Update src/pipeline.py

src/pipeline.py

@@ -40,7 +40,7 @@ def load_pipeline(pipeline=None) -> StableDiffusionXLPipeline:
         deepcache_output = pipeline(prompt=prompt, output_type="pil", num_inference_steps=20, generator=generator, guidance_scale=5.0)
     deepcache_output[0][0].save(f"./../retrained_final_image_croissant_orig_{num}.png")
     
-    pipeline.scheduler.prepare_loss()
+    # pipeline.scheduler.prepare_loss()
 
     for _ in range(1):
         deepcache_output = pipeline(prompt=prompt, output_type="pil", num_inference_steps=20, generator=generator, guidance_scale=5.0)
@@ -54,7 +54,7 @@ def load_pipeline(pipeline=None) -> StableDiffusionXLPipeline:
     optimizer = torch.optim.Adam(loss_model.parameters(), lr=1e-4)
     
     # Generate the dataset by running the diffusion process
-    num_inference_steps = 13
+    num_inference_steps = 20
     generator = torch.manual_seed(0)
     
     # Run the pipeline to generate samples and collect diffusion paths