'adam', 'adamw'])
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parser.add_argument('--lr', type=float, default=None)
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parser.add_argument('--lr_pretrained', '-lrp', type=float, default=None)
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parser.add_argument('--lr_schedule', '-lrs', type=str, default=None, choices=['constant', 'sqroot', 'cos', 'poly'])
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parser.add_argument('--early_stopping_patience', '-esp', type=int, default=None)
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parser.add_argument('--log_dir', type=str, default=None)
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parser.add_argument('--save_dir', type=str, default=None)
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parser.add_argument('--load_dir', type=str, default=None)
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parser.add_argument('--val_iter', '-viter', type=int, default=None)
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parser.add_argument('--save_iter', '-siter', type=int, default=None)
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args = parser.parse_args()
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# load config file
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if args.stage == 0:
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config_path = 'configs/train_config.yaml'
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elif args.stage == 1:
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config_path = 'configs/finetune_config.yaml'
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elif args.stage == 2:
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config_path = 'configs/test_config.yaml'
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with open(config_path, 'r') as f:
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config = yaml.safe_load(f)
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config = EasyDict(config)
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# copy parsed arguments
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for key in args.__dir__():
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if key[:2] != '__' and getattr(args, key) is not None:
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setattr(config, key, getattr(args, key))
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# retrieve data root
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with open('data_paths.yaml', 'r') as f:
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path_dict = yaml.safe_load(f)
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config.root_dir = path_dict[config.dataset]
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if config.save_dir == '':
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config.save_dir = config.log_dir
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if config.load_dir == '':
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config.load_dir = config.log_dir
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# for debugging
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if config.debug_mode:
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config.n_steps = 10
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config.log_iter = 1
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config.val_iter = 5
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config.save_iter = 5
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config.n_eval_batches = 4
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if config.stage == 2:
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config.n_eval_batches = 2
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config.log_dir += '_debugging'
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config.save_dir += '_debugging'
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config.load_dir += '_debugging'
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if config.stage == 0:
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config.load_dir += '_debugging'
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if config.stage <= 1:
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config.save_dir += '_debugging'
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# model-specific hyper-parameters
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config.n_levels = 4
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# adjust backbone names
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if config.image_backbone in ['beit_base', 'beit_large']:
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config.image_backbone += '_patch16_224_in22k'
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if config.image_backbone in ['vit_tiny', 'vit_small', 'vit_base', 'vit_large']:
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config.image_backbone += '_patch16_224'
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if config.label_backbone in ['vit_tiny', 'vit_small', 'vit_base', 'vit_large']:
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config.label_backbone += '_patch16_224'
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# create experiment name
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if config.exp_name == '':
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if config.stage == 0:
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if config.task == '':
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config.exp_name = f'{config.model}_fold:{config.task_fold}{config.name_postfix}'
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else:
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config.exp_name = f'{config.model}_task:{config.task}{config.name_postfix}'
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else:
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fold_dict = {}
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for fold in TASKS_GROUP_TEST:
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for task in TASKS_GROUP_TEST[fold]:
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fold_dict[task] = fold
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task_fold = fold_dict[config.task]
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config.exp_name = f'{config.model}_fold:{task_fold}{config.name_postfix}'

‎configs/finetune_config.yaml‎

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# environment settings
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seed: 0
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precision: bf16
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strategy: ddp
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# data arguments
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dataset: taskonomy
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num_workers: 4
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global_batch_size: 1
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shot: 10
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eval_batch_size: 5
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n_eval_batches: 2
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img_size: 224
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support_idx: 0
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channel_idx: -1
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# model arguments
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model: VTM
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semseg_threshold: 0.2
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attn_dropout: 0.5
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# training arguments
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n_steps: 20000
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n_schedule_steps: 20000
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optimizer: adam
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lr: 0.005
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lr_schedule: constant
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lr_warmup: 0
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lr_warmup_scale: 0.
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schedule_from: 0
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weight_decay: 0.
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lr_decay_degree: 0.9
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mask_value: -1.
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early_stopping_patience: 5
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# logging arguments
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log_dir: FINETUNE
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save_dir: FINETUNE
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load_dir: TRAIN
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log_iter: 100
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val_iter: 100
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save_iter: 100
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load_step: 0

‎configs/test_config.yaml‎

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# environment settings
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seed: 0
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precision: bf16
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strategy: ddp
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# data arguments
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dataset: taskonomy
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test_split: muleshoe
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num_workers: 4
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shot: 10
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eval_batch_size: 8
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n_eval_batches: -1
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img_size: 224
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support_idx: 0
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channel_idx: -1
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# model arguments
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model: VTM
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semseg_threshold: 0.2
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# logging arguments
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log_dir: TEST
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save_dir: FINETUNE
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load_dir: TRAIN
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load_step: 0

‎configs/train_config.yaml‎

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# environment settings
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seed: 0
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precision: bf16
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strategy: ddp
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# data arguments
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dataset: taskonomy
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task_fold: 0
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num_workers: 4
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global_batch_size: 8
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max_channels: 5
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shot: 4
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n_buildings: -1
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domains_per_batch: 2
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eval_batch_size: 8
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n_eval_batches: 10
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img_size: 224
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image_augmentation: True
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unary_augmentation: True
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binary_augmentation: True
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mixed_augmentation: True
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channel_idx: -1
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# model arguments
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model: VTM
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image_backbone: beit_base_patch16_224_in22k
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label_backbone: vit_base_patch16_224
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image_encoder_weights: imagenet
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drop_rate: 0.
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drop_path_rate: 0.1
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attn_drop_rate: 0.
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n_attn_heads: 4
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semseg_threshold: 0.2
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channel_idx: -1
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n_levels: 4
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bitfit: True
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# training arguments
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n_steps: 300000
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optimizer: adam
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lr: 0.0001
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lr_pretrained: 0.00001
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lr_schedule: poly
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lr_warmup: 5000
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lr_warmup_scale: 0.
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schedule_from: 0
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weight_decay: 0.
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lr_decay_degree: 0.9
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mask_value: -1.
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early_stopping_patience: -1
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# logging arguments
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log_dir: TRAIN
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save_dir: TRAIN
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load_dir: TRAIN
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log_iter: 100
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val_iter: 20000
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save_iter: 20000
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load_step: -1

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