Computes the minimum along segments of a tensor.
tf.math.segment_min(
    data, segment_ids, name=None
)
  Read the section on segmentation for an explanation of segments.
Computes a tensor such that \(output_i = \min_j(data_j)\) where min is over j such that segment_ids[j] == i.
If the min is empty for a given segment ID i, output[i] = 0.
c = tf.constant([[1,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.math.segment_min(c, tf.constant([0, 0, 1])).numpy()
array([[1, 2, 2, 1],
       [5, 6, 7, 8]], dtype=int32)
  
| Args | |
|---|---|
| data | A Tensor. Must be one of the following types:float32,float64,int32,uint8,int16,int8,int64,bfloat16,uint16,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_min