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Functions73 in github.com/cewang-sysu/DuDoTrans

⨍ Functions 73◇ Types & classes 23
↓ 10 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.)
network_swinir.py:15
↓ 6 callersMethod__init__
(self, in_ch, out_ch, bilinear=True)
modules/Unet_parts.py:50
↓ 6 callersMethodflops
(self)
network_swinir.py:484
↓ 4 callersMethodforward_features
(self, x)
network_swinir.py:794
↓ 3 callersMethodcalculate_metric
(self, pred, gt)
main.py:118
↓ 2 callersMethod_radon_transform
(self, num_view=96, start_ang=0, end_ang=2*np.pi, num_detectors=800)
loaders/load_dataset.py:24
↓ 2 callersMethodcalculate_mask
(self, x_size)
network_swinir.py:216
↓ 2 callersMethodril
(self, img)
modules/reconstructor.py:28
↓ 2 callersFunctionwindow_partition
Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size, C)
network_swinir.py:33
↓ 1 callersMethod__init__
(self, dset, img_h=512, img_w=512)
modules/reconstructor.py:10
↓ 1 callersMethodcheck_image_size
(self, x)
network_swinir.py:787
↓ 1 callersMethodradon_senet_gt
(self, img)
modules/reconstructor.py:34
↓ 1 callersMethodsave_checkpoint
(self, num_epoch, state, num_iter)
main.py:112
↓ 1 callersMethodtrain
(self)
main.py:69
↓ 1 callersFunctionwindow_reverse
Args: windows: (num_windows*B, window_size, window_size, C) window_size (int): Window size H (int): Height of image
network_swinir.py:48
Method__getitem__
(self, index)
loaders/load_dataset.py:65
Method__init__
(self, dim, window_size, num_heads, qkv_bias=True, qk_scale=None, attn_drop=0., proj_drop=0.)
network_swinir.py:79
Method__init__
(self, dim, input_resolution, num_heads, window_size=7, shift_size=0, mlp_ratio=4., qkv_bias=
network_swinir.py:183
Method__init__
(self, input_resolution, dim, norm_layer=nn.LayerNorm)
network_swinir.py:309
Method__init__
(self, dim, input_resolution, depth, num_heads, window_size, mlp_ratio=4., qkv_bias=True, qk_
network_swinir.py:369
Method__init__
(self, dim, input_resolution, depth, num_heads, window_size, mlp_ratio=4., qkv_bias=True, qk_
network_swinir.py:442
Method__init__
(self, img_size=224, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None)
network_swinir.py:506
Method__init__
(self, img_size=224, patch_size=4, in_chans=3, embed_dim=96, norm_layer=None)
network_swinir.py:549
Method__init__
(self, scale, num_feat)
network_swinir.py:580
Method__init__
(self, scale, num_feat, num_out_ch, input_resolution=None)
network_swinir.py:604
Method__init__
(self, img_size=64, patch_size=1, in_chans=1, out_chans=1, embed_dim=96, depths=[6, 6, 6, 6],
network_swinir.py:646
Method__init__
(self, learning_rate=0.0001, is_restart=True, max_epoch=100, is_cuda=True, num_view=96)
main.py:18
Method__init__
(self)
modules/reconstructor.py:41
Method__init__
(self, n_channels, n_classes)
modules/unet_model.py:10
Method__init__
(self, in_ch, out_ch)
modules/Unet_parts.py:10
Method__init__
(self, in_ch, out_ch)
modules/Unet_parts.py:27
Method__init__
(self, in_ch, out_ch)
modules/Unet_parts.py:37
Method__init__
(self, in_ch, out_ch, bilinear=True,up_factor=2)
modules/Unet_parts.py:82
Method__init__
(self, in_ch, out_ch)
modules/Unet_parts.py:117
Method__init__
(self, in_ch, out_ch)
modules/Unet_parts.py:126
Method__init__
(self, base_path, poission_level=5e6, gaussian_level=0.05, num_view=96)
loaders/load_dataset.py:15
Method__len__
(self)
loaders/load_dataset.py:102
Method_init_weights
(self, m)
network_swinir.py:770
Methodextra_repr
(self)
network_swinir.py:147
Methodextra_repr
(self)
network_swinir.py:281
Methodextra_repr
(self)
network_swinir.py:339
Methodextra_repr
(self)
network_swinir.py:407
Methodflops
(self, N)
network_swinir.py:150
Methodflops
(self)
network_swinir.py:285
Methodflops
(self)
network_swinir.py:342
Methodflops
(self)
network_swinir.py:410
Methodflops
(self)
network_swinir.py:530
Methodflops
(self)
network_swinir.py:567
Methodflops
(self)
network_swinir.py:612
Methodflops
(self)
network_swinir.py:845
Methodforward
(self, x)
network_swinir.py:24
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
network_swinir.py:114
Methodforward
(self, x, x_size)
network_swinir.py:239
Methodforward
x: B, H*W, C
network_swinir.py:316
Methodforward
(self, x, x_size)
network_swinir.py:397
Methodforward
(self, x, x_size)
network_swinir.py:481
Methodforward
(self, x)
network_swinir.py:524
Methodforward
(self, x, x_size)
network_swinir.py:562
Methodforward
(self, x)
network_swinir.py:809
Methodforward
(self, img, img_gt, sinos)
modules/reconstructor.py:20
Methodforward
(self, pred, gt)
modules/reconstructor.py:44
Methodforward
(self, x_in)
modules/unet_model.py:24
Methodforward
(self, x)
modules/Unet_parts.py:21
Methodforward
(self, x)
modules/Unet_parts.py:31
Methodforward
(self, x)
modules/Unet_parts.py:44
Methodforward
(self, x1, x2)
modules/Unet_parts.py:63
Methodforward
(self, x1, x2)
modules/Unet_parts.py:96
Methodforward
(self, x)
modules/Unet_parts.py:121
Methodforward
(self, x)
modules/Unet_parts.py:135
Methodinference
(self)
main.py:130
Methodno_weight_decay
(self)
network_swinir.py:780
Methodno_weight_decay_keywords
(self)
network_swinir.py:784
Methodril
(self, num_view=96, start_ang=0, end_ang=2*np.pi, num_detectors=800)
loaders/load_dataset.py:45