Python - tensorflow.math.unsorted_segment_sum()

Introduction

tensorflow.math.unsorted_segment_sum() is a function in TensorFlow library that computes the sum of values in a tensor along specified segments. It is primarily used when dealing with sparse data or when the order of segments doesn't matter.

Syntax

tensorflow.math.unsorted_segment_sum(
    data,
    segment_ids,
    num_segments,
    name=None
)

Parameters

• data: A tensor, the tensor containing values for which sum needs to be computed.
• segment_ids: A tensor, the tensor containing segment indices specifying which segments to sum.
• num_segments: An integer or scalar tensor, the number of different segments.
• name: (Optional) A string, the name for the operation.

Returns

• A tensor with shape [num_segments], the tensor with sums of values along segments.

Example

import tensorflow as tf

# Create input tensors
data = tf.constant([2, 3, 4, 5, 6, 7, 8, 9], dtype=tf.float32)
segment_ids = tf.constant([0, 1, 2, 0, 0, 1, 2, 2], dtype=tf.int32)
num_segments = 3

# Compute unsorted segment sum
result = tf.math.unsorted_segment_sum(data, segment_ids, num_segments)

print(result)

Output

tf.Tensor([11.  9. 19.], shape=(3,), dtype=float32)

In the example above, the unsorted_segment_sum() function computes the sums of values from the data tensor based on the segment_ids tensor. The resulting tensor has three values, representing the sums of values for each segment.

Conclusion

The tensorflow.math.unsorted_segment_sum() function is useful for aggregating data along segments in a tensor. It allows you to efficiently compute segment-wise sums without requiring the segments to be sorted.