SYMBOL INDEX (260 symbols across 18 files)

FILE: UV_manipulation_2.py
  function load_512_ifo_dict (line 16) | def load_512_ifo_dict():
  function load_mean (line 21) | def load_mean():
  function alignment (line 25) | def alignment(mesh):
  function import_uv_info (line 35) | def import_uv_info(instance, res, uv_layout='oval', topology='full'):
  function from_UV_2_3D (line 61) | def from_UV_2_3D(uv, uv_layout='oval', topology='full', plot=False):

FILE: config.py
  class EasyDict (line 13) | class EasyDict(dict):
    method __init__ (line 14) | def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs)
    method __getattr__ (line 15) | def __getattr__(self, name): return self[name]
    method __setattr__ (line 16) | def __setattr__(self, name, value): self[name] = value
    method __delattr__ (line 17) | def __delattr__(self, name): del self[name]

FILE: config_test.py
  class EasyDict (line 13) | class EasyDict(dict):
    method __init__ (line 14) | def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs)
    method __getattr__ (line 15) | def __getattr__(self, name): return self[name]
    method __setattr__ (line 16) | def __setattr__(self, name, value): self[name] = value
    method __delattr__ (line 17) | def __delattr__(self, name): del self[name]

FILE: dataset.py
  class TFRecordDataset (line 21) | class TFRecordDataset:
    method __init__ (line 22) | def __init__(self,
    method configure (line 124) | def configure(self, minibatch_size, lod=0):
    method get_minibatch_tf (line 133) | def get_minibatch_tf(self): # => images, labels
    method get_minibatch_np (line 137) | def get_minibatch_np(self, minibatch_size, lod=0): # => images, labels
    method get_random_labels_tf (line 144) | def get_random_labels_tf(self, minibatch_size): # => labels
    method get_random_labels_np (line 151) | def get_random_labels_np(self, minibatch_size): # => labels
    method parse_tfrecord_tf (line 157) | def parse_tfrecord_tf(self, record):
    method parse_tfrecord_np (line 164) | def parse_tfrecord_np(self, record):
  class SyntheticDataset (line 173) | class SyntheticDataset:
    method __init__ (line 174) | def __init__(self, resolution=1024, num_channels=3, dtype='uint8', dyn...
    method configure (line 192) | def configure(self, minibatch_size, lod=0):
    method get_minibatch_tf (line 197) | def get_minibatch_tf(self): # => images, labels
    method get_minibatch_np (line 205) | def get_minibatch_np(self, minibatch_size, lod=0): # => images, labels
    method get_random_labels_tf (line 211) | def get_random_labels_tf(self, minibatch_size): # => labels
    method get_random_labels_np (line 215) | def get_random_labels_np(self, minibatch_size): # => labels
    method _generate_images (line 221) | def _generate_images(self, minibatch, lod, shape): # to be overridden ...
    method _generate_labels (line 224) | def _generate_labels(self, minibatch): # to be overridden by subclasses
  function load_dataset (line 230) | def load_dataset(class_name='dataset.TFRecordDataset', data_dir=None, ve...

