<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def get_batch(self):
 """Returns set of nth-farthest input tensors and labels. Returns: 1. tf.Tensor (`batch_size`, `num_objects`, (`num_features` + 3 * `num_objects`)). 2. tf.Tensor (`batch_size`). Output object reference label. """

    params = [self._batch_size, self._num_objects, self._num_features]
    inputs, labels = tf.py_func(self._get_batch_data, params,
                                [tf.float32, tf.float32])
    inputs = tf.reshape(inputs, [self._batch_size, self._num_objects,
                                 self._num_features + self._num_objects * 3])
    labels = tf.reshape(labels, [-1])
    return inputs, labels