Merge pull request #7828 from tensorflow/skleinfeld-patch-2

Adding missing close parenthesis in code listing.

tensorflow/g3doc/api_docs/python/array_ops.md

@@ -476,53 +476,57 @@ shape(squeeze(t, [2, 4])) ==> [1, 2, 3, 1]
 
 ### `tf.expand_dims(input, axis=None, name=None, dim=None)` {#expand_dims}
 
-Inserts a axisension of 1 into a tensor's shape.
+Inserts a dimension of 1 into a tensor's shape.
 
-Given a tensor `input`, this operation inserts a axisension of 1 at the
+Given a tensor `input`, this operation inserts a dimension of 1 at the
-axisension index `axis` of `input`'s shape. The axisension index `axis` starts at
+dimension index `axis` of `input`'s shape. The dimension index `axis` starts
-zero; if you specify a negative number for `axis` it is counted backward from
+at zero; if you specify a negative number for `axis` it is counted backward
-the end.
+from the end.
 
-This operation is useful if you want to add a batch axisension to a single
+This operation is useful if you want to add a batch dimension to a single
 element. For example, if you have a single image of shape `[height, width,
-channels]`, you can make it a batch of 1 image with `expand_axiss(image, 0)`,
+channels]`, you can make it a batch of 1 image with `expand_dims(image, 0)`,
 which will make the shape `[1, height, width, channels]`.
 
 Other examples:
 
-```prettyprint
+```python
 # 't' is a tensor of shape [2]
-shape(expand_axiss(t, 0)) ==> [1, 2]
+shape(expand_dims(t, 0)) ==> [1, 2]
-shape(expand_axiss(t, 1)) ==> [2, 1]
+shape(expand_dims(t, 1)) ==> [2, 1]
-shape(expand_axiss(t, -1)) ==> [2, 1]
+shape(expand_dims(t, -1)) ==> [2, 1]
 
