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Functions576 in github.com/JCBrouwer/maua-stylegan2

⨍ Functions 576◇ Types & classes 120
↓ 2 callersFunctionreduce_loss_dict
(loss_dict)
distributed.py:102
↓ 2 callersFunctionrender_latents
(latents)
select_latents.py:299
↓ 2 callersMethodreset_parameter_averaging
(self)
lucidrains.py:617
↓ 2 callersMethodreshape_weight_to_matrix
(self, weight)
validation/spectral_norm.py:16
↓ 2 callersFunctionsafe_concat
(arr, el, dim=0)
contrastive_learner.py:22
↓ 2 callersMethodsave
(self, label)
validation/lpips/base_model.py:31
↓ 2 callersFunctionset_requires_grad
(model, bool)
lucidrains.py:198
↓ 2 callersFunctionspatial_average
(in_tens, keepdim=True)
validation/lpips/networks_basic.py:9
↓ 2 callersFunctionsynchronize
()
distributed.py:17
↓ 2 callersMethodtrain_dataloader
(self)
lightning.py:83
↓ 2 callersFunctiontranslate_mat
(t_x, t_y)
augment.py:25
↓ 2 callersMethodupdate_average
(self, old, new)
lucidrains.py:68
↓ 2 callersFunctionupsample
(in_tens, out_H=64)
validation/lpips/networks_basic.py:13
↓ 1 callersMethodEMA
(self)
lucidrains.py:608
↓ 1 callersMethod__init__
(self, master, **kw)
select_latents.py:30
↓ 1 callersMethod__init__
(self, requires_grad=False)
accelerate/accelerate_inception.py:30
↓ 1 callersMethod__init__
(self, requires_grad=False)
accelerate/accelerate_logcosh.py:35
↓ 1 callersMethod__init__
(self, requires_grad=False)
accelerate/accelerate_segnet.py:29
↓ 1 callersMethod_bottleneck
(self, h)
models/autoencoder.py:665
↓ 1 callersMethod_find_layer
(self)
contrastive_learner.py:124
↓ 1 callersMethod_get_bilinear
(self, hidden)
contrastive_learner.py:203
↓ 1 callersMethod_get_key_encoder
(self)
contrastive_learner.py:197
↓ 1 callersMethod_get_projection_fn
(self, hidden)
contrastive_learner.py:208
↓ 1 callersMethod_get_same_padding
(self, size, kernel, dilation, stride)
lucidrains.py:316
↓ 1 callersMethod_init_weights
(self)
lucidrains.py:597
↓ 1 callersMethod_reparameterize
(self, mu, logvar)
models/autoencoder.py:659
↓ 1 callersFunctionadd_drop
(label)
select_latents.py:403
↓ 1 callersFunctionadd_images
(n)
select_latents.py:432
↓ 1 callersFunctionadd_intro
(label)
select_latents.py:374
↓ 1 callersMethodadd_support_to
( self, widget=None, xscrollbar=None, yscrollbar=None, what="units", horizontal_factor=None, vertical_
select_latents.py:85
↓ 1 callersFunctionaffine_grid
(grid, mat)
augment.py:254
↓ 1 callersFunctionapply_color
(img, mat)
augment.py:344
↓ 1 callersMethodbackward_train
(self)
validation/lpips/dist_model.py:177
↓ 1 callersFunctionbernoulli_sample
(size, p)
augment.py:139
↓ 1 callersFunctioncalc_fid
(sample_mean, sample_cov, real_mean, real_cov, eps=1e-6)
validation/calc_fid.py:32
↓ 1 callersMethodcalculate_fid
(self)
lucidrains.py:993
↓ 1 callersMethodcalculate_ppl
(self)
lucidrains.py:1045
↓ 1 callersFunctioncircular_mask
(h, w, center=None, radius=None, soft=0)
audioreactive/examples/temper.py:41
↓ 1 callersMethodclamp_weights
(self)
validation/lpips/dist_model.py:142
↓ 1 callersMethodclear
(self)
lucidrains.py:1131
↓ 1 callersFunctioncompress
Expand or compress signal. Values above/below (depending on invert) threshold are multiplied by ratio. Args: signal (th.tensor): Signal t
audioreactive/signal.py:295
↓ 1 callersMethodcompute_accuracy
d0, d1 are Variables, judge is a Tensor
validation/lpips/dist_model.py:180
↓ 1 callersMethodcompute_sigma
(self, module)
validation/spectral_norm.py:24
↓ 1 callersFunctioncycle
(iterable)
lucidrains.py:117
↓ 1 callersFunctiond_logistic_loss
(real_pred, fake_pred)
train_profile.py:66
↓ 1 callersFunctiond_logistic_loss
(real_pred, fake_pred)
train.py:65
↓ 1 callersMethodd_logistic_loss
(self, real_pred, fake_pred)
lightning.py:96
↓ 1 callersMethodd_r1_loss
(self, real_pred, real_img)
lightning.py:101
↓ 1 callersFunctiond_r1_penalty
(real_img, real_pred, args)
train_profile.py:72
↓ 1 callersFunctiond_r1_penalty
(real_img, real_pred, args)
train.py:71
↓ 1 callersFunctiondata_sampler
(dataset, shuffle, distributed)
train_profile.py:32
↓ 1 callersFunctiondata_sampler
(dataset, shuffle, distributed)
train.py:31
↓ 1 callersFunctiondata_sampler
(dataset, shuffle, distributed)
accelerate/accelerate_logcosh.py:14
