TensorFlow 2 version | View source on GitHub |
Computes the sum along sparse segments of a tensor.
tf.sparse.segment_sum(
data, indices, segment_ids, name=None, num_segments=None
)
Read the section on segmentation for an explanation of segments.
Like tf.math.segment_sum
, but segment_ids
can have rank less than data
's
first dimension, selecting a subset of dimension 0, specified by indices
.
segment_ids
is allowed to have missing ids, in which case the output will
be zeros at those indices. In those cases num_segments
is used to determine
the size of the output.
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]]
# With missing segment ids.
tf.sparse.segment_sum(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]]
# 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.math.segment_sum(c, tf.constant([0, 0, 1]))
Args | |
---|---|
data
|
A Tensor with data that will be assembled in the output.
|
indices
|
A 1-D Tensor with indices into data . Has same rank as
segment_ids .
|
segment_ids
|
A 1-D Tensor with indices into the output Tensor . Values
should be sorted and can be repeated.
|
name
|
A name for the operation (optional). |
num_segments
|
An optional int32 scalar. Indicates the size of the output
Tensor .
|
Returns | |
---|---|
A tensor of the shape as data, except for dimension 0 which
has size k , the number of segments specified via num_segments or
inferred for the last element in segments_ids .
|