/TensorFlow 2.4

# tf.raw_ops.SparseSegmentSum

Computes the sum along sparse segments of a tensor.

Read the section on segmentation for an explanation of segments.

Like `SegmentSum`, but `segment_ids` can have rank less than `data`'s first dimension, selecting a subset of dimension 0, specified by `indices`.

#### For example:

```c = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])

# Select two rows, one segment.
tf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 0]))
# => [[0 0 0 0]]

# Select two rows, two segment.
tf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 1]))
# => [[ 1  2  3  4]
#     [-1 -2 -3 -4]]

# Select all rows, two segments.
tf.sparse_segment_sum(c, tf.constant([0, 1, 2]), tf.constant([0, 0, 1]))
# => [[0 0 0 0]
#     [5 6 7 8]]

# Which is equivalent to:
tf.segment_sum(c, tf.constant([0, 0, 1]))
```
Args
`data` A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `int64`, `bfloat16`, `uint16`, `half`, `uint32`, `uint64`.
`indices` A `Tensor`. Must be one of the following types: `int32`, `int64`. A 1-D tensor. Has same rank as `segment_ids`.
`segment_ids` A `Tensor`. Must be one of the following types: `int32`, `int64`. A 1-D tensor. Values should be sorted and can be repeated.
`name` A name for the operation (optional).
Returns
A `Tensor`. Has the same type as `data`.