SYMBOL INDEX (1259 symbols across 117 files)

FILE: src/tha4/app/character_model_ifacialmocap_puppeteer.py
  class FpsStatistics (line 28) | class FpsStatistics:
    method __init__ (line 29) | def __init__(self):
    method add_fps (line 33) | def add_fps(self, fps):
    method get_average_fps (line 38) | def get_average_fps(self):
  class MainFrame (line 45) | class MainFrame(wx.Frame):
    method __init__ (line 48) | def __init__(self, pose_converter: IFacialMocapPoseConverter, device: ...
    method create_receiving_socket (line 71) | def create_receiving_socket(self):
    method create_timers (line 76) | def create_timers(self):
    method on_close (line 82) | def on_close(self, event: wx.Event):
    method on_start_capture (line 94) | def on_start_capture(self, event: wx.Event):
    method read_ifacialmocap_pose (line 109) | def read_ifacialmocap_pose(self):
    method on_erase_background (line 123) | def on_erase_background(self, event: wx.Event):
    method create_animation_panel (line 126) | def create_animation_panel(self, parent):
    method create_ui (line 198) | def create_ui(self):
    method create_connection_panel (line 216) | def create_connection_panel(self, parent):
    method create_capture_panel (line 232) | def create_capture_panel(self, parent):
    method create_rotation_column (line 249) | def create_rotation_column(self, parent, rotation_names):
    method paint_capture_panel (line 272) | def paint_capture_panel(self, event: wx.Event):
    method update_capture_panel (line 275) | def update_capture_panel(self, event: wx.Event):
    method convert_to_100 (line 282) | def convert_to_100(x):
    method paint_source_image_panel (line 285) | def paint_source_image_panel(self, event: wx.Event):
    method update_source_image_bitmap (line 288) | def update_source_image_bitmap(self):
    method draw_nothing_yet_string (line 298) | def draw_nothing_yet_string(self, dc):
    method paint_result_image_panel (line 305) | def paint_result_image_panel(self, event: wx.Event):
    method update_result_image_bitmap (line 308) | def update_result_image_bitmap(self, event: Optional[wx.Event] = None):
    method blend_with_background (line 377) | def blend_with_background(self, numpy_image, background):
    method load_model (line 383) | def load_model(self, event: wx.Event):

FILE: src/tha4/app/character_model_manual_poser.py
  class MorphCategoryControlPanel (line 20) | class MorphCategoryControlPanel(wx.Panel):
    method __init__ (line 21) | def __init__(self,
    method update_ui (line 56) | def update_ui(self):
    method on_choice_updated (line 71) | def on_choice_updated(self, event: wx.Event):
    method set_param_value (line 77) | def set_param_value(self, pose: List[float]):
  class SimpleParamGroupsControlPanel (line 96) | class SimpleParamGroupsControlPanel(wx.Panel):
    method __init__ (line 97) | def __init__(self, parent,
    method set_param_value (line 125) | def set_param_value(self, pose: List[float]):
  class MainFrame (line 137) | class MainFrame(wx.Frame):
    method __init__ (line 142) | def __init__(self, device: torch.device):
    method init_left_panel (line 178) | def init_left_panel(self):
    method on_erase_background (line 198) | def on_erase_background(self, event: wx.Event):
    method init_control_panel (line 201) | def init_control_panel(self):
    method init_right_panel (line 253) | def init_right_panel(self):
    method create_param_category_choice (line 278) | def create_param_category_choice(self, param_category: PoseParameterCa...
    method load_model (line 288) | def load_model(self, event: wx.Event):
    method paint_source_image_panel (line 312) | def paint_source_image_panel(self, event: wx.Event):
    method paint_result_image_panel (line 315) | def paint_result_image_panel(self, event: wx.Event):
    method draw_nothing_yet_string_to_bitmap (line 318) | def draw_nothing_yet_string_to_bitmap(self, bitmap):
    method get_current_pose (line 330) | def get_current_pose(self):
    method update_images (line 338) | def update_images(self, event: wx.Event):
    method on_save_image (line 400) | def on_save_image(self, event: wx.Event):
    method save_last_numpy_image (line 425) | def save_last_numpy_image(self, image_file_name):

FILE: src/tha4/app/character_model_mediapipe_puppeteer.py
  class FpsStatistics (line 25) | class FpsStatistics:
    method __init__ (line 26) | def __init__(self):
    method add_fps (line 30) | def add_fps(self, fps):
    method get_average_fps (line 35) | def get_average_fps(self):
  class MainFrame (line 42) | class MainFrame(wx.Frame):
    method __init__ (line 45) | def __init__(self,
    method create_timers (line 75) | def create_timers(self):
    method on_close (line 81) | def on_close(self, event: wx.Event):
    method on_erase_background (line 90) | def on_erase_background(self, event: wx.Event):
    method create_animation_panel (line 93) | def create_animation_panel(self, parent):
    method create_ui (line 168) | def create_ui(self):
    method create_capture_panel (line 183) | def create_capture_panel(self, parent):
    method paint_webcam_capture_panel (line 199) | def paint_webcam_capture_panel(self, event: wx.Event):
    method create_rotation_column (line 202) | def create_rotation_column(self, parent, rotation_names):
    method update_capture_panel (line 225) | def update_capture_panel(self, event: wx.Event):
    method update_mediapipe_face_pose (line 252) | def update_mediapipe_face_pose(self, detection_result):
    method convert_to_100 (line 274) | def convert_to_100(x):
    method paint_source_image_panel (line 277) | def paint_source_image_panel(self, event: wx.Event):
    method update_source_image_bitmap (line 280) | def update_source_image_bitmap(self):
    method draw_nothing_yet_string (line 290) | def draw_nothing_yet_string(self, dc):
    method paint_result_image_panel (line 297) | def paint_result_image_panel(self, event: wx.Event):
    method update_result_image_bitmap (line 300) | def update_result_image_bitmap(self, event: Optional[wx.Event] = None):
    method blend_with_background (line 375) | def blend_with_background(self, numpy_image, background):
    method load_model (line 381) | def load_model(self, event: wx.Event):

FILE: src/tha4/app/distill.py
  function run_config (line 8) | def run_config(config_file_name: str):

FILE: src/tha4/app/full_manual_poser.py
  class MorphCategoryControlPanel (line 21) | class MorphCategoryControlPanel(wx.Panel):
    method __init__ (line 22) | def __init__(self,
    method update_ui (line 57) | def update_ui(self):
    method on_choice_updated (line 72) | def on_choice_updated(self, event: wx.Event):
    method set_param_value (line 78) | def set_param_value(self, pose: List[float]):
  class SimpleParamGroupsControlPanel (line 97) | class SimpleParamGroupsControlPanel(wx.Panel):
    method __init__ (line 98) | def __init__(self, parent,
    method set_param_value (line 126) | def set_param_value(self, pose: List[float]):
  function convert_output_image_from_torch_to_numpy (line 138) | def convert_output_image_from_torch_to_numpy(output_image):
  class MainFrame (line 158) | class MainFrame(wx.Frame):
    method __init__ (line 159) | def __init__(self, poser: Poser, device: torch.device):
    method init_left_panel (line 197) | def init_left_panel(self):
    method on_erase_background (line 217) | def on_erase_background(self, event: wx.Event):
    method init_control_panel (line 220) | def init_control_panel(self):
    method init_right_panel (line 273) | def init_right_panel(self):
    method create_param_category_choice (line 298) | def create_param_category_choice(self, param_category: PoseParameterCa...
    method load_image (line 308) | def load_image(self, event: wx.Event):
    method paint_source_image_panel (line 334) | def paint_source_image_panel(self, event: wx.Event):
    method paint_result_image_panel (line 337) | def paint_result_image_panel(self, event: wx.Event):
    method draw_nothing_yet_string_to_bitmap (line 340) | def draw_nothing_yet_string_to_bitmap(self, bitmap):
    method get_current_pose (line 352) | def get_current_pose(self):
    method update_images (line 360) | def update_images(self, event: wx.Event):
    method on_save_image (line 422) | def on_save_image(self, event: wx.Event):
    method save_last_numpy_image (line 447) | def save_last_numpy_image(self, image_file_name):

FILE: src/tha4/charmodel/character_model.py
  class CharacterModel (line 12) | class CharacterModel:
    method __init__ (line 13) | def __init__(self,
    method get_poser (line 23) | def get_poser(self, device: torch.device):
    method get_character_image (line 35) | def get_character_image(self, device: torch.device):
    method save (line 44) | def save(self, file_name: str):
    method load (line 60) | def load(file_name: str):

FILE: src/tha4/dataset/image_poses_and_aother_images_dataset.py
  class ImagePosesAndOtherImagesDataset (line 7) | class ImagePosesAndOtherImagesDataset(Dataset):
    method __init__ (line 8) | def __init__(self,
    method get_main_image (line 18) | def get_main_image(self):
    method get_other_image (line 23) | def get_other_image(self, image_index: int):
    method __len__ (line 28) | def __len__(self):
    method __getitem__ (line 31) | def __getitem__(self, index):

FILE: src/tha4/distiller/config_based_training_tasks.py
  function get_torchrun_executable (line 11) | def get_torchrun_executable():
  class RdzvConfig (line 15) | class RdzvConfig:
    method __init__ (line 16) | def __init__(self, id: int, port: int):
  function run_standalone_config_based_training_script (line 21) | def run_standalone_config_based_training_script(
  function define_standalone_config_based_training_tasks (line 44) | def define_standalone_config_based_training_tasks(

FILE: src/tha4/distiller/distiller_config.py
  function copy_file (line 19) | def copy_file(source_file_name: str, dest_file_name):
  class DistillerConfig (line 25) | class DistillerConfig:
    method check (line 43) | def check(self):
    method check_prefix (line 66) | def check_prefix(prefix):
    method check_character_image_file_name (line 71) | def check_character_image_file_name(file_name):
    method check_face_mask_image_file_name (line 83) | def check_face_mask_image_file_name(file_name):
    method check_batch_size (line 101) | def check_batch_size(value, field_name: str):
    method check_num_cpu_workers (line 107) | def check_num_cpu_workers(value):
    method check_num_gpus (line 111) | def check_num_gpus(value):
    method check_random_seed (line 115) | def check_random_seed(value, field_name: str):
    method check_num_training_examples_per_sample_output (line 120) | def check_num_training_examples_per_sample_output(value, field_name):
    method save (line 124) | def save(self, file_name: str):
    method config_yaml_file_name (line 130) | def config_yaml_file_name(self):
    method create_config_yaml_file (line 133) | def create_config_yaml_file(self):
    method load (line 139) | def load(file_name: str) -> 'DistillerConfig':
    method face_morpher_prefix (line 145) | def face_morpher_prefix(self):
    method get_face_morpher_trainer (line 148) | def get_face_morpher_trainer(self, world_size: Optional[int] = None, b...
    method body_morpher_prefix (line 162) | def body_morpher_prefix(self):
    method get_body_morpher_trainer (line 165) | def get_body_morpher_trainer(self, world_size: Optional[int] = None, b...
    method character_model_prefix (line 235) | def character_model_prefix(self):
    method character_model_face_morpher_file_name (line 238) | def character_model_face_morpher_file_name(self):
    method character_model_body_morpher_file_name (line 241) | def character_model_body_morpher_file_name(self):
    method character_model_character_png_file_name (line 244) | def character_model_character_png_file_name(self):
    method character_model_yaml_file_name (line 247) | def character_model_yaml_file_name(self):
    method define_tasks (line 250) | def define_tasks(self, workspace: Workspace):

FILE: src/tha4/distiller/ui/distiller_config_state.py
  class DistillerConfigState (line 9) | class DistillerConfigState:
    method __init__ (line 10) | def __init__(self):
    method load (line 15) | def load(self, file_name):
    method need_to_check_overwrite (line 23) | def need_to_check_overwrite(self):
    method save (line 32) | def save(self):
    method updating_value (line 38) | def updating_value(self, value_func: Callable[[], Any]):
    method set_prefix (line 45) | def set_prefix(self, new_value):
    method set_character_image_file_name (line 53) | def set_character_image_file_name(self, new_value):
    method set_face_mask_image_file_name (line 61) | def set_face_mask_image_file_name(self, new_value):
    method set_num_cpu_workers (line 69) | def set_num_cpu_workers(self, new_value: int):
    method set_num_gpus (line 74) | def set_num_gpus(self, new_value: int):
    method set_face_morpher_random_seed_0 (line 79) | def set_face_morpher_random_seed_0(self, new_value: int):
    method set_face_morpher_random_seed_1 (line 84) | def set_face_morpher_random_seed_1(self, new_value: int):
    method set_face_morpher_num_training_examples_per_sample_output (line 89) | def set_face_morpher_num_training_examples_per_sample_output(self, new...
    method set_face_morpher_batch_size (line 95) | def set_face_morpher_batch_size(self, new_value: int):
    method set_body_morpher_random_seed_0 (line 100) | def set_body_morpher_random_seed_0(self, new_value: int):
    method set_body_morpher_random_seed_1 (line 105) | def set_body_morpher_random_seed_1(self, new_value: int):
    method set_body_morpher_num_training_examples_per_sample_output (line 110) | def set_body_morpher_num_training_examples_per_sample_output(self, new...
    method set_body_morpher_batch_size (line 116) | def set_body_morpher_batch_size(self, new_value: int):
    method get_relative_path_to_cwd (line 121) | def get_relative_path_to_cwd(self, file_name: str, message: str):
    method can_show_character_image (line 130) | def can_show_character_image(self):
    method can_show_face_mask_image (line 133) | def can_show_face_mask_image(self):
    method can_show_mask_on_face_image (line 136) | def can_show_mask_on_face_image(self):
    method can_save (line 139) | def can_save(self):

