SYMBOL INDEX (130 symbols across 13 files)

FILE: data.py
  function provide_data (line 24) | def provide_data(dataset_name='', parent_dir='', batch_size=8, subset=None,
  function _parser_rendered_dataset (line 40) | def _parser_rendered_dataset(
  function multi_input_fn_record (line 130) | def multi_input_fn_record(

FILE: dataset_utils.py
  class AlignedRenderedDataset (line 38) | class AlignedRenderedDataset(object):
    method __init__ (line 39) | def __init__(self, rendered_filepattern, use_semantic_map=True):
    method __iter__ (line 52) | def __iter__(self):
    method __next__ (line 55) | def __next__(self):
    method next (line 58) | def next(self):
  function filter_out_sparse_renders (line 114) | def filter_out_sparse_renders(dataset_dir, splits, ratio_threshold=0.15):
  function _to_example (line 153) | def _to_example(dictionary):
  function _generate_tfrecord_dataset (line 172) | def _generate_tfrecord_dataset(generator,
  function export_aligned_dataset_to_tfrecord (line 193) | def export_aligned_dataset_to_tfrecord(
  function main (line 218) | def main(argv):

FILE: evaluate_quantitative_metrics.py
  function _extract_real_and_fake_from_concatenated_output (line 34) | def _extract_real_and_fake_from_concatenated_output(val_set_out_dir):
  function compute_l1_loss_metric (line 56) | def compute_l1_loss_metric(image_set1_paths, image_set2_paths):
  function compute_psnr_loss_metric (line 76) | def compute_psnr_loss_metric(image_set1_paths, image_set2_paths):
  function evaluate_experiment (line 96) | def evaluate_experiment(val_set_out_dir, title='experiment',
  function main (line 114) | def main(argv):

FILE: layers.py
  class LayerInstanceNorm (line 20) | class LayerInstanceNorm(object):
    method __init__ (line 22) | def __init__(self, scope_suffix='instance_norm'):
    method __call__ (line 26) | def __call__(self, x):
  function layer_norm (line 32) | def layer_norm(x, scope='layer_norm'):
  function pixel_norm (line 36) | def pixel_norm(x):
  function global_avg_pooling (line 48) | def global_avg_pooling(x):
  class FullyConnected (line 52) | class FullyConnected(object):
    method __init__ (line 54) | def __init__(self, n_out_units, scope_suffix='FC'):
    method __call__ (line 64) | def __call__(self, x):
  function init_he_scale (line 69) | def init_he_scale(shape, slope=1.0):
  class LayerConv (line 83) | class LayerConv(object):
    method __init__ (line 86) | def __init__(self,
    method __call__ (line 129) | def __call__(self, x):
  class LayerTransposedConv (line 151) | class LayerTransposedConv(object):
    method __init__ (line 154) | def __init__(self,
    method __call__ (line 197) | def __call__(self, x):
  class ResBlock (line 210) | class ResBlock(object):
    method __init__ (line 211) | def __init__(self,
    method __call__ (line 242) | def __call__(self, x_init):
  class BasicBlock (line 250) | class BasicBlock(object):
    method __init__ (line 251) | def __init__(self,
    method __call__ (line 287) | def __call__(self, x_init):
  class LayerDense (line 298) | class LayerDense(object):
    method __init__ (line 301) | def __init__(self, name, n, use_scaling=False, relu_slope=1.):
    method __call__ (line 322) | def __call__(self, x):
  class LayerPipe (line 327) | class LayerPipe(object):
    method __init__ (line 330) | def __init__(self, functions):
    method __call__ (line 338) | def __call__(self, x, **kwargs):
  function downscale (line 346) | def downscale(x, n=2):
  function upscale (line 361) | def upscale(x, n):
  function tile_and_concatenate (line 378) | def tile_and_concatenate(x, z, n_z):
  function minibatch_mean_variance (line 385) | def minibatch_mean_variance(x):
  function scalar_concat (line 402) | def scalar_concat(x, scalar):

FILE: losses.py
  function gradient_penalty_loss (line 22) | def gradient_penalty_loss(y_xy, xy, iwass_target=1, iwass_lambda=10):
  function KL_loss (line 30) | def KL_loss(mean, logvar):
  function l2_regularize (line 36) | def l2_regularize(x):
  function L1_loss (line 40) | def L1_loss(x, y):
  class PerceptualLoss (line 44) | class PerceptualLoss:
    method __init__ (line 45) | def __init__(self, x, y, image_shape, layers, w_layers, w_act=0.1):
    method __call__ (line 65) | def __call__(self):
  function lsgan_appearance_E_loss (line 69) | def lsgan_appearance_E_loss(disc_response):
  function lsgan_loss (line 76) | def lsgan_loss(disc_response, is_real):
  function multiscale_discriminator_loss (line 84) | def multiscale_discriminator_loss(Ds_responses, is_real):

