SYMBOL INDEX (790 symbols across 54 files)

FILE: Image Processor/align_images.py
  function multi_worker (line 19) | def multi_worker(queue):
  function vis (line 37) | def vis(image_path, r):
  function detect (line 45) | def detect(model, image_path):
  function align (line 54) | def align(image, mask_rcnn_res):
  function pad_image (line 74) | def pad_image(image, side_length=512):
  function get_largest_bbox (line 90) | def get_largest_bbox(mask):
  function rotate_image (line 103) | def rotate_image(image, angle, image_centre=None):
  function make_bb_mask (line 112) | def make_bb_mask(image, top_left, bottom_right):
  function angle_trunc (line 124) | def angle_trunc(a):
  function get_tilt (line 130) | def get_tilt(p1, p2, tilt_from='vertical', degrees=True):
  function get_best_bbox (line 150) | def get_best_bbox(result):
  class myMaskRCNNConfig (line 161) | class myMaskRCNNConfig(Config):

FILE: Image Processor/cv_tools.py
  function show (line 17) | def show(image: np.ndarray) -> None:
  function resize (line 28) | def resize(image: np.ndarray, resize_factor=None, resize_to=None) -> np....
  function crop (line 62) | def crop(image: np.ndarray, top_left: Tuple[int], bottom_right: Tuple[in...
  function compute_PCA (line 71) | def compute_PCA(image: np.ndarray, display=False) -> tuple:
  function threshold (line 98) | def threshold(image: np.ndarray, show_thresholded: bool = False, show_mo...
  function find_contours (line 126) | def find_contours(image: np.ndarray) -> List[np.ndarray]:
  function draw_contours (line 142) | def draw_contours(image: np.ndarray, contours: List[np.ndarray]) -> np.n...
  function draw_lines (line 154) | def draw_lines(image: np.ndarray, lines: List[np.ndarray]) -> np.ndarray:
  function hough_lines (line 183) | def hough_lines(image: np.ndarray) -> (np.ndarray, List[np.ndarray]):
  function filter_lines (line 203) | def filter_lines(lines: List[np.ndarray], angle_thresh: list = [(0, 45),...
  function segment_by_angle_kmeans (line 234) | def segment_by_angle_kmeans(lines: np.ndarray, k: int = 2, **kwargs) -> ...
  function segmented_intersections (line 268) | def segmented_intersections(lines: np.ndarray) -> List[List[int]]:
  function intersection (line 281) | def intersection(line1: np.ndarray, line2: np.ndarray) -> List[int]:
  function filter_intersects (line 303) | def filter_intersects(intersects: List[List[int]], pad_thickness: int, h...
  function draw_intersections (line 329) | def draw_intersections(image: np.ndarray, intersects: list, pad_thicknes...
  function pad_to_square (line 348) | def pad_to_square(img, pad_value=0):
  function find_bbox (line 395) | def find_bbox(contours):
  function crop_resize (line 411) | def crop_resize(img, resize_size=64, foreground='black', show_bbox=False):

FILE: Image Processor/download_utils.py
  function download_file_from_google_drive (line 3) | def download_file_from_google_drive(id, destination):

FILE: Image Processor/mrcnn/config.py
  class Config (line 17) | class Config(object):
    method __init__ (line 213) | def __init__(self):
    method display (line 230) | def display(self):

FILE: Image Processor/mrcnn/model.py
  function log (line 38) | def log(text, array=None):
  class BatchNorm (line 53) | class BatchNorm(KL.BatchNormalization):
    method call (line 61) | def call(self, inputs, training=None):
  function compute_backbone_shapes (line 71) | def compute_backbone_shapes(config, image_shape):
  function identity_block (line 95) | def identity_block(input_tensor, kernel_size, filters, stage, block,
  function conv_block (line 130) | def conv_block(input_tensor, kernel_size, filters, stage, block,
  function resnet_graph (line 171) | def resnet_graph(input_image, architecture, stage5=False, train_bn=True):
  function apply_box_deltas_graph (line 213) | def apply_box_deltas_graph(boxes, deltas):
  function clip_boxes_graph (line 237) | def clip_boxes_graph(boxes, window):
  class ProposalLayer (line 255) | class ProposalLayer(KE.Layer):
    method __init__ (line 270) | def __init__(self, proposal_count, nms_threshold, config=None, **kwargs):
    method call (line 276) | def call(self, inputs):
    method compute_output_shape (line 331) | def compute_output_shape(self, input_shape):
  function log2_graph (line 339) | def log2_graph(x):
  class PyramidROIAlign (line 344) | class PyramidROIAlign(KE.Layer):
    method __init__ (line 364) | def __init__(self, pool_shape, **kwargs):
    method call (line 368) | def call(self, inputs):
    method compute_output_shape (line 449) | def compute_output_shape(self, input_shape):
  function overlaps_graph (line 457) | def overlaps_graph(boxes1, boxes2):
  function detection_targets_graph (line 486) | def detection_targets_graph(proposals, gt_class_ids, gt_boxes, gt_masks,...
  class DetectionTargetLayer (line 622) | class DetectionTargetLayer(KE.Layer):
    method __init__ (line 647) | def __init__(self, config, **kwargs):
    method call (line 651) | def call(self, inputs):
    method compute_output_shape (line 667) | def compute_output_shape(self, input_shape):
    method compute_mask (line 676) | def compute_mask(self, inputs, mask=None):
  function refine_detections_graph (line 684) | def refine_detections_graph(rois, probs, deltas, window, config):
  class DetectionLayer (line 782) | class DetectionLayer(KE.Layer):
    method __init__ (line 791) | def __init__(self, config=None, **kwargs):
    method call (line 795) | def call(self, inputs):
    method compute_output_shape (line 822) | def compute_output_shape(self, input_shape):
  function rpn_graph (line 830) | def rpn_graph(feature_map, anchors_per_location, anchor_stride):
  function build_rpn_model (line 874) | def build_rpn_model(anchor_stride, anchors_per_location, depth):
  function fpn_classifier_graph (line 900) | def fpn_classifier_graph(rois, feature_maps, image_meta,
  function build_fpn_mask_graph (line 956) | def build_fpn_mask_graph(rois, feature_maps, image_meta,
  function smooth_l1_loss (line 1012) | def smooth_l1_loss(y_true, y_pred):
  function rpn_class_loss_graph (line 1022) | def rpn_class_loss_graph(rpn_match, rpn_class_logits):
  function rpn_bbox_loss_graph (line 1047) | def rpn_bbox_loss_graph(config, target_bbox, rpn_match, rpn_bbox):
  function mrcnn_class_loss_graph (line 1076) | def mrcnn_class_loss_graph(target_class_ids, pred_class_logits,
  function mrcnn_bbox_loss_graph (line 1112) | def mrcnn_bbox_loss_graph(target_bbox, target_class_ids, pred_bbox):
  function mrcnn_mask_loss_graph (line 1143) | def mrcnn_mask_loss_graph(target_masks, target_class_ids, pred_masks):
  function load_image_gt (line 1186) | def load_image_gt(dataset, config, image_id, augment=False, augmentation...
  function build_detection_targets (line 1289) | def build_detection_targets(rpn_rois, gt_class_ids, gt_boxes, gt_masks, ...
  function build_rpn_targets (line 1445) | def build_rpn_targets(image_shape, anchors, gt_class_ids, gt_boxes, conf...
  function generate_random_rois (line 1556) | def generate_random_rois(image_shape, count, gt_class_ids, gt_boxes):
  function data_generator (line 1630) | def data_generator(dataset, config, shuffle=True, augment=False, augment...
  class MaskRCNN (line 1820) | class MaskRCNN():
    method __init__ (line 1826) | def __init__(self, mode, config, model_dir):
    method build (line 1839) | def build(self, mode, config):
    method find_last (line 2066) | def find_last(self):
    method load_weights (line 2095) | def load_weights(self, filepath, by_name=False, exclude=None):
    method get_imagenet_weights (line 2139) | def get_imagenet_weights(self):
    method compile (line 2153) | def compile(self, learning_rate, momentum):
    method set_trainable (line 2201) | def set_trainable(self, layer_regex, keras_model=None, indent=0, verbo...
    method set_log_dir (line 2238) | def set_log_dir(self, model_path=None):
    method train (line 2276) | def train(self, train_dataset, val_dataset, learning_rate, epochs, lay...
    method mold_inputs (line 2378) | def mold_inputs(self, images):
    method unmold_detections (line 2417) | def unmold_detections(self, detections, mrcnn_mask, original_image_shape,
    method detect (line 2482) | def detect(self, images, verbose=0):
    method detect_molded (line 2540) | def detect_molded(self, molded_images, image_metas, verbose=0):
    method get_anchors (line 2598) | def get_anchors(self, image_shape):
    method ancestor (line 2620) | def ancestor(self, tensor, name, checked=None):
    method find_trainable_layer (line 2648) | def find_trainable_layer(self, layer):
    method get_trainable_layers (line 2657) | def get_trainable_layers(self):
    method run_graph (line 2669) | def run_graph(self, images, outputs, image_metas=None):
  function compose_image_meta (line 2725) | def compose_image_meta(image_id, original_image_shape, image_shape,
  function parse_image_meta (line 2750) | def parse_image_meta(meta):
  function parse_image_meta_graph (line 2774) | def parse_image_meta_graph(meta):
  function mold_image (line 2798) | def mold_image(images, config):
  function unmold_image (line 2806) | def unmold_image(normalized_images, config):
  function trim_zeros_graph (line 2815) | def trim_zeros_graph(boxes, name='trim_zeros'):
  function batch_pack_graph (line 2827) | def batch_pack_graph(x, counts, num_rows):
  function norm_boxes_graph (line 2837) | def norm_boxes_graph(boxes, shape):
  function denorm_boxes_graph (line 2854) | def denorm_boxes_graph(boxes, shape):

