def test_add():
INT_OVERFLOW = 2**30
A = np.ones((INT_OVERFLOW, 2))
B = np.ones((INT_OVERFLOW, 2))
A.attach_grad()
with mx.autograd.record():
C = np.add(A, B)
assert C.shape == (INT_OVERFLOW, 2)
assert C[0][0] == 2
C.backward()
assert A.grad.shape == (INT_OVERFLOW, 2)
assert A.grad[0][0] == 1
def test_add():
A = np.ones((INT_OVERFLOW, 2))
B = np.ones((INT_OVERFLOW, 2))
A[-1, -1] = 2
A.attach_grad()
with mx.autograd.record():
C = np.add(A, B)
C.backward()
assert C.shape == (INT_OVERFLOW, 2)
assert C[-1, -1] == 3
assert A.grad.shape == (INT_OVERFLOW, 2)
assert A.grad[-1, -1] == 1
def test_binary_broadcast():
A = np.ones((INT_OVERFLOW, 2))
B = np.ones((INT_OVERFLOW, 1))
C = np.add(A, B)
assert C.shape == (INT_OVERFLOW, 2)
assert C[0][0] == 2