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TensorFlow: Upstream changes to git.
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Changes:
- Lot of updates to docs.

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keveman committed Nov 9, 2015
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162 changes: 81 additions & 81 deletions tensorflow/g3doc/api_docs/python/array_ops.md
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30 changes: 15 additions & 15 deletions tensorflow/g3doc/api_docs/python/client.md
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Expand Up @@ -110,11 +110,11 @@ the session constructor.
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>target</b>: (Optional.) The execution engine to connect to.
* <b>`target`</b>: (Optional.) The execution engine to connect to.
Defaults to using an in-process engine. At present, no value
other than the empty string is supported.
* <b>graph</b>: (Optional.) The `Graph` to be launched (described above).
* <b>config</b>: (Optional.) A [`ConfigProto`](https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/config.proto)
* <b>`graph`</b>: (Optional.) The `Graph` to be launched (described above).
* <b>`config`</b>: (Optional.) A [`ConfigProto`](https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/config.proto)
protocol buffer with configuration options for the session.


Expand Down Expand Up @@ -163,9 +163,9 @@ one of the following types:
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>fetches</b>: A single graph element, or a list of graph elements
* <b>`fetches`</b>: A single graph element, or a list of graph elements
(described above).
* <b>feed_dict</b>: A dictionary that maps graph elements to values
* <b>`feed_dict`</b>: A dictionary that maps graph elements to values
(described above).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>
Expand All @@ -176,10 +176,10 @@ one of the following types:
##### Raises: <a class="md-anchor" id="AUTOGENERATED-raises-"></a>


* <b>RuntimeError</b>: If this `Session` is in an invalid state (e.g. has been
* <b>`RuntimeError`</b>: If this `Session` is in an invalid state (e.g. has been
closed).
* <b>TypeError</b>: If `fetches` or `feed_dict` keys are of an inappropriate type.
* <b>ValueError</b>: If `fetches` or `feed_dict` keys are invalid or refer to a
* <b>`TypeError`</b>: If `fetches` or `feed_dict` keys are of an inappropriate type.
* <b>`ValueError`</b>: If `fetches` or `feed_dict` keys are invalid or refer to a
`Tensor` that doesn't exist.


Expand All @@ -194,7 +194,7 @@ Calling this method frees all resources associated with the session.
##### Raises: <a class="md-anchor" id="AUTOGENERATED-raises-"></a>


* <b>RuntimeError</b>: If an error occurs while closing the session.
* <b>`RuntimeError`</b>: If an error occurs while closing the session.



Expand Down Expand Up @@ -318,10 +318,10 @@ the session constructor.
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>target</b>: (Optional.) The execution engine to connect to.
* <b>`target`</b>: (Optional.) The execution engine to connect to.
Defaults to using an in-process engine. At present, no value
other than the empty string is supported.
* <b>graph</b>: (Optional.) The `Graph` to be launched (described above).
* <b>`graph`</b>: (Optional.) The `Graph` to be launched (described above).


- - -
Expand Down Expand Up @@ -398,10 +398,10 @@ Creates a new OpError indicating that a particular op failed.
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>node_def</b>: The graph_pb2.NodeDef proto representing the op that failed.
* <b>op</b>: The ops.Operation that failed, if known; otherwise None.
* <b>message</b>: The message string describing the failure.
* <b>error_code</b>: The error_codes_pb2.Code describing the error.
* <b>`node_def`</b>: The graph_pb2.NodeDef proto representing the op that failed.
* <b>`op`</b>: The ops.Operation that failed, if known; otherwise None.
* <b>`message`</b>: The message string describing the failure.
* <b>`error_code`</b>: The error_codes_pb2.Code describing the error.


