def do(ct_size: int, batch_size: int) -> None:
# third party
import numpy as np
import tenseal as ts
# syft absolute
import syft as sy
sy.load("tenseal")
sy.logger.add(sys.stderr, "ERROR")
duet = sy.launch_duet(loopback=True,
network_url=f"http://127.0.0.1:{PORT}/")
duet.requests.add_handler(action="accept")
context = ts.context(ts.SCHEME_TYPE.CKKS,
8192,
coeff_mod_bit_sizes=[60, 40, 40, 60],
n_threads=1)
context.global_scale = pow(2, 40)
data = np.random.uniform(-10, 10, 100)
enc = []
for i in range(ct_size):
enc.append(ts.ckks_vector(context, data))
start = time.time()
_ = context.send(duet, pointable=True)
for chunk in chunks(enc, batch_size):
_ = sy.lib.python.List(chunk).send(duet, pointable=True)
sys.stderr.write(
f"[{ct_size}][{batch_size}] DO sending took {time.time() - start} sec\n"
)
sy.core.common.event_loop.loop.run_forever()
async def main():
duet = sy.launch_duet(network_url=NETWORK_URL, loopback=True)
duet.requests.add_handler(action="accept")
n_iterations_per_epoch = 10_000
for i in range(N_EPOCHS):
rets = await train(duet, i, n_iterations_per_epoch)
print(f"Epoch {i+1} - Average return: {sum(rets) / len(rets):.4f}")
def do_test(port: int) -> None:
# syft absolute
import syft as sy
duet = sy.launch_duet(loopback=True,
network_url=f"http://127.0.0.1:{port}/")
_ = sy.lib.python.List([1, 2, 3]).send(duet)
sy.core.common.event_loop.loop.run_forever()
def do_send(data: Any, port: int) -> None:
# syft absolute
import syft as sy
duet = sy.launch_duet(loopback=True,
network_url=f"http://127.0.0.1:{port}/")
duet.requests.add_handler(action="accept")
_ = data.send(duet, pointable=True)
sy.core.common.event_loop.loop.run_forever()
def do_test(port: int) -> None:
# syft absolute
import syft as sy
sy.logger.add(sys.stderr, "ERROR")
duet = sy.launch_duet(loopback=True,
network_url=f"http://127.0.0.1:{port}/")
duet.requests.add_handler(action="accept")
_ = sy.lib.python.List([1, 2, 3]).send(duet, pointable=True)
sy.core.common.event_loop.loop.run_forever()
def do_test(port: int) -> None:
# third party
import torch
# syft absolute
import syft as sy
sy.logger.add(sys.stderr, "ERROR")
duet = sy.launch_duet(loopback=True,
network_url=f"http://127.0.0.1:{port}/")
duet.requests.add_handler(action="accept")
t = torch.randn(20).reshape(4, 5)
_ = t.send(duet, pointable=True)
sy.core.common.event_loop.loop.run_forever()
def do() -> None:
# syft absolute
import syft as sy
_ = sy.logger.add(
sink="syft_do.log",
level="TRACE",
)
duet = sy.launch_duet(loopback=True, network_url="http://localhost:5000")
duet.requests.add_handler(action="accept")
t = th.randn(4000000)
print("DO: Tensor sum:", t.sum())
start = time.time()
tp = t.send(duet, pointable=True)
end = time.time()
print("DO: Pointer: ", tp, "serialized in", end - start)
print("DO: Store: ", duet.store)
sy.core.common.event_loop.loop.run_forever()
print("DO: DONE")
import syft as sy
# Launch a Duet Server and upload data
duet = sy.launch_duet(loopback=True)
import torch as th
import numpy as np
data = th.FloatTensor(np.array([5, 15, 25, 35, 45, 55]).reshape(-1, 1))
data = data.tag("DO1 data")
data = data.describe("Dataset of 6 samples, 1 feature")
data_ptr = data.send(duet, pointable=True)
duet.store.pandas
data
duet.requests.add_handler(
action="accept",
print_local=True, # print the result in your notebook
)
def connect_to_duet(self, loopback=True):
self.duet = sy.launch_duet(loopback=loopback)
return self.duet
