Google I/O is a wrap! Catch up on TensorFlow sessions

# 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]]]
```

Args:

• 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,
)```

### node

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

### operator::tensorflow::Input

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

### operator::tensorflow::Output

` operator::tensorflow::Output() const `
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]