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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 | |
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sp_input
|
The input SparseTensor.
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perm
|
A permutation of the dimensions of sp_input.
|
name
|
A name prefix for the returned tensors (optional) |
Returns | |
|---|---|
A transposed SparseTensor.
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Raises | |
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TypeError
|
If sp_input is not a SparseTensor.
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