SYMBOL INDEX (1360 symbols across 120 files)

FILE: dnnlib/util.py
  class EasyDict (line 40) | class EasyDict(dict):
    method __getattr__ (line 43) | def __getattr__(self, name: str) -> Any:
    method __setattr__ (line 49) | def __setattr__(self, name: str, value: Any) -> None:
    method __delattr__ (line 52) | def __delattr__(self, name: str) -> None:
  class Logger (line 56) | class Logger(object):
    method __init__ (line 59) | def __init__(self, file_name: str = None, file_mode: str = "w", should...
    method __enter__ (line 72) | def __enter__(self) -> "Logger":
    method __exit__ (line 75) | def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> N...
    method write (line 78) | def write(self, text: Union[str, bytes]) -> None:
    method flush (line 93) | def flush(self) -> None:
    method close (line 100) | def close(self) -> None:
  function set_cache_dir (line 120) | def set_cache_dir(path: str) -> None:
  function make_cache_dir_path (line 124) | def make_cache_dir_path(*paths: str) -> str:
  function format_time (line 139) | def format_time(seconds: Union[int, float]) -> str:
  function format_time_brief (line 153) | def format_time_brief(seconds: Union[int, float]) -> str:
  function ask_yes_no (line 167) | def ask_yes_no(question: str) -> bool:
  function tuple_product (line 177) | def tuple_product(t: Tuple) -> Any:
  function get_dtype_and_ctype (line 201) | def get_dtype_and_ctype(type_obj: Any) -> Tuple[np.dtype, Any]:
  function is_pickleable (line 224) | def is_pickleable(obj: Any) -> bool:
  function get_module_from_obj_name (line 236) | def get_module_from_obj_name(obj_name: str) -> Tuple[types.ModuleType, s...
  function get_obj_from_module (line 277) | def get_obj_from_module(module: types.ModuleType, obj_name: str) -> Any:
  function get_obj_by_name (line 287) | def get_obj_by_name(name: str) -> Any:
  function call_func_by_name (line 293) | def call_func_by_name(*args, func_name: str = None, **kwargs) -> Any:
  function construct_class_by_name (line 301) | def construct_class_by_name(*args, class_name: str = None, **kwargs) -> ...
  function get_module_dir_by_obj_name (line 306) | def get_module_dir_by_obj_name(obj_name: str) -> str:
  function is_top_level_function (line 312) | def is_top_level_function(obj: Any) -> bool:
  function get_top_level_function_name (line 317) | def get_top_level_function_name(obj: Any) -> str:
  function list_dir_recursively_with_ignore (line 329) | def list_dir_recursively_with_ignore(dir_path: str, ignores: List[str] =...
  function copy_files_and_create_dirs (line 362) | def copy_files_and_create_dirs(files: List[Tuple[str, str]]) -> None:
  function is_url (line 378) | def is_url(obj: Any, allow_file_urls: bool = False) -> bool:
  function open_url (line 396) | def open_url(url: str, cache_dir: str = None, num_attempts: int = 10, ve...

FILE: gen_images.py
  function parse_range (line 25) | def parse_range(s: Union[str, List]) -> List[int]:
  function parse_vec2 (line 43) | def parse_vec2(s: Union[str, Tuple[float, float]]) -> Tuple[float, float]:
  function make_transform (line 57) | def make_transform(translate: Tuple[float,float], angle: float):
  function generate_images (line 80) | def generate_images(

FILE: gradio_utils/utils.py
  class ImageMask (line 6) | class ImageMask(gr.components.Image):
    method __init__ (line 13) | def __init__(self, **kwargs):
    method preprocess (line 19) | def preprocess(self, x):
  function get_valid_mask (line 33) | def get_valid_mask(mask: np.ndarray):
  function draw_points_on_image (line 44) | def draw_points_on_image(image,
  function draw_mask_on_image (line 112) | def draw_mask_on_image(image, mask):
  function on_change_single_global_state (line 128) | def on_change_single_global_state(keys,
  function get_latest_points_pair (line 149) | def get_latest_points_pair(points_dict):

FILE: gui_utils/gl_utils.py
  function init_egl (line 20) | def init_egl():
  function get_texture_format (line 77) | def get_texture_format(dtype, channels):
  function prepare_texture_data (line 82) | def prepare_texture_data(image):
  function draw_pixels (line 92) | def draw_pixels(image, *, pos=0, zoom=1, align=0, rint=True):
  function read_pixels (line 115) | def read_pixels(width, height, *, pos=0, dtype='uint8', channels=3):
  class Texture (line 129) | class Texture:
    method __init__ (line 130) | def __init__(self, *, image=None, width=None, height=None, channels=No...
    method delete (line 162) | def delete(self):
    method __del__ (line 167) | def __del__(self):
    method bind (line 174) | def bind(self):
    method update (line 180) | def update(self, image):
    method draw (line 193) | def draw(self, *, pos=0, zoom=1, align=0, rint=False, color=1, alpha=1...
    method is_compatible (line 202) | def is_compatible(self, *, image=None, width=None, height=None, channe...
  class Framebuffer (line 221) | class Framebuffer:
    method __init__ (line 222) | def __init__(self, *, texture=None, width=None, height=None, channels=...
    method delete (line 273) | def delete(self):
    method __del__ (line 284) | def __del__(self):
    method bind (line 291) | def bind(self):
    method blit (line 301) | def blit(self, dst=None):
  function draw_shape (line 309) | def draw_shape(vertices, *, mode=gl.GL_TRIANGLE_FAN, pos=0, size=1, colo...
  function draw_arrow (line 336) | def draw_arrow(x1, y1, x2, y2, l=10, width=1.0):
  function draw_rect (line 377) | def draw_rect(*, pos=0, pos2=None, size=None, align=0, rint=False, color...
  function _setup_rect (line 394) | def _setup_rect(rx, ry):
  function draw_circle (line 404) | def draw_circle(*, center=0, radius=100, hole=0, color=1, alpha=1):
  function _setup_circle (line 410) | def _setup_circle(hole):

FILE: gui_utils/glfw_window.py
  class GlfwWindow (line 16) | class GlfwWindow: # pylint: disable=too-many-public-methods
    method __init__ (line 17) | def __init__(self, *, title='GlfwWindow', window_width=1920, window_he...
    method close (line 45) | def close(self):
    method __del__ (line 53) | def __del__(self):
    method window_width (line 60) | def window_width(self):
    method window_height (line 64) | def window_height(self):
    method content_width (line 68) | def content_width(self):
    method content_height (line 73) | def content_height(self):
    method title_bar_height (line 78) | def title_bar_height(self):
    method monitor_width (line 83) | def monitor_width(self):
    method monitor_height (line 88) | def monitor_height(self):
    method frame_delta (line 93) | def frame_delta(self):
    method set_title (line 96) | def set_title(self, title):
    method set_window_size (line 99) | def set_window_size(self, width, height):
    method set_content_size (line 106) | def set_content_size(self, width, height):
    method maximize (line 109) | def maximize(self):
    method set_position (line 112) | def set_position(self, x, y):
    method center (line 115) | def center(self):
    method set_vsync (line 118) | def set_vsync(self, vsync):
    method set_fps_limit (line 124) | def set_fps_limit(self, fps_limit):
    method should_close (line 127) | def should_close(self):
    method skip_frame (line 130) | def skip_frame(self):
    method skip_frames (line 133) | def skip_frames(self, num): # Do not update window for the next N frames.
    method is_skipping_frames (line 136) | def is_skipping_frames(self):
    method capture_next_frame (line 139) | def capture_next_frame(self):
    method pop_captured_frame (line 142) | def pop_captured_frame(self):
    method pop_drag_and_drop_paths (line 147) | def pop_drag_and_drop_paths(self):
    method draw_frame (line 152) | def draw_frame(self): # To be overridden by subclass.
    method make_context_current (line 157) | def make_context_current(self):
    method begin_frame (line 161) | def begin_frame(self):
    method end_frame (line 198) | def end_frame(self):
    method _attach_glfw_callbacks (line 218) | def _attach_glfw_callbacks(self):
    method _glfw_key_callback (line 222) | def _glfw_key_callback(self, _window, key, _scancode, action, _mods):
    method _glfw_drop_callback (line 226) | def _glfw_drop_callback(self, _window, paths):

FILE: gui_utils/imgui_utils.py
  function set_default_style (line 14) | def set_default_style(color_scheme='dark', spacing=9, indent=23, scrollb...
  function grayed_out (line 42) | def grayed_out(cond=True):
  function item_width (line 70) | def item_width(width=None):
  function scoped_by_object_id (line 80) | def scoped_by_object_id(method):
  function button (line 90) | def button(label, width=0, enabled=True):
  function collapsing_header (line 98) | def collapsing_header(text, visible=None, flags=0, default=False, enable...
  function popup_button (line 112) | def popup_button(label, width=0, enabled=True):
  function input_text (line 120) | def input_text(label, value, buffer_length, flags, width=None, help_text...
  function drag_previous_control (line 137) | def drag_previous_control(enabled=True):
  function drag_button (line 151) | def drag_button(label, width=0, enabled=True):
  function drag_hidden_window (line 158) | def drag_hidden_window(label, x, y, width, height, enabled=True):
  function click_hidden_window (line 171) | def click_hidden_window(label, x, y, width, height, img_w, img_h, enable...

FILE: gui_utils/imgui_window.py
  class ImguiWindow (line 19) | class ImguiWindow(glfw_window.GlfwWindow):
    method __init__ (line 20) | def __init__(self, *, title='ImguiWindow', font=None, font_sizes=range...
    method close (line 45) | def close(self):
    method _glfw_key_callback (line 56) | def _glfw_key_callback(self, *args):
    method font_size (line 61) | def font_size(self):
    method spacing (line 65) | def spacing(self):
    method set_font_size (line 68) | def set_font_size(self, target): # Applied on next frame.
    method begin_frame (line 71) | def begin_frame(self):
    method end_frame (line 85) | def end_frame(self):
  class _GlfwRenderer (line 95) | class _GlfwRenderer(imgui.integrations.glfw.GlfwRenderer):
    method __init__ (line 96) | def __init__(self, *args, **kwargs):
    method scroll_callback (line 100) | def scroll_callback(self, window, x_offset, y_offset):

FILE: gui_utils/text_utils.py
  function get_default_font (line 22) | def get_default_font():
  function get_pil_font (line 29) | def get_pil_font(font=None, size=32):
  function get_array (line 36) | def get_array(string, *, dropshadow_radius: int=None, **kwargs):
  function _get_array_priv (line 45) | def _get_array_priv(
  function _get_array_impl (line 74) | def _get_array_impl(string, *, font=None, size=32, outline=0, outline_pa...
  function _get_array_impl_dropshadow (line 96) | def _get_array_impl_dropshadow(string, *, font=None, size=32, radius: in...
  function get_texture (line 120) | def get_texture(string, bilinear=True, mipmap=True, **kwargs):

FILE: legacy.py
  function load_network_pkl (line 22) | def load_network_pkl(f, force_fp16=False):
  class _TFNetworkStub (line 62) | class _TFNetworkStub(dnnlib.EasyDict):
  class _LegacyUnpickler (line 65) | class _LegacyUnpickler(pickle.Unpickler):
    method find_class (line 66) | def find_class(self, module, name):
  function _collect_tf_params (line 73) | def _collect_tf_params(tf_net):
  function _populate_module_params (line 86) | def _populate_module_params(module, *patterns):
  function convert_tf_generator (line 107) | def convert_tf_generator(tf_G):
  function convert_tf_discriminator (line 208) | def convert_tf_discriminator(tf_D):
  function convert_network_pickle (line 297) | def convert_network_pickle(source, dest, force_fp16):

FILE: stylegan_human/PP_HumanSeg/deploy/infer.py
  class DeployConfig (line 36) | class DeployConfig:
    method __init__ (line 37) | def __init__(self, path):
    method transforms (line 46) | def transforms(self):
    method model (line 50) | def model(self):
    method params (line 54) | def params(self):
    method _load_transforms (line 57) | def _load_transforms(self, t_list):
  class Predictor (line 67) | class Predictor:
    method __init__ (line 68) | def __init__(self, args):
    method preprocess (line 89) | def preprocess(self, img):
    method run (line 97) | def run(self, img, bg):
    method postprocess (line 117) | def postprocess(self, pred, img, ori_shape, bg):

FILE: stylegan_human/alignment.py
  function angle_between_points (line 25) | def angle_between_points(p0,p1,p2):
  function crop_img_with_padding (line 36) | def crop_img_with_padding(img, keypoints, rect):
  function run (line 101) | def run(args):

FILE: stylegan_human/bg_white.py
  function bg_white (line 8) | def bg_white(seg, raw, blur_level=3, gaussian=81):
  function main (line 40) | def main(

FILE: stylegan_human/dnnlib/tflib/autosummary.py
  function _create_var (line 47) | def _create_var(name: str, value_expr: TfExpression) -> TfExpression:
  function autosummary (line 79) | def autosummary(name: str, value: TfExpressionEx, passthru: TfExpression...
  function finalize_autosummaries (line 120) | def finalize_autosummaries() -> None:
  function save_summaries (line 179) | def save_summaries(file_writer, global_step=None):

FILE: stylegan_human/dnnlib/tflib/custom_ops.py
  function _find_compiler_bindir (line 38) | def _find_compiler_bindir():
  function _get_compute_cap (line 44) | def _get_compute_cap(device):
  function _get_cuda_gpu_arch_string (line 51) | def _get_cuda_gpu_arch_string():
  function _run_cmd (line 58) | def _run_cmd(cmd):
  function _prepare_nvcc_cli (line 65) | def _prepare_nvcc_cli(opts):
  function get_plugin (line 89) | def get_plugin(cuda_file):

