import numpy,math

def softmax(inMatrix):

    m,n = numpy.shape(inMatrix)

    outMatrix = numpy.mat(numpy.zeros((m,n)))

    soft_sum = 0

    for idx in range(0,n):

        outMatrix[0,idx] = math.exp(inMatrix[0,idx])

        soft_sum += outMatrix[0,idx]

    for idx in range(0,n):

        outMatrix[0,idx] = outMatrix[0,idx] / soft_sum

    return outMatrix

aa = numpy.matrix([1,2,3,4,5,4,3,9,8])

outMatrix = softmax(aa)

print(outMatrix)