tensorflow::ops::MatrixDiagPartV3

#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,
    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) - offset, and x = 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)).

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 band from each batch.
tf.matrix_diag_part(input, k = (-1, 2))
  ==> [[[0, 3, 8],  # Output shape: (2, 4, 3)
        [2, 7, 6],
        [1, 6, 7],
        [5, 8, 0]],
       [[0, 3, 4],
        [4, 3, 8],
        [5, 2, 7],
        [1, 6, 0]]]
 

# LEFT_RIGHT alignment.
tf.matrix_diag_part(input, k = (-1, 2), align="LEFT_RIGHT")
  ==> [[[3, 8, 0],  # Output shape: (2, 4, 3)
        [2, 7, 6],
        [1, 6, 7],
        [0, 5, 8]],
       [[3, 4, 0],
        [4, 3, 8],
        [5, 2, 7],
        [0, 1, 6]]]
 

# max_diag_len can be shorter than the main diagonal.
tf.matrix_diag_part(input, k = (-2, -1))
  ==> [[[5, 8],
        [9, 0]],
       [[1, 6],
        [5, 0]]]
 

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



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: The extracted diagonal(s). 
    • 








Constructors and Destructors







MatrixDiagPartV3(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input k, ::tensorflow::Input padding_value)








MatrixDiagPartV3(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input k, ::tensorflow::Input padding_value, const MatrixDiagPartV3::Attrs & attrs)













Public attributes







diagonal









operation














Public functions







node() const 




::tensorflow::Node *








operator::tensorflow::Input() const 













operator::tensorflow::Output() const 


















Public static functions







Align(StringPiece x)














Structs







tensorflow::ops::MatrixDiagPartV3::Attrs



Optional attribute setters for MatrixDiagPartV3. 







Public attributes




diagonal


::tensorflow::Output diagonal








operation


Operation operation






Public functions




MatrixDiagPartV3


 MatrixDiagPartV3(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input k,
  ::tensorflow::Input padding_value
)








MatrixDiagPartV3


 MatrixDiagPartV3(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input k,
  ::tensorflow::Input padding_value,
  const MatrixDiagPartV3::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
)