MatrixDiagPart

public final class MatrixDiagPart

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 <= n+y < M and 0 <= n+x < N,
     padding_value                 ; otherwise.
 
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,
     padding_value                 ; otherwise.
 
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]]]
 

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output <T>
asOutput ()
Returns the symbolic handle of the tensor.
static <T extends TType > MatrixDiagPart <T>
create ( Scope scope, Operand <T> input, Operand < TInt32 > k, Operand <T> paddingValue)
Factory method to create a class wrapping a new MatrixDiagPart operation.
Output <T>
diagonal ()
The extracted diagonal(s).

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "MatrixDiagPartV2"

Public Methods

public Output <T> asOutput ()

Returns the symbolic handle of the 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 MatrixDiagPart <T> create ( Scope scope, Operand <T> input, Operand < TInt32 > k, Operand <T> paddingValue)

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

Parameters
scope current scope
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]`.
paddingValue The value to fill the area outside the specified diagonal band with. Default is 0.
Returns
  • a new instance of MatrixDiagPart

public Output <T> diagonal ()

The extracted diagonal(s).