fix IndexError, change callback type

modules/processing_callbacks.py

@@ -73,7 +73,7 @@ def diffusers_callback(pipe, step: int = 0, timestep: int = 0, kwargs: dict = {}
             if 'negative_prompt_embeds' in kwargs:
                 kwargs["negative_prompt_embeds"] = prompt_parser_diffusers.embedder("negative_prompt_embeds", step + 1)
         except Exception as e:
-            shared.log.debug(f"Callback: {e}")
+            debug_callback(f"Callback: {e}")
     if step == int(getattr(pipe, 'num_timesteps', 100) * p.cfg_end) and 'prompt_embeds' in kwargs and 'negative_prompt_embeds' in kwargs:
         if "PAG" in shared.sd_model.__class__.__name__:
             pipe._guidance_scale = 1.001 if pipe._guidance_scale > 1 else pipe._guidance_scale  # pylint: disable=protected-access

modules/prompt_parser_diffusers.py

@@ -172,11 +172,12 @@ class PromptEmbedder:
         for i in range(self.batchsize):
             if len(batch[i]) == 0: # if not using prompt-scheduling, this will be len(batch[i])==1
                 return None
-            else:
-                # causes error in callback
+            try:
                 res.append(batch[i][step]) # and this requests element for specific step when called from callback - but self.scheduled_prompt==False so len(batch[i])==1 and step is list index out-of-bounds!
-                if step != 0:  # For Callback
-                    res.append(batch[i][step])  # Diffusers internally doubles batch dimension
+            except IndexError:
+                res.append(batch[i][0])
+            if step != 0:  # For Callback
+                res.append(res[-1])  # Diffusers internally doubles batch dimension
         return torch.cat(res)