tensorflow::ops::BatchToSpaceND
#include <array_ops.h>
BatchToSpace for ND tensors of type T.
Summary
This operation reshapes the "batch" dimension 0 into M + 1
dimensions of shape block_shape + [batch]
, interleaves these blocks back into the grid defined by the spatial dimensions [1, ..., M]
, to obtain a result with the same rank as the input. The spatial dimensions of this intermediate result are then optionally cropped according to crops
to produce the output. This is the reverse of SpaceToBatch. See below for a precise description.
Arguments:
 scope: A Scope object
 input: ND with shape
input_shape = [batch] + spatial_shape + remaining_shape
, where spatial_shape has M dimensions.  block_shape: 1D with shape
[M]
, all values must be >= 1.  crops: 2D with shape
[M, 2]
, all values must be >= 0.crops[i] = [crop_start, crop_end]
specifies the amount to crop from input dimensioni + 1
, which corresponds to spatial dimensioni
. It is required thatcrop_start[i] + crop_end[i] <= block_shape[i] * input_shape[i + 1]
.
This operation is equivalent to the following steps:
 Reshape
input
toreshaped
of shape: [block_shape[0], ..., block_shape[M1], batch / prod(block_shape), input_shape[1], ..., input_shape[N1]]  Permute dimensions of
reshaped
to producepermuted
of shape [batch / prod(block_shape),input_shape[1], block_shape[0], ..., input_shape[M], block_shape[M1],input_shape[M+1], ..., input_shape[N1]]  Reshape
permuted
to producereshaped_permuted
of shape [batch / prod(block_shape),input_shape[1] * block_shape[0], ..., input_shape[M] * block_shape[M1],input_shape[M+1], ..., input_shape[N1]]  Crop the start and end of dimensions
[1, ..., M]
ofreshaped_permuted
according tocrops
to produce the output of shape: [batch / prod(block_shape),input_shape[1] * block_shape[0]  crops[0,0]  crops[0,1], ..., input_shape[M] * block_shape[M1]  crops[M1,0]  crops[M1,1],input_shape[M+1], ..., input_shape[N1]]
Some examples:
(1) For the following input of shape [4, 1, 1, 1]
, block_shape = [2, 2]
, and crops = [[0, 0], [0, 0]]
:
```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]
, block_shape = [2, 2]
, and crops = [[0, 0], [0, 0]]
:
```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]
, block_shape = [2, 2]
, and crops = [[0, 0], [0, 0]]
:
```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, 3, 1]
, block_shape = [2, 2]
, and crops = [[0, 0], [2, 0]]
:
```prettyprint x = [[[[0], [1], [3]]], [[[0], [9], [11]]], [[[0], [2], [4]]], [[[0], [10], [12]]], [[[0], [5], [7]]], [[[0], [13], [15]]], [[[0], [6], [8]]], [[[0], [14], [16]]]] ```
The output tensor has shape [2, 2, 4, 1]
and value:
```prettyprint x = [[[[1], [2], [3], [4]], [[5], [6], [7], [8]]], [[[9], [10], [11], [12]], [[13], [14], [15], [16]]]] ```
Returns:
Output
: The output tensor.
Constructors and Destructors 


BatchToSpaceND(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input block_shape, ::tensorflow::Input crops)

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
BatchToSpaceND
BatchToSpaceND( const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input block_shape, ::tensorflow::Input crops )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const