tensorflow::ops::BatchToSpace
#include <array_ops.h>
BatchToSpace for 4D tensors of type T.
Summary
This is a legacy version of the more general BatchToSpaceND.
Rearranges (permutes) data from batch into blocks of spatial data, followed by cropping. This is the reverse transformation of SpaceToBatch. More specifically, this op outputs a copy of the input tensor where values from the batch
dimension are moved in spatial blocks to the height
and width
dimensions, followed by cropping along the height
and width
dimensions.
Arguments:
 scope: A Scope object
 input: 4D tensor with shape
[batch*block_size*block_size, height_pad/block_size, width_pad/block_size, depth]
. Note that the batch size of the input tensor must be divisible byblock_size * block_size
.  crops: 2D tensor of nonnegative integers with shape
[2, 2]
. It specifies how many elements to crop from the intermediate result across the spatial dimensions as follows:crops = [[crop_top, crop_bottom], [crop_left, crop_right]]
Returns:
Output
: 4D with shape[batch, height, width, depth]
, where:height = height_pad  crop_top  crop_bottom width = width_pad  crop_left  crop_right
The attr block_size
must be greater than one. It indicates the block size.
Some examples:
(1) For the following input of shape [4, 1, 1, 1]
and block_size of 2:
```prettyprint [[[[1]]], [[[2]]], [[[3]]], [[[4]]]] ```
The output tensor has shape [1, 2, 2, 1]
and value:
```prettyprint x = [[[[1], [2]], [[3], [4]]]] ```
(2) For the following input of shape [4, 1, 1, 3]
and block_size of 2:
```prettyprint [[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]] ```
The output tensor has shape [1, 2, 2, 3]
and value:
```prettyprint x = [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]] ```
(3) For the following input of shape [4, 2, 2, 1]
and block_size of 2:
```prettyprint x = [[[[1], [3]], [[5], [7]]], [[[2], [4]], [[10], [12]]], [[[5], [7]], [[13], [15]]], [[[6], [8]], [[14], [16]]]] ```
The output tensor has shape [1, 4, 4, 1]
and value:
```prettyprint x = [[[1], [2], [3], [4]], [[5], [6], [7], [8]], [[9], [10], [11], [12]], [[13], [14], [15], [16]]] ```
(4) For the following input of shape [8, 1, 2, 1]
and block_size of 2:
```prettyprint x = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]], [[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]] ```
The output tensor has shape [2, 2, 4, 1]
and value:
```prettyprint x = [[[[1], [3]], [[5], [7]]], [[[2], [4]], [[10], [12]]], [[[5], [7]], [[13], [15]]], [[[6], [8]], [[14], [16]]]] ```
Constructors and Destructors 


BatchToSpace(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input crops, int64 block_size)

Public attributes 


output

Public functions 


node() const

::tensorflow::Node *

operator::tensorflow::Input() const


operator::tensorflow::Output() const


Public attributes
output
::tensorflow::Output output
Public functions
BatchToSpace
BatchToSpace( const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input crops, int64 block_size )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const