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#!/usr/bin/python

import glob
import math
import os
import getopt
import sys

from PIL import Image

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import pandas
import numpy
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import confusion_matrix, zero_one_loss

# Must declare data_dir as the directory of training and test files

train_data = data_dir + "kddcup.data.corrected"
train_labels = data_dir + "train_labels.txt"
test_data = data_dir + "corrected"

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import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np

# Define custom py_func which takes also a grad op as argument:
def py_func(func, inp, Tout, stateful=True, name=None, grad=None):
    
    # Need to generate a unique name to avoid duplicates:
    rnd_name = 'PyFuncGrad' + str(np.random.randint(0, 1E+8))
    

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import tensorflow as tf
import numpy as np
import os

import zconfig
import utils

class DenoisingAutoencoder(object):

    """ Implementation of Denoising Autoencoders using TensorFlow.

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Install caffe with python 3.5 and pyenv

Tested on Ubuntu 14.04.

Setting up a new python environment using pyenv

Install desired version of python 3 (e.g. 3.5.1). Make sure to use the --enable-shared flag to generate python shared libraries, which will later be linked to.

env PYTHON_CONFIGURE_OPTS="--enable-shared" pyenv install 3.5.1