Update generated Python Op docs.

Change: 141462624

tensorflow/g3doc/api_docs/python/contrib.layers.md

@@ -332,7 +332,7 @@ Flattens the input while maintaining the batch_size.
 ##### Raises:
 
 
-*  <b>`ValueError`</b>: if inputs.shape is wrong.
+*  <b>`ValueError`</b>: if inputs.dense_shape is wrong.
 
 
 - - -

tensorflow/g3doc/api_docs/python/contrib.learn.md

@@ -347,9 +347,12 @@ Constructs an `Estimator` instance.
              `labels=None`.
       * `mode` specifies if this training, evaluation or
              prediction. See `ModeKeys`.
-      * `params` is a `dict` of hyperparameters. Will receive what
+      * `params` is a `dict` of hyperparameters.  Will receive what
              is passed to Estimator in `params` parameter. This allows
              to configure Estimators from hyper parameter tuning.
+      * `config` is a Configuration object. Will receive what is passed to
+             Estimator in `config` parameter. This allows updating things in
+             your model_fn based on configuration such as num_ps_replicas.
 
     * Returns:
       `ModelFnOps`
@@ -367,6 +370,8 @@ Constructs an `Estimator` instance.
       * `(features, labels) -> (predictions, loss, train_op)`
       * `(features, labels, mode) -> (predictions, loss, train_op)`
       * `(features, labels, mode, params) -> (predictions, loss, train_op)`
+      * `(features, labels, mode, params, config) ->
+         (predictions, loss, train_op)`
 
 
 *  <b>`model_dir`</b>: Directory to save model parameters, graph and etc. This can

tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.image.decode_jpeg.md

-### `tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, name=None)` {#decode_jpeg}
+### `tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, dct_method=None, name=None)` {#decode_jpeg}
 
 Decode a JPEG-encoded image to a uint8 tensor.
 
@@ -33,6 +33,13 @@ downscaling the image later.
 *  <b>`acceptable_fraction`</b>: An optional `float`. Defaults to `1`.
     The minimum required fraction of lines before a truncated
     input is accepted.
+*  <b>`dct_method`</b>: An optional `string`. Defaults to `""`.
+    string specifying a hint about the algorithm used for
+    decompression.  Defaults to "" which maps to a system-specific
+    default.  Currently valid values are ["INTEGER_FAST",
+    "INTEGER_ACCURATE"].  The hint may be ignored (e.g., the internal
+    jpeg library changes to a version that does not have that specific
+    option.)
 *  <b>`name`</b>: A name for the operation (optional).
 
 ##### Returns:

tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.contrib.layers.flatten.md

@@ -18,5 +18,5 @@ Flattens the input while maintaining the batch_size.
 ##### Raises:
 
 
-*  <b>`ValueError`</b>: if inputs.shape is wrong.
+*  <b>`ValueError`</b>: if inputs.dense_shape is wrong.
 

tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.learn.Estimator.md

@@ -19,9 +19,12 @@ Constructs an `Estimator` instance.
              `labels=None`.
       * `mode` specifies if this training, evaluation or
              prediction. See `ModeKeys`.
-      * `params` is a `dict` of hyperparameters. Will receive what
+      * `params` is a `dict` of hyperparameters.  Will receive what
              is passed to Estimator in `params` parameter. This allows
              to configure Estimators from hyper parameter tuning.
+      * `config` is a Configuration object. Will receive what is passed to
+             Estimator in `config` parameter. This allows updating things in
+             your model_fn based on configuration such as num_ps_replicas.
 
     * Returns:
       `ModelFnOps`
@@ -39,6 +42,8 @@ Constructs an `Estimator` instance.
       * `(features, labels) -> (predictions, loss, train_op)`
       * `(features, labels, mode) -> (predictions, loss, train_op)`
       * `(features, labels, mode, params) -> (predictions, loss, train_op)`
+      * `(features, labels, mode, params, config) ->
+         (predictions, loss, train_op)`
 
 
 *  <b>`model_dir`</b>: Directory to save model parameters, graph and etc. This can

tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.parse_example.md

@@ -93,15 +93,15 @@ Then the output is a dictionary:
   "kw": SparseTensor(
       indices=[[0, 0], [0, 1], [1, 0]],
       values=["knit", "big", "emmy"]
-      shape=[2, 2]),
+      dense_shape=[2, 2]),
   "dank": SparseTensor(
       indices=[[1, 0]],
       values=[42],
-      shape=[2, 1]),
+      dense_shape=[2, 1]),
   "gps": SparseTensor(
       indices=[],
       values=[],
-      shape=[2, 0]),
+      dense_shape=[2, 0]),
 }
 ```
 
@@ -170,7 +170,7 @@ Then the output is a dictionary:
   "sparse": SparseTensor(
       indices=[[0, 3], [0, 20], [1, 42]],
       values=[0.5, -1.0, 0.0]
-      shape=[2, 100]),
+      dense_shape=[2, 100]),
 }
 ```
 

tensorflow/g3doc/api_docs/python/image.md

@@ -47,7 +47,7 @@ convert $src.gif -coalesce $dst.gif
 
 - - -
 
-### `tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, name=None)` {#decode_jpeg}
+### `tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, dct_method=None, name=None)` {#decode_jpeg}
 
 Decode a JPEG-encoded image to a uint8 tensor.
 
@@ -82,6 +82,13 @@ downscaling the image later.
 *  <b>`acceptable_fraction`</b>: An optional `float`. Defaults to `1`.
     The minimum required fraction of lines before a truncated
     input is accepted.
+*  <b>`dct_method`</b>: An optional `string`. Defaults to `""`.
+    string specifying a hint about the algorithm used for
+    decompression.  Defaults to "" which maps to a system-specific
+    default.  Currently valid values are ["INTEGER_FAST",
+    "INTEGER_ACCURATE"].  The hint may be ignored (e.g., the internal
+    jpeg library changes to a version that does not have that specific
+    option.)
 *  <b>`name`</b>: A name for the operation (optional).
 
 ##### Returns:

tensorflow/g3doc/api_docs/python/io_ops.md

@@ -1636,15 +1636,15 @@ Then the output is a dictionary:
   "kw": SparseTensor(
       indices=[[0, 0], [0, 1], [1, 0]],
       values=["knit", "big", "emmy"]
-      shape=[2, 2]),
+      dense_shape=[2, 2]),
   "dank": SparseTensor(
       indices=[[1, 0]],
       values=[42],
-      shape=[2, 1]),
+      dense_shape=[2, 1]),
   "gps": SparseTensor(
       indices=[],
       values=[],
-      shape=[2, 0]),
+      dense_shape=[2, 0]),
 }
 ```
 
@@ -1713,7 +1713,7 @@ Then the output is a dictionary:
   "sparse": SparseTensor(
       indices=[[0, 3], [0, 20], [1, 42]],
       values=[0.5, -1.0, 0.0]
-      shape=[2, 100]),
+      dense_shape=[2, 100]),
 }
 ```