Update generated Python Op docs.

Change: 138541463

7 files changed, 32 insertions, 38 deletions

diff --git a/tensorflow/g3doc/api_docs/python/contrib.distributions.md b/tensorflow/g3doc/api_docs/python/contrib.distributions.md
index 45c9792755..a97795573e 100644
--- a/tensorflow/g3doc/api_docs/python/contrib.distributions.md
+++ b/tensorflow/g3doc/api_docs/python/contrib.distributions.md
@@ -23063,6 +23063,19 @@ will broadcast in the case of multidimensional sets of parameters.
 
 Get the KL-divergence KL(dist_a || dist_b).
 
+If there is no KL method registered specifically for `type(dist_a)` and
+`type(dist_b)`, then the class hierarchies of these types are searched.
+
+If one KL method is registered between any pairs of classes in these two
+parent hierarchies, it is used.
+
+If more than one such registered method exists, the method whose registered
+classes have the shortest sum MRO paths to the input types is used.
+
+If more than one such shortest path exists, the first method
+identified in the search is used (favoring a shorter MRO distance to
+`type(dist_a)`).
+
 ##### Args:
 
 
@@ -23132,22 +23145,3 @@ Initialize the KL registrar.
 
 
 
-
-## Other Functions and Classes
-- - -
-
-### `tf.contrib.distributions.register_pairwise_kls(kl_classes, kl_fn)` {#register_pairwise_kls}
-
-Registers `kl_fn` for each pair of classes in `kl_classes`.
-
-##### Args:
-
-
-*  <b>`kl_classes`</b>: classes for which to register KL implementation
-*  <b>`kl_fn`</b>: The function to use for the KL divergence.
-
-##### Returns:
-
-  None
-
-
diff --git a/tensorflow/g3doc/api_docs/python/contrib.learn.md b/tensorflow/g3doc/api_docs/python/contrib.learn.md
index 363150c25b..3e4cc2144c 100644
--- a/tensorflow/g3doc/api_docs/python/contrib.learn.md
+++ b/tensorflow/g3doc/api_docs/python/contrib.learn.md
@@ -968,7 +968,7 @@ Input of `fit` and `evaluate` should have following features,
     whose `value` is a `Tensor`.
 - - -
 
-#### `tf.contrib.learn.DNNRegressor.__init__(hidden_units, feature_columns, model_dir=None, weight_column_name=None, optimizer=None, activation_fn=relu, dropout=None, gradient_clip_norm=None, enable_centered_bias=False, config=None, feature_engineering_fn=None)` {#DNNRegressor.__init__}
+#### `tf.contrib.learn.DNNRegressor.__init__(hidden_units, feature_columns, model_dir=None, weight_column_name=None, optimizer=None, activation_fn=relu, dropout=None, gradient_clip_norm=None, enable_centered_bias=False, config=None, feature_engineering_fn=None, label_dimension=1)` {#DNNRegressor.__init__}
 
 Initializes a `DNNRegressor` instance.
 
@@ -1004,6 +1004,7 @@ Initializes a `DNNRegressor` instance.
                     labels which are the output of `input_fn` and
                     returns features and labels which will be fed
                     into the model.
+*  <b>`label_dimension`</b>: Dimension of the label for multilabels. Defaults to 1.
 
 ##### Returns:
 
@@ -1636,7 +1637,7 @@ Construct a `LinearRegressor` estimator object.
 *  <b>`enable_centered_bias`</b>: A bool. If True, estimator will learn a centered
     bias variable for each class. Rest of the model structure learns the
     residual after centered bias.
-*  <b>`label_dimension`</b>: dimension of the label for multilabels.
+*  <b>`label_dimension`</b>: Dimension of the label for multilabels. Defaults to 1.
   _joint_weights: If True use a single (possibly partitioned) variable to
     store the weights. It's faster, but requires all feature columns are
     sparse and have the 'sum' combiner. Incompatible with SDCAOptimizer.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.contrib.learn.LinearRegressor.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.contrib.learn.LinearRegressor.md
index 2352b13897..02cf9a8674 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.contrib.learn.LinearRegressor.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.contrib.learn.LinearRegressor.md
@@ -63,7 +63,7 @@ Construct a `LinearRegressor` estimator object.
 *  <b>`enable_centered_bias`</b>: A bool. If True, estimator will learn a centered
     bias variable for each class. Rest of the model structure learns the
     residual after centered bias.
-*  <b>`label_dimension`</b>: dimension of the label for multilabels.
+*  <b>`label_dimension`</b>: Dimension of the label for multilabels. Defaults to 1.
   _joint_weights: If True use a single (possibly partitioned) variable to
     store the weights. It's faster, but requires all feature columns are
     sparse and have the 'sum' combiner. Incompatible with SDCAOptimizer.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.contrib.distributions.kl.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.contrib.distributions.kl.md
index ac63815077..08378205ac 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.contrib.distributions.kl.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.contrib.distributions.kl.md
@@ -2,6 +2,19 @@
 
