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Functions103 in github.com/NVlabs/MUNIT

⨍ Functions 103◇ Types & classes 21

↓ 32 callersMethoddecode

(self, hiddens)

networks.py:179

↓ 21 callersMethodencode

networks.py:174

↓ 14 callersMethod__init__

(self, input_dim, output_dim, dim, n_blk, norm='none', activ='relu')

networks.py:257

↓ 8 callersFunctionget_scheduler

(optimizer, hyperparameters, iterations=-1)

↓ 8 callersMethodrecon_criterion

(self, input, target)

↓ 6 callersFunctionweights_init

(init_type='gaussian')

↓ 6 callersFunctionwrite_one_row_html

(html_file, iterations, img_filename, all_size)

↓ 5 callersFunctionget_data_loader_folder

(input_folder, batch_size, train, new_size=None, height=256, width=256, num_workers

↓ 5 callersMethodsave

(self, snapshot_dir, iterations)

↓ 4 callersMethod__compute_kl

↓ 4 callersMethodcalc_dis_loss

(self, input_fake, input_real)

↓ 4 callersMethodcalc_gen_loss

(self, input_fake)

↓ 4 callersFunctionget_data_loader_list

(root, file_list, batch_size, train, new_size=None, height=256, width=256, num_work

↓ 4 callersFunctionget_model_list

↓ 4 callersFunctionl2normalize

networks.py:514

↓ 4 callersMethodrecon_criterion

(self, input, target)

↓ 4 callersFunctionvgg_preprocess

↓ 3 callersMethodforward

↓ 3 callersFunctionget_config

↓ 3 callersMethodsample

(self, x_a, x_b)

↓ 3 callersFunctionwrite_2images

(image_outputs, display_image_num, image_directory, postfix)

↓ 2 callersFunction__conversion_core

(state_dict_base, trainer_name)

↓ 2 callersFunction__write_images

(image_outputs, display_image_num, file_name)

↓ 2 callersMethodcompute_vgg_loss

(self, vgg, img, target)

↓ 2 callersMethodcompute_vgg_loss

(self, vgg, img, target)

↓ 2 callersFunctionload_inception

↓ 2 callersFunctionload_vgg16

Use the model from https://github.com/abhiskk/fast-neural-style/blob/master/neural_style/utils.py

↓ 2 callersFunctionpytorch03_to_pytorch04

(state_dict_base, trainer_name)

↓ 1 callersMethod__init__

(self, hyperparameters)

↓ 1 callersMethod_made_params

networks.py:545

↓ 1 callersMethod_make_net

↓ 1 callersMethod_make_params

networks.py:555

↓ 1 callersMethod_update_u_v

networks.py:531

↓ 1 callersMethodassign_adain_params

(self, adain_params, model)

networks.py:130

↓ 1 callersMethoddecode

(self, content, style)

networks.py:123

↓ 1 callersMethoddis_update

(self, x_a, x_b, hyperparameters)

↓ 1 callersMethodencode

networks.py:117

↓ 1 callersMethodforward

networks.py:267

↓ 1 callersMethodgen_update

(self, x_a, x_b, hyperparameters)

↓ 1 callersFunctionget_all_data_loaders

↓ 1 callersMethodget_num_adain_params

networks.py:141

↓ 1 callersFunctionis_image_file

↓ 1 callersFunctionmake_dataset

↓ 1 callersFunctionprepare_sub_folder

(output_directory)

↓ 1 callersMethodresume

(self, checkpoint_dir, hyperparameters)

↓ 1 callersFunctionslerp

original: Animating Rotation with Quaternion Curves, Ken Shoemake https://arxiv.org/abs/1609.04468 Code: https://github.com/soumith/dcgan

↓ 1 callersMethodupdate_learning_rate

↓ 1 callersFunctionwrite_html

(filename, iterations, image_save_iterations, image_directory, all_size=1536)

↓ 1 callersFunctionwrite_loss

(iterations, trainer, train_writer)

Method__enter__

(self, exc_type, exc_value, exc_tb)

Method__getitem__

Method__getitem__

Method__getitem__

(self, input_dim, params)

(self, input_dim, params)

(self, input_dim, params)

networks.py:152

(self, n_downsample, input_dim, dim, style_dim, norm, activ, pad_type)

networks.py:189

(self, n_downsample, n_res, input_dim, dim, norm, activ, pad_type)

networks.py:207

(self, n_upsample, n_res, dim, output_dim, res_norm='adain', activ='relu', pad_type='zero')

networks.py:224

(self, num_blocks, dim, norm='in', activation='relu', pad_type='zero')

networks.py:246

(self, dim, norm='in', activation='relu', pad_type='zero')

networks.py:274

(self, input_dim ,output_dim, kernel_size, stride, padding=0, norm='none', activation='relu',

networks.py:289

(self, input_dim, output_dim, norm='none', activation='relu')

networks.py:350

networks.py:400

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

networks.py:454

(self, num_features, eps=1e-5, affine=True)

networks.py:486

(self, module, name='weight', power_iterations=1)

networks.py:523

(self, root, flist, transform=None, flist_reader=default_flist_reader, loader=default_loader)

(self, root, flist, transform=None, flist_reader=default_flist_reader, loader=default_loader)

(self, root, transform=None, return_paths=False, loader=default_loader)

(self, hyperparameters)

networks.py:481

Functiondefault_flist_reader

flist format: impath label\nimpath label\n ...(same to caffe's filelist)

Functiondefault_loader

Methoddis_update

(self, x_a, x_b, hyperparameters)

Functioneformat

networks.py:111

networks.py:164

networks.py:203

networks.py:220

networks.py:239

networks.py:253

networks.py:282

networks.py:341

networks.py:388

networks.py:420

networks.py:466

networks.py:496

networks.py:574

(self, x_a, x_b)

(self, x_a, x_b)

Methodgen_update

(self, x_a, x_b, hyperparameters)

Functionget_slerp_interp

modified from: PyTorch inference for "Progressive Growing of GANs" with CelebA snapshot https://github.com/ptrblck/prog_gans_pytorch_inferenc

Functioninit_fun

(self, checkpoint_dir, hyperparameters)

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