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Functions88 in github.com/diffusion-classifier/diffusion-classifier

↓ 4 callersFunctioneval_prob
(unet, latent, cond_emb, scheduler, args, all_noise=None)
run_winoground.py:19
↓ 4 callersFunctionget_target_dataset
Get the torchvision dataset that we want to use. If the dataset doesn't have a class_to_idx attribute, we add it. Also add a file-to-class map
diffusion/datasets.py:85
↓ 3 callersFunctionget_transform
(interpolation=InterpolationMode.BICUBIC, size=512)
eval_prob_adaptive.py:28
↓ 3 callersMethodname
(self)
diffusion/dataset/imagenet.py:63
↓ 2 callersFunctionget_classnames
(source)
diffusion/dataset/imagenet_classnames.py:200
↓ 2 callersFunctionget_scheduler_config
(args)
diffusion/models.py:36
↓ 2 callersFunctionget_sd_model
(args)
diffusion/models.py:16
↓ 2 callersMethodget_test_path
(self)
diffusion/dataset/imagenet.py:48
↓ 2 callersFunctionimage_correct
(result)
run_winoground.py:237
↓ 2 callersMethodpath_to_cls
(self, path)
diffusion/datasets.py:73
↓ 2 callersFunctionproject_logits
(logits, class_sublist_mask, device)
diffusion/dataset/imagenet.py:89
↓ 2 callersFunctiontext_correct
(result)
run_winoground.py:232
↓ 1 callersMethod__getitem__
(self, idx)
diffusion/dataset/common.py:123
↓ 1 callersMethod__init__
( self, root=DATASET_ROOT, transform=lambda x: x, )
diffusion/datasets.py:58
↓ 1 callersMethod__init__
(self, preprocess, location=os.path.expanduser('~/data'), b
diffusion/dataset/imagenet.py:9
↓ 1 callersMethod__init__
(self, *args, **kwargs)
diffusion/dataset/objectnet.py:76
↓ 1 callersMethod__init__
(self, indices)
diffusion/dataset/common.py:13
↓ 1 callersFunctionaccuracy
(logits, targets, img_paths, args)
diffusion/dataset/objectnet.py:128
↓ 1 callersFunctioncenter_crop_arr
Center cropping implementation from ADM. https://github.com/openai/guided-diffusion/blob/8fb3ad9197f16bbc40620447b2742e13458d2831/guided_diff
eval_prob_dit.py:26
↓ 1 callersFunctioncls_from_dir
(name)
scripts/print_dit_acc.py:50
↓ 1 callersFunctionconf_interval
(p, n, z=1.96)
run_winoground.py:244
↓ 1 callersFunctioneval_error
(unet, scheduler, latent, all_noise, ts, noise_idxs, text_embeds, text_embed_idxs, batch_size=3
eval_prob_adaptive.py:98
↓ 1 callersFunctioneval_prob
(unet, latent, cond_emb, diffusion, args, all_noise=None)
eval_prob_dit.py:89
↓ 1 callersFunctioneval_prob_adaptive
(unet, latent, text_embeds, scheduler, args, latent_size=64, all_noise=None)
eval_prob_adaptive.py:44
↓ 1 callersFunctionfilter_imageneta
(files, labels)
scripts/print_dit_acc.py:12
↓ 1 callersMethodget_class_sublist_and_mask
(self)
diffusion/dataset/imagenet.py:103
↓ 1 callersMethodget_class_sublist_and_mask
(self)
diffusion/dataset/imagenet.py:113
↓ 1 callersFunctionget_classes_templates
Get a template for the text prompt. Args: dataset: dataset name Returns: template: template for the text prompt
diffusion/utils.py:47
↓ 1 callersFunctionget_features
(is_train, image_encoder, dataset, device)
diffusion/dataset/common.py:90
↓ 1 callersFunctionget_features_helper
(image_encoder, dataloader, device)
diffusion/dataset/common.py:60
↓ 1 callersFunctionget_formatstr
(n)
diffusion/utils.py:38
↓ 1 callersFunctionget_imageneta_files
(args, labels, test_subdir=True)
scripts/print_dit_acc.py:18
↓ 1 callersFunctionget_metadata
()
diffusion/dataset/objectnet.py:15
↓ 1 callersFunctionget_shared_files
(args, labels, test_subdir=True, imageneta=False)
scripts/print_dit_acc.py:33
↓ 1 callersMethodget_test_dataset
(self)
diffusion/dataset/imagenet.py:60
↓ 1 callersMethodget_test_dataset
(self)
diffusion/dataset/objectnet.py:99
↓ 1 callersMethodget_test_sampler
(self)
