code: def prepare_data(problem, hparams, params, config):
    
    input_fn = problem.make_estimator_input_fn(
        tf.estimator.ModeKeys.EVAL, hparams, force_repeat=True)
    dataset = input_fn(params, config)
    features, _ = dataset.make_one_shot_iterator().get_next()
    inputs, labels = features["targets"], features["inputs"]
    inputs = tf.to_float(inputs)
    input_shape = inputs.shape.as_list()
    inputs = tf.reshape(inputs, [hparams.batch_size] + input_shape[1:])
    labels = tf.reshape(labels, [hparams.batch_size])
    return inputs, labels, features
docs: Construct input pipeline.