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from __future__ import annotations | |
import dataclasses | |
import inspect | |
import os | |
from typing import Optional, Any | |
from fastapi import FastAPI | |
from gradio import Blocks | |
from modules import errors, timer, extensions, shared, util | |
def report_exception(c, job): | |
errors.report(f"Error executing callback {job} for {c.script}", exc_info=True) | |
class ImageSaveParams: | |
def __init__(self, image, p, filename, pnginfo): | |
self.image = image | |
"""the PIL image itself""" | |
self.p = p | |
"""p object with processing parameters; either StableDiffusionProcessing or an object with same fields""" | |
self.filename = filename | |
"""name of file that the image would be saved to""" | |
self.pnginfo = pnginfo | |
"""dictionary with parameters for image's PNG info data; infotext will have the key 'parameters'""" | |
class ExtraNoiseParams: | |
def __init__(self, noise, x, xi): | |
self.noise = noise | |
"""Random noise generated by the seed""" | |
self.x = x | |
"""Latent representation of the image""" | |
self.xi = xi | |
"""Noisy latent representation of the image""" | |
class CFGDenoiserParams: | |
def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, text_cond, text_uncond, denoiser=None): | |
self.x = x | |
"""Latent image representation in the process of being denoised""" | |
self.image_cond = image_cond | |
"""Conditioning image""" | |
self.sigma = sigma | |
"""Current sigma noise step value""" | |
self.sampling_step = sampling_step | |
"""Current Sampling step number""" | |
self.total_sampling_steps = total_sampling_steps | |
"""Total number of sampling steps planned""" | |
self.text_cond = text_cond | |
""" Encoder hidden states of text conditioning from prompt""" | |
self.text_uncond = text_uncond | |
""" Encoder hidden states of text conditioning from negative prompt""" | |
self.denoiser = denoiser | |
"""Current CFGDenoiser object with processing parameters""" | |
class CFGDenoisedParams: | |
def __init__(self, x, sampling_step, total_sampling_steps, inner_model): | |
self.x = x | |
"""Latent image representation in the process of being denoised""" | |
self.sampling_step = sampling_step | |
"""Current Sampling step number""" | |
self.total_sampling_steps = total_sampling_steps | |
"""Total number of sampling steps planned""" | |
self.inner_model = inner_model | |
"""Inner model reference used for denoising""" | |
class AfterCFGCallbackParams: | |
def __init__(self, x, sampling_step, total_sampling_steps): | |
self.x = x | |
"""Latent image representation in the process of being denoised""" | |
self.sampling_step = sampling_step | |
"""Current Sampling step number""" | |
self.total_sampling_steps = total_sampling_steps | |
"""Total number of sampling steps planned""" | |
class UiTrainTabParams: | |
def __init__(self, txt2img_preview_params): | |
self.txt2img_preview_params = txt2img_preview_params | |
class ImageGridLoopParams: | |
def __init__(self, imgs, cols, rows): | |
self.imgs = imgs | |
self.cols = cols | |
self.rows = rows | |
class BeforeTokenCounterParams: | |
prompt: str | |
steps: int | |
styles: list | |
is_positive: bool = True | |
class ScriptCallback: | |
script: str | |
callback: any | |
name: str = "unnamed" | |
def add_callback(callbacks, fun, *, name=None, category='unknown', filename=None): | |
if filename is None: | |
stack = [x for x in inspect.stack() if x.filename != __file__] | |
filename = stack[0].filename if stack else 'unknown file' | |
extension = extensions.find_extension(filename) | |
extension_name = extension.canonical_name if extension else 'base' | |
callback_name = f"{extension_name}/{os.path.basename(filename)}/{category}" | |
if name is not None: | |
callback_name += f'/{name}' | |
unique_callback_name = callback_name | |
for index in range(1000): | |
existing = any(x.name == unique_callback_name for x in callbacks) | |
if not existing: | |
break | |
unique_callback_name = f'{callback_name}-{index+1}' | |
callbacks.append(ScriptCallback(filename, fun, unique_callback_name)) | |
