SpaceToBatch for 4-D tensors of type T.

tf.nn.space_to_batch( input, paddings, block_size=None, name=None, block_shape=None )

This is a legacy version of the more general SpaceToBatchND.

Zero-pads and then rearranges (permutes) blocks of spatial data into batch. More specifically, this op outputs a copy of the input tensor where values from the `height`

and `width`

dimensions are moved to the `batch`

dimension. After the zero-padding, both `height`

and `width`

of the input must be divisible by the block size.

Args | |
---|---|

`input` | A `Tensor` . 4-D with shape `[batch, height, width, depth]` . |

`paddings` | A `Tensor` . Must be one of the following types: `int32` , `int64` . 2-D tensor of non-negative integers with shape `[2, 2]` . It specifies the padding of the input with zeros across the spatial dimensions as follows: paddings = [[pad_top, pad_bottom], [pad_left, pad_right]] The effective spatial dimensions of the zero-padded input tensor will be: height_pad = pad_top + height + pad_bottom width_pad = pad_left + width + pad_right The attr - Non-overlapping blocks of size
`block_size x block size` in the height and width dimensions are rearranged into the batch dimension at each location. - The batch of the output tensor is
`batch * block_size * block_size` . - Both height_pad and width_pad must be divisible by block_size.
The shape of the output will be: [batch Some examples: (1) For the following input of shape x = [[[[1], [2]], [[3], [4]]]] The output tensor has shape [[[[1]]], [[[2]]], [[[3]]], [[[4]]]] (2) For the following input of shape x = [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]] The output tensor has shape [[[[1, 2, 3]]], [[[4, 5, 6]]], [[[7, 8, 9]]], [[[10, 11, 12]]]] (3) For the following input of shape x = [[[[1], [2], [3], [4]], [[5], [6], [7], [8]], [[9], [10], [11], [12]], [[13], [14], [15], [16]]]] The output tensor has shape x = [[[[1], [3]], [[9], [11]]], [[[2], [4]], [[10], [12]]], [[[5], [7]], [[13], [15]]], [[[6], [8]], [[14], [16]]]] (4) For the following input of shape x = [[[[1], [2], [3], [4]], [[5], [6], [7], [8]]], [[[9], [10], [11], [12]], [[13], [14], [15], [16]]]] The output tensor has shape x = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]], [[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]] Among others, this operation is useful for reducing atrous convolution into regular convolution. |

`block_size` | An `int` that is `>= 2` . |

`name` | A name for the operation (optional). |

Returns | |
---|---|

A `Tensor` . Has the same type as `input` . |

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/nn/space_to_batch