FILE: stylegan_human/dnnlib/tflib/network.py
  function import_handler (line 31) | def import_handler(handler_func):
  class Network (line 37) | class Network:
    method __init__ (line 75) | def __init__(self, name: str = None, func_name: Any = None, **static_k...
    method _init_fields (line 102) | def _init_fields(self) -> None:
    method _init_graph (line 127) | def _init_graph(self) -> None:
    method reset_own_vars (line 189) | def reset_own_vars(self) -> None:
    method reset_vars (line 193) | def reset_vars(self) -> None:
    method reset_trainables (line 197) | def reset_trainables(self) -> None:
    method get_output_for (line 201) | def get_output_for(self, *in_expr: TfExpression, return_as_list: bool ...
    method get_var_local_name (line 236) | def get_var_local_name(self, var_or_global_name: Union[TfExpression, s...
    method find_var (line 242) | def find_var(self, var_or_local_name: Union[TfExpression, str]) -> TfE...
    method get_var (line 247) | def get_var(self, var_or_local_name: Union[TfExpression, str]) -> np.n...
    method set_var (line 252) | def set_var(self, var_or_local_name: Union[TfExpression, str], new_val...
    method __getstate__ (line 257) | def __getstate__(self) -> dict:
    method __setstate__ (line 269) | def __setstate__(self, state: dict) -> None:
    method clone (line 303) | def clone(self, name: str = None, **new_static_kwargs) -> "Network":
    method copy_own_vars_from (line 318) | def copy_own_vars_from(self, src_net: "Network") -> None:
    method copy_vars_from (line 323) | def copy_vars_from(self, src_net: "Network") -> None:
    method copy_trainables_from (line 328) | def copy_trainables_from(self, src_net: "Network") -> None:
    method convert (line 333) | def convert(self, new_func_name: str, new_name: str = None, **new_stat...
    method setup_as_moving_average_of (line 343) | def setup_as_moving_average_of(self, src_net: "Network", beta: TfExpre...
    method run (line 355) | def run(self,
    method list_ops (line 457) | def list_ops(self) -> List[TfExpression]:
    method list_layers (line 465) | def list_layers(self) -> List[Tuple[str, TfExpression, List[TfExpressi...
    method print_layers (line 508) | def print_layers(self, title: str = None, hide_layers_with_no_params: ...
    method setup_weight_histograms (line 537) | def setup_weight_histograms(self, title: str = None) -> None:
  function _handle_legacy_output_transforms (line 557) | def _handle_legacy_output_transforms(output_transform, dynamic_kwargs):
  function _legacy_output_transform_func (line 577) | def _legacy_output_transform_func(*expr, out_mul=1.0, out_add=0.0, out_s...

FILE: stylegan_human/dnnlib/tflib/ops/fused_bias_act.py
  function _get_plugin (line 17) | def _get_plugin():
  function fused_bias_act (line 36) | def fused_bias_act(x, b=None, axis=1, act='linear', alpha=None, gain=Non...
  function _fused_bias_act_ref (line 74) | def _fused_bias_act_ref(x, b, axis, act, alpha, gain):
  function _fused_bias_act_cuda (line 102) | def _fused_bias_act_cuda(x, b, axis, act, alpha, gain):

FILE: stylegan_human/dnnlib/tflib/ops/upfirdn_2d.py
  function _get_plugin (line 16) | def _get_plugin():
  function upfirdn_2d (line 21) | def upfirdn_2d(x, k, upx=1, upy=1, downx=1, downy=1, padx0=0, padx1=0, p...
  function _upfirdn_2d_ref (line 68) | def _upfirdn_2d_ref(x, k, upx, upy, downx, downy, padx0, padx1, pady0, p...
  function _upfirdn_2d_cuda (line 107) | def _upfirdn_2d_cuda(x, k, upx, upy, downx, downy, padx0, padx1, pady0, ...
  function filter_2d (line 146) | def filter_2d(x, k, gain=1, data_format='NCHW', impl='cuda'):
  function upsample_2d (line 171) | def upsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl='c...
  function downsample_2d (line 204) | def downsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl=...
  function upsample_conv_2d (line 236) | def upsample_conv_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW',...
  function conv_downsample_2d (line 298) | def conv_downsample_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW...
  function _shape (line 339) | def _shape(tf_expr, dim_idx):
  function _setup_kernel (line 346) | def _setup_kernel(k):
  function _simple_upfirdn_2d (line 355) | def _simple_upfirdn_2d(x, k, up=1, down=1, pad0=0, pad1=0, data_format='...

FILE: stylegan_human/dnnlib/tflib/optimizer.py
  class Optimizer (line 30) | class Optimizer:
    method __init__ (line 42) | def __init__(self,
    method _get_device (line 86) | def _get_device(self, device_name: str):
    method register_gradients (line 116) | def register_gradients(self, loss: TfExpression, trainable_vars: Union...
    method apply_updates (line 158) | def apply_updates(self, allow_no_op: bool = False) -> tf.Operation:
    method reset_optimizer_state (line 268) | def reset_optimizer_state(self) -> None:
    method get_loss_scaling_var (line 273) | def get_loss_scaling_var(self, device: str) -> Union[tf.Variable, None]:
    method apply_loss_scaling (line 277) | def apply_loss_scaling(self, value: TfExpression) -> TfExpression:
    method undo_loss_scaling (line 284) | def undo_loss_scaling(self, value: TfExpression) -> TfExpression:
  class SimpleAdam (line 292) | class SimpleAdam:
    method __init__ (line 295) | def __init__(self, name="Adam", learning_rate=0.001, beta1=0.9, beta2=...
    method variables (line 303) | def variables(self):
    method compute_gradients (line 306) | def compute_gradients(self, loss, var_list, gate_gradients=tf.train.Op...
    method apply_gradients (line 310) | def apply_gradients(self, grads_and_vars):

FILE: stylegan_human/dnnlib/tflib/tfutil.py
  function run (line 30) | def run(*args, **kwargs) -> Any:
  function is_tf_expression (line 36) | def is_tf_expression(x: Any) -> bool:
  function shape_to_list (line 41) | def shape_to_list(shape: Iterable[tf.Dimension]) -> List[Union[int, None]]:
  function flatten (line 46) | def flatten(x: TfExpressionEx) -> TfExpression:
  function log2 (line 52) | def log2(x: TfExpressionEx) -> TfExpression:
  function exp2 (line 58) | def exp2(x: TfExpressionEx) -> TfExpression:
  function lerp (line 64) | def lerp(a: TfExpressionEx, b: TfExpressionEx, t: TfExpressionEx) -> TfE...
  function lerp_clip (line 70) | def lerp_clip(a: TfExpressionEx, b: TfExpressionEx, t: TfExpressionEx) -...
  function absolute_name_scope (line 76) | def absolute_name_scope(scope: str) -> tf.name_scope:
  function absolute_variable_scope (line 81) | def absolute_variable_scope(scope: str, **kwargs) -> tf.variable_scope:
  function _sanitize_tf_config (line 86) | def _sanitize_tf_config(config_dict: dict = None) -> dict:
  function init_tf (line 109) | def init_tf(config_dict: dict = None) -> None:
  function assert_tf_initialized (line 137) | def assert_tf_initialized():
  function create_session (line 143) | 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 196) | def set_vars(var_to_value_dict: dict) -> None:
  function create_var_with_large_initial_value (line 222) | def create_var_with_large_initial_value(initial_value: np.ndarray, *args...
  function convert_images_from_uint8 (line 232) | def convert_images_from_uint8(images, drange=[-1,1], nhwc_to_nchw=False):
  function convert_images_to_uint8 (line 242) | def convert_images_to_uint8(images, drange=[-1,1], nchw_to_nhwc=False, s...

FILE: stylegan_human/dnnlib/util.py
  class EasyDict (line 41) | class EasyDict(dict):
    method __getattr__ (line 44) | def __getattr__(self, name: str) -> Any:
    method __setattr__ (line 50) | def __setattr__(self, name: str, value: Any) -> None:
    method __delattr__ (line 53) | def __delattr__(self, name: str) -> None:
  class Logger (line 57) | class Logger(object):
    method __init__ (line 60) | def __init__(self, file_name: str = None, file_mode: str = "w", should...
    method __enter__ (line 73) | def __enter__(self) -> "Logger":
    method __exit__ (line 76) | def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> N...
    method write (line 79) | def write(self, text: Union[str, bytes]) -> None:
    method flush (line 94) | def flush(self) -> None:
    method close (line 101) | def close(self) -> None:
  function set_cache_dir (line 121) | def set_cache_dir(path: str) -> None:
  function make_cache_dir_path (line 125) | def make_cache_dir_path(*paths: str) -> str:
  function format_time (line 140) | def format_time(seconds: Union[int, float]) -> str:
  function ask_yes_no (line 154) | def ask_yes_no(question: str) -> bool:
  function tuple_product (line 164) | def tuple_product(t: Tuple) -> Any:
  function get_dtype_and_ctype (line 188) | def get_dtype_and_ctype(type_obj: Any) -> Tuple[np.dtype, Any]:
  function is_pickleable (line 211) | def is_pickleable(obj: Any) -> bool:
  function get_module_from_obj_name (line 223) | def get_module_from_obj_name(obj_name: str) -> Tuple[types.ModuleType, s...
  function get_obj_from_module (line 264) | def get_obj_from_module(module: types.ModuleType, obj_name: str) -> Any:
  function get_obj_by_name (line 274) | def get_obj_by_name(name: str) -> Any:
  function call_func_by_name (line 280) | def call_func_by_name(*args, func_name: str = None, **kwargs) -> Any:
  function construct_class_by_name (line 289) | def construct_class_by_name(*args, class_name: str = None, **kwargs) -> ...
  function get_module_dir_by_obj_name (line 294) | def get_module_dir_by_obj_name(obj_name: str) -> str:
  function is_top_level_function (line 300) | def is_top_level_function(obj: Any) -> bool:
  function get_top_level_function_name (line 305) | def get_top_level_function_name(obj: Any) -> str:
  function list_dir_recursively_with_ignore (line 317) | def list_dir_recursively_with_ignore(dir_path: str, ignores: List[str] =...
  function copy_files_and_create_dirs (line 350) | def copy_files_and_create_dirs(files: List[Tuple[str, str]]) -> None:
  function is_url (line 366) | def is_url(obj: Any, allow_file_urls: bool = False) -> bool:
  function open_url (line 384) | def open_url(url: str, cache_dir: str = None, num_attempts: int = 10, ve...

FILE: stylegan_human/edit.py
  function main (line 55) | def main(

FILE: stylegan_human/edit/edit_helper.py
  function conv_warper (line 10) | def conv_warper(layer, input, style, noise):
  function decoder (line 58) | def decoder(G, style_space, latent, noise):
  function encoder_ifg (line 76) | def encoder_ifg(G, noise, attr_name, truncation=1, truncation_latent=None,
  function encoder_ss (line 122) | def encoder_ss(G, noise, attr_name, truncation=1, truncation_latent=None,
  function encoder_sefa (line 180) | def encoder_sefa(G, noise, attr_name, truncation=1, truncation_latent=None,

FILE: stylegan_human/generate.py
  function generate_images (line 48) | def generate_images(

FILE: stylegan_human/insetgan.py
  class InsetGAN (line 19) | class InsetGAN(torch.nn.Module):
    method __init__ (line 20) | def __init__(self, stylebody_ckpt, styleface_ckpt):
    method loss_coarse (line 59) | def loss_coarse(self, A_face, B, p1=500, p2=0.05):
    method get_border_mask (line 67) | def get_border_mask(A, x, spec):
    method get_body_mask (line 76) | def get_body_mask(A, crop, padding=4):
    method loss_border (line 81) | def loss_border(self, A_face, B, p1=10000, p2=2, spec=None):
    method loss_body (line 87) | def loss_body(self, A, B, crop, p1=9000, p2=0.1):
    method loss_face (line 94) | def loss_face(self, A, B, crop, p1=5000, p2=1.75):
    method loss_reg (line 100) | def loss_reg(self, w, w_mean, p1, w_plus_delta=None, p2=None):
    method detect_face_dlib (line 104) | def detect_face_dlib(self, img):
    method dual_optimizer (line 117) | def dual_optimizer(self,
  function main (line 347) | def main(

FILE: stylegan_human/interpolation.py
  function lerp (line 22) | def lerp(code1, code2, alpha):
  function slerp (line 27) | def slerp(code1, code2, alpha, DOT_THRESHOLD=0.9995): # Spherical linear...
  function generate_image_from_z (line 49) | def generate_image_from_z(G, z, noise_mode, truncation_psi, device):
  function get_concat_h (line 58) | def get_concat_h(im1, im2):
  function make_latent_interp_animation (line 65) | def make_latent_interp_animation(G, code1, code2, img1, img2, num_interp...
  function main (line 106) | def main(

