code: def train_input_fn():
      """Train input function."""
      classes = tf.SparseTensor(
          values=[
              "first1",
              "first2",
              "second1",
              "third1",
              "third2",
              "third3",
              "fourth1",
          ],
          indices=[
              [0, 0],
              [0, 1],
              [1, 0],
              [2, 0],
              [2, 1],
              [2, 2],
              [3, 0],
          ],
          dense_shape=[4, 3],
      )
      scores = tf.SparseTensor(
          values=[0.9, 0.9, 0.9, 0.9, 0.8, 0.7, 0.9],
          indices=[
              [0, 0],
              [0, 1],
              [1, 0],
              [2, 0],
              [2, 1],
              [2, 2],
              [3, 0],
          ],
          dense_shape=[4, 3],
      )
      return {
          "classes": classes,
          "scores": scores,
      }, classes
  
file_path: model-analysis/tensorflow_model_analysis/eval_saved_model/example_trainers/fixed_prediction_classifier.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
  from tensorflow.python.estimator.canned import prediction_keys
label_desc: Use image node_id 2 for calling a global function with example usage: train_input_fn() and returns: dict,  classes