Merge pull request #7731 from opparco/master

Add cfg_denoised_callback
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AUTOMATIC1111 2023-02-19 11:09:47 +03:00 committed by GitHub
commit 3fcc087317
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2 changed files with 33 additions and 0 deletions

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@ -46,6 +46,18 @@ class CFGDenoiserParams:
"""Total number of sampling steps planned""" """Total number of sampling steps planned"""
class CFGDenoisedParams:
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: class UiTrainTabParams:
def __init__(self, txt2img_preview_params): def __init__(self, txt2img_preview_params):
self.txt2img_preview_params = txt2img_preview_params self.txt2img_preview_params = txt2img_preview_params
@ -68,6 +80,7 @@ callback_map = dict(
callbacks_before_image_saved=[], callbacks_before_image_saved=[],
callbacks_image_saved=[], callbacks_image_saved=[],
callbacks_cfg_denoiser=[], callbacks_cfg_denoiser=[],
callbacks_cfg_denoised=[],
callbacks_before_component=[], callbacks_before_component=[],
callbacks_after_component=[], callbacks_after_component=[],
callbacks_image_grid=[], callbacks_image_grid=[],
@ -150,6 +163,14 @@ def cfg_denoiser_callback(params: CFGDenoiserParams):
report_exception(c, 'cfg_denoiser_callback') report_exception(c, 'cfg_denoiser_callback')
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 before_component_callback(component, **kwargs): def before_component_callback(component, **kwargs):
for c in callback_map['callbacks_before_component']: for c in callback_map['callbacks_before_component']:
try: try:
@ -283,6 +304,14 @@ def on_cfg_denoiser(callback):
add_callback(callback_map['callbacks_cfg_denoiser'], callback) add_callback(callback_map['callbacks_cfg_denoiser'], callback)
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_before_component(callback): def on_before_component(callback):
"""register a function to be called before a component is created. """register a function to be called before a component is created.
The callback is called with arguments: The callback is called with arguments:

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@ -8,6 +8,7 @@ from modules import prompt_parser, devices, sd_samplers_common
from modules.shared import opts, state from modules.shared import opts, state
import modules.shared as shared import modules.shared as shared
from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback
samplers_k_diffusion = [ samplers_k_diffusion = [
('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}), ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}),
@ -136,6 +137,9 @@ class CFGDenoiser(torch.nn.Module):
x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond={"c_crossattn": [uncond], "c_concat": [image_cond_in[-uncond.shape[0]:]]}) x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond={"c_crossattn": [uncond], "c_concat": [image_cond_in[-uncond.shape[0]:]]})
denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps)
cfg_denoised_callback(denoised_params)
devices.test_for_nans(x_out, "unet") devices.test_for_nans(x_out, "unet")
if opts.live_preview_content == "Prompt": if opts.live_preview_content == "Prompt":