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Types & classes28 in github.com/MediaBrain-SJTU/MVFA-AD

⨍ Functions 142◇ Types & classes 28
↓ 4 callersClassBinaryDiceLoss
loss.py:89
↓ 4 callersClassCLIP_Inplanted
CLIP/adapter.py:32
↓ 4 callersClassFocalLoss
copy from: https://github.com/Hsuxu/Loss_ToolBox-PyTorch/blob/master/FocalLoss/FocalLoss.py This is a implementation of Focal Loss with smoot
loss.py:7
↓ 4 callersClassLayerScale
CLIP/transformer.py:45
↓ 3 callersClassCLIP
CLIP/model.py:149
↓ 2 callersClassBottleneck
CLIP/modified_resnet.py:47
↓ 2 callersClassCLIPTextCfg
CLIP/model.py:46
↓ 2 callersClassCLIPVisionCfg
CLIP/model.py:21
↓ 2 callersClassClipAdapter
CLIP/adapter.py:14
↓ 2 callersClassMedDataset
dataset/medical_few.py:14
↓ 2 callersClassMedTestDataset
dataset/medical_zero.py:173
↓ 2 callersClassMedTrainDataset
dataset/medical_zero.py:14
↓ 2 callersClassResidualAttentionBlock
CLIP/transformer.py:197
↓ 2 callersClassTransformer
CLIP/transformer.py:300
↓ 1 callersClassAttention
CLIP/transformer.py:95
↓ 1 callersClassAttentionPool2d
CLIP/modified_resnet.py:95
↓ 1 callersClassAttentionalPooler
CLIP/transformer.py:171
↓ 1 callersClassCustomTextCLIP
CLIP/model.py:215
↓ 1 callersClassLayerNorm
Subclass torch's LayerNorm (with cast back to input dtype).
CLIP/transformer.py:30
↓ 1 callersClassModifiedResNet
A ResNet class that is similar to torchvision's but contains the following changes: - There are now 3 "stem" convolutions as opposed to 1, wi
CLIP/modified_resnet.py:132
↓ 1 callersClassPatchDropout
https://arxiv.org/abs/2212.00794
CLIP/transformer.py:55
↓ 1 callersClassSimpleTokenizer
CLIP/tokenizer.py:74
↓ 1 callersClassTextTransformer
CLIP/transformer.py:540
↓ 1 callersClassVisionTransformer
CLIP/transformer.py:350
ClassCustomResidualAttentionBlock
CLIP/transformer.py:259
ClassLayerNormFp32
Subclass torch's LayerNorm to handle fp16 (by casting to float32 and back).
CLIP/transformer.py:21
ClassMultimodalTransformer
CLIP/transformer.py:668
ClassQuickGELU
CLIP/transformer.py:39