 Get the KL-divergence KL(dist_a || dist_b).
 
+If there is no KL method registered specifically for `type(dist_a)` and
+`type(dist_b)`, then the class hierarchies of these types are searched.
+
+If one KL method is registered between any pairs of classes in these two
+parent hierarchies, it is used.
+
+If more than one such registered method exists, the method whose registered
+classes have the shortest sum MRO paths to the input types is used.
+
+If more than one such shortest path exists, the first method
+identified in the search is used (favoring a shorter MRO distance to
+`type(dist_a)`).
+
 ##### Args:
 
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.distributions.register_pairwise_kls.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.distributions.register_pairwise_kls.md
deleted file mode 100644
index d3b9ff5211..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.distributions.register_pairwise_kls.md
+++ /dev/null
@@ -1,14 +0,0 @@
-### `tf.contrib.distributions.register_pairwise_kls(kl_classes, kl_fn)` {#register_pairwise_kls}
-
-Registers `kl_fn` for each pair of classes in `kl_classes`.
-
-##### Args:
-
-
-*  <b>`kl_classes`</b>: classes for which to register KL implementation
-*  <b>`kl_fn`</b>: The function to use for the KL divergence.
-
-##### Returns:
-
-  None
-
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.learn.DNNRegressor.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.learn.DNNRegressor.md
index b8ec5779f3..74a1773c77 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.learn.DNNRegressor.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.learn.DNNRegressor.md
@@ -53,7 +53,7 @@ Input of `fit` and `evaluate` should have following features,
     whose `value` is a `Tensor`.
 - - -
 
-#### `tf.contrib.learn.DNNRegressor.__init__(hidden_units, feature_columns, model_dir=None, weight_column_name=None, optimizer=None, activation_fn=relu, dropout=None, gradient_clip_norm=None, enable_centered_bias=False, config=None, feature_engineering_fn=None)` {#DNNRegressor.__init__}
+#### `tf.contrib.learn.DNNRegressor.__init__(hidden_units, feature_columns, model_dir=None, weight_column_name=None, optimizer=None, activation_fn=relu, dropout=None, gradient_clip_norm=None, enable_centered_bias=False, config=None, feature_engineering_fn=None, label_dimension=1)` {#DNNRegressor.__init__}
 
 Initializes a `DNNRegressor` instance.
 
@@ -89,6 +89,7 @@ Initializes a `DNNRegressor` instance.
                     labels which are the output of `input_fn` and
                     returns features and labels which will be fed
                     into the model.
+*  <b>`label_dimension`</b>: Dimension of the label for multilabels. Defaults to 1.
 
 ##### Returns:
 
diff --git a/tensorflow/g3doc/api_docs/python/index.md b/tensorflow/g3doc/api_docs/python/index.md
index 47e4639a12..9556b3b1c1 100644
--- a/tensorflow/g3doc/api_docs/python/index.md
+++ b/tensorflow/g3doc/api_docs/python/index.md
@@ -758,7 +758,6 @@
   * [`NormalWithSoftplusSigma`](../../api_docs/python/contrib.distributions.md#NormalWithSoftplusSigma)
   * [`Poisson`](../../api_docs/python/contrib.distributions.md#Poisson)
   * [`QuantizedDistribution`](../../api_docs/python/contrib.distributions.md#QuantizedDistribution)
-  * [`register_pairwise_kls`](../../api_docs/python/contrib.distributions.md#register_pairwise_kls)
   * [`RegisterKL`](../../api_docs/python/contrib.distributions.md#RegisterKL)
   * [`StudentT`](../../api_docs/python/contrib.distributions.md#StudentT)
   * [`StudentTWithAbsDfSoftplusSigma`](../../api_docs/python/contrib.distributions.md#StudentTWithAbsDfSoftplusSigma)