TensorFlow 2 version
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View source on GitHub
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Computes the mean along sparse segments of a tensor.
tf.sparse.segment_mean(
data, indices, segment_ids, name=None, num_segments=None
)
Read the section on segmentation for an explanation of segments.
Like tf.math.segment_mean, 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.
Args | |
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data
|
A Tensor with data that will be assembled in the output.
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indices
|
A 1-D Tensor with indices into data. Has same rank as
segment_ids.
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segment_ids
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A 1-D Tensor with indices into the output Tensor. Values
should be sorted and can be repeated.
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name
|
A name for the operation (optional). |
num_segments
|
An optional int32 scalar. Indicates the size of the output
Tensor.
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Returns | |
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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.
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