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   "source": [
    "# Variational Inference: Bayesian Neural Networks\n",
    "\n",
    "(c) 2017 by Thomas Wiecki, updated by Maxim Kochurov\n",
    "\n",
    "Original blog post: http://twiecki.github.io/blog/2016/06/01/bayesian-deep-learning/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Current trends in Machine Learning\n",
    "\n",
    "There are currently three big trends in machine learning: **Probabilistic Programming**, **Deep Learning** and \"**Big Data**\". Inside of PP, a lot of innovation is in making things scale using **Variational Inference**. In this blog post, I will show how to use **Variational Inference** in PyMC3 to fit a simple Bayesian Neural Network. I will also discuss how bridging Probabilistic Programming and Deep Learning can open up very interesting avenues to explore in future research.\n",
    "\n",
    "### Probabilistic Programming at scale\n",
    "**Probabilistic Programming** allows very flexible creation of custom probabilistic models and is mainly concerned with **insight** and learning from your data. The approach is inherently **Bayesian** so we can specify **priors** to inform and constrain our models and get uncertainty estimation in form of a **posterior** distribution. Using [MCMC sampling algorithms](http://twiecki.github.io/blog/2015/11/10/mcmc-sampling/) we can draw samples from this posterior to very flexibly estimate these models. PyMC3 and [Stan](http://mc-stan.org/) are the current state-of-the-art tools to consruct and estimate these models. One major drawback of sampling, however, is that it's often very slow, especially for high-dimensional models. That's why more recently, **variational inference** algorithms have been developed that are almost as flexible as MCMC but much faster. Instead of drawing samples from the posterior, these algorithms instead fit a distribution (e.g. normal) to the posterior turning a sampling problem into and optimization problem. [ADVI](http://arxiv.org/abs/1506.03431) -- Automatic Differentation Variational Inference -- is implemented in PyMC3 and [Stan](http://mc-stan.org/), as well as a new package called [Edward](https://github.com/blei-lab/edward/) which is mainly concerned with Variational Inference. \n",
    "\n",
    "Unfortunately, when it comes to traditional ML problems like classification or (non-linear) regression, Probabilistic Programming often plays second fiddle (in terms of accuracy and scalability) to more algorithmic approaches like [ensemble learning](https://en.wikipedia.org/wiki/Ensemble_learning) (e.g. [random forests](https://en.wikipedia.org/wiki/Random_forest) or [gradient boosted regression trees](https://en.wikipedia.org/wiki/Boosting_(machine_learning)).\n",
    "\n",
    "### Deep Learning\n",
    "\n",
    "Now in its third renaissance, deep learning has been making headlines repeatadly by dominating almost any object recognition benchmark, [kicking ass at Atari games](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf), and [beating the world-champion Lee Sedol at Go](http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html). From a statistical point, Neural Networks are extremely good non-linear function approximators and representation learners. While mostly known for classification, they have been extended to unsupervised learning with [AutoEncoders](https://arxiv.org/abs/1312.6114) and in all sorts of other interesting ways (e.g. [Recurrent Networks](https://en.wikipedia.org/wiki/Recurrent_neural_network), or [MDNs](http://cbonnett.github.io/MDN_EDWARD_KERAS_TF.html) to estimate multimodal distributions). Why do they work so well? No one really knows as the statistical properties are still not fully understood.\n",
    "\n",
    "A large part of the innoviation in deep learning is the ability to train these extremely complex models. This rests on several pillars:\n",
    "* Speed: facilitating the GPU allowed for much faster processing.\n",
    "* Software: frameworks like [Theano](http://deeplearning.net/software/theano/) and [TensorFlow](https://www.tensorflow.org/) allow flexible creation of abstract models that can then be optimized and compiled to CPU or GPU.\n",
    "* Learning algorithms: training on sub-sets of the data -- stochastic gradient descent -- allows us to train these models on massive amounts of data. Techniques like drop-out avoid overfitting.\n",
    "* Architectural: A lot of innovation comes from changing the input layers, like for convolutional neural nets, or the output layers, like for [MDNs](http://cbonnett.github.io/MDN_EDWARD_KERAS_TF.html).\n",
    "\n",
    "### Bridging Deep Learning and Probabilistic Programming\n",
    "On one hand we have Probabilistic Programming which allows us to build rather small and focused models in a very principled and well-understood way to gain insight into our data; on the other hand we have deep learning which uses many heuristics to train huge and highly complex models that are amazing at prediction. Recent innovations in variational inference allow probabilistic programming to scale model complexity as well as data size. We are thus at the cusp of being able to combine these two approaches to hopefully unlock new innovations in Machine Learning. For more motivation, see also [Dustin Tran's](https://twitter.com/dustinvtran) recent [blog post](http://dustintran.com/blog/a-quick-update-edward-and-some-motivations/).\n",
    "\n",
    "While this would allow Probabilistic Programming to be applied to a much wider set of interesting problems, I believe this bridging also holds great promise for innovations in Deep Learning. Some ideas are:\n",
    "* **Uncertainty in predictions**: As we will see below, the Bayesian Neural Network informs us about the uncertainty in its predictions. I think uncertainty is an underappreciated concept in Machine Learning as it's clearly important for real-world applications. But it could also be useful in training. For example, we could train the model specifically on samples it is most uncertain about.\n",
    "* **Uncertainty in representations**: We also get uncertainty estimates of our weights which could inform us about the stability of the learned representations of the network.\n",
    "* **Regularization with priors**: Weights are often L2-regularized to avoid overfitting, this very naturally becomes a Gaussian prior for the weight coefficients. We could, however, imagine all kinds of other priors, like spike-and-slab to enforce sparsity (this would be more like using the L1-norm).\n",
    "* **Transfer learning with informed priors**: If we wanted to train a network on a new object recognition data set, we could bootstrap the learning by placing informed priors centered around weights retrieved from other pre-trained networks, like [GoogLeNet](https://arxiv.org/abs/1409.4842). \n",
    "* **Hierarchical Neural Networks**: A very powerful approach in Probabilistic Programming is hierarchical modeling that allows pooling of things that were learned on sub-groups to the overall population (see my tutorial on [Hierarchical Linear Regression in PyMC3](http://twiecki.github.io/blog/2014/03/17/bayesian-glms-3/)). Applied to Neural Networks, in hierarchical data sets, we could train individual neural nets to specialize on sub-groups while still being informed about representations of the overall population. For example, imagine a network trained to classify car models from pictures of cars. We could train a hierarchical neural network where a sub-neural network is trained to tell apart models from only a single manufacturer. The intuition being that all cars from a certain manufactures share certain similarities so it would make sense to train individual networks that specialize on brands. However, due to the individual networks being connected at a higher layer, they would still share information with the other specialized sub-networks about features that are useful to all brands. Interestingly, different layers of the network could be informed by various levels of the hierarchy -- e.g. early layers that extract visual lines could be identical in all sub-networks while the higher-order representations would be different. The hierarchical model would learn all that from the data.\n",
    "* **Other hybrid architectures**: We can more freely build all kinds of neural networks. For example, Bayesian non-parametrics could be used to flexibly adjust the size and shape of the hidden layers to optimally scale the network architecture to the problem at hand during training. Currently, this requires costly hyper-parameter optimization and a lot of tribal knowledge."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bayesian Neural Networks in PyMC3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generating data\n",
    "\n",
    "First, lets generate some toy data -- a simple binary classification problem that's not linearly separable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import theano\n",
    "floatX = theano.config.floatX\n",
    "import pymc3 as pm\n",
    "import theano.tensor as T\n",
    "import sklearn\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from warnings import filterwarnings\n",
    "filterwarnings('ignore')\n",
    "sns.set_style('white')\n",
    "from sklearn import datasets\n",
