TensorFlow 2 version | View source on GitHub |
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 .
|