def sort_callbacks(category, unordered_callbacks, *, enable_user_sort=True): | |
callbacks = unordered_callbacks.copy() | |
callback_lookup = {x.name: x for x in callbacks} | |
dependencies = {} | |
order_instructions = {} | |
for extension in extensions.extensions: | |
for order_instruction in extension.metadata.list_callback_order_instructions(): | |
if order_instruction.name in callback_lookup: | |
if order_instruction.name not in order_instructions: | |
order_instructions[order_instruction.name] = [] | |
order_instructions[order_instruction.name].append(order_instruction) | |
if order_instructions: | |
for callback in callbacks: | |
dependencies[callback.name] = [] | |
for callback in callbacks: | |
for order_instruction in order_instructions.get(callback.name, []): | |
for after in order_instruction.after: | |
if after not in callback_lookup: | |
continue | |
dependencies[callback.name].append(after) | |
for before in order_instruction.before: | |
if before not in callback_lookup: | |
continue | |
dependencies[before].append(callback.name) | |
sorted_names = util.topological_sort(dependencies) | |
callbacks = [callback_lookup[x] for x in sorted_names] | |
if enable_user_sort: | |
for name in reversed(getattr(shared.opts, 'prioritized_callbacks_' + category, [])): | |
index = next((i for i, callback in enumerate(callbacks) if callback.name == name), None) | |
if index is not None: | |
callbacks.insert(0, callbacks.pop(index)) | |
return callbacks | |
def ordered_callbacks(category, unordered_callbacks=None, *, enable_user_sort=True): | |
if unordered_callbacks is None: | |
unordered_callbacks = callback_map.get('callbacks_' + category, []) | |
if not enable_user_sort: | |
return sort_callbacks(category, unordered_callbacks, enable_user_sort=False) | |
callbacks = ordered_callbacks_map.get(category) | |
if callbacks is not None and len(callbacks) == len(unordered_callbacks): | |
return callbacks | |
callbacks = sort_callbacks(category, unordered_callbacks) | |
ordered_callbacks_map[category] = callbacks | |
return callbacks | |
def enumerate_callbacks(): | |
for category, callbacks in callback_map.items(): | |
if category.startswith('callbacks_'): | |
category = category[10:] | |
yield category, callbacks | |
callback_map = dict( | |
callbacks_app_started=[], | |
callbacks_model_loaded=[], | |
callbacks_ui_tabs=[], | |
callbacks_ui_train_tabs=[], | |
callbacks_ui_settings=[], | |
callbacks_before_image_saved=[], | |
callbacks_image_saved=[], | |
callbacks_extra_noise=[], | |
callbacks_cfg_denoiser=[], | |
callbacks_cfg_denoised=[], | |
callbacks_cfg_after_cfg=[], | |
callbacks_before_component=[], | |
callbacks_after_component=[], | |
callbacks_image_grid=[], | |
callbacks_infotext_pasted=[], | |
callbacks_script_unloaded=[], | |
callbacks_before_ui=[], | |
callbacks_on_reload=[], | |
callbacks_list_optimizers=[], | |
callbacks_list_unets=[], | |
callbacks_before_token_counter=[], | |
) | |
ordered_callbacks_map = {} | |
def clear_callbacks(): | |
for callback_list in callback_map.values(): | |
callback_list.clear() | |
ordered_callbacks_map.clear() | |
def app_started_callback(demo: Optional[Blocks], app: FastAPI): | |
for c in ordered_callbacks('app_started'): | |
try: | |
c.callback(demo, app) | |
timer.startup_timer.record(os.path.basename(c.script)) | |
except Exception: | |
report_exception(c, 'app_started_callback') | |
def app_reload_callback(): | |
for c in ordered_callbacks('on_reload'): | |
try: | |
c.callback() | |
except Exception: | |
report_exception(c, 'callbacks_on_reload') | |
def model_loaded_callback(sd_model): | |
for c in ordered_callbacks('model_loaded'): | |
try: | |
c.callback(sd_model) | |
except Exception: | |
report_exception(c, 'model_loaded_callback') | |
def ui_tabs_callback(): | |
res = [] | |
for c in ordered_callbacks('ui_tabs'): | |
try: | |
res += c.callback() or [] | |
except Exception: | |
report_exception(c, 'ui_tabs_callback') | |
return res | |
def ui_train_tabs_callback(params: UiTrainTabParams): | |
