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| author |  Vijay Vasudevan <vrv@google.com> | 2016-11-03 17:07:01 -0800 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2016-11-03 18:24:53 -0700 |
| commit | 818993c7751601527d662d2417f220e4e856e4ef (patch) | |
| tree | a9cb33d6332f3e37d740cd6eb6984a1837714237 /tensorflow/g3doc/tutorials | |
| parent | a19c425536bba29997807bbbd5ed43386d3cb7bd (diff) | |
Merge changes from github.
Change: 138143557
Diffstat (limited to 'tensorflow/g3doc/tutorials')
| -rw-r--r-- | tensorflow/g3doc/tutorials/input_fn/index.md | 4 | ||||
| -rw-r--r-- | tensorflow/g3doc/tutorials/monitors/index.md | 4 |
2 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/g3doc/tutorials/input_fn/index.md b/tensorflow/g3doc/tutorials/input_fn/index.md index c562084a83..870e47b196 100644 --- a/tensorflow/g3doc/tutorials/input_fn/index.md +++ b/tensorflow/g3doc/tutorials/input_fn/index.md @@ -15,9 +15,9 @@ tutorial](../tflearn/index.md): ```py training_set = tf.contrib.learn.datasets.base.load_csv_with_header( - filename=IRIS_TRAINING, target_dtype=np.int) + filename=IRIS_TRAINING, target_dtype=np.int, features_dtype=np.float32) test_set = tf.contrib.learn.datasets.base.load_csv_with_header( - filename=IRIS_TEST, target_dtype=np.int) + filename=IRIS_TEST, target_dtype=np.int, features_dtype=np.float32) ... classifier.fit(x=training_set.data, diff --git a/tensorflow/g3doc/tutorials/monitors/index.md b/tensorflow/g3doc/tutorials/monitors/index.md index a086361925..65211d2f23 100644 --- a/tensorflow/g3doc/tutorials/monitors/index.md +++ b/tensorflow/g3doc/tutorials/monitors/index.md @@ -27,9 +27,9 @@ IRIS_TEST = "iris_test.csv" # Load datasets. training_set = tf.contrib.learn.datasets.base.load_csv_with_header( - filename=IRIS_TRAINING, target_dtype=np.int) + filename=IRIS_TRAINING, target_dtype=np.int, features_dtype=np.float32) test_set = tf.contrib.learn.datasets.base.load_csv_with_header( - filename=IRIS_TEST, target_dtype=np.int) + filename=IRIS_TEST, target_dtype=np.int, features_dtype=np.float32) # Specify that all features have real-value data feature_columns = [tf.contrib.layers.real_valued_column("", dimension=4)] |