SYMBOL INDEX (422 symbols across 57 files)

FILE: implementations/aae/aae.py
  function reparameterization (line 39) | def reparameterization(mu, logvar):
  class Encoder (line 46) | class Encoder(nn.Module):
    method __init__ (line 47) | def __init__(self):
    method forward (line 61) | def forward(self, img):
  class Decoder (line 70) | class Decoder(nn.Module):
    method __init__ (line 71) | def __init__(self):
    method forward (line 84) | def forward(self, z):
  class Discriminator (line 90) | class Discriminator(nn.Module):
    method __init__ (line 91) | def __init__(self):
    method forward (line 103) | def forward(self, z):
  function sample_image (line 148) | def sample_image(n_row, batches_done):

FILE: implementations/acgan/acgan.py
  function weights_init_normal (line 37) | def weights_init_normal(m):
  class Generator (line 46) | class Generator(nn.Module):
    method __init__ (line 47) | def __init__(self):
    method forward (line 69) | def forward(self, noise, labels):
  class Discriminator (line 77) | class Discriminator(nn.Module):
    method __init__ (line 78) | def __init__(self):
    method forward (line 102) | def forward(self, img):
  function sample_image (line 152) | def sample_image(n_row, batches_done):

FILE: implementations/began/began.py
  function weights_init_normal (line 38) | def weights_init_normal(m):
  class Generator (line 47) | class Generator(nn.Module):
    method __init__ (line 48) | def __init__(self):
    method forward (line 68) | def forward(self, noise):
  class Discriminator (line 75) | class Discriminator(nn.Module):
    method __init__ (line 76) | def __init__(self):
    method forward (line 95) | def forward(self, img):

FILE: implementations/bgan/bgan.py
  class Generator (line 40) | class Generator(nn.Module):
    method __init__ (line 41) | def __init__(self):
    method forward (line 60) | def forward(self, z):
  class Discriminator (line 66) | class Discriminator(nn.Module):
    method __init__ (line 67) | def __init__(self):
    method forward (line 79) | def forward(self, img):
  function boundary_seeking_loss (line 85) | def boundary_seeking_loss(y_pred, y_true):

FILE: implementations/bicyclegan/bicyclegan.py
  function sample_images (line 102) | def sample_images(batches_done):
  function reparameterization (line 125) | def reparameterization(mu, logvar):

FILE: implementations/bicyclegan/datasets.py
  class ImageDataset (line 11) | class ImageDataset(Dataset):
    method __init__ (line 12) | def __init__(self, root, input_shape, mode="train"):
    method __getitem__ (line 23) | def __getitem__(self, index):
    method __len__ (line 39) | def __len__(self):

FILE: implementations/bicyclegan/models.py
  function weights_init_normal (line 9) | def weights_init_normal(m):
  class UNetDown (line 23) | class UNetDown(nn.Module):
    method __init__ (line 24) | def __init__(self, in_size, out_size, normalize=True, dropout=0.0):
    method forward (line 32) | def forward(self, x):
  class UNetUp (line 36) | class UNetUp(nn.Module):
    method __init__ (line 37) | def __init__(self, in_size, out_size):
    method forward (line 46) | def forward(self, x, skip_input):
  class Generator (line 52) | class Generator(nn.Module):
    method __init__ (line 53) | def __init__(self, latent_dim, img_shape):
    method forward (line 77) | def forward(self, x, z):
  class Encoder (line 102) | class Encoder(nn.Module):
    method __init__ (line 103) | def __init__(self, latent_dim, input_shape):
    method forward (line 112) | def forward(self, img):
  class MultiDiscriminator (line 126) | class MultiDiscriminator(nn.Module):
    method __init__ (line 127) | def __init__(self, input_shape):
    method compute_loss (line 155) | def compute_loss(self, x, gt):
    method forward (line 160) | def forward(self, x):

FILE: implementations/ccgan/ccgan.py
  function apply_random_mask (line 84) | def apply_random_mask(imgs):
  function save_sample (line 95) | def save_sample(saved_samples):

FILE: implementations/ccgan/datasets.py
  class ImageDataset (line 10) | class ImageDataset(Dataset):
    method __init__ (line 11) | def __init__(self, root, transforms_x=None, transforms_lr=None, mode='...
    method __getitem__ (line 17) | def __getitem__(self, index):
    method __len__ (line 26) | def __len__(self):

