Update generated Python Op docs.

Change: 140789077

7 files changed, 114 insertions, 77 deletions

diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md
index ad46827ac2..118158d490 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md
@@ -1,50 +1,52 @@
-SparseTensorValue(indices, values, shape)
+Stores the calculated numpy arrays representing a `SparseTensor`.
+
+Returned as the output of a session.run on a `SparseTensor` object.
 - - -
 
-#### `tf.SparseTensorValue.__getnewargs__()` {#SparseTensorValue.__getnewargs__}
+#### `tf.SparseTensorValue.__getitem__(i)` {#SparseTensorValue.__getitem__}
+
 
-Return self as a plain tuple.  Used by copy and pickle.
 
 
 - - -
 
-#### `tf.SparseTensorValue.__getstate__()` {#SparseTensorValue.__getstate__}
+#### `tf.SparseTensorValue.__init__(indices, values, dense_shape=None, shape=None)` {#SparseTensorValue.__init__}
+
 
-Exclude the OrderedDict from pickling
 
 
 - - -
 
-#### `tf.SparseTensorValue.__new__(_cls, indices, values, shape)` {#SparseTensorValue.__new__}
+#### `tf.SparseTensorValue.__iter__()` {#SparseTensorValue.__iter__}
+
 
-Create new instance of SparseTensorValue(indices, values, shape)
 
 
 - - -
 
-#### `tf.SparseTensorValue.__repr__()` {#SparseTensorValue.__repr__}
+#### `tf.SparseTensorValue.dense_shape` {#SparseTensorValue.dense_shape}
+
 
-Return a nicely formatted representation string
 
 
 - - -
 
 #### `tf.SparseTensorValue.indices` {#SparseTensorValue.indices}
 
-Alias for field number 0
+
 
 
 - - -
 
 #### `tf.SparseTensorValue.shape` {#SparseTensorValue.shape}
 
-Alias for field number 2
+
 
 
 - - -
 
 #### `tf.SparseTensorValue.values` {#SparseTensorValue.values}
 
-Alias for field number 1
+
 
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md
index 97fb6b760c..a0252d096a 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md
@@ -208,7 +208,7 @@ Split the values of a `Tensor` into the TensorArray.
 #### Other Methods
 - - -
 
-#### `tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, elem_shape=None, name=None)` {#TensorArray.__init__}
+#### `tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, element_shape=None, name=None)` {#TensorArray.__init__}
 
 Construct a new TensorArray or wrap an existing TensorArray handle.
 
@@ -239,8 +239,9 @@ is created within a `while_loop`.
     `TensorArray.flow`.
 *  <b>`infer_shape`</b>: (optional, default: True) If True, shape inference
     is enabled.  In this case, all elements must have the same shape.
-*  <b>`elem_shape`</b>: (optional, default: None) A TensorShape object specifying
-    the shape of all the elements of the TensorArray.
+*  <b>`element_shape`</b>: (optional, default: None) A `TensorShape` object specifying
+    the shape constraints of each of the elements of the TensorArray.
+    Need not be fully defined.
 *  <b>`name`</b>: A name for the operation (optional).
 
 ##### Raises:
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.SparseTensorValue.__new__.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.SparseTensorValue.__new__.md
deleted file mode 100644
index e805f29b98..0000000000
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.SparseTensorValue.__new__.md
+++ /dev/null
@@ -1,4 +0,0 @@
-#### `tf.SparseTensorValue.__new__(_cls, indices, values, shape)` {#SparseTensorValue.__new__}
-
-Create new instance of SparseTensorValue(indices, values, shape)
-
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.SparseTensor.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.SparseTensor.md
index d89b4e70c4..137cf621d4 100644
--- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.SparseTensor.md
+++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.SparseTensor.md
@@ -1,37 +1,41 @@
 Represents a sparse tensor.
 
 TensorFlow represents a sparse tensor as three separate dense tensors:
-`indices`, `values`, and `shape`.  In Python, the three tensors are
+`indices`, `values`, and `dense_shape`.  In Python, the three tensors are
 collected into a `SparseTensor` class for ease of use.  If you have separate
-`indices`, `values`, and `shape` tensors, wrap them in a `SparseTensor`
+`indices`, `values`, and `dense_shape` tensors, wrap them in a `SparseTensor`
 object before passing to the ops below.
 
