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| author |  Mark Daoust <markdaoust@google.com> | 2018-07-06 05:46:42 -0700 |
|---|---|---|
| committer |  GitHub <noreply@github.com> | 2018-07-06 05:46:42 -0700 |
| commit | 9f3bd2cf1eccdc76ed1934ade96c6cd4464bb8b2 (patch) | |
| tree | aa40a871f75e4e7fb6e4c84f49530640f116d813 /tensorflow/examples | |
| parent | 3f18817317940253e6ec0e6b412492c5add5927b (diff) | |
lint fix
Diffstat (limited to 'tensorflow/examples')
| -rw-r--r-- | tensorflow/examples/tutorials/mnist/mnist_deep.py | 4 |
1 files changed, 3 insertions, 1 deletions
diff --git a/tensorflow/examples/tutorials/mnist/mnist_deep.py b/tensorflow/examples/tutorials/mnist/mnist_deep.py index 47d2777813..5d8d8d84fe 100644 --- a/tensorflow/examples/tutorials/mnist/mnist_deep.py +++ b/tensorflow/examples/tutorials/mnist/mnist_deep.py @@ -170,7 +170,9 @@ def main(_): accuracy_l = [] for _ in range(20): batch = mnist.test.next_batch(500, shuffle=False) - accuracy_l.append(accuracy.eval(feed_dict={x: batch[0], y_: batch[1], keep_prob: 1.0})) + accuracy_l.append(accuracy.eval(feed_dict={x: batch[0], + y_: batch[1], + keep_prob: 1.0})) print('test accuracy %g' % numpy.mean(accuracy_l)) |