FILE: implementations/ccgan/models.py
  class UNetDown (line 10) | class UNetDown(nn.Module):
    method __init__ (line 11) | def __init__(self, in_size, out_size, normalize=True, dropout=0.0):
    method forward (line 22) | def forward(self, x):
  class UNetUp (line 26) | class UNetUp(nn.Module):
    method __init__ (line 27) | def __init__(self, in_size, out_size, dropout=0.0):
    method forward (line 39) | def forward(self, x, skip_input):
  class Generator (line 45) | class Generator(nn.Module):
    method __init__ (line 46) | def __init__(self, input_shape):
    method forward (line 65) | def forward(self, x, x_lr):
  class Discriminator (line 83) | class Discriminator(nn.Module):
    method __init__ (line 84) | def __init__(self, input_shape):
    method forward (line 110) | def forward(self, img):

FILE: implementations/cgan/cgan.py
  class Generator (line 39) | class Generator(nn.Module):
    method __init__ (line 40) | def __init__(self):
    method forward (line 61) | def forward(self, noise, labels):
  class Discriminator (line 69) | class Discriminator(nn.Module):
    method __init__ (line 70) | def __init__(self):
    method forward (line 87) | def forward(self, img, labels):
  function sample_image (line 129) | def sample_image(n_row, batches_done):

FILE: implementations/cluster_gan/clustergan.py
  function sample_z (line 41) | def sample_z(shape=64, latent_dim=10, n_c=10, fix_class=-1, req_grad=Fal...
  function calc_gradient_penalty (line 70) | def calc_gradient_penalty(netD, real_data, generated_data):
  function initialize_weights (line 106) | def initialize_weights(net):
  function softmax (line 120) | def softmax(x):
  class Reshape (line 124) | class Reshape(nn.Module):
    method __init__ (line 128) | def __init__(self, shape=[]):
    method forward (line 132) | def forward(self, x):
    method extra_repr (line 135) | def extra_repr(self):
  class Generator_CNN (line 143) | class Generator_CNN(nn.Module):
    method __init__ (line 150) | def __init__(self, latent_dim, n_c, x_shape, verbose=False):
    method forward (line 188) | def forward(self, zn, zc):
  class Encoder_CNN (line 196) | class Encoder_CNN(nn.Module):
    method __init__ (line 202) | def __init__(self, latent_dim, n_c, verbose=False):
    method forward (line 236) | def forward(self, in_feat):
  class Discriminator_CNN (line 248) | class Discriminator_CNN(nn.Module):
    method __init__ (line 257) | def __init__(self, wass_metric=False, verbose=False):
    method forward (line 294) | def forward(self, img):

FILE: implementations/cogan/cogan.py
  function weights_init_normal (line 42) | def weights_init_normal(m):
  class CoupledGenerators (line 51) | class CoupledGenerators(nn.Module):
    method __init__ (line 52) | def __init__(self):
    method forward (line 81) | def forward(self, noise):
  class CoupledDiscriminators (line 90) | class CoupledDiscriminators(nn.Module):
    method __init__ (line 91) | def __init__(self):
    method forward (line 112) | def forward(self, img1, img2):

FILE: implementations/cogan/mnistm.py
  class MNISTM (line 19) | class MNISTM(data.Dataset):
    method __init__ (line 29) | def __init__(self, root, mnist_root="data", train=True, transform=None...
    method __getitem__ (line 53) | def __getitem__(self, index):
    method __len__ (line 79) | def __len__(self):
    method _check_exists (line 86) | def _check_exists(self):
    method download (line 91) | def download(self):

FILE: implementations/context_encoder/context_encoder.py
  function weights_init_normal (line 56) | def weights_init_normal(m):
  function save_sample (line 109) | def save_sample(batches_done):

FILE: implementations/context_encoder/datasets.py
  class ImageDataset (line 11) | class ImageDataset(Dataset):
    method __init__ (line 12) | def __init__(self, root, transforms_=None, img_size=128, mask_size=64,...
    method apply_random_mask (line 20) | def apply_random_mask(self, img):
    method apply_center_mask (line 30) | def apply_center_mask(self, img):
    method __getitem__ (line 39) | def __getitem__(self, index):
    method __len__ (line 52) | def __len__(self):