 # 't2' is a tensor of shape [2, 3, 5]
-shape(expand_axiss(t2, 0)) ==> [1, 2, 3, 5]
+shape(expand_dims(t2, 0)) ==> [1, 2, 3, 5]
-shape(expand_axiss(t2, 2)) ==> [2, 3, 1, 5]
+shape(expand_dims(t2, 2)) ==> [2, 3, 1, 5]
-shape(expand_axiss(t2, 3)) ==> [2, 3, 5, 1]
+shape(expand_dims(t2, 3)) ==> [2, 3, 5, 1]
 ```
 
 This operation requires that:
 
-`-1-input.axiss() <= axis <= input.axiss()`
+`-1-input.dims() <= dim <= input.dims()`
 
-This operation is related to `squeeze()`, which removes axisensions of
+This operation is related to `squeeze()`, which removes dimensions of
 size 1.
 
 ##### Args:
 
 
 *  <b>`input`</b>: A `Tensor`.
-*  <b>`axis`</b>: A `Tensor`. Must be one of the following types: `int32`, `int64`.
+*  <b>`axis`</b>: 0-D (scalar). Specifies the dimension index at which to
-    0-D (scalar). Specifies the axisension index at which to
     expand the shape of `input`.
-*  <b>`name`</b>: A name for the operation (optional).
+*  <b>`name`</b>: The name of the output `Tensor`.
+*  <b>`dim`</b>: 0-D (scalar). Equivalent to `axis`, to be deprecated.
 
 ##### Returns:
 
-  A `Tensor`. Has the same type as `input`.
+  A `Tensor` with the same data as `input`, but its shape has an additional
-  Contains the same data as `input`, but its shape has an additional
+  dimension of size 1 added.
-  axisension of size 1 added.
+
+##### Raises:
+
+
+*  <b>`ValueError`</b>: if both `dim` and `axis` are specified.
 
 
 - - -

tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.expand_dims.md

@@ -1,50 +1,54 @@
 ### `tf.expand_dims(input, axis=None, name=None, dim=None)` {#expand_dims}
 
-Inserts a axisension of 1 into a tensor's shape.
+Inserts a dimension of 1 into a tensor's shape.
 
-Given a tensor `input`, this operation inserts a axisension of 1 at the
+Given a tensor `input`, this operation inserts a dimension of 1 at the
-axisension index `axis` of `input`'s shape. The axisension index `axis` starts at
+dimension index `axis` of `input`'s shape. The dimension index `axis` starts
-zero; if you specify a negative number for `axis` it is counted backward from
+at zero; if you specify a negative number for `axis` it is counted backward
-the end.
+from the end.
 
-This operation is useful if you want to add a batch axisension to a single
+This operation is useful if you want to add a batch dimension to a single
 element. For example, if you have a single image of shape `[height, width,
-channels]`, you can make it a batch of 1 image with `expand_axiss(image, 0)`,
+channels]`, you can make it a batch of 1 image with `expand_dims(image, 0)`,
 which will make the shape `[1, height, width, channels]`.
 
 Other examples:
 
-```prettyprint
+```python
 # 't' is a tensor of shape [2]
-shape(expand_axiss(t, 0)) ==> [1, 2]
+shape(expand_dims(t, 0)) ==> [1, 2]
-shape(expand_axiss(t, 1)) ==> [2, 1]
+shape(expand_dims(t, 1)) ==> [2, 1]
-shape(expand_axiss(t, -1)) ==> [2, 1]
+shape(expand_dims(t, -1)) ==> [2, 1]
 
 # 't2' is a tensor of shape [2, 3, 5]
-shape(expand_axiss(t2, 0)) ==> [1, 2, 3, 5]
+shape(expand_dims(t2, 0)) ==> [1, 2, 3, 5]
-shape(expand_axiss(t2, 2)) ==> [2, 3, 1, 5]
+shape(expand_dims(t2, 2)) ==> [2, 3, 1, 5]
-shape(expand_axiss(t2, 3)) ==> [2, 3, 5, 1]
+shape(expand_dims(t2, 3)) ==> [2, 3, 5, 1]
 ```
 
 This operation requires that:
 
-`-1-input.axiss() <= axis <= input.axiss()`
+`-1-input.dims() <= dim <= input.dims()`
 
-This operation is related to `squeeze()`, which removes axisensions of
+This operation is related to `squeeze()`, which removes dimensions of
 size 1.
 
 ##### Args:
 
 
 *  <b>`input`</b>: A `Tensor`.
-*  <b>`axis`</b>: A `Tensor`. Must be one of the following types: `int32`, `int64`.
+*  <b>`axis`</b>: 0-D (scalar). Specifies the dimension index at which to
-    0-D (scalar). Specifies the axisension index at which to
     expand the shape of `input`.
-*  <b>`name`</b>: A name for the operation (optional).
+*  <b>`name`</b>: The name of the output `Tensor`.
+*  <b>`dim`</b>: 0-D (scalar). Equivalent to `axis`, to be deprecated.
 
 ##### Returns:
 
-  A `Tensor`. Has the same type as `input`.
+  A `Tensor` with the same data as `input`, but its shape has an additional
-  Contains the same data as `input`, but its shape has an additional
+  dimension of size 1 added.
-  axisension of size 1 added.
+
+##### Raises:
+
+
+*  <b>`ValueError`</b>: if both `dim` and `axis` are specified.
 

