Computes the sum along sparse segments of a tensor.
Read [the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation) for an explanation of segments.
Like `SegmentSum`, but `segment_ids` can have rank less than `data`'s first dimension, selecting a subset of dimension 0, specified by `indices`.
For example:
c = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])
# Select two rows, one segment.
tf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 0]))
# => [[0 0 0 0]]
# Select two rows, two segment.
tf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 1]))
# => [[ 1 2 3 4]
# [-1 -2 -3 -4]]
# Select all rows, two segments.
tf.sparse_segment_sum(c, tf.constant([0, 1, 2]), tf.constant([0, 0, 1]))
# => [[0 0 0 0]
# [5 6 7 8]]
# Which is equivalent to:
tf.segment_sum(c, tf.constant([0, 0, 1]))
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> SparseSegmentSum<T> | |
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
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 SparseSegmentSum<T> create (Scope scope, Operand<T> data, Operand<? extends TNumber> indices, Operand<? extends TNumber> segmentIds)
Factory method to create a class wrapping a new SparseSegmentSum 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. |
Returns
- a new instance of SparseSegmentSum
public Output<T> output ()
Has same shape as data, except for dimension 0 which has size `k`, the number of segments.