modified: gradio_app.py

gradio_app.py

@@ -253,6 +253,13 @@ def infer(prompt, sample_image, recraft_model, seed=0):
 
     model.to(device)
 
+    print(f"Model device: {model.device}")
+    print(f"Noise device: {noise.device}")
+    print(f"Image IDs device: {img_ids.device}")
+    print(f"T5 output device: {t5_out.device}")
+    print(f"Text IDs device: {txt_ids.device}")
+    print(f"L pooled device: {l_pooled.device}")
+
     # Run the denoising process
     with accelerator.autocast(), torch.no_grad():
         x = flux_train_utils.denoise(