Update generated Python Op docs.

Change: 142495971

2 files changed, 12 insertions, 6 deletions

diff --git a/tensorflow/g3doc/api_docs/python/contrib.layers.md b/tensorflow/g3doc/api_docs/python/contrib.layers.md
index a776cb197f..673536140a 100644
--- a/tensorflow/g3doc/api_docs/python/contrib.layers.md
+++ b/tensorflow/g3doc/api_docs/python/contrib.layers.md
@@ -79,9 +79,10 @@ can have speed penalty, specially in distributed settings.
     `data_format` is `NHWC` and the second dimension if `data_format` is
     `NCHW`.
 *  <b>`decay`</b>: decay for the moving average. Reasonable values for `decay` are close
-    to 1.0, typically in the multiple-nines range: 0.999, 0.99, 0.9, etc. Lower
-    `decay` value (recommend trying `decay`=0.9) if model experiences reasonably
-    good training performance but poor validation and/or test performance.
+    to 1.0, typically in the multiple-nines range: 0.999, 0.99, 0.9, etc.
+    Lower `decay` value (recommend trying `decay`=0.9) if model experiences
+    reasonably good training performance but poor validation and/or test
+    performance. Try zero_debias_moving_mean=True for improved stability.
 *  <b>`center`</b>: If True, subtract `beta`. If False, `beta` is ignored.
 *  <b>`scale`</b>: If True, multiply by `gamma`. If False, `gamma` is
     not used. When the next layer is linear (also e.g. `nn.relu`), this can be
@@ -113,6 +114,8 @@ can have speed penalty, specially in distributed settings.
     example selection.)
 *  <b>`fused`</b>: Use nn.fused_batch_norm if True, nn.batch_normalization otherwise.
 *  <b>`data_format`</b>: A string. `NHWC` (default) and `NCHW` are supported.
+*  <b>`zero_debias_moving_mean`</b>: Use zero_debias for moving_mean. It creates a new
+    pair of variables 'moving_mean/biased' and 'moving_mean/local_step'.
 *  <b>`scope`</b>: Optional scope for `variable_scope`.
 
 ##### Returns:
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.layers.batch_norm.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.layers.batch_norm.md
index 504157c51f..2b23d99de2 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.layers.batch_norm.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.contrib.layers.batch_norm.md
@@ -29,9 +29,10 @@ can have speed penalty, specially in distributed settings.
     `data_format` is `NHWC` and the second dimension if `data_format` is
     `NCHW`.
 *  <b>`decay`</b>: decay for the moving average. Reasonable values for `decay` are close
-    to 1.0, typically in the multiple-nines range: 0.999, 0.99, 0.9, etc. Lower
-    `decay` value (recommend trying `decay`=0.9) if model experiences reasonably
-    good training performance but poor validation and/or test performance.
+    to 1.0, typically in the multiple-nines range: 0.999, 0.99, 0.9, etc.
+    Lower `decay` value (recommend trying `decay`=0.9) if model experiences
+    reasonably good training performance but poor validation and/or test
+    performance. Try zero_debias_moving_mean=True for improved stability.
 *  <b>`center`</b>: If True, subtract `beta`. If False, `beta` is ignored.
 *  <b>`scale`</b>: If True, multiply by `gamma`. If False, `gamma` is
     not used. When the next layer is linear (also e.g. `nn.relu`), this can be
@@ -63,6 +64,8 @@ can have speed penalty, specially in distributed settings.
     example selection.)
 *  <b>`fused`</b>: Use nn.fused_batch_norm if True, nn.batch_normalization otherwise.
 *  <b>`data_format`</b>: A string. `NHWC` (default) and `NCHW` are supported.
+*  <b>`zero_debias_moving_mean`</b>: Use zero_debias for moving_mean. It creates a new
+    pair of variables 'moving_mean/biased' and 'moving_mean/local_step'.
 *  <b>`scope`</b>: Optional scope for `variable_scope`.
 
 ##### Returns: