code: def test_tokenizer_oov_flag():
      """Test of Out of Vocabulary (OOV) flag in text.Tokenizer"""
      x_train = ["This text has only known words"]
      x_test = [
          "This text has some unknown words"
      ]  # 2 OOVs: some, unknown
  
      # Default, without OOV flag
      tokenizer = text.Tokenizer()
      tokenizer.fit_on_texts(x_train)
      x_test_seq = tokenizer.texts_to_sequences(x_test)
      assert len(x_test_seq[0]) == 4  # discards 2 OOVs
  
      # With OOV feature
      tokenizer = text.Tokenizer(oov_token="<unk>")
      tokenizer.fit_on_texts(x_train)
      x_test_seq = tokenizer.texts_to_sequences(x_test)
      assert len(x_test_seq[0]) == 6
  
imports: from collections import OrderedDict
  import numpy
  import pytest
  from tensorflow import keras
  from keras_preprocessing import text
label_desc: Use image node_id 13 for calling a global function with example usage: test_tokenizer_oov_flag() without return types