Update generated Python Op docs.

Change: 140678314

10 files changed, 60 insertions, 52 deletions

diff --git a/tensorflow/g3doc/api_docs/python/array_ops.md b/tensorflow/g3doc/api_docs/python/array_ops.md
index adbd947a9f..5a3d73ae49 100644
--- a/tensorflow/g3doc/api_docs/python/array_ops.md
+++ b/tensorflow/g3doc/api_docs/python/array_ops.md
@@ -724,12 +724,12 @@ tf.strided_slice(input, [1, 1, 0], [2, -1, 3], [1, -1, 1]) ==>[[[4, 4, 4],
 
 - - -
 
-### `tf.split(split_dim, num_split, value, name='split')` {#split}
+### `tf.split(axis, num_split, value, name='split', split_dim=None)` {#split}
 
 Splits a tensor into `num_split` tensors along one dimension.
 
-Splits `value` along dimension `split_dim` into `num_split` smaller tensors.
-Requires that `num_split` evenly divide `value.shape[split_dim]`.
+Splits `value` along dimension `axis` into `num_split` smaller tensors.
+Requires that `num_split` evenly divide `value.shape[axis]`.
 
 For example:
 
@@ -757,11 +757,12 @@ tf.unpack(t, axis=axis)
 ##### Args:
 
 
-*  <b>`split_dim`</b>: A 0-D `int32` `Tensor`. The dimension along which to split.
+*  <b>`axis`</b>: A 0-D `int32` `Tensor`. The dimension along which to split.
     Must be in the range `[0, rank(value))`.
 *  <b>`num_split`</b>: A Python integer. The number of ways to split.
 *  <b>`value`</b>: The `Tensor` to split.
 *  <b>`name`</b>: A name for the operation (optional).
+*  <b>`split_dim`</b>: The old (deprecated) name for axis.
 
 ##### Returns:
 
@@ -1216,20 +1217,20 @@ This is the opposite of pack.  The numpy equivalent is
 
 - - -
 
-### `tf.reverse_sequence(input, seq_lengths, seq_dim, batch_dim=None, name=None)` {#reverse_sequence}
+### `tf.reverse_sequence(input, seq_lengths, seq_axis=None, batch_axis=None, name=None, seq_dim=None, batch_dim=None)` {#reverse_sequence}
 
 Reverses variable length slices.
 
-This op first slices `input` along the dimension `batch_dim`, and for each
+This op first slices `input` along the dimension `batch_axis`, and for each
 slice `i`, reverses the first `seq_lengths[i]` elements along
-the dimension `seq_dim`.
+the dimension `seq_axis`.
 
 The elements of `seq_lengths` must obey `seq_lengths[i] < input.dims[seq_dim]`,
 and `seq_lengths` must be a vector of length `input.dims[batch_dim]`.
 
-The output slice `i` along dimension `batch_dim` is then given by input
+The output slice `i` along dimension `batch_axis` is then given by input
 slice `i`, with the first `seq_lengths[i]` slices along dimension
-`seq_dim` reversed.
+`seq_axis` reversed.
 
 For example:
 
@@ -1282,8 +1283,8 @@ output[2:, :, 3, :, ...] = input[2:, :, 3, :, ...]
 *  <b>`seq_lengths`</b>: A `Tensor`. Must be one of the following types: `int32`, `int64`.
     1-D with length `input.dims(batch_dim)` and
     `max(seq_lengths) < input.dims(seq_dim)`
-*  <b>`seq_dim`</b>: An `int`. The dimension which is partially reversed.
-*  <b>`batch_dim`</b>: An optional `int`. Defaults to `0`.
+*  <b>`seq_axis`</b>: An `int`. The dimension which is partially reversed.
+*  <b>`batch_axis`</b>: An optional `int`. Defaults to `0`.
     The dimension along which reversal is performed.
 *  <b>`name`</b>: A name for the operation (optional).
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.reverse_sequence.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.reverse_sequence.md
index 03dd068320..b950cd5fe6 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.reverse_sequence.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.reverse_sequence.md
@@ -1,17 +1,17 @@
-### `tf.reverse_sequence(input, seq_lengths, seq_dim, batch_dim=None, name=None)` {#reverse_sequence}
+### `tf.reverse_sequence(input, seq_lengths, seq_axis=None, batch_axis=None, name=None, seq_dim=None, batch_dim=None)` {#reverse_sequence}
 
 Reverses variable length slices.
 