FILE: networks.py
  class RenderingModel (line 21) | class RenderingModel(object):
    method __init__ (line 23) | def __init__(self, model_name, use_appearance=True):
    method __call__ (line 30) | def __call__(self, x_in, z_app=None):
    method get_appearance_encoder (line 33) | def get_appearance_encoder(self):
    method get_generator (line 36) | def get_generator(self):
    method get_content_encoder (line 39) | def get_content_encoder(self):
  class ModelPGGAN (line 49) | class ModelPGGAN(RenderingModel):
    method __init__ (line 51) | def __init__(self, use_appearance=True):
    method __call__ (line 61) | def __call__(self, x_in, z_app=None):
    method get_appearance_encoder (line 65) | def get_appearance_encoder(self):
    method get_generator (line 68) | def get_generator(self):
    method get_content_encoder (line 71) | def get_content_encoder(self):
  class PatchGANDiscriminator (line 75) | class PatchGANDiscriminator(object):
    method __init__ (line 77) | def __init__(self, name_scope, input_nc, nf=64, n_layers=3, get_fmaps=...
    method __call__ (line 133) | def __call__(self, x, x_cond=None):
  class MultiScaleDiscriminator (line 158) | class MultiScaleDiscriminator(object):
    method __init__ (line 160) | def __init__(self, name_scope, input_nc, num_scales=3, nf=64, n_layers=3,
    method __call__ (line 171) | def __call__(self, x, x_cond=None, params=None):
  class GeneratorPGGAN (line 184) | class GeneratorPGGAN(object):
    method __init__ (line 185) | def __init__(self, appearance_vec_size=8, use_scaling=True,
    method __call__ (line 287) | def __call__(self, x, appearance_embedding=None, encoder_fmaps=None):
  class DRITAppearanceEncoderConcat (line 328) | class DRITAppearanceEncoderConcat(object):
    method __init__ (line 330) | def __init__(self, name_scope, input_nc, normalize_encoder):
    method __call__ (line 361) | def __call__(self, x):

FILE: neural_rerendering.py
  function build_model_fn (line 35) | def build_model_fn(use_exponential_moving_average=True):
  function make_sample_grid_and_save (line 147) | def make_sample_grid_and_save(est, dataset_name, dataset_parent_dir, gri...
  function visualize_image_sequence (line 187) | def visualize_image_sequence(est, dataset_name, dataset_parent_dir,
  function train (line 222) | def train(dataset_name, dataset_parent_dir, load_pretrained_app_encoder,
  function _build_inference_estimator (line 300) | def _build_inference_estimator(model_dir):
  function evaluate_sequence (line 306) | def evaluate_sequence(dataset_name, dataset_parent_dir, virtual_seq_name,
  function evaluate_image_set (line 315) | def evaluate_image_set(dataset_name, dataset_parent_dir, subset_suffix,
  function _load_and_concatenate_image_channels (line 341) | def _load_and_concatenate_image_channels(rgb_path=None, rendered_path=None,
  function infer_dir (line 378) | def infer_dir(model_dir, input_dir, output_dir):
  function joint_interpolation (line 414) | def joint_interpolation(model_dir, app_input_dir, st_app_basename,
  function interpolate_appearance (line 491) | def interpolate_appearance(model_dir, input_dir, target_img_basename,
  function main (line 563) | def main(argv):

FILE: options.py
  function validate_options (line 175) | def validate_options():
  function list_options (line 191) | def list_options():

FILE: pretrain_appearance.py
  function _load_and_concatenate_image_channels (line 30) | def _load_and_concatenate_image_channels(
  function read_single_appearance_input (line 62) | def read_single_appearance_input(rgb_img_path):
  function get_triplet_input_fn (line 73) | def get_triplet_input_fn(dataset_path, dist_file_path=None, k_max_neares...
  function get_tf_triplet_dataset_iter (line 116) | def get_tf_triplet_dataset_iter(
  function build_model_fn (line 146) | def build_model_fn(batch_size, lr_app_pretrain=0.0001, adam_beta1=0.0,
  function compute_dist_matrix (line 214) | def compute_dist_matrix(imageset_dir, dist_file_path, recompute_dist=Fal...
  function train_appearance (line 231) | def train_appearance(train_dir, imageset_dir, dist_file_path):
  function main (line 257) | def main(argv):

FILE: segment_dataset.py
  function get_semantic_color_coding (line 33) | def get_semantic_color_coding():
  function _apply_colors (line 111) | def _apply_colors(seg_images_path, save_dir, idx_to_color):
  function segment_images (line 132) | def segment_images(images_path, xception_frozen_graph_path, save_dir,
  function segment_and_color_dataset (line 184) | def segment_and_color_dataset(dataset_dir, xception_frozen_graph_path,

FILE: staged_model.py
  function create_computation_graph (line 27) | def create_computation_graph(x_in, x_gt, x_app=None, arch_type='pggan',

FILE: style_loss.py
  function gram_matrix (line 25) | def gram_matrix(layer):
  function compute_gram_matrices (line 39) | def compute_gram_matrices(
  function compute_pairwise_style_loss_v2 (line 48) | def compute_pairwise_style_loss_v2(image_paths_list):

FILE: utils.py
  function crop_to_multiple (line 27) | def crop_to_multiple(img, size_multiple=64):
  function get_central_crop (line 36) | def get_central_crop(img, crop_height=512, crop_width=512):
  function load_global_step_from_checkpoint_dir (line 49) | def load_global_step_from_checkpoint_dir(checkpoint_dir):
  function model_vars (line 66) | def model_vars(prefix):
  function to_png (line 85) | def to_png(x):
  function images_to_grid (line 104) | def images_to_grid(images):
  function save_images (line 119) | def save_images(image, output_dir, cur_nimg):
  class HookReport (line 139) | class HookReport(tf.train.SessionRunHook):
    method __init__ (line 154) | def __init__(self, period, batch_size):
    method disable (line 167) | def disable(self):
    method begin (line 181) | def begin(self):
    method before_run (line 187) | def before_run(self, run_context):
    method after_run (line 194) | def after_run(self, run_context, run_values):
    method end (line 226) | def end(self, session=None):
    method log_tensor (line 230) | def log_tensor(cls, tensor, name):