    "from sklearn.preprocessing import scale\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from sklearn.datasets import make_moons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X, Y = make_moons(noise=0.2, random_state=0, n_samples=1000)\n",
    "X = scale(X)\n",
    "X = X.astype(floatX)\n",
    "Y = Y.astype(floatX)\n",
    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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ze3DHjFy88lAeJgztpThO+f6p2km+rtGBc03sPdz2cq7R4Vc+NTInDZNG9kH3\nJKuvhHkApBI1tYsRQLw2LVsMwIXFT6vdhbqmwPI42rg6klAZ22DKATmcSIYb7S6MUuZvsJ4Eqa52\nxrh+qGnQZujkGcus0iLfCdRiMmDRDUO8C4coiFnRVrPBu4iQ14VrmeSlLYBwsqekEl8fPYuh2T2w\nYvFYajSBlH2txeOMthiQEGvSNDZp8cO6L+EWPAmVsY2ka+JwQgHf0+7CJMWbkRRrxjmKd1TX6GiX\nHKTvfmlSPKh73bQyI19PuK7RgXOMiTYpzuI3gZL2TKXj0Dpqqa0dZmU/t4ducSacayJHI4ALDTIM\neh1G5fZUlX2tVu3Nd/+3oZk+BqtZj7hoEzErvdO6qBEIVVlZJF0ThxMK+BPbhbGYDIiPNVGNNquT\nFAtStq7FZMDwgWnE7ONrhvaCQadjlihFWwzoFm+mGu64GCNxApUnWqWnGLx7u77jS4o3IyXRSqyX\nJk3yt00dCJfbg//uKSUqoCm1DiXxh9tG4Nm/7VcMT+8pqcBL9433/ptVosZajFTV2VBTb0NG9zhV\nDV0AYOLwPszkMZrk6PVXZ8LudIXEyKktDQyVseUiLpyLCW60uzB2pwutdnr4e2h2D02TW7DZurqo\nKGomse8xWZ52i63NzyiQJnba+ObkZ+PtzUfQTNlzj7Ua4XF7/Ay9Xq/zCqWQmoNkpimXQfndAx3Q\no1uMKg++pt6GxpY2VdnXSjXlm3acwK1TB2J38RnyuM7vn8tLsmjRF98IR029DZt2nMD+I2eZTUHU\novX5CpWx5SIunIsJ/uR2YZT2tKeOydJ0PFZpzOz8bBQdriT+XdHhSsyZPIBYoqTWA6xtsKOu0YHu\nSTq/iT0l0YrcvimYPyMH//j0GHF8h76vRmllE/XYJ840Yu6fPofd6QowFPNn5MKgD4wSzMnPxusq\nFhsSHg/Qand5PfjdJRXUfVfJ81frcf7silR8ureM+Pr+I2fRYmujiqMIAvDYvJFITbQiLTlatbG1\nmAz4ZFdpSPtd054vl9tDVJoLtbENl4gLh9OR8Ce4C8PywronWZGiIdmKtXe6/ZtTGJWbrllvWosm\nt2TI5BN7dZ0NW/eXY9eh02hzkUuWWAZbQspwlxsekmGQlM72HzmLc40OmE06OJzsWHn3JCsSYoxY\nt7EEX3xVztRQHz4wDW9vPqLocbbYnFhTUIJvvquiHkusFyc3WAEAi1mPVz88iJog2nQq7aUD9BwD\nkngO7Xh25hJWAAAgAElEQVRS33KatgA3thzOBfg3oQsTyn0/ltfe0OzEH179ErqoKLgJUmkpiVY4\n2twBe55aNL5jrUYAoE7sdgWjqRV5y05fw7C2oNjvnkoG22omNzkBxPv9zqfHmCprkuqZRxCYYh9S\nGPnzopNM4w8o773bHG7YHDbieeSo1SSvrhPbp5Ycr/GTQ506JgtJcWb8g9AL/Rcje1ND/B4PvAl6\nXOyEw2HDjXYXpz37fr6TtNLeqUcAiNqmAJpanVj0/BcBnpwWje+mVicqa1uDauQRDFV12qMDgiDg\nhXvGYMu+cuz7thI19XakJFqQ2y8VM6/ph/tf+h/1fImxZjx912jEx5pw17KtxPdIC4m3Nx9RndnO\nMthmkx4OZ6DRly9YSHvNLE1yi1mPrfsvCOpU1dmw+XwoXV5J4N3C+KFa8Vpovc85HM4F+LejixPM\nvh8tIYiWHS4nNdGC2gY7TEY97E53QO9lQPTktJRW1TbYAQiaG3kEi04nZrTLYXmYdqcbm3b+iLho\nE4AoCBDHvXV/Ob45dhZ1jHKv+mYH7n9pO2KtJmpHsJp6GyprW1RtKXSLN2NkTjr2fVtJNKysTH35\ndgZpr3nzrlJk9Yyn7JXT1WFokYGys8pbGKy2nhwOR4SLq1wkaJGTpIl1AMC0MVmK4hyZ6fEYPaQn\nnG3kCdpXzERSV7Oa2eNKSbQiLTmGKqGqBp0O54VYlKVDpcQxCamMLNpiYOYC7C6uwMYdJ7yGXVIG\nZRlsibomJ1OLXDxvlGK0ISnOjOfuHosFMwdjVG5P4ntG5qSje5KyqIhSV7f8qzP9lPHyhvYKSrBH\nTfkcFzvhcJThS9pLDNYkvaXoJJ5ZOBrXjcrE/z23FRSpauw7Qk+MAvw9Jr1eh9n52dhdfIbZK1va\ng5fC+p8XlTHfT+K6kZmYMa6fd+KvrG3Fk+t2o4bgLaYmimIupKiD2Ug3+HZCuDlUjMxJR1pytGK0\noa7JgUde2enNcgfI2yMGvU4x30FJlGbGuH64depAP4Gb4uM1mqMhaureudgJh6MM/4ZcYrDDvx4s\nfvF/6J5kRWy0CY0tyt4jCbnHVNfoYEqgThjay2uspXD/LZP6Y01BCb48dEbRUFrNBkwc3jsgKzoz\nPR5XU5THRuX2hMVkCEg6k4yRXgcE0W8l6L+V7oFer1O1pSDfiiBtj9DyHW6Z1N9bsx5tMSApjhxK\nlz5HefZ2MGpyrLp337akHA6HDTfaFwFa+g0nxZupCUYSkuGKtRrQbNMeCpV7TKyEtNRECxbMHBRQ\n6qPT6zBjfF8c/KGaarRTEy0Y1C8V82fkINpKDumzEvVYUQeTkZ4pzoIm6cpCfg/kY+4Wb0aTzaWY\nVCbfC5bnO8THGPGPT4/h7ue3obredv4zEqjjpXm+vuOjedxWswEOp8uv7v2t82VuvkprU8dkISXR\nyj1sDkcl/JvShQlGwcxiMmBQv1QU7ie30/Ql2mKE2aRHbYO65gw6nRiilntMrIS03H6p9Guqs4ES\noQcADLw8GXffMIRZc8xK1Kuqs1GjDg6nC3lDewURCma08KIgef3AhQXY7Pxs75gdbS4sen4b8W/V\nJG9JBl0eVaAtSpQ8X5pqmtybb2hp87vfXJWMw2k//FvTSWjxjmmwFMxY9a7zZ+RgV3GFoidZU2/D\nNVf1UmXgAWDskMtwq0pJSvN5L2/r/nKUHK/xGgm1CmoAsO2b04iPNauq7RW7WEliINLP7KYUv5s5\nCA6nG/c8vw21jeTIhC5KTEZLijNhcL9UbD9AFzpJijMhKc6CZltbgNfvdnuwpqAYe0sqca7J7rcA\na3N72tU8w+50obK2hSp16ktyggUvLB6HhFjlhDCLyYCM7nFYMHMw8XkmRT+4UAqH0z74tyfMBKvv\nLUdt9yff90uTarTVhInDeysax5REK+bPyEGM1egX1hw+MA2AKF/qa4C3fX0a3/54juhp+Xpnr314\nyG8h4Ctnuf/IWdX3AAB2F5/BDddegVa7i7oAYt1zJXEaVu/tKABXD07HkRN1ONdkx+HSc7CYyOHx\n5AQLVi4Zj4TYQPlSt9uDJSu2++35yhdgtHHm9E2Bw+kmLgC1RC0k6hrtqGtyMO8nic42xkqL4FAs\nkjmcSIA/vWEmWO9YjtpWlKwmG4Bo9Gj72yNz0hFtNVHDmnMmD6Aa4M+Lyoha34CYfUxiT0kF6igd\ny2hU19tx258/Q5vLQ10Ase65kjgNK1HLYjZg54ELCyda/TUA/HxQT6/3Kjdwr354kJqk9XlRGW6Z\n1J8Zqdj2dTk8HnFvfFRuT+/1a4laSJhNejz1+h7NsqedhdIiOFSLZA4nUuBGO4xo9Y5ZqO03rLRI\naHO58cnukwHHyOwZ77enSfOkaAaYpvXNWmzUNTrQLd5CDEVLYWgSzjYP8VyAuntOWpS43R6sLShW\naBhCHpDVbECs1YDaBjtToU4KiX9WRG4GAoj3ccW/DmDhrwZjyugs3HDtFXhj02G/hZJUSlVdb/dr\n8KJW993/fOplTyMBpec7VItkDidS4EvNMKLGO1aLlNxFQgrtKhmshmYHtn1N3oM9W9uKNkbdkt3p\nwrGTdaplRyXBFWmxQSI1yYoROWmqjqfmXID6ey4Xp/EVoJHTPcmKCUN7UbOuHU4XHp83Eq89fC1W\nPzjB25hEzvpNh7F5VylNHdbL7pIK/PbJ/2L+01uw+IUvsKuYbYz3lFSgsrZFkyRstzgTVQDH935G\nEmqeb9brkXhNHI4S3GiHEZbBCkYNSlIb81WsmjYmy+vVKRms78rrqcloNoeYvCRH8kAXLtuKR1/b\nhSiVydKSgVRabMyfkYv8qzORnGCBLgpeQ0LzslnnAoK75yxjICVqLZg5iKk4lpYcw1So09IBDbjg\nTdc0OFQlEAJR1OuW0y3ejD/cNoJqxLQuKMOF0vNdWtEYskUyhxMp8PB4GAllVy5AWXdcKYSeEGNU\nOEOgRZaHG9XIU0rnkwwkbR95Tn62tyVmbYMd3eJMaNVY8yw/VzD3nB3Ct6PV7kJCrLldn6WWDmha\nSTnfO1utCMrowZehd1q85gz1zk7uUnq+M9O1XxOHE+lwox1m2tOViwZtv1nJYPVOi6eKgVjNeqQl\nR/v9juUdRkWJJt5MyZ72NWS0xYa8jvicCj1vEnKjqfWeq80XaM9nqaUDmlak65+Tn42S4zUorWwk\nLq6sZgPyhikrscnvZ6Qkdyk93+1dWHE4kQh/asNMMF252gPLsOj1OuQN603s7JU3rHfAuFjeoSAA\nI3PT8X+zBuHdLd9rNmRaw8USeh1gNOjhbHNTz6X1nrOMwdDsHoqLDzWwzmEx6RT7h1vNesRGix3D\nJF1v3+xxAHhr8xFiVvqYwem4YWJ/pCXHBLW4oSV3NTY7MDPvJ0hLjgGATn++tVwTh9NViBIEpTSY\nzuPUqVPIy8tDYWEhMjIyOns4XRpRYKMVgOA3WUte0+7iM6iptyM5wYzBP+mO3+Znw9Hm8Zt07U4X\nfvvEp8w91WljsnDHjFxm6JTkqeX2TcHWr8oVk7Ikxl15GWZNuMIbDQjWQNDG6TvGKophlLzKYMPE\nrTYn1hSU4NAP1X6Z5rdM6o+/FpT49ayWM21MlnexEG0xBNRV250uLFy2lejJS8p18ykJcvLr8X12\nkuIsWLJiOzNCYNBFwWjUweZw+6mradUh0HJPeZ0251KBG+1LAJKRlOs+t5w3IMU/1KC6nmyk2twe\n/PaJ/zK1tbsnWbH6wQnMiVEeBpewmPSqumhdP6oP7vxloF65FtSGeF/98CA27yoN+Hsp4S+YMLHv\nQqm63o4UHw31mPMqYloWDSQqalpw5zNbmIsgaYHFGue6jSUo3Ffm/czNJj1RA10J33NpXdDxumoO\n5wJ8ydnFUeNBkMKZm3eVYvOuUq8n5BEEP8+OVPs7ZXSWYjMMJS1sVhhcUKXZJdZlt3cCV1O/a3e6\nqApte0oq4HJ7/Ay62hrgdRtL/LYkaurt2Lq/HCajDgtnDQEQGHonedMspD3zhqp6JLWcQ11MNziM\n/olXStoA6zcdDtg6CcZgS+e6ZVJ/vPPpMaZB5nXVHC+trUBFBZCeDkRHK7//EqFTlq4HDx7E7Nmz\nO+PUFw2+pVd3PrMFC5dtxdqCYrhltdVKe8XSpFi4jy7wAYiTbrTFQC1zklDKymXtizucHphN9F7W\nEl8eOo0WW3BJaoByfa+aGu/qOhv2llQSX/u86CR1fHani3qv/7v7JF798KDfZyjVjyfEmpklZHIs\nOmDx3r/h5bfuxmvr78LLb92NeV+sg85zweiSyp7sThcqalrQ0OxQpVWulpp6G9YUlHhr3wXhwrO3\nftNh77nV1lVL4+S11hchLheweDEwcCBwxRXi/xcvFn/PCb+nvXbtWmzcuBFWq7oaUg4ZtR6J2tIi\nNR50q92lWEaklJXLypruniSG7UnhaF/sTg/WFJTg3l9fSXmdHX1QKwHLGmtSvJmqSW5zuKnjq6xt\nZd7rzbtKYTjvZbeL++9H7sfveH9Ma6zC9G8+BgCsu2YeAP8FljwsTZNu9SUhxoiGljZVw0lJtOLQ\nD9XE1ySPX83n0j1JF5bwOd8D70Tuvx9YufLCz6WlF35esaJThhRJhN3T7t27N1atWhXu00YU7fUS\ntHgkLHERLSQnWOBoc+GWSf0xbUwWUhMtAMSkJiBQ2IWGkrjK7VMHonePWMXxlByvCbh/aqMPagVX\nlMaakmDRND4R5S0A72fY2gocPy7+XwG/Z6q1FSgoIL5vxPEimNtEY9zU6sTbm494DbavF6xksHU6\noKGlTVVkBBAbm9Q0kBc5kkFW87nIxyn31tuL2mco4tDwrET0uRnPLjZs6JzrizDCvoScNGkSTp06\nFe7TRgTBJtnIV/1qPUWAXVqkhWab2NNZGvOq+69BY0ub5r1W4EIZzq5Dp1HT4EBKghlXD7rMm9hV\ndrZZ8RikvfM1BcWq9pi1CK6wSoYcTje1bSltbz8tOQZWs4GZgX/uXDNcd98DfLYZKCsDevcGpk8H\nli8HDMqJWxOTXbixvJzY2TulqQZJLedQmZgOm8ONjTtOwOlyY/vX2r6TUs6DtMet1wGSXZOyx+0O\nN1LP50zcPKk/Sii9ySWDrPS5AAiZdj+NLren7nKJnumGDYrPSpc4d0UFUE6pmigvF1/v2zf4MV8E\n8LhPGNE6IdCM/C2T+mtSevI1PLRSHaXaYFoDEEDMKPbtU62E2+1ByfEanDvf0etckwMlx2vQanOq\nrtWWh3bXFBTjv3tKie8lTeg0Y3zzpP6oqGkhthSVh0tZfclpe/sWkyhoQqqNl7hr99uI3ePjbTDC\ng6Rn6oMqB/JT0hBfFbgnXROXgrqYbn6/++KrcjgYn72arP7kBCse+u0wmIw6vzptaVGnVryFtUiq\nqrOpXqwGQygb+oSNzgwld8S509NF419aGvhar17i65c4EfYEXrwEMyGwjLwWpSdfw1NTb8OmHSew\n/8hZv0nRIwhEQ0JTTFObDUzigVU7/EQ/PB7gxJlGPLj6S9XSnr7XKTXeoEGa0OXGOCHGiHc+PYZF\nz28jXovF5UR6QyUQnQ6cPy+rLzlrb3/etBzooqLwedHJgHtrbnNgxIki8oVs2AAsXerNpKU9Uw6j\nGXuzhmNiVWCYcW/f4QFZ5CyDnZpowYv3jkddkwNvf3IERYfJyXc19TbERZuQniIabLfbg493nvB7\nNoYPTMOU0Zd7+7CThE5IiyRAfPajLYYOlSXVEsGKCJRCyT7PSpc5d3S06K37LgYkpk/nWeTgRjts\naJ0QlIz8S/eN9/5brdKTxWRARvc4LJg5OCDk7nZ7oIuK8jueJHhCG/OaghJiL22AHkpsaHagtJLc\nO/pMdTOSEyyoIfT31ukACAi4TjVKaqwJXZKAldeOS9cS5XZh3o63vCFAT69eaJ00GYYXn4cl2hKU\n4pZkmEhtUZNaziG2mmwY5eFB1jP1yqjZGDWoJ2I+2wxPWTmqY5Oxt+9wrB93K3VcJAb1S0VCrBlm\nkx4/nmmgvi85weJ3j0kLzo93/ohpY7Kw+sEJikleFpOBmHQWazUSjTZrkaQ2qUytfG3E0FGhZDWl\nVh0Zxl6+XPz/hg3isXr1uhB253SO0c7IyMB7773XGafuNLROCEpGvrGlrV1yqHK9cpqHU8zYh1TK\nBiaNp7SCrIMNiJ28+mUkoaY+0AhfNzITM8b1C7hONdnxShntDc0O7DxIblHaZ/lTgE+oWnfyJGLX\nvILPD51B6UNP4bapA4P6HOxOF746WhXw+7qYbqhNSEVqPaE+XBYeZD1TRosJUX95EW9snIPdn31N\nrNNWwmo2YP6MHHFcjY7z3cPIDOqX6qfGphRVkjxyFiTDX1VnQ1bPeDTb2hQXSVpzSELd0KfDCXUo\nWcsedUeGsQ0GMby+dCmv0ybAJYaCRGsGuJr+175oyXBOijejrtERkppV377SrDH3zUhENcEjBtht\nDzPT470Z53J0OmDB/8slthudPyPXO9H73nel7HiLSQ+PIBCzf6VM4Xue30bMlja3OTDo213E4+Z+\nuwufbj3izVqW9+NWgrbYcBjN2J01jPg3nmnT/CYv1udjc7jxt81HsPO7OlQmpms22AAwYmAP6M4b\nN9ZixKCL8hp3IDR941mGv9nWhhcWj1PsV77mfPRES6a5UrvbiEIKJZMIJpQs7VGXlop7VtIe9f33\nd/y5SURHi946N9h+RNjSMfJpj8yillCqmlV/OCQf5WM2mwwABOwurvBKa8pJSbTC0eaG3ekKmOgT\nYs3ITIsnNrLITItHtwQr0XOVDCzpWlnZ8XanGx/v/BG6qKgLIfvz4b+39tdiYxE9tJ7Ucg4pjeRo\ngpSFvfPgadxw7RVIiNVmFFle8j8m3gFBEMuzUppqUBOXgr19h6N67FzMk733lkn98XlRGTEZbuv+\nclWysDS2fX0a3/54zpv8SCtXMxp1XuOudG2+C05W2FrJ8LfaXVRvPZjERIlwN/RpN6EKJQezR/3U\nU0B9PfDFF8Dp0zyMHSYi+GmMTNpTEqJ1QlAy8mqlOCtrWwBEIS05WnMzBd8xv/bhIb89bFqYu6nV\niUXPf0FdRDx39xg8sGqHt2WkTica7OfuHuN9jzx8z7pWNdnxe0oqMPsXP4Hl9w8DGzZAKCvD1PhU\nJF8+DOvH3QqPLrDeuC6mG6rjU5HWGBjGlrKwHY0O3PP8Nvx8sLIeuPw+0xYbHp0O666Zh7dHz/aT\nIO1+pBq/kS2EGlraqBEWJYN97dAMHDpey2z+Id3nFlsbVRTG7nCrLjMcmZMOo14XsACTa+G3Z39Z\nbWJiUjy90Qyt3W3EEapQspY9ankYPSMDmD1b9Mrj44O/Fo4qusBTGTmEqiRE7YTAMvJKY7llUn+8\n/d+jKNxX7vXCzCYdJlzVy9tsQ6unXny8hng+nQ4QPIDlfP2