tf.sparse.retain

Computes the sum along sparse segments of a tensor divided by the sqrt(N).

tf.sparse.segment_sqrt_n(
    data, indices, segment_ids, num_segments=None, name=None
)

Read the section on segmentation for an explanation of segments.

Like tf.sparse.segment_mean, but instead of dividing by the size of the segment, N, divide by sqrt(N) instead.

Args
`data`	A `Tensor` with data that will be assembled in the output.
`indices`	A 1-D `Tensor` with indices into `data`. Has same rank as `segment_ids`.
`segment_ids`	A 1-D `Tensor` with indices into the output `Tensor`. Values should be sorted and can be repeated.
`num_segments`	An optional int32 scalar. Indicates the size of the output `Tensor`.
`name`	A name for the operation (optional).

Returns
A `tensor` of the shape as data, except for dimension 0 which has size `k`, the number of segments specified via `num_segments` or inferred for the last element in `segments_ids`.

TensorFlow

tf.sparse / retain

Args

Returns

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 / retain

Args

Returns