tf.raw_ops.SparseSegmentSum

Computes the sum along sparse segments of a tensor.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.SparseSegmentSum

tf.raw_ops.SparseSegmentSum(
    data, indices, segment_ids, name=None
)

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
data	A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64.
indices	A Tensor. Must be one of the following types: int32, int64. A 1-D tensor. Has same rank as segment_ids.
segment_ids	A Tensor. Must be one of the following types: int32, int64. A 1-D tensor. Values should be sorted and can be repeated.
name	A name for the operation (optional).

Returns
A Tensor. Has the same type as data.