Update app.py

app.py

@@ -213,14 +213,14 @@ class main():
                                     [negative_prompt], padding="max_length", max_length=max_length, return_tensors="pt"
                                 )
         uncond_embeddings = self.text_encoder(uncond_input.input_ids.to(device))[0]
-        text_embeddings = torch.cat([uncond_embeddings, text_embeddings])
+        text_embeddings = torch.cat([uncond_embeddings, text_embeddings]).bfloat16()
         self.noise_scheduler.set_timesteps(ddim_steps) 
         latents = latents * self.noise_scheduler.init_noise_sigma
             
         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