Refactor CUDA device usage in app.py

app.py

@@ -118,7 +118,7 @@ def process(input_fg, prompt, input_undo_steps, image_width, image_height, seed,
 
     fg = resize_and_center_crop(input_fg, image_width, image_height)
     concat_conds = numpy2pytorch([fg]).to(device="cuda", dtype=vae.dtype)
-    concat_conds = vae.encode(concat_conds).latent_dist.mode() * vae.config.scaling_factor
+    concat_conds = vae.encode(torch.tensor(concat_conds)).latent_dist.mode() * vae.config.scaling_factor
 
     conds = encode_cropped_prompt_77tokens(prompt)
     unconds = encode_cropped_prompt_77tokens(n_prompt)