import tensorflow as tf

    learning_rate,
    num_train_steps,
    num_warmup_steps,
    use_tpu,
    use_one_hot_embeddings,
):
    """Returns `model_fn` closure for TPUEstimator."""

    def model_fn(features, labels, mode, params):  # pylint: disable=unused-argument
        """The `model_fn` for TPUEstimator."""

        tf.logging.info("*** Features ***")
        for name in sorted(features.keys()):
            tf.logging.info("  name = %s, shape = %s" % (name, features[name].shape))

        input_ids = features["input_ids"]
        input_mask = features["input_mask"]
        segment_ids = features["segment_ids"]
        masked_lm_positions = features["masked_lm_positions"]
        masked_lm_ids = features["masked_lm_ids"]
        masked_lm_weights = features["masked_lm_weights"]
        next_sentence_labels = features["next_sentence_labels"]
