SparseSegmentMeanWithNumSegments

public final class SparseSegmentMeanWithNumSegments

Computes the mean along sparse segments of a tensor.

Like `SparseSegmentMean`, but allows missing ids in `segment_ids`. If an id is missing, the `output` tensor at that position will be zeroed.

Read [the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation) for an explanation of segments.

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of the tensor.
static <T extends TNumber> SparseSegmentMeanWithNumSegments<T>
create(Scope scope, Operand<T> data, Operand<? extends TNumber> indices, Operand<? extends TNumber> segmentIds, Operand<? extends TNumber> numSegments)
Factory method to create a class wrapping a new SparseSegmentMeanWithNumSegments operation.
Output<T>
output()
Has same shape as data, except for dimension 0 which has size `num_segments`.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "SparseSegmentMeanWithNumSegments"

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static SparseSegmentMeanWithNumSegments<T> create (Scope scope, Operand<T> data, Operand<? extends TNumber> indices, Operand<? extends TNumber> segmentIds, Operand<? extends TNumber> numSegments)

Factory method to create a class wrapping a new SparseSegmentMeanWithNumSegments operation.

Parameters
scope current scope
indices A 1-D tensor. Has same rank as `segment_ids`.
segmentIds A 1-D tensor. Values should be sorted and can be repeated.
numSegments Should equal the number of distinct segment IDs.
Returns
  • a new instance of SparseSegmentMeanWithNumSegments

public Output<T> output ()

Has same shape as data, except for dimension 0 which has size `num_segments`.