code: def test_lemmatizer_label_data():
      nlp = English()
      lemmatizer = nlp.add_pipe("trainable_lemmatizer")
      lemmatizer.min_tree_freq = 1
      train_examples = []
      for t in TRAIN_DATA:
          train_examples.append(
              Example.from_dict(nlp.make_doc(t[0]), t[1])
          )
  
      nlp.initialize(get_examples=lambda: train_examples)
  
      nlp2 = English()
      lemmatizer2 = nlp2.add_pipe("trainable_lemmatizer")
      lemmatizer2.initialize(
          get_examples=lambda: train_examples,
          labels=lemmatizer.label_data,
      )
  
      # Verify that the labels and trees are the same.
      assert lemmatizer.labels == lemmatizer2.labels
      assert lemmatizer.trees.to_bytes() == lemmatizer2.trees.to_bytes()
  
imports: import pickle
  import hypothesis.strategies
  import pytest
  from hypothesis import given
  from spacy import util
  from spacy.lang.en import English
  from spacy.language import Language
  from spacy.pipeline._edit_tree_internals.edit_trees import EditTrees
  from spacy.strings import StringStore
  from spacy.training import Example
  from spacy.util import make_tempdir
label_desc: Use image node_id 7 for calling a global function with example usage: test_lemmatizer_label_data() without return types