Attend the Women in ML Symposium on December 7
Stay organized with collections Save and categorize content based on your preferences.

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,
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) - 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]]]

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)

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,
)

MatrixDiagPartV3

MatrixDiagPartV3(
const ::tensorflow::Scope & scope,
::tensorflow::Input input,
::tensorflow::Input k,
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
)
[{ "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" }]