xNLnTFjQmkwEr77tGTEqraERmejzT\nU1Vz3++YkYuJI/rg7uVfEN9XU2+D6977gDWvABB7f6fWnw1QCfPFYTRjb9/h3vf44puFXdtoD6p0\nb05+tvcapEVZTt8Urwa8w2hGZeKF8DcpYTEp3oyUBAt1q4LFDRN/imjrCVU1/F8eOgNdlJh3ICdK\nBxRs/8Gva9htUwfC5fZgT0kF6hod3nptqRZfSQufFUFRSjpTk5hYsP0H7D9y9uJpSiKFkoNFyx61\nvNSrrAx4800gIYErloUBbrQ10FklISQjzxpLVZ0N97+0A+VV/iIlDqcHn+w+iWMn6/DC4nGaogbM\nhC8BeGzeCLz6wUFimJa2oEmINWPwT1LJx1R5bt/7npYcje5JZO+sZ3QUoj/4D/EYI44X4e3Rs4n7\nvlK2tTxUTcrCDqZ0j5T8pyRC4ovFZMCgfqlUkRca3ZPEY6mJUgBsr93j8ZdflRYp+4+cRV2TA93i\nLRia3cPbKU6NFj4QXC9sNYmJsVZjUI1eLmrUllp1ZpkZBwBPRNOE2uSwjsbudMHR5kYKIwFLbrB9\nOXGmEa/++xB18txdfAalFQ2q5VBTEq1ITYymenvVdeqSj2iEQnZ0XLoBOkr4T9qfJuHR6bHumnm4\nf/5qLLh1Nf5vziqsu2YeMZxOa8ChJDmrNvmP5mHOn5EDq5m8WKT9XjqWXq/DnPxsRFsM0JEk1DQg\nXY9carS20Y7Nu0qxftNh1Vr4e0oq0Ob24I4ZuVj94ATFpDMJ1rOi0wGTRvRGUyu5mYtcAviSY/ly\n4J57gMxMQK8X/3/PPf571GrC6JwOhRttDQQzoQKh60jkq4u86Pkv0EyZfNRQdLiS6llV19uxaPk2\nP91li8mA4QPTiO8fPjANacnRsJrJOtQWs75dCxot952W/fur34wVw38E6hJSUR/bDd2TrMjqSd6T\ncxqtilnYwZTukRYzWjOYJZEXEnnDeike64FVO1Ba0UQMfWuhpt6GytpW5iLlw63fIUrF4kC6N1ob\nd7CeletGZmLmhCsUNdAvWaT98cOHgWPHxP+vWOFf7iWF0UlwxbKwwMPjGtESsgt1drc8zKrUmYtF\nQ7MD3eLpnZwE+Cch/W7mIBVHpc3G7XThoP6+M5P9KOG/xN/cgJcem4yEGCPe/u9RVNS2esP8VrMe\nI3PSse28Nre5zUHtT80q3dOSUBVMBjPr/uj1OuqxWGI3AJAcb0arT54CCzHyIzC3bT7dy24BKxEf\nY8SHX3yPb45VhbRKo83t6VoCKp0Ba3+cK5Z1Otxoa0TLhBrK5gOsMGtUFCBo9JJSEtW1wQSAwv3l\nOPhDNVps5EhB0eFKTBqZSY0kOM57S+3Z79dqyIjJfpTyGOPy5Ug3iKpocilXm8MNq9mAHnEmTNnw\nCkYcL0JqYzWq41O9e9spybHtKt3TdA0UlO4P7VgssRsAuLxnAs6ea2Vut0iMzElHWnIM1SjSSgRJ\n1De34dM9F9TiQlWloVYDnQO6MhpXLOtU+BMaJEoTaqibD9TU26jhbJrB7pMWh1NVzXAT4p5SiQ0A\nMYu2zsZsGkmSFvUdGyCExYNpVykOozyG9XntP3IWi4r+jsE+WeRSf+pePeIwYMPf2KV7eZcjrqIc\n2ytcONMqqEqoChat9yczPZ656NtPUG0DgPgYE8xGHWob7AFe/fCBaUQde7UGm0UoqjSCSXDrMqiR\nIFVCSRmNK5Z1Ktxo+xDKxvehzjTfxCjLSU20YNiANOw/chZVdTavR9Nqb8MvRvRGi70NJcdrUd/k\nQHKCBXHRJuw/chaf7C711sj+YmQf/OWNIlQzMohppCRakZYco9mDCeX91gQh/Mf6vBqr6zGgeCfx\ntZ8d3Y0ol9PbRMSP85OffsMG3FRWhhsk3fKnRN3ycCDdY1oL1YRYMzJSY1V50r60udxYdd94ONo8\nGvab2Z3k1BDMd0f+nHU5ARU1hLJNptruXe0tM+MERRd/UkNDRyiLhbL5QIvNiS8ojTsA4Mr+3TFj\nXD+43R58urfM69FU19vxye6TmDYmC3995FrUNTpQsP2HgHIX6edcnxphLUhGWa0HEw4lN1/ULA5Y\nn1dffSsMp8n9pqNYzRFkk5+kWw6rscPrWX3vcVWdzVtj7du7XLrXzy4cjd8++SlcGjLRbA433tp8\nBPf++kq/39udLmonsKgoHYD2Ge2keAuiLewIl/RZG/U6rDkv4nKu0eFXA67X65hRiU5bUAZLqNpk\nhqOkKxTRgEuYLvA0djwd0fg+lM0H1hSUMBOB9h85i8+KyqhZuVJIMT7GSDX+/91TCo9H9IY8AuBs\nI0+uVrMecdEmolFW68F0xP0moWVxwPq8rhgxAFFamyN0cj2r/B5L9rimwYGNO07AIwi485dicmFc\nrBn5P79clciKLyXHawKkalkRC4fThbyhvVB8vMb7/FjMepRVqvfyaxvsWLJie8DnSPqs7U43Glsu\nVFioec7CvaAMCaF81jqye1coowGXMJf8nerIxveh2DuzO11UJTKJ2vMZ4LR9SalO+l+fH6Maf8k7\nl8KXel0UcS984vA+VIU239+xPJiOut++56BFFViTNu3zmjN1ILBbY8ZsR05+CqhRBSvcV4Y5kwd4\n77WkYCYt3tRAU2hjRZikKgSpr/ue4jMqr+oCpM+RtBCkwXrOwrWgDCmhfNY6snuX1mgA98iJXPJG\nuyNVzkKxd6bUElENFrMe0RaDovH3RTLYVrMeDqc7INlIuidaPZOOvN8BIWGKY0SbtJmfl9aM2Y6c\n/HwhTGxqBExsDjcqa1uRmS7Wpev1OswY109VNYEETaFNTYTpk/OypSx0OmDClRn4+lgVzjUFahJI\nn6P0b7VIi1j5c9Zqc+LzInJJWqgWlB1CKJ+1jirp0hIN4B45kwiN94SPcKicaW3b6ItS60l1RKGu\nyR6U8Y+LNmHlfddQ1ajk6ldK7Q878n77jgWgZysriWgQPy81whO+sFoX5ue333NwuYDFi4GBA4Er\nrhD/v3gx4HJpeGb8IylJ8WZ0T1L/rNG2eZTEYdREAoDzYih5VxANNnDhc1SrsiaRFG8mPmfiNhS5\nbDGihVeCaZPZ2gocPy7+X44aZTStaFFS09IitKNh3adO4pI32sGqnHUUcvU01vhoEpVyHE4XgKig\njH9NvQ1mo56a/a0k0Smno+63WkMAtHNxoKXHrzT59ekjFtPrzyvG/ec/XgMbNIyJjXWPfflkV6lf\nn3HW32Wmx6lWaJMiFjT5USUjm5xg8fZQZ1VNSC1goy0GTc826TmzO1049AO5Dat0rogWXlFraBmL\nPS9aF6hqUKukpuSRh8t4qrlPnQSPNSAy6jZZYWb5+JLiLRgxMA06XRSxHlaOWJIVzew7zfpb2mQV\nbKg7lPdb2r92tLlVe1thW4xJk19bG/DKK4D7fD7ByZPBZfZKqAg1SveS1msb8G/yIaGkJqa0zaMm\nt4G1790t3oyVS8YjIdYMu9OFfUfOUm9DY4vD2wI21mpk7mNLZPWMx3zC3nRdo4MqbwoAOX1TIjM0\nLmX2zcgAACAASURBVKG2dlrLvnIoS7pYYffERMBkEv/dibkgfoQqG78DiBIErVpa4ePUqVPIy8tD\nYWEhMjIyOvx8HVXmoea4awuKiQZ12pgsb+ckefnK8IFp58u8TjKTh6Rj2GxOzHu60C+jNi7GhJ8P\nTsf2r04Rk9Skv6Vd18JlW4mTZfckK1Y/OIF5H9tzv+WLnJREK5pbncRr0OkACAjYlw8Lra3AgAGi\noZaTmQn7NwdR59JruwfHj4urf9KHrteL3tH5ia3V5sSrHx7C/w6cJmqL0z4ntZ+N9L74GCP+8ekx\nVbkNdqcroDe7hO/zvuq9A5q6l2X1jEezrQ019TYkJ1hgMRlgc7ThXKPDu9CdT2k4wnqWrWY93njs\nF4ixmlSPJWLwzXkAmM8iDh/u2IQvlwsYNgw4cCDwtXvuEY1ha6vo1ZL258MxRkDxOxuWMTCI4KVj\n+Al143u1SVpqMqrf3nwkIBP6450/YsLQXkyDPWFoL9w8qT8qalqw9M29fgYbAJpanPiutA5vPPYL\n/PUjcVEgGT6rWQ+PIMDt9njHK5/M21PW1p77Lc/yZYnCXDcyEzPG9QvtYkxtZivDc/CUleOJp/6N\nb3VJ2kqLNCQeRVtNuPm6bGw/cJp4KFpEROmzkT/bFpPeb8FEyrqW/424vSPA7nD79dsGgHUbSzS3\nG222teG5u8fgrc1HUHy8Bqeqm5GSaMX4q3ph/owcptFlPcsTh/fpegablMw1blznerFOJ1BXR37N\nNxmts7XNI8Xbp8CNdgeipnzE7nTh2Mk6amhP7JzUQjXqB76rQkqCGTUNgUkyKYkWuN0e3P38NqZR\nK61shMstIC7a5Dfx2hxufLzzR+iionDb1IHEBcgcn+xdVqg7lFEM1iLHajYg1mogymuGBK2ZrQwD\nWxWbjB9c0RCMGkuLNE5soRT6kVDbvMY36zrwb8Sw/YShvbBg5iC/8sHCfdpFfmrqbfjb5iN+AkHV\ndTZs3V+OWKsRd8zIZT6HkbBNFjJI4d3SUiAuDmhqCnx/ODp0qTWGna1tHq7KjyDhRruDUPKeb57U\n3y+cSGumIHZOiqIa9XONDlhM5JaY5xrt2P4N2cPyxeMBviuvZ47X5fYwa55pZW0dIVahJOCx7O7R\nMBsN2hcIarxnrXtdDAO7t+/wgE5hiqVFra3AiRPA3LniXvnmzYoTWyiFfgBtSX+SJ58UTy/LKpGV\nIlbWtlD34VmkJFqpyWS7i8/A5faIOvuU5/CikTdl5TzQCIcXq9YY+u7Pnzj/zGZlha/cKxK8fQaX\nfPZ4R6GUpLWmoMSvVIoW4h6Zk46kODO15hgA7M4L4WxdFGDQidJoakUydDogIcbIHK9SljitrE1r\nSZgalMrG0pJjtJXYqc0UDTazVZbZ6+rdBxuunIL1424NeCu1tMjlAhYtAtLSgNxc4Gc/A95+G7ju\nOnGPTSHDV2uPbhZ1jQ5VSV/ABU9ebV9xu9MVlP49ICaL0ZLJquvt2LyrVNVz2J4SzYiA5dG2tIgL\nvlCWc6klOhqYOpX82tSp/sbQ5QJ+/3vx94MHhz97uyPK3kJEF30qgydcmsKskGRygoUqdKLTAYIH\nfnt8VXU2VQY4LtqEq7ITsfOAeqEJAMhMi0fvtHjqeJPiLailTYZ1Nj+RDl+CVT9T+oxC7Tmq9p6D\n3euSZfa6klOx8eU98GgJV99/P7Bqlf/vmpqA114DzGbFjNZQeZFutwcF239Q3WZT+jyS4sEM0ZuN\nOrz4z69RfLxGtdHuFm9GfZPDG8a+8dqfYHfxGWoyImm8ES2aEiwsj7Z3b2D1avHfoVIbC6VymXSs\nF14QKy4kwp29HcGdzC6iJ5VNuDWFjXodtQxlUL9UbKU1ABGAP/3uavTvk+SdSMQFgAXVjPaYgOix\nONvoGuUk9Loo/PTybnC7Pcjtm0JM/hkx8EIHMcJw8dTrezCKcC+1loRp+Yzk+489o6MwLt2AX+Vd\nrun6NSk1MSZDT0YGdEp7XedLaCyAtkVHayvw0Uf04370kWp96fYmW67fdJipZGY1G+BwugL2g1kL\nrVirEb97tpCpry+ne5IVLywe59e5bG1BsaJMr5z2qvBFJGrDu+1NplLK75Ab89ZWYONG8rE2bhRL\nIjdvFrO2aaHFMOj2+xGBncwuoieVTbg1hddvOowTZxoDfi/Wieag+HgN1evwNdiAOOGNyu2pWGPN\n8ohpuD0CNn9Ziq37ymF3umEy6qCLAhxOj5+3b9DrqOev9rmXvp6c1gQoLZ+R13P8xU/guvc+RH/w\nH+jKy4FlGiUPtXjPjMmwMP1nKP3suLjAcNgVV+eakp4qKoBT5C5jAMTXOjij1e50obK2BbspWuE6\nnZilPyc/Gw0tbaoTvWKtRuL3RImROelIiDUjIdbsHR8tqmMxiU1uSAvI9oimRHQnsHAkc9EiVB6P\n+EDIjfmCBfTvWlmZv2ftpizgIiB7u7OJsCetYwhHkwq152u2tUEAqF44SxpSGi9tP5HlEQOA2aiD\nTqcjJvlI++JSd6/Lusfi+UVjvKUut00diJLjNcwJ9vOiMuwuPoOaBrvXSx4+MI0oACO/zmA/I8vv\nHwbWUMJoakJbWjNFly8H2trQ9O6HsJ6rRk1cCvb2HY71I2cD27/HyNefRW7Jl4qZ5ZrC1enpQEaG\neEwSGRkdltHqF/2os4Eq6iAAM8b1Q7TVhGhKeZT8mqMtBixZsV3TeKxmAyYO7x2wuGFFdZxtbvTr\nlUh8naaOxvpMukQnsI4O77IiVG+9BTT6zBPSd7Ktjf5d0+nohtqXUGdvd8GmJBHyhHUsapNgwnW+\nNQUlROOX0T0WN0/qT/w7X2nIVx+agPyrMwOSiubPyKXKUGZ0j8Wy/xtNlBYlcbqqGX/bfMT7c5vb\ng2ZbG/NvbA4Xquvtfok+AFQlQAX1GbEmjjfeALKzlSUIteg2nw8Hev7zH0TXnkVdTCL2X34V1o+7\nFR6dHrdtfwO5H7/D1EwmydQqJj1FRwO//CX99V/+UvWEIz+/En6JhIz3afFYpWuua1JOaIuKAqIA\npCZakDe0F958bCJRA5+ptx4F7C6ugNWsh9VsoD6HbrcHawuKsXDZVtz5zBYsXLYVawuK/aRegY5J\nruww5LK7odLSZkWoGikL+82bRd19EmoMNhC67O0IlilV4pLwtLWEaUMR8go2Ce1UVTPuXv4FRuX2\npK7aLSYDMrrHYcHMwcSx0iRP58/IRZvbQx0XiT0lFbh16kBYTAbNTRkkig5XYvWDExQ9yqBqiZUm\nDmnyUEpiURtKPB8OlD6V1OZzmHLwE7h1erw9ejZGHC8ij2XDBrj/9GesL/wxeO/sqadEYYqPPrpQ\nZxsXJ2YCqwh5BuMdaintGprdQ/X3RRrLbhXHtpj0GJXbkyqO4vsdoO2ZS/vZ0n533tBe+J1PXbiE\nWl2FcEbtQkaoO2exIlQ0ysvFCgij0f+7lp8v6vGTFMikve2MDHFxGmx4X+5RR7BMqRIR+HSFHjXZ\nxqEMebHOx0xCg1iaorTX7jtRpafE+L3GCrvq9TpN+uN1TQ5vkg7LqLK4kOgTw0z2CSojXOvEQUti\nURNKZHj1I44X4bPciUhtpDScKC/H+3//Hzb+cCFSoTqnQj7ZZmSIk+1994kegkqvI5icDi0Ltalj\nsqivyReX8rGwsDncfuIoEjRZ3ymjL0fR4Uqxo10UOQGNtGhWa4yD1dvv9P3vUBspVrIbjV69xP9I\n3zWjkXwsKYEtWEiLlfx84OOPye8Pd6JbEFwSRhtQTvwJdaIa7Xy3TOpPTULzhbRq17KwoGUJy8dF\n0qOWSPXxcC0mA3V/Wq8D3ITJEdAWNtWsSKV14lBKYmFlijK8+pQm0QhUx6cirbEq4HVPRga2V5DD\nboremXyyLSsD/v53IDlZ9WTb0OzAlwfJCWSs86tdqHVPsp4XAfKH9LwOze6B/YwmIFGQNwwNHKfb\n7cGSFdv9tpgkWd9pY7Kw+sEJOHayDo++tot4DpJxVWuMtUaEImL/W0uFBO3vSYtZyestKCB7yXJ8\nQ9vy75o82hUdLUaUmpvF35eVBbfIIC1WfBPe5HSBRLdLxmizPNCOCHmxzqfG2yVNLKFYWMjH9dG2\n7/HJbvIXTm3NM81gazkGaWyqvBL5lz0jAzh3LnipRtoExfDqa+JS4OmTieqxE5H28TuBh5w0Gadb\nyasjZslROydbyWDsPHga5yh5G6zzs6IfvtA+Y9LzyioXi4oCaO2LfMe5pqCYmhApfV/790lC9yT1\nxlWtMdYaEQp31QqRYPUFlELqUoRq3jxg0CD6h3fZZcCsWezQtlwFbfJk8ndYiyfM+v7o9eR99AiQ\nKVXikkhE84WU+NORiWqk8/mqU9Eg7bVr7V3t+7fy5CNpXHf+chCmjL4cVvMFKVSr2YApoy/383Dt\nTheKDleyL9YHnQ7IvzozKMUtTYpU8t6/334L3HYb+b2sJBZ5Ykp2trhfLO2LMxLWYm+ahRcfzUfu\nR28SVZQMLz7PVHCjRiLUTLYMJINBM9iK50egkprVbIDVrEcU/JO55M8Y63mlleCmJlqRmmhhjtPu\ndGFvCf05rK4Tv69a+7Zreb9adbn2fGdDitpe1nJoPdvvuMM/ZJ2VJfaMJ5GRIXb1UtuPOzoasFrp\nJY4qnnsvrO8PrXA/AmRKlbhkPG0WHdFQQdrDirYY/AQgAH+PktaiUD5RBLOX5k34KT6D6no7UhMt\nAUluer0Od/5yEOZMHoDK2lYAAtKSAw2m5kS08yVAYQsB+obbgqlRJYWh33oL+Pe/xUXA8uXU48b6\nJvMQ9us0i6lItKNxgdokMqVICCn6AcD7b6NeRwz/Xn91JvV5YUn2AmDep4qaFpxromsRSPoAgPbt\nFrXvVxsRCnb/O+QEo6XN8lLffBPYuvVCYhjr+CkpYr9sLYSqYYeSMtzkyaq0+yMNbrQRWllMuaGU\n5BO7JwXuZVlMBtx9wxDEWI1+E8XQ7B64/upMr6Y3ENzCYt3GEr89aCnJzSMIuPOXgwLugVyK1Dd5\nRmsiWntEK9qN1hpV1gTV1OS/l6bmuIS98aA6SLWjcYHSIis5wYKfD+qpOhIiz5GQ/i3vAy+Ff12M\nSoXURAuGZvfAtq9PezUDpDawt04eAIB+n5SeQ9/vq9btlja3B1NGZ+GGa68IWGiruSdyOsIZCBqt\nC1mWlwoE7jEvXw5s3x7YK/vAAXFBrGUfOlQNO1jHmTHjQv/uLlanzY32eULVlk++hyV5FbS9LN+J\npabehk07TmD/kbP4ZHcpusVZMCJHLNfSurAQ2xuSxTgK95VhzuQB1AmJljxDS0QjEZQGeKhRK0Go\nNEEBolGX9tKio8UvuYYve9Da38uXiw+Rr2BFXJz4O5eLGnJkGYxu8WasXDLeqyYWLCxvfv+Rsxia\n3YO4hz0qtycA+In8+LaBZd0npYRInS7Kr/+79DeScSVlcZMy0UPRkjPkGvntQetCVm1lhrTHDKjr\nla2WUCm6KR0nAmVKleBG+zyhaKigJiRJS2yzmAz4ZFep3yRX2yh2Jjr0Qw2WLxqjaWFRWdtK1WG2\nOdzUJh8APXlmyujLMW1Mlt/5hw9MAwBvmU3E9CDWsoJWM0GdPCker08f9fWuhDFo1v42GMRNYF/B\niqYmsXmITkf1YFgGY/Tgy+gGW8N9Uwr/Th2TBYNeF/C83jypP+5e/gXx73y/H1pDx24P/Ay/32uU\nraI5+dl4YNWOgEz0jTtOoMXWRqznpqFGN4EWSQsbao2U2sqMsrILe8zBJLvRCJWiWwQ3/ggWbrRl\ntKehgpp9X/lelu/eN83gn6pqxtynPsUvRoiJXWoWFm5FhSFypidr4eErlCLf/54zeUBk6DAHIyKh\nZoLS64GEBHq9a0OD2D0pOjq0QhbtyCDXFD2ijNm+9BnUtbqJn6tS+Dcl0RqwEHa7PVj57gFq8xva\nXq/0PdHrorDrELl8TYK0MKZtFR38vgonK5uJxyncX45Dx2uIzXB8USrrokXSIk7+VL5gW75cfK7f\nfJP+N+npF/aYQ7EPLSdUnnAX9KhpcKPdTnyNrqPNhZQEdjcuaS9L/kVPijMzs3ztTo9feF1pYfHZ\nXopONcQM4LTkGOJrlbUt1NaINfU21NTb8MmuUuIEJRd66RSCFZFYvlwM7/3tb+TXPR6gslJdco7H\n499GU+0YSF5usOU60Bg9oty3HXtPYtXP5xINjNrwr8VkQPckMWHt86KTzG5e8r3egByRKDC1BQDy\nwpi2VUQz2BJSM5xmWxsWULxuNWVdpEhaWMu/WBEU1iJz9Wrxuabp3vvuMYdiH5qjSAQs77omkk7x\nXc8WYv7TW/DbJ/+Lu5dvU9TnliYzuX4xy2D7oqZUxO50MQUsxl95WcDkI13PU+v2UDWmUxKt2LTj\nROTqLit5pSxlJYMBiI2lvy6VzKhJzqF5Jh99BJSUBI6DpYMcbLmOD4oldIz7lvvtLpicDurnrLb8\nSXreldpvyvd6pb+TFsJKBhsINPysrSK1bN1fjrueLQzQIldb1tVp5V9qNLZppV3338/WvR8yBHj6\naVHLvKZG7OJ1110BJY/tyshmaaWTXguVtnoEwz3tIKElnEmTg8Wkg93pIWaPt9ic+LxIhYIQATWl\nIkph+mljAz0zNdKSLDWriNBdbodXitZWUf+YxuTJYj2qmuQckigEIBr1wYMDw+VK0YGO9mAU1N6S\nWs6hMlFcHMg/ZzXefEOzAzsPnlYcRt7QXgHaAGq1z30JTPJSYelVQJIYVlvW1WnlX0rPlprtF3ky\nV3o6MGWKKD06aJCY7yGJlfTpI35XFi0SF5XBPp8s71+6Lt/Xpk4Vf79pU2i01SOYi+tqOhg1+88S\n8TFmPLdoJJLizAHlI2sKSoJe+ScnWIilImrLs0iSk0qTo7TguP7qTHyyu5T4nrDWndJoT32nUgb5\nokXB6S3L8fVkAHFS1DpphrqmVEHtrS6m24WfKZ8zKRdECm1/efCMYiSpe5IVv5s5yG9vV602gKSk\n5qtD4EtacgysZgOxJa1BFwWXGvfdB9+Fi9qyrk4p/1JjkNUudOXJXL//vf/3QMqhOXlSlAk1GtvX\neIO12Ghr85ciLS31346Sv582ji5Y7gVwo60KrfvPgDi5mY16JMSa/TJ17U4XtcsXACTGGlHfTA+x\nD+qXqkqPXG0fa4A9OUYBeOz2kchMj4fd6erwiaddjRXaU9/JMviZmaKhBC4YyvXr6R51fDy9PaEv\nGzaIEpDBTJqhnGQY921v3+FwGC98rlo+Zy2NQUjPpRptgOQEC5b93xi4PQL1mbGYDMgb1ov4fZg0\nsg/0PhnuJqPe21uehu/CRWlfHwAqalqYXcg6rPxLjUFOTwdiYsjPckyM/0JXSuZiLQYktJZ5+RpQ\ngH78118HbBpEnkjjCHXHszAT+SOMAOSTj5r95+QECxxtroCyjrpGh9iBiMKAzGTsOVxJ3bubk5/N\nHBurPIuWOcyaHFOTrEhLvlCu1FETT8gaKwTrlao1+AaDOAn4tsiUc8MNwP79QHExu0+wNKGqjQ50\nZAas7L41JvfAF5ddifXjbvV7m9rPWW1o22o2YOLw3sTnUo32+c8H9cT/b+/d46Oqzv3/z2RyJzME\nCEhIMuELLYooRrxbPVTRaikIHuHoES0RbwiGeMOqr5bjiyrleNCvQuultiJfbX96rEdApdUKaNXj\nvVwragNyD5JwSUKGXCbZvz8Wm+zZs9baa1/mlnner9e8lMzM3mvvWXs9az3reT7PoP6FhskeuJoF\nP/nB/0F3t4bPt3zH7V+6ez/YJwd/fOtrfLy5XjhZME9ceFH6Z48ajG5Nw+xH1hw/3xknDcJFZ5Rj\n89ZGHGhqi396pFtlMZGWuIqugWqaF8+A/vCH4sC3I/LAQaV2pHFZToCMtiVO99WOHO3EnEffjRkc\nZAYyO8uHr3YclAbbtHVGB8F8tImf/vLJ5no8+bNxSpHDdoyxVyI0ZjwrrOAmL1PF4IfDwMcfi7WR\nAeCDD4CvvrI+X0UF2ye//HLg6adj3584MXFuO9N96zPoBOxf/S1KHP7OVq7tfoFcjDnxBNwy+RQU\ncupk6+jn06PHdbJ8wNDSIK677EQ8e0wYxWyMAXCrjE28cBhKigtiRFt0975diWHevv4Lq7bE9Ge9\nMM/AfgX44RkVwhrhniGZiHZOmIjGsIb+DbuRJzKELS3sOTjxRPZvfTXct691bIdqmhfPgD7/PHOv\nd8qDepUwt8NtxbMUgIy2BVaDT/8gc5XrAWc6+p612fjIDGSkW8PBlg7huQYWR+9ns7bx08saDrcp\n1bHW8Vp32Q7xqLLmaFXKM/gA26cbOBCYN4892Dt2iKteAMA336id7/LLWbTtq6/aa2c8OXbf/ICr\n31k2OR3QN19ZkU3vb5Gu7qh0qW4N2La3Gfc9+SFXGEWHV2Us+9gxZYgkhmUTF93wW030Gw4d5dYI\njwumiahWUYHNp/wAi0t+jO8WvoOyQh/+c2ApgvsFue+LF/dEkhtXw1Z64ioTTpkB9cJgA7HbYm6C\nVVMEMtoWWAV1PXbHWITbInh1zTd4S5IbbTQ+PAPZEu6wDE4779QhUQNnYX52zGRBJyuLva+KXWPs\nRoTGTMoUVtApLIxVPjPv+8nc3qKKGDqVlUC/fsAf/iB2sQMsEnbhQvszfw8DbJz+zrLJ6Q9GD7El\noSpLYdy+jx878NGmvSxCjYNsImiOqXAycVENoEtIxoVpIrr08wN47dN6oJktDna3avhb6WmYIDLa\nq1ax/5oDvwCW8rV1q7wPy1Bxs6vg97PKYzk57JmRbYt5VYwkiQiXC+FenOdmB6uSfX2LWLT2379p\nkB7HWOJTN5C/ufdiPH3fJfjFjedKg1/6BXIx7swKTLvsxKi/h9siQvvQ3c3et4utspgeoU+MeMQ1\nslaWz2nOXbUzMPn94vf69AHOO48VUrA6pp0yhIBaTm4CUc3htuJQc7twf1nU/xsPt6FRIhJkLrer\n6xTMfmQNbl34DmY/suZ4TrbdZ0LWn63awSuj6wmFhWirqMSH/zwc89brp0+AcJq5a5d4NXzwIHOV\n83j9detcaZkGgR1uvRV46inmFdBL9P7jH/xyoJISu+kiAiPshZMmTcKvfvUrnHnmmZ6esLu7Gw8+\n+CC+/vpr5Obm4qGHHkKlqBZriiBzHXd1dePpVzcKVcR0eMbH6E4Trebzc/3w+7Ow5otd2LS1MWp/\nvG+fHBTk+bkr9EH9klhlyyYJLaygEjmqEh0r43vfYwMHj9ZW4KWX1I5jd+avEGDjKjrfJk63Uoxt\nzPFnYfl7dVKPEu/vJcX5gM/HfS55z6JnMRVQC6Azt8OzQEwJPA9AVncXJq57A92+LGRpnBtZWgrs\nEeTYy+I6VFzNTlMo/X4WJGfO3Vb1MMU7hTLOCJ+g//iP/8D999+PSy65BHfeeSdyc70JmHjnnXfQ\n0dGBl19+GevXr8fChQvx1FNPeXLseCEbfJ5dvokbrGKmqCDHUSBYW0fX8VW4eSD5w1tfC13qKVFl\nywbxCnCLQSVy1I3b7qc/BTo6xEbbDnZm/hYBNl2/fAjPrf42rkZBhKqLnWe4igpyovaszYQGBbB9\nX6zHQq8kpjIRjEdMhbE/q5QR9XLSIIK31TfjvaWYsOHP4i/178+M5A6OGFR5OfsvL9JbdcLJq2KX\nnW3tHXrjjZ5AToB5lFRTuNK8iIiwJ15wwQVYuXIlnnjiCUyZMgXz5s3DkCFDjr9v/H87fPHFF7jw\nwgsBAFVVVdi8ebOj4yQD8+BjJ7K8JdwhreozY+IoRLq68fHmehxqbkdJcT4ONbdzhR8+3lyPf7tk\nhPDcBXl+XHXR947nh6aD8Y5HgFvMzDscBv7nf/if/dOfgJ//HCgpUS9LaCYUAvLyxPrlqgSDwA03\n2Jv5WwTYvPLi37Cyrie4J6G61wq0dUTw1KsbscYwAd5/6KjQ4Pl8QOXgAFqPbQHpK26ewIrVRDAe\nMRXG/vzdwVYsevEL7PyuBd3drK1DBwePp2/GJRCTg3lxkNfZjnO2fir/0saNbO+aZ7R1VTQ3an28\nKnZWBruwEJg5k6309aA4Yx1v1RSuNC0iIu0JBQUFqK2txb59+3DbbbchGAxC0zT4fD6sXr3a0QmP\nHDmCIoPGs9/vRyQSQXYaJLWbUQ04AYADTW3Ch19fYXy+5TscamlH/2A+cnP8QqWmxsNHsb2+WXju\no+1duOvxv+FgS1vqVRKywJMAN54LfOJEVrFIZNj27GGD05QpzFiK3HaBAMsV5eWwFhcz0RWnFBUB\nV13F9uaC/LKpQiQTje7ycrxXzx8Iky0/ay4IooqmAdvre1bYuov8rJMHR01CVCaC+t95iml5x1TP\nnJKfm423P94Z09Zte5uxbNUW3Dz51IQGYho9ANnb6zGwRR6LA4DFfsycCfz5z9GSpStXAhdfzN77\ny1+cuZqdbEW1tPTEg8gm1mmSwmUXaU949913MX/+fFxwwQVYu3ZtlLF1SlFREVpbW4//u7u7Oy0N\nNqCm2KQjC6gyu8YONMsHr5LiAgwtDUrPrR8j1VZUcSccBmbPji7awZM55LFnT4+hFu17zZ/PVrWL\nF7PIWv0982zfDqEQG/yeeMK+sdaR7A+GL/sJ9oTFE8BER+cb96zN+cyqiPayP9/yXYxHS20iKBJH\ncKdbrrKKTqTEaZRHa9/p8L2zkL+KNtLSwlTIfvxjpiegZ07s3s28SoEAcP31PXrjADumitu5vl4s\npOKWNEnhsouwJ8+ZMwdffvklHn74YZx33nmenXDMmDFYu3Ytxo8fj/Xr12PEiBGeHTvemIN4VANO\nAPEesxPxllOGl6BvUR7OHHlCVO6qjGSvqOKOvrp+7TX3g4A+QxftewWDrGShUWzCKmAzEOBHi0+f\nztJpvFgNCCYa2QsWYuBjf0us7jUH8551SXEBjoTFugQyxFHj9ichh5rbhbEhbe1driY1aqvoSqtF\nNQAAIABJREFUPgmXOM3PzUZpaCAwebJaINjq1cDh2MhzAKxfP/lkzwp8xQpg716W2mglD1paCgwZ\nIg52c8tjj7HrS9OFIQ/hlQwcOBArV65EoceuhUsvvRQffvghrrnmGmiahgULFnh6/HjAG2xOHV6C\nWyafEhNANaBvPgKFuThytFMpoMqOix1g+9U3TTwZzy7fhM++3AegZ9WhC73wSImCHvGktjY6l9QN\nxhk6b9/LuFc+fDhzH1oFrlVXsx+KF7Hq1YAiCLDJB+JmFOxEo5s9SlYZFzrBPrk4crTj+H5waFAA\nre0R5chwK/oF8zCon1jG1+mkpq0jgvbOLpQUF1i2NWGBmGaMEz2Zq3nvXmv9gWeeYUGYOry9ZXOc\nie4hEj27evpkRQUwfjyrxGflGdDp6vKmeEmK4dM0kcBs8tm9ezfGjRuH1atXo1yPVEwCzy7fxB3w\nCvL8uPTsSsyYOAqdXd1Rg5fqYNbWEcHsR9YoudgBYPz5Q5Htz+K257JzQlj3TYNQCOY3917c+1ba\nkQgz2M88Ixc8scPQoSzP0zxhFaWLzZ/PSm7yBj2/n+WR6rP9JFUWMk48zUbBSayD3RQlu/0cYH1W\nFD0+bEiQ+/crLhzmaBtI9Iw7OZ753uTn8tMyecdOZEpeFOEwU/K78EK+vveQIcxwO2HoUGDDBuD+\n+9mzU18fm6515pnsM2ZmzmTPnP683HEH3zMwejR7ZnljgOh5TlN62QjuPTL39dH2rqj9Yq+Vo3j8\n6JwQFjz/Gfe9dd80CF3m6ZYCpsw993i3wtYRRb7K0sVEgWu33spc6TpJilj1OjrfboqSXY/SuDMr\ncO1lJ2Hukr9x328Jd2D8+UPx+ZbvPFmZernSNd8b3WAX5GWjvSMiPbaXSoO2KCxkgZg33sjvx5Mn\ns/1ruwU7ADbBPfdcYMuWnr+ZV+H/8i98o52T0/O8RCJstW/cagoG2RbT7NnAyJGx3wd63d52LxzF\n3WGe6aoMNnoKVrgtgr59crBs1RZ8vLkeB5vbj9eilq1ozAMGfHxP1KB+BfD7/dI9sokXDkO2odRg\nwtxsycBJ5KnViqGoCDh0iKWgGIPCrAoN6AOO14INHq/MvTAKTlKUVIM2Bxbn45xjCoT3LnlfuN1z\noKkNk8d+DzdMHOXJJMSrSY3s3hQVZOORmgsweEBiFQdjkPUpvb8uX84CzcrLgSuuYH8TyMJaUlAQ\nbbCNrFjBUi1XruS/b5Tyveee2IDS5ma2Z1JRwfbQ01ieVBUy2scQufumXXai5WCz/9BR1D76Lg62\ntMHv80WlaqlEb5sHjOXv1QlXy4MHFEojTUuKC7zPd05V7IqgVFYCr7wCnHOOuOzgkSNsRfHaa8CM\nGT17zlaFBhoaxMVGnBjcVKn5yxngnaQoqXiUfD7gvuln480Pv43K1+ah7wd7vTJ1ezzZvTnQ1Ia8\nnOzkPY92+pSmsZWDpgHvvy/OjPD5mGHfs0e85y3bgd21i+WCq9T9tqrOpVJatxeQ+om7CUJ3ae0/\ndBSa1mNs//DW10LtcSMHmtugaRDmVn+8ud5ST1jXOL5l8qlRms0Di/OPa49baaHrA0IyNMQTjl3t\n4oMHWSqYyndaWnqqG+nnEsVVGGfyerGRBx5wpgGua6LX1kZrn+vuRL09Vt93WztAomPuVCt+xsRR\nGH/+UOEp/T4ffvX8J5YGG0jd7Z6k6OjLMPYHs54+r0/pn9m5kxnbnTvFBjsUYgb3gw/kQWqyvlha\nyvajRc+k/mypVOdatIg9N0OHsliSoUPZv9NEnlQVMtqwdvddfcn3MWyIw/zZYzQcii0OIEJfeS++\n+4f44RkVgM+HNV/sQs2j7+LZ5ZswffxITwoxpD0y8f/Ro2NznvXUlH791M+xYgVzwT3wAHOb8zDP\n5FUGRzNmI/nMM+L28AZBr4uFSK5BdeJoxu/Pwg0TRyE/lz/sRLo1NDbJn5H+wbyU7utO743nmPvD\nyJFi4R+9T9ndbtqzh7m+6+rknxs0SPzeFVcwFUKrIh6yCbpu2PXsCauiIWlO77oah1i5+37/+pdS\n/WMV+gXzbM+y//jW1zGyjkZXu1MXeNIiVOOBTARl1KhoeUSd/fuBadOA996TFz0A2DHnzGHayGZ4\ncqPNzfLBUaTQZA5yk7XHHFQTDrO63MY2qko58rDav1+wwHHg1qHmdrR1WKQOCbBThzuZJC19y4i5\nP8m0C4zV5OxsN+nGsm/fnhxtHgYxrSiqqqLFjMwa5IEA+1skIi8uYp40p6k8qSppPmJ7gyxIZkDf\nfGza2uj6HHZn2arBPnb23xJRSSjhiMT/t24VG+S9e1kt64oKtgIRBckAzCW+Zg3/veJidl7jTL62\nVlxyUxTFameFY3TFqwjKOJFyVHBF+ocPdzRxlOVEW2G3DneyiIuOvh3srpiNfcqO5r5uLAsLgVNP\nFbvRdaMdDLKYkdLSHgOsPzs8DfKWFhZ4lpXFnvE0r87lFWk6UnuLzKU1+nsDWUS3C4YNCeIWm7me\nKsE+dhHt2z/3+j9sHyvl0GfXunHSZ/8ydu1iBruqSiwfetFFYrWmPXui612Hw2IDDwBlZfwoVjtS\njsZVhXH/UYTdmtyAmivSIbJnTURBnj+lXeIikhZXYjdA02h8RW7qqir5XvFHH7HPZElMSnExy7L4\n5huWBmmc7Fp5d8LhjHF/W5FZVytB5NKadtmJ2LS10dHKYEDffJwzajBumXyq7ZWs13rEiaoklDI0\nNamLrRw+zAaB++4D1q5lxtjoZn/3XbVUkvp6ubv9jDP4fy8tZalmohW6TlFRj7uwo0NtNeXEyCq4\nIt14bXjPWmFeNrfEJgAECnNx/fiRMccVbfPItn961daQmXAY2LaN6YSXl/Mnc8EgM57GPm40vrLV\nbEeHOFUsPx9Ytw74938X14vX98B5Xh+VQDPdQ9XL3d9W9LJe6xyZS8uO+AnAAsN+ceO5GDyg0PHA\nIEuRcRLQkshKQilBaSmL4laRPNy1i7nwnn+en8OqupcmK+np87GBcNQo56lbR470uAtratRWUxMn\nOkt3MQ/eZWXM6zB/PgB39Z95z9re/S2o/b98IRVz/xRNGKaPH3lcI8E8kWjriOC3yzdj09ZGNPaW\nrSGdSAS46y7Wf/WJX04O/7M33CCvIy2rNZ2dLTeWzc2szrUIkacJkD87vSzP2i1p3lu9h+fSmjFx\n1PFobRXOPaUUQ0uDjg12W0cE9Y2tuPayEz2LEk+5VJR4U1jIVJxUMKdsGd3sgHoqicy9qOe98iLJ\n6+vFwTo8Vqxg7n876W520QfvDRtYBScAeOEF4LTT0FkzB59u4HsUVFIbdfJzszGoXwFeWLUFDy0V\n13U290/RNs/cJe9z/37X4+/hhl++jTWf70JDb9wa0kVHjJ6azmO104PB2D7L6+NmjKtZ1RTCOXPk\nimkXXSQ+p+zZGTuW/3ev0hudkMRzk/a4Ddo6Img8fBSvv78Nn2/5Dg2HjiI/zw/AFyNP6KWe87TL\nTkRTa6drd59IX/niMytw21WjXU0yUtLlqAdqPfec3PVcVQV89pn1yldFncwsYOHzyfWQAebS/MlP\n1Pe1/X7mzl+yxDriXEV3WXZdAq3nFWMm4Hc/vCnm71k+4On7LkFpSR+FCxH3SSNGjW6ZhrmoXKeM\ntNfkD4dZMKWo75SXszrYw4bZ87jYFfcJh4GTThJ7fwIBtnUkKz1rPmefY32otTVWqzxZwkMpIHpE\nRtshRkMFwBOjZadogZM9RXPRiLzcbAAajrZ3Kcmtyo6X0tHozc1slbF2rdhdXlvrbSWgxkbgL39h\nusg8S5KVBfz0p2y/XB+grPa0dXRDnJvLBpBXXxXvpfv9LKr3lFNi37MagMJh4OSTufesofgE3Hb9\nYrTnRHtorIyg+bmRFRHh9cn6xlbcuvAdqciWHUSTDJWJaMImq7JJ1datLA9bNFvJymKBX3b3gEWF\nOUTPiVU7qquBpUvVzh0OMy3x55/nnx+w1zbVc6rIBdu9L3GAjHaKIFtB8AZCN1WJ2joiePrVjVjN\nUZ6yU9VI1Ibx5w/F5LHfS72Vd2Mjq8bF0x73qhKQ0RDu2MEGTd5KW1RfOzc3urwhD/MA0djIvAWi\nKPdQCLjyytjVgNUAJBmIu7P8uLX619hXHL3XKOo/vAneKcNLhOpnPgCL77kIQ0ujV2bxXmmrTEQT\nNllVWdVZrbRDIZYhYadfSyZrwuckHGbxGrw9aZVVtur5QyH2fOzbp942GXZWzk7uSxxIoeVQZmMn\nxcsqElxlT1GUe676fVkb/vLxdtzyq3cw+5E1eHb5JnR1GUbSZO5DNTXxH3bAWWoUD6OSmKbZLxd6\nwgnAtdeySHEdvVBDZSV/L72kBJgyRXzMnTuBJ55A55139fxNJcVGkvrlC1XgvB+NUY634O1Dr/l8\nFwry+Gl5A4/Fj5j7oixlbOhg+6qF5qBOlbTIhKVOqijrFRayCZmIK6+0b0isIrm3bYt9hmV70jNm\nqBtsq/Pv3OntM2xHvVAlwj0BkNFOEewEitk18PWNrVGDnxc54LJj6KudqMHMa5lNJ8Qx/xiA3BD6\n/T0BQdOniwPPdu1ikb979gCbNrHX/v1MKvLLL8V5qXqwXGWlsHmHX/xvPPfyp2wSpTIASQZi36RJ\nmHH12fjNvRfj6fsuwW/uvRg3C1IbZRM8tqaOpSXcgTmPruVO/IyBocYJw3/VXBjzd5H8cEFedswk\nQ2UybGvC7GaCqjKp0lm0iNWdNk70AgGWYeBEeET2nBQWsvgL3jO8aBE7ZyAQ3Q49TdGL88uw+wzb\nucdW7UpghHsK+S7TG7f7W3ZSvFRyuGUuPC9ywFVLLQJsMKte/Sxyfm0oq+dGZtMpdqQQnSAzhJoG\n/PWvrK4wwCRURcpTy5axXFrjfSkpkZ9bj/a+6Samu87Z9erX1ICP3v47uvIKcPOPhqul2FioUKmo\n8skmeO0dEYw7s+J4KlZebjaOtkeO16DmpZLJ0jPNf8/xZ0XFcQzom4/R3xuIWyafgsKCXOV2Giez\nlqmTxXAfrKSat6y7d//yFzYRLC0FLr6YaezbWd3q6Hu748fz69S3tPRs65ifYV3VzLjtY1Y1U0H2\nnMqw+wzbyQ23alcCK4nRStslXV3deHb5Jsx+ZA1uXShwCSsiWkGYXY4qRQlkLjwvihrYUbZqbjgM\n34oV/DdFBTDiRTwrAclm4uXlPYUTZK5EHaf3Zdgw4Wq7MVCCQ336sxVhdq51kQbAExUqKy/SzKtG\n4zf3Xown7v4higr4xzWuYnXvEQCu4pgxbVM38LpH4MmfjcMd/z4mxmADQGF+NvoH8oXt1OsHWHrE\nnBSMMaO6qjNvx9TXM4neefPUzwXEesLefJPFSVRWsuekokL8m6sUHLHbn83PqYyyMmfPsJOVcwpU\nEqOVtkvciEyYsaNZPGPiKHRGurD2i91o62CrkoI8P7o1DeGjHZbqZ14UNTAfAz5+INBwfxj+PYLo\nZpEed7yQiUe4RTYTP3SIBcHpq66FC9keOy9CFnB+XyRt+GT42WjPyetZEdrRcnahQqXqRcrLyUZj\nUxv3GI2Hj6Lx8FH8+X+3OwoAk3kEjF6pA8388xvbKb2WiESpzo4OvMqqTqGwi3LfNhcY2bGDvWbO\nZAprr7widnGrFBwx9meVSG3jcypLiSwvZ0psVp4oHk5WzvEcPxQho+2CeEmDWrkc9UHm3b/3GGwA\nONrehTc++BZH2yIK6md9XBc1ME8ylr9Xh1X/uz3mcyPOORm+VFM7ipcUotkQFhbyXYqHD7PPrlnD\nH4zc3JeFC9G19l1g0yZkad3o8mVhR0kIz1/4UwCGFWECByCVSaLVts3r72+L6l9uJshGzBNvI8a0\nM6Vr2f6t1HC179iFgwPL1Z43q0mVXfeuCJnx/+Mf+ZXyjJSXWxccqagABg5kq3k72waFhSxd8cor\n+cb1qqucGWwdp0VIkiilSkbbBfGUBpXtkcsGGQDYWNeAkuICNCjsWdutFMZDP8Ytk09Ftj8rZjCb\nPnEU8FHy94ISAm+FwEvtWraM5Y3378832lb3RbZaue8++Ddu6GmS1o3hDdtR/f7/w+8uuil2CyQB\nA5CKF0m2Ij9z5An4fMt33GO7mSDLJt79g3l47I6xPZXFjt1zf2mp+FokcpzNA07Az/6/r7En/JWa\nl8BqUuVE+pPXb2TG38pgA9FKZ7KV67x50e/ZiWuJV4WvFFg524WMtgvcBHSJxFmMgTM8VbTC/GxJ\nJC7jQFMbfnhGBTcH1oluuSrSgTnTyuoVFrLiCDJ98J072auqiq28Ve6LiiCKYNV0/ref4cDPfsEm\nUUnCapIoWsX++Pyh+PNH27nfsT1BNhiuQ2FNOPE+3NKOcFsEffP93Huev2hRrPKbxOW6tmwMdrey\nAEGpl8BsWEWTKjvuXVm/kRl/KwKB6PPL6tuPHs0/hoorP97GNY2KkJDRdoGToh7G/bP9h44ey1P1\noa0jgoHFBSgqyMG2vT2zW/3h/uunO9HWEUH/QL5w302npLgAt0w+BUUFOa72rJ3CHZjTcEZrG/Ng\nq1q96/BhJqPa1GR9X8x7j+bVimTVVNLSiBlnDgCMKzuV/UVVtSgPEE389OfDaoIszeLgGK6SCRNx\nQsmPsa85VtAmJrBMx2qFaDJc3eXlWF16Op479/qYj0Z5CSIRFtS0YgW73yruY9XJcG1tdDS4+RpE\n0eJWXH99dJS6rL69F658kXFNYB9NNqSI5hKzNKiV/riK1rJbzFrNXkotpqzOeDIRrWLmz2f7fVZG\nW5caLSgQDzp62UVRQI5Ry1ykTHXCCcCnn7L2qShBJUNnWTL4ylQAZ0wcZa1SJlCA2zRhGh4YMZV7\n3Jt/NNy5Ctaxa6nPCeLWxf/LlV49LqNanAecdRbrB2ZUJDJF902fCDzzjFwDf9cuph2uis/HotUr\nK1lhHqs+IVMTq6xkGgROjG0KaIEnmt55VQlEtjLYf+holHGTi0y4pyAvG5eeHYpaTXuxZw2kkc54\nMhCtxA4fVqvepQtW7N4dO+iYZVFFc2zjakXkMv3uO5YSduqpwA9+APzmN7FtBnoMhN0VphsUBl9Z\nAJhlFodk2+CUzR/iyuvm4MN/HrYdWCZdIR5bFfZT8RLU1vINNqDmPhatQO+5R76C1q+hooIZcN5k\nz1iDu6CAVfLS++GOHWp9orAQ6NePb7T79XO+Ok5kH00RaKXtEfoKtG+fHPzhra+5xm3/oaOeFjvo\nH8zD4ZZ2qWCEV7jROu/VyLSfy8rY4MbTOrdi+nQ22D7wgJrIhHHVZzSAon3KnJye8o284wCJ1Vm2\nUYjB7O1R0u3ftUNc0OJY1bS2ispYL5JMU9vGfZA+Pz8aDnz/++J+old1s+sWlq1ujdegb8089hjf\nwNfWWqdeqXgdvF5pp4gWeKKhlbZLzCvQ/GOKTjrGGf/140cqq4hZMaBvPh65/UJ0dWtxd1XHK7Wt\nV1BfLy7WICrgocKyZSwd7PBhtc/zBFHmzBGvAnkGG7Cfc+sFNvONzd4jpSwOhUhrrlfKIxUsyzQx\nmW51aWlsJLiKW1gWFa5TXMzc8jt3svtQVcU0BXbvjt4fz85mq2xRNTmrPiFry+7dzvqTVylvaUaG\n+zXdY1YeMxpsI7rRU1ERGzYkeFwVTVRQ4UBTG+5/8gO88cE25MTZPe2FVnlaI9OQ7tvXWrHJKbt2\nyffDs7JiFZmMbZ071/459VShBOkst3VEsP8fW6HJCkRYFGJQUimTqdBZGV8PVLDMymxRWu2lpVLN\neFxxRWz7VFTXZL+h38+iudev7znGjh3s3z/5CV/9zk2fiEd/ShEt8ERDRtsFdvaodeNmlCr1gRnl\ngrzsKNnSx+4Ye/zhXvqLHx3/vJm4VRcyYaeYSa9CpchJU5O9Sl5FRczYVlYC113HBhenXHttz8AK\nRLd15Ejg7bftH1M3YG6MnAJG+d9ZL25BY3Ag/4M+H3PbSgpOKMvyOjW+Hki5GtsaI70qu9dVVbGr\nfJln4rnnenKrrSpvNTXx31u1iu9ud9Mn4tGf4txHUxXa03ZBfWOr8h61uW6vKE9b5GZuOtKOOY+u\nxUHOqpZXb9trMnJPW2WfVWXf0MzIkSxAbfduoE8f6+hyEcZ9O1FbRfj9bLLh97NVVigUGwVsdMGa\n04lcRuaa+9NNa3+HSeveEH6+8/Ya5CxZLHzfVhaHYB84qZkRZnd3aWmPW958ryV1zgEA1dXA0qWx\nxzX+hrfdxvqtZI+f61pW6ROySHav+1Mc+2iqQkbbBbIAGDNujdv2+mbULFrLfe942ohZ6MFD7Ka2\npT12glzsGkweRUUsKtcO+uBaWmp/4mBm1qzoaHIjHufA8p6brO4u3Lz2d/jxxrfg12INSUPxCXj9\n6ZWYPuVMaX9zYnhTKjNCNW9eFPwI8AO7zMd1G2DHa6dq+pVV8JyTvpZBedq9cLRNHDK3XEGeX1qp\nSxXdjTj/9x8LP5MIF7V0T643YqfgvdHt6uPXh7ZkwADmLudhrE9sRN+3Uwk4smLVKnEVJj2dSHUw\ntKgjzYuR6M7yY8UZVwhT2vSyolZbQVz3swWyingJR+VeFxYy6VARemCX7LhuXcu8dqpWN+N9V2Ur\nym57eim9dMRNHKJymkt/8SNPjJs+oPB0xHXiKU1qxsmgmHZEImwfVWSAzUEuxj3PiROdnXP3buDn\nP+fvuVZX87+jD66ygJxgkL3n9zOhFxHmiYiF4eWiOPDyYiSyursw6YuVwnseVVa0Q3EgV8AqM8LL\nc3nK4sXWkzkr7OzxW/UHt2U5vShnmiH04pE3Mcj0tvu4zJm2CnQbWJyP804dkhBp0ozCSpBCthL5\n7DNn56yoYC+eBGQkwoLXRFKVsrSkYcOA994DGhpYpPtZZ8kLTLhRmFIUuuDJ/854bykmbPiz8NAx\nZUU9EAwC4lv0J64EgyyYzE0qmoq0sGp/cJN+5WWJ0QyAVtoeEY8VqGxA8fmAeTed27td1MlANoD4\n/WzvVxRtXF8P7Nvn7LzGgdbs6lOJXl60iEUam1m/nlVXGj6clTC0cok6XfHYXGkZPVT5kXac/y1/\nshPxZeGN036M58beAMD7raC0zoxwGg1vXDVb7QWL+kNtbfTn3KRf2dmKIshopzKyAWVgcQEGD4hf\n4JmZto4I6htbU9dd6BWyAUTTWP3ejtjiEgBYveCiIvnxKyuZ4ZcNtCJXpGzfrqODiWLwWL6cHSsS\nYQOv0a0aCAA1Nez8blycNgdeY4zE/71mBEqaG/jf1TSsOOMKdGexXHi3W0HmfqycLpZMRP3Bbiqa\ncfvi+98HBg9mrxEj2Gv2bJYuZjToov7wzDOsWIhKepnVyl9m8I21ugkAZLQTglODlwoDijGf9taF\n72D2I2vw7PJN6OoSpJukO7IBxOcDLrlEHCQzb551+tbkySxK2zjQLljAIr+bm2P3hGfPZp8zD9jm\ngby+Xhw9rguU3HMPsGRJdBtbWpjrPTvb3YrHzkrrWNu7Wo7ghVVb8PCfd2J/UQn3q4eKB+FwUX/P\nAjr1fnznQ6vw0lOr0NVyRBiXkvRtJ9XgLNUgLOOqWdPYb9/SwiZye/awLaGSkp5zzZol7g9dXcCL\nLzKjqrdp4ULm7dHFhrKymIDLwoU93+NNQGQG/+BBJuWrGpCWCWgpzK5du7QRI0Zou3btSnZTHBGJ\ndGm/fW2jNuOXb2kT716uzfjlW9pvX9uoRSJdjo5xhcNjuOG3r23UJty1POb129c2JuT8SaG2VtPY\nsCZ/1db2fKe1VdMqK8Wfrahgn+/s7PlOZyf729ChmpaVpWmBgPj7Q4eyzx49Gv0d/e/19Zrm9/O/\n6/dr2o4d4vYNHcra39rK/l/2GQkdt9eI71Nrq6Z99ZWmzZp1vO1Ng4Zoy0+foF1xx6va8tMncL/b\ncXuNtrfhiHa0vVN6biv0fqyfqz44SIvApzUNGnL8dzna3unJuaS0tmpaXZ3lvdQ0TdwPzf1O5XhW\n/VP06tNH/VkQtbeqStxv9edBfxaCQetrznAyPk87noIKXgqSJEP4QakQQyq4D71GD75ZurTH/cfD\nmM8qE7zQS2+eckr0353kd48eDWzcGPv36mrg+efF31u9Grj0UmsxDRuFO3T0POdPN+zGhJVP4vxt\nn2FAcyN8oQr49Gj6118XFi9ZcfoEPDf2Bsx4bynO2fopSloakRWqQJZKyUcFjP1YKOKiUv7SDXYD\n/GQ6AYEAu5fz56sfz0qQxS2VlezYopW5qN+ahYpOOol/jF5cAMQuGWu04y2o0BsMnkzxLRGCLklF\nNoDoGI2dXbEKJ0pqMkIh1lbuj5UFfPstMHasdfvsKkyFw3hp2bv405YjaM9hQVt5ne3o13oQ5/1o\nDGZ89EfLicm+4CDcPn0J2nPykNfZjgHhg3hw3lUoDQmkTW2i9+Pcjnb8elkNBjfvj/1QvI2C3cmQ\nlZEdORLYskX9eLL+6QW6wp6IrCz+tdiZ+IpU2jKMjN3TjregQm8ospHWkbVuqa+3rtJl3KuV7cuN\nHcs/vltBFCN79ohrbWsaq+qlEihkDm767DMWqGYOvju239p98smYOnsCfr2sBjet/R2yunsG7vXr\nd6DrNUEgk4GSlkb0az0IAGjPyUNk6DD0G9zP8nuq6P24X+tBDBQFvMUzStlJgF9pqTyv/ptv7B1P\n1j+9wCpgTDT5MN73DC0AYpeMNNqJEFToDQYvFQLhkoZsANExR8XqKTihEAtaKypirswXXogNIlI5\nvh3Ky8XFR0Ihdj47KUK5uSxo7ayz+EFQx4KasnbsgF/TMLh5PyatewOP/eFu/HpZDZ5+bhbm/fo2\n+HZaexJ04RQdr/uW3o8P9emPBlFhksJCFv0fD5wE+FmpnolWtbLJh/77l5XJ2+uEyZOBK68Uvy+q\nhKc68e3FBUDskpFGOxGr4N5i8FI2sjbeyAaQYFBcDlNH05iWuB6da8539nrlM3ky8K8nz30RAAAg\nAElEQVT/Kn6vsJCtlmtq2OrZKkVIlq8tWTkOb9iOwc374YeGkiMHlAaY9sIidObmxbVvzZg4Cpdd\nPBKbTj6f/4GWFhb9b8SJKhwP2QRt8GAmesM7p0z1LEtwZ2UrUt2Lsn69c8M9eDAwbVqPyp5x4vfE\nE3ytAAA4VRDDI5r4GieWs2axAiduf4feQnLj4OTEK3r8aHunNuOXb3Gjomf88i3PokeTHfntJQmJ\nrE01jNHdfr+mhUKaNn26pjU1xb5vFf3Ni8Lu7GTR1KKob9krK4t9zxiFa26vVcR5p+C3lEUaDx2q\naZs2sePYbbPg1RUKaXt37E9I3zracECLFBXJfxvz72p1v1SQZSQMHappNTXsZT5njSAiXxbF7aY9\nonujv2bNYt8XRa0fPappo0f39A+/n0WPt7Tw+6asD5qyDTz5HXoBGWm0NS2xqUwZafB6E6IBSjU1\nzPjy+3uOVVfHDKDPZ/84N98sTvUxt1cldchIXZ3YKPv9rM2i1DCeUQa0xsK+WrfVPUkEVtdWV2f/\nfqlgnAjY+Z1ranq+J+onPp99g8ab4E2fLp+MnXSS9fGt7p2xb1qlq8Xjd+gFZKzR7k2rYCIJOM17\nrayMXj2EQuIVuihntapKfXCWtTMUYgbYPGg2NGhaWRn/O/pq1MaEpT44SJt+47NaQ9EA+TETgdW1\nNTRY57PH6/yyczY0aNqQIfzPDBrE8vCdoBvOhgbWF0Ih/jkCgR4Pk4imJnFfNnuYrDwZTvpthpCx\nRluHVsEZih2RCx6yFZvsVVWl/lnjKsvv17Tycmbw9cFN5Rqs2mkcNI1udNHn9VWObIA2vZafPkGb\ncNdyoYCK05WTrWdXZaVbW6u2Ele99zzq6ux5VvRzWv2Offqw/mI2fLw2Gv+uusVjXik3NMQeu7ra\n+jo0TW0FbaffZpi7POONNpFheLVfKVMPM7909+WsWeLVQyDAVlK8/T7z4GvnGuy0UzSh4LlfLYxP\nN6A1DyzV3j53sjb5zle1Gb98S3v2T3/Xum67ja00Be1WMcSRSJf2+5c+0X5251Lt32/7f9rP7lyq\n/f6lT+ReMoGh6Aa0rsrKnnZYqcI1NbnrP62typOd4+e0UqszG76mJk2bNk3TSkvFkzL976LfPBiM\nnijq39X7rx6Hod+7pibxKh1gioD6dah4Muz02wxzl5PRJqLo9Z4HL/fJRMcKBHoC16ZN07R163oM\nr9XqvKwsejXtxTWourJFAXFDhmjap59Gr6paW+Vu3qwsTdu0qac/tZoMhuk6lSV/Ozu1jROmafWB\ngVoXoHX6srQuQNsXHKhtnDBNPHERGIr9RQO0mvv+O/pcsvvrtv/YNdrG46r8joGApuXk8N+z4+Up\nKmJGX5+wWX3Xaj985Eh2DaqeDDv9NpHbKylAUoz222+/rd11112WnyOjnTi80ElPeVRn+aqIorUP\nHGCuwlAoeqXT1OR+9WDnGvSJgnl1qDpwG1/G1XZTEzvujTeqD6QWxk41MFSob37s1XF7Tew9kxiK\nTl+WdtOMp6LPJfpdm5rc9x+riZt5BWvWqpe5oK1eTrIUVF+hEFtNi943rrRFz0BlZfQ9NHuUZNeV\nqEDGFCDhedoPPfQQHn30UXTHSwOXcES8FeJSAq/r9opKI86fz3TAd+6MznGeN089N1ukbKVyDebq\nUKedxt7fsAH4+GOx0IUMTeu5jvJydtz//m/x5/X823AY2LwZ+J//4X9uxQq0HW5WEzsKh+FbsULa\nTN/KlbH3TZInbRR2OX4u0e/a0OC+/1iJ6uiiKT/5SWwOfXY2qxDnVNJZJjPqlj17mBCPiL172f2x\nU9HL+Dts2EBqacdIuNEeM2YMHnzwwUSflpCQCIW4lCBeMonG0ohWkpXz50eLR4gQGQGZvKV+DSJh\nlHnzgP793Q/eumCMqAxpMMjOpU8cTjtNauya/7lDTexo1y74d+2UNs2/Z3fPfdOFSgChofhk+NnH\nNdNjhJXMJS+96D+qojqrVonlSK+6yvr7PJxM1lSpqGATCpEYjPH+6AIqwWD0Z1paogWIdAoLWbEd\nkeJacTFT8MsQ4ma0X3nlFUyYMCHqtXHjRowfPx4+ny9epyUc0Bt00pWIt0xiOMxWsjsFhmXXLrZa\n01cP69fbMwKRCFuJHDzI/45eUUs2aejbl1Vk4hEKMfUpqwmFFa2twN13R08cRFRUIPj9SjXJ38WL\nYTVy+CoqmByp0dMwYgTQ3g7U1KC7shIRXxb2BQcdry7GPRcPr/qPipyolRxpTU20gQwEmGyujFFx\nVDGcNImppc2YIX7fqG+/YEG0EpwRkZdp0SK+4tr69bGGvhcTN6M9depUvPHGG1Gv0aNHx+t0hAt6\ng066Mnb0t1UxuqMvvVQsMVleDhw9ygYkq9UDzwjoK+gjR/jf6exkA71o0rBzJ7BvH5M15XHllWy1\nZDWhsKKsDFizRu2zkyYhvzhoLfkbDgNvvql0PMybFz1h2LMHePpp4P33kbVxI/70m9dx+/Ql+N1F\nN6E7q2dyoiQv7EX/UZETtZIjXbyY/ZaffspW5du2ATfeKD5nVRXwySfRbQ+FxCtjEXp7/X6mr19Z\nGX39qvdHVpBHNGHp6AAOHeJ/R2ToeyEZqT1ORNNbdNKVEO1XuqnZbHZHi9zPBw8yV7Gx+IbqICdz\nu+s8+ywzyKJJQ3c32yvt7mYrNbO+c3U1238Oh4GCAmD8eDt3oYeLLgJ27xa/n5UVc526xn15Hx+G\nNNWjvI8vWodcpSpaSQnbfhDdp/Xrgfvvx9RbLsdlF490pqdvR7/dipISYMoU/nvGSRtPA133uvzb\nvwETJrD95O5uYPbsaLdznz7AzJmsvfn50X1/yxbxyphHZSW7h3V1bMLwz38CX37Zc/3hMCs1u2CB\n9fPlZKvB65iUdCUZ0W8ff/yxdscdd1h+jqLHE4dIIa413N67U8Dc0toqzk/1+1nUq0jZzBgh3tCg\naatXs//ycCrmInrV1vboO8+cyU9DstKh5l3vrFnyKPnKSr6a1bFI4a7KSq07Kys6d1q/z1aR934/\nS02T3aeysuPndizOYs7PdiPUI4pUN2vJm88pi8ZvbWX3WEU1TD+WqI+K+qvqvRHR2iqOhJdlTshy\n6DMk7SspRluV3mi0Uz0PWm/fkXB7708Bc0tnJ8tPlRmRVavEqTB2xDqcyqaKXg7kSC1fWVn2VK/0\n66qrY8be6vMqbX3zTev8cVF6kMz4is5dVRUtSWssKGMHo6HV1cZE90Qm0qNivHjXeeAAy6XWJzw+\nn6bl5qoZYTu560YD7/OxyaIu5KILEH31FemRSyCjnSDSLQ86kQVV0hYrI2JVEcvvFxt93iBkRxzD\n6qUX/pCpWDmdCGiafAVpfl+vWKZyzFtukRvkHTtYlSmVNurwVopG42F3whQIOCveYVYbE90TXVGO\n957Px9otOw9vgiiaIEyfLp8E2NU+ED0zP/2pWkUvq36VAZDRThDpZAQTVbo0rVEZyHVXpcxVLFuF\nm4VSvF5pOy2xaaVPbb5Pbiqk8YQzZEY5FJK79fXSkqptUal+Jfv9VbDr7dAV5exco+w8o0erTZp4\nqCicGfXKZTK+du6h29oBaQwFoiWAdMuDzpgUMDdYBUZVV7MgK1ma0EUXqUfQqgRi2WHSJGDYMGdC\nHdXVscFzs2YBt90WG8FrznUG1ILqdHhBSWvXAiNH8tPSdu4UR9f7fMCcOdF/s2rL9u3AsmUsoMsu\nKhHNdu6FTkUF0K+f+H1ejrfsPBs3ioMnrQK8ZAFl5eXAY4/1pN5VVbFANR6inH/RPeT1qwyBjHYC\nSDcjmFEpYDq8CF0ZssEqFGKpU3rErChC/Ikn1CNorZS0rPD7Y6PTCwvFKWc8ysvZdx97jEUIv/46\n8PnnLMp81Srg5JOjI+NF2JmAGKOo9dS6M85gkcklJSzKXZXKSnZfnbbFLioRzU7O368fi/K3c16n\n12klGpOby8RNRO188sno1Du7ZFJUuCJktBNAuhnBjEoBM0t+qhgdgBkSXczEjDnHWpRmFgyqi3UU\nFgKXX27v2oxoGjOy5hScRYtYmlBOjvz7ZWXAunU9ExBdHvVf/iV6YNbV12RiF7IJiN/PTQkDEJta\n9913LO9dFV7uu+pkqLWVeRj0iVd5OWClOyEyeI2NLI+9sVHt/MYJ16xZYnEd2XmdTvqsRGPuuYel\ngZkZPVqcU81DRUmNAEBGOyGkoxHU82Yd5bKmEyLJz3goLPFcenbEOtyIR3R3s3xdo7YzwIx3djYT\nZpExZQpbUZ11FjPSe/bIpUx1tybPgyHbMrj1VuCbb1hecU0Ny4sG7LuRAwG2sra6p6qyoqEQ6xfj\nxzPlrz17gKYm5vIVGRyzwWtrA04/nX1/3Dj23x/8gOXOy7j11p7J3l13yXPgeefVr1M0yeSRlcUm\nCDLRGNlvcuCAeGXv87FJoPG3qa7mf9YLpcLeRrI31WX0pkA0UR50qkaP66R6ipor3FT98rpimFVg\njSwf3E2AlFWAWyhkHWEsCpaqrhZHA4uigM01n0Mhdpx16+wFg82aZZ2rzKuCJqoRLivLeeONmvav\n/8raKotoFkX/n3RSTxqXzyev9CULbNTz5EWR1DXyCmkxwWlWbNokvl+yYLmyMhblL6oRn6FR4aqQ\n0U4wvdoIpht2avt6+V2v22qcLNTUaNrs2fKazYFATy6x1XVs2sQ+19rK6mqrDvq5udYTBv24xsFb\nZBiLijStTx/5Of1+Zuiqqth/zWVR9fOIUp+amli6lJ56pFqWUxfRMedpG3Ovd+yQl8YcMqQnzUzP\n07abqyyKGtfbYif7wFwm04h+/2STSD1tTva+SI8gQ6PCVSGjTWQubhSWEq3OJDtfIMBWolaGz/i6\n7jp711FXJ15V2XnJ7o2btLZQiBlHkaEIBHoMtGjFa/ZAGI2HHUW6mhr2Mk6cCgrUvjtzprXRsrMq\n1a/DbnqfbOKp0r+Mym0yJbsMEkXxCjLaRGbjRmEp0epMKudTNXxGV6rqca1kRN0aAxXDmJMjbqvb\nXHarCYXq9atIgopePp89KVCRgTd7E0IhufdF9V7Y2U7RaWgQu8ozSH7UK8hoE5mNm700o5tQHxjj\nuQ+n0la7GuXmFZHsHngheerWMPr9mnb11Zp2wgnMwBnb6laf3Wpbw0vJVzu/j35v7LiN3bZVNPFU\n3U6x8x2vt5J6OWS0CULTnO2luTHasvOpBKXJvmtnRWw0olbnNa/ehgzRtJNPtuc2t/JCWBmbYLDn\nfpeVRQdeufUGWK366uut99W9flVWqsl7mvuATHlMtrfOC35T7V+y1TkV+vAMMtoE4RQn7nGZ/rOT\nakl22uXVSkevDiaTEzUbCdVrsVN1ine/7URIm1+zZvEnLXqbSkvVjmO3OpqTl6yPyeIPrDwR69ZZ\n//5O+j0V+vAMMtoE4QSnKV+ywcurgU1Pz5KtqNyudFTTv0SlOK1oamKR2HoaVUWFeJVrvAY7Rtvv\nZ8YtFOJHnOsTDNVj6qtUNxMH1ZfVNoNo/zoQkEd98yLQzR4YJ1tKlNLlGWS0CcIJTvbpZIY+FBIP\npvE0rLKIaRF20r9UV/Kiczc1sTxt2fmMhSlEBVhkL5HH4LrrWKqWikvcWA2rszM2etzrl+y+yox2\nMMjyylUmA1aeHydbSpTS5Roy2gThBCf7dDJDn5XlfbCOedANBKKjrwMBZlzMgiZWq6CvvlI3LlYT\nDnMbj+1TH209qu1tOKJ13K6watXP4TQtTcUjIXqVlvIFUOrqNO3TT90Fxun9wu59tZpQXnml2mSA\nXNopCRltgnCK3UFNZujjsdI2nreuTrzyVslbNmJHGc2qXKfgHm4fPEybevsftf3FJ6ifw0vVONXX\np5/2XJfbNCve66ST+H+vqZH/3rJysOXl4vOFQtY1xCl4LKmQ9jhBOMWObjgg17m+8kpxxS23+suF\nhazowptv8t/fuJH/d15ZxHBYfByAFR4R3QtzcZaRI4HnnuMepnLfNsx852n0P7xffK6ysuhz2K1a\npsMr8alCMMiuRcesY79zp1ibXfX4Y8eK3xdVprMqB7t3r/iYF13Evi+rCkaVt5JLsmcNMmilTaQF\ndvbpZAE58cz7dpLDzHPLy47j87HoY9G9sJk7vL9PP21fYCD//fJyJtphpqnJ/up25Ehnq2Djatcq\nzaqyMlZm1fhv3vd0PXLee8bUN952hqifNTWJV+HBYLQEK6VppSRktAkiGfAMfTyNtpMcZp7+tNPB\n3IFaWSegrT5pLP/9qir+fbEzOdEN2YED9tK0Kir4ojai/XRddMT4ext/f8G+vvbVV/aFcnj33dzP\nVLd1aE87JSGjTRBe4iY61s4g6eQ8dlWyqqrct1PHwUq/G9D2FZVoh/IFK2fRfVGZnAwZEr1SV703\n1dX8PG5Zip3KylQ/RllZz+pZttJ2eh79XCrpV5SmlZKQ0SYIL3ArjKIa+OPmPPp3RTrQ5peo0pOT\nwdwr7XLjS+QiVzHAZte/VZqWTCnM6nxudOxFrnOVa7LCToofpWmlDGS0CcIL3LoSVfO+vXBZygo4\nmM+7erVYmtKqXrWRzk57Bkj1VVYm3s+V5WzLJDc3bWJR4Zs2WZfJlE22rOpbqxzDKGOq74GLJha0\n15wRkNEmCLd4kR6jslfsZRqO6mrUXJTD6UpfdL7Ro91V5pJNWlpbmTvb7SRHhhfFMFSOYZwkiVLu\naK85IyCjTRBu8aqKkdUq2stqSUbjqypI4lRq1WqyYSfvW/TS84tl1xmPfVkvoqytjtHUFD1RMkeg\nuy3jSaQVZLQJwi1epcdYGZh4pOHoxT9mzrQu0lFZKXY5u1Ho+uqrnut2Y7irq+XVqerqrN3dTvBi\ny8KJJr2owIkRXQZWlh5GpBVktAnCC7xMj5Gtipyex2qlZcddbnelrzrZ0CcQxlKUdiVGRffBqwpq\nVscWrXztlD0151XL9rutjifa/yZXetpCRpsgvCBR6TF2z6NirFRzqCsrnUutOpF8Xb3aviCMqB2J\nyDmW5d6b739TE9+Im49RVye+Vp9PPFGymoTZqaNOpBRktAnCSxI1APLO41RIQzWH2umetqY5TxOz\nqyXOW/EnU0dbdL8CAbUVf0OD2Nvg9/NT3lQmYeZtCXKdpw1ktAki3ZGt5lSMlVUOtTFH2Wx8QyFW\nllKXv7RCdVKj500bq5IZXyIFM54R9jKAzw52VOBEkx7ZShvgt11lEiYLACTXeUpDBUMIIt0xF6rY\nvp39u7ZWreiDrMDE9OnAl18Cjz8OZGez1+OPAxs2ANdfzz7zwgvAaaexYiCRiLythYXA8OHyAijh\nMHDzzcCSJUBnZ+z7VVXADTfwv8srsFFaCoRC/M9XVLD344Gs6IYZXnEWgLWtspL/nSFDgL59+d8R\nXa/O+PHiwi+ithApARltgkhnwmFg+XL+e2vXAuXl/PfMxkpUsex3v+Mb2HnzgOefZ5WsjBOFe+5x\nfi16FbCRI9mxRRw8CDz0UE97s7KAQIC9XniBVd4yTiBkkxK3FdRkqBhPHVHlrMJCYPJk/nf27gXO\nOit2siS73mCQ3bc5c+JTxUtUeYzwjmQv9WWQe5wgLLBy/U6fbs8FquK+tlLwsiuLaVXv2/zKyupx\nC6sKqCRLR1tV01y2t25su6p73Wobw+v0wXhG5xNRkNEmiHTGjjCHV8bKaUSzeWA3ioTYSe8yCqnY\nDTLzOlBQJZVr1iymk+73i3PhRVXLjMjkZ2WyrF6nD/KgimAJg4w2QaQ7KgOml8bKSUSzrJ12X6qR\n7/EMMlNZWZpV58rKmIjNaac5M3BeX6tX3odkRudnIGS0CSLdSbTr10lEs4N62jGvQIBFlJtzzL1W\niVNBZaIkS/fi/T0YlEfhx+ta3U7okjVxylAoEI0g0h09ovsf/wC+/pr9V4/2BrwPDpJFNFdW8qOx\n7URSm5k2Ddi0Cdi3D1i8uOe6gOQEmcmC//TIa9lnWlr4f29uZgFiIuJ1rSoR/TKSFZ2foZDRJoje\ngnnw1aOxR40CRoyIjap2cx5RRPPkyfzB304ktd/PIsL1CPbnnwdOOUVsVBYtAmpqWGS0TiDAotrd\nXisP2QREj7x2OklZu1Y+uRJF+S9aZP9cXpGs6PxMJdlLfRnkHicIF8QzOMiJS151T1ulEIada41H\n8JlKGVXRZ0TCMHbcyU6uKZ5qfcmKzs9AyGgTRDojGohle8hWe6d2aGhgGuGi4DMj5oHdSYlJHlbX\nqlLhyq5BE00SjFHgos/MnCne147HPnwi07FIxzzukNEmiHTEaiC2krKcPj2+59c0+YSCl6cdj0Ao\nK0+DU4PW2ckMNO/41dXsWmSrz0SmSFE6Vq+CjDZBpCNWA7FVsQ1jrrPX50+00IaVdrpsNeum1Kks\nGj4U6rlmq+pf8XQnuxXCIVIOMtoEkW6o5sWKlMLs7J06OX8yClHYyQHXr91NfrGdymgyVL0RTnEq\nhEOkLBQ9ThDphkr0MsC0wAMB/ufcpOLIzr9zJ0t74hHPQhTmqOrKSutrV72PPEpLWcEOK6yuOd4R\n/337svvBIyuLX3CESGnIaBNEuqGaFxsMAtXV/M9NnBifvFzdGPJwU4jCCnOu+pdfAjNm8D+rpyE5\nzS9uawN+8ANgzx7rdtm9ZlHFNqeFWJqagK4u/ntdXex9Iq0go00Q6Uay82Ktzp9MoQ3jytUqp9np\nfTzvPGD9euZktqK8XP2aVURb7OJECIdIachoE0Q6oiKyEQ4DK1fyv//66+5c1aLzP/FE6ghtWCnF\nAfbFShobmTqbKv36qV+zG3e9CCdCOERK49M0lelicti9ezfGjRuH1atXo1xUF5ggMplwmA3mpaWx\nA/DWrWxftLs79nt+PzNkw4d7d36A/f/Agaze9ooVzNhUVDCDvWhRtMFMJfTr6NuXuYx59xMA1qwB\nxo1TP25lJXPVqxjHcJjtYW/fHvve0KFs0uHEyEYizL2eTr8HIYRW2gSRzsh0oxOhCV1YyAzTAw/0\nBE+ddhp7b8MG8Qo31cjNBZYsAc46Sx4ANnq0OLCLx+7d6ivkeG17qHgciLQhob9aS0sL5s6diyNH\njqCzsxP33XcfTj/99EQ2gSAyB90IPPFE7Hteuqr14CkdPXgKYMYhHVC9hpIS4NRT2Z62CnYnR7pb\nnrcqdos+wSPSmoS6xxcvXoxgMIjq6mps27YNd999N1577TXh58k9ThAuibdrNBwGTj4Z2LEj9j03\nLt1EYvca2tpYMNqmTSwC2+9ne9eNjbHfr611NnEJh4Ft29j/DxuW+veQSBgJXWlXV1cjNzcXANDV\n1YW8vLxEnp4gMg/dNbpggXjv2w0qwVOpvrqzew35+cC6dcxIb9zIXObFxeLJkV0iEbbdsGIFy3sP\nhWgPmjhO3HrAK6+8gmXLlkX9bcGCBRg9ejQaGhowd+5cPPDAA/E6PUEQRuLlGtX3zXnBU+lSS9np\nNZSUABdf3PNvryZHvWG7gYgbcTPaU6dOxdSpU2P+/vXXX+Ouu+7Cvffei7PPPjtepycIIhEkat88\nnnh5DW4nR1a52gsWpMc9JeJGQn0tdXV1qK2txeOPP46TTjopkacmCCIeRCIspSwQAFpa2N+CQWD6\ndG+CpxJFPAPA7NAbthuIuJJQo/3oo4+io6MDDz/8MACgqKgITz31VCKbQBCEjizHW5V77mGpUkaa\nm5mudTrtv8Z771+V3rDdQMSVhD5VZKAJIgUwRpS7CXTqja7cZKdF9YbtBiKupNFUmCAIT/Aq0Ilc\nufEhVVz1REpCimgEkUl4WZQiEYprmQgpmBESyGgTRCbhZVGKZFcb6+3IJGqJjIWmbgSRSXgd6ESu\nXIJIKLTSJohMwuvVMblyCSKh0JNFEJlGPFbHyY66JogMgYw2QWQaqZKTTBCEbchoE0SmQqtjgkg7\naE+bIAiCINIEMtoEQRDxJBwGtm61lwNPEALIaBMEQcSDSAS44w5g1ChgxAj23zvuYH8nCIfQnjZB\nEEQ8oLrYRByglTZBEITXeCkXSxAGyGgTBEF4jZdysQRhgIw2QRCE11AxFSJOkNEmCILwGiqmQsQJ\nCkQjCIKIB1RMhYgDZLQJgiDiAcnFEnGAjDZBEEQ8IblYwkNoT5sgCIIg0gQy2gRBEASRJpDRJgiC\nIIg0gYw2QRAEQaQJZLQJgiAIIk0go00QBEEQaQIZbYIgCIJIE8hoEwRBEESaQEabIAiCINIEMtoE\nQRAEkSaktIxpV1cXAGDfvn1JbglBEARBJI7BgwcjOzvWRKe00W5oaAAATJs2LcktIQiCIIjEsXr1\napSXl8f83adpmpaE9ijR1taGzZs3Y+DAgfD7/cluDkEQBEEkBNFKO6WNNkEQBEEQPVAgGkEQBEGk\nCWS0CYIgCCJNIKNNEARBEGkCGW2CIAiCSBPIaFvQ0tKCmTNn4rrrrsPVV1+NdevWJbtJGcNf//pX\n3H333cluRq+mu7sb8+bNw9VXX43rr78eO3bsSHaTMoYNGzbg+uuvT3YzMobOzk7MnTsX1157LaZM\nmYLVq1cnu0mOSOk87VRg6dKlOPfcc1FdXY1t27bh7rvvxmuvvZbsZvV6HnroIXzwwQcYOXJkspvS\nq3nnnXfQ0dGBl19+GevXr8fChQvx1FNPJbtZvZ5nn30WK1euREFBQbKbkjGsXLkSxcXF+K//+i8c\nPnwYkydPxrhx45LdLNvQStuC6upqXHPNNQCYQlteXl6SW5QZjBkzBg8++GCym9Hr+eKLL3DhhRcC\nAKqqqrB58+YktygzCIVCWLJkSbKbkVFcfvnlqK2tBQBompa22h+00jbwyiuvYNmyZVF/W7BgAUaP\nHo2GhgbMnTsXDzzwQJJa1zsR3fPx48fjk08+SVKrMocjR46gqKjo+L/9fj8ikQhX1IHwjssuuwy7\nd+9OdjMyij59+gBgfX7OnDm44447ktwiZ9CTaWDq1KmYOnVqzN+//vpr3HXXXQq/6FcAAAJFSURB\nVLj33ntx9tlnJ6FlvRfRPScSQ1FREVpbW4//u7u7mww20Wupr6/H7Nmzce2112LixInJbo4jyD1u\nQV1dHWpra/Hoo49i7NixyW4OQXjKmDFj8Le//Q0AsH79eowYMSLJLSKI+NDY2IgZM2Zg7ty5mDJl\nSrKb4xiaUlvw6KOPoqOjAw8//DAAtjKhQB2it3DppZfiww8/xDXXXANN07BgwYJkN4kg4sLTTz+N\n5uZmPPnkk3jyyScBsIDA/Pz8JLfMHqQ9ThAEQRBpArnHCYIgCCJNIKNNEARBEGkCGW2CIAiCSBPI\naBMEQRBEmkBGmyAIgiDSBDLaBEEAAD755BNccMEFOHDgwPG//f73v0dNTU0SW0UQhBEy2gRBAADO\nOeccTJw4ET//+c8BMLGVl19++bhGAUEQyYfytAmCOE5HRwemTp2Kq666Ci+++CL+8z//E6effnqy\nm0UQxDHIaBMEEcU///lPTJo0CbfcckvaFlUgiN4KuccJgoji73//O/r164ePPvoIkUgk2c0hCMIA\nGW2CII5TV1eHJUuW4KWXXkJubi7p7BNEikFGmyAIAEB7ezvuvPNOzJ07FxUVFVi4cCFefPFFrF+/\nPtlNIwjiGGS0CYIAACxYsAAjRozApEmTAABlZWW4//77MXfu3Kia2wRBJA8KRCMIgiCINIFW2gRB\nEASRJpDRJgiCIIg0gYw2QRAEQaQJZLQJgiAIIk0go00QBEEQaQIZbYIgCIJIE8hoEwRBEESaQEab\nIAiCINKE/x9ZWdTv3sEE4gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c2706a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(X[Y==0, 0], X[Y==0, 1], label='Class 0')\n",
