# MatrixDiagPartV2

public final class MatrixDiagPartV2

Returns the batched diagonal part of a batched tensor.

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 &lt;= n+y &lt; M and 0 &lt;= n+x &lt; 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 &lt;= n+y &lt; M and 0 &lt;= n+x &lt; 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) ==&gt; [[1, 6, 7],  # Output shape: (2, 3)
[5, 2, 7]]

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

# A tridiagonal band from each batch.
tf.matrix_diag_part(input, k = (-1, 1))
==&gt; [[[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)
==&gt; [[[4, 9, 9],  # Output shape: (2, 3, 3)
[3, 8, 9],
[2, 7, 6]],
[[2, 9, 9],
[3, 4, 9],
[4, 3, 8]]]
``````

### Public Methods

 Output asOutput() Returns the symbolic handle of a tensor. static MatrixDiagPartV2 create(Scope scope, Operand input, Operand k, Operand paddingValue) Factory method to create a class wrapping a new MatrixDiagPartV2 operation. Output diagonal() The extracted diagonal(s).

## Public Methods

#### public Output<T> asOutput()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

#### public static MatrixDiagPartV2<T> create(Scope scope, Operand<T> input, Operand<Integer> k, Operand<T> paddingValue)

Factory method to create a class wrapping a new MatrixDiagPartV2 operation.

##### Parameters
scope current scope Rank `r` tensor where `r >= 2`. 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]`. The value to fill the area outside the specified diagonal band with. Default is 0.
##### Returns
• a new instance of MatrixDiagPartV2

#### public Output<T> diagonal()

The extracted diagonal(s).

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