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tensorflow::
ops::
MatrixSetDiag
#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 main diagonal of the innermost matrices. These will be overwritten by the values in
diagonal
.
The output is computed as follows:
Assume
input
has
k+1
dimensions
[I, J, K, ..., M, N]
and
diagonal
has
k
dimensions
[I, J, K, ..., min(M, N)]
. Then the output is a tensor of rank
k+1
with dimensions
[I, J, K, ..., M, N]
where:
-
output[i, j, k, ..., m, n] = diagonal[i, j, k, ..., n]
for
m == n
.
-
output[i, j, k, ..., m, n] = input[i, j, k, ..., m, n]
for
m != n
.
Args:
-
scope: A
Scope
object
-
input: Rank
k+1
, where
k >= 1
.
-
diagonal: Rank
k
, where
k >= 1
.
Returns:
-
Output
: Rank
k+1
, with
output.shape = input.shape
.
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
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Last updated 2021-08-16 UTC.
[null,null,["Last updated 2021-08-16 UTC."],[],[],null,["# tensorflow::ops::MatrixSetDiag Class Reference\n\ntensorflow::\nops::\nMatrixSetDiag\n================================\n\n`\n#include \u003carray_ops.h\u003e\n`\n\n\nReturns a batched matrix tensor with new batched diagonal values.\n\nSummary\n-------\n\n\nGiven\n`\ninput\n`\nand\n`\ndiagonal\n`\n, this operation returns a tensor with the same shape and values as\n`\ninput\n`\n, except for the main diagonal of the innermost matrices. These will be overwritten by the values in\n`\ndiagonal\n`\n.\n\n\nThe output is computed as follows:\n\n\nAssume\n`\ninput\n`\nhas\n`\nk+1\n`\ndimensions\n`\n[I, J, K, ..., M, N]\n`\nand\n`\ndiagonal\n`\nhas\n`\nk\n`\ndimensions\n`\n[I, J, K, ..., min(M, N)]\n`\n. Then the output is a tensor of rank\n`\nk+1\n`\nwith dimensions\n`\n[I, J, K, ..., M, N]\n`\nwhere:\n\n\n- `\n output[i, j, k, ..., m, n] = diagonal[i, j, k, ..., n]\n ` for `\n m == n\n ` .\n- `\n output[i, j, k, ..., m, n] = input[i, j, k, ..., m, n]\n ` for `\n m != n\n ` .\n\n\u003cbr /\u003e\n\n\nArgs:\n\n- scope: A [Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- input: Rank `\n k+1\n ` , where `\n k \u003e= 1\n ` .\n- diagonal: Rank `\n k\n ` , where `\n k \u003e= 1\n ` .\n\n\u003cbr /\u003e\n\n\nReturns:\n\n- `\n `[Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` : Rank `\n k+1\n ` , with `\n output.shape = input.shape\n ` .\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| ` `[MatrixSetDiag](#classtensorflow_1_1ops_1_1_matrix_set_diag_1af9f6deaf5d71f88356239fd1fceb3bd5)` (const :: `[tensorflow::Scope](/versions/r2.6/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` input, :: `[tensorflow::Input](/versions/r2.6/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` diagonal) ` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|\n| ` `[operation](#classtensorflow_1_1ops_1_1_matrix_set_diag_1ac564fb65fed63cd95c5a876d8cfcb004)` ` | ` `[Operation](/versions/r2.6/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n| ` `[output](#classtensorflow_1_1ops_1_1_matrix_set_diag_1a58d08deb35db4f1602c1df59432ade6c)` ` | ` :: `[tensorflow::Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n\n| ### Public functions ||\n|-------------------------------------------------------------------------------------------------------------------------------|--------------------------|\n| ` `[node](#classtensorflow_1_1ops_1_1_matrix_set_diag_1a20fc7ca0974220bfcd3a3aee08803d6c)` () const ` | ` ::tensorflow::Node * ` |\n| ` `[operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_matrix_set_diag_1af98eee12ae5e443a923b794be760afd7)` () const ` | ` ` |\n| ` `[operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_matrix_set_diag_1adf4b733c12f7c7dc2387318fafff0413)` () const ` | ` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output\n\n```text\n::tensorflow::Output output\n``` \n\nPublic functions\n----------------\n\n### MatrixSetDiag\n\n```gdscript\n MatrixSetDiag(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input diagonal\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n```"]]
