컬렉션을 사용해 정리하기
내 환경설정을 기준으로 콘텐츠를 저장하고 분류하세요.
텐서플로우:: 작전:: SparseReduceSumSparse
#include <sparse_ops.h>
SparseTensor의 차원 전체에 걸쳐 요소의 합을 계산합니다.
요약
이 작업은 SparseTensor를 사용하며 tf.reduce_sum()
에 대응하는 희소입니다. SparseReduceSum 과 달리 이 Op는 SparseTensor를 반환합니다.
reduction_axes
에 지정된 차원을 따라 sp_input
줄입니다. keep_dims
true가 아닌 이상, 텐서의 순위는 reduction_axes
각 항목에 대해 1씩 감소합니다. keep_dims
true이면 축소된 치수가 길이 1로 유지됩니다.
reduction_axes
항목이 없으면 모든 차원이 줄어들고 단일 요소가 있는 텐서가 반환됩니다. 또한 축은 음수일 수 있으며 이는 Python의 인덱싱 규칙에 따라 해석됩니다.
인수:
- 범위: 범위 개체
- input_indices: 2-D. SparseTensor에서 비어 있지 않은 값의 인덱스가 있는
N x R
행렬(표준 순서가 아닐 수 있음) - 입력_값: 1-D.
input_indices
에 해당하는 N
개의 비어 있지 않은 값. - input_shape: 1-D. 입력 SparseTensor의 모양입니다.
- 감소_축: 1-D. 길이 - 축소 축을 포함하는
K
벡터입니다.
선택적 속성( Attrs
참조):
- keep_dims: true인 경우 길이가 1인 축소된 치수를 유지합니다.
보고:
공개 속성
공공 기능
공개 정적 함수
KeepDims
Attrs KeepDims(
bool x
)
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: 2025-07-26(UTC)
[null,null,["최종 업데이트: 2025-07-26(UTC)"],[],[],null,["# tensorflow::ops::SparseReduceSumSparse Class Reference\n\ntensorflow::ops::SparseReduceSumSparse\n======================================\n\n`#include \u003csparse_ops.h\u003e`\n\nComputes the sum of elements across dimensions of a SparseTensor.\n\nSummary\n-------\n\nThis Op takes a SparseTensor and is the sparse counterpart to `tf.reduce_sum()`. In contrast to [SparseReduceSum](/versions/r2.0/api_docs/cc/class/tensorflow/ops/sparse-reduce-sum#classtensorflow_1_1ops_1_1_sparse_reduce_sum), this Op returns a SparseTensor.\n\nReduces `sp_input` along the dimensions given in `reduction_axes`. Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained with length 1.\n\nIf `reduction_axes` has no entries, all dimensions are reduced, and a tensor with a single element is returned. Additionally, the axes can be negative, which are interpreted according to the indexing rules in Python.\n\nArguments:\n\n- scope: A [Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input_indices: 2-D. `N x R` matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering.\n- input_values: 1-D. `N` non-empty values corresponding to `input_indices`.\n- input_shape: 1-D. Shape of the input SparseTensor.\n- reduction_axes: 1-D. Length-`K` vector containing the reduction axes.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/sparse-reduce-sum-sparse/attrs#structtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1_1_attrs)):\n\n- keep_dims: If true, retain reduced dimensions with length 1.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output_indices\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output_values\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) output_shape\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseReduceSumSparse](#classtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1a6f708aa542de1f8a78354e33cd93ba1f)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input_indices, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input_values, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input_shape, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` reduction_axes)` ||\n| [SparseReduceSumSparse](#classtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1a3993e307a94ec2d2689f821a60717e99)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input_indices, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input_values, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input_shape, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` reduction_axes, const `[SparseReduceSumSparse::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/sparse-reduce-sum-sparse/attrs#structtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1a163cffc8414946a47057a91af8be0e12) | [Operation](/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output_indices](#classtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1a2c546e86ac344ff2cc261c06aac187f4) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [output_shape](#classtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1ad3c4282b03471d1e02bba7e17a46fca6) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [output_values](#classtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1a19b2438eeddfcd3e79017ecb5de54318) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public static functions ||\n|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [KeepDims](#classtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1a8dbe087349a7dd3db345a7abd6752c3d)`(bool x)` | [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/sparse-reduce-sum-sparse/attrs#structtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::SparseReduceSumSparse::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/sparse-reduce-sum-sparse/attrs) | Optional attribute setters for [SparseReduceSumSparse](/versions/r2.0/api_docs/cc/class/tensorflow/ops/sparse-reduce-sum-sparse#classtensorflow_1_1ops_1_1_sparse_reduce_sum_sparse). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output_indices\n\n```scdoc\n::tensorflow::Output output_indices\n``` \n\n### output_shape\n\n```scdoc\n::tensorflow::Output output_shape\n``` \n\n### output_values\n\n```scdoc\n::tensorflow::Output output_values\n``` \n\nPublic functions\n----------------\n\n### SparseReduceSumSparse\n\n```gdscript\n SparseReduceSumSparse(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input_indices,\n ::tensorflow::Input input_values,\n ::tensorflow::Input input_shape,\n ::tensorflow::Input reduction_axes\n)\n``` \n\n### SparseReduceSumSparse\n\n```gdscript\n SparseReduceSumSparse(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input_indices,\n ::tensorflow::Input input_values,\n ::tensorflow::Input input_shape,\n ::tensorflow::Input reduction_axes,\n const SparseReduceSumSparse::Attrs & attrs\n)\n``` \n\nPublic static functions\n-----------------------\n\n### KeepDims\n\n```text\nAttrs KeepDims(\n bool x\n)\n```"]]