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Functions470 in github.com/Lizhe1228/MambaDFuse

⨍ Functions 470◇ Types & classes 81

models/loss_med.py:75

models/loss_med.py:84

(self, upscale_factor)

models/basicblock.py:141

(self, num_features, num_classes)

models/basicblock.py:157

(self, submodule)

models/basicblock.py:176

(self, submodule)

models/basicblock.py:192

(self, in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='CRC', negative_sl

models/basicblock.py:212

(self, in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='CL', d_rate=0.25,

models/basicblock.py:246

(self, in_channels=50, out_channels=50, kernel_size=3, stride=1, padding=1, bias=True, mode='CL', d_rate=0.5,

models/basicblock.py:299

(self, channel=64, reduction=16)

models/basicblock.py:334

(self, in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='CRC', reduction=1

models/basicblock.py:355

(self, in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='CRC', reduction=1

models/basicblock.py:374

(self, nc=64, gc=32, kernel_size=3, stride=1, padding=1, bias=True, mode='CR', negative_slope=0.2)

models/basicblock.py:394

(self, nc=64, gc=32, kernel_size=3, stride=1, padding=1, bias=True, mode='CR', negative_slope=0.2)

models/basicblock.py:417

(self, nc=64, kernel_size=1, stride=1, padding=0, bias=True, act_mode='B', downsample=False, downsample_mode='

models/basicblock.py:544

(self, feature_layer=34, use_bn=False, use_input_norm=True,

models/network_feature.py:17

(self, window_size=11, size_average=True)

models/loss_ssim.py:66

models/loss_vif.py:15

models/loss_vif.py:44

models/loss_vif.py:56

models/loss_vif.py:74

models/loss_vif.py:84

(self, channel)

models/refine.py:14

(self, channel, reduction)

models/refine.py:31

(self, channel, reduction)

models/refine.py:54

(self, nc, shiftPixel=1)

models/refine.py:99

(self, nc, out, shiftPixel=1, gc=1)

models/refine.py:149

(self, n_feat, out_channel)

models/refine.py:273

(self, n_feat, out_channel)

models/refine.py:291

(self, in_channels, panchannels, n_feat)

models/refine.py:311

(self, channel, negative_slope=0.2, scale=2 ** 0.5)

models/op/fused_act.py:76

data/dataset_wogt.py:106

Method__missing__

utils/utils_mat.py:54

Method__missing__

utils/utils_option.py:243

models/basicblock.py:201

Method_init_weights

models/network.py:390

Functionaccumulate_flops

utils/utils_modelsummary.py:125

Functionadd_activation_counter_hook_function

utils/utils_modelsummary.py:398

Functionadd_activation_counter_variable_or_reset

utils/utils_modelsummary.py:415

Kai Zhang, 11/Jan/2019.

utils/utils_bnorm.py:69

Functionadd_extra_repr

utils/utils_modelsummary.py:140

Functionadd_flops_counter_hook_function

utils/utils_modelsummary.py:230

Functionadd_flops_counter_variable_or_reset

utils/utils_modelsummary.py:255

Functionall_gather

utils/utils_dist.py:143

Methodallocate_inference_cache

(self, batch_size, max_seqlen, dtype=None, **kwargs)

mamba_simple.py:591

Methodallocate_inference_cache

(self, batch_size, max_seqlen, dtype=None, **kwargs)

mamba_simple.py:970

Functionaugment_img_contrast

utils/utils_image.py:405

Functionaugment_img_np3

utils/utils_image.py:471

Functionaugment_img_tensor

Kai Zhang (github: https://github.com/cszn)

utils/utils_image.py:452

Functionaugment_img_tensor4

Kai Zhang (github: https://github.com/cszn)

utils/utils_image.py:431

Functionaugment_imgs

(img_list, hflip=True, rot=True)

utils/utils_image.py:499

(ctx, gradgrad_input, gradgrad_bias)

models/op/fused_act.py:44

(ctx, grad_output)

models/op/fused_act.py:65

(ctx, gradgrad_input)

models/op/upfirdn2d.py:63

Functionbn_flops_counter_hook

(module, input, output)

utils/utils_modelsummary.py:315

utils/utils_sisr.py:364

utils/utils_sisr.py:383

Functioncal_pca_matrix

(path='PCA_matrix.mat', ksize=15, l_max=12.0, dim_pca=15, num_samples=500)

