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Functions266 in github.com/csguoh/AdaptIR

⨍ Functions 266◇ Types & classes 49
Method__init__
(self, optimizer, milestones, gamma=0.1, r
utils/schedulers.py:24
Method__init__
(self, optimizer, total_iter, last_epoch=-1)
utils/schedulers.py:86
Method__init__
(self, optimizer, periods, restart_weights=(1, ),
utils/schedulers.py:160
Method__init__
(self, optimizer, periods, restart_weights=(1, ),
utils/schedulers.py:207
Method__init__
Args: optimizer (Optimizer): Wrapped optimizer. warmup_epochs (int): Maximum number of iterations for linear warmup
utils/schedulers.py:270
Method__init__
(self, task_num=0, bar_width=50, start=True)
utils/common.py:265
Method__init__
(self, test=False)
utils/image_utils.py:15
Method__init__
(self, args)
utils/dataset_utils.py:311
Method__init__
(self, args)
utils/dataset_utils.py:377
Method__init__
(self, args)
utils/dataset_utils.py:437
Method__init__
(self)
utils/val_utils.py:10
Method__init__
(self)
utils/val_utils.py:79
Method__init__
(self, num_channels: int, eps: float = 1e-6)
net/ipt.py:21
Method__init__
( self, img_dim, patch_dim, num_channels, embeddin
net/ipt.py:251
Method__init__
(self, max_position_embeddings, embedding_dim, seq_length)
net/ipt.py:362
Method__init__
(self, encoder_layer, num_layers)
net/ipt.py:381
Method__init__
(self, d_model, nhead, dim_feedforward=2048, dropout=0.1, no_norm=False, activation="relu")
net/ipt.py:396
Method__init__
(self, decoder_layer, num_layers)
net/ipt.py:432
Method__init__
(self, d_model, nhead, dim_feedforward=2048, dropout=0.1, no_norm=False, activation="relu")
net/ipt.py:445
Method__init__
(self, d_model)
net/ipt.py:509
Method__init__
(self, in_chl, out_chl, down=False)
net/edt.py:39
Method__init__
(self, in_chl, out_chl)
net/edt.py:80
Method__init__
(self, in_chl, out_chl)
net/edt.py:110
Method__init__
(self, in_chl, out_chl)
net/edt.py:135
Method__init__
(self, dim, window_size, num_heads, qkv_bias=True, qk_scale=None, attn_drop=0., index=0)
net/edt.py:245
Method__init__
(self, dim, input_resolution, num_heads, window_size, shift_size, mlp_ratio=4., qkv_bias=True
net/edt.py:336
Method__init__
(self, dim, input_resolution, depth, num_heads, window_size, mlp_ratio=4., qkv_bias=True, qk_
net/edt.py:495
Method__init__
(self, dim, input_resolution, depth, num_heads, window_size, mlp_ratio=4., qkv_bias=True, qk_
net/edt.py:568
Method__init__
(self, img_size=224, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None)
net/edt.py:611
Method__init__
(self, img_size=224, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None)
net/edt.py:654
Method__init__
(self, scale, num_feat, input_resolution=None)
net/edt.py:685
Method__init__
(self, scale, num_feat, num_out_ch, input_resolution=None)
net/edt.py:722
Method__init__
(self, img_size=64, patch_size=1, embed_dim=96, depths=[6, 6, 6, 6], num_heads=[6, 6, 6, 6],
net/edt.py:766
Method__init__
(self, config)
net/edt.py:885
Method__init__
(self,d_model)
net/edt.py:1091
Method__init__
(self,d_model)
net/edt.py:1114
Method__init__
(self, d_model)
net/edt.py:1130
Method__init__
( self, rgb_range, rgb_mean=(0.4488, 0.4371, 0.4040), rgb_std=(1.0, 1.0, 1.0), sign=-1)
net/common.py:16
Method__init__
( self, conv, in_channels, out_channels, kernel_size, stride=1, bias=False, bn=True, act=nn.Re
net/common.py:28
Method__init__
(self, conv, scale, n_feats, bn=False, act=False, bias=True)
net/common.py:64
Method__len__
(self)
utils/dataset_utils.py:306
Method__len__
(self)
utils/dataset_utils.py:372
Method__len__
(self)
utils/dataset_utils.py:432
Method__len__
(self)
utils/dataset_utils.py:481
Method_add_gaussian_noise
(self, clean_patch)
utils/dataset_utils.py:385
Method_get_closed_form_lr
Called when epoch is passed as a param to the `step` function of the scheduler.
