컬렉션을 사용해 정리하기
내 환경설정을 기준으로 콘텐츠를 저장하고 분류하세요.
텐서플로우:: 작전:: 탠 껍질
#include <math_ops.h>
x 요소별로 tan을 계산합니다.
요약
입력 텐서가 주어지면 이 함수는 텐서에 있는 모든 요소의 탄젠트를 계산합니다. 입력 범위는 (-inf, inf)
이고 출력 범위는 (-inf, inf)
입니다. 입력이 경계 외부에 있으면 nan
반환됩니다.
x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 200, 10000, float("inf")])
tf.math.tan(x) ==> [nan 0.45231566 -0.5463025 1.5574077 2.572152 -1.7925274 0.32097113 nan]
인수:
보고:
공개 속성
공공 기능
마디
::tensorflow::Node * node() const
operator::tensorflow::Input() const
연산자::텐서플로우::출력
operator::tensorflow::Output() const
달리 명시되지 않는 한 이 페이지의 콘텐츠에는 Creative Commons Attribution 4.0 라이선스에 따라 라이선스가 부여되며, 코드 샘플에는 Apache 2.0 라이선스에 따라 라이선스가 부여됩니다. 자세한 내용은 Google Developers 사이트 정책을 참조하세요. 자바는 Oracle 및/또는 Oracle 계열사의 등록 상표입니다.
최종 업데이트: 2025-07-25(UTC)
[null,null,["최종 업데이트: 2025-07-25(UTC)"],[],[],null,["# tensorflow::ops::Tan Class Reference\n\ntensorflow::ops::Tan\n====================\n\n`#include \u003cmath_ops.h\u003e`\n\nComputes tan of x element-wise.\n\nSummary\n-------\n\nGiven an input tensor, this function computes tangent 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 `(-inf, inf)`. If input lies outside the boundary, `nan` is returned.\n\n\n```gdscript\n x = tf.constant([-float(\"inf\"), -9, -0.5, 1, 1.2, 200, 10000, float(\"inf\")])\n tf.math.tan(x) ==\u003e [nan 0.45231566 -0.5463025 1.5574077 2.572152 -1.7925274 0.32097113 nan]\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| [Tan](#classtensorflow_1_1ops_1_1_tan_1ab55fbba17be79b5811f49b2728dd4cbc)`(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_tan_1afb37a60014fe1eab1803711757f8c027) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [y](#classtensorflow_1_1ops_1_1_tan_1a43c28a4fa5ec96c4d509e1b31eb2bd5b) | `::`[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_tan_1a284777905469857d2f3aefaa520a991d)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_tan_1a8fec1bcffaaefa2d23940a641ec04cbf)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_tan_1a0bd2bfaa65fd5352902950aba2a2a29e)`() 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### Tan\n\n```gdscript\n Tan(\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```"]]