Update generated Python Op docs.

Change: 140794278

13 files changed, 59 insertions, 417 deletions

diff --git a/tensorflow/g3doc/api_docs/python/contrib.framework.md b/tensorflow/g3doc/api_docs/python/contrib.framework.md
index 49892fdcaf..a10cd9d097 100644
--- a/tensorflow/g3doc/api_docs/python/contrib.framework.md
+++ b/tensorflow/g3doc/api_docs/python/contrib.framework.md
@@ -59,7 +59,7 @@ Assert `tensor` is 0-D, of type `tf.int32` or `tf.int64`.
 
 - - -
 
-### `tf.contrib.framework.convert_to_tensor_or_sparse_tensor(value, dtype=None, name=None)` {#convert_to_tensor_or_sparse_tensor}
+### `tf.convert_to_tensor_or_sparse_tensor(value, dtype=None, name=None)` {#convert_to_tensor_or_sparse_tensor}
 
 Converts value to a `SparseTensor` or `Tensor`.
 
diff --git a/tensorflow/g3doc/api_docs/python/framework.md b/tensorflow/g3doc/api_docs/python/framework.md
index c064ea3141..7aae9ea276 100644
--- a/tensorflow/g3doc/api_docs/python/framework.md
+++ b/tensorflow/g3doc/api_docs/python/framework.md
@@ -2551,6 +2551,31 @@ unmodified. Otherwise, it is converted to a `Tensor` using
 
 - - -
 
+### `tf.convert_to_tensor_or_sparse_tensor(value, dtype=None, name=None)` {#convert_to_tensor_or_sparse_tensor}
+
+Converts value to a `SparseTensor` or `Tensor`.
+
+##### Args:
+
+
+*  <b>`value`</b>: A `SparseTensor`, `SparseTensorValue`, or an object whose type has a
+    registered `Tensor` conversion function.
+*  <b>`dtype`</b>: Optional element type for the returned tensor. If missing, the
+    type is inferred from the type of `value`.
+*  <b>`name`</b>: Optional name to use if a new `Tensor` is created.
+
+##### Returns:
+
+  A `SparseTensor` or `Tensor` based on `value`.
+
+##### Raises:
+
+
+*  <b>`RuntimeError`</b>: If result type is incompatible with `dtype`.
+
+
+- - -
+
 ### `tf.get_default_graph()` {#get_default_graph}
 
 Returns the default graph for the current thread.
@@ -2795,7 +2820,7 @@ The following standard keys are defined:
   for more details.
 * `SUMMARIES`: the summary `Tensor` objects that have been created in the
   graph. See
-  [`tf.contrib.deprecated.merge_all_summaries()`](../../api_docs/python/train.md#merge_all_summaries)
+  [`tf.summary.merge_all()`](../../api_docs/python/summary.md#merge_all)
   for more details.
 * `QUEUE_RUNNERS`: the `QueueRunner` objects that are used to
   produce input for a computation. See
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.framework.convert_to_tensor_or_sparse_tensor.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.convert_to_tensor_or_sparse_tensor.md
index 089f02a9b4..1999e71180 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.framework.convert_to_tensor_or_sparse_tensor.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.convert_to_tensor_or_sparse_tensor.md
@@ -1,4 +1,4 @@
-### `tf.contrib.framework.convert_to_tensor_or_sparse_tensor(value, dtype=None, name=None)` {#convert_to_tensor_or_sparse_tensor}
+### `tf.convert_to_tensor_or_sparse_tensor(value, dtype=None, name=None)` {#convert_to_tensor_or_sparse_tensor}
 
