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import examples .util
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import torch
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import visdom
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- from examples .multiprocess_launcher import MultiProcessLauncher
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+ from deeplearning .projects .crypten .examples .multiprocess_launcher import (
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+ MultiProcessLauncher ,
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+ )
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from examples .util import NoopContextManager , process_mnist_files
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from torchvision .datasets .mnist import MNIST
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import examples .util
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import torch
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import visdom
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- from examples .multiprocess_launcher import MultiProcessLauncher
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+ from deeplearning .projects .crypten .examples .multiprocess_launcher import (
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+ MultiProcessLauncher ,
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+ )
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def compute_rewards (weights , dataset , epsilon = 0.0 ):
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import logging
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import os
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- from examples .multiprocess_launcher import MultiProcessLauncher
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+ from deeplearning .projects .crypten .examples .multiprocess_launcher import (
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+ MultiProcessLauncher ,
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+ )
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parser = argparse .ArgumentParser (description = "CrypTen Autograd CNN Training" )
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import logging
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import os
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- from examples .multiprocess_launcher import MultiProcessLauncher
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+ from deeplearning .projects .crypten .examples .multiprocess_launcher import (
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+ MultiProcessLauncher ,
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+ )
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parser = argparse .ArgumentParser (description = "CrypTen Cifar Training" )
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import logging
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import os
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- from examples .multiprocess_launcher import MultiProcessLauncher
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+ from deeplearning .projects .crypten .examples .multiprocess_launcher import (
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+ MultiProcessLauncher ,
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+ )
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from mpc_imagenet import run_experiment
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import logging
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import os
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- from examples .multiprocess_launcher import MultiProcessLauncher
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+ from deeplearning .projects .crypten .examples .multiprocess_launcher import (
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+ MultiProcessLauncher ,
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+ )
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parser = argparse .ArgumentParser (description = "CrypTen Linear SVM Training" )
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import logging
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import os
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- from examples .multiprocess_launcher import MultiProcessLauncher
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+ from deeplearning .projects .crypten .examples .multiprocess_launcher import (
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+ MultiProcessLauncher ,
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+ )
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parser = argparse .ArgumentParser (description = "CrypTen TFEncrypted Benchmarks" )
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