tf.sparse_reorder
tf.sparse_reorder
tf.sparse_reorder
sparse_reorder( sp_input, name=None )
Defined in tensorflow/python/ops/sparse_ops.py
.
See the guide: Sparse Tensors > Manipulation
Reorders a SparseTensor
into the canonical, row-major ordering.
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 inputSparseTensor
. -
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
: Ifsp_input
is not aSparseTensor
.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/sparse_reorder