tf.sparse.reduce

TensorFlow 1 version

View source on GitHub

Reorders a SparseTensor into the canonical, row-major ordering.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.sparse.reorder, tf.compat.v1.sparse_reorder

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`.

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.sparse / reduce_max

View aliases

Args

Returns

Raises