test_boundary_optimization.py 文件源码

def create_cost_soft_min_distance(self, c, s):
  """Creates a soft-min distance of the centers to the points"""
  c_shape = c.get_shape().as_list();        
  s_shape = s.get_shape().as_list();

  #expand matrices
  cc = tf.reshape(c, [c_shape[0], c_shape[1], 1]);    
  ss = tf.reshape(s, [s_shape[0], s_shape[1], 1]);
  ss = tf.transpose(ss, perm = [0,2,1]);
  cc = tf.tile(cc, [1, 1, s_shape[0]]);
  ss = tf.tile(ss, [c_shape[0], 1, 1]);

  #pairwise distances
  dist2 = tf.sqrt(tf.reduce_sum(tf.squared_difference(cc,ss), reduction_indices = 1));
  dist2 = tf.reduce_mean(dist2, reduction_indices=0); # hack: get rid of batches here 

  #softmin
  return tf.reduce_sum(tf.mul(tf.nn.softmax(tf.scalar_mul(tf.constant(-1.0,"float32"), dist2)), dist2),reduction_indices = 0);