Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
tensor akışı:: işlem:: Cosh
#include <math_ops.h> X'in hiperbolik kosinüsünü öğe bazında hesaplar.
Özet
Bir giriş tensörü verildiğinde, bu fonksiyon tensördeki her elemanın hiperbolik kosinüsünü hesaplar. Giriş aralığı [-inf, inf] ve çıkış aralığı [1, inf] şeklindedir.
x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 2, 10, float("inf")])
tf.math.cosh(x) ==> [inf 4.0515420e+03 1.1276259e+00 1.5430807e+00 1.8106556e+00 3.7621956e+00 1.1013233e+04 inf]
Argümanlar:
İade:
Genel özellikler
Kamu işlevleri
düğüm
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operatör::tensorflow::Çıktı
operator::tensorflow::Output() const
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::Cosh Class Reference\n\ntensorflow::ops::Cosh\n=====================\n\n`#include \u003cmath_ops.h\u003e`\n\nComputes hyperbolic cosine of x element-wise.\n\nSummary\n-------\n\nGiven an input tensor, this function computes hyperbolic cosine of every element in the tensor. [Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input) range is `[-inf, inf]` and output range is `[1, inf]`.\n\n\n```gdscript\n x = tf.constant([-float(\"inf\"), -9, -0.5, 1, 1.2, 2, 10, float(\"inf\")])\n tf.math.cosh(x) ==\u003e [inf 4.0515420e+03 1.1276259e+00 1.5430807e+00 1.8106556e+00 3.7621956e+00 1.1013233e+04 inf]\n \n```\n\n\u003cbr /\u003e\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The y tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [Cosh](#classtensorflow_1_1ops_1_1_cosh_1a03ce002815c91b3e9e551f178a9948fd)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` x)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_cosh_1a9e146c30bb44c25ed63fc55581c22a0c) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [y](#classtensorflow_1_1ops_1_1_cosh_1a390e2a4558b9d1461f29be57ee0dadbf) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|----------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_cosh_1a99d194a00f9e0765ccc92b75bb1c8d99)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_cosh_1ae34e8ebed3608f3c74458b161c0a56e6)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_cosh_1ae4a8b1e4d557b893f302f647462b37b3)`() const ` | ` ` ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### y\n\n```text\n::tensorflow::Output y\n``` \n\nPublic functions\n----------------\n\n### Cosh\n\n```gdscript\n Cosh(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x\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```"]]
