Functions — github.com/TPCD/DCCL

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Functions480 in github.com/TPCD/DCCL

⨍ Functions 480◇ Types & classes 94

↓ 1 callersMethodfilter_by_th

(self, i)

project_utils/infomap_cluster_utils.py:444

↓ 1 callersFunctionfind_classes

(classes_file)

data/fgvc_aircraft.py:23

↓ 1 callersMethodfit_once

(self, X, random_state)

methods/clustering/faster_mix_k_means_pytorch.py:113

↓ 1 callersFunctionget_2d_sincos_pos_embed_from_grid

(embed_dim, grid)

project_utils/pos_embed.py:29

↓ 1 callersFunctionget_aircraft_datasets

(train_transform, test_transform, train_classes=range(50), prop_train_labels=0.8, split_tr

data/fgvc_aircraft.py:215

↓ 1 callersFunctionget_cifar_100_datasets

(train_transform, test_transform, train_classes=range(80), prop_train_labels=0.8, split

data/cifar.py:137

↓ 1 callersFunctionget_cub_datasets

(train_transform, test_transform, train_classes=range(160), prop_train_labels=0.8, split_t

data/cub.py:187

↓ 1 callersFunctionget_dist_nbr

(features, k=80, knn_method='faiss-cpu', device=0)

project_utils/infomap_cluster_utils.py:345

↓ 1 callersFunctionget_file

(path)

project_utils/slurm_out_parser.py:25

↓ 1 callersFunctionget_flower_datasets

(train_transform, test_transform, train_classes=range(51), prop_train_labels=0.8, split_tr

data/flower.py:212

↓ 1 callersFunctionget_food_datasets

(train_transform, test_transform, train_classes=range(51), prop_train_labels=0.8, split_tr

data/food.py:175

↓ 1 callersFunctionget_herbarium_datasets

(train_transform, test_transform, train_classes=range(500), prop_train_labels=0.8,

data/herbarium_19.py:79

↓ 1 callersMethodget_knns

(self, th=None)

project_utils/infomap_cluster_utils.py:457

↓ 1 callersFunctionget_links_with_label

(single, links, nbrs, dists, min_sim, label_mark, if_labeled, args=None)

project_utils/infomap_cluster_utils.py:115

↓ 1 callersFunctionget_pets_datasets

(train_transform, test_transform, train_classes=range(19), prop_train_labels=0.8, split_tr

data/pets.py:199

↓ 1 callersFunctionget_scars_datasets

(train_transform, test_transform, train_classes=range(160), prop_train_labels=0.8, split_t

data/stanford_cars.py:114

↓ 1 callersFunctionget_train_val_indices

(train_dataset, val_split=0.2)

data/pets.py:180

↓ 1 callersFunctionget_train_val_indices

(train_dataset, val_split=0.2)

data/food.py:156

↓ 1 callersFunctionget_train_val_indices

(train_dataset, val_split=0.2)

data/imagenet.py:62

↓ 1 callersFunctionget_train_val_indices

(train_dataset, val_split=0.2)

data/cub.py:165

↓ 1 callersFunctionget_train_val_indices

(train_dataset, val_split=0.2)

data/fgvc_aircraft.py:195

↓ 1 callersFunctionget_train_val_indices

(train_dataset, val_instances_per_class=5)

data/herbarium_19.py:58

↓ 1 callersFunctionget_train_val_indices

(train_dataset, val_split=0.2)

data/stanford_cars.py:94

↓ 1 callersMethodimg

self.img('input_img',t.Tensor(64,64))

project_utils/visualization_utils.py:973

↓ 1 callersMethodimg_grid

Turning a batch of images to a grid e.g. input shape: (36, 64, 64) Will be a grid of 6x6, each grid is an image size

project_utils/visualization_utils.py:988

↓ 1 callersFunctioninfo_nce_logits

(features, args)

project_utils/contrastive_utils.py:114

↓ 1 callersMethodinterpolate_pos_encoding

(self, x, w, h)

model/attribute_transformer.py:25

↓ 1 callersMethodinterpolate_pos_encoding

(self, x, w, h)

model/vision_transformer.py:175

↓ 1 callersMethodis_better

(self, a, best)

project_utils/general_utils.py:348

↓ 1 callersFunctionkmeans_semi_sup

In this case, the test loader needs to have the labelled and unlabelled subsets of the training data

methods/ssk_means.py:23

↓ 1 callersFunctionkmeans_semi_sup

In this case, the test loader needs to have the labelled and unlabelled subsets of the training data

methods/clustering/ssk_means.py:23

↓ 1 callersFunctionknns2ordered_nbrs

(knns, sort=True)

project_utils/infomap_cluster_utils.py:81

↓ 1 callersMethodlog

(self, *args, **kwargs)

project_utils/visualization_utils.py:867

↓ 1 callersFunctionmain

()

data/pets.py:238

↓ 1 callersFunctionmain

()

data/food.py:214

↓ 1 callersFunctionmain

()

data/cub.py:226

↓ 1 callersFunctionmain

()

data/fgvc_aircraft.py:255

↓ 1 callersFunctionmain

()

data/flower.py:250

↓ 1 callersFunctionmain

()

methods/clustering/faster_mix_k_means_pytorch.py:278

↓ 1 callersFunctionmake_dataset

(dir, image_ids, targets)

data/pets.py:20

↓ 1 callersFunctionmake_dataset

(dir, image_ids, targets)

data/food.py:21

↓ 1 callersFunctionmake_dataset

(dir, image_ids, targets)

data/fgvc_aircraft.py:12

↓ 1 callersFunctionmake_dataset

(dir, image_ids, targets)

data/flower.py:22

↓ 1 callersMethodnext

(self)