FILE: stylegan_human/legacy.py
  function load_network_pkl (line 22) | def load_network_pkl(f, force_fp16=False, G_only=False):
  class _TFNetworkStub (line 75) | class _TFNetworkStub(dnnlib.EasyDict):
  class _LegacyUnpickler (line 78) | class _LegacyUnpickler(pickle.Unpickler):
    method find_class (line 79) | def find_class(self, module, name):
  function num_range (line 86) | def num_range(s: str) -> List[int]:
  function load_pkl (line 100) | def load_pkl(file_or_url):
  function visual (line 107) | def visual(output, out_path):
  function save_obj (line 120) | def save_obj(obj, path):
  function convert_to_rgb (line 128) | def convert_to_rgb(state_ros, state_nv, ros_name, nv_name):
  function convert_conv (line 135) | def convert_conv(state_ros, state_nv, ros_name, nv_name):
  function convert_blur_kernel (line 143) | def convert_blur_kernel(state_ros, state_nv, level):
  function determine_config (line 150) | def determine_config(state_nv):
  function convert (line 161) | def convert(network_pkl, output_file, G_only=False):

FILE: stylegan_human/openpose/src/body.py
  class Body (line 14) | class Body(object):
    method __init__ (line 15) | def __init__(self, model_path):
    method __call__ (line 23) | def __call__(self, oriImg):

FILE: stylegan_human/openpose/src/model.py
  function make_layers (line 7) | def make_layers(block, no_relu_layers):
  class bodypose_model (line 24) | class bodypose_model(nn.Module):
    method __init__ (line 25) | def __init__(self):
    method forward (line 114) | def forward(self, x):
  class handpose_model (line 143) | class handpose_model(nn.Module):
    method __init__ (line 144) | def __init__(self):
    method forward (line 204) | def forward(self, x):

FILE: stylegan_human/openpose/src/util.py
  function padRightDownCorner (line 12) | def padRightDownCorner(img, stride, padValue):
  function transfer (line 35) | def transfer(model, model_weights):
  function draw_bodypose (line 42) | def draw_bodypose(canvas, candidate, subset,show_number=False):
  function npmax (line 81) | def npmax(array):
  function npmax_with_score (line 89) | def npmax_with_score(array):

FILE: stylegan_human/pti/pti_models/e4e/encoders/helpers.py
  class Flatten (line 11) | class Flatten(Module):
    method forward (line 12) | def forward(self, input):
  function l2_norm (line 16) | def l2_norm(input, axis=1):
  class Bottleneck (line 22) | class Bottleneck(namedtuple('Block', ['in_channel', 'depth', 'stride'])):
  function get_block (line 26) | def get_block(in_channel, depth, num_units, stride=2):
  function get_blocks (line 30) | def get_blocks(num_layers):
  class SEModule (line 57) | class SEModule(Module):
    method __init__ (line 58) | def __init__(self, channels, reduction):
    method forward (line 66) | def forward(self, x):
  class bottleneck_IR (line 76) | class bottleneck_IR(Module):
    method __init__ (line 77) | def __init__(self, in_channel, depth, stride):
    method forward (line 92) | def forward(self, x):
  class bottleneck_IR_SE (line 98) | class bottleneck_IR_SE(Module):
    method __init__ (line 99) | def __init__(self, in_channel, depth, stride):
    method forward (line 117) | def forward(self, x):
  function _upsample_add (line 123) | def _upsample_add(x, y):

FILE: stylegan_human/pti/pti_models/e4e/encoders/model_irse.py
  class Backbone (line 9) | class Backbone(Module):
    method __init__ (line 10) | def __init__(self, input_size, num_layers, mode='ir', drop_ratio=0.4, ...
    method forward (line 44) | def forward(self, x):
  function IR_50 (line 51) | def IR_50(input_size):
  function IR_101 (line 57) | def IR_101(input_size):
  function IR_152 (line 63) | def IR_152(input_size):
  function IR_SE_50 (line 69) | def IR_SE_50(input_size):
  function IR_SE_101 (line 75) | def IR_SE_101(input_size):
  function IR_SE_152 (line 81) | def IR_SE_152(input_size):

FILE: stylegan_human/pti/pti_models/e4e/encoders/psp_encoders.py
  class ProgressiveStage (line 12) | class ProgressiveStage(Enum):
  class GradualStyleBlock (line 34) | class GradualStyleBlock(Module):
    method __init__ (line 35) | def __init__(self, in_c, out_c, spatial):
    method forward (line 51) | def forward(self, x):
  class GradualStyleEncoder (line 58) | class GradualStyleEncoder(Module):
    method __init__ (line 59) | def __init__(self, num_layers, mode='ir', opts=None):
    method forward (line 95) | def forward(self, x):
  class Encoder4Editing (line 124) | class Encoder4Editing(Module):
    method __init__ (line 125) | def __init__(self, num_layers, mode='ir', opts=None):
    method get_deltas_starting_dimensions (line 165) | def get_deltas_starting_dimensions(self):
    method set_progressive_stage (line 169) | def set_progressive_stage(self, new_stage: ProgressiveStage):
    method forward (line 173) | def forward(self, x):

FILE: stylegan_human/pti/pti_models/e4e/latent_codes_pool.py
  class LatentCodesPool (line 5) | class LatentCodesPool:
    method __init__ (line 11) | def __init__(self, pool_size):
    method query (line 21) | def query(self, ws):
    method handle_w (line 42) | def handle_w(self, w, return_ws):

FILE: stylegan_human/pti/pti_models/e4e/psp.py
  function get_keys (line 10) | def get_keys(d, name):
  class pSp (line 17) | class pSp(nn.Module):
    method __init__ (line 19) | def __init__(self, opts):
    method set_encoder (line 29) | def set_encoder(self):
    method load_weights (line 40) | def load_weights(self):
    method forward (line 56) | def forward(self, x, resize=True, latent_mask=None, input_code=False, ...
    method __load_latent_avg (line 93) | def __load_latent_avg(self, ckpt, repeat=None):

FILE: stylegan_human/pti/pti_models/e4e/stylegan2/model.py
  class PixelNorm (line 11) | class PixelNorm(nn.Module):
    method __init__ (line 12) | def __init__(self):
    method forward (line 15) | def forward(self, input):
  function make_kernel (line 19) | def make_kernel(k):
  class Upsample (line 30) | class Upsample(nn.Module):
    method __init__ (line 31) | def __init__(self, kernel, factor=2):
    method forward (line 45) | def forward(self, input):
  class Downsample (line 51) | class Downsample(nn.Module):
    method __init__ (line 52) | def __init__(self, kernel, factor=2):
    method forward (line 66) | def forward(self, input):
  class Blur (line 72) | class Blur(nn.Module):
    method __init__ (line 73) | def __init__(self, kernel, pad, upsample_factor=1):
    method forward (line 85) | def forward(self, input):
  class EqualConv2d (line 91) | class EqualConv2d(nn.Module):
    method __init__ (line 92) | def __init__(
    method forward (line 111) | def forward(self, input):
    method __repr__ (line 122) | def __repr__(self):
  class EqualLinear (line 129) | class EqualLinear(nn.Module):
    method __init__ (line 130) | def __init__(
    method forward (line 148) | def forward(self, input):
    method __repr__ (line 160) | def __repr__(self):
  class ScaledLeakyReLU (line 166) | class ScaledLeakyReLU(nn.Module):
    method __init__ (line 167) | def __init__(self, negative_slope=0.2):
    method forward (line 172) | def forward(self, input):
  class ModulatedConv2d (line 178) | class ModulatedConv2d(nn.Module):
    method __init__ (line 179) | def __init__(
    method __repr__ (line 227) | def __repr__(self):
    method forward (line 233) | def forward(self, input, style):
  class NoiseInjection (line 277) | class NoiseInjection(nn.Module):
    method __init__ (line 278) | def __init__(self):
    method forward (line 283) | def forward(self, image, noise=None):
  class ConstantInput (line 291) | class ConstantInput(nn.Module):
    method __init__ (line 292) | def __init__(self, channel, size=4):
    method forward (line 297) | def forward(self, input):
  class StyledConv (line 304) | class StyledConv(nn.Module):
    method __init__ (line 305) | def __init__(
    method forward (line 332) | def forward(self, input, style, noise=None):
  class ToRGB (line 341) | class ToRGB(nn.Module):
    method __init__ (line 342) | def __init__(self, in_channel, style_dim, upsample=True, blur_kernel=[...
    method forward (line 351) | def forward(self, input, style, skip=None):
  class Generator (line 363) | class Generator(nn.Module):
    method __init__ (line 364) | def __init__(
    method make_noise (line 451) | def make_noise(self):
    method mean_latent (line 462) | def mean_latent(self, n_latent):
    method get_latent (line 470) | def get_latent(self, input):
    method forward (line 473) | def forward(
  class ConvLayer (line 552) | class ConvLayer(nn.Sequential):
    method __init__ (line 553) | def __init__(
  class ResBlock (line 601) | class ResBlock(nn.Module):
    method __init__ (line 602) | def __init__(self, in_channel, out_channel, blur_kernel=[1, 3, 3, 1]):
    method forward (line 612) | def forward(self, input):
  class Discriminator (line 622) | class Discriminator(nn.Module):
    method __init__ (line 623) | def __init__(self, size, channel_multiplier=2, blur_kernel=[1, 3, 3, 1]):
    method forward (line 662) | def forward(self, input):

FILE: stylegan_human/pti/pti_models/e4e/stylegan2/op/fused_act.py
  class FusedLeakyReLU (line 13) | class FusedLeakyReLU(nn.Module):
    method __init__ (line 14) | def __init__(self, channel, negative_slope=0.2, scale=2 ** 0.5):
    method forward (line 21) | def forward(self, input):
  function fused_leaky_relu (line 25) | def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2 ** 0.5):

FILE: stylegan_human/pti/pti_models/e4e/stylegan2/op/fused_bias_act.cpp
  function fused_bias_act (line 11) | torch::Tensor fused_bias_act(const torch::Tensor& input, const torch::Te...
  function PYBIND11_MODULE (line 19) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: stylegan_human/pti/pti_models/e4e/stylegan2/op/upfirdn2d.cpp
  function upfirdn2d (line 12) | torch::Tensor upfirdn2d(const torch::Tensor& input, const torch::Tensor&...
  function PYBIND11_MODULE (line 21) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: stylegan_human/pti/pti_models/e4e/stylegan2/op/upfirdn2d.py
  function upfirdn2d (line 11) | def upfirdn2d(input, kernel, up=1, down=1, pad=(0, 0)):
  function upfirdn2d_native (line 19) | def upfirdn2d_native(

FILE: stylegan_human/pti/training/coaches/base_coach.py
  class BaseCoach (line 18) | class BaseCoach:
    method __init__ (line 19) | def __init__(self, data_loader, use_wandb):
    method restart_training (line 44) | def restart_training(self):
    method get_inversion (line 55) | def get_inversion(self, w_path_dir, image_name, image):
    method load_inversions (line 71) | def load_inversions(self, w_path_dir, image_name):
    method calc_inversions (line 85) | def calc_inversions(self, image, image_name):
    method train (line 98) | def train(self):
    method configure_optimizers (line 101) | def configure_optimizers(self):
    method calc_loss (line 106) | def calc_loss(self, generated_images, real_images, log_name, new_G, us...
    method forward (line 127) | def forward(self, w):
    method initilize_e4e (line 132) | def initilize_e4e(self):
    method get_e4e_inversion (line 143) | def get_e4e_inversion(self, image):

FILE: stylegan_human/pti/training/coaches/localitly_regulizer.py
  function l2_loss (line 8) | def l2_loss(real_images, generated_images):
  class Space_Regulizer (line 13) | class Space_Regulizer:
    method __init__ (line 14) | def __init__(self, original_G, lpips_net):
    method get_morphed_w_code (line 19) | def get_morphed_w_code(self, new_w_code, fixed_w):
    method get_image_from_ws (line 28) | def get_image_from_ws(self, w_codes, G):
    method ball_holder_loss_lazy (line 31) | def ball_holder_loss_lazy(self, new_G, num_of_sampled_latents, w_batch...
    method space_regulizer_loss (line 61) | def space_regulizer_loss(self, new_G, w_batch, use_wandb):

FILE: stylegan_human/pti/training/coaches/multi_id_coach.py
  class MultiIDCoach (line 13) | class MultiIDCoach(BaseCoach):
    method __init__ (line 15) | def __init__(self, data_loader, use_wandb):
    method train (line 18) | def train(self):

FILE: stylegan_human/pti/training/coaches/single_id_coach.py
  class SingleIDCoach (line 11) | class SingleIDCoach(BaseCoach):
    method __init__ (line 13) | def __init__(self, data_loader, use_wandb):
    method train (line 16) | def train(self):

FILE: stylegan_human/pti/training/projectors/w_plus_projector.py
  function project (line 22) | def project(

FILE: stylegan_human/pti/training/projectors/w_projector.py
  function project (line 22) | def project(

FILE: stylegan_human/run_pti.py
  function run_PTI (line 16) | def run_PTI(run_name='', use_wandb=False, use_multi_id_training=False):

FILE: stylegan_human/style_mixing.py
  function generate_style_mix (line 41) | def generate_style_mix(

FILE: stylegan_human/stylemixing_video.py
  function style_mixing_video (line 49) | def style_mixing_video(network_pkl: str,

FILE: stylegan_human/torch_utils/custom_ops.py
  function _find_compiler_bindir (line 32) | def _find_compiler_bindir():
  function _get_mangled_gpu_name (line 45) | def _get_mangled_gpu_name():
  function get_plugin (line 61) | def get_plugin(module_name, sources, **build_kwargs):
  function get_plugin_v3 (line 142) | def get_plugin_v3(module_name, sources, headers=None, source_dir=None, *...

