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Functions124 in github.com/SeuTao/FaceBagNet

⨍ Functions 124◇ Types & classes 22
↓ 46 callersMethodwrite
(self, message, is_terminal=1, is_file=1 )
utils.py:79
↓ 5 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.)
model/MultiModalViT.py:36
↓ 5 callersMethod__init__
(self, num_class=2, is_first_bn = False, type = "A")
model/FaceBagNet.py:293
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, groups, reduction, stride=1, downsample_kernel_size=1, downs
model/FaceBagNet.py:227
↓ 4 callersFunctiondo_valid_test
( net, test_loader, criterion )
metric.py:135
↓ 4 callersFunctionmetric
(logit, truth)
metric.py:77
↓ 4 callersMethodstep
(self, epoch=None)
loss/cyclic_lr.py:59
↓ 3 callersFunctionTTA_36_cropps
(image, target_shape=(32, 32, 3))
process/augmentation.py:114
↓ 3 callersFunctioncalculate
(threshold, dist, actual_issame)
metric.py:19
↓ 3 callersFunctioncolor_augumentor
(image, target_shape=(32, 32, 3), is_infer=False)
process/augmentation.py:217
↓ 3 callersFunctiondepth_augumentor
(image, target_shape=(32, 32, 3), is_infer=False)
process/augmentation.py:239
↓ 3 callersMethodforward_res3
(self, x)
model/FaceBagNet.py:356
↓ 3 callersFunctionget_model
(model_name, image_size, patch_size, num_class=2)
model/__init__.py:35
↓ 3 callersFunctionir_augumentor
(image, target_shape=(32, 32, 3), is_infer=False)
process/augmentation.py:261
↓ 3 callersFunctionrandom_cropping
(image, target_shape=(32, 32, 3), is_random = True)
process/augmentation.py:15
↓ 3 callersFunctionrandom_resize
(img, probability = 0.5, minRatio = 0.2)
process/augmentation.py:201
↓ 2 callersFunctionACER
(threshold, dist, actual_issame)
metric.py:27
↓ 2 callersFunctionFeedForward
(dim, expansion_factor = 4, dropout = 0., dense = nn.Linear)
model/MLPMixer.py:14
↓ 2 callersMethod_make_layer
(self, block, inplanes, planes, blocks, stride=1)
model/FaceBagNet.py:427
↓ 2 callersFunctioncalculate_accuracy
(threshold, dist, actual_issame)
metric.py:6
↓ 2 callersMethodflush
(self)
utils.py:91
↓ 2 callersMethodforward
(self, x)
model/FaceBagNet.py:329
↓ 2 callersFunctionget_augment
(image_mode)
process/augmentation.py:6
↓ 2 callersFunctioninfer_test
( net, test_loader)
metric.py:181
↓ 2 callersFunctionload_test_list
()
process/data_helper.py:30
↓ 2 callersFunctionload_train_list
()
process/data_helper.py:10
↓ 2 callersFunctionload_val_list
()
process/data_helper.py:20
↓ 2 callersMethodopen
(self, file, mode=None)
utils.py:75
↓ 2 callersFunctionsubmission
(probs, outname, mode='valid')
process/data_helper.py:54
↓ 2 callersFunctiontime_to_str
(t, mode='min')
utils.py:97
↓ 2 callersFunctiontransform_balance
(train_list)
process/data_helper.py:41
↓ 1 callersFunctionConvMixer
(dim, depth, kernel_size=9, patch_size=7, n_classes=1000)
model/ConvMixer.py:11
↓ 1 callersFunctionFaceBagNet_model_A
(num_classes=2)
model/FaceBagNet.py:268
↓ 1 callersFunctionFaceBagNet_model_B
(num_classes=2)
model/FaceBagNet.py:275
↓ 1 callersFunctionFaceBagNet_model_C
(num_classes=2)
model/FaceBagNet.py:282
↓ 1 callersFunctionMLPMixer
(*, image_size, channels, patch_size, dim, depth, num_classes, expansion_factor = 4, dropout = 0.,
model/MLPMixer.py:23
↓ 1 callersFunctionPermutator
(*, image_size, patch_size, dim, depth, num_classes, segments, expansion_factor = 4, dropout = 0.)
