2 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/examples/tutorials/mnist/fully_connected_feed.py b/tensorflow/examples/tutorials/mnist/fully_connected_feed.py
index fbf4000e8f..be50f4529f 100644
--- a/tensorflow/examples/tutorials/mnist/fully_connected_feed.py
+++ b/tensorflow/examples/tutorials/mnist/fully_connected_feed.py
@@ -108,7 +108,7 @@ def do_eval(sess,
                                images_placeholder,
                                labels_placeholder)
     true_count += sess.run(eval_correct, feed_dict=feed_dict)
-  precision = true_count / num_examples
+  precision = float(true_count) / num_examples
   print('  Num examples: %d  Num correct: %d  Precision @ 1: %0.04f' %
         (num_examples, true_count, precision))
 
@@ -146,7 +146,7 @@ def run_training():
     init = tf.global_variables_initializer()
 
     # Create a saver for writing training checkpoints.
-    saver = tf.train.Saver(write_version=tf.train.SaverDef.V2)
+    saver = tf.train.Saver()
 
     # Create a session for running Ops on the Graph.
     sess = tf.Session()
diff --git a/tensorflow/examples/tutorials/mnist/mnist_softmax.py b/tensorflow/examples/tutorials/mnist/mnist_softmax.py
index 9d00c0f9af..42a406d386 100644
--- a/tensorflow/examples/tutorials/mnist/mnist_softmax.py
+++ b/tensorflow/examples/tutorials/mnist/mnist_softmax.py
@@ -25,7 +25,6 @@ from __future__ import print_function
 import argparse
 import sys
 
-# Import data
 from tensorflow.examples.tutorials.mnist import input_data
 
 import tensorflow as tf
@@ -34,6 +33,7 @@ FLAGS = None
 
 
 def main(_):
+  # Import data
   mnist = input_data.read_data_sets(FLAGS.data_dir, one_hot=True)
 
   # Create the model
@@ -58,8 +58,8 @@ def main(_):
   train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
 
   sess = tf.InteractiveSession()
-  # Train
   tf.global_variables_initializer().run()
+  # Train
   for _ in range(1000):
     batch_xs, batch_ys = mnist.train.next_batch(100)
     sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})