FILE: stylegan_human/torch_utils/misc.py
  function constant (line 24) | def constant(value, shape=None, dtype=None, device=None, memory_format=N...
  function nan_to_num (line 51) | def nan_to_num(input, nan=0.0, posinf=None, neginf=None, *, out=None): #...
  class suppress_tracer_warnings (line 71) | class suppress_tracer_warnings(warnings.catch_warnings):
    method __enter__ (line 72) | def __enter__(self):
  function assert_shape (line 82) | def assert_shape(tensor, ref_shape):
  function profiled_function (line 100) | def profiled_function(fn):
  class InfiniteSampler (line 111) | class InfiniteSampler(torch.utils.data.Sampler):
    method __init__ (line 112) | def __init__(self, dataset, rank=0, num_replicas=1, shuffle=True, seed...
    method __iter__ (line 125) | def __iter__(self):
  function params_and_buffers (line 147) | def params_and_buffers(module):
  function named_params_and_buffers (line 151) | def named_params_and_buffers(module):
  function copy_params_and_buffers (line 155) | def copy_params_and_buffers(src_module, dst_module, require_all=False):
  function ddp_sync (line 169) | def ddp_sync(module, sync):
  function check_ddp_consistency (line 180) | def check_ddp_consistency(module, ignore_regex=None):
  function print_module_summary (line 194) | def print_module_summary(module, inputs, max_nesting=3, skip_redundant=T...

FILE: stylegan_human/torch_utils/models.py
  class PixelNorm (line 19) | class PixelNorm(nn.Module):
    method __init__ (line 20) | def __init__(self):
    method forward (line 23) | def forward(self, input):
  function make_kernel (line 27) | def make_kernel(k):
  class Upsample (line 35) | class Upsample(nn.Module):
    method __init__ (line 36) | def __init__(self, kernel, factor=2):
    method forward (line 50) | def forward(self, input):
  class Downsample (line 55) | class Downsample(nn.Module):
    method __init__ (line 56) | def __init__(self, kernel, factor=2):
    method forward (line 70) | def forward(self, input):
  class Blur (line 75) | class Blur(nn.Module):
    method __init__ (line 76) | def __init__(self, kernel, pad, upsample_factor=1):
    method forward (line 88) | def forward(self, input):
  class EqualConv2d (line 93) | class EqualConv2d(nn.Module):
    method __init__ (line 94) | def __init__(
    method forward (line 113) | def forward(self, input):
    method __repr__ (line 123) | def __repr__(self):
  class EqualLinear (line 130) | class EqualLinear(nn.Module):
    method __init__ (line 131) | def __init__(
    method forward (line 148) | def forward(self, input):
    method __repr__ (line 158) | def __repr__(self):
  class ScaledLeakyReLU (line 164) | class ScaledLeakyReLU(nn.Module):
    method __init__ (line 165) | def __init__(self, negative_slope=0.2):
    method forward (line 169) | def forward(self, input):
  class ModulatedConv2d (line 174) | class ModulatedConv2d(nn.Module):
    method __init__ (line 175) | def __init__(
    method __repr__ (line 218) | def __repr__(self):
    method forward (line 224) | def forward(self, input, style):
  class NoiseInjection (line 268) | class NoiseInjection(nn.Module):
    method __init__ (line 269) | def __init__(self):
    method forward (line 273) | def forward(self, image, noise=None):
  class ConstantInput (line 280) | class ConstantInput(nn.Module):
    method __init__ (line 281) | def __init__(self, channel, size=4):
    method forward (line 285) | def forward(self, input):
  class StyledConv (line 291) | class StyledConv(nn.Module):
    method __init__ (line 292) | def __init__(
    method forward (line 315) | def forward(self, input, style, noise=None):
  class ToRGB (line 322) | class ToRGB(nn.Module):
    method __init__ (line 323) | def __init__(self, in_channel, style_dim, upsample=True, blur_kernel=[...
    method forward (line 331) | def forward(self, input, style, skip=None):
  class Generator (line 342) | class Generator(nn.Module):
    method __init__ (line 343) | def __init__(
    method make_noise (line 444) | def make_noise(self):
    method mean_latent (line 455) | def mean_latent(self, n_latent):
    method get_latent (line 463) | def get_latent(self, input):
    method forward (line 466) | def forward(
  class ConvLayer (line 558) | class ConvLayer(nn.Sequential):
    method __init__ (line 559) | def __init__(
  class ResBlock (line 606) | class ResBlock(nn.Module):
    method __init__ (line 607) | def __init__(self, in_channel, out_channel, blur_kernel=[1, 3, 3, 1]):
    method forward (line 617) | def forward(self, input):
  class StyleDiscriminator (line 627) | class StyleDiscriminator(nn.Module):
    method __init__ (line 628) | def __init__(
    method forward (line 673) | def forward(self, input):
  class StyleEncoder (line 701) | class StyleEncoder(nn.Module):
    method __init__ (line 702) | def __init__(self, size, w_dim=512):
    method forward (line 731) | def forward(self, input):
  function kaiming_init (line 737) | def kaiming_init(m):
  function normal_init (line 748) | def normal_init(m):

FILE: stylegan_human/torch_utils/models_face.py
  class PixelNorm (line 17) | class PixelNorm(nn.Module):
    method __init__ (line 18) | def __init__(self):
    method forward (line 21) | def forward(self, input):
  function make_kernel (line 25) | def make_kernel(k):
  class Upsample (line 36) | class Upsample(nn.Module):
    method __init__ (line 37) | def __init__(self, kernel, factor=2):
    method forward (line 51) | def forward(self, input):
  class Downsample (line 57) | class Downsample(nn.Module):
    method __init__ (line 58) | def __init__(self, kernel, factor=2):
    method forward (line 72) | def forward(self, input):
  class Blur (line 78) | class Blur(nn.Module):
    method __init__ (line 79) | def __init__(self, kernel, pad, upsample_factor=1):
    method forward (line 91) | def forward(self, input):
  class EqualConv2d (line 97) | class EqualConv2d(nn.Module):
    method __init__ (line 98) | def __init__(
    method forward (line 117) | def forward(self, input):
    method __repr__ (line 128) | def __repr__(self):
  class EqualLinear (line 135) | class EqualLinear(nn.Module):
    method __init__ (line 136) | def __init__(
    method forward (line 154) | def forward(self, input):
    method __repr__ (line 166) | def __repr__(self):
  class ScaledLeakyReLU (line 172) | class ScaledLeakyReLU(nn.Module):
    method __init__ (line 173) | def __init__(self, negative_slope=0.2):
    method forward (line 178) | def forward(self, input):
  class ModulatedConv2d (line 184) | class ModulatedConv2d(nn.Module):
    method __init__ (line 185) | def __init__(
    method __repr__ (line 233) | def __repr__(self):
    method forward (line 239) | def forward(self, input, style):
  class NoiseInjection (line 283) | class NoiseInjection(nn.Module):
    method __init__ (line 284) | def __init__(self):
    method forward (line 289) | def forward(self, image, noise=None):
  class ConstantInput (line 297) | class ConstantInput(nn.Module):
    method __init__ (line 298) | def __init__(self, channel, size=4):
    method forward (line 303) | def forward(self, input):
  class StyledConv (line 310) | class StyledConv(nn.Module):
    method __init__ (line 311) | def __init__(
    method forward (line 338) | def forward(self, input, style, noise=None):
  class ToRGB (line 347) | class ToRGB(nn.Module):
    method __init__ (line 348) | def __init__(self, in_channel, style_dim, upsample=True, blur_kernel=[...
    method forward (line 357) | def forward(self, input, style, skip=None):
  class Generator (line 369) | class Generator(nn.Module):
    method __init__ (line 370) | def __init__(
    method make_noise (line 473) | def make_noise(self):
    method mean_latent (line 484) | def mean_latent(self, n_latent):
    method get_latent (line 492) | def get_latent(self, input):
    method forward (line 495) | def forward(
  class ConvLayer (line 585) | class ConvLayer(nn.Sequential):
    method __init__ (line 586) | def __init__(
  class ResBlock (line 634) | class ResBlock(nn.Module):
    method __init__ (line 635) | def __init__(self, in_channel, out_channel, blur_kernel=[1, 3, 3, 1]):
    method forward (line 645) | def forward(self, input):
  class StyleDiscriminator (line 655) | class StyleDiscriminator(nn.Module):
    method __init__ (line 656) | def __init__(
    method forward (line 721) | def forward(self, input):
  class StyleEncoder (line 749) | class StyleEncoder(nn.Module):
    method __init__ (line 750) | def __init__(self, size, w_dim=512):
    method forward (line 784) | def forward(self, input):
  function kaiming_init (line 790) | def kaiming_init(m):
  function normal_init (line 801) | def normal_init(m):

FILE: stylegan_human/torch_utils/op_edit/fused_act.py
  class FusedLeakyReLUFunctionBackward (line 22) | class FusedLeakyReLUFunctionBackward(Function):
    method forward (line 24) | def forward(ctx, grad_output, out, negative_slope, scale):
    method backward (line 45) | def backward(ctx, gradgrad_input, gradgrad_bias):
  class FusedLeakyReLUFunction (line 54) | class FusedLeakyReLUFunction(Function):
    method forward (line 56) | def forward(ctx, input, bias, negative_slope, scale):
    method backward (line 66) | def backward(ctx, grad_output):
  class FusedLeakyReLU (line 76) | class FusedLeakyReLU(nn.Module):
    method __init__ (line 77) | def __init__(self, channel, negative_slope=0.2, scale=2 ** 0.5):
    method forward (line 84) | def forward(self, input):
  function fused_leaky_relu (line 88) | def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2 ** 0.5):

FILE: stylegan_human/torch_utils/op_edit/fused_bias_act.cpp
  function fused_bias_act (line 13) | torch::Tensor fused_bias_act(const torch::Tensor& input, const torch::Te...
  function PYBIND11_MODULE (line 21) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: stylegan_human/torch_utils/op_edit/upfirdn2d.cpp
  function upfirdn2d (line 14) | torch::Tensor upfirdn2d(const torch::Tensor& input, const torch::Tensor&...
  function PYBIND11_MODULE (line 23) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: stylegan_human/torch_utils/op_edit/upfirdn2d.py
  class UpFirDn2dBackward (line 21) | class UpFirDn2dBackward(Function):
    method forward (line 23) | def forward(
    method backward (line 65) | def backward(ctx, gradgrad_input):
  class UpFirDn2d (line 90) | class UpFirDn2d(Function):
    method forward (line 92) | def forward(ctx, input, kernel, up, down, pad):
    method backward (line 129) | def backward(ctx, grad_output):
  function upfirdn2d (line 147) | def upfirdn2d(input, kernel, up=1, down=1, pad=(0, 0)):
  function upfirdn2d_native (line 161) | def upfirdn2d_native(

FILE: stylegan_human/torch_utils/ops/bias_act.cpp
  function has_same_layout (line 18) | static bool has_same_layout(torch::Tensor x, torch::Tensor y)
  function bias_act (line 34) | static torch::Tensor bias_act(torch::Tensor x, torch::Tensor b, torch::T...
  function PYBIND11_MODULE (line 96) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)

FILE: stylegan_human/torch_utils/ops/bias_act.h
  type bias_act_kernel_params (line 14) | struct bias_act_kernel_params

FILE: stylegan_human/torch_utils/ops/bias_act.py
  function _init (line 43) | def _init():
  function bias_act (line 57) | def bias_act(x, b=None, dim=1, act='linear', alpha=None, gain=None, clam...
  function _bias_act_ref (line 96) | def _bias_act_ref(x, b=None, dim=1, act='linear', alpha=None, gain=None,...
  function _bias_act_cuda (line 131) | def _bias_act_cuda(dim=1, act='linear', alpha=None, gain=None, clamp=None):

FILE: stylegan_human/torch_utils/ops/conv2d_gradfix.py
  function no_weight_gradients (line 28) | def no_weight_gradients():
  function conv2d (line 37) | def conv2d(input, weight, bias=None, stride=1, padding=0, dilation=1, gr...
  function conv_transpose2d (line 42) | def conv_transpose2d(input, weight, bias=None, stride=1, padding=0, outp...
  function _should_use_custom_op (line 49) | def _should_use_custom_op(input):
  function _tuple_of_ints (line 60) | def _tuple_of_ints(xs, ndim):
  function _conv2d_gradfix (line 70) | def _conv2d_gradfix(transpose, weight_shape, stride, padding, output_pad...

FILE: stylegan_human/torch_utils/ops/conv2d_resample.py
  function _get_weight_shape (line 23) | def _get_weight_shape(w):
  function _conv2d_wrapper (line 31) | def _conv2d_wrapper(x, w, stride=1, padding=0, groups=1, transpose=False...
  function conv2d_resample (line 61) | def conv2d_resample(x, w, f=None, up=1, down=1, padding=0, groups=1, fli...

