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docker_images/diffusers/app/pipelines/text_to_image.py

@@ -160,20 +160,20 @@ def __call__(self, inputs: str, **kwargs) -> "Image.Image":
     def _process_req(self, inputs, **kwargs):
         # only one image per prompt is supported
         kwargs["num_images_per_prompt"] = 1
-    
+
         if "num_inference_steps" not in kwargs:
             default_num_steps = os.getenv("DEFAULT_NUM_INFERENCE_STEPS")
             if default_num_steps:
                 kwargs["num_inference_steps"] = int(default_num_steps)
             elif self.is_karras_compatible:
                 kwargs["num_inference_steps"] = 20
             # Else, don't specify anything, leave the default behaviour
-        
+
         if "seed" in kwargs:
             seed = int(kwargs["seed"])
             generator = torch.Generator().manual_seed(kwargs["seed"])
             kwargs["generator"] = generator
             kwargs.pop("seed")
-            
+
         images = self.ldm(inputs, **kwargs)["images"]
         return images[0]