model/ViP.py:22
↓ 1 callersMethod__init__
(self, *fns)
model/ViP.py:15
↓ 1 callersMethodfeatures
(self, x)
model/FaceBagNet.py:247
↓ 1 callersMethodforward_features
(self, x)
model/MultiModalViT.py:268
↓ 1 callersFunctionget_fusion_model
(model_name, image_size, patch_size, num_class=2)
model/__init__.py:3
↓ 1 callersMethodget_lr
(self)
loss/cyclic_lr.py:51
↓ 1 callersFunctionget_num_layer_for_vit
(var_name, num_max_layer)
loss/optim_factory.py:31
↓ 1 callersFunctionget_parameter_groups
(model, weight_decay=1e-5, skip_list=(), get_num_layer=None, get_layer_scale=None)
loss/optim_factory.py:56
↓ 1 callersFunctionget_position_angle_vec
(position)
model/MultiModalViT.py:164
↓ 1 callersFunctionget_sinusoid_encoding_table
Sinusoid position encoding table
model/MultiModalViT.py:160
↓ 1 callersMethodlogits
(self, x)
model/FaceBagNet.py:255
↓ 1 callersFunctionmain
(config)
train_fusion.py:216
↓ 1 callersFunctionmain
(config)
train.py:223
↓ 1 callersMethodno_weight_decay
(self)
model/MultiModalViT.py:258
↓ 1 callersFunctionrun_check_train_data
()
process/data_fusion.py:163
↓ 1 callersFunctionrun_check_train_data
()
process/data.py:129
↓ 1 callersFunctionrun_test
(config, dir)
train_fusion.py:170
↓ 1 callersFunctionrun_test
(config, dir)
train.py:175
↓ 1 callersFunctionrun_train
(config)
train_fusion.py:10
↓ 1 callersFunctionrun_train
(config)
train.py:11
↓ 1 callersMethodset_mode
(self, mode, fold_index)
process/data_fusion.py:24
↓ 1 callersMethodset_mode
(self, mode, fold_index)
process/data.py:26
FunctionTPR_FPR
( dist, actual_issame, fpr_target = 0.001)
metric.py:35
FunctionTTA_18_cropps
(image, target_shape=(32, 32, 3))
process/augmentation.py:65
FunctionTTA_5_cropps
(image, target_shape=(32, 32, 3))
process/augmentation.py:30
Method__getitem__
(self, index)
process/data_fusion.py:51
Method__getitem__
(self, index)
process/data.py:53
Method__init__
(self)
utils.py:71
Method__init__
(self, dim, fn)
model/MLPMixer.py:6
Method__init__
(self, drop_prob=None)
model/MultiModalViT.py:24
Method__init__
( self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., a
model/MultiModalViT.py:56
Method__init__
(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr
model/MultiModalViT.py:103
Method__init__
(self, img_size=224, patch_size=16, in_chans=3, embed_dim=768)
model/MultiModalViT.py:137
Method__init__
(self, img_size=224, patch_size=16, in_chans=3,
model/MultiModalViT.py:177
Method__init__
(self, fn)
model/ConvMixer.py:4
Method__init__
(self, channels, reduction)
model/FaceBagNet.py:17
Method__init__
(self, inplanes, planes, groups, reduction, stride=1, downsample=None)
model/FaceBagNet.py:66
Method__init__
(self, inplanes, planes, groups, reduction, stride=1, downsample=None, base_width=4)
model/FaceBagNet.py:89
Method__init__
Parameters ---------- block (nn.Module): Bottleneck class. - For SENet154: SEBottleneck - For SE-ResN
model/FaceBagNet.py:110
Method__init__
(self, num_class=2, type = 'A', fusion = 'se_fusion')
model/FaceBagNet.py:392
Method__init__
(self, dim, fn)
model/ViP.py:6
Method__init__
(self, optimizer, T_max, T_mult, model, out_dir, take_snapshot, eta_min=0, last_epoch=-1)
loss/cyclic_lr.py:36
Method__init__
(self, values)
loss/optim_factory.py:46
Method__init__
(self, mode, fold_index = None, image_size = 128, augment = None, balance = True, )
process/data_fusion.py:7
Method__init__
(self, mode, modality='color', fold_index=-1, image_size=128, augment = None, augmentor = None, balance = True
process/data.py:6
Method__len__
(self)
process/data_fusion.py:159
Method__len__
(self)
process/data.py:124
Function_cfg
(url='', **kwargs)
model/MultiModalViT.py:11
Method_init_weights
(self, m)
model/MultiModalViT.py:245
Functionacc
(preds,targs,th=0.0)
utils.py:26
Functionbce_criterion
(logit, truth, is_average=True)
utils.py:47
Functioncreate_optimizer
(args, model, get_num_layer=None, get_layer_scale=None, filter_bias_and_bn=True, skip_list=None)
loss/optim_factory.py:98
Functiondo_valid
( net, test_loader, criterion )
metric.py:86
Functiondot_numpy
(vector1 , vector2,emb_size = 512)
utils.py:31
Functionempty
(dir)
utils.py:64
Methodextra_repr
(self)
model/MultiModalViT.py:31
Methodforward
(self, x)
model/MLPMixer.py:11
Methodforward
(self, x)
model/MultiModalViT.py:28
Methodforward
(self, x)
model/MultiModalViT.py:45
Methodforward
(self, x)
model/MultiModalViT.py:79
Methodforward
(self, x)
model/MultiModalViT.py:123
Methodforward
(self, x, **kwargs)
model/MultiModalViT.py:149
Methodforward
(self, x)
model/MultiModalViT.py:294
Methodforward
(self, x)
model/ConvMixer.py:8
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