-This op first slices `input` along the dimension `batch_dim`, and for each
+This op first slices `input` along the dimension `batch_axis`, and for each
 slice `i`, reverses the first `seq_lengths[i]` elements along
-the dimension `seq_dim`.
+the dimension `seq_axis`.
 
 The elements of `seq_lengths` must obey `seq_lengths[i] < input.dims[seq_dim]`,
 and `seq_lengths` must be a vector of length `input.dims[batch_dim]`.
 
-The output slice `i` along dimension `batch_dim` is then given by input
+The output slice `i` along dimension `batch_axis` is then given by input
 slice `i`, with the first `seq_lengths[i]` slices along dimension
-`seq_dim` reversed.
+`seq_axis` reversed.
 
 For example:
 
@@ -64,8 +64,8 @@ output[2:, :, 3, :, ...] = input[2:, :, 3, :, ...]
 *  <b>`seq_lengths`</b>: A `Tensor`. Must be one of the following types: `int32`, `int64`.
     1-D with length `input.dims(batch_dim)` and
     `max(seq_lengths) < input.dims(seq_dim)`
-*  <b>`seq_dim`</b>: An `int`. The dimension which is partially reversed.
-*  <b>`batch_dim`</b>: An optional `int`. Defaults to `0`.
+*  <b>`seq_axis`</b>: An `int`. The dimension which is partially reversed.
+*  <b>`batch_axis`</b>: An optional `int`. Defaults to `0`.
     The dimension along which reversal is performed.
 *  <b>`name`</b>: A name for the operation (optional).
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.reduce_join.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.reduce_join.md
index ad49e98274..a93d8208ff 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.reduce_join.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.reduce_join.md
@@ -1,4 +1,4 @@
-### `tf.reduce_join(inputs, reduction_indices, keep_dims=None, separator=None, name=None)` {#reduce_join}
+### `tf.reduce_join(inputs, axis=None, keep_dims=False, separator='', name=None, reduction_indices=None)` {#reduce_join}
 
 Joins a string Tensor across the given dimensions.
 
@@ -6,7 +6,7 @@ Computes the string join across dimensions in the given string Tensor of shape
 `[d_0, d_1, ..., d_n-1]`.  Returns a new Tensor created by joining the input
 strings with the given separator (default: empty string).  Negative indices are
 counted backwards from the end, with `-1` being equivalent to `n - 1`.  Passing
-an empty `reduction_indices` joins all strings in linear index order and outputs
+an empty `axis` joins all strings in linear index order and outputs
 a scalar string.
 
 
@@ -31,9 +31,9 @@ tf.reduce_join(a, []) ==> ["abcd"]
 
 *  <b>`inputs`</b>: A `Tensor` of type `string`.
     The input to be joined.  All reduced indices must have non-zero size.
-*  <b>`reduction_indices`</b>: A `Tensor` of type `int32`.
+*  <b>`axis`</b>: A `Tensor` of type `int32`.
     The dimensions to reduce over.  Dimensions are reduced in the
-    order specified.  Omitting `reduction_indices` is equivalent to passing
+    order specified.  Omitting `axis` is equivalent to passing
     `[n-1, n-2, ..., 0]`.  Negative indices from `-n` to `-1` are supported.
 *  <b>`keep_dims`</b>: An optional `bool`. Defaults to `False`.
     If `True`, retain reduced dimensions with length `1`.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.split.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.split.md
index b6bfac36d4..23bc8386c2 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.split.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.split.md
@@ -1,9 +1,9 @@
-### `tf.split(split_dim, num_split, value, name='split')` {#split}
+### `tf.split(axis, num_split, value, name='split', split_dim=None)` {#split}
 
 Splits a tensor into `num_split` tensors along one dimension.
 
-Splits `value` along dimension `split_dim` into `num_split` smaller tensors.
-Requires that `num_split` evenly divide `value.shape[split_dim]`.
+Splits `value` along dimension `axis` into `num_split` smaller tensors.
+Requires that `num_split` evenly divide `value.shape[axis]`.
 
