Update generated Python Op docs.

Change: 136637890

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

@@ -20217,8 +20217,8 @@ Additional documentation from `TransformedDistribution`:
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -20335,8 +20335,8 @@ Additional documentation from `TransformedDistribution`:
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -20419,8 +20419,8 @@ Implements `(log o p o g^{-1})(y) + (log o det o J o g^{-1})(y)`,
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -20458,8 +20458,8 @@ Additional documentation from `TransformedDistribution`:
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -20611,8 +20611,8 @@ Implements `p(g^{-1}(y)) det|J(g^{-1}(y))|`, where `g^{-1}` is the
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -20665,8 +20665,8 @@ Samples from the base distribution and then passes through
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -20714,8 +20714,8 @@ Additional documentation from `TransformedDistribution`:
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 

tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.summary.merge_all.md

+### `tf.summary.merge_all(key='summaries')` {#merge_all}
+
+Merges all summaries collected in the default graph.
+
+##### Args:
+
+
+*  <b>`key`</b>: `GraphKey` used to collect the summaries.  Defaults to
+    `GraphKeys.SUMMARIES`.
+
+##### Returns:
+
+  If no summaries were collected, returns None.  Otherwise returns a scalar
+  `Tensor` of type `string` containing the serialized `Summary` protocol
+  buffer resulting from the merging.
+

tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.contrib.distributions.TransformedDistribution.md

@@ -182,8 +182,8 @@ Additional documentation from `TransformedDistribution`:
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -300,8 +300,8 @@ Additional documentation from `TransformedDistribution`:
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -384,8 +384,8 @@ Implements `(log o p o g^{-1})(y) + (log o det o J o g^{-1})(y)`,
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -423,8 +423,8 @@ Additional documentation from `TransformedDistribution`:
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -576,8 +576,8 @@ Implements `p(g^{-1}(y)) det|J(g^{-1}(y))|`, where `g^{-1}` is the
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -630,8 +630,8 @@ Samples from the base distribution and then passes through
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 
@@ -679,8 +679,8 @@ Additional documentation from `TransformedDistribution`:
 
 ##### <b>`condition_kwargs`</b>:
 
-*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 *  <b>`bijector_kwargs`</b>: Python dictionary of arg names/values forwarded to the bijector.
+*  <b>`distribution_kwargs`</b>: Python dictionary of arg names/values forwarded to the distribution.
 
 ##### Args:
 

tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.summary.audio.md

+### `tf.summary.audio(name, tensor, sample_rate, max_outputs=3, collections=None)` {#audio}
+
+Outputs a `Summary` protocol buffer with audio.
+
+The summary has up to `max_outputs` summary values containing audio. The
+audio is built from `tensor` which must be 3-D with shape `[batch_size,
+frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are
+assumed to be in the range of `[-1.0, 1.0]` with a sample rate of
+`sample_rate`.
+
+The `tag` in the outputted Summary.Value protobufs is generated based on the
+name, with a suffix depending on the max_outputs setting:
+
+*  If `max_outputs` is 1, the summary value tag is '*name*/audio'.
+*  If `max_outputs` is greater than 1, the summary value tags are
+   generated sequentially as '*name*/audio/0', '*name*/audio/1', etc
+
+##### Args:
+
+
+*  <b>`name`</b>: A name for the generated node. Will also serve as a series name in
+    TensorBoard.
+*  <b>`tensor`</b>: A 3-D `float32` `Tensor` of shape `[batch_size, frames, channels]`
+    or a 2-D `float32` `Tensor` of shape `[batch_size, frames]`.
+*  <b>`sample_rate`</b>: A Scalar `float32` `Tensor` indicating the sample rate of the
+    signal in hertz.
+*  <b>`max_outputs`</b>: Max number of batch elements to generate audio for.
+*  <b>`collections`</b>: Optional list of ops.GraphKeys.  The collections to add the
+    summary to.  Defaults to [_ops.GraphKeys.SUMMARIES]
+
+##### Returns:
+
+  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
+  buffer.
+

tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.summary.image.md

+### `tf.summary.image(name, tensor, max_outputs=3, collections=None)` {#image}
+
+Outputs a `Summary` protocol buffer with images.
+
+The summary has up to `max_images` summary values containing images. The
+images are built from `tensor` which must be 4-D with shape `[batch_size,
+height, width, channels]` and where `channels` can be:
+
+*  1: `tensor` is interpreted as Grayscale.
+*  3: `tensor` is interpreted as RGB.
+*  4: `tensor` is interpreted as RGBA.
+
+The images have the same number of channels as the input tensor. For float
+input, the values are normalized one image at a time to fit in the range
+`[0, 255]`.  `uint8` values are unchanged.  The op uses two different
+normalization algorithms:
+
+*  If the input values are all positive, they are rescaled so the largest one
+   is 255.
+
+*  If any input value is negative, the values are shifted so input value 0.0
+   is at 127.  They are then rescaled so that either the smallest value is 0,
+   or the largest one is 255.
+
+The `tag` in the outputted Summary.Value protobufs is generated based on the
+name, with a suffix depending on the max_outputs setting:
+
+*  If `max_outputs` is 1, the summary value tag is '*name*/image'.
+*  If `max_outputs` is greater than 1, the summary value tags are
+   generated sequentially as '*name*/image/0', '*name*/image/1', etc.
+
+##### Args:
+
+
+*  <b>`name`</b>: A name for the generated node. Will also serve as a series name in
+    TensorBoard.
+*  <b>`tensor`</b>: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height,
+    width, channels]` where `channels` is 1, 3, or 4.
+*  <b>`max_outputs`</b>: Max number of batch elements to generate images for.
+*  <b>`collections`</b>: Optional list of ops.GraphKeys.  The collections to add the
+    summary to.  Defaults to [_ops.GraphKeys.SUMMARIES]
+
+##### Returns:
+
+  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
+  buffer.
+

tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.summary.histogram.md

+### `tf.summary.histogram(name, values, collections=None)` {#histogram}
+
+Outputs a `Summary` protocol buffer with a histogram.
+
+The generated
+[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
+has one summary value containing a histogram for `values`.
+
+This op reports an `InvalidArgument` error if any value is not finite.
+
+##### Args:
+
+
+*  <b>`name`</b>: A name for the generated node. Will also serve as a series name in
+    TensorBoard.
+*  <b>`values`</b>: A real numeric `Tensor`. Any shape. Values to use to
+    build the histogram.
+*  <b>`collections`</b>: Optional list of graph collections keys. The new summary op is
+    added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
+
+##### Returns:
+
+  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
+  buffer.
+

tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.summary.merge.md

+### `tf.summary.merge(inputs, collections=None, name=None)` {#merge}
+
+Merges summaries.
+
+This op creates a
+[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
+protocol buffer that contains the union of all the values in the input
+summaries.
+
+When the Op is run, it reports an `InvalidArgument` error if multiple values
+in the summaries to merge use the same tag.
+
+##### Args:
+
+
+*  <b>`inputs`</b>: A list of `string` `Tensor` objects containing serialized `Summary`
+    protocol buffers.
+*  <b>`collections`</b>: Optional list of graph collections keys. The new summary op is
+    added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
+*  <b>`name`</b>: A name for the operation (optional).
+
+##### Returns:
+
+  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
+  buffer resulting from the merging.
+

tensorflow/g3doc/api_docs/python/index.md

@@ -629,7 +629,12 @@
   * [`py_func`](../../api_docs/python/script_ops.md#py_func)
 
 * **[Summary Operations](../../api_docs/python/summary.md)**:
+  * [`audio`](../../api_docs/python/summary.md#audio)
   * [`get_summary_description`](../../api_docs/python/summary.md#get_summary_description)
+  * [`histogram`](../../api_docs/python/summary.md#histogram)
+  * [`image`](../../api_docs/python/summary.md#image)
+  * [`merge`](../../api_docs/python/summary.md#merge)
+  * [`merge_all`](../../api_docs/python/summary.md#merge_all)
   * [`scalar`](../../api_docs/python/summary.md#scalar)
   * [`tensor_summary`](../../api_docs/python/summary.md#tensor_summary)
 

tensorflow/g3doc/api_docs/python/summary.md

@@ -60,6 +60,170 @@ The generated Summary has a Tensor.proto containing the input Tensor.
 *  <b>`ValueError`</b>: If tensor has the wrong shape or type.
 
