SYMBOL INDEX (193 symbols across 21 files)

FILE: arglib/arglib.py
  class BaseArgs (line 9) | class BaseArgs(ABC):
    method __init__ (line 10) | def __init__(self):
    method add_args (line 22) | def add_args(self):
    method parse (line 47) | def parse(self):
    method log (line 50) | def log(self):
    method add_bool_arg (line 58) | def add_bool_arg(parser, name, default=True):
    method validate (line 65) | def validate(self):
    method process (line 70) | def process(self):
  class TrainArgs (line 88) | class TrainArgs(BaseArgs):
    method __init__ (line 89) | def __init__(self):
    method add_args (line 92) | def add_args(self):
    method validate (line 127) | def validate(self):
    method process (line 132) | def process(self):
  class TestArgs (line 147) | class TestArgs(BaseArgs):
    method __init__ (line 148) | def __init__(self):
    method add_args (line 151) | def add_args(self):
    method validate (line 170) | def validate(self):
    method process (line 178) | def process(self):

FILE: data_loader/data_loader.py
  class DataLoader (line 9) | class DataLoader(object):
    method __init__ (line 10) | def __init__(self, args):
    method get_image (line 33) | def get_image(self, is_train, black_list=None, is_real=False):
    method get_w_by_ind (line 72) | def get_w_by_ind(self, ind):
    method get_real_w (line 84) | def get_real_w(self, is_train, black_list=None, is_real=False):
    method batch_samples (line 90) | def batch_samples(self, get_sample_func, is_train, black_list=None, is...
    method get_batch (line 106) | def get_batch(self, is_train=True, is_cross=False, ws=True):

FILE: inference.py
  class Inference (line 10) | class Inference(object):
    method __init__ (line 11) | def __init__(self, args, model):
    method infer_pairs (line 15) | def infer_pairs(self):
    method infer_on_dirs (line 33) | def infer_on_dirs(self):
    method interpolate (line 62) | def interpolate(self, w_space=True):

FILE: main.py
  function init_logger (line 21) | def init_logger(args):
  function main (line 46) | def main():

FILE: model/arcface/arcface.py
  class Arcfacelayer (line 12) | class Arcfacelayer(tf.keras.layers.Layer):
    method __init__ (line 13) | def __init__(self, output_dim=num_classes, s=64., m=0.50):
    method build (line 19) | def build(self, input_shape):
    method call (line 29) | def call(self, embedding, labels):
    method compute_output_shape (line 67) | def compute_output_shape(self, input_shape):

FILE: model/arcface/inference.py
  class MyArcFace (line 10) | class MyArcFace:
    method __init__ (line 11) | def __init__(self, path_to_weights):
    method get_best_face (line 18) | def get_best_face(self, faces, resolution):
    method __detect_face (line 48) | def __detect_face(self, img):
    method __preprocess (line 68) | def __preprocess(self, img, bbox=None, landmark=None):
    method process_image (line 92) | def process_image(self, img):
    method __call__ (line 105) | def __call__(self, img):

FILE: model/arcface/resnet.py
  function residual_unit_v3 (line 9) | def residual_unit_v3(input, num_filter, stride, dim_match, name):
  function get_fc1 (line 83) | def get_fc1(input):
  function ResNet50 (line 113) | def ResNet50():
  class train_model (line 179) | class train_model(tf.keras.Model):
    method __init__ (line 180) | def __init__(self):
    method call (line 185) | def call(self, x, y):

FILE: model/attr_encoder.py
  class AttrEncoder (line 8) | class AttrEncoder(Model):
    method __init__ (line 9) | def __init__(self, args):
    method call (line 21) | def call(self, input_x):
    method my_save (line 29) | def my_save(self, reason=''):

FILE: model/discriminator.py
  class W_D (line 7) | class W_D(Model):
    method __init__ (line 8) | def __init__(self, args):
    method call (line 25) | def call(self, x):
    method my_save (line 38) | def my_save(self, reason=''):

FILE: model/face_detector.py
  class FaceDetector (line 4) | class FaceDetector(object):
    method __init__ (line 5) | def __init__(self, args, model_path):
    method _build (line 11) | def _build(self):
    method __call__ (line 15) | def __call__(self, input_x):
    method sample_call (line 32) | def sample_call(self, input_x):

FILE: model/generator.py
  class G (line 13) | class G(Model):
    method __init__ (line 14) | def __init__(self, args, id_model_path, image_G,
    method call (line 39) | def call(self, x1, x2):
    method my_save (line 60) | def my_save(self, reason=''):

FILE: model/id_encoder.py
  class IDEncoder (line 5) | class IDEncoder(Model):
    method __init__ (line 7) | def __init__(self, args, model_path, intermediate_layers_names=None):
    method crop_faces (line 24) | def crop_faces(self, img):
    method preprocess (line 53) | def preprocess(self, img):
    method call (line 83) | def call(self, input_x, get_intermediate=False):

FILE: model/landmarks.py
  class LandmarksDetector (line 10) | class LandmarksDetector(Model):
    method __init__ (line 11) | def __init__(self, args, model_path, face_detection_model_path):
    method preprocess (line 21) | def preprocess(self, imgs, face_detection=False):
    method lazy_preprocess (line 30) | def lazy_preprocess(self, imgs):
    method hard_preprocess (line 34) | def hard_preprocess(self, imgs):
    method postprocess (line 80) | def postprocess(self, landmarks, details, face_detection=False):
    method lazy_postprocess (line 88) | def lazy_postprocess(self, batch_lnds, details):
    method hard_postprocess (line 92) | def hard_postprocess(self, batch_lnds, details):
    method call (line 105) | def call(self, input_x, face_detection=False):

FILE: model/latent_mapping.py
  class LatentMappingNetwork (line 8) | class LatentMappingNetwork(Model):
    method __init__ (line 9) | def __init__(self, args):
    method call (line 30) | def call(self, x):
    method my_save (line 47) | def my_save(self, reason=''):

FILE: model/model.py
  class Network (line 16) | class Network(Model):
    method __init__ (line 17) | def __init__(self, args, id_net_path, base_generator,
    method call (line 27) | def call(self):
    method my_save (line 30) | def my_save(self, reason):
    method my_load (line 36) | def my_load(self):
    method train (line 39) | def train(self):
    method test (line 42) | def test(self):
    method _set_trainable_behavior (line 45) | def _set_trainable_behavior(self, trainable):

FILE: model/stylegan.py
  function nf (line 15) | def nf(stage, fmap_base=8192, fmap_decay=1.0, fmap_max=512):
  function LeakyReLU (line 18) | def LeakyReLU(alpha, name):
  function GetWeights (line 24) | def GetWeights(gain=math.sqrt(2)):
  function runtime_coef (line 27) | def runtime_coef(kernel_size, gain, fmaps_in, fmaps_out, lrmul=1.0):
  function pixel_norm (line 35) | def pixel_norm(x, epsilon=1e-8):
  class PixelNorm (line 39) | class PixelNorm(Layer):
    method __init__ (line 40) | def __init__(self, name):
    method call (line 43) | def call(self, inputs):
  class InstanceNorm (line 46) | class InstanceNorm(Layer):
    method __init__ (line 47) | def __init__(self, name):
    method call (line 50) | def call(self, x):
  function Identity (line 60) | def Identity(name):
  function Broadcast (line 63) | def Broadcast(name, dlatent_broadcast=18):
  class Truncation (line 68) | class Truncation(Layer):
    method __init__ (line 69) | def __init__(self, name, num_layers=18, truncation_psi=0.7, truncation...
    method build (line 75) | def build(self, input_shape):
    method call (line 78) | def call(self, inputs):
  class DenseLayer (line 87) | class DenseLayer(Dense):
    method __init__ (line 88) | def __init__(self, units, name, kernel_initializer=GetWeights(), gain=...
    method call (line 93) | def call(self, inputs):
  class Conv2d (line 106) | class Conv2d(Conv2D):
    method __init__ (line 107) | def __init__(self, filters, kernel_size, name, gain=math.sqrt(2), lrmu...
    method call (line 115) | def call(self, inputs):
  class Const (line 132) | class Const(Layer):
    method __init__ (line 133) | def __init__(self, name):
    method build (line 136) | def build(self, input_shape):
    method call (line 139) | def call(self, inputs):
  class RandomNoise (line 142) | class RandomNoise(Layer):
    method __init__ (line 143) | def __init__(self, name, layer_idx):
    method build (line 150) | def build(self, input_shape):
    method call (line 153) | def call(self, inputs):
  class ApplyNoise (line 156) | class ApplyNoise(Layer):
    method __init__ (line 157) | def __init__(self, name, is_const_noise):
    method build (line 161) | def build(self, input_shape):
    method call (line 165) | def call(self, inputs):
  class ApplyBias (line 172) | class ApplyBias(Layer):
    method __init__ (line 173) | def __init__(self, name, lrmul=1.0):
    method build (line 177) | def build(self, input_shape):
    method call (line 180) | def call(self, x):
  class StridedSlice (line 185) | class StridedSlice(Layer):
    method __init__ (line 186) | def __init__(self, layer_idx, name):
    method call (line 190) | def call(self, inputs):
  class StyleModApply (line 193) | class StyleModApply(Layer):
    method __init__ (line 194) | def __init__(self, name):
    method call (line 197) | def call(self, inputs):
  function _blur2d (line 203) | def _blur2d(x, f=[1,2,1], normalize=True, flip=False, stride=1):
  function Blur (line 232) | def Blur(name, blur_filter=[1,2,1]):
  function _downscale2d (line 237) | def _downscale2d(x, factor=2, gain=1):
  function _upscale2d (line 259) | def _upscale2d(x, factor=2, gain=1):
  function Downscaled2d (line 278) | def Downscaled2d(name, factor=2, gain=1):
  function Upscaled2d (line 281) | def Upscaled2d(name, factor=2, gain=1):
  function Conv2d_downscale2d (line 284) | def Conv2d_downscale2d(model, filters, kernel_size, name, gain=math.sqrt...
  function Upscale2d_conv2d (line 301) | def Upscale2d_conv2d(x, filters, kernel_size, name, use_bias, gain=math....
  class Conv2d_transpose (line 312) | class Conv2d_transpose(Conv2DTranspose):
    method __init__ (line 313) | def __init__(self, filters, kernel_size, name, gain=math.sqrt(2), lrmu...
    method build (line 321) | def build(self, input_shape):
    method call (line 325) | def call(self, inputs):
  class MinibatchStddevLayer (line 342) | class MinibatchStddevLayer(tf.keras.layers.Layer):
    method __init__ (line 343) | def __init__(self, group_size =4, num_new_features=1):
    method __call__ (line 348) | def __call__(self, x, *args, **kwargs):
  function minibatch_stddev_layer (line 364) | def minibatch_stddev_layer(x, group_size=4, num_new_features=1):
  function StyleGAN_G_mapping (line 379) | def StyleGAN_G_mapping( latent_size=512, dlatent_size=512, mapping_layer...
  function StyleGAN_G_synthesis (line 410) | def StyleGAN_G_synthesis(dlatent_size=512, resolution=1024, is_const_noi...
  class StyleGAN_G (line 471) | class StyleGAN_G(Model):
    method __init__ (line 472) | def __init__(self, resolution=1024, latent_size=512, dlatent_size=512,...
    method call (line 480) | def call(self, inputs):
    method generate_sample (line 485) | def generate_sample(self, seed=5, is_visualize=False):
  class StyleGAN_D (line 503) | class StyleGAN_D(Model):
    method __init__ (line 504) | def __init__(self, resolution=1024, mbstd_group_size=4, mbstd_num_feat...
    method call (line 547) | def call(self, inputs):
  function copy_weights_to_keras_model (line 551) | def copy_weights_to_keras_model(model, all_weights):

