Update app.py

app.py

@@ -213,8 +213,12 @@ class main():
         for i,t in enumerate(tqdm.tqdm(self.noise_scheduler.timesteps)):
             latent_model_input = torch.cat([latents] * 2)
             latent_model_input = self.noise_scheduler.scale_model_input(latent_model_input, timestep=t)
-            print("going into inference 1")
             with self.network:
+                print(latent_model_input.device)
+                print(self.unet.device)
+                print(self.text_encoder.device)
+                print(self.vae.device)
+                print(self.network.proj.device)
                 noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=text_embeddings, timestep_cond= None).sample
                 #guidance
             noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)