tensorflow:: ops:: SparseSegmentSum

Computes the sum along sparse segments of a tensor.

Summary

Read the section on 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]))

Args:

• scope: A Scope object
• indices: A 1-D tensor. Has same rank as segment_ids .
• segment_ids: A 1-D tensor. Values should be sorted and can be repeated.

Returns:

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

Public attributes

Operation operation

::tensorflow::Output output

Public functions

 SparseSegmentSum(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input data,
  ::tensorflow::Input indices,
  ::tensorflow::Input segment_ids
)

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const