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TensorFlow: Upstream changes to git.
Changes: - Lot of updates to docs. Base CL: 107357203
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‎tensorflow/g3doc/api_docs/python/array_ops.md

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‎tensorflow/g3doc/api_docs/python/client.md

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@@ -110,11 +110,11 @@ the session constructor.
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##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>
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* <b>target</b>: (Optional.) The execution engine to connect to.
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* <b>`target`</b>: (Optional.) The execution engine to connect to.
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Defaults to using an in-process engine. At present, no value
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other than the empty string is supported.
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* <b>graph</b>: (Optional.) The `Graph` to be launched (described above).
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* <b>config</b>: (Optional.) A [`ConfigProto`](https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/config.proto)
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* <b>`graph`</b>: (Optional.) The `Graph` to be launched (described above).
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* <b>`config`</b>: (Optional.) A [`ConfigProto`](https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/config.proto)
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protocol buffer with configuration options for the session.
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##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>
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* <b>fetches</b>: A single graph element, or a list of graph elements
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* <b>`fetches`</b>: A single graph element, or a list of graph elements
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(described above).
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* <b>feed_dict</b>: A dictionary that maps graph elements to values
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* <b>`feed_dict`</b>: A dictionary that maps graph elements to values
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(described above).
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##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>
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##### Raises: <a class="md-anchor" id="AUTOGENERATED-raises-"></a>
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* <b>RuntimeError</b>: If this `Session` is in an invalid state (e.g. has been
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* <b>`RuntimeError`</b>: If this `Session` is in an invalid state (e.g. has been
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closed).
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* <b>TypeError</b>: If `fetches` or `feed_dict` keys are of an inappropriate type.
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* <b>ValueError</b>: If `fetches` or `feed_dict` keys are invalid or refer to a
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* <b>`TypeError`</b>: If `fetches` or `feed_dict` keys are of an inappropriate type.
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* <b>`ValueError`</b>: If `fetches` or `feed_dict` keys are invalid or refer to a
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`Tensor` that doesn't exist.
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##### Raises: <a class="md-anchor" id="AUTOGENERATED-raises-"></a>
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* <b>RuntimeError</b>: If an error occurs while closing the session.
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* <b>`RuntimeError`</b>: If an error occurs while closing the session.
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##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>
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* <b>target</b>: (Optional.) The execution engine to connect to.
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* <b>`target`</b>: (Optional.) The execution engine to connect to.
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Defaults to using an in-process engine. At present, no value
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other than the empty string is supported.
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* <b>graph</b>: (Optional.) The `Graph` to be launched (described above).
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* <b>`graph`</b>: (Optional.) The `Graph` to be launched (described above).
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- - -
@@ -398,10 +398,10 @@ Creates a new OpError indicating that a particular op failed.
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##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>
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* <b>node_def</b>: The graph_pb2.NodeDef proto representing the op that failed.
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* <b>op</b>: The ops.Operation that failed, if known; otherwise None.
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* <b>message</b>: The message string describing the failure.
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* <b>error_code</b>: The error_codes_pb2.Code describing the error.
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* <b>`node_def`</b>: The graph_pb2.NodeDef proto representing the op that failed.
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* <b>`op`</b>: The ops.Operation that failed, if known; otherwise None.
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* <b>`message`</b>: The message string describing the failure.
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* <b>`error_code`</b>: The error_codes_pb2.Code describing the error.
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‎tensorflow/g3doc/api_docs/python/constant_op.md

