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Update generated Python Op docs.

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A. Unique TensorFlower 2017-01-11 12:51:50 -08:00 committed by TensorFlower Gardener
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45
tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.TensorArray.md
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@ -64,25 +64,6 @@ must all match.
The in the `TensorArray` selected by `indices`, packed into one tensor. The in the `TensorArray` selected by `indices`, packed into one tensor.
- - -
#### `tf.TensorArray.pack(*args, **kwargs)` {#TensorArray.pack}
Return the values in the TensorArray as a stacked `Tensor`.
All of the values must have been written and their shapes must all match.
If input shapes have rank-`R`, then output shape will have rank-`(R+1)`.
##### Args:
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
All the tensors in the TensorArray stacked into one tensor.
- - - - - -
#### `tf.TensorArray.stack(name=None)` {#TensorArray.stack} #### `tf.TensorArray.stack(name=None)` {#TensorArray.stack}
@ -171,32 +152,6 @@ Scatter the values of a `Tensor` in specific indices of a `TensorArray`.
* <b>`ValueError`</b>: if the shape inference fails. * <b>`ValueError`</b>: if the shape inference fails.
- - -
#### `tf.TensorArray.unpack(*args, **kwargs)` {#TensorArray.unpack}
Unstack the values of a `Tensor` in the TensorArray.
If input value shapes have rank-`R`, then the output TensorArray will
contain elements whose shapes are rank-`(R-1)`.
##### Args:
* <b>`value`</b>: (N+1)-D. Tensor of type `dtype`. The Tensor to unstack.
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
A new TensorArray object with flow that ensures the unstack occurs.
Use this object all for subsequent operations.
##### Raises:
* <b>`ValueError`</b>: if the shape inference fails.
- - - - - -
#### `tf.TensorArray.unstack(value, name=None)` {#TensorArray.unstack} #### `tf.TensorArray.unstack(value, name=None)` {#TensorArray.unstack}

45
tensorflow/g3doc/api_docs/python/tensor_array_ops.md
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@ -81,25 +81,6 @@ must all match.
The in the `TensorArray` selected by `indices`, packed into one tensor. The in the `TensorArray` selected by `indices`, packed into one tensor.
- - -
#### `tf.TensorArray.pack(*args, **kwargs)` {#TensorArray.pack}
Return the values in the TensorArray as a stacked `Tensor`.
All of the values must have been written and their shapes must all match.
If input shapes have rank-`R`, then output shape will have rank-`(R+1)`.
##### Args:
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
All the tensors in the TensorArray stacked into one tensor.
- - - - - -
#### `tf.TensorArray.stack(name=None)` {#TensorArray.stack} #### `tf.TensorArray.stack(name=None)` {#TensorArray.stack}
@ -188,32 +169,6 @@ Scatter the values of a `Tensor` in specific indices of a `TensorArray`.
* <b>`ValueError`</b>: if the shape inference fails. * <b>`ValueError`</b>: if the shape inference fails.
- - -
#### `tf.TensorArray.unpack(*args, **kwargs)` {#TensorArray.unpack}
Unstack the values of a `Tensor` in the TensorArray.
If input value shapes have rank-`R`, then the output TensorArray will
contain elements whose shapes are rank-`(R-1)`.
##### Args:
* <b>`value`</b>: (N+1)-D. Tensor of type `dtype`. The Tensor to unstack.
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
A new TensorArray object with flow that ensures the unstack occurs.
Use this object all for subsequent operations.
##### Raises:
* <b>`ValueError`</b>: if the shape inference fails.
- - - - - -
#### `tf.TensorArray.unstack(value, name=None)` {#TensorArray.unstack} #### `tf.TensorArray.unstack(value, name=None)` {#TensorArray.unstack}