Cifar10 Collages.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from os import listdir\n",
    "from os.path import join, exists\n",
    "import matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def order_columns(column_names):\n",
    "    column_names = sorted(column_names, key=lambda x: int(x.split('-')[-1]) + 100 if 'classifier' in x else int(x.split('-')[-1])) \n",
    "    column_names.remove\n",
    "    return column_names\n",
    "\n",
    "def extract_layer_saturation(df, excluded = 'classifier-6', epoch=19):\n",
    "    df = df.reindex(sorted(df.columns), axis=1)\n",
    "    cols = list(df.columns)\n",
    "    #print(cols)\n",
    "    train_cols = [col for col in cols if 'train' in col and not excluded in col and not 'accuracy' in col and not 'loss' in col]\n",
    "    train_cols = order_columns(train_cols)\n",
    "    \n",
    "    #print(list(train_cols))\n",
    "    epoch_df = df[df.index.values == epoch]\n",
    "    accuray = epoch_df['test_accuracy'].values[0]\n",
    "    epoch_df = epoch_df[train_cols]\n",
    "    \n",
    "    return epoch_df, accuray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "                         "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_saturation_level(df, title=''):\n",
    "    cols = list(df.columns)\n",
    "    col_names = ['Layer {}'.format(i+1) for i in range(len(df.columns))]\n",
    "    plt.figure(figsize=(7,5))\n",
    "    plt.grid()\n",
    "    plt.bar(list(range(len(cols))), df.values[0])\n",
    "    plt.xticks(list(range(len(cols))), col_names, rotation='vertical', fontsize=16)\n",
    "    plt.ylim((0,100))\n",
    "    plt.yticks(fontsize=16)\n",
    "    plt.xlabel('Layers', fontsize=16)\n",
    "    plt.title(title, fontsize=16)\n",
    "    plt.ylabel('Saturation in %', rotation='vertical', fontsize=16)\n",
    "    plt.show()\n",
    "    \n",
    "def plot_saturation_level_ax(df, ax, acc=-1):\n",
    "    cols = list(df.columns)\n",
    "    col_names = [i+1 for i in range(len(df.columns))]\n",
    "    ax.grid()\n",
    "    ax.bar(list(range(len(cols))), df.values[0])\n",
    "    ax.set_xticks([])\n",
    "    ax.set_ylim((0,100))\n",
    "    ax.text(1, 80, 'Accuray: {}'.format(acc))\n",
    "    #plt.yticks(fontsize=16)\n",
    "    #plt.xlabel('Layers', fontsize=16)\n",
    "    #plt.title(title, fontsize=16)\n",
    "    #plt.ylabel('Saturation in %', rotation='vertical', fontsize=16)_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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w+/Vzgm35KoIGgSa5z31IGajO3fXQQ48MPggOyD4G+me7LHrU63v7KcHB+kaCSvNsoF3C+JYELffrgbeAy4GKhPG/B74kqJz/maAl/GfhuPOBF6ut73sEZ0O+JOgjHlvHfxNcNLmeoE/7peG4fonrS1jOAIK+118RtGJPBnYLx5UBbxA0TDwWPm6u5f3XKGPCuHGx+aqXg6BR4qNw/b8Khx0Rvv8vCQ4+ngR+GI6bHftcwtdtw2nXhcuYDRxSvUxhGTYT7Ixjj/vCcXsA9xJUMNaF73lItjOlhx56FN7D3HOli7BI/ghbHV8lOPX/a4LuIx08yUVvkvvM7AKCVu6jPbgTkIiISEpN0nXEzMaY2WdmtihhWCsze8aCH2V5JuwzFvvBgjvNbJmZvWXB7aqkQORRVo4kuL3bGoLuGWeokp0+TZ0Tdx9D0DXqqPS9C2kKebRNkQxSTiRTmqqP9jiC05mJrgZmeXDHg1l8d2HGQIL+OQcS3Ff13iYqo+SGceRBVtz9t+7+fXffzd2PcPdXs12mPDOOJs6Juz/i392eUpqPceTBNkUybhzKiWRAk1S03f15gr55iU4n+FEBwr9nJAx/2AOvAHtakl/FkvykrEgUyolEpaxIFMqJZEo27zrSxoOrwwn/xm6qvy9V73daEQ6TwqWsSBTKiUSlrEgUyok0Wi7+YE2yG/MnvWLTzEYSnLZhp5126rnffvslm0yameLiYlasWFHjdl5JKCsFTDmRqJQViUI5kfpYsmTJGndP+WNA2axof2pmbd19dXjK5bNweAVVf72qiODWaDW4+/3A/QBlZWW+YMGCTJZXmkh5eTnFxcWbEwYpK1KDciJRKSsShXIi9WFmqX5ZF8hu15EZwPDw+XBgesLwYeFVvb2AdbFTN1KwlBWJQjmRqJQViUI5kUZrkhZtM5tI8KMGrc2sAriB4FcF/2ZmPyX4cYOzw8lnAicT/JLPBoJfbZQCMXToUGbPng3QQlmR2ignEpWyIlEoJ5IpefODNTolk1/M7DV3L8vEspWV/KGcSFTKikShnEhUUbOSza4jIiIiIiJ5SxVtEREREZEMUEVbRERERCQDVNEWEREREckAVbRFRERERDJAFW0RERERkQxQRTuiqVOnYma899572S5Kvdxyyy107NiRgw46iKeffjrpNO7OtddeS6dOnejcuTN33nlnlfHz589n++23Z8qUKU1R5GYvn7PSp08fSktLKS0tpV27dpxxxhkATJ8+ne7du1NaWkpZWRkvvvhilfnWr1/Pvvvuy6hRo+LDXnvtNbp160bHjh259NJLid1q9Msvv+SEE07gwAMP5IQTTmDt2rVAkNNLL72Ujh070r17d15//fX4ssxsuJktDR/DE4b3NLO3zWyZmd1pZhYOb2Vmz4TTP2Nme4XDLZxuWRo+0jrlc05mzZpFjx49KC0tpXfv3ixbFnyczz//PD169GCHHXaosj157rnn4rkqLS2lZcuWTJs2Dag9c4WkELMSM2XKFMyM2G3xJkyYUCUr2223HW+++SaVlZVVhrdu3ZrLLrss4+8xlygn3+XkmWeeoWfPnnTr1o2ePXvy7LPPAmQnJ+6eF4+ePXt6Jp199tneu3dvv+GGGzK6ni1btqRtWYsXL/bu3bv7xo0b/YMPPvAOHTokXf6YMWP8vPPO861bt7q7+6efflqlPP379/eBAwf65MmT01a2VIAFrqzUKRtZSXTmmWf6+PHj3d29srLSt23b5u7uCxcu9IMOOqjKtJdeeqkPHTrUL7nkkviwww47zF966SXftm2bDxgwwGfOnOnu7r/+9a/9lltucXf3W265xa+88kp3d3/yySd9wIABvm3bNn/55Zf98MMPd2AB0Ar4IPy7V/h8Lw8q7vOAIwEDngIGhsNHA1eHz68GbgufnxxOZ8pJTVFzcuCBB/o777zj7u533323Dx8+3N3dV6xY4QsXLvTzzjuv1u3JF1984XvttZd/8803NcYlZq6+tE1JLZey4u6+fv1679Onjx9xxBE+f/78GvO+9dZbXlxcnHT9PXr08Dlz5tS73MpJas0hJ6+//rqvWrXK3d3ffvttb9euXdL1NzQn7tGzohbtCL7++mvmzp3LQw89xKRJk6qMGz16NN26daOkpISrr74agGXLlnH88cdTUlJCjx49WL58ObNnz+bUU0+Nzzdq1CjGjRsHQPv27fnd735H7969mTx5Mg888ACHHXYYJSUlDB48mA0bNlBZWUlxcTGbN28GghbC9u3bx18nM336dIYMGUKLFi0oLi6mY8eOzJs3r8Z09957L9dffz3bbRfEYZ999omPu+uuuxg8eHCVYVK7fM9KTGVlJc8++2y8dXHXXXclbCzmm2++iT+HoOX6008/5cQTT4wPW716NevXr+fII4/EzBg2bFi8BXP69OkMHx40Sg8fPrzK8GHDhmFm9OrVi6+++gpgR+Ak4Bl3/9Ld1wLPAAPMrC2wu7u/HG4UHwZizaGnA+PD5+OrDX84nD5j8j0nZsb69esBWLduHe3atYuXq3v37vFtTTJTpkxh4MCB7LzzzlWGV89coSjUrABcd911XHnllbRs2TLpOiZOnMjQoUNrDF+6dCmfffYZffr0qbV8+UY5qZqTQw89ND5Nly5d2LhxI5s2baqyzKbKiSraEUybNo0BAwbQqVMnWrVqFT9l/dRTTzFt2jReffVVFi5cyJVXXgnAueeeyyWXXMLChQt56aWXaNu2bcp1tGzZkhdffJEhQ4Zw5plnMn/+fBYuXEjnzp156KGH2G233ejXrx9PPvkkAJMmTWLw4MHsuOOO3Hfffdx33301lrlq1Sr222+/+OuioiJWrVpVY7rly5fz2GOPUVZWxsCBA1m6dGl8/qlTp3LxxRfX/0MrUPmelZipU6dy3HHHsfvuu1cZdvDBB3PKKacwZswYALZt28YVV1zBH/7whxrrKyoqSrq+Tz/9NP45tG3bls8++6zWMhJUtPcFViYsviIctm/4vPpwgDbuvhog/Bs7kqy+rIzI95w8+OCDnHzyyRQVFfHII4/Ed+5RTJo0KWnlKVnmCkGhZuWNN95g5cqVVSp+1T322GNJszJx4kTOOeecKgf8+U45qT0njz/+OIceeigtWrSoMrypcqKKdgQTJ05kyJAhAAwZMoSJEycC8K9//YsRI0bEW15atWpFZWUlq1atYtCgQUAQzOotM8mcc8458eeLFi2iT58+dOvWjQkTJrB48WIAfvaznzF27FgAxo4dy4gRIwC4+OKLk1aGkzXKJQvUpk2baNmyJQsWLODCCy/kggsuAOCyyy7jtttuY/vtt09Zfgnke1YS32f1HdygQYN47733mDZtGtdddx0A99xzDyeffHKVDWlD1lfbPLFZk01ex/C6NMmeOd9zcvvttzNz5kwqKioYMWIEv/zlL1OWF4IzHW+//TYnnXRSjXG1tV7mu0LMyrZt27j88sv505/+VGuZX331VXbeeWe6du1aY1xtB2v5TDlJbvHixVx11VX89a9/rTGuqXKyQ8bX0Mx98cUXPPvssyxatAgzY+vWrZgZo0ePxt1rBKK2ysAOO+zAtm3b4q83btxYZfwuu+wSf37++eczbdo0SkpKGDduHLNnzwbg6KOPpry8nDlz5rB169akG5hERUVFrFz5XeNcRUVFldMtidMNHjwYCCpLsX+MBQsWxP9x16xZw8yZM9lhhx0K7tRtVIWQldj7nDdvHlOnTk06/phjjmH58uWsWbOGl19+mRdeeIF77rmHr7/+mm+//ZZdd92V//zP/6Si4rvG5sT1tWnThtWrV9O2bVtWr14d77aUrIzAZoKW6n6JbweYHQ4vqjb84/D5p2bW1t1Xh11MPostFqh6VJBm+Z6Tzz//nIULF3LEEUcAwc55wIABdS435m9/+xuDBg1ixx13rDI8VebyVaFmpbKykkWLFtGvXz8APvnkE0477TRmzJhBWVkZUHslaeHChWzZsoWePXvWWb58opz0A2rmpKKigkGDBvHwww9zwAEHVFlmU+ZELdopTJkyhWHDhvHhhx9SXl7OypUrKS4u5sUXX+TEE09kzJgxbNiwAQjulrD77rtTVFQU71e6adMmNmzYwP77788777zDpk2bWLduHbNmzap1nZWVlbRt25bNmzczYcKEKuOGDRvG0KFD45Xhupx22mlMmjSJTZs2sWLFCpYuXcrhhx9eY7ozzjgjfkXunDlz6NSpEwArVqygvLyc8vJyzjrrLO655x5VsutQCFkBmDx5MqeeemqV/nDLli2Lb7xff/11vv32W77//e8zYcIEPvroI8rLy/njH//IsGHDuPXWW2nbti277bYbr7zyCu7Oww8/zOmnnx4vy/jxQffp8ePHVxn+8MMP4+688sor7LHHHhBUtJ8GTjSzvcK7h5wIPB12Cak0s17h3UaGAdPDIs8AYncnGV5t+DDL4LnEfM/JXnvtxbp161iyZAkQXP3fuXPnSJ9Nba3WyTJXCAo1K3vssQdr1qyJ73969epVpZK9bds2Jk+eHG8ISlSIZz6Uk5o5+eqrrzjllFO45ZZbOProo2ust0lzEuWKyebwyNTVvH379vWnnnqqyrA77rjDL774YncP7orQuXNnLykp8d/85jfu7r5kyRLv37+/d+vWzXv06OHLly939+BuCp06dfJTTjnFBw0a5GPHjnV39/33398///zz+PLvueceb9++vfft29dHjRpV5era1atXe8uWLX3t2rXxYffee6/fe++9Sct/8803e4cOHbxTp07xuzq4uw8cODB+Re7atWv95JNP9q5du3qvXr38zTffrLGc4cOH664jKRRCVmp7n7feeqsfcsghXlJS4r169fIXXnihxvLHjh1b5a4j8+fP9y5duniHDh38kksuid+1ZM2aNX7sscd6x44d/dhjj/UvvvjC3d23bdvmP//5z71Dhw7etWtXnz9/fjwnwAXAsvAxwsPvGigDFgHLgb8AFg7/PjALWBr+bRUON+BuYLly0vCcPPHEE961a1fv3r279+3bN17eefPm+b777us777yzt2rVyg855JD4/CtWrPB27drF736U6jOrL21TmldWqn8OiXcdee655/yII45Ius7i4mJ/9913k46LQjnJj5zcdNNNvvPOO3tJSUn8kXhHtcbmxD16VmI7nWavrKzMY/dPzGdTpkxh+vTpPPLII9kuSkaZ2WvuXpaJZSsr+UM5abxCyAkoK+lQCFlRThqvEHIC0bOS1T7aZnYQ8FjCoA7A9cCewIXA5+Hwa9x9ZhMXL+f84he/4KmnnmLmzML7KJSV+inUrCgn9VOoOQFlpb4KNSvKSf0Uak7qkjMt2ma2PbAKOAIYAXzt7n+MOn+hHCkWirqOFJUViVFOJCplRaJQTiSqqC3auXQx5HHAcnf/MNsFkZynrEgUyolEpaxIFMqJ1FsuVbSHABMTXo8ys7fMbEx4JwGRGGVFolBOJCplRaJQTqTecuI+2mb2PeA04DfhoHuBmwh+XOIm4E8EdxWoPt9IYCQE996N3ccx5u1V6yKtv9u+ezSs4NLkMpUVyS/KiUSlrEgUyok0VE700Taz04FL3P3EJOPaA//n7nXe9TxZ36f2Vz8Zaf3lt54StajSRGrr+5SprEjzpJxIVMqKRKGcSFTNrY/2UBJOx4S/1BYziOA+uCKgrEg0yolEpaxIFMqJNEjWu46Y2c7ACcBFCYNHm1kpwSmZ8mrjpEApKxKFciJRKSsShXIijZH1ira7byD4lbbEYedlqTiSw5QViUI5kaiUFYlCOZHGaHBFO7ww4D1375DG8kgjROmTrv7oIiIiIk2jMX20DWifpnKIiIiIiOSVOlu0zWxrXaMJ+iaJiIiIiEg1qbqOfElwX8h3koxrAbyd9hKJiIiIiOSBVBXt14DW7r68+ggza0HQqi0iIiIiItWkqmhfAWxONsLdN5lZcfqLJCIiIiLS/NVZ0Xb3xSnGf5je4ohkh+7YIiIiIunW4LuOWOCYdBZGRERERCRfNOb2ft8DnktXQURERERE8kmq2/sNq2P099JcFhERERGRvJHqYsixBHce2ZRknO44IiIiIiJSi1QV7aXAVe5eo4uImbUYUHVeAAAgAElEQVQENmSkVCJSL7qYU0REJPekqmjPAQ4meV/sreF4EWlGolTKQRXzZPTZiYhIfaS6vd9FdYzbDPRPe4lERERERPJAqhbtjDOzcqCSoIV8i7uXmVkr4DGgPVAO/Njd12arjJIblBWJQjmpnVrkq1JWJArlRBoj1V1HDgKOd/e7w9f/oOrdRv7D3d9PQzn6u/uahNdXA7Pc/VYzuzp8fVUa1tOsaKeYlLKSZzKUc+VEolJWJArlRBok1X20rwK+Tnh9FDAhfCwmCFYmnA6MD5+PB87I0Hqk+VNWJArlRKJSViQK5UQiSVXRPgaYmvB6q7s/5O4PAdcAvdNQBgf+aWavmdnIcFgbd18NEP7dJw3rkeZPWZEolBOJSlmRKJQTabBUfbT3cff1Ca/jP2Dj7pVm1iYNZTja3T82s32AZ8zsvagzhoEfCdCmTRtmz55dZfwV3bZEWk5svrdXrYs0fbd994haxCrqu/z6lj/K9NU/o0yK8n7r+VlmNStN+dnVV33KX99cZVoGypMz25Rc09zLnwEZy0oGtn+SPRnLieQ/c/faR5qtIghYeZJxHYAX3b1d2gpj9luCrioXAv3cfbWZtQVmu/tBdc1bVlbmCxYsqDKsvn0/M90nOtPlybV7KTemPGb2mruX1TZfNrKSy33h61P+XOv735jy5GJOaitrLmju5W+MXMxKPn7OuaA5bVOk+UqVlZhULdpPAjcB5yUZd2M4vsHMbBdgu7B1fBfgROB3wAxgOHBr+Hd6Y9YjzZ+yIlEoJ/ktnZVXZUWiUE6ksVJVtK8HXjKzNwj6an8CtCXo9L8X0KuR628DTDWzWFkedfd/mNl84G9m9lPgI+DsRq5Hmj9lRaJQTtIoz1vAlRWJIqM5yfP/MSH1D9Z8YmZlwC+BgUBr4AtgJvBnd/+iMSt39w+AkiTDvwCOa8yyJb8oKxKFciJRKSsShXIijZXyB2vc/Uvgv8KHiIiIiIhEkOoHa/YAStz9+fD1NdXmuauQfwlJp3wkqvr2LdWFVCIiIs1fqhbtXwFbgOfD19fw3X21i4EdgesyUzQRERERkeYrVUV7EDAg4fVmdz8PwMyKCPpqq6ItIiIiIlJNql+GbOfuFQmv7489CYcXZaRUIiIiIiLNXKqKNma2d+y5u1+VbLiIiIiIiFSVquvIXGAEMDrJuBHAy2kvkYhIgdIF1iIiTacpbjyQqqJ9I/CcmbUDnuC7H6w5E7gAOLZRaxcRERERyVOpuo68TvBzoz2BZ4H3gFlAGTDA3edntngiIiIiIs1TqhbtVcAjwM+B5QQ/u77W3TdkumAiIiKSHbqXv0h6pKpoXwz8P2Ae8C4wDngUUEVbRCQF9bkWESlsdXYdcffp7n42Qb/svwI/BirMbIaZDTazHZuikCIiIiIizU3K2/sBuPtX7v5Xd+8NdAYWALcDqzNZOBERERGR5ipV15EqzKwFcBhwBNAGeCkThRLJdeq/KCIiIqlEqmibWW9gGEHXkc8IL5B09w8zWDYRERFpBtT4IJJcnV1HzOy3ZrYc+Hs46BR37+TuN6Wjkm1m+5nZc2b2rpktNrP/TFjvKjN7M3yc3Nh1SfOmrEgUyolEpaxIFMqJNFaqFu1ewLXANHffmIH1bwGucPfXzWw34DUzeyYcd7u7/zED65TmSVmRKJQTiSqnslLfFmG1IDeZnMqJND91VrTdfUAmV+7uqwkvqHT3SjN7F9g3k+uU5klZkSgKLSe6fWDDFVpWpGGUE2msSHcdaQpm1h44FHg1HDTKzN4yszFmtlfWCiY5R1mRKJQTiUpZkSiUE2kIc/dslwEz2xWYA/ze3Z8wszbAGsCBm4C27n5BkvlGAiMB2rRp03PSpElVxr+9al2k9Xfbd4+CmT42bVNoTHn69+//mruXVR+ezawklrU5T1/fXGVaY8qTizlJLGuhTZ9p2qY0fPr6yrXy1Ie2KU27r2/OMrFNqS7rFe3wR2/+D3ja3f+cZHx74P/cvWtdyykrK/MFCxZUGVbf06qFMH1TnkJuTHnMrEaAs52VxvSPzKXpc627QWPKk4s5SSxroU2fadqmNF0f7VwrT31om6LuYlGle5uSTFa7jpiZAQ8B7yaG18zaJkw2CFjU1GWT3KKsSBTKiUSlrEgUyok0Vr1+sCYDjgbOA942szfDYdcAQ82slOCUTDlwUXaKl99yqQUiAmVFolBOJKqCykoz297nkoLKiaRfViva7v4iYElGzWzqskhuU1YkCuVEolJWJArlpG7qypJaztx1REREREQkn2S764iIiIiIZIBanLNPLdoiIiIiIhmgiraIiIiISAaooi0iIiIikgHqoy0idVIfP4lKt5ATEalKFW0RERERyXjDSiE23KjriIiIiIhIBqiiLSIiIiKSAapoi4iIiIhkgCraIiIiIiIZoIq2iIiIiEgGqKItIiIiIpIBur2fRKZ75IpIOmmbUpgK8RZvUrjUoi0iIiIikgE526JtZgOAO4DtgQfd/dYsF0lylLIiUSkrEoVykltyuQVcWcms+n73uZiVnKxom9n2wN3ACUAFMN/MZrj7O9ktmeQaZSX35OKGDpQViUY5kaiUFYkiV7uOHA4sc/cP3P1bYBJwepbLJLlJWZGolBWJQjmRqJQVScncPdtlqMHMzgIGuPvPwtfnAUe4+6hq040ERoYvDwLeb9KCSibt7+57p5pIWSl4kXIC0bKinOQ1bVMkCm1TJKpIWcnJriOAJRlW44jA3e8H7s98cSSHKSsSVcqsKCeCtikSnbYpklKudh2pAPZLeF0EfJylskhuU1YkKmVFolBOJCplRVLK1Yr2fOBAMys2s+8BQ4AZWS6T5CZlRaJSViQK5USiUlYkpZzsOuLuW8xsFPA0wS1zxrj74iwXS3KQsiJRKSsShXIiUSkrEkVOXgwpIiIiItLc5WrXERERERGRZk0VbRERERGRDFBFW0REREQkA1TRFhERERHJAFW0RUREREQyQBVtEREREZEMUEVbRERERCQDVNEWEREREckAVbRFRERERDJAFW0RERERkQxokoq2mY0xs8/MbFHCsFZm9oyZLQ3/7hUONzO708yWmdlbZtajKcoouUFZkSiUE4lKWZEolBPJlKZq0R4HDKg27GpglrsfCMwKXwMMBA4