FILE: implementations/context_encoder/models.py
  class Generator (line 6) | class Generator(nn.Module):
    method __init__ (line 7) | def __init__(self, channels=3):
    method forward (line 39) | def forward(self, x):
  class Discriminator (line 43) | class Discriminator(nn.Module):
    method __init__ (line 44) | def __init__(self, channels=3):
    method forward (line 65) | def forward(self, img):

FILE: implementations/cyclegan/cyclegan.py
  function sample_images (line 135) | def sample_images(batches_done):

FILE: implementations/cyclegan/datasets.py
  function to_rgb (line 10) | def to_rgb(image):
  class ImageDataset (line 16) | class ImageDataset(Dataset):
    method __init__ (line 17) | def __init__(self, root, transforms_=None, unaligned=False, mode="trai...
    method __getitem__ (line 24) | def __getitem__(self, index):
    method __len__ (line 42) | def __len__(self):

FILE: implementations/cyclegan/models.py
  function weights_init_normal (line 6) | def weights_init_normal(m):
  class ResidualBlock (line 22) | class ResidualBlock(nn.Module):
    method __init__ (line 23) | def __init__(self, in_features):
    method forward (line 36) | def forward(self, x):
  class GeneratorResNet (line 40) | class GeneratorResNet(nn.Module):
    method __init__ (line 41) | def __init__(self, input_shape, num_residual_blocks):
    method forward (line 86) | def forward(self, x):
  class Discriminator (line 95) | class Discriminator(nn.Module):
    method __init__ (line 96) | def __init__(self, input_shape):
    method forward (line 121) | def forward(self, img):

FILE: implementations/cyclegan/utils.py
  class ReplayBuffer (line 13) | class ReplayBuffer:
    method __init__ (line 14) | def __init__(self, max_size=50):
    method push_and_pop (line 19) | def push_and_pop(self, data):
  class LambdaLR (line 36) | class LambdaLR:
    method __init__ (line 37) | def __init__(self, n_epochs, offset, decay_start_epoch):
    method step (line 43) | def step(self, epoch):

FILE: implementations/dcgan/dcgan.py
  function weights_init_normal (line 36) | def weights_init_normal(m):
  class Generator (line 45) | class Generator(nn.Module):
    method __init__ (line 46) | def __init__(self):
    method forward (line 66) | def forward(self, z):
  class Discriminator (line 73) | class Discriminator(nn.Module):
    method __init__ (line 74) | def __init__(self):
    method forward (line 94) | def forward(self, img):

FILE: implementations/discogan/datasets.py
  class ImageDataset (line 11) | class ImageDataset(Dataset):
    method __init__ (line 12) | def __init__(self, root, transforms_=None, mode='train'):
    method __getitem__ (line 17) | def __getitem__(self, index):
    method __len__ (line 33) | def __len__(self):

FILE: implementations/discogan/discogan.py
  function sample_images (line 112) | def sample_images(batches_done):

FILE: implementations/discogan/models.py
  function weights_init_normal (line 6) | def weights_init_normal(m):
  class UNetDown (line 20) | class UNetDown(nn.Module):
    method __init__ (line 21) | def __init__(self, in_size, out_size, normalize=True, dropout=0.0):
    method forward (line 31) | def forward(self, x):
  class UNetUp (line 35) | class UNetUp(nn.Module):
    method __init__ (line 36) | def __init__(self, in_size, out_size, dropout=0.0):
    method forward (line 44) | def forward(self, x, skip_input):
  class GeneratorUNet (line 51) | class GeneratorUNet(nn.Module):
    method __init__ (line 52) | def __init__(self, input_shape):
    method forward (line 72) | def forward(self, x):
  class Discriminator (line 94) | class Discriminator(nn.Module):
    method __init__ (line 95) | def __init__(self, input_shape):
    method forward (line 118) | def forward(self, img):

FILE: implementations/dragan/dragan.py
  function weights_init_normal (line 37) | def weights_init_normal(m):
  class Generator (line 46) | class Generator(nn.Module):
    method __init__ (line 47) | def __init__(self):
    method forward (line 67) | def forward(self, noise):
  class Discriminator (line 74) | class Discriminator(nn.Module):
    method __init__ (line 75) | def __init__(self):
    method forward (line 95) | def forward(self, img):
  function compute_gradient_penalty (line 144) | def compute_gradient_penalty(D, X):

