87: segment_sum | unsorted_segment_sum | TensorFlow | Tutorial

Welcome to this tutorial on segment_sum and unsorted_segment_sum in TensorFlow!

Both segment_sum and unsorted_segment_sum are functions in TensorFlow that can be used to perform operations on segments of a larger tensor.

segment_sum

The segment_sum function in TensorFlow computes the sum of values in the tensor along the segments specified by a segment_ids tensor.

For example:

import tensorflow as tf

data = tf.constant([1, 2, 3, 4, 5])
segment_ids = tf.constant([0, 0, 1, 1, 2])

result = tf.math.segment_sum(data, segment_ids)

print(result.numpy())

unsorted_segment_sum

The unsorted_segment_sum function in TensorFlow is similar to segment_sum, but it does not require the segment IDs to be sorted.

For example:

import tensorflow as tf

data = tf.constant([1, 2, 3, 4, 5])
segment_ids = tf.constant([2, 1, 2, 0, 1])

result = tf.math.unsorted_segment_sum(data, segment_ids, num_segments=3)

print(result.numpy())

These functions can be useful in scenarios where you need to aggregate data along different segments or groups in a tensor.

Thank you for reading this tutorial on segment_sum and unsorted_segment_sum in TensorFlow. We hope you found it helpful!