# tensorflow::ops::BatchToSpaceND

`#include <array_ops.h>`

[BatchToSpace](https://www.tensorflow.org/versions/r2.0/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.

Arguments:

- scope: A [Scope](https://www.tensorflow.org/versions/r2.0/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/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output`: The output tensor.

<br />

| ### Constructors and Destructors ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/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/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input input, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input block_shape, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input crops)` ||

| ### Public attributes ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/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/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation` |
| `https://www.tensorflow.org/versions/r2.0/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/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output` |

| ### Public functions ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/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/r2.0/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/r2.0/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 
```