Demo of implementation "attention" in tensorflow

tf_attention.py

import tensorflow as tf

def tf_attention():
    a = tf.constant([[2,3],[4,5]])
    b = tf.constant([[[1,1,1],[2,2,2]],[[3,3,3],[4,4,4]]])
    ##
    #what we want is: [[[2,2,2],[6,6,6]],[[12,12,12],[20,20,20]]]
    #then sum it over dimension-1 to get: [[ 8  8  8], [32 32 32]]
    ##
    d = tf.expand_dims(a, 2)
    e = tf.tile(d,[1,1,3])
    # two ways of element-wise muliplication.
    #c = tf.multiply(b, e)
    c = b*e
    f = tf.reduce_sum(c, axis=1)
    with tf.Session() as sess:
        print(sess.run(e))
        print(sess.run(c))
        print(sess.run(f))

if __name__ == '__main__':
    tf_attention()