Computes the sum along sparse segments of a tensor.
Like `SparseSegmentSum`, 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/sparse#Segmentation) for an explanation of segments.
For example:
c = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])
tf.sparse_segment_sum_with_num_segments(
c, tf.constant([0, 1]), tf.constant([0, 0]), num_segments=3)
# => [[0 0 0 0]
# [0 0 0 0]
# [0 0 0 0]]
tf.sparse_segment_sum_with_num_segments(c,
tf.constant([0, 1]),
tf.constant([0, 2],
num_segments=4))
# => [[ 1 2 3 4]
# [ 0 0 0 0]
# [-1 -2 -3 -4]
# [ 0 0 0 0]]
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> SparseSegmentSumWithNumSegments<T> | |
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
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 SparseSegmentSumWithNumSegments<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 SparseSegmentSumWithNumSegments 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 SparseSegmentSumWithNumSegments
public Output<T> output ()
Has same shape as data, except for dimension 0 which has size `num_segments`.