def generate_binary_triple(size0, size1, device=None):
"""Generate binary triples of given size"""
generator = TTPClient.get().get_generator(device=device)
a = generate_kbit_random_tensor(size0,
generator=generator,
device=device)
b = generate_kbit_random_tensor(size1,
generator=generator,
device=device)
if comm.get().get_rank() == 0:
# Request c from TTP
c = TTPClient.get().ttp_request("binary", device, size0, size1)
else:
size2 = torch.broadcast_tensors(a, b)[0].size()
c = generate_kbit_random_tensor(size2,
generator=generator,
device=device)
# Stack to vectorize scatter function
a = BinarySharedTensor.from_shares(a)
b = BinarySharedTensor.from_shares(b)
c = BinarySharedTensor.from_shares(c)
return a, b, c
def generate_binary_triple(size):
"""Generate binary triples of given size"""
generator = TTPClient.get().generator
a = generate_kbit_random_tensor(size, generator=generator)
b = generate_kbit_random_tensor(size, generator=generator)
if comm.get().get_rank() == 0:
# Request c from TTP
c = TTPClient.get().ttp_request("binary", size)
else:
c = generate_kbit_random_tensor(size, generator=generator)
# Stack to vectorize scatter function
a = BinarySharedTensor.from_shares(a)
b = BinarySharedTensor.from_shares(b)
c = BinarySharedTensor.from_shares(c)
return a, b, c
def B2A_rng(size):
"""Generate random bit tensor as arithmetic and binary shared tensors"""
generator = TTPClient.get().generator
# generate random bit
rB = generate_kbit_random_tensor(size, bitlength=1, generator=generator)
if comm.get().get_rank() == 0:
# Request rA from TTP
rA = TTPClient.get().ttp_request("B2A", size)
else:
rA = generate_random_ring_element(size, generator=generator)
rA = ArithmeticSharedTensor.from_shares(rA, precision=0)
rB = BinarySharedTensor.from_shares(rB)
return rA, rB
