code: def test_classify_batch():
      out = text_classification(
          [classify_context, classify_context],
          [classify_labels, classify_labels],
      )
      assert isinstance(out, list), "Output is not a list"
  
      for out in out:
          assert isinstance(out, dict), "List item is not a dict"
          assert len(out.keys()) == len(
              classify_labels
          ), "Incorrect number of labels"
          assert classify_correct == max(
              out, key=out.get
          ), "Classification is severely wrong"
  
imports: from backprop import Emotion, ImageClassification, QA, Summarisation, TextClassification, TextGeneration, TextVectorisation
  import numpy
  import torch
  import os
label_desc: Use image node_id 10 for calling a global function with example usage: test_classify_batch() without return types