my-sd/modules/script_callbacks.py

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import dataclasses
import inspect
import os
from collections import namedtuple
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from typing import Optional, Any
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from fastapi import FastAPI
from gradio import Blocks
from modules import errors, timer
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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'"""
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class ExtraNoiseParams:
def __init__(self, noise, x, xi):
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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"""
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class CFGDenoiserParams:
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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"""
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self.sampling_step = sampling_step
"""Current Sampling step number"""
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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"""
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self.denoiser = denoiser
"""Current CFGDenoiser object with processing parameters"""
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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
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"""Inner model reference used for denoising"""
class AfterCFGCallbackParams:
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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:
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def __init__(self, imgs, cols, rows):
self.imgs = imgs
self.cols = cols
self.rows = rows
@dataclasses.dataclass
class BeforeTokenCounterParams:
prompt: str
steps: int
styles: list
is_positive: bool = True
ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"])
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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=[],
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callbacks_extra_noise=[],
callbacks_cfg_denoiser=[],
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callbacks_cfg_denoised=[],
callbacks_cfg_after_cfg=[],
callbacks_before_component=[],
callbacks_after_component=[],
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callbacks_image_grid=[],
callbacks_infotext_pasted=[],
callbacks_script_unloaded=[],
callbacks_before_ui=[],
callbacks_on_reload=[],
callbacks_list_optimizers=[],
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callbacks_list_unets=[],
callbacks_before_token_counter=[],
)
event_subscriber_map = dict(
callbacks_setting_updated=[],
)
def clear_callbacks():
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for callback_list in callback_map.values():
callback_list.clear()
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def app_started_callback(demo: Optional[Blocks], app: FastAPI):
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for c in callback_map['callbacks_app_started']:
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try:
c.callback(demo, app)
timer.startup_timer.record(os.path.basename(c.script))
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except Exception:
report_exception(c, 'app_started_callback')
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def app_reload_callback():
for c in callback_map['callbacks_on_reload']:
try:
c.callback()
except Exception:
report_exception(c, 'callbacks_on_reload')
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def model_loaded_callback(sd_model):
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for c in callback_map['callbacks_model_loaded']:
try:
c.callback(sd_model)
except Exception:
report_exception(c, 'model_loaded_callback')
def ui_tabs_callback():
res = []
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for c in callback_map['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 callback_map['callbacks_ui_train_tabs']:
try:
c.callback(params)
except Exception:
report_exception(c, 'callbacks_ui_train_tabs')
def ui_settings_callback():
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for c in callback_map['callbacks_ui_settings']:
try:
c.callback()
except Exception:
report_exception(c, 'ui_settings_callback')
def before_image_saved_callback(params: ImageSaveParams):
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for c in callback_map['callbacks_before_image_saved']:
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try:
c.callback(params)
except Exception:
report_exception(c, 'before_image_saved_callback')
def image_saved_callback(params: ImageSaveParams):
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for c in callback_map['callbacks_image_saved']:
try:
c.callback(params)
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except Exception:
report_exception(c, 'image_saved_callback')
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def extra_noise_callback(params: ExtraNoiseParams):
for c in callback_map['callbacks_extra_noise']:
try:
c.callback(params)
except Exception:
report_exception(c, 'callbacks_extra_noise')
def cfg_denoiser_callback(params: CFGDenoiserParams):
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for c in callback_map['callbacks_cfg_denoiser']:
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try:
c.callback(params)
except Exception:
report_exception(c, 'cfg_denoiser_callback')
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def cfg_denoised_callback(params: CFGDenoisedParams):
for c in callback_map['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 callback_map['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 callback_map['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 callback_map['callbacks_after_component']:
try:
c.callback(component, **kwargs)
except Exception:
report_exception(c, 'after_component_callback')
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def image_grid_callback(params: ImageGridLoopParams):
for c in callback_map['callbacks_image_grid']:
try:
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c.callback(params)
except Exception:
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report_exception(c, 'image_grid')
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def infotext_pasted_callback(infotext: str, params: dict[str, Any]):
for c in callback_map['callbacks_infotext_pasted']:
try:
c.callback(infotext, params)
except Exception:
report_exception(c, 'infotext_pasted')
def script_unloaded_callback():
for c in reversed(callback_map['callbacks_script_unloaded']):
try:
c.callback()
except Exception:
report_exception(c, 'script_unloaded')
def before_ui_callback():
for c in reversed(callback_map['callbacks_before_ui']):
try:
c.callback()
except Exception:
report_exception(c, 'before_ui')
def list_optimizers_callback():
res = []
for c in callback_map['callbacks_list_optimizers']:
try:
c.callback(res)
except Exception:
report_exception(c, 'list_optimizers')
return res
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def list_unets_callback():
res = []
for c in callback_map['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 callback_map['callbacks_before_token_counter']:
try:
c.callback(params)
except Exception:
report_exception(c, 'before_token_counter')
def setting_updated_event_subscriber_chain(handler, component, setting_name: str):
"""
Arguments:
- handler: The returned handler from calling an event subscriber.
