Optimal Binary Search Tree DP cost

class Solution:
    def optimalSearchTree(self, A,F, n):
        dp=[[-1]*(1+n) for i in range(n+1)]
        def find(i,j):
            #very important base case
            if i>j:return 0
            if dp[i][j]!=-1:return dp[i][j]
            if j==i:dp[i][j]=F[i]
            else:
                ans=float('inf')
                for k in range(i,j+1):
                    left=find(i,k-1)#cost of LBSR
                    right=find(k+1,j)#cost of RBST
                    ans=min(ans,sum(F[i:j+1])+left+right)# additionally we add each node cost in range(i,j+1) to compensate extra height gained
                dp[i][j]=ans
            return dp[i][j]
        return find(0,len(A)-1)