Move device initialization for FLUX pipeline and VAE to CPU, add CUDA support in generate_item_image function

app.py

@@ -20,9 +20,8 @@ from live_preview_helpers import flux_pipe_call_that_returns_an_iterable_of_imag
 
 llm_client = Client("Qwen/Qwen2.5-72B-Instruct")
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to(device)
-good_vae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="vae", torch_dtype=torch.bfloat16).to(device)
+pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
+good_vae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="vae", torch_dtype=torch.bfloat16)
 pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
 
 def generate_t2i_prompt(item_name):
@@ -57,6 +56,7 @@ Focus on the item itself, ensuring it is fully described, and specify a plain, w
 @spaces.GPU(duration=75)
 def generate_item_image(object_t2i_prompt):
     trial_id = ""
+    pipe.cuda()
     for image in pipe.flux_pipe_call_that_returns_an_iterable_of_images(
         prompt=object_t2i_prompt,
         guidance_scale=3.5,