tf.sparse.to

TensorFlow 1 version

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Transposes a SparseTensor

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.sparse.transpose, tf.compat.v1.sparse_transpose

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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tf.sparse / to_dense

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Args

Returns

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