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Functions932 in github.com/SLDGroup/MERIT

⨍ Functions 932◇ Types & classes 209
Method__init__
(self, dim, init_values=1e-5, inplace=False)
lib/maxxvit_4out.py:780
Method__init__
(self, dim, init_values=1e-5, inplace=False)
lib/maxxvit_4out.py:791
Method__init__
( self, dim: int, dim_out: int, pool_type: str = 'avg2',
lib/maxxvit_4out.py:809
Method__init__
( self, dim: int, dim_out: int, stride: int = 1, r
lib/maxxvit_4out.py:872
Method__init__
( self, in_chs: int, out_chs: int, stride: int = 1,
lib/maxxvit_4out.py:962
Method__init__
( self, in_chs: int, out_chs: Optional[int] = None, kernel_siz
lib/maxxvit_4out.py:1053
Method__init__
( self, dim: int, partition_type: str = 'block', cfg: MaxxVitT
lib/maxxvit_4out.py:1176
Method__init__
( self, dim: int, cfg: MaxxVitTransformerCfg = MaxxVitTransformerCfg(),
lib/maxxvit_4out.py:1239
Method__init__
( self, dim: int, partition_type: str = 'block', cfg: MaxxVitT
lib/maxxvit_4out.py:1347
Method__init__
( self, dim: int, dim_out: int, stride: int = 1, c
lib/maxxvit_4out.py:1409
Method__init__
( self, dim, dim_out, stride=1, num_conv=2,
lib/maxxvit_4out.py:1453
Method__init__
( self, in_chs: int, out_chs: int, stride: int = 2,
lib/maxxvit_4out.py:1487
Method__init__
( self, cfg: MaxxVitCfg, img_size: Union[int, Tuple[int, int]] = 224,
lib/maxxvit_4out.py:1603
Method__init__
(self,ch_in,ch_out)
lib/decoders.py:7
Method__init__
(self,F_g,F_l,F_int)
lib/decoders.py:39
Method__init__
(self, in_planes, ratio=16)
lib/decoders.py:68
Method__init__
(self, kernel_size=7)
lib/decoders.py:91
Method__init__
(self, channels=[512,320,128,64])
lib/decoders.py:108
Method__init__
(self, channels=[512,320,128,64])
lib/decoders.py:189
Method__init__
(self, n_class=1, img_size=224)
lib/networks.py:109
Method__init__
(self, n_class=1, img_size=224, model_scale='small')
lib/networks.py:165
Method__init__
(self, n_class=1, img_size=224)
lib/networks.py:222
Method__init__
(self, n_class=1, img_size=224, model_scale='small', decoder_aggregation='additive')
lib/networks.py:288
Method__init__
(self, n_class=1, img_size=224)
lib/networks.py:352
Method__init__
(self, n_class=1, img_size_s1=(256,256), img_size_s2=(224,224), model_scale='small', decoder_aggregation='addi
lib/networks.py:425
Method__init__
(self, n_class=1, img_size_s1=(256,256), img_size_s2=(224,224), model_scale='small', decoder_aggregation='addi
lib/networks.py:515
Method__init__
(self, n_class=1, img_size_s1=(256,256), img_size_s2=(224,224), decoder_aggregation='additive', interpolation=
lib/networks.py:633
Method__init__
(self, n_class=1, img_size_s1=(256,256), img_size_s2=(224,224), decoder_aggregation='additive', interpolation=
lib/networks.py:728
Method__init__
( self, in_chs, out_chs, kernel_size=1, stride=1, pad=0, dilation=1, groups=1, bn_weig
lib/models_timm/levit.py:128
Method__init__
(self, in_features, out_features, bn_weight_init=1, resolution=-100000)
lib/models_timm/levit.py:152
Method__init__
(self, in_features, out_features, bias=True, std=0.02)
lib/models_timm/levit.py:176
Method__init__
(self, m, drop)
lib/models_timm/levit.py:213
Method__init__
(self, stride, resolution)
lib/models_timm/levit.py:227
Method__init__
( self, dim, key_dim, num_heads=8, attn_ratio=4, act_layer=None, resolution=14, use_conv=False)
lib/models_timm/levit.py:241
Method__init__
( self, in_dim, out_dim, key_dim, num_heads=8, attn_ratio=2, act_layer=None, stride=2,
lib/models_timm/levit.py:310
Method__init__
(self, *args, **kwargs)
lib/models_timm/levit.py:539
Method__init__
(self, model, return_nodes: Union[Dict[str, str], List[str]], squeeze_out: bool = True)
lib/models_timm/fx_features.py:97
Method__init__
