code: def test_no_update_listener_in_predict():
      orig_config = Config().from_str(cfg_string)
      nlp = util.load_model_from_config(
          orig_config, auto_fill=True, validate=True
      )
      listener = (
          nlp.get_pipe("tagger")
          .model.get_ref("tok2vec")
          .get_ref("listener")
      )
      transformer = nlp.get_pipe("transformer")
  
      text = "This is awesome"
      examples = [
          Example.from_dict(
              nlp.make_doc(text), {"tags": ["A", "B", "C"]}
          )
      ]
      docs = [eg.predicted for eg in examples]
      nlp.initialize(lambda: examples)
  
      transformer.update(examples)
      assert listener._backprop is not None
  
      transformer.predict(docs)
      assert listener._backprop is not None
  
imports: import pytest
  from packaging.version import Version
  import torch
  import spacy
  from spacy.language import Language
  from spacy.training.example import Example
  from spacy.util import make_tempdir
  from spacy.vocab import Vocab
  from spacy.tokens import Doc
  from spacy import util
  from thinc.api import Model, Config, get_current_ops, NumpyOps
  from spacy.tests.util import assert_docs_equal
  from .util import DummyTransformer, _assert_equal_tensors
  from ..None import TransformerModel
  from ..pipeline_component import Transformer
  from ..layers import TransformerListener
  from ..data_classes import TransformerData, FullTransformerBatch
label_desc: Use image node_id 21 for calling a global function with example usage: test_no_update_listener_in_predict() without return types