Computes the mean along segments of a tensor.
tf.math.segment_mean(
    data, segment_ids, name=None
)
  Read the section on segmentation for an explanation of segments.
Computes a tensor such that \(output_i = \frac{\sum_j data_j}{N}\) where mean is over j such that segment_ids[j] == i and N is the total number of values summed.
If the mean is empty for a given segment ID i, output[i] = 0.
c = tf.constant([[1.0,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.math.segment_mean(c, tf.constant([0, 0, 1])).numpy()
array([[2.5, 2.5, 2.5, 2.5],
       [5., 6., 7., 8.]], dtype=float32)
  
| Args | |
|---|---|
| data | 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. | 
| segment_ids | A Tensor. Must be one of the following types:int32,int64. A 1-D tensor whose size is equal to the size ofdata's first dimension. Values should be sorted and can be repeated. | 
| name | A name for the operation (optional). | 
| Returns | |
|---|---|
| A Tensor. Has the same type asdata. | 
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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/math/segment_mean