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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def add_evaluation_step(result_tensor, ground_truth_tensor):
 """Inserts the operations we need to evaluate the accuracy of our results. Args: result_tensor: The new final node that produces results. ground_truth_tensor: The node we feed ground truth data into. Returns: Tuple of (evaluation step, prediction). """

  with tf.name_scope('accuracy'):
    with tf.name_scope('correct_prediction'):
      prediction = tf.argmax(result_tensor, 1)
      correct_prediction = tf.equal(prediction, ground_truth_tensor)
    with tf.name_scope('accuracy'):
      evaluation_step = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
  tf.summary.scalar('accuracy', evaluation_step)
  return evaluation_step, prediction