Functions — github.com/SLDGroup/MERIT

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Functions932 in github.com/SLDGroup/MERIT

⨍ Functions 932◇ Types & classes 209

Method__init__

( self, dim, dim_out=None, feat_size=None, stride=1, num_heads=4, dim_head=16, r=9, qk

lib/models_timm/layers/lambda_layer.py:67

Method__init__

( self, channels, rd_ratio=1./16, rd_channels=None, rd_divisor=1, act_layer=nn.ReLU, g

lib/models_timm/layers/cbam.py:22

Method__init__

( self, channels, rd_ratio=1./16, rd_channels=None, rd_divisor=1, act_layer=nn.ReLU, g

lib/models_timm/layers/cbam.py:42

Method__init__

(self, kernel_size=7, gate_layer='sigmoid')

lib/models_timm/layers/cbam.py:57

Method__init__

(self, kernel_size=7, gate_layer='sigmoid')

lib/models_timm/layers/cbam.py:71

Method__init__

( self, channels, rd_ratio=1./16, rd_channels=None, rd_divisor=1, spatial_kernel_size=

lib/models_timm/layers/cbam.py:99

Method__init__

(self, num_features, apply_act=True, momentum=0.1, eps=1e-5, **_)

lib/models_timm/layers/evo_norm.py:139

Method__init__

(self, num_features, apply_act=True, momentum=0.1, eps=1e-5, **_)

lib/models_timm/layers/evo_norm.py:174

Method__init__

(self, num_features, groups=32, group_size=None, apply_act=True, eps=1e-5, **_)

lib/models_timm/layers/evo_norm.py:209

Method__init__

(self, num_features, groups=32, group_size=None, apply_act=True, eps=1e-3, **_)

lib/models_timm/layers/evo_norm.py:240

Method__init__

( self, num_features, groups=32, group_size=None, apply_act=True, act_layer=None, eps=

lib/models_timm/layers/evo_norm.py:257

Method__init__

( self, num_features, groups=32, group_size=None, apply_act=True, act_layer=None, eps=

lib/models_timm/layers/evo_norm.py:292

Method__init__

( self, num_features, groups=32, group_size=None, apply_act=True, act_layer=None, eps=

lib/models_timm/layers/evo_norm.py:307

Method__init__

( self, num_features, groups=32, group_size=None, apply_act=True, act_layer=None, eps=

lib/models_timm/layers/evo_norm.py:341

Method__init__

(self, num_channels, **kwargs)

lib/models_timm/layers/norm.py:33

Method__init__

(self, num_channels, eps=1e-6, affine=True)

lib/models_timm/layers/norm.py:47

Method__init__

(self, num_channels, eps=1e-6, affine=True)

lib/models_timm/layers/norm.py:61

Method__init__

(self, num_channels, eps=1e-6)

lib/models_timm/layers/norm.py:108

Method__init__

(self, inplace: bool = False)

lib/models_timm/layers/activations.py:21

Method__init__

(self, inplace: bool = False)

lib/models_timm/layers/activations.py:52

Method__init__

(self, inplace: bool = False)

lib/models_timm/layers/activations.py:66

Method__init__

(self, inplace: bool = False)

lib/models_timm/layers/activations.py:80

Method__init__

(self, inplace: bool = False)

lib/models_timm/layers/activations.py:96

Method__init__

(self, inplace: bool = False)

lib/models_timm/layers/activations.py:116

Method__init__

(self, num_parameters: int = 1, init: float = 0.25, inplace: bool = False)

lib/models_timm/layers/activations.py:127

Method__init__

(self, inplace: bool = False)

lib/models_timm/layers/activations.py:141

Method__init__

(self, in_features, hidden_features=None, out_features=None, act_layer=nn.Sigmoid, bias=True, drop=0.)

