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tensorflow::
ops::
MirrorPad
#include <array_ops.h>
Pads a tensor with mirrored values.
Summary
This operation pads a
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]]
Args:
-
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:
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2021-08-16 UTC.
[null,null,["Last updated 2021-08-16 UTC."],[],[],null,["# tensorflow::ops::MirrorPad Class Reference\n\ntensorflow::\nops::\nMirrorPad\n============================\n\n`\n#include \u003carray_ops.h\u003e\n`\n\n\nPads a tensor with mirrored values.\n\nSummary\n-------\n\n\nThis operation pads a\n`\ninput\n`\nwith mirrored values according to the\n`\npaddings\n`\nyou specify.\n`\npaddings\n`\nis an integer tensor with shape\n`\n[n, 2]\n`\n, where n is the rank of\n`\ninput\n`\n. For each dimension D of\n`\ninput\n`\n,\n`\npaddings[D, 0]\n`\nindicates how many values to add before the contents of\n`\ninput\n`\nin that dimension, and\n`\npaddings[D, 1]\n`\nindicates how many values to add after the contents of\n`\ninput\n`\nin that dimension. Both\n`\npaddings[D, 0]\n`\nand\n`\npaddings[D, 1]\n`\nmust be no greater than\n`\ninput.dim_size(D)\n`\n(or\n`\ninput.dim_size(D) - 1\n`\n) if\n`\ncopy_border\n`\nis true (if false, respectively).\n\n\nThe padded size of each dimension D of the output is:\n\n\n`\npaddings(D, 0) + input.dim_size(D) + paddings(D, 1)\n`\n\n\nFor example:\n\n\n```text\n# 't' is [[1, 2, 3], [4, 5, 6]].\n# 'paddings' is [[1, 1]], [2, 2]].\n# 'mode' is SYMMETRIC.\n# rank of 't' is 2.\npad(t, paddings) ==\u003e [[2, 1, 1, 2, 3, 3, 2]\n [2, 1, 1, 2, 3, 3, 2]\n [5, 4, 4, 5, 6, 6, 5]\n [5, 4, 4, 5, 6, 6, 5]]\n```\n\n\u003cbr /\u003e\n\n\nArgs:\n\n- scope: A [Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input: The input tensor to be padded.\n- paddings: A two-column matrix specifying the padding sizes. The number of rows must be the same as the rank of `\n input\n ` .\n- mode: Either `\n REFLECT\n ` or `\n SYMMETRIC\n ` . 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 `\n input\n ` is `\n [1, 2, 3]\n ` and `\n paddings\n ` is `\n [0, 2]\n ` , then the output is `\n [1, 2, 3, 2, 1]\n ` in reflect mode, and it is `\n [1, 2, 3, 3, 2]\n ` in symmetric mode.\n\n\u003cbr /\u003e\n\n\nReturns:\n\n- `\n `[Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` : The padded tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| ` `[MirrorPad](#classtensorflow_1_1ops_1_1_mirror_pad_1ade8674bcac38c7b92e49227402b3aeab)` (const :: `[tensorflow::Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` paddings, StringPiece mode) ` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|\n| ` `[operation](#classtensorflow_1_1ops_1_1_mirror_pad_1a20963b11eba097a4a292d10fe912fe9f)` ` | ` `[Operation](/versions/r2.6/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n| ` `[output](#classtensorflow_1_1ops_1_1_mirror_pad_1acddc2951f705b38786a6c90517025bbd)` ` | ` :: `[tensorflow::Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n\n| ### Public functions ||\n|--------------------------------------------------------------------------------------------------------------------------|--------------------------|\n| ` `[node](#classtensorflow_1_1ops_1_1_mirror_pad_1ac601ae413e0e24707abfe6bd6e000e3e)` () const ` | ` ::tensorflow::Node * ` |\n| ` `[operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_mirror_pad_1a27d0164d159236fcb1639d0dd7604c31)` () const ` | ` ` |\n| ` `[operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_mirror_pad_1a682f1e9bfbad14b9b9529733b71dba26)` () const ` | ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output\n\n```text\n::tensorflow::Output output\n``` \n\nPublic functions\n----------------\n\n### MirrorPad\n\n```gdscript\n MirrorPad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input paddings,\n StringPiece mode\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n```"]]
