Update app.py

app.py

@@ -28,8 +28,7 @@ def get_target_style_embeddings(target_texts_batch):
     return mean_embeddings.float().cpu().numpy()
 
 def get_luar_embeddings(texts_batch):
-    print("HERE", texts_batch)
-    assert set([len(texts) for texts in texts_batch]) == 1
+    assert len(set([len(texts) for texts in texts_batch])) == 1
     episodes = texts_batch
     tokenized_episodes = [luar_tokenizer(episode, max_length=512, padding="longest", truncation=True, return_tensors="pt").to(device) for episode in episodes]
     episode_lengths = [t["attention_mask"].shape[0] for t in tokenized_episodes]