tf.sparse.transpose
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 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/sparse/transpose