Update backend.py

flux_app/backend.py

@@ -30,7 +30,7 @@ class ModelManager:
 
         self.initialize_models()
     
-    @spaces.GPU(duration=300)
+    @spaces.GPU(duration=100)
     def initialize_models(self):
         """Initializes the diffusion pipelines and autoencoders."""
         self.taef1 = AutoencoderTiny.from_pretrained(TAEF1_MODEL, torch_dtype=DTYPE).to(DEVICE)
@@ -48,10 +48,10 @@ class ModelManager:
         ).to(DEVICE)
 
         setattr(self.pipe, "flux_pipe_call_that_returns_an_iterable_of_images", self.process_images)
-    @spaces.GPU(duration=300)
+    @spaces.GPU(duration=100)
     def process_images(self, *args, **kwargs):
         return flux_pipe_call_that_returns_an_iterable_of_images(self.pipe, *args, **kwargs)
-    @spaces.GPU(duration=300)
+    @spaces.GPU(duration=100)
     def generate_image(self, prompt_mash, steps, seed, cfg_scale, width, height, lora_scale):
         """Generates an image using the FLUX pipeline."""
         self.pipe.to(DEVICE)  # Ensure pipeline is on GPU
@@ -70,7 +70,7 @@ class ModelManager:
                 good_vae=self.good_vae,
             ):
                 yield img
-    @spaces.GPU(duration=300)
+    @spaces.GPU(duration=100)
     def generate_image_to_image(self, prompt_mash, image_input_path, image_strength, steps, cfg_scale, width, height, lora_scale, seed):
         """Generates an image using image-to-image processing."""
         generator = torch.Generator(device=DEVICE).manual_seed(seed)