code: def bench_text_embeddings(model, texts):
      total_duration, embeddings = duration(
          lambda: model.encode_text(model.preprocess_text(texts))
      )
      total_length = len(embeddings)
      print(f"Throughput: {total_length/total_duration:.2f} queries/s")
  
file_path: uform/scripts/bench.py
imports: import requests
  from time import perf_counter
  from typing import List
  from PIL import Image
  import torch
  from uform import get_model
  from uform.gen_model import VLMForCausalLM, VLMProcessor
  from transformers import InstructBlipProcessor, InstructBlipForConditionalGeneration
  from transformers import AutoProcessor, LlavaForConditionalGeneration
label_desc: Use image node_id 5 for calling a global function with example usage: bench_text_embeddings(model, texts) without return types