FILE: src/tha4/distiller/ui/distiller_ui_main_frame.py
  function wx_bind_event (line 16) | def wx_bind_event(widget, evt):
  class DistillerUiMainFrame (line 24) | class DistillerUiMainFrame(wx.Frame):
    method __init__ (line 29) | def __init__(self):
    method init_ui (line 42) | def init_ui(self):
    method init_menus (line 59) | def init_menus(self):
    method init_bitmaps (line 91) | def init_bitmaps(self):
    method create_panel (line 102) | def create_panel(self, parent, sizer, *args, **kwargs):
    method init_left_panel (line 112) | def init_left_panel(self, parent):
    method on_erase_background (line 137) | def on_erase_background(self, event):
    method on_face_image_panel_paint (line 140) | def on_face_image_panel_paint(self, event):
    method on_face_mask_image_panel_paint (line 143) | def on_face_mask_image_panel_paint(self, event):
    method on_mask_on_face_image_panel_paint (line 146) | def on_mask_on_face_image_panel_paint(self, event):
    method init_middle_panel (line 149) | def init_middle_panel(self, parent):
    method init_prefix_panel (line 171) | def init_prefix_panel(self, parent):
    method on_prefix_change_button (line 192) | def on_prefix_change_button(self, event):
    method init_character_image_file_name_panel (line 204) | def init_character_image_file_name_panel(self, parent):
    method on_character_image_change_button (line 224) | def on_character_image_change_button(self, event):
    method update_face_image_bitmap (line 237) | def update_face_image_bitmap(self, new_file_name: str):
    method init_face_mask_image_file_name_panel (line 244) | def init_face_mask_image_file_name_panel(self, parent):
    method on_face_mask_image_change_button (line 264) | def on_face_mask_image_change_button(self, event):
    method update_face_mask_image_bitmap (line 277) | def update_face_mask_image_bitmap(self, new_file_name):
    method update_mask_on_face_image_bitmap (line 285) | def update_mask_on_face_image_bitmap(self):
    method init_num_cpu_workers_panel (line 300) | def init_num_cpu_workers_panel(self, parent):
    method init_num_gpus_panel (line 320) | def init_num_gpus_panel(self, parent):
    method init_face_morpher_random_seed_0_panel (line 340) | def init_face_morpher_random_seed_0_panel(self, parent):
    method init_face_morpher_random_seed_1_panel (line 372) | def init_face_morpher_random_seed_1_panel(self, parent):
    method init_face_morpher_batch_size_panel (line 404) | def init_face_morpher_batch_size_panel(self, parent):
    method init_body_morpher_random_seed_0_panel (line 422) | def init_body_morpher_random_seed_0_panel(self, parent):
    method init_body_morpher_random_seed_1_panel (line 454) | def init_body_morpher_random_seed_1_panel(self, parent):
    method init_body_morpher_batch_size_panel (line 486) | def init_body_morpher_batch_size_panel(self, parent):
    method init_num_training_examples_per_sample_output_panel (line 504) | def init_num_training_examples_per_sample_output_panel(self, parent):
    method on_close (line 533) | def on_close(self, event):
    method create_help_button_func (line 546) | def create_help_button_func(self, html_file_name: str):
    method create_param_name_panel_with_help_button (line 559) | def create_param_name_panel_with_help_button(
    method create_vertically_centered_text_panel (line 571) | def create_vertically_centered_text_panel(self, parent, text: str, min...
    method init_right_panel (line 583) | def init_right_panel(self, parent):
    method populate_distiller_config (line 601) | def populate_distiller_config(self):
    method update_ui (line 626) | def update_ui(self):
    method draw_nothing_yet_string_to_bitmap (line 660) | def draw_nothing_yet_string_to_bitmap(self, bitmap, width: int, height...
    method try_saving (line 672) | def try_saving(self):
    method on_save (line 701) | def on_save(self, event):
    method on_new (line 704) | def on_new(self, event):
    method on_open (line 717) | def on_open(self, event):
    method on_run (line 743) | def on_run(self, event):

FILE: src/tha4/image_util.py
  function grid_change_to_numpy_image (line 11) | def grid_change_to_numpy_image(torch_image, num_channels=3):
  function resize_PIL_image (line 29) | def resize_PIL_image(pil_image, size=(256, 256)):
  function convert_output_image_from_torch_to_numpy (line 36) | def convert_output_image_from_torch_to_numpy(output_image):
  function convert_linear_to_srgb (line 56) | def convert_linear_to_srgb(image: torch.Tensor) -> torch.Tensor:

FILE: src/tha4/mocap/ifacialmocap_pose.py
  function create_default_ifacialmocap_pose (line 6) | def create_default_ifacialmocap_pose():

FILE: src/tha4/mocap/ifacialmocap_pose_converter.py
  class IFacialMocapPoseConverter (line 5) | class IFacialMocapPoseConverter(ABC):
    method convert (line 7) | def convert(self, ifacialmocap_pose: Dict[str, float]) -> List[float]:
    method init_pose_converter_panel (line 11) | def init_pose_converter_panel(self, parent):

FILE: src/tha4/mocap/ifacialmocap_pose_converter_25.py
  class EyebrowDownMode (line 20) | class EyebrowDownMode(Enum):
  class WinkMode (line 27) | class WinkMode(Enum):
  function rad_to_deg (line 32) | def rad_to_deg(rad):
  function deg_to_rad (line 36) | def deg_to_rad(deg):
  function clamp (line 40) | def clamp(x, min_value, max_value):
  class IFacialMocapPoseConverter25Args (line 44) | class IFacialMocapPoseConverter25Args:
    method __init__ (line 45) | def __init__(self,
    method set_smile_threshold_min (line 89) | def set_smile_threshold_min(self, new_value: float):
    method set_smile_threshold_max (line 92) | def set_smile_threshold_max(self, new_value: float):
    method set_eye_surprised_max (line 95) | def set_eye_surprised_max(self, new_value: float):
    method set_eye_blink_max (line 98) | def set_eye_blink_max(self, new_value: float):
    method set_eyebrow_down_max (line 101) | def set_eyebrow_down_max(self, new_value: float):
    method set_cheek_squint_min (line 104) | def set_cheek_squint_min(self, new_value: float):
    method set_cheek_squint_max (line 107) | def set_cheek_squint_max(self, new_value: float):
    method set_jaw_open_min (line 110) | def set_jaw_open_min(self, new_value: float):
    method set_jaw_open_max (line 113) | def set_jaw_open_max(self, new_value: float):
    method set_mouth_frown_max (line 116) | def set_mouth_frown_max(self, new_value: float):
    method set_mouth_funnel_min (line 119) | def set_mouth_funnel_min(self, new_value: float):
    method set_mouth_funnel_max (line 122) | def set_mouth_funnel_max(self, new_value: float):
  class IFacialMocapPoseConverter25 (line 126) | class IFacialMocapPoseConverter25(IFacialMocapPoseConverter):
    method __init__ (line 127) | def __init__(self, args: Optional[IFacialMocapPoseConverter25Args] = N...
    method init_pose_converter_panel (line 188) | def init_pose_converter_panel(self, parent):
    method create_spin_control (line 324) | def create_spin_control(self, parent, label: str, initial_value: float...
    method restart_breathing_cycle_clicked (line 347) | def restart_breathing_cycle_clicked(self, event: wx.Event):
    method change_eyebrow_down_mode (line 350) | def change_eyebrow_down_mode(self, event: wx.Event):
    method change_wink_mode (line 361) | def change_wink_mode(self, event: wx.Event):
    method change_iris_size (line 368) | def change_iris_size(self, event: wx.Event):
    method link_left_right_irises_clicked (line 380) | def link_left_right_irises_clicked(self, event: wx.Event):
    method decompose_head_body_param (line 387) | def decompose_head_body_param(self, param, threshold=2.0 / 3):
    method convert (line 397) | def convert(self, ifacialmocap_pose: Dict[str, float]) -> List[float]:
  function create_ifacialmocap_pose_converter (line 612) | def create_ifacialmocap_pose_converter(

FILE: src/tha4/mocap/ifacialmocap_v2.py
  function parse_ifacialmocap_v2_pose (line 11) | def parse_ifacialmocap_v2_pose(ifacialmocap_output):
  function parse_ifacialmocap_v1_pose (line 51) | def parse_ifacialmocap_v1_pose(ifacialmocap_output):

FILE: src/tha4/mocap/mediapipe_face_pose.py
  class MediaPipeFacePose (line 8) | class MediaPipeFacePose:
    method __init__ (line 12) | def __init__(self, blendshape_params: Optional[Dict[str, float]], xfor...
    method get_json (line 23) | def get_json(self):
    method save (line 29) | def save(self, file_name: str):
    method load (line 35) | def load(file_name: str):

FILE: src/tha4/mocap/mediapipe_face_pose_converter.py
  class MediaPipeFacePoseConverter (line 7) | class MediaPipeFacePoseConverter(ABC):
    method convert (line 9) | def convert(self, mediapipe_face_pose: MediaPipeFacePose) -> List[float]:
    method init_pose_converter_panel (line 13) | def init_pose_converter_panel(

FILE: src/tha4/mocap/mediapipe_face_pose_converter_00.py
  class EyebrowDownMode (line 22) | class EyebrowDownMode(Enum):
  class WinkMode (line 29) | class WinkMode(Enum):
  function rad_to_deg (line 34) | def rad_to_deg(rad):
  function deg_to_rad (line 38) | def deg_to_rad(deg):
  function clamp (line 42) | def clamp(x, min_value, max_value):
  class MediaPipeFacePoseConverter00Args (line 46) | class MediaPipeFacePoseConverter00Args:
    method __init__ (line 47) | def __init__(self,
    method set_smile_threshold_min (line 99) | def set_smile_threshold_min(self, new_value: float):
    method set_smile_threshold_max (line 102) | def set_smile_threshold_max(self, new_value: float):
    method set_eye_surprised_max (line 105) | def set_eye_surprised_max(self, new_value: float):
    method set_eye_blink_max (line 108) | def set_eye_blink_max(self, new_value: float):
    method set_eyebrow_down_max (line 111) | def set_eyebrow_down_max(self, new_value: float):
    method set_cheek_squint_min (line 114) | def set_cheek_squint_min(self, new_value: float):
    method set_cheek_squint_max (line 117) | def set_cheek_squint_max(self, new_value: float):
    method set_jaw_open_min (line 120) | def set_jaw_open_min(self, new_value: float):
    method set_jaw_open_max (line 123) | def set_jaw_open_max(self, new_value: float):
    method set_mouth_frown_max (line 126) | def set_mouth_frown_max(self, new_value: float):
    method set_mouth_funnel_min (line 129) | def set_mouth_funnel_min(self, new_value: float):
    method set_mouth_funnel_max (line 132) | def set_mouth_funnel_max(self, new_value: float):
  class MediaPoseFacePoseConverter00 (line 136) | class MediaPoseFacePoseConverter00(MediaPipeFacePoseConverter):
    method __init__ (line 137) | def __init__(self, args: Optional[MediaPipeFacePoseConverter00Args] = ...
    method init_pose_converter_panel (line 199) | def init_pose_converter_panel(
    method create_spin_control (line 352) | def create_spin_control(self, parent, label: str, initial_value: float...
    method extract_euler_angles (line 375) | def extract_euler_angles(self, mediapipe_face_pose: MediaPipeFacePose):
    method calibrate_face_orientation_clicked (line 380) | def calibrate_face_orientation_clicked(self, event: wx.Event):
    method restart_breathing_cycle_clicked (line 393) | def restart_breathing_cycle_clicked(self, event: wx.Event):
    method change_eyebrow_down_mode (line 396) | def change_eyebrow_down_mode(self, event: wx.Event):
    method change_wink_mode (line 407) | def change_wink_mode(self, event: wx.Event):
    method change_iris_size (line 414) | def change_iris_size(self, event: wx.Event):
    method link_left_right_irises_clicked (line 426) | def link_left_right_irises_clicked(self, event: wx.Event):
    method decompose_head_body_param (line 433) | def decompose_head_body_param(self, param, threshold=2.0 / 3):
    method convert (line 443) | def convert(self, mediapipe_face_pose: MediaPipeFacePose) -> List[float]:

FILE: src/tha4/nn/common/conv_block_factory.py
  class ConvBlockFactory (line 12) | class ConvBlockFactory:
    method __init__ (line 13) | def __init__(self,
    method create_conv3 (line 19) | def create_conv3(self,
    method create_conv7_block (line 33) | def create_conv7_block(self, in_channels: int, out_channels: int):
    method create_conv3_block (line 39) | def create_conv3_block(self, in_channels: int, out_channels: int):
    method create_downsample_block (line 45) | def create_downsample_block(self, in_channels: int, out_channels: int,...
    method create_resnet_block (line 51) | def create_resnet_block(self, num_channels: int, is_1x1: bool):

FILE: src/tha4/nn/common/poser_args.py
  class PoserArgs00 (line 11) | class PoserArgs00:
    method __init__ (line 12) | def __init__(self,
    method create_alpha_block (line 31) | def create_alpha_block(self):
    method create_all_channel_alpha_block (line 42) | def create_all_channel_alpha_block(self):
    method create_color_change_block (line 53) | def create_color_change_block(self):
    method create_grid_change_block (line 62) | def create_grid_change_block(self):

FILE: src/tha4/nn/common/poser_encoder_decoder_00.py
  class PoserEncoderDecoder00Args (line 17) | class PoserEncoderDecoder00Args(PoserArgs00):
    method __init__ (line 18) | def __init__(self,
  class PoserEncoderDecoder00 (line 43) | class PoserEncoderDecoder00(Module):
    method __init__ (line 44) | def __init__(self, args: PoserEncoderDecoder00Args):
    method get_num_output_channels_from_level (line 93) | def get_num_output_channels_from_level(self, level: int):
    method get_num_output_channels_from_image_size (line 96) | def get_num_output_channels_from_image_size(self, image_size: int):
    method forward (line 99) | def forward(self, image: Tensor, pose: Optional[Tensor] = None) -> Lis...

