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tf.sparse_transpose

tf.sparse_transpose(
    sp_input,
    perm=None,
    name=None
)

Defined in tensorflow/python/ops/sparse_ops.py.

See the guide: Sparse Tensors > Manipulation

Transposes a SparseTensor

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.

© 2018 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/api_docs/python/tf/sparse_transpose