def experiment_functions():
  """Get the necessary functions to run an experiment."""
  # Build the memory-intensive embeddings once and enclose them in all the
  # functions that use it.
  embeddings = embedding_utils.PretrainedWordEmbeddings(
      embeddings_path=FLAGS.embeddings_path,
      max_vocab_size=FLAGS.max_vocab_size,
      num_oov_buckets=1000,
      lowercase=True)
  model_fn = functools.partial(model_function, embeddings=embeddings)
  train_input_fn = functools.partial(
      input_function, is_train=True, embeddings=embeddings)
  eval_input_fn = functools.partial(
      input_function, is_train=False, embeddings=embeddings)
  serving_input_receiver_fn = functools.partial(
      serving_input_receiver_function, embeddings=embeddings)
  return (model_fn, train_input_fn, eval_input_fn, serving_input_receiver_fn)
Get the necessary functions to run an experiment.
language/question_answering/decatt_docreader/models/nq_long_model.py