diffusion/dataset/imagenet.py:57
↓ 1 callersMethodget_train_sampler
(self)
diffusion/dataset/imagenet.py:54
↓ 1 callersFunctionget_transform
(image_size)
eval_prob_dit.py:51
↓ 1 callersFunctiongroup_correct
(result)
run_winoground.py:241
↓ 1 callersFunctionis_correct
(labels, folder, subdirs, file, test_subdir=True, idx_map=None)
scripts/print_dit_acc.py:58
↓ 1 callersFunctionmain
()
eval_prob_adaptive.py:125
↓ 1 callersFunctionmain
()
run_winoground.py:75
↓ 1 callersFunctionmain
()
eval_prob_dit.py:173
↓ 1 callersFunctionmain
()
scripts/print_acc.py:16
↓ 1 callersFunctionmain
()
scripts/print_dit_acc.py:89
↓ 1 callersFunctionmaybe_dictionarize
(batch)
diffusion/dataset/common.py:46
↓ 1 callersFunctionmean_per_class_acc
(correct, labels)
scripts/print_acc.py:8
↓ 1 callersFunctionnormal_kl
Compute the KL divergence between two gaussians. Shapes are automatically broadcasted, so batches can be compared to scalars, among other
eval_prob_dit.py:60
↓ 1 callersMethodpopulate_test
(self)
diffusion/dataset/imagenet.py:39
↓ 1 callersMethodpopulate_train
(self)
diffusion/dataset/imagenet.py:24
↓ 1 callersFunctionsave_noise
()
scripts/save_noise.py:5
Method__getitem__
(self, index)
diffusion/datasets.py:77
Method__getitem__
(self, index)
diffusion/dataset/objectnet.py:66
Method__getitem__
(self, index)
diffusion/dataset/common.py:37
Method__init__
( self, variant="matched-frequency", root=DATASET_ROOT, transf
diffusion/datasets.py:45
Method__init__
(self, *args, **kwargs)
diffusion/dataset/imagenet.py:98
Method__init__
(self, label_map, path, transform)
diffusion/dataset/objectnet.py:54
Method__init__
(self, path, transform, flip_label_prob=0.0)
diffusion/dataset/common.py:23
Method__init__
(self, is_train, image_encoder, dataset, device)
diffusion/dataset/common.py:117
Method__iter__
(self)
diffusion/dataset/common.py:16
Method__len__
(self)
diffusion/datasets.py:70
Method__len__
(self)
diffusion/dataset/objectnet.py:63
Method__len__
(self)
diffusion/dataset/common.py:19
Method__len__
(self)
diffusion/dataset/common.py:120
Function_convert_image_to_rgb
(image)
eval_prob_adaptive.py:24
Function_convert_image_to_rgb
(image)
eval_prob_dit.py:47
Methodaccuracy
(self, logits, targets, img_paths, args)
diffusion/dataset/objectnet.py:157
Functioncenter_crop_resize
(img, interpolation=InterpolationMode.BILINEAR)
eval_prob_adaptive.py:39
Functioncrop
(img)
diffusion/dataset/objectnet.py:45
Functionget_dataloader
(dataset, is_train, args, image_encoder=None)
diffusion/dataset/common.py:129
Functionget_datetimestr
()
diffusion/utils.py:33
Methodget_test_dataset
(self)
diffusion/dataset/imagenet.py:68
Methodget_test_dataset
(self)
diffusion/dataset/objectnet.py:147
Methodget_test_sampler
(self)
diffusion/dataset/imagenet.py:119
Methodget_test_sampler
(self)
diffusion/dataset/objectnet.py:140
Methodget_train_sampler
(self)
diffusion/dataset/imagenet.py:73
Functionis_correct_wrapper
(args)
scripts/print_dit_acc.py:85
Methodpopulate_train
(self)
diffusion/dataset/imagenet.py:106
Methodpopulate_train
(self)
diffusion/dataset/imagenet.py:116
Methodpopulate_train
(self)
diffusion/dataset/objectnet.py:96
Methodproject_labels
(self, labels, device)
diffusion/dataset/imagenet.py:127
Methodproject_labels
(self, labels, device)
diffusion/dataset/objectnet.py:150
Methodproject_logits
(self, logits, device)
diffusion/dataset/imagenet.py:109
Methodproject_logits
(self, logits, device)
diffusion/dataset/imagenet.py:131
Methodproject_logits
(self, logits, device)
diffusion/dataset/objectnet.py:105
Functionsave_latent
(vae, latent, path, scaling=1 / 0.18125)
diffusion/utils.py:17
Methodscatter_weights
(self, weights)
diffusion/dataset/objectnet.py:117