FILE: implementations/dualgan/datasets.py
  class ImageDataset (line 11) | class ImageDataset(Dataset):
    method __init__ (line 12) | def __init__(self, root, transforms_=None, mode="train"):
    method __getitem__ (line 17) | def __getitem__(self, index):
    method __len__ (line 33) | def __len__(self):

FILE: implementations/dualgan/dualgan.py
  function compute_gradient_penalty (line 116) | def compute_gradient_penalty(D, real_samples, fake_samples):
  function sample_images (line 138) | def sample_images(batches_done):

FILE: implementations/dualgan/models.py
  function weights_init_normal (line 8) | def weights_init_normal(m):
  class UNetDown (line 22) | class UNetDown(nn.Module):
    method __init__ (line 23) | def __init__(self, in_size, out_size, normalize=True, dropout=0.0):
    method forward (line 33) | def forward(self, x):
  class UNetUp (line 37) | class UNetUp(nn.Module):
    method __init__ (line 38) | def __init__(self, in_size, out_size, dropout=0.0):
    method forward (line 50) | def forward(self, x, skip_input):
  class Generator (line 57) | class Generator(nn.Module):
    method __init__ (line 58) | def __init__(self, channels=3):
    method forward (line 78) | def forward(self, x):
  class Discriminator (line 102) | class Discriminator(nn.Module):
    method __init__ (line 103) | def __init__(self, in_channels=3):
    method forward (line 122) | def forward(self, img):

FILE: implementations/ebgan/ebgan.py
  function weights_init_normal (line 38) | def weights_init_normal(m):
  class Generator (line 47) | class Generator(nn.Module):
    method __init__ (line 48) | def __init__(self):
    method forward (line 67) | def forward(self, noise):
  class Discriminator (line 74) | class Discriminator(nn.Module):
    method __init__ (line 75) | def __init__(self):
    method forward (line 96) | def forward(self, img):
  function pullaway_loss (line 142) | def pullaway_loss(embeddings):

FILE: implementations/esrgan/datasets.py
  function denormalize (line 16) | def denormalize(tensors):
  class ImageDataset (line 23) | class ImageDataset(Dataset):
    method __init__ (line 24) | def __init__(self, root, hr_shape):
    method __getitem__ (line 44) | def __getitem__(self, index):
    method __len__ (line 51) | def __len__(self):

FILE: implementations/esrgan/models.py
  class FeatureExtractor (line 8) | class FeatureExtractor(nn.Module):
    method __init__ (line 9) | def __init__(self):
    method forward (line 14) | def forward(self, img):
  class DenseResidualBlock (line 18) | class DenseResidualBlock(nn.Module):
    method __init__ (line 23) | def __init__(self, filters, res_scale=0.2):
    method forward (line 40) | def forward(self, x):
  class ResidualInResidualDenseBlock (line 48) | class ResidualInResidualDenseBlock(nn.Module):
    method __init__ (line 49) | def __init__(self, filters, res_scale=0.2):
    method forward (line 56) | def forward(self, x):
  class GeneratorRRDB (line 60) | class GeneratorRRDB(nn.Module):
    method __init__ (line 61) | def __init__(self, channels, filters=64, num_res_blocks=16, num_upsamp...
    method forward (line 86) | def forward(self, x):
  class Discriminator (line 96) | class Discriminator(nn.Module):
    method __init__ (line 97) | def __init__(self, input_shape):
    method forward (line 126) | def forward(self, img):

FILE: implementations/gan/gan.py
  class Generator (line 38) | class Generator(nn.Module):
    method __init__ (line 39) | def __init__(self):
    method forward (line 58) | def forward(self, z):
  class Discriminator (line 64) | class Discriminator(nn.Module):
    method __init__ (line 65) | def __init__(self):
    method forward (line 77) | def forward(self, img):

FILE: implementations/infogan/infogan.py
  function weights_init_normal (line 41) | def weights_init_normal(m):
  function to_categorical (line 50) | def to_categorical(y, num_columns):
  class Generator (line 58) | class Generator(nn.Module):
    method __init__ (line 59) | def __init__(self):
    method forward (line 80) | def forward(self, noise, labels, code):
  class Discriminator (line 88) | class Discriminator(nn.Module):
    method __init__ (line 89) | def __init__(self):
    method forward (line 114) | def forward(self, img):
  function sample_image (line 181) | def sample_image(n_row, batches_done):

