Merge pull request #7731 from opparco/master

Add cfg_denoised_callback

2 files changed, 33 insertions, 0 deletions

diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index 4bb45ec7..edd0e2a7 100644
--- a/modules/script_callbacks.py
+++ b/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:

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 86d657e2..528f513f 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/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":