Computes a tensor such that \(output_i = \min_j(data_j)\) where min is over j such that segment_ids[j] == i.
If the min is empty for a given segment ID i, output[i] = 0.
Caution: On CPU, values in segment_ids are always validated to be sorted, and an error is thrown for indices that are not increasing. On GPU, this does not throw an error for unsorted indices. On GPU, out-of-order indices result in safe but unspecified behavior, which may include treating out-of-order indices as the same as a smaller following index.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-05-19 UTC."],[],[],null,["# tensorflow::ops::SegmentMin Class Reference\n\ntensorflow::ops::SegmentMin\n===========================\n\n`#include \u003cmath_ops.h\u003e`\n\nComputes the minimum along segments of a tensor.\n\nSummary\n-------\n\nRead [the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation) for an explanation of segments.\n\nComputes a tensor such that \\\\(output_i = \\\\min_j(data_j)\\\\) where `min` is over `j` such that `segment_ids[j] == i`.\n\nIf the min is empty for a given segment ID `i`, `output[i] = 0`.\n\nCaution: On CPU, values in `segment_ids` are always validated to be sorted, and an error is thrown for indices that are not increasing. On GPU, this does not throw an error for unsorted indices. On GPU, out-of-order indices result in safe but unspecified behavior, which may include treating out-of-order indices as the same as a smaller following index.\n\n\n\u003cbr /\u003e\n\nFor example:\n\nc = tf.constant(\\[\\[1,2,3,4\\], \\[4, 3, 2, 1\\], \\[5,6,7,8\\]\\]) tf.math.segment_min(c, tf.constant(\\[0, 0, 1\\])).numpy() array(\\[\\[1, 2, 2, 1\\], \\[5, 6, 7, 8\\]\\], dtype=int32)\n\nArgs:\n\n- scope: A [Scope](/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- segment_ids: A 1-D tensor whose size is equal to the size of `data`'s first dimension. Values should be sorted and can be repeated.\n\n\u003cbr /\u003e\n\nCaution: The values are always validated to be sorted on CPU, never validated on GPU.\n\nReturns:\n\n- [Output](/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| [SegmentMin](#classtensorflow_1_1ops_1_1_segment_min_1a3012dce1d5e46fd538083a4543420a89)`(const ::`[tensorflow::Scope](/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` data, ::`[tensorflow::Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` segment_ids)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_segment_min_1a1dd3ab9be4244f9e51ee31f1249735ff) | [Operation](/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_segment_min_1aa79a959666dedb9e81ae623ed8ba28a8) | `::`[tensorflow::Output](/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_segment_min_1a0315622df52ece6431d28d99520c1eef)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_segment_min_1aa2819b4005543663b84fe92fcbbec66a)`() const ` | |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_segment_min_1a479837a013d764ff8d54553f71f32b83)`() 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### SegmentMin\n\n```gdscript\n SegmentMin(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input data,\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```"]]