 Converts value to a `SparseTensor` or `Tensor`.
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.merge_all_summaries.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.merge_all_summaries.md
deleted file mode 100644
index 40143de15d..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.merge_all_summaries.md
+++ /dev/null
@@ -1,16 +0,0 @@
-### `tf.merge_all_summaries(key='summaries')` {#merge_all_summaries}
-
-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.
-
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.image_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.image_summary.md
deleted file mode 100644
index 5df729544b..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.image_summary.md
+++ /dev/null
@@ -1,48 +0,0 @@
-### `tf.image_summary(tag, tensor, max_images=3, collections=None, name=None)` {#image_summary}
-
-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` argument is a scalar `Tensor` of type `string`.  It is used to
-build the `tag` of the summary values:
-
-*  If `max_images` is 1, the summary value tag is '*tag*/image'.
-*  If `max_images` is greater than 1, the summary value tags are
-   generated sequentially as '*tag*/image/0', '*tag*/image/1', etc.
-
-##### Args:
-
-
-*  <b>`tag`</b>: A scalar `Tensor` of type `string`. Used to build the `tag`
-    of the summary values.
-*  <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_images`</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]
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
-  buffer.
-
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.scalar_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.scalar_summary.md
deleted file mode 100644
index 1e8c3479e4..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.scalar_summary.md
+++ /dev/null
@@ -1,21 +0,0 @@
-### `tf.scalar_summary(tags, values, collections=None, name=None)` {#scalar_summary}
-
-Outputs a `Summary` protocol buffer with scalar values.
-
-The input `tags` and `values` must have the same shape.  The generated
-summary has a summary value for each tag-value pair in `tags` and `values`.
-
-##### Args:
-
-
-*  <b>`tags`</b>: A `string` `Tensor`.  Tags for the summaries.
-*  <b>`values`</b>: A real numeric Tensor.  Values for the summaries.
-*  <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.
-
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.histogram_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.histogram_summary.md
deleted file mode 100644
index 1ede11e820..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.histogram_summary.md
+++ /dev/null
@@ -1,25 +0,0 @@
-### `tf.histogram_summary(tag, values, collections=None, name=None)` {#histogram_summary}
-
-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>`tag`</b>: A `string` `Tensor`. 0-D.  Tag to use for the summary value.
-*  <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]`.
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
-  buffer.
-
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.merge_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.merge_summary.md
deleted file mode 100644
index b61a501c2d..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.merge_summary.md
+++ /dev/null
@@ -1,26 +0,0 @@
-### `tf.merge_summary(inputs, collections=None, name=None)` {#merge_summary}
-
-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.
-
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.GraphKeys.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.GraphKeys.md
index ff09e97780..74b46140d2 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.GraphKeys.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.GraphKeys.md
@@ -27,7 +27,7 @@ The following standard keys are defined:
   for more details.
 * `SUMMARIES`: the summary `Tensor` objects that have been created in the
   graph. See
-  [`tf.contrib.deprecated.merge_all_summaries()`](../../api_docs/python/train.md#merge_all_summaries)
+  [`tf.summary.merge_all()`](../../api_docs/python/summary.md#merge_all)
   for more details.
 * `QUEUE_RUNNERS`: the `QueueRunner` objects that are used to
   produce input for a computation. See
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.audio_summary.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.audio_summary.md
deleted file mode 100644
index c0aff77770..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.audio_summary.md
+++ /dev/null
@@ -1,36 +0,0 @@
-### `tf.audio_summary(tag, tensor, sample_rate, max_outputs=3, collections=None, name=None)` {#audio_summary}
-
-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` argument is a scalar `Tensor` of type `string`.  It is used to
-build the `tag` of the summary values:
-
-*  If `max_outputs` is 1, the summary value tag is '*tag*/audio'.
-*  If `max_outputs` is greater than 1, the summary value tags are
-   generated sequentially as '*tag*/audio/0', '*tag*/audio/1', etc.
-
-##### Args:
-
-
-*  <b>`tag`</b>: A scalar `Tensor` of type `string`. Used to build the `tag`
-    of the summary values.
-*  <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]
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
-  buffer.
-
diff --git a/tensorflow/g3doc/api_docs/python/index.md b/tensorflow/g3doc/api_docs/python/index.md
index 5c04276e93..eafb30c332 100644
--- a/tensorflow/g3doc/api_docs/python/index.md
+++ b/tensorflow/g3doc/api_docs/python/index.md
@@ -9,6 +9,7 @@
   * [`control_dependencies`](../../api_docs/python/framework.md#control_dependencies)
   * [`convert_to_tensor`](../../api_docs/python/framework.md#convert_to_tensor)
   * [`convert_to_tensor_or_indexed_slices`](../../api_docs/python/framework.md#convert_to_tensor_or_indexed_slices)
+  * [`convert_to_tensor_or_sparse_tensor`](../../api_docs/python/framework.md#convert_to_tensor_or_sparse_tensor)
   * [`device`](../../api_docs/python/framework.md#device)
   * [`DeviceSpec`](../../api_docs/python/framework.md#DeviceSpec)
   * [`Dimension`](../../api_docs/python/framework.md#Dimension)
@@ -569,6 +570,7 @@
   * [`weighted_cross_entropy_with_logits`](../../api_docs/python/nn.md#weighted_cross_entropy_with_logits)
   * [`weighted_moments`](../../api_docs/python/nn.md#weighted_moments)
   * [`with_space_to_batch`](../../api_docs/python/nn.md#with_space_to_batch)
+  * [`zero_fraction`](../../api_docs/python/nn.md#zero_fraction)
 