FILE: dataset_tool.py
  function error (line 26) | def error(msg):
  class TFRecordExporter (line 32) | class TFRecordExporter:
    method __init__ (line 33) | def __init__(self, tfrecord_dir, expected_images, print_progress=True,...
    method close (line 49) | def close(self):
    method choose_shuffled_order (line 59) | def choose_shuffled_order(self): # Note: Images and labels must be add...
    method add_image (line 64) | def add_image(self, img):
    method add_shape (line 89) | def add_shape(self, img):
    method add_both (line 113) | def add_both(self, img):
    method add_labels (line 137) | def add_labels(self, labels):
    method __enter__ (line 144) | def __enter__(self):
    method __exit__ (line 147) | def __exit__(self, *args):
  class ExceptionInfo (line 152) | class ExceptionInfo(object):
    method __init__ (line 153) | def __init__(self):
  class WorkerThread (line 159) | class WorkerThread(threading.Thread):
    method __init__ (line 160) | def __init__(self, task_queue):
    method run (line 164) | def run(self):
  class ThreadPool (line 177) | class ThreadPool(object):
    method __init__ (line 178) | def __init__(self, num_threads):
    method add_task (line 188) | def add_task(self, func, args=()):
    method get_result (line 194) | def get_result(self, func): # returns (result, args)
    method finish (line 201) | def finish(self):
    method __enter__ (line 205) | def __enter__(self): # for 'with' statement
    method __exit__ (line 208) | def __exit__(self, *excinfo):
    method process_items_concurrently (line 211) | def process_items_concurrently(self, item_iterator, process_func=lambd...
  function display (line 239) | def display(tfrecord_dir):
  function extract (line 265) | def extract(tfrecord_dir, output_dir):
  function compare (line 292) | def compare(tfrecord_dir_a, tfrecord_dir_b, ignore_labels):
  function create_mnist (line 335) | def create_mnist(tfrecord_dir, mnist_dir):
  function create_mnistrgb (line 359) | def create_mnistrgb(tfrecord_dir, mnist_dir, num_images=1000000, random_...
  function create_cifar10 (line 376) | def create_cifar10(tfrecord_dir, cifar10_dir):
  function create_cifar100 (line 403) | def create_cifar100(tfrecord_dir, cifar100_dir):
  function create_svhn (line 425) | def create_svhn(tfrecord_dir, svhn_dir):
  function create_lsun (line 452) | def create_lsun(tfrecord_dir, lmdb_dir, resolution=256, max_images=None):
  function create_celeba (line 485) | def create_celeba(tfrecord_dir, celeba_dir, cx=89, cy=121):
  function create_celebahq (line 504) | def create_celebahq(tfrecord_dir, celeba_dir, delta_dir, num_threads=4, ...
  function create_from_images (line 648) | def create_from_images(tfrecord_dir, image_dir, shuffle):
  function create_from_pkl (line 682) | def create_from_pkl(tfrecord_dir, image_dir, shuffle):
  function create_from_pkl_img (line 713) | def create_from_pkl_img(tfrecord_dir, image_dir, pickle_dir, shuffle):
  function create_from_pkl_img_norm (line 746) | def create_from_pkl_img_norm(tfrecord_dir, mein3d_image_dir, mein3d_pick...
  function create_from_hdf5 (line 829) | def create_from_hdf5(tfrecord_dir, hdf5_filename, shuffle):
  function execute_cmdline (line 844) | def execute_cmdline(argv):

FILE: legacy.py
  class LegacyUnpickler (line 19) | class LegacyUnpickler(pickle.Unpickler):
    method __init__ (line 20) | def __init__(self, *args, **kwargs):
    method find_class (line 23) | def find_class(self, module, name):
  function patch_theano_gan (line 39) | def patch_theano_gan(state):
  function ignore_unknown_theano_network (line 103) | def ignore_unknown_theano_network(state):

FILE: loss.py
  function fp32 (line 15) | def fp32(*values):
  function G_wgan_acgan (line 24) | def G_wgan_acgan(G, D, opt, training_set, minibatch_size,
  function D_wgangp_acgan (line 43) | def D_wgangp_acgan(G, D, opt, training_set, minibatch_size, reals, labels,

FILE: metrics/frechet_inception_distance.py
  class InvalidFIDException (line 48) | class InvalidFIDException(Exception):
  function create_inception_graph (line 52) | def create_inception_graph(pth):
  function _get_inception_layer (line 64) | def _get_inception_layer(sess):
  function get_activations (line 88) | def get_activations(images, sess, batch_size=50, verbose=False):
  function calculate_frechet_distance (line 125) | def calculate_frechet_distance(mu1, sigma1, mu2, sigma2):
  function calculate_activation_statistics (line 156) | def calculate_activation_statistics(images, sess, batch_size=50, verbose...
  function check_or_download_inception (line 184) | def check_or_download_inception(inception_path):
  function _handle_path (line 202) | def _handle_path(path, sess):
  function calculate_fid_given_paths (line 215) | def calculate_fid_given_paths(paths, inception_path):
  class API (line 249) | class API:
    method __init__ (line 250) | def __init__(self, num_images, image_shape, image_dtype, minibatch_size):
    method get_metric_names (line 257) | def get_metric_names(self):
    method get_metric_formatting (line 260) | def get_metric_formatting(self):
    method begin (line 263) | def begin(self, mode):
    method feed (line 267) | def feed(self, mode, minibatch):
    method end (line 271) | def end(self, mode):

