Functions — github.com/JCBrouwer/maua-stylegan2

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Functions576 in github.com/JCBrouwer/maua-stylegan2

⨍ Functions 576◇ Types & classes 120

↓ 1 callersFunctionprepare

(env, dataset, n_worker, sizes=(128, 256, 512, 1024), resample=Image.LANCZOS)

prepare_data.py:47

↓ 1 callersMethodprepare_data

(self)

lightning.py:224

↓ 1 callersMethodprint_log

(self)

lucidrains.py:1119

↓ 1 callersFunctionrandom_apply_affine

(img, p, G=None, antialiasing_kernel=SYM6)

augment.py:292

↓ 1 callersFunctionrandom_apply_color

(img, p, C=None)

augment.py:355

↓ 1 callersMethodremove

(self, module)

validation/spectral_norm.py:40

↓ 1 callersFunctionremove_drop

(label)

select_latents.py:419

↓ 1 callersFunctionremove_intro

(label)

select_latents.py:390

↓ 1 callersFunctionrender

( generator, latents, noise, offset, duration, batch_size, out_size, output_fi

render.py:14

↓ 1 callersMethodreparameterize

(self, mu, logvar)

models/autoencoder.py:120

↓ 1 callersMethodreparameterize

(self, mu, log_var)

models/autoencoder.py:459

↓ 1 callersFunctionresize_and_convert

(img, size, resample, quality=100)

prepare_data.py:16

↓ 1 callersFunctionresize_multiple

(img, sizes=(128, 256, 512, 1024), resample=Image.LANCZOS, quality=100)

prepare_data.py:26

↓ 1 callersFunctionrotate3d_mat

(axis, theta)

augment.py:67

↓ 1 callersFunctionsample_affine

(p, size, height, width)

augment.py:151

↓ 1 callersFunctionsample_color

(p, size)

augment.py:210

↓ 1 callersFunctionsample_data

(loader)

train_profile.py:53

↓ 1 callersFunctionsample_data

(loader)

train.py:52

↓ 1 callersFunctionsample_data

(loader)

accelerate/accelerate_inception.py:18

↓ 1 callersFunctionsample_data

(loader)

accelerate/accelerate_logcosh.py:23

↓ 1 callersFunctionsample_data

(loader)

accelerate/accelerate_segnet.py:17

↓ 1 callersMethodsampling

(self)

models/autoencoder.py:670

↓ 1 callersFunctionsaturation_mat

(axis, i)

augment.py:109

↓ 1 callersFunctionscale3d_mat

↓ 1 callersMethodset_data_src

(self, folder)

lucidrains.py:742

↓ 1 callersFunctionslerp

Interpolation along geodesic of n-dimensional unit sphere from https://github.com/soumith/dcgan.torch/issues/14#issuecomment-200025792 Args:

audioreactive/latent.py:29

↓ 1 callersFunctiontensor2im

(image_tensor, imtype=np.uint8, cent=1.0, factor=255.0 / 2.0)

validation/lpips/util.py:87

↓ 1 callersFunctiontensor2np

(tensor_obj)

validation/lpips/util.py:36

↓ 1 callersFunctiontrain

(args, loader, generator, discriminator, contrast_learner, g_optim, d_optim, g_ema)

train_profile.py:110

↓ 1 callersFunctiontrain

(args, loader, generator, discriminator, contrast_learner, g_optim, d_optim, g_ema)

train.py:105

↓ 1 callersFunctiontrain

(latent_dim, num_repeats, learning_rate, lambda_vgg, lambda_mse)

accelerate/accelerate_inception.py:82

↓ 1 callersFunctiontrain

(latent_dim, learning_rate, number_filters, vae_alpha, vae_beta, kl_divergence_weight)

accelerate/accelerate_logcosh.py:93

↓ 1 callersFunctiontrain

(learning_rate, lambda_mse)

accelerate/accelerate_segnet.py:89

↓ 1 callersFunctiontranslate3d_mat

(t_x, t_y, t_z)

augment.py:57

↓ 1 callersFunctiontry_sample_affine_and_pad

(img, p, pad_k, G=None)

augment.py:270

↓ 1 callersMethodupdate_average

(self, old, new)

contrastive_learner.py:100

↓ 1 callersFunctionupfirdn2d_native

( input, kernel, up_x, up_y, down_x, down_y, pad_x0, pad_x1, pad_y0, pad_y1 )

op/upfirdn2d.py:159

↓ 1 callersFunctionupscale2d

(x, factor=2, gain=1)

models/stylegan1.py:169

↓ 1 callersMethodwrite_config

(self)

lucidrains.py:718

FunctionPYBIND11_MODULE

op/fused_bias_act.cpp:19

FunctionPYBIND11_MODULE

(self, module, inputs)

validation/spectral_norm.py:46

lookahead_minimax.py:59

(self, folder, image_size, transparent=False)