-Concretely, the sparse tensor `SparseTensor(indices, values, shape)`
+Concretely, the sparse tensor `SparseTensor(indices, values, dense_shape)`
 comprises the following components, where `N` and `ndims` are the number
 of values and number of dimensions in the `SparseTensor`, respectively:
 
-* `indices`: A 2-D int64 tensor of shape `[N, ndims]`, which specifies
+* `indices`: A 2-D int64 tensor of dense_shape `[N, ndims]`, which specifies
   the indices of the elements in the sparse tensor that contain nonzero
   values (elements are zero-indexed). For example, `indices=[[1,3], [2,4]]`
   specifies that the elements with indexes of [1,3] and [2,4] have
   nonzero values.
 
-* `values`: A 1-D tensor of any type and shape `[N]`, which supplies the
+* `values`: A 1-D tensor of any type and dense_shape `[N]`, which supplies the
   values for each element in `indices`. For example, given
   `indices=[[1,3], [2,4]]`, the parameter `values=[18, 3.6]` specifies
   that element [1,3] of the sparse tensor has a value of 18, and element
   [2,4] of the tensor has a value of 3.6.
 
-* `shape`: A 1-D int64 tensor of shape `[ndims]`, which specifies the shape
-  of the sparse tensor. Takes a list indicating the number of elements in
-  each dimension. For example, `shape=[3,6]` specifies a two-dimensional 3x6
-  tensor, `shape=[2,3,4]` specifies a three-dimensional 2x3x4 tensor, and
-  `shape=[9]` specifies a one-dimensional tensor with 9 elements.
+* `dense_shape`: A 1-D int64 tensor of dense_shape `[ndims]`, which specifies
+the
+  dense_shape of the sparse tensor. Takes a list indicating the number of
+  elements
+  in each dimension. For example, `dense_shape=[3,6]` specifies a
+  two-dimensional
+  3x6 tensor, `dense_shape=[2,3,4]` specifies a three-dimensional 2x3x4
+  tensor, and
+  `dense_shape=[9]` specifies a one-dimensional tensor with 9 elements.
 
 The corresponding dense tensor satisfies:
 
 ```python
-dense.shape = shape
+dense.shape = dense_shape
 dense[tuple(indices[i])] = values[i]
 ```
 
@@ -44,7 +48,7 @@ obtained by calling `tf.sparse_reorder(st)`.
 Example: The sparse tensor
 
 ```python
-SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], shape=[3, 4])
+SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], dense_shape=[3, 4])
 ```
 
 represents the dense tensor
@@ -57,27 +61,34 @@ represents the dense tensor
 
 - - -
 
-#### `tf.SparseTensor.__init__(indices, values, shape)` {#SparseTensor.__init__}
+#### `tf.SparseTensor.__init__(indices, values, dense_shape=None, shape=None)` {#SparseTensor.__init__}
 
 Creates a `SparseTensor`.
 
 ##### Args:
 
 
-*  <b>`indices`</b>: A 2-D int64 tensor of shape `[N, ndims]`.
-*  <b>`values`</b>: A 1-D tensor of any type and shape `[N]`.
-*  <b>`shape`</b>: A 1-D int64 tensor of shape `[ndims]`.
+*  <b>`indices`</b>: A 2-D int64 tensor of dense_shape `[N, ndims]`.
+*  <b>`values`</b>: A 1-D tensor of any type and dense_shape `[N]`.
+*  <b>`dense_shape`</b>: A 1-D int64 tensor of dense_shape `[ndims]`.
+*  <b>`shape`</b>: Temporary.  Legacy naming of dense_shape.  Only one of `shape` or
+    `dense_shape` must be provided.
 
 ##### Returns:
 
-  A `SparseTensor`
+  A `SparseTensor`.
+
+##### Raises:
+
+
+*  <b>`ValueError`</b>: if both `shape` and `dense_shape` are provided.
 
