with tf.name_scope('digit1/'):
  with tf.variable_scope('digit1/'):
    softmax1_weights = tf.get_variable('digit1_w', shape=[num_hidden, num_labels],
                                      initializer=tf.contrib.layers.xavier_initializer())
    softmax1_biases = tf.get_variable('digit1_b', shape=[num_labels],
                                      initializer=tf.random_uniform_initializer(-0.1, 0.1))

  tf.summary.histogram('weights', softmax1_weights)
  tf.summary.histogram('bias', softmax1_biases)

summary = tf.summary.merge_all()