भाग 2: Syft Keras सह सुरक्षित मॉडेल सर्व्हिंग

In [1]:

    

import numpy as np
import tensorflow as tf
from tensorflow.keras import Sequential
from tensorflow.keras.layers import AveragePooling2D, Conv2D, Dense, Activation, Flatten, ReLU, Activation

import syft as sy
hook = sy.KerasHook(tf.keras)


    

In [2]:

    

num_classes = 10
input_shape = (1, 28, 28, 1)


    

In [3]:

    

model = Sequential()

model.add(Conv2D(10, (3, 3), batch_input_shape=input_shape))
model.add(AveragePooling2D((2, 2)))
model.add(Activation('relu'))
model.add(Conv2D(32, (3, 3)))
model.add(AveragePooling2D((2, 2)))
model.add(Activation('relu'))
model.add(Conv2D(64, (3, 3)))
model.add(AveragePooling2D((2, 2)))
model.add(Activation('relu'))
model.add(Flatten())
model.add(Dense(num_classes, name="logit"))


    

    




WARNING:tensorflow:From /usr/local/miniconda3/envs/syft/lib/python3.6/site-packages/tensorflow/python/ops/resource_variable_ops.py:435: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.






    




WARNING:tensorflow:From /usr/local/miniconda3/envs/syft/lib/python3.6/site-packages/tensorflow/python/ops/resource_variable_ops.py:435: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.

In [4]:

    

pre_trained_weights = 'short-conv-mnist.h5'
model.load_weights(pre_trained_weights)


    

In [5]:

    

AUTO = False

alice = sy.TFEWorker(host='localhost:4000', auto_managed=AUTO)
bob = sy.TFEWorker(host='localhost:4001', auto_managed=AUTO)
carol = sy.TFEWorker(host='localhost:4002', auto_managed=AUTO)

cluster = sy.TFECluster(alice, bob, carol)
cluster.start()


    

    




INFO:tf_encrypted:If not done already, please launch the following command in a terminal on host localhost:4000: 'python -m tf_encrypted.player --config /var/folders/mh/7hh_sz1d3532_k9w4kcmnt8c0000gn/T/tfe.config server0'
This can be done automatically in a local subprocess by setting `auto_managed=True` when instantiating a TFEWorker.

INFO:tf_encrypted:If not done already, please launch the following command in a terminal on host localhost:4001: 'python -m tf_encrypted.player --config /var/folders/mh/7hh_sz1d3532_k9w4kcmnt8c0000gn/T/tfe.config server1'
This can be done automatically in a local subprocess by setting `auto_managed=True` when instantiating a TFEWorker.

INFO:tf_encrypted:If not done already, please launch the following command in a terminal on host localhost:4002: 'python -m tf_encrypted.player --config /var/folders/mh/7hh_sz1d3532_k9w4kcmnt8c0000gn/T/tfe.config server2'
This can be done automatically in a local subprocess by setting `auto_managed=True` when instantiating a TFEWorker.

In [6]:

    

model.share(cluster)


    

    




INFO:tf_encrypted:Starting session on target 'grpc://localhost:4000' using config graph_options {
}

In [7]:

    

model.serve(num_requests=3)


    

    




Served encrypted prediction 1 to client.
Served encrypted prediction 2 to client.
Served encrypted prediction 3 to client.

In [8]:

    

model.stop()
cluster.stop()

if not AUTO:
    process_ids = !ps aux | grep '[p]ython -m tf_encrypted.player --config' | awk '{print $2}'
    for process_id in process_ids:
        !kill {process_id}
        print("Process ID {id} has been killed.".format(id=process_id))


    

    




INFO:tf_encrypted:Please terminate the process on host 'localhost:4000'.
INFO:tf_encrypted:Please terminate the process on host 'localhost:4001'.
INFO:tf_encrypted:Please terminate the process on host 'localhost:4002'.






    




Process ID 12470 has been killed.
Process ID 12474 has been killed.
Process ID 12464 has been killed.

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