Update generated Python Op docs.

Change: 147258931
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A. Unique TensorFlower 2017-02-11 16:33:26 -08:00 committed by TensorFlower Gardener
parent ff2d9e99ba
commit 0bbb224f4c
4 changed files with 8 additions and 8 deletions
tensorflow/g3doc/api_docs/python

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@ -1,6 +1,6 @@
Variable scope object to carry defaults to provide to get_variable.
Variable scope object to carry defaults to provide to `get_variable`.
Many of the arguments we need for get_variable in a variable store are most
Many of the arguments we need for `get_variable` in a variable store are most
easily handled with a context. This object is used for the defaults.
Attributes:

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@ -43,7 +43,7 @@ Some useful partitioners are available. See, e.g.,
* <b>`initializer`</b>: Initializer for the variable if one is created.
* <b>`regularizer`</b>: A (Tensor -> Tensor or None) function; the result of
applying it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
@{tf.GraphKeys.REGULARIZATION_LOSSES} and can be used for regularization.
* <b>`collections`</b>: List of graph collections keys to add the Variable to.
Defaults to `[GraphKeys.LOCAL_VARIABLES]` (see `tf.Variable`).
* <b>`caching_device`</b>: Optional device string or function describing where the

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@ -40,7 +40,7 @@ Some useful partitioners are available. See, e.g.,
* <b>`initializer`</b>: Initializer for the variable if one is created.
* <b>`regularizer`</b>: A (Tensor -> Tensor or None) function; the result of
applying it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
@{tf.GraphKeys.REGULARIZATION_LOSSES} and can be used for regularization.
* <b>`trainable`</b>: If `True` also add the variable to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see `tf.Variable`).
* <b>`collections`</b>: List of graph collections keys to add the Variable to.

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@ -1976,7 +1976,7 @@ Some useful partitioners are available. See, e.g.,
* <b>`initializer`</b>: Initializer for the variable if one is created.
* <b>`regularizer`</b>: A (Tensor -> Tensor or None) function; the result of
applying it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
@{tf.GraphKeys.REGULARIZATION_LOSSES} and can be used for regularization.
* <b>`trainable`</b>: If `True` also add the variable to the graph collection
`GraphKeys.TRAINABLE_VARIABLES` (see `tf.Variable`).
* <b>`collections`</b>: List of graph collections keys to add the Variable to.
@ -2068,7 +2068,7 @@ Some useful partitioners are available. See, e.g.,
* <b>`initializer`</b>: Initializer for the variable if one is created.
* <b>`regularizer`</b>: A (Tensor -> Tensor or None) function; the result of
applying it on a newly created variable will be added to the collection
GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
@{tf.GraphKeys.REGULARIZATION_LOSSES} and can be used for regularization.
* <b>`collections`</b>: List of graph collections keys to add the Variable to.
Defaults to `[GraphKeys.LOCAL_VARIABLES]` (see `tf.Variable`).
* <b>`caching_device`</b>: Optional device string or function describing where the
@ -2115,9 +2115,9 @@ Some useful partitioners are available. See, e.g.,
### `class tf.VariableScope` {#VariableScope}
Variable scope object to carry defaults to provide to get_variable.
Variable scope object to carry defaults to provide to `get_variable`.
Many of the arguments we need for get_variable in a variable store are most
Many of the arguments we need for `get_variable` in a variable store are most
easily handled with a context. This object is used for the defaults.
Attributes: