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⨍ Functions 211◇ Types & classes 49

(self, dataset, scale_min=1, scale_max=None, augment=False, sample_q=None)

datasets/wrappers.py:13

(self, normalized_shape)

models/cross_att.py:17

(self, normalized_shape)

models/cross_att.py:34

(self, dim, LayerNorm_type)

models/cross_att.py:54

(self, in_channels, out_channels, kernel_size, padding, stride, bias=True)

models/cross_att.py:66

(self, dim, num_heads, attn_drop=0., proj_drop=0.)

models/cross_att.py:94

( self, dim, num_heads=12, qk_scale=None, attn_dro

models/cross_att.py:127

( self, dim, num_heads, mlp_ratio=4.0, qk_scale=None, drop=0.0

models/cross_att.py:169

( self, dim, num_heads )

models/cross_att.py:210

( self, in_dim=0, out_dim=0, hidden_list = [], bias=True, bn=False, act=nn.ReLU(True),

models/linear.py:24

(self, conv, scale, n_feats, bn=True, act=False, bias=True)

models/resencoder.py:45

(self, args, conv=default_conv)

models/resencoder.py:75

models/resencoder.py:141

(self, encoder_spec, no_imnet)

models/lccd.py:13

(self, in_dim, out_dim, hidden_list)

models/mlp.py:9

(self, in_dim, out_dim, n_resblocks, conv=default_conv)

models/fusionnet.py:35

(self, inplanes, planes, stride=1)

CLIP/model.py:13

(self, spacial_dim: int, embed_dim: int, num_heads: int, output_dim: int = None)

CLIP/model.py:57

(self, layers, output_dim, heads, input_resolution=224, width=64)

CLIP/model.py:101

(self, d_model: int, n_head: int, attn_mask: torch.Tensor = None)

CLIP/model.py:176

(self, width: int, layers: int, heads: int, attn_mask: torch.Tensor = None)

CLIP/model.py:200

(self, input_resolution: int, patch_size: int, width: int, layers: int, heads: int, output_dim: int)

CLIP/model.py:211

CLIP_training/dataloader/dataset.py:52

datasets/image_folder.py:59

datasets/image_folder.py:94

datasets/wrappers.py:20

utils_clip/logger.py:75

CLIP_training/utils/logger.py:75

Functioncalc_psnr

Functioncompute_num_params

(model, text=False)

Functiondecorator

datasets/datasets.py:8

Functiondecorator

models/models.py:8

Functiondefault_conv

(in_channels, out_channels, kernel_size, bias=True)

models/resencoder.py:14

Functiondefault_conv

(in_channels, out_channels, kernel_size, bias=True)

models/fusionnet.py:4

CLIP_training/model/model.py:341

CLIP/model.py:341

Emit a record. If the stream was not opened because 'delay' was specified in the constructor, open it before calling the supe

utils_clip/logger.py:64

Emit a record. If the stream was not opened because 'delay' was specified in the constructor, open it before calling the supe

CLIP_training/utils/logger.py:64

Functionensure_dir

utils_clip/util.py:54

Functionensure_dir

CLIP_training/utils/util.py:54

Functioneval_psnr

(loader, model)

Functionfind_file_path_in_yaml

utils_clip/util.py:42

Functionfind_file_path_in_yaml

CLIP_training/utils/util.py:42

(self, x: torch.Tensor)

CLIP_training/model/model.py:40

CLIP_training/model/model.py:66

CLIP_training/model/model.py:135

(self, x: torch.Tensor)

CLIP_training/model/model.py:164

(self, x: torch.Tensor)

CLIP_training/model/model.py:171

(self, x: torch.Tensor)

CLIP_training/model/model.py:193

(self, x: torch.Tensor)

CLIP_training/model/model.py:206

(self, x: torch.Tensor)

CLIP_training/model/model.py:227

models/cross_att.py:28

models/cross_att.py:46

models/cross_att.py:61

models/cross_att.py:72

models/cross_att.py:86

Args: x: input features with shape of (num_windows*B, N, C) mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh

models/cross_att.py:105

models/cross_att.py:150

models/cross_att.py:202

models/cross_att.py:227

models/linear.py:18

models/linear.py:39

models/resencoder.py:37

models/resencoder.py:112

models/resencoder.py:164

(self, src_lr, tgt_lr, coord_hr, prompt_src, prompt_tgt)

models/lccd.py:30

models/mlp.py:21

models/fusionnet.py:26

models/fusionnet.py:48

(self, x: torch.Tensor)

CLIP/model.py:40

CLIP/model.py:66

CLIP/model.py:135

(self, x: torch.Tensor)

CLIP/model.py:164

(self, x: torch.Tensor)

CLIP/model.py:171

(self, x: torch.Tensor)

CLIP/model.py:193

(self, x: torch.Tensor)

CLIP/model.py:206

(self, x: torch.Tensor)

CLIP/model.py:227

Functionget_cosine_schedule_with_warmup

Create a schedule with a learning rate that decreases following the values of the cosine function between the initial lr set in the optimizer

utils_clip/custom_schedulers.py:11

Functionget_cosine_with_hard_restarts_schedule_with_warmup

Create a schedule with a learning rate that decreases following the values of the cosine function between the initial lr set in the optimizer

utils_clip/custom_schedulers.py:46

Functionget_cosine_with_hard_restarts_schedule_with_warmup

Create a schedule with a learning rate that decreases following the values of the cosine function between the initial lr set in the optimizer

CLIP_training/utils/custom_schedulers.py:46

Functionload_from_yaml_file

utils_clip/util.py:37

Functionload_from_yaml_file

CLIP_training/utils/util.py:37

Methodload_state_dict

(self, state_dict, strict=True)

models/resencoder.py:170

Functionlr_lambda

utils_clip/custom_schedulers.py:36

Functionlr_lambda

CLIP_training/utils/custom_schedulers.py:36

(dataset_spec, args=None)

datasets/datasets.py:14

(model_spec, args=None, load_sd=False)

models/models.py:14

Functionmake_coord

Make coordinates at grid centers.

Functionmake_edsr

(n_resblocks=24, n_feats=256, outdim=768, res_scale=0.1, scale=1, no_upsampling=True)

models/resencoder.py:206

Functionmake_edsr_baseline

(n_resblocks=16, n_feats=64, outdim=128, res_scale=1, scale=1, no_upsampling=True)

models/resencoder.py:191

Functionmake_optimizer_D

(param_list, optimizer_spec, load_sd=False)

Functionmake_optimizer_G

(param_list, optimizer_spec, load_sd=False)

utils_clip/util.py:15

Functionpercentile_clip

(input_tensor, reference_tensor=None, p_min=0.01, p_max=99.9, strictlyPositive=True)

Functionrandom_selection

Functionread_json

utils_clip/util.py:59

Functionread_json

CLIP_training/utils/util.py:59

Functionregister

datasets/datasets.py:7

Functionregister

models/models.py:7

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