- - -
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98 changes: 49 additions & 49 deletions tensorflow/g3doc/api_docs/python/constant_op.md
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Expand Up @@ -51,9 +51,9 @@ tf.zeros([3, 4], int32) ==> [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>shape</b>: Either a list of integers, or a 1-D `Tensor` of type `int32`.
* <b>dtype</b>: The type of an element in the resulting `Tensor`.
* <b>name</b>: A name for the operation (optional).
* <b>`shape`</b>: Either a list of integers, or a 1-D `Tensor` of type `int32`.
* <b>`dtype`</b>: The type of an element in the resulting `Tensor`.
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand All @@ -80,11 +80,11 @@ tf.zeros_like(tensor) ==> [[0, 0, 0], [0, 0, 0]]
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>tensor</b>: A `Tensor`.
* <b>dtype</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
* <b>`tensor`</b>: A `Tensor`.
* <b>`dtype`</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
`int8`, `int16`, `int32`, `int64`, `uint8`, or `complex64`.

* <b>name</b>: A name for the operation (optional).
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand All @@ -110,9 +110,9 @@ tf.ones([2, 3], int32) ==> [[1, 1, 1], [1, 1, 1]]
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>shape</b>: Either a list of integers, or a 1-D `Tensor` of type `int32`.
* <b>dtype</b>: The type of an element in the resulting `Tensor`.
* <b>name</b>: A name for the operation (optional).
* <b>`shape`</b>: Either a list of integers, or a 1-D `Tensor` of type `int32`.
* <b>`dtype`</b>: The type of an element in the resulting `Tensor`.
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand All @@ -139,11 +139,11 @@ tf.ones_like(tensor) ==> [[1, 1, 1], [1, 1, 1]]
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>tensor</b>: A `Tensor`.
* <b>dtype</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
* <b>`tensor`</b>: A `Tensor`.
* <b>`dtype`</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
`int8`, `int16`, `int32`, `int64`, `uint8`, or `complex64`.

* <b>name</b>: A name for the operation (optional).
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand Down Expand Up @@ -171,10 +171,10 @@ fill(dims, 9) ==> [[9, 9, 9]
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>dims</b>: A `Tensor` of type `int32`.
* <b>`dims`</b>: A `Tensor` of type `int32`.
1-D. Represents the shape of the output tensor.
* <b>value</b>: A `Tensor`. 0-D (scalar). Value to fill the returned tensor.
* <b>name</b>: A name for the operation (optional).
* <b>`value`</b>: A `Tensor`. 0-D (scalar). Value to fill the returned tensor.
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand Down Expand Up @@ -220,16 +220,16 @@ Creates a constant tensor.
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>value</b>: A constant value (or list) of output type `dtype`.
* <b>`value`</b>: A constant value (or list) of output type `dtype`.


* <b>dtype</b>: The type of the elements of the resulting tensor.
* <b>`dtype`</b>: The type of the elements of the resulting tensor.


* <b>shape</b>: Optional dimensions of resulting tensor.
* <b>`shape`</b>: Optional dimensions of resulting tensor.


* <b>name</b>: Optional name for the tensor.
* <b>`name`</b>: Optional name for the tensor.

