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# tensorflow::ops::MatrixSetDiagV3

`#include <array_ops.h>`

Returns a batched matrix tensor with new batched diagonal values.

## Summary

Given `input` and `diagonal`, this operation returns a tensor with the same shape and values as `input`, except for the specified diagonals of the innermost matrices. These will be overwritten by the values in `diagonal`.

`input` has `r+1` dimensions `[I, J, ..., L, M, N]`. When `k` is scalar or `k[0] == k[1]`, `diagonal` has `r` dimensions `[I, J, ..., L, max_diag_len]`. Otherwise, it has `r+1` dimensions `[I, J, ..., L, num_diags, max_diag_len]`. `num_diags` is the number of diagonals, `num_diags = k[1] - k[0] + 1`. `max_diag_len` is the longest diagonal in the range `[k[0], k[1]]`, `max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))`

The output is a tensor of rank `k+1` with dimensions `[I, J, ..., L, M, N]`. If `k` is scalar or `k[0] == k[1]`:

```output[i, j, ..., l, m, n]
= diagonal[i, j, ..., l, n-max(k[1], 0)] ; if n - m == k[1]
input[i, j, ..., l, m, n]              ; otherwise
```

Otherwise,

```output[i, j, ..., l, m, n]
= diagonal[i, j, ..., l, diag_index, index_in_diag] ; if k[0] <= d <= k[1]
input[i, j, ..., l, m, n]                         ; otherwise
```
where `d = n - m`, `diag_index = k[1] - d`, and `index_in_diag = n - max(d, 0) + offset`.

`offset` is zero except when the alignment of the diagonal is to the right.

```offset = max_diag_len - diag_len(d) ; if (`align` in {RIGHT_LEFT, RIGHT_RIGHT}
and `d >= 0`) or
(`align` in {LEFT_RIGHT, RIGHT_RIGHT}
and `d <= 0`)
0                          ; otherwise
```
where `diag_len(d) = min(cols - max(d, 0), rows + min(d, 0))`.

For example:

```# The main diagonal.
input = np.array([[[7, 7, 7, 7],              # Input shape: (2, 3, 4)
[7, 7, 7, 7],
[7, 7, 7, 7]],
[[7, 7, 7, 7],
[7, 7, 7, 7],
[7, 7, 7, 7]]])
diagonal = np.array([[1, 2, 3],               # Diagonal shape: (2, 3)
[4, 5, 6]])
tf.matrix_set_diag(input, diagonal)
==> [[[1, 7, 7, 7],  # Output shape: (2, 3, 4)
[7, 2, 7, 7],
[7, 7, 3, 7]],
[[4, 7, 7, 7],
[7, 5, 7, 7],
[7, 7, 6, 7]]]```

```# A superdiagonal (per batch).
tf.matrix_set_diag(input, diagonal, k = 1)
==> [[[7, 1, 7, 7],  # Output shape: (2, 3, 4)
[7, 7, 2, 7],
[7, 7, 7, 3]],
[[7, 4, 7, 7],
[7, 7, 5, 7],
[7, 7, 7, 6]]]```

```# A band of diagonals.
diagonals = np.array([[[0, 9, 1],  # Diagonal shape: (2, 4, 3)
[6, 5, 8],
[1, 2, 3],
[4, 5, 0]],
[[0, 1, 2],
[5, 6, 4],
[6, 1, 2],
[3, 4, 0]]])
tf.matrix_set_diag(input, diagonals, k = (-1, 2))
==> [[[1, 6, 9, 7],  # Output shape: (2, 3, 4)
[4, 2, 5, 1],
[7, 5, 3, 8]],
[[6, 5, 1, 7],
[3, 1, 6, 2],
[7, 4, 2, 4]]]```

```# LEFT_RIGHT alignment.
diagonals = np.array([[[9, 1, 0],  # Diagonal shape: (2, 4, 3)
[6, 5, 8],
[1, 2, 3],
[0, 4, 5]],
[[1, 2, 0],
[5, 6, 4],
[6, 1, 2],
[0, 3, 4]]])
tf.matrix_set_diag(input, diagonals, k = (-1, 2), align="LEFT_RIGHT")
==> [[[1, 6, 9, 7],  # Output shape: (2, 3, 4)
[4, 2, 5, 1],
[7, 5, 3, 8]],
[[6, 5, 1, 7],
[3, 1, 6, 2],
[7, 4, 2, 4]]]```

Args:

• scope: A Scope object
• input: Rank `r+1`, where `r >= 1`.
• diagonal: Rank `r` when `k` is an integer or `k[0] == k[1]`. Otherwise, it has rank `r+1`. `k >= 1`.
• 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]`.

Optional attributes (see `Attrs`):

• align: Some diagonals are shorter than `max_diag_len` and need to be padded. `align` is a string specifying how superdiagonals and subdiagonals should be aligned, respectively. There are four possible alignments: "RIGHT_LEFT" (default), "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals to the right (left-pads the row) and subdiagonals to the left (right-pads the row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is the opposite alignment.

Returns:

• `Output`: Rank `r+1`, with `output.shape = input.shape`.

### Constructors and Destructors

`MatrixSetDiagV3(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input diagonal, ::tensorflow::Input k)`
`MatrixSetDiagV3(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input diagonal, ::tensorflow::Input k, const MatrixSetDiagV3::Attrs & attrs)`

### Public attributes

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

### Public functions

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

### Public static functions

`Align(StringPiece x)`
`Attrs`

### Structs

tensorflow::ops::MatrixSetDiagV3::Attrs

Optional attribute setters for MatrixSetDiagV3.

## Public attributes

### operation

`Operation operation`

### output

`::tensorflow::Output output`

## Public functions

### MatrixSetDiagV3

``` MatrixSetDiagV3(
const ::tensorflow::Scope & scope,
::tensorflow::Input input,
::tensorflow::Input diagonal,
::tensorflow::Input k
)```

### MatrixSetDiagV3

``` MatrixSetDiagV3(
const ::tensorflow::Scope & scope,
::tensorflow::Input input,
::tensorflow::Input diagonal,
::tensorflow::Input k,
const MatrixSetDiagV3::Attrs & attrs
)```

### node

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

### operator::tensorflow::Input

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

### operator::tensorflow::Output

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

## Public static functions

### Align

```Attrs Align(
StringPiece x
)```
[]
[]