# tensorflow::ops::BatchToSpaceND Class Reference

# tensorflow::
ops::
BatchToSpaceND

`
#include <array_ops.h>
`


[BatchToSpace](https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/batch-to-space#classtensorflow_1_1ops_1_1_batch_to_space)
for N-D 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.


Args:

- scope: A [Scope](https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object
- input: N-D with shape `
  input_shape = [batch] + spatial_shape + remaining_shape
  ` , where spatial_shape has M dimensions.
- block_shape: 1-D with shape `
  [M]
  ` , all values must be \>= 1.
- crops: 2-D with shape `
  [M, 2]
  ` , all values must be \>= 0. `
  crops[i] = [crop_start, crop_end]
  ` specifies the amount to crop from input dimension `
  i + 1
  ` , which corresponds to spatial dimension `
  i
  ` . It is required that `
  crop_start[i] + crop_end[i] <= block_shape[i] * input_shape[i + 1]
  ` .

<br />


This operation is equivalent to the following steps:


1. Reshape `
   input
   ` to `
   reshaped
   ` of shape: \[block_shape\[0\], ..., block_shape\[M-1\], batch / prod(block_shape), input_shape\[1\], ..., input_shape\[N-1\]\]
2. Permute dimensions of `
   reshaped
   ` to produce `
   permuted
   ` of shape \[batch / prod(block_shape),input_shape\[1\], block_shape\[0\], ..., input_shape\[M\], block_shape\[M-1\],input_shape\[M+1\], ..., input_shape\[N-1\]\]
3. Reshape `
   permuted
   ` to produce `
   reshaped_permuted
   ` of shape \[batch / prod(block_shape),input_shape\[1\] \* block_shape\[0\], ..., input_shape\[M\] \* block_shape\[M-1\],input_shape\[M+1\], ..., input_shape\[N-1\]\]
4. Crop the start and end of dimensions `
   [1, ..., M]
   ` of `
   reshaped_permuted
   ` according to `
   crops
   ` 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\[M-1\] - crops\[M-1,0\] - crops\[M-1,1\],input_shape\[M+1\], ..., input_shape\[N-1\]\]

<br />


Some examples:


(1) For the following input of shape
`
[4, 1, 1, 1]
`
,
`
block_shape = [2, 2]
`
, and
`
crops = [[0, 0], [0, 0]]
`
:


```
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
```

<br />


The output tensor has shape
`
[1, 2, 2, 1]
`
and value:


```
x = [[[[1], [2]], [[3], [4]]]]
```

<br />


(2) For the following input of shape
`
[4, 1, 1, 3]
`
,
`
block_shape = [2, 2]
`
, and
`
crops = [[0, 0], [0, 0]]
`
:


```
[[[[1, 2, 3]]], [[[4, 5, 6]]], [[[7, 8, 9]]], [[[10, 11, 12]]]]
```

<br />


The output tensor has shape
`
[1, 2, 2, 3]
`
and value:


```
x = [[[[1, 2, 3], [4, 5, 6]],
      [[7, 8, 9], [10, 11, 12]]]]
```

<br />


(3) For the following input of shape
`
[4, 2, 2, 1]
`
,
`
block_shape = [2, 2]
`
, and
`
crops = [[0, 0], [0, 0]]
`
:


```
x = [[[[1], [3]], [[9], [11]]],
     [[[2], [4]], [[10], [12]]],
     [[[5], [7]], [[13], [15]]],
     [[[6], [8]], [[14], [16]]]]
```

<br />


The output tensor has shape
`
[1, 4, 4, 1]
`
and value:


```
x = [[[[1],   [2],  [3],  [4]],
     [[5],   [6],  [7],  [8]],
     [[9],  [10], [11],  [12]],
     [[13], [14], [15],  [16]]]]
```

<br />


(4) For the following input of shape
`
[8, 1, 3, 1]
`
,
`
block_shape = [2, 2]
`
, and
`
crops = [[0, 0], [2, 0]]
`
:


```
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]]]]
```

<br />


The output tensor has shape
`
[2, 2, 4, 1]
`
and value:


```
x = [[[[1],   [2],  [3],  [4]],
      [[5],   [6],  [7],  [8]]],
     [[[9],  [10], [11],  [12]],
      [[13], [14], [15],  [16]]]]
```

<br />


Returns:

- `
  https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output
  ` : The output tensor.

<br />

| ### Constructors and Destructors ||
|---|---|
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/batch-to-space-n-d#classtensorflow_1_1ops_1_1_batch_to_space_n_d_1ae9fc7cf839b67ec1692eb9dbd13dab3f (const :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input input, :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input block_shape, :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input crops) ` ||

| ### Public attributes ||
|---|---|
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/batch-to-space-n-d#classtensorflow_1_1ops_1_1_batch_to_space_n_d_1a1e8d19aed27a8ba75041200ee25a7310 ` | ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation ` |
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/batch-to-space-n-d#classtensorflow_1_1ops_1_1_batch_to_space_n_d_1a2f9a5258c2d37ba9ce71c6ebfe2f754d ` | ` :: https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output ` |

| ### Public functions ||
|---|---|
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/batch-to-space-n-d#classtensorflow_1_1ops_1_1_batch_to_space_n_d_1a8c320b154abac62302b289161e5aa745 () const ` | ` ::tensorflow::Node * ` |
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/batch-to-space-n-d#classtensorflow_1_1ops_1_1_batch_to_space_n_d_1a94adde19cfddf4d1109cceff401543c8 () const ` | ` ` |
| ` https://www.tensorflow.org/versions/r2.5/api_docs/cc/class/tensorflow/ops/batch-to-space-n-d#classtensorflow_1_1ops_1_1_batch_to_space_n_d_1a17e07f190557e6565111355cc159b528 () const ` | ` ` |

## Public attributes

### operation

```
Operation operation
```

### 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 
```