SYMBOL INDEX (336 symbols across 30 files) 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 50) | def close(self): method choose_shuffled_order (line 60) | def choose_shuffled_order(self): # Note: Images and labels must be add... method add_image (line 65) | def add_image(self, img): method add_labels (line 90) | def add_labels(self, labels): method __enter__ (line 97) | def __enter__(self): method __exit__ (line 100) | def __exit__(self, *args): class ExceptionInfo (line 105) | class ExceptionInfo(object): method __init__ (line 106) | def __init__(self): class WorkerThread (line 112) | class WorkerThread(threading.Thread): method __init__ (line 113) | def __init__(self, task_queue): method run (line 117) | def run(self): class ThreadPool (line 130) | class ThreadPool(object): method __init__ (line 131) | def __init__(self, num_threads): method add_task (line 141) | def add_task(self, func, args=()): method get_result (line 147) | def get_result(self, func): # returns (result, args) method finish (line 154) | def finish(self): method __enter__ (line 158) | def __enter__(self): # for 'with' statement method __exit__ (line 161) | def __exit__(self, *excinfo): method process_items_concurrently (line 164) | def process_items_concurrently(self, item_iterator, process_func=lambd... function display (line 192) | def display(tfrecord_dir): function extract (line 218) | def extract(tfrecord_dir, output_dir): function compare (line 245) | def compare(tfrecord_dir_a, tfrecord_dir_b, ignore_labels): function create_mnist (line 288) | def create_mnist(tfrecord_dir, mnist_dir): function create_mnistrgb (line 312) | def create_mnistrgb(tfrecord_dir, mnist_dir, num_images=1000000, random_... function create_cifar10 (line 329) | def create_cifar10(tfrecord_dir, cifar10_dir): function create_cifar100 (line 356) | def create_cifar100(tfrecord_dir, cifar100_dir): function create_svhn (line 378) | def create_svhn(tfrecord_dir, svhn_dir): function create_lsun (line 405) | def create_lsun(tfrecord_dir, lmdb_dir, resolution=256, max_images=None): function create_lsun_wide (line 438) | def create_lsun_wide(tfrecord_dir, lmdb_dir, width=512, height=384, max_... function create_celeba (line 483) | def create_celeba(tfrecord_dir, celeba_dir, cx=89, cy=121): function create_from_images (line 502) | def create_from_images(tfrecord_dir, image_dir, shuffle): function create_from_hdf5 (line 530) | def create_from_hdf5(tfrecord_dir, hdf5_filename, shuffle): function execute_cmdline (line 545) | def execute_cmdline(argv): FILE: dnnlib/submission/internal/local.py class TargetOptions (line 7) | class TargetOptions(): method __init__ (line 8) | def __init__(self): class Target (line 11) | class Target(): method __init__ (line 12) | def __init__(self): method finalize_submit_config (line 15) | def finalize_submit_config(self, submit_config, host_run_dir): method submit (line 19) | def submit(self, submit_config, host_run_dir): FILE: dnnlib/submission/run_context.py class RunContext (line 23) | class RunContext(object): method __init__ (line 35) | def __init__(self, submit_config: submit.SubmitConfig, config_module: ... method __enter__ (line 57) | def __enter__(self) -> "RunContext": method __exit__ (line 60) | def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> N... method update (line 63) | def update(self, loss: Any = 0, cur_epoch: Any = 0, max_epoch: Any = N... method should_stop (line 74) | def should_stop(self) -> bool: method get_time_since_start (line 78) | def get_time_since_start(self) -> float: method get_time_since_last_update (line 82) | def get_time_since_last_update(self) -> float: method get_last_update_interval (line 86) | def get_last_update_interval(self) -> float: method close (line 90) | def close(self) -> None: method get (line 106) | def get(): FILE: dnnlib/submission/submit.py class SubmitTarget (line 29) | class SubmitTarget(Enum): class PathType (line 37) | class PathType(Enum): class