MHyOBe5uojJIbxqGsSGrjUE4kmnEoK5LaOJQTyYAmqWi7+/PAl9UGnw6MD5+PB85IGP6wB14B9jSztk1RTsk+ZUWiUE4kKmVFolBOJFN2yOK627j7agB3X21m+4TD9wVWJkxXEQ5bXX0BZjaS4GiSnXbaqed+++2X2RJLkyguLmbFihVbEwYpK1KDciJRKSsShXIi9bFkyZI17r53qumyWdGujSUZ5skmdPf7gfsBysrKfMGCBZkslzSR8vJyiouLN0eYVFkpYMqJRKWsSBTKidSHmX0YZbps3nXk09iplvDvZ+HwCiDxkK8I+LiJyya5RVmRKJQTiUpZkSiUE2m0bFa0ZwDDw+fDgekJw4eFV/X2AtbFTt1IwVJWJArlRKJSViQK5UQarUm6jpjZRKAf0NrMKoAbgFuBv5nZT4GPgLPDyWcCJwPLgA3AiKYoo+SGoUOHMnv2bIAWyorURjmRqJQViUI5kUwx96Tdipod9X3KL2b2mruXZWLZykr+UE4kKmVFolBOJKqoWdEvQ4qIiIiIZIAq2iIiIiIiGaCKtoiIiIhIBqiiLSIiIiKSAapoi4iIiIhkgCraIiIiIiIZoIp2HaZOnYqZ8d5772W7KPVyyy230LFjRw466CCefvrppNO4O9deey2dOnWic+fO3HnnnfFxs2fPprS0lC5dutC3b18ANm7cyOGHH05JSQldunThhhtuiE//05/+lJKSErp3785ZZ53F119/ndk3mGPyOSd9+vShtLSU0tJS2rVrxxlnnBEflywnAO3bt6dbt26UlpZSVvbdnY+uu+46unfvTmlpKSeeeCIff1x4P6SWz1mZNWsWPXr0oLS0lN69e7Ns2TIA7rvvvngeevfuzTvvvAMEP3e90047xfN18cUXx5f17bffMnLkSDp16sTBBx/M448/nvk3mWMKMSvjxo1j7733jmfiwQcfjM9z5ZVX0qVLFzp37syll16Ku1NZWRmftrS0lNatW3PZZZc1yfvMFYWYk8svvzz+nXfq1Ik999wzPs/2228fH3faaafFh59//vkUFxfHx7355puZfYOJ3D0vHj179vR0O/vss713795+ww03pH3ZibZs2ZK2ZS1evNi7d+/uGzdu9A8++MA7dOiQdPljxozx8847z7du3eru7p9++qm7u69du9Y7d+7sH374YZXh27Zt88rKSnd3//bbb/3www/3l19+2d3d161bF1/u5Zdf7rfcckuj3wewwJtJVvI5J4nOPPNMHz9+vLvXnhN39/33398///zzGvMn5uSOO+7wiy66qNHvoznlxD2/s3LggQf6O++84+7ud999tw8fPtzdq37v06dP95NOOsnd3VesWOFdunRJus7rr7/er732Wnd337p1a9I81ZeyklwuZWXs2LF+ySWX1Jh+7ty5ftRRR/mWLVt8y5Yt3qtXL3/uuedqTNejRw+fM2dOo96DcpJcLuUk0Z133ukjRoyIv95ll12SrnP48OE+efLk9LyBUNSsqEW7Fl9//TVz587loYceYtKkSVXGjR49mm7dulFSUsLVV18NwLJlyzj++OMpKSmhR48eLF++nNmzZ3PqqafG5xs1ahTjxo0Dgla/3/3ud/Tu3ZvJkyfzwAMPcNhhh1FSUsLgwYPZsGEDlZWVFBcXs3nzZgDWr19P+/bt46+TmT59OkOGDKFFixYUFxfTsWNH5s2bV2O6e++9l+uvv57ttgsisM8++wDw6KOPcuaZZ/LDH/6wynAzY9dddwVg8+bNbN68GTMDYPfddweCg7Z///vf8eGFIN9zElNZWcmzzz4bb9GuLSd1ieUE4JtvvimonED+Z8XMWL9+PQDr1q2jXbt2QMO+9zFjxvCb3/wGgO22247WrVunnCefFGpWamNmbNy4kW+//ZZNmzaxefNm2rRpU2WapUuX8tlnn9GnT586l5VPlBOYOHEiQ4cOrd8H18RU0a7FtGnTGDBgAJ06daJVq1a8/vrrADz11FNMmzaNV199lYULF3LllVcCcO6553LJJZewcOFCXnrpJdq2bZtyHS1btuTFF19kyJAhnHnmmcyfP5+FCxfSuXNnHnroIXbbbTf69evHk08+CcCkSZMYPHgwO+64I/fddx/33XdfjWWuWrWK/fbbL/66qKiIVatW1Zhu+fLlPPbYY5SVlTFw4ECWLl0KwJIlS1i7di39+vWjZ8+ePPzww/F5tm7dSmlpKfvssw8nnHACRxxxRHzciBEj+MEPfsB7773HL37xiygfcV7I95zETJ06leOOOy5eaaorJ2bGiSeeSM+ePbn//vurLOfaa69lv/32Y8KECfzud79L+d7zSb5n5cEHH+Tkk0+mqKiIRx55JL5zB7j77rs54IADuPLKK6t0U1uxYgWHHnooffv25YUXXgDgq6++AoKuRj169ODss8/m008/Tfne80khZ+Xxxx+Pd0NcuXIlAEceeST9+/enbdu2tG3blpNOOonOnTtXWebEiRM555xzCuoAvpBzAvDhhx+yYsUKjj322PiwjRs3UlZWRq9evZg2bVqV6a+99lq6d+/O5ZdfzqZNm1K+93RRRbsWEydOZMiQIQAMGTKEiRMnAvCvf/2LESNGsPPOOwPQqlUrKisrWbVqFYMGDQKCYMbG1+Wcc86JP1+0aBF9+vShW7duTJgwgcWLFwPws5/9jLFjxwIwduxYRowYAcDFF19cpU9jTHA2o6pkG55NmzbRsmVLFixYwIUXXsgFF1wAwJYtW3jttdd48sknefrpp7nppptYsmQJEPR9evPNN6moqGDevHksWrQovryxY8fy8ccf07lzZx577LGU7z1f5HtOEt9nYqtBXTmZO3cur7/+Ok899RR33303zz//fHy+3//+96xcuZJzzz2Xv/zlLynfez7J96zcfvvtzJw5k4qKCkaMGMEvf/nL+LhLLrmE5cuXc9ttt3HzzTcD0LZtWz766CPeeOMN/vznP/OTn/yE9evXs2XLFioqKjj66KN5/fXXOfLII/nVr36V8r3nk0LNyo9+9CPKy8t56623OP744xk+fDgQtMS+++67VFRUsGrVKp599tkq2xUIKni53rKZboWak5hJkyZx1llnsf3228eHffTRRyxYsIBHH32Uyy67jOXLlwNBn/D33nuP+fPn8+WXX3LbbbelfO/pskOTrakZ+eKLL3j22WdZtGgRZsbWrVsxM0aPHo271whEstAA7LDDDmzbti3+euPGjVXG77LLLvHn559/PtOmTaOkpIRx48Yxe/ZsAI4++mjKy8uZM2cOW7dupWvXrnWWvaioKN4KAFBRUZH0dEtRURGDBw8GYNCgQfF/jKKiIlq3bs0uu+zCLrvswjHHHMPChQvp1KlTfN4999yTfv368Y9//KNKebbffnvOOecc/vCHP8SXl88KISex9zlv3jymTp1aZf7achJbzj777MOgQYOYN28exxxzTJVl/uQnP+GUU07hxhtvrLOc+SLfs/L555+zcOHC+Fmuc845hwEDBtRY1pAhQ/iP//gPAFq0aEGLFi0A6NmzJwcccABLliyhZ8+e7LzzzvEKwdlnn81DDz1UZxnzSSFn5fvf/358ugsvvJCrrroKCM6o9erVK959ceDAgbzyyivx7crChQvZsmULPXv2rLN8+aSQcxIzadIk7r777irDYsvp0KED/fr144033uCAAw6It963aNGCESNG8Mc//rHOMqaTWrSTmDJlCsOGDePDDz+kvLyclStXUlxczIsvvsiJJ57ImDFj2LBhAwBffvklu+++O0VFRfHTFJs2bWLDhg3sv//+vPPOO2zatIl169Yxa9asWtdZWVlJ27Zt2bx5MxMmTKgybtiwYQwdOjRS5fW0005j0qRJbNq0iRUrVrB06VIOP/zwGtOdccYZPPvsswDMmTMnXpE+/fTTeeGFF9iyZQsbNmzg1VdfpXPnznz++efxU7r//ve/+de//sXBBx+Mu8evBHZ3/v73v3PwwQenLGc+KIScAEyePJlTTz2Vli1bxofVlpNvvvmGyspKIOiP+89//jO+0Y11TwKYMWNGweQE8j8re+21F+vWrYuf1XjmmWfip/YTv/cnn3ySAw88EAh2pFu3bgXggw8+YOnSpXTo0AEz40c/+lF8Jz5r1iwOOeSQlOXMF4WcldWrV8enmzFjRnz4D3/4Q+bMmcOWLVvYvHkzc+bMqdJ1pDn00023Qs4JwPvvv8/atWs58sgj48PWrl0b7xKyZs0a5s6dG992xLLl7kybNi3lwUBaRblisjk80nk1b9++ff2pp56qMuyOO+7wiy++2N3db7nlFu/cubOXlJT4b37zG3d3X7Jkiffv39+7devmPXr08OXLl7u7+69//Wvv1KmTn3LKKT5o0CAfO3asu9e8M8M999zj7du39759+/qoUaOqXF27evVqb9mypa9duzY+7N577/V77703aflvvvlm79Chg3fq1MlnzpwZHz5w4EBftWqVuwd3jTj55JO9a9eu3qtXL3/zzTfj040ePdo7d+7sXbp08dtvv93d3RcuXOilpaXerVs379Kli994443uHtwR4KijjvKuXbt6ly5d/Cc/+UmVuww0FM3gyu9CyElt79M9eU6WL1/u3bt39+7du/shhxziN998c3z6M88807t06eLdunXzU0891SsqKmr/cCNqDjlxL4ysPPHEE961a1fv3r279+3bN17eSy+91A855BAvKSnxfv36+aJFi9zdfcqUKX7IIYd49+7d/dBDD/UZM2bEl1teXu59+vTxbt26+bHHHhu/u01jKCu5n5Wrr746nol+/fr5u+++6+7BHS9GjhzpBx98sHfu3Nkvv/zyKussLi6OT9tYyknu58Td/YYbbvCrrrqqyjLnzp0bn75r167+4IMPxsf1798/Xk8599xz43dRa4yoWbFg2uwws4OAxA69HYDrgT2BC4HPw+HXuPvMupZVVlbmCxYsyEg5s23KlClMnz6dRx55JNtFaTJm9pq7lyW8VlZSUE6Uk6iUFWUlqkLLinLSMIWWE6iZldpktY+2u78PlAKY2fbAKmAqMAK43d2brhNNjvrFL37BU089xcyZdf7/5j1lpW7KSUA5SU1ZCSgrqSkrykkUykndculiyOOA5e7+YSHdnieVu+66K9tFyEXKSjXKSVLKSRLKSlLKShLKSg3KSRLKSd1y6WLIIcDEhNejzOwtMxtjZntlq1CSk5QViUI5kaiUFYlCOZF6y4kWbTP7HnAa8Jtw0L3ATYCHf/8EXJBkvpHASIA2bdrEr1KPeXvVujrX223fPeo1nWRftrMizUOmciL5R1mRKJQTaaisXgwZL4TZ6cAl7n5iknHtgf9z9zrvxZLsIoP2Vz9Z53rLbz2lXtNJ06ntIoNsZ0VyS1PnRJovZUWiUE4kqqgXQ+ZK15GhJJyOMbPE3wUdBCyqMYcUKmVFolBOJCplRaJQTqRBst51xMx2Bk4ALkoYPNrMSglOyZRXGycFSlmRKJQTiUpZkSiUE2mMrFe03X0D8P1qw87LUnEkhykrEoVyIlEpKxKFciKNkStdR0RERERE8kqdLdpmtitwM9ARuB34CJhE8MtI/wJGuvvaTBdS0kMX/ImIiIg0nVQt2ncBrYEvgGkEFwP8HPgRsDfw3xktnYiIiIhIM5Wqj/ZAgtbr7YDzgAfcfTWAmQ0HXshs8UREREREmqdUFe2W4UUAmNn6WCUbIPwJUv0SkoiIiIhIEqm6jnxiZq3C51U68JrZfsBXGSmViIiIiEgzl6qifQOwE4C7z602rg8wPhOFEhERERFp7ursOuLuj9Ux7tH0F0dEJHfpzj0iIlIfDb6PtgWOSWdhRERERETyRWN+sOZ7wHPpKoiIiIiISD5J9YM1w+oY/b00l0VEMixq1wd1kRAREWm8VLf3Gwu8BmxKMs7SXxwRERERkfyQqqK9FLjK3Wt0ETGzlsCGjJRKRERERKSZS1XRngMcTPK+2FvD8ZJB6TjVr9P8TUvdLiQqZSV/6bsVEUh9e7+L6hi3Geif9hKJiIiIiOSBVC3aGWdm5UAlQQv5FncvC3+N8jGgPVAO/Njd12arjJIblBWJQjmRqJQViUI5kcZIddeRg4Dj3f3u8PU/qHq3kf9w9/fTUI7+7r4m4fXVwCx3v9XMrg5fX5WG9UjzV3BZKZRT0Gl+nwWXE2kwZUWiUE6kQVK1aF9F1X7YRwGXh89LCYI1IgPlOh3oFz4fD8xGAZbklBWJQjmRqJQViSItOSmUhpRCluoHa44Bpia83uruD7n7Q8A1QO80lMGBf5rZa2Y2MhzWxt1XA4R/90nDeqT5U1YkCuVEolJWJArlRBosVYv2Pu6+PuF1/Ads3L3SzNqkoQxHu/vHZrYP8IyZvRd1xjDwIwHatGnD7Nmzq4y/otuWOuePTR91urdXratzum777lHn+IZIx3uo7/vMYVnPSl0ZiH3/6f6c07m8dP9PpFMa15n1nESVB/+TzV2zyYpklXIiDWbuXvtIs1UEAStPMq4D8KK7t0tbYcx+C3wNXAj0c/fVZtYWmO3uB9U1b1lZmS9YsKDKsHT/Cl42TvGk8/Z+zekUlZm95u5ldYz/LTmWlUx9zulcXj5kPVGu5iSq5vQ/2dw196xI01BOJKpUWYlJ1XXkSeCmWsbdGI5vMDPbxcx2iz0HTgQWATOA4eFkw4HpjVmPNH/KikShnEhUyopEoZxIY6XqOnI98JKZvUHQV/sToC1wBrAX0KuR628DTDWzWFkedfd/mNl84G9m9lPgI+DsRq5Hmj9lRaJQTtKkAH4Eq9lkRa2eWdVsciK5KdUP1nxiZmXAL4GBQGvgC2Am8Gd3/6IxK3f3D4CSJMO/AI5rzLIlvygrEoVyUhjScRCgrEgUyok0VsofrHH3L4H/Ch8iIiIiIhJBqh+s2QMocffnw9fXVJvnLv0SUsMU0qnAAjgF3SCFlAHJT8qwiEjdUrVo/wrYAjwfvr6G7+6rXQzsCFyXmaKJiIiINIwOBCUXpKpoDwIGJLze7O7nAZhZEUFfbVW0RURERESqSVXRbufuFQmv7489cfeKsLItIlmmlhtRBkREck+q+2hjZnvHnrv7VcmGi4iIiIhIValatOcCI4DRScaNAF5Oe4maObUqiYi2AyIiAqkr2jcCz5lZO+AJvvvBmjOBC4BjM1s8EREREZHmKVVF+3WCnxsdDYwi6GqyDXgVGODu8zNbPBERERGRzMnkbYhTVbRXAY8APweWE/zs+lp339CotUpO02lvkdyie9GLSBTaf+eeVBdDXkxwv+x5wIvAYGDnTBdKRERERKS5q7NF292nA9PNbE/gHOA8YLSZ/RMYD8xw982ZL6aIiKSDWrxERJpOqq4jALj7V8Bfgb+aWTFBhfv2cFjrzBVPRERE0kkHWyJNJ1JFO8bMWgCHAUcAbYCXMlEoERERyX2qtIvULeUP1gCYWW8zux/4FLgZeAXo5O79M1k4EREREZHmqs4WbTP7LUE3kVbAZOAUd5+brpWb2X7Aw8APCG4beL+73xGu90Lg83DSa9x9ZrrWK82PsiJRKCcSVa5kRXeUyW25khNpvlJ1HekFXAtMc/eNGVj/FuAKd3/dzHYDXjOzZ8Jxt7v7HzOwTmmelBWJQjmRqJQViUI5kUZJddeRAZlcubuvBlaHzyvN7F1g30yuU5onZUWiUE4kKmVFolBOpLHM3bNdBgDMrD3wPNAV+CVwPrAeWEBwNLk2yTwjgZEAbdq06Tlp0qQq499eta7OdXbbd4+0T5eNdaaaLtsL5oUAACAASURBVFPrjCpK2arr37//a+5elmxcrmYlG99tbLps5S6dGrLO5piTdE/XHNaZbtqmNM10UWQrA1Hk0zYlqlz+PnJZurcpiXKiom1muwJzgN+7+xNm1gZYAzhwE9DW3S+oaxllZWW+YMGCKsOiXg2dzumysc5U02VqnVE1pA+imSUNcC5nJRvfbWy6bOUunRqyzuaYk3RP1xzWmW7apjTNdFHk8l1H8mmbElUufx+5LJ3blOoi3XUkk8xsR+BxYIK7PwHg7p+6+1Z33wY8AByezTJKblBWJArlRKJSViQK5UQaI6sVbTMz4CHgXXf/c8LwtgmTDQIWNXXZJLcoKxKFciJRKSsShXIijVWvH6zJgKMJbh/4tpm9GQ67BhhqZqUEp2TKgYuyUzzJIcqKRKGcSFTKikRRsDlRN5T0yGpF291fBCzJKN2LUqpQViQK5USiUlZS0z2+lRNpvGy3aItIM6YdsYhEodZRKVRZvxhSRERERCQfqUVbREREpIBk42xkoZ7VUEVbREREJIcVaiU1H6jriIiIiIhIBqiiLSIiIiKSAeo6IiIiIiINks5uLfnYRUYt2iIiIiIiGaAWbRERyah8bKUSEYlCFW1pMO08RURERGqnriMiIiIiIhmgiraIiIiISAaooi0iIiIikgHqoy0iIiI5IRs/DS6SSTlb0TazAcAdwPbAg+5+a5aLJDlKWZGolBWJQjmRqJSV7GhON2PIya4jZrY9cDcwEDgEGGpmh2S3VJKLlBWJSlmRKJQTiUpZkShytUX7cGCZu38AYGaTgNOBd7JaKslFykqOy6GWB2Ulx+VIVpSTHJcjOQFlJeflQlZyskUb2BdYmfC6IhwmUp2yIlEpKxKFciJRKSuSkrl7tstQg5mdDZzk7j8LX58HHO7uv6g23UhgZPjyIOD9Ji2oZNL+7r53qomUlYIXKScQLSvKSV7TNkWi0DZFooqUlVztOlIB7Jfwugj4uPpE7n4/cH9TFUpykrIiUaXMinIiaJsi0WmbIinlateR+cCBZlZsZt8DhgAzslwmyU3KikSlrEgUyolEpaxISjnZou3uW8xsFPA0wS1zxrj74iwXS3KQsiJRKSsShXIiUSkrEkVO9tEWEREREWnucrXriIiIiIhIs6aKtoiIiIhIBqiiLSIiIiKSAapoi4iIiIhkgCraIiIiIiIZoIq2iIiIiEgGqKItIiIiIpIBqmiLiIiIiGSAKtoiIiIiIhmgiraIiIiISAY0SUXbzMaY2WdmtihhWCsze8bMloZ/9wqHm5ndaWbLzOwtM+vRFGWU3KCsSBTKiUSlrEgUyolkSlO1aI8DBlQbdjUwy93/f3t3Hh9Vfe9//PWpqFSuKKhQMFSCAYlkE6JSRRZRC+IG6BWuCqJIrWKvXaxU+6tW7QNLvRetWrwqm14Fi5WlAqKCoKKVTbCoiCChgLgAEaK5IIHP74+ZjAlZ5kAyme39fDzyyJzv9yzfmXnPme+c+c457YH54WmAvkD78N8IYFwDtVESwySUFYluEsqJBDMJZUWim4RyIjHQIB1td38d2HFA8aXA5PDtycBlFcqf8pB/AMeaWauGaKfEn7IiQSgnEpSyIkEoJxIr8Ryj3dLdtwKE/7cIl58IbKow3+ZwmaQvZUWCUE4kKGVFglBOpM4axbsB1bBqyrzaGc1GEPrahu9///td2rRpE8t2SQPJzMxkw4YN+wLMqqykMeVEglJWJAjlRA7G2rVrt7n7CdHmi2dH+3Mza+XuW8NfuXwRLt8MVExiBvBpdStw98eBxwEKCwt92bJlsWyvNJCioiIyMzP3VihSVqQK5USCUlYkCOVEDoaZbQwyXzyHjswChoZvDwVmVigfEv5Vb1dgZ/lXN5K2lBUJQjmRoJQVCUI5kTprkCPaZjYF6Akcb2abgbuA+4G/mtn1wL+AK8KzzwEuBNYBpcCwhmijJIbBgwezcOFCgCOVFamJciJBKSsShHIisWLu1Q4rSjr6Sia1mNlydy+MxbqVldShnEhQyooEoZxIUEGzoitDioiIiIjEgDraIiIiIiIxoI62iIiIiEgMqKMtIiIiIhID6miLiIiIiMSAOtoiIiIiIjGgjvYBpk+fjpmxZs2aeDfloIwePZqsrCxOOeUU5s2bV+087s6dd95Jhw4dyM7O5s9//jMAzzzzDHl5eeTl5XHWWWexatWqyDJt27YlNzeXgoICCgu/O4vNqlWr+NGPfkRubi4XX3wxu3btiu0dTEDpmJU//elPFBQUUFBQQE5ODocddhg7duxg06ZN9OrVi+zsbDp16sRDDz0UWVdNWfn2228ZNmwYubm55Ofnl5/DFoDnnnuOvLw8OnXqxK9//etI+caNG+nduzd5eXn07NkT4PDyOjP7o5mtDv9dWaH8XDNbES6fbGaNwuXNzGy6mb1nZkvMLKfCMv9Zl8e4olTOybXXXktmZmYkEytXrgRC+fnZz35GVlYWeXl5rFixIrLMYYcdFpn/kksuiZSfc845kfLWrVtz2WWXxfYOJqBUzkpN+5SFCxdyzDHHRJ77e+65J7LMSy+9xCmnnEJWVhb3339/pDzds5KOOYFQVgoKCujUqRM9evSotNy+ffs47bTTuOiiiyJl8+fPp3PnzhQUFNCtWzfWrVsXmzsWjbunxF+XLl28PlxxxRXerVs3v+uuu+plfTUpKyurt3W9//77npeX57t37/ZPPvnE27VrV+36J0yY4Ndcc43v27fP3d0///xzd3dfvHix79ixw93d58yZ42eccUZkmZNOOsm//PLLKusqLCz0hQsXurv7+PHj/be//W293R93d2CZKyvunlhZqWjWrFneq1cvd3f/9NNPffny5e7uvmvXLm/fvr2///777l5zVh555BG/9tprI+vv3Lmz79u3z7dt2+Zt2rTxL774wt3dhwwZ4q+++qq7u19++eU+adIkd3efP3++A9s9dC2AfsArhC7C1QRYBjQldDBhE9AhPN89wPXh238C7grf7gjMD9/OAVYrJ9FzMnToUJ82bVqV8tmzZ3ufPn18//79/vbbb1fapzRp0iTq9gcMGOCTJ0+u2504gPYp30mkfcprr73m/fr1q7aN7dq18/Xr1/uePXs8Ly8vsk+pqL6zopx8J5FyUlxc7NnZ2b5x48ZK5eX+67/+ywcPHlwpS+3bt/cPPvjA3d0fffRRHzp0aL3dH/fgWdER7Qq+/vprFi9ezPjx45k6dWqlujFjxkSOvI0aNQqAdevWcd5555Gfn0/nzp1Zv349CxcurPSJauTIkUyaNAkIHR2+55576NatG9OmTeOJJ57g9NNPJz8/n4EDB1JaWkpJSQmZmZns3bsXgF27dtG2bdvIdHVmzpzJoEGDOPLII8nMzCQrK4slS5ZUmW/cuHH87ne/43vfCz3tLVq0AOCss86iWbNmAHTt2pXNmzdHfaw++ugjunfvDsD555/P3/72t6jLpJJ0zUpFU6ZMYfDgwQC0atWKzp07A3D00UeTnZ3Nli1bgJqz8sEHH9C7d+/I+o899liWLVvGJ598QocOHTjhhBMAOO+886pdplevXgDHhptzKrDI3cvc/RtgFdAHOA7Y4+5rw/O9AgyssMx8AHdfA7Q1s5ZANvCPGh/Eg5DqOalt+SFDhmBmdO3ala+++oqtW4NdobqkpIQFCxak3VHKVM9KkH1KRUuWLCErK4t27dpxxBFHMGjQIGbOnFlpnnTMSrrm5Nlnn2XAgAH88Ic/rFQOsHnzZmbPns3w4cMrrcvMIt+g7ty5k9atW0d/gGNAHe0KZsyYQZ8+fejQoQPNmzePfN05d+5cZsyYwTvvvMOqVasiX2VfddVV3HzzzaxatYq33nqLVq1aRd1G48aNefPNNxk0aBADBgxg6dKlrFq1iuzsbMaPH8/RRx9Nz549mT17NgBTp05l4MCBHH744Tz22GM89thjVda5ZcsW2rRpE5nOyMiIdHIqWr9+Pc899xyFhYX07duXjz/+uMo848ePp2/fvpFpM+OCCy6gS5cuPP7445HynJwcZs2aBcC0adPYtGlT1PueStI9K6Wlpbz00ksMHDiwyrJFRUW8++67nHnmmUDNWcnPz2fmzJmUlZWxYcMGli9fzqZNm8jKymLNmjUUFRVRVlbGjBkzKi1T3umePn06wPfM7DhCHeu+ZnaUmR0P9ALaANuAw82sfNzT5eFywssMADCzM4CTgAxgNdC9hqfloKR6TgDuvPNO8vLy+PnPf86ePXuiLr97924KCwvp2rUrM2bMqLK+6dOn07t3b5o2bRr1vqeSVM9KbfuUt99+m/z8fPr27cv7778feL3pmJV0zcnatWspLi6mZ8+edOnShaeeeiqyzK233sqYMWMinfNyTz75JBdeeCEZGRk8/fTTkQ8fDU0d7QqmTJnCoEGDABg0aBBTpkwB4NVXX2XYsGEcddRRADRv3pySkhK2bNlC//79gVAwy+trc+WVkaGjrF69mnPOOYfc3FyeeeaZyA5m+PDhTJw4EYCJEycybNgwAG688UZuvPHGKusMfYNRmZlVKduzZw+NGzdm2bJl3HDDDVx33XWV6l977TXGjx/PH//4x0jZ4sWLWbFiBXPnzuXRRx/l9ddfB2DChAk8+uijdOnShZKSEo444oio9z2VpHtW/v73v3P22WfTvHnzSuVff/01AwcO5MEHH4y8+dWUleuuu46MjAwKCwu59dZbOeuss2jUqBHNmjVj3LhxXHnllZxzzjm0bduWRo0aAfDAAw+waNEiTjvtNBYtWgSwFyhz95eBOcBbwBTg7XC5A4OAsWa2BCgBysLNvR9oZmYrgVuAd8PLfAh89yKog1TPyejRo1mzZg1Lly5lx44dkX1Hbcv/61//YtmyZTz77LPceuutrF+/vtJ8Fb8pSSepnpWa9imdO3dm48aNrFq1iltuuSVydDrIetMxK+mak7KyMpYvX87s2bOZN28e9957L2vXruXFF1+kRYsWdOnSpcq6xo4dy5w5c9i8eTPDhg3jF7/4RdT7HguN4rLVBLR9+3YWLFjA6tWrMTP27duHmTFmzBjcvUogqgsNQKNGjdi/f39kevfu3ZXqmzRpErl97bXXMmPGDPLz85k0aVLkx2Bnn302RUVFLFq0iH379pGTk0NtMjIyKh1R3rx5c7VfkWRkZESOQPbv3z/ywgB47733GD58OHPnzuW4446LlJevp0WLFvTv358lS5bQvXt3OnbsyMsvvwyEPmmWf7JNB+meFQgdwTjwDW7v3r0MHDiQq666igEDBkTKa8pKo0aNGDt2bGS+s846i/bt2wNw8cUXc/HFFwPw+OOPc9hhhwGhPL7wwgtAqFP/5z//GXffCeDufwD+AGBmzwIfh8vfBs4Jl18AdAiX7wKGhcsN2BD+w93HFxYWPlnrgxlFOuSk/OjYkUceybBhw3jggQeiLl/+v127dvTs2ZN3332Xk08+GQg9ZkuWLCn/tiJtpENWatqnVDwafeGFF3LTTTexbdu2qOtNx6ykc04yMjI4/vjjadKkCU2aNKF79+6sWrWKFStWMGvWLObMmcPu3bvZtWsXV199NWPHjmXVqlWRb1avvPJK+vTpU2sbY0VHtMOef/55hgwZwsaNGykqKmLTpk1kZmby5ptvcsEFFzBhwgRKS0sB2LFjB02bNiUjIyPy1eeePXsoLS3lpJNO4oMPPmDPnj3s3LmT+fPn17jNkpISWrVqxd69e3nmmWcq1Q0ZMoTBgwdX6eBU55JLLmHq1Kns2bOHDRs28PHHH3PGGWdUme+yyy5jwYIFACxatIgOHToAoSNMAwYM4Omnn46UAXzzzTeUlJREbr/88suRF9MXX3wBwP79+7nvvvuq/QSbqtI5KxAa67Zo0SIuvfTSSJm7c/3115OdnV3lqEFNWSktLeWbb74B4JVXXqFRo0aceuqplZYpLi7mL3/5S2Ts3bZt2yJvEKNHj4bQ0BDM7LDwEBLMLA/IA14OT7cI/z8SuB14LDx9rJmVfxUzHHg93PmOLFMX6ZCT8nHX7s6MGTMi+4dLLrmEp556CnfnH//4B8cccwytWrWiuLg4Mrxk27ZtLF68OPKcQ2ho0UUXXUTjxo2jtjGVpENWatqnfPbZZ5EO4ZIlS9i/fz/HHXccp59+Oh9//DEbNmzg22+/ZerUqZXOUpOOWUnnnFx66aW88cYblJWVUVpayjvvvEN2djajR49m8+bNFBUVMXXqVM4991z+93//l2bNmrFz507Wrg39POeVV14hOzs7wKMcA0F+MZkMf3X9NW+PHj187ty5lcoeeughv/HGG93dffTo0Z6dne35+fn+m9/8xt3d165d67169fLc3Fzv3Lmzr1+/3t3db7vtNu/QoYP369fP+/fv7xMnTnT3qmfw+Mtf/uJt27b1Hj16+MiRIyv9Inbr1q3euHFjLy4ujpSNGzfOx40bV23777vvPm/Xrp136NDB58yZEynv27evb9myxd1Dv9q98MILPScnx7t27eorV650d/frr7/ejz32WM/Pz/f8/HwvfyzXr1/veXl5npeX56eeeqrfd999kfU++OCD3r59e2/fvr3ffvvtvn///uAPdgAk8C+/0zkr7u4TJ070K6+8stI633jjDQc8Nzc3kqPZs2e7e81Z2bBhg3fo0ME7duzovXv39qKiosj6Bg0a5NnZ2Z6dne1TpkyJlE+bNs2zsrK8ffv2fv311zuw3ENv0o2BD8J//wAKPPx8Ezq7yIfAR8CtFcp/ROio9xrgBaBZhbo3lJPoOenVq5fn5OR4p06d/KqrrvKSkhJ3d9+/f7/fdNNN3q5dO8/JyfGlS5e6e+gMRzk5OZ6Xl+c5OTn+5JNPRn3M6ov2KYm5T3n44Yf91FNP9by8PD/zzDN98eLFkeVnz57t7du393bt2lV6/6npMasPykli5sTdfcyYMZ6dne2dOnXysWPHVln/gWeweeGFFyL7mx49ekTue30JmhULzZv8CgsLfdmyZfFuRr15/vnnmTlzJk8//XS8mxIXZrbc3Qujz3nwlJXUoZwEl845AWXlYKRzVpST4NI5JxA8K3Edo21mpwDPVShqB/yO0Cm7bgC+DJff4e5zGrh5cXPLLbcwd+5c5sxJm7sclbJSPWWlMuWkespJVcpK9ZSVypST6iknwSXMEW0zOwzYApxJ6AdKX7v7A0GXT7VPiumutk+KyoqUU04kKGVFglBOJKigR7QT6ceQvYH17r4x3g2RhKesSBDKiQSlrEgQyokctEQ6vd8gQue/LTfSzIYQupTyL929+MAFzGwEMAKgZcuWkdPOlPvnlp3Vbij3xGPqp8UxkqztbkD1nhVJScqJBKWsSBDKiRy0hBg6Ej7F1qdAJ3f/PHwZ5G2AA/cCrdz9utrWUd1XMm1HVX9u56L7+9VHs2MmWdtdn2r6SiZWWZHkpJxIUMqKBKGcSFDJNnSkL7DC3T8HcPfP3X2fu+8HngCqnmxR0pWyIkEoJxKUsiJBKCdySBKloz2YCl/HmFmrCnX9gdUN3iJJVMqKBKGcSFDKigShnMghifsYbTM7Cjgf+EmF4jFmVkDoK5miA+okTSkrEoRyIkEpKxKEciJ1cVAdbTNrBJRfw/JDdy+rawPcvRQ47oCya+q6Xkk9yooEoZxIUMqKBKGcSF3UOnTEzO43s5zw7RxClzB+I/z3oZnF6cLxIiIiIiKJLdoY7euAteHbfwbGufux7n4s8Bfg0Vg2TkREREQkWUXraDeuME8u8GCFuoeAzrFolIiIiIhIsovW0V7EdwP8lwLnVqjrCXwZgzaJiIiIiCS9aD+G/BnwipkNADYCfzezNwn9yrYrcHWM2yciIiIikpRqPaLt7hsInWXkf4G9wEKgBHgL6OzuM2LdQBERERGRZBT19H7uvpfQVY+eiH1zROKjtsve11RXXi/po7aciFSkrIgI1OHKkBbSvT4bIyIiIiKSKupyCfYjgNfqqyEiIiIiIqmk1qEjZjakluoj6rkt0gD0daaIiIhIw4g2RnsisBzYU02d1X9zRERERERSQ7SO9sfA7e5eZYiImTUGSmPSKhERERGRJBeto70I6Ej1Y7H3hevlINV1+MahnCFDQ0NiR4+5iIiIVKfWjra7/6SWur1Ar3pvkYiIiIhICoh6Hu1YM7MiQhfB2QeUuXuhmTUHngPaAkXAv7t7cbzaKIlBWTk46XqkXTmRoJQVCUI5kbqIdtaRU4Dz3P3R8PRLVD7byE/d/aN6aEcvd99WYXoUMN/d7zezUeHp2+thO5L8lBUJIiFzkq4ffhJcQmZFEo5yIock2nm0bwe+rjB9FvBM+O99QsGKhUuByeHbk4HLYrQdSX7KigShnEhQyooEoZxIINE62t2B6RWm97n7eHcfD9wBdKuHNjjwspktN7MR4bKW7r4VIPy/RT1sR5KfsiJBKCcSlLIiQSgncsiijdFu4e67KkxHLmDj7iVm1rIe2nC2u39qZi2AV8xsTdAFw4EfAdCyZUsWLlxYqf6XuWXVLlc+3z+37Ky2PvfEY6LW12XZaO2qS31d153g4pKVmuqi1dfHY3ooGSyvT/Lnui4Sdp+Sxs9JoopbVmoTLUfS4GKWE0l95u41V5ptIRSwomrq2gFvunvremuM2d2EhqrcAPR0961m1gpY6O6n1LZsYWGhL1u2rFJZtPGQdamP17KxXneiMLPl7l5YS/3dNFBWaqqLVl8fj2mititRJFJO6qNeYifRslIb5SR+GjonkryiZaVctKEjs4F7a6j7fbj+kJlZEzM7uvw2cAGwGpgFDA3PNhSYWZftSPJTViQI5USCUlYkCOVE6ira0JHfAW+Z2buExmp/BrQiNOi/GdC1jttvCUw3s/K2POvuL5nZUuCvZnY98C/gijpuR5KfsiJBKCcSlLIiQcQ0J9G+mZTkF+2CNZ+ZWSHwC6AvcDywHZgD/Le7b6/Lxt39EyC/mvLtQO+6rFtSi7IiQSgnEpSyIkEoJ1JXUS9Y4+47gN+G/0QkRWgcqIiISGxFu2DNMUC+u78enr7jgGUe1pWQJIh07tSl830/FHq8REQkVUQ7ov0roAx4PTx9B9+dVzsTOBz4f7FpmoiISPX0gUxEkkG0jnZ/oE+F6b3ufg2AmWUQGqutjraIiIiIyAGidbRbu/vmCtOPl99w983hzraIHCIdlRMREUld0c6jjZmdUH7b3W+vrlxERERERCqL1tFeDAyroW4Y8Hb9NkdEREREJDVEGzrye+A1M2sNvMB3F6wZAFwHnBvb5omIpIdYXLI76PIiIhIb0TraKwhdbnQMMJLQEfD9wDtAH3dfGtvmiYgIxHY8v34rIJKc9NpNfNE62luAp4GbgPWELrte7O6lsW6YiIiIHBx1vEQSS7SO9o3A1cAS4ENgEvAsoI62SArTm7WIiEjd1fpjSHef6e5XEBqX/T/AvwObzWyWmQ00s8MbopEiIiIiIskm6un9ANz9K3f/H3fvBmQDy4CxwNZYNk5EREREJFkF6miXM7MjgdOBM4GWwD9j0SgRERERkWQXbYw2AGbWDRhCaOjIF4R/IOnuG2PYNhERqQcacy8iEh+1drTN7G7gGqA5MA3o5+6L62vjZtYGeAr4AaHTBj7u7g+Ft3sD8GV41jvcfU59bVeSj7IiQSgnEpSykj7q8kFTOZG6inZEuytwJzDD3XfHYPtlwC/dfYWZHQ0sN7NXwnVj3f2BGGxTkpOyIkEoJxJUXLOibxmShvYpUie1drTdvU8sN+7uWwn/oNLdS8zsQ+DEWG5TkpOyIkEoJxKUsiJBKCfpI1Yffg/qx5CxZGZtgdMIXXUSYKSZvWdmE8ysWdwaJglHWZEglBMJSlmRIJQTORTm7vFuA2b2b8Ai4A/u/oKZtQS2AQ7cC7Ry9+uqWW4EMAKgZcuWXaZOnVqp/p9bdla7vdwTj6lzfbyWTeR21eZgl+3Vq9dydy88sDweWampLlp9vJ6vhmhXLB3MthMpJ3WtT9QsJKpk3qdEq2/IfW06SMZ9Sk3tO5Ce7/pTX/uUA8W9ox2+6M2LwDx3/+9q6tsCL7p7Tm3rKSws9GXLllUqi/Y1QF3q47VsIrerNge7rJlVCXC8slJTXbT6eD1fDdGuWDqYbSdSTupan6hZSFTJvE+JVt+Q+9p0kIz7lJradyA93/WnPvYp1Ql0er9YMTMDxgMfVgyvmbUKj4sC6A+sjkf7JHEoKxKEclL/UvWNXFmRIJQTqau4drSBswmdPvCfZrYyXHYHMNjMCgh9JVME/CQ+zZMEoqxIEMqJBJW0WdER7waVtDmRxBDXjra7vwlYNVU6F6VUoqxIEMqJBKWsSBDKidRVwpx1REREREQklaijLSIiIiISA/Eeoy0iIiJJQOO7G54e8+SnI9oiIiIiIjGgI9oiIiIiKSYVz5+fjNTRFhEREUCdL5H6po62iIgcMnXMRFKTXtv1Qx1tERERqTN1zESqUkdbRA6axv6JiEhN9B7wHZ11REREREQkBtTRFhERERGJAQ0dEREREZHANDQkOHW0pd7ohSciFdW0TwDtF9KN3h8kXWnoiIiIiIhIDOiItoiIxIWOcopIqkvYjraZ9QEeAg4DnnT3++PcJElQyooEpaxIEMpJw0vWD13KysFL1uf6UCXk0BEzOwx4FOgLnAoMNrNT49sqSUTKigSlrEgQyokEpaxIEIl6RPsMYJ27fwJgZlOBS4EP4toqSUTKSpKJ49EMZUWCUE4SUIIeBVVWYqAuF0RLxJyYu8dt4zUxs8uBPu4+PDx9DXCmu488YL4RwIjw5CnARw3aUImlk9z9hGgzKStpL1BOIFhWlJOUpn2KBKF9igQVKCuJekTbqimr8onA3R8HHo99cySBKSsSVNSsKCeC9ikSnPYpElVCjtEGNgNtKkxnAJ/GqS2S2JQVCUpZkSCUEwlKWZGoErWjvRRo+AmPAAAAG5pJREFUb2aZZnYEMAiYFec2SWJSViQoZUWCUE4kKGVFokrIoSPuXmZmI4F5hE6ZM8Hd349zsyQBKSsSlLIiQSgnEpSyIkEk5I8hRURERESSXaIOHRERERERSWrqaIuIiIiIxIA62iIiIiIiMaCOtoiIiIhIDKijLSIiIiISA+poi4iIiIjEgDraIiIiIiIxoI62iIiIiEgMqKMtIiIiIhID6miLiIiIiMRAg3S0zWyCmX1hZqsrlDU3s1fM7OPw/2bhcjOzP5vZOjN7z8w6N0QbJTEoKxKEciJBKSsShHIisdJQR7QnAX0OKBsFzHf39sD88DRAX6B9+G8EMK6B2iiJYRLKikQ3CeVEgpmEsiLRTUI5kRhokI62u78O7Dig+FJgcvj2ZOCyCuVPecg/gGPNrFVDtFPiT1mRIJQTCUpZkSCUE4mVRnHcdkt33wrg7lvNrEW4/ERgU4X5NofLth64AjMbQejTJN///ve7tGnTJrYtlgaRmZnJhg0b9lUoUlakCuVEglJWJAjlRA7G2rVrt7n7CdHmi2dHuyZWTZlXN6O7Pw48DlBYWOjLli2LZbukgRQVFZGZmbk3wKzKShpTTiQoZUWCUE7kYJjZxiDzxfOsI5+Xf9US/v9FuHwzUPEjXwbwaQO3TRKLsiJBKCcSlLIiQSgnUmfx7GjPAoaGbw8FZlYoHxL+VW9XYGf5VzeStpQVCUI5kaCUFQlCOZE6a5ChI2Y2BegJHG9mm4G7gPuBv5rZ9cC/gCvCs88BLgTWAaXAsIZooySGwYMHs3DhQoAjlRWpiXIiQSkrEoRyIrFi7tUOK0o6GvuUWsxsubsXxmLdykrqUE4kKGVFglBOJKigWdGVIUVEREREYkAdbRERERGRGFBHW0REREQkBtTRFhERERGJAXW0RURERERiQB3tsOnTp2NmrFmzJt5NOSijR48mKyuLU045hXnz5lU7z7XXXktmZiYFBQUUFBSwcuVKAIqLi+nfvz95eXmcccYZrF69OrLMV199xeWXX07Hjh3Jzs7m7bffBuDKK6+MrKdt27YUFBTE/k4mmFTOSrlbbrmFf/u3f4tMT5o0iRNOOCHy3D/55JORuttvv52cnBxycnJ47rnnIuWPPPIIWVlZmBnbtm2r/zuU4FI5J+ecc04kC61bt+ayyy6L1C1cuJCCggI6depEjx49IuXXXXcdLVq0ICcnp9K6Vq5cSdeuXSkoKKCwsJAlS5bE5o4lsFTOSk3vPzt37uTiiy8mPz+fTp06MXHixMgykydPpn379rRv357JkycDUFpaSr9+/ejYsSOdOnVi1KhRsb+DCSaVc1LTPmXhwoUcc8wxkbp77rkHgI8++ihSVlBQQNOmTXnwwQcBuPvuuznxxBMjdXPmzGmYO1oTd0+Jvy5dunhdXHHFFd6tWze/66676rSeaMrKyuptXe+//77n5eX57t27/ZNPPvF27dpVu/6hQ4f6tGnTqpT/6le/8rvvvtvd3T/88EM/99xzI3VDhgzxJ554wt3d9+zZ48XFxVWW/8UvfuG///3v6+vuVAIsc2Wl3tYVNCvu7kuXLvWrr77amzRpEimbOHGi33zzzVXmffHFF/28887zvXv3+tdff+1dunTxnTt3urv7ihUrfMOGDX7SSSf5l19+WW/3pSLlJH45KTdgwACfPHmyu7sXFxd7dna2b9y40d3dP//888h8ixYt8uXLl3unTp0qLX/++ef7nDlz3N199uzZ3qNHj3q7PxUpK4n1/vOHP/zBf/3rX7u7+xdffOHNmjXzPXv2+Pbt2z0zM9O3b9/uO3bs8MzMTN+xY4d/8803vmDBAncPvSd169Ytkpv6pJwk1j7ltdde8379+kVtb8uWLb2oqMjd3e+66y7/05/+VD93oBZBs6Ij2sDXX3/N4sWLGT9+PFOnTq1UN2bMGHJzc8nPz498gl63bh3nnXce+fn5dO7cmfXr17Nw4UIuuuiiyHIjR45k0qRJALRt25Z77rmHbt26MW3aNJ544glOP/108vPzGThwIKWlpZSUlJCZmcnevXsB2LVrF23bto1MV2fmzJkMGjSII488kszMTLKysg7qaNAHH3xA7969AejYsSNFRUV8/vnn7Nq1i9dff53rr78egCOOOIJjjz220rLuzl//+lcGDx4ceHupINWzsm/fPm677TbGjBkT6PH44IMP6NGjB40aNaJJkybk5+fz0ksvAXDaaafRtm3bQOtJNamek3IlJSUsWLAgcvTp2WefZcCAAfzwhz8EoEWLFpF5u3fvTvPmzausw8zYtWsXEDrK2bp16xq3l4rSJSsHMjNKSkpwd77++muaN29Oo0aNmDdvHueffz7NmzenWbNmnH/++bz00kscddRR9OrVCwi9J3Xu3JnNmzcH3l6yS5ecHLhPCWL+/PmcfPLJnHTSSYGXaUjqaAMzZsygT58+dOjQgebNm7NixQoA5s6dy4wZM3jnnXdYtWoVv/71rwG46qqruPnmm1m1ahVvvfUWrVq1irqNxo0b8+abbzJo0CAGDBjA0qVLWbVqFdnZ2YwfP56jjz6anj17Mnv2bACmTp3KwIEDOfzww3nsscd47LHHqqxzy5YttGnTJjKdkZHBli1bqt3+nXfeSV5eHj//+c/Zs2cPAPn5+bzwwgsALFmyhI0bN7J582Y++eQTTjjhBIYNG8Zpp53G8OHD+eabbyqt74033qBly5a0b98+6n1PJamelUceeYRLLrmk2nb+7W9/Iy8vj8svv5xNmzYBoQzNnTuX0tJStm3bxmuvvRapS2epnpNy06dPp3fv3jRt2hSAtWvXUlxcTM+ePenSpQtPPfVU1Pvx4IMPctttt9GmTRt+9atfMXr06KjLpJJ0yEp17z8jR47kww8/pHXr1uTm5vLQQw/xve99L9B6v/rqK/7+979HDhSlg3TICVTdpwC8/fbb5Ofn07dvX95///0qy0ydOrXKQb9HHnmEvLw8rrvuOoqLi6Pe91hSRxuYMmUKgwYNAmDQoEFMmTIFgFdffZVhw4Zx1FFHAdC8eXNKSkrYsmUL/fv3B0LBLK+vzZVXXhm5vXr1as455xxyc3N55plnIsEZPnx4ZJzaxIkTGTYsdFXXG2+8kRtvvLHKOkPfXFRmZlXKRo8ezZo1a1i6dCk7duzgj3/8IwCjRo2iuLiYgoICHn74YU477TQaNWpEWVkZK1as4Kc//SnvvvsuTZo04f7776/ymKXb0WxI7ax8+umnTJs2jVtuuaXKvBdffDFFRUW89957nHfeeQwdOhSACy64gAsvvJCzzjqLwYMH86Mf/YhGjRpFvY+pLpVzcuD9rLgfKCsrY/ny5cyePZt58+Zx7733snbt2lrvx7hx4xg7diybNm1i7NixkW/S0kWqZ6Wm95958+ZRUFDAp59+ysqVKxk5ciS7du2Kut6ysjIGDx7Mz372M9q1axf1vqeKVM9JxftZcZ/SuXNnNm7cyKpVq7jllluqHOn+9ttvmTVrFldccUWk7Kc//Snr169n5cqVtGrVil/+8pdR73sspf074vbt21mwYAGrV6/GzNi3bx9mxpgxY3D3KoGoLjQAjRo1Yv/+/ZHp3bt3V6pv0qRJ5Pa1117LjBkzyM/PZ9KkSSxcuBCAs88+m6KiIhYtWsS+ffuq/GjoQBkZGZWOHm7evLnar13LP8keeeSRDBs2jAceeACApk2bRl4w7k5mZiaZmZmUlpaSkZHBmWeeCcDll19eqaNdVlbGCy+8wPLly2ttX6pJ9ay8++67rFu3jqysLCD046OsrCzWrVvHcccdF5nvhhtu4Pbbb49M33nnndx5550A/Md//EfafctxoFTPScX7uWTJEqZPn15p+eOPP54mTZrQpEkTunfvzqpVq+jQoUON25w8eTIPPfQQAFdccQXDhw+vtY2pJB2yUtP7z8SJExk1ahRmRlZWFpmZmaxZs4aMjIxIm8rX27Nnz8j0iBEjaN++Pbfeemut7Usl6ZCT8vt54D6l4pHtCy+8kJtuuolt27Zx/PHHA6Ej+p07d6Zly5aR+SrevuGGGyoNl4mHtD+i/fzzzzNkyBA2btxIUVERmzZtIjMzkzfffJMLLriACRMmUFpaCsCOHTto2rQpGRkZzJgxA4A9e/ZQWlrKSSedxAcffMCePXvYuXMn8+fPr3GbJSUltGrVir179/LMM89UqhsyZAiDBw+OfEqszSWXXMLUqVPZs2cPGzZs4OOPP+aMM86oMt/WrVuB0ItvxowZkRfGV199xbfffgvAk08+Sffu3WnatCk/+MEPaNOmDR999BEQGv906qmnRtb36quv0rFjRzIyMqK2MZWkelb69evHZ599RlFREUVFRRx11FGsW7cO+C5DALNmzSI7OxsIjenevn07AO+99x7vvfceF1xwQdT2pLJUz0m5adOmcdFFF9G4ceNI2aWXXsobb7xBWVkZpaWlvPPOO5Gs1KR169YsWrQIgAULFqTVB7V0yEpN7z8//OEPI+38/PPP+eijj2jXrh0//vGPefnllykuLqa4uJiXX36ZH//4xwD89re/ZefOnZGzS6SLdMgJVL9P+eyzzyIfHJYsWcL+/fsrHfip7tv1iu9X06dPj/phIOaC/GIyGf4O9de8PXr08Llz51Yqe+ihh/zGG290d/fRo0d7dna25+fn+29+8xt3d1+7dq336tXLc3NzvXPnzr5+/Xp3d7/tttu8Q4cO3q9fP+/fv79PnDjR3b3KWRf+8pe/eNu2bb1Hjx4+cuRIHzp0aKRu69at3rhx40pn+Rg3bpyPGzeu2vbfd9993q5dO+/QoUOlX2D37dvXt2zZ4u7uvXr18pycHO/UqZNfddVVXlJS4u7ub731lmdlZfkpp5zi/fv39x07dkSWf/fdd71Lly6em5vrl156aaW6oUOH1tie+kIC/vI7HbJSUcWzjowaNcpPPfVUz8vL8549e/qHH37o7u7/93//59nZ2Z6dne1nnnmmv/vuu5UemxNPPNEPO+wwb9WqlV9//fU1P7iHSDkJiUdOqruf7u5jxozx7Oxs79Spk48dOzZSPmjQIP/BD37gjRo18hNPPNGffPJJd3d/4403vHPnzp6Xl+dnnHGGL1u2rOYHtw6UlZBEef/ZsmWLn3/++ZG6p59+OrL8+PHj/eSTT/aTTz7ZJ0yY4O7umzZtcsA7duzo+fn5np+fHzkzVn1STkISZZ/y8MMPR957zjzzTF+8eHGk7ptvvvHmzZv7V199VWmZq6++2nNycjw3N9cvvvhi//TTT6t/YOsoaFYsNG/yKyws9GXLlsW7GXX2/PPPM3PmTJ5++ul4NyWuzGy5uxfGYt3KSupQTqJTTkKUleiUFeUkCOUkJGhW4jpG28xOAZ6rUNQO+B1wLHAD8GW4/A53j/MZx2PvlltuYe7cufE/uXoCUlYqU1aqp5xUppzUTFmpTFmpnnJSmXJy8BLmiLaZHQZsAc4EhgFfu/sDQZdPlU+KElLbJ0VlRcopJxKUsiJBKCcSVNAj2on0Y8jewHp33xjvhkjCU1YkCOVEglJWJAjlRA5aInW0BwFTKkyPNLP3zGyCmTWLV6MkISkrEoRyIkEpKxKEciIHLSHOo21mRwCXAL8JF40D7gU8/P+/gOuqWW4EMAJC502seO5NgH9u2VllW7knHlN/DZcGF6us1EQZSk4NnRNJXsqKBKGcyKFKiDHaZnYpcLO7VzkBr5m1BV5091pPhFjd2Ke2o2ZXma/o/n51aao0kJrGPsUqKzVRhhJbouREEp+yIkEoJxJUso3RHkyFr2PMrFWFuv7A6gZvkSQqZUWCUE4kKGVFglBO5JDEfeiImR0FnA/8pELxGDMrIPSVTNEBdZKmlBUJQjmRoJQVCUI5kbqIe0fb3UuB4w4ouyZOzZEEpqxIEMqJBKWsSBDKidRF4KEjZna0mbU0M4tlg0REREREUkGtR7TDJ2f/LaFf0maEi/ea2XLgd+4+P8btExFJGPpxrIiIHIxoQ0ceAroAowgd/b4FmA4UAxPN7NfuPjW2TRQRERERST7ROtqDgQ7uvh3AzOYDb7p7lpm9B0wE1NEWERERETlAtDHau4GyCtNlQGMAd/8H0CZG7RIRERERSWrRjmj/FZhlZn8GDPhP4AWInEPyy9g2T0REREQkOUXraN9O6HKjowh1tOcCfwjXGTAkdk0TEREREUletXa03f1b4PfhvwPrPgU+jVG7UprOXJB49JxIXSlDUpHyICJQh0uwW0j3+myMiIiIiEiqOOSONnAE8Fp9NUREREREJJVEu2BNbWOwj6jntoiIiIiIpIxoP4acCCwH9lRTp0uxi4iIiIjUIFpH+2PgdnevMkTEzBoDpTFplYiIiIhIkovW0V4EdKT6sdj7wvVST/Qr9eTREM+V8pAa9DyKiKSvaKf3+0ktdXuBXvXeIhERERGRFBDtiHbMmVkRUELoCHmZuxeaWXPgOaAtUAT8u7sXx6uNkhiUFQlCOZGglBUJQjmRuqj19H5mdoqZ3Vxh+iUzW1Dh75R6akcvdy9w98Lw9Chgvru3B+aHp0VAWZFglBMJSlmRIJQTOSTRzqN9O/B1hemzgGfCf+8Tu2BdCkwO354MXBaj7UjyU1YkCOVEglJWJAjlRAKJ1tHuDkyvML3P3ce7+3jgDqBbPbTBgZfNbLmZjQiXtXT3rQDh/y3qYTuS/JQVCUI5kaCUFQlCOZFDFm2Mdgt331VhOnIBG3cvMbOW9dCGs939UzNrAbxiZmuCLhgO/AiAli1bsnDhwkr1v8wtq7JM+Tz/3LKzSl3uicfUW3lt26ipXTWV17aNNNPgWTnY8vrUENtIUXHZp8QzK3LI4pIVSToxy4ne31OfuXvNlWZbCAWsqJq6dsCb7t663hpjdjehoSo3AD3dfauZtQIWunut48ELCwt92bJllcpqO61WTXX1Vd5Q20hVZra8wli46urvpgGyEs/nJB2f94OVKDmprU7PY2JIpKxI4lJOJKhoWSkX7Yj2bOBe4Jpq6n4frj9kZtYE+F746HgT4ALgHmAWMBS4P/x/Zl22k8rS5UWqrEgQyokElWhZSZd9ebJJtJxI8onW0f4d8JaZvUtorPZnQCtCg/6bAV3ruP2WwHQzK2/Ls+7+kpktBf5qZtcD/wKuqON2JPkpKxKEciJBKSsShHIidRLtgjWfmVkh8AugL3A8sB2YA/y3u2+vy8bd/RMgv5ry7UDvuqxbUouyIkEoJxKUsiJBKCdSV1EvWOPuO4Dfhv9EDlm6fDWaiOO9RUREpOHV2tE2s2OAfHd/PTx9xwHLPKwrIYmIiIiIVBXtiPavgDLg9fD0HXx3Xu1M4HDg/8WmaSIiIiIiyStaR7s/0KfC9F53vwbAzDIIjdVWR1tE6lU6DKdJh/soIpLuol0ZsrW7b64w/Xj5jXB5RkxaJSIiIiKS5KJ1tDGzE8pvu/vt1ZWLiIiIiEhl0YaOLAaGAWOqqRsGvF3vLRKRqDTsIHUdynOrPIiIJKZoHe3fA6+ZWWvgBb67YM0A4Drg3Ng2T0REREQkOUXraK8gdLnRMcBIQkNN9gPvAH3cfWlsmyciIiIi5fQNVnKJ1tHeAjwN3ASsJ3TZ9WJ3L411w6Ru9EIUkVSn/ZyIJLpoP4a8kdD5spcAbwIDgaNi3SgRERERkWRXa0fb3We6+xWExmX/D/DvwGYzm2VmA83s8IZopIiIiIhIsok2dAQAd/+KUEf7f8wsE7gGGBsuOz52zRMREUkdGu4ikl6inke7IjM7EjgdOBNoCfwzFo0SEREREUl2gTraZtbNzB4HPgfuA/4BdHD3XnXZuJm1MbPXzOxDM3vfzP4zXH63mW0xs5Xhvwvrsh1JfspKMG1Hza7yl06UEwlKWZEglBOpq1qHjpjZ3YSGiTQHpgH93H1xPW6/DPilu68ws6OB5Wb2SrhurLs/UI/bEpL6a0tlRYJI6Zwk8es3ESVNVvS8x1XS5EQSU7Qx2l2BO4EZ7r67vjfu7luBreHbJWb2IXBifW9Hkp+yIkEoJxKUsiJBKCdSV9HOOtLH3afGopN9IDNrC5xG6GI4ACPN7D0zm2BmzWK9fUkeysrBS8chJcqJBKWsSBDKiRwKc/d4twEz+zdgEfAHd3/BzFoC2wAH7gVauft11Sw3AhgB0LJlyy5Tp06tVP/PLTurbCv3xGNqrauv8mTbRkM4mG336tVrubsXHlje0FnR8x4fQdubKDmprS6ez3uqS/d9itS/RMlJbZSHxFBTVg4U9452+FzcLwLz3P2/q6lvC7zo7jm1raewsNCXLVtWqay2cW011dVXebJtoyEczLbNrEqA45EVPe/xEbS9iZKT2uri+bynunTfp0j9S5Sc1EZ5SAzVZaU6gc6jHStmZsB44MOK4TWzVuFxUQD9gdXxaJ8kDmVFglBOKtMbcs2UlfRyqK8F5UTqKq4dbeBsQmc1+aeZrQyX3QEMNrMCQl/JFAE/iU/z0kcSvCErKxKEciJBKSsShHIidRLXjra7vwlYNVVzGrotktiUFQlCOZGglBUJQjmRuor3EW0RERE5BEnwTaRI2lNHW6LSzlwkteg1ndr0/Iocmli8dgJdgl1ERERERA6OjmiLiIikAR3pTm16fhOTOtpyyPSiFhERiQ29x6YGDR0REREREYkBHdEWSWO6Gp2IgF7vIrGijraIiIhIitKHqPjS0BERERERkRjQEW0REYnQ0S8RkfqjjraIiIhUSx+8ROpGHW0RqRd6QxYREalMHW0RETlkh/IBSx/KRBKbXqP1Rx1tqXd6gaY2Pb/p6WCfd+UktekDVmrQcxJ76miLSExpRy4iktq0n69Zwna0zawP8BBwGPCku98f5yZJglJWJChlJbElypu1cnLoEuU5bCjplpV0e37rQ0KeR9vMDgMeBfoCpwKDzezU+LZKEpGyIkEpKxKEciJBKSsSRKIe0T4DWOfunwCY2VTgUuCDuLZKEpGyksQa+OiIspKklJPUVtPzmwRHT5WVANL99x2J2tE+EdhUYXozcGac2iKJTVmRoJQVCUI5SXC1dcQauJOmrNRBfXbAD/bDWkPmxNw9JiuuCzO7Avixuw8PT18DnOHutxww3whgRHjyFOCjBm2oxNJJ7n5CtJmUlbQXKCcQLCvKSUrTPkWC0D5FggqUlUQ9or0ZaFNhOgP49MCZ3P1x4PGGapQkJGVFgoqaFeVE0D5FgtM+RaJKyB9DAkuB9maWaWZHAIOAWXFukyQmZUWCUlYkCOVEglJWJKqEPKLt7mVmNhKYR+iUORPc/f04N0sSkLIiQSkrEoRyIkEpKxJEQo7RFhERERFJdok6dEREREREJKmpoy0iIiIiEgPqaIuIiIiIxIA62iIiIiIiMaCOtoiIiIhIDKijLSIiIiISA+poi4iIiIjEgDraIiIiIiIx8P8BqwKnQGtZYwQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 8\n",
    "identifieer = 'ADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ADAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 8\n",
    "identifieer = 'ADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 32\n",
    "identifieer = 'ADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 128\n",
    "identifieer = 'ADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 512\n",
    "identifieer = 'ADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RADAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 8\n",
    "identifieer = 'RADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 32\n",
    "identifieer = 'RADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 128\n",
    "identifieer = 'RADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 512\n",
    "identifieer = 'RADAM'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gradient Decent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 8\n",
    "identifieer = '0'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 32\n",
    "identifieer = '0'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 128\n",
    "identifieer = '0'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5BdkE1y/9vNz6+LA92JZllHD99VOCdXkRwQGQOnnOTEgZaOzcXS+99Erhi6ACugboW99l0atGv9sIgoMTXxNUEuYAbeL6NyU4M7MZ+A9wPbA6rv9dwAaCysgfCM50XB72uxSYV25++xKc7dpAcI1H6Tz+H8FF3psJrkm5Lux3Svz84qbTn+DaiY0EZykmAweE/fKBRQQHYp4KX3dW8f0rlDGu3/jS8cqXg+AgzH/D+d8Qdjsu/P4bCCpbzwCHhf3mlC6X8HNWOOymcBpzgG7lyxSWYQfBzkfp69GwXwvgEYIdqk3hdx5S35nSSy+99Mr0l7mnSxN/kcwRHlV+i6Apy0iC5lAdvJKLdCX9mdllBGcxTvDgTm0iIiJSTp00hTKzsWb2hZktievWysxesOAhcC+EbT5LH5D0gJktN7P/WHD7RGkkMigr3ye43eg6guZG56hSkTx1nRN3H0vQ1O/45H0LqQsZtE6RFFJORJKjrq6xGE9wej7ezcBLHtyR5iW+vZBsAEH7uk4E9zV/pI7KKOlhPBmQFXe/3d2/5+4HuPtx7v5WfZcpw4ynjnPi7k/4t7dLloZjPBmwTpGUG49yIlJrdVKxcPdXCNrWxjub4CFGhH/Piev+uAfeBA60Sp46KplJWZEolBOJSlmRKJQTkeSoz7tCtfbg7h2Ef0sf4tOWsvcbXx12k8ZLWZEolBOJSlmRKJQTkRpKxwfkVfYgoEqvMDezKwlOQ/Ld73736Hbt2lU2mDQwOTk5rFy5ssLtJSuhrDRiyolEpaxIFMqJ1MRHH320zt3r8uGDDUJ9Viw+N7Msd18bnkL8Iuy+mrJPB80muFVnBe7+V+CvAPn5+b5gwYJUllfqSGFhITk5OTviOikrUoFyIlEpKxKFciI1YWaf1ncZ0lF9NoWaAQwL3w8Dpsd1HxredaEA2FR6KlIaLWVFolBOJCplRaJQTkRqqE7OWJjZkwQPUTrIzFYDvyF4avM/zWwEwcOUzg8HnwmcQfCkxG0ET8WWRuKiiy5izpw5AE2UFamKciJRKSsShXIikhwZ84A8nWLMLGb2jrvnp2LaykrmUE4kKmVFolBOJKpUZqUhq8+mUCIiIiIikiFUsRARERERkVpTxUJERERERGpNFQsREREREak1VSxERERERKTWVLEQEREREZFaU8UioqlTp2JmLFu2rL6LUiOjRo2iY8eOdOnSheeff77SYUaMGEFeXh49e/bkvPPOY8uWLQD84Q9/oFu3bvTs2ZN+/frx6affPmTyv//9L6eddhq5ubl069aNwsJCANydW2+9lc6dO5Obm8sDDzyQ8u+YbjI5K6WuvfZa9t9//wrdp0yZgplRekvFHTt2MGzYMHr06EFubi6jRo2KDbtx40bOO+88unbtSm5uLm+88UZyv1Cay+ScXHrppeTk5NCrVy969erFu+++W6b//Pnz2WuvvZgyZUqsW1XrlIceeoiOHTtiZqxbty5l3yudZXJWqtpmTJ8+nZ49e9KrVy/y8/OZN28eAO+++y7f//73OfLII+nZsydPPfVUnX2fdNcYc1JcXMygQYPo2bMnxx57LEuWLAFg1apV9O3bl9zcXI488kjuv//+2LQ2bNjAqaeeSqdOnTj11FMpLi6OzeO6666jY8eO9OzZk4ULF8bGmTBhAp06daJTp05MmDAh1t3Mjjaz98xsuZk9YGYWdm9lZi+Y2cfh35ZhdwuHW25m/zGzo+KmNSwc/mMzG5Ym8zjfzJaa2W4zi3ZrXXfPiNfRRx/tqXT++ed7nz59/De/+U1K57Nz586kTWvp0qXes2dP//rrr/2TTz7xDh06VDr9TZs2xd5ff/31PmrUKHd3nz17tm/dutXd3R9++GG/4IILYsOdfPLJPmvWLHd3LykpiQ03duxYv+SSS3zXrl3u7v7555/vUdmBBa6sVKs+suLuPn/+fP/JT37izZo1K9N98+bNfuKJJ/pxxx3n8+fPd3f3iRMn+oUXXuju7lu3bvXDDz/cV65c6e7uQ4cO9ccee8zd3bdv3+7FxcU1Lrdyklh95GTYsGE+efLkKsvTt29fHzBgQJlhqlqnLFy40FeuXOmHH364f/nll3tcdmUlsfrISlXbjJKSEt+9e7e7uy9evNi7dOni7u4ffvihf/TRR+7uXlRU5IceeugerTuqopwklk45ueGGG/z22293d/cPPvjAf/CDH7i7+5o1a/ydd95x92Db1KlTJ1+6dKm7u48cOTK2nzNq1Ci/8cYb3d39mWee8f79+/vu3bv9jTfe8GOPPdbd3devX+85OTm+fv1637Bhg+fk5PiGDRscWAC8DXwfMOBZYIC7A4wGbg7f3wzcE74/IxzOgALgrbB7K+CT8G/L8H3LsF99ziMX6ALMAfI9Qs51xiKCLVu28NprrzFmzBgmTZpUpt/o0aPp0aMHeXl53HzzzQAsX76cH/7wh+Tl5XHUUUexYsUK5syZw49+9KPYeNdccw3jx48HoH379vzud7+jT58+TJ48mccee4xjjjmGvLw8Bg8ezLZt2ygpKSEnJ4cdO3YAsHnzZtq3bx/7XJnp06czZMgQmjRpQk5ODh07duTtt9+uMFzz5s2BoJL51VdfEVZU6du3L/vttx8ABQUFrF69GoD333+fnTt3cuqppwKw//77x4Z75JFH+PWvf813vhNE65BDDqnBkm74Mj0ru3btYuTIkYwePbpCv9tuu40bb7yRpk2bxrqZGVu3bmXnzp189dVX7LvvvjRv3pzNmzfzyiuvMGLECAD23XdfDjzwwIhLueHL9JxU58EHH2Tw4MFl1g3VrVN69+5N+/btazSPTJLpWalqm7H//vvHtkVbt26Nve/cuTOdOnUCoE2bNhxyyCF8+eWXNV6umaax5uT999+nX79+AHTt2pXCwkI+//xzsrKyOOqo4ED9AQccQG5uLkVFRbF5DhsWHKwfNmwY06ZNi3UfOnQoZkZBQQEbN25k7dq1PP/885x66qm0atWKli1bcuqpp/Lcc88B7AM0d/c3PNgLfxw4Jyzy2UDpqY0J5bo/HtaX3gQONLMs4HTgBXff4O7FwAtA/7Bfvc3D3T9w9w+r/AEroYpFBNOmTaN///507tyZVq1axU6PPfvss0ybNo233nqLxYsXc+ONNwJw8cUX87Of/YzFixfz+uuvk5WVlXAeTZs2Zd68eQwZMoRzzz2X+fPns3jxYnJzcxkzZgwHHHAAp5xyCs888wwAkyZNYvDgweyzzz48+uijPProoxWmWVRURLt27WKfs7OzY/9Y5Q0fPpxDDz2UZcuWce2111boP2bMGAYMGADARx99xIEHHsi5555L7969GTlyJLt27QJgxYoVPPXUU+Tn5zNgwAA+/vjjhN89k2R6Vh566CHOOuusCuVctGgRq1atKrNRAjjvvPNo1qwZWVlZHHbYYdxwww20atWKTz75hIMPPpjhw4fTu3dvLr/8crZu3Zrwu2eKTM8JwK233krPnj25/vrr2b59e2z8qVOncvXVV5cZtrp1SmOX6VmpbpsxdepUunbtysCBAxk7dmyFcd9++22++eYbjjjiiITfMdM11pzk5eXxr3/9Cwjy8Omnn8YOgpYqLCxk0aJFHHfccQCxigdAVlYWX3zxRbVlqaaM+wDxM1sNtA3ft3b3tQDh39IjKW2BVZWMU133+pxHjaliEcGTTz7JkCFDABgyZAhPPvkkAC+++CLDhw+PHVlr1aoVJSUlFBUVMWjQICD4RyztX50LL7ww9n7JkiWceOKJ9OjRg4kTJ7J06VIALr/8csaNGwfAuHHjGD58OABXX311hQ01BGcgyis96lPeuHHjWLNmDbm5uRXarP79739nwYIFjBw5EoCdO3fy6quvcu+99zJ//nw++eST2FGN7du307RpUxYsWMAVV1zBZZddlvC7Z5JMzsqaNWuYPHlyhYrn7t27uf7667nvvvsqTOPtt99mr732Ys2aNaxcuZL77ruPTz75hJ07d7Jw4UL+53/+h0WLFtGsWTPuvvvuhN89U2RyTiBoM71s2TLmz5/Phg0buOeeewD4+c9/zj333MNee+1VZvjq1imNXaZnpbptxqBBg1i2bBnTpk3jtttuKzPe2rVrueSSSxg3blzsKHZj1lhzcvPNN1NcXEyvXr148MEH6d27N3vvvXdsvC1btjB48GD+9Kc/xVpnVKWqstRkXwqoOHC5UasYp6bd63seVdo78SCN2/r165k9ezZLlizBzNi1axdmxujRo3H3CuGqLIAAe++9N7t37459/vrrr8v0b9asWez9pZdeyrRp08jLy2P8+PHMmTMHgBNOOIHCwkLmzp3Lrl276N69e7Vlz87OZtWqbyunq1evpk2bNlUOv9dee3HhhRfy+9//PrYyePHFF7nrrruYO3cuTZo0iU23d+/edOjQAYBzzjmHN998kxEjRpCdnc3gwYOBYKNQOp3GINOzsmjRIpYvX07Hjh0B2LZtGx07duSdd95hyZIlnHLKKQB89tlnnHXWWcyYMYN//OMf9O/fn3322YdDDjmEE044gQULFnDSSSeRnZ0dO4J03nnnNZqKRabnBIgdDWzSpAnDhw/n3nvvBWDBggWxnZ9169Yxc+ZM9t5772rXKY1ZY8hKlG3GSSedxIoVK1i3bh0HHXQQmzdvZuDAgdx5550UFBRUW47GoDHnpHnz5rGKjLuTk5NDTk4OENw8ZPDgwVx88cWce+65sWm1bt2atWvXkpWVxdq1a2PNqqoqS3Z2duz7lXYPt3c7gOz4YgJrwvefm1mWu68Nmxp9UTo60K6ScVYDp5TrPifsXp/zqDFV8xOYMmUKQ4cO5dNPP6WwsJBVq1aRk5PDvHnzOO200xg7dizbtm0DgjsNNG/enOzs7Fibve3bt7Nt2zYOP/xw3n//fbZv386mTZt46aWXqpxnSUkJWVlZ7Nixg4kTJ5bpN3ToUC666KJIO+xnnXUWkyZNYvv27axcuZKPP/6YY489tsww7s7y5ctj759++mm6du0KBDuSV111FTNmzCjTHvqYY46huLg41q519uzZdOvWDQh2CGbPng3A3Llz6dy5c8JyZopMz8rAgQP57LPPKCwspLCwkP3224/ly5fTokUL1q1bF+teUFDAjBkzyM/P57DDDmP27Nm4O1u3buXNN9+ka9euHHroobRr144PPwyabr700kuxDGW6TM8JBEeTIVinTJs2LbZzsXLlylhOzjvvPB5++GHOOeecatcpjVljyEpV24zly5fHdoAXLlzIN998w/e+9z2++eYbBg0axNChQzn//PMjLMXM15hzsnHjRr755hsA/va3v3HSSSfRvHlz3J0RI0aQm5vLL37xiwrzLL2z04QJEzj77LNj3R9//HHcnTfffJMWLVqQlZXF6aefzqxZsyguLqa4uJhZs2Zx+umnQ1CxKDGzgvAuSkOB6eFsZgCld10aVq770PDOTQXAprAZ0/PAaWbWMry702nA82G/+pxHzUW5wrshvFJ1t4WTTz7Zn3322TLd7r//fr/66qvdPbijQG5urufl5fmvfvUrd3f/6KOPvG/fvt6jRw8/6qijfMWKFe4e3Imgc+fOPnDgQB80aJCPGzfO3b3C3U4efvhhb9++vZ988sl+zTXX+LBhw2L91q5d602bNi1zF4xHHnnEH3nkkUrLf+edd3qHDh28c+fOPnPmzFj3AQMGeFFRke/atcuPP/547969ux955JH+4x//OHaXqH79+vkhhxzieXl5npeX52eeeWZs/FmzZnmPHj28e/fuPmzYMN++fbu7uxcXF/sZZ5zh3bt394KCAn/33XdrtLxL0QDvzJHpWSmv/F2h4pdD6V2hSkpK/LzzzvNu3bp5bm6ujx49OjbcokWL/Oijj/YePXr42Wef7Rs2bKh0etVRTtIzJ3379o2tUy6++GIvKSmpMJ3yd46qap1y//33e9u2bX2vvfbyrKwsHzFiRPULuArKSnpmpaptxt133+3dunXzvLw8Lygo8FdffdXd3Z944gnfe++9Y9ulvLw8X7RoUY2XbVWUk4aVk9dff907duzoXbp08UGDBsW2I6+++qoD3qNHj1