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Update generated Python Op docs.
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Change: 143924077
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tensorflower-gardener committed Jan 9, 2017
1 parent efd40e5 commit c5798b3
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2 changes: 1 addition & 1 deletion tensorflow/g3doc/api_docs/python/array_ops.md
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Expand Up @@ -2209,7 +2209,7 @@ The attr `block_size` indicates the input block size and how the data is moved.

* Chunks of data of size `block_size * block_size` from depth are rearranged
into non-overlapping blocks of size `block_size x block_size`
* The width the output tensor is `input_width * block_size`, whereas the
* The width the output tensor is `input_depth * block_size`, whereas the
height is `input_height * block_size`.
* The depth of the input tensor must be divisible by
`block_size * block_size`.
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2 changes: 1 addition & 1 deletion tensorflow/g3doc/api_docs/python/contrib.rnn.md
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Expand Up @@ -31,7 +31,7 @@ LSTM (Long Short Term Memory) or GRU (Gated Recurrent Unit), and a number
of operators that allow add dropouts, projections, or embeddings for inputs.
Constructing multi-layer cells is supported by the class `MultiRNNCell`,
or by calling the `rnn` ops several times. Every `RNNCell` must have the
properties below and and implement `__call__` with the following signature.
properties below and implement `__call__` with the following signature.
- - -

#### `tf.contrib.rnn.RNNCell.__call__(inputs, state, scope=None)` {#RNNCell.__call__}
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Expand Up @@ -10,7 +10,7 @@ The attr `block_size` indicates the input block size and how the data is moved.

* Chunks of data of size `block_size * block_size` from depth are rearranged
into non-overlapping blocks of size `block_size x block_size`
* The width the output tensor is `input_width * block_size`, whereas the
* The width the output tensor is `input_depth * block_size`, whereas the
height is `input_height * block_size`.
* The depth of the input tensor must be divisible by
`block_size * block_size`.
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@@ -1,252 +1,8 @@

- - -

#### `tf.summary.TaggedRunMetadata.ByteSize()` {#TaggedRunMetadata.ByteSize}




- - -

#### `tf.summary.TaggedRunMetadata.Clear()` {#TaggedRunMetadata.Clear}




- - -

#### `tf.summary.TaggedRunMetadata.ClearExtension(extension_handle)` {#TaggedRunMetadata.ClearExtension}




- - -

#### `tf.summary.TaggedRunMetadata.ClearField(field_name)` {#TaggedRunMetadata.ClearField}




- - -

#### `tf.summary.TaggedRunMetadata.CopyFrom(other_msg)` {#TaggedRunMetadata.CopyFrom}

Copies the content of the specified message into the current message.

The method clears the current message and then merges the specified
message using MergeFrom.

##### Args:


* <b>`other_msg`</b>: Message to copy into the current one.


- - -

#### `tf.summary.TaggedRunMetadata.DiscardUnknownFields()` {#TaggedRunMetadata.DiscardUnknownFields}




- - -

#### `tf.summary.TaggedRunMetadata.FindInitializationErrors()` {#TaggedRunMetadata.FindInitializationErrors}

Finds required fields which are not initialized.

##### Returns:

A list of strings. Each string is a path to an uninitialized field from
the top-level message, e.g. "foo.bar[5].baz".


- - -

#### `tf.summary.TaggedRunMetadata.FromString(s)` {#TaggedRunMetadata.FromString}




- - -

#### `tf.summary.TaggedRunMetadata.HasExtension(extension_handle)` {#TaggedRunMetadata.HasExtension}




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#### `tf.summary.TaggedRunMetadata.HasField(field_name)` {#TaggedRunMetadata.HasField}




- - -

#### `tf.summary.TaggedRunMetadata.IsInitialized(errors=None)` {#TaggedRunMetadata.IsInitialized}

Checks if all required fields of a message are set.

##### Args:


* <b>`errors`</b>: A list which, if provided, will be populated with the field
paths of all missing required fields.

##### Returns:

True iff the specified message has all required fields set.


- - -

#### `tf.summary.TaggedRunMetadata.ListFields()` {#TaggedRunMetadata.ListFields}




- - -

#### `tf.summary.TaggedRunMetadata.MergeFrom(msg)` {#TaggedRunMetadata.MergeFrom}




- - -

#### `tf.summary.TaggedRunMetadata.MergeFromString(serialized)` {#TaggedRunMetadata.MergeFromString}




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#### `tf.summary.TaggedRunMetadata.ParseFromString(serialized)` {#TaggedRunMetadata.ParseFromString}

Parse serialized protocol buffer data into this message.

Like MergeFromString(), except we clear the object first and
do not return the value that MergeFromString returns.


- - -

#### `tf.summary.TaggedRunMetadata.RegisterExtension(extension_handle)` {#TaggedRunMetadata.RegisterExtension}




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#### `tf.summary.TaggedRunMetadata.SerializePartialToString()` {#TaggedRunMetadata.SerializePartialToString}




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#### `tf.summary.TaggedRunMetadata.SerializeToString()` {#TaggedRunMetadata.SerializeToString}




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#### `tf.summary.TaggedRunMetadata.SetInParent()` {#TaggedRunMetadata.SetInParent}

Sets the _cached_byte_size_dirty bit to true,
and propagates this to our listener iff this was a state change.


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#### `tf.summary.TaggedRunMetadata.WhichOneof(oneof_name)` {#TaggedRunMetadata.WhichOneof}

Returns the name of the currently set field inside a oneof, or None.


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#### `tf.summary.TaggedRunMetadata.__deepcopy__(memo=None)` {#TaggedRunMetadata.__deepcopy__}




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#### `tf.summary.TaggedRunMetadata.__eq__(other)` {#TaggedRunMetadata.__eq__}




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#### `tf.summary.TaggedRunMetadata.__getstate__()` {#TaggedRunMetadata.__getstate__}

Support the pickle protocol.


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#### `tf.summary.TaggedRunMetadata.__hash__()` {#TaggedRunMetadata.__hash__}




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#### `tf.summary.TaggedRunMetadata.__init__(**kwargs)` {#TaggedRunMetadata.__init__}




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#### `tf.summary.TaggedRunMetadata.__ne__(other_msg)` {#TaggedRunMetadata.__ne__}




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#### `tf.summary.TaggedRunMetadata.__repr__()` {#TaggedRunMetadata.__repr__}




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#### `tf.summary.TaggedRunMetadata.__setstate__(state)` {#TaggedRunMetadata.__setstate__}

Support the pickle protocol.


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#### `tf.summary.TaggedRunMetadata.__str__()` {#TaggedRunMetadata.__str__}




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#### `tf.summary.TaggedRunMetadata.__unicode__()` {#TaggedRunMetadata.__unicode__}




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#### `tf.summary.TaggedRunMetadata.run_metadata` {#TaggedRunMetadata.run_metadata}

Magic attribute generated for "run_metadata" proto field.


- - -

#### `tf.summary.TaggedRunMetadata.tag` {#TaggedRunMetadata.tag}

Magic attribute generated for "tag" proto field.


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