Update pipeline.py

pipeline.py

@@ -34,13 +34,6 @@ class SuperDiffPipeline(DiffusionPipeline, ConfigMixin):
 
         """
         super().__init__()
-        # Register additional parameters for flexibility
-        # Explicitly assign required components
-        #self.unet = unet
-        #self.vae = vae
-        #self.text_encoder = text_encoder
-        #self.tokenizer = tokenizer
-        #self.scheduler = scheduler
 
         device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -53,21 +46,6 @@ class SuperDiffPipeline(DiffusionPipeline, ConfigMixin):
                               text_encoder=text_encoder,
                               tokenizer=tokenizer,)
 
-
-        #self.register_to_config(
-        #    vae=vae.__class__.__name__,
-        #    scheduler=scheduler.__class__.__name__,
-        #    tokenizer=tokenizer.__class__.__name__,
-        #    unet=unet.__class__.__name__,
-        #    text_encoder=text_encoder.__class__.__name__,
-        #    device=device,
-        #    batch_size=None,
-        #    num_inference_steps=None,
-        #    guidance_scale=None,
-        #    lift=None,
-        #    seed=None,
-        #)
-
     @torch.no_grad
     def get_batch(self, latents: Callable, nrow: int, ncol: int) -> Callable:
         """get_batch.