hOnnnmGXd3X7dunf/gBz/wjh07+g8l1996AAAgAElEQVR+8ANfv369u7vv3r3bf/rTn3qHDh28e/fuse2Yu/uYMWP8iCOO8COOOMLHjh3r7l56V6h8YAmwAngIsKAX3wNeAj4O/7YKuxvw53D494i70xJwGbA8fA2P616f8xhEcEZjO/B5WBGpNuelIzZ4+fn5Xnrv/Ew2ZcoUpk+fzhNPPFHfRUkpM3vH3aPdM7mGlJXMoZzUXmPICSgrydAYsqKc1F5jyAmkNisNWb1eY2FmXYD4K4U7AL8GDgSuAErvIXeLu8+s4+KlnWuvvZZnn32WmTMb36JQVmqmsWZFOamZxpoTUFZqqrFmRTmpmcaaE/lW2pyxMLO9gCLgOGA4sMXd7406fmM5EtBYVHckQFmRUsqJRKWsSBTKiUSlMxaVS6eLt/sBK9z90/ouiKQ9ZUWiUE4kKmVFolBORBJIp4rFEODJuM/XmNl/zGxsePW6SCllRaJQTiQqZUWiUE5EEkiL51iY2b7AWcCvwk6PAHcQPKDjDuA+givZy493JXAlBPcljr/PsGQmZUWiUE4kKmVFolBORKJJi2sszOxs4Gfuflol/doD/3b3ap+yoraLmaWqtovKisRTTiQqZUWiUE4kKl1jUbm0OGMBXETc6cXSJwmGHwcR3FtXBJQViUY5kaiUFYlCOWkA2t/8TKThCu8eGHn40mElmnqvWJjZfsCpwFVxnUebWS+CU4yF5fpJkjS0fyhlpX6kYkUdP3yyKScNR32vg5SVhkHrFJGGo94rFu6+jeDpgfHdLqmn4kgaU1YkCuVEolJWMlOyKyLKiUh0e1yxCC9kWubuHZJYHkljNT26WN9HI6VhqO+jkdJwaJ0iIpLeanO7WQPaJ6kcIiIiIiLSgFV7xsLMdlXXm6BtoYiIiIiINHKJmkJtILgv8/uV9GsCvJf0EomIiIiISIOTqGLxDnCQu68o38PMmhCctRAREdE1EBKJrquSqJSVhidRxeKXwI7Kerj7djPLSX6RRERERESkoam2YuHuSxP0/zS5xRERERERkYZoj+8KZYGTklkYERERERFpmGpzu9l9gZeTVRAREREREWm4Et1udmg1vfdNcllERERERKSBSnTx9jiCO0Ntr6Sf7gglIiIiIiJA4orFx8BN7l6hyZOZNQW2paRUIiIiIiLSoCS6xmIu0LWKfrvC/iIiIiIi0sglut3sVdX02wH0TXqJRERERESkwUnUFCrlzKwQKCE4A7LT3fPNrBXwFNAeKAQucPfi+iqjpAdlRaJQTiQqZUWiUE5Eokt0V6guwA/d/c/h5+coezeo/3H3D5NQjr7uvi7u883AS+5+t5ndHH6+KQnzkYZPWaml9jc/E2m4wrsHprgkKaWcSFTKikShnIhEkOgai5uALXGfjwcmhq+lBP9IqXA2MCF8PwE4J0XzkYZPWZEolBOJSlmRKJQTkUokagp1EvDzuM+73H0MgJkdACxMQhkcmGVmDvzF3f8KtHb3tQDuvtbMDknCfKThU1YkCuUkSRrB2S1lRaJQTkQiMnevuqfZZndvHvf5THd/uqr+e1QAszbuvib8p3wBuBaY4e4Hxg1T7O4tKxn3SuBKgNatWx89adKkMv3fK9oUqQw92rbY8y9QA6kuT5Tpx0873YaP17dv33fcPT++Wyqz0pjUNIfpNnw85SS1UvFbap0iWqdIVOmQlZqsUyRxxaIIOMHdCyvp1wGY5+5tklYYs9sJml5dAZwSHgXIAua4e5fqxs3Pz/cFCxaU6ZZuR9tSXZ4o04+fdroNH8/Mqv2HTXZWGpOa5jDdho+nnKRWKn5LrVNE6xSJKh2ysqfrlMYq0TUWzwB3VNHvt2H/PWZmzcImVZhZM+A0YAkwAxgWDjYMmF6b+UjDp6xIFMqJRKWsSBTKiUjNJLrG4tfA62a2CJgKfAZkEVyk1BIoqOX8WwNTzay0LP9w9+fMbD7wTzMbAfwXOL+W85GGT1mRKJQTiUpZkSiUkyRKt5YkknyJHpD3mZnlA78ABgAHAeuBmcAf3H19bWbu7p8AeZV0Xw/0q820JbMoKxKFciJRKSvJVZsmJelMORGpmYQPyHP3DcD/hi8REREREZEKEj0grwWQ5+6vhJ9vKTfOg3rSpIiIiIiIJDpjcQOwE3gl/HwLwbUWADnAPsBtqSmaiIiIiIg0FIkqFoOA/nGfd7j7JQBmlk1wrYUqFiIiIiIijVyiikUbd18d9/mvpW/cfXVYuRCRJMvUCyFFREQkcyV6jgVmdnDpe3e/qbLuIiIiIiLSuCWqWLwGDK+i33DgjeQWR0REREREGqJETaF+C7xsZm2Af/HtA/LOBS4DfpDa4jVuepCMiIiIiDQUic5YLCR4fP3RwGxgGfASkA/0d/f5qS2eiIiIiIg0BInOWBQBTwA/BVYALYFid9+W6oKJiIiIiEjDkahicTXwE+Bt4ANgPPAPQBULEZF6puaSIiKSTqptCuXu0939fILrKv4CXACsNrMZZjbYzPapi0KKiIiIiEh6S3TGAgB330hQsfiLmeUAlwB/DLsdlLriiYiISG3p2TgiUhciVSxKmVkT4BjgOKA18HoqCiWS7rSRFhERESkrUsXCzPoAQwmaQn1BeEG3u3+awrKJSESq6IiIiEh9q7ZiYWa3EzR7agVMBga6+2vJmrmZtQMeBw4FdgN/dff7w/leAXwZDnqLu89M1nyl4VFWJArlpHq62PtbyopEoZyI1EyiMxYFwK3ANHf/OgXz3wn80t0XmtkBwDtm9kLY74/ufm8K5ikNk7IiUSgnEpWyIlE0qpzo4IPUVrUVC3fvn8qZu/taYG34vsTMPgDapnKe0jApKxKFciJRKSsShXIiUjM1ung7lcysPdAbeAs4AbjGzIYCCwiOFhTXX+kknSgrEoVyIlEpKxXpuq2KlBORxMzd67sMmNn+wFzgLnf/l5m1BtYBDtwBZLn7ZZWMdyVwJUDr1q2PnjRpUpn+7xVtijT/Hm1bNJrhS4dNx+Hj9e3b9x13zy/fvT6zks7LribDp0MOazN8vLrOSbpJt98mnXJenrKSPr9NOuQwfvh4ysmeL7tUTD8dhq/pOqWxq/eKRfiQvX8Dz7v7Hyrp3x74t7t3r246+fn5vmDBgjLdatpWsDEMH3+EKd2Gj2dmFf5h6zsr6bzsajJ8OuSwNsPHq+ucpJt0+23SKeflKSvp89ukQw7jh4+nnKTXb5MOw9dknSIJnrydamZmwBjgg/h/VjPLihtsELCkrssm6UVZkSiUE4lKWZEolBORmqnvayxOILid7Xtm9m7Y7RbgIjPrRXCKsRC4qn6KJ2lEWZEolBOJSlmRKJQTkRqo14qFu88DrJJeuhe0lKGsSBTKiUSlrEgUyolIzdT3GQsRERGpId21SUTSkSoWIiIRpcOFhPHDi4iIpJN6vXhbREREREQygyoWIiIiIiJSa2oKJSIikmR1+YwOEZF0oTMWIiIiIiJSa6pYiIiIiIhIrakplIiIiEgG0p3mpK7pjIWIiIiIiNSazliIiIiINAA6AyHpTmcsRERERESk1nTGQkRERKQe6AyEZBqdsRARERERkVpTxUJERERERGpNFQsREREREam1tK1YmFl/M/vQzJab2c31XR5JX8qKRKWsSBTKiUSlrIiUlZYVCzPbC/gzMADoBlxkZt3qt1SSjpQViUpZkSiUE4lKWRGpKC0rFsCxwHJ3/8TdvwEmAWfXc5kkPSkrEpWyIlEoJxKVsiJSjrl7fZehAjM7D+jv7peHny8BjnP3a8oNdyVwZfixC/BhnRZUUulwdz840UDKSqMXKScQLSvKSUbTOkWi0DpFooqclcYkXZ9jYZV0q1ADcve/An9NfXEkjSkrElXCrCgngtYpEp3WKSLlpGtTqNVAu7jP2cCaeiqLpDdlRaJSViQK5USiUlZEyknXisV8oJOZ5ZjZvsAQYEY9l0nSk7IiUSkrEoVyIlEpKyLlpGVTKHffaWbXAM8DewFj3X1pPRdL0pCyIlEpKxKFciJRKSsiFaXlxdsiIiIiItKwpGtTKBERERERaUBUsRARERERkVpTxUJERERERGpNFQsREREREak1VSxERERERKTWVLEQEREREZFaU8VCRERERERqTRULERERERGpNVUsRERERESk1lSxEBERERGRWquTioWZjTWzL8xsSVy3Vmb2gpl9HP5tGXY3M3vAzJab2X/M7Ki6KKOkB2VFolBOJCplRaJQTkSSo67OWIwH+pfrdjPwkrt3Al4KPwMMADqFryuBR+qojJIexqOsSGLjUU4kmvEoK5LYeJQTkVqrk4qFu78CbCjX+WxgQvh+AnBOXPfHPfAmcKCZZdVFOaX+KSsShXIiUSkrEoVyIpIce9fjvFu7+1oAd19rZoeE3dsCq+KGWx12W1t+AmZ2JcHRAr773e8e3a5du9SWWOpETk4OK1eu3BXXSVmRCpQTiUpZkSiUE6mJjz76aJ27H1zf5Ug39VmxqIpV0s0rG9Dd/wr8FSA/P98XLFiQynJJHSksLCQnJ2dHhEGVlUZMOZGolBWJQjmRmjCzT+u7DOmoPu8K9XnpqcPw7xdh99VAfJU+G1hTx2WT9KKsSBTKiUSlrEgUyolIDdVnxWIGMCx8PwyYHtd9aHjXhQJgU+mpSGm0lBWJQjmRqJQViUI5EamhOmkKZWZPAqcAB5nZauA3wN3AP81sBPBf4Pxw8JnAGcByYBswvC7KKOnhoosuYs6cOQBNlBWpinIiUSkrEoVyIpIc5l5ps8AGR20XM4uZvePu+amYtrKSOZQTiUpZkSiUE4kqlVlpyPTkbRERERERqTVVLEREREREpNZUsRARERERkVpTxUJERERERGpNFQsREREREak1VSxERERERKTWVLGoxtSpUzEzli1bVt9FqZFRo0bRsWNHunTpwvPPP1/pMCNGjCAvL4+ePXty3nnnsWXLFgD+8Ic/0K1bN3r27Em/fv349NNvn1jfv39/DjzwQH70ox+Vmdall15KTk4OvXr1olevXrz77rup+3JpKJNzUuraa69l//33r9B9ypQpmBmlt1B84YUXOProo+nRowdHH300s2fPTknZG6pMzkpV64Hp06fTs2dPevXqRX5+PvPmzYuNc+ONN3LkkUeSm5vLddddR+ntz0855RS6dOkSm9YXX3xR6TwzWSZnxd259dZb6dy5M7m5uTzwwANA9VmZMGECnTp1olOnTkyYMCHW/dZbb6Vdu3aVrp8ag0zOyYknnhhbB7Rp04ZzzjkHCPJz3XXX0bFjR3r27MnChQsBePnll2PD9+rVi6ZNmzJt2jQAXnrpJY466ih69epFnz59WL58ed180cbI3TPidfTRR3uynX/++d6nTx//zW9+k/Rpx9u5c2fSprV06VLv2bOnf/311/7JJ594hw4dKp3+pk2bYu+vv/56HzVqlLu7z54927du3eru7g8//LBfcMEFseFefPFFnzFjhg8cOLDMtIYNG+aTJ09O2ndwdwcWeAPJSibnxN19/vz5/pOf/MSbNWtWpvvmzZv9xBNP9OOOO87nz5/v7u4LFy70oqIid3d/7733vE2bNkkrc2UaUk7cMzsrVa0HSkpKfPfu3e7uvnjxYu/SpYu7u7/22mt+/PHH+86dO33nzp1eUFDgL7/8sru7n3zyybFMJYuyUrn6yMrYsWP9kksu8V27drm7++eff+7uVWdl/fr1npOT4+vXr/cNGzZ4Tk6Ob9iwwd3d33jjDV+zZk2F9dOeUk4qV1/bn1LnnnuuT5gwwd3dn3nmGe/fv7/v3r3b33jjDT/22GMrDL9+/Xpv2bJlbH+mU6dO/v7777u7+5///GcfNmxYrb9HKrPSkF86Y1GFLVu28NprrzFmzBgmTZpUpt/o0aPp0aMHeXl53HzzzQAsX76cH/7wh+Tl5XHUUUexYsUK5syZU+bo/jXXXMP48eMBaN++Pb/73e/o06cPkydP5rHHHuOYY44hLy+PwYMHs23bNkpKSsjJyWHHjh0AbN68mfbt28c+V2b69OkMGTKEJk2akJOTQ8eOHXn77bcrDNe8eXMgqFh+9dVXmBkAffv2Zb/99gOgoKCA1atXx8bp168fBxxwQE0XZUbL9Jzs2rWLkSNHMnr06Ar9brvtNm688UaaNm0a69a7d2/atGkDwJFHHsnXX3/N9u3bIy7NzJbpWanK/vvvH1u/bN26NfbezPj666/55ptv2L59Ozt27KB169aRp5vJMj0rjzzyCL/+9a/5zneCXZBDDjkEqDorzz//PKeeeiqtWrWiZcuWnHrqqTz33HNAsJ3Kysqq8TLOBJmek1IlJSXMnj07dsZi+vTpDB06FDOjoKCAjRs3snbt2jLjTJkyhQEDBsT2Z8yMzZs3A7Bp06bYdkqSTxWLKkybNo3+/fvTuXNnWrVqFTvV9uyzzzJt2jTeeustFi9ezI033gjAxRdfzM9+9jMWL17M66+/HmlF17RpU+bNm8eQIUM499xzmT9/PosXLyY3N5cxY8ZwwAEHcMopp/DMM88AMGnSJAYPHsw+++zDo48+yqOPPlphmkVFRbRr1y72OTs7m6KiokrnP3z4cA499FCWLVvGtddeW6H/mDFjGDBgQOKFRXA6umfPnlx//fWNakcy03Py0EMPcdZZZ1Uo56JFi1i1alWFZnHx/u///o/evXvTpEmThN+xMcj0rEDV64GpU6fStWtXBg4cyNixYwH4/ve/T9++fcnKyiIrK4vTTz+d3Nzc2DjDhw+nV69e3HHHHQQHBxuPTM/KihUreOqpp8jPz2fAgAF8/PHHsX6VZaUmGWxMMj0npaZOnUq/fv1iB0SjjD9p0iQuuuii2Oe//e1vnHHGGWRnZ/PEE0/EKluSfKpYVOHJJ59kyJAhAAwZMoQnn3wSgBdffJHhw4fHasGtWrWipKSEoqIiBg0aBAT/iKX9q3PhhRfG3i9ZsoQTTzyRHj16MHHiRJYuXQrA5Zdfzrhx4wAYN24cw4cPB+Dqq6/m6quvrjDNyjbApUd9yhs3bhxr1qwhNzeXp556qky/v//97yxYsICRI0cm/B6jRo1i2bJlzJ8/nw0bNnDPPfckHCdTZHJO1qxZw+TJkytUOnfv3s3111/PfffdV2WZly5dyk033cRf/vKXhN+vscjkrED164FBgwaxbNkypk2bxm233QYER08/+OADVq9eTVFREbNnz+aVV14BYOLEibz33nu8+uqrvPrqqzzxxBMJv3smyfSsbN++naZNm7JgwQKuuOIKLrvssli/yrJSk+1aY5LpOYn/nvGVhETjr127lvfee4/TTz891u2Pf/wjM2fOZPXq1QwfPpxf/OIXVc5Pamfv+i5AOlq/fj2zZ89myZIlmBm7du3CzBg9ejTuXuEfoKqjaXvvvTe7d++Off7666/L9G/WrFns/aWXXsq0adPIy8tj/PjxzJkzB4ATTjiBwsJC5s6dy65du+jevXu1Zc/OzmbVqlWxz6tXr672lN9ee+3FhRdeyO9///vYyuDFF1/krrvuYu7cuZGONpce9WjSpAnDhw/n3nvvTThOJsj0nCxatIjly5fTsWNHALZt20bHjh155513WLJkCaeccgoAn332GWeddRYzZswgPz+f1atXM2jQIB5//HGOOOKIasvRWGR6ViDaeuCkk05ixYoVrFu3jqlTp1JQUBC76HbAgAG8+eabnHTSSbRt2xaAAw44gB//+Me8/fbbDB06tNpyZorGkJXs7GwGDx4MBBWJ0m1PvPisZGdnx8pUOt3S9U9j1RhyUvo93377baZOnRp5/H/+858MGjSIffbZB4Avv/ySxYsXc9xxxwFBZal///7VllH2nM5YVGLKlCkMHTqUTz/9lMLCQlatWkVOTg7z5s3jtNNOY+zYsWzbtg2ADRs20Lx5c7Kzs2N3H9i+fTvbtm3j8MMP5/3332f79u1s2rSJl156qcp5lpSUkJWVxY4dO5g4cWKZfkOHDuWiiy6qdOVb3llnncWkSZPYvn07K1eu5OOPP+bYY48tM4y7x+6I4O48/fTTdO3aFQh2Jq+66ipmzJgRa/eaSGnbRndn2rRpCVcqmSLTczJw4EA+++wzCgsLKSwsZL/99mP58uW0aNGCdevWxboXFBTEKhUbN25k4MCBjBo1ihNOOKGmizRjZXpWoOr1wPLly2M7NQsXLuSbb77he9/7Hocddhhz585l586d7Nixg7lz55Kbm8vOnTtZt24dADt27ODf//53o1mnQOPIyjnnnBO7Y9zcuXPp3LkzUHVWTj/9dGbNmkVxcTHFxcXMmjWrzNHoxqgx5ARg8uTJ/OhHPypzLd9ZZ53F448/jrvz5ptv0qJFizLNusqf4WjZsiWbNm3io48+AoK7F8Y3u5Qkq++rx5P1SubdFk4++WR/9tlny3S7//77/eqrr3Z391GjRnlubq7n5eX5r371K3d3/+ijj7xv377eo0cPP+qoo3zFihXu7j5y5Ejv3LmzDxw40AcNGuTjxo1zd/fDDz/cv/zyy9j0H374YW/fvr2ffPLJfs0115S5Y8HatWu9adOmXlxcHOv2yCOP+COPPFJp+e+8807v0KGDd+7c2WfOnBnrPmDAAC8qKvJdu3b58ccf7927d/cjjzzSf/zjH8fuEtWvXz8/5JBDPC8vz/Py8vzMM8+Mjd+nTx8/6KCDvGnTpt62bVt/7rnn3N29b9++sWldfPHFXlJSUqPlXRkawJ05Mj0n5VV115X4O/jccccdvt9++8Xyk5eXF7vjSyo0hJy4N46sVLUeuPvuu71bt26el5fnBQUF/uqrr7p7cJeZK6+80rt27eq5ubl+/fXXu7v7li1b/KijjvIePXp4t27d/LrrrkvKHWmUlfTJSnFxsZ9xxhnevXt3Lygo8Hfffdfdq86Ku/uYMWP8iCOO8COOOMLHjh0b6z5y5Ehv27atm5m3bdu21ndHUk7SJydVfc/du3f7T3/6U+/QoYN37969zB3kVq5c6W3atIndcazUv/71L+/evbv37NnTTz755Nh3r41UZqUhvyxYNvXDzLoA8Y37OwC/Bg4ErgC+DLvf4u4zq5tWfn6+l95LP9NMmTKF6dOnN6p2xmb2jrvnx31WVhJQTpSTqJQVZSWqxpYV5WTPNLacQMWsSKBer7Fw9w+BXgBmthdQBEwFhgN/dPfG0Vi/Gtdeey3PPvssM2dWu77KeMpK9ZSTgHKSmLISUFYSU1aUkyiUE4mXThdv9wNWuPunutvDtx588MH6LkI6UlbKUU4qpZxUQlmplLJSCWWlAuWkEsqJxEuni7eHAE/Gfb7GzP5jZmPNrGV9FUrSkrIiUSgnEpWyIlEoJyIJpMUZCzPbFzgL+FXY6RHgDsDDv/cBl1Uy3pXAlQCtW7cuczs6Sb33ijZV279H2xZJn6eyIlEoJxKVsiJRKCci0dTrxduxQpidDfzM3U+rpF974N/uXu39BjP5oqh01f7mZ6rtX3j3wD2edlUXRSkrDY9yIulAWZEolBOJShdvVy4tzlgAFxF3etHMstx9bfhxELCkXkol6UhZkSiUkwYolZXQaigrEoVyIhJBvVcszGw/4FTgqrjOo82sF8EpxsJy/aSRUlYkCuVEolJWGqa6roAqJ5mvukyl6IBGxqr3ioW7bwO+V67bJfVUHEljyopEoZxIVMqKRKGciERX7xULERERkWSrp6Z1kkaUgbpX7e1mzWx/M/uTmf3bzPqZWScze8fMis1ssm6vJiIiIiIikPg5Fg8CBwHrgWkEFy/9FDgTOBj4fyktnYiIiIiINAiJmkINADoQVEAuAR4rvQuCmQ0DXk1t8URERKSx0EW0EoWaOKWvRBWLpuFFS5jZ5rhbqxE+0l5NoUQasWTuBGhDIVFp51NEJD0lagr1mZm1Ct+XWVubWTtgY0pKJSIiIiIiDUqiMxa/Ab4L4O6vlet3IjAhFYUSEZHMobNRIiKNQ7UVC3d/qpp+/0h+cSQdJHsnIJOaLWTSdxERERFJpkRNoapkgZOSWRgREREREWmY9rhiAewLvJysgoiIiIiISMNVbVMoMxtaTe99k1wWERERERFpoBJdvD0OeAfYXkk/S35xRERERESkIUpUsfgYuMndKzR5MrOmwLaUlEpERERERBqURNdYzAW6VtFvV9hfREREREQauUS3m72qmn47gL5JL5GIiIiIiDQ4iZpCpZyZFQIlBGdAdrp7fvi076eA9kAhcIG7F9dXGSU9KCsShXIiUSkrEoVyIhJdortCdQF+6O5/Dj8/R9m7Qf2Pu3+YhHL0dfd1cZ9vBl5y97vN7Obw801JmE+jliFPv1VW6kAGZEU5kaiUFYlCORGJINE1FjcBW+I+Hw9MDF9LCf6RUuFsYEL4fgJwTormIw2fsiJRKCcSlbIiUSgnIpVIVLE4CZga93mXu49x9zHALUCfJJTBgVlm9o6ZXRl2a+3uawHCv4ckYT7S8CkrEoVyIlEpKxKFciISkbl71T3NNrt787jPZ7r701X136MCmLVx9zVmdgjwAnAtMMPdD4wbptjdW1Yy7pXAlQCtW7c+etKkSWX6v1e0qdp592jbokbDNXTJXh7JGK6qZdu3b9933D0/vlu6ZyVTcgLJXR6p/D+s65zInmmM6xTZM1qnSBTpuk6RxBWLIuAEdy+spF8HYJ67t0laYcxuJ2h6dQVwiruvNbMsYI67d6lu3Pz8fF+wYEGZblHbiWdAe/JIkr08kjFcVcvWzKr9h03HrGRKTiC5yyOV/4d1nRPZM41xnSJ7RusUiaIhrFMaq0RNoZ4B7qii32/D/nvMzJqZ2QGl74HTgCXADGBYONgwYHpt5iMNn7IiUSgnEpWyIlEoJyI1k+h2s78GXjezRQTXWnwGZBFcpNQSKKjl/FsDU82stCz/cPfnzGw+8E8zGwH8Fzi/lvORhk9ZqUZjOesWgXJShxp47pQViToXCwMAACAASURBVEI5qUMNfJ0iJH5A3mdmlg/8AhgAHASsB2YCf3D39bWZubt/AuRV0n090K8205bMoqxIFMqJRKWs1K2GusOonIjUTMIH5Ln7BuB/w5eIiIiIiEgFiR6Q1wLIc/dXws+3lBvnQT1pMrV0UbGIiIiINASJzljcAOwEXgk/38K3z7XIAfYBbktN0UREREREpKFIVLEYBPSP+7zD3S8BMLNsgmstVLEQEREREWnkEt1uto27r477/NfSN2H37JSUSkREREREGpSEF2+b2cHu/iWAu98U3z2VBRMRkeRrqHfnERGR9JeoYvEaMBwYXUm/4cAbSS9RGouyQdZGW6JSVkRERCSTJKpY/BZ42czaAP/i2wfknQtcBvwgtcUTEREREZGGINE1FgsJHl9/NDAbWAa8BOQD/d19fmqLJyIiIiIiDUGiMxZFwBPAT4EVQEug2N23pbpgIiIS0HNqRESkIUh0xuJqgudVvA3MAwYD+6W6UCIiIiIi0rBUe8bC3acD083sQOBC4BJgtJnNAiYAM9x9R+qLKSLJoAvGRSQqnSkTkZpKeLtZAHffCPwF+IuZ5RBUMP4YdjsodcUTaXi08y4iIiKNUaSKRSkzawIcAxwHtAZeT0WhRESkfulotYhEoYNpEi9SxcLM+gBDgQuALwgv6Hb3T1NYNhEREYlIO3giUt+qvXjbzG43sxXA02Gnge7e2d3vSEalwszamdnLZvaBmS01s/8vbr5FZvZu+DqjtvOShk1ZkSiUE4lKWZEolBORmkl0xqIAuBWY5u5fp2D+O4FfuvtCMzsAeMfMXgj7/dHd703BPKVhUlYkCuVEolJWJArlRKQGEt0Vqn8qZ+7ua4G14fsSM/sAaJvKeUrDpKxIFMqJRKWsSBTKiUjNmLvXdxkAMLP2wCtAd+AXwKXAZmABwdGC4krGuRK4EqB169ZHT5o0qUz/94o2VTvPHm1bJH24+phnouHqY541LVt5ffv2fcfd8yvrl65ZSdXyiyKdf9tULo+6zklUyfxtE00vmdOKn57WKfWflVT9tsmY3v/f3r3HSV3XfR9/fRSFJBVJRWBJlhRZYXcRNuDCE1wWN6ipgCZEoIAiJXZn3hrJlcd8oOhdl1piGgczAsNbwALkKhAUJGFR1iCVg3ImE0FcIpDD5/5jZ8c9z2+ZmZ3fzLyfj8c+mN/5MzPv+THf+f4OmZS7isKak0QLa+4yZZ+SzULRsDCzLwNLgIfc/SUzawHsAhx4EGjp7iPqWkdRUZEXFxdXGhf0RLZEzpeKbcaaLxXbrG9tVZlZjR/YMGclWa9fEGF+b5P5ejR0ToJK9Em0ibxCU5jf20zapwSVivc2EevLpNxVFNacJFpYc5cJ+5RsV6/LzSaDmZ0A/D9gmru/BODuH1WY/izwpxSVJyGirEgQyokEpazELxuuRKWcJEY2ZEVS3LAwMwMmAe+6+88rjG8ZOa4RoD+wJhX1SXhkc1a0Mw4u3XKi9zZ10i0rkhrKiUj9pLrH4kLK7uL9NzNbHRl3NzDYzDpT1sW4CbglNeVJiCgrEoRyIkEpKxKEciJSDyltWLj7UsBqmDSvoWuRcFNWJIhszol6P+onm7MiwSknIvWT6h4LEZG0oS/vIpIK2vdIuqjzztsiIiIiIiJBqMdCREQki+jXbxFJFjUsREREQkwNARFJF2pYiIiIiEglatDKsdA5FiIiIiIiEjf1WIiIiCSYfu2VVFDuJNXUYyEiIiIiInFTj4WIiIhICqiHQTKNeixERERERCRualiIiIiIiEjc1LAQEREREZG4qWEhIiIiIiJxU8NCRERERETiFtqGhZn1NbP3zWyDmY1NdT0SXsqKBKWsSBDKiQSlrIhUFsqGhZkdD/wK6AecDww2s/NTW5WEkbIiQSkrEoRyIkEpKyLVhbJhAXQDNrj7B+7+OTADuDrFNUk4KSsSlLIiQSgnEpSyIlJFWBsWrYGtFYa3RcaJVKWsSFDKigShnEhQyopIFebuqa6hGjO7Dvhf7n5TZHgo0M3db6sy3yhgVGTwPOD9Bi1Ukulsdz8j1kzKStYLlBMIlhXlJKNpnyJBaJ8iQQXOSjZplOoCarENaFNhOAfYUXUmd38GeKahipJQUlYkqJhZUU4E7VMkOO1TRKoI66FQK4FzzSzXzE4EBgEvp7gmCSdlRYJSViQI5USCUlZEqghlj4W7HzazMcAC4HhgsruvTXFZEkLKigSlrEgQyokEpayIVBfKcyxERERERCS9hPVQKBERERERSSNqWIiIiIiISNzUsBARERERkbipYSEiIiIiInFTw0JEREREROKmhoWIiIiIiMRNDQsREREREYmbGhYiIiIiIhI3NSxERERERCRualiIiIiIiEjcGqRhYWaTzeyfZramwrjmZvZnM1sf+fe0yHgzsyfMbIOZvWNmXRqiRgkHZUWCUE4kKGVFglBORBKjoXospgJ9q4wbCyx093OBhZFhgH7AuZG/UcDEBqpRwmEqyorENhXlRIKZirIisU1FORGJW4M0LNz9NWB3ldFXA89FHj8HXFNh/G+9zF+BZmbWsiHqlNRTViQI5USCUlYkCOVEJDFSeY5FC3ffCRD598zI+NbA1grzbYuMk+ylrEgQyokEpaxIEMqJSD01SnUBNbAaxnmNM5qNoqwbki996Utd27Rpk8y6pIHk5uby4YcfHgkwq7KSxZQTCUpZkSCUE6mPdevW7XL3M1JdR9iksmHxkZm1dPedkS7Ef0bGbwMqfvJygB01rcDdnwGeASgqKvLi4uJk1isNZNOmTeTm5h6qMEpZkWqUEwlKWZEglBOpDzPbnOoawiiVh0K9DNwQeXwDMKfC+GGRqy70APaWd0VK1lJWJAjlRIJSViQI5USknhqkx8LMpgO9gNPNbBtwL/Aw8AczGwlsAa6LzD4PuBzYAOwHhjdEjRIOgwcPZvHixQCNlRWpjXIiQSkrEoRyIpIY5l7jYYFpR12MmcXMVrl7UTLWraxkDuVEglJWJAjlRIJKZlbSme68LSIiIiIicVPDQkRERERE4qaGhYiIiIiIxE0NCxERERERiZsaFiIiIiIiEjc1LEREREREJG5qWFQxa9YszIz33nsv1aXUy/jx4znnnHM477zzWLBgQY3zjBw5ksLCQgoKCrj22mvZt28fAK+99hpdunShUaNGvPjii5WWOf744+ncuTOdO3fmqquuSvrzSCfZmJUtW7bQu3dvLrjgAgoKCpg3bx4A06ZNi+akc+fOHHfccaxevRqAcePG0aZNG7785S83zBMMmUzOyY033khubm70fS9/z6dNm0ZBQQEFBQX07NmTkpISAA4cOEC3bt0oLCykY8eO3HvvvdF11Za5bJLJWXF3xo0bR/v27cnLy+OJJ54Aji0rF198cTRzrVq14pprrkn+kwyRTM5Jbe+tu/ODH/yAc845h4KCAt56661Ky3322We0bt2aMWPGAFBaWlrp/6TTTz+dH/7wh8l9glLG3TPir2vXrp4I1113nV900UV+7733JmR9tTl8+HDC1rV27VovKCjwAwcO+AcffODt2rWrcf179+6NPr799tt9/Pjx7u7+4YcfeklJiQ8dOtRnzpxZaZmmTZsmrM76AIpdWXH3cGXl5ptv9qeeeiq6rrPPPrvasu+8847n5uZGh5cvX+47duxISpaUky+kIic33HBDtX2Gu/uyZct89+7d7u4+b94879atm7u7Hz161EtLS93d/fPPP/du3br58uXL3b32zCWKsvKFVGRl8uTJPnToUD9y5Ii7u3/00UfufmxZqWjAgAH+3HPPJez5KCdfSEVOKqr43s6dO9f79u3rR48e9eXLl0dzUu4HP/iBDx482G+99dYa19WlSxdfsmRJYp5MRDKzks5/6rGoYN++fSxbtoxJkyYxY8aMStMmTJhAfn4+hYWFjB07FoANGzbwjW98g8LCQrp06cLGjRtZvHgxV155ZXS5MWPGMHXqVADatm3LAw88wEUXXcTMmTN59tln+frXv05hYSEDBw5k//79lJaWkpuby6FDh4CyVnjbtm2jwzWZM2cOgwYNonHjxuTm5nLOOeewYsWKavOdcsopQFlj8t///jdmFq2roKCA445THILK1qyYGZ999hkAe/fupVWrVtWWnT59OoMHD44O9+jRg5YtW8Z8TTNRpuekNj179uS0004Dyt7/bdu2AWX5Ke+5OnToEIcOHYpmq7bMZYtMz8rEiRO55557ov/PnHnmmcCxZaVcaWkpixYtyqoei0zPSbmq7+2cOXMYNmwYZkaPHj349NNP2blzJwCrVq3io48+ok+fPjWua/369fzzn//k4osvjvHqSiLom2QFs2fPpm/fvrRv357mzZtHu9rmz5/P7NmzefPNNykpKeGuu+4CYMiQIdx6662UlJTwxhtvBPry1KRJE5YuXcqgQYMYMGAAK1eupKSkhLy8PCZNmsTJJ59Mr169mDt3LgAzZsxg4MCBnHDCCTz99NM8/fTT1da5fft22rRpEx3Oyclh+/btNW5/+PDhnHXWWbz33nvcdtttMes9cOAARUVF9OjRg9mzZ8ecP1tka1buu+8+fve735GTk8Pll1/Ok08+WW25F154oVLDIptlQ07GjRtHQUEBt99+OwcPHqw2fdKkSfTr1y86fOTIETp37syZZ57JN7/5Tbp37x6dVt/9UybJ9Kxs3LiRF154gaKiIvr168f69eurzVOfrEDZIUGXXXZZtFGaDTI9J+Wqvre1LX/06FHuuOMOHn300VrXNX36dK6//vqs+7EiVdSwqGD69OkMGjQIgEGDBjF9+nQA/vKXvzB8+HBOOukkAJo3b05paSnbt2+nf//+QNkHsXx6Xa6//vro4zVr1nDxxReTn5/PtGnTWLt2LQA33XQTU6ZMAWDKlCkMHz4cgNGjRzN69Ohq6yzrkaustg/QlClT2LFjB3l5ebzwwgsx692yZQvFxcX8/ve/54c//CEbN26MuUw2yNasTJ8+nRtvvJFt27Yxb948hg4dytGjR6PLvPnmm5x00kl06tQp5vPLBpmek/Hjx/Pee++xcuVKdu/ezSOPPFJp+quvvsqkSZMqjT/++ONZvXo127ZtY8WKFaxZsyY6rb77p0yS6Vk5ePAgTZo0obi4mJtvvpkRI0ZUml7frED13tFskOk5qfg8K763tS3/1FNPcfnll1dqdFQ1Y8aMrMtJKjVKdQFh8cknn7Bo0SLWrFmDmXHkyBHMjAkTJuDu1T4ANYUcoFGjRpW+aB04cKDS9KZNm0Yf33jjjcyePZvCwkKmTp3K4sWLAbjwwgvZtGkTS5Ys4ciRIzG/pOXk5LB169bo8LZt22o8RKXc8ccfz/XXX8+jjz4a3RnUpnw97dq1o1evXrz99tt87Wtfq3OZTJfNWZk0aRKvvPIKAP/xH//BgQMH2LVrV/SwBu3Av5ANOSn/9bNx48YMHz6cxx57LDrtnXfe4aabbmL+/Pl85StfqbZss2bN6NWrF6+88kqleuqzf8oU2ZCVnJwcBg4cCED//v0rvbfHkpVPPvmEFStWMGvWrDrryyTZkJPy51n1va1t+eXLl/P666/z1FNPsW/fPj7//HO+/OUv8/DDDwNQUlLC4cOH6dq1a531SeKoxyLixRdfZNiwYWzevJlNmzaxdetWcnNzWbp0KX369GHy5Mns378fgN27d3PKKaeQk5MTPTzo4MGD7N+/n7PPPpu///3vHDx4kL1797Jw4cJat1laWkrLli05dOgQ06ZNqzRt2LBhDB48ONB/rFdddRUzZszg4MGDfPjhh6xfv55u3bpVmsfd2bBhQ/TxH//4Rzp06FDnevfs2RM9tGHXrl0sW7aM888/P2Y9mS6bs/LVr341Wue7777LgQMHOOOMMwA4evQoM2fOjP6alu0yPSdA9Bhnd2f27NnRLxdbtmxhwIABPP/887Rv3z46/8cff8ynn34KwL///W/+8pe/0KFDh2PaP2WSbMjKNddcw6JFiwBYsmRJNBf1zUq5mTNncuWVV9KkSZOYNWaKbMgJ1PzeXnXVVfz2t7/F3fnrX//KqaeeSsuWLZk2bRpbtmxh06ZNPPbYYwwbNizaqIDs7NVKuVSfPZ6ov3ivtnDppZf6/PnzK417/PHHffTo0e7uPn78eM/Ly/PCwkL/yU9+4u7u69at8969e3t+fr536dLFN27c6O7ud955p7dv396vuOIK79+/v0+ZMsXd3c8++2z/+OOPo+t/6qmnvG3btn7ppZf6mDFj/IYbbohO27lzpzdp0sT37NkTHTdx4kSfOHFijfX/7Gc/83bt2nn79u193rx50fH9+vXz7du3+5EjR7xnz57eqVMn79ixo3/nO9+JXoVlxYoV3rp1az/ppJO8efPmfv7557t72dU6OnXq5AUFBd6pUyf/zW9+cywv7TEhxFfmyOasrF271nv27OkFBQVeWFjoCxYsiC7/6quvevfu3att78477/TWrVu7mXnr1q0TeiUT5SR1OXF37927dzQnQ4YMiV7FZ+TIkd6sWTMvLCz0wsJCL38tS0pKvHPnzp6fn+8dO3b0+++/3929zswlirKS2qzs2bPHL7/8cu/UqZP36NHDV69e7e71z0pdr1kiKCepzUltz/Po0aP+/e9/39u1a+edOnXylStXVlv/lClTql0VKjc31999990a64lXMrOSzn9W9tqkv6KiIi8uLk51GQnz4osvMmfOHJ5//vlUl5ISZrbK3YuSsW5lJXMoJ8Flc05AWamPbM6KchJcNucEkpuVdJbScyzM7Dyg4hl67YB7gGbAzcDHkfF3u/u8Bi4vZW677Tbmz58fvfmYKCu1UVYqU05qppxUp6zUTFmpTDmpmXIitQlNj4WZHQ9sB7oDw4F97v5Y3Ut9IdN+Cch2df0SoKxIOeVEglJWJAjlRIJSj0XNwnTy9mXARnffnOpCJPSUFQlCOZGglBUJQjkRiSFMl5sdBEyvMDzGzIYBxcAd7r6n6gJmNgoYBdCiRYvoZdAk4ykrEoRyIkEpKxKEciISQygOhTKzE4EdQEd3/8jMWgC7AAceBFq6+4i61qEuxsxSWxejsiIVKScSlLIiQSgnEpQOhapZWA6F6ge85e4fAbj7R+5+xN2PAs8CNV/sWLKRsiJBKCcSlLIiQSgnIgGE5VCowVToXjSzlu6+MzLYH1iTkqqyTNuxc2scv+nhKwJNbyDKigShnEhQykoaCMH/P8qJSAApb1iY2UnAN4FbKoyeYGadKeti3FRlmmQpZUWCUE4kKGVFglBO0kcIGqBZr14NCzNrBORFBt9198PxFuDu+4GvVBk3NN71SuZRVsIjzL1bykn6SPWXAGUlMyQ7R8pJ5qgrK6neH2WKOhsWZvYw8Dt3X2NmnYA5fPHh+tjMrnL3d5NdpKQ/fWClnLIgIiKSmWL1WIyg7A6TAE8AE8tvBmNmtwO/Av4zeeWJiEi2UiNURCS9xGpYNOGLK0flA30qTHscuDcZRYmIiIiIVKUfHMItVsNiCWUnJD0OrKSsd+J/ItN6AR8nrTJJO/qwi0hFte0TIP79gvY3mSWZ76eyItJwYjUsfgD82cwGAJuBP5rZUsqugtAD+G6S6xMRERERkTRQ5w3y3P1Dyq4C9TvgELAYKAXeALq4++xkFygiIiIiIuEX83Kz7n6IsrtKPpv8ckQk2+mwBRERkfRUZ49FXazMJYksRkRERERE0tMxNyyAE4FXE1WIiIiIiIikr1g3yBtWx+QTE1yLiIiIiIikqVjnWEwBVgEHa5hmiS9HRERERETSUayGxXrgx+5e7ZAnM2sC7E9KVSIiIiIiklaC3CCvAzWfS3EkMl1CRFfUEREREZFUqLNh4e631DHtENA74RWJiIiIiEjaiXkfi2Qzs02U3XTvCHDY3YvMrDnwAtAW2AR82933pKpGCQdlRYJQTiQoZUWCUE5Egot1VajzgG+4+68iw69Q+WpQ33P39xNQR29331VheCyw0N0fNrOxkeEfJ2A7kv6UlQaQAYfUKScSlLIiQSgnIgHEuo/Fj4F9FYZ7AtMif2sp+yAlw9XAc5HHzwHXJGk7kv6UFQlCOZGglBUJQjkRqUGsQ6EuAX5YYfiIu08CMLOTgbcSUIMD/2NmDvza3Z8BWrj7TgB332lmZyZgO5L+lBUJQjmRoJSVBpLmvaDKiUhA5u61TzT7zN1PqTD8LXf/Y23Tj6kAs1buviPyofwzcBvwsrs3qzDPHnc/rYZlRwGjAFq0aNF1xowZlab/bfveGreZ3/rUQNPrEs+yyRTPc4739Ypn3VX17t17lbsXVRyXzKzUpbba66o/3aUyC/XJSphyItXF+uxk6z4lG2mfopwkSrKykIh9isRuWGwHLnT3TTVMawcsdfdWCSvG7D7KDr26GegV+RWgJbDY3c+ra9mioiIvLi6uNC7WLyTx/IIS1l9f4nnO8b5e8ay7KjOr8wOb6KzUpbbaIfXvd7KkMgv1yUqYciLVxfrsZOs+JRtpn6KcJEqyspDofUq2inUo1FzgQWBoDdPuj0w/ZmbWFDjO3Usjj/sADwAvAzcAD0f+nRPPdiT9KSsShHLS8ML6I0ssykripWsW6qKcJF4yf/SV1IvVsLgHeMPM3gZmAf8AWlJ2ktJpQI84t98CmGVm5bX83t1fMbOVwB/MbCSwBbguzu1I+lNWEixDd97KiQSlrEgQyolIPcS6Qd4/zKwI+BHQDzgd+ASYB/zc3T+JZ+Pu/gFQWMP4T4DL4lm3ZBZlRYJQTiQoZUWCUE5E6ifmDfLcfTfwX5E/ERHJIhnasyUiIkkQ6wZ5pwKF7v5aZPjuKss8qTtNitRNX8xEREQkG8Tqsfg/wGHgtcjw3ZSdawGQC5wA/DQ5pYmIiIiISLqI1bDoD/StMHzI3YcCmFkOZedaqGEhIiIiIpLlYjUsWrn7tgrDz5Q/cPdtkcaFiCSJDqMSERGRdHFcrBnM7Izyx+7+45rGi4iIiIhIdovVsFgGDK9l2nBgeWLLERERERGRdBTrUKj7gVfNrBXwEl/cIG8AMAL4z+SWl5l0eEtmSdX7Wdt2G2LbIiIiIlXF6rF4i7Lb13cFFgHvAQuBIqCvu69MbnkiIiIiIpIOYvVYbAeeB74PbAROA/a4+/5kFyYiIiIiIukjVsNiNPBdYAXwLjAV+D2ghoWISEjEOixOh1+KiEhDqLNh4e5zgDlm1gy4HhgKTDCz/wGeA15290PJL1NERETiFauRqUaoBKGcSG1iXm4WwN0/dfdfu/tFQB5QDPwC2JnM4kREREREJD3EOhSqEjNrDHwd6A60AN5IRlGZIJ7WvH4JEMk++tyLSJhonyTHIlDDwswuAoYB3wb+SeSEbnffnMTaREREpAp94RORsKrzUCgzu8/MNgJ/jIy6wt3bu/uDiWhUmFkbM3vVzN41s7Vm9r8rbHe7ma2O/F0e77YkvSkrEoRyIkEpKxKEciJSP7F6LHoA44DZ7n4gCds/DNzh7m+Z2cnAKjP7c2TaL9z9sSRsM+1l6a9VyooEoZxIUMqKBKGciNRDrKtC9U3mxt19J5ETwN291MzeBVonc5uSnpQVCUI5kaCUFQlCORGpn3qdvJ1MZtYWuAB4E7gQGGNmwyi7AtUd7r4nddVJmCgrEoRyElyW9oJGKSvBKCfWFuVEpE7m7qmuATP7MrAEeMjdXzKzFsAuwIEHgZbuPqKG5UYBowBatGjRdcaMGZWm/2373hq3l9/61Linp2rZTK2rqt69e69y96Kq41ORldqmBX1uDf1+pbquZK+7oobOSSz1zXmyly1fPhszWpWyEmzZTPz/JZ33KfGIJyexlk9VBuOtqyH2Kdku5Q0LMzsB+BOwwN1/XsP0tsCf3L1TXespKiry4uLiSuPivRFQXdNTtWym1lWVmVX7wKYqK/He1bih369U15XsdVfU0DmJJVWXmQ5rFlJZV1XKSrBlM/H/l3Tep8Qj3h6mbMtCIvYpEvAGecliZgZMAt6t+GE1s5YVZusPrGno2iRclBUJQjmRoJQVCUI5EamfVJ9jcSEwFPibma2OjLsbGGxmnSnrYtwE3JKa8iRElBUJItQ5yfZj1EMm1FmR0FBOROohpQ0Ld18KWA2T5jV0LRJuyooEkck5UaMksTI5K5I4yolI/aT0UCgREREREckMqT4USkQkbajXQMJOGc0sej8l3ahhISIiEiL6MikNQTmTZNChUCIiIiIiEjf1WIiIiCSYfg0WkWykHgsREREREYmbeixERERE0pB6xiRs1GMhIiIiIiJxU8NCRERERETipkOhRERERFKgtkOZQIczSXpSj4WIiIiIiMRNDQsREREREYmbGhYiIiIiIhI3NSxERERERCRualiIiIiIiEjcQtuwMLO+Zva+mW0ws7GprkfCS1mRoJQVCUI5kaCUFZHKQtmwMLPjgV8B/YDzgcFmdn5qq5IwUlYkKGVFglBOJChlRaS6UDYsgG7ABnf/wN0/B2YAV6e4JgknZUWCUlYkCOVEglJWRKowd091DdWY2bVAX3e/KTI8FOju7mOqzDcKGBUZPA94v0ELlWQ6293PiDWTspL1AuUEgmVFOclo2qdIENqnSFCBs5JNwnrnbathXLUWkLs/AzyT/HIkxJQVCSpmVpQTQfsUCU77FJEqwnoo1DagTYXhHGBHimqRcFNWJChlRYJQTiQoZUWkirA2LFYC55pZrpmdCAwCXk5xTRJOyooEpaxIEMqJBKWsiFQRykOh3P2wmY0BFgDHA5PdfW2Ky5IQUlYkKGVFglBOJChlRaS6UJ68LSIiIiIi6SWsh0KJiIiIiEgaUcNCRERERETipoaFiIiIiIjETQ0LERERERGJmxoWIiIiIiISNzUsREREREQkbmpYiIiIiIhI3NSwEBERERGRuKlhISIiIiIicVPDQkRERERE4tYgdfCSKgAAGf1JREFUDQszm2xm/zSzNRXGNTezP5vZ+si/p0XGm5k9YWYbzOwdM+vSEDVKOCgrEoRyIkEpKxKEciKSGA3VYzEV6Ftl3FhgobufCyyMDAP0A86N/I0CJjZQjRIOU1FWJLapKCcSzFSUFYltKsqJSNwapGHh7q8Bu6uMvhp4LvL4OeCaCuN/62X+CjQzs5YNUaeknrIiQSgnEpSyIkEoJyKJ0SiF227h7jsB3H2nmZ0ZGd8a2Fphvm2RcTurrsDMRlH2awFf+tKXurZp0ya5FUuDyM3N5cMPPzxSYZSyItUoJxKUsiJBKCdSH+vWrdvl7mekuo6wSWXDojZWwzivaUZ3fwZ4BqCoqMiLi4uTWZc0kE2bNpGbm3sowKzKShZTTiQoZUWCUE6kPsxsc6prCKNUXhXqo/Kuw8i//4yM3wZUbNLnADsauDYJF2VFglBOJChlRYJQTkTqKZUNi5eBGyKPbwDmVBg/LHLVhR7A3vKuSMlayooEoZxIUMqKBKGciNRTgxwKZWbTgV7A6Wa2DbgXeBj4g5mNBLYA10VmnwdcDmwA9gPDG6JGCYfBgwezePFigMbKitRGOZGglBUJQjkRSQxzr/GwwLSjYxczi5mtcveiZKxbWckcyokEpaxIEMqJBJXMrKQz3XlbRERERETipoaFiIiIiIjETQ0LERERERGJmxoWIiIiIiISNzUsREREREQkbmpYRMyaNQsz47333kt1KfUyfvx4zjnnHM477zwWLFhQ4zw33ngjubm5dO7cmc6dO7N69erotMWLF9O5c2c6duzIpZdeCsDWrVvp3bs3eXl5dOzYkccffzw6/3333Ufr1q2j65o3b15yn2AIZXJW3J1x48bRvn178vLyeOKJJ6LT6puV66+/PpqTtm3b0rlz5+Q+wZDJ5JxcfPHF0fe2VatWXHPNNdFpNeUEYMSIEZx55pl06tSp0rruvPNOOnToQEFBAf379+fTTz9NzhMLsUzOSm37lGnTplFQUEBBQQE9e/akpKQkusynn37KtddeS4cOHcjLy2P58uXRaU8++STnnXceHTt25K677kruEwyZbMzJ4sWLOfXUU6P7mwceeCC6TG37lJ/+9KcUFBTQuXNn+vTpw44dundhg3L3jPjr2rWrx+O6667ziy66yO+999641hPL4cOHE7autWvXekFBgR84cMA/+OADb9euXY3rv+GGG3zmzJnVxu/Zs8fz8vJ88+bN7u7+0Ucfubv7jh07fNWqVe7u/tlnn/m5557ra9eudXf3e++91x999NGEPYfaAMWurCRsXUGzMnnyZB86dKgfOXLE3b/IxLFkpaIf/ehHfv/99yfs+ZRTTlKTk4oGDBjgzz33nLvXnhN39yVLlviqVau8Y8eOlZZfsGCBHzp0yN3d77rrLr/rrrsS9nwqUlbCtU9ZtmyZ7969293d582b5926dYsuM2zYMH/22Wfd3f3gwYO+Z88ed3dftGiRX3bZZX7gwIFK60ok5SRcOXn11Vf9iiuuqHHdte1T9u7dG338+OOP+y233JKop1NJMrOSzn/qsQD27dvHsmXLmDRpEjNmzKg0bcKECeTn51NYWMjYsWMB2LBhA9/4xjcoLCykS5cubNy4kcWLF3PllVdGlxszZgxTp04FoG3btjzwwANcdNFFzJw5k2effZavf/3rFBYWMnDgQPbv309paSm5ubkcOnQIgM8++4y2bdtGh2syZ84cBg0aROPGjcnNzeWcc