import tensorflow as tf

    saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")
    with self.test_session(graph=tf.Graph()) as sess:
      # Creates an inference graph.
      # Hidden 1
      images = tf.constant(1.2, tf.float32, shape=[100, 28])
      with tf.name_scope("hidden1"):
        weights = tf.Variable(
            tf.truncated_normal([28, 128],
                                stddev=1.0 / math.sqrt(float(28))),
            name="weights")
        biases = tf.Variable(tf.zeros([128]),
                             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"):