(self, hooks, named_modules, out_map=None, default_hook_type='forward')
lib/models_timm/features.py:92
Method__init__
( self, model, out_indices=(0, 1, 2, 3, 4), out_map=None, feature_concat=False, flatte
lib/models_timm/features.py:177
Method__init__
( self, model, out_indices=(0, 1, 2, 3, 4), out_map=None, feature_concat=False, flatte
lib/models_timm/features.py:224
Method__init__
( self, model, out_indices=(0, 1, 2, 3, 4), out_map=None, out_as_dict=False, no_rewrit
lib/models_timm/features.py:248
Method__init__
( self, in_chs, out_chs=None, kernel_size=7, strid
lib/models_timm/convnext.py:145
Method__init__
( self, in_chs, out_chs, kernel_size=7, stride=2,
lib/models_timm/convnext.py:195
Method__init__
( self, dim: int, dim_out: Optional[int] = None, dim_head: int
lib/models_timm/maxxvit.py:688
Method__init__
( self, dim: int, dim_out: Optional[int] = None, dim_head: int
lib/models_timm/maxxvit.py:733
Method__init__
(self, dim, init_values=1e-5, inplace=False)
lib/models_timm/maxxvit.py:779
Method__init__
(self, dim, init_values=1e-5, inplace=False)
lib/models_timm/maxxvit.py:790
Method__init__
( self, dim: int, dim_out: int, pool_type: str = 'avg2',
lib/models_timm/maxxvit.py:808
Method__init__
( self, dim: int, dim_out: int, stride: int = 1, r
lib/models_timm/maxxvit.py:871
Method__init__
( self, in_chs: int, out_chs: int, stride: int = 1,
lib/models_timm/maxxvit.py:961
Method__init__
( self, in_chs: int, out_chs: Optional[int] = None, kernel_siz
lib/models_timm/maxxvit.py:1052
Method__init__
( self, dim: int, partition_type: str = 'block', cfg: MaxxVitT
lib/models_timm/maxxvit.py:1175
Method__init__
( self, dim: int, cfg: MaxxVitTransformerCfg = MaxxVitTransformerCfg(),
lib/models_timm/maxxvit.py:1238
Method__init__
( self, dim: int, partition_type: str = 'block', cfg: MaxxVitT
lib/models_timm/maxxvit.py:1346
Method__init__
( self, dim: int, dim_out: int, stride: int = 1, c
lib/models_timm/maxxvit.py:1408
Method__init__
( self, dim, dim_out, stride=1, num_conv=2,
lib/models_timm/maxxvit.py:1452
Method__init__
( self, in_chs: int, out_chs: int, stride: int = 2,
lib/models_timm/maxxvit.py:1486
Method__init__
( self, cfg: MaxxVitCfg, img_size: Union[int, Tuple[int, int]] = 224,
lib/models_timm/maxxvit.py:1602
Method__init__
(self, window_size, num_heads, prefix_tokens=0)
lib/models_timm/vision_transformer_relpos.py:207
Method__init__
(self, dim, num_heads=8, qkv_bias=False, rel_pos_cls=None, attn_drop=0., proj_drop=0.)
lib/models_timm/vision_transformer_relpos.py:238
Method__init__
(self, dim, init_values=1e-5, inplace=False)
lib/models_timm/vision_transformer_relpos.py:271
Method__init__
( self, dim, num_heads, mlp_ratio=4., qkv_bias=False, rel_pos_cls=None, init_values=None,
lib/models_timm/vision_transformer_relpos.py:282
Method__init__
( self, dim, num_heads, mlp_ratio=4., qkv_bias=False, rel_pos_cls=None, init_values=None,
lib/models_timm/vision_transformer_relpos.py:306
Method__init__
Args: img_size (int, tuple): input image size patch_size (int, tuple): patch size in_chans (int): number
lib/models_timm/vision_transformer_relpos.py:345
Method__init__
( self, dim, seq_len, mlp_ratio=(0.5, 4.0), mlp_layer=Mlp, norm_layer=partial(nn.Layer
lib/models_timm/mlp_mixer.py:150
Method__init__
( self, dim, seq_len, mlp_ratio=4, mlp_layer=Mlp, norm_layer=Affine, act_layer=nn.GELU
lib/models_timm/mlp_mixer.py:182
Method__init__
(self, dim, seq_len, norm_layer=nn.LayerNorm)
lib/models_timm/mlp_mixer.py:206
Method__init__
( self, dim, seq_len, mlp_ratio=4, mlp_layer=GatedMlp, norm_layer=partial(nn.LayerNorm
lib/models_timm/mlp_mixer.py:229
Method__init__
( self, num_classes=1000, img_size=224, in_chans=3,
lib/models_timm/mlp_mixer.py:246
Method__init__
