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tensorflow::ops::SparseSegmentSqrtN
#include <math_ops.h>
Computes the sum along sparse segments of a tensor divided by the sqrt of N.
Summary
N is the size of the segment being reduced.
See tf.sparse.segment_sum for usage examples.
Args:
- scope: A Scope object
- indices: A 1-D tensor. Has same rank as
segment_ids.
- segment_ids: A 1-D tensor. Values should be sorted and can be repeated.
Returns:
Output: Has same shape as data, except for dimension 0 which has size k, the number of segments.
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tensorflow::ops::SparseSegmentSqrtN Class Reference\n\ntensorflow::ops::SparseSegmentSqrtN\n===================================\n\n`#include \u003cmath_ops.h\u003e`\n\nComputes the sum along sparse segments of a tensor divided by the sqrt of N.\n\nSummary\n-------\n\nN is the size of the segment being reduced.\n\nSee `tf.sparse.segment_sum` for usage examples.\n\nArgs:\n\n- scope: A [Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- indices: A 1-D tensor. Has same rank as `segment_ids`.\n- segment_ids: A 1-D tensor. Values should be sorted and can be repeated.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Has same shape as data, except for dimension 0 which has size `k`, the number of segments.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseSegmentSqrtN](#classtensorflow_1_1ops_1_1_sparse_segment_sqrt_n_1a40f8ad324c1d7f4dd4c3f768b107dc39)`(const ::`[tensorflow::Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` data, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` segment_ids)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_segment_sqrt_n_1ac6e04b8ae49c040d4fb78539251f732c) | [Operation](/versions/r2.14/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_sparse_segment_sqrt_n_1ad4bf36c9267e5d6245c5b1d143049272) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|---------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_sparse_segment_sqrt_n_1ad30c396ef181cd74984b1d23ff3bdee3)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_segment_sqrt_n_1adbc1ac76f231ca09d1ba5df15369c510)`() const ` | |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_segment_sqrt_n_1aba2d284339055dbd154009532a171823)`() const ` | |\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### SparseSegmentSqrtN\n\n```gdscript\n SparseSegmentSqrtN(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input data,\n ::tensorflow::Input indices,\n ::tensorflow::Input segment_ids\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```"]]
