Functions — github.com/ChongQingNoSubway/SelfReg-UNet

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Functions3,840 in github.com/ChongQingNoSubway/SelfReg-UNet

⨍ Functions 3,840◇ Types & classes 731

↓ 2 callersFunctionadaptive_catavgmax_pool2d

(x, output_size=1)

src/train_acdc/lib/models_timm/layers/adaptive_avgmax_pool.py:30

↓ 2 callersFunctionbhwc_to_bchw

Permutes a tensor from the shape (B, H, W, C) to (B, C, H, W).

src/train_acdc/lib/models_timm/swin_transformer_v2_cr.py:109

↓ 2 callersFunctionblockify

image to blocks Args: x (Tensor): with shape (B, H, W, C) block_size (int): edge length of a single square block in units of H, W

src/train_acdc/lib/models_timm/nest.py:142

↓ 2 callersMethodbottleneck_fn

(self, xs)

src/train_acdc/lib/models_timm/densenet.py:61

↓ 2 callersFunctionbuild_fourier_pos_embed

( feat_shape: List[int], bands: Optional[torch.Tensor] = None, num_bands: int = 64,

src/train_acdc/lib/models_timm/layers/pos_embed.py:72

↓ 2 callersFunctioncal_rel_pos_type

Spatial Relative Positional Embeddings.

src/train_acdc/lib/models_timm/mvitv2.py:211

↓ 2 callersMethodcell_forward

(self, x_left, x_right)

src/train_acdc/lib/models_timm/pnasnet.py:120

↓ 2 callersFunctionclean_state_dict

(state_dict)

src/train_acdc/lib/models_timm/helpers.py:36

↓ 2 callersFunctionconv2d_same

( x, weight: torch.Tensor, bias: Optional[torch.Tensor] = None, stride: Tuple[int, int] = (1, 1),

src/train_acdc/lib/models_timm/layers/conv2d_same.py:13

↓ 2 callersFunctioncreate_conv2d_pad

(in_chs, out_chs, kernel_size, **kwargs)

src/train_acdc/lib/models_timm/layers/conv2d_same.py:33

↓ 2 callersFunctioncreate_feature_extractor

(model: nn.Module, return_nodes: Union[Dict[str, str], List[str]])

src/train_acdc/lib/models_timm/fx_features.py:58

↓ 2 callersFunctioncreate_norm_act_layer

(layer_name, num_features, act_layer=None, apply_act=True, jit=False, **kwargs)

src/train_acdc/lib/models_timm/layers/create_norm_act.py:44

↓ 2 callersFunctioncreate_resnetv2_stem

( in_chs, out_chs=64, stem_type='', preact=True, conv_layer=StdConv2d, norm_layer=partial(Grou

src/train_acdc/lib/models_timm/resnetv2.py:312

↓ 2 callersFunctioncreate_shortcut

( downsample_type, in_chs, out_chs, kernel_size, stride, dilation=(1, 1), norm_layer=None, preact=Fals

src/train_acdc/lib/models_timm/regnet.py:228

↓ 2 callersFunctiondeblockify

blocks to image Args: x (Tensor): with shape (B, T, N, C) where T is number of blocks and N is sequence size per block block_size

src/train_acdc/lib/models_timm/nest.py:159

↓ 2 callersFunctionextend_tuple

(x, n)

src/train_acdc/lib/models_timm/layers/helpers.py:34

↓ 2 callersMethodfeat_mult

(self)

src/train_acdc/lib/models_timm/layers/adaptive_avgmax_pool.py:111

↓ 2 callersFunctionflatten_modules

(named_modules, depth=1, prefix='', module_types='sequential')

src/train_acdc/lib/models_timm/helpers.py:792

↓ 2 callersMethodforward_cls

(self, x)

src/train_acdc/lib/models_timm/volo.py:549

↓ 2 callersMethodforward_features

(self, x)

src/train_acdc/lib/models_timm/dla.py:347

↓ 2 callersMethodforward_features

(self, x0)

