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텐서플로우:: 작전:: 비정형Bincount
#include <math_ops.h>
정수 배열에서 각 값의 발생 횟수를 셉니다.
요약
길이 size
와 weights
와 동일한 dtype을 가진 벡터를 출력합니다. weights
비어 있으면 인덱스 i
값 i
가 arr
에 계산되는 횟수를 저장합니다. weights
비어 있지 않으면 인덱스 i
는 arr
의 해당 값이 i
인 각 인덱스의 weights
값의 합을 저장합니다.
arr
의 값이 [0, size) 범위를 벗어나면 무시됩니다.
인수:
- 범위: 범위 개체
- 분할: 1D int64
Tensor
. - 값: 2D int
Tensor
. - 크기: 음수가 아닌 정수 스칼라
Tensor
. - 가중치: int32, int64, float32 또는 float64
Tensor
input
과 동일한 형태를 갖거나 길이가 0인 Tensor
입니다. 이 경우 모든 가중치가 1인 것처럼 작동합니다.
선택적 속성( Attrs
참조):
- 바이너리 출력: 부울; 커널이 출현 횟수 또는 발생 횟수를 계산해야 하는지 여부입니다.
보고:
-
Output
: 길이가 size
와 같은 1D Tensor
또는 [batch_size, size
]의 2D Tensor
. [0, 크기) 범위에 있는 각 값의 개수 또는 합산된 가중치입니다.
공개 속성
공공 기능
마디
::tensorflow::Node * node() const
operator::tensorflow::Input() const
연산자::텐서플로우::출력
operator::tensorflow::Output() const
공개 정적 함수
바이너리 출력
Attrs BinaryOutput(
bool x
)
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최종 업데이트: 2025-07-26(UTC)
[null,null,["최종 업데이트: 2025-07-26(UTC)"],[],[],null,["# tensorflow::ops::RaggedBincount Class Reference\n\ntensorflow::ops::RaggedBincount\n===============================\n\n`#include \u003cmath_ops.h\u003e`\n\nCounts the number of occurrences of each value in an integer array.\n\nSummary\n-------\n\nOutputs a vector with length `size` and the same dtype as `weights`. If `weights` are empty, then index `i` stores the number of times the value `i` is counted in `arr`. If `weights` are non-empty, then index `i` stores the sum of the value in `weights` at each index where the corresponding value in `arr` is `i`.\n\nValues in `arr` outside of the range \\[0, size) are ignored.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- splits: 1D int64 [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor).\n- values: 2D int [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor).\n- size: non-negative int scalar [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor).\n- weights: is an int32, int64, float32, or float64 [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with the same shape as `input`, or a length-0 [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor), in which case it acts as all weights equal to 1.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/ragged-bincount/attrs#structtensorflow_1_1ops_1_1_ragged_bincount_1_1_attrs)):\n\n- binary_output: bool; Whether the kernel should count the appearance or number of occurrences.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): 1D [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with length equal to `size` or 2D [Tensor](/versions/r2.3/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with \\[batch_size, `size`\\]. The counts or summed weights for each value in the range \\[0, size).\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [RaggedBincount](#classtensorflow_1_1ops_1_1_ragged_bincount_1af6554de96f809fccbd678adaffbc3c24)`(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)` splits, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` values, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` size, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` weights)` ||\n| [RaggedBincount](#classtensorflow_1_1ops_1_1_ragged_bincount_1ab10c029cf1e632fc88ce35a983cecd43)`(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)` splits, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` values, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` size, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` weights, const `[RaggedBincount::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/ragged-bincount/attrs#structtensorflow_1_1ops_1_1_ragged_bincount_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_ragged_bincount_1a733325350aabe10af880482ad5e1f9e0) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_ragged_bincount_1a29aa4960a91cfce90a6ff9b5bdd8f47d) | `::`[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_ragged_bincount_1ab80b688c6e079f3cb485c27bae9fc4f6)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_ragged_bincount_1a3ee830fe3366afe1d6d8185e5d362999)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_ragged_bincount_1a0258579a8e475e40192adf1f9d54b806)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------|\n| [BinaryOutput](#classtensorflow_1_1ops_1_1_ragged_bincount_1a9853523da24b28968c4a53efae303ab9)`(bool x)` | [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/ragged-bincount/attrs#structtensorflow_1_1ops_1_1_ragged_bincount_1_1_attrs) |\n\n| ### Structs ||\n|------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::RaggedBincount::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/ragged-bincount/attrs) | Optional attribute setters for [RaggedBincount](/versions/r2.3/api_docs/cc/class/tensorflow/ops/ragged-bincount#classtensorflow_1_1ops_1_1_ragged_bincount). |\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### RaggedBincount\n\n```gdscript\n RaggedBincount(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input splits,\n ::tensorflow::Input values,\n ::tensorflow::Input size,\n ::tensorflow::Input weights\n)\n``` \n\n### RaggedBincount\n\n```gdscript\n RaggedBincount(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input splits,\n ::tensorflow::Input values,\n ::tensorflow::Input size,\n ::tensorflow::Input weights,\n const RaggedBincount::Attrs & attrs\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``` \n\nPublic static functions\n-----------------------\n\n### BinaryOutput\n\n```text\nAttrs BinaryOutput(\n bool x\n)\n```"]]