SpaceToBatch

public final class SpaceToBatch

SpaceToBatch for 4-D tensors of type T.

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.

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of the tensor.
static <T extends TType> SpaceToBatch<T>
create(Scope scope, Operand<T> input, Operand<? extends TNumber> paddings, Long blockSize)
Factory method to create a class wrapping a new SpaceToBatch operation.
Output<T>
output()

Inherited Methods

org.tensorflow.op.RawOp
final boolean
equals(Object obj)
final int
hashCode()
Operation
op()
Return this unit of computation as a single Operation.
final String
toString()
boolean
equals(Object arg0)
final Class<?>
getClass()
int
hashCode()
final void
notify()
final void
notifyAll()
String
toString()
final void
wait(long arg0, int arg1)
final void
wait(long arg0)
final void
wait()
org.tensorflow.op.Op
abstract ExecutionEnvironment
env()
Return the execution environment this op was created in.
abstract Operation
op()
Return this unit of computation as a single Operation.
org.tensorflow.Operand
abstract Output<T>
asOutput()
Returns the symbolic handle of the tensor.
abstract T
asTensor()
Returns the tensor at this operand.
abstract Shape
shape()
Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<T>
type()
Returns the tensor type of this operand
org.tensorflow.ndarray.Shaped
abstract int
rank()
abstract Shape
shape()
abstract long
size()
Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "SpaceToBatch"

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static SpaceToBatch<T> create (Scope scope, Operand<T> input, Operand<? extends TNumber> paddings, Long blockSize)

Factory method to create a class wrapping a new SpaceToBatch operation.

Parameters
scope current scope
input 4-D with shape `[batch, height, width, depth]`.
paddings 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 `block_size` must be greater than one. It indicates the block size.

* 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:

[batchblock_sizeblock_size, height_pad/block_size, width_pad/block_size, depth]

Some examples:

(1) For the following input of shape `[1, 2, 2, 1]` and block_size of 2: 

x = [[[[1], [2]], [[3], [4]]]]
The output tensor has shape `[4, 1, 1, 1]` and value: 
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
(2) For the following input of shape `[1, 2, 2, 3]` and block_size of 2: 
x = [[[[1, 2, 3], [4, 5, 6]],
       [[7, 8, 9], [10, 11, 12]]]]
The output tensor has shape `[4, 1, 1, 3]` and value: 
[[[[1, 2, 3]]], [[[4, 5, 6]]], [[[7, 8, 9]]], [[[10, 11, 12]]]]
(3) For the following input of shape `[1, 4, 4, 1]` and block_size of 2: 
x = [[[[1],   [2],  [3],  [4]],
       [[5],   [6],  [7],  [8]],
       [[9],  [10], [11],  [12]],
       [[13], [14], [15],  [16]]]]
The output tensor has shape `[4, 2, 2, 1]` and value: 
x = [[[[1], [3]], [[9], [11]]],
      [[[2], [4]], [[10], [12]]],
      [[[5], [7]], [[13], [15]]],
      [[[6], [8]], [[14], [16]]]]
(4) For the following input of shape `[2, 2, 4, 1]` and block_size of 2: 
x = [[[[1],   [2],  [3],  [4]],
       [[5],   [6],  [7],  [8]]],
      [[[9],  [10], [11],  [12]],
       [[13], [14], [15],  [16]]]]
The output tensor has shape `[8, 1, 2, 1]` and value: 
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.
Returns
  • a new instance of SpaceToBatch

public Output<T> output ()