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand Down Expand Up @@ -258,12 +258,12 @@ tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0 11.0 12.0]
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>start</b>: A `Tensor`. Must be one of the following types: `float32`, `float64`.
* <b>`start`</b>: A `Tensor`. Must be one of the following types: `float32`, `float64`.
First entry in the range.
* <b>stop</b>: A `Tensor`. Must have the same type as `start`.
* <b>`stop`</b>: A `Tensor`. Must have the same type as `start`.
Last entry in the range.
* <b>num</b>: A `Tensor` of type `int32`. Number of values to generate.
* <b>name</b>: A name for the operation (optional).
* <b>`num`</b>: A `Tensor` of type `int32`. Number of values to generate.
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand Down Expand Up @@ -292,12 +292,12 @@ tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>start</b>: A 0-D (scalar) of type `int32`. First entry in sequence.
* <b>limit</b>: A 0-D (scalar) of type `int32`. Upper limit of sequence,
* <b>`start`</b>: A 0-D (scalar) of type `int32`. First entry in sequence.
* <b>`limit`</b>: A 0-D (scalar) of type `int32`. Upper limit of sequence,
exclusive.
* <b>delta</b>: A 0-D `Tensor` (scalar) of type `int32`. Optional. Default is 1.
* <b>`delta`</b>: A 0-D `Tensor` (scalar) of type `int32`. Optional. Default is 1.
Number that increments `start`.
* <b>name</b>: A name for the operation (optional).
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand Down Expand Up @@ -368,17 +368,17 @@ Outputs random values from a normal distribution.
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>shape</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
* <b>mean</b>: A 0-D Tensor or Python value of type `dtype`. The mean of the normal
* <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
* <b>`mean`</b>: A 0-D Tensor or Python value of type `dtype`. The mean of the normal
distribution.
* <b>stddev</b>: A 0-D Tensor or Python value of type `dtype`. The standard deviation
* <b>`stddev`</b>: A 0-D Tensor or Python value of type `dtype`. The standard deviation
of the normal distribution.
* <b>dtype</b>: The type of the output.
* <b>seed</b>: A Python integer. Used to create a random seed for the distribution.
* <b>`dtype`</b>: The type of the output.
* <b>`seed`</b>: A Python integer. Used to create a random seed for the distribution.
See
[`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
for behavior.
* <b>name</b>: A name for the operation (optional).
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand All @@ -398,17 +398,17 @@ deviations from the mean are dropped and re-picked.
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>shape</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
* <b>mean</b>: A 0-D Tensor or Python value of type `dtype`. The mean of the
* <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
* <b>`mean`</b>: A 0-D Tensor or Python value of type `dtype`. The mean of the
truncated normal distribution.
* <b>stddev</b>: A 0-D Tensor or Python value of type `dtype`. The standard deviation
* <b>`stddev`</b>: A 0-D Tensor or Python value of type `dtype`. The standard deviation
of the truncated normal distribution.
* <b>dtype</b>: The type of the output.
* <b>seed</b>: A Python integer. Used to create a random seed for the distribution.
* <b>`dtype`</b>: The type of the output.
* <b>`seed`</b>: A Python integer. Used to create a random seed for the distribution.
See
[`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
for behavior.
* <b>name</b>: A name for the operation (optional).
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand All @@ -428,17 +428,17 @@ the upper bound `maxval` is excluded.
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>shape</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
* <b>minval</b>: A 0-D Tensor or Python value of type `dtype`. The lower bound on the
* <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
* <b>`minval`</b>: A 0-D Tensor or Python value of type `dtype`. The lower bound on the
range of random values to generate.
* <b>maxval</b>: A 0-D Tensor or Python value of type `dtype`. The upper bound on
* <b>`maxval`</b>: A 0-D Tensor or Python value of type `dtype`. The upper bound on
the range of random values to generate.
* <b>dtype</b>: The type of the output.
* <b>seed</b>: A Python integer. Used to create a random seed for the distribution.
* <b>`dtype`</b>: The type of the output.
* <b>`seed`</b>: A Python integer. Used to create a random seed for the distribution.
See
[`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
for behavior.
* <b>name</b>: A name for the operation (optional).
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand All @@ -464,12 +464,12 @@ to one and only one `output[i]`. For example, a mapping that might occur for a
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>value</b>: A Tensor to be shuffled.
* <b>seed</b>: A Python integer. Used to create a random seed for the distribution.
* <b>`value`</b>: A Tensor to be shuffled.
* <b>`seed`</b>: A Python integer. Used to create a random seed for the distribution.
See
[`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed)
for behavior.
* <b>name</b>: A name for the operation (optional).
* <b>`name`</b>: A name for the operation (optional).

##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>

Expand Down Expand Up @@ -575,6 +575,6 @@ with tf.Session() as sess2:
##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>


* <b>seed</b>: integer.
* <b>`seed`</b>: integer.


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