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Functions226 in github.com/MLforHealth/S2SD

⨍ Functions 226◇ Types & classes 66

(self, embed_dim, mode, **kwargs)

metrics/rho_spectrum.py:7

(self, **kwargs)

metrics/c_f1.py:6

(self, metric_names, opt)

metrics/__init__.py:62

(self, **kwargs)

metrics/c_mAP_lim.py:8

(self, **kwargs)

metrics/mAP.py:8

(self, k, **kwargs)

metrics/c_recall.py:4

(self, **kwargs)

metrics/c_nmi.py:4

(self, **kwargs)

metrics/nmi.py:4

(self, mode, **kwargs)

metrics/dists.py:7

architectures/resnet50.py:13

architectures/googlenet.py:13

(self, opt, return_embed_dict=False)

architectures/bninception.py:11

(self, model, device_ids, dim)

utilities/misc.py:34

(self, save_path)

utilities/logger.py:9

(self, save_path, title='Training Log', figsize=(25,19))

utilities/logger.py:31

utilities/logger.py:85

LOGGER Internal Structure: self.progress_saver: Contains multiple Progress_Saver instances to log metrics for main metric subsets (e

utilities/logger.py:100

batchminer/diva_shared_distance_apn.py:5

batchminer/epshn.py:5

batchminer/random_distance.py:5

batchminer/npair.py:3

batchminer/ephn.py:5

batchminer/random.py:6

batchminer/easypositive.py:5

batchminer/parametric.py:5

batchminer/epdn.py:5

batchminer/lifted.py:4

batchminer/distance.py:7

batchminer/intra_random.py:6

batchminer/softhard.py:5

batchminer/rho_distance.py:5

batchminer/semihard.py:5

batchminer/diva_shared_distance_an.py:5

(self, image_dict, opt, is_validation=False)

datasets/basic_dataset_scaffold.py:10

(self, opt, image_dict, image_list)

datasampler/greedy_coreset_sampler.py:16

(self, opt, image_dict, image_list)

datasampler/fid_batchmatch_sampler.py:16

(self, method='class_random', random_subset_perc=0.1, batch_size=128, samples_per_class=4)

datasampler/samplers.py:22

(self, opt, image_dict, image_list)

datasampler/d2_coreset_sampler.py:16

(self, opt, image_dict, image_list)

datasampler/disthist_batchmatch_sampler.py:16

(self, opt, image_dict, image_list, **kwargs)

datasampler/class_random_sampler.py:16

(self, opt, image_dict, image_list=None)

datasampler/random_sampler.py:16

(self, opt, batchminer)

criteria/snr.py:12

criteria/softtriplet.py:12

(self, opt, batchminer)

criteria/margin.py:12

criteria/npair.py:12

(self, opt, batchminer)

criteria/triplet.py:12

(self, opt, batchminer)

criteria/angular.py:12

(self, opt, batchminer)

criteria/contrastive.py:12

criteria/arcface.py:12

Args: margin: Triplet Margin. nu: Regularisation Parameter for beta values if they are le

criteria/adversarial_separation.py:13

criteria/softmax.py:13

(self, opt, batchminer)

criteria/lifted.py:12

Args: opt: Namespace containing all relevant parameters.

criteria/proxynca.py:13

Args: margin: Triplet Margin.

criteria/histogram.py:13

Args: opt: Namespace containing all relevant parameters.

criteria/s2sd.py:13

(self, opt, batchminer)

criteria/quadruplet.py:11

criteria/multisimilarity.py:11

datasampler/greedy_coreset_sampler.py:39

datasampler/fid_batchmatch_sampler.py:38

datasampler/samplers.py:58

datasampler/d2_coreset_sampler.py:38

datasampler/disthist_batchmatch_sampler.py:39

datasampler/class_random_sampler.py:35

datasampler/random_sampler.py:28

datasets/basic_dataset_scaffold.py:88

datasampler/greedy_coreset_sampler.py:155

datasampler/fid_batchmatch_sampler.py:147

datasampler/samplers.py:100

datasampler/d2_coreset_sampler.py:144

datasampler/disthist_batchmatch_sampler.py:164

datasampler/class_random_sampler.py:48

datasampler/random_sampler.py:40

Functionbasic_training_parameters

parameters.py:5

Functionbatch_creation_parameters

parameters.py:171

Methodbatchfinder

datasampler/greedy_coreset_sampler.py:54

Methodbatchfinder

datasampler/d2_coreset_sampler.py:53

Functionbatchmining_specific_parameters

parameters.py:159

(self, target_labels, k_closest_classes)

metrics/a_recall.py:8

Methodcreate_storage

(self, dataloader, model, device)

datasampler/greedy_coreset_sampler.py:78

Methodcreate_storage

(self, dataloader, model, device)

datasampler/fid_batchmatch_sampler.py:70

Methodcreate_storage

(self, dataloader, model, device)

datasampler/d2_coreset_sampler.py:75

Methodcreate_storage

(self, dataloader, model, device)

datasampler/disthist_batchmatch_sampler.py:72

Methoddisthist_match

datasampler/disthist_batchmatch_sampler.py:105

Functionevaluate

Parent-Function to compute evaluation metrics, print summary string and store checkpoint files/plot sample recall plots.

evaluation/__init__.py:7

Functionevaluate

(dataset, LOG, **kwargs)

evaluation/evaluate.py:24

(self, x, warmup=False, **kwargs)

architectures/resnet50.py:38

architectures/googlenet.py:24

(self, x, warmup=False, **kwargs)

architectures/bninception.py:37

utilities/misc.py:39

(self, batch, labels, **kwargs)

criteria/snr.py:29

(self, batch, labels, **kwargs)

criteria/softtriplet.py:50

(self, batch, labels, **kwargs)

criteria/margin.py:39

(self, batch, labels, **kwargs)

criteria/npair.py:29

(self, batch, labels, **kwargs)

criteria/triplet.py:27

(self, batch, labels, **kwargs)

criteria/angular.py:29

(self, batch, labels, **kwargs)

criteria/contrastive.py:27

(self, batch, labels, **kwargs)

criteria/arcface.py:36

(self, feature_dict)

criteria/adversarial_separation.py:49

Container which applies a simple identity function. Input: x: any torch tensor input.

criteria/adversarial_separation.py:66

(self, batch, labels, **kwargs)

criteria/softmax.py:33

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