Update src/pipeline.py

src/pipeline.py

@@ -139,13 +139,13 @@ def load_pipeline() -> Pipeline:
     quantize_(pipeline.vae, int8_weight_only())
     pipeline.vae = torch.compile(pipeline.vae, mode="max-autotune", fullgraph=True)
     with torch.inference_mode():  
-        for _ in range(2):
-            pipeline(prompt="insensible, timbale, pothery, electrovital, actinogram, taxis, intracerebellar, centrodesmus", width=1024, height=1024, guidance_scale=0.0, num_inference_steps=4, max_sequence_length=256)
+        # for _ in range(2):
+        pipeline(prompt="insensible, timbale, pothery, electrovital, actinogram, taxis, intracerebellar, centrodesmus", width=1024, height=1024, guidance_scale=0.0, num_inference_steps=4, max_sequence_length=256)
     torch.cuda.empty_cache()
     return pipeline
 
 
-sample = 1
+sample = False
 @torch.inference_mode()
 def infer(request: TextToImageRequest, pipeline: Pipeline, generator: Generator) -> Image:
     global sample