update annotations

docs/talib/finetune.rst

@@ -74,7 +74,7 @@ Adaptive Fine-tuning
 Bi-Tuning
 ------------------------------------------
 
-.. autoclass:: talib.finetune.bi_tuning.Bituning
+.. autoclass:: talib.finetune.bi_tuning.BiTuning
 
 
 

examples/domain_adaptation/image_classification/adda.py

@@ -288,7 +288,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
                         help='seed for initializing training. ')
     parser.add_argument('--per-class-eval', action='store_true',
                         help='whether output per-class accuracy during evaluation')
-    parser.add_argument("--log", type=str, default='dann',
+    parser.add_argument("--log", type=str, default='adda',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_adaptation/image_classification/addagrl.py

@@ -286,7 +286,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
                         help='seed for initializing training. ')
     parser.add_argument('--per-class-eval', action='store_true',
                         help='whether output per-class accuracy during evaluation')
-    parser.add_argument("--log", type=str, default='dann',
+    parser.add_argument("--log", type=str, default='addagrl',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_adaptation/image_classification/self_ensemble.py

@@ -251,7 +251,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='DANN for Unsupervised Domain Adaptation')
+    parser = argparse.ArgumentParser(description='Self Ensemble for Unsupervised Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')

examples/domain_adaptation/image_regression/dann.py

@@ -228,7 +228,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
 
-    parser = argparse.ArgumentParser(description='Source Only for Regression Domain Adaptation')
+    parser = argparse.ArgumentParser(description='DANN for Regression Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')
@@ -269,7 +269,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='dann',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_adaptation/image_regression/dd.py

@@ -266,7 +266,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
 
-    parser = argparse.ArgumentParser(description='MDD for Regression Domain Adaptation')
+    parser = argparse.ArgumentParser(description='DD for Regression Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')
@@ -309,7 +309,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='mdd',
+    parser.add_argument("--log", type=str, default='dd',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model." 

examples/domain_adaptation/image_regression/rsd.py

@@ -222,7 +222,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
 
-    parser = argparse.ArgumentParser(description='Source Only for Regression Domain Adaptation')
+    parser = argparse.ArgumentParser(description='RSD for Regression Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')
@@ -263,7 +263,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='rsd',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model." 

examples/domain_adaptation/keypoint_detection/regda.py

@@ -431,7 +431,7 @@ def validate(val_loader, model, criterion, visualize, args: argparse.Namespace):
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
 
-    parser = argparse.ArgumentParser(description='Source Only for Keypoint Detection Domain Adaptation')
+    parser = argparse.ArgumentParser(description='RegDA for Keypoint Detection Domain Adaptation')
     # dataset parameters
     parser.add_argument('source_root', help='root path of the source dataset')
     parser.add_argument('target_root', help='root path of the target dataset')
@@ -485,7 +485,7 @@ def validate(val_loader, model, criterion, visualize, args: argparse.Namespace):
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='regda',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test'],
                         help="When phase is 'test', only test the model.")

examples/domain_adaptation/keypoint_detection/regda_fast.py

@@ -431,7 +431,7 @@ def validate(val_loader, model, criterion, visualize, args: argparse.Namespace):
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
 
-    parser = argparse.ArgumentParser(description='Source Only for Keypoint Detection Domain Adaptation')
+    parser = argparse.ArgumentParser(description='RegDA (fast) for Keypoint Detection Domain Adaptation')
     # dataset parameters
     parser.add_argument('source_root', help='root path of the source dataset')
     parser.add_argument('target_root', help='root path of the target dataset')
@@ -485,7 +485,7 @@ def validate(val_loader, model, criterion, visualize, args: argparse.Namespace):
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='regda_fast',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test'],
                         help="When phase is 'test', only test the model.")

