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TensorFlow 1 version
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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 | |
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data
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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.
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segment_ids
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A Tensor. Must be one of the following types: int32, int64.
A tensor whose shape is a prefix of data.shape.
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num_segments
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A Tensor. Must be one of the following types: int32, int64.
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name
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A name for the operation (optional). |
Returns | |
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A Tensor. Has the same type as data.
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