lib/models_timm/layers/mlp.py:39

Method__init__

( self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, gate_

lib/models_timm/layers/mlp.py:72

Method__init__

( self, in_features, hidden_features=None, out_features=None, act_layer=nn.ReLU, norm_

lib/models_timm/layers/mlp.py:106

Method__init__

(self, dim, max_res=224, linear_bands: bool = False)

lib/models_timm/layers/pos_embed.py:196

Method__init__

(self, channels=None, kernel_size=3, gamma=2, beta=1, act_layer=None, gate_layer='sigmoid')

lib/models_timm/layers/eca.py:121

Method__init__

(self, channels, filt_size=3, stride=2)

lib/models_timm/layers/blur_pool.py:29

Method__init__

( self, in_channels, out_channels, kernel_size=1, stride=1, padding='', dilation=1, groups=1,

lib/models_timm/layers/conv_bn_act.py:59

Method__init__

(self, flatten=False)

lib/models_timm/layers/adaptive_avgmax_pool.py:53

Method__init__

(self, output_size=1)

lib/models_timm/layers/adaptive_avgmax_pool.py:71

Method__init__

(self, output_size=1, pool_type='fast', flatten=False)

lib/models_timm/layers/adaptive_avgmax_pool.py:82

Method__init__

( self, num_features, eps=1e-5, momentum=0.1, affi

lib/models_timm/layers/norm_act.py:33

Method__init__

( self, normalization_shape: Union[int, List[int], torch.Size], eps=1e-5, affine=True,

lib/models_timm/layers/norm_act.py:206

Method__init__

( self, num_channels, eps=1e-5, affine=True, apply_act=True, act_layer=nn.ReLU, inplac

lib/models_timm/layers/norm_act.py:230

Method__init__

(self, radix, cardinality)

lib/models_timm/layers/split_attn.py:17

Method__init__

(self, kernel_size=3, stride=1, padding=0, same=False)

lib/models_timm/layers/median_pool.py:18

Method__init__

Args: block_size (int): block size win_size (int): neighbourhood window size dim_head (int): attention he

lib/models_timm/layers/halo_attn.py:67

Method__init__

(self, in_channels, out_channels, kernel_size=3, stride=1, padding='', dilation=1, groups=1,

lib/models_timm/layers/cond_conv2d.py:43

Method__init__

(self, num_features, apply_act=True, act_layer=nn.ReLU, inplace=None, rms=True, eps=1e-5, **_)

lib/models_timm/layers/filter_response_norm.py:46

Method__init__

( self, img_size=224, patch_size=16, in_chans=3, e

lib/models_timm/layers/patch_embed.py:18

Method__init__

(self, no_jit=False)

lib/models_timm/layers/space_to_depth.py:31

Method__init__

(self, block_size)

lib/models_timm/layers/space_to_depth.py:44

Method__init__

Selective Kernel Attention Module Selective Kernel attention mechanism factored out into its own module.

lib/models_timm/layers/selective_kernel.py:23

Method__init__

(self, in_channels, out_channels, kernel_size=3, stride=1, padding='', dilation=1, depthwise=

lib/models_timm/layers/mixed_conv2d.py:26

Method__init__

(self, base, original_pool=7)

lib/models_timm/layers/test_time_pool.py:17

Method__init__

(self, num_features, eps=1e-5, momentum=0.1, affine=True, track_running_stats=True, num_split

lib/models_timm/layers/split_batchnorm.py:20

Method__len__

(self)

utils/dataset_ACDC.py:58

Method__len__

(self)

utils/dataset_synapse.py:58

Method__len__

(self)

lib/models_timm/features.py:80

Method__post_init__

(self)

lib/maxxvit_4out.py:182

Method__post_init__

(self)

lib/maxxvit_4out.py:213

Method__post_init__

(self)

lib/models_timm/maxxvit.py:181

Method__post_init__

(self)

lib/models_timm/maxxvit.py:212

Method__repr__

(self)

lib/models_timm/layers/adaptive_avgmax_pool.py:114

Method__setstate__

(self, state)

lib/models_timm/layers/ml_decoder.py:56

Method_collect_output_hook

(self, hook_id, *args)

lib/models_timm/features.py:109

Function_float_to_int

Symbolic tracing helper to substitute for inbuilt `int`. Hint: Inbuilt `int` can't accept an argument of type `Proxy`

lib/models_timm/layers/trace_utils.py:8

Function_init_conv

(module, name, scheme='')

lib/maxxvit_4out.py:927

Function_init_conv

(module, name, scheme='')

lib/models_timm/maxxvit.py:926

Function_init_transformer

(module, name, scheme='')

