LU decomposition of a matrix. U matrix has 1's on the diagonals

Question

I am writing code for decomposing a matrix A into the form L U. However, the U Matrix which I get has 1's all on the diagonal. My findings reveal that the variable summ1 is always 0 and that's why the U matrix has 1's on the diagonal. The algorithm seems okay after cross-checking with the mathematical part. Could someone advise what could be a fix for this? ( I am assuming Lii = Aii )

Output: A =

[1, 2, 3]

[4, 5, 6]

[7, 8, 9]

L =

[1, 0, 0]

[4.0, 5, 0]

[7.0, 8.0, 9]

U =

[1.0, 2.0, 3.0]

[0, 1.0, 1.2]

[0, 0, 1.0]

class Matrix:  
  def __init__(self,row=0,col=0, data=[]):
  assert row * col == len(data) , 'Dimensions do not match'
  self.row = row
  self.col = col  
  self.data = data 

 
  def __repr__(self):
    self.data_modified = [ [self.data[i*self.col + j] for j in range(self.col) ] for in range(self.row) ]

    for i in self.data_modified:
      print(i)
    return ""  

  def __mul__(self,other):
    assert self.col == other.row , 'Dimensions not suitable for Matrix Multiplication'
    list3 = []
    for i in range(self.row):
      for j in range(other.col):
        summ = 0
        for k in range(0,self.col):
          summ += (self.data[i*self.col + k]*other.data[k * other.col + j])
        list3.append(summ)      

A = [1,2,3,4,5,6,7,8,9]
A_row = 3
A_col = 3
L = [ 0 for i in range(A_row * A_col)]
U = [ 0 for i in range(A_row * A_col)]

for i in range(A_row):  
  L[i*A_col + i] = A[i*A_col + i]

for i in range(A_row):
  summ1 = 0
  summ2 = 0

  for j in range(i,A_col):
    for k in range(0,i-1):      
      summ1 += L[i*A_col+k]*U[k*A_col+j]   
    U[i*A_col + j] = ( A[i*A_col + j] - summ1 )/L[i*A_col+i]
    
  for j in range(i):
    for k in range(0,j-1):
      summ2 += L[i*A_col+k]*U[k*A_col+j]    
    L[i*A_col + j] = ( A[i*A_col + j] - summ2 )/U[j*A_col+j]

A1 = Matrix(3,3,A)
print("A=")
print(A1)

L1 = Matrix(3,3,L)
print("L =")
print(L1)

U1= Matrix(3,3,U)
print("U =")
print(U1)

print(L1*U1)