Fix StableDiffusionXLPAGInpaintPipeline

src/diffusers/pipelines/auto_pipeline.py

@@ -953,7 +953,8 @@ def from_pretrained(cls, pretrained_model_or_path, **kwargs):
         if "enable_pag" in kwargs:
             enable_pag = kwargs.pop("enable_pag")
             if enable_pag:
-                orig_class_name = config["_class_name"].replace("Pipeline", "PAGPipeline")
+                to_replace = "InpaintPipeline" if "Inpaint" in config["_class_name"] else "Pipeline"
+                orig_class_name = config["_class_name"].replace(to_replace, "PAG" + to_replace)
 
         inpainting_cls = _get_task_class(AUTO_INPAINT_PIPELINES_MAPPING, orig_class_name)
 

src/diffusers/pipelines/pag/pipeline_pag_sd_xl_inpaint.py

@@ -1471,6 +1471,14 @@ def denoising_value_valid(dnv):
             generator,
             self.do_classifier_free_guidance,
         )
+        if self.do_perturbed_attention_guidance:
+            if self.do_classifier_free_guidance:
+                mask, _ = mask.chunk(2)
+                masked_image_latents, _ = masked_image_latents.chunk(2)
+            mask = self._prepare_perturbed_attention_guidance(mask, mask, self.do_classifier_free_guidance)
+            masked_image_latents = self._prepare_perturbed_attention_guidance(
+                masked_image_latents, masked_image_latents, self.do_classifier_free_guidance
+            )
 
         # 8. Check that sizes of mask, masked image and latents match
         if num_channels_unet == 9:
@@ -1659,10 +1667,10 @@ def denoising_value_valid(dnv):
 
                 if num_channels_unet == 4:
                     init_latents_proper = image_latents
-                    if self.do_classifier_free_guidance:
-                        init_mask, _ = mask.chunk(2)
+                    if self.do_perturbed_attention_guidance:
+                        init_mask, *_ = mask.chunk(3) if self.do_classifier_free_guidance else mask.chunk(2)
                     else:
-                        init_mask = mask
+                        init_mask, *_ = mask.chunk(2) if self.do_classifier_free_guidance else mask
 
                     if i < len(timesteps) - 1:
                         noise_timestep = timesteps[i + 1]