SAG patch for auto1111(dev) 335428c2c8139dfe07ba096a6defa75036660244

0001-patch-in-callbacks-for-SAG-to-dev.patch

From cef07987cc6e1776d3c3d88691ce94c8fc2c3a0c Mon Sep 17 00:00:00 2001
From: papuSpartan <30642826+papuSpartan@users.noreply.github.com>
Date: Wed, 3 May 2023 20:06:27 -0500
Subject: [PATCH] patch in callbacks for SAG to dev

---
 modules/script_callbacks.py       | 31 ++++++++++++++++++++++++++++++-
 modules/sd_samplers_kdiffusion.py |  9 ++++++++-
 2 files changed, 38 insertions(+), 2 deletions(-)

diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index 17109732..e0436a00 100644
--- a/modules/script_callbacks.py
+++ b/modules/script_callbacks.py
@@ -53,7 +53,7 @@ class CFGDenoiserParams:
 
 
 class CFGDenoisedParams:
-    def __init__(self, x, sampling_step, total_sampling_steps):
+    def __init__(self, x, sampling_step, total_sampling_steps, inner_model):
         self.x = x
         """Latent image representation in the process of being denoised"""
 
@@ -63,6 +63,22 @@ class CFGDenoisedParams:
         self.total_sampling_steps = total_sampling_steps
         """Total number of sampling steps planned"""
 
+        self.inner_model = inner_model
+        """Inner model reference that is being 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"""
+
+        self.total_sampling_steps = total_sampling_steps
+        """Total number of sampling steps planned"""
+
+        self.output_altered = False
+        """A flag for CFGDenoiser that indicates whether the output has been altered by the callback"""
+
 
 class UiTrainTabParams:
     def __init__(self, txt2img_preview_params):
@@ -87,6 +103,7 @@ 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=[],
@@ -185,6 +202,12 @@ def cfg_denoised_callback(params: CFGDenoisedParams):
         except Exception:
             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']:
@@ -331,6 +354,12 @@ 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 has completed.
+    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_after_cfg'], callback)
 
 def on_before_component(callback):
     """register a function to be called before a component is created.
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index eb98e599..8e63859b 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -9,6 +9,7 @@ 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'], {}),
@@ -161,7 +162,7 @@ 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")
@@ -181,7 +182,13 @@ 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
 
 
-- 
2.40.0.windows.1