Update generated Python Op docs.

Change: 147122384

2 files changed, 8 insertions, 2 deletions

diff --git a/tensorflow/g3doc/api_docs/python/contrib.learn.md b/tensorflow/g3doc/api_docs/python/contrib.learn.md
index 13f2f8c9d4..3af0320800 100644
--- a/tensorflow/g3doc/api_docs/python/contrib.learn.md
+++ b/tensorflow/g3doc/api_docs/python/contrib.learn.md
@@ -860,7 +860,7 @@ Returns a path in which the eval process will look for checkpoints.
 An Estimator for K-Means clustering.
 - - -
 
-#### `tf.contrib.learn.KMeansClustering.__init__(num_clusters, model_dir=None, initial_clusters='random', distance_metric='squared_euclidean', random_seed=0, use_mini_batch=True, kmeans_plus_plus_num_retries=2, relative_tolerance=None, config=None)` {#KMeansClustering.__init__}
+#### `tf.contrib.learn.KMeansClustering.__init__(num_clusters, model_dir=None, initial_clusters='random', distance_metric='squared_euclidean', random_seed=0, use_mini_batch=True, mini_batch_steps_per_iteration=1, kmeans_plus_plus_num_retries=2, relative_tolerance=None, config=None)` {#KMeansClustering.__init__}
 
 Creates a model for running KMeans training and inference.
 
@@ -876,6 +876,9 @@ Creates a model for running KMeans training and inference.
 *  <b>`random_seed`</b>: Python integer. Seed for PRNG used to initialize centers.
 *  <b>`use_mini_batch`</b>: If true, use the mini-batch k-means algorithm. Else assume
     full batch.
+*  <b>`mini_batch_steps_per_iteration`</b>: number of steps after which the updated
+    cluster centers are synced back to a master copy. See clustering_ops.py
+    for more details.
 *  <b>`kmeans_plus_plus_num_retries`</b>: For each point that is sampled during
     kmeans++ initialization, this parameter specifies the number of
     additional points to draw from the current distribution before selecting
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.contrib.learn.KMeansClustering.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.contrib.learn.KMeansClustering.md
index 4eb8750685..712b3d1140 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.contrib.learn.KMeansClustering.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.contrib.learn.KMeansClustering.md
@@ -1,7 +1,7 @@
 An Estimator for K-Means clustering.
 - - -
 
-#### `tf.contrib.learn.KMeansClustering.__init__(num_clusters, model_dir=None, initial_clusters='random', distance_metric='squared_euclidean', random_seed=0, use_mini_batch=True, kmeans_plus_plus_num_retries=2, relative_tolerance=None, config=None)` {#KMeansClustering.__init__}
+#### `tf.contrib.learn.KMeansClustering.__init__(num_clusters, model_dir=None, initial_clusters='random', distance_metric='squared_euclidean', random_seed=0, use_mini_batch=True, mini_batch_steps_per_iteration=1, kmeans_plus_plus_num_retries=2, relative_tolerance=None, config=None)` {#KMeansClustering.__init__}
 
 Creates a model for running KMeans training and inference.
 
@@ -17,6 +17,9 @@ Creates a model for running KMeans training and inference.
 *  <b>`random_seed`</b>: Python integer. Seed for PRNG used to initialize centers.
 *  <b>`use_mini_batch`</b>: If true, use the mini-batch k-means algorithm. Else assume
     full batch.
+*  <b>`mini_batch_steps_per_iteration`</b>: number of steps after which the updated
+    cluster centers are synced back to a master copy. See clustering_ops.py
+    for more details.
 *  <b>`kmeans_plus_plus_num_retries`</b>: For each point that is sampled during
     kmeans++ initialization, this parameter specifies the number of
     additional points to draw from the current distribution before selecting