- component: The component that is updated. The component should provide
the value of setting after update.
- setting_name: The name of the setting.
"""
for param in event_subscriber_map['callbacks_setting_updated']:
handler = handler.then(
fn=lambda *args: param["fn"](*args, setting_name),
inputs=param["inputs"] + [component],
outputs=param["outputs"],
show_progress=False,
)
def add_callback(callbacks, fun):
stack = [x for x in inspect.stack() if x.filename != __file__]
filename = stack[0].filename if stack else 'unknown file'
callbacks.append(ScriptCallback(filename, fun))
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
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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)
def remove_callbacks_for_function(callback_func):
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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)
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def on_app_started(callback):
"""register a function to be called when the webui started, the gradio `Block` component and
fastapi `FastAPI` object are passed as the arguments"""
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add_callback(callback_map['callbacks_app_started'], callback)
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def on_before_reload(callback):
"""register a function to be called just before the server reloads."""
add_callback(callback_map['callbacks_on_reload'], callback)
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def on_model_loaded(callback):
"""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. """
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add_callback(callback_map['callbacks_model_loaded'], callback)
def on_ui_tabs(callback):
"""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
"""
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add_callback(callback_map['callbacks_ui_tabs'], callback)
def on_ui_train_tabs(callback):
"""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)
def on_ui_settings(callback):
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"""register a function to be called before UI settings are populated; add your settings
by using shared.opts.add_option(shared.OptionInfo(...)) """
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add_callback(callback_map['callbacks_ui_settings'], callback)
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def on_before_image_saved(callback):
"""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.
"""
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add_callback(callback_map['callbacks_before_image_saved'], callback)
def on_image_saved(callback):
"""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.
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"""
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add_callback(callback_map['callbacks_image_saved'], callback)
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def on_extra_noise(callback):
"""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)
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def on_cfg_denoiser(callback):
"""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.
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"""
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add_callback(callback_map['callbacks_cfg_denoiser'], callback)
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def on_cfg_denoised(callback):
"""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)
def on_cfg_after_cfg(callback):
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"""register a function to be called in the kdiffussion cfg_denoiser method after cfg calculations are completed.
The callback is called with one argument:
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- params: AfterCFGCallbackParams - parameters to be passed to the script for post-processing after cfg calculation.
"""
add_callback(callback_map['callbacks_cfg_after_cfg'], callback)
def on_before_component(callback):
"""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)
def on_after_component(callback):
"""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)
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def on_image_grid(callback):
"""register a function to be called before making an image grid.
The callback is called with one argument:
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- params: ImageGridLoopParams - parameters to be used for grid creation. Can be modified.
"""
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add_callback(callback_map['callbacks_image_grid'], callback)
def on_infotext_pasted(callback):
"""register a function to be called before applying an infotext.
The callback is called with two arguments:
- infotext: str - raw infotext.
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- result: dict[str, any] - parsed infotext parameters.
"""
add_callback(callback_map['callbacks_infotext_pasted'], callback)
def on_script_unloaded(callback):
"""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)
def on_before_ui(callback):
"""register a function to be called before the UI is created."""
add_callback(callback_map['callbacks_before_ui'], callback)
def on_list_optimizers(callback):
"""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)
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def on_list_unets(callback):
"""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)
def on_before_token_counter(callback):
"""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)
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def on_setting_updated_subscriber(subscriber_params):
"""register a function to be called after settings update. `subscriber_params`
should contain necessary fields to register an gradio event handler. Necessary
fields are ["fn", "outputs", "inputs"].
Setting name and setting value after update will be append to inputs. So be
sure to handle these extra params when defining the callback function.
"""
event_subscriber_map['callbacks_setting_updated'].append(subscriber_params)
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