How To Construct Square Of Pairwise Difference From A Vector In Tensorflow?

I have a 1D vector having N dimension in TensorFlow, how to construct sum of a pairwise squared difference? Example Input Vector [1,2,3] Output 6 Computed As (1-2)^2+(1-3)^2+(2-3)^

Solution 1:

For pair-wise difference, subtract the input and the transpose of input and take only the upper triangular part, like:

pair_diff = tf.matrix_band_part(a[...,None] - 
                      tf.transpose(a[...,None]), 0, -1)

Then you can square and sum the differences.

Code:

a = tf.constant([1,2,3])
pair_diff = tf.matrix_band_part(a[...,None] - 
                      tf.transpose(a[...,None]), 0, -1)
output = tf.reduce_sum(tf.square(pair_diff))

with tf.Session() as sess:
  print(sess.run(output))
  # 6