Update app.py

app.py

@@ -89,13 +89,12 @@ class ModelWrapper:
         else:
             raise NotImplementedError()
         
+        prompt_embed = prompt_embed.to(dtype=torch.float16)
         DTYPE = prompt_embed.dtype
         print(DTYPE)
         
         for constant in all_timesteps:
             current_timesteps = torch.ones(len(prompt_embed), device="cuda", dtype=torch.long) * constant
-            print(type(current_timesteps))
-            print(type(noise))
             eval_images = self.model(noise, current_timesteps, prompt_embed, added_cond_kwargs=unet_added_conditions).sample
             print(type(eval_images))