FILE: src/tha4/nn/common/poser_encoder_decoder_00_separable.py
  class PoserEncoderDecoder00Separable (line 14) | class PoserEncoderDecoder00Separable(Module):
    method __init__ (line 15) | def __init__(self, args: PoserEncoderDecoder00Args):
    method get_num_output_channels_from_level (line 64) | def get_num_output_channels_from_level(self, level: int):
    method get_num_output_channels_from_image_size (line 67) | def get_num_output_channels_from_image_size(self, image_size: int):
    method forward (line 70) | def forward(self, image: Tensor, pose: Optional[Tensor] = None) -> Lis...

FILE: src/tha4/nn/common/resize_conv_encoder_decoder.py
  class ResizeConvEncoderDecoderArgs (line 14) | class ResizeConvEncoderDecoderArgs:
    method __init__ (line 15) | def __init__(self,
  class ResizeConvEncoderDecoder (line 36) | class ResizeConvEncoderDecoder(Module):
    method __init__ (line 37) | def __init__(self, args: ResizeConvEncoderDecoderArgs):
    method get_num_output_channels_from_level (line 84) | def get_num_output_channels_from_level(self, level: int):
    method get_num_output_channels_from_image_size (line 87) | def get_num_output_channels_from_image_size(self, image_size: int):
    method forward (line 90) | def forward(self, feature: Tensor) -> List[Tensor]:

FILE: src/tha4/nn/common/resize_conv_unet.py
  class ResizeConvUNetArgs (line 13) | class ResizeConvUNetArgs:
    method __init__ (line 14) | def __init__(self,
  class ResizeConvUNet (line 40) | class ResizeConvUNet(Module):
    method __init__ (line 41) | def __init__(self, args: ResizeConvUNetArgs):
    method forward (line 91) | def forward(self, feature: Tensor) -> List[Tensor]:

FILE: src/tha4/nn/common/unet.py
  class Identity (line 13) | class Identity(Module):
    method __init__ (line 14) | def __init__(self):
    method forward (line 17) | def forward(self, x):
  class IdentityFactory (line 21) | class IdentityFactory(ModuleFactory):
    method create (line 22) | def create(self) -> Module:
  function init_to_zero (line 26) | def init_to_zero(module: Module):
  class Upsample (line 33) | class Upsample(Module):
    method __init__ (line 34) | def __init__(self, in_channels: int, out_channels: Optional[int] = Non...
    method forward (line 44) | def forward(self, x):
  class Downsample (line 49) | class Downsample(Module):
    method __init__ (line 50) | def __init__(self, in_channels: int, out_channels: Optional[int] = Non...
    method forward (line 60) | def forward(self, x):
  function GroupNorm32 (line 65) | def GroupNorm32(channels):
  class SamplingMode (line 69) | class SamplingMode(Enum):
  class ResBlockArgs (line 75) | class ResBlockArgs:
    method __init__ (line 76) | def __init__(self,
  function apply_scaleshift (line 90) | def apply_scaleshift(x: Tensor, scaleshift: Tensor, condition_bias: floa...
  class ResBlock (line 100) | class ResBlock(Module):
    method __init__ (line 101) | def __init__(self,
    method forward (line 154) | def forward(self, x: Tensor, cond0: Optional[Tensor] = None, cond1: Op...
  class AttentionBlockArgs (line 168) | class AttentionBlockArgs:
    method __init__ (line 169) | def __init__(self,
  function qkv_attention_legacy (line 178) | def qkv_attention_legacy(qkv: torch.Tensor, num_heads: int):
  function qkv_attention (line 192) | def qkv_attention(qkv: torch.Tensor, num_heads: int):
  class AttentionBlock (line 205) | class AttentionBlock(Module):
    method __init__ (line 206) | def __init__(self,
    method forward (line 230) | def forward(self, x: torch.Tensor):
  class Arity3To1 (line 242) | class Arity3To1(Module):
    method __init__ (line 243) | def __init__(self, module: Module):
    method forward (line 247) | def forward(self, x: Tensor, y: Optional[Tensor] = None, z: Optional[T...
  class DownsamplingBlock (line 251) | class DownsamplingBlock(Module):
    method __init__ (line 252) | def __init__(self,
    method forward (line 296) | def forward(self, h: Tensor, cond0: Optional[Tensor] = None, cond1: Op...
  class UpsamplingBlock (line 308) | class UpsamplingBlock(Module):
    method __init__ (line 309) | def __init__(self,
    method forward (line 351) | def forward(self,
  function compute_timestep_embedding (line 365) | def compute_timestep_embedding(t: Tensor, out_channels: int):
  class TimeEmbedding (line 379) | class TimeEmbedding(Module):
    method __init__ (line 380) | def __init__(self, out_channels: int):
    method forward (line 384) | def forward(self, t: Tensor):
  class UnetArgs (line 388) | class UnetArgs:
    method __init__ (line 389) | def __init__(self,
  class Unet (line 438) | class Unet(Module):
    method __init__ (line 439) | def __init__(self, args: UnetArgs):
    method forward (line 531) | def forward(self, x: Tensor, t: Tensor, cond: Tensor):
  class UnetWithFirstConvAddition (line 549) | class UnetWithFirstConvAddition(Module):
    method __init__ (line 550) | def __init__(self, args: UnetArgs):
    method forward (line 642) | def forward(self, x: Tensor, t: Tensor, cond: Tensor, first_conv_addit...

FILE: src/tha4/nn/conv.py
  function create_conv7 (line 11) | def create_conv7(in_channels: int, out_channels: int,
  function create_conv7_from_block_args (line 21) | def create_conv7_from_block_args(in_channels: int,
  function create_conv3 (line 33) | def create_conv3(in_channels: int,
  function create_conv3_from_block_args (line 44) | def create_conv3_from_block_args(in_channels: int, out_channels: int,
  function create_conv1 (line 54) | def create_conv1(in_channels: int, out_channels: int,
  function create_conv1_from_block_args (line 64) | def create_conv1_from_block_args(in_channels: int,
  function create_conv7_block (line 78) | def create_conv7_block(in_channels: int, out_channels: int,
  function create_conv7_block_from_block_args (line 91) | def create_conv7_block_from_block_args(
  function create_conv3_block (line 103) | def create_conv3_block(in_channels: int, out_channels: int,
  function create_conv3_block_from_block_args (line 116) | def create_conv3_block_from_block_args(
  function create_downsample_block (line 127) | def create_downsample_block(in_channels: int, out_channels: int,
  function create_downsample_block_from_block_args (line 150) | def create_downsample_block_from_block_args(in_channels: int, out_channe...
  function create_upsample_block (line 164) | def create_upsample_block(in_channels: int,
  function create_upsample_block_from_block_args (line 180) | def create_upsample_block_from_block_args(in_channels: int,

FILE: src/tha4/nn/eyebrow_decomposer/eyebrow_decomposer_00.py
  class EyebrowDecomposer00Args (line 15) | class EyebrowDecomposer00Args(PoserEncoderDecoder00Args):
    method __init__ (line 16) | def __init__(self,
  class EyebrowDecomposer00 (line 36) | class EyebrowDecomposer00(Module):
    method __init__ (line 37) | def __init__(self, args: EyebrowDecomposer00Args):
    method forward (line 46) | def forward(self, image: Tensor, *args) -> List[Tensor]:
  class EyebrowDecomposer00Factory (line 75) | class EyebrowDecomposer00Factory(ModuleFactory):
    method __init__ (line 76) | def __init__(self, args: EyebrowDecomposer00Args):
    method create (line 80) | def create(self) -> Module:

FILE: src/tha4/nn/eyebrow_morphing_combiner/eyebrow_morphing_combiner_00.py
  class EyebrowMorphingCombiner00Args (line 15) | class EyebrowMorphingCombiner00Args(PoserEncoderDecoder00Args):
    method __init__ (line 16) | def __init__(self,
  class EyebrowMorphingCombiner00 (line 37) | class EyebrowMorphingCombiner00(Module):
    method __init__ (line 38) | def __init__(self, args: EyebrowMorphingCombiner00Args):
    method forward (line 47) | def forward(self, background_layer: Tensor, eyebrow_layer: Tensor, pos...
  class EyebrowMorphingCombiner00Factory (line 85) | class EyebrowMorphingCombiner00Factory(ModuleFactory):
    method __init__ (line 86) | def __init__(self, args: EyebrowMorphingCombiner00Args):
    method create (line 90) | def create(self) -> Module:

FILE: src/tha4/nn/face_morpher/face_morpher_08.py
  class FaceMorpher08Args (line 19) | class FaceMorpher08Args:
    method __init__ (line 20) | def __init__(self,
  class FaceMorpher08 (line 48) | class FaceMorpher08(Module):
    method __init__ (line 49) | def __init__(self, args: FaceMorpher08Args):
    method create_alpha_block (line 104) | def create_alpha_block(self):
    method create_color_change_block (line 114) | def create_color_change_block(self):
    method create_grid_change_block (line 123) | def create_grid_change_block(self):
    method get_num_output_channels_from_level (line 131) | def get_num_output_channels_from_level(self, level: int):
    method get_num_output_channels_from_image_size (line 134) | def get_num_output_channels_from_image_size(self, image_size: int):
    method merge_down (line 137) | def merge_down(self, top_layer: Tensor, bottom_layer: Tensor):
    method apply_grid_change (line 142) | def apply_grid_change(self, grid_change, image: Tensor) -> Tensor:
    method apply_color_change (line 155) | def apply_color_change(self, alpha, color_change, image: Tensor) -> Te...
    method forward (line 158) | def forward(self, image: Tensor, pose: Tensor, *args) -> List[Tensor]:
  class FaceMorpher08Factory (line 205) | class FaceMorpher08Factory(ModuleFactory):
    method __init__ (line 206) | def __init__(self, args: FaceMorpher08Args):
    method create (line 210) | def create(self) -> Module:

FILE: src/tha4/nn/image_processing_util.py
  function apply_rgb_change (line 6) | def apply_rgb_change(alpha: Tensor, color_change: Tensor, image: Tensor):
  function apply_grid_change (line 13) | def apply_grid_change(grid_change, image: Tensor) -> Tensor:
  class GridChangeApplier (line 27) | class GridChangeApplier:
    method __init__ (line 28) | def __init__(self):
    method apply (line 33) | def apply(self, grid_change: Tensor, image: Tensor, align_corners: boo...
  function apply_color_change (line 57) | def apply_color_change(alpha, color_change, image: Tensor) -> Tensor:

FILE: src/tha4/nn/init_function.py
  function create_init_function (line 9) | def create_init_function(method: str = 'none') -> Callable[[Module], Mod...
  class HeInitialization (line 35) | class HeInitialization:
    method __init__ (line 36) | def __init__(self, a: int = 0, mode: str = 'fan_in', nonlinearity: str...
    method __call__ (line 41) | def __call__(self, module: Module) -> Module:
  class NormalInitialization (line 47) | class NormalInitialization:
    method __init__ (line 48) | def __init__(self, mean: float = 0.0, std: float = 1.0):
    method __call__ (line 52) | def __call__(self, module: Module) -> Module:
  class XavierInitialization (line 58) | class XavierInitialization:
    method __init__ (line 59) | def __init__(self, gain: float = 1.0):
    method __call__ (line 62) | def __call__(self, module: Module) -> Module:
  class ZeroInitialization (line 68) | class ZeroInitialization:
    method __call__ (line 69) | def __call__(self, module: Module) -> Module:
  class NoInitialization (line 74) | class NoInitialization:
    method __call__ (line 75) | def __call__(self, module: Module) -> Module:

FILE: src/tha4/nn/morpher/morpher_00.py
  function apply_color_change (line 12) | def apply_color_change(alpha, color_change, image: Tensor) -> Tensor:
  class Morpher00Args (line 16) | class Morpher00Args:
    method __init__ (line 17) | def __init__(self,
  class Morpher00 (line 35) | class Morpher00(Module):
    method __init__ (line 36) | def __init__(self, args: Morpher00Args):
    method forward (line 42) | def forward(self, image: torch.Tensor, pose: torch.Tensor) -> List[Ten...
  class Morpher00Factory (line 75) | class Morpher00Factory(ModuleFactory):
    method __init__ (line 76) | def __init__(self, args: Morpher00Args):
    method create (line 79) | def create(self) -> Module:

FILE: src/tha4/nn/nonlinearity_factory.py
  class ReLUFactory (line 8) | class ReLUFactory(ModuleFactory):
    method __init__ (line 9) | def __init__(self, inplace: bool = False):
    method create (line 12) | def create(self) -> Module:
  class LeakyReLUFactory (line 16) | class LeakyReLUFactory(ModuleFactory):
    method __init__ (line 17) | def __init__(self, inplace: bool = False, negative_slope: float = 1e-2):
    method create (line 21) | def create(self) -> Module:
  class ELUFactory (line 25) | class ELUFactory(ModuleFactory):
    method __init__ (line 26) | def __init__(self, inplace: bool = False, alpha: float = 1.0):
    method create (line 30) | def create(self) -> Module:
  class ReLU6Factory (line 34) | class ReLU6Factory(ModuleFactory):
    method __init__ (line 35) | def __init__(self, inplace: bool = False):
    method create (line 38) | def create(self) -> Module:
  class SiLUFactory (line 42) | class SiLUFactory(ModuleFactory):
    method __init__ (line 43) | def __init__(self, inplace: bool = False):
    method create (line 46) | def create(self) -> Module:
  class HardswishFactory (line 50) | class HardswishFactory(ModuleFactory):
    method __init__ (line 51) | def __init__(self, inplace: bool = False):
    method create (line 54) | def create(self) -> Module:
  class TanhFactory (line 58) | class TanhFactory(ModuleFactory):
    method create (line 59) | def create(self) -> Module:
  class SigmoidFactory (line 63) | class SigmoidFactory(ModuleFactory):
    method create (line 64) | def create(self) -> Module:
  function resolve_nonlinearity_factory (line 68) | def resolve_nonlinearity_factory(nonlinearity_fatory: Optional[ModuleFac...

