'grad = (y-p)/(p-p^2)'

def exact_backward(self, req, out_grad, in_data, out_data, in_grad, aux):

    p = in_data[0].asnumpy()
    y = in_data[1].asnumpy()
    grad = ((p - y) / ((p + self.eps) * (self.eps1 - p)))
    self.assign(in_grad[0], req[0], mx.nd.array(grad))