utils/schedulers.py:332
Method_init_weights
(self, m)
net/edt.py:837
Functionaccuracy
Computes the precision@k for the specified values of k
utils/val_utils.py:28
Functionaverage
assumes C x W x H [0..1] :param img_np_list: :return:
utils/image_io.py:360
Functionbgr2ycbcr
bgr version of rgb2ycbcr only_y: only return Y channel Input: uint8, [0, 255] float, [0, 1]
utils/val_utils.py:184
Functionbox
(x)
utils/imresize.py:216
Functioncalc_psnr
(sr, hr, scale=2, rgb_range=1.0, benchmark=True)
utils/common.py:131
Functioncalc_psnr
(sr, hr, scale=2, rgb_range=1.0, benchmark=True)
utils/val_utils.py:139
Functioncalculate_psnr_ssim
(img1, img2, to_y=True, bd=0)
utils/common.py:83
Methodconfigure_optimizers
(self)
train.py:71
Methodconfigure_optimizers
(self)
test.py:53
Functioncreate_augmentations
convention: original, left, upside-down, right, rot1, rot2, rot3 :param np_image: :return:
utils/image_io.py:197
Functioncreate_video_augmentations
convention: original, left, upside-down, right, rot1, rot2, rot3 :param np_video: :return:
utils/image_io.py:211
Functioncrop_np_image
(img_np, d=32)
utils/image_io.py:63
Functioncrop_patch
(im, pch_size)
utils/image_utils.py:49
Functioncubic
(x)
utils/imresize.py:202
Functiondefault_conv
(in_channels, out_channels, kernel_size, bias=True)
net/common.py:10
Methoddegrade
(self, clean_patch_1, clean_patch_2, degrade_type=None)
utils/degradation_utils.py:44
Methodextra_repr
(self)
net/edt.py:299
Methodextra_repr
(self)
net/edt.py:450
Methodextra_repr
(self)
net/edt.py:533
FunctionflipRotx8_forward
(model, inp)
utils/common.py:248
Methodflops
(self, x_size)
net/edt.py:66
Methodflops
(self, x_size)
net/edt.py:99
Methodflops
(self, x_size)
net/edt.py:125
Methodflops
(self, x_size)
net/edt.py:150
Methodflops
(self, x_size)
net/edt.py:302
Methodflops
(self)
net/edt.py:454
Methodflops
(self)
net/edt.py:536
Methodflops
(self)
net/edt.py:635
Methodflops
(self)
net/edt.py:672
Methodflops
(self)
net/edt.py:701
Methodflops
(self)
net/edt.py:732
Methodflops
(self)
net/edt.py:872
Functionfn
(step)
utils/schedulers.py:354
Methodforward
(self,x)
train.py:45
Methodforward
(self,x)
test.py:38
Methodforward
(self, x)
utils/image_utils.py:18
Methodforward
(self, x: torch.Tensor)
net/ipt.py:27
Methodforward
(self, x, de_id=None)
net/ipt.py:91
Methodforward
(self, x, query_idx, con=False)
net/ipt.py:319
Methodforward
(self, x, position_ids=None)
net/ipt.py:371
Methodforward
(self, src, pos=None)
net/ipt.py:387
Methodforward
(self, src, pos=None)
net/ipt.py:418
Methodforward
(self, tgt, memory, pos=None, query_pos=None)
net/ipt.py:437
Methodforward
(self, tgt, memory, pos=None, query_pos=None)
net/ipt.py:473
Methodforward
(self, x)
net/ipt.py:558
Methodforward
(self, x)
net/edt.py:54
Methodforward
(self, x)
net/edt.py:91
Methodforward
(self, x, skip)
net/edt.py:118
Methodforward
(self, x, skip)
net/edt.py:143
Methodforward
(self, x)
net/edt.py:170
Methodforward
Args: x: input features with shape of (num_windows*B, N, C) mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh
net/edt.py:258
Methodforward
(self, x, x_size)
net/edt.py:407
Methodforward
(self, x, x_size)
net/edt.py:523
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