FILE: implementations/lsgan/lsgan.py
  function weights_init_normal (line 36) | def weights_init_normal(m):
  class Generator (line 45) | class Generator(nn.Module):
    method __init__ (line 46) | def __init__(self):
    method forward (line 65) | def forward(self, z):
  class Discriminator (line 72) | class Discriminator(nn.Module):
    method __init__ (line 73) | def __init__(self):
    method forward (line 93) | def forward(self, img):

FILE: implementations/munit/datasets.py
  class ImageDataset (line 11) | class ImageDataset(Dataset):
    method __init__ (line 12) | def __init__(self, root, transforms_=None, mode="train"):
    method __getitem__ (line 19) | def __getitem__(self, index):
    method __len__ (line 35) | def __len__(self):

FILE: implementations/munit/models.py
  function weights_init_normal (line 8) | def weights_init_normal(m):
  class LambdaLR (line 17) | class LambdaLR:
    method __init__ (line 18) | def __init__(self, n_epochs, offset, decay_start_epoch):
    method step (line 24) | def step(self, epoch):
  class Encoder (line 33) | class Encoder(nn.Module):
    method __init__ (line 34) | def __init__(self, in_channels=3, dim=64, n_residual=3, n_downsample=2...
    method forward (line 39) | def forward(self, x):
  class Decoder (line 50) | class Decoder(nn.Module):
    method __init__ (line 51) | def __init__(self, out_channels=3, dim=64, n_residual=3, n_upsample=2,...
    method get_num_adain_params (line 79) | def get_num_adain_params(self):
    method assign_adain_params (line 87) | def assign_adain_params(self, adain_params):
    method forward (line 101) | def forward(self, content_code, style_code):
  class ContentEncoder (line 113) | class ContentEncoder(nn.Module):
    method __init__ (line 114) | def __init__(self, in_channels=3, dim=64, n_residual=3, n_downsample=2):
    method forward (line 140) | def forward(self, x):
  class StyleEncoder (line 149) | class StyleEncoder(nn.Module):
    method __init__ (line 150) | def __init__(self, in_channels=3, dim=64, n_downsample=2, style_dim=8):
    method forward (line 170) | def forward(self, x):
  class MLP (line 179) | class MLP(nn.Module):
    method __init__ (line 180) | def __init__(self, input_dim, output_dim, dim=256, n_blk=3, activ="rel...
    method forward (line 188) | def forward(self, x):
  class MultiDiscriminator (line 197) | class MultiDiscriminator(nn.Module):
    method __init__ (line 198) | def __init__(self, in_channels=3):
    method compute_loss (line 225) | def compute_loss(self, x, gt):
    method forward (line 230) | def forward(self, x):
  class ResidualBlock (line 243) | class ResidualBlock(nn.Module):
    method __init__ (line 244) | def __init__(self, features, norm="in"):
    method forward (line 259) | def forward(self, x):
  class AdaptiveInstanceNorm2d (line 268) | class AdaptiveInstanceNorm2d(nn.Module):
    method __init__ (line 271) | def __init__(self, num_features, eps=1e-5, momentum=0.1):
    method forward (line 283) | def forward(self, x):
    method __repr__ (line 300) | def __repr__(self):
  class LayerNorm (line 304) | class LayerNorm(nn.Module):
    method __init__ (line 305) | def __init__(self, num_features, eps=1e-5, affine=True):
    method forward (line 315) | def forward(self, x):

FILE: implementations/munit/munit.py
  function sample_images (line 139) | def sample_images(batches_done):

FILE: implementations/pix2pix/datasets.py
  class ImageDataset (line 11) | class ImageDataset(Dataset):
    method __init__ (line 12) | def __init__(self, root, transforms_=None, mode="train"):
    method __getitem__ (line 19) | def __getitem__(self, index):
    method __len__ (line 35) | def __len__(self):