FILE: Image Processor/mrcnn/parallel_model.py
  class ParallelModel (line 22) | class ParallelModel(KM.Model):
    method __init__ (line 30) | def __init__(self, keras_model, gpu_count):
    method __getattribute__ (line 41) | def __getattribute__(self, attrname):
    method summary (line 48) | def summary(self, *args, **kwargs):
    method make_parallel (line 54) | def make_parallel(self):
  function build_model (line 128) | def build_model(x_train, num_classes):

FILE: Image Processor/mrcnn/utils.py
  function extract_bboxes (line 34) | def extract_bboxes(mask):
  function compute_iou (line 60) | def compute_iou(box, boxes, box_area, boxes_area):
  function compute_overlaps (line 81) | def compute_overlaps(boxes1, boxes2):
  function compute_overlaps_masks (line 100) | def compute_overlaps_masks(masks1, masks2):
  function non_max_suppression (line 122) | def non_max_suppression(boxes, scores, threshold):
  function apply_box_deltas (line 159) | def apply_box_deltas(boxes, deltas):
  function box_refinement_graph (line 183) | def box_refinement_graph(box, gt_box):
  function box_refinement (line 209) | def box_refinement(box, gt_box):
  class Dataset (line 239) | class Dataset(object):
    method __init__ (line 255) | def __init__(self, class_map=None):
    method add_class (line 262) | def add_class(self, source, class_id, class_name):
    method add_image (line 276) | def add_image(self, source, image_id, path, **kwargs):
    method image_reference (line 285) | def image_reference(self, image_id):
    method prepare (line 294) | def prepare(self, class_map=None):
    method map_source_class_id (line 330) | def map_source_class_id(self, source_class_id):
    method get_source_class_id (line 338) | def get_source_class_id(self, class_id, source):
    method image_ids (line 345) | def image_ids(self):
    method source_image_link (line 348) | def source_image_link(self, image_id):
    method load_image (line 355) | def load_image(self, image_id):
    method load_mask (line 368) | def load_mask(self, image_id):
  function resize_image (line 388) | def resize_image(image, min_dim=None, max_dim=None, min_scale=None, mode...
  function resize_mask (line 495) | def resize_mask(mask, scale, padding, crop=None):
  function minimize_mask (line 517) | def minimize_mask(bbox, mask, mini_shape):
  function expand_mask (line 537) | def expand_mask(bbox, mini_mask, image_shape):
  function mold_mask (line 556) | def mold_mask(mask, config):
  function unmold_mask (line 560) | def unmold_mask(mask, bbox, image_shape):
  function generate_anchors (line 583) | def generate_anchors(scales, ratios, shape, feature_stride, anchor_stride):
  function generate_pyramid_anchors (line 622) | def generate_pyramid_anchors(scales, ratios, feature_shapes, feature_str...
  function trim_zeros (line 646) | def trim_zeros(x):
  function compute_matches (line 656) | def compute_matches(gt_boxes, gt_class_ids, gt_masks,
  function compute_ap (line 715) | def compute_ap(gt_boxes, gt_class_ids, gt_masks,
  function compute_ap_range (line 754) | def compute_ap_range(gt_box, gt_class_id, gt_mask,
  function compute_recall (line 778) | def compute_recall(pred_boxes, gt_boxes, iou):
  function batch_slice (line 803) | def batch_slice(inputs, graph_fn, batch_size, names=None):
  function download_trained_weights (line 840) | def download_trained_weights(coco_model_path, verbose=1):
  function norm_boxes (line 853) | def norm_boxes(boxes, shape):
  function denorm_boxes (line 870) | def denorm_boxes(boxes, shape):
  function resize (line 887) | def resize(image, output_shape, order=1, mode='constant', cval=0, clip=T...

FILE: Image Processor/mrcnn/visualize.py
  function display_images (line 35) | def display_images(images, titles=None, cols=4, cmap=None, norm=None,
  function random_colors (line 59) | def random_colors(N, bright=True):
  function apply_mask (line 72) | def apply_mask(image, mask, color, alpha=0.5):
  function display_instances (line 83) | def display_instances(image, boxes, masks, class_ids, class_names,
  function display_differences (line 170) | def display_differences(image,
  function draw_rois (line 208) | def draw_rois(image, rois, refined_rois, mask, class_ids, class_names, l...
  function draw_box (line 270) | def draw_box(image, box, color):
  function display_top_masks (line 282) | def display_top_masks(image, mask, class_ids, class_names, limit=4):
  function plot_precision_recall (line 305) | def plot_precision_recall(AP, precisions, recalls):
  function plot_overlaps (line 320) | def plot_overlaps(gt_class_ids, pred_class_ids, pred_scores,
  function draw_boxes (line 359) | def draw_boxes(image, boxes=None, refined_boxes=None,
  function display_table (line 461) | def display_table(table):
  function display_weight_stats (line 475) | def display_weight_stats(model):

FILE: Image Processor/setup.py
  function _parse_requirements (line 16) | def _parse_requirements(file_path):

FILE: stylegan2-tpu/align_mammos.py
  function flipImage (line 12) | def flipImage(image):

FILE: stylegan2-tpu/convert_ckpt_to_pkl.py
  function main (line 17) | def main():

FILE: stylegan2-tpu/convert_pkl_to_ckpt.py
  function main (line 19) | def main():