(self, latent_dim, input_channel, upsample, rgba=False)

lucidrains.py:281

Method__init__

(self, in_chan, out_chan, kernel, demod=True, stride=1, dilation=1, **kwargs)

lucidrains.py:306

Method__init__

(self, latent_dim, input_channels, filters, upsample=True, upsample_rgb=True, rgba=False)

lucidrains.py:343

Method__init__

(self, input_channels, filters, downsample=True)

lucidrains.py:379

Method__init__

(self, image_size, latent_dim, network_capacity=16, transparent=False, attn_layers=[])

lucidrains.py:402

Method__init__

( self, image_size, network_capacity=16, fq_layers=[], fq_dict_size=256, attn_layers=[], transparent=F

lucidrains.py:450

Method__init__

( self, image_size, latent_dim=512, style_depth=8, network_capacity=16

lucidrains.py:513

Method__init__

( self, name, results_dir, models_dir, image_size, network_cap

lucidrains.py:626

Method__init__

G_optimizer: generator optimizer D_optimizer: discriminator optimizer la_steps (int): number of lookahead steps la_al

lookahead_minimax.py:19

Method__init__

(self, path, transform, resolution=256)

generate_video.py:463

Method__init__

(self, fn, p)

contrastive_learner.py:77

Method__init__

(self, net, layer=-2)

contrastive_learner.py:116

Method__init__

( self, net, image_size, hidden_layer=-2, project_hidden=True,

contrastive_learner.py:157

Method__init__

(self, root, horizontal_factor=1, vertical_factor=1)

select_latents.py:58

Method__init__

( self, master, width=None, anchor=N, height=None, mousewheel_

select_latents.py:138

Method__init__

(self)

accelerate/accelerate_inception.py:68

Method__init__

(self)

accelerate/accelerate_logcosh.py:73

Method__init__

(self)

accelerate/accelerate_segnet.py:67

Method__init__

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

op/fused_act.py:75

Method__init__

(self, in_channels, pool_features)

validation/inception.py:191

Method__init__

(self, in_channels, channels_7x7)

validation/inception.py:216

Method__init__

(self, in_channels)

validation/inception.py:244

Method__init__

(self, in_channels)

validation/inception.py:277

Method__init__

(self, name="weight", n_power_iterations=1, dim=0, eps=1e-12)

validation/spectral_norm.py:5

Method__init__

(self)

validation/lpips/base_model.py:6

Method__init__

( self, model="net-lin", net="alex", colorspace="rgb", spatial=False, use_gpu=True, gpu_ids=[0] )

validation/lpips/__init__.py:14

Method__init__

(self, requires_grad=False, pretrained=True)

validation/lpips/pretrained_networks.py:7

Method__init__

(self, requires_grad=False, pretrained=True)

validation/lpips/pretrained_networks.py:58

Method__init__

(self, requires_grad=False, pretrained=True, num=18)

validation/lpips/pretrained_networks.py:140

Method__init__

(self)

validation/lpips/networks_basic.py:101

Method__init__

(self, chn_in, chn_out=1, use_dropout=False)

validation/lpips/networks_basic.py:113

Method__init__

(self, chn_mid=32, use_sigmoid=True)

validation/lpips/networks_basic.py:126

Method__init__

(self, chn_mid=32)

validation/lpips/networks_basic.py:155

Method__init__

(self, use_gpu=True, colorspace="Lab")

validation/lpips/networks_basic.py:169

Method__init__

(self)

models/stylegan2.py:16

Method__init__

(self, kernel, factor=2)

models/stylegan2.py:35

Method__init__

(self, kernel, factor=2)

models/stylegan2.py:56

Method__init__

(self, in_channel, out_channel, kernel_size, stride=1, padding=0, bias=True)

models/stylegan2.py:96

Method__init__

(self, in_dim, out_dim, bias=True, bias_init=0, lr_mul=1, activation=None)

models/stylegan2.py:124

Method__init__

(self, negative_slope=0.2)

models/stylegan2.py:153

Method__init__

( self, in_channel, out_channel, kernel_size, style_dim, demod

models/stylegan2.py:165

Method__init__

(self)

models/stylegan2.py:258

Method__init__

(self, channel, size=4)

models/stylegan2.py:270

Method__init__

(self, latent_dim, channel, size=4)

models/stylegan2.py:282

Method__init__

(self, layer)

models/stylegan2.py:298

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