 * **[Neural Network RNN Cells](../../api_docs/python/rnn_cell.md)**:
   * [`BasicLSTMCell`](../../api_docs/python/rnn_cell.md#BasicLSTMCell)
@@ -616,7 +618,6 @@
   * [`add_queue_runner`](../../api_docs/python/train.md#add_queue_runner)
   * [`AggregationMethod`](../../api_docs/python/train.md#AggregationMethod)
   * [`assert_global_step`](../../api_docs/python/train.md#assert_global_step)
-  * [`audio_summary`](../../api_docs/python/train.md#audio_summary)
   * [`basic_train_loop`](../../api_docs/python/train.md#basic_train_loop)
   * [`checkpoint_exists`](../../api_docs/python/train.md#checkpoint_exists)
   * [`CheckpointSaverHook`](../../api_docs/python/train.md#CheckpointSaverHook)
@@ -640,13 +641,9 @@
   * [`GradientDescentOptimizer`](../../api_docs/python/train.md#GradientDescentOptimizer)
   * [`gradients`](../../api_docs/python/train.md#gradients)
   * [`hessians`](../../api_docs/python/train.md#hessians)
-  * [`histogram_summary`](../../api_docs/python/train.md#histogram_summary)
-  * [`image_summary`](../../api_docs/python/train.md#image_summary)
   * [`inverse_time_decay`](../../api_docs/python/train.md#inverse_time_decay)
   * [`LoggingTensorHook`](../../api_docs/python/train.md#LoggingTensorHook)
   * [`LooperThread`](../../api_docs/python/train.md#LooperThread)
-  * [`merge_all_summaries`](../../api_docs/python/train.md#merge_all_summaries)
-  * [`merge_summary`](../../api_docs/python/train.md#merge_summary)
   * [`MomentumOptimizer`](../../api_docs/python/train.md#MomentumOptimizer)
   * [`MonitoredSession`](../../api_docs/python/train.md#MonitoredSession)
   * [`MonitoredTrainingSession`](../../api_docs/python/train.md#MonitoredTrainingSession)
@@ -663,7 +660,6 @@
   * [`replica_device_setter`](../../api_docs/python/train.md#replica_device_setter)
   * [`RMSPropOptimizer`](../../api_docs/python/train.md#RMSPropOptimizer)
   * [`Scaffold`](../../api_docs/python/train.md#Scaffold)
-  * [`scalar_summary`](../../api_docs/python/train.md#scalar_summary)
   * [`Server`](../../api_docs/python/train.md#Server)
   * [`SessionCreator`](../../api_docs/python/train.md#SessionCreator)
   * [`SessionManager`](../../api_docs/python/train.md#SessionManager)
@@ -682,7 +678,6 @@
   * [`SyncReplicasOptimizerV2`](../../api_docs/python/train.md#SyncReplicasOptimizerV2)
   * [`WorkerSessionCreator`](../../api_docs/python/train.md#WorkerSessionCreator)
   * [`write_graph`](../../api_docs/python/train.md#write_graph)
-  * [`zero_fraction`](../../api_docs/python/train.md#zero_fraction)
 
 * **[Wraps python functions](../../api_docs/python/script_ops.md)**:
   * [`py_func`](../../api_docs/python/script_ops.md#py_func)
diff --git a/tensorflow/g3doc/api_docs/python/nn.md b/tensorflow/g3doc/api_docs/python/nn.md
index 948b63a3d0..1285cffe7c 100644
--- a/tensorflow/g3doc/api_docs/python/nn.md
+++ b/tensorflow/g3doc/api_docs/python/nn.md
@@ -3930,3 +3930,31 @@ Produces the average pool of the input tensor for quantized types.
 *  <b>`max_output`</b>: A `Tensor` of type `float32`. The float value that the highest quantized output value represents.
 