FILE: metrics/inception_score.py
  function get_inception_score (line 41) | def get_inception_score(images, splits=10):
  function _init_inception (line 72) | def _init_inception():
  class API (line 121) | class API:
    method __init__ (line 122) | def __init__(self, num_images, image_shape, image_dtype, minibatch_size):
    method get_metric_names (line 128) | def get_metric_names(self):
    method get_metric_formatting (line 131) | def get_metric_formatting(self):
    method begin (line 134) | def begin(self, mode):
    method feed (line 138) | def feed(self, mode, minibatch):
    method end (line 141) | def end(self, mode):

FILE: metrics/ms_ssim.py
  function _FSpecialGauss (line 25) | def _FSpecialGauss(size, sigma):
  function _SSIMForMultiScale (line 38) | def _SSIMForMultiScale(img1, img2, max_val=255, filter_size=11, filter_s...
  function _HoxDownsample (line 110) | def _HoxDownsample(img):
  function msssim (line 113) | def msssim(img1, img2, max_val=255, filter_size=11, filter_sigma=1.5, k1...
  class API (line 176) | class API:
    method __init__ (line 177) | def __init__(self, num_images, image_shape, image_dtype, minibatch_size):
    method get_metric_names (line 181) | def get_metric_names(self):
    method get_metric_formatting (line 184) | def get_metric_formatting(self):
    method begin (line 187) | def begin(self, mode):
    method feed (line 191) | def feed(self, mode, minibatch):
    method end (line 196) | def end(self, mode):

FILE: metrics/sliced_wasserstein.py
  function get_descriptors_for_minibatch (line 13) | def get_descriptors_for_minibatch(minibatch, nhood_size, nhoods_per_image):
  function finalize_descriptors (line 27) | def finalize_descriptors(desc):
  function sliced_wasserstein (line 38) | def sliced_wasserstein(A, B, dir_repeats, dirs_per_repeat):
  function downscale_minibatch (line 55) | def downscale_minibatch(minibatch, lod):
  function pyr_down (line 72) | def pyr_down(minibatch): # matches cv2.pyrDown()
  function pyr_up (line 76) | def pyr_up(minibatch): # matches cv2.pyrUp()
  function generate_laplacian_pyramid (line 83) | def generate_laplacian_pyramid(minibatch, num_levels):
  function reconstruct_laplacian_pyramid (line 90) | def reconstruct_laplacian_pyramid(pyramid):
  class API (line 98) | class API:
    method __init__ (line 99) | def __init__(self, num_images, image_shape, image_dtype, minibatch_size):
    method get_metric_names (line 110) | def get_metric_names(self):
    method get_metric_formatting (line 113) | def get_metric_formatting(self):
    method begin (line 116) | def begin(self, mode):
    method feed (line 120) | def feed(self, mode, minibatch):
    method end (line 125) | def end(self, mode):

FILE: misc.py
  function load_pkl (line 27) | def load_pkl(filename):
  function save_pkl (line 31) | def save_pkl(obj, filename):
  function adjust_dynamic_range (line 38) | def adjust_dynamic_range(data, drange_in, drange_out):
  function create_image_grid (line 45) | def create_image_grid(images, grid_size=None):
  function convert_to_pil_image (line 62) | def convert_to_pil_image(image, drange=[0,1]):
  function save_image (line 75) | def save_image(image, filename, drange=[0,1], quality=95):
  function save_image_grid (line 82) | def save_image_grid(images, filename, drange=[0,1], grid_size=None):
  class OutputLogger (line 98) | class OutputLogger(object):
    method __init__ (line 99) | def __init__(self):
    method set_log_file (line 103) | def set_log_file(self, filename, mode='wt'):
    method write (line 110) | def write(self, data):
    method flush (line 116) | def flush(self):
  class TeeOutputStream (line 120) | class TeeOutputStream(object):
    method __init__ (line 121) | def __init__(self, child_streams, autoflush=False):
    method write (line 125) | def write(self, data):
    method flush (line 131) | def flush(self):
  function init_output_logging (line 137) | def init_output_logging():
  function set_output_log_file (line 144) | def set_output_log_file(filename, mode='wt'):
  function create_result_subdir (line 151) | def create_result_subdir(result_dir, desc):
  function format_time (line 187) | def format_time(seconds):
  function locate_result_subdir (line 197) | def locate_result_subdir(run_id_or_result_subdir):
  function list_network_pkls (line 218) | def list_network_pkls(run_id_or_result_subdir, include_final=True):
  function locate_network_pkl (line 227) | def locate_network_pkl(run_id_or_result_subdir_or_network_pkl, snapshot=...
  function get_id_string_for_network_pkl (line 244) | def get_id_string_for_network_pkl(network_pkl):
  function load_network_pkl (line 251) | def load_network_pkl(run_id_or_result_subdir_or_network_pkl, snapshot=No...
  function random_latents (line 254) | def random_latents(num_latents, G, random_state=None):
  function load_dataset_for_previous_run (line 260) | def load_dataset_for_previous_run(run_id, **kwargs): # => dataset_obj, m...
  function apply_mirror_augment (line 305) | def apply_mirror_augment(minibatch):
  function draw_text_label (line 316) | def draw_text_label(img, text, x, y, alignx=0.5, aligny=0.5, color=255, ...
  function setup_text_label (line 329) | def setup_text_label(text, font='Calibri', fontsize=32, padding=6, glow_...

