|  TensorFlow 2 version |  View source on GitHub | 
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 | |
|---|---|
| data | A Tensorwith data that will be assembled in the output. | 
| indices | A 1-D Tensorwith indices intodata. Has same rank assegment_ids. | 
| segment_ids | A 1-D Tensorwith indices into the outputTensor. 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 tensorof the shape as data, except for dimension 0 which
has sizek, the number of segments specified vianum_segmentsor
inferred for the last element insegments_ids. |