Stay organized with collections
Save and categorize content based on your preferences.
tensorflow::
ops::
PadV2
#include <array_ops.h>
Pads a tensor.
Summary
This operation pads
input
according to the
paddings
and
constant_values
you specify.
paddings
is an integer tensor with shape
[Dn, 2]
, where n is the rank of
input
. For each dimension D of
input
,
paddings[D, 0]
indicates how many padding values to add before the contents of
input
in that dimension, and
paddings[D, 1]
indicates how many padding values to add after the contents of
input
in that dimension.
constant_values
is a scalar tensor of the same type as
input
that indicates the value to use for padding
input
.
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, 1], [2, 2]]
# 'paddings' is [[1, 1], [2, 2]]
# 'constant_values' is 0
# rank of 't' is 2
pad(t, paddings) ==> [[0, 0, 0, 0, 0, 0]
[0, 0, 1, 1, 0, 0]
[0, 0, 2, 2, 0, 0]
[0, 0, 0, 0, 0, 0]]
Args:
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::PadV2 Class Reference\n\ntensorflow::\nops::\nPadV2\n========================\n\n`\n#include \u003carray_ops.h\u003e\n`\n\n\nPads a tensor.\n\nSummary\n-------\n\n\nThis operation pads\n`\ninput\n`\naccording to the\n`\npaddings\n`\nand\n`\nconstant_values\n`\nyou specify.\n`\npaddings\n`\nis an integer tensor with shape\n`\n[Dn, 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 padding values to add before the contents of\n`\ninput\n`\nin that dimension, and\n`\npaddings[D, 1]\n`\nindicates how many padding values to add after the contents of\n`\ninput\n`\nin that dimension.\n`\nconstant_values\n`\nis a scalar tensor of the same type as\n`\ninput\n`\nthat indicates the value to use for padding\n`\ninput\n`\n.\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```gdscript\n# 't' is [[1, 1], [2, 2]]\n# 'paddings' is [[1, 1], [2, 2]]\n# 'constant_values' is 0\n# rank of 't' is 2\npad(t, paddings) ==\u003e [[0, 0, 0, 0, 0, 0]\n [0, 0, 1, 1, 0, 0]\n [0, 0, 2, 2, 0, 0]\n [0, 0, 0, 0, 0, 0]]\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\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 output tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| ` `[PadV2](#classtensorflow_1_1ops_1_1_pad_v2_1a7bfe2355f5a726124af6e6f1b824b9cb)` (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, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` constant_values) ` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|\n| ` `[operation](#classtensorflow_1_1ops_1_1_pad_v2_1aa6b1cf71582c8eb44a33bac7b2750a55)` ` | ` `[Operation](/versions/r2.6/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n| ` `[output](#classtensorflow_1_1ops_1_1_pad_v2_1ad73c63310fcef6d2993c1a43c93aa7a1)` ` | ` :: `[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_pad_v2_1a4f62d5b59022fec3a068bd2196a98891)` () const ` | ` ::tensorflow::Node * ` |\n| ` `[operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_pad_v2_1a74d06bca0cc72234b6a1578639fca7f5)` () const ` | ` ` |\n| ` `[operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_pad_v2_1ad0329a090a7e956fcd77489c7d27edc4)` () 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### PadV2\n\n```gdscript\n PadV2(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input paddings,\n ::tensorflow::Input constant_values\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```"]]
