Merge changes from github.

Change: 151046259

4 files changed, 11 insertions, 7 deletions

diff --git a/tensorflow/examples/learn/README.md b/tensorflow/examples/learn/README.md
index b36986855f..37157fc296 100644
--- a/tensorflow/examples/learn/README.md
+++ b/tensorflow/examples/learn/README.md
@@ -1,7 +1,7 @@
 # TF Learn Examples
 
 Learn is a high-level API for TensorFlow that allows you to create,
-train, and use deep learning models easily. See the [Quickstart tutorial](../../g3doc/tutorials/tflearn/index.md)
+train, and use deep learning models easily. See the [Quickstart tutorial](https://www.tensorflow.org/get_started/tflearn)
 for an introduction to the API.
 
 To run most of these examples, you need to install the `scikit learn` library (`sudo pip install sklearn`).
diff --git a/tensorflow/examples/learn/boston.py b/tensorflow/examples/learn/boston.py
index 2986ff9106..19cfdee513 100644
--- a/tensorflow/examples/learn/boston.py
+++ b/tensorflow/examples/learn/boston.py
@@ -16,19 +16,22 @@
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
-from sklearn import cross_validation
+
+from sklearn import datasets
+from sklearn import model_selection
 from sklearn import metrics
 from sklearn import preprocessing
+
 import tensorflow as tf
 
 
 def main(unused_argv):
   # Load dataset
-  boston = tf.contrib.learn.datasets.load_dataset('boston')
+  boston = datasets.load_boston()
   x, y = boston.data, boston.target
 
   # Split dataset into train / test
-  x_train, x_test, y_train, y_test = cross_validation.train_test_split(
+  x_train, x_test, y_train, y_test = model_selection.train_test_split(
       x, y, test_size=0.2, random_state=42)
 
   # Scale data (training set) to 0 mean and unit standard deviation.
diff --git a/tensorflow/examples/learn/iris.py b/tensorflow/examples/learn/iris.py
index 7b65eb521a..ec2aa9b573 100644
--- a/tensorflow/examples/learn/iris.py
+++ b/tensorflow/examples/learn/iris.py
@@ -17,7 +17,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-
+from sklearn import datasets
 from sklearn import metrics
 from sklearn import model_selection
 
@@ -26,7 +26,7 @@ import tensorflow as tf
 
 def main(unused_argv):
   # Load dataset.
-  iris = tf.contrib.learn.datasets.load_dataset('iris')
+  iris = datasets.load_iris()
   x_train, x_test, y_train, y_test = model_selection.train_test_split(
       iris.data, iris.target, test_size=0.2, random_state=42)
 
diff --git a/tensorflow/examples/learn/text_classification.py b/tensorflow/examples/learn/text_classification.py
index c3d00a11b9..7e10014c39 100644
--- a/tensorflow/examples/learn/text_classification.py
+++ b/tensorflow/examples/learn/text_classification.py
@@ -24,6 +24,7 @@ import numpy as np
 import pandas
 from sklearn import metrics
 import tensorflow as tf
+from tensorflow.contrib.layers.python.layers import encoders
 
 learn = tf.contrib.learn
 
@@ -37,7 +38,7 @@ n_words = 0
 def bag_of_words_model(features, target):
   """A bag-of-words model. Note it disregards the word order in the text."""
   target = tf.one_hot(target, 15, 1, 0)
-  features = tf.contrib.layers.bow_encoder(
+  features = encoders.bow_encoder(
       features, vocab_size=n_words, embed_dim=EMBEDDING_SIZE)
   logits = tf.contrib.layers.fully_connected(features, 15, activation_fn=None)
   loss = tf.contrib.losses.softmax_cross_entropy(logits, target)