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# tensorflow:: ops:: MatrixDiagPart

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

Returns the batched diagonal part of a batched tensor.

## Summary

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

Assume ``` input ``` has ``` k ``` dimensions ``` [I, J, K, ..., M, N] ``` , then the output is a tensor of rank ``` k - 1 ``` with dimensions ``` [I, J, K, ..., min(M, N)] ``` where:

``` diagonal[i, j, k, ..., n] = input[i, j, k, ..., n, n] ``` .

The input must be at least a matrix.

For example:

```# 'input' is [[[1, 0, 0, 0]
[0, 2, 0, 0]
[0, 0, 3, 0]
[0, 0, 0, 4]],
[[5, 0, 0, 0]
[0, 6, 0, 0]
[0, 0, 7, 0]
[0, 0, 0, 8]]]```

`and input.shape = (2, 4, 4)`

`tf.matrix_diag_part(input) ==> [[1, 2, 3, 4], [5, 6, 7, 8]]`

```which has shape (2, 4)
```

Args:

• scope: A Scope object
• input: Rank ``` k ``` tensor where ``` k >= 2 ``` .

Returns:

• ``` Output ``` : The extracted diagonal(s) having shape ``` diagonal.shape = input.shape[:-2] + [min(input.shape[-2:])] ``` .

### Constructors and Destructors

``` MatrixDiagPart (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

### MatrixDiagPart

``` MatrixDiagPart(
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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