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Types & classes59 in github.com/RetroCirce/HTS-Audio-Transformer

↓ 115 callersClassConvBlock
models.py:26
↓ 9 callersClassConvPreWavBlock
models.py:2190
↓ 9 callersClassLeeNetConvBlock
models.py:1606
↓ 9 callersClassLeeNetConvBlock2
models.py:1697
↓ 4 callersClassConvBlock5x5
models.py:72
↓ 4 callersClassDaiNetResBlock
models.py:1804
↓ 4 callersClassHTSAT_Swin_Transformer
r"""HTSAT based on the Swin Transformer Args: spec_size (int | tuple(int)): Input Spectrogram size. Default 256 patch_size (int |
model/htsat.py:380
↓ 4 callersClassSEDDataset
data_generator.py:21
↓ 3 callersClassESC_Dataset
data_generator.py:185
↓ 3 callersClassSCV2_Dataset
data_generator.py:233
↓ 3 callersClassSEDWrapper
sed_model.py:35
↓ 3 callersClass_ResNet
models.py:698
↓ 3 callersClassdata_prep
main.py:41
↓ 2 callersClassDESED_Dataset
data_generator.py:280
↓ 2 callersClass_ResNetWav1d
models.py:2002
↓ 1 callersClassAsymmetricLoss
utils.py:28
↓ 1 callersClassAttBlock
models.py:109
↓ 1 callersClassBasicLayer
A basic Swin Transformer layer for one stage. Args: dim (int): Number of input channels. input_resolution (tuple[int]): Input res
model/htsat.py:311
↓ 1 callersClassDropPath
Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
model/layers.py:52
↓ 1 callersClassEnsemble_SEDWrapper
sed_model.py:259
↓ 1 callersClassMlp
MLP as used in Vision Transformer, MLP-Mixer and related networks
model/layers.py:94
↓ 1 callersClassPatchEmbed
2D Image to Patch Embedding
model/layers.py:62
↓ 1 callersClassSwinTransformerBlock
r""" Swin Transformer Block. Args: dim (int): Number of input channels. input_resolution (tuple[int]): Input resulotion. n
model/htsat.py:145
↓ 1 callersClassWindowAttention
r""" Window based multi-head self attention (W-MSA) module with relative position bias. It supports both of shifted and non-shifted window. Ar
model/htsat.py:60
ClassCnn10
models.py:485
ClassCnn14
models.py:140
ClassCnn14_16k
models.py:2543
ClassCnn14_8k
models.py:2640
ClassCnn14_DecisionLevelAtt
models.py:3216
ClassCnn14_DecisionLevelAvg
models.py:3111
ClassCnn14_DecisionLevelMax
models.py:3013
ClassCnn14_emb128
models.py:1124
ClassCnn14_emb32
models.py:1215
ClassCnn14_emb512
models.py:1033
ClassCnn14_mel128
models.py:2921
ClassCnn14_mel32
models.py:2830
ClassCnn14_mixup_time_domain
models.py:2737
ClassCnn14_no_dropout
models.py:315
ClassCnn14_no_specaug
models.py:231
ClassCnn6
models.py:400
ClassDaiNet19
models.py:1870
ClassInvertedResidual
models.py:1424
ClassLeeNet11
models.py:1631
ClassLeeNet24
models.py:1731
ClassMobileNetV1
models.py:1306
ClassMobileNetV2
models.py:1476
ClassPatchMerging
r""" Patch Merging Layer. Args: input_resolution (tuple[int]): Resolution of input feature. dim (int): Number of input channels.
model/htsat.py:269
ClassPredictor
predict.py:14
ClassRes1dNet31
models.py:2080
ClassRes1dNet51
models.py:2135
ClassResNet22
models.py:772
ClassResNet38
models.py:859
ClassResNet54
models.py:946
ClassWavegram_Cnn14
models.py:2227
ClassWavegram_Logmel128_Cnn14
models.py:2429
ClassWavegram_Logmel_Cnn14
models.py:2315
Class_ResnetBasicBlock
models.py:581
Class_ResnetBasicBlockWav1d
models.py:1944
Class_ResnetBottleneck
models.py:639