FILE: stylegan2-tpu/dataset_tool.py
  function error (line 27) | def error(msg):
  class TFRecordExporter (line 33) | class TFRecordExporter:
    method __init__ (line 34) | def __init__(self, tfrecord_dir, expected_images, print_progress=True,...
    method close (line 51) | def close(self):
    method choose_shuffled_order (line 61) | def choose_shuffled_order(self): # Note: Images and labels must be add...
    method add_image (line 66) | def add_image(self, img):
    method add_labels (line 89) | def add_labels(self, labels):
    method __enter__ (line 96) | def __enter__(self):
    method __exit__ (line 99) | def __exit__(self, *args):
  class ExceptionInfo (line 104) | class ExceptionInfo(object):
    method __init__ (line 105) | def __init__(self):
  class WorkerThread (line 111) | class WorkerThread(threading.Thread):
    method __init__ (line 112) | def __init__(self, task_queue):
    method run (line 116) | def run(self):
  class ThreadPool (line 129) | class ThreadPool(object):
    method __init__ (line 130) | def __init__(self, num_threads):
    method add_task (line 140) | def add_task(self, func, args=()):
    method get_result (line 146) | def get_result(self, func): # returns (result, args)
    method finish (line 153) | def finish(self):
    method __enter__ (line 157) | def __enter__(self): # for 'with' statement
    method __exit__ (line 160) | def __exit__(self, *excinfo):
    method process_items_concurrently (line 163) | def process_items_concurrently(self, item_iterator, process_func=lambd...
  function display (line 191) | def display(tfrecord_dir):
  function extract (line 217) | def extract(tfrecord_dir, output_dir):
  function compare (line 244) | def compare(tfrecord_dir_a, tfrecord_dir_b, ignore_labels):
  function create_mnist (line 287) | def create_mnist(tfrecord_dir, mnist_dir):
  function create_mnistrgb (line 311) | def create_mnistrgb(tfrecord_dir, mnist_dir, num_images=1000000, random_...
  function create_cifar10 (line 328) | def create_cifar10(tfrecord_dir, cifar10_dir):
  function create_cifar100 (line 355) | def create_cifar100(tfrecord_dir, cifar100_dir):
  function create_svhn (line 377) | def create_svhn(tfrecord_dir, svhn_dir):
  function create_lsun (line 404) | def create_lsun(tfrecord_dir, lmdb_dir, resolution=256, max_images=None):
  function create_lsun_wide (line 437) | def create_lsun_wide(tfrecord_dir, lmdb_dir, width=512, height=384, max_...
  function create_celeba (line 482) | def create_celeba(tfrecord_dir, celeba_dir, cx=89, cy=121):
  function create_from_images (line 500) | def create_from_images(tfrecord_dir, image_dir, shuffle, res_log2=7, res...
  function create_from_hdf5 (line 539) | def create_from_hdf5(tfrecord_dir, hdf5_filename, shuffle):
  function execute_cmdline (line 554) | def execute_cmdline(argv):

FILE: stylegan2-tpu/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: stylegan2-tpu/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: stylegan2-tpu/dnnlib/submission/submit.py
  class SubmitTarget (line 33) | class SubmitTarget(Enum):
  class PathType (line 41) | class PathType(Enum):
  class PlatformExtras (line 53) | class PlatformExtras:
    method __init__ (line 61) | def __init__(self):
  class SubmitConfig (line 68) | class SubmitConfig(util.EasyDict):
    method __init__ (line 91) | def __init__(self):
  function get_path_from_template (line 120) | def get_path_from_template(path_template: str, path_type: PathType = Pat...
  function get_template_from_path (line 142) | def get_template_from_path(path: str) -> str:
  function convert_path (line 148) | def convert_path(path: str, path_type: PathType = PathType.AUTO) -> str:
  function set_user_name_override (line 155) | def set_user_name_override(name: str) -> None:
  function get_user_name (line 161) | def get_user_name():
  function make_run_dir_path (line 174) | def make_run_dir_path(*paths):
  function _create_run_dir_local (line 193) | def _create_run_dir_local(submit_config: SubmitConfig) -> str:
  function _get_next_run_id_local (line 212) | def _get_next_run_id_local(run_dir_root: str) -> int:
  function _populate_run_dir (line 228) | def _populate_run_dir(submit_config: SubmitConfig, run_dir: str) -> None:
  function run_wrapper (line 257) | def run_wrapper(submit_config: SubmitConfig) -> None:
  function submit_run (line 350) | def submit_run(submit_config: SubmitConfig, run_func_name: str, **run_fu...

FILE: stylegan2-tpu/dnnlib/tflib/autosummary.py
  function _create_var (line 46) | def _create_var(name: str, value_expr: TfExpression) -> TfExpression:
  function get_tpu_summary (line 82) | def get_tpu_summary(model_dir=None):
  function image_grid (line 93) | def image_grid(input_tensor, grid_shape, image_shape=(32, 32), num_chann...
  function get_num_replicas (line 144) | def get_num_replicas():
  function set_num_replicas (line 148) | def set_num_replicas(n):
  function _i (line 152) | def _i(x): return tf.transpose(x, [0, 2, 3, 1])
  function _o (line 153) | def _o(x): return tf.transpose(x, [0, 3, 1, 2])
  function autoimages (line 155) | def autoimages(summary_name, images, grid_shape=None, res=None):
  function autosummary (line 208) | def autosummary(name: str, value: TfExpressionEx, passthru: TfExpression...
  function finalize_autosummaries (line 252) | def finalize_autosummaries() -> None:
  function save_summaries (line 311) | def save_summaries(file_writer, global_step=None):

FILE: stylegan2-tpu/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: stylegan2-tpu/dnnlib/tflib/network.py
  function import_handler (line 32) | def import_handler(handler_func):
  class Network (line 38) | class Network:
    method __init__ (line 76) | def __init__(self, name: str = None, scope: str = None, func_name: Any...
    method ensure (line 105) | def ensure(self):
    method _init_fields (line 113) | def _init_fields(self) -> None:
    method _init_graph (line 139) | def _init_graph(self) -> None:
    method _init_graph_ (line 143) | def _init_graph_(self) -> None:
    method reset_own_vars (line 206) | def reset_own_vars(self) -> None:
    method reset_vars (line 210) | def reset_vars(self) -> None:
    method reset_trainables (line 214) | def reset_trainables(self) -> None:
    method get_output_for (line 218) | def get_output_for(self, *in_expr: TfExpression, return_as_list: bool ...
    method get_var_local_name (line 253) | def get_var_local_name(self, var_or_global_name: Union[TfExpression, s...
    method find_var (line 259) | def find_var(self, var_or_local_name: Union[TfExpression, str]) -> TfE...
    method get_var (line 264) | def get_var(self, var_or_local_name: Union[TfExpression, str]) -> np.n...
    method set_var (line 269) | def set_var(self, var_or_local_name: Union[TfExpression, str], new_val...
    method __getstate__ (line 274) | def __getstate__(self) -> dict:
    method __setstate__ (line 286) | def __setstate__(self, state: dict) -> None:
    method clone (line 320) | def clone(self, name: str = None, **new_static_kwargs) -> "Network":
    method clone2 (line 326) | def clone2(self, name: str = None, **new_static_kwargs) -> ("Network",...
    method copy_own_vars_from (line 345) | def copy_own_vars_from(self, src_net: "Network") -> None:
    method copy_vars_from (line 350) | def copy_vars_from(self, src_net: "Network") -> None:
    method copy_trainables_from (line 355) | def copy_trainables_from(self, src_net: "Network") -> None:
    method convert (line 360) | def convert(self, new_func_name: str, new_name: str = None, **new_stat...
    method setup_as_moving_average_of (line 370) | def setup_as_moving_average_of(self, src_net: "Network", beta: TfExpre...
    method run (line 382) | def run(self,
    method list_ops (line 484) | def list_ops(self) -> List[TfExpression]:
    method list_layers (line 492) | def list_layers(self) -> List[Tuple[str, TfExpression, List[TfExpressi...
    method print_layers (line 535) | def print_layers(self, title: str = None, hide_layers_with_no_params: ...
    method setup_weight_histograms (line 564) | def setup_weight_histograms(self, title: str = None) -> None:
  function _handle_legacy_output_transforms (line 584) | def _handle_legacy_output_transforms(output_transform, dynamic_kwargs):
  function _legacy_output_transform_func (line 604) | def _legacy_output_transform_func(*expr, out_mul=1.0, out_add=0.0, out_s...

