fix use_guidance when controlnet is a multi and does not have config

src/diffusers/pipelines/flux/pipeline_flux_controlnet.py

@@ -752,7 +752,7 @@ def __call__(
                 if not isinstance(control_mode, int):
                     raise ValueError(" For `FluxControlNet`, `control_mode` should be an `int` or `None`")
                 control_mode = torch.tensor(control_mode).to(device, dtype=torch.long)
-                control_mode = control_mode.view(-1,1).expand(control_image.shape[0], 1)
+                control_mode = control_mode.view(-1, 1).expand(control_image.shape[0], 1)
 
         elif isinstance(self.controlnet, FluxMultiControlNetModel):
             control_images = []
@@ -789,11 +789,13 @@ def __call__(
 
             # Here we ensure that `control_mode` has the same length as the control_image.
             if isinstance(control_mode, list) and len(control_mode) != len(control_image):
-                raise ValueError("For Multi-ControlNet, `control_mode` must be a list of the same " +
-                                    " length as the number of controlnets (control images) specified")
+                raise ValueError(
+                    "For Multi-ControlNet, `control_mode` must be a list of the same "
+                    + " length as the number of controlnets (control images) specified"
+                )
             if not isinstance(control_mode, list):
                 control_mode = [control_mode] * len(control_image)
-            # set control mode  
+            # set control mode
             control_modes = []
             for cmode in control_mode:
                 if cmode is None:
@@ -846,9 +848,12 @@ def __call__(
                 # broadcast to batch dimension in a way that's compatible with ONNX/Core ML
                 timestep = t.expand(latents.shape[0]).to(latents.dtype)
 
-                guidance = (
-                    torch.tensor([guidance_scale], device=device) if self.controlnet.config.guidance_embeds else None
-                )
+                if isinstance(self.controlnet, FluxMultiControlNetModel):
+                    use_guidance = self.controlnet.nets[0].config.guidance_embeds
+                else:
+                    use_guidance = self.controlnet.config.guidance_embeds
+
+                guidance = torch.tensor([guidance_scale], device=device) if use_guidance else None
                 guidance = guidance.expand(latents.shape[0]) if guidance is not None else None
 
                 # controlnet