Direct users of the old KMeans estimator to use the new one that's built from the core Estimator API.

PiperOrigin-RevId: 172108321

1 files changed, 18 insertions, 2 deletions

diff --git a/tensorflow/contrib/learn/python/learn/estimators/kmeans.py b/tensorflow/contrib/learn/python/learn/estimators/kmeans.py
index a92302420f..992b804f59 100644
--- a/tensorflow/contrib/learn/python/learn/estimators/kmeans.py
+++ b/tensorflow/contrib/learn/python/learn/estimators/kmeans.py
@@ -12,7 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-"""Implementation of k-means clustering on top of `Estimator` API."""
+"""Implementation of k-means clustering on top of `Estimator` API.
+
+This module is deprecated. Please use
+@{tf.contrib.factorization.KMeansClustering} instead of
+@{tf.contrib.learn.KMeansClustering}. It has a similar interface, but uses the
+@{tf.estimator.Estimator} API instead of @{tf.contrib.learn.Estimator}.
+"""
 
 from __future__ import absolute_import
 from __future__ import division
@@ -29,12 +35,17 @@ from tensorflow.python.framework import ops
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import state_ops
-from tensorflow.python.summary import summary
 from tensorflow.python.ops.control_flow_ops import with_dependencies
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.summary import summary
 from tensorflow.python.training import session_run_hook
 from tensorflow.python.training.session_run_hook import SessionRunArgs
+from tensorflow.python.util.deprecation import deprecated
+
+_USE_TF_CONTRIB_FACTORIZATION = (
+    'Please use tf.contrib.factorization.KMeansClustering instead of'
+    ' tf.contrib.learn.KMeansClustering. It has a similar interface, but uses'
+    ' the tf.estimator.Estimator API instead of tf.contrib.learn.Estimator.')
 
 
 class _LossRelativeChangeHook(session_run_hook.SessionRunHook):
@@ -153,6 +164,7 @@ class KMeansClustering(estimator.Estimator):
   ALL_SCORES = 'all_scores'
   LOSS_OP_NAME = 'kmeans_loss'
 
+  @deprecated(None, _USE_TF_CONTRIB_FACTORIZATION)
   def __init__(self,
                num_clusters,
                model_dir=None,
@@ -204,6 +216,7 @@ class KMeansClustering(estimator.Estimator):
         model_dir=model_dir,
         config=config)
 
+  @deprecated(None, _USE_TF_CONTRIB_FACTORIZATION)
   def predict_cluster_idx(self, input_fn=None):
     """Yields predicted cluster indices."""
     key = KMeansClustering.CLUSTER_IDX
@@ -212,6 +225,7 @@ class KMeansClustering(estimator.Estimator):
     for result in results:
       yield result[key]
 
+  @deprecated(None, _USE_TF_CONTRIB_FACTORIZATION)
   def score(self, input_fn=None, steps=None):
     """Predict total sum of distances to nearest clusters.
 
@@ -229,6 +243,7 @@ class KMeansClustering(estimator.Estimator):
         self.evaluate(
             input_fn=input_fn, steps=steps)[KMeansClustering.SCORES])
 
+  @deprecated(None, _USE_TF_CONTRIB_FACTORIZATION)
   def transform(self, input_fn=None, as_iterable=False):
     """Transforms each element to distances to cluster centers.
 
@@ -255,6 +270,7 @@ class KMeansClustering(estimator.Estimator):
     else:
       return results
 
+  @deprecated(None, _USE_TF_CONTRIB_FACTORIZATION)
   def clusters(self):
     """Returns cluster centers."""
     return super(KMeansClustering, self).get_variable_value(self.CLUSTERS)