code: def _train_input_fn():
      """Train input function."""
      features = tf.compat.v1.data.make_one_shot_iterator(
          tf.data.Dataset.from_tensors(
              tf.constant(["3", "0", "1", "2"])
          )
          .repeat()
          .map(_parse_csv)
      ).get_next()
  
      return features, features["input_index"]
  
file_path: model-analysis/tensorflow_model_analysis/eval_saved_model/example_trainers/fake_multi_examples_per_input_estimator.py
imports: import tensorflow
  from tensorflow import estimator
  from tensorflow_model_analysis.eval_saved_model import export
  from tensorflow_model_analysis.eval_saved_model.example_trainers import util
  from tensorflow.python.estimator.canned import metric_keys
label_desc: Use image node_id 9 for calling a global function with example usage: _train_input_fn() and returns: features,  features