# tensorflow::ops::MatrixDiagPartV2

`#include <array_ops.h>`

Returns the batched diagonal part of a batched tensor.

## Summary

Returns a tensor with the `k[0]`-th to `k[1]`-th diagonals of the batched `input`.

Assume `input` has `r` dimensions `[I, J, ..., L, M, N]`. Let `max_diag_len` be the maximum length among all diagonals to be extracted, `max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))` Let `num_diags` be the number of diagonals to extract, `num_diags = k[1] - k[0] + 1`.

If `num_diags == 1`, the output tensor is of rank `r - 1` with shape `[I, J, ..., L, max_diag_len]` and values:

```diagonal[i, j, ..., l, n]
= input[i, j, ..., l, n+y, n+x] ; if 0 <= n+y < M and 0 <= n+x < N,
```
where `y = max(-k[1], 0)`, `x = max(k[1], 0)`.

Otherwise, the output tensor has rank `r` with dimensions `[I, J, ..., L, num_diags, max_diag_len]` with values:

```diagonal[i, j, ..., l, m, n]
= input[i, j, ..., l, n+y, n+x] ; if 0 <= n+y < M and 0 <= n+x < N,
```
where `d = k[1] - m`, `y = max(-d, 0)`, and `x = max(d, 0)`.

The input must be at least a matrix.

For example:

```input = np.array([[[1, 2, 3, 4],  # Input shape: (2, 3, 4)
[5, 6, 7, 8],
[9, 8, 7, 6]],
[[5, 4, 3, 2],
[1, 2, 3, 4],
[5, 6, 7, 8]]])```

```# A main diagonal from each batch.
tf.matrix_diag_part(input) ==> [[1, 6, 7],  # Output shape: (2, 3)
[5, 2, 7]]```

```# A superdiagonal from each batch.
tf.matrix_diag_part(input, k = 1)
==> [[2, 7, 6],  # Output shape: (2, 3)
[4, 3, 8]]```

```# A tridiagonal band from each batch.
tf.matrix_diag_part(input, k = (-1, 1))
==> [[[2, 7, 6],  # Output shape: (2, 3, 3)
[1, 6, 7],
[5, 8, 0]],
[[4, 3, 8],
[5, 2, 7],
[1, 6, 0]]]```

```# Padding value = 9
tf.matrix_diag_part(input, k = (1, 3), padding_value = 9)
==> [[[4, 9, 9],  # Output shape: (2, 3, 3)
[3, 8, 9],
[2, 7, 6]],
[[2, 9, 9],
[3, 4, 9],
[4, 3, 8]]]
```

Arguments:

• scope: A Scope object
• input: Rank `r` tensor where `r >= 2`.
• k: Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main diagonal, and negative value means subdiagonals. `k` can be a single integer (for a single diagonal) or a pair of integers specifying the low and high ends of a matrix band. `k[0]` must not be larger than `k[1]`.
• padding_value: The value to fill the area outside the specified diagonal band with. Default is 0.

Returns:

• `Output`: The extracted diagonal(s).

### Constructors and Destructors

`MatrixDiagPartV2(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input k, ::tensorflow::Input padding_value)`

### 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

### MatrixDiagPartV2

``` MatrixDiagPartV2(
const ::tensorflow::Scope & scope,
::tensorflow::Input input,
::tensorflow::Input k,
`::tensorflow::Node * node() const `
` operator::tensorflow::Input() const `
` operator::tensorflow::Output() const `