FILE: myutil.py
  function crop_im (line 6) | def crop_im(img):
  function crop_im_512 (line 12) | def crop_im_512(img_377):
  function crop_im_377 (line 26) | def crop_im_377(img_512):
  function concat_image (line 42) | def concat_image(im1, im2):
  function rgb2tf (line 53) | def rgb2tf(img):
  function tf2rgb (line 56) | def tf2rgb(img):
  function files_gen (line 59) | def files_gen(path):
  function files (line 64) | def files(path):

FILE: networks.py
  function lerp (line 15) | def lerp(a, b, t): return a + (b - a) * t
  function lerp_clip (line 16) | def lerp_clip(a, b, t): return a + (b - a) * tf.clip_by_value(t, 0.0, 1.0)
  function cset (line 17) | def cset(cur_lambda, new_cond, new_lambda): return lambda: tf.cond(new_c...
  function get_weight (line 22) | def get_weight(shape, gain=np.sqrt(2), use_wscale=False, fan_in=None):
  function dense (line 34) | def dense(x, fmaps, gain=np.sqrt(2), use_wscale=False):
  function conv2d (line 44) | def conv2d(x, fmaps, kernel, gain=np.sqrt(2), use_wscale=False):
  function apply_bias (line 53) | def apply_bias(x):
  function leaky_relu (line 64) | def leaky_relu(x, alpha=0.2):
  function upscale2d (line 72) | def upscale2d(x, factor=2):
  function upscale2d_conv2d (line 86) | def upscale2d_conv2d(x, fmaps, kernel, gain=np.sqrt(2), use_wscale=False):
  function downscale2d (line 98) | def downscale2d(x, factor=2):
  function conv2d_downscale2d (line 109) | def conv2d_downscale2d(x, fmaps, kernel, gain=np.sqrt(2), use_wscale=Fal...
  function pixel_norm (line 120) | def pixel_norm(x, epsilon=1e-8):
  function minibatch_stddev_layer (line 127) | def minibatch_stddev_layer(x, group_size=4):
  function G_paper (line 144) | def G_paper(
  function D_paper (line 278) | def D_paper(

FILE: test.py
  function setup_snapshot_image_grid (line 22) | def setup_snapshot_image_grid(G, training_set,
  function process_reals (line 56) | def process_reals(x, lod, mirror_augment, drange_data, drange_net):
  class TrainingSchedule (line 86) | class TrainingSchedule:
    method __init__ (line 87) | def __init__(
  function train_progressive_gan (line 134) | def train_progressive_gan(

