# 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:

<br />

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

<br />

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

<br />

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

<br />

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]]])
```

<br />


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

<br />


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

<br />


```
# 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]]]
```

<br />


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

<br />

Arguments:

- scope: A [Scope](https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_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.

<br />

Returns:

- `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output`: The extracted diagonal(s).

<br />

| ### Constructors and Destructors ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/matrix-diag-part-v2#classtensorflow_1_1ops_1_1_matrix_diag_part_v2_1ad3de7ab4ab1196ff0eb0a0b9712563ef(const ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input input, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input k, ::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input padding_value)` ||

| ### Public attributes ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/matrix-diag-part-v2#classtensorflow_1_1ops_1_1_matrix_diag_part_v2_1a7a8892ae88249cf5f89b97544d71a59c` | `::https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output` |
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/matrix-diag-part-v2#classtensorflow_1_1ops_1_1_matrix_diag_part_v2_1aefc836bb535eab5db669667a152eba42` | `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation` |

| ### Public functions ||
|---|---|
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/matrix-diag-part-v2#classtensorflow_1_1ops_1_1_matrix_diag_part_v2_1a0b20ceb05713921670ce29cf7671a152() const ` | `::tensorflow::Node *` |
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/matrix-diag-part-v2#classtensorflow_1_1ops_1_1_matrix_diag_part_v2_1acb91e8a485455813fcd8d9d3558c793b() const ` | ` `` ` |
| `https://www.tensorflow.org/versions/r2.0/api_docs/cc/class/tensorflow/ops/matrix-diag-part-v2#classtensorflow_1_1ops_1_1_matrix_diag_part_v2_1a18e6d0e922c930c2880112f18f2ac011() 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::Input padding_value
)
```

### node

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

### operator::tensorflow::Input

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

### operator::tensorflow::Output

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