|  TensorFlow 1 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_inputis not aSparseTensor. |