FILE: stylegan2-tpu/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: stylegan2-tpu/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: stylegan2-tpu/dnnlib/tflib/optimizer.py
  function all_sum_plain (line 31) | def all_sum_plain(g, colocate=False, *args, **kws):
  function all_sum_gpu (line 48) | def all_sum_gpu(g, *args, **kws):
  function all_sum_tpu (line 57) | def all_sum_tpu(g, colocate=True, *args, **kws):
  function all_sum (line 66) | def all_sum(cores, g, colocate=True, *args, **kws):
  class Optimizer (line 75) | class Optimizer:
    method __init__ (line 87) | def __init__(self,
    method _get_device (line 133) | def _get_device(self, device_name: str):
    method register_gradients (line 166) | def register_gradients(self, loss: TfExpression, trainable_vars: Union...
    method apply_updates (line 208) | def apply_updates(self, allow_no_op: bool = False) -> tf.Operation:
    method reset_optimizer_state (line 319) | def reset_optimizer_state(self) -> None:
    method get_loss_scaling_var (line 324) | def get_loss_scaling_var(self, device: str) -> Union[tf.Variable, None]:
    method apply_loss_scaling (line 328) | def apply_loss_scaling(self, value: TfExpression) -> TfExpression:
    method undo_loss_scaling (line 335) | def undo_loss_scaling(self, value: TfExpression) -> TfExpression:
  class SimpleAdam (line 343) | class SimpleAdam:
    method __init__ (line 346) | def __init__(self, name="Adam", learning_rate=0.001, beta1=0.9, beta2=...
    method variables (line 354) | def variables(self):
    method compute_gradients (line 357) | def compute_gradients(self, loss, var_list, gate_gradients=tf.train.Op...
    method apply_gradients (line 361) | def apply_gradients(self, grads_and_vars):

FILE: stylegan2-tpu/dnnlib/tflib/tfutil.py
  function run (line 29) | def run(*args, **kwargs) -> Any:
  function is_tf_expression (line 35) | def is_tf_expression(x: Any) -> bool:
  function shape_to_list (line 40) | def shape_to_list(shape: Iterable[tf.Dimension]) -> List[Union[int, None]]:
  function flatten (line 45) | def flatten(x: TfExpressionEx) -> TfExpression:
  function log2 (line 51) | def log2(x: TfExpressionEx) -> TfExpression:
  function exp2 (line 57) | def exp2(x: TfExpressionEx) -> TfExpression:
  function lerp (line 63) | def lerp(a: TfExpressionEx, b: TfExpressionEx, t: TfExpressionEx) -> TfE...
  function lerp_clip (line 69) | def lerp_clip(a: TfExpressionEx, b: TfExpressionEx, t: TfExpressionEx) -...
  function absolute_name_scope (line 75) | def absolute_name_scope(scope: str) -> tf.name_scope:
  function absolute_variable_scope (line 80) | def absolute_variable_scope(scope: str, **kwargs) -> tf.variable_scope:
  function _sanitize_tf_config (line 85) | def _sanitize_tf_config(config_dict: dict = None) -> dict:
  function init_tf (line 108) | def init_tf(config_dict: dict = None) -> None:
  function assert_tf_initialized (line 136) | def assert_tf_initialized():
  function create_session (line 142) | def create_session(config_dict: dict = None, force_as_default: bool = Fa...
  function init_uninitialized_vars (line 166) | def init_uninitialized_vars(target_vars: List[tf.Variable] = None) -> None:
  function set_vars (line 197) | def set_vars(var_to_value_dict: dict) -> None:
  function create_var_with_large_initial_value (line 235) | def create_var_with_large_initial_value(initial_value: np.ndarray, *args...
  function create_var_with_large_initial_value2 (line 244) | def create_var_with_large_initial_value2(initial_value: np.ndarray, *arg...
  function convert_images_from_uint8 (line 254) | def convert_images_from_uint8(images, drange=[-1,1], nhwc_to_nchw=False):
  function convert_images_to_uint8 (line 264) | def convert_images_to_uint8(images, drange=[-1,1], nchw_to_nhwc=False, s...

FILE: stylegan2-tpu/dnnlib/tflib/tpu_summaries.py
  class TpuSummaries (line 57) | class TpuSummaries(object):
    method __init__ (line 66) | def __init__(self, log_dir, save_summary_steps=32):
    method image (line 74) | def image(self, name, tensor, reduce_fn):
    method scalar (line 81) | def scalar(self, name, tensor, reduce_fn=tf.math.reduce_mean):
    method get_host_call (line 91) | def get_host_call(self):
    method _host_call_fn (line 101) | def _host_call_fn(self, step, *args):

FILE: stylegan2-tpu/dnnlib/util.py
  class EasyDict (line 36) | class EasyDict(dict):
    method __getattr__ (line 39) | def __getattr__(self, name: str) -> Any:
    method __setattr__ (line 45) | def __setattr__(self, name: str, value: Any) -> None:
    method __delattr__ (line 48) | def __delattr__(self, name: str) -> None:
  class Logger (line 52) | class Logger(object):
    method __init__ (line 55) | def __init__(self, file_name: str = None, file_mode: str = "w", should...
    method __enter__ (line 68) | def __enter__(self) -> "Logger":
    method __exit__ (line 71) | def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> N...
    method write (line 74) | def write(self, text: str) -> None:
    method flush (line 93) | def flush(self) -> None:
    method close (line 106) | def close(self) -> None:
  function format_time (line 130) | def format_time(seconds: Union[int, float]) -> str:
  function ask_yes_no (line 144) | def ask_yes_no(question: str) -> bool:
  function tuple_product (line 154) | def tuple_product(t: Tuple) -> Any:
  function get_dtype_and_ctype (line 178) | def get_dtype_and_ctype(type_obj: Any) -> Tuple[np.dtype, Any]:
  function is_pickleable (line 201) | def is_pickleable(obj: Any) -> bool:
  function get_module_from_obj_name (line 213) | def get_module_from_obj_name(obj_name: str) -> Tuple[types.ModuleType, s...
  function get_obj_from_module (line 254) | def get_obj_from_module(module: types.ModuleType, obj_name: str) -> Any:
  function get_obj_by_name (line 264) | def get_obj_by_name(name: str) -> Any:
  function call_func_by_name (line 270) | def call_func_by_name(*args, func_name: str = None, **kwargs) -> Any:
  function get_module_dir_by_obj_name (line 278) | def get_module_dir_by_obj_name(obj_name: str) -> str:
  function is_top_level_function (line 284) | def is_top_level_function(obj: Any) -> bool:
  function get_top_level_function_name (line 289) | def get_top_level_function_name(obj: Any) -> str:
  function list_dir_recursively_with_ignore (line 298) | def list_dir_recursively_with_ignore(dir_path: str, ignores: List[str] =...
  function copy_files_and_create_dirs (line 331) | def copy_files_and_create_dirs(files: List[Tuple[str, str]]) -> None:
  function is_url (line 347) | def is_url(obj: Any, allow_file_urls: bool = False) -> bool:
  function open_url (line 365) | def open_url(url: str, cache_dir: str = None, num_attempts: int = 10, ve...