 
 - - -
 
 #### `tf.SparseTensor.get_shape()` {#SparseTensor.get_shape}
 
-Get the `TensorShape` that represents the shape of the dense tensor.
+Get the `TensorShape` representing the shape of the dense tensor.
 
 ##### Returns:
 
@@ -92,7 +103,7 @@ The indices of non-zero values in the represented dense tensor.
 
 ##### Returns:
 
-  A 2-D Tensor of int64 with shape `[N, ndims]`, where `N` is the
+  A 2-D Tensor of int64 with dense_shape `[N, ndims]`, where `N` is the
     number of non-zero values in the tensor, and `ndims` is the rank.
 
 
@@ -109,7 +120,7 @@ The non-zero values in the represented dense tensor.
 
 - - -
 
-#### `tf.SparseTensor.shape` {#SparseTensor.shape}
+#### `tf.SparseTensor.dense_shape` {#SparseTensor.dense_shape}
 
 A 1-D Tensor of int64 representing the shape of the dense tensor.
 
@@ -132,7 +143,7 @@ The `Operation` that produces `values` as an output.
 
 #### `tf.SparseTensor.graph` {#SparseTensor.graph}
 
-The `Graph` that contains the index, value, and shape tensors.
+The `Graph` that contains the index, value, and dense_shape tensors.
 
 
 
@@ -248,3 +259,10 @@ available, or `session` must be specified explicitly.
 
 
 
+- - -
+
+#### `tf.SparseTensor.shape` {#SparseTensor.shape}
+
+Legacy property returning `dense_shape`.
+
+
diff --git a/tensorflow/g3doc/api_docs/python/index.md b/tensorflow/g3doc/api_docs/python/index.md
index ae1f47ec43..5c04276e93 100644
--- a/tensorflow/g3doc/api_docs/python/index.md
+++ b/tensorflow/g3doc/api_docs/python/index.md
@@ -415,7 +415,6 @@
   * [`transpose_image`](../../api_docs/python/image.md#transpose_image)
 
 * **[Sparse Tensors](../../api_docs/python/sparse_ops.md)**:
-  * [`shape`](../../api_docs/python/sparse_ops.md#shape)
   * [`sparse_add`](../../api_docs/python/sparse_ops.md#sparse_add)
   * [`sparse_concat`](../../api_docs/python/sparse_ops.md#sparse_concat)
   * [`sparse_fill_empty_rows`](../../api_docs/python/sparse_ops.md#sparse_fill_empty_rows)
diff --git a/tensorflow/g3doc/api_docs/python/sparse_ops.md b/tensorflow/g3doc/api_docs/python/sparse_ops.md
index 433a5cd4eb..35611e117c 100644
--- a/tensorflow/g3doc/api_docs/python/sparse_ops.md
+++ b/tensorflow/g3doc/api_docs/python/sparse_ops.md
@@ -21,37 +21,41 @@ dimension, and dense along all other dimensions.
 Represents a sparse tensor.
 
 TensorFlow represents a sparse tensor as three separate dense tensors:
-`indices`, `values`, and `shape`.  In Python, the three tensors are
+`indices`, `values`, and `dense_shape`.  In Python, the three tensors are
 collected into a `SparseTensor` class for ease of use.  If you have separate
-`indices`, `values`, and `shape` tensors, wrap them in a `SparseTensor`
+`indices`, `values`, and `dense_shape` tensors, wrap them in a `SparseTensor`
 object before passing to the ops below.
 
-Concretely, the sparse tensor `SparseTensor(indices, values, shape)`
+Concretely, the sparse tensor `SparseTensor(indices, values, dense_shape)`
 comprises the following components, where `N` and `ndims` are the number
 of values and number of dimensions in the `SparseTensor`, respectively:
 
-* `indices`: A 2-D int64 tensor of shape `[N, ndims]`, which specifies
+* `indices`: A 2-D int64 tensor of dense_shape `[N, ndims]`, which specifies
   the indices of the elements in the sparse tensor that contain nonzero
   values (elements are zero-indexed). For example, `indices=[[1,3], [2,4]]`
   specifies that the elements with indexes of [1,3] and [2,4] have
   nonzero values.
 