examples/domain_adaptation/openset_domain_adaptation/dann.py

@@ -241,7 +241,7 @@ def validate(val_loader: DataLoader, model: Classifier, args: argparse.Namespace
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='PyTorch Domain Adaptation')
+    parser = argparse.ArgumentParser(description='DANN for Openset Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')

examples/domain_adaptation/openset_domain_adaptation/osbp.py

@@ -230,7 +230,7 @@ def validate(val_loader: DataLoader, model: Classifier, args: argparse.Namespace
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='PyTorch Domain Adaptation')
+    parser = argparse.ArgumentParser(description='OSBP for Openset Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')

examples/domain_adaptation/openset_domain_adaptation/source_only.py

@@ -218,7 +218,7 @@ def validate(val_loader: DataLoader, model: Classifier, args: argparse.Namespace
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='PyTorch Domain Adaptation')
+    parser = argparse.ArgumentParser(description='Source Only for Openset Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')

examples/domain_adaptation/partial_domain_adaptation/afn.py

@@ -205,7 +205,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='AFN for Unsupervised Domain Adaptation')
+    parser = argparse.ArgumentParser(description='AFN for Partial Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')

examples/domain_adaptation/partial_domain_adaptation/dann.py

@@ -204,7 +204,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description='DANN for Unsupervised Domain Adaptation')
+    parser = argparse.ArgumentParser(description='DANN for Partial Domain Adaptation')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')

examples/domain_adaptation/re_identification/baseline.py

@@ -239,7 +239,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
         name for name in datasets.__dict__
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
-    parser = argparse.ArgumentParser(description="Baseline for Domain Adaptive ReID")
+    parser = argparse.ArgumentParser(description="Baseline for Domain Adaptative ReID")
     # dataset parameters
     parser.add_argument('source_root', help='root path of the source dataset')
     parser.add_argument('target_root', help='root path of the target dataset')

examples/domain_adaptation/re_identification/baseline_cluster.py

@@ -306,7 +306,7 @@ def train(train_target_iter: ForeverDataIterator, model, optimizer, criterion_ce
         name for name in datasets.__dict__
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
-    parser = argparse.ArgumentParser(description="Cluster Baseline for Domain Adaptive ReID")
+    parser = argparse.ArgumentParser(description="Cluster Baseline for Domain Adaptative ReID")
     # dataset parameters
     parser.add_argument('source_root', help='root path of the source dataset')
     parser.add_argument('target_root', help='root path of the target dataset')
@@ -351,7 +351,7 @@ def train(train_target_iter: ForeverDataIterator, model, optimizer, criterion_ce
     parser.add_argument('--print-freq', type=int, default=40)
     parser.add_argument('--seed', default=None, type=int, help='seed for initializing training.')
     parser.add_argument('--rerank', action='store_true', help="evaluation only")
-    parser.add_argument("--log", type=str, default='baseline',
+    parser.add_argument("--log", type=str, default='baseline_cluster',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_adaptation/re_identification/idm.py

@@ -367,7 +367,7 @@ def reshape(tensor):
         if name.islower() and not name.startswith("__")
         and callable(models.__dict__[name])
     )
-    parser = argparse.ArgumentParser(description="IDM for Domain Adaptive ReID")
+    parser = argparse.ArgumentParser(description="IDM for Domain Adaptative ReID")
     # dataset parameters
     parser.add_argument('source_root', help='root path of the source dataset')
     parser.add_argument('target_root', help='root path of the target dataset')
@@ -414,7 +414,7 @@ def reshape(tensor):
     parser.add_argument('--print-freq', type=int, default=40)
     parser.add_argument('--seed', default=None, type=int, help='seed for initializing training.')
     parser.add_argument('--rerank', action='store_true', help="evaluation only")
-    parser.add_argument("--log", type=str, default='baseline',
+    parser.add_argument("--log", type=str, default='idm',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_adaptation/re_identification/mmt.py

