t5 to cpu

app.py

@@ -187,6 +187,8 @@ def edit(brush_canvas, source_prompt, inversion_guidance,
     print(f'optimizing & editing noise, {target_prompt} with seed {seed}, noise_scale {noise_scale}, training_epochs {training_epochs}')
     model.to(device)
     if training_epochs != 0:
+        t5.to('cpu')
+        clip.to('cpu')
         torch.set_grad_enabled(True)
         inp_optim["img"] = z0
         _, info, _, _, trainable_noise_list = denoise_with_noise_optim(model,**inp_optim,token_ids=token_ids,source_mask=source_mask,training_steps=1,training_epochs=training_epochs,learning_rate=0.01,seed=seed,noise_scale=noise_scale,timesteps=timesteps,info=info,guidance=denoise_guidance)
@@ -233,8 +235,8 @@ def edit(brush_canvas, source_prompt, inversion_guidance,
             Image.fromarray(binary_mask, mode="L").save(output_path.replace(target_object,f'{target_object}_mask'))
         t1 = time.perf_counter()  
         print(f"Done in {t1 - t0:.1f}s.", f'Saving {output_path} .' if save else 'No saving files.')
-        t5.to(device)
-        clip.to(device)
+    t5.to(device)
+    clip.to(device)
     
     return img