Propose a hack data of Summation operation

[CIntellifusion]

Hello!

A implementation like this may pass the original test data.

def gradient(self, out_grad, node):
        return Tensor(array_api.ones_like(out_grad))

But when given 2 matrix , it fail.

So I sincerely propose to add this sample to function summation_backward() in test_autograd_hw.py of hw1

gradient_check(lambda A,C : ndl.summation(ndl.reshape(A,shape=(10,5))+C, axes=None),
                   ndl.Tensor(np.random.randn(50)),
                   ndl.Tensor(np.random.randn(10,5)), backward=True)

this originates from the last sample of function test_compute_gradient() with other operations removed.

I hope this may discover problems earlier to save time.
Thanks for your attention.