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tensorflow::
ops::
DiagPart
#include <array_ops.h>
Returns the diagonal part of the tensor.
Summary
This operation returns a tensor with the
diagonal
part of the
input
. The
diagonal
part is computed as follows:
Assume
input
has dimensions
[D1,..., Dk, D1,..., Dk]
, then the output is a tensor of rank
k
with dimensions
[D1,..., Dk]
where:
diagonal[i1,..., ik] = input[i1, ..., ik, i1,..., ik]
.
For example:
# 'input' is [[1, 0, 0, 0]
[0, 2, 0, 0]
[0, 0, 3, 0]
[0, 0, 0, 4]]
tf.diag_part(input) ==> [1, 2, 3, 4]
Args:
-
scope: A
Scope
object
-
input: Rank k tensor where k is even and not zero.
Returns:
-
Output
: The extracted diagonal.
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2021-08-16 UTC.
[null,null,["Last updated 2021-08-16 UTC."],[],[],null,["# tensorflow::ops::DiagPart Class Reference\n\ntensorflow::\nops::\nDiagPart\n===========================\n\n`\n#include \u003carray_ops.h\u003e\n`\n\n\nReturns the diagonal part of the tensor.\n\nSummary\n-------\n\n\nThis operation returns a tensor with the\n`\ndiagonal\n`\npart of the\n`\ninput\n`\n. The\n`\ndiagonal\n`\npart is computed as follows:\n\n\nAssume\n`\ninput\n`\nhas dimensions\n`\n[D1,..., Dk, D1,..., Dk]\n`\n, then the output is a tensor of rank\n`\nk\n`\nwith dimensions\n`\n[D1,..., Dk]\n`\nwhere:\n\n\n`\ndiagonal[i1,..., ik] = input[i1, ..., ik, i1,..., ik]\n`\n.\n\n\nFor example:\n\n\n```text\n# 'input' is [[1, 0, 0, 0]\n [0, 2, 0, 0]\n [0, 0, 3, 0]\n [0, 0, 0, 4]]\n```\n\n\u003cbr /\u003e\n\n\n```scdoc\ntf.diag_part(input) ==\u003e [1, 2, 3, 4]\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 k tensor where k is even and not zero.\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 ` : The extracted diagonal.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| ` `[DiagPart](#classtensorflow_1_1ops_1_1_diag_part_1a722e0fbf9139d42128d88361fcceffbb)` (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) ` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|\n| ` `[diagonal](#classtensorflow_1_1ops_1_1_diag_part_1a5c2700969d74c5dcd441f482f69f0575)` ` | ` :: `[tensorflow::Output](/versions/r2.6/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n| ` `[operation](#classtensorflow_1_1ops_1_1_diag_part_1a4a4d8b4387110108a77726a4e37f75ef)` ` | ` `[Operation](/versions/r2.6/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n\n| ### Public functions ||\n|-------------------------------------------------------------------------------------------------------------------------|--------------------------|\n| ` `[node](#classtensorflow_1_1ops_1_1_diag_part_1a7f5dfaa792daf4eebe39b740aaa5a117)` () const ` | ` ::tensorflow::Node * ` |\n| ` `[operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_diag_part_1aef16d4b10102516c099741c0935952e9)` () const ` | ` ` |\n| ` `[operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_diag_part_1a3ffd8291e65d1b66c89fbcc0bb34225e)` () const ` | ` ` |\n\nPublic attributes\n-----------------\n\n### diagonal\n\n```text\n::tensorflow::Output diagonal\n``` \n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### DiagPart\n\n```gdscript\n DiagPart(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input\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```"]]