PlatformExtras (line 49) | class PlatformExtras: method __init__ (line 57) | def __init__(self): class SubmitConfig (line 64) | class SubmitConfig(util.EasyDict): method __init__ (line 87) | def __init__(self): function get_path_from_template (line 116) | def get_path_from_template(path_template: str, path_type: PathType = Pat... function get_template_from_path (line 138) | def get_template_from_path(path: str) -> str: function convert_path (line 144) | def convert_path(path: str, path_type: PathType = PathType.AUTO) -> str: function set_user_name_override (line 151) | def set_user_name_override(name: str) -> None: function get_user_name (line 157) | def get_user_name(): function make_run_dir_path (line 173) | def make_run_dir_path(*paths): function _create_run_dir_local (line 192) | def _create_run_dir_local(submit_config: SubmitConfig) -> str: function _get_next_run_id_local (line 211) | def _get_next_run_id_local(run_dir_root: str) -> int: function _populate_run_dir (line 227) | def _populate_run_dir(submit_config: SubmitConfig, run_dir: str) -> None: function run_wrapper (line 256) | def run_wrapper(submit_config: SubmitConfig) -> None: function submit_run (line 310) | def submit_run(submit_config: SubmitConfig, run_func_name: str, **run_fu... FILE: dnnlib/tflib/autosummary.py function _create_var (line 45) | def _create_var(name: str, value_expr: TfExpression) -> TfExpression: function autosummary (line 77) | def autosummary(name: str, value: TfExpressionEx, passthru: TfExpression... function finalize_autosummaries (line 118) | def finalize_autosummaries() -> None: function save_summaries (line 177) | def save_summaries(file_writer, global_step=None): FILE: dnnlib/tflib/custom_ops.py function _find_compiler_bindir (line 36) | def _find_compiler_bindir(): function _get_compute_cap (line 42) | def _get_compute_cap(device): function _get_cuda_gpu_arch_string (line 49) | def _get_cuda_gpu_arch_string(): function _run_cmd (line 56) | def _run_cmd(cmd): function _prepare_nvcc_cli (line 63) | def _prepare_nvcc_cli(opts): function get_plugin (line 87) | def get_plugin(cuda_file): FILE: dnnlib/tflib/network.py function import_handler (line 29) | def import_handler(handler_func): class Network (line 35) | class Network: method __init__ (line 73) | def __init__(self, name: str = None, func_name: Any = None, **static_k... method _init_fields (line 100) | def _init_fields(self) -> None: method _init_graph (line 125) | def _init_graph(self) -> None: method reset_own_vars (line 187) | def reset_own_vars(self) -> None: method reset_vars (line 191) | def reset_vars(self) -> None: method reset_trainables (line 195) | def reset_trainables(self) -> None: method get_output_for (line 199) | def get_output_for(self, *in_expr: TfExpression, return_as_list: bool ... method get_var_local_name (line 234) | def get_var_local_name(self, var_or_global_name: Union[TfExpression, s... method find_var (line 240) | def find_var(self, var_or_local_name: Union[TfExpression, str]) -> TfE... method get_var (line 245) | def get_var(self, var_or_local_name: Union[TfExpression, str]) -> np.n... method set_var (line 250) | def set_var(self, var_or_local_name: Union[TfExpression, str], new_val... method __getstate__ (line 255) | def __getstate__(self) -> dict: method __setstate__ (line 267) | def __setstate__(self, state: dict) -> None: method clone (line 301) | def clone(self, name: str = None, **new_static_kwargs) -> "Network": method copy_own_vars_from (line 316) | def copy_own_vars_from(self, src_net: "Network") -> None: method copy_vars_from (line 321) | def copy_vars_from(self, src_net: "Network") -> None: method copy_trainables_from (line 326) | def copy_trainables_from(self, src_net: "Network") -> None: method convert (line 331) | def convert(self, new_func_name: str, new_name: str = None, **new_stat... method setup_as_moving_average_of (line 341) | def setup_as_moving_average_of(self, src_net: "Network", beta: TfExpre... method run (line 353) | def run(self, method list_ops (line 455) | def list_ops(self) -> List[TfExpression]: method list_layers (line 463) | def list_layers(self) -> List[Tuple[str, TfExpression, List[TfExpressi... method print_layers (line 506) | def print_layers(self, title: str = None, hide_layers_with_no_params: ... method setup_weight_histograms (line 535) | def setup_weight_histograms(self, title: str = None) -> None: function _handle_legacy_output_transforms (line 555) | def _handle_legacy_output_transforms(output_transform, dynamic_kwargs): function _legacy_output_transform_func (line 575) | def _legacy_output_transform_func(*expr, out_mul=1.0, out_add=0.0, out_s... FILE: dnnlib/tflib/ops/fused_bias_act.py function _get_plugin (line 15) | def _get_plugin(): function fused_bias_act (line 34) | def fused_bias_act(x, b=None, axis=1, act='linear', alpha=None, gain=Non... function _fused_bias_act_ref (line 72) | def _fused_bias_act_ref(x, b, axis, act, alpha, gain): function _fused_bias_act_cuda (line 100) | def _fused_bias_act_cuda(x, b, axis, act, alpha, gain): FILE: dnnlib/tflib/ops/upfirdn_2d.py function _get_plugin (line 14) | def _get_plugin(): function upfirdn_2d (line 19) | def upfirdn_2d(x, k, upx=1, upy=1, downx=1, downy=1, padx0=0, padx1=0, p... function _upfirdn_2d_ref (line 66) | def _upfirdn_2d_ref(x, k, upx, upy, downx, downy, padx0, padx1, pady0, p... function _upfirdn_2d_cuda (line 105) | def _upfirdn_2d_cuda(x, k, upx, upy, downx, downy, padx0, padx1, pady0, ... function filter_2d (line 144) | def filter_2d(x, k, gain=1, data_format='NCHW', impl='cuda'): function upsample_2d (line 169) | def upsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl='c... function downsample_2d (line 202) | def downsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl=... function upsample_conv_2d (line 234) | def upsample_conv_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW',... function conv_downsample_2d (line 296) | def conv_downsample_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW... function _shape (line 337) | def _shape(tf_expr, dim_idx): function _setup_kernel (line 344) | def _setup_kernel(k): function _simple_upfirdn_2d (line 353) | def _simple_upfirdn_2d(x, k, up=1, down=1, pad0=0, pad1=0, data_format='... FILE: dnnlib/tflib/optimizer.py class Optimizer (line 26) | class Optimizer: method __init__ (line 38) | def __init__(self, method _get_device (line 82) | def _get_device(self, device_name: str): method register_gradients (line 112) | def register_gradients(self, loss: TfExpression, trainable_vars: Union... method apply_updates (line 154) | def apply_updates(self, allow_no_op: bool = False) -> tf.Operation: method reset_optimizer_state (line 264) | def reset_optimizer_state(self) -> None: method get_loss_scaling_var (line 269) | def get_loss_scaling_var(self, device: str) -> Union[tf.Variable, None]: method apply_loss_scaling (line 273) | def apply_loss_scaling(self, value: TfExpression) -> TfExpression: method undo_loss_scaling (line 280) | def undo_loss_scaling(self, value: TfExpression) -> TfExpression: method _broadcast_nccl (line 287) | def _broadcast_nccl(self): method _broadcast_fallback (line 297) | def _broadcast_fallback(self): class SimpleAdam (line 324) | class SimpleAdam: method __init__ (line 327) | def __init__(self, name="Adam", learning_rate=0.001, beta1=0.9, beta2=... method variables (line 335) | def variables(self): method compute_gradients (line 338) | def compute_gradients(self, loss, var_list, gate_gradients=tf.train.Op... method apply_gradients (line 342) | def apply_gradients(self, grads_and_vars): FILE: dnnlib/tflib/tfutil.py function run (line 28) | def run(*args, **kwargs) -> Any: function is_tf_expression (line 34) | def is_tf_expression(x: Any) -> bool: function shape_to_list (line 39) | def shape_to_list(shape: Iterable[tf.Dimension]) -> List[Union[int, None]]: function flatten (line 44) | def flatten(x: TfExpressionEx) -> TfExpression: function log2 (line 50) | def log2(x: TfExpressionEx) -> TfExpression: function exp2 (line 56) | def exp2(x: TfExpressionEx) -> TfExpression: function lerp (line 62) | def lerp(a: TfExpressionEx, b: TfExpressionEx, t: TfExpressionEx) -> TfE... function lerp_clip (line 68) | def lerp_clip(a: TfExpressionEx, b: TfExpressionEx, t: TfExpressionEx) -... function absolute_name_scope (line 74) | def absolute_name_scope(scope: str) -> tf.name_scope: function absolute_variable_scope (line 79) | def absolute_variable_scope(scope: str, **kwargs) -> tf.variable_scope: function _sanitize_tf_config (line 84) | def _sanitize_tf_config(config_dict: dict = None) -> dict: function init_tf (line 107) | def init_tf(config_dict: dict = None) -> None: function assert_tf_initialized (line 135) | def assert_tf_initialized(): function create_session (line 141) | def create_session(config_dict: dict = None, force_as_default: bool = Fa... function init_uninitialized_vars (line 164) | def init_uninitialized_vars(target_vars: List[tf.Variable] = None) -> None: function set_vars (line 194) | def set_vars(var_to_value_dict: dict) -> None: function create_var_with_large_initial_value (line 220) | def create_var_with_large_initial_value(initial_value: np.ndarray, *args... function convert_images_from_uint8 (line 230) | def convert_images_from_uint8(images, drange=[-1,1], nhwc_to_nchw=False): function convert_images_to_uint8 (line 240) | def convert_images_to_uint8(images, drange=[-1,1], nchw_to_nhwc=False, s... FILE: dnnlib/util.py class EasyDict (line 35) | class EasyDict(dict): method __getattr__ (line 38) | def __getattr__(self, name: str) -> Any: method __setattr__ (line 44) | def __setattr__(self, name: str, value: Any) -> None: method __delattr__ (line 47) | def __delattr__(self, name: str) -> None: class Logger (line 51) | class Logger(object): method __init__ (line 54) | def __init__(self, file_name: str = None, file_mode: str = "w", should... method __enter__ (line 67) | def __enter__(self) -> "Logger": method __exit__ (line 70) | def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> N... method write (line 73) | def write(self, text: str) -> None: method flush (line 86) | def flush(self) -> None: method close (line 93) | def close(self) -> None: function format_time (line 111) | def format_time(seconds: Union[int, float]) -> str: function ask_yes_no (line 125) | def ask_yes_no(question: str) -> bool: function tuple_product (line 135) | def tuple_product(t: Tuple) -> Any: function get_dtype_and_ctype (line 159) | def get_dtype_and_ctype(type_obj: Any) -> Tuple[np.dtype, Any]: function is_pickleable (line 182) | def is_pickleable(obj: Any) -> bool: function get_module_from_obj_name (line 194) | def get_module_from_obj_name(obj_name: str) -> Tuple[types.ModuleType, s... function get_obj_from_module (line 235) | def get_obj_from_module(module: types.ModuleType, obj_name: str) -> Any: function get_obj_by_name (line 245) | def get_obj_by_name(name: str) -> Any: function call_func_by_name (line 251) | def call_func_by_name(*args, func_name: str = None, **kwargs) -> Any: function get_module_dir_by_obj_name (line 259) | def get_module_dir_by_obj_name(obj_name: str) -> str: function is_top_level_function (line 265) | def is_top_level_function(obj: Any) -> bool: function get_top_level_function_name (line 270) | def get_top_level_function_name(obj: Any) -> str: function list_dir_recursively_with_ignore (line 279) | def list_dir_recursively_with_ignore(dir_path: str, ignores: List[str] =... function copy_files_and_create_dirs (line 312) | def copy_files_and_create_dirs(files: List[Tuple[str, str]]) -> None: function is_url (line 328) | def is_url(obj: Any, allow_file_urls: bool = False) -> bool: function open_url (line 346) | def open_url(url: str, cache_dir: str = None, num_attempts: int = 10, ve... FILE: metrics/frechet_inception_distance.py class FID (line 20) | class FID(metric_base.MetricBase): method __init__ (line 21) | def __init__(self, num_images, minibatch_per_gpu, **kwargs): method _evaluate (line 26) | def _evaluate(self, Gs, Gs_kwargs, num_gpus): FILE: metrics/inception_score.py class IS (line 18) | class IS(metric_base.MetricBase): method __init__ (line 19) | def __init__(self, num_images, num_splits, minibatch_per_gpu, **kwargs): method _evaluate (line 25) | def _evaluate(self, Gs, Gs_kwargs, num_gpus): FILE: metrics/linear_separability.py function prob_normalize (line 65) | def prob_normalize(p): function mutual_information (line 70) | def mutual_information(p): function entropy (line 84) | def entropy(p): function conditional_entropy (line 94) | def conditional_entropy(p): class LS (line 103) | class LS(metric_base.MetricBase): method __init__ (line 104) | def __init__(self, num_samples, num_keep, attrib_indices, minibatch_pe... method _evaluate (line 112) | def _evaluate(self, Gs, Gs_kwargs, num_gpus): FILE: metrics/metric_base.py class MetricBase (line 23) | class MetricBase: method __init__ (line 24) | def __init__(self, name): method close (line 34) | def close(self): method _reset (line 37) | def _reset(self, network_pkl=None, run_dir=None, data_dir=None, datase... method configure_progress_reports (line 55) | def configure_progress_reports(self, plo, phi, pmax, psec=15): method run (line 61) | def run(self, network_pkl, run_dir=None, data_dir=None, dataset_args=N... method get_result_str (line 79) | def get_result_str(self): method update_autosummaries (line 90) | def update_autosummaries(self): method _evaluate (line 94) | def _evaluate(self, Gs, Gs_kwargs, num_gpus): method _report_result (line 97) | def _report_result(self, value, suffix='', fmt='%-10.4f'): method _report_progress (line 100) | def _report_progress(self, pcur, pmax, status_str=''): method _get_cache_file_for_reals (line 110) | def _get_cache_file_for_reals(self, extension='pkl', **kwargs): method _get_dataset_obj (line 119) | def _get_dataset_obj(self): method _iterate_reals (line 124) | def _iterate_reals(self, minibatch_size): method _iterate_fakes (line 132) | def _iterate_fakes(self, Gs, minibatch_size, num_gpus): method _get_random_labels_tf (line 139) | def _get_random_labels_tf(self, minibatch_size): class MetricGroup (line 145) | class MetricGroup: method __init__ (line 146) | def __init__(self, metric_kwarg_list): method run (line 149) | def run(self, *args, **kwargs): method get_result_str (line 153) | def get_result_str(self): method update_autosummaries (line 156) | def update_autosummaries(self): class DummyMetric (line 163) | class DummyMetric(MetricBase): method _evaluate (line 164) | def _evaluate(self, Gs, Gs_kwargs, num_gpus): FILE: metrics/perceptual_path_length.py function normalize (line 19) | def normalize(v): function slerp (line 23) | def slerp(a, b, t): class PPL (line 34) | class PPL(metric_base.MetricBase): method __init__ (line 35) | def __init__(self, num_samples, epsilon, space, sampling, crop, miniba... method _evaluate (line 47) | def _evaluate(self, Gs, Gs_kwargs, num_gpus): FILE: metrics/precision_recall.py function batch_pairwise_distances (line 20) | def batch_pairwise_distances(U, V): class DistanceBlock (line 38) | class DistanceBlock(): method __init__ (line 40) | def __init__(self, num_features, num_gpus): method pairwise_distances (line 55) | def pairwise_distances(self, U, V): class ManifoldEstimator (line 61) | class ManifoldEstimator(): method __init__ (line 63) | def __init__(self, distance_block, features, row_batch_size, col_batch... method evaluate (line 96) | def evaluate(self, eval_features, return_realism=False, return_neighbo... function knn_precision_recall_features (line 138) | def knn_precision_recall_features(ref_features, eval_features, feature_n... class PR (line 171) | class PR(metric_base.MetricBase): method __init__ (line 172) | def __init__(self, num_images, nhood_size, minibatch_per_gpu, row_batc... method _evaluate (line 