tf.sparse.reorder
bookmark_borderbookmark
Stay organized with collections
Save and categorize content based on your preferences.
Reorders a SparseTensor
into the canonical, row-major ordering.
View aliases
Compat aliases for migration
See
Migration guide for
more details.
tf.compat.v1.sparse.reorder
, tf.compat.v1.sparse_reorder
tf.sparse.reorder(
sp_input, name=None
)
Note that by convention, all sparse ops preserve the canonical ordering
along increasing dimension number. The only time ordering can be violated
is during manual manipulation of the indices and values to add entries.
Reordering does not affect the shape of the SparseTensor
.
For example, if sp_input
has shape [4, 5]
and indices
/ values
:
[0, 3]: b
[0, 1]: a
[3, 1]: d
[2, 0]: c
then the output will be a SparseTensor
of shape [4, 5]
and
indices
/ values
:
[0, 1]: a
[0, 3]: b
[2, 0]: c
[3, 1]: d
Args |
sp_input
|
The input SparseTensor .
|
name
|
A name prefix for the returned tensors (optional)
|
Returns |
A SparseTensor with the same shape and non-empty values, but in
canonical ordering.
|
Raises |
TypeError
|
If sp_input is not a SparseTensor .
|
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 2023-03-17 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2023-03-17 UTC."],[],[]]