FILE: stylegan2-tpu/encoder/generator_model.py
  function create_stub (line 8) | def create_stub(name, batch_size):
  function create_variable_for_generator (line 12) | def create_variable_for_generator(name, batch_size, tiled_dlatent, model...
  class Generator (line 26) | class Generator:
    method __init__ (line 27) | def __init__(self, model, batch_size, clipping_threshold=2, tiled_dlat...
    method reset_dlatents (line 87) | def reset_dlatents(self):
    method set_dlatents (line 90) | def set_dlatents(self, dlatents):
    method stochastic_clip_dlatents (line 105) | def stochastic_clip_dlatents(self):
    method get_dlatents (line 108) | def get_dlatents(self):
    method get_dlatent_avg (line 111) | def get_dlatent_avg(self):
    method set_dlatent_avg (line 114) | def set_dlatent_avg(self, dlatent_avg):
    method reset_dlatent_avg (line 117) | def reset_dlatent_avg(self):
    method generate_images (line 120) | def generate_images(self, dlatents=None):

FILE: stylegan2-tpu/encoder/perceptual_model.py
  function load_images (line 12) | def load_images(images_list, image_size=256):
  function tf_custom_l1_loss (line 22) | def tf_custom_l1_loss(img1,img2):
  function tf_custom_logcosh_loss (line 25) | def tf_custom_logcosh_loss(img1,img2):
  function unpack_bz2 (line 28) | def unpack_bz2(src_path):
  class PerceptualModel (line 35) | class PerceptualModel:
    method __init__ (line 36) | def __init__(self, args, batch_size=1, perc_model=None, sess=None, opt...
    method compare_images (line 85) | def compare_images(self,img1,img2):
    method add_placeholder (line 90) | def add_placeholder(self, var_name):
    method assign_placeholder (line 95) | def assign_placeholder(self, var_name, var_val):
    method build_perceptual_model (line 98) | def build_perceptual_model(self, generator):
    method generate_face_mask (line 158) | def generate_face_mask(self, im):
    method load_images (line 187) | def load_images(self, images_list):
    method set_reference_images (line 192) | def set_reference_images(self, images_list):
    method set_reference_image_data (line 195) | def set_reference_image_data(self, loaded_image, images_list=None):
    method optimize (line 258) | def optimize(self, iterations=200):

FILE: stylegan2-tpu/generate_images_tpu.py
  function rand_latent (line 24) | def rand_latent(n, seed=None):
  function tfinit (line 35) | def tfinit():
  function load_checkpoint (line 39) | def load_checkpoint(path, checkpoint_num=None):
  function get_checkpoint (line 50) | def get_checkpoint(path):
  function get_grid_size (line 55) | def get_grid_size(n):
  function gen_images (line 68) | def gen_images(latents, truncation_psi_val, outfile=None, display=False,...
  function grab (line 92) | def grab(save_dir, i, n=1, latents=None, **kwargs):

FILE: stylegan2-tpu/mammos.py
  function with_session (line 52) | def with_session(sess, f, *args, **kws):
  function with_session_async (line 56) | async def with_session_async(sess, f, *args, **kws):
  function init (line 60) | def init(session=None, num_channels=None, resolution=None, label_size=No...
  function load_checkpoint (line 80) | def load_checkpoint(path, session=None, var_list=None):
  function get_images (line 98) | def get_images(tags, seed = 0, mu = 0, sigma = 0, truncation=None):

FILE: stylegan2-tpu/metrics/frechet_inception_distance.py
  class FID (line 21) | class FID(metric_base.MetricBase):
    method __init__ (line 22) | def __init__(self, num_images, minibatch_per_gpu, **kwargs):
    method _evaluate (line 27) | def _evaluate(self, Gs, Gs_kwargs, num_gpus):

FILE: stylegan2-tpu/metrics/inception_score.py
  class IS (line 19) | class IS(metric_base.MetricBase):
    method __init__ (line 20) | def __init__(self, num_images, num_splits, minibatch_per_gpu, **kwargs):
    method _evaluate (line 26) | def _evaluate(self, Gs, Gs_kwargs, num_gpus):

FILE: stylegan2-tpu/metrics/linear_separability.py
  function prob_normalize (line 66) | def prob_normalize(p):
  function mutual_information (line 71) | def mutual_information(p):
  function entropy (line 85) | def entropy(p):
  function conditional_entropy (line 95) | def conditional_entropy(p):
  class LS (line 104) | class LS(metric_base.MetricBase):
    method __init__ (line 105) | def __init__(self, num_samples, num_keep, attrib_indices, minibatch_pe...
    method _evaluate (line 113) | def _evaluate(self, Gs, Gs_kwargs, num_gpus):

FILE: stylegan2-tpu/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: stylegan2-tpu/metrics/perceptual_path_length.py
  function normalize (line 20) | def normalize(v):
  function slerp (line 24) | def slerp(a, b, t):
  class PPL (line 35) | class PPL(metric_base.MetricBase):
    method __init__ (line 36) | def __init__(self, num_samples, epsilon, space, sampling, crop, miniba...
    method _evaluate (line 48) | def _evaluate(self, Gs, Gs_kwargs, num_gpus):

FILE: stylegan2-tpu/metrics/precision_recall.py
  function batch_pairwise_distances (line 21) | def batch_pairwise_distances(U, V):
  class DistanceBlock (line 39) | class DistanceBlock():
    method __init__ (line 41) | def __init__(self, num_features, num_gpus):
    method pairwise_distances (line 56) | def pairwise_distances(self, U, V):
  class ManifoldEstimator (line 62) | class ManifoldEstimator():
    method __init__ (line 64) | def __init__(self, distance_block, features, row_batch_size, col_batch...
    method evaluate (line 97) | def evaluate(self, eval_features, return_realism=False, return_neighbo...
  function knn_precision_recall_features (line 139) | def knn_precision_recall_features(ref_features, eval_features, feature_n...
  class PR (line 172) | class PR(metric_base.MetricBase):
    method __init__ (line 173) | def __init__(self, num_images, nhood_size, minibatch_per_gpu, row_batc...
    method _evaluate (line 181) | def _evaluate(self, Gs, Gs_kwargs, num_gpus):