FILE: test.py
  function main (line 20) | def main():

FILE: trainer.py
  function id_loss_func (line 10) | def id_loss_func(y_gt, y_pred):
  class Trainer (line 14) | class Trainer(object):
    method __init__ (line 15) | def __init__(self, args, model, data_loader):
    method train (line 67) | def train(self):
    method train_epoch (line 95) | def train_epoch(self):
    method test (line 264) | def test(self):
    method test_reconstruction (line 392) | def test_reconstruction(self, img, errors_dict, display=False, display...
    method generator_gan_loss (line 410) | def generator_gan_loss(self, fake_logit):
    method discriminator_loss (line 417) | def discriminator_loss(self, fake_logit, real_logit):
    method R1_gp (line 432) | def R1_gp(self, D, x):

FILE: utils/general_utils.py
  function read_image (line 15) | def read_image(img_path, resolution, align=False):
  function find_file_by_str (line 24) | def find_file_by_str(search_dir, s):
  function read_SG_image (line 29) | def read_SG_image(img_path, size=256, resize=True):
  function read_and_align_image (line 45) | def read_and_align_image(img_path, output_size=1024):
  function gaussian_image (line 161) | def gaussian_image(size, sigma, dim=2):
  function inverse_gaussian_image (line 179) | def inverse_gaussian_image(size, sigma, dim=2):
  function is_float (line 190) | def is_float(tensor):
  function convert_tensor_to_image (line 198) | def convert_tensor_to_image(tensor):
  function save_image (line 216) | def save_image(img, file_path):
  function mark_landmarks (line 230) | def mark_landmarks(img, lnd, color=None):
  function get_weights (line 250) | def get_weights(slope=0.2):
  function np_permute (line 269) | def np_permute(tensor, permute):

FILE: utils/generate_fake_data.py
  function main (line 17) | def main(args):

FILE: writer.py
  class Writer (line 7) | class Writer(object):
    method set_writer (line 11) | def set_writer(results_dir):
    method add_scalar (line 18) | def add_scalar(tag, val, step):
    method add_image (line 23) | def add_image(tag, val, step):
    method flush (line 33) | def flush():