-* `values`: A 1-D tensor of any type and shape `[N]`, which supplies the
+* `values`: A 1-D tensor of any type and dense_shape `[N]`, which supplies the
   values for each element in `indices`. For example, given
   `indices=[[1,3], [2,4]]`, the parameter `values=[18, 3.6]` specifies
   that element [1,3] of the sparse tensor has a value of 18, and element
   [2,4] of the tensor has a value of 3.6.
 
-* `shape`: A 1-D int64 tensor of shape `[ndims]`, which specifies the shape
-  of the sparse tensor. Takes a list indicating the number of elements in
-  each dimension. For example, `shape=[3,6]` specifies a two-dimensional 3x6
-  tensor, `shape=[2,3,4]` specifies a three-dimensional 2x3x4 tensor, and
-  `shape=[9]` specifies a one-dimensional tensor with 9 elements.
+* `dense_shape`: A 1-D int64 tensor of dense_shape `[ndims]`, which specifies
+the
+  dense_shape of the sparse tensor. Takes a list indicating the number of
+  elements
+  in each dimension. For example, `dense_shape=[3,6]` specifies a
+  two-dimensional
+  3x6 tensor, `dense_shape=[2,3,4]` specifies a three-dimensional 2x3x4
+  tensor, and
+  `dense_shape=[9]` specifies a one-dimensional tensor with 9 elements.
 
 The corresponding dense tensor satisfies:
 
 ```python
-dense.shape = shape
+dense.shape = dense_shape
 dense[tuple(indices[i])] = values[i]
 ```
 
@@ -64,7 +68,7 @@ obtained by calling `tf.sparse_reorder(st)`.
 Example: The sparse tensor
 
 ```python
-SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], shape=[3, 4])
+SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], dense_shape=[3, 4])
 ```
 
 represents the dense tensor
@@ -77,27 +81,34 @@ represents the dense tensor
 
 - - -
 
-#### `tf.SparseTensor.__init__(indices, values, shape)` {#SparseTensor.__init__}
+#### `tf.SparseTensor.__init__(indices, values, dense_shape=None, shape=None)` {#SparseTensor.__init__}
 
 Creates a `SparseTensor`.
 
 ##### Args:
 
 
-*  <b>`indices`</b>: A 2-D int64 tensor of shape `[N, ndims]`.
-*  <b>`values`</b>: A 1-D tensor of any type and shape `[N]`.
-*  <b>`shape`</b>: A 1-D int64 tensor of shape `[ndims]`.
+*  <b>`indices`</b>: A 2-D int64 tensor of dense_shape `[N, ndims]`.
+*  <b>`values`</b>: A 1-D tensor of any type and dense_shape `[N]`.
+*  <b>`dense_shape`</b>: A 1-D int64 tensor of dense_shape `[ndims]`.
+*  <b>`shape`</b>: Temporary.  Legacy naming of dense_shape.  Only one of `shape` or
+    `dense_shape` must be provided.
 
 ##### Returns:
 
-  A `SparseTensor`
+  A `SparseTensor`.
+
+##### Raises:
+
+
+*  <b>`ValueError`</b>: if both `shape` and `dense_shape` are provided.
 
 
 - - -
 
 #### `tf.SparseTensor.get_shape()` {#SparseTensor.get_shape}
 
-Get the `TensorShape` that represents the shape of the dense tensor.
+Get the `TensorShape` representing the shape of the dense tensor.
 
 ##### Returns:
 
@@ -112,7 +123,7 @@ The indices of non-zero values in the represented dense tensor.
 
 ##### Returns:
 
-  A 2-D Tensor of int64 with shape `[N, ndims]`, where `N` is the
+  A 2-D Tensor of int64 with dense_shape `[N, ndims]`, where `N` is the
     number of non-zero values in the tensor, and `ndims` is the rank.
 
 
@@ -129,7 +140,7 @@ The non-zero values in the represented dense tensor.
 
 - - -
 
-#### `tf.SparseTensor.shape` {#SparseTensor.shape}
+#### `tf.SparseTensor.dense_shape` {#SparseTensor.dense_shape}
 
 A 1-D Tensor of int64 representing the shape of the dense tensor.
 
