4220e2c69f73f71e23bcd948df0fa20f37ff5d17,examples/pond.py,,,#,8

Before Change

from tensorflow_encrypted.protocol import Pond, Server
from tensorflow_encrypted.layer import Conv2D

server0 = Server("/job:localhost/replica:0/task:0/device:CPU:0")
server1 = Server("/job:localhost/replica:0/task:0/device:CPU:1")
crypto_producer = Server("/job:localhost/replica:0/task:0/device:CPU:2")

with Pond(server0, server1, crypto_producer) as prot:

    a = prot.define_constant(np.array([4, 3, 2, 1]).reshape(2, 2))
    b = prot.define_constant(np.array([4, 3, 2, 1]).reshape(2, 2))

After Change

config = tfe.LocalConfig(3)

with Pond(*config.players) as prot:

    a = prot.define_constant(np.array([4, 3, 2, 1]).reshape(2, 2))
    b = prot.define_constant(np.array([4, 3, 2, 1]).reshape(2, 2))
    c = a * b

    d = prot.define_private_variable(np.array([1., 2., 3., 4.]).reshape(2, 2))
    e = prot.define_private_variable(np.array([1., 2., 3., 4.]).reshape(2, 2))
    // f = (d * .5 + e * .5)
    f = d * e

    // convolutions
    conv_input_shape = (32, 1, 28, 28)  // NCHW
    conv_input = prot.define_private_variable(np.random.normal(size=conv_input_shape))
    conv_layer = Conv2D((4, 4, 1, 20), strides=2)
    conv_layer.initialize(conv_input_shape)
    conv_out = conv_layer.forward(conv_input)

    with config.session() as sess:
        sess.run(tf.global_variables_initializer())

        print("multiplication : ")

Instances