    "ax.scatter(X[Y==1, 0], X[Y==1, 1], color='r', label='Class 1')\n",
    "sns.despine(); ax.legend()\n",
    "ax.set(xlabel='X', ylabel='Y', title='Toy binary classification data set');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model specification\n",
    "\n",
    "A neural network is quite simple. The basic unit is a [perceptron](https://en.wikipedia.org/wiki/Perceptron) which is nothing more than [logistic regression](http://pymc-devs.github.io/pymc3/notebooks/posterior_predictive.html#Prediction). We use many of these in parallel and then stack them up to get hidden layers. Here we will use 2 hidden layers with 5 neurons each which is sufficient for such a simple problem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def construct_nn(ann_input, ann_output):\n",
    "    n_hidden = 5\n",
    "    \n",
    "    # Initialize random weights between each layer\n",
    "    init_1 = np.random.randn(X.shape[1], n_hidden).astype(floatX)\n",
    "    init_2 = np.random.randn(n_hidden, n_hidden).astype(floatX)\n",
    "    init_out = np.random.randn(n_hidden).astype(floatX)\n",
    "        \n",
    "    with pm.Model() as neural_network:\n",
    "        # Weights from input to hidden layer\n",
    "        weights_in_1 = pm.Normal('w_in_1', 0, sd=1, \n",
    "                                 shape=(X.shape[1], n_hidden), \n",
    "                                 testval=init_1)\n",
    "        \n",
    "        # Weights from 1st to 2nd layer\n",
    "        weights_1_2 = pm.Normal('w_1_2', 0, sd=1, \n",
    "                                shape=(n_hidden, n_hidden), \n",
    "                                testval=init_2)\n",
    "        \n",
    "        # Weights from hidden layer to output\n",
    "        weights_2_out = pm.Normal('w_2_out', 0, sd=1, \n",
    "                                  shape=(n_hidden,), \n",
    "                                  testval=init_out)\n",
    "        \n",
    "        # Build neural-network using tanh activation function\n",
    "        act_1 = pm.math.tanh(pm.math.dot(ann_input, \n",
    "                                         weights_in_1))\n",
    "        act_2 = pm.math.tanh(pm.math.dot(act_1, \n",
    "                                         weights_1_2))\n",
    "        act_out = pm.math.sigmoid(pm.math.dot(act_2, \n",
    "                                              weights_2_out))\n",
    "        \n",
    "        # Binary classification -> Bernoulli likelihood\n",
    "        out = pm.Bernoulli('out', \n",
    "                           act_out,\n",
    "                           observed=ann_output,\n",
    "                           total_size=Y_train.shape[0] # IMPORTANT for minibatches\n",
    "                          )\n",
    "    return neural_network\n",
    "\n",
    "# Trick: Turn inputs and outputs into shared variables. \n",
    "# It's still the same thing, but we can later change the values of the shared variable \n",
    "# (to switch in the test-data later) and pymc3 will just use the new data. \n",
    "# Kind-of like a pointer we can redirect.\n",
    "# For more info, see: http://deeplearning.net/software/theano/library/compile/shared.html\n",
    "ann_input = theano.shared(X_train)\n",
    "ann_output = theano.shared(Y_train)\n",
    "neural_network = construct_nn(ann_input, ann_output)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's not so bad. The `Normal` priors help regularize the weights. Usually we would add a constant `b` to the inputs but I omitted it here to keep the code cleaner."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Variational Inference: Scaling model complexity\n",
    "\n",
    "We could now just run a MCMC sampler like [NUTS](../api/inference.rst) which works pretty well in this case, but as I already mentioned, this will become very slow as we scale our model up to deeper architectures with more layers.\n",
    "\n",
    "Instead, we will use the brand-new [ADVI](../api/inference.rst) variational inference algorithm which was recently added to `PyMC3`, and updated to use the operator variational inference (OPVI) framework. This is much faster and will scale better. Note, that this is a mean-field approximation so we ignore correlations in the posterior."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pymc3.theanof import set_tt_rng, MRG_RandomStreams\n",
    "set_tt_rng(MRG_RandomStreams(42))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Average Loss = 137.97: 100%|██████████| 30000/30000 [00:09<00:00, 3139.84it/s]\n",
      "Finished [100%]: Average Loss = 137.82\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 11.5 s, sys: 818 ms, total: 12.3 s\n",
      "Wall time: 15.6 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "with neural_network:\n",
    "    inference = pm.ADVI()\n",
    "    approx = pm.fit(n=30000, method=inference)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And using old interface. Performance is nearly the same"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Average ELBO = -170.65: 100%|██████████| 30000/30000 [00:09<00:00, 3083.15it/s]\n",
      "Finished [100%]: Average ELBO = -159.53\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 11.1 s, sys: 565 ms, total: 11.7 s\n",
      "Wall time: 11.6 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "with neural_network:\n",
    "    advifit = pm.advi(n=30000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "~ 12 seconds on my laptop. That's pretty good considering that NUTS is having a really hard time. Further below we make this even faster. To make it really fly, we probably want to run the Neural Network on the GPU.\n",
    "\n",
    "As samples are more convenient to work with, we can very quickly draw samples from the variational approximation using the `sample` method (this is just sampling from Normal distributions, so not at all the same like MCMC):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "trace = approx.sample(draws=5000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting the objective function (ELBO) we can see that the optimization slowly improves the fit over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VXWYvdge3Z5I0l0vAzNXhaEW7fXGFsr4d/Az6tG5lLZhRYpauphT+k8id7mTJ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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113088710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(-inference.hist, label='new ADVI', alpha=.3)\n",
    "plt.plot(advifit.elbo_vals, label='old ADVI', alpha=.3)\n",
    "plt.legend()\n",
    "plt.ylabel('ELBO')\n",
    "plt.xlabel('iteration');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we trained our model, lets predict on the hold-out set using a posterior predictive check (PPC). \n",
    "\n",
    "1. We can use [`sample_ppc()`](../api/inference.rst) to generate new data (in this case class predictions) from the posterior (sampled from the variational estimation).\n",
    "2. It is better to get the node directly and build theano graph using our approximation (`approx.sample_node`) , we get a lot of speed up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sigmoid.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We can get predicted probability from model\n",
    "neural_network.out.distribution.p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# create symbolic input\n",
    "x = T.matrix('X')\n",
    "# symbolic number of samples is supported, we build vectorized posterior on the fly\n",
    "n = T.iscalar('n')\n",
    "# Do not forget test_values or set theano.config.compute_test_value = 'off'\n",
    "x.tag.test_value = np.empty_like(X_train[:10])\n",
    "n.tag.test_value = 100\n",
    "_sample_proba = approx.sample_node(neural_network.out.distribution.p, \n",
    "                                   size=n,\n",
    "                                   more_replacements={ann_input: x})\n",
    "# It is time to compile the function\n",
    "# No updates are needed for Approximation random generator \n",
    "# Efficient vectorized form of sampling is used\n",
    "sample_proba = theano.function([x, n], _sample_proba)\n",
    "\n",
    "# Create bechmark functions\n",
    "def production_step1():\n",
    "    ann_input.set_value(X_test)\n",
    "    ann_output.set_value(Y_test)\n",
    "    with neural_network:\n",
    "        ppc = pm.sample_ppc(trace, samples=500, progressbar=False)\n",
    "\n",
    "    # Use probability of > 0.5 to assume prediction of class 1\n",
    "    pred = ppc['out'].mean(axis=0) > 0.5\n",
    "    \n",
