tf.sparse.transpose
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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.  |  
    © 2020 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/versions/r2.3/api_docs/python/tf/sparse/transpose