FILE: stylegan_human/torch_utils/ops/filtered_lrelu.cpp
  function filtered_lrelu (line 16) | static std::tuple<torch::Tensor, torch::Tensor, int> filtered_lrelu(
  function filtered_lrelu_act (line 213) | static torch::Tensor filtered_lrelu_act(torch::Tensor x, torch::Tensor s...
  function PYBIND11_MODULE (line 294) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)

FILE: stylegan_human/torch_utils/ops/filtered_lrelu.h
  type filtered_lrelu_kernel_params (line 14) | struct filtered_lrelu_kernel_params
  type filtered_lrelu_act_kernel_params (line 55) | struct filtered_lrelu_act_kernel_params
  type filtered_lrelu_kernel_spec (line 73) | struct filtered_lrelu_kernel_spec

FILE: stylegan_human/torch_utils/ops/filtered_lrelu.py
  function _init (line 23) | def _init():
  function _get_filter_size (line 43) | def _get_filter_size(f):
  function _parse_padding (line 50) | def _parse_padding(padding):
  function filtered_lrelu (line 64) | def filtered_lrelu(x, fu=None, fd=None, b=None, up=1, down=1, padding=0,...
  function _filtered_lrelu_ref (line 129) | def _filtered_lrelu_ref(x, fu=None, fd=None, b=None, up=1, down=1, paddi...
  function _filtered_lrelu_cuda (line 167) | def _filtered_lrelu_cuda(up=1, down=1, padding=0, gain=np.sqrt(2), slope...

FILE: stylegan_human/torch_utils/ops/fma.py
  function fma (line 17) | def fma(a, b, c): # => a * b + c
  class _FusedMultiplyAdd (line 22) | class _FusedMultiplyAdd(torch.autograd.Function): # a * b + c
    method forward (line 24) | def forward(ctx, a, b, c): # pylint: disable=arguments-differ
    method backward (line 31) | def backward(ctx, dout): # pylint: disable=arguments-differ
  function _unbroadcast (line 51) | def _unbroadcast(x, shape):

FILE: stylegan_human/torch_utils/ops/grid_sample_gradfix.py
  function grid_sample (line 29) | def grid_sample(input, grid):
  function _should_use_custom_op (line 36) | def _should_use_custom_op():
  class _GridSample2dForward (line 46) | class _GridSample2dForward(torch.autograd.Function):
    method forward (line 48) | def forward(ctx, input, grid):
    method backward (line 56) | def backward(ctx, grad_output):
  class _GridSample2dBackward (line 63) | class _GridSample2dBackward(torch.autograd.Function):
    method forward (line 65) | def forward(ctx, grad_output, input, grid):
    method backward (line 72) | def backward(ctx, grad2_grad_input, grad2_grad_grid):

FILE: stylegan_human/torch_utils/ops/upfirdn2d.cpp
  function upfirdn2d (line 18) | static torch::Tensor upfirdn2d(torch::Tensor x, torch::Tensor f, int upx...
  function PYBIND11_MODULE (line 100) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)

FILE: stylegan_human/torch_utils/ops/upfirdn2d.h
  type upfirdn2d_kernel_params (line 16) | struct upfirdn2d_kernel_params
  type upfirdn2d_kernel_spec (line 47) | struct upfirdn2d_kernel_spec

FILE: stylegan_human/torch_utils/ops/upfirdn2d.py
  function _init (line 28) | def _init():
  function _parse_scaling (line 39) | def _parse_scaling(scaling):
  function _parse_padding (line 48) | def _parse_padding(padding):
  function _get_filter_size (line 59) | def _get_filter_size(f):
  function setup_filter (line 74) | def setup_filter(f, device=torch.device('cpu'), normalize=True, flip_fil...
  function upfirdn2d (line 122) | def upfirdn2d(x, f, up=1, down=1, padding=0, flip_filter=False, gain=1, ...
  function _upfirdn2d_ref (line 171) | def _upfirdn2d_ref(x, f, up=1, down=1, padding=0, flip_filter=False, gai...
  function _upfirdn2d_cuda (line 216) | def _upfirdn2d_cuda(up=1, down=1, padding=0, flip_filter=False, gain=1):
  function filter2d (line 274) | def filter2d(x, f, padding=0, flip_filter=False, gain=1, impl='cuda'):
  function upsample2d (line 310) | def upsample2d(x, f, up=2, padding=0, flip_filter=False, gain=1, impl='c...
  function downsample2d (line 349) | def downsample2d(x, f, down=2, padding=0, flip_filter=False, gain=1, imp...

FILE: stylegan_human/torch_utils/persistence.py
  function persistent_class (line 37) | def persistent_class(orig_class):
  function is_persistent (line 136) | def is_persistent(obj):
  function import_hook (line 149) | def import_hook(hook):
  function _reconstruct_persistent_obj (line 181) | def _reconstruct_persistent_obj(meta):
  function _module_to_src (line 208) | def _module_to_src(module):
  function _src_to_module (line 218) | def _src_to_module(src):
  function _check_pickleable (line 233) | def _check_pickleable(obj):

FILE: stylegan_human/torch_utils/training_stats.py
  function init_multiprocessing (line 36) | def init_multiprocessing(rank, sync_device):
  function report (line 58) | def report(name, value):
  function report0 (line 105) | def report0(name, value):
  class Collector (line 115) | class Collector:
    method __init__ (line 135) | def __init__(self, regex='.*', keep_previous=True):
    method names (line 143) | def names(self):
    method update (line 149) | def update(self):
    method _get_delta (line 172) | def _get_delta(self, name):
    method num (line 182) | def num(self, name):
    method mean (line 190) | def mean(self, name):
    method std (line 200) | def std(self, name):
    method as_dict (line 214) | def as_dict(self):
    method __getitem__ (line 228) | def __getitem__(self, name):
  function _sync (line 236) | def _sync(names):

FILE: stylegan_human/training/augment.py
  function matrix (line 48) | def matrix(*rows, device=None):
  function translate2d (line 58) | def translate2d(tx, ty, **kwargs):
  function translate3d (line 65) | def translate3d(tx, ty, tz, **kwargs):
  function scale2d (line 73) | def scale2d(sx, sy, **kwargs):
  function scale3d (line 80) | def scale3d(sx, sy, sz, **kwargs):
  function rotate2d (line 88) | def rotate2d(theta, **kwargs):
  function rotate3d (line 95) | def rotate3d(v, theta, **kwargs):
  function translate2d_inv (line 105) | def translate2d_inv(tx, ty, **kwargs):
  function scale2d_inv (line 108) | def scale2d_inv(sx, sy, **kwargs):
  function rotate2d_inv (line 111) | def rotate2d_inv(theta, **kwargs):
  class AugmentPipe (line 122) | class AugmentPipe(torch.nn.Module):
    method __init__ (line 123) | def __init__(self,
    method forward (line 186) | def forward(self, images, debug_percentile=None):

FILE: stylegan_human/training/dataset.py
  class Dataset (line 26) | class Dataset(torch.utils.data.Dataset):
    method __init__ (line 27) | def __init__(self,
    method _get_raw_labels (line 53) | def _get_raw_labels(self):
    method close (line 66) | def close(self): # to be overridden by subclass
    method _load_raw_image (line 69) | def _load_raw_image(self, raw_idx): # to be overridden by subclass
    method _load_raw_labels (line 72) | def _load_raw_labels(self): # to be overridden by subclass
    method __getstate__ (line 75) | def __getstate__(self):
    method __del__ (line 78) | def __del__(self):
    method __len__ (line 84) | def __len__(self):
    method __getitem__ (line 87) | def __getitem__(self, idx):
    method get_label (line 97) | def get_label(self, idx):
    method get_details (line 105) | def get_details(self, idx):
    method name (line 113) | def name(self):
    method image_shape (line 117) | def image_shape(self):
    method num_channels (line 121) | def num_channels(self):
    method resolution (line 126) | def resolution(self):
    method label_shape (line 132) | def label_shape(self):
    method label_dim (line 142) | def label_dim(self):
    method has_labels (line 147) | def has_labels(self):
    method has_onehot_labels (line 151) | def has_onehot_labels(self):
  class ImageFolderDataset (line 156) | class ImageFolderDataset(Dataset):
    method __init__ (line 157) | def __init__(self,
    method _file_ext (line 186) | def _file_ext(fname):
    method _get_zipfile (line 189) | def _get_zipfile(self):
    method _open_file (line 195) | def _open_file(self, fname):
    method close (line 202) | def close(self):
    method __getstate__ (line 209) | def __getstate__(self):
    method _load_raw_image (line 212) | def _load_raw_image(self, raw_idx):
    method _load_raw_labels (line 224) | def _load_raw_labels(self):

FILE: stylegan_human/training/loss.py
  class Loss (line 19) | class Loss:
    method accumulate_gradients (line 20) | def accumulate_gradients(self, phase, real_img, real_c, gen_z, gen_c, ...
  class StyleGAN2Loss (line 25) | class StyleGAN2Loss(Loss):
    method __init__ (line 26) | def __init__(self, device, G, D, augment_pipe=None, r1_gamma=10, style...
    method run_G (line 42) | def run_G(self, z, c, update_emas=False):
    method run_D (line 52) | def run_D(self, img, c, blur_sigma=0, update_emas=False):
    method accumulate_gradients (line 63) | def accumulate_gradients(self, phase, real_img, real_c, gen_z, gen_c, ...

FILE: stylegan_human/training/networks_stylegan2.py
  function normalize_2nd_moment (line 27) | def normalize_2nd_moment(x, dim=1, eps=1e-8):
  function modulated_conv2d (line 33) | def modulated_conv2d(
  class FullyConnectedLayer (line 95) | class FullyConnectedLayer(torch.nn.Module):
    method __init__ (line 96) | def __init__(self,
    method forward (line 113) | def forward(self, x):
    method extra_repr (line 128) | def extra_repr(self):
  class Conv2dLayer (line 134) | class Conv2dLayer(torch.nn.Module):
    method __init__ (line 135) | def __init__(self,
    method forward (line 173) | def forward(self, x, gain=1):
    method extra_repr (line 184) | def extra_repr(self):
  class MappingNetwork (line 192) | class MappingNetwork(torch.nn.Module):
    method __init__ (line 193) | def __init__(self,
    method forward (line 232) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
    method extra_repr (line 269) | def extra_repr(self):
  class SynthesisLayer (line 275) | class SynthesisLayer(torch.nn.Module):
    method __init__ (line 276) | def __init__(self,
    method forward (line 310) | def forward(self, x, w, noise_mode='random', fused_modconv=True, gain=1):
    method extra_repr (line 331) | def extra_repr(self):
  class ToRGBLayer (line 339) | class ToRGBLayer(torch.nn.Module):
    method __init__ (line 340) | def __init__(self, in_channels, out_channels, w_dim, kernel_size=1, co...
    method forward (line 352) | def forward(self, x, w, fused_modconv=True):
    method extra_repr (line 358) | def extra_repr(self):
  class SynthesisBlock (line 364) | class SynthesisBlock(torch.nn.Module):
    method __init__ (line 365) | def __init__(self,
    method forward (line 416) | def forward(self, x, img, ws, force_fp32=False, fused_modconv=None, up...
    method extra_repr (line 462) | def extra_repr(self):
  class SynthesisNetwork (line 468) | class SynthesisNetwork(torch.nn.Module):
    method __init__ (line 469) | def __init__(self,
    method forward (line 502) | def forward(self, ws, return_feature=False, **block_kwargs):
    method extra_repr (line 524) | def extra_repr(self):
  class Generator (line 533) | class Generator(torch.nn.Module):
    method __init__ (line 534) | def __init__(self,
    method forward (line 556) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
  function imresize (line 569) | def imresize(image, size):
  class DiscriminatorBlock (line 585) | class DiscriminatorBlock(torch.nn.Module):
    method __init__ (line 586) | def __init__(self,
    method forward (line 636) | def forward(self, x, img, force_fp32=False):
    method extra_repr (line 668) | def extra_repr(self):
  class MinibatchStdLayer (line 674) | class MinibatchStdLayer(torch.nn.Module):
    method __init__ (line 675) | def __init__(self, group_size, num_channels=1):
    method forward (line 680) | def forward(self, x):
    method extra_repr (line 697) | def extra_repr(self):
  class DiscriminatorEpilogue (line 703) | class DiscriminatorEpilogue(torch.nn.Module):
    method __init__ (line 704) | def __init__(self,
    method forward (line 730) | def forward(self, x, img, cmap, force_fp32=False):
    method extra_repr (line 758) | def extra_repr(self):
  class Discriminator (line 764) | class Discriminator(torch.nn.Module):
    method __init__ (line 765) | def __init__(self,
    method forward (line 808) | def forward(self, img, c, update_emas=False, **block_kwargs):
    method extra_repr (line 821) | def extra_repr(self):

FILE: stylegan_human/training/networks_stylegan3.py
  function modulated_conv2d (line 26) | def modulated_conv2d(
  class FullyConnectedLayer (line 70) | class FullyConnectedLayer(torch.nn.Module):
    method __init__ (line 71) | def __init__(self,
    method forward (line 90) | def forward(self, x):
    method extra_repr (line 104) | def extra_repr(self):
  class MappingNetwork (line 110) | class MappingNetwork(torch.nn.Module):
    method __init__ (line 111) | def __init__(self,
    method forward (line 136) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
    method extra_repr (line 164) | def extra_repr(self):
  class SynthesisInput (line 170) | class SynthesisInput(torch.nn.Module):
    method __init__ (line 171) | def __init__(self,
    method forward (line 199) | def forward(self, w):
    method extra_repr (line 246) | def extra_repr(self):
  class SynthesisLayer (line 254) | class SynthesisLayer(torch.nn.Module):
    method __init__ (line 255) | def __init__(self,
    method forward (line 330) | def forward(self, x, w, noise_mode='random', force_fp32=False, update_...
    method design_lowpass_filter (line 365) | def design_lowpass_filter(numtaps, cutoff, width, fs, radial=False):
    method extra_repr (line 387) | def extra_repr(self):
  class SynthesisNetwork (line 400) | class SynthesisNetwork(torch.nn.Module):
    method __init__ (line 401) | def __init__(self,
    method forward (line 465) | def forward(self, ws, **layer_kwargs):
    method extra_repr (line 481) | def extra_repr(self):
  class Generator (line 491) | class Generator(torch.nn.Module):
    method __init__ (line 492) | def __init__(self,
    method forward (line 513) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
  function imresize (line 527) | def imresize(image, size):