FILE: src/tha4/nn/normalization.py
  class PixelNormalization (line 12) | class PixelNormalization(Module):
    method __init__ (line 13) | def __init__(self, epsilon=1e-8):
    method forward (line 17) | def forward(self, x):
  class NormalizationLayerFactory (line 21) | class NormalizationLayerFactory(ABC):
    method __init__ (line 22) | def __init__(self):
    method create (line 26) | def create(self, num_features: int, affine: bool = True) -> Module:
    method resolve_2d (line 30) | def resolve_2d(factory: Optional['NormalizationLayerFactory']) -> 'Nor...
  class Bias2d (line 37) | class Bias2d(Module):
    method __init__ (line 38) | def __init__(self, num_features: int):
    method forward (line 43) | def forward(self, x):
  class NoNorm2dFactory (line 47) | class NoNorm2dFactory(NormalizationLayerFactory):
    method __init__ (line 48) | def __init__(self):
    method create (line 51) | def create(self, num_features: int, affine: bool = True) -> Module:
  class BatchNorm2dFactory (line 58) | class BatchNorm2dFactory(NormalizationLayerFactory):
    method __init__ (line 59) | def __init__(self,
    method get_weight_mean (line 68) | def get_weight_mean(self):
    method get_weight_std (line 74) | def get_weight_std(self):
    method create (line 80) | def create(self, num_features: int, affine: bool = True) -> Module:
  class InstanceNorm2dFactory (line 90) | class InstanceNorm2dFactory(NormalizationLayerFactory):
    method __init__ (line 91) | def __init__(self):
    method create (line 94) | def create(self, num_features: int, affine: bool = True) -> Module:
  class PixelNormFactory (line 98) | class PixelNormFactory(NormalizationLayerFactory):
    method __init__ (line 99) | def __init__(self):
    method create (line 102) | def create(self, num_features: int, affine: bool = True) -> Module:
  class LayerNorm2d (line 106) | class LayerNorm2d(Module):
    method __init__ (line 107) | def __init__(self, channels: int, affine: bool = True):
    method forward (line 116) | def forward(self, x):
  class LayerNorm2dFactory (line 121) | class LayerNorm2dFactory(NormalizationLayerFactory):
    method __init__ (line 122) | def __init__(self):
    method create (line 125) | def create(self, num_features: int, affine: bool = True) -> Module:

FILE: src/tha4/nn/pass_through.py
  class PassThrough (line 4) | class PassThrough(Module):
    method __init__ (line 5) | def __init__(self):
    method forward (line 8) | def forward(self, x):

FILE: src/tha4/nn/resnet_block.py
  class ResnetBlock (line 13) | class ResnetBlock(Module):
    method create (line 15) | def create(num_channels: int,
    method __init__ (line 29) | def __init__(self,
    method forward (line 63) | def forward(self, x):

FILE: src/tha4/nn/resnet_block_seperable.py
  class ResnetBlockSeparable (line 14) | class ResnetBlockSeparable(Module):
    method create (line 16) | def create(num_channels: int,
    method __init__ (line 31) | def __init__(self,
    method forward (line 67) | def forward(self, x):

FILE: src/tha4/nn/separable_conv.py
  function create_separable_conv3 (line 9) | def create_separable_conv3(in_channels: int, out_channels: int,
  function create_separable_conv7 (line 24) | def create_separable_conv7(in_channels: int, out_channels: int,
  function create_separable_conv3_block (line 39) | def create_separable_conv3_block(
  function create_separable_conv7_block (line 56) | def create_separable_conv7_block(
  function create_separable_downsample_block (line 73) | def create_separable_downsample_block(
  function create_separable_upsample_block (line 103) | def create_separable_upsample_block(

FILE: src/tha4/nn/siren/face_morpher/siren_face_morpher_00.py
  class SirenFaceMorpher00Args (line 12) | class SirenFaceMorpher00Args:
    method __init__ (line 13) | def __init__(self,
  class SirenFaceMorpher00 (line 28) | class SirenFaceMorpher00(Module):
    method __init__ (line 29) | def __init__(self, args: SirenFaceMorpher00Args):
    method forward (line 34) | def forward(self, pose: Tensor, position: Optional[Tensor] = None) -> ...
  class SirenFaceMorpher00Factory (line 54) | class SirenFaceMorpher00Factory(ModuleFactory):
    method __init__ (line 55) | def __init__(self, args: SirenFaceMorpher00Args):
    method create (line 58) | def create(self) -> Module:

FILE: src/tha4/nn/siren/face_morpher/siren_face_morpher_00_trainer.py
  function get_poser (line 23) | def get_poser():
  class SirenFaceMorpher00TrainerArgs (line 29) | class SirenFaceMorpher00TrainerArgs:
    method __init__ (line 30) | def __init__(self,
    method get_character_image (line 75) | def get_character_image(self):
    method get_face_mask_image (line 83) | def get_face_mask_image(self):
    method get_training_dataset (line 97) | def get_training_dataset(self):
    method get_module_factory (line 103) | def get_module_factory(self):
    method transform_pose_to_module_input (line 115) | def transform_pose_to_module_input(self, pose: Tensor):
    method transform_original_image_to_module_input (line 118) | def transform_original_image_to_module_input(self, image: Tensor):
    method transform_poser_posed_image_to_groundtruth (line 123) | def transform_poser_posed_image_to_groundtruth(self, image: Tensor):
    method get_training_computation_protocol (line 128) | def get_training_computation_protocol(self):
    method get_learning_rate (line 134) | def get_learning_rate(self, examples_seen_so_far) -> Dict[str, float]:
    method get_optimizer_factories (line 152) | def get_optimizer_factories(self):
    method get_poser (line 157) | def get_poser(self):
    method get_training_protocol (line 160) | def get_training_protocol(self, world_size: int):
    method get_sample_output_protocol (line 175) | def get_sample_output_protocol(self):
    method get_loss (line 185) | def get_loss(self):
    method create_trainer (line 205) | def create_trainer(self, prefix: str, world_size: int, distrib_backend...

FILE: src/tha4/nn/siren/face_morpher/siren_face_morpher_protocols_00.py
  class SirenMorpherProtocol00Keys (line 23) | class SirenMorpherProtocol00Keys:
  class SirenMorpherProtocol00Indices (line 43) | class SirenMorpherProtocol00Indices:
  class SirenFaceMorpherComputationProtocol00 (line 50) | class SirenFaceMorpherComputationProtocol00(ComposableCachedComputationP...
    method __init__ (line 51) | def __init__(self,
  class SirenFaceMorpherSampleOutputProtocol00 (line 110) | class SirenFaceMorpherSampleOutputProtocol00(SampleOutputProtocol):
    method __init__ (line 111) | def __init__(self,
    method get_examples_per_sample_output (line 132) | def get_examples_per_sample_output(self) -> int:
    method get_random_seed (line 135) | def get_random_seed(self) -> int:
    method get_sample_output_data (line 138) | def get_sample_output_data(self, validation_dataset: Dataset, device: ...
    method save_sample_output_data (line 153) | def save_sample_output_data(self,

FILE: src/tha4/nn/siren/morpher/siren_morpher_03.py
  class SirenMorpherLevelArgs (line 14) | class SirenMorpherLevelArgs:
    method __init__ (line 15) | def __init__(self,
  class SirenMorpher03Args (line 25) | class SirenMorpher03Args:
    method __init__ (line 26) | def __init__(self,
  class SirenMorpher03 (line 42) | class SirenMorpher03(Module):
    method __init__ (line 43) | def __init__(self, args: SirenMorpher03Args):
    method get_position_grid (line 92) | def get_position_grid(self, n: int, image_size: int, device: torch.dev...
    method get_pose_image (line 101) | def get_pose_image(self, pose: Tensor, image_size: int):
    method forward (line 107) | def forward(self, image: Tensor, pose: Tensor) -> List[Tensor]:
  class SirenMorpher03Factory (line 148) | class SirenMorpher03Factory(ModuleFactory):
    method __init__ (line 149) | def __init__(self, args: SirenMorpher03Args):
    method create (line 152) | def create(self):

FILE: src/tha4/nn/siren/morpher/siren_morpher_03_trainer.py
  function get_poser (line 20) | def get_poser():
  class LossTerm (line 26) | class LossTerm(Enum):
    method get_loss (line 32) | def get_loss(self, protocol: SirenMorpherComputationProtocol03):
  class LossWeights (line 53) | class LossWeights:
    method __init__ (line 54) | def __init__(self, weights: Optional[Dict[LossTerm, float]] = None):
  class TrainingPhase (line 64) | class TrainingPhase:
    method __init__ (line 65) | def __init__(self,
  class LearningRateFunc (line 74) | class LearningRateFunc:
    method __init__ (line 75) | def __init__(self, phases: List[TrainingPhase], keys: List[str]):
    method make_learning_rate_dict (line 79) | def make_learning_rate_dict(self, keys: List[str], value: float):
    method __call__ (line 85) | def __call__(self, examples_seen_so_far: int) -> Dict[str, float]:
  class LossWeightFunc (line 92) | class LossWeightFunc:
    method __init__ (line 93) | def __init__(self, phases: List[TrainingPhase], term: LossTerm):
    method __call__ (line 97) | def __call__(self, examples_seen_so_far: int) -> float:
  class TrainingPhases (line 104) | class TrainingPhases:
    method __init__ (line 105) | def __init__(self, phases: List[TrainingPhase]):
    method make_learning_rate_dict (line 112) | def make_learning_rate_dict(self, keys: List[str], value: float):
    method get_learning_rate_func (line 118) | def get_learning_rate_func(self, keys: List[str]):
    method get_loss_weight_func (line 121) | def get_loss_weight_func(self, term: LossTerm) -> Callable[[int], float]:
  class SirenMorpher03TrainerArgs (line 125) | class SirenMorpher03TrainerArgs:
    method __init__ (line 126) | def __init__(self,
    method get_character_image (line 160) | def get_character_image(self):
    method get_training_dataset (line 168) | def get_training_dataset(self):
    method get_module_factory (line 174) | def get_module_factory(self):
    method get_training_computation_protocol (line 195) | def get_training_computation_protocol(self):
    method get_optimizer_factories (line 202) | def get_optimizer_factories(self):
    method get_poser (line 207) | def get_poser(self):
    method get_training_protocol (line 210) | def get_training_protocol(self, world_size: int):
    method get_sample_output_protocol (line 225) | def get_sample_output_protocol(self):
    method get_loss (line 237) | def get_loss(self):
    method create_trainer (line 249) | def create_trainer(self, prefix: str, world_size: int, distrib_backend...

FILE: src/tha4/nn/siren/morpher/siren_morpher_protocols_03.py
  class SirenMorpherProtocol03Keys (line 27) | class SirenMorpherProtocol03Keys:
  class SirenMorpherProtocol03Indices (line 57) | class SirenMorpherProtocol03Indices:
  class SirenMorpherComputationProtocol03 (line 75) | class SirenMorpherComputationProtocol03(ComposableCachedComputationProto...
    method __init__ (line 76) | def __init__(self,
  class SirenMorpherTrainingProtocol03 (line 160) | class SirenMorpherTrainingProtocol03(AbstractTrainingProtocol):
    method __init__ (line 161) | def __init__(self,
    method run_training_iteration (line 178) | def run_training_iteration(
  class SirenMorpherSampleOutputProtocol (line 217) | class SirenMorpherSampleOutputProtocol(SampleOutputProtocol):
    method __init__ (line 218) | def __init__(self,
    method get_examples_per_sample_output (line 281) | def get_examples_per_sample_output(self) -> int:
    method get_random_seed (line 284) | def get_random_seed(self) -> int:
    method get_sample_output_data (line 287) | def get_sample_output_data(self, validation_dataset: Dataset, device: ...
    method save_sample_output_data (line 300) | def save_sample_output_data(self,

FILE: src/tha4/nn/siren/vanilla/siren.py
  class SineLinearLayer (line 12) | class SineLinearLayer(Module):
    method __init__ (line 13) | def __init__(self,
    method forward (line 38) | def forward(self, x: Tensor):
  class SirenArgs (line 42) | class SirenArgs:
    method __init__ (line 43) | def __init__(
  class Siren (line 62) | class Siren(Module):
    method __init__ (line 63) | def __init__(self, args: SirenArgs):
    method forward (line 84) | def forward(self, x: Tensor) -> Tensor:
  class SirenFactory (line 94) | class SirenFactory(ModuleFactory):
    method __init__ (line 95) | def __init__(self, args: SirenArgs):
    method create (line 99) | def create(self) -> Module:

FILE: src/tha4/nn/spectral_norm.py
  function apply_spectral_norm (line 5) | def apply_spectral_norm(module: Module, use_spectrial_norm: bool = False...

