tf.sparse.reorder
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Reorders a SparseTensor into the canonical, row-major ordering.
tf.sparse.reorder(
sp_input, name=None
)
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] and
indices / 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.
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.sparse.reorder\n\n\u003cbr /\u003e\n\n|---------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/sparse/reorder) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/ops/sparse_ops.py#L680-L728) |\n\nReorders a `SparseTensor` into the canonical, row-major ordering.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.sparse.reorder`](/api_docs/python/tf/sparse/reorder), [`tf.compat.v1.sparse_reorder`](/api_docs/python/tf/sparse/reorder)\n\n\u003cbr /\u003e\n\n tf.sparse.reorder(\n sp_input, name=None\n )\n\nNote that by convention, all sparse ops preserve the canonical ordering\nalong increasing dimension number. The only time ordering can be violated\nis during manual manipulation of the indices and values to add entries.\n\nReordering does not affect the shape of the `SparseTensor`.\n\nFor example, if `sp_input` has shape `[4, 5]` and `indices` / `values`: \n\n [0, 3]: b\n [0, 1]: a\n [3, 1]: d\n [2, 0]: c\n\nthen the output will be a `SparseTensor` of shape `[4, 5]` and\n`indices` / `values`: \n\n [0, 1]: a\n [0, 3]: b\n [2, 0]: c\n [3, 1]: d\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------|---------------------------------------------------|\n| `sp_input` | The input `SparseTensor`. |\n| `name` | A name prefix for the returned tensors (optional) |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `SparseTensor` with the same shape and non-empty values, but in canonical ordering. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|-------------|----------------------------------------|\n| `TypeError` | If `sp_input` is not a `SparseTensor`. |\n\n\u003cbr /\u003e"]]
TensorFlow 1 version
View source on GitHub