@@ -152,7 +163,7 @@ The `Operation` that produces `values` as an output.
 
 #### `tf.SparseTensor.graph` {#SparseTensor.graph}
 
-The `Graph` that contains the index, value, and shape tensors.
+The `Graph` that contains the index, value, and dense_shape tensors.
 
 
 
@@ -268,59 +279,68 @@ available, or `session` must be specified explicitly.
 
 
 
+- - -
+
+#### `tf.SparseTensor.shape` {#SparseTensor.shape}
+
+Legacy property returning `dense_shape`.
+
+
 
 - - -
 
 ### `class tf.SparseTensorValue` {#SparseTensorValue}
 
-SparseTensorValue(indices, values, shape)
+Stores the calculated numpy arrays representing a `SparseTensor`.
+
+Returned as the output of a session.run on a `SparseTensor` object.
 - - -
 
-#### `tf.SparseTensorValue.__getnewargs__()` {#SparseTensorValue.__getnewargs__}
+#### `tf.SparseTensorValue.__getitem__(i)` {#SparseTensorValue.__getitem__}
+
 
-Return self as a plain tuple.  Used by copy and pickle.
 
 
 - - -
 
-#### `tf.SparseTensorValue.__getstate__()` {#SparseTensorValue.__getstate__}
+#### `tf.SparseTensorValue.__init__(indices, values, dense_shape=None, shape=None)` {#SparseTensorValue.__init__}
+
 
-Exclude the OrderedDict from pickling
 
 
 - - -
 
-#### `tf.SparseTensorValue.__new__(_cls, indices, values, shape)` {#SparseTensorValue.__new__}
+#### `tf.SparseTensorValue.__iter__()` {#SparseTensorValue.__iter__}
+
 
-Create new instance of SparseTensorValue(indices, values, shape)
 
 
 - - -
 
-#### `tf.SparseTensorValue.__repr__()` {#SparseTensorValue.__repr__}
+#### `tf.SparseTensorValue.dense_shape` {#SparseTensorValue.dense_shape}
+
 
-Return a nicely formatted representation string
 
 
 - - -
 
 #### `tf.SparseTensorValue.indices` {#SparseTensorValue.indices}
 
-Alias for field number 0
+
 
 
 - - -
 
 #### `tf.SparseTensorValue.shape` {#SparseTensorValue.shape}
 
-Alias for field number 2
+
 
 
 - - -
 
 #### `tf.SparseTensorValue.values` {#SparseTensorValue.values}
 
-Alias for field number 1
+
 
 
 
diff --git a/tensorflow/g3doc/api_docs/python/tensor_array_ops.md b/tensorflow/g3doc/api_docs/python/tensor_array_ops.md
index 61927d4694..c5019f41bf 100644
--- a/tensorflow/g3doc/api_docs/python/tensor_array_ops.md
+++ b/tensorflow/g3doc/api_docs/python/tensor_array_ops.md
@@ -225,7 +225,7 @@ Split the values of a `Tensor` into the TensorArray.
 #### Other Methods
 - - -
 
-#### `tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, elem_shape=None, name=None)` {#TensorArray.__init__}
+#### `tf.TensorArray.__init__(dtype, size=None, dynamic_size=None, clear_after_read=None, tensor_array_name=None, handle=None, flow=None, infer_shape=True, element_shape=None, name=None)` {#TensorArray.__init__}
 
 Construct a new TensorArray or wrap an existing TensorArray handle.
 
@@ -256,8 +256,9 @@ is created within a `while_loop`.
     `TensorArray.flow`.
 *  <b>`infer_shape`</b>: (optional, default: True) If True, shape inference
     is enabled.  In this case, all elements must have the same shape.
-*  <b>`elem_shape`</b>: (optional, default: None) A TensorShape object specifying
-    the shape of all the elements of the TensorArray.
+*  <b>`element_shape`</b>: (optional, default: None) A `TensorShape` object specifying
+    the shape constraints of each of the elements of the TensorArray.
+    Need not be fully defined.
 *  <b>`name`</b>: A name for the operation (optional).
 
 ##### Raises: