PySparNN custom distance different outputs

pysparnn_outputs

# In[5]:
B = sparse.csr_matrix([[1, 1, 1],[1, 1, 1],[1, 1, 1]])
A = sparse.csr_matrix(
[
    [2, 2, 1],
    [1, 0, 1],
    [1, 1, 1]
])

# In[6]:
u_dist = UserCustomDistance(A, range(A.shape[0]))
u_dist._distance(A)
# Out[6]: 
array([[-2.,  1.,  0.],
       [ 1.,  1.,  1.],
       [ 0.,  1.,  0.]])

# In[7]:
su_dist = SpencerUserCustomDistance(A, range(A.shape[0]))
su_dist._distance(A)
# Out[7]: 
array([[-6,  0, -2],
       [ 0,  1,  1],
       [-2,  1,  0]])
       
# In [8]:
u_dist._distance(B)
Out[8]: 
array([[ 0.,  1.,  0.],
       [ 0.,  1.,  0.],
       [ 0.,  1.,  0.]])

# In [9]:
su_dist._distance(B)
Out[9]: 
array([[-2,  1,  0],
       [-2,  1,  0],
       [-2,  1,  0]])