Update app.py

app.py

@@ -220,6 +220,7 @@ 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(text_embeddings.dtype)
             with network:
                 noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=text_embeddings, timestep_cond= None).sample