@Namespace(value="tensorflow::ops") @NoOffset @Properties(inherit=tensorflow.class) public class MirrorPad extends Pointer
input
with mirrored values according to the paddings
you specify. paddings
is an integer tensor with shape [n, 2]
, where n is
the rank of input
. For each dimension D of input
, paddings[D, 0]
indicates
how many values to add before the contents of input
in that dimension, and
paddings[D, 1]
indicates how many values to add after the contents of input
in that dimension. Both paddings[D, 0]
and paddings[D, 1]
must be no greater
than input.dim_size(D)
(or input.dim_size(D) - 1
) if copy_border
is true
(if false, respectively).
The padded size of each dimension D of the output is:
paddings(D, 0) + input.dim_size(D) + paddings(D, 1)
For example:
# 't' is [[1, 2, 3], [4, 5, 6]].
# 'paddings' is [[1, 1]], [2, 2]].
# 'mode' is SYMMETRIC.
# rank of 't' is 2.
pad(t, paddings) ==> [[2, 1, 1, 2, 3, 3, 2]
[2, 1, 1, 2, 3, 3, 2]
[5, 4, 4, 5, 6, 6, 5]
[5, 4, 4, 5, 6, 6, 5]]
Arguments:
* scope: A Scope object
* input: The input tensor to be padded.
* paddings: A two-column matrix specifying the padding sizes. The number of
rows must be the same as the rank of input
.
* mode: Either REFLECT
or SYMMETRIC
. In reflect mode the padded regions
do not include the borders, while in symmetric mode the padded regions
do include the borders. For example, if input
is [1, 2, 3]
and paddings
is [0, 2]
, then the output is [1, 2, 3, 2, 1]
in reflect mode, and
it is [1, 2, 3, 3, 2]
in symmetric mode.
Returns:
* Output
: The padded tensor.Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
---|
MirrorPad(Pointer p)
Pointer cast constructor.
|
MirrorPad(Scope scope,
Input input,
Input paddings,
BytePointer mode) |
MirrorPad(Scope scope,
Input input,
Input paddings,
String mode) |
Modifier and Type | Method and Description |
---|---|
Input |
asInput() |
Output |
asOutput() |
Node |
node() |
Operation |
operation() |
MirrorPad |
operation(Operation setter) |
Output |
output() |
MirrorPad |
output(Output setter) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public MirrorPad(Pointer p)
Pointer(Pointer)
.public MirrorPad(@Const @ByRef Scope scope, @ByVal Input input, @ByVal Input paddings, @tensorflow.StringPiece BytePointer mode)
public Node node()
Copyright © 2022. All rights reserved.