Add an in-memory evaluator for Estimator. It will run evaluation without a...

Add an in-memory evaluator for Estimator. It will run evaluation without a checkpoint. This will let user get evaluation metrics on more steps without saving.

  Example:

  ```python
  def train_input_fn():
    ...
    return train_dataset

  def eval_input_fn():
    ...
    return eval_dataset

  estimator = tf.estimator.DNNClassifier(...)

  evaluator = tf.contrib.estimator.InMemoryEvaluatorHook(
      estimator, eval_input_fn)
  estimator.train(train_input_fn, hooks=[evaluator])
  ```

PiperOrigin-RevId: 197181726