↓ 1 callersMethoddecode
(self, z)
models/autoencoder.py:113
↓ 1 callersMethoddecode
(self, inputs)
models/autoencoder.py:392
↓ 1 callersMethoddecode
(self, inputs)
models/autoencoder.py:472
↓ 1 callersFunctiondefault
(value, d)
lucidrains.py:113
↓ 1 callersFunctiondiscriminator_fill_statedict
(statedict, vars, size)
convert_weight.py:104
↓ 1 callersMethodencode
(self, input)
models/autoencoder.py:104
↓ 1 callersMethodencode
(self, inputs)
models/autoencoder.py:389
↓ 1 callersMethodencode
(self, inputs)
models/autoencoder.py:464
↓ 1 callersFunctionextract_feature_from_samples
(generator, inception, truncation, truncation_latent, batch_size, n_sample, device)
validation/calc_fid.py:15
↓ 1 callersFunctionextract_features
(loader, inception, device)
validation/calc_inception.py:61
↓ 1 callersFunctionfid_inception_v3
Build pretrained Inception model for FID computation The Inception model for FID computation uses a different set of weights and has a slight
validation/inception.py:163
↓ 1 callersMethodforward
(self, x, aug_x, accumulate=False)
contrastive_learner.py:230
↓ 1 callersMethodforward
( self, styles, noise=None, truncation=1, map_latents=False, r
models/stylegan1.py:581
↓ 1 callersMethodforward_train
(self)
validation/lpips/dist_model.py:163
↓ 1 callersFunctiong_non_saturating_loss
(fake_pred)
train_profile.py:79
↓ 1 callersFunctiong_non_saturating_loss
(fake_pred)
train.py:78
↓ 1 callersMethodg_nonsaturating_loss
(self, fake_pred)
lightning.py:106
↓ 1 callersFunctiong_path_length_regularization
(generator, mean_path_length, args)
train_profile.py:83
↓ 1 callersFunctiong_path_length_regularization
(generator, mean_path_length, args)
train.py:82
↓ 1 callersMethodg_path_regularize
(self, fake_img, latents, mean_path_length, decay=0.01)
lightning.py:110
↓ 1 callersFunctiongenerate
( ckpt, audio_file, initialize=None, get_latents=None, get_noise=None, get_bends=None,
generate_audiovisual.py:59
↓ 1 callersFunctiongenerate
(args, g_ema, device, mean_latent)
generate.py:8
↓ 1 callersFunctiongenerate_images
(n)
select_latents.py:262
↓ 1 callersFunctionget_bends
(args)
audioreactive/examples/kelp.py:113
↓ 1 callersFunctionget_kth_value
(unsorted, k, axis=-1)
validation/metrics.py:188
↓ 1 callersFunctionget_latents
(selection, args)
audioreactive/examples/default.py:12
↓ 1 callersFunctionget_lr
(t, initial_lr, rampdown=0.25, rampup=0.05)
projector.py:47
↓ 1 callersFunctionget_noise
(height, width, scale, num_scales, args)
audioreactive/examples/default.py:28
↓ 1 callersFunctionget_noise_range
Gets the correct number of noise resolutions for a given resolution of StyleGAN 1 or 2
generate_audiovisual.py:22
↓ 1 callersFunctionget_padding
(G, height, width)
augment.py:259
↓ 1 callersFunctiongradient_penalty
(images, output, weight=10)
lucidrains.py:146
↓ 1 callersFunctioninitialize
(args)
audioreactive/examples/kelp.py:18
↓ 1 callersFunctionis_empty
(t)
lucidrains.py:127
↓ 1 callersFunctionlatent_noise
(latent, strength)
projector.py:55
↓ 1 callersMethodload_config
(self)
lucidrains.py:721
↓ 1 callersFunctionload_generator
Loads a StyleGAN 1 or 2 generator
generate_audiovisual.py:37
↓ 1 callersFunctionload_patched_inception_v3
()
validation/calc_inception.py:51
↓ 1 callersFunctionluma_flip_mat
(axis, i)
augment.py:99
↓ 1 callersFunctionmake_grid
(shape, x0, x1, y0, y1, device)
augment.py:244
↓ 1 callersFunctionmake_image
(tensor)
projector.py:61
↓ 1 callersMethodmean_latent
(self, n_latent)
models/stylegan2.py:483
↓ 1 callersFunctionnoise_normalize_
(noises)
projector.py:39
↓ 1 callersFunctionnoise_regularize
(noises)
projector.py:16
↓ 1 callersFunctionnormalize
Normalize signal between 0 and 1 Args: signal (np.array/th.tensor): Signal to normalize Returns: np.array/th.tensor: Normali
audioreactive/signal.py:243
↓ 1 callersMethodonMouseWheel
(event)
select_latents.py:118
↓ 1 callersFunctionpercentile
Calculate percentile of signal Args: signal (np.array/th.tensor): Signal to normalize p (int): [0-100]. Percentile to find R
audioreactive/signal.py:257
↓ 1 callersFunctionprepare
(env, vae, loader, total, batch_size, n_worker, size=1024)
prepare_vae_codes.py:22
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