for c in ordered_callbacks('ui_train_tabs'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'callbacks_ui_train_tabs') | |
def ui_settings_callback(): | |
for c in ordered_callbacks('ui_settings'): | |
try: | |
c.callback() | |
except Exception: | |
report_exception(c, 'ui_settings_callback') | |
def before_image_saved_callback(params: ImageSaveParams): | |
for c in ordered_callbacks('before_image_saved'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'before_image_saved_callback') | |
def image_saved_callback(params: ImageSaveParams): | |
for c in ordered_callbacks('image_saved'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'image_saved_callback') | |
def extra_noise_callback(params: ExtraNoiseParams): | |
for c in ordered_callbacks('extra_noise'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'callbacks_extra_noise') | |
def cfg_denoiser_callback(params: CFGDenoiserParams): | |
for c in ordered_callbacks('cfg_denoiser'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'cfg_denoiser_callback') | |
def cfg_denoised_callback(params: CFGDenoisedParams): | |
for c in ordered_callbacks('cfg_denoised'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'cfg_denoised_callback') | |
def cfg_after_cfg_callback(params: AfterCFGCallbackParams): | |
for c in ordered_callbacks('cfg_after_cfg'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'cfg_after_cfg_callback') | |
def before_component_callback(component, **kwargs): | |
for c in ordered_callbacks('before_component'): | |
try: | |
c.callback(component, **kwargs) | |
except Exception: | |
report_exception(c, 'before_component_callback') | |
def after_component_callback(component, **kwargs): | |
for c in ordered_callbacks('after_component'): | |
try: | |
c.callback(component, **kwargs) | |
except Exception: | |
report_exception(c, 'after_component_callback') | |
def image_grid_callback(params: ImageGridLoopParams): | |
for c in ordered_callbacks('image_grid'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'image_grid') | |
def infotext_pasted_callback(infotext: str, params: dict[str, Any]): | |
for c in ordered_callbacks('infotext_pasted'): | |
try: | |
c.callback(infotext, params) | |
except Exception: | |
report_exception(c, 'infotext_pasted') | |
def script_unloaded_callback(): | |
for c in reversed(ordered_callbacks('script_unloaded')): | |
try: | |
c.callback() | |
except Exception: | |
report_exception(c, 'script_unloaded') | |
def before_ui_callback(): | |
for c in reversed(ordered_callbacks('before_ui')): | |
try: | |
c.callback() | |
except Exception: | |
report_exception(c, 'before_ui') | |
def list_optimizers_callback(): | |
res = [] | |
for c in ordered_callbacks('list_optimizers'): | |
try: | |
c.callback(res) | |
except Exception: | |
report_exception(c, 'list_optimizers') | |
return res | |
def list_unets_callback(): | |
res = [] | |
for c in ordered_callbacks('list_unets'): | |
try: | |
c.callback(res) | |
except Exception: | |
report_exception(c, 'list_unets') | |
return res | |
def before_token_counter_callback(params: BeforeTokenCounterParams): | |
for c in ordered_callbacks('before_token_counter'): | |
try: | |
c.callback(params) | |
except Exception: | |
report_exception(c, 'before_token_counter') | |
def remove_current_script_callbacks(): | |
stack = [x for x in inspect.stack() if x.filename != __file__] | |
filename = stack[0].filename if stack else 'unknown file' | |
if filename == 'unknown file': | |
return | |
for callback_list in callback_map.values(): | |
for callback_to_remove in [cb for cb in callback_list if cb.script == filename]: | |
callback_list.remove(callback_to_remove) | |
for ordered_callbacks_list in ordered_callbacks_map.values(): | |
for callback_to_remove in [cb for cb in ordered_callbacks_list if cb.script == filename]: | |
ordered_callbacks_list.remove(callback_to_remove) | |
def remove_callbacks_for_function(callback_func): | |
for callback_list in callback_map.values(): | |
for callback_to_remove in [cb for cb in callback_list if cb.callback == callback_func]: | |
callback_list.remove(callback_to_remove) | |
for ordered_callback_list in ordered_callbacks_map.values(): | |
for callback_to_remove in [cb for cb in ordered_callback_list if cb.callback == callback_func]: | |
ordered_callback_list.remove(callback_to_remove) | |
def on_app_started(callback, *, name=None): | |
"""register a function to be called when the webui started, the gradio `Block` component and | |
fastapi `FastAPI` object are passed as the arguments""" | |
add_callback(callback_map['callbacks_app_started'], callback, name=name, category='app_started') | |
def on_before_reload(callback, *, name=None): | |
"""register a function to be called just before the server reloads.""" | |
add_callback(callback_map['callbacks_on_reload'], callback, name=name, category='on_reload') | |
def on_model_loaded(callback, *, name=None): | |
"""register a function to be called when the stable diffusion model is created; the model is | |
passed as an argument; this function is also called when the script is reloaded. """ | |
add_callback(callback_map['callbacks_model_loaded'], callback, name=name, category='model_loaded') | |
def on_ui_tabs(callback, *, name=None): | |
"""register a function to be called when the UI is creating new tabs. | |
The function must either return a None, which means no new tabs to be added, or a list, where | |
each element is a tuple: | |
(gradio_component, title, elem_id) | |
gradio_component is a gradio component to be used for contents of the tab (usually gr.Blocks) | |
title is tab text displayed to user in the UI | |
elem_id is HTML id for the tab | |
""" | |
add_callback(callback_map['callbacks_ui_tabs'], callback, name=name, category='ui_tabs') | |
def on_ui_train_tabs(callback, *, name=None): | |
"""register a function to be called when the UI is creating new tabs for the train tab. | |
Create your new tabs with gr.Tab. | |
""" | |
add_callback(callback_map['callbacks_ui_train_tabs'], callback, name=name, category='ui_train_tabs') | |
def on_ui_settings(callback, *, name=None): | |
"""register a function to be called before UI settings are populated; add your settings | |
by using shared.opts.add_option(shared.OptionInfo(...)) """ | |
add_callback(callback_map['callbacks_ui_settings'], callback, name=name, category='ui_settings') | |
def on_before_image_saved(callback, *, name=None): | |
"""register a function to be called before an image is saved to a file. | |
The callback is called with one argument: | |
- params: ImageSaveParams - parameters the image is to be saved with. You can change fields in this object. | |
""" | |
add_callback(callback_map['callbacks_before_image_saved'], callback, name=name, category='before_image_saved') | |
def on_image_saved(callback, *, name=None): | |
"""register a function to be called after an image is saved to a file. | |
The callback is called with one argument: | |
- params: ImageSaveParams - parameters the image was saved with. Changing fields in this object does nothing. | |
""" | |
add_callback(callback_map['callbacks_image_saved'], callback, name=name, category='image_saved') | |
def on_extra_noise(callback, *, name=None): | |
"""register a function to be called before adding extra noise in img2img or hires fix; | |
The callback is called with one argument: | |
- params: ExtraNoiseParams - contains noise determined by seed and latent representation of image | |
""" | |
add_callback(callback_map['callbacks_extra_noise'], callback, name=name, category='extra_noise') | |
def on_cfg_denoiser(callback, *, name=None): | |
"""register a function to be called in the kdiffussion cfg_denoiser method after building the inner model inputs. | |
The callback is called with one argument: | |
- params: CFGDenoiserParams - parameters to be passed to the inner model and sampling state details. | |
""" | |
add_callback(callback_map['callbacks_cfg_denoiser'], callback, name=name, category='cfg_denoiser') | |
def on_cfg_denoised(callback, *, name=None): | |
"""register a function to be called in the kdiffussion cfg_denoiser method after building the inner model inputs. | |
