[Doubt] Would iteratively setting a non-local variable as the answer result in correct gradients about autograd HOT 2 CLOSED

import autograd.numpy as np
from autograd import grad
from autograd.util import quick_grad_check


def some_function(x, y):
    return x + y + x*y

class A(object):
    def call(self, X):
        self.ans = np.zeros(X.shape)
        for t in range(X.shape[0]):
            self.ans = some_function(X[t], self.ans)

        return np.sum(self.ans**2)


a = A()
print grad(a.call)(np.random.randn(5))
quick_grad_check(a.call, np.random.randn(5))

class A(object):
    def __init__(self, ans):
        self.ans = ans

    def call(self, X):
        for t in range(X.shape[0]):
            self.ans = some_function(X[t], self.ans)

        return np.sum(self.ans**2)


a = A(5.)
print grad(a.call)(np.random.randn(3))
print grad(a.call)(np.random.randn(3))