 
+- - -
+
+### `tf.summary.histogram(name, values, collections=None)` {#histogram}
+
+Outputs a `Summary` protocol buffer with a histogram.
+
+The generated
+[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
+has one summary value containing a histogram for `values`.
+
+This op reports an `InvalidArgument` error if any value is not finite.
+
+##### Args:
+
+
+*  <b>`name`</b>: A name for the generated node. Will also serve as a series name in
+    TensorBoard.
+*  <b>`values`</b>: A real numeric `Tensor`. Any shape. Values to use to
+    build the histogram.
+*  <b>`collections`</b>: Optional list of graph collections keys. The new summary op is
+    added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
+
+##### Returns:
+
+  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
+  buffer.
+
+
+- - -
+
+### `tf.summary.audio(name, tensor, sample_rate, max_outputs=3, collections=None)` {#audio}
+
+Outputs a `Summary` protocol buffer with audio.
+
+The summary has up to `max_outputs` summary values containing audio. The
+audio is built from `tensor` which must be 3-D with shape `[batch_size,
+frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are
+assumed to be in the range of `[-1.0, 1.0]` with a sample rate of
+`sample_rate`.
+
+The `tag` in the outputted Summary.Value protobufs is generated based on the
+name, with a suffix depending on the max_outputs setting:
+
+*  If `max_outputs` is 1, the summary value tag is '*name*/audio'.
+*  If `max_outputs` is greater than 1, the summary value tags are
+   generated sequentially as '*name*/audio/0', '*name*/audio/1', etc
+
+##### Args:
+
+
+*  <b>`name`</b>: A name for the generated node. Will also serve as a series name in
+    TensorBoard.
+*  <b>`tensor`</b>: A 3-D `float32` `Tensor` of shape `[batch_size, frames, channels]`
+    or a 2-D `float32` `Tensor` of shape `[batch_size, frames]`.
+*  <b>`sample_rate`</b>: A Scalar `float32` `Tensor` indicating the sample rate of the
+    signal in hertz.
+*  <b>`max_outputs`</b>: Max number of batch elements to generate audio for.
+*  <b>`collections`</b>: Optional list of ops.GraphKeys.  The collections to add the
+    summary to.  Defaults to [_ops.GraphKeys.SUMMARIES]
+
+##### Returns:
+
+  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
+  buffer.
+
+
+- - -
+
+### `tf.summary.image(name, tensor, max_outputs=3, collections=None)` {#image}
+
+Outputs a `Summary` protocol buffer with images.
+
+The summary has up to `max_images` summary values containing images. The
+images are built from `tensor` which must be 4-D with shape `[batch_size,
+height, width, channels]` and where `channels` can be:
+
+*  1: `tensor` is interpreted as Grayscale.
+*  3: `tensor` is interpreted as RGB.
+*  4: `tensor` is interpreted as RGBA.
+
+The images have the same number of channels as the input tensor. For float
+input, the values are normalized one image at a time to fit in the range
+`[0, 255]`.  `uint8` values are unchanged.  The op uses two different
+normalization algorithms:
+
+*  If the input values are all positive, they are rescaled so the largest one
+   is 255.
+
+*  If any input value is negative, the values are shifted so input value 0.0
+   is at 127.  They are then rescaled so that either the smallest value is 0,
+   or the largest one is 255.
+
+The `tag` in the outputted Summary.Value protobufs is generated based on the
+name, with a suffix depending on the max_outputs setting:
+
+*  If `max_outputs` is 1, the summary value tag is '*name*/image'.
+*  If `max_outputs` is greater than 1, the summary value tags are
+   generated sequentially as '*name*/image/0', '*name*/image/1', etc.
+
+##### Args:
+
+
+*  <b>`name`</b>: A name for the generated node. Will also serve as a series name in
+    TensorBoard.
+*  <b>`tensor`</b>: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height,
+    width, channels]` where `channels` is 1, 3, or 4.
+*  <b>`max_outputs`</b>: Max number of batch elements to generate images for.
+*  <b>`collections`</b>: Optional list of ops.GraphKeys.  The collections to add the
+    summary to.  Defaults to [_ops.GraphKeys.SUMMARIES]
+
+##### Returns:
+
+  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
+  buffer.
+
+
+- - -
+
+### `tf.summary.merge(inputs, collections=None, name=None)` {#merge}
+
+Merges summaries.
+
+This op creates a
+[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
+protocol buffer that contains the union of all the values in the input
+summaries.
+
+When the Op is run, it reports an `InvalidArgument` error if multiple values
+in the summaries to merge use the same tag.
+
+##### Args:
+
+
+*  <b>`inputs`</b>: A list of `string` `Tensor` objects containing serialized `Summary`
+    protocol buffers.
+*  <b>`collections`</b>: Optional list of graph collections keys. The new summary op is
+    added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
+*  <b>`name`</b>: A name for the operation (optional).
+
+##### Returns:
+
+  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
+  buffer resulting from the merging.
+
+
+- - -
+
+### `tf.summary.merge_all(key='summaries')` {#merge_all}
+
+Merges all summaries collected in the default graph.
+
+##### Args:
+
+
+*  <b>`key`</b>: `GraphKey` used to collect the summaries.  Defaults to
+    `GraphKeys.SUMMARIES`.
+
+##### Returns:
+
+  If no summaries were collected, returns None.  Otherwise returns a scalar
+  `Tensor` of type `string` containing the serialized `Summary` protocol
+  buffer resulting from the merging.
+
+
 
 ## Utilities
 - - -