def init_generators(self, seed_current: int, seed_next: int) -> None:
"""Initialize the generators - that are used for Pseudo Random Zero Shares.
Args:
seed_current (int): the seed for our party
seed_next (int): thee seed for the next party
"""
generator_current = get_new_generator(seed_current)
generator_next = get_new_generator(seed_next)
self.przs_generators = [generator_current, generator_next]
def test_przs_generate_random_share(get_clients) -> None:
"""Test przs_generate_random_share method from Session."""
session = Session()
SessionManager.setup_mpc(session)
gen1 = get_new_generator(42)
gen2 = get_new_generator(43)
session.przs_generators = [gen1, gen2]
share = session.przs_generate_random_share(shape=(2, 1))
assert isinstance(share, ShareTensor)
target_tensor = torch.tensor(
([-1540733531777602634], [2813554787685566880]))
assert (share.tensor == target_tensor).all()
def test_prrs_share_tensor() -> None:
"""Test przs_generate_random_share method from Session for ShareTensor."""
session = Session() # default protocol: FSS
SessionManager.setup_mpc(session)
seed1 = secrets.randbits(32)
seed2 = secrets.randbits(32)
gen1 = get_new_generator(seed1)
gen2 = get_new_generator(seed2)
session.przs_generators = [gen1, gen2]
shape = (2, 1)
share = session.prrs_generate_random_share(shape=shape)
assert isinstance(share, ShareTensor)
new_gen1 = get_new_generator(seed1)
share1 = generate_random_element(generator=new_gen1,
shape=shape,
tensor_type=session.tensor_type)
target_tensor = share1
assert (share.tensor == target_tensor).all()
def test_przs_rs_tensor() -> None:
"""Test przs_generate_random_share method from Session for ReplicatedSharedTensor."""
falcon = Falcon(security_type="malicious")
session = Session(protocol=falcon)
SessionManager.setup_mpc(session)
seed1 = secrets.randbits(32)
seed2 = secrets.randbits(32)
gen1 = get_new_generator(seed1)
gen2 = get_new_generator(seed2)
session.przs_generators = [gen1, gen2]
shape = (2, 1)
share = session.przs_generate_random_share(shape=shape)
assert isinstance(share, ReplicatedSharedTensor)
new_gen1 = get_new_generator(seed1)
new_gen2 = get_new_generator(seed2)
share1 = generate_random_element(generator=new_gen1,
shape=shape,
tensor_type=session.tensor_type)
share2 = generate_random_element(generator=new_gen2,
shape=shape,
tensor_type=session.tensor_type)
target_tensor = share1 - share2
assert (share.shares[0] == target_tensor).all()