Computes the maximum along segments of a tensor.
tf.math.segment_max( data, segment_ids, name=None )
Read the section on segmentation for an explanation of segments.
Computes a tensor such that \(output_i = \max_j(data_j)\) where max
is over j
such that segment_ids[j] == i
.
If the max 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.segment_max(c, tf.constant([0, 0, 1])) # ==> [[4, 3, 3, 4], # [5, 6, 7, 8]]
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 of data '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 as data . |
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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/r2.3/api_docs/python/tf/math/segment_max