tensorflow::ops::SegmentMean

Computes the mean along segments of a tensor.

Summary

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.

For example:

c = tf.constant([[1.0,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.segment_mean(c, tf.constant([0, 0, 1]))
# ==> [[2.5, 2.5, 2.5, 2.5],
#      [5, 6, 7, 8]]

Args:

• scope: A Scope object
• segment_ids: A 1-D tensor whose size is equal to the size of data's first dimension. Values should be sorted and can be repeated.

Returns:

• Output: Has same shape as data, except for dimension 0 which has size k, the number of segments.

Public attributes

Operation operation

::tensorflow::Output output

Public functions

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

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const