using System;
using System.Linq;
using MathNet.Numerics.LinearAlgebra;
using MathNet.Numerics.LinearAlgebra.Double;
using System.Globalization;

namespace InverseMatrix
{
    class Program
    {

        static string FindInverse(string[] args)
        {
            var matStr = Console.ReadLine();

            var splMat = matStr.Split(" \\\\ ");
            var dim = splMat.Length;
            var mat = new double[dim, dim];

            for (var row = 0; row < dim; row++)
            {
                var rowContents = splMat[row].Split(" & ").Select(x => double.Parse(x)).ToArray();
                for (var col = 0; col < dim; col++)
                    mat[row, col] = rowContents[col];
            }
            Matrix<double> A = DenseMatrix.OfArray(mat);
            var B = A.Inverse();
            var answer = "";
            var invMat = B.ToRowArrays();
            for (var i = 0; i < invMat.GetLength(0); i++)
            {
                for (var k = 0; k < invMat[i].Length; k++)
                {
                    if (double.IsNaN(invMat[i][k]) || double.IsInfinity(invMat[i][k]))
                    {
                        return "unsolvable";
                    }
                }
            }
            for (var i = 0; i < invMat.GetLength(0); i++)
            {
                var row = new string[invMat[i].Length];
                for (var k = 0; k < invMat[i].Length; k++)
                {
                    row[k] = invMat[i][k].ToString(CultureInfo.InvariantCulture);
                }
                answer += string.Join(" & ", row);
                if (i != invMat.GetLength(0) - 1)
                    answer += " \\\\ ";
            }
            return answer;
        }
    }
}