Fix typerror in pipeline handling for MultiControlNets which only contain a...

Fix typerror in pipeline handling for MultiControlNets which only contain a single ControlNet (#4454)

* Handle single controlnet in multicontrolnet

* Fix formatting

src/diffusers/pipelines/controlnet/pipeline_controlnet.py

@@ -947,7 +947,10 @@ class StableDiffusionControlNetPipeline(
                 if isinstance(controlnet_keep[i], list):
                     cond_scale = [c * s for c, s in zip(controlnet_conditioning_scale, controlnet_keep[i])]
                 else:
-                    cond_scale = controlnet_conditioning_scale * controlnet_keep[i]
+                    controlnet_cond_scale = controlnet_conditioning_scale
+                    if isinstance(controlnet_cond_scale, list):
+                        controlnet_cond_scale = controlnet_cond_scale[0]
+                    cond_scale = controlnet_cond_scale * controlnet_keep[i]
 
                 down_block_res_samples, mid_block_res_sample = self.controlnet(
                     control_model_input,

src/diffusers/pipelines/controlnet/pipeline_controlnet_img2img.py

@@ -1034,7 +1034,10 @@ class StableDiffusionControlNetImg2ImgPipeline(
                 if isinstance(controlnet_keep[i], list):
                     cond_scale = [c * s for c, s in zip(controlnet_conditioning_scale, controlnet_keep[i])]
                 else:
-                    cond_scale = controlnet_conditioning_scale * controlnet_keep[i]
+                    controlnet_cond_scale = controlnet_conditioning_scale
+                    if isinstance(controlnet_cond_scale, list):
+                        controlnet_cond_scale = controlnet_cond_scale[0]
+                    cond_scale = controlnet_cond_scale * controlnet_keep[i]
 
                 down_block_res_samples, mid_block_res_sample = self.controlnet(
                     control_model_input,

src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py

@@ -1269,7 +1269,10 @@ class StableDiffusionControlNetInpaintPipeline(
                 if isinstance(controlnet_keep[i], list):
                     cond_scale = [c * s for c, s in zip(controlnet_conditioning_scale, controlnet_keep[i])]
                 else:
-                    cond_scale = controlnet_conditioning_scale * controlnet_keep[i]
+                    controlnet_cond_scale = controlnet_conditioning_scale
+                    if isinstance(controlnet_cond_scale, list):
+                        controlnet_cond_scale = controlnet_cond_scale[0]
+                    cond_scale = controlnet_cond_scale * controlnet_keep[i]
 
                 down_block_res_samples, mid_block_res_sample = self.controlnet(
                     control_model_input,

src/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl.py

@@ -967,7 +967,10 @@ class StableDiffusionXLControlNetPipeline(DiffusionPipeline, TextualInversionLoa
                 if isinstance(controlnet_keep[i], list):
                     cond_scale = [c * s for c, s in zip(controlnet_conditioning_scale, controlnet_keep[i])]
                 else:
-                    cond_scale = controlnet_conditioning_scale * controlnet_keep[i]
+                    controlnet_cond_scale = controlnet_conditioning_scale
+                    if isinstance(controlnet_cond_scale, list):
+                        controlnet_cond_scale = controlnet_cond_scale[0]
+                    cond_scale = controlnet_cond_scale * controlnet_keep[i]
 
                 added_cond_kwargs = {"text_embeds": add_text_embeds, "time_ids": add_time_ids}
                 down_block_res_samples, mid_block_res_sample = self.controlnet(