tensorflow::ops::UnsortedSegmentMin

Computes the minimum along segments of a tensor.

Summary

Read the section on segmentation for an explanation of segments.

This operator is similar to the unsorted segment sum operator found (here). Instead of computing the sum over segments, it computes the minimum such that:

\(output_i = {j...} data_[j...]\) where min is over tuples j... such that segment_ids[j...] == i.

If the minimum is empty for a given segment ID i, it outputs the largest possible value for the specific numeric type, output[i] = numeric_limits::max().

For example:

c = tf.constant([[1,2,3,4], [5,6,7,8], [4,3,2,1]])
tf.unsorted_segment_min(c, tf.constant([0, 1, 0]), num_segments=2)
# ==> [[ 1,  2, 2, 1],
#       [5,  6, 7, 8]]

If the given segment ID i is negative, then the corresponding value is dropped, and will not be included in the result.

Arguments:

• scope: A Scope object
• segment_ids: A tensor whose shape is a prefix of data.shape.

Returns:

• Output: Has same shape as data, except for the first segment_ids.rank dimensions, which are replaced with a single dimension which has size num_segments.

Public attributes

Operation operation

::tensorflow::Output output

 UnsortedSegmentMin(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input data,
  ::tensorflow::Input segment_ids,
  ::tensorflow::Input num_segments
)

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const