FILE: src/tha4/nn/upscaler/upscaler_02.py
  class Upscaler02Args (line 12) | class Upscaler02Args:
    method __init__ (line 13) | def __init__(self,
  function apply_color_change (line 33) | def apply_color_change(alpha, color_change, image: Tensor) -> Tensor:
  class Upscaler02 (line 37) | class Upscaler02(Module):
    method __init__ (line 38) | def __init__(self, args: Upscaler02Args):
    method check_image (line 53) | def check_image(self, image: torch.Tensor):
    method forward (line 59) | def forward(self,
  class Upscaler02Factory (line 105) | class Upscaler02Factory(ModuleFactory):
    method __init__ (line 106) | def __init__(self, args: Upscaler02Args):
    method create (line 109) | def create(self) -> Module:

FILE: src/tha4/nn/util.py
  function wrap_conv_or_linear_module (line 12) | def wrap_conv_or_linear_module(module: Module,
  class BlockArgs (line 22) | class BlockArgs:
    method __init__ (line 23) | def __init__(self,
    method wrap_module (line 33) | def wrap_module(self, module: Module) -> Module:
    method get_init_func (line 36) | def get_init_func(self) -> Callable[[Module], Module]:

FILE: src/tha4/poser/general_poser_02.py
  class GeneralPoser02 (line 10) | class GeneralPoser02(Poser):
    method __init__ (line 11) | def __init__(self,
    method get_image_size (line 38) | def get_image_size(self) -> int:
    method get_modules (line 41) | def get_modules(self):
    method get_pose_parameter_groups (line 51) | def get_pose_parameter_groups(self) -> List[PoseParameterGroup]:
    method get_num_parameters (line 54) | def get_num_parameters(self) -> int:
    method pose (line 57) | def pose(self, image: Tensor, pose: Tensor, output_index: Optional[int...
    method get_posing_outputs (line 63) | def get_posing_outputs(self, image: Tensor, pose: Tensor) -> List[Tens...
    method get_output_length (line 81) | def get_output_length(self) -> int:
    method free (line 84) | def free(self):
    method get_dtype (line 87) | def get_dtype(self) -> torch.dtype:
    method to (line 90) | def to(self, device: torch.device) -> 'GeneralPoser02':

FILE: src/tha4/poser/modes/mode_07.py
  class Network (line 24) | class Network(Enum):
    method outputs_key (line 32) | def outputs_key(self):
  class Branch (line 36) | class Branch(Enum):
  class FiveStepPoserComputationProtocol (line 47) | class FiveStepPoserComputationProtocol(CachedComputationProtocol):
    method __init__ (line 48) | def __init__(self, eyebrow_morphed_image_index: int):
    method compute_func (line 54) | def compute_func(self):
    method compute_output (line 72) | def compute_output(self, key: str, state: ComputationState) -> List[Te...
  function load_eyebrow_decomposer (line 137) | def load_eyebrow_decomposer(file_name: str):
  function load_eyebrow_morphing_combiner (line 158) | def load_eyebrow_morphing_combiner(file_name: str):
  function load_face_morpher (line 180) | def load_face_morpher(file_name: str):
  function apply_color_change (line 206) | def apply_color_change(alpha, color_change, image: Tensor) -> Tensor:
  function load_morpher_00 (line 210) | def load_morpher_00(file_name: str):
  function load_upscaler_02 (line 241) | def load_upscaler_02(file_name: str):
  function create_poser (line 272) | def create_poser(

FILE: src/tha4/poser/modes/mode_12.py
  class Network (line 20) | class Network(Enum):
    method outputs_key (line 26) | def outputs_key(self):
  class Branch (line 30) | class Branch(Enum):
  class FiveStepPoserComputationProtocol (line 41) | class FiveStepPoserComputationProtocol(CachedComputationProtocol):
    method __init__ (line 42) | def __init__(self, eyebrow_morphed_image_index: int):
    method compute_func (line 48) | def compute_func(self):
    method compute_output (line 66) | def compute_output(self, key: str, state: ComputationState) -> Any:
  function load_eyebrow_decomposer (line 99) | def load_eyebrow_decomposer(file_name: str):
  function load_eyebrow_morphing_combiner (line 120) | def load_eyebrow_morphing_combiner(file_name: str):
  function load_face_morpher (line 142) | def load_face_morpher(file_name: str):
  function apply_color_change (line 165) | def apply_color_change(alpha, color_change, image: Tensor) -> Tensor:
  function create_poser (line 169) | def create_poser(

FILE: src/tha4/poser/modes/mode_14.py
  class Keys (line 19) | class Keys:
  class Indices (line 35) | class Indices:
  class TwoStepPoserComputationProtocol (line 40) | class TwoStepPoserComputationProtocol(CachedComputationProtocol):
    method __init__ (line 41) | def __init__(self, keys: Optional[Keys] = None, indices: Optional[Indi...
    method compute_func (line 52) | def compute_func(self):
    method compute_output (line 58) | def compute_output(self, key: str, state: ComputationState) -> Any:
  function load_face_morpher (line 93) | def load_face_morpher(file_name: Optional[str] = None):
  function load_body_morpher (line 109) | def load_body_morpher(file_name: Optional[str] = None):
  function create_poser (line 134) | def create_poser(

FILE: src/tha4/poser/modes/pose_parameters.py
  function get_pose_parameters (line 4) | def get_pose_parameters():

FILE: src/tha4/poser/poser.py
  class PoseParameterCategory (line 9) | class PoseParameterCategory(Enum):
  class PoseParameterGroup (line 20) | class PoseParameterGroup:
    method __init__ (line 21) | def __init__(self,
    method get_arity (line 47) | def get_arity(self) -> int:
    method get_group_name (line 50) | def get_group_name(self) -> str:
    method get_parameter_names (line 53) | def get_parameter_names(self) -> List[str]:
    method is_discrete (line 56) | def is_discrete(self) -> bool:
    method get_range (line 59) | def get_range(self) -> Tuple[float, float]:
    method get_default_value (line 62) | def get_default_value(self):
    method get_parameter_index (line 65) | def get_parameter_index(self):
    method get_category (line 68) | def get_category(self) -> PoseParameterCategory:
  class PoseParameters (line 72) | class PoseParameters:
    method __init__ (line 73) | def __init__(self, pose_parameter_groups: List[PoseParameterGroup]):
    method get_parameter_index (line 76) | def get_parameter_index(self, name: str) -> int:
    method get_parameter_name (line 85) | def get_parameter_name(self, index: int) -> str:
    method get_pose_parameter_groups (line 95) | def get_pose_parameter_groups(self):
    method get_parameter_count (line 98) | def get_parameter_count(self):
    class Builder (line 104) | class Builder:
      method __init__ (line 105) | def __init__(self):
      method add_parameter_group (line 109) | def add_parameter_group(self,
      method build (line 128) | def build(self) -> 'PoseParameters':
  class Poser (line 132) | class Poser(ABC):
    method get_image_size (line 134) | def get_image_size(self) -> int:
    method get_output_length (line 138) | def get_output_length(self) -> int:
    method get_pose_parameter_groups (line 142) | def get_pose_parameter_groups(self) -> List[PoseParameterGroup]:
    method get_num_parameters (line 146) | def get_num_parameters(self) -> int:
    method pose (line 150) | def pose(self, image: Tensor, pose: Tensor, output_index: int = 0) -> ...
    method get_posing_outputs (line 154) | def get_posing_outputs(self, image: Tensor, pose: Tensor) -> List[Tens...
    method get_dtype (line 157) | def get_dtype(self) -> torch.dtype:
    method to (line 161) | def to(self, device: torch.device):

FILE: src/tha4/pytasuku/indexed/all_tasks.py
  class AllTasks (line 8) | class AllTasks(NoIndexCommandTasks):
    method __init__ (line 9) | def __init__(
    method execute_run_command (line 20) | def execute_run_command(self):
    method execute_clean_command (line 24) | def execute_clean_command(self):

FILE: src/tha4/pytasuku/indexed/bundled_indexed_file_tasks.py
  class BundledIndexedTasks (line 9) | class BundledIndexedTasks:
    method indexed_tasks_command_names (line 14) | def indexed_tasks_command_names(self) -> Iterable[str]:
    method get_indexed_tasks (line 18) | def get_indexed_tasks(self, command_name) -> IndexedTasks:
  function define_all_tasks_from_list (line 22) | def define_all_tasks_from_list(workspace: Workspace, prefix: str, tasks:...

FILE: src/tha4/pytasuku/indexed/indexed_file_tasks.py
  class IndexedFileTasks (line 8) | class IndexedFileTasks(IndexedTasks, abc.ABC):
    method __init__ (line 9) | def __init__(self, workspace: Workspace, prefix: str):
    method file_list (line 14) | def file_list(self) -> List[str]:
    method get_file_name (line 18) | def get_file_name(self, *indices: int) -> str:

FILE: src/tha4/pytasuku/indexed/indexed_tasks.py
  class IndexedTasks (line 7) | class IndexedTasks(abc.ABC):
    method __init__ (line 8) | def __init__(self, workspace: Workspace, prefix: str):
    method run_command (line 14) | def run_command(self) -> str:
    method clean_command (line 19) | def clean_command(self) -> str:
    method shape (line 24) | def shape(self) -> List[int]:
    method arity (line 29) | def arity(self) -> int:
    method define_tasks (line 33) | def define_tasks(self):

FILE: src/tha4/pytasuku/indexed/no_index_command_tasks.py
  class NoIndexCommandTasks (line 8) | class NoIndexCommandTasks(IndexedTasks, abc.ABC):
    method __init__ (line 9) | def __init__(self, workspace: Workspace, prefix: str, command_name: st...
    method run_command (line 16) | def run_command(self):
    method clean_command (line 20) | def clean_command(self):
    method arity (line 24) | def arity(self) -> int:
    method shape (line 28) | def shape(self) -> List[int]:
    method execute_run_command (line 32) | def execute_run_command(self):
    method execute_clean_command (line 36) | def execute_clean_command(self):
    method define_tasks (line 39) | def define_tasks(self):

FILE: src/tha4/pytasuku/indexed/no_index_file_tasks.py
  class NoIndexFileTasks (line 9) | class NoIndexFileTasks(IndexedFileTasks, abc.ABC):
    method __init__ (line 10) | def __init__(self, workspace: Workspace, prefix: str, command_name: st...
    method file_name (line 18) | def file_name(self):
    method create_file_task (line 22) | def create_file_task(self):
    method get_file_name (line 25) | def get_file_name(self, *indices: int) -> str:
    method run_command (line 31) | def run_command(self):
    method clean_command (line 35) | def clean_command(self):
    method arity (line 39) | def arity(self) -> int:
    method shape (line 43) | def shape(self) -> List[int]:
    method file_list (line 47) | def file_list(self) -> List[str]:
    method clean (line 50) | def clean(self):
    method define_tasks (line 53) | def define_tasks(self):

FILE: src/tha4/pytasuku/indexed/one_index_file_tasks.py
  class OneIndexFileTasks (line 10) | class OneIndexFileTasks(IndexedFileTasks, abc.ABC):
    method __init__ (line 11) | def __init__(self, workspace: Workspace, prefix: str, command_name: st...
    method run_command (line 21) | def run_command(self) -> str:
    method clean_command (line 25) | def clean_command(self) -> str:
    method shape (line 29) | def shape(self) -> List[int]:
    method arity (line 33) | def arity(self) -> int:
    method file_name (line 37) | def file_name(self, index):
    method create_file_tasks (line 41) | def create_file_tasks(self, index):
    method get_file_name (line 44) | def get_file_name(self, *indices: int) -> str:
    method file_list (line 51) | def file_list(self):
    method clean (line 57) | def clean(self):
    method define_tasks (line 61) | def define_tasks(self):

FILE: src/tha4/pytasuku/indexed/simple_no_index_file_tasks.py
  class SimpleNoIndexFileTasks (line 7) | class SimpleNoIndexFileTasks(NoIndexFileTasks):
    method __init__ (line 8) | def __init__(self,
    method file_name (line 24) | def file_name(self):
    method create_file_task (line 27) | def create_file_task(self):

FILE: src/tha4/pytasuku/indexed/two_indices_file_tasks.py
  class TwoIndicesFileTasks (line 9) | class TwoIndicesFileTasks(IndexedFileTasks, abc.ABC):
    method __init__ (line 10) | def __init__(self, workspace: Workspace, prefix: str, command_name: str,
    method run_command (line 21) | def run_command(self) -> str:
    method clean_command (line 25) | def clean_command(self) -> str:
    method shape (line 29) | def shape(self) -> List[int]:
    method arity (line 33) | def arity(self) -> int:
    method file_name (line 37) | def file_name(self, index0: int, index1: int) -> str:
    method file_list (line 41) | def file_list(self) -> List[str]:
    method create_file_tasks (line 49) | def create_file_tasks(self, index0: int, index1: int):
    method get_file_name (line 52) | def get_file_name(self, *indices: int) -> str:
    method clean (line 58) | def clean(self):
    method define_tasks (line 62) | def define_tasks(self):

FILE: src/tha4/pytasuku/indexed/util.py
  function delete_file (line 9) | def delete_file(file_name):
  function all_tasks_from_named_tasks_map (line 17) | def all_tasks_from_named_tasks_map(
  function create_tasks_hierarchy_helper (line 38) | def create_tasks_hierarchy_helper(
  function create_task_hierarchy (line 60) | def create_task_hierarchy(
  function write_done_file (line 68) | def write_done_file(file_name: str):

FILE: src/tha4/pytasuku/task.py
  class Task (line 6) | class Task:
    method __init__ (line 7) | def __init__(self, workspace: 'Workspace', name: str, dependencies: Li...
    method run (line 13) | def run(self):
    method can_run (line 17) | def can_run(self) -> bool:
    method needs_to_be_run (line 21) | def needs_to_be_run(self) -> bool:
    method name (line 25) | def name(self) -> str:
    method dependencies (line 29) | def dependencies(self) -> List[str]:
    method workspace (line 33) | def workspace(self) -> 'Workspace':
    method timestamp (line 37) | def timestamp(self) -> float:
  class CommandTask (line 41) | class CommandTask(Task):
    method __init__ (line 42) | def __init__(self, workspace, name, dependencies):
    method needs_to_be_run (line 46) | def needs_to_be_run(self):
  class PlaceholderTask (line 50) | class PlaceholderTask(Task):
    method __init__ (line 51) | def __init__(self, workspace, name):
    method can_run (line 55) | def can_run(self):
    method run (line 58) | def run(self):
    method needs_to_be_run (line 62) | def needs_to_be_run(self):
    method timestamp (line 66) | def timestamp(self) -> float:
  class FileTask (line 73) | class FileTask(Task):
    method __init__ (line 74) | def __init__(self, workspace, name, dependencies):
    method timestamp (line 78) | def timestamp(self):
    method needs_to_be_run (line 82) | def needs_to_be_run(self):

FILE: src/tha4/pytasuku/task_selector_ui.py
  class TaskSelectorUi (line 7) | class TaskSelectorUi(Frame):
    method __init__ (line 8) | def __init__(self, root, workspace: Workspace):
    method add_tree_nodes (line 46) | def add_tree_nodes(self):
    method run_selected_task (line 94) | def run_selected_task(self):
  function run_task_selector_ui (line 104) | def run_task_selector_ui(workspace: Workspace):

FILE: src/tha4/pytasuku/util.py
  function create_delete_all_task (line 8) | def create_delete_all_task(workspace: Workspace, name: str, files: List[...

