DISCLAIMER: This is a proof-of-concept implementation. It does not represent a remotely product ready implementation or follow proper conventions for security, convenience, or scalability. It is part of a broader proof-of-concept demonstrating the vision of the OpenMined project, its major moving parts, and how they might work together.
In [1]:
from syft.he.paillier import KeyPair
from syft.nn.linear import LinearClassifier
import numpy as np
In [2]:
pubkey,prikey = KeyPair().generate(n_length=1024)
In [3]:
model = LinearClassifier(n_inputs=4,n_labels=2).encrypt(pubkey)
In [4]:
input = np.array([[0,0,1,1],[0,0,1,0],[1,0,1,1],[0,0,1,0]])
target = np.array([[0,1],[0,0],[1,1],[0,0]])
In [5]:
for iter in range(3):
for i in range(len(input)):
print("Grads:" + str((model.learn(input=input[i],target=target[i],alpha=0.5))))
In [6]:
model = model.decrypt(prikey)
In [7]:
for i in range(len(input)):
print(model.forward(input[i]))
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