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# tensorflow::ops::SegmentMean

`#include <math_ops.h>`

Computes the mean along segments of a tensor.

## Summary

Read the section on segmentation for an explanation of segments.

Computes a tensor such that \(output_i = { data_j}{N}\) where `mean` is over `j` such that `segment_ids[j] == i` and `N` is the total number of values summed.

If the mean is empty for a given segment ID `i`, `output[i] = 0`.

For example:

```c = tf.constant([[1.0,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.segment_mean(c, tf.constant([0, 0, 1]))
# ==> [[2.5, 2.5, 2.5, 2.5],
#      [5, 6, 7, 8]]
```

Arguments:

• scope: A Scope object
• segment_ids: A 1-D tensor whose size is equal to the size of `data`'s first dimension. Values should be sorted and can be repeated.

Returns:

• `Output`: Has same shape as data, except for dimension 0 which has size `k`, the number of segments.

### Constructors and Destructors

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

### Public attributes

`operation`
`Operation`
`output`
`::tensorflow::Output`

### Public functions

`node() const `
`::tensorflow::Node *`
`operator::tensorflow::Input() const `
``` ```
``` ```
`operator::tensorflow::Output() const `
``` ```
``` ```

## Public attributes

### operation

`Operation operation`

### output

`::tensorflow::Output output`

## Public functions

### SegmentMean

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

### node

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

### operator::tensorflow::Input

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

### operator::tensorflow::Output

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