import tensorflow as tf

      #accuracy1 = tf.reduce_sum(
      #                         tf.nn.in_top_k(tf.cast(tf.Variable(predictions2), tf.float32),
      #                         tf.cast((tf.constant(np_labels), 1), tf.float32)))
      accuracy1 = tf.reduce_sum(
          input_tensor=tf.cast(tf.nn.in_top_k(predictions=tf.constant(predictions1),
              targets=tf.constant(np_labels), k=1), tf.float32))

      accuracy5 = tf.reduce_sum(
          input_tensor=tf.cast(tf.nn.in_top_k(predictions=tf.constant(predictions1),
              targets=tf.constant(np_labels), k=5), tf.float32))
      np_accuracy1, np_accuracy5 =  sess.run([accuracy1, accuracy5])

      ##print(labels)
      total_accuracy1 += np_accuracy1
      total_accuracy5 += np_accuracy5
      print("Processed %d images. (Top1 accuracy, Top5 accuracy) = (%0.4f, %0.4f)" \