FILE: tfutil.py
  function run (line 18) | def run(*args, **kwargs): # Run the specified ops in the default session.
  function is_tf_expression (line 21) | def is_tf_expression(x):
  function shape_to_list (line 24) | def shape_to_list(shape):
  function flatten (line 27) | def flatten(x):
  function log2 (line 31) | def log2(x):
  function exp2 (line 35) | def exp2(x):
  function lerp (line 39) | def lerp(a, b, t):
  function lerp_clip (line 43) | def lerp_clip(a, b, t):
  function absolute_name_scope (line 47) | def absolute_name_scope(scope): # Forcefully enter the specified name sc...
  function init_tf (line 53) | def init_tf(config_dict=dict()):
  function create_session (line 62) | def create_session(config_dict=dict(), force_as_default=False):
  function init_uninited_vars (line 82) | def init_uninited_vars(vars=None):
  function set_vars (line 103) | def set_vars(var_to_value_dict):
  function autosummary (line 137) | def autosummary(name, value):
  function finalize_autosummaries (line 156) | def finalize_autosummaries():
  function _create_autosummary_var (line 174) | def _create_autosummary_var(name, value_expr):
  function save_summaries (line 199) | def save_summaries(filewriter, global_step=None):
  function import_module (line 210) | def import_module(module_or_obj_name):
  function find_obj_in_module (line 222) | def find_obj_in_module(module, relative_obj_name):
  function import_obj (line 228) | def import_obj(obj_name):
  function call_func_by_name (line 232) | def call_func_by_name(*args, func=None, **kwargs):
  class Optimizer (line 244) | class Optimizer:
    method __init__ (line 245) | def __init__(
    method register_gradients (line 275) | def register_gradients(self, loss, vars):
    method apply_updates (line 302) | def apply_updates(self):
    method reset_optimizer_state (line 373) | def reset_optimizer_state(self):
    method get_loss_scaling_var (line 377) | def get_loss_scaling_var(self, device):
    method apply_loss_scaling (line 386) | def apply_loss_scaling(self, value):
    method undo_loss_scaling (line 393) | def undo_loss_scaling(self, value):
  class Network (line 414) | class Network:
    method __init__ (line 415) | def __init__(self,
    method _init_fields (line 433) | def _init_fields(self):
    method _init_graph (line 454) | def _init_graph(self):
    method reset_vars (line 492) | def reset_vars(self):
    method reset_trainables (line 496) | def reset_trainables(self):
    method get_output_for (line 500) | def get_output_for(self, *in_expr, return_as_list=False, **dynamic_kwa...
    method get_var_localname (line 514) | def get_var_localname(self, var_or_globalname):
    method find_var (line 523) | def find_var(self, var_or_localname):
    method get_var (line 529) | def get_var(self, var_or_localname):
    method set_var (line 534) | def set_var(self, var_or_localname, new_value):
    method __getstate__ (line 538) | def __getstate__(self):
    method __setstate__ (line 548) | def __setstate__(self, state):
    method clone (line 574) | def clone(self, name=None):
    method copy_vars_from (line 587) | def copy_vars_from(self, src_net):
    method copy_trainables_from (line 593) | def copy_trainables_from(self, src_net):
    method convert (line 599) | def convert(self, name=None, func=None, **static_kwargs):
    method setup_as_moving_average_of (line 606) | def setup_as_moving_average_of(self, src_net, beta=0.99, beta_nontrain...
    method fit (line 619) | def fit(self, *in_arrays,
    method run (line 663) | def run(self, *in_arrays,
    method list_layers (line 723) | def list_layers(self):
    method print_layers (line 755) | def print_layers(self, title=None, hide_layers_with_no_params=False):
    method setup_weight_histograms (line 780) | def setup_weight_histograms(self, title=None):

FILE: train.py
  function setup_snapshot_image_grid (line 22) | def setup_snapshot_image_grid(G, training_set,
  function process_reals (line 56) | def process_reals(x, lod, mirror_augment, drange_data, drange_net):
  class TrainingSchedule (line 86) | class TrainingSchedule:
    method __init__ (line 87) | def __init__(
  function train_progressive_gan (line 134) | def train_progressive_gan(

FILE: util_scripts.py
  function get_generator (line 35) | def get_generator(run_id, snapshot=None, image_shrink=1, minibatch_size=8):
  function fit_real_images (line 49) | def fit_real_images(run_id, snapshot=None, num_pngs=1, image_shrink=1, p...
  function generate_fake_images_glob (line 91) | def generate_fake_images_glob(run_id, snapshot=None, grid_size=[1,1], nu...
  function generate_fake_images (line 111) | def generate_fake_images(run_id, snapshot=None, grid_size=[1,1],batch_si...
  function generate_interpolation_video (line 149) | def generate_interpolation_video(run_id, snapshot=None, grid_size=[1,1],...
  function generate_interpolation_images (line 188) | def generate_interpolation_images(run_id, snapshot=None, grid_size=[1,1]...
  function generate_interpolation_video_bydim (line 239) | def generate_interpolation_video_bydim(run_id, snapshot=None, grid_size=...
  function generate_training_video (line 280) | def generate_training_video(run_id, duration_sec=20.0, time_warp=1.5, mp...
  function evaluate_metrics (line 331) | def evaluate_metrics(run_id, log, metrics, num_images, real_passes, mini...
  function fix_obj (line 431) | def fix_obj(fp):