diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 7d9dd736..57dfd457 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -53,6 +53,21 @@ class CFGDenoiserParams: 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""" @@ -63,6 +78,9 @@ class CFGDenoisedParams: self.total_sampling_steps = total_sampling_steps """Total number of sampling steps planned""" + self.output_altered = False + """A flag for CFGDenoiser indicating whether the output has been altered by the callback""" + class UiTrainTabParams: def __init__(self, txt2img_preview_params): @@ -87,6 +105,7 @@ callback_map = dict( callbacks_image_saved=[], callbacks_cfg_denoiser=[], callbacks_cfg_denoised=[], + callbacks_cfg_after_cfg=[], callbacks_before_component=[], callbacks_after_component=[], callbacks_image_grid=[], @@ -186,6 +205,14 @@ def cfg_denoised_callback(params: CFGDenoisedParams): 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: @@ -332,6 +359,14 @@ def on_cfg_denoised(callback): add_callback(callback_map['callbacks_cfg_denoised'], callback) +def on_cfg_after_cfg(callback): + """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) + + def on_before_component(callback): """register a function to be called before a component is created. The callback is called with arguments: diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index e9e41818..55f0d3a3 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -8,6 +8,7 @@ from modules.shared import opts, state import modules.shared as shared from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback +from modules.script_callbacks import AfterCFGCallbackParams, cfg_after_cfg_callback samplers_k_diffusion = [ ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}), @@ -160,7 +161,7 @@ class CFGDenoiser(torch.nn.Module): fake_uncond = torch.cat([x_out[i:i+1] for i in denoised_image_indexes]) x_out = torch.cat([x_out, fake_uncond]) # we skipped uncond denoising, so we put cond-denoised image to where the uncond-denoised image should be - denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps) + denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps, self.inner_model) cfg_denoised_callback(denoised_params) devices.test_for_nans(x_out, "unet") @@ -180,6 +181,11 @@ class CFGDenoiser(torch.nn.Module): if self.mask is not None: denoised = self.init_latent * self.mask + self.nmask * denoised + after_cfg_callback_params = AfterCFGCallbackParams(denoised, state.sampling_step, state.sampling_steps) + cfg_after_cfg_callback(after_cfg_callback_params) + if after_cfg_callback_params.output_altered: + denoised = after_cfg_callback_params.x + self.step += 1 return denoised