src/train_acdc/lib/models_timm/coat.py:508

↓ 2 callersMethodforward_head

(self, x)

src/train_acdc/lib/models_timm/inception_v3.py:397

↓ 2 callersMethodforward_postaux

(self, x)

src/train_acdc/lib/models_timm/inception_v3.py:386

↓ 2 callersMethodforward_preaux

(self, x)

src/train_acdc/lib/models_timm/inception_v3.py:368

↓ 2 callersMethodforward_tokens

(self, x)

src/train_acdc/lib/models_timm/volo.py:534

↓ 2 callersFunctiongen_relative_position_index

(window_size: Tuple[int, int])

src/train_acdc/lib/models_timm/beit.py:115

↓ 2 callersFunctiongen_relative_position_index

( q_size: Tuple[int, int], k_size: Tuple[int, int] = None, class_token: bool = False)

src/train_acdc/lib/models_timm/vision_transformer_relpos.py:70

↓ 2 callersFunctionget_1d_sincos_pos_embed_from_grid

embed_dim: output dimension for each position pos: a list of positions to be encoded: size (M,) out: (M, D)

src/train_acdc/lib/gcn_lib/pos_embed.py:67

↓ 2 callersMethodget_attention

(self, x)

src/train_acdc/lib/models_timm/convit.py:94

↓ 2 callersMethodget_attention_biases

(self, device: torch.device)

src/train_acdc/lib/models_timm/levit.py:272

↓ 2 callersMethodget_attention_biases

(self, device: torch.device)

src/train_acdc/lib/models_timm/levit.py:359

↓ 2 callersFunctionget_b16_config

Returns the ViT-B/16 configuration.

src/train_acdc/networks_trans/vit_seg_configs.py:3

↓ 2 callersFunctionget_b16_config

Returns the ViT-B/16 configuration.

src/train_synase/networks_trans/vit_seg_configs.py:3

↓ 2 callersMethodget_bias

(self)

src/train_acdc/lib/models_timm/vision_transformer_relpos.py:187

↓ 2 callersFunctionget_config

Get a yacs CfgNode object with default values.

src/train_acdc/config.py:222

↓ 2 callersMethodget_embed

(self, shape: List[int])

src/train_acdc/lib/models_timm/layers/pos_embed.py:201

↓ 2 callersFunctionget_init_weights_vit

(mode='jax', head_bias: float = 0.)

src/train_acdc/lib/models_timm/vision_transformer.py:597

↓ 2 callersFunctionget_l16_config

Returns the ViT-L/16 configuration.

src/train_acdc/networks_trans/vit_seg_configs.py:69

↓ 2 callersFunctionget_l16_config

Returns the ViT-L/16 configuration.

src/train_synase/networks_trans/vit_seg_configs.py:69

↓ 2 callersFunctionget_padding

(kernel_size, stride, dilation=1)

src/train_acdc/lib/models_timm/resnet.py:323

↓ 2 callersFunctionget_same_padding

(x: int, k: int, s: int, d: int)

src/train_acdc/lib/models_timm/layers/padding.py:18

↓ 2 callersFunctiongrid_partition

(x, grid_size: List[int])

src/train_acdc/lib/maxxvit_4out.py:1143

↓ 2 callersFunctiongrid_partition

(x, grid_size: List[int])

src/train_acdc/lib/models_timm/maxxvit.py:1143

↓ 2 callersFunctiongrid_reverse

(windows, grid_size: List[int], img_size: List[int])

src/train_acdc/lib/maxxvit_4out.py:1153

↓ 2 callersFunctiongrid_reverse

(windows, grid_size: List[int], img_size: List[int])

src/train_acdc/lib/models_timm/maxxvit.py:1153

↓ 2 callersFunctiongroup_rms

(x, groups: int = 32, eps: float = 1e-5)

src/train_acdc/lib/models_timm/layers/evo_norm.py:90

↓ 2 callersFunctiongroup_with_matcher

( named_objects, group_matcher: Union[Dict, Callable], output_values: bool = False,