tensorflow/g3doc/tutorials/input_fn/index.md

@@ -286,7 +286,7 @@ accept a _pandas_ `Dataframe` and return feature column and label values as
 
 ```python
 def input_fn(data_set):
-  feature_cols = {k: tf.constant(data_set[k].values
+  feature_cols = {k: tf.constant(data_set[k].values)
                   for k in FEATURES}
   labels = tf.constant(data_set[LABEL].values)
   return feature_cols, labels

tensorflow/python/ops/array_ops.py

@@ -130,13 +130,59 @@ _baseslice = slice
 
 # pylint: disable=redefined-builtin,protected-access
 def expand_dims(input, axis=None, name=None, dim=None):
+  """Inserts a dimension of 1 into a tensor's shape.
+
+  Given a tensor `input`, this operation inserts a dimension of 1 at the
+  dimension index `axis` of `input`'s shape. The dimension index `axis` starts
+  at zero; if you specify a negative number for `axis` it is counted backward
+  from the end.
+
+  This operation is useful if you want to add a batch dimension to a single
+  element. For example, if you have a single image of shape `[height, width,
+  channels]`, you can make it a batch of 1 image with `expand_dims(image, 0)`,
+  which will make the shape `[1, height, width, channels]`.
+
+  Other examples:
+
+  ```python
+  # 't' is a tensor of shape [2]
+  shape(expand_dims(t, 0)) ==> [1, 2]
+  shape(expand_dims(t, 1)) ==> [2, 1]
+  shape(expand_dims(t, -1)) ==> [2, 1]
+
+  # 't2' is a tensor of shape [2, 3, 5]
+  shape(expand_dims(t2, 0)) ==> [1, 2, 3, 5]
+  shape(expand_dims(t2, 2)) ==> [2, 3, 1, 5]
+  shape(expand_dims(t2, 3)) ==> [2, 3, 5, 1]
+  ```
+
+  This operation requires that:
+
+  `-1-input.dims() <= dim <= input.dims()`
+
+  This operation is related to `squeeze()`, which removes dimensions of
+  size 1.
+
+  Args:
+    input: A `Tensor`.
+    axis: 0-D (scalar). Specifies the dimension index at which to
+      expand the shape of `input`.
+    name: The name of the output `Tensor`.
+    dim: 0-D (scalar). Equivalent to `axis`, to be deprecated.
+
+  Returns:
+    A `Tensor` with the same data as `input`, but its shape has an additional
+    dimension of size 1 added.
+
+  Raises:
+    ValueError: if both `dim` and `axis` are specified.
+  """
   # TODO(aselle): Remove argument dim
   if dim is not None:
     if axis is not None:
       raise ValueError("can't specify both 'dim' and 'axis'")
     axis = dim
   return gen_array_ops._expand_dims(input, axis, name)
-expand_dims.__doc__ = gen_array_ops._expand_dims.__doc__.replace("dim", "axis")
 # pylint: enable=redefined-builtin,protected-access
 
 

tensorflow/workspace.bzl

@@ -64,7 +64,7 @@ def tf_workspace(path_prefix = "", tf_repo_name = ""):
 
   native.new_http_archive(
     name = "nasm",
-    url = "http://www.nasm.us/pub/nasm/releasebuilds/2.12.02/nasm-2.12.02.tar.bz2",
+    url = "http://pkgs.fedoraproject.org/repo/pkgs/nasm/nasm-2.12.02.tar.bz2/d15843c3fb7db39af80571ee27ec6fad/nasm-2.12.02.tar.bz2",
     sha256 = "00b0891c678c065446ca59bcee64719d0096d54d6886e6e472aeee2e170ae324",
     strip_prefix = "nasm-2.12.02",
     build_file = str(Label("//third_party:nasm.BUILD")),
@@ -228,7 +228,7 @@ def tf_workspace(path_prefix = "", tf_repo_name = ""):
 
   native.new_http_archive(
     name = "zlib_archive",
-    url = "http://zlib.net/zlib-1.2.8.tar.gz",
+    url = "http://zlib.net/fossils/zlib-1.2.8.tar.gz",
     sha256 = "36658cb768a54c1d4dec43c3116c27ed893e88b02ecfcb44f2166f9c0b7f2a0d",
     strip_prefix = "zlib-1.2.8",
     build_file = str(Label("//:zlib.BUILD")),