FILE: stylegan_human/training/training_loop.py
  function setup_snapshot_image_grid (line 31) | def setup_snapshot_image_grid(training_set, random_seed=0):
  function save_image_grid (line 70) | def save_image_grid(img, fname, drange, grid_size):
  function training_loop (line 90) | def training_loop(

FILE: stylegan_human/training_scripts/sg2/train.py
  class UserError (line 30) | class UserError(Exception):
  function setup_training_loop_kwargs (line 35) | def setup_training_loop_kwargs(
  function subprocess_fn (line 378) | def subprocess_fn(rank, args, temp_dir):
  class CommaSeparatedList (line 403) | class CommaSeparatedList(click.ParamType):
    method convert (line 406) | def convert(self, value, param, ctx):
  function main (line 458) | def main(ctx, outdir, dry_run, **config_kwargs):

FILE: stylegan_human/training_scripts/sg2/training/dataset.py
  class Dataset (line 29) | class Dataset(torch.utils.data.Dataset):
    method __init__ (line 30) | def __init__(self,
    method _get_raw_labels (line 59) | def _get_raw_labels(self):
    method close (line 72) | def close(self): # to be overridden by subclass
    method _load_raw_image (line 75) | def _load_raw_image(self, raw_idx): # to be overridden by subclass
    method _load_raw_labels (line 78) | def _load_raw_labels(self): # to be overridden by subclass
    method __getstate__ (line 81) | def __getstate__(self):
    method __del__ (line 84) | def __del__(self):
    method __len__ (line 90) | def __len__(self):
    method __getitem__ (line 93) | def __getitem__(self, idx):
    method get_label (line 103) | def get_label(self, idx):
    method get_details (line 111) | def get_details(self, idx):
    method name (line 119) | def name(self):
    method image_shape (line 123) | def image_shape(self):
    method num_channels (line 127) | def num_channels(self):
    method resolution (line 132) | def resolution(self):
    method label_shape (line 141) | def label_shape(self):
    method label_dim (line 151) | def label_dim(self):
    method has_labels (line 156) | def has_labels(self):
    method has_onehot_labels (line 160) | def has_onehot_labels(self):
  class ImageFolderDataset (line 165) | class ImageFolderDataset(Dataset):
    method __init__ (line 166) | def __init__(self,
    method _file_ext (line 204) | def _file_ext(fname):
    method _get_zipfile (line 207) | def _get_zipfile(self):
    method _open_file (line 213) | def _open_file(self, fname):
    method close (line 220) | def close(self):
    method __getstate__ (line 227) | def __getstate__(self):
    method _load_raw_image (line 230) | def _load_raw_image(self, raw_idx): #load single image
    method _load_raw_labels (line 242) | def _load_raw_labels(self):

FILE: stylegan_human/training_scripts/sg2/training/networks.py
  function normalize_2nd_moment (line 23) | def normalize_2nd_moment(x, dim=1, eps=1e-8):
  function modulated_conv2d (line 29) | def modulated_conv2d(
  class FullyConnectedLayer (line 91) | class FullyConnectedLayer(torch.nn.Module):
    method __init__ (line 92) | def __init__(self,
    method forward (line 107) | def forward(self, x):
  class Conv2dLayer (line 125) | class Conv2dLayer(torch.nn.Module):
    method __init__ (line 126) | def __init__(self,
    method forward (line 162) | def forward(self, x, gain=1):
  class MappingNetwork (line 176) | class MappingNetwork(torch.nn.Module):
    method __init__ (line 177) | def __init__(self,
    method forward (line 216) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, skip...
  class SynthesisLayer (line 256) | class SynthesisLayer(torch.nn.Module):
    method __init__ (line 257) | def __init__(self,
    method forward (line 293) | def forward(self, x, w, noise_mode='random', fused_modconv=True, gain=1):
  class ToRGBLayer (line 323) | class ToRGBLayer(torch.nn.Module):
    method __init__ (line 324) | def __init__(self, in_channels, out_channels, w_dim, kernel_size=1, co...
    method forward (line 333) | def forward(self, x, w, fused_modconv=True):
  class SynthesisBlock (line 342) | class SynthesisBlock(torch.nn.Module):
    method __init__ (line 343) | def __init__(self,
    method forward (line 397) | def forward(self, x, img, ws, force_fp32=False, fused_modconv=None, **...
  class SynthesisNetwork (line 448) | class SynthesisNetwork(torch.nn.Module):
    method __init__ (line 449) | def __init__(self,
    method forward (line 483) | def forward(self, ws, return_feature=False, **block_kwargs):
  class Generator (line 508) | class Generator(torch.nn.Module):
    method __init__ (line 509) | def __init__(self,
    method forward (line 532) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, inpu...
  class DiscriminatorBlock (line 557) | class DiscriminatorBlock(torch.nn.Module):
    method __init__ (line 558) | def __init__(self,
    method forward (line 610) | def forward(self, x, img, force_fp32=False):
  class MinibatchStdLayer (line 649) | class MinibatchStdLayer(torch.nn.Module):
    method __init__ (line 650) | def __init__(self, group_size, num_channels=1):
    method forward (line 655) | def forward(self, x):
  class DiscriminatorEpilogue (line 675) | class DiscriminatorEpilogue(torch.nn.Module):
    method __init__ (line 676) | def __init__(self,
    method forward (line 709) | def forward(self, x, img, cmap, force_fp32=False):
  class Discriminator (line 746) | class Discriminator(torch.nn.Module):
    method __init__ (line 747) | def __init__(self,
    method forward (line 792) | def forward(self, img, c, **block_kwargs):

FILE: stylegan_human/training_scripts/sg3/train.py
  function subprocess_fn (line 29) | def subprocess_fn(rank, c, temp_dir):
  function launch_training (line 53) | def launch_training(c, desc, outdir, dry_run):
  function init_dataset_kwargs (line 104) | def init_dataset_kwargs(data, square=False):
  function parse_comma_separated_list (line 120) | def parse_comma_separated_list(s):
  function main (line 170) | def main(**kwargs):

FILE: stylegan_human/training_scripts/sg3/training/dataset.py
  class Dataset (line 31) | class Dataset(torch.utils.data.Dataset):
    method __init__ (line 32) | def __init__(self,
    method _get_raw_labels (line 62) | def _get_raw_labels(self):
    method close (line 75) | def close(self): # to be overridden by subclass
    method _load_raw_image (line 78) | def _load_raw_image(self, raw_idx): # to be overridden by subclass
    method _load_raw_labels (line 81) | def _load_raw_labels(self): # to be overridden by subclass
    method __getstate__ (line 84) | def __getstate__(self):
    method __del__ (line 87) | def __del__(self):
    method __len__ (line 93) | def __len__(self):
    method __getitem__ (line 96) | def __getitem__(self, idx):
    method get_label (line 106) | def get_label(self, idx):
    method get_details (line 114) | def get_details(self, idx):
    method name (line 122) | def name(self):
    method image_shape (line 126) | def image_shape(self):
    method num_channels (line 130) | def num_channels(self):
    method resolution (line 135) | def resolution(self):
    method label_shape (line 144) | def label_shape(self):
    method label_dim (line 154) | def label_dim(self):
    method has_labels (line 159) | def has_labels(self):
    method has_onehot_labels (line 163) | def has_onehot_labels(self):
  class ImageFolderDataset (line 168) | class ImageFolderDataset(Dataset):
    method __init__ (line 169) | def __init__(self,
    method _file_ext (line 208) | def _file_ext(fname):
    method _get_zipfile (line 211) | def _get_zipfile(self):
    method _open_file (line 217) | def _open_file(self, fname):
    method close (line 224) | def close(self):
    method __getstate__ (line 231) | def __getstate__(self):
    method _load_raw_image (line 234) | def _load_raw_image(self, raw_idx):
    method _load_raw_labels (line 246) | def _load_raw_labels(self):

FILE: stylegan_human/training_scripts/sg3/training/networks_stylegan2.py
  function normalize_2nd_moment (line 28) | def normalize_2nd_moment(x, dim=1, eps=1e-8):
  function modulated_conv2d (line 34) | def modulated_conv2d(
  class FullyConnectedLayer (line 96) | class FullyConnectedLayer(torch.nn.Module):
    method __init__ (line 97) | def __init__(self,
    method forward (line 114) | def forward(self, x):
    method extra_repr (line 129) | def extra_repr(self):
  class Conv2dLayer (line 135) | class Conv2dLayer(torch.nn.Module):
    method __init__ (line 136) | def __init__(self,
    method forward (line 174) | def forward(self, x, gain=1):
    method extra_repr (line 185) | def extra_repr(self):
  class MappingNetwork (line 193) | class MappingNetwork(torch.nn.Module):
    method __init__ (line 194) | def __init__(self,
    method forward (line 233) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
    method extra_repr (line 270) | def extra_repr(self):
  class SynthesisLayer (line 276) | class SynthesisLayer(torch.nn.Module):
    method __init__ (line 277) | def __init__(self,
    method forward (line 316) | def forward(self, x, w, noise_mode='random', fused_modconv=True, gain=1):
    method extra_repr (line 343) | def extra_repr(self):
  class ToRGBLayer (line 351) | class ToRGBLayer(torch.nn.Module):
    method __init__ (line 352) | def __init__(self, in_channels, out_channels, w_dim, kernel_size=1, co...
    method forward (line 364) | def forward(self, x, w, fused_modconv=True):
    method extra_repr (line 370) | def extra_repr(self):
  class SynthesisBlock (line 376) | class SynthesisBlock(torch.nn.Module):
    method __init__ (line 377) | def __init__(self,
    method forward (line 433) | def forward(self, x, img, ws, force_fp32=False, fused_modconv=None, up...
    method extra_repr (line 485) | def extra_repr(self):
  class SynthesisNetwork (line 491) | class SynthesisNetwork(torch.nn.Module):
    method __init__ (line 492) | def __init__(self,
    method forward (line 527) | def forward(self, ws, **block_kwargs):
    method extra_repr (line 544) | def extra_repr(self):
  class Generator (line 553) | class Generator(torch.nn.Module):
    method __init__ (line 554) | def __init__(self,
    method forward (line 575) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
  class DiscriminatorBlock (line 583) | class DiscriminatorBlock(torch.nn.Module):
    method __init__ (line 584) | def __init__(self,
    method forward (line 636) | def forward(self, x, img, force_fp32=False):
    method extra_repr (line 674) | def extra_repr(self):
  class MinibatchStdLayer (line 680) | class MinibatchStdLayer(torch.nn.Module):
    method __init__ (line 681) | def __init__(self, group_size, num_channels=1):
    method forward (line 686) | def forward(self, x):
    method extra_repr (line 703) | def extra_repr(self):
  class DiscriminatorEpilogue (line 709) | class DiscriminatorEpilogue(torch.nn.Module):
    method __init__ (line 710) | def __init__(self,
    method forward (line 743) | def forward(self, x, img, cmap, force_fp32=False):
    method extra_repr (line 779) | def extra_repr(self):
  class Discriminator (line 785) | class Discriminator(torch.nn.Module):
    method __init__ (line 786) | def __init__(self,
    method forward (line 831) | def forward(self, img, c, update_emas=False, **block_kwargs):
    method extra_repr (line 844) | def extra_repr(self):

FILE: stylegan_human/training_scripts/sg3/training/networks_stylegan3.py
  function modulated_conv2d (line 27) | def modulated_conv2d(
  class FullyConnectedLayer (line 71) | class FullyConnectedLayer(torch.nn.Module):
    method __init__ (line 72) | def __init__(self,
    method forward (line 91) | def forward(self, x):
    method extra_repr (line 105) | def extra_repr(self):
  class MappingNetwork (line 111) | class MappingNetwork(torch.nn.Module):
    method __init__ (line 112) | def __init__(self,
    method forward (line 137) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
    method extra_repr (line 165) | def extra_repr(self):
  class SynthesisInput (line 171) | class SynthesisInput(torch.nn.Module):
    method __init__ (line 172) | def __init__(self,
    method forward (line 205) | def forward(self, w):
    method extra_repr (line 252) | def extra_repr(self):
  class SynthesisLayer (line 260) | class SynthesisLayer(torch.nn.Module):
    method __init__ (line 261) | def __init__(self,
    method forward (line 344) | def forward(self, x, w, noise_mode='random', force_fp32=False, update_...
    method design_lowpass_filter (line 379) | def design_lowpass_filter(numtaps, cutoff, width, fs, radial=False):
    method extra_repr (line 401) | def extra_repr(self):
  class SynthesisNetwork (line 414) | class SynthesisNetwork(torch.nn.Module):
    method __init__ (line 415) | def __init__(self,
    method forward (line 483) | def forward(self, ws, **layer_kwargs):
    method extra_repr (line 502) | def extra_repr(self):
  class Generator (line 512) | class Generator(torch.nn.Module):
    method __init__ (line 513) | def __init__(self,
    method forward (line 534) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...