FILE: stylegan2-tpu/prepare_image.py
  class Namespace (line 23) | class Namespace():
  function _int64_feature (line 28) | def _int64_feature(value):
  function _bytes_feature (line 35) | def _bytes_feature(value):
  function _convert_to_example (line 40) | def _convert_to_example(filename, image_buffer, label_int, label_str, he...
  class ImageCoder (line 75) | class ImageCoder(object):
    method __init__ (line 78) | def __init__(self, session=None):
    method __del__ (line 97) | def __del__(self):
    method png_to_jpeg (line 100) | def png_to_jpeg(self, image_data):
    method cmyk_to_rgb (line 104) | def cmyk_to_rgb(self, image_data):
    method decode_jpeg (line 108) | def decode_jpeg(self, image_data):
  function parse_tfrecord_tf (line 117) | def parse_tfrecord_tf(record):
  function parse_tfrecord_file (line 122) | def parse_tfrecord_file(tfr_file, num_threads=8):
  function init_dataset (line 127) | def init_dataset(dset):
  function iterate_stylegan_records (line 134) | def iterate_stylegan_records(tfr_file, session=None):
  function _is_png (line 148) | def _is_png(filename):
  function _is_png_data (line 151) | def _is_png_data(image_data):
  function _is_cmyk (line 154) | def _is_cmyk(filename):
  function get_coder (line 157) | def get_coder(coder=None):
  function getfile (line 163) | def getfile(path):
  function _process_image (line 173) | def _process_image(filename, coder=None):
  function tf_randi (line 205) | def tf_randi(*args, **kws):
  function tf_rand (line 213) | def tf_rand(*args, **kws):
  function tf_biased_rand (line 222) | def tf_biased_rand(*args, bias=1, **kws):
  function tf_between (line 232) | def tf_between(*args, bias=1, **kws):
  function random_crop (line 238) | def random_crop(image_bytes, scope=None, resize=None, method=tf.image.Re...
  function distorted_bounding_box_crop (line 264) | def distorted_bounding_box_crop(image_bytes,
  function _at_least_x_are_equal (line 314) | def _at_least_x_are_equal(a, b, x):
  function _decode_and_random_crop (line 320) | def _decode_and_random_crop(image_bytes, image_size, resize=True, method...
  function _decode_and_center_crop (line 345) | def _decode_and_center_crop(image_bytes, image_size, resize=True, method...
  function get_target (line 366) | def get_target(target=None):
  function main (line 377) | def main():
  function convert_to_example (line 400) | def convert_to_example(csvline, categories):
  function main2 (line 419) | def main2():

FILE: stylegan2-tpu/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: stylegan2-tpu/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: stylegan2-tpu/random_crops.py
  function random_crop (line 13) | def random_crop(image, target, samples, file):

FILE: stylegan2-tpu/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: stylegan2-tpu/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: stylegan2-tpu/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: stylegan2-tpu/run_training.py
  function run (line 38) | def run(dataset, data_dir, result_dir, config_id, num_gpus, total_kimg, ...
  function _str_to_bool (line 144) | def _str_to_bool(v):
  function _parse_comma_sep (line 154) | def _parse_comma_sep(s):
  function main (line 176) | def main():

FILE: stylegan2-tpu/tflex.py
  class _DefaultState (line 21) | class _DefaultState(threading.local):
    method __init__ (line 22) | def __init__(self, **kws):
    method save (line 27) | def save(self):
    method restore (line 30) | def restore(self, state):
  function with_defaults (line 37) | def with_defaults(thunk):
  function get_default (line 55) | def get_default(name, required=True):
  function set_default (line 62) | def set_default(name, value):
  function ensure_default (line 66) | def ensure_default(name, value):
  function get_default_session (line 73) | def get_default_session(required=False):
  function get_default_graph (line 76) | def get_default_graph(required=False):
  class Future (line 79) | class Future(object):
    method __init__ (line 80) | def __init__(self, dependencies, thunk, *args, **kws):
    method run (line 94) | def run(self):
    method run_async (line 101) | def run_async(self):
    method join (line 108) | def join(self):
  function defer (line 115) | def defer(thunk, *args, **kws):
  function parallelize (line 123) | def parallelize(xs, thunk, *args, daemon=True):
  function parallelize_verbose (line 131) | def parallelize_verbose(label, xs, thunk, *args, daemon=True):
  function parallelize_verbose (line 142) | def parallelize_verbose(label, xs, thunk, *args, daemon=True, synchronou...
  function group (line 162) | def group(n, iterable, fillvalue=None):
  function tuples (line 167) | def tuples(*args, **kws):
  class Namespace (line 170) | class Namespace(object):
  function reroute (line 188) | def reroute(addr, host=None):
  class TPUClusterResolver (line 208) | class TPUClusterResolver(BaseTPUClusterResolver):
    method __init__ (line 209) | def __init__(self, *args, host=None, **kws):
    method master (line 216) | def master(self, *args, **kws):
    method cluster_spec (line 220) | def cluster_spec(self):
  function init_tpu (line 227) | def init_tpu(name, host=None, timeout_in_ms=600 * 60 * 1000):
  function get_session (line 242) | def get_session(session=None):
  function get_devices (line 247) | def get_devices(session=None):
  function has_gpu (line 255) | def has_gpu(session=None):
  function has_tpu (line 264) | def has_tpu(session=None):
  function get_cores_from_devices (line 273) | def get_cores_from_devices(devices):
  function get_cores (line 281) | def get_cores(session=None, devices=None):
  function get_cpus (line 286) | def get_cpus(session=None, devices=None):
  function get_tpu_resolver (line 292) | def get_tpu_resolver(tpu_name='auto'):
  function pretty (line 301) | def pretty(x, ellipsize=120):
  function print_backtrace (line 307) | def print_backtrace():
  class Session (line 314) | class Session(tf.Session):
    method __init__ (line 315) | def __init__(self, target='auto', graph=None, config=None, init_tpu=Fa...
    method _spec (line 342) | def _spec(self):
    method ensure (line 345) | def ensure(self):
    method run (line 352) | def run(self, *args, **kws):
  function split_by_params (line 371) | def split_by_params(vs, n=20e6, f=None):
  function latest_checkpoint (line 386) | def latest_checkpoint(checkpoint_dir, latest_filename=None):
  function truncate_value (line 395) | def truncate_value(variable, value, reshape=True):
  function initialize_tpu (line 412) | def initialize_tpu(session=None, timeout_in_ms=None):
  function load (line 421) | def load(variable, value, session=None, timeout_in_ms=None):
  function eval (line 432) | def eval(variable, session=None, timeout_in_ms=None):
  function grab_values (line 439) | def grab_values(variables, reader, reshape=False):
  function assign_values (line 446) | def assign_values(variables, values, session=None, timeout_in_ms=60000):
  function load_snapshot (line 459) | def load_snapshot(ckpt, session=None, var_list=None, reshape=False):
  function get_variable (line 467) | def get_variable(name, var_list=None):
  function load_weights (line 476) | def load_weights(ckpt, session=None, var_list=None, reshape=False):
  function load_variables (line 489) | def load_variables(ckpt, session=None, var_list=None, reshape=False):
  function maketree (line 497) | def maketree(path):
  function cast_variables (line 505) | def cast_variables(variables, graph=None, cache_ops=None):
  function variable_name (line 527) | def variable_name(variable):
  function save_variables (line 532) | def save_variables(ckpt, session=None, var_list=None):
  function fetch_variables (line 550) | def fetch_variables(session=None, var_list=None):
  function partition_variables (line 557) | def partition_variables(session=None, var_list=None):
  class Saver (line 563) | class Saver(object):
    method __init__ (line 564) | def __init__(
    method restore (line 598) | def restore(self, sess, save_path):
    method save (line 610) | def save(self,
    method fetch (line 638) | def fetch(self, sess, var_list=None):
    method variables (line 644) | def variables(self, sess, var_list=None):
    method assign (line 650) | def assign(self, sess, variables, values):
  class Commands (line 653) | class Commands(object):
    method __init__ (line 654) | def __init__(self, path='commands'):
    method has (line 661) | def has(self, name, **keys):
    method add (line 673) | def add(self, name, action=None):
    method full_path (line 679) | def full_path(self, name):
    method check (line 682) | def check(self, *args, **keys):
    method run (line 697) | def run(self, op):
    method run_with_args (line 711) | def run_with_args(self, op, *args, **keys):
  function commands (line 717) | def commands(**keys):
  class CommandArgs (line 736) | class CommandArgs(object):
    method __init__ (line 737) | def __init__(self, *args, **keys):
    method __enter__ (line 742) | def __enter__(self):
    method __exit__ (line 748) | def __exit__(self, *excinfo):
  function check_commands (line 752) | def check_commands():
  function check_commands_with_args (line 759) | def check_commands_with_args(*args, **keys):
  function add_command (line 767) | def add_command(name, action=None, **keys):
  function register_command (line 771) | def register_command(*args, **keys):
  function has_command (line 786) | def has_command(name):
  function run_command (line 790) | def run_command(command_name):
  function run_command_with_args (line 794) | def run_command_with_args(command_name, *args, **keys):
  function command_arg (line 798) | def command_arg(x, unset=None):
  function command_args (line 810) | def command_args():
  function attach_debugger (line 815) | def attach_debugger():
  function print_status (line 822) | def print_status():
  function utc (line 833) | def utc():
  function heartbeat (line 839) | def heartbeat():
  function freeze_forever (line 852) | def freeze_forever():
  function quit (line 875) | def quit():
  function should_quit (line 884) | def should_quit():
  function save_and_quit (line 888) | def save_and_quit():
  function throw_exception (line 896) | def throw_exception():
  function nullcontext (line 904) | def nullcontext(enter_result=None):
  function set_override_device (line 907) | def set_override_device(value, session=None):
  function has_override_device (line 912) | def has_override_device(session=None):
  function get_override_device (line 916) | def get_override_device(session=None):
  function set_override_cores (line 921) | def set_override_cores(value, session=None):
  function has_override_cores (line 926) | def has_override_cores(session=None):
  function get_override_cores (line 930) | def get_override_cores(session=None):
  function device_for_tpu_core (line 935) | def device_for_tpu_core(task=0, core=0, job_name="tpu_worker"):
  function device (line 938) | def device(name=''):
  function tuples (line 963) | def tuples(l, n=2):
  function sha256hex (line 971) | def sha256hex(x):
  function sha256label (line 976) | def sha256label(x):

