Mantieni tutto organizzato con le raccolte
Salva e classifica i contenuti in base alle tue preferenze.
tensoreflusso:: ops:: Pad
#include <array_ops.h> Riempie un tensore con zeri.
Riepilogo
Questa operazione riempie un input con zeri in base ai paddings specificati. paddings è un tensore intero con forma [Dn, 2] , dove n è il rango input . Per ogni dimensione D di input , paddings[D, 0] indica quanti zeri aggiungere prima del contenuto di input in quella dimensione e paddings[D, 1] indica quanti zeri aggiungere dopo il contenuto di input in quella dimensione.
La dimensione riempita di ciascuna dimensione D dell'output è:
paddings(D, 0) + input.dim_size(D) + paddings(D, 1)
Per esempio:
# 't' is [[1, 1], [2, 2]]
# 'paddings' is [[1, 1], [2, 2]]
# 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]] Argomenti:
Resi:
-
Output : il tensore di uscita.
Attributi pubblici
Funzioni pubbliche
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatore::tensorflow::Output
operator::tensorflow::Output() const
Salvo quando diversamente specificato, i contenuti di questa pagina sono concessi in base alla licenza Creative Commons Attribution 4.0, mentre gli esempi di codice sono concessi in base alla licenza Apache 2.0. Per ulteriori dettagli, consulta le norme del sito di Google Developers. Java è un marchio registrato di Oracle e/o delle sue consociate.
Ultimo aggiornamento 2025-07-26 UTC.
[null,null,["Ultimo aggiornamento 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::Pad Class Reference\n\ntensorflow::ops::Pad\n====================\n\n`#include \u003carray_ops.h\u003e`\n\nPads a tensor with zeros.\n\nSummary\n-------\n\nThis operation pads a `input` with zeros according to the `paddings` 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 zeros to add before the contents of `input` in that dimension, and `paddings[D, 1]` indicates how many zeros to add after the contents of `input` in that dimension.\n\nThe padded size of each dimension D of the output is:\n\n\n`paddings(D, 0) + input.dim_size(D) + paddings(D, 1)`\n\nFor example:\n\n\n```text\n# 't' is [[1, 1], [2, 2]]\n# 'paddings' is [[1, 1], [2, 2]]\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\nArguments:\n\n- scope: A [Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The output tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [Pad](#classtensorflow_1_1ops_1_1_pad_1a85413c81814471dc1ba383fffd013f80)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` paddings)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_pad_1a563b99bce289e4fa9fff7224401df773) | [Operation](/versions/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_pad_1aa9ec34eb45ae5c727d6bba3e8b51be74) | `::`[tensorflow::Output](/versions/r2.1/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|---------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_pad_1a56e85f7a36d0008faa2e054812438b98)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_pad_1a800a33c0560ed61b5f202d6a5aaf4ca9)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_pad_1a177bc15a4ed8369a6438d47130f9ac27)`() 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### Pad\n\n```gdscript\n Pad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input paddings\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```"]]
