def test_bin_xor(get_clients, bit, security) -> None:
parties = get_clients(3)
protocol = Falcon(security)
session = Session(protocol=protocol, parties=parties)
session.ring_size = 2
SessionManager.setup_mpc(session)
ring_size = 2
sh_x = torch.tensor([[0, 1, 0], [1, 0, 1]], dtype=torch.bool)
shares_x = [sh_x, sh_x, sh_x]
rst_list_x = ReplicatedSharedTensor.distribute_shares(shares=shares_x,
session=session,
ring_size=ring_size)
x = MPCTensor(shares=rst_list_x, session=session)
x.shape = sh_x.shape
sh_b = torch.tensor([bit], dtype=torch.bool)
shares_b = [sh_b, sh_b, sh_b]
rst_list_b = ReplicatedSharedTensor.distribute_shares(shares=shares_b,
session=session,
ring_size=ring_size)
b = MPCTensor(shares=rst_list_b, session=session)
b.shape = sh_b.shape
secret_x = ReplicatedSharedTensor.shares_sum(shares_x, ring_size)
secret_b = ReplicatedSharedTensor.shares_sum(shares_b, ring_size)
result = operator.xor(x, b)
expected_res = secret_x ^ secret_b
assert (result.reconstruct(decode=False) == expected_res).all()
def test_prime_xor(get_clients, security, bit) -> None:
parties = get_clients(3)
protocol = Falcon(security)
session = Session(protocol=protocol, parties=parties)
session.ring_size = PRIME_NUMBER
SessionManager.setup_mpc(session)
ring_size = PRIME_NUMBER
x_sh1 = torch.tensor([[17, 44], [8, 20]], dtype=torch.uint8)
x_sh2 = torch.tensor([[8, 51], [27, 52]], dtype=torch.uint8)
x_sh3 = torch.tensor([[42, 40], [32, 63]], dtype=torch.uint8)
bit_sh_1, bit_sh_2, bit_sh_3 = bit
b_sh1 = torch.tensor([bit_sh_1], dtype=torch.uint8)
b_sh2 = torch.tensor([bit_sh_2], dtype=torch.uint8)
b_sh3 = torch.tensor([bit_sh_3], dtype=torch.uint8)
shares_x = [x_sh1, x_sh2, x_sh3]
shares_b = [b_sh1, b_sh2, b_sh3]
rst_list_x = ReplicatedSharedTensor.distribute_shares(shares=shares_x,
session=session,
ring_size=ring_size)
rst_list_b = ReplicatedSharedTensor.distribute_shares(shares=shares_b,
session=session,
ring_size=ring_size)
x = MPCTensor(shares=rst_list_x, session=session)
b = MPCTensor(shares=rst_list_b, session=session)
x.shape = x_sh1.shape
b.shape = b_sh1.shape
secret_x = ReplicatedSharedTensor.shares_sum(shares_x, ring_size)
secret_b = ReplicatedSharedTensor.shares_sum(shares_b, ring_size)
result = operator.xor(x, b)
expected_res = secret_x ^ secret_b
assert (result.reconstruct(decode=False) == expected_res).all()
