How to prevent memory leak when solving a linear system of equations using left_kernel ?

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I am having a problem when running the left_kernel function multiple times. Every time I call the function It takes a new part of the memory although I do not create new variables. I tried finding out where does the memory disappear, but without any luck. here is an example code:

    sage: mat
    69 x 70 dense matrix over Symbolic Ring (type 'print mat.str()' to see all of the entries)
    sage: get_memory_usage() #memory check before call
    1170.34765625
    sage: Inter_mat=mat.transpose() 
    sage: Solution=Inter_mat.left_kernel()
    sage: get_memory_usage() #memory check after 1st call
    1190.5390625
    sage: Inter_mat=mat.transpose()
    sage: Solution=Inter_mat.left_kernel()
    sage: get_memory_usage()  #memory check after 2nd call
    1194.73828125
    sage: Inter_mat=mat.transpose()
    sage: Solution=Inter_mat.left_kernel()
    sage: get_memory_usage()  #memory check after 3rd call
    1217.76953125

As you can see every time I call the function, the memory usage increases. Is there a way to release the memory that was used in a previous call ? My program stops after a few iterations because of lack of memory.

Update: (Creating the matrix "mat")

mat=[]
for Coord in range(len(M_col)):
  if(M[M_row[Coord],M_col[Coord]]!=0):
    s=M[M_row[Coord],M_col[Coord]]
    if(s==1):
      temp_v=vector(Poly)(x=a^M_col[Coord],y=FIELDinfoBook[M_row[Coord]])
      mat.append(vector(W,temp_v))
    else:
      up=[i for i in range(s)]
      down=list(up)
      down.reverse()
      for Cup in range(s):
        for Cdown in range(s):
          if(up[Cup]+down[Cdown]<s):
            temp_v=list(zero_vector(sum(Len_Poly)))
            for j in range(down[Cdown],l+1):
              for i in range(up[Cup],Len_Poly[j]):
            comb1=len(Combinations(j,down[Cdown]).list())
            comb2=len(Combinations(i,up[Cup]).list())
            temp=comb1*comb2*x^(i-up[Cup])*y^(j-down[Cdown])
            temp=temp(x=a^M_col[Coord],y=FIELDinfoBook[M_row[Coord]])
            temp_v[Len_Poly_inc[j]+i]=(temp)
              mat.append(vector(temp_v))

The matrix M is a sparse matrix with integers (mostly ones) at certain positions. M_col and M_row are lists with the locations of nonzero elements.

sage: M
64 x 63 dense matrix over Integer Ring (type 'print M.str()' to see all of the entries)

Poly is a list of bivariate polynomials created like this:

Poly=[]
    for j in range(l+1):
      for i in range(Len_Poly[j]):
        Poly.append(x^i*y^j)

And l=1 , Len_poly=[63, 7] and Len_poly_inc=[0, 63, 70]