 
+
+## Other Functions and Classes
+- - -
+
+### `tf.nn.zero_fraction(value, name=None)` {#zero_fraction}
+
+Returns the fraction of zeros in `value`.
+
+If `value` is empty, the result is `nan`.
+
+This is useful in summaries to measure and report sparsity.  For example,
+
+```python
+    z = tf.Relu(...)
+    summ = tf.contrib.deprecated.scalar_summary('sparsity', tf.nn.zero_fraction(z))
+```
+
+##### Args:
+
+
+*  <b>`value`</b>: A tensor of numeric type.
+*  <b>`name`</b>: A name for the operation (optional).
+
+##### Returns:
+
+  The fraction of zeros in `value`, with type `float32`.
+
+
diff --git a/tensorflow/g3doc/api_docs/python/train.md b/tensorflow/g3doc/api_docs/python/train.md
index d215b6febc..cf49c55d3d 100644
--- a/tensorflow/g3doc/api_docs/python/train.md
+++ b/tensorflow/g3doc/api_docs/python/train.md
@@ -3880,240 +3880,6 @@ This method is completely compatible with the `tf.Session.run()` method.
 
 
 
-## Summary Operations
-
-The following ops output
-[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
-protocol buffers as serialized string tensors.
-
-You can fetch the output of a summary op in a session, and pass it to
-a [SummaryWriter](../../api_docs/python/train.md#SummaryWriter) to append it
-to an event file.  Event files contain
-[`Event`](https://www.tensorflow.org/code/tensorflow/core/util/event.proto)
-protos that can contain `Summary` protos along with the timestamp and
-step.  You can then use TensorBoard to visualize the contents of the
-event files.  See [TensorBoard and
-Summaries](../../how_tos/summaries_and_tensorboard/index.md) for more
-details.
-
-- - -
-
-### `tf.scalar_summary(tags, values, collections=None, name=None)` {#scalar_summary}
-
-Outputs a `Summary` protocol buffer with scalar values.
-
-The input `tags` and `values` must have the same shape.  The generated
-summary has a summary value for each tag-value pair in `tags` and `values`.
-
-##### Args:
-
-
-*  <b>`tags`</b>: A `string` `Tensor`.  Tags for the summaries.
-*  <b>`values`</b>: A real numeric Tensor.  Values for the summaries.
-*  <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.
-
-
-- - -
-
-### `tf.image_summary(tag, tensor, max_images=3, collections=None, name=None)` {#image_summary}
-
-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` argument is a scalar `Tensor` of type `string`.  It is used to
-build the `tag` of the summary values:
-
-*  If `max_images` is 1, the summary value tag is '*tag*/image'.
-*  If `max_images` is greater than 1, the summary value tags are
-   generated sequentially as '*tag*/image/0', '*tag*/image/1', etc.
-
-##### Args:
-
-
-*  <b>`tag`</b>: A scalar `Tensor` of type `string`. Used to build the `tag`
-    of the summary values.
-*  <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_images`</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]
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
-  buffer.
-
-
-- - -
-
-### `tf.audio_summary(tag, tensor, sample_rate, max_outputs=3, collections=None, name=None)` {#audio_summary}
-
-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` argument is a scalar `Tensor` of type `string`.  It is used to
-build the `tag` of the summary values:
-
-*  If `max_outputs` is 1, the summary value tag is '*tag*/audio'.
-*  If `max_outputs` is greater than 1, the summary value tags are
-   generated sequentially as '*tag*/audio/0', '*tag*/audio/1', etc.
-
-##### Args:
-
-
-*  <b>`tag`</b>: A scalar `Tensor` of type `string`. Used to build the `tag`
-    of the summary values.
-*  <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]
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
-  buffer.
-
-
-- - -
-
-### `tf.histogram_summary(tag, values, collections=None, name=None)` {#histogram_summary}
-
-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>`tag`</b>: A `string` `Tensor`. 0-D.  Tag to use for the summary value.
-*  <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]`.
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  A scalar `Tensor` of type `string`. The serialized `Summary` protocol
-  buffer.
-
-
-- - -
-
-### `tf.nn.zero_fraction(value, name=None)` {#zero_fraction}
-
-Returns the fraction of zeros in `value`.
-
-If `value` is empty, the result is `nan`.
-
-This is useful in summaries to measure and report sparsity.  For example,
-
-```python
-    z = tf.Relu(...)
-    summ = tf.contrib.deprecated.scalar_summary('sparsity', tf.nn.zero_fraction(z))
-```
-
-##### Args:
-
-
-*  <b>`value`</b>: A tensor of numeric type.
-*  <b>`name`</b>: A name for the operation (optional).
-
-##### Returns:
-
-  The fraction of zeros in `value`, with type `float32`.
-
-
-
-- - -
-
-### `tf.merge_summary(inputs, collections=None, name=None)` {#merge_summary}
-
-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.merge_all_summaries(key='summaries')` {#merge_all_summaries}
-
-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.
-
-
-
 ## Reading Summaries from Event Files
 
 See [Summaries and