FILE: implementations/pix2pix/models.py
  function weights_init_normal (line 6) | def weights_init_normal(m):
  class UNetDown (line 20) | class UNetDown(nn.Module):
    method __init__ (line 21) | def __init__(self, in_size, out_size, normalize=True, dropout=0.0):
    method forward (line 31) | def forward(self, x):
  class UNetUp (line 35) | class UNetUp(nn.Module):
    method __init__ (line 36) | def __init__(self, in_size, out_size, dropout=0.0):
    method forward (line 48) | def forward(self, x, skip_input):
  class GeneratorUNet (line 55) | class GeneratorUNet(nn.Module):
    method __init__ (line 56) | def __init__(self, in_channels=3, out_channels=3):
    method forward (line 83) | def forward(self, x):
  class Discriminator (line 109) | class Discriminator(nn.Module):
    method __init__ (line 110) | def __init__(self, in_channels=3):
    method forward (line 130) | def forward(self, img_A, img_B):

FILE: implementations/pix2pix/pix2pix.py
  function sample_images (line 107) | def sample_images(batches_done):

FILE: implementations/pixelda/mnistm.py
  class MNISTM (line 19) | class MNISTM(data.Dataset):
    method __init__ (line 29) | def __init__(self,
    method __getitem__ (line 60) | def __getitem__(self, index):
    method __len__ (line 86) | def __len__(self):
    method _check_exists (line 93) | def _check_exists(self):
    method download (line 101) | def download(self):

FILE: implementations/pixelda/pixelda.py
  function weights_init_normal (line 45) | def weights_init_normal(m):
  class ResidualBlock (line 54) | class ResidualBlock(nn.Module):
    method __init__ (line 55) | def __init__(self, in_features=64, out_features=64):
    method forward (line 66) | def forward(self, x):
  class Generator (line 70) | class Generator(nn.Module):
    method __init__ (line 71) | def __init__(self):
    method forward (line 86) | def forward(self, img, z):
  class Discriminator (line 95) | class Discriminator(nn.Module):
    method __init__ (line 96) | def __init__(self):
    method forward (line 114) | def forward(self, img):
  class Classifier (line 120) | class Classifier(nn.Module):
    method __init__ (line 121) | def __init__(self):
    method forward (line 138) | def forward(self, img):

FILE: implementations/relativistic_gan/relativistic_gan.py
  class Generator (line 37) | class Generator(nn.Module):
    method __init__ (line 38) | def __init__(self):
    method forward (line 58) | def forward(self, z):
  class Discriminator (line 65) | class Discriminator(nn.Module):
    method __init__ (line 66) | def __init__(self):
    method forward (line 86) | def forward(self, img):

FILE: implementations/sgan/sgan.py
  function weights_init_normal (line 37) | def weights_init_normal(m):
  class Generator (line 46) | class Generator(nn.Module):
    method __init__ (line 47) | def __init__(self):
    method forward (line 69) | def forward(self, noise):
  class Discriminator (line 76) | class Discriminator(nn.Module):
    method __init__ (line 77) | def __init__(self):
    method forward (line 101) | def forward(self, img):

FILE: implementations/softmax_gan/softmax_gan.py
  class Generator (line 38) | class Generator(nn.Module):
    method __init__ (line 39) | def __init__(self):
    method forward (line 58) | def forward(self, z):
  class Discriminator (line 64) | class Discriminator(nn.Module):
    method __init__ (line 65) | def __init__(self):
    method forward (line 76) | def forward(self, img):
  function log (line 117) | def log(x):

FILE: implementations/srgan/datasets.py
  class ImageDataset (line 16) | class ImageDataset(Dataset):
    method __init__ (line 17) | def __init__(self, root, hr_shape):
    method __getitem__ (line 37) | def __getitem__(self, index):
    method __len__ (line 44) | def __len__(self):

FILE: implementations/srgan/models.py
  class FeatureExtractor (line 8) | class FeatureExtractor(nn.Module):
    method __init__ (line 9) | def __init__(self):
    method forward (line 14) | def forward(self, img):
  class ResidualBlock (line 18) | class ResidualBlock(nn.Module):
    method __init__ (line 19) | def __init__(self, in_features):
    method forward (line 29) | def forward(self, x):
  class GeneratorResNet (line 33) | class GeneratorResNet(nn.Module):
    method __init__ (line 34) | def __init__(self, in_channels=3, out_channels=3, n_residual_blocks=16):
    method forward (line 64) | def forward(self, x):
  class Discriminator (line 74) | class Discriminator(nn.Module):
    method __init__ (line 75) | def __init__(self, input_shape):
    method forward (line 104) | def forward(self, img):