@@ -411,7 +411,7 @@ def train(train_target_iter: ForeverDataIterator, model_1: DataParallel, model_1
         name for name in datasets.__dict__
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
-    parser = argparse.ArgumentParser(description="MMT for Domain Adaptive ReID")
+    parser = argparse.ArgumentParser(description="MMT for Domain Adaptative ReID")
     # dataset parameters
     parser.add_argument('source_root', help='root path of the source dataset')
     parser.add_argument('target_root', help='root path of the target dataset')
@@ -459,7 +459,7 @@ def train(train_target_iter: ForeverDataIterator, model_1: DataParallel, model_1
     parser.add_argument('--print-freq', type=int, default=40)
     parser.add_argument('--seed', default=None, type=int, help='seed for initializing training.')
     parser.add_argument('--rerank', action='store_true', help="evaluation only")
-    parser.add_argument("--log", type=str, default='baseline',
+    parser.add_argument("--log", type=str, default='mmt',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_adaptation/re_identification/spgan.py

@@ -362,7 +362,7 @@ def train(train_source_iter: ForeverDataIterator, train_target_iter: ForeverData
         name for name in datasets.__dict__
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
-    parser = argparse.ArgumentParser(description='SPGAN for ReID')
+    parser = argparse.ArgumentParser(description='SPGAN for Domain Adaptative ReID')
     # dataset parameters
     parser.add_argument('root', metavar='DIR',
                         help='root path of dataset')

examples/domain_adaptation/semantic_segmentation/cycada.py

@@ -322,7 +322,7 @@ def train(train_source_iter, train_target_iter, netG_S2T, netG_T2S, netD_S, netD
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
     # dataset parameters
-    parser = argparse.ArgumentParser(description='Cycada for Segmentation')
+    parser = argparse.ArgumentParser(description='Cycada for Segmentation Domain Adaptation')
     parser.add_argument('source_root', help='root path of the source dataset')
     parser.add_argument('target_root', help='root path of the target dataset')
     parser.add_argument('-s', '--source', help='source domain(s)')

examples/domain_adaptation/semantic_segmentation/cycle_gan.py

@@ -269,7 +269,7 @@ def train(train_source_iter, train_target_iter, netG_S2T, netG_T2S, netD_S, netD
         name for name in datasets.__dict__
         if not name.startswith("__") and callable(datasets.__dict__[name])
     )
-    parser = argparse.ArgumentParser(description='CycleGAN for Segmentation')
+    parser = argparse.ArgumentParser(description='CycleGAN for Segmentation Domain Adaptation')
     # dataset parameters
     parser.add_argument('source_root', help='root path of the source dataset')
     parser.add_argument('target_root', help='root path of the target dataset')

examples/domain_generalization/image_classification/baseline.py

@@ -231,7 +231,7 @@ def train(train_iter: ForeverDataIterator, model: Classifier, optimizer,
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=0, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='baseline',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_generalization/image_classification/coral.py

@@ -270,7 +270,7 @@ def train(train_iter: ForeverDataIterator, model: Classifier, optimizer, lr_sche
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='coral',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_generalization/image_classification/groupdro.py

@@ -255,7 +255,7 @@ def train(train_iter: ForeverDataIterator, model: Classifier, optimizer, lr_sche
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='groupdro',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_generalization/image_classification/irm.py

@@ -271,7 +271,7 @@ def train(train_iter: ForeverDataIterator, model: Classifier, optimizer, lr_sche
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='irm',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."

examples/domain_generalization/image_classification/mixstyle.py

@@ -245,7 +245,7 @@ def train(train_iter: ForeverDataIterator, model: Classifier, optimizer,
                         metavar='N', help='print frequency (default: 100)')
     parser.add_argument('--seed', default=None, type=int,
                         help='seed for initializing training. ')
-    parser.add_argument("--log", type=str, default='src_only',
+    parser.add_argument("--log", type=str, default='mixstyle',
                         help="Where to save logs, checkpoints and debugging images.")
     parser.add_argument("--phase", type=str, default='train', choices=['train', 'test', 'analysis'],
                         help="When phase is 'test', only test the model."