TensorFlow 2 version |
Computes the sum along segments of a tensor.
tf.math.unsorted_segment_sum(
data, segment_ids, num_segments, name=None
)
Read the section on segmentation for an explanation of segments.
Computes a tensor such that
\(output[i] = \sum_{j...} data[j...]\) where the sum is over tuples j...
such
that segment_ids[j...] == i
. Unlike SegmentSum
, segment_ids
need not be sorted and need not cover all values in the full
range of valid values.
If the sum is empty for a given segment ID i
, output[i] = 0
.
If the given segment ID i
is negative, the value is dropped and will not be
added to the sum of the segment.
num_segments
should equal the number of distinct segment IDs.
c = tf.constant([[1,2,3,4], [5,6,7,8], [4,3,2,1]])
tf.unsorted_segment_sum(c, tf.constant([0, 1, 0]), num_segments=2)
# ==> [[ 5, 5, 5, 5],
# [5, 6, 7, 8]]
Args | |
---|---|
data
|
A Tensor . Must be one of the following types: float32 , float64 , int32 , uint8 , int16 , int8 , complex64 , int64 , qint8 , quint8 , qint32 , bfloat16 , uint16 , complex128 , half , uint32 , uint64 .
|
segment_ids
|
A Tensor . Must be one of the following types: int32 , int64 .
A tensor whose shape is a prefix of data.shape .
|
num_segments
|
A Tensor . Must be one of the following types: int32 , int64 .
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A Tensor . Has the same type as data .
|