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# tensorflow:: ops:: DiagPart

``` #include <array_ops.h> ```

Returns the diagonal part of the tensor.

## Summary

This operation returns a tensor with the ``` diagonal ``` part of the ``` input ``` . The ``` diagonal ``` part is computed as follows:

Assume ``` input ``` has dimensions ``` [D1,..., Dk, D1,..., Dk] ``` , then the output is a tensor of rank ``` k ``` with dimensions ``` [D1,..., Dk] ``` where:

``` diagonal[i1,..., ik] = input[i1, ..., ik, i1,..., ik] ``` .

For example:

```# 'input' is [[1, 0, 0, 0]
[0, 2, 0, 0]
[0, 0, 3, 0]
[0, 0, 0, 4]]```

```tf.diag_part(input) ==> [1, 2, 3, 4]
```

Args:

• scope: A Scope object
• input: Rank k tensor where k is even and not zero.

Returns:

• ``` Output ``` : The extracted diagonal.

### Constructors and Destructors

``` DiagPart (const :: tensorflow::Scope & scope, :: tensorflow::Input input) ```

### Public attributes

``` diagonal ```
``` :: tensorflow::Output ```
``` operation ```
``` Operation ```

### Public functions

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

## Public attributes

### diagonal

`::tensorflow::Output diagonal`

### operation

`Operation operation`

## Public functions

### DiagPart

``` DiagPart(
const ::tensorflow::Scope & scope,
::tensorflow::Input input
)```

### node

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

### operator::tensorflow::Input

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

### operator::tensorflow::Output

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