tensorflow::ops::BatchToSpace

#include <array_ops.h>

BatchToSpace for 4-D 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: 4-D 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 by block_size * block_size.
  • crops: 2-D tensor of non-negative 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: 4-D 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]], [[9], [11]]], [[[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