SegmentMean

public final class SegmentMean

Computes the mean along segments of a tensor.

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

Computes a tensor such that \\(output_i = \frac{\sum_j data_j}{N}\\) where `mean` is over `j` such that `segment_ids[j] == i` and `N` is the total number of values summed.

If the mean is empty for a given segment ID `i`, `output[i] = 0`.

For example:

c = tf.constant([[1.0,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
 tf.segment_mean(c, tf.constant([0, 0, 1]))
 # ==> [[2.5, 2.5, 2.5, 2.5],
 #      [5, 6, 7, 8]]
 

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 TType > SegmentMean <T>
create ( Scope scope, Operand <T> data, Operand <? extends TNumber > segmentIds)
Factory method to create a class wrapping a new SegmentMean operation.
Output <T>
output ()
Has same shape as data, except for dimension 0 which has size `k`, the number of segments.

Inherited Methods

Constants

public static final String OP_NAME

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

Constant Value: "SegmentMean"

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 SegmentMean <T> create ( Scope scope, Operand <T> data, Operand <? extends TNumber > segmentIds)

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

Parameters
scope current scope
segmentIds A 1-D tensor whose size is equal to the size of `data`'s first dimension. Values should be sorted and can be repeated.
Returns
  • a new instance of SegmentMean

public Output <T> output ()

Has same shape as data, except for dimension 0 which has size `k`, the number of segments.