FILE: stylegan_human/utils/ImagesDataset.py
  class ImagesDataset (line 11) | class ImagesDataset(Dataset):
    method __init__ (line 13) | def __init__(self, source_root, source_transform=None):
    method __len__ (line 17) | def __len__(self):
    method __getitem__ (line 20) | def __getitem__(self, index):

FILE: stylegan_human/utils/data_utils.py
  function is_image_file (line 14) | def is_image_file(filename):
  function tensor2im (line 18) | def tensor2im(var):
  function make_dataset (line 28) | def make_dataset(dir):

FILE: stylegan_human/utils/face_alignment.py
  function get_landmark (line 12) | def get_landmark(img, detector, predictor):
  function align_face_for_insetgan (line 34) | def align_face_for_insetgan(img, detector, predictor, output_size=256):
  function align_face_for_projector (line 137) | def align_face_for_projector(img, detector, predictor, output_size):
  function reverse_quad_transform (line 227) | def reverse_quad_transform(image, quad_to_map_to, alpha):

FILE: stylegan_human/utils/log_utils.py
  function log_image_from_w (line 12) | def log_image_from_w(w, G, name):
  function log_images_from_w (line 21) | def log_images_from_w(ws, G, names):
  function plot_image_from_w (line 27) | def plot_image_from_w(w, G):
  function plot_image (line 34) | def plot_image(img):
  function save_image (line 41) | def save_image(name, method_type, results_dir, image, run_id):
  function save_w (line 45) | def save_w(w, G, name, method_type, results_dir):
  function save_concat_image (line 51) | def save_concat_image(base_dir, image_latents, new_inv_image_latent, new_G,
  function save_single_image (line 65) | def save_single_image(base_dir, image_latent, G, file_name):
  function create_alongside_images (line 71) | def create_alongside_images(images):
  function get_image_from_w (line 76) | def get_image_from_w(w, G):

FILE: stylegan_human/utils/models_utils.py
  function toogle_grad (line 10) | def toogle_grad(model, flag=True):
  function load_tuned_G (line 15) | def load_tuned_G(run_id, type):
  function load_old_G (line 24) | def load_old_G():

FILE: stylegan_human/utils/util.py
  function visual (line 10) | def visual(output, out_path):
  function get_lr (line 21) | def get_lr(t, initial_lr, rampdown=0.25, rampup=0.05):
  function latent_noise (line 30) | def latent_noise(latent, strength):
  function noise_regularize_ (line 35) | def noise_regularize_(noises):
  function noise_normalize_ (line 58) | def noise_normalize_(noises):
  function tensor_to_numpy (line 66) | def tensor_to_numpy(x):
  function numpy_to_tensor (line 73) | def numpy_to_tensor(x):
  function tensor_to_pil (line 79) | def tensor_to_pil(x):

FILE: torch_utils/custom_ops.py
  function _find_compiler_bindir (line 29) | def _find_compiler_bindir():
  function _get_mangled_gpu_name (line 44) | def _get_mangled_gpu_name():
  function get_plugin (line 59) | def get_plugin(module_name, sources, headers=None, source_dir=None, **bu...

FILE: torch_utils/misc.py
  function constant (line 22) | def constant(value, shape=None, dtype=None, device=None, memory_format=N...
  function nan_to_num (line 49) | def nan_to_num(input, nan=0.0, posinf=None, neginf=None, *, out=None): #...
  function suppress_tracer_warnings (line 71) | def suppress_tracer_warnings():
  function assert_shape (line 82) | def assert_shape(tensor, ref_shape):
  function profiled_function (line 100) | def profiled_function(fn):
  class InfiniteSampler (line 111) | class InfiniteSampler(torch.utils.data.Sampler):
    method __init__ (line 112) | def __init__(self, dataset, rank=0, num_replicas=1, shuffle=True, seed...
    method __iter__ (line 125) | def __iter__(self):
  function params_and_buffers (line 147) | def params_and_buffers(module):
  function named_params_and_buffers (line 151) | def named_params_and_buffers(module):
  function copy_params_and_buffers (line 155) | def copy_params_and_buffers(src_module, dst_module, require_all=False):
  function ddp_sync (line 169) | def ddp_sync(module, sync):
  function check_ddp_consistency (line 180) | def check_ddp_consistency(module, ignore_regex=None):
  function print_module_summary (line 196) | def print_module_summary(module, inputs, max_nesting=3, skip_redundant=T...

FILE: torch_utils/ops/bias_act.cpp
  function has_same_layout (line 16) | static bool has_same_layout(torch::Tensor x, torch::Tensor y)
  function bias_act (line 32) | static torch::Tensor bias_act(torch::Tensor x, torch::Tensor b, torch::T...
  function PYBIND11_MODULE (line 94) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)

FILE: torch_utils/ops/bias_act.h
  type bias_act_kernel_params (line 12) | struct bias_act_kernel_params

FILE: torch_utils/ops/bias_act.py
  function _init (line 38) | def _init():
  function bias_act (line 52) | def bias_act(x, b=None, dim=1, act='linear', alpha=None, gain=None, clam...
  function _bias_act_ref (line 91) | def _bias_act_ref(x, b=None, dim=1, act='linear', alpha=None, gain=None,...
  function _bias_act_cuda (line 126) | def _bias_act_cuda(dim=1, act='linear', alpha=None, gain=None, clamp=None):

FILE: torch_utils/ops/conv2d_gradfix.py
  function no_weight_gradients (line 25) | def no_weight_gradients(disable=True):
  function conv2d (line 35) | def conv2d(input, weight, bias=None, stride=1, padding=0, dilation=1, gr...
  function conv_transpose2d (line 40) | def conv_transpose2d(input, weight, bias=None, stride=1, padding=0, outp...
  function _should_use_custom_op (line 47) | def _should_use_custom_op(input):
  function _tuple_of_ints (line 55) | def _tuple_of_ints(xs, ndim):
  function _conv2d_gradfix (line 66) | def _conv2d_gradfix(transpose, weight_shape, stride, padding, output_pad...

FILE: torch_utils/ops/conv2d_resample.py
  function _get_weight_shape (line 21) | def _get_weight_shape(w):
  function _conv2d_wrapper (line 29) | def _conv2d_wrapper(x, w, stride=1, padding=0, groups=1, transpose=False...
  function conv2d_resample (line 46) | def conv2d_resample(x, w, f=None, up=1, down=1, padding=0, groups=1, fli...

FILE: torch_utils/ops/filtered_lrelu.cpp
  function filtered_lrelu (line 16) | static std::tuple<torch::Tensor, torch::Tensor, int> filtered_lrelu(
  function filtered_lrelu_act (line 213) | static torch::Tensor filtered_lrelu_act(torch::Tensor x, torch::Tensor s...
  function PYBIND11_MODULE (line 294) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)

FILE: torch_utils/ops/filtered_lrelu.h
  type filtered_lrelu_kernel_params (line 14) | struct filtered_lrelu_kernel_params
  type filtered_lrelu_act_kernel_params (line 55) | struct filtered_lrelu_act_kernel_params
  type filtered_lrelu_kernel_spec (line 73) | struct filtered_lrelu_kernel_spec

FILE: torch_utils/ops/filtered_lrelu.py
  function _init (line 23) | def _init():
  function _get_filter_size (line 35) | def _get_filter_size(f):
  function _parse_padding (line 42) | def _parse_padding(padding):
  function filtered_lrelu (line 56) | def filtered_lrelu(x, fu=None, fd=None, b=None, up=1, down=1, padding=0,...
  function _filtered_lrelu_ref (line 121) | def _filtered_lrelu_ref(x, fu=None, fd=None, b=None, up=1, down=1, paddi...
  function _filtered_lrelu_cuda (line 159) | def _filtered_lrelu_cuda(up=1, down=1, padding=0, gain=np.sqrt(2), slope...

FILE: torch_utils/ops/fma.py
  function fma (line 15) | def fma(a, b, c): # => a * b + c
  class _FusedMultiplyAdd (line 20) | class _FusedMultiplyAdd(torch.autograd.Function): # a * b + c
    method forward (line 22) | def forward(ctx, a, b, c): # pylint: disable=arguments-differ
    method backward (line 29) | def backward(ctx, dout): # pylint: disable=arguments-differ
  function _unbroadcast (line 49) | def _unbroadcast(x, shape):

FILE: torch_utils/ops/grid_sample_gradfix.py
  function grid_sample (line 26) | def grid_sample(input, grid):
  function _should_use_custom_op (line 33) | def _should_use_custom_op():
  class _GridSample2dForward (line 38) | class _GridSample2dForward(torch.autograd.Function):
    method forward (line 40) | def forward(ctx, input, grid):
    method backward (line 48) | def backward(ctx, grad_output):
  class _GridSample2dBackward (line 55) | class _GridSample2dBackward(torch.autograd.Function):
    method forward (line 57) | def forward(ctx, grad_output, input, grid):
    method backward (line 64) | def backward(ctx, grad2_grad_input, grad2_grad_grid):

FILE: torch_utils/ops/upfirdn2d.cpp
  function upfirdn2d (line 16) | static torch::Tensor upfirdn2d(torch::Tensor x, torch::Tensor f, int upx...
  function PYBIND11_MODULE (line 102) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)

FILE: torch_utils/ops/upfirdn2d.h
  type upfirdn2d_kernel_params (line 14) | struct upfirdn2d_kernel_params
  type upfirdn2d_kernel_spec (line 45) | struct upfirdn2d_kernel_spec

FILE: torch_utils/ops/upfirdn2d.py
  function _init (line 23) | def _init():
  function _parse_scaling (line 35) | def _parse_scaling(scaling):
  function _parse_padding (line 44) | def _parse_padding(padding):
  function _get_filter_size (line 55) | def _get_filter_size(f):
  function setup_filter (line 70) | def setup_filter(f, device=torch.device('cpu'), normalize=True, flip_fil...
  function upfirdn2d (line 118) | def upfirdn2d(x, f, up=1, down=1, padding=0, flip_filter=False, gain=1, ...
  function _upfirdn2d_ref (line 167) | def _upfirdn2d_ref(x, f, up=1, down=1, padding=0, flip_filter=False, gai...
  function _upfirdn2d_cuda (line 217) | def _upfirdn2d_cuda(up=1, down=1, padding=0, flip_filter=False, gain=1):
  function filter2d (line 277) | def filter2d(x, f, padding=0, flip_filter=False, gain=1, impl='cuda'):
  function upsample2d (line 313) | def upsample2d(x, f, up=2, padding=0, flip_filter=False, gain=1, impl='c...
  function downsample2d (line 352) | def downsample2d(x, f, down=2, padding=0, flip_filter=False, gain=1, imp...

FILE: torch_utils/persistence.py
  function persistent_class (line 35) | def persistent_class(orig_class):
  function is_persistent (line 134) | def is_persistent(obj):
  function import_hook (line 147) | def import_hook(hook):
  function _reconstruct_persistent_obj (line 179) | def _reconstruct_persistent_obj(meta):
  function _module_to_src (line 206) | def _module_to_src(module):
  function _src_to_module (line 216) | def _src_to_module(src):
  function _check_pickleable (line 231) | def _check_pickleable(obj):

FILE: torch_utils/training_stats.py
  function init_multiprocessing (line 34) | def init_multiprocessing(rank, sync_device):
  function report (line 56) | def report(name, value):
  function report0 (line 103) | def report0(name, value):
  class Collector (line 113) | class Collector:
    method __init__ (line 133) | def __init__(self, regex='.*', keep_previous=True):
    method names (line 141) | def names(self):
    method update (line 147) | def update(self):
    method _get_delta (line 170) | def _get_delta(self, name):
    method num (line 180) | def num(self, name):
    method mean (line 188) | def mean(self, name):
    method std (line 198) | def std(self, name):
    method as_dict (line 212) | def as_dict(self):
    method __getitem__ (line 226) | def __getitem__(self, name):
  function _sync (line 234) | def _sync(names):

FILE: training/augment.py
  function matrix (line 48) | def matrix(*rows, device=None):
  function translate2d (line 58) | def translate2d(tx, ty, **kwargs):
  function translate3d (line 65) | def translate3d(tx, ty, tz, **kwargs):
  function scale2d (line 73) | def scale2d(sx, sy, **kwargs):
  function scale3d (line 80) | def scale3d(sx, sy, sz, **kwargs):
  function rotate2d (line 88) | def rotate2d(theta, **kwargs):
  function rotate3d (line 95) | def rotate3d(v, theta, **kwargs):
  function translate2d_inv (line 105) | def translate2d_inv(tx, ty, **kwargs):
  function scale2d_inv (line 108) | def scale2d_inv(sx, sy, **kwargs):
  function rotate2d_inv (line 111) | def rotate2d_inv(theta, **kwargs):
  class AugmentPipe (line 122) | class AugmentPipe(torch.nn.Module):
    method __init__ (line 123) | def __init__(self,
    method forward (line 186) | def forward(self, images, debug_percentile=None):

FILE: training/dataset.py
  class Dataset (line 26) | class Dataset(torch.utils.data.Dataset):
    method __init__ (line 27) | def __init__(self,
    method _get_raw_labels (line 53) | def _get_raw_labels(self):
    method close (line 66) | def close(self): # to be overridden by subclass
    method _load_raw_image (line 69) | def _load_raw_image(self, raw_idx): # to be overridden by subclass
    method _load_raw_labels (line 72) | def _load_raw_labels(self): # to be overridden by subclass
    method __getstate__ (line 75) | def __getstate__(self):
    method __del__ (line 78) | def __del__(self):
    method __len__ (line 84) | def __len__(self):
    method __getitem__ (line 87) | def __getitem__(self, idx):
    method get_label (line 97) | def get_label(self, idx):
    method get_details (line 105) | def get_details(self, idx):
    method name (line 113) | def name(self):
    method image_shape (line 117) | def image_shape(self):
    method num_channels (line 121) | def num_channels(self):
    method resolution (line 126) | def resolution(self):
    method label_shape (line 132) | def label_shape(self):
    method label_dim (line 142) | def label_dim(self):
    method has_labels (line 147) | def has_labels(self):
    method has_onehot_labels (line 151) | def has_onehot_labels(self):
  class ImageFolderDataset (line 156) | class ImageFolderDataset(Dataset):
    method __init__ (line 157) | def __init__(self,
    method _file_ext (line 186) | def _file_ext(fname):
    method _get_zipfile (line 189) | def _get_zipfile(self):
    method _open_file (line 195) | def _open_file(self, fname):
    method close (line 202) | def close(self):
    method __getstate__ (line 209) | def __getstate__(self):
    method _load_raw_image (line 212) | def _load_raw_image(self, raw_idx):
    method _load_raw_labels (line 224) | def _load_raw_labels(self):

FILE: training/loss.py
  class Loss (line 19) | class Loss:
    method accumulate_gradients (line 20) | def accumulate_gradients(self, phase, real_img, real_c, gen_z, gen_c, ...
  class StyleGAN2Loss (line 25) | class StyleGAN2Loss(Loss):
    method __init__ (line 26) | def __init__(self, device, G, D, augment_pipe=None, r1_gamma=10, style...
    method run_G (line 42) | def run_G(self, z, c, update_emas=False):
    method run_D (line 52) | def run_D(self, img, c, blur_sigma=0, update_emas=False):
    method accumulate_gradients (line 63) | def accumulate_gradients(self, phase, real_img, real_c, gen_z, gen_c, ...