utils/utils_sisr.py:100

Functioncalculate_psnr

(img1, img2, border=0)

utils/utils_image.py:652

Functioncalculate_psnrb

Calculate PSNR-B (Peak Signal-to-Noise Ratio). Ref: Quality assessment of deblocked images, for JPEG image deblocking evaluation # https://git

utils/utils_image.py:763

Functioncalculate_ssim

calculate SSIM the same outputs as MATLAB's img1, img2: [0, 255]

utils/utils_image.py:673

# complex's conjugation t: NxCxHxWx2 output: NxCxHxWx2

utils/utils_sisr.py:398

Functionchannel_convert

(in_c, tar_type, img_list)

utils/utils_image.py:628

Functioncircular_pad

# x[N, 1, W, H] -> x[N, 1, W + 2 pad, H + 2 pad] (pariodic padding)

utils/utils_sisr.py:503

Functioncompute_average_activation_cost

A method that will be available after add_activation_counting_methods() is called on a desired net object. Returns current mean activati

utils/utils_modelsummary.py:345

Functioncompute_average_flops_cost

A method that will be available after add_flops_counting_methods() is called on a desired net object. Returns current mean flops consump

utils/utils_modelsummary.py:178

Functionconv_activation_counter_hook

Calculate the activations in the convolutional operation. Reference: Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, Piot

utils/utils_modelsummary.py:430

Functionconv_flops_counter_hook

(conv_module, input, output)

utils/utils_modelsummary.py:274

Methodcurrent_losses

models/model_base.py:57

Methodcurrent_results

(self, need_H=True)

models/model_plain.py:307

Methodcurrent_visuals

(self, need_H=False)

models/model_plain.py:295

Functiondconv_flops_counter_hook

(dconv_module, input, output)

utils/utils_modelsummary.py:461

Functiondefine_D

models/select_network.py:56

Functiondefine_F

(opt, use_bn=False)

models/select_network.py:123

Methoddefine_loss

models/model_base.py:32

Functiondel_extra_repr

utils/utils_modelsummary.py:148

FunctiondeleteLayer

Kai Zhang, 11/Jan/2019.

utils/utils_bnorm.py:20

Functiondict2str

(opt, indent_l=1)

utils/utils_option.py:210

Functiondict_to_nonedict

utils/utils_option.py:230

Functiondownsample_avgpool

(in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=1, bias=True, mode='2R', negative_slope=0.2

models/basicblock.py:520

Functiondownsample_maxpool

(in_channels=64, out_channels=64, kernel_size=3, stride=1, padding=0, bias=True, mode='2R', negative_slope=0.2

models/basicblock.py:507

Functiondownsample_strideconv

(in_channels=64, out_channels=64, kernel_size=2, stride=2, padding=0, bias=True, mode='2R', negative_slope=0.2

models/basicblock.py:495

Functionempty_flops_counter_hook

(module, input, output)

utils/utils_modelsummary.py:443

Methodextra_repr

models/basicblock.py:148

Methodfeed_data

(self, data, need_GT=False, phase='test')

models/model_plain.py:166

utils/utils_sisr.py:417

Functionfind_last_checkpoint

# --------------------------------------- # Kai Zhang (github: https://github.com/cszn) # 03/Mar/2019 # -----------------------------

utils/utils_model.py:20

Functionfind_last_checkpoint

Args: save_dir: model folder net_type: 'G' or 'D' or 'optimizerG' or 'optimizerD' Return: init_iter: iteration numb

utils/utils_option.py:162

models/network.py:219

models/network.py:256

models/network.py:301

Functionflops_repr

utils/utils_modelsummary.py:134

utils/utils_logger.py:65

hidden_states: (B, L, D) Returns: same shape as hidden_states

mamba_simple.py:187

r"""Pass the input through the encoder layer. Args: hidden_states: the sequence to the encoder layer (required). resi

mamba_simple.py:563

hidden_states: (B, L, D) Returns: same shape as hidden_states

mamba_simple.py:732

utils/utils_model.py:310

models/loss.py:42

Forward function. Args: x (Tensor): Input tensor with shape (n, c, h, w). gt (Tensor): Ground-truth tensor with shape

models/loss.py:72

(self, input, target_is_real)

models/loss.py:127

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