src/train_acdc/lib/models_timm/helpers.py:641

↓ 2 callersMethodinit_weights

(self, scheme='')

src/train_acdc/lib/maxxvit_4out.py:1577

↓ 2 callersMethodinit_weights

(self, scheme='')

src/train_acdc/lib/models_timm/maxxvit.py:1577

↓ 2 callersMethodinit_weights

(self)

src/train_acdc/lib/models_timm/swin_transformer_v2_cr.py:391

↓ 2 callersMethodinit_weights

(self, nlhb=False)

src/train_acdc/lib/models_timm/sequencer.py:312

↓ 2 callersMethodinit_weights

(self, nlhb=False)

src/train_acdc/lib/models_timm/mlp_mixer.py:286

↓ 2 callersFunctioninplace_abn

(x, weight, bias, running_mean, running_var, training=True, momentum=0.1, eps=1e-05, activ

src/train_acdc/lib/models_timm/layers/inplace_abn.py:10

↓ 2 callersFunctioninstance_rms

(x, eps: float = 1e-5)

src/train_acdc/lib/models_timm/layers/evo_norm.py:47

↓ 2 callersFunctioninv_freq_bands

( num_bands: int, temperature: float = 100000., step: int = 2, dtype: torch.dt

src/train_acdc/lib/models_timm/layers/pos_embed.py:22

↓ 2 callersFunctioninv_instance_rms

(x, eps: float = 1e-5)

src/train_acdc/lib/models_timm/layers/filter_response_norm.py:14

↓ 2 callersFunctionis_scriptable

()

src/train_acdc/lib/models_timm/layers/config.py:63

↓ 2 callersFunctionis_stem_deep

(stem_type)

src/train_acdc/lib/models_timm/resnetv2.py:308

↓ 2 callersMethodload_from

(self, weights, n_block)

src/train_acdc/networks_trans/vit_seg_modeling.py:189

↓ 2 callersMethodload_from

(self, weights, n_block)

src/train_synase/networks_trans/vit_seg_modeling.py:189

↓ 2 callersMethodload_pretrained

(self, checkpoint_path, prefix='resnet/')

src/train_acdc/lib/models_timm/resnetv2.py:407

↓ 2 callersFunctionload_state_dict

(checkpoint_path, use_ema=True)

src/train_acdc/lib/models_timm/helpers.py:45

↓ 2 callersFunctionload_state_dict_from_hf

(model_id: str, filename: str = 'pytorch_model.bin')

src/train_acdc/lib/models_timm/hub.py:95

↓ 2 callersMethodmax

(self)

src/train_synase/levit/utils.py:65

↓ 2 callersFunctionnorm_cdf

(x)

src/train_acdc/lib/models_timm/layers/weight_init.py:11

↓ 2 callersFunctionparse_model_name

(model_name)

src/train_acdc/lib/models_timm/factory.py:10

↓ 2 callersFunctionreduce_feat_size

(feat_size, stride=2)

src/train_acdc/lib/models_timm/byobnet.py:1357

↓ 2 callersFunctionregister_block

(block_type:str, block_fn: nn.Module)

src/train_acdc/lib/models_timm/byobnet.py:1263

↓ 2 callersFunctionrel_logits_1d

Compute relative logits along one dimension As per: https://gist.github.com/aravindsrinivas/56359b79f0ce4449bcb04ab4b56a57a2 Originally from

src/train_acdc/lib/models_timm/layers/bottleneck_attn.py:28

↓ 2 callersFunctionrel_logits_1d

Compute relative logits along one dimension As per: https://gist.github.com/aravindsrinivas/56359b79f0ce4449bcb04ab4b56a57a2 Originally from

src/train_acdc/lib/models_timm/layers/halo_attn.py:30

↓ 2 callersMethodreset_classifier

(self, num_classes, global_pool='avg')

src/train_acdc/lib/models_timm/dla.py:341

↓ 2 callersMethodresize_mat

(self, x, t: int)

src/train_acdc/lib/models_timm/layers/non_local_attn.py:85

↓ 2 callersFunctionresnet26d

Constructs a ResNet-26-D model.

