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Transposes a SparseTensor
tf.sparse.transpose( sp_input, perm=None, name=None )
The returned tensor's dimension i will correspond to the input dimension perm[i]
. If perm
is not given, it is set to (n-1...0), where n is the rank of the input tensor. Hence by default, this operation performs a regular matrix transpose on 2-D input Tensors.
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 [5, 4]
and indices
/ values
:
[0, 2]: c [1, 0]: a [1, 3]: d [3, 0]: b
Args | |
---|---|
sp_input | The input SparseTensor . |
perm | A permutation of the dimensions of sp_input . |
name | A name prefix for the returned tensors (optional) |
Returns | |
---|---|
A transposed SparseTensor . |
Raises | |
---|---|
TypeError | If sp_input is not a SparseTensor . |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/sparse/transpose