# tensorflow::ops::UnsortedSegmentMin Class Reference

# tensorflow::ops::UnsortedSegmentMin

`#include <math_ops.h>`

Computes the minimum along segments of a tensor.

## Summary

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

This operator is similar to the unsorted segment sum operator found [(here)](https://www.tensorflow.org/versions/r2.3/api_docs/cc/api_docs/python/math_ops.md#UnsortedSegmentSum). Instead of computing the sum over segments, it computes the minimum such that:

\\(output_i = {j...} data_\[j...\]\\) where min is over tuples `j...` such that `segment_ids[j...] == i`.

If the minimum is empty for a given segment ID `i`, it outputs the largest possible value for the specific numeric type, `output[i] = numeric_limits::max()`.

For example:


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

<br />

If the given segment ID `i` is negative, then the corresponding value is dropped, and will not be included in the result.

Arguments:

- scope: A [Scope](https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object
- segment_ids: A tensor whose shape is a prefix of `data.shape`.

<br />

Returns:

- `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output`: Has same shape as data, except for the first `segment_ids.rank` dimensions, which are replaced with a single dimension which has size `num_segments`.

<br />

| ### Constructors and Destructors ||
|---|---|
| `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/unsorted-segment-min#classtensorflow_1_1ops_1_1_unsorted_segment_min_1ae09110a9077ca38485a301f9ae09b945(const ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input data, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input segment_ids, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input num_segments)` ||

| ### Public attributes ||
|---|---|
| `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/unsorted-segment-min#classtensorflow_1_1ops_1_1_unsorted_segment_min_1ab42b66ddb9fc903f0cfcddfe78b69c08` | `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation` |
| `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/unsorted-segment-min#classtensorflow_1_1ops_1_1_unsorted_segment_min_1a796647a1e666d85ae64c1250449fafc0` | `::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output` |

| ### Public functions ||
|---|---|
| `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/unsorted-segment-min#classtensorflow_1_1ops_1_1_unsorted_segment_min_1ad0692a88c3ca15e43bfa4c812b16c984() const ` | `::tensorflow::Node *` |
| `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/unsorted-segment-min#classtensorflow_1_1ops_1_1_unsorted_segment_min_1a46d76058fd1e0e8a4990ecce6b5ab032() const ` | ` `` ` |
| `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/unsorted-segment-min#classtensorflow_1_1ops_1_1_unsorted_segment_min_1a2e739c76ea6491258b10031e06bd5a11() const ` | ` `` ` |

## Public attributes

### operation

```
Operation operation
```

### output

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

## Public functions

### UnsortedSegmentMin

```
 UnsortedSegmentMin(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input data,
  ::tensorflow::Input segment_ids,
  ::tensorflow::Input num_segments
)
```

### node

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

### operator::tensorflow::Input

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

### operator::tensorflow::Output

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