# tensorflow::ops::SparseSegmentSum

`#include <math_ops.h>`

Computes the sum along sparse segments of a tensor.

## Summary

Read [the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation) for an explanation of segments.

Like `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/segment-sum#classtensorflow_1_1ops_1_1_segment_sum`, 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]])
```

<br />


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

<br />


```
# 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]]
```

<br />


```
# 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]]
```

<br />


```
# Which is equivalent to:
tf.segment_sum(c, tf.constant([0, 0, 1]))
```

<br />

Arguments:

- scope: A [Scope](https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object
- indices: A 1-D tensor. Has same rank as `segment_ids`.
- segment_ids: A 1-D tensor. Values should be sorted and can be repeated.

<br />

Returns:

- `https://www.tensorflow.org/versions/r2.0/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.

<br />

| ### Constructors and Destructors ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/sparse-segment-sum#classtensorflow_1_1ops_1_1_sparse_segment_sum_1a02259862f31344aafc95082e08aa9aab(const ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input data, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input indices, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input segment_ids)` ||

| ### Public attributes ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/sparse-segment-sum#classtensorflow_1_1ops_1_1_sparse_segment_sum_1ad649884f20027c1aad55e81c08e7957b` | `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation` |
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/sparse-segment-sum#classtensorflow_1_1ops_1_1_sparse_segment_sum_1a40540c212fd500b0d52073ad1fc9d0c8` | `::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output` |

| ### Public functions ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/sparse-segment-sum#classtensorflow_1_1ops_1_1_sparse_segment_sum_1a51e3e189f4da0718eca9673f4245f2b2() const ` | `::tensorflow::Node *` |
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/sparse-segment-sum#classtensorflow_1_1ops_1_1_sparse_segment_sum_1a61710c54c59674e886a27a1025c266ba() const ` | ` `` ` |
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/sparse-segment-sum#classtensorflow_1_1ops_1_1_sparse_segment_sum_1ad6961f104657b05da798100d4ac7f68b() const ` | ` `` ` |

## Public attributes

### operation

```
Operation operation
```

### output

```
::tensorflow::Output output
```

## Public functions

### SparseSegmentSum

```
 SparseSegmentSum(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input data,
  ::tensorflow::Input indices,
  ::tensorflow::Input segment_ids
)
```

### node

```
::tensorflow::Node * node() const 
```

### operator::tensorflow::Input

```
 operator::tensorflow::Input() const 
```

### operator::tensorflow::Output

```
 operator::tensorflow::Output() const 
```