lib/maxxvit_4out.py:838

Function_init_transformer

(module, name, scheme='')

lib/models_timm/maxxvit.py:837

Function_init_weights

(module, name=None, head_init_scale=1.0)

lib/models_timm/convnext.py:416

Function_init_weights

Mixer weight initialization (trying to match Flax defaults)

lib/models_timm/mlp_mixer.py:329

Method_init_weights

(self, module, name, scheme='')

lib/maxxvit_4out.py:1673

Method_init_weights

(self, module, name, scheme='')

lib/models_timm/maxxvit.py:1667

Function_layer_norm_cf_sqm

(x: torch.Tensor, weight: torch.Tensor, bias: torch.Tensor, eps: float)

lib/models_timm/layers/norm.py:91

Function_natural_key

(string_)

lib/models_timm/registry.py:54

Functionadd_ml_decoder_head

(model)

lib/models_timm/layers/ml_decoder.py:9

Functionadjust_lr

(optimizer, init_lr, epoch, decay_rate=0.1, decay_epoch=30)

utils/utils.py:46

Functionapply_rot_embed_list

(x: List[torch.Tensor], sin_emb, cos_emb)

lib/models_timm/layers/pos_embed.py:152

Functionapply_rot_embed_split

(x: torch.Tensor, emb)

lib/models_timm/layers/pos_embed.py:158

Functionapply_test_time_pool

(model, config, use_test_size=False)

lib/models_timm/layers/test_time_pool.py:39

Functionavg_pool2d_same

(x, kernel_size: List[int], stride: List[int], padding: List[int] = (0, 0), ceil_mode: boo

lib/models_timm/layers/pool2d_same.py:14

Methodbackward

(ctx, grad_output)

lib/models_timm/layers/activations_me.py:43

Methodbackward

(ctx, grad_output)

lib/models_timm/layers/activations_me.py:117

Methodbackward

(ctx, grad_output)

lib/models_timm/layers/activations_me.py:154

Methodbackward

(ctx, grad_output)

lib/models_timm/layers/activations_me.py:201

Functionbuild_sincos2d_pos_embed

Args: feat_shape: dim: temperature: reverse_coord: stack grid order W, H instead of H, W interleave_sin_

lib/models_timm/layers/pos_embed.py:33

Methodchannels

feature channels accessor

lib/models_timm/features.py:62

Functioncheckpoint_filter_fn

(state_dict, model)

lib/models_timm/levit.py:571

Functioncheckpoint_filter_fn

Remap FB checkpoints -> timm

lib/models_timm/convnext.py:429

Functioncheckpoint_filter_fn

Remap checkpoints if needed

lib/models_timm/mlp_mixer.py:363

Functionclip_gradient

For calibrating misalignment gradient via cliping gradient technique :param optimizer: :param grad_clip: :return:

utils/utils.py:33

Functioncoatnet_0_224

(pretrained=False, **kwargs)

lib/maxxvit_4out.py:1815

Functioncoatnet_0_224

(pretrained=False, **kwargs)

lib/models_timm/maxxvit.py:1797

Functioncoatnet_0_rw_224

(pretrained=False, **kwargs)

lib/maxxvit_4out.py:1755

Functioncoatnet_0_rw_224

(pretrained=False, **kwargs)

lib/models_timm/maxxvit.py:1737

Functioncoatnet_1_224

(pretrained=False, **kwargs)

lib/maxxvit_4out.py:1820

Functioncoatnet_1_224

(pretrained=False, **kwargs)

lib/models_timm/maxxvit.py:1802

Functioncoatnet_1_rw_224

(pretrained=False, **kwargs)

lib/maxxvit_4out.py:1760

Functioncoatnet_1_rw_224

(pretrained=False, **kwargs)

lib/models_timm/maxxvit.py:1742

Functioncoatnet_2_224

(pretrained=False, **kwargs)

lib/maxxvit_4out.py:1825

Functioncoatnet_2_224

(pretrained=False, **kwargs)

lib/models_timm/maxxvit.py:1807

Functioncoatnet_2_rw_224

(pretrained=False, **kwargs)

lib/maxxvit_4out.py:1765

Functioncoatnet_2_rw_224

(pretrained=False, **kwargs)

lib/models_timm/maxxvit.py:1747

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