Add cfg_denoised_callback

modules/script_callbacks.py

@@ -46,6 +46,18 @@ class CFGDenoiserParams:
         """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:
     def __init__(self, txt2img_preview_params):
         self.txt2img_preview_params = txt2img_preview_params
@@ -68,6 +80,7 @@ callback_map = dict(
     callbacks_before_image_saved=[],
     callbacks_image_saved=[],
     callbacks_cfg_denoiser=[],
+    callbacks_cfg_denoised=[],
     callbacks_before_component=[],
     callbacks_after_component=[],
     callbacks_image_grid=[],
@@ -150,6 +163,14 @@ def cfg_denoiser_callback(params: CFGDenoiserParams):
             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):
     for c in callback_map['callbacks_before_component']:
         try:
@@ -283,6 +304,14 @@ def on_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):
     """register a function to be called before a component is created.
     The callback is called with arguments:

modules/sd_samplers_kdiffusion.py

@@ -8,6 +8,7 @@ from modules import prompt_parser, devices, sd_samplers_common
 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
 
 samplers_k_diffusion = [
     ('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]:]]})
 
+        denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps)
+        cfg_denoised_callback(denoised_params)
+
         devices.test_for_nans(x_out, "unet")
 
         if opts.live_preview_content == "Prompt":