tf.raw_ops.UnsortedSegmentSum

Computes the sum along segments of a tensor.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.UnsortedSegmentSum

tf.raw_ops.UnsortedSegmentSum(
    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.

Caution: On CPU, values in segment_ids are always validated to be less than num_segments, and an error is thrown for out-of-bound indices. On GPU, this does not throw an error for out-of-bound indices. On Gpu, out-of-bound indices result in safe but unspecified behavior, which may include ignoring out-of-bound indices or outputting a tensor with a 0 stored in the first dimension of its shape if num_segments is 0.

c = [[1,2,3,4], [5,6,7,8], [4,3,2,1]]
tf.math.unsorted_segment_sum(c, [0, 1, 0], num_segments=2).numpy()
array([[5, 5, 5, 5],
       [5, 6, 7, 8]], dtype=int32)

Args
data	A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, qint16, quint16, uint16, complex128, half, uint32, uint64.
segment_ids	A Tensor. Must be one of the following types: int16, int32, int64. A tensor whose shape is a prefix of data.shape. The values must be less than num_segments. Caution: The values are always validated to be in range on CPU, never validated on GPU.
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.