code: def setUp(self) -> None:
      tf.random.set_seed(42)
      np.random.seed(42)
      self.data = [("a b", "c"), ("a b c", "d")]
      tokenizer_encoder = KerasTokenizer(lower=False, filters="")
      tokenizer_decoder = KerasTokenizer(lower=False, filters="")
      tokenizer_encoder.fit(["a b c <start> <end>"])
      tokenizer_decoder.fit(["c d <start> <end>"])
      self.vectorizer = Vectorizer(
          tokenizer_encoder=tokenizer_encoder,
          tokenizer_decoder=tokenizer_decoder,
          max_output_len=3,
      )
      self.preprocessor = Preprocessor()
      batch_generator = DatasetGenerator(2)
      data_prep = [self.preprocessor(d) for d in self.data]
      data_vecs = [self.vectorizer(d) for d in data_prep]
      self.dataset = batch_generator(lambda: data_vecs)
      self.loss_func = masked_crossentropy
  
file_path: headliner/tests/test_training.py
imports: import unittest
  import numpy
  import tensorflow
  from headliner.losses import masked_crossentropy
  from headliner.model.basic_summarizer import BasicSummarizer
  from headliner.model.attention_summarizer import AttentionSummarizer
  from headliner.model.transformer_summarizer import TransformerSummarizer
  from headliner.preprocessing.dataset_generator import DatasetGenerator
  from headliner.preprocessing.keras_tokenizer import KerasTokenizer
  from headliner.preprocessing.preprocessor import Preprocessor
  from headliner.preprocessing.vectorizer import Vectorizer
label_desc: Use image node_id 1 for calling the TestTraining obj's underlying member method code with example usage: obj.setUp() without return types