FILE: implementations/stargan/datasets.py
  class CelebADataset (line 12) | class CelebADataset(Dataset):
    method __init__ (line 13) | def __init__(self, root, transforms_=None, mode="train", attributes=No...
    method get_annotations (line 22) | def get_annotations(self):
    method __getitem__ (line 36) | def __getitem__(self, index):
    method __len__ (line 45) | def __len__(self):

FILE: implementations/stargan/models.py
  function weights_init_normal (line 6) | def weights_init_normal(m):
  class ResidualBlock (line 17) | class ResidualBlock(nn.Module):
    method __init__ (line 18) | def __init__(self, in_features):
    method forward (line 31) | def forward(self, x):
  class GeneratorResNet (line 35) | class GeneratorResNet(nn.Module):
    method __init__ (line 36) | def __init__(self, img_shape=(3, 128, 128), res_blocks=9, c_dim=5):
    method forward (line 75) | def forward(self, x, c):
  class Discriminator (line 87) | class Discriminator(nn.Module):
    method __init__ (line 88) | def __init__(self, img_shape=(3, 128, 128), c_dim=5, n_strided=6):
    method forward (line 111) | def forward(self, img):

FILE: implementations/stargan/stargan.py
  function criterion_cls (line 76) | def criterion_cls(logit, target):
  function compute_gradient_penalty (line 142) | def compute_gradient_penalty(D, real_samples, fake_samples):
  function sample_images (line 173) | def sample_images(batches_done):

FILE: implementations/unit/datasets.py
  class ImageDataset (line 10) | class ImageDataset(Dataset):
    method __init__ (line 11) | def __init__(self, root, transforms_=None, unaligned=False, mode="trai...
    method __getitem__ (line 18) | def __getitem__(self, index):
    method __len__ (line 28) | def __len__(self):

FILE: implementations/unit/models.py
  function weights_init_normal (line 8) | def weights_init_normal(m):
  class LambdaLR (line 17) | class LambdaLR:
    method __init__ (line 18) | def __init__(self, n_epochs, offset, decay_start_epoch):
    method step (line 24) | def step(self, epoch):
  class ResidualBlock (line 33) | class ResidualBlock(nn.Module):
    method __init__ (line 34) | def __init__(self, features):
    method forward (line 49) | def forward(self, x):
  class Encoder (line 53) | class Encoder(nn.Module):
    method __init__ (line 54) | def __init__(self, in_channels=3, dim=64, n_downsample=2, shared_block...
    method reparameterization (line 81) | def reparameterization(self, mu):
    method forward (line 86) | def forward(self, x):
  class Generator (line 93) | class Generator(nn.Module):
    method __init__ (line 94) | def __init__(self, out_channels=3, dim=64, n_upsample=2, shared_block=...
    method forward (line 119) | def forward(self, x):
  class Discriminator (line 130) | class Discriminator(nn.Module):
    method __init__ (line 131) | def __init__(self, input_shape):
    method forward (line 153) | def forward(self, img):

FILE: implementations/unit/unit.py
  function sample_images (line 150) | def sample_images(batches_done):
  function compute_kl (line 163) | def compute_kl(mu):

FILE: implementations/wgan/wgan.py
  class Generator (line 39) | class Generator(nn.Module):
    method __init__ (line 40) | def __init__(self):
    method forward (line 59) | def forward(self, z):
  class Discriminator (line 65) | class Discriminator(nn.Module):
    method __init__ (line 66) | def __init__(self):
    method forward (line 77) | def forward(self, img):

FILE: implementations/wgan_div/wgan_div.py
  class Generator (line 42) | class Generator(nn.Module):
    method __init__ (line 43) | def __init__(self):
    method forward (line 62) | def forward(self, z):
  class Discriminator (line 68) | class Discriminator(nn.Module):
    method __init__ (line 69) | def __init__(self):
    method forward (line 80) | def forward(self, img):

FILE: implementations/wgan_gp/wgan_gp.py
  class Generator (line 42) | class Generator(nn.Module):
    method __init__ (line 43) | def __init__(self):
    method forward (line 62) | def forward(self, z):
  class Discriminator (line 68) | class Discriminator(nn.Module):
    method __init__ (line 69) | def __init__(self):
    method forward (line 80) | def forward(self, img):
  function compute_gradient_penalty (line 119) | def compute_gradient_penalty(D, real_samples, fake_samples):