project_utils/data_utils.py:32

↓ 1 callersFunctionnormalize

(mean, std)

data/augmentations/cut_out.py:52

↓ 1 callersFunctionparse_multiple_files

(all_paths, rx_dict, root_dir=save_root_dir, save_name='test.pkl', verbose=True, save=False)

project_utils/slurm_out_parser.py:95

↓ 1 callersFunctionparse_out_file

(path, rx_dict, root_dir=save_root_dir, save_name='test.pkl', save=True, verbose=True)

project_utils/slurm_out_parser.py:35

↓ 1 callersFunctionplot_2D_embedding_mask

(save_path, lowDWeights, labels, mask)

project_utils/visualization_utils.py:278

↓ 1 callersFunctionplot_with_domains_and_pic

(save_path, lowDWeights, labels, pic_path)

project_utils/visualization_utils.py:164

↓ 1 callersMethodprepare_tokens

(self, x)

model/attribute_transformer.py:47

↓ 1 callersFunctionpurity_score

(y_true, y_pred)

project_utils/cluster_utils.py:66

↓ 1 callersMethodreset

(self)

project_utils/general_utils.py:17

↓ 1 callersMethodreset

(self)

project_utils/cluster_utils.py:123

↓ 1 callersFunctionscipy_optimise

(merge_test_loader, args)

methods/estimate_k/estimate_k.py:206

↓ 1 callersFunctionset_seed

(seed)

G0_CUB200.py:44

↓ 1 callersMethodstep

(self, metrics, epoch=None)

project_utils/general_utils.py:330

↓ 1 callersFunctionstrip_state_dict

Strip 'module' from start of state_dict keys Useful if model has been trained as DataParallel model

project_utils/general_utils.py:44

↓ 1 callersFunctionsubsample_classes

(dataset, include_classes=range(60))

data/pets.py:165

↓ 1 callersFunctionsubsample_classes

(dataset, include_classes=range(60))

data/food.py:141

↓ 1 callersFunctionsubsample_classes

(dataset, include_classes=range(160))

data/cub.py:147

↓ 1 callersFunctionsubsample_classes

(dataset, include_classes=range(60))

data/fgvc_aircraft.py:179

↓ 1 callersFunctionsubsample_classes

(dataset, include_classes=range(250))

data/herbarium_19.py:43

↓ 1 callersFunctionsubsample_classes

(dataset, include_classes=range(60))

data/flower.py:178

↓ 1 callersFunctionsubsample_classes

(dataset, include_classes=range(160))

data/stanford_cars.py:79

↓ 1 callersFunctionto_tensor

()

data/augmentations/cut_out.py:42

↓ 1 callersFunctiontrain

(projectors, student, train_loaders_dict, test_loader, unlabelled_train_loader, whole_train_test_loader,

G0_CUB200.py:65

↓ 1 callersFunctiontrain

(projectors, student, train_loaders, test_loader, unlabelled_train_loader, whole_train_test_loader, args)

methods/representation_learning/representation_learning.py:179

↓ 1 callersFunctionvisualize

(features_path, output_path, show_num_identities_for_each_domain, plot_by_domain=False, if_from_numpy='',

project_utils/visualization_utils.py:388

FunctionAutoContrast

(img, _)

data/augmentations/randaugment.py:64

FunctionBrightness

(img, v)

data/augmentations/randaugment.py:110

FunctionColor

(img, v)

data/augmentations/randaugment.py:105

FunctionContrast

(img, v)

data/augmentations/randaugment.py:100

FunctionCutout

(img, v)

data/augmentations/randaugment.py:120

FunctionEqualize

(img, _)

data/augmentations/randaugment.py:72

FunctionFlip

(img, _)

data/augmentations/randaugment.py:76

FunctionIdentity

(img, v)

data/augmentations/randaugment.py:159

FunctionInvert

(img, _)

data/augmentations/randaugment.py:68

FunctionPairEnum

(x,mask=None)

project_utils/cluster_utils.py:155

FunctionPosterize

(img, v)

data/augmentations/randaugment.py:94

FunctionRotate

(img, v)

data/augmentations/randaugment.py:57

FunctionSamplePairing

(imgs)

data/augmentations/randaugment.py:150

FunctionSharpness

(img, v)

data/augmentations/randaugment.py:115

FunctionShearX

(img, v)

data/augmentations/randaugment.py:13

FunctionShearY

(img, v)

data/augmentations/randaugment.py:20

FunctionSolarize

(img, v)

data/augmentations/randaugment.py:80

FunctionSolarizeAdd

(img, addition=0, threshold=128)

data/augmentations/randaugment.py:85

MethodStabilityLoss

(self, old_vertex, new_vertex)

model/meta_graph.py:78

MethodStabilityLoss

(self, old_vertex, new_vertex)

model/meta_graph.py:156

FunctionTranslateX

(img, v)

data/augmentations/randaugment.py:27

FunctionTranslateXabs

(img, v)

data/augmentations/randaugment.py:35

FunctionTranslateY

(img, v)

data/augmentations/randaugment.py:42

FunctionTranslateYabs

(img, v)

data/augmentations/randaugment.py:50

Method__call__

(self, input)

project_utils/visualization_utils.py:835

Method__call__

(self, x)

project_utils/contrastive_utils.py:162

Method__call__

(self, input)

project_utils/cluster_and_log_utils.py:127

Method__call__

(self, img)

data/augmentations/randaugment.py:237

Method__call__

(self, img)

data/augmentations/randaugment.py:257

Method__call__

(self, img)

data/augmentations/randaugment.py:289

Method__call__

(self, x)

methods/representation_learning/representation_learning.py:133

Method__call__

(self, x)

methods/partitioning/subset_len.py:38

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