180) | def _evaluate(self, Gs, Gs_kwargs, num_gpus): FILE: pretrained_networks.py function get_path_or_url (line 57) | def get_path_or_url(path_or_gdrive_path): function load_networks (line 64) | def load_networks(path_or_gdrive_path): FILE: projector.py class Projector (line 16) | class Projector: method __init__ (line 17) | def __init__(self): method _info (line 50) | def _info(self, *args): method set_network (line 54) | def set_network(self, Gs, minibatch_size=1): method run (line 134) | def run(self, target_images): method start (line 147) | def start(self, target_images): method step (line 167) | def step(self): method get_cur_step (line 194) | def get_cur_step(self): method get_dlatents (line 197) | def get_dlatents(self): method get_noises (line 200) | def get_noises(self): method get_images (line 203) | def get_images(self): FILE: run_generator.py function generate_images (line 19) | def generate_images(network_pkl, seeds, truncation_psi): function style_mixing_example (line 40) | def style_mixing_example(network_pkl, row_seeds, col_seeds, truncation_p... function _parse_num_range (line 90) | def _parse_num_range(s): function main (line 119) | def main(): FILE: run_metrics.py function run (line 20) | def run(network_pkl, metrics, dataset, data_dir, mirror_augment): function _str_to_bool (line 31) | def _str_to_bool(v): function main (line 52) | def main(): FILE: run_projector.py function project_image (line 21) | def project_image(proj, targets, png_prefix, num_snapshots): function project_generated_images (line 34) | def project_generated_images(network_pkl, seeds, num_snapshots, truncati... function project_real_images (line 55) | def project_real_images(network_pkl, dataset_name, data_dir, num_images,... function _parse_num_range (line 73) | def _parse_num_range(s): function main (line 97) | def main(): FILE: run_training.py function run (line 36) | def run(dataset, data_dir, result_dir, config_id, num_gpus, total_kimg, ... function _str_to_bool (line 124) | def _str_to_bool(v): function _parse_comma_sep (line 134) | def _parse_comma_sep(s): function main (line 156) | def main(): FILE: training/dataset.py class TFRecordDataset (line 19) | class TFRecordDataset: method __init__ (line 20) | def __init__(self, method close (line 122) | def close(self): method configure (line 126) | def configure(self, minibatch_size, lod=0): method get_minibatch_tf (line 135) | def get_minibatch_tf(self): # => images, labels method get_minibatch_np (line 139) | def get_minibatch_np(self, minibatch_size, lod=0): # => images, labels method get_random_labels_tf (line 147) | def get_random_labels_tf(self, minibatch_size): # => labels method get_random_labels_np (line 155) | def get_random_labels_np(self, minibatch_size): # => labels method parse_tfrecord_tf (line 162) | def parse_tfrecord_tf(record): method parse_tfrecord_np (line 171) | def parse_tfrecord_np(record): function load_dataset (line 181) | def load_dataset(class_name=None, data_dir=None, verbose=False, **kwargs): FILE: training/loss.py function G_logistic (line 18) | def G_logistic(G, D, opt, training_set, minibatch_size): function G_logistic_ns (line 27) | def G_logistic_ns(G, D, opt, training_set, minibatch_size): function D_logistic (line 36) | def D_logistic(G, D, opt, training_set, minibatch_size, reals, labels): function D_logistic_r1 (line 52) | def D_logistic_r1(G, D, opt, training_set, minibatch_size, reals, labels... function D_logistic_r2 (line 70) | def D_logistic_r2(G, D, opt, training_set, minibatch_size, reals, labels... function G_wgan (line 92) | def G_wgan(G, D, opt, training_set, minibatch_size): function D_wgan (line 101) | def D_wgan(G, D, opt, training_set, minibatch_size, reals, labels, wgan_... function D_wgan_gp (line 119) | def D_wgan_gp(G, D, opt, training_set, minibatch_size, reals, labels, wg... function G_logistic_ns_pathreg (line 148) | def G_logistic_ns_pathreg(G, D, opt, training_set, minibatch_size, pl_mi... FILE: training/misc.py function open_file_or_url (line 20) | def open_file_or_url(file_or_url): function load_pkl (line 25) | def load_pkl(file_or_url): function save_pkl (line 29) | def save_pkl(obj, filename): function adjust_dynamic_range (line 36) | def adjust_dynamic_range(data, drange_in, drange_out): function create_image_grid (line 43) | def create_image_grid(images, grid_size=None): function convert_to_pil_image (line 60) | def convert_to_pil_image(image, drange=[0,1]): function save_image_grid (line 73) | def save_image_grid(images, filename, drange=[0,1], grid_size=None): function apply_mirror_augment (line 76) | def apply_mirror_augment(minibatch): function parse_config_for_previous_run (line 85) | def parse_config_for_previous_run(run_dir): function setup_snapshot_image_grid (line 95) | def setup_snapshot_image_grid(training_set, FILE: training/networks_stylegan.py function _blur2d (line 21) | def _blur2d(x, f=[1,2,1], normalize=True, flip=False, stride=1): function _upscale2d (line 50) | def _upscale2d(x, factor=2, gain=1): function _downscale2d (line 69) | def _downscale2d(x, factor=2, gain=1): function blur2d (line 95) | def blur2d(x, f=[1,2,1], normalize=True): function upscale2d (line 107) | def upscale2d(x, factor=2): function downscale2d (line 119) | def downscale2d(x, factor=2): function get_weight (line 134) | def get_weight(shape, gain=np.sqrt(2), use_wscale=False, lrmul=1): function dense (line 153) | def dense(x, fmaps, **kwargs): function conv2d (line 163) | def conv2d(x, fmaps, kernel, **kwargs): function upscale2d_conv2d (line 173) | def upscale2d_conv2d(x, fmaps, kernel, fused_scale='auto', **kwargs): function conv2d_downscale2d (line 192) | def conv2d_downscale2d(x, fmaps, kernel, fused_scale='auto', **kwargs): function apply_bias (line 212) | def apply_bias(x, lrmul=1): function leaky_relu (line 222) | def leaky_relu(x, alpha=0.2): function pixel_norm (line 238) | def pixel_norm(x, epsilon=1e-8): function instance_norm (line 246) | def instance_norm(x, epsilon=1e-8): function style_mod (line 260) | def style_mod(x, dlatent, **kwargs): function apply_noise (line 269) | def apply_noise(x, noise_var=None, randomize_noise=True): function minibatch_stddev_layer (line 282) | def minibatch_stddev_layer(x, group_size=4, num_new_features=1): function G_style (line 301) | def G_style( function G_mapping (line 383) | def G_mapping( function G_synthesis (line 439) | def G_synthesis( function D_basic (line 563) | def D_basic( FILE: training/networks_stylegan2.py function get_weight (line 22) | def get_weight(shape, gain=1, use_wscale=True, lrmul=1, weight_var='weig... function dense_layer (line 41) | def dense_layer(x, fmaps, gain=1, use_wscale=True, lrmul=1, weight_var='... function conv2d_layer (line 51) | def conv2d_layer(x, fmaps, kernel, up=False, down=False, resample_kernel... function apply_bias_act (line 66) | def apply_bias_act(x, act='linear', alpha=None, gain=None, lrmul=1, bias... function naive_upsample_2d (line 73) | def naive_upsample_2d(x, factor=2): function naive_downsample_2d (line 80) | def naive_downsample_2d(x, factor=2): function modulated_conv2d_layer (line 89) | def modulated_conv2d_layer(x, y, fmaps, kernel, up=False, down=False, de... function minibatch_stddev_layer (line 132) | def minibatch_stddev_layer(x, group_size=4, num_new_features=1): function G_main (line 151) | def G_main( function G_mapping (line 251) | def G_mapping( function G_synthesis_stylegan_revised (line 307) | def G_synthesis_stylegan_revised( function G_synthesis_stylegan2 (line 417) | def G_synthesis_stylegan2( function D_stylegan (line 512) | def D_stylegan( function D_stylegan2 (line 613) | def D_stylegan2( FILE: training/training_loop.py function process_reals (line 22) | def process_reals(x, labels, lod, mirror_augment, drange_data, drange_net): function training_schedule (line 47) | def training_schedule( function training_loop (line 105) | def training_loop(