Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
tensor akışı:: işlem:: Lgamma
#include <math_ops.h> Gamma(x) öğesinin mutlak değerinin öğe bazında günlüğünü hesaplar.
Özet
Pozitif sayılar için bu işlev, tensördeki her öğe için log((input - 1)!) değerini hesaplar. lgamma(5) = log((5-1)!) = log(4!) = log(24) = 3.1780539
Örnek:
x = tf.constant([0, 0.5, 1, 4.5, -4, -5.6])
tf.math.lgamma(x) ==> [inf, 0.5723649, 0., 2.4537368, inf, -4.6477685]
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: 2025-07-27 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-27 UTC."],[],[],null,["# tensorflow::ops::Lgamma Class Reference\n\ntensorflow::ops::Lgamma\n=======================\n\n`#include \u003cmath_ops.h\u003e`\n\nComputes the log of the absolute value of `Gamma(x)` element-wise.\n\nSummary\n-------\n\nFor positive numbers, this function computes log((input - 1)!) for every element in the tensor. `lgamma(5) = log((5-1)!) = log(4!) = log(24) = 3.1780539`\n\nExample:\n\n\n```gdscript\nx = tf.constant([0, 0.5, 1, 4.5, -4, -5.6])\ntf.math.lgamma(x) ==\u003e [inf, 0.5723649, 0., 2.4537368, inf, -4.6477685]\n```\n\n\u003cbr /\u003e\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The y tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [Lgamma](#classtensorflow_1_1ops_1_1_lgamma_1a150fec9302f3622dc8885f6d75980d58)`(const ::`[tensorflow::Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` x)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_lgamma_1aaede98d02e1e19ad09b9578d91655e12) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [y](#classtensorflow_1_1ops_1_1_lgamma_1aa40f8955ff20a832e557ea33b2b764ba) | `::`[tensorflow::Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_lgamma_1a68ff86c03e6c325c055e727edbb4486c)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_lgamma_1a71994d50b4db9b4158d3b0cc2f6111d4)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_lgamma_1acbf27ddfeef1916a009c8b2356ecabe6)`() 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### Lgamma\n\n```gdscript\n Lgamma(\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```"]]
