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텐서플로우:: 작전:: 플로어모드
#include <math_ops.h> 요소별 나눗셈의 나머지를 반환합니다.
요약
x < 0 xor y < 0 일 때
사실, 이는 여기서 결과가 바닥 분할과 일치한다는 점에서 Python 의미론을 따릅니다. 예: floor(x / y) * y + mod(x, y) = x .
참고 : FloorMod 방송을 지원합니다. 방송에 대한 자세한 내용은 여기에서 확인하세요.
인수:
보고:
공개 속성
공공 기능
마디
::tensorflow::Node * node() const
operator::tensorflow::Input() const
연산자::텐서플로우::출력
operator::tensorflow::Output() const
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최종 업데이트: 2025-07-26(UTC)
[null,null,["최종 업데이트: 2025-07-26(UTC)"],[],[],null,["# tensorflow::ops::FloorMod Class Reference\n\ntensorflow::ops::FloorMod\n=========================\n\n`#include \u003cmath_ops.h\u003e`\n\nReturns element-wise remainder of division.\n\nSummary\n-------\n\nWhen `x \u003c 0` xor `y \u003c 0` is\n\ntrue, this follows Python semantics in that the result here is consistent with a flooring divide. E.g. `floor(x / y) * y + mod(x, y) = x`.\n\n*NOTE* : [FloorMod](/versions/r2.3/api_docs/cc/class/tensorflow/ops/floor-mod#classtensorflow_1_1ops_1_1_floor_mod) supports broadcasting. More about broadcasting [here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html)\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 z tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [FloorMod](#classtensorflow_1_1ops_1_1_floor_mod_1a34457c7c33286a90d5b2877cf949255a)`(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, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` y)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_floor_mod_1a3a085f39f4494b346d655dee742ee76f) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [z](#classtensorflow_1_1ops_1_1_floor_mod_1ac4d9bd96ad307be9f91f52b0aad17227) | `::`[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_floor_mod_1a76a8f84a099ed7f2172c23952b8e56bc)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_floor_mod_1a40e8c3fb00de30f9b6f361d180336097)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_floor_mod_1ad99a283a5c4fede4a1dd8801952061d2)`() const ` | ` ` ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### z\n\n```text\n::tensorflow::Output z\n``` \n\nPublic functions\n----------------\n\n### FloorMod\n\n```gdscript\n FloorMod(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x,\n ::tensorflow::Input y\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```"]]