 For example:
 
@@ -31,11 +31,12 @@ tf.unpack(t, axis=axis)
 ##### Args:
 
 
-*  <b>`split_dim`</b>: A 0-D `int32` `Tensor`. The dimension along which to split.
+*  <b>`axis`</b>: A 0-D `int32` `Tensor`. The dimension along which to split.
     Must be in the range `[0, rank(value))`.
 *  <b>`num_split`</b>: A Python integer. The number of ways to split.
 *  <b>`value`</b>: The `Tensor` to split.
 *  <b>`name`</b>: A name for the operation (optional).
+*  <b>`split_dim`</b>: The old (deprecated) name for axis.
 
 ##### Returns:
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.sparse_concat.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.sparse_concat.md
index 618f1f0fef..70cab998b4 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.sparse_concat.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.sparse_concat.md
@@ -1,4 +1,4 @@
-### `tf.sparse_concat(concat_dim, sp_inputs, name=None, expand_nonconcat_dim=False)` {#sparse_concat}
+### `tf.sparse_concat(axis, sp_inputs, name=None, expand_nonconcat_dim=False, concat_dim=None)` {#sparse_concat}
 
 Concatenates a list of `SparseTensor` along the specified dimension.
 
@@ -27,7 +27,7 @@ This op runs in `O(M log M)` time, where `M` is the total number of non-empty
 values across all inputs. This is due to the need for an internal sort in
 order to concatenate efficiently across an arbitrary dimension.
 
-For example, if `concat_dim = 1` and the inputs are
+For example, if `axis = 1` and the inputs are
 
     sp_inputs[0]: shape = [2, 3]
     [0, 2]: "a"
@@ -52,7 +52,7 @@ Graphically this is equivalent to doing
     [    a] concat [  d e  ] = [    a   d e  ]
     [b c  ]        [       ]   [b c          ]
 
-Another example, if 'concat_dim = 1' and the inputs are
+Another example, if 'axis = 1' and the inputs are
 
     sp_inputs[0]: shape = [3, 3]
     [0, 2]: "a"
@@ -83,12 +83,13 @@ Graphically this is equivalent to doing
 ##### Args:
 
 
-*  <b>`concat_dim`</b>: Dimension to concatenate along. Must be in range [-rank, rank),
+*  <b>`axis`</b>: Dimension to concatenate along. Must be in range [-rank, rank),
     where rank is the number of dimensions in each input `SparseTensor`.
 *  <b>`sp_inputs`</b>: List of `SparseTensor` to concatenate.
 *  <b>`name`</b>: A name prefix for the returned tensors (optional).
 *  <b>`expand_nonconcat_dim`</b>: Whether to allow the expansion in the non-concat
     dimensions. Defaulted to False.
+*  <b>`concat_dim`</b>: The old (deprecated) name for axis.
 
 ##### Returns:
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.sparse_split.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.sparse_split.md
index e3e608a9e2..a92e79f53b 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.sparse_split.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.sparse_split.md
@@ -1,10 +1,10 @@
-### `tf.sparse_split(split_dim, num_split, sp_input, name=None)` {#sparse_split}
+### `tf.sparse_split(axis, num_split, sp_input, name=None, split_dim=None)` {#sparse_split}
 
-Split a `SparseTensor` into `num_split` tensors along `split_dim`.
+Split a `SparseTensor` into `num_split` tensors along `axis`.
 
-If the `sp_input.shape[split_dim]` is not an integer multiple of `num_split`
-each slice starting from 0:`shape[split_dim] % num_split` gets extra one
-dimension. For example, if `split_dim = 1` and `num_split = 2` and the
+If the `sp_input.shape[axis]` is not an integer multiple of `num_split`
+each slice starting from 0:`shape[axis] % num_split` gets extra one
+dimension. For example, if `axis = 1` and `num_split = 2` and the
 input is:
 
     input_tensor = shape = [2, 7]
@@ -24,10 +24,11 @@ Graphically the output tensors are:
 ##### Args:
 
 
-*  <b>`split_dim`</b>: A 0-D `int32` `Tensor`. The dimension along which to split.
+*  <b>`axis`</b>: A 0-D `int32` `Tensor`. The dimension along which to split.
 *  <b>`num_split`</b>: A Python integer. The number of ways to split.
 *  <b>`sp_input`</b>: The `SparseTensor` to split.
 *  <b>`name`</b>: A name for the operation (optional).
+*  <b>`split_dim`</b>: Deprecated old name for axis.
 