FILE: src/tha4/pytasuku/workspace.py
  class WorkspaceState (line 8) | class WorkspaceState(Enum):
  class NodeState (line 13) | class NodeState(Enum):
  class FuncCommandTask (line 18) | class FuncCommandTask(CommandTask):
    method __init__ (line 19) | def __init__(self, workspace, name, dependencies, func):
    method run (line 23) | def run(self):
  class FuncFileTask (line 27) | class FuncFileTask(FileTask):
    method __init__ (line 28) | def __init__(self, workspace, name, dependencies, func):
    method run (line 32) | def run(self):
  function do_nothing (line 36) | def do_nothing():
  class Workspace (line 40) | class Workspace:
    method __init__ (line 41) | def __init__(self):
    method modified (line 48) | def modified(self) -> bool:
    method state (line 52) | def state(self) -> WorkspaceState:
    method in_session (line 56) | def in_session(self) -> bool:
    method task_exists (line 59) | def task_exists(self, name: str) -> bool:
    method task_exists_and_not_placeholder (line 62) | def task_exists_and_not_placeholder(self, name: str) -> bool:
    method get_task (line 65) | def get_task(self, name: str) -> Task:
    method add_task (line 68) | def add_task(self, task):
    method start_session (line 81) | def start_session(self):
    method end_session (line 90) | def end_session(self):
    method session (line 97) | def session(self):
    method check_cycle (line 104) | def check_cycle(self):
    method dfs (line 110) | def dfs(self, name, node_states):
    method run (line 122) | def run(self, name):
    method run_helper (line 129) | def run_helper(self, name):
    method needs_to_run (line 138) | def needs_to_run(self, name):
    method create_command_task (line 148) | def create_command_task(self, name, dependencies, func=do_nothing):
    method create_file_task (line 151) | def create_file_task(self, name, dependencies, func):
  function command_task (line 155) | def command_task(workspace: Workspace, name: str, dependencies: List[str]):
  function file_task (line 163) | def file_task(workspace: Workspace, name: str, dependencies: List[str]):

FILE: src/tha4/sampleoutput/general_sample_output_protocol.py
  class ImageType (line 18) | class ImageType(Enum):
  class SampleImageSpec (line 25) | class SampleImageSpec:
    method __init__ (line 26) | def __init__(self, value_func: TensorCachedComputationFunc, image_type...
  class SampleImageSaver (line 31) | class SampleImageSaver:
    method __init__ (line 32) | def __init__(self,
    method save_sample_output_data (line 41) | def save_sample_output_data(self,
    method convert_to_numpy_image (line 94) | def convert_to_numpy_image(self, image: torch.Tensor):
  class GeneralSampleOutputProtocol (line 106) | class GeneralSampleOutputProtocol(SampleOutputProtocol):
    method __init__ (line 107) | def __init__(self,
    method get_examples_per_sample_output (line 120) | def get_examples_per_sample_output(self) -> int:
    method get_random_seed (line 123) | def get_random_seed(self) -> int:
    method get_sample_output_data (line 126) | def get_sample_output_data(self, validation_dataset: Dataset, device: ...
    method save_sample_output_data (line 132) | def save_sample_output_data(self,

FILE: src/tha4/sampleoutput/poser_sampler_output_protocol.py
  class PoserSampleOutputProtocol (line 13) | class PoserSampleOutputProtocol(SampleOutputProtocol):
    method __init__ (line 14) | def __init__(self,
    method get_examples_per_sample_output (line 50) | def get_examples_per_sample_output(self) -> int:
    method get_random_seed (line 53) | def get_random_seed(self) -> int:
    method get_sample_output_data (line 56) | def get_sample_output_data(self, validation_dataset: Dataset, device: ...
    method save_sample_output_data (line 62) | def save_sample_output_data(self,

FILE: src/tha4/sampleoutput/sample_image_creator.py
  class ImageSource (line 15) | class ImageSource(Enum):
  class ImageType (line 20) | class ImageType(Enum):
  class SampleImageSpec (line 27) | class SampleImageSpec:
    method __init__ (line 28) | def __init__(self, image_source: ImageSource, index: int, image_type: ...
  function torch_rgb_to_numpy_image (line 34) | def torch_rgb_to_numpy_image(torch_image: Tensor, min_pixel_value=-1.0, ...
  function torch_rgba_to_numpy_image (line 45) | def torch_rgba_to_numpy_image(torch_image: Tensor, min_pixel_value=-1.0,...
  function torch_grid_change_to_numpy_image (line 57) | def torch_grid_change_to_numpy_image(torch_image, num_channels=3):
  class SampleImageSaver (line 74) | class SampleImageSaver:
    method __init__ (line 75) | def __init__(self,
    method save_sample_output_image (line 86) | def save_sample_output_image(self, batch: List[Tensor], outputs: List[...
    method save_sample_output_data (line 132) | def save_sample_output_data(self,
    method convert_to_numpy_image (line 140) | def convert_to_numpy_image(self, image: torch.Tensor):

FILE: src/tha4/shion/base/dataset/lazy_dataset.py
  class LazyDataset (line 6) | class LazyDataset(Dataset):
    method __init__ (line 7) | def __init__(self, source_func: Callable[[], Dataset]):
    method get_source (line 11) | def get_source(self):
    method __len__ (line 16) | def __len__(self):
    method __getitem__ (line 19) | def __getitem__(self, item):

FILE: src/tha4/shion/base/dataset/lazy_tensor_dataset.py
  class LazyTensorDataset (line 7) | class LazyTensorDataset(Dataset):
    method __init__ (line 8) | def __init__(self, file_name: str):
    method get_dataset (line 12) | def get_dataset(self):
    method __len__ (line 25) | def __len__(self):
    method __getitem__ (line 29) | def __getitem__(self, item):

FILE: src/tha4/shion/base/dataset/png_in_dir_dataset.py
  class PngInDirDataset (line 11) | class PngInDirDataset(Dataset):
    method __init__ (line 12) | def __init__(self, dir: str,
    method get_file_names (line 29) | def get_file_names(self):
    method __len__ (line 36) | def __len__(self):
    method __getitem__ (line 40) | def __getitem__(self, item):

FILE: src/tha4/shion/base/dataset/util.py
  function get_indexed_batch (line 7) | def get_indexed_batch(dataset: Dataset, example_indices: List[int], devi...

FILE: src/tha4/shion/base/dataset/xformed_dataset.py
  class XformedDataset (line 6) | class XformedDataset(Dataset):
    method __init__ (line 7) | def __init__(self, source: Dataset, xform_func: Callable[[Any], Any]):
    method __len__ (line 11) | def __len__(self):
    method __getitem__ (line 14) | def __getitem__(self, item):

FILE: src/tha4/shion/base/image_util.py
  function numpy_srgb_to_linear (line 10) | def numpy_srgb_to_linear(x):
  function numpy_linear_to_srgb (line 15) | def numpy_linear_to_srgb(x):
  function numpy_alpha_devide (line 20) | def numpy_alpha_devide(rgb, a, epsilon=1e-5):
  function torch_srgb_to_linear (line 26) | def torch_srgb_to_linear(x: torch.Tensor):
  function torch_linear_to_srgb (line 31) | def torch_linear_to_srgb(x):
  function numpy_image_linear_to_srgb (line 36) | def numpy_image_linear_to_srgb(image):
  function numpy_image_srgb_to_linear (line 47) | def numpy_image_srgb_to_linear(image):
  function pytorch_rgb_to_numpy_image (line 58) | def pytorch_rgb_to_numpy_image(torch_image: Tensor, min_pixel_value=-1.0...
  function pytorch_rgba_to_numpy_image_greenscreen (line 69) | def pytorch_rgba_to_numpy_image_greenscreen(torch_image: Tensor,
  function pytorch_rgba_to_numpy_image (line 90) | def pytorch_rgba_to_numpy_image(
  function pil_image_has_transparency (line 111) | def pil_image_has_transparency(pil_image):
  function extract_numpy_image_from_PIL_image (line 127) | def extract_numpy_image_from_PIL_image(pil_image, scale=2.0, offset=-1.0,
  function extract_numpy_image_from_PIL_image_with_pytorch_layout (line 152) | def extract_numpy_image_from_PIL_image_with_pytorch_layout(pil_image, sc...
  function extract_numpy_image_from_filelike_with_pytorch_layout (line 165) | def extract_numpy_image_from_filelike_with_pytorch_layout(file, scale=2....
  function extract_numpy_image_from_filelike (line 173) | def extract_numpy_image_from_filelike(file, scale=1.0, offset=0.0,
  function extract_pytorch_image_from_filelike (line 183) | def extract_pytorch_image_from_filelike(file, scale=2.0, offset=-1.0, pr...
  function extract_pytorch_image_from_PIL_image (line 194) | def extract_pytorch_image_from_PIL_image(pil_image, scale=2.0, offset=-1...
  function convert_pytorch_image_to_zero_to_one_numpy_image (line 201) | def convert_pytorch_image_to_zero_to_one_numpy_image(
  function convert_zero_to_one_numpy_image_to_PIL_image (line 211) | def convert_zero_to_one_numpy_image_to_PIL_image(
  function save_numpy_image (line 233) | def save_numpy_image(numpy_image, file_name: str, save_straight_alpha=Tr...
  function resize_PIL_image (line 239) | def resize_PIL_image(pil_image, size=(256, 256)):

FILE: src/tha4/shion/base/loss/computed_scale_loss.py
  class ComputedScaleLoss (line 7) | class ComputedScaleLoss(Loss):
    method __init__ (line 8) | def __init__(self,
    method compute (line 16) | def compute(self, state: ComputationState, log_func: Optional[Callable...

FILE: src/tha4/shion/base/loss/computed_scaled_l2_loss.py
  class ComputedScaledL2Loss (line 7) | class ComputedScaledL2Loss(Loss):
    method __init__ (line 8) | def __init__(self,
    method compute (line 18) | def compute(

FILE: src/tha4/shion/base/loss/l1_loss.py
  class L1Loss (line 9) | class L1Loss(Loss):
    method __init__ (line 10) | def __init__(self,
    method compute (line 18) | def compute(self, state: ComputationState, log_func: Optional[Callable...
  class ListL1Loss (line 27) | class ListL1Loss(Loss):
    method __init__ (line 28) | def __init__(self,
    method compute (line 36) | def compute(self, state: ComputationState, log_func: Optional[Callable...
  class MaskedL1Loss (line 49) | class MaskedL1Loss(Loss):
    method __init__ (line 50) | def __init__(self,
    method compute (line 60) | def compute(self, state: ComputationState, log_func: Optional[Callable...

FILE: src/tha4/shion/base/loss/l2_loss.py
  class L2Loss (line 7) | class L2Loss(Loss):
    method __init__ (line 8) | def __init__(self,
    method compute (line 16) | def compute(

FILE: src/tha4/shion/base/loss/sum_loss.py
  class SumLoss (line 10) | class SumLoss(Loss):
    method __init__ (line 11) | def __init__(self, losses: List[Tuple[str, Loss]]):
    method compute (line 14) | def compute(self,

FILE: src/tha4/shion/base/loss/time_dependently_weighted_loss.py
  class TimeDependentlyWeightedLoss (line 9) | class TimeDependentlyWeightedLoss(Loss):
    method __init__ (line 10) | def __init__(self,
    method compute (line 18) | def compute(self,

FILE: src/tha4/shion/base/module_accumulators.py
  function accumulate_modules (line 10) | def accumulate_modules(new_module: Module, accumulated_module: Module, b...
  class DecayAccumulator (line 23) | class DecayAccumulator(ModuleAccumulator):
    method __init__ (line 24) | def __init__(self, decay: float = 0.999):
    method accumulate (line 27) | def accumulate(self, module: Module, output: Module, examples_seen_so_...

FILE: src/tha4/shion/base/optimizer_factories.py
  class AdamOptimizerFactory (line 9) | class AdamOptimizerFactory(OptimizerFactory):
    method __init__ (line 10) | def __init__(self, betas: Tuple[float, float] = (0.9, 0.999), epsilon:...
    method create (line 16) | def create(self, parameters: Iterable[Parameter]) -> Optimizer:
  class AdamWOptimizerFactory (line 20) | class AdamWOptimizerFactory(OptimizerFactory):
    method __init__ (line 21) | def __init__(self, betas: Tuple[float, float] = (0.9, 0.999), epsilon:...
    method create (line 27) | def create(self, parameters: Iterable[Parameter]) -> Optimizer:
  class SparseAdamOptimizerFactory (line 31) | class SparseAdamOptimizerFactory(OptimizerFactory):
    method __init__ (line 32) | def __init__(self, betas: Tuple[float, float] = (0.9, 0.999), epsilon:...
    method create (line 37) | def create(self, parameters: Iterable[Parameter]) -> Optimizer:
  class RMSpropOptimizerFactory (line 41) | class RMSpropOptimizerFactory(OptimizerFactory):
    method __init__ (line 42) | def __init__(self):
    method create (line 45) | def create(self, parameters: Iterable[Parameter]) -> Optimizer:

FILE: src/tha4/shion/base/protocol/single_network_from_batch_input_computation_protocol.py
  class SingleNetworkBatchInputComputationProtocol (line 9) | class SingleNetworkBatchInputComputationProtocol(CachedComputationProtoc...
    method __init__ (line 10) | def __init__(self,
    method compute_output (line 21) | def compute_output(self, key: str, state: ComputationState) -> Any:

FILE: src/tha4/shion/base/training/single_network.py
  class SingleNetworkTrainingProtocol (line 18) | class SingleNetworkTrainingProtocol(TrainingProtocol):
    method __init__ (line 19) | def __init__(self,
    method get_optimizer_factories (line 36) | def get_optimizer_factories(self) -> Dict[str, OptimizerFactory]:
    method get_checkpoint_examples (line 39) | def get_checkpoint_examples(self) -> List[int]:
    method get_random_seed (line 42) | def get_random_seed(self) -> int:
    method get_batch_size (line 45) | def get_batch_size(self) -> int:
    method get_learning_rate (line 48) | def get_learning_rate(self, examples_seen_so_far: int) -> Dict[str, fl...
    method run_training_iteration (line 51) | def run_training_iteration(
  class SingleNetworkValidationProtocol (line 76) | class SingleNetworkValidationProtocol(ValidationProtocol):
    method __init__ (line 77) | def __init__(
    method get_batch_size (line 87) | def get_batch_size(self, ) -> int:
    method get_examples_per_validation_iteration (line 90) | def get_examples_per_validation_iteration(self) -> int:
    method run_validation_iteration (line 93) | def run_validation_iteration(

FILE: src/tha4/shion/base/training/single_network_with_minibatch.py
  class SingleNetworkWithMinibatchTrainingProtocol (line 18) | class SingleNetworkWithMinibatchTrainingProtocol(TrainingProtocol):
    method __init__ (line 19) | def __init__(self,
    method get_optimizer_factories (line 39) | def get_optimizer_factories(self) -> Dict[str, OptimizerFactory]:
    method get_checkpoint_examples (line 42) | def get_checkpoint_examples(self) -> List[int]:
    method get_random_seed (line 45) | def get_random_seed(self) -> int:
    method get_batch_size (line 48) | def get_batch_size(self) -> int:
    method get_learning_rate (line 51) | def get_learning_rate(self, examples_seen_so_far: int) -> Dict[str, fl...
    method run_training_iteration (line 54) | def run_training_iteration(

FILE: src/tha4/shion/base/training/two_networks_training_protocol.py
  class TwoNetworksWithMinibatchTrainingProtocol (line 14) | class TwoNetworksWithMinibatchTrainingProtocol(TrainingProtocol):
    method __init__ (line 15) | def __init__(self,
    method get_optimizer_factories (line 41) | def get_optimizer_factories(self) -> Dict[str, OptimizerFactory]:
    method get_checkpoint_examples (line 44) | def get_checkpoint_examples(self) -> List[int]:
    method get_random_seed (line 47) | def get_random_seed(self) -> int:
    method get_batch_size (line 50) | def get_batch_size(self) -> int:
    method get_learning_rate (line 53) | def get_learning_rate(self, examples_seen_so_far: int) -> Dict[str, fl...
    method run_training_iteration (line 56) | def run_training_iteration(

FILE: src/tha4/shion/core/cached_computation.py
  class ComputationState (line 9) | class ComputationState:
    method __init__ (line 10) | def __init__(self,
  function create_get_item_func (line 27) | def create_get_item_func(func: CachedComputationFunc, index):
  function create_batch_element_func (line 35) | def create_batch_element_func(index: int) -> TensorCachedComputationFunc:
  class CachedComputationProtocol (line 42) | class CachedComputationProtocol(ABC):
    method get_output (line 43) | def get_output(self, key: str, state: ComputationState) -> Any:
    method compute_output (line 52) | def compute_output(self, key: str, state: ComputationState) -> Any:
    method get_output_func (line 55) | def get_output_func(self, key: str) -> CachedComputationFunc:
  class ComposableCachedComputationProtocol (line 65) | class ComposableCachedComputationProtocol(CachedComputationProtocol):
    method __init__ (line 66) | def __init__(self, computation_steps: Optional[Dict[str, ComposableCac...
    method compute_output (line 71) | def compute_output(self, key: str, state: ComputationState) -> Any:
  function batch_indexing_func (line 78) | def batch_indexing_func(index: int):
  function proxy_func (line 85) | def proxy_func(key: str):
  function output_array_indexing_func (line 92) | def output_array_indexing_func(key: str, index: int):
  function add_step (line 99) | def add_step(step_dict: Dict[str, ComposableCachedComputationStep], name...
  function zeros_like_func (line 107) | def zeros_like_func(key: str):

FILE: src/tha4/shion/core/load_save.py
  function torch_save (line 6) | def torch_save(content, file_name):
  function torch_load (line 12) | def torch_load(file_name):

FILE: src/tha4/shion/core/loss.py
  class Loss (line 9) | class Loss(ABC):
    method compute (line 11) | def compute(

FILE: src/tha4/shion/core/module_accumulator.py
  class ModuleAccumulator (line 7) | class ModuleAccumulator(ABC):
    method accumulate (line 9) | def accumulate(self, module: Module, output: Module, examples_seen_so_...

FILE: src/tha4/shion/core/module_factory.py
  class ModuleFactory (line 6) | class ModuleFactory(ABC):
    method create (line 8) | def create(self) -> Module:

FILE: src/tha4/shion/core/optimizer_factory.py
  class OptimizerFactory (line 7) | class OptimizerFactory(ABC):
    method create (line 9) | def create(self, parameters: Iterable[Parameter]):

FILE: src/tha4/shion/core/training/distrib/device_mapper.py
  class SimpleCudaDeviceMapper (line 6) | class SimpleCudaDeviceMapper:
    method __call__ (line 7) | def __call__(self, rank, local_rank):
  class UserSpecifiedLocalRankToDeviceMapper (line 11) | class UserSpecifiedLocalRankToDeviceMapper:
    method __init__ (line 12) | def __init__(self, device_map: Dict[int, torch.device]):
    method __call__ (line 15) | def __call__(self, rank, local_rank):

FILE: src/tha4/shion/core/training/distrib/distributed_trainer.py
  class DistributedTrainer (line 31) | class DistributedTrainer:
    method __init__ (line 32) | def __init__(self,
    method get_sample_output_data_file_name (line 82) | def get_sample_output_data_file_name(self):
    method save_sample_output_data (line 85) | def save_sample_output_data(self, rank: int, device: torch.device):
    method load_sample_output_data (line 97) | def load_sample_output_data(self, rank: int, device: torch.device):
    method get_snapshot_prefix (line 104) | def get_snapshot_prefix(self) -> str:
    method can_load_training_state (line 107) | def can_load_training_state(self, prefix: str, world_size: int) -> bool:
    method load_training_state (line 115) | def load_training_state(self, prefix, rank: int, local_rank: int, devi...
    method checkpoint_prefix (line 126) | def checkpoint_prefix(prefix: str, checkpoint_index: int) -> str:
    method get_checkpoint_prefix (line 129) | def get_checkpoint_prefix(self, checkpoint_index) -> str:
    method get_initial_training_state (line 132) | def get_initial_training_state(self, rank: int, local_rank: int, devic...
    method load_previous_training_state (line 145) | def load_previous_training_state(self,
    method get_log_dir (line 171) | def get_log_dir(self):
    method get_summary_writer (line 177) | def get_summary_writer(self, rank: int) -> Optional[SummaryWriter]:
    method get_effective_training_epoch_size (line 184) | def get_effective_training_epoch_size(self, world_size: int):
    method get_training_epoch_index (line 191) | def get_training_epoch_index(self, examples_seen_so_far: int, world_si...
    method get_next_training_batch (line 196) | def get_next_training_batch(self, examples_seen_so_far: int, world_siz...
    method get_next_checkpoint_num_examples (line 226) | def get_next_checkpoint_num_examples(self, examples_seen_so_far) -> int:
    method get_next_snapshot_num_examples (line 232) | def get_next_snapshot_num_examples(self, examples_seen_so_far) -> int:
    method get_next_validation_num_examples (line 235) | def get_next_validation_num_examples(self, examples_seen_so_far) -> int:
    method get_next_sample_output_num_examples (line 241) | def get_next_sample_output_num_examples(self, examples_seen_so_far) ->...
    method get_next_num_examples (line 247) | def get_next_num_examples(self, examples_seen_so_far) -> Dict[str, int]:
    method get_next_validation_batch (line 255) | def get_next_validation_batch(self, device: torch.device):
    method get_checkpoint_index_to_save (line 274) | def get_checkpoint_index_to_save(self, examples_seen_so_far: int) -> int:
    method barrier (line 281) | def barrier(self, local_rank: int):
    method train (line 287) | def train(self,
    method get_default_arg_parser (line 392) | def get_default_arg_parser() -> argparse.ArgumentParser:
    method run_with_args (line 398) | def run_with_args(trainer_factory: Callable[[int, str], 'DistributedTr...
    method run (line 411) | def run(trainer_factory: Callable[[int, str], 'DistributedTrainer'],

FILE: src/tha4/shion/core/training/distrib/distributed_training_states.py
  class DistributedTrainingState (line 18) | class DistributedTrainingState:
    method __init__ (line 19) | def __init__(self,
    method get_examples_seen_so_far_file_name (line 30) | def get_examples_seen_so_far_file_name(prefix) -> str:
    method get_module_file_name (line 34) | def get_module_file_name(prefix, module_name) -> str:
    method get_accumulated_module_file_name (line 38) | def get_accumulated_module_file_name(prefix, module_name) -> str:
    method get_optimizer_file_name (line 42) | def get_optimizer_file_name(prefix, module_name) -> str:
    method get_rng_state_file_name (line 46) | def get_rng_state_file_name(prefix, rank: int):
    method mkdir (line 49) | def mkdir(self, prefix: str):
    method save_data (line 52) | def save_data(self, prefix: str, rank: int):
    method save (line 83) | def save(self, prefix: str, rank: int, barrier_func: Callable[[], None]):
    method get_examples_seen_so_far (line 91) | def get_examples_seen_so_far(prefix: str) -> int:
    method load (line 97) | def load(
    method new (line 155) | def new(module_factories: Dict[str, ModuleFactory],
    method can_load (line 201) | def can_load(prefix: str,

FILE: src/tha4/shion/core/training/distrib/distributed_training_tasks.py
  function get_torchrun_executable (line 11) | def get_torchrun_executable():
  function run_distributed_training_script (line 15) | def run_distributed_training_script(
  class RdzvConfig (line 33) | class RdzvConfig:
    method __init__ (line 34) | def __init__(self, id: int, port: int):
  function run_standalone_distributed_training_script (line 39) | def run_standalone_distributed_training_script(
  function define_distributed_training_tasks (line 60) | def define_distributed_training_tasks(
  function define_standalone_distributed_training_tasks (line 83) | def define_standalone_distributed_training_tasks(

FILE: src/tha4/shion/core/training/sample_output_protocol.py
  class SampleOutputProtocol (line 9) | class SampleOutputProtocol(ABC):
    method get_examples_per_sample_output (line 11) | def get_examples_per_sample_output(self) -> int:
    method get_random_seed (line 15) | def get_random_seed(self) -> int:
    method get_sample_output_data (line 19) | def get_sample_output_data(self, validation_dataset: Dataset, device: ...
    method save_sample_output_data (line 23) | def save_sample_output_data(
  class AbstractSampleOutputProtocol (line 34) | class AbstractSampleOutputProtocol(SampleOutputProtocol, ABC):
    method __init__ (line 35) | def __init__(self, examples_per_sample_output: int, random_seed: int):
    method get_examples_per_sample_output (line 39) | def get_examples_per_sample_output(self) -> int:
    method get_random_seed (line 42) | def get_random_seed(self) -> int:

FILE: src/tha4/shion/core/training/single/training_states.py
  class TrainingState (line 17) | class TrainingState:
    method __init__ (line 18) | def __init__(self,
    method get_examples_seen_so_far_file_name (line 29) | def get_examples_seen_so_far_file_name(prefix) -> str:
    method get_module_file_name (line 33) | def get_module_file_name(prefix, module_name) -> str:
    method get_accumulated_module_file_name (line 37) | def get_accumulated_module_file_name(prefix, module_name) -> str:
    method get_optimizer_file_name (line 41) | def get_optimizer_file_name(prefix, module_name) -> str:
    method get_rng_state_file_name (line 45) | def get_rng_state_file_name(prefix):
    method save (line 48) | def save(self, prefix):
    method get_examples_seen_so_far (line 71) | def get_examples_seen_so_far(prefix: str) -> int:
    method load (line 77) | def load(prefix: str,
    method new (line 126) | def new(module_factories: Dict[str, ModuleFactory],
    method can_load (line 163) | def can_load(prefix: str,

