Functions — github.com/RahulBhalley/progressive-growing-of-gans.pytorch

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Functions79 in github.com/RahulBhalley/progressive-growing-of-gans.pytorch

⨍ Functions 79 ◇ Types & classes 13

↓ 8 callersFunctionget_module_names

(model)

network.py:62

↓ 7 callersMethod__init__

(self)

custom_layers.py:31

↓ 7 callersFunctionconv

(layers, c_in, c_out, k_size, stride=1, pad=0, leaky=True, wn=False, pixel=True, only=False)

network.py:30

↓ 7 callersFunctiondeconv

(layers, c_in, c_out, k_size, stride=1, pad=0, leaky=True, wn=False, pixel=False, only=False)

network.py:12

↓ 6 callersFunctiondeepcopy_module

(module, target)

network.py:46

↓ 5 callersMethodadd_scalar

(self, index, val, niter)

tf_recorder.py:25

↓ 4 callersMethodupdate_alpha

(self, delta)

custom_layers.py:44

↓ 3 callersMethodadd_image_grid

(self, index, ngrid, x, niter)

tf_recorder.py:31

↓ 3 callersMethodflush_network

(self)

network.py:168

↓ 3 callersMethodgrow_network

(self, resl)

network.py:141

↓ 3 callersFunctionmake_grid

Make a grid of images. Args: tensor (Tensor or list): 4D mini-batch Tensor of shape (B x C x H x W) or a list of images all of

utils.py:87

↓ 2 callersMethodfrom_rgb_block

(self, ndim)

network.py:275

↓ 2 callersMethodget_state

(self, target)

pggan.py:396

↓ 2 callersFunctionmake_image_grid

(x, ngrid)

utils.py:31

↓ 2 callersFunctionnorm_ip

(img, min, max)

utils.py:130

↓ 2 callersFunctionnorm_range

(t, range)

utils.py:134

↓ 2 callersMethodrenew_everything

Renew the dataloader

pggan.py:185

↓ 2 callersMethodto_rgb_block

(self, c_in)

network.py:126

↓ 1 callersMethod__init__

(self, config)

network.py:73

↓ 1 callersMethodadd_noise

(self, x)

pggan.py:241

↓ 1 callersMethodcompute_gradient_penalty

(self, real_samples, fake_samples)

pggan.py:254

↓ 1 callersMethodfeed_interpolated_input

(self, x)

pggan.py:223

↓ 1 callersMethodfirst_block

(self)

network.py:92

↓ 1 callersMethodget_batch

(self)

dataloader.py:58

↓ 1 callersMethodget_init_dis

(self)

network.py:280

↓ 1 callersMethodget_init_gen

(self)

network.py:133

↓ 1 callersMethodintermediate_block

Return layers according to `resl`

network.py:101

↓ 1 callersMethodintermediate_block

(self, resl)

network.py:254

↓ 1 callersMethodlast_block

(self)

network.py:245

↓ 1 callersFunctionlinear

(layers, c_in, c_out, sig=True, wn=False)

network.py:39

↓ 1 callersMethodrenew

(self, resl)

dataloader.py:29

↓ 1 callersMethodresl_scheduler

This method will schedule image resolution `self.resl` progressively It should be called every iteration to ensure real value is upda

pggan.py:99

↓ 1 callersMethodsnapshot

(self, path)

pggan.py:412

↓ 1 callersMethodtrain

(self)

pggan.py:349

↓ 1 callersMethodtrain_step

(self, config, device)

(self, layer1, layer2)

(self, averaging='all')

(self, c_in, c_out, k_size, stride, pad, bias=False)

custom_layers.py:110

Method__init__

(self, c_in, c_out, k_size, stride, pad)

(self, index, x_input, model)

tf_recorder.py:38

Methodadd_image_single

(self, index, x, niter)

tf_recorder.py:35

Methodadd_scalars

(self, index, group_dict, niter)

tf_recorder.py:28

Functionadjust_dyn_range

(x, drange_in, drange_out)

(self, x, labels=None)

network.py:195

Methodforward

(self, x, labels=None)

(writer, key, value, step)

Save a given Tensor into an image file. Args: tensor (Tensor or list): Image to be saved. If given a mini-batch tensor, saves

utils.py:164

Functionsave_image_grid

(x, path, imsize=512, ngrid=4)

utils.py:51

Functionsave_image_single

(x, path, imsize=512)

Functionsoft_copy_param

Soft copy the parameters of a link to another link