Merge pull request #4021 from AUTOMATIC1111/add-kdiff-cfgdenoiser-callback

        """dictionary with parameters for image's PNG info data; infotext will have the key 'parameters'"""

class CFGDenoiserParams:

    def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps):

        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"""

ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"])

callbacks_app_started = []

callbacks_model_loaded = []

callbacks_ui_settings = []

callbacks_before_image_saved = []

callbacks_image_saved = []

callbacks_cfg_denoiser = []

def clear_callbacks():

    callbacks_ui_settings.clear()

    callbacks_before_image_saved.clear()

    callbacks_image_saved.clear()

    callbacks_cfg_denoiser.clear()

def app_started_callback(demo: Blocks, app: FastAPI):

    for c in callbacks_app_started:

            report_exception(c, 'image_saved_callback')

def cfg_denoiser_callback(params: CFGDenoiserParams):

    for c in callbacks_cfg_denoiser:

        try:

            c.callback(params)

        except Exception:

            report_exception(c, 'cfg_denoiser_callback')

def add_callback(callbacks, fun):

    stack = [x for x in inspect.stack() if x.filename != __file__]

    filename = stack[0].filename if len(stack) > 0 else 'unknown file'

        - params: ImageSaveParams - parameters the image was saved with. Changing fields in this object does nothing.

    """

    add_callback(callbacks_image_saved, callback)

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.

    """

    add_callback(callbacks_cfg_denoiser, callback)

from modules.shared import opts, cmd_opts, state

import modules.shared as shared

from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback

SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])

        image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_cond])

        sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma])

        denoiser_params = CFGDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps)

        cfg_denoiser_callback(denoiser_params)

        x_in = denoiser_params.x

        image_cond_in = denoiser_params.image_cond

        sigma_in = denoiser_params.sigma

        if tensor.shape[1] == uncond.shape[1]:

            cond_in = torch.cat([tensor, uncond])