FILE: src/tha4/shion/core/training/single/training_tasks.py
  class TrainingTasks (line 27) | class TrainingTasks:
    method __init__ (line 28) | def __init__(
    method get_sample_output_data_file_name (line 120) | def get_sample_output_data_file_name(self):
    method save_sample_output_data (line 123) | def save_sample_output_data(self):
    method get_module_file_name (line 132) | def get_module_file_name(self, checkpoint_index, module_name):
    method get_last_module_file_name (line 135) | def get_last_module_file_name(self, module_name):
    method get_log_dir (line 138) | def get_log_dir(self):
    method get_summary_writer (line 144) | def get_summary_writer(self) -> SummaryWriter:
    method get_train_command_name (line 149) | def get_train_command_name(self) -> str:
    method get_snapshot_prefix (line 152) | def get_snapshot_prefix(self) -> str:
    method get_checkpoint_prefix (line 155) | def get_checkpoint_prefix(self, checkpoint_index) -> str:
    method can_load_training_state (line 158) | def can_load_training_state(self, prefix) -> bool:
    method load_training_state (line 165) | def load_training_state(self, prefix) -> TrainingState:
    method get_initial_training_state (line 173) | def get_initial_training_state(self) -> TrainingState:
    method load_previous_training_state (line 184) | def load_previous_training_state(self, target_checkpoint_examples: int...
    method get_next_checkpoint_num_examples (line 200) | def get_next_checkpoint_num_examples(self, examples_seen_so_far) -> int:
    method get_next_snapshot_num_examples (line 206) | def get_next_snapshot_num_examples(self, examples_seen_so_far) -> int:
    method get_next_validation_num_examples (line 209) | def get_next_validation_num_examples(self, examples_seen_so_far) -> int:
    method get_next_sample_output_num_examples (line 215) | def get_next_sample_output_num_examples(self, examples_seen_so_far) ->...
    method get_next_num_examples (line 221) | def get_next_num_examples(self, examples_seen_so_far) -> Dict[str, int]:
    method get_checkpoint_index_to_save (line 229) | def get_checkpoint_index_to_save(self, examples_seen_so_far: int) -> int:
    method get_next_training_batch (line 236) | def get_next_training_batch(self):
    method get_next_validation_batch (line 253) | def get_next_validation_batch(self):
    method get_checkpoint_index (line 272) | def get_checkpoint_index(self, target_checkpoint_examples: int):
    method train (line 275) | def train(self, target_checkpoint_examples: Optional[int] = None):

FILE: src/tha4/shion/core/training/swarm/swarm_training_tasks.py
  function define_standalone_swarm_training_tasks (line 10) | def define_standalone_swarm_training_tasks(

FILE: src/tha4/shion/core/training/swarm/swarm_unit_trainer.py
  class SwarmUnitTrainer (line 26) | class SwarmUnitTrainer:
    method __init__ (line 27) | def __init__(self,
    method get_sample_output_data_file_name (line 75) | def get_sample_output_data_file_name(self):
    method save_sample_output_data (line 78) | def save_sample_output_data(self, device: torch.device):
    method load_sample_output_data (line 88) | def load_sample_output_data(self, device: torch.device):
    method get_snapshot_prefix (line 92) | def get_snapshot_prefix(self) -> str:
    method can_load_training_state (line 95) | def can_load_training_state(self, prefix: str) -> bool:
    method load_training_state (line 102) | def load_training_state(self, prefix, device: torch.device) -> Trainin...
    method checkpoint_prefix (line 111) | def checkpoint_prefix(prefix: str, checkpoint_index: int) -> str:
    method get_checkpoint_prefix (line 114) | def get_checkpoint_prefix(self, checkpoint_index) -> str:
    method get_initial_training_state (line 117) | def get_initial_training_state(self, device: torch.device) -> Training...
    method load_previous_training_state (line 128) | def load_previous_training_state(self,
    method get_log_dir (line 151) | def get_log_dir(self):
    method get_summary_writer (line 157) | def get_summary_writer(self) -> Optional[SummaryWriter]:
    method get_next_training_batch (line 162) | def get_next_training_batch(self, device: torch.device):
    method get_next_checkpoint_num_examples (line 179) | def get_next_checkpoint_num_examples(self, examples_seen_so_far) -> int:
    method get_next_snapshot_num_examples (line 185) | def get_next_snapshot_num_examples(self, examples_seen_so_far) -> int:
    method get_next_validation_num_examples (line 188) | def get_next_validation_num_examples(self, examples_seen_so_far) -> int:
    method get_next_sample_output_num_examples (line 194) | def get_next_sample_output_num_examples(self, examples_seen_so_far) ->...
    method get_next_num_examples (line 200) | def get_next_num_examples(self, examples_seen_so_far) -> Dict[str, int]:
    method get_next_validation_batch (line 208) | def get_next_validation_batch(self, device: torch.device):
    method get_checkpoint_index_to_save (line 227) | def get_checkpoint_index_to_save(self, examples_seen_so_far: int) -> int:
    method train (line 234) | def train(self,
    method run (line 332) | def run(trainer_factory: Dict[int, Callable[[], 'SwarmUnitTrainer']],

FILE: src/tha4/shion/core/training/training_protocol.py
  class TrainingProtocol (line 12) | class TrainingProtocol(ABC):
    method get_optimizer_factories (line 14) | def get_optimizer_factories(self) -> Dict[str, OptimizerFactory]:
    method get_checkpoint_examples (line 18) | def get_checkpoint_examples(self) -> List[int]:
    method get_random_seed (line 22) | def get_random_seed(self) -> int:
    method get_batch_size (line 26) | def get_batch_size(self) -> int:
    method get_learning_rate (line 30) | def get_learning_rate(self, examples_seen_so_far: int) -> Dict[str, fl...
    method run_training_iteration (line 34) | def run_training_iteration(
  class AbstractTrainingProtocol (line 47) | class AbstractTrainingProtocol(TrainingProtocol, ABC):
    method __init__ (line 48) | def __init__(self,
    method get_optimizer_factories (line 60) | def get_optimizer_factories(self) -> Dict[str, OptimizerFactory]:
    method get_checkpoint_examples (line 63) | def get_checkpoint_examples(self) -> List[int]:
    method get_random_seed (line 66) | def get_random_seed(self) -> int:
    method get_batch_size (line 69) | def get_batch_size(self) -> int:
    method get_learning_rate (line 72) | def get_learning_rate(self, examples_seen_so_far: int) -> Dict[str, fl...

FILE: src/tha4/shion/core/training/util.py
  function optimizer_to_device (line 8) | def optimizer_to_device(optim: Optimizer, device: torch.device):
  function zero_module (line 15) | def zero_module(module: Module):
  function get_least_greater_multiple (line 21) | def get_least_greater_multiple(x: int, m: int) -> int:
  function create_log_func (line 32) | def create_log_func(summary_writer, prefix: str, examples_seen_so_far: i...
  function set_learning_rate (line 39) | def set_learning_rate(module, lr):

FILE: src/tha4/shion/core/training/validation_protocol.py
  class ValidationProtocol (line 10) | class ValidationProtocol(ABC):
    method get_batch_size (line 12) | def get_batch_size(self) -> int:
    method get_examples_per_validation_iteration (line 16) | def get_examples_per_validation_iteration(self) -> int:
    method run_validation_iteration (line 20) | def run_validation_iteration(
  class AbstractValidationProtocol (line 32) | class AbstractValidationProtocol(ValidationProtocol, ABC):
    method __init__ (line 33) | def __init__(self,
    method get_batch_size (line 39) | def get_batch_size(self) -> int:
    method get_examples_per_validation_iteration (line 42) | def get_examples_per_validation_iteration(self) -> int:

FILE: src/tha4/shion/nn00/block_args.py
  class BlockArgs (line 12) | class BlockArgs:
    method __init__ (line 13) | def __init__(

FILE: src/tha4/shion/nn00/conv.py
  function create_conv7 (line 9) | def create_conv7(
  function create_conv3 (line 19) | def create_conv3(in_channels: int,
  function create_conv1 (line 28) | def create_conv1(
  function create_conv7_block (line 37) | def create_conv7_block(
  function create_conv3_block (line 53) | def create_conv3_block(
  function create_downsample_block (line 69) | def create_downsample_block(
  function create_upsample_block (line 91) | def create_upsample_block(

FILE: src/tha4/shion/nn00/initialization_funcs.py
  class HeInitialization (line 9) | class HeInitialization:
    method __init__ (line 10) | def __init__(self, a: int = 0, mode: str = 'fan_in', nonlinearity: str...
    method __call__ (line 15) | def __call__(self, module: Module) -> Module:
  class NormalInitialization (line 21) | class NormalInitialization:
    method __init__ (line 22) | def __init__(self, mean: float = 0.0, std: float = 1.0):
    method __call__ (line 26) | def __call__(self, module: Module) -> Module:
  class XavierInitialization (line 32) | class XavierInitialization:
    method __init__ (line 33) | def __init__(self, gain: float = 1.0):
    method __call__ (line 36) | def __call__(self, module: Module) -> Module:
  class ZeroInitialization (line 42) | class ZeroInitialization:
    method __call__ (line 43) | def __call__(self, module: Module) -> Module:
  class NoInitialization (line 49) | class NoInitialization:
    method __call__ (line 50) | def __call__(self, module: Module) -> Module:
  function resolve_initialization_func (line 54) | def resolve_initialization_func(initialization: Optional[Callable[[Modul...

FILE: src/tha4/shion/nn00/linear_module_args.py
  class LinearModuleArgs (line 9) | class LinearModuleArgs:
    method __init__ (line 10) | def __init__(
    method wrap_linear_module (line 17) | def wrap_linear_module(self, module: Module) -> Module:
  function wrap_linear_module (line 24) | def wrap_linear_module(module: Module, linear_module_args: Optional[Line...

FILE: src/tha4/shion/nn00/nonlinearity_factories.py
  class ReLUFactory (line 10) | class ReLUFactory(ModuleFactory):
    method __init__ (line 11) | def __init__(self, inplace: bool = False):
    method create (line 14) | def create(self) -> Module:
  class LeakyReLUFactory (line 18) | class LeakyReLUFactory(ModuleFactory):
    method __init__ (line 19) | def __init__(self, inplace: bool = False, negative_slope: float = 1e-2):
    method create (line 23) | def create(self) -> Module:
  class ELUFactory (line 27) | class ELUFactory(ModuleFactory):
    method __init__ (line 28) | def __init__(self, inplace: bool = False, alpha: float = 1.0):
    method create (line 32) | def create(self) -> Module:
  class ReLU6Factory (line 36) | class ReLU6Factory(ModuleFactory):
    method __init__ (line 37) | def __init__(self, inplace: bool = False):
    method create (line 40) | def create(self) -> Module:
  class SiLUFactory (line 44) | class SiLUFactory(ModuleFactory):
    method __init__ (line 45) | def __init__(self, inplace: bool = False):
    method create (line 48) | def create(self) -> Module:
  class HardswishFactory (line 52) | class HardswishFactory(ModuleFactory):
    method __init__ (line 53) | def __init__(self, inplace: bool = False):
    method create (line 56) | def create(self) -> Module:
  class TanhFactory (line 60) | class TanhFactory(ModuleFactory):
    method create (line 61) | def create(self) -> Module:
  class SigmoidFactory (line 65) | class SigmoidFactory(ModuleFactory):
    method create (line 66) | def create(self) -> Module:
  class Swish (line 70) | class Swish(Module):
    method __init__ (line 71) | def __init__(self):
    method forward (line 74) | def forward(self, x: Tensor):
  class SwishFactory (line 78) | class SwishFactory(ModuleFactory):
    method create (line 79) | def create(self) -> Module:
  function resolve_nonlinearity_factory (line 83) | def resolve_nonlinearity_factory(nonlinearity_factory: Optional[ModuleFa...

FILE: src/tha4/shion/nn00/normalization_layer_factories.py
  class Bias2d (line 12) | class Bias2d(Module):
    method __init__ (line 13) | def __init__(self, num_features: int):
    method forward (line 18) | def forward(self, x):
  class NoNorm2dFactory (line 22) | class NoNorm2dFactory(NormalizationLayerFactory):
    method __init__ (line 23) | def __init__(self):
    method create (line 26) | def create(self, num_features: int, affine: bool = True) -> Module:
  class BatchNorm2dFactory (line 33) | class BatchNorm2dFactory(NormalizationLayerFactory):
    method __init__ (line 34) | def __init__(self,
    method get_weight_mean (line 43) | def get_weight_mean(self):
    method get_weight_std (line 49) | def get_weight_std(self):
    method create (line 55) | def create(self, num_features: int, affine: bool = True) -> Module:
  class InstanceNorm2dFactory (line 65) | class InstanceNorm2dFactory(NormalizationLayerFactory):
    method __init__ (line 66) | def __init__(self):
    method create (line 69) | def create(self, num_features: int, affine: bool = True) -> Module:
  class LayerNorm2d (line 73) | class LayerNorm2d(Module):
    method __init__ (line 74) | def __init__(self, channels: int, affine: bool = True):
    method forward (line 83) | def forward(self, x):
  class LayerNorm2dFactory (line 89) | class LayerNorm2dFactory(NormalizationLayerFactory):
    method __init__ (line 90) | def __init__(self):
    method create (line 93) | def create(self, num_features: int, affine: bool = True) -> Module:
  class GroupNormFactory (line 97) | class GroupNormFactory(NormalizationLayerFactory):
    method __init__ (line 98) | def __init__(self, num_groups: int, eps=1e-6):
    method create (line 103) | def create(self, num_features: int, affine: bool = True) -> Module:
  function resolve_normalization_layer_factory (line 107) | def resolve_normalization_layer_factory(factory: Optional['Normalization...

FILE: src/tha4/shion/nn00/normalization_layer_factory.py
  class NormalizationLayerFactory (line 6) | class NormalizationLayerFactory(ABC):
    method __init__ (line 7) | def __init__(self):
    method create (line 11) | def create(self, num_features: int, affine: bool = True) -> Module:

FILE: src/tha4/shion/nn00/pass_through.py
  class PassThrough (line 4) | class PassThrough(Module):
    method __init__ (line 5) | def __init__(self):
    method forward (line 8) | def forward(self, x):

FILE: src/tha4/shion/nn00/resnet_block.py
  class ResnetBlock (line 10) | class ResnetBlock(Module):
    method __init__ (line 11) | def __init__(self,
    method forward (line 51) | def forward(self, x):