View source on GitHub 
BatchToSpace for ND tensors of type T.
tf.batch_to_space(
input, block_shape, crops, name=None
)
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 tf.space_to_batch
).
Examples:
For the following input of shape
[4, 1, 1, 1]
,block_shape = [2, 2]
, andcrops = [[0, 0], [0, 0]]
:[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
The output tensor has shape
[1, 2, 2, 1]
and value:x = [[[[1], [2]], [[3], [4]]]]
For the following input of shape
[4, 1, 1, 3]
,block_shape = [2, 2]
, andcrops = [[0, 0], [0, 0]]
:[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
The output tensor has shape
[1, 2, 2, 3]
and value:x = [[[[1, 2, 3], [4, 5, 6 ]], [[7, 8, 9], [10, 11, 12]]]]
For the following input of shape
[4, 2, 2, 1]
,block_shape = [2, 2]
, andcrops = [[0, 0], [0, 0]]
: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:x = [[[1], [2], [ 3], [ 4]], [[5], [6], [ 7], [ 8]], [[9], [10], [11], [12]], [[13], [14], [15], [16]]]
For the following input of shape
[8, 1, 3, 1]
,block_shape = [2, 2]
, andcrops = [[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]]]]
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]]]]
Returns  

A Tensor . Has the same type as input .