 ##### Returns:
 
@@ -37,4 +38,5 @@ Graphically the output tensors are:
 
 
 *  <b>`TypeError`</b>: If `sp_input` is not a `SparseTensor`.
+*  <b>`ValueError`</b>: If the deprecated `split_dim` and `axis` are both non None.
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md
index e9bdda200f..8abe6fba48 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.SummaryWriter.md
@@ -28,7 +28,7 @@ Please switch to tf.summary.FileWriter. The interface and behavior is the same;
     # Launch the graph in a session.
     sess = tf.Session()
     # Create a summary writer, add the 'graph' to the event file.
-    writer = tf.train.SummaryWriter(<some-directory>, sess.graph)
+    writer = tf.summary.FileWriter(<some-directory>, sess.graph)
     ```
 
     The other arguments to the constructor control the asynchronous writes to
diff --git a/tensorflow/g3doc/api_docs/python/sparse_ops.md b/tensorflow/g3doc/api_docs/python/sparse_ops.md
index 2590b21fcc..433a5cd4eb 100644
--- a/tensorflow/g3doc/api_docs/python/sparse_ops.md
+++ b/tensorflow/g3doc/api_docs/python/sparse_ops.md
@@ -566,7 +566,7 @@ equal to:
 
 - - -
 
-### `tf.sparse_concat(concat_dim, sp_inputs, name=None, expand_nonconcat_dim=False)` {#sparse_concat}
+### `tf.sparse_concat(axis, sp_inputs, name=None, expand_nonconcat_dim=False, concat_dim=None)` {#sparse_concat}
 
 Concatenates a list of `SparseTensor` along the specified dimension.
 
@@ -595,7 +595,7 @@ This op runs in `O(M log M)` time, where `M` is the total number of non-empty
 values across all inputs. This is due to the need for an internal sort in
 order to concatenate efficiently across an arbitrary dimension.
 
-For example, if `concat_dim = 1` and the inputs are
+For example, if `axis = 1` and the inputs are
 
     sp_inputs[0]: shape = [2, 3]
     [0, 2]: "a"
@@ -620,7 +620,7 @@ Graphically this is equivalent to doing
     [    a] concat [  d e  ] = [    a   d e  ]
     [b c  ]        [       ]   [b c          ]
 
-Another example, if 'concat_dim = 1' and the inputs are
+Another example, if 'axis = 1' and the inputs are
 
     sp_inputs[0]: shape = [3, 3]
     [0, 2]: "a"
@@ -651,12 +651,13 @@ Graphically this is equivalent to doing
 ##### Args:
 
 
-*  <b>`concat_dim`</b>: Dimension to concatenate along. Must be in range [-rank, rank),
+*  <b>`axis`</b>: Dimension to concatenate along. Must be in range [-rank, rank),
     where rank is the number of dimensions in each input `SparseTensor`.
 *  <b>`sp_inputs`</b>: List of `SparseTensor` to concatenate.
 *  <b>`name`</b>: A name prefix for the returned tensors (optional).
 *  <b>`expand_nonconcat_dim`</b>: Whether to allow the expansion in the non-concat
     dimensions. Defaulted to False.
+*  <b>`concat_dim`</b>: The old (deprecated) name for axis.
 
 ##### Returns:
 
@@ -768,13 +769,13 @@ shape `[9, 4]` and `indices` / `values`:
 
 - - -
 
-### `tf.sparse_split(split_dim, num_split, sp_input, name=None)` {#sparse_split}
+### `tf.sparse_split(axis, num_split, sp_input, name=None, split_dim=None)` {#sparse_split}
 
-Split a `SparseTensor` into `num_split` tensors along `split_dim`.
+Split a `SparseTensor` into `num_split` tensors along `axis`.
 
