# tf.math.unsorted_segment_sum

Defined in generated file: python/ops/gen_math_ops.py

Computes the sum along segments of a tensor.

### Aliases:

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


Read the section on segmentation for an explanation of segments.

Computes a tensor such that $$output[i] = \sum_{j...} data[j...]$$ where the sum is over tuples j... such that segment_ids[j...] == i. Unlike SegmentSum, segment_ids need not be sorted and need not cover all values in the full range of valid values.

If the sum is empty for a given segment ID i, output[i] = 0. If the given segment ID i is negative, the value is dropped and will not be added to the sum of the segment.

num_segments should equal the number of distinct segment IDs.

c = tf.constant([[1,2,3,4], [5,6,7,8], [4,3,2,1]])
tf.unsorted_segment_sum(c, tf.constant([0, 1, 0]), num_segments=2)
# ==> [[ 5,  5, 5, 5],
#       [5,  6, 7, 8]]


#### Args:

• data: A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64.
• segment_ids: A Tensor. Must be one of the following types: int32, int64. A tensor whose shape is a prefix of data.shape.
• num_segments: A Tensor. Must be one of the following types: int32, int64.
• name: A name for the operation (optional).

#### Returns:

A Tensor. Has the same type as data.