up

examples/community/llm_grounded_diffusion.py

@@ -1534,17 +1534,17 @@ class LLMGroundedDiffusionPipeline(
         return emb
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.guidance_scale
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixinguidance_scale
     def guidance_scale(self):
         return self._guidance_scale
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.guidance_rescale
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.guidance_rescale
     def guidance_rescale(self):
         return self._guidance_rescale
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.clip_skip
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.clip_skip
     def clip_skip(self):
         return self._clip_skip
 
@@ -1552,12 +1552,12 @@ class LLMGroundedDiffusionPipeline(
     # of the Imagen paper: https://huggingface.co/papers/2205.11487 . `guidance_scale = 1`
     # corresponds to doing no classifier free guidance.
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.do_classifier_free_guidance
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.do_classifier_free_guidance
     def do_classifier_free_guidance(self):
         return self._guidance_scale > 1 and self.unet.config.time_cond_proj_dim is None
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.cross_attention_kwargs
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.cross_attention_kwargs
     def cross_attention_kwargs(self):
         return self._cross_attention_kwargs
 

src/diffusers/pipelines/controlnet_xs/pipeline_controlnet_xs.py

@@ -616,22 +616,22 @@ class StableDiffusionControlNetXSPipeline(
         return latents
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.guidance_scale
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixinguidance_scale
     def guidance_scale(self):
         return self._guidance_scale
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.clip_skip
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.clip_skip
     def clip_skip(self):
         return self._clip_skip
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.do_classifier_free_guidance
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.do_classifier_free_guidance
     def do_classifier_free_guidance(self):
         return self._guidance_scale > 1 and self.unet.config.time_cond_proj_dim is None
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.cross_attention_kwargs
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.cross_attention_kwargs
     def cross_attention_kwargs(self):
         return self._cross_attention_kwargs
 

src/diffusers/pipelines/controlnet_xs/pipeline_controlnet_xs_sd_xl.py

@@ -702,22 +702,22 @@ class StableDiffusionXLControlNetXSPipeline(
             self.vae.decoder.mid_block.to(dtype)
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.guidance_scale
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixinguidance_scale
     def guidance_scale(self):
         return self._guidance_scale
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.clip_skip
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.clip_skip
     def clip_skip(self):
         return self._clip_skip
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.do_classifier_free_guidance
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.do_classifier_free_guidance
     def do_classifier_free_guidance(self):
         return self._guidance_scale > 1 and self.unet.config.time_cond_proj_dim is None
 
     @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.cross_attention_kwargs
+    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_utils.StableDiffusionMixin.cross_attention_kwargs
     def cross_attention_kwargs(self):
         return self._cross_attention_kwargs
 

src/diffusers/pipelines/pag/pipeline_pag_controlnet_sd_xl.py

@@ -940,10 +940,7 @@ class StableDiffusionXLControlNetPAGPipeline(
         self.vae.to(dtype=torch.float32)
         use_torch_2_0_or_xformers = isinstance(
             self.vae.decoder.mid_block.attentions[0].processor,
-            (
-                AttnProcessor2_0,
-                XFormersAttnProcessor,
-            ),
+            (AttnProcessor2_0, XFormersAttnProcessor),
         )
         # if xformers or torch_2_0 is used attention block does not need
         # to be in float32 which can save lots of memory

src/diffusers/pipelines/pag/pipeline_pag_controlnet_sd_xl_img2img.py

@@ -1053,10 +1053,7 @@ class StableDiffusionXLControlNetPAGImg2ImgPipeline(
         self.vae.to(dtype=torch.float32)
         use_torch_2_0_or_xformers = isinstance(
             self.vae.decoder.mid_block.attentions[0].processor,
-            (
-                AttnProcessor2_0,
-                XFormersAttnProcessor,
-            ),
+            (AttnProcessor2_0, XFormersAttnProcessor),
         )
         # if xformers or torch_2_0 is used attention block does not need
         # to be in float32 which can save lots of memory

src/diffusers/pipelines/pag/pipeline_pag_sd_xl_img2img.py

@@ -914,10 +914,7 @@ class StableDiffusionXLPAGImg2ImgPipeline(
         self.vae.to(dtype=torch.float32)
         use_torch_2_0_or_xformers = isinstance(
             self.vae.decoder.mid_block.attentions[0].processor,
-            (
-                AttnProcessor2_0,
-                XFormersAttnProcessor,
-            ),
+            (AttnProcessor2_0, XFormersAttnProcessor),
         )
         # if xformers or torch_2_0 is used attention block does not need
         # to be in float32 which can save lots of memory

src/diffusers/pipelines/pag/pipeline_pag_sd_xl_inpaint.py

@@ -1005,10 +1005,7 @@ class StableDiffusionXLPAGInpaintPipeline(
         self.vae.to(dtype=torch.float32)
         use_torch_2_0_or_xformers = isinstance(
             self.vae.decoder.mid_block.attentions[0].processor,
-            (
-                AttnProcessor2_0,
-                XFormersAttnProcessor,
-            ),
+            (AttnProcessor2_0, XFormersAttnProcessor),
         )
         # if xformers or torch_2_0 is used attention block does not need
         # to be in float32 which can save lots of memory

src/diffusers/pipelines/t2i_adapter/pipeline_stable_diffusion_xl_adapter.py

@@ -783,10 +783,7 @@ class StableDiffusionXLAdapterPipeline(
         self.vae.to(dtype=torch.float32)
         use_torch_2_0_or_xformers = isinstance(
             self.vae.decoder.mid_block.attentions[0].processor,
-            (
-                AttnProcessor2_0,
-                XFormersAttnProcessor,
-            ),
+            (AttnProcessor2_0, XFormersAttnProcessor),
         )
         # if xformers or torch_2_0 is used attention block does not need
         # to be in float32 which can save lots of memory