The callback is called with one argument: | |
- params: CFGDenoisedParams - parameters to be passed to the inner model and sampling state details. | |
""" | |
add_callback(callback_map['callbacks_cfg_denoised'], callback, name=name, category='cfg_denoised') | |
def on_cfg_after_cfg(callback, *, name=None): | |
"""register a function to be called in the kdiffussion cfg_denoiser method after cfg calculations are completed. | |
The callback is called with one argument: | |
- params: AfterCFGCallbackParams - parameters to be passed to the script for post-processing after cfg calculation. | |
""" | |
add_callback(callback_map['callbacks_cfg_after_cfg'], callback, name=name, category='cfg_after_cfg') | |
def on_before_component(callback, *, name=None): | |
"""register a function to be called before a component is created. | |
The callback is called with arguments: | |
- component - gradio component that is about to be created. | |
- **kwargs - args to gradio.components.IOComponent.__init__ function | |
Use elem_id/label fields of kwargs to figure out which component it is. | |
This can be useful to inject your own components somewhere in the middle of vanilla UI. | |
""" | |
add_callback(callback_map['callbacks_before_component'], callback, name=name, category='before_component') | |
def on_after_component(callback, *, name=None): | |
"""register a function to be called after a component is created. See on_before_component for more.""" | |
add_callback(callback_map['callbacks_after_component'], callback, name=name, category='after_component') | |
def on_image_grid(callback, *, name=None): | |
"""register a function to be called before making an image grid. | |
The callback is called with one argument: | |
- params: ImageGridLoopParams - parameters to be used for grid creation. Can be modified. | |
""" | |
add_callback(callback_map['callbacks_image_grid'], callback, name=name, category='image_grid') | |
def on_infotext_pasted(callback, *, name=None): | |
"""register a function to be called before applying an infotext. | |
The callback is called with two arguments: | |
- infotext: str - raw infotext. | |
- result: dict[str, any] - parsed infotext parameters. | |
""" | |
add_callback(callback_map['callbacks_infotext_pasted'], callback, name=name, category='infotext_pasted') | |
def on_script_unloaded(callback, *, name=None): | |
"""register a function to be called before the script is unloaded. Any hooks/hijacks/monkeying about that | |
the script did should be reverted here""" | |
add_callback(callback_map['callbacks_script_unloaded'], callback, name=name, category='script_unloaded') | |
def on_before_ui(callback, *, name=None): | |
"""register a function to be called before the UI is created.""" | |
add_callback(callback_map['callbacks_before_ui'], callback, name=name, category='before_ui') | |
def on_list_optimizers(callback, *, name=None): | |
"""register a function to be called when UI is making a list of cross attention optimization options. | |
The function will be called with one argument, a list, and shall add objects of type modules.sd_hijack_optimizations.SdOptimization | |
to it.""" | |
add_callback(callback_map['callbacks_list_optimizers'], callback, name=name, category='list_optimizers') | |
def on_list_unets(callback, *, name=None): | |
"""register a function to be called when UI is making a list of alternative options for unet. | |
The function will be called with one argument, a list, and shall add objects of type modules.sd_unet.SdUnetOption to it.""" | |
add_callback(callback_map['callbacks_list_unets'], callback, name=name, category='list_unets') | |
def on_before_token_counter(callback, *, name=None): | |
"""register a function to be called when UI is counting tokens for a prompt. | |
The function will be called with one argument of type BeforeTokenCounterParams, and should modify its fields if necessary.""" | |
add_callback(callback_map['callbacks_before_token_counter'], callback, name=name, category='before_token_counter') | |