tensorflow::
ops::
MatrixSetDiagV2
#include <array_ops.h>
Returns a batched matrix tensor with new batched diagonal values.
Summary
Given
input
and
diagonal
, this operation returns a tensor with the same shape and values as
input
, except for the specified diagonals of the innermost matrices. These will be overwritten by the values in
diagonal
.
input
has
r+1
dimensions
[I, J, ..., L, M, N]
. When
k
is scalar or
k[0] == k[1]
,
diagonal
has
r
dimensions
[I, J, ..., L, max_diag_len]
. Otherwise, it has
r+1
dimensions
[I, J, ..., L, num_diags, max_diag_len]
.
num_diags
is the number of diagonals,
num_diags = k[1] - k[0] + 1
.
max_diag_len
is the longest diagonal in the range
[k[0], k[1]]
,
max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))
The output is a tensor of rank
k+1
with dimensions
[I, J, ..., L, M, N]
. If
k
is scalar or
k[0] == k[1]
:
output[i, j, ..., l, m, n] = diagonal[i, j, ..., l, n-max(k[1], 0)] ; if n - m == k[1] input[i, j, ..., l, m, n] ; otherwise
Otherwise,
output[i, j, ..., l, m, n] = diagonal[i, j, ..., l, diag_index, index_in_diag] ; if k[0] <= d <= k[1] input[i, j, ..., l, m, n] ; otherwise
d = n - m
,
diag_index = k[1] - d
, and
index_in_diag = n - max(d, 0)
.
For example:
# The main diagonal. input = np.array([[[7, 7, 7, 7], # Input shape: (2, 3, 4) [7, 7, 7, 7], [7, 7, 7, 7]], [[7, 7, 7, 7], [7, 7, 7, 7], [7, 7, 7, 7]]]) diagonal = np.array([[1, 2, 3], # Diagonal shape: (2, 3) [4, 5, 6]]) tf.matrix_set_diag(diagonal) ==> [[[1, 7, 7, 7], # Output shape: (2, 3, 4) [7, 2, 7, 7], [7, 7, 3, 7]], [[4, 7, 7, 7], [7, 5, 7, 7], [7, 7, 6, 7]]]
# A superdiagonal (per batch). tf.matrix_set_diag(diagonal, k = 1) ==> [[[7, 1, 7, 7], # Output shape: (2, 3, 4) [7, 7, 2, 7], [7, 7, 7, 3]], [[7, 4, 7, 7], [7, 7, 5, 7], [7, 7, 7, 6]]]
# A band of diagonals. diagonals = np.array([[[1, 2, 3], # Diagonal shape: (2, 2, 3) [4, 5, 0]], [[6, 1, 2], [3, 4, 0]]]) tf.matrix_set_diag(diagonals, k = (-1, 0)) ==> [[[1, 7, 7, 7], # Output shape: (2, 3, 4) [4, 2, 7, 7], [0, 5, 3, 7]], [[6, 7, 7, 7], [3, 1, 7, 7], [7, 4, 2, 7]]]
Args:
- scope: A Scope object
-
input: Rank
r+1
, wherer >= 1
. -
diagonal: Rank
r
whenk
is an integer ork[0] == k[1]
. Otherwise, it has rankr+1
.k >= 1
. -
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 thank[1]
.
Returns:
-
Output
: Rankr+1
, withoutput.shape = input.shape
.
Constructors and Destructors |
|
---|---|
MatrixSetDiagV2
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
input, ::
tensorflow::Input
diagonal, ::
tensorflow::Input
k)
|
Public attributes |
|
---|---|
operation
|
|
output
|
Public functions |
|
---|---|
node
() const
|
::tensorflow::Node *
|
operator::tensorflow::Input
() const
|
|
operator::tensorflow::Output
() const
|
|
Public attributes
Public functions
MatrixSetDiagV2
MatrixSetDiagV2( const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input diagonal, ::tensorflow::Input k )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const