tf.batch_to_space( input, crops, block_size, name=None )
Defined in tensorflow/python/ops/array_ops.py
.
See the guide: Tensor Transformations > Slicing and Joining
BatchToSpace for 4-D tensors of type T.
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.
input
: A Tensor
. 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
: A Tensor
. Must be one of the following types: int32
, int64
. 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]]
block_size
: An int
that is >= 2
.name
: A name for the operation (optional).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/api_docs/python/tf/batch_to_space