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Diffstat (limited to 'tensorflow/docs_src/tutorials/wide_and_deep.md')
| -rw-r--r-- | tensorflow/docs_src/tutorials/wide_and_deep.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/tensorflow/docs_src/tutorials/wide_and_deep.md b/tensorflow/docs_src/tutorials/wide_and_deep.md index b5e5981fe1..dd830eeca9 100644 --- a/tensorflow/docs_src/tutorials/wide_and_deep.md +++ b/tensorflow/docs_src/tutorials/wide_and_deep.md @@ -255,7 +255,7 @@ After reading in the data, you can train and evaluate the model: m.fit(input_fn=train_input_fn, steps=200) results = m.evaluate(input_fn=eval_input_fn, steps=1) for key in sorted(results): - print "%s: %s" % (key, results[key]) + print("%s: %s" % (key, results[key])) ``` The first line of the output should be something like `accuracy: 0.84429705`. We |