( self, drop_prob: float = 0.1, block_size: int = 7, gamma_sca
lib/models_timm/layers/drop.py:108
Method__init__
(self, mode: bool)
lib/models_timm/layers/config.py:30
Method__init__
(self, mode: bool)
lib/models_timm/layers/config.py:49
Method__init__
(self, mode: bool)
lib/models_timm/layers/config.py:68
Method__init__
( self, scriptable: Optional[bool] = None, exportable: Optional[bool] = No
lib/models_timm/layers/config.py:86
Method__init__
(self, in_channels, block_size, groups, act_layer=nn.ReLU, norm_layer=nn.BatchNorm2d)
lib/models_timm/layers/non_local_attn.py:74
Method__init__
( self, in_channels, block_size=7, groups=2, rd_ratio=0.25, rd_channels=None, rd_divisor=8,
lib/models_timm/layers/non_local_attn.py:129
Method__init__
( self, in_channel, out_channels, kernel_size, stride=1, padding='SAME', dilation=1, g
lib/models_timm/layers/std_conv.py:56
Method__init__
( self, in_channels, out_channels, kernel_size, stride=1, padding=None, dilation=1, gr
lib/models_timm/layers/std_conv.py:85
Method__init__
( self, in_channels, out_channels, kernel_size, stride=1, padding='SAME', dilation=1,
lib/models_timm/layers/std_conv.py:114
Method__init__
( self, dim, dim_out=None, feat_size=None, stride=1, num_heads=4, dim_head=None, qk_ra
lib/models_timm/layers/bottleneck_attn.py:106
Method__init__
( self, in_features: int, out_features: int = None, embed_dim:
lib/models_timm/layers/attention_pool2d.py:30
Method__init__
(self, kernel_size: int, stride=None, padding=0, dilation=1, ceil_mode=False)
lib/models_timm/layers/pool2d_same.py:45
Method__init__
(self, inplace: bool = False)
lib/models_timm/layers/activations_jit.py:33
Method__init__
(self, inplace: bool = False)
lib/models_timm/layers/activations_jit.py:55
Method__init__
(self, inplace: bool = False)
lib/models_timm/layers/activations_jit.py:69
Method__init__
(self, inplace: bool = False)
lib/models_timm/layers/activations_jit.py:86
Method__init__
(self, num_features, eps=1e-5, momentum=0.1, affine=True, apply_act=True, act_layer="leaky_re
lib/models_timm/layers/inplace_abn.py:40
Method__init__
(self, in_chs, num_classes, pool_type='avg', drop_rate=0., use_conv=False)
lib/models_timm/layers/classifier.py:41
Method__init__
(self, channels, add_maxpool=False, gate_layer='hard_sigmoid', **_)
lib/models_timm/layers/squeeze_excite.py:59
Method__init__
( self, channels, rd_ratio=1. / 16, rd_channels=None, rd_divisor=8, bias=True, act_lay
lib/models_timm/layers/squeeze_excite.py:86
Method__init__
(self, inplace: bool = False)
lib/models_timm/layers/activations_me.py:53
Method__init__
(self, inplace: bool = False)
lib/models_timm/layers/activations_me.py:127
Method__init__
(self, inplace: bool = False)
lib/models_timm/layers/activations_me.py:171
Method__init__
(self, inplace: bool = False)
lib/models_timm/layers/activations_me.py:211
Method__init__
(self, d_model, nhead=8, dim_feedforward=2048, dropout=0.1, activation="relu", layer_norm_eps
lib/models_timm/layers/ml_decoder.py:36
Method__init__
(self, num_classes, num_of_groups=-1, decoder_embedding=768, initial_num_features=2048)
lib/models_timm/layers/ml_decoder.py:104
Method__init__
(self, channels, use_attn=True, fuse_add=False, fuse_scale=True, init_last_zero=False, rd_rat
lib/models_timm/layers/global_context.py:21
Method__init__
(self, in_channels, out_channels, kernel_size=3, stride=1, dilation=1, padding='', bias=False,
lib/models_timm/layers/separable_conv.py:17
Method__init__
(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bia
lib/models_timm/layers/conv2d_same.py:24
Method__init__
( self, channels, feat_size=None, extra_params=False, extent=0, use_mlp=True, rd_ratio
lib/models_timm/layers/gather_excite.py:28
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