tf.sparse.reorder | TensorFlow v2.16.1 (original) (raw)
tf.sparse.reorder
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Reorders a SparseTensor into the canonical, row-major ordering.
View aliases
Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.sparse.reorder, tf.compat.v1.sparse_reorder
tf.sparse.reorder(
sp_input, name=None
)
Used in the notebooks
| Used in the tutorials |
|---|
| Client-efficient large-model federated learning via `federated_select` and sparse aggregation |
Note that by convention, all sparse ops preserve the canonical ordering along increasing dimension number. The only time ordering can be violated is during manual manipulation of the indices and values to add entries.
Reordering does not affect the shape of the SparseTensor.
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 [4, 5] andindices / values:
[0, 1]: a
[0, 3]: b
[2, 0]: c
[3, 1]: d
| Args | |
|---|---|
| sp_input | The input SparseTensor. |
| name | A name prefix for the returned tensors (optional) |
| Returns |
|---|
| A SparseTensor with the same shape and non-empty values, but in canonical ordering. |
| Raises | |
|---|---|
| TypeError | If sp_input is not a SparseTensor. |