Computes the mean along sparse segments of a tensor.
tf.compat.v1.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 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. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/compat/v1/sparse_segment_mean