Convert input_ids to float32 data type

app.py

@@ -27,7 +27,8 @@ scheduler = LMSDiscreteScheduler(beta_start=beta_start, beta_end=beta_end, beta_
 def text_enc(prompts, maxlen=None):
     if maxlen is None: maxlen = tokenizer.model_max_length
     inp = tokenizer(prompts, padding="max_length", max_length=maxlen, truncation=True, return_tensors="pt")
-    input_ids = inp.input_ids.long()  # Convert input_ids to Long data type
+    input_ids = inp.input_ids
+    input_ids = input_ids.to(torch.float32)  # Convert input_ids to float32 data type
     return text_encoder(input_ids)[0]
 
 def do_both(prompts):