Update pipeline_pag_controlnet_sd_img2img.py

Author: SahilCarterr

src/diffusers/pipelines/pag/pipeline_pag_controlnet_sd_img2img.py

@@ -1234,6 +1234,13 @@ def __call__(
                 device,
                 generator,
             )
+        
+        timestep_cond = None
+        if self.unet.config.time_cond_proj_dim is not None:
+            guidance_scale_tensor = torch.tensor(self.guidance_scale - 1).repeat(batch_size * num_images_per_prompt)
+            timestep_cond = self.get_guidance_scale_embedding(
+                guidance_scale_tensor, embedding_dim=self.unet.config.time_cond_proj_dim
+            ).to(device=device, dtype=latents.dtype)
 
         # 7. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline
         extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)
@@ -1317,6 +1324,7 @@ def __call__(
                     latent_model_input,
                     t,
                     encoder_hidden_states=prompt_embeds,
+                    timestep_cond=timestep_cond,
                     cross_attention_kwargs=self.cross_attention_kwargs,
                     down_block_additional_residuals=down_block_res_samples,
                     mid_block_additional_residual=mid_block_res_sample,
@@ -1344,6 +1352,7 @@ def __call__(
 
                     latents = callback_outputs.pop("latents", latents)
                     prompt_embeds = callback_outputs.pop("prompt_embeds", prompt_embeds)
+                    negative_prompt_embeds = callback_outputs.pop("negative_prompt_embeds", negative_prompt_embeds)
                 # call the callback, if provided
                 if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):
                     progress_bar.update()