import tensorflow as tf

                             name="biases")
        hidden1 = tf.nn.relu(tf.matmul(images, weights) + biases)
      # Hidden 2
      with tf.name_scope("hidden2"):
        weights = tf.Variable(
            tf.truncated_normal([128, 32],
                                stddev=1.0 / math.sqrt(float(128))),
            name="weights")
        biases = tf.Variable(tf.zeros([32]),
                             name="biases")
        hidden2 = tf.nn.relu(tf.matmul(hidden1, weights) + biases)
      # Linear
      with tf.name_scope("softmax_linear"):
        weights = tf.Variable(
            tf.truncated_normal([32, 10],
                                stddev=1.0 / math.sqrt(float(32))),