-If the `sp_input.shape[split_dim]` is not an integer multiple of `num_split`
-each slice starting from 0:`shape[split_dim] % num_split` gets extra one
-dimension. For example, if `split_dim = 1` and `num_split = 2` and the
+If the `sp_input.shape[axis]` is not an integer multiple of `num_split`
+each slice starting from 0:`shape[axis] % num_split` gets extra one
+dimension. For example, if `axis = 1` and `num_split = 2` and the
 input is:
 
     input_tensor = shape = [2, 7]
@@ -794,10 +795,11 @@ Graphically the output tensors are:
 ##### Args:
 
 
-*  <b>`split_dim`</b>: A 0-D `int32` `Tensor`. The dimension along which to split.
+*  <b>`axis`</b>: A 0-D `int32` `Tensor`. The dimension along which to split.
 *  <b>`num_split`</b>: A Python integer. The number of ways to split.
 *  <b>`sp_input`</b>: The `SparseTensor` to split.
 *  <b>`name`</b>: A name for the operation (optional).
+*  <b>`split_dim`</b>: Deprecated old name for axis.
 
 ##### Returns:
 
@@ -807,6 +809,7 @@ Graphically the output tensors are:
 
 
 *  <b>`TypeError`</b>: If `sp_input` is not a `SparseTensor`.
+*  <b>`ValueError`</b>: If the deprecated `split_dim` and `axis` are both non None.
 
 
 - - -
diff --git a/tensorflow/g3doc/api_docs/python/string_ops.md b/tensorflow/g3doc/api_docs/python/string_ops.md
index 7e75148891..fc27ba36f0 100644
--- a/tensorflow/g3doc/api_docs/python/string_ops.md
+++ b/tensorflow/g3doc/api_docs/python/string_ops.md
@@ -105,7 +105,7 @@ string tensor.
 
 - - -
 
-### `tf.reduce_join(inputs, reduction_indices, keep_dims=None, separator=None, name=None)` {#reduce_join}
+### `tf.reduce_join(inputs, axis=None, keep_dims=False, separator='', name=None, reduction_indices=None)` {#reduce_join}
 
 Joins a string Tensor across the given dimensions.
 
@@ -113,7 +113,7 @@ Computes the string join across dimensions in the given string Tensor of shape
 `[d_0, d_1, ..., d_n-1]`.  Returns a new Tensor created by joining the input
 strings with the given separator (default: empty string).  Negative indices are
 counted backwards from the end, with `-1` being equivalent to `n - 1`.  Passing
-an empty `reduction_indices` joins all strings in linear index order and outputs
+an empty `axis` joins all strings in linear index order and outputs
 a scalar string.
 
 
@@ -138,9 +138,9 @@ tf.reduce_join(a, []) ==> ["abcd"]
 
 *  <b>`inputs`</b>: A `Tensor` of type `string`.
     The input to be joined.  All reduced indices must have non-zero size.
-*  <b>`reduction_indices`</b>: A `Tensor` of type `int32`.
+*  <b>`axis`</b>: A `Tensor` of type `int32`.
     The dimensions to reduce over.  Dimensions are reduced in the
-    order specified.  Omitting `reduction_indices` is equivalent to passing
+    order specified.  Omitting `axis` is equivalent to passing
     `[n-1, n-2, ..., 0]`.  Negative indices from `-n` to `-1` are supported.
 *  <b>`keep_dims`</b>: An optional `bool`. Defaults to `False`.
     If `True`, retain reduced dimensions with length `1`.
diff --git a/tensorflow/g3doc/api_docs/python/train.md b/tensorflow/g3doc/api_docs/python/train.md
index ece566e65f..8e3fc525fd 100644
--- a/tensorflow/g3doc/api_docs/python/train.md
+++ b/tensorflow/g3doc/api_docs/python/train.md
@@ -4154,7 +4154,7 @@ Please switch to tf.summary.FileWriter. The interface and behavior is the same;
     # Launch the graph in a session.
     sess = tf.Session()
     # Create a summary writer, add the 'graph' to the event file.
-    writer = tf.train.SummaryWriter(<some-directory>, sess.graph)
+    writer = tf.summary.FileWriter(<some-directory>, sess.graph)
     ```
 
     The other arguments to the constructor control the asynchronous writes to