    "def production_step2():\n",
    "    sample_proba(X_test, 500).mean(0) > 0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See the difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "223 ms ± 1.38 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%timeit production_step1()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "53.1 ms ± 311 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit production_step2()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's go ahead and generate predictions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred = sample_proba(X_test, 500).mean(0) > 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VyjXBU/mzEekFPaku40e5Rp4wiUYjuovXqCEFuN5sv+jGdmRGI7Y+E29TsLHq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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115ea41d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(X_test[pred==0, 0], X_test[pred==0, 1])\n",
    "ax.scatter(X_test[pred==1, 0], X_test[pred==1, 1], color='r')\n",
    "sns.despine()\n",
    "ax.set(title='Predicted labels in testing set', xlabel='X', ylabel='Y');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy = 93.2%\n"
     ]
    }
   ],
   "source": [
    "print('Accuracy = {}%'.format((Y_test == pred).mean() * 100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hey, our neural network did all right!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lets look at what the classifier has learned\n",
    "\n",
    "For this, we evaluate the class probability predictions on a grid over the whole input space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "grid = pm.floatX(np.mgrid[-3:3:100j,-3:3:100j])\n",
    "grid_2d = grid.reshape(2, -1).T\n",
    "dummy_out = np.ones(grid.shape[1], dtype=np.int8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ppc = sample_proba(grid_2d ,500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Probability surface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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R2cNQxlBmhIGMKgmDGRG5J1exqEAi7en9bGFfFUGXyAcMZQxlRhjKqNIwmBFReQorSEBF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MIfRKNRdHd3o3EoUyUSiWBgYIB5PAkzwhlkCbHB7rwaM4X4YHfWndEtUZaLkbW9VXwrynKpri4y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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115d1e9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = sns.diverging_palette(250, 12, s=85, l=25, as_cmap=True)\n",
    "fig, ax = plt.subplots(figsize=(16, 9))\n",
    "contour = ax.contourf(grid[0], grid[1], ppc.mean(axis=0).reshape(100, 100), cmap=cmap)\n",
    "ax.scatter(X_test[pred==0, 0], X_test[pred==0, 1])\n",
    "ax.scatter(X_test[pred==1, 0], X_test[pred==1, 1], color='r')\n",
    "cbar = plt.colorbar(contour, ax=ax)\n",
    "_ = ax.set(xlim=(-3, 3), ylim=(-3, 3), xlabel='X', ylabel='Y');\n",
    "cbar.ax.set_ylabel('Posterior predictive mean probability of class label = 0');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Uncertainty in predicted value\n",
    "\n",
    "So far, everything I showed we could have done with a non-Bayesian Neural Network. The mean of the posterior predictive for each class-label should be identical to maximum likelihood predicted values. However, we can also look at the standard deviation of the posterior predictive to get a sense for the uncertainty in our predictions. Here is what that looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2Hh0QyrIZrfaZ9TjomQgoD6B4v7lbMXgZbS+0mpHx+IWO4DdCK/yp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\nR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oSY96fo8cSMPygRLRLRVf+F6PduhnjKKZAEAeIppyD6vZv7xpFFnJbYo6RXQkwjLVKB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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115f1ab70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = sns.cubehelix_palette(light=1, as_cmap=True)\n",
    "fig, ax = plt.subplots(figsize=(16, 9))\n",
    "contour = ax.contourf(grid[0], grid[1], ppc.std(axis=0).reshape(100, 100), cmap=cmap)\n",
    "ax.scatter(X_test[pred==0, 0], X_test[pred==0, 1])\n",
    "ax.scatter(X_test[pred==1, 0], X_test[pred==1, 1], color='r')\n",
    "cbar = plt.colorbar(contour, ax=ax)\n",
    "_ = ax.set(xlim=(-3, 3), ylim=(-3, 3), xlabel='X', ylabel='Y');\n",
    "cbar.ax.set_ylabel('Uncertainty (posterior predictive standard deviation)');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that very close to the decision boundary, our uncertainty as to which label to predict is highest. You can imagine that associating predictions with uncertainty is a critical property for many applications like health care. To further maximize accuracy, we might want to train the model primarily on samples from that high-uncertainty region."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mini-batch ADVI\n",
    "\n",
    "So far, we have trained our model on all data at once. Obviously this won't scale to something like ImageNet. Moreover, training on mini-batches of data (stochastic gradient descent) avoids local minima and can lead to faster convergence.\n",
    "\n",
    "Fortunately, ADVI can be run on mini-batches as well. It just requires some setting up:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Average Loss = 129.65: 100%|██████████| 40000/40000 [00:06<00:00, 5965.07it/s]\n",
      "Finished [100%]: Average Loss = 129.5\n"
     ]
    }
   ],
   "source": [
    "minibatch_x = pm.Minibatch(X_train, batch_size=50)\n",
    "minibatch_y = pm.Minibatch(Y_train, batch_size=50)\n",
    "neural_network_minibatch = construct_nn(minibatch_x, minibatch_y)\n",
    "with neural_network_minibatch:\n",
    "    approx = pm.fit(40000, method=pm.ADVI())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+aydi/rxg71DqBGP/PizRguYUHP9PxChM8AQAWFPLCm+Z1TqPFMgeNEknXr5b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\nxARPREQkQkzwREREIsQET0REJEL/D/kOERK2xqVDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115ec8320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(inference.hist)\n",
    "plt.ylabel('ELBO')\n",
    "plt.xlabel('iteration');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, mini-batch ADVI's running time is much lower. It also seems to converge faster.\n",
    "\n",
    "For fun, we can also look at the trace. The point is that we also get uncertainty of our Neural Network weights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KZ1XK0zi2hlabIzl4PZ7rUFrsTF9sTixEE2MYWhHPtbGMKgPDN1EvX+x6PEPNdV2/qptY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\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/0yu6EJR8cAsOBO0+OHh7xdzbWQFSeWGVWtcTHPAItfcp1A1jMxjQcAmlTbrN/zYj7AiA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      "text/plain": [
       "<matplotlib.figure.Figure at 0x118f4def0>"
      ]
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   ],
   "source": [
    "pm.traceplot(trace);"
   ]
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   "source": [
    "## Summary\n",
    "\n",
    "Hopefully this blog post demonstrated a very powerful new inference algorithm available in PyMC3: [ADVI](http://pymc-devs.github.io/pymc3/api.html#advi). I also think bridging the gap between Probabilistic Programming and Deep Learning can open up many new avenues for innovation in this space, as discussed above. Specifically, a hierarchical neural network sounds pretty bad-ass. These are really exciting times.\n",
    "\n",
    "## Next steps\n",
    "\n",
    "[`Theano`](http://deeplearning.net/software/theano/), which is used by `PyMC3` as its computational backend, was mainly developed for estimating neural networks and there are great libraries like [`Lasagne`](https://github.com/Lasagne/Lasagne) that build on top of `Theano` to make construction of the most common neural network architectures easy. Ideally, we wouldn't have to build the models by hand as I did above, but use the convenient syntax of `Lasagne` to construct the architecture, define our priors, and run ADVI. \n",
    "\n",
    "You can also run this example on the GPU by setting `device = gpu` and `floatX = float32` in your `.theanorc`.\n",
    "\n",
    "You might also argue that the above network isn't really deep, but note that we could easily extend it to have more layers, including convolutional ones to train on more challenging data sets.\n",
    "\n",
    "I also presented some of this work at PyData London, view the video below:\n",
    "<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/LlzVlqVzeD8\" frameborder=\"0\" allowfullscreen></iframe>\n",
    "\n",
    "Finally, you can download this NB [here](https://github.com/twiecki/WhileMyMCMCGentlySamples/blob/master/content/downloads/notebooks/bayesian_neural_network.ipynb). Leave a comment below, and [follow me on twitter](https://twitter.com/twiecki).\n",
    "\n",
    "## Acknowledgements\n",
    "\n",
    "[Taku Yoshioka](https://github.com/taku-y) did a lot of work on ADVI in PyMC3, including the mini-batch implementation as well as the sampling from the variational posterior. I'd also like to the thank the Stan guys (specifically Alp Kucukelbir and Daniel Lee) for deriving ADVI and teaching us about it. Thanks also to Chris Fonnesbeck, Andrew Campbell, Taku Yoshioka, and Peadar Coyle for useful comments on an earlier draft."
   ]
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