Package org.tensorflow.op.nn

Class SpaceToBatch<T>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.nn.SpaceToBatch<T>

Type Parameters:

T - data type for output() output

All Implemented Interfaces:

Op, Operand<T>

@Operator(group="nn")
public final class SpaceToBatch<T>
extends PrimitiveOp
implements Operand<T>

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.

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method	Description
Output<T>	asOutput()	Returns the symbolic handle of a tensor.
static <T,U extends java.lang.Number> SpaceToBatch<T>	create(Scope scope, Operand<T> input, Operand<U> paddings, java.lang.Long blockSize)	Factory method to create a class to wrap a new SpaceToBatch operation to the graph.
Output<T>	output()

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, toString

Method Detail

create

public static <T,U extends java.lang.Number> SpaceToBatch<T> create(Scope scope,
                                                                    Operand<T> input,
                                                                    Operand<U> paddings,
                                                                    java.lang.Long blockSize)

Factory method to create a class to wrap a new SpaceToBatch operation to the graph.

Parameters:

scope - current graph 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.

blockSize -

Returns:

a new instance of SpaceToBatch

output

public Output<T> output()

asOutput

public Output<T> asOutput()

Description copied from interface: Operand

Returns the symbolic handle of a 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.

Specified by:

asOutput in interface Operand<T>

See Also:

OperationBuilder.addInput(Output)