src/train_acdc/lib/models_timm/resnet.py:809

↓ 2 callersFunctionresnet50d

Constructs a ResNet-50-D model.

src/train_acdc/lib/models_timm/resnet.py:825

↓ 2 callersMethodrgb_loader

(self, path)

src/train_acdc/utils/dataloader.py:94

↓ 2 callersMethodrgb_loader

(self, path)

src/train_synase/utils/dataloader.py:94

↓ 2 callersFunctionrun_function

(start, end, functions)

src/train_acdc/lib/models_timm/helpers.py:766

↓ 2 callersMethodstep

(self)

src/train_synase/utils/misc.py:110

↓ 2 callersMethodtrain

(self, mode=True)

src/train_acdc/lib/models_timm/levit.py:267

↓ 2 callersMethodupdate

(self, value, n=1)

src/train_acdc/levit/utils.py:31

↓ 2 callersMethodupdate

(self, value, n=1)

src/train_synase/levit/utils.py:31

↓ 2 callersMethodupdate_input_size

Method updates the image resolution to be processed and window size and so the pair-wise relative positions. Args: new_window_siz

src/train_acdc/lib/models_timm/swin_transformer_v2_cr.py:717

↓ 2 callersFunctionwindow_partition

Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size, C)

src/train_acdc/network/swin_transformer_unet_skip_expand_decoder_sys.py:27

↓ 2 callersFunctionwindow_partition

(x, window_size: List[int])

src/train_acdc/lib/maxxvit_4out.py:1125

↓ 2 callersFunctionwindow_partition

Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size, C)

src/train_acdc/lib/models_timm/swin_transformer.py:101

↓ 2 callersFunctionwindow_partition

(x, window_size: List[int])

src/train_acdc/lib/models_timm/maxxvit.py:1125

↓ 2 callersFunctionwindow_partition

Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size, C)

src/train_acdc/lib/models_timm/swin_transformer_v2_cr.py:114

↓ 2 callersFunctionwindow_partition

Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size, C)

src/train_acdc/lib/models_timm/swin_transformer_v2.py:94

↓ 2 callersFunctionwindow_partition

Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size,

src/train_acdc/modelsHiFormer/utils.py:40

↓ 2 callersFunctionwindow_partition

Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size, C)

src/train_synase/networks/swin_transformer_unet_skip_expand_decoder_sys.py:27

↓ 2 callersFunctionwindow_partition

Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size,

src/train_synase/modelsHiFormer/utils.py:40

↓ 2 callersFunctionwindow_reverse

(windows, window_size: List[int], img_size: List[int])

src/train_acdc/lib/maxxvit_4out.py:1135

↓ 2 callersFunctionwindow_reverse

(windows, window_size: List[int], img_size: List[int])

src/train_acdc/lib/models_timm/maxxvit.py:1135

↓ 1 callersFunctionBuild_LeViT_UNet_128s

(num_classes=4, distillation=True, pretrained=False, fuse=False)

src/train_synase/levit/LeViTUNet128s.py:31

↓ 1 callersMethod__init__

(self, num=40)

src/train_acdc/utils/utils.py:56

↓ 1 callersMethod__init__

(self, model, out_indices, out_map=None)

src/train_acdc/lib/models_timm/fx_features.py:69

↓ 1 callersMethod__init__

( self, block_args, num_classes=1000, in_chans=3, stem_size=16, fix_stem=False, num_features=1280,

src/train_acdc/lib/models_timm/mobilenetv3.py:125

↓ 1 callersMethod__init__

( self, in_chans=3, num_classes=1000, global_pool='avg', output_stride=32, initial_chs

src/train_acdc/lib/models_timm/rexnet.py:147

↓ 1 callersMethod__init__

(self, fn)

src/train_acdc/lib/models_timm/convmixer.py:32

↓ 1 callersMethod__init__

( self, inplanes, planes, stride=1, downsample=None, cardinality=1, base_width=64, sk_

src/train_acdc/lib/models_timm/sknet.py:49

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