FILE: training/networks_stylegan2.py
  function normalize_2nd_moment (line 27) | def normalize_2nd_moment(x, dim=1, eps=1e-8):
  function modulated_conv2d (line 33) | def modulated_conv2d(
  class FullyConnectedLayer (line 95) | class FullyConnectedLayer(torch.nn.Module):
    method __init__ (line 96) | def __init__(self,
    method forward (line 113) | def forward(self, x):
    method extra_repr (line 128) | def extra_repr(self):
  class Conv2dLayer (line 134) | class Conv2dLayer(torch.nn.Module):
    method __init__ (line 135) | def __init__(self,
    method forward (line 173) | def forward(self, x, gain=1):
    method extra_repr (line 184) | def extra_repr(self):
  class MappingNetwork (line 192) | class MappingNetwork(torch.nn.Module):
    method __init__ (line 193) | def __init__(self,
    method forward (line 232) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
    method extra_repr (line 269) | def extra_repr(self):
  class SynthesisLayer (line 275) | class SynthesisLayer(torch.nn.Module):
    method __init__ (line 276) | def __init__(self,
    method forward (line 310) | def forward(self, x, w, noise_mode='random', fused_modconv=True, gain=1):
    method extra_repr (line 331) | def extra_repr(self):
  class ToRGBLayer (line 339) | class ToRGBLayer(torch.nn.Module):
    method __init__ (line 340) | def __init__(self, in_channels, out_channels, w_dim, kernel_size=1, co...
    method forward (line 352) | def forward(self, x, w, fused_modconv=True):
    method extra_repr (line 358) | def extra_repr(self):
  class SynthesisBlock (line 364) | class SynthesisBlock(torch.nn.Module):
    method __init__ (line 365) | def __init__(self,
    method forward (line 416) | def forward(self, x, img, ws, force_fp32=False, fused_modconv=None, up...
    method extra_repr (line 462) | def extra_repr(self):
  class SynthesisNetwork (line 468) | class SynthesisNetwork(torch.nn.Module):
    method __init__ (line 469) | def __init__(self,
    method forward (line 502) | def forward(self, ws, return_feature=False, **block_kwargs):
    method extra_repr (line 524) | def extra_repr(self):
  class Generator (line 533) | class Generator(torch.nn.Module):
    method __init__ (line 534) | def __init__(self,
    method forward (line 558) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
  function imresize (line 576) | def imresize(image, size):
  class DiscriminatorBlock (line 592) | class DiscriminatorBlock(torch.nn.Module):
    method __init__ (line 593) | def __init__(self,
    method forward (line 643) | def forward(self, x, img, force_fp32=False):
    method extra_repr (line 675) | def extra_repr(self):
  class MinibatchStdLayer (line 681) | class MinibatchStdLayer(torch.nn.Module):
    method __init__ (line 682) | def __init__(self, group_size, num_channels=1):
    method forward (line 687) | def forward(self, x):
    method extra_repr (line 704) | def extra_repr(self):
  class DiscriminatorEpilogue (line 710) | class DiscriminatorEpilogue(torch.nn.Module):
    method __init__ (line 711) | def __init__(self,
    method forward (line 737) | def forward(self, x, img, cmap, force_fp32=False):
    method extra_repr (line 765) | def extra_repr(self):
  class Discriminator (line 771) | class Discriminator(torch.nn.Module):
    method __init__ (line 772) | def __init__(self,
    method forward (line 815) | def forward(self, img, c, update_emas=False, **block_kwargs):
    method extra_repr (line 828) | def extra_repr(self):

FILE: training/networks_stylegan3.py
  function modulated_conv2d (line 26) | def modulated_conv2d(
  class FullyConnectedLayer (line 70) | class FullyConnectedLayer(torch.nn.Module):
    method __init__ (line 71) | def __init__(self,
    method forward (line 90) | def forward(self, x):
    method extra_repr (line 104) | def extra_repr(self):
  class MappingNetwork (line 110) | class MappingNetwork(torch.nn.Module):
    method __init__ (line 111) | def __init__(self,
    method forward (line 136) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
    method extra_repr (line 164) | def extra_repr(self):
  class SynthesisInput (line 170) | class SynthesisInput(torch.nn.Module):
    method __init__ (line 171) | def __init__(self,
    method forward (line 199) | def forward(self, w):
    method extra_repr (line 246) | def extra_repr(self):
  class SynthesisLayer (line 254) | class SynthesisLayer(torch.nn.Module):
    method __init__ (line 255) | def __init__(self,
    method forward (line 330) | def forward(self, x, w, noise_mode='random', force_fp32=False, update_...
    method design_lowpass_filter (line 365) | def design_lowpass_filter(numtaps, cutoff, width, fs, radial=False):
    method extra_repr (line 387) | def extra_repr(self):
  class SynthesisNetwork (line 400) | class SynthesisNetwork(torch.nn.Module):
    method __init__ (line 401) | def __init__(self,
    method forward (line 465) | def forward(self, ws, return_feature=False, **layer_kwargs):
    method extra_repr (line 486) | def extra_repr(self):
  class Generator (line 496) | class Generator(torch.nn.Module):
    method __init__ (line 497) | def __init__(self,
    method forward (line 518) | def forward(self, z, c, truncation_psi=1, truncation_cutoff=None, upda...
  function imresize (line 537) | def imresize(image, size):

FILE: training/training_loop.py
  function setup_snapshot_image_grid (line 31) | def setup_snapshot_image_grid(training_set, random_seed=0):
  function save_image_grid (line 70) | def save_image_grid(img, fname, drange, grid_size):
  function training_loop (line 90) | def training_loop(

FILE: visualizer_drag.py
  class Visualizer (line 29) | class Visualizer(imgui_window.ImguiWindow):
    method __init__ (line 30) | def __init__(self, capture_dir=None):
    method close (line 66) | def close(self):
    method add_recent_pickle (line 72) | def add_recent_pickle(self, pkl, ignore_errors=False):
    method load_pickle (line 75) | def load_pickle(self, pkl, ignore_errors=False):
    method print_error (line 78) | def print_error(self, error):
    method defer_rendering (line 84) | def defer_rendering(self, num_frames=1):
    method clear_result (line 87) | def clear_result(self):
    method set_async (line 90) | def set_async(self, is_async):
    method _adjust_font_size (line 98) | def _adjust_font_size(self):
    method check_update_mask (line 104) | def check_update_mask(self, **args):
    method capture_image_frame (line 116) | def capture_image_frame(self):
    method get_drag_info (line 125) | def get_drag_info(self):
    method draw_frame (line 133) | def draw_frame(self):
  class AsyncRenderer (line 253) | class AsyncRenderer:
    method __init__ (line 254) | def __init__(self):
    method close (line 265) | def close(self):
    method is_async (line 275) | def is_async(self):
    method set_async (line 278) | def set_async(self, is_async):
    method set_args (line 281) | def set_args(self, **args):
    method _set_args_async (line 298) | def _set_args_async(self, **args):
    method _set_args_sync (line 310) | def _set_args_sync(self, **args):
    method get_result (line 315) | def get_result(self):
    method clear_result (line 324) | def clear_result(self):
    method _process_fn (line 331) | def _process_fn(args_queue, result_queue):
  function main (line 353) | def main(

FILE: visualizer_drag_gradio.py
  function reverse_point_pairs (line 32) | def reverse_point_pairs(points):
  function clear_state (line 39) | def clear_state(global_state, target=None):
  function init_images (line 61) | def init_images(global_state):
  function update_image_draw (line 102) | def update_image_draw(image, points, mask, show_mask, global_state=None):
  function preprocess_mask_info (line 115) | def preprocess_mask_info(global_state, image):
  function on_change_pretrained_dropdown (line 350) | def on_change_pretrained_dropdown(pretrained_value, global_state):
  function on_click_reset_image (line 368) | def on_click_reset_image(global_state):
  function on_change_update_image_seed (line 386) | def on_change_update_image_seed(seed, global_state):
  function on_click_latent_space (line 404) | def on_click_latent_space(latent_space, global_state):
  function on_change_lr (line 428) | def on_change_lr(lr, global_state):
  function on_click_start (line 446) | def on_click_start(global_state, image):
  function on_click_stop (line 672) | def on_click_stop(global_state):
  function on_click_remove_point (line 695) | def on_click_remove_point(global_state):
  function on_click_reset_mask (line 710) | def on_click_reset_mask(global_state):
  function on_click_enable_draw (line 731) | def on_click_enable_draw(global_state, image):
  function on_click_remove_draw (line 746) | def on_click_remove_draw(global_state, image):
  function on_click_add_point (line 768) | def on_click_add_point(global_state, image: dict):
  function on_click_image (line 789) | def on_click_image(global_state, evt: gr.SelectData):
  function on_click_clear_points (line 829) | def on_click_clear_points(global_state):
  function on_click_show_mask (line 849) | def on_click_show_mask(global_state, show_mask):

FILE: viz/capture_widget.py
  class CaptureWidget (line 21) | class CaptureWidget:
    method __init__ (line 22) | def __init__(self, viz):
    method dump_png (line 30) | def dump_png(self, image):
    method __call__ (line 53) | def __call__(self, show=True):

FILE: viz/drag_widget.py
  class DragWidget (line 10) | class DragWidget:
    method __init__ (line 11) | def __init__(self, viz):
    method action (line 32) | def action(self, click, down, x, y):
    method add_point (line 38) | def add_point(self, click, x, y):
    method init_mask (line 52) | def init_mask(self, w, h):
    method draw_mask (line 56) | def draw_mask(self, x, y):
    method stop_drag (line 66) | def stop_drag(self):
    method set_points (line 70) | def set_points(self, points):
    method reset_point (line 73) | def reset_point(self):
    method load_points (line 78) | def load_points(self, suffix):
    method __call__ (line 91) | def __call__(self, show=True):

FILE: viz/latent_widget.py
  class LatentWidget (line 18) | class LatentWidget:
    method __init__ (line 19) | def __init__(self, viz):
    method __call__ (line 31) | def __call__(self, show=True):

FILE: viz/pickle_widget.py
  function _locate_results (line 22) | def _locate_results(pattern):
  class PickleWidget (line 27) | class PickleWidget:
    method __init__ (line 28) | def __init__(self, viz):
    method add_recent (line 38) | def add_recent(self, pkl, ignore_errors=False):
    method load (line 47) | def load(self, pkl, ignore_errors=False):
    method __call__ (line 72) | def __call__(self, show=True):
    method list_runs_and_pkls (line 136) | def list_runs_and_pkls(self, parents):
    method resolve_pkl (line 151) | def resolve_pkl(self, pattern):

FILE: viz/renderer.py
  class CapturedException (line 27) | class CapturedException(Exception):
    method __init__ (line 28) | def __init__(self, msg=None):
  class CaptureSuccess (line 41) | class CaptureSuccess(Exception):
    method __init__ (line 42) | def __init__(self, out):
  function add_watermark_np (line 48) | def add_watermark_np(input_image_array, watermark_text="AI Generated"):
  class Renderer (line 70) | class Renderer:
    method __init__ (line 71) | def __init__(self, disable_timing=False):
    method render (line 85) | def render(self, **args):
    method get_network (line 133) | def get_network(self, pkl, key, **tweak_kwargs):
    method _get_pinned_buf (line 179) | def _get_pinned_buf(self, ref):
    method to_device (line 187) | def to_device(self, buf):
    method to_cpu (line 190) | def to_cpu(self, buf):
    method _ignore_timing (line 193) | def _ignore_timing(self):
    method _apply_cmap (line 196) | def _apply_cmap(self, x, name='viridis'):
    method init_network (line 208) | def init_network(self, res,
    method update_lr (line 265) | def update_lr(self, lr):
    method _render_drag_impl (line 272) | def _render_drag_impl(self, res,