FILE: stylegan2-tpu/tflex_test.py
  function make_future (line 5) | def make_future(label, delay=0.0, deps=[], thunk=None, args=[]):
  function warmup (line 18) | def warmup():
  function test1 (line 21) | def test1():
  function test2 (line 27) | def test2():
  function test3 (line 33) | def test3():
  function test4 (line 37) | def test4():
  function test5 (line 44) | def test5():
  function run_test (line 54) | def run_test(name, thunk, *args, **kws):
  function run_tests (line 63) | def run_tests():

FILE: stylegan2-tpu/training/dataset.py
  class TFRecordDataset (line 23) | class TFRecordDataset:
    method __init__ (line 24) | def __init__(self,
    method close (line 149) | def close(self):
    method configure (line 153) | def configure(self, minibatch_size, lod=0):
    method get_minibatch_tf (line 163) | def get_minibatch_tf(self): # => images, labels
    method get_minibatch_np (line 167) | def get_minibatch_np(self, minibatch_size, lod=0): # => images, labels
    method get_random_labels_tf (line 180) | def get_random_labels_tf(self, minibatch_size): # => labels
    method get_random_labels_np (line 188) | def get_random_labels_np(self, minibatch_size): # => labels
    method parse_tfrecord_tf (line 195) | def parse_tfrecord_tf(record):
    method parse_tfrecord_tf_float (line 204) | def parse_tfrecord_tf_float(record):
    method parse_tfrecord_np (line 210) | def parse_tfrecord_np(record):
  function load_dataset (line 220) | def load_dataset(class_name=None, data_dir=None, verbose=False, **kwargs):

FILE: stylegan2-tpu/training/imagenet_input.py
  class Namespace (line 21) | class Namespace:
  function distorted_bounding_box_crop (line 28) | def distorted_bounding_box_crop(image_bytes,
  function _at_least_x_are_equal (line 88) | def _at_least_x_are_equal(a, b, x):
  function _decode_and_random_crop (line 95) | def _decode_and_random_crop(image_bytes, image_size):
  function _decode_and_center_crop_image (line 109) | def _decode_and_center_crop_image(image_bytes, image_size, crop_padding=...
  function _decode_and_center_crop (line 133) | def _decode_and_center_crop(image_bytes, image_size, crop_padding=None):
  function _flip (line 145) | def _flip(image):
  function preprocess_for_train (line 151) | def preprocess_for_train(image_bytes, use_bfloat16, image_size):
  function preprocess_for_eval (line 170) | def preprocess_for_eval(image_bytes, use_bfloat16, image_size):
  function preprocess_image (line 188) | def preprocess_image(image_bytes,
  function image_serving_input_fn (line 238) | def image_serving_input_fn():
  function _int64_feature (line 257) | def _int64_feature(value):
  function _bytes_feature (line 264) | def _bytes_feature(value):
  function _convert_to_example (line 269) | def _convert_to_example(image_buffer, label):
  class ImageNetTFExampleInput (line 289) | class ImageNetTFExampleInput(object):
    method __init__ (line 300) | def __init__(self,
    method set_shapes (line 315) | def set_shapes(self, batch_size, images, labels):
    method dataset_parser (line 334) | def dataset_parser(self, value):
    method dataset_parser_static (line 374) | def dataset_parser_static(self, value):
    method dataset_parser_dynamic (line 407) | def dataset_parser_dynamic(self, image_bytes, label):
    method pad_dataset (line 414) | def pad_dataset(self, dataset, num_hosts):
    method make_source_dataset (line 430) | def make_source_dataset(self, index, num_hosts):
    method input_fn (line 447) | def input_fn(self, params):
  class ImageNetInput (line 533) | class ImageNetInput(ImageNetTFExampleInput):
    method __init__ (line 550) | def __init__(self,
    method _get_null_input (line 589) | def _get_null_input(self, data):
    method dataset_parser (line 603) | def dataset_parser(self, value):
    method make_source_dataset (line 609) | def make_source_dataset(self, index, num_hosts):
  class ImageNetBigtableInput (line 674) | class ImageNetBigtableInput(ImageNetTFExampleInput):
    method __init__ (line 678) | def __init__(self, is_training, use_bfloat16, transpose_input, selecti...
    method make_source_dataset (line 693) | def make_source_dataset(self, index, num_hosts):

FILE: stylegan2-tpu/training/loss.py
  function G_logistic (line 18) | def G_logistic(G, D, opt, training_set, minibatch_size):
  function G_logistic_ns (line 28) | def G_logistic_ns(G, D, opt, training_set, minibatch_size):
  function D_logistic (line 38) | def D_logistic(G, D, opt, training_set, minibatch_size, reals, labels):
  function D_logistic_r1 (line 57) | def D_logistic_r1(G, D, opt, training_set, minibatch_size, reals, labels...
  function D_logistic_r2 (line 78) | def D_logistic_r2(G, D, opt, training_set, minibatch_size, reals, labels...
  function G_wgan (line 103) | def G_wgan(G, D, opt, training_set, minibatch_size):
  function D_wgan (line 113) | def D_wgan(G, D, opt, training_set, minibatch_size, reals, labels, wgan_...
  function D_wgan_gp (line 135) | def D_wgan_gp(G, D, opt, training_set, minibatch_size, reals, labels, wg...
  function G_logistic_ns_pathreg (line 170) | def G_logistic_ns_pathreg(G, D, opt, training_set, minibatch_size, pl_mi...

FILE: stylegan2-tpu/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, filename=None):
  function save_pkl (line 30) | def save_pkl(obj, filename):
  function adjust_dynamic_range (line 37) | def adjust_dynamic_range(data, drange_in, drange_out):
  function create_image_grid (line 44) | def create_image_grid(images, grid_size=None):
  function convert_to_pil_image (line 61) | def convert_to_pil_image(image, drange=[0,1]):
  function save_image_grid (line 74) | def save_image_grid(images, filename, drange=[0,1], grid_size=None):
  function apply_mirror_augment (line 77) | def apply_mirror_augment(minibatch):
  function parse_config_for_previous_run (line 86) | def parse_config_for_previous_run(run_dir):
  function setup_snapshot_image_grid (line 96) | def setup_snapshot_image_grid(training_set,

FILE: stylegan2-tpu/training/networks_stylegan.py
  function _i (line 17) | def _i(x): return tf.transpose(x, [0,2,3,1])
  function _o (line 18) | def _o(x): return tf.transpose(x, [0,3,1,2])
  function _blur2d (line 24) | def _blur2d(x, f=[1,2,1], normalize=True, flip=False, stride=1):
  function _upscale2d (line 53) | def _upscale2d(x, factor=2, gain=1):
  function _downscale2d (line 72) | def _downscale2d(x, factor=2, gain=1):
  function blur2d (line 98) | def blur2d(x, f=[1,2,1], normalize=True):
  function upscale2d (line 110) | def upscale2d(x, factor=2):
  function downscale2d (line 122) | def downscale2d(x, factor=2):
  function get_weight (line 137) | def get_weight(shape, gain=np.sqrt(2), use_wscale=False, lrmul=1):
  function dense (line 156) | def dense(x, fmaps, **kwargs):
  function conv2d (line 166) | def conv2d(x, fmaps, kernel, **kwargs):
  function upscale2d_conv2d (line 176) | def upscale2d_conv2d(x, fmaps, kernel, fused_scale='auto', **kwargs):
  function conv2d_downscale2d (line 195) | def conv2d_downscale2d(x, fmaps, kernel, fused_scale='auto', **kwargs):
  function apply_bias (line 215) | def apply_bias(x, lrmul=1):
  function leaky_relu (line 225) | def leaky_relu(x, alpha=0.2):
  function pixel_norm (line 241) | def pixel_norm(x, epsilon=1e-8):
  function instance_norm (line 249) | def instance_norm(x, epsilon=1e-8):
  function style_mod (line 263) | def style_mod(x, dlatent, **kwargs):
  function apply_noise (line 272) | def apply_noise(x, noise_var=None, randomize_noise=True):
  function minibatch_stddev_layer (line 285) | def minibatch_stddev_layer(x, group_size=4, num_new_features=1):
  function G_style (line 304) | def G_style(
  function G_mapping (line 386) | def G_mapping(
  function G_synthesis (line 442) | def G_synthesis(
  function D_basic (line 566) | def D_basic(

FILE: stylegan2-tpu/training/networks_stylegan2.py
  function _i (line 22) | def _i(x): return tf.transpose(x, [0,2,3,1])
  function _o (line 23) | def _o(x): return tf.transpose(x, [0,3,1,2])
  function get_weight (line 28) | def get_weight(shape, gain=1, use_wscale=True, lrmul=1, weight_var='weig...
  function dense_layer (line 47) | def dense_layer(x, fmaps, gain=1, use_wscale=True, lrmul=1, weight_var='...
  function conv2d_layer (line 57) | def conv2d_layer(x, fmaps, kernel, up=False, down=False, resample_kernel...
  function apply_bias_act (line 72) | def apply_bias_act(x, act='linear', alpha=None, gain=None, lrmul=1, bias...
  function naive_upsample_2d (line 79) | def naive_upsample_2d(x, factor=2):
  function naive_downsample_2d (line 86) | def naive_downsample_2d(x, factor=2):
  function modulated_conv2d_layer (line 95) | def modulated_conv2d_layer(x, y, fmaps, kernel, up=False, down=False, de...
  function minibatch_stddev_layer (line 138) | def minibatch_stddev_layer(x, group_size=4, num_new_features=1):
  function G_main (line 157) | def G_main(
  function G_mapping (line 257) | def G_mapping(
  function G_synthesis_stylegan_revised (line 313) | def G_synthesis_stylegan_revised(
  function G_synthesis_stylegan2 (line 425) | def G_synthesis_stylegan2(
  function D_stylegan (line 525) | def D_stylegan(
  function D_stylegan2 (line 625) | def D_stylegan2(
  function weight_initializer (line 720) | def weight_initializer(initializer=NORMAL_INIT, stddev=0.02):
  function spectral_norm (line 739) | def spectral_norm(inputs, epsilon=1e-12, singular_value="left", return_n...
  function graph_name (line 820) | def graph_name(name):
  function graph_spectral_norm (line 831) | def graph_spectral_norm(w):
  function graph_images (line 846) | def graph_images(images, res):
  function conv2d (line 855) | def conv2d(inputs, output_dim, k_h, k_w, d_h, d_w, stddev=0.02, name="co...
  function non_local_block (line 874) | def non_local_block(x, name, use_sn):

FILE: stylegan2-tpu/training/train_runner.py
  function device_for_tpu_core (line 41) | def device_for_tpu_core(task=0, core=0):
  function wrap_computation_in_while_loop (line 47) | def wrap_computation_in_while_loop(op_fn, n, parallel_iterations=1):
  function tpu_ordinal_fn (line 63) | def tpu_ordinal_fn(shard_index_in_host):
  class TrainRunner (line 77) | class TrainRunner(object):
    method __init__ (line 80) | def __init__(self, iterations, train_steps):
    method device_for_host (line 114) | def device_for_host(self, task=0, cpu=0):
    method build_enqueue_ops (line 118) | def build_enqueue_ops(self, input_fn, params, host_id):
    method initialize (line 170) | def initialize(self, input_fn, model_fn, params):
    method train (line 264) | def train(self, num_threads=2):
    method shutdown (line 313) | def shutdown(self):

FILE: stylegan2-tpu/training/training_loop.py
  function process_reals (line 27) | def process_reals(x, labels, lod, mirror_augment, drange_data, drange_net):
  function training_schedule (line 54) | def training_schedule(
  function get_input_fn (line 109) | def get_input_fn(training_set, batch_size):
  function get_input_fn (line 121) | def get_input_fn(training_set):
  function set_shapes (line 133) | def set_shapes(batch_size, num_channels, resolution, label_size, images,...
  function tf_randi (line 157) | def tf_randi(*args, **kws):
  function tf_rand (line 166) | def tf_rand(*args, **kws):
  function tf_biased_rand (line 176) | def tf_biased_rand(*args, bias=1, **kws):
  function tf_between (line 187) | def tf_between(*args, bias=1, **kws):
  function random_crop (line 194) | def random_crop(image_bytes, scope=None, resize=None, method=tf.image.Re...
  function _decode_and_center_crop (line 215) | def _decode_and_center_crop(image_bytes, image_size, crop_padding=0):
  function parse_header (line 262) | def parse_header(x):
  function csv_dataset (line 268) | def csv_dataset(path, spec=None, **kws):
  function imagenet_dataset (line 274) | def imagenet_dataset(path, resize=None, seed=None):
  function get_input_fn (line 293) | def get_input_fn(load_training_set, num_cores, mirror_augment, drange_net):
  function training_loop (line 489) | def training_loop(

FILE: stylegan2-tpu/view.py
  function rand_latent (line 72) | def rand_latent(n, seed=None):
  function tfinit (line 88) | def tfinit():
  function load_checkpoint (line 95) | def load_checkpoint(path):
  function get_grid_size (line 113) | def get_grid_size(n):
  function gen_images (line 125) | def gen_images(latents, outfile=None, display=False, labels=None, random...
  function grab (line 148) | def grab(name, postfix, i, n=1, latents=None, **kwargs):
  function grab_grid (line 157) | def grab_grid(i, n=1, latents=None, outfile=None, **kwargs):
  function post_picture (line 167) | def post_picture(channel_name, image, text=None, name='test', kind='png'):