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@@ -51,9 +51,9 @@ tf.zeros([3, 4], int32) ==> [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]
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##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>
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* <b>shape</b>: Either a list of integers, or a 1-D `Tensor` of type `int32`.
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* <b>dtype</b>: The type of an element in the resulting `Tensor`.
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* <b>name</b>: A name for the operation (optional).
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* <b>`shape`</b>: Either a list of integers, or a 1-D `Tensor` of type `int32`.
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* <b>`dtype`</b>: The type of an element in the resulting `Tensor`.
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* <b>`name`</b>: A name for the operation (optional).
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##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>
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@@ -80,11 +80,11 @@ tf.zeros_like(tensor) ==> [[0, 0, 0], [0, 0, 0]]
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##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>
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* <b>tensor</b>: A `Tensor`.
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* <b>dtype</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
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* <b>`tensor`</b>: A `Tensor`.
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* <b>`dtype`</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
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`int8`, `int16`, `int32`, `int64`, `uint8`, or `complex64`.
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* <b>name</b>: A name for the operation (optional).
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* <b>`name`</b>: A name for the operation (optional).
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##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>
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* <b>shape</b>: Either a list of integers, or a 1-D `Tensor` of type `int32`.
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* <b>dtype</b>: The type of an element in the resulting `Tensor`.
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* <b>name</b>: A name for the operation (optional).
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* <b>`shape`</b>: Either a list of integers, or a 1-D `Tensor` of type `int32`.
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* <b>`dtype`</b>: The type of an element in the resulting `Tensor`.
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* <b>`name`</b>: A name for the operation (optional).
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##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>
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##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>
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* <b>tensor</b>: A `Tensor`.
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* <b>dtype</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
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* <b>`tensor`</b>: A `Tensor`.
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* <b>`dtype`</b>: A type for the returned `Tensor`. Must be `float32`, `float64`,
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`int8`, `int16`, `int32`, `int64`, `uint8`, or `complex64`.
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* <b>name</b>: A name for the operation (optional).
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* <b>`name`</b>: A name for the operation (optional).
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##### Returns: <a class="md-anchor" id="AUTOGENERATED-returns-"></a>
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* <b>dims</b>: A `Tensor` of type `int32`.
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* <b>`dims`</b>: A `Tensor` of type `int32`.
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1-D. Represents the shape of the output tensor.
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* <b>value</b>: A `Tensor`. 0-D (scalar). Value to fill the returned tensor.
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* <b>name</b>: A name for the operation (optional).
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* <b>`value`</b>: A `Tensor`. 0-D (scalar). Value to fill the returned tensor.
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* <b>`name`</b>: A name for the operation (optional).
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* <b>value</b>: A constant value (or list) of output type `dtype`.
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* <b>`value`</b>: A constant value (or list) of output type `dtype`.
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* <b>dtype</b>: The type of the elements of the resulting tensor.
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* <b>`dtype`</b>: The type of the elements of the resulting tensor.
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* <b>shape</b>: Optional dimensions of resulting tensor.
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* <b>`shape`</b>: Optional dimensions of resulting tensor.
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* <b>name</b>: Optional name for the tensor.
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* <b>`name`</b>: Optional name for the tensor.
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##### Args: <a class="md-anchor" id="AUTOGENERATED-args-"></a>
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* <b>start</b>: A `Tensor`. Must be one of the following types: `float32`, `float64`.
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* <b>`start`</b>: A `Tensor`. Must be one of the following types: `float32`, `float64`.
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First entry in the range.
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* <b>stop</b>: A `Tensor`. Must have the same type as `start`.
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* <b>`stop`</b>: A `Tensor`. Must have the same type as `start`.
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* <b>num</b>: A `Tensor` of type `int32`. Number of values to generate.
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* <b>name</b>: A name for the operation (optional).
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* <b>`num`</b>: A `Tensor` of type `int32`. Number of values to generate.
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* <b>`name`</b>: A name for the operation (optional).
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* <b>start</b>: A 0-D (scalar) of type `int32`. First entry in sequence.
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* <b>limit</b>: A 0-D (scalar) of type `int32`. Upper limit of sequence,
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* <b>`start`</b>: A 0-D (scalar) of type `int32`. First entry in sequence.
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* <b>`limit`</b>: A 0-D (scalar) of type `int32`. Upper limit of sequence,
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* <b>delta</b>: A 0-D `Tensor` (scalar) of type `int32`. Optional. Default is 1.
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* <b>`delta`</b>: A 0-D `Tensor` (scalar) of type `int32`. Optional. Default is 1.
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* <b>name</b>: A name for the operation (optional).
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* <b>`name`</b>: A name for the operation (optional).
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* <b>shape</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
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* <b>mean</b>: A 0-D Tensor or Python value of type `dtype`. The mean of the normal
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* <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
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* <b>`mean`</b>: A 0-D Tensor or Python value of type `dtype`. The mean of the normal
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* <b>stddev</b>: A 0-D Tensor or Python value of type `dtype`. The standard deviation
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* <b>`stddev`</b>: A 0-D Tensor or Python value of type `dtype`. The standard deviation
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* <b>dtype</b>: The type of the output.
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* <b>seed</b>: A Python integer. Used to create a random seed for the distribution.
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* <b>`dtype`</b>: The type of the output.
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* <b>`seed`</b>: A Python integer. Used to create a random seed for the distribution.
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* <b>name</b>: A name for the operation (optional).
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* <b>`name`</b>: A name for the operation (optional).
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* <b>shape</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
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* <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
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* <b>`mean`</b>: A 0-D Tensor or Python value of type `dtype`. The mean of the
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* <b>stddev</b>: A 0-D Tensor or Python value of type `dtype`. The standard deviation
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* <b>`stddev`</b>: A 0-D Tensor or Python value of type `dtype`. The standard deviation
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* <b>dtype</b>: The type of the output.
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* <b>seed</b>: A Python integer. Used to create a random seed for the distribution.
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* <b>`dtype`</b>: The type of the output.
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* <b>`seed`</b>: A Python integer. Used to create a random seed for the distribution.
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* <b>name</b>: A name for the operation (optional).
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* <b>`name`</b>: A name for the operation (optional).
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* <b>`shape`</b>: A 1-D integer Tensor or Python array. The shape of the output tensor.
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* <b>`minval`</b>: A 0-D Tensor or Python value of type `dtype`. The lower bound on the
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* <b>`maxval`</b>: A 0-D Tensor or Python value of type `dtype`. The upper bound on
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* <b>`dtype`</b>: The type of the output.
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* <b>`seed`</b>: A Python integer. Used to create a random seed for the distribution.
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* <b>`name`</b>: A name for the operation (optional).
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* <b>`value`</b>: A Tensor to be shuffled.
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* <b>`seed`</b>: A Python integer. Used to create a random seed for the distribution.
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* <b>`seed`</b>: integer.
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