85hxYoVgZ/373//ewYMGMBXv/pVAM4880wAWrZsSZcuXQA4+eSTycvLY/v27YHXm8kyPSsTJ07knnvu4bjjynYN5ZmIJyvuzh/+8AcGDx4c7EXOAJmek3KlpaUsWrQo2mNRW04ALrnkEpo3b15tHX369KFRo7J7tfbo0YNt27bVur1MlOlZqW2f0rNnT0477TSg8vv+2Wef8dprrzFy5EgATjzxRJo1axZd19ixY2ncuHGldWWDbM1JXWrbp5xyyinRx//6178ws5jrksRRwwKYPXs2ffv2pX379jRv3py33noLgPnz5zN79mzefPNNSkpKot2uQ4YM4dZbb6WkpIQ33niDli1bxtxGkyZNWLp0KYMGDWLAgAGsXLmSkpIS8vLymDRpEieffDK9evVi7ty5AMyYMYOBAwdywgkn8PTTT/P0009XW+f27dtp06ZNdDgnJ6fWBsC4ceMoKCjg9ttv5+DBgwCsW7eOPXv20KtXL7p27cpvf/vbastt2rSJt99+m+7du0fH/fKXv6SgoIARI0awZ8+emM89k2R6VjZu3MgLL7xAUVER/fr1Y/369cCxZwXg9ddfp0WLFpx77rkxn3umyPSclJs1axaXXXZZ9D/yIDmpy+TJk+nXr1+9lkl3mZ6V2vYpFU2aNCn6vn/wwQecccYZDB8+nAsuuICbbrqJf/3rX0BZvl5//XW6d+/OpZdeysqVK2M+90yRzTlZvnw5hYWF9OvXj7Vr1wZ6vcaNG0ebNm2YNm1apcOnJPnUsACmT5/OoEGDABg0aBDTp08H4C9/+QvDhw/npJNOAqB58+aUlpayfft2+vfvD5R9EMun1+X666+PPl6zZg0XX3wx+fn5TJs2LfpBuemmm5gyZQoAU6ZMYfjw4QCMHj2a0aNHV1tnWU9cZTW1zMePH897773HypUr2b17N4888ggAhw8fZtWqVcydO5cFCxbw4IMPsm7duuhy+/btY+DAgfz3f/939IvD9773PTZu3Mjq1atp2bIld9xxR8znnkkyPSsHDx6kSZMmFBcXc/PNNzNixAjg2LJS8TXLpt4KyPycVHyeFd/bWDmpy0MPPUSjRo0YMmRIoPkzRaZnpbZ9SrlXX32VSZMmVfp/6a233uJ73/seb7/9Nk2bNuXhhx+OTtuzZw9//etfefTRR/n2t79dYx2ZKFtz0qVLFzZv3kxJSQm33XZbpfO56vLQQw+xdetWhgwZwi9/+ctAy0hiNEp1Aan2ySefsGjRItasWYOZceTIEcyMCRMm4O7VPgC17cQaNWrE0aNHo8MHDhyoNL1p06bRxzfeeCOzZ8+msLCQqVOnsnjxYgAuvPBCNm3axJIlSzhy5Ei1E5KqysnJYevWrdHhbdu20apVq2rzlf9S0bhxY4YPH85jjz0WXf7000+nadOmNG3alEsuuYSSkhLat2/PoUOHGDhwIEOGDGHAgAHRdbVo0SL6+Oabb67UrZrpsiErOTk5DBw4EID+/ftH/9M4lqxA2ReBl156iVWrVtVZXybJhpyUP88VK1Ywa9asSsvXlpO6PPfcc/zpT39i4cKFWXXYQjZkpbZ9CsA777zDTTfdxPz58/nKV74SnT8nJyfa83nttddGGxY5OTkMGDAAM6Nbt24cd9xx7Nq1izPOOKPOWtNdNuek4g9Vl19+Od///vfZtWsXp59+ep3bLfed73yHK664gvvvvz/Q/BK/rO+xePHFFxk2bBibN29m06ZNbN26ldzcXJYuXUqfPn2YPHky+/fvB2D37t2ccsop5OTkMHv2bKCslb1//37OPvts/v73v3Pw4EH27t3LwoULa91maWkpLVu25NChQ0ybNq3StGHDhjF48OBKO9/aXHXVVcyYMYODBw/y4Ycfsn79erp161Ztvp07dwJlO5vZs2dHdwRXX301r7/+OocPH2b//v28+eab5OXl4e6MHDmSvLw8fvSjH9W4Lig7DCLWTiWTZENWrrnmGhYtWgTAkiVLol8IjyUrUPZrWocOHcjJyYlZY6bIhpwAzJw5kyuvvJImTZpEx9WWk7q88sorPPLII7z88suBflXNJNmQldr2KVu2bGHAgAE8//zzlRqeZ511Fm3atOH9998HYOHChZx//vnV1rVu3To+//zzwF8w01k25+Qf//hHtKG0YsUKjh49Gm2E1qbiYVQvv/wyHTp0iFmnJFCqzx5P1N+xXm3h0ksv9fnz51ca9/jjj/vo0aPd3X38+PGel5fnhYWF/pOf/MTd3detW+e9e/f2/Px879Kli2/cuNHd3e+8805v3769X3HFFd6/f3+fMmWKu7ufffbZ/vHHH0fX/9RTT3nbtm390ksv9TFjxvgNN9wQnbZz505v0qRJ9CoY7u4TJ070iRMn1lj/z372M2/Xrp23b9/e582bFx3fr18/3759u7u79+7d2zt16uQdO3b0IUOGeGlpaXS+CRMmeF5ennfs2NF/8YtfuLv766+/7oDn5+d7YWGhFxYW+ty5c93d/bvf/a536tTJ8/Pz/Vvf+pbv2LEj+ItdD4TwyhzZkJU9e/b45Zdf7p06dfIePXr46tWro/PVNyvuZVckq62eRFBOyjR0Tmp7nu4158TdfdCgQX7WWWd5o0aNvHXr1v6b3/zG3d2/9rWveU5OTjQ/6XgFF2Wl/vuUkSNHerNmzaLve8XX8O233/auXbt6fn6+X3311dGrRx08eNCHDBniHTt29AsuuMAXLlwY/MUOSDkpE5acPPnkk37++ed7QUGBd+/e3ZctWxZdvrZ9yoABA7xjx46en5/vV155pW/bti34i10PycxKOv9Z2WuT/oqKiry4uDjVZcTtxRdfZM6cOTz//POpLiWlzGyVuxclY93KSuZQTmJTTsooK7EpK8pJEMpJmWRmJZ2l9BwLMzsPeKHCqHbAPUAz4Gbg48j4u9094+/EdttttzF//vysvOlcLMpKZcpKzZSTypST2ikrlSkrNVNOKlNOJJbQ9FiY2fHAdqA7MBzY5+6PBV0+U34JkDJ1/RKgrEg55USCUlYkCOVEglKPRc3CdPL2ZcBGd9+c6kIk9JQVCUI5kaCUFQlCORGJIUwNi0HA9ArDY8zsHTObbGanpaooCSVlRYJQTiQoZUWCUE5EYgjFfSzM7ETgKuAnkVETgQcBj/z7f4ERNSw3ChgFZfdXKL/Ocrm/bd9bbVv5rU9NXOHS4JQVCSJZOZHMo6xIEMqJSDChOMfCzK4GbnX3PjVMawv8yd3rvGFCTccuth07t9p8mx6+Ip5SpYHUduyisiIVNXROJH0pKxKEciJB6RyLmoXlUKjBVOheNLOWFab1B9Y0eEUSVsqKBKGcSFDKigShnIgEkPJDoczsJOCbwC0VRk8ws86UdTFuqjJNspSyIkEoJxKUsiJBKCciwaW8YeHu+4GvVBk3NEXlSIgpKxKEciJBKSsShHISfjqcOTwCHwplZiebWQszs2QWJCIiIiIi6afOHovIzWD+i7IrHeRERh8ys1XAPe6+MMn1iYiISBaq7Vdo/TotyaJsxS/WoVCPA12BsZT1btwGzAL2AFPM7C53n5HcEkVERERi0xdDCUI5SZ5YDYvBQHt3/wTAzBYCS939HDN7B5gCqGEhIiIioaUvktlJ73vDi9WwOAAcrjB8GGgC4O5/NbM2ySpMGpY+fCIiIiISj1gNiz8AL5vZE4AB/xt4CaLXcP44ueWJiIiIiEg6iNWw+DFlt68fS1nDYj7wUGSaAcOSV5qIiIhkOvWYSxDKSXqos2Hh7p8D90f+qk7bAexIUl2hk8hA68MhIiIiIpkm8H0sqrIylySyGBERERERSU/H3LAATgReTVQhIiIiIiKSvmLdIK+ucyhOTHAtElI6dEtEEkn7FBGRzBTr5O0pwCrgYA3TLPHliIhIJlDjQUQk+8RqWKwHfuzu1Q55MrMmwP6kVCUiIiIiImklVsNiCdCBms+lOBKZLiIV6JfayjLp9ajruWTS8xQRETkWsS43e0sd0w4BvRNekYiEWm1foPXFWuKlDImIpLdYPRZJZ2abgFLKekAOu3uRmTUHXgDaApuAb7v7nlTVKOGgrEgQyokEpaxIEMqJSHCxrgp1HvANd/9VZPgVKl8N6nvu/n4C6ujt7rsqDI8FFrr7w2Y2NjL84wRsJ+OE8Re+JNekrEgQyokEpaxIEMqJSACxeix+TOXzKHoCt0ced6bsgzQ8CXVdDfSKPH4OWIw+sFIzZSWAsB6+1IDbV04kKGVFglBORGoQq2FxCfDDCsNH3H0SgJmdDLyVgBoc+B8zc+DX7v4M0MLddwK4+04zOzMB25H0p6xIEMpJhkliA1RZkSCUE5GAzN1rn2j2mbufUmH4W+7+x9qmH1MBZq3cfUfkQ/ln4DbgZXdvVmGePe5+Wg3LjgJGAbRo0aLrjBkzKk3/2/a91baX3/rUmNNqUt/561qmvuOPZRv1dSyvVSKfR1W9e/de5e5FFcelIisN8Z4k6j08lppSnet4n3tYcpKI5xJEOmUl2/cp2Sqs+5SgdSkn4dUQ+5T65LemrEjshsV24EJ331TDtHbAUndvlbBizO4D9gE3A70ivwK0BBa7+3l1LVtUVOTFxcWVxiXy0pDH8otZfQ8/SeQ26utYXqtkHl5jZnV+YBsqKw3xnjTE4UAN8fyOZRvxPvew5CTWtERpiEPaErWNbN+nZKuw7lOC1qWchFdD7FPqk99YWclWsQ6Fmgs8CAytYdr9kenHzMyaAse5e2nkcR/gAeBl4Abg4ci/c+LZTjYK6zH1xyobs5Ku71UqZWNO6qIM1U5ZiU8qfwhrSMqJSP3EaljcA7xhZm8Ds4B/AC2Ba4DTgB5xbr8FMMvMymv5vbu/YmYrgT+Y2UhgC3BdnNuR9KesSBDKiQSlrEgQykmSpGNDU2KLdYO8f5hZEfAjoB9wOvAJMA/4ubt/Es/G3f0DoLCG8Z8Al8WzbsksykrDS8edvnLS8FKZk3i2raxIEMpJ/MJ4eLAkT8wb5Ln7buC/In9ShT4A2SnV73uqty8iIiJSVawb5J0KFLr7a5Hhu6ss86TuNCkiIiIiIrF6LP4PcBh4LTJ8N2XnWgDkAicAP01OaSIiIiIiki5iNSz6A30rDB9y96EAZpZD2bkWaliIiNRCh62JiEi2OC7G9Fbuvq3C8DPlDyLjc5JSlYiIiIiIpJWYJ2+b2Rnu/jGAu/+44vhkFiYi9adfx0VERCRVYjUslgHDgQk1TBsOLE94RSmmL2bJk+2vbbY///rQa5Vcen2lKmVCRBIhVsPifuBVM2sFvMQXN8gbAIwA/jO55YmIiIiISDqI1bB4i7Lb108AxlB2TsZR4E2gr7uvTG55IiIiUh/qfZB4KUNyrGI1LLYDzwPfBzYCpwF73H1/sguTL+gDLiIiIommu2JLosW6KtRoyu5XsQJYCgwETkp2USIiIiIikl7qbFi4+xx3v46y8yp+DXwb2GZmL5vZQDM7oSGKFBERERGRcIt5uVkAd/+UsobFr80sFxgK/CIy7vTklScikpl0SIE0NGVORJIt1qFQlZhZY+DrQHegBfC3ZBQlIiIiIiLpJVCPhZldBAyj7FCofxI5odvdN8ezcTNrA/wWOIuyq0094+6Pm9l9wM3Ax5FZ73b3efFsS9KbsiJBZEJO9Ktyw0inrCgTqZNOOREJgzobFpEPzlCgOTATuMLdlyVw+4eBO9z9LTM7GVhlZn+OTPuFuz+WwG1JelNWJAjlRIJSViQI5USkHmL1WPQAxgGz3f1Aojfu7juBnZHHpWb2LtA60duR9KesSBDKiQSlrEgQyolI/cS6KlRfd5+RjEZFVWbWFriAspvvAYwxs3fMbLKZnZbs7Uv6UFYkCOVEglJWatd27Nxqf9lKORGJzdw91TVgZl8GlgAPuftLZtYC2AU48CDQ0t1H1LDcKGAUQIsWLbrOmDGj0vS/bd9bbVv5rU+tc1qixmsb9dtGVb17917l7kVVxzd0VsL6emXrNqoKS06O5blkynsS1m1U1dBZqU19aj7WZcL6noRxG1WFJSfHIpHZSsRnLtHbSHW2qqotK9ku5Q2LyL0w/gQscPef1zC9LfAnd+9U13qKioq8uLi40ri6TnirbVqixmsb9dtGVWZW7QObiqyE9fXK1m1UFZac1DUt09+TsG6jqobOSm2O5UTsRN0dOdXvSRi3UVVYcnIsEpmtRHzmEr2NVGerqpqyIgGvCpUsZmbAJODdih9WM2sZOa4RoD+wJhX1SXgoKxKEciJBKSsShHISjK5cJuVS2rAALqTsqlN/M7PVkXF3A4PNrDNlXYybgFtSU56EiLIiQSgnElSosqIvZqEVqpyIhF1KGxbuvhSwGibpWtBSibIiQSgnEpSyIkEoJyL1U687b4uIiIiIiNQk1YdCiYiIyDHQ4VMiEjbqsRARERERkbipx0JEREQkZBLVI6WeLWlI6rEQEREREZG4qcdCREREJE2oB0LCTA0LERERkRRQI0EyjRoWIiIiCaYvjCKSjXSOhYiIiIiIxE0NCxERERERiZsaFiIiIiIiEjc1LEREREREJG5qWIiIiIiISNzUsBARERERkbipYSEiIiIiInELbcPCzPqa2ftmtsHMxqa6HgkvZUWCUlYkCOVEglJWRCoLZcPCzI4HfgX0A84HBpvZ+amtSsJIWZGglBUJQjmRoJQVkepC2bAAugEb3P0Dd/8cmAFcneKaJJyUFQlKWZEglBMJSlkRqSKsDYvWwNYKw9si40SqUlYkKGVFglBOJChlRaQKc/dU11CNmV0H/C93vykyPBTo5u63VZlvFDAqMnge8H6DFirJdLa7nxFrJmUl6wXKCQTLinKS0bRPkSC0T5GgAmclmzRKdQG12Aa0qTCcA+yoOpO7PwM801BFSSgpKxJUzKwoJ4L2KRKc9ikiVYT1UKiVwLlmlmtmJwKDgJdTXJOEk7IiQSkrEoRyIkEpKyJVhLLHwt0Pm9kYYAFwPDDZ3demuCwJIWVFglJWJAjlRIJSVkSqC+U5FiIiIiIikl7CeiiUiIiIiIikETUsREREREQkbmpYiIiIiIhI3NSwEBERERGRuKlhISIiIiIicVPDQkRERERE4qaGhYiIiIiIxE0NCxERERERidv/BzSdcBAnrOb1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 512\n",
    "identifieer = '0'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decaying Learning Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 8\n",
    "identifieer = 'LRS'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CsC1fTdAgUCf3uQ8pA+W5ux566JHGB8EB2afAqZkuix5V+twuJzhY305QaZ4DtEgY35ig5X4z8A7wc6A0YfxvgS8IKuf/S9ASfkU47lLglXLr25/gbMgXBH3EY+v4b4KLJjcT9GkfGY7rk7i+hOX0I+h7vZGgFftJ4KBwXA/gXwQNE0+EjzsqeP17lTFh3ITYfOXLQdAo8Um4/mvDYSeEr/8LgoOPGcC3w3FzYu9L+DwvnHZTuIw5QKfyZQrLsJNgZxx7PBiOOwR4gKCCsSl8zYMynSk99NCj4T3MPVu6CIvkjrDV8U2CU/+/JOg+0saTXPQm2c/MLiNo5T7JgzsBiYiIpFQnXUfMbJyZfWZmixOGNTWzFy34UZYXwz5jsR8suMfMlpnZOxbcrkoaiBzKyokEt3dbT9A943xVsmtPXefE3ccRdI36Tu29CqkLObRNkTRSTiRd6qqP9gSC05mJRgGzPLjjwSy+vjDjLIL+Oe0I7qv6QB2VUbLDBHIgK+5+m7sf7u4HufsJ7v5mpsuUYyZQxzlx98f969tTSv0xgRzYpkjaTUA5kTSok4q2u79M0Dcv0XkEPypA+Pf8hOGPeeAN4FBL8qtYkpuUFYlCOZGolBWJQjmRdMnkXUeae3B1OOHf2E31W1L2fqel4TBpuJQViUI5kaiUFYlCOZEay8YfrEl2Y/6kV2ya2XCC0zZ885vf7N6qVatkk0k9U1BQwIoVK/a6nVcSykoDppxIVMqKRKGcSFV8+OGH69095Y8BZbKivdbM8tx9TXjK5bNweCllf70qn+DWaHtx94eBhwF69OjhCxYsSGd5pY6UlJRQUFCwM2GQsiJ7UU4kKmVFolBOpCrMLNUv6wKZ7TryLDA0/H8oMD1h+JDwqt6ewKbYqRtpsJQViUI5kaiUFYlCOZEaq5MWbTObTPCjBs3MrBS4leBXBf9iZpcT/LjBwHDymcDZBL/ks43gVxulgRg8eDBz5swBaKSsSEWUE4lKWZEolBNJl5z5wRqdksktZvaWu/dIx7KVldyhnEhUyopEoZxIVFGzksmuIyIiIiIiOUsVbRERERGRNFBFW0REREQkDVTRFhERERFJA1W0RURERETSQBVtEREREZE0UEU7oqlTp2JmvP/++5kuSpXceeedtG3blg4dOvD8888nnebSSy+loKCALl260KVLF95++20ANmzYwIABAygqKuL4449n8eLF8Xk2btzIRRddxDHHHEPHjh15/fXXyyzzrrvuwsxYv359+l5clsrlrJx88snxnLRo0YLzzz8fAHdn5MiRtG3blqKiIhYuXFhmvs2bN9OyZUtGjBgRH9anTx86dOgQX95nn31GQ9IQc1LZNqV169YUFhbSpUsXevT4+o5Zt912Gy1btowvb+bMmel9gVkol7Mya9YsunXrRpcuXejVqxfLli0D4MEHH4znoVevXixduhSAF198ke7du1NYWEj37t2ZPXt2fFlfffUVw4cPp3379hxzzDE8/fTT6X+RWaQh5mTChAkcccQR8e3Do48+Wma+8vueLVu2xKft0qULzZo142c/+1l6X6C758Sje/funk4DBw70Xr16+a233prW9ezatavWlrVkyRIvKiry7du3+8cff+xt2rRJuvyhQ4f6k08+udfwa6+91m+77TZ3d3/vvff8tNNOi48bMmSIP/LII+7uvmPHDt+wYUN83CeffOJ9+/b1b3/7275u3bpqlR1Y4MpKpTKRlUQXXHCBT5w40d3dZ8yY4f369fM9e/b466+/7scff3yZaUeOHOmDBw/2q6++Oj6sd+/ePn/+/BqVWzlJLZtyUtk25aijjkq6vbj11lv997//fY3LrqyklomstGvXzpcuXeru7vfdd58PHTrU3d03bdoUn2b69On+3e9+193dFy5c6KtXr3Z393fffddbtGgRn+6WW27xm266yd3dd+/eXa39j3KSWjblZPz48WX2K+Ul2/ck6tatm7/00kvVKnvUrKhFO4Ivv/ySV199lbFjxzJlypQy48aMGUNhYSHFxcWMGjUKgGXLlnHGGWdQXFxMt27dWL58OXPmzOGcc86JzzdixAgmTJgABC05v/nNb+jVqxdPPvkkjzzyCMcddxzFxcVceOGFbNu2jS1btlBQUMDOnTuB4CitdevW8efJTJ8+nUGDBtGoUSMKCgpo27Yt8+bNi/y6ly5dyumnnw7AMcccQ0lJCWvXrmXz5s28/PLLXH755QDsv//+HHroofH5fv7znzNmzBjMLPK6ckVDycqWLVuYPXt2vKVy+vTpDBkyBDOjZ8+ebNy4kTVrgl8kfuutt1i7di19+/at+huaoxpqTirapkjFcj0rZsbmzZsB2LRpEy1atADg4IMPjk+zdevW+P6ka9eu8WmOPfZYtm/fzo4dOwAYN24cN9xwAwDf+MY3aNasWcR3uf5rqDmpTKp9z0cffcRnn33GySefnHJZNaGKdgTTpk2jX79+tG/fnqZNm8ZPiz/33HNMmzaNN998k0WLFnHdddcB8IMf/ICrr76aRYsW8dprr5GXl5dyHY0bN+aVV15h0KBBXHDBBcyfP59FixbRsWNHxo4dy0EHHUSfPn2YMWMGAFOmTOHCCy9kv/3248EHH+TBBx/ca5mrV6+mVatW8ef5+fmsXr066fpvuukmioqK+PnPfx7faBUXF/PMM88AMG/ePFauXElpaSkff/wxRxxxBMOGDaNr165cccUVbN26FYBnn32Wli1bUlxcHPXtzSkNISsQnKI8/fTT4zvDiubfs2cP11xzDb///e+TLmfYsGF06dKF22+/naCBoGFoqDmpaJsCwY60b9++dO/enYcffrjMcv70pz9RVFTEZZddxoYNG1K+9lyS61l59NFHOfvss8nPz+fxxx+PVwQB7rvvPo4++miuu+467rnnnr3mffrpp+natSuNGjVi48aNANx8881069aNgQMHNqiDuIack6effpqioiIuuugiVq1aBZBy3wMwefJkLr744rQ3CqqiHcHkyZMZNGgQAIMGDWLy5MkA/OMf/2DYsGE0adIEgKZNm7JlyxZWr17NgAEDgCCYsfGVufjii+P/L168mJNPPpnCwkImTZrEkiVLALjiiisYP348AOPHj2fYsGEAXHXVVVx11VV7LTNZxSVZoO68807ef/995s+fzxdffMHvfvc7AEaNGsWGDRvo0qUL9957L127dmXfffdl165dLFy4kB//+Mf861//4oADDmD06NFs27aN3/72t/zmN79J+XpzVa5nJfF1Dh48OOX8999/P2effXaZDWnMpEmTePfdd5k7dy5z587l8ccfr3B9uaah5qSibQrAq6++ysKFC3nuuee47777ePnllwH48Y9/zPLly3n77bfJy8vjmmuuSfnac0muZ+Xuu+9m5syZlJaWMmzYMH7xi1/Ex1199dUsX76c3/3ud9xxxx1l5luyZAnXX389Dz30EAC7du2itLSUk046iYULF3LiiSdy7bXXpnztuaKh5uTcc8+lpKSEd955hzPOOIOhQ4cCVLrviZkyZUqZ7VO67Jv2NdRzn3/+ObNnz2bx4sWYGbt378bMGDNmDO6+VyAqapXbd9992bNnT/z59u3by4w/4IAD4v9feumlTJs2jeLiYiZMmMCcOXMAOOmkkygpKeGll15i9+7ddO7cudKy5+fnx4/uAEpLS5OebokdyTZq1Ihhw4Zx1113AcGpu9gXxt0pKCigoKCAbdu2kZ+fzwknnADARRddxOjRo1m+fDkrVqyIt2aXlpbSrVs35s2bx7e+9a1Ky5oLGkJWYq9z3rx5TJ06NeX8r7/+OnPnzuX+++/nyy+/5KuvvuLAAw9k9OjRtGzZEoCDDjqI//qv/2LevHkMGTKk0nLmgoack4q2KUB8OUceeSQDBgxg3rx5nHLKKTRv3jw+/5VXXlnm1Hauy/WsrFu3jkWLFsX3JRdffDH9+vXba1mDBg3ixz/+cZllDRgwgMcee4yjjz4agMMPP5wmTZrEK48DBw5k7NixlZYxVzTknBx++OHx6a688kquv/56gEr3PQCLFi1i165ddO/evdLy1Qa1aKfw1FNPMWTIEFauXElJSQmrVq2ioKCAV155hb59+zJu3Di2bdsGwBdffMHBBx9Mfn4+06ZNA2DHjh1s27aNo446iqVLl7Jjxw42bdrErFmzKlznli1byMvLY+fOnUyaNKnMuCFDhjB48OD4UWJlvve97zFlyhR27NjBihUr+Oijjzj++OP3mi7Wl9bdmTZtWvyLsXHjRr766isgOG1zyimncPDBB/Otb32LVq1a8cEHHwDB1cCdOnWisLCQzz77jJKSEkpKSsjPz2fhwoUNopINDSMrAE8++STnnHMOjRs3LjP/Y489hrvzxhtvcMghh5CXl8ekSZP45JNPKCkp4a677mLIkCGMHj2aXbt2xe9Is3PnTv72t7+l3CDnioack4q2KVu3bmXLli1A0B/3hRdeiOchtn2CoCtKQ8kJ5H5WDjvsMDZt2sSHH34IBHcU6dixIxD0n42ZMWMG7dq1A4IM9e/fnzvvvJOTTjopPo2Zce6558YrfLH9UkPQkHOSuH149tln48Mr2vfElD/bllZRrpisD490Xc3bu3dvf+6558oM++Mf/+hXXXWVu7vfeeed3rFjRy8uLvYbbrjB3d0//PBDP/XUU72wsNC7devmy5cvd3f3X/7yl96+fXvv37+/DxgwwMePH+/ue19tf//993vr1q29d+/ePmLEiPjVte7ua9as8caNG5e5y8cDDzzgDzzwQNLy33HHHd6mTRtv3769z5w5Mz78rLPOil+5feqpp3rnzp392GOP9R/84Ae+ZcsWd3d/7bXXvG3btt6hQwcfMGCAf/HFF/H5//Wvf3n37t29sLDQzzvvvDLjYiq6i0AU1MMrvxtCVip6nXv27PGf/OQn3qZNG+/cuXPSu4kkXh3+5Zdferdu3bywsNA7derkI0eOrNaV7MpJ/cpJRduU5cuXe1FRkRcVFXmnTp38jjvuiM/zwx/+0Dt37uyFhYV+7rnn+qefflr5G1wBZSU7s/LMM894586dvaioyHv37h0v78iRI71Tp05eXFzsffr08cWLF7u7++233+5NmjTx4uLi+GPt2rXu7l5SUuInn3yyFxYW+mmnneYrV66s2hvuykl9y8moUaO8U6dOXlRU5H369PH33ntvr+UnuzNJQUFB0mmrImpWLJi2/uvRo4cvWLAg08VIu6eeeorp06fnfH9WM3vL3XuknrLqlJXcoZzUXEPICSgrtaEhZEU5qbmGkBOInpWM9tE2sw7AEwmD2gC3AIcCVwLrwuE3unvD+5WCcn7605/y3HPPNcgfbFBWqqahZkU5qZqGmhNQVqqqoWZFOamahpqTymRNi7aZ7QOsBk4AhgFfuvtdUedvKEeKDUVlR4rKisQoJxKVsiJRKCcSVdQW7Wy6GPJ0YLm7r8x0QSTrKSsShXIiUSkrEoVyIlWWTRXtQcDkhOcjzOwdMxtnZodlqlCSlZQViUI5kaiUFYlCOZEqy4r7aJvZ/sD3gBvCQQ8AtwMe/v0f4LIk8w0HhgM0b948flufmHdXb4q0/sKWh1Sv4FLn0pUVyS3KiUSlrEgUyolUV1b00Taz84Cr3X2vH6Q3s9bA39y90punJuv71HrUjEjrLxndP2pRpY5U1PcpXVmR+kk5kaiUFYlCOZGo6lsf7cEknI4xs7yEcQOAxXVeIslWyopEoZxIVMqKRKGcSLVkvOuImTUBzgR+lDB4jJl1ITglU1JunDRQyopEoZxIVMqKRKGcSE1kvKLt7tuAw8sNuyRDxZEspqxIFMqJRKWsSBTKidREtbuOmNn+ZvZxbRZGRERERCRX1KSPtgGta6kcIiIiIiI5pdKuI2a2u7LRBH2TRERERESknFR9tL8guC/k0iTjGgHv1nqJRERERERyQKqK9ltAM3dfXn6EmTUiaNUWEREREZFyUlW0rwF2Jhvh7jvMrKD2iyQiIiIiUv9VWtF29yUpxq+s3eKIiIiIiOSGmtzez8zslNosjIiIiIhIrqjJ7f32B/5ZWwUREREREcklqW7vN6SS0fvXcllERERERHJGqosMTi70AAAgAElEQVQhxxPceWRHknG644iIiIiISAVSVbQ/Aq539726iJhZY2BbWkolIiIiIlLPpapovwQcQ/K+2LvD8ZIlWo+akXKaktH966AkIiIiIpLq9n4/qmTcTuDUWi+RiIiIiEgOSNWinXZmVgJsIWgh3+XuPcysKfAE0BooAb7v7hsyVUbJDspK7Yhy5gPq79kP5USiUlYkCuVEaqLS2/uZWQczuzrh+d/NbHbCo0MtleNUd+/i7j3C56OAWe7eDpgVPhcBZUWiUU4kKmVFolBOpFpS3Uf7euDLhOffASaFjyWkL1jnARPD/ycC56dpPVL/KSsShXIiUSkrEoVyIpGkqmifAkxNeL7b3ce6+1jgRqBXLZTBgRfM7C0zGx4Oa+7uawDCv0fWwnqk/lNWJArlRKJSViQK5USqLVUf7SPdfXPC8/gP2Lj7FjNrXgtlOMndPzWzI4EXzez9qDOGgR8O0Lx5c+bMmVNm/DWFuyItJzbfu6s3RZq+sOUhUYtYRrqXH+X1ln+PqiJK+atb9ojSlpUseG11Jtu+F2mQtpxIzlFWJArlRKrN3L3ikWarCQJWkmRcG+AVd29Ra4Uxu42gq8qVQB93X2NmecAcd6+0P3iPHj18wYIFZYZV9aKvdF8klg3Lr8kFbnV5+0AzeyuhL1yy8bdRx1mprxcHlpdt34uaqOucNDTZ/NlXlbIiUSgnElWqrMSkatGeAdwOXJJk3K/D8dVmZgcA3whbxw8A+gK/AZ4FhgKjw7/Ta7Ieqf+Ulfojk5Uz5USiUlYkCuVEaipVRfsW4DUz+xdBX+1/A3kEnf4PA3rWcP3NgalmFivLn93972Y2H/iLmV0OfAIMrOF6JIl61oqrrEgUyolEpaxIFMqJ1EiqH6z5t5n1AH4BnAU0Az4HZgL/6+6f12Tl7v4xUJxk+OfA6TVZtuQWZUWiUE4kKmVFolBOpKZS/mCNu38B/Cp8iIiIJFXPzpJJLdJnL5JcpRVtMzsEKHb3l8PnN5ab5179EpKIiIiIyN5StWhfC+wCXg6f38jX99UuAPYDbk5P0URERERE6q9UFe0BQL+E5zvd/RIAM8sn6KutirZIhum0rYiISPZJVdFu4e6lCc8fjv3j7qVhZVvSJJfuYSsiIiLS0KT6CXbM7IjY/+5+fbLhIiIiIiJSVqqK9qvAsArGDQNer93iiIiIiIjkhlRdR34N/NPMWgDP8PUP1lwAXAaclt7iZTd17aic+g1/rarvhd677KTvvESl77CIQOqK9kKCnxsdA4wgaAHfA7wJ9HP3+ektnoiI5CpVRkUk16WqaK8GHgd+Aiwn+Nn1De6+Ld0FExEREZHc0RDPCqaqaF8F/BCYB7wHTAD+DKiiLSK1oiFueDNF77VkA+VQGpJKK9ruPh2YbmaHAhcDlwBjzOwFYCLwrLvvTH8xRURERHKLDjpyX6oWbQDcfSPwEPCQmRUQVLjvDoc1S1/xRERERKQhyoUDkUgV7RgzawQcB5wANAdeS0ehRERERCA3KlvScEWqaJtZL2AI8H3gM8ILJN19ZRrLJiIiIhmgO8KI1I5Kf7DGzG4zs+XAX8NB/d29vbvfXhuVbDNrZWb/NLP3zGyJmf2/hPWuNrO3w8fZNV2X1G/KikShnEhUyopEoZxITaVq0e4J3ARMc/ftaVj/LuAad19oZgcBb5nZi+G4u939rjSsU+onZUWiUE4kKmVFolBOpEZS3XWkXzpX7u5rgDXh/1vM7D2gZTrXKfWTsiJRKCcSlbIiUSgn9Us29uevtOtIXTKz1kBXgl+dBBhhZu+Y2TgzOyxjBZOso6xIFMqJRKWsSBTKiVSHuXumy4CZHQi8BPzW3Z8xs+bAesCB24E8d78syXzDgeEAzZs37z5lypQy499dvSnS+gtbHtJgpo9Nm43TJzr11FPfcvce5YdnMivZ/N5VZfpsyGFNpk+UjTlJLGtNXlsU2fbZZFPOy8vGrFT3c68L9XkbVBPZmBPI7qxURTZsgxKnr4mKslJexivaZrYf8DfgeXf/3yTjWwN/c/fOlS2nR48evmDBgjLDqnoKoSFMn3i6JNumT2RmewU401nJ5veuKtNnQw5rMn2ibMxJYlk1fcXT1sX0ibIxK9l81476vA2qiWzMCWR3VqoiG7ZBidPXRLKsJJPRriNmZsBY4L3E8JpZXsJkA4DFdV02yS7KikShnEhUyopEoZxITVXpB2vS4CSCX5l818zeDofdCAw2sy4Ep2RKgB9lpniSRZQViUI5kaiUFYlCOZEayWhF291fASzJqJl1XRbJbsqKRKGcSFTKikShnEhNZc1dR0REREREckmmu46IiIiISD3U0C7mrA5VtEVERDKsvt+lJJuo8ifZRBVtERGRHKeKvEhmqI+2iIiIiEgaqKItIiIiIpIG6joiIiJSz6griEj9oIq2iIiIiDQ4dXHAqq4jIiIiIiJpoIq2iIiIiEgaqOuIiIiISD2Q7nuE6x7ktU8VbREREZEcpIpz5qnriIiIiIhIGqiiLSIiIiKSBqpoi4iIiIikQdZWtM2sn5l9YGbLzGxUpssj2UtZkaiUFYlCOZGolBVJJSsr2ma2D3AfcBbQCRhsZp0yWyrJRsqKRKWsSBTKiUSlrEgUWVnRBo4Hlrn7x+7+FTAFOC/DZZLspKxIVMqKRKGcSFTKiqRk7p7pMuzFzC4C+rn7FeHzS4AT3H1EuemGA8PDpx2AD+q0oJJOR7n7EakmUlYavEg5gWhZUU5ymrYpEoW2KRJVpKxk6320LcmwvY4I3P1h4OH0F0eymLIiUaXMinIiaJsi0WmbIilla9eRUqBVwvN84NMMlUWym7IiUSkrEoVyIlEpK5JStla05wPtzKzAzPYHBgHPZrhMkp2UFYlKWZEolBOJSlmRlLKy64i77zKzEcDzwD7AOHdfkuFiSRZSViQqZUWiUE4kKmVFosjKiyFFREREROq7bO06IiIiIiJSr6miLSIiIiKSBqpoi4iIiIikgSraIiIiIiJpoIq2iIiIiEgaqKItIiIiIpIGqmiLiIiIiKSBKtoiIiIiImmgiraIiIiISBqooi0iIiIikgZ1UtE2s3Fm9pmZLU4Y1tTMXjSzj8K/h4XDzczuMbNlZvaOmXWrizJKdlBWJArlRKJSViQK5UTSpa5atCcA/coNGwXMcvd2wKzwOcBZQLvwMRx4oI7KKNlhAsqKpDYB5USimYCyIqlNQDmRNKiTira7vwx8UW7wecDE8P+JwPkJwx/zwBvAoWaWVxfllMxTViQK5USiUlYkCuVE0mXfDK67ubuvAXD3NWZ2ZDi8JbAqYbrScNia8gsws+EER5N885vf7N6qVav0lljqREFBAStWrNidMEhZkb0oJxKVsiJRKCdSFR9++OF6dz8i1XSZrGhXxJIM82QTuvvDwMMAPXr08AULFqSzXFJHSkpKKCgo2BlhUmWlAVNOJCplRaJQTqQqzGxllOkyedeRtbFTLeHfz8LhpUDiIV8+8Gkdl02yi7IiUSgnEpWyIlEoJ1JjmaxoPwsMDf8fCkxPGD4kvKq3J7ApdupGGixlRaJQTiQqZUWiUE6kxuqk64iZTQb6AM3MrBS4FRgN/MXMLgc+AQaGk88EzgaWAduAYXVRRskOgwcPZs6cOQCNlBWpiHIiUSkrEoVyIuli7km7FdU76vuUW8zsLXfvkY5lKyu5QzmRqJQViUI5kaiiZkW/DCkiIiIikgaqaIuIiIiIpIEq2iIiIiIiaaCKtoiIiIhIGqiiLSIiIiKSBqpoi4iIiIikgSralZg6dSpmxvvvv5/polTJnXfeSdu2benQoQPPP/980mncnZtuuon27dvTsWNH7rnnHgCmT59OUVERXbp0oUePHrzyyisArFy5ku7du9OlSxeOPfZYHnzwwfiyvvrqK4YPH0779u055phjePrpp9P/IrNILufk5JNPpkuXLnTp0oUWLVpw/vnnAxXnJGbz5s20bNmSESNGxIe99dZbFBYW0rZtW0aOHEns1qJffPEFZ555Ju3atePMM89kw4YNQJDRkSNH0rZtW4qKili4cGF8WRMnTqRdu3YAnc0s9oMSmFl3M3vXzJaZ2T1mZuHwpmb2opl9FP49LBxu4XTLzOwdM+tW4ze2ErmclVmzZtGtWze6dOlCr169WLZsGQAvv/wy3bp1Y9999+Wpp56KT1/RNmXbtm3079+fY445hmOPPZZRo0al/wVmoYaYlQkTJnDEEUfEtzmPPvpofJ5+/fpx6KGHcs4555RZ1p/+9Cfatm2LmbF+/fr0vbAs1RBz8vOf/zyekfbt23PooYfG5/nkk0/o27cvHTt2pFOnTpSUlFS6rDrh7jnx6N69u9e2gQMHeq9evfzWW2+t9WUn2rVrV60ta8mSJV5UVOTbt2/3jz/+2Nu0aZN0+ePGjfNLLrnEd+/e7e7ua9eudXf3LVu2+J49e9zdfdGiRd6hQwd3d9+xY4dv3749Ps1RRx3lq1evdnf3W265xW+66SZ3d9+9e7evW7euxq8DWOD1JCu5nJNEF1xwgU+cONHdK85JzMiRI33w4MF+9dVXx4cdd9xx/tprr/mePXu8X79+PnPmTHd3/+Uvf+l33nmnu7vfeeedft1117m7+4wZM7xfv36+Z88ef/311/344493d/fPP//cCwoK/PPPP3fgX8DHwGEeVNznAScCBjwHnBUOHwOMCv8fBfwu/P/scDoDegJvhsObapsSiJqVdu3a+dKlS93d/b777vOhQ4e6u/uKFSt80aJFfskll/iTTz4Zn76ibcrWrVt99uzZ8Wl69eoVz0pN1KdtinvDzMr48ePLbDMS/eMf//Bnn33W+/fvX2b4woULfcWKFX7UUUc1uH2Pe8PMSaJ77rnHhw0bFn/eu3dvf+GFF9w92K5s3bo18rKqKmpW1KJdgS+//JJXX32VsWPHMmXKlDLjxowZQ2FhIcXFxfHWlmXLlnHGGWdQXFxMt27dWL58OXPmzClz9D1ixAgmTJgAQOvWrfnNb35Dr169ePLJJ3nkkUc47rjjKC4u5sILL2Tbtm1s2bKFgoICdu7cCQSthK1bt44/T2b69OkMGjSIRo0aUVBQQNu2bZk3b95e0z3wwAPccsstfOMbQQSOPPJIAA488EDCRkC2bt0a/3///fenUaNGAOzYsYM9e/bElzVu3DhuuOEGAL7xjW/QrFmziO9y/ZfrOYnZsmULs2fPjrdoV5QTCFqu165dS9++fePD1qxZw+bNmznxxBMxM4YMGcK0adPiZRk6NGiUHjp0aJnhQ4YMwczo2bMnGzduZM2aNTz//POceeaZNG3aFGA38CLQz8zygIPd/fVwI/gYcH5YhPOAieH/E8sNfyzcbr4BHBou57sVvhnVlOtZMTM2b94MwKZNm2jRokW8XEVFRfFtTUxF25QmTZpw6qmnxqfp1q0bpaWl0d7kHNFQs1KZ008/nYMOOmiv4V27dqV169Yp589FyglMnjyZwYMHA7B06VJ27drFmWeeCQT7qSZNmkReVrqool2BadOm0a9fP9q3b0/Tpk3jp62fe+45pk2bxptvvsmiRYu47rrrAPjBD37A1VdfzaJFi3jttdfIy8tLuY7GjRvzyiuvMGjQIC644ALmz5/PokWL6NixI2PHjuWggw6iT58+zJgxA4ApU6Zw4YUXst9++/Hggw+W6b4Rs3r1alq1ahV/np+fz+rVq/eabvny5TzxxBP06NGDs846i48++ig+burUqRxzzDH079+fcePGxYevWrWKoqIiWrVqxfXXX0+LFi3YuHEjADfffDPdunVj4MCBrF27NspbnBNyPScxU6dO5fTTT+fggw8uM6x8Tvbs2cM111zD73//+73Wl5+fn3R9a9eujb8PeXl5fPbZZ5WWsfxwoBRoGT5KkwwHaO7uawDCv0eGw1sCqypYVq3K9aw8+uijnH322eTn5/P4449H6vKRbJuSaOPGjfz1r3/l9NNPT7msXNKQs/L0009TVFTERRddxKpVq/aaV77WkHMCQfezFStWcNpppwHw4Ycfcuihh3LBBRfQtWtXfvnLX7J79+5Iy0onVbQrMHnyZAYNGgTAoEGDmDx5MgD/+Mc/GDZsWPwoqWnTpmzZsoXVq1czYMAAIAhmbHxlLr744vj/ixcv5uSTT6awsJBJkyaxZMkSAK644grGjx8PwPjx4xk2bBgAV111FVddddVeywwa8spKbG2M2bFjB40bN2bBggVceeWVXHbZZfFxAwYM4P3332fatGncfPPN8eGtWrXinXfeYdmyZUycOJG1a9eya9cuSktLOemkk1i4cCEnnngi1157bcrXnityPSeJrzPWahCTLCf3338/Z599dvmKcJXXV9k8yYYDTtD9I9nwylQ0T+WFq4Zcz8rdd9/NzJkzKS0tZdiwYfziF79IWd5k25SYXbt2MXjwYEaOHEmbNm1SLiuXNNSsnHvuuZSUlPDOO+9wxhlnxM90SXINNScxU6ZM4aKLLmKfffYBgm3G3Llzueuuu5g/fz4ff/xxvHW+Otun2rJvna2pHvn888+ZPXs2ixcvxszYvXs3ZsaYMWNw970CUcGOn3333bdMF4vt27eXGX/AAQfE/7/00kuZNm0axcXFTJgwgTlz5gBw0kknUVJSwksvvcTu3bvp3LlzpWXPz88v0wpQWlqa9BRJfn4+F154IRBUmGJfjESnnHIKy5cvZ/369WW6g7Ro0YJjjz2WuXPncuGFF9KkSZP4l3fgwIGMHTu20jLmioaQk9jrnDdvHlOnTk06PjEnr7/+OnPnzuX+++/nyy+/5KuvvuLAAw/k//2//1fm9H/i+po3b86aNWvIy8tjzZo18W5MFZUxPz8//rpjLweYQ9AanV9u+Kfh/2vNLM/d14RdQz6LLRZolWSeWu2rkOtZWbduHYsWLeKEE04Agp1zv379Kl1uosRtykUXXQTA8OHDadeuHT/72c8iLycXNOSsHH744fHprrzySq6//vpK19eQNeScxEyZMoX77ruvzHK7du0aPzA///zzeeONN/je975Xo+1TTalFO4mnnnqKIUOGsHLlSkpKSli1ahUFBQW88sor9O3bl3HjxrFt2zYguGPCwQcfTH5+frxv6Y4dO9i2bRtHHXUUS5cuZceOHWzatIlZs2ZVuM4tW7aQl5fHzp07mTRpUplxQ4YMYfDgwUkrw+V973vfY8qUKezYsYMVK1bw0Ucfcfzxx+813fnnn8/s2bMBeOmll2jfvj0Q9OGKfSEXLlzIV199xeGHH05paSn/+c9/ANiwYQOvvvoqHTp0wMw499xz41+4WbNm0alTp5TlzAUNIScATz75JOeccw6NGzeOD6soJ5MmTeKTTz6hpKSEu+66iyFDhjB69Gjy8vI46KCDeOONN3B3HnvsMc4777x4WSZODLpPT5w4sczwxx57DHfnjTfe4JBDDiEvL4/vfve7vPDCC7G7k+wD9AWeD7uEbDGznuHdRoYA08MiPwvEmseGlhs+JLz7SE9gU7ic5JfBV1OuZ+Wwww5j06ZNfPjhhwC8+OKLdOzYsdLlVrRNAfjVr37Fpk2b+MMf/pCyfLmmIWdlzZo18emeffbZlBlqyBpyTgA++OADNmzYwIknnhgfdtxxx7FhwwbWrVsHwOzZs+nUqVO1tk+1KsoVk/XhUZtX8/bu3dufe+65MsP++Mc/+lVXXeXuwZ0ROnbs6MXFxX7DDTe4u/uHH37op556qhcWFnq3bt18+fLl7h7cUaF9+/bev39/HzBggI8fP97dfa8rpO+//35v3bq19+7d20eMGFHmitg1a9Z448aNfcOGDfFhDzzwgD/wwANJy3/HHXd4mzZtvH379mWu1j/rrLPidwrZsGGDn3322d65c2fv2bOnv/322+7uPnr0aO/UqZMXFxd7z549fe7cue7u/sILL3hhYaEXFRV5YWGhP/TQQ/HllpSU+Mknn+yFhYV+2mmn+cqVK6O/2RWgHlz53RByUtHrrCgnicrfQWD+/Pl+7LHHeps2bfzqq6+O37Vk/fr1ftppp3nbtm39tNNO888//9zd3ffs2eM/+clPvE2bNt65c2efP39+fFljx471o48+2oHtwDAPP1ugB7AYWA78CbBw+OHALOCj8G/TcLgB94XTvwv0cG1T9hIlK88884x37tzZi4qKvHfv3vHyzps3z1u2bOlNmjTxpk2beqdOndy94m3KqlWrHPBjjjnGi4uLvbi42B955JGqveFJ1IdtinvDzsqoUaO8U6dOXlRU5H369PH33nsvPn+vXr28WbNm3rhxY2/ZsqX//e9/j783LVu29H322cfz8vL88ssvj/5mJ6GcZH9O3N1vvfVWv/766/dabmy70rlzZx86dKjv2LEj5bKqK2pWYjuhjDCzDsATCYPaALcAhwJXAuvC4Te6+8zKltWjRw9fsGBBWsqZaU899RTTp0/n8ccfz3RR6oyZveXuPRKeKyspKCfKSVTKirISVUPLinJSPQ0tJ7B3ViqS0T7a7v4B0AXAzPYBVgNTgWHA3e5+VwaLlxV++tOf8txzzzFzZqXf35ynrFROOQkoJ6kpKwFlJTVlRTmJQjmpXDZdDHk6sNzdV6a6G0FDcu+992a6CNlIWSlHOUlKOUlCWUlKWUlCWdmLcpKEclK5bLoYchAwOeH5iPAnkcfFfi5ZJKSsSBTKiUSlrEgUyolUWVa0aJvZ/sD3gBvCQQ8AtxPcz/Z24H+Ay5LMNxwYDsEtwsrd8ot3V2+qdL2FLQ+pWcGlzqUrK5JblBOJSlmRKJQTqa6MXgwZL4TZecDV7t43ybjWwN/cvdIbMya7yKD1qBmVrrdkdP+qFlXqSEUXGaQrK1I/KScSlbIiUSgnElXUiyGzpevIYBJOx4Q/KBEzgOB2XSKgrEg0yolEpaxIFMqJVEvGu46YWRPgTOBHCYPHmFkXglMyJeXGSQOlrEgUyolEpaxIFMqJ1ETGK9ruvo3gxyQSh12SoeJIFlNWJArlRKJSViQK5URqIlu6joiIiIiI5JRKK9pmdqCZ/cHM/mZmp5tZOzN7y8w2mNmTup2NiIiIiEhyqVq07wWaAZ8D0wguBvgJcC5wBPDfaS2diIiIiEg9laqP9llAG4IK+SXAI+6+BsDMhgJz01s8EREREZH6KVVFu3F4EQBmtjlWyQYIf4JUXUdERERERJJI1XXk32bWNPy/zK+7mFkrYGNaSiUiIiIiUs+lqmjfCnwTwN1fLTfuZGBiOgolIiIiIlLfVdp1xN2fqGTcn2u/OCKZ0XrUjErHl4zuX+l4ERERkfKqfR9tC5xSm4UREREREckVNfnBmv2Bf9ZWQUREREREckmlXUfMbEglo/ev5bKIiIiIiOSMVLf3Gw+8BexIMs5qvzgiIiIiIrkhVUX7I+B6d9+ri4iZNQa2paVUIiIiIiL1XKqK9kvAMSTvi707HC/1hO6sIVEpK8npfRERkapIdXu/H1Uybidwaq2XSEREREQkB6Rq0U47MysBthC0kO9y9x7hr1E+AbQGSoDvu/uGTJVRsoOyIlEoJxKVsiJRKCdSE5Xe3s/MOpjZ1QnP/25msxMeHWqpHKe6exd37xE+HwXMcvd2wKzwuQgoKxKNciJRKSsShXIi1ZLqPtrXA18mPP8OMCl8LCF9wTqPr3/efSJwfprWI/WfsiJRKCcSlbIiUSgnEkmqriOnAD9LeL7b3ccCmNlBwMJaKIMDL5iZAw+5+8NAc3dfA+Dua8zsyFpYj9R/yopEoZzUkRy4OFRZkSiUE6m2VBXtI919c8Lz+A/YuPsWM2teC2U4yd0/DUP6opm9H3VGMxsODAdo3rw5c+bMKTP+msJdlc4fm/7d1Zsqna6w5SFRi1Sry6ptUd+PLJbxrDQU9fz9UE7qSA68H2nLiuQU5USqzdy94pFmqwkCVpJkXBvgFXdvUWuFMbuNoKvKlUCf8CgxD5jj7pX2B+/Ro4cvWLCgzLCorS212SqTzS082Vy28szsrYS+cMnG30YGstJQ1Jf3QznJrPr0ftR1VqR+Uk4kqlRZiUnVR3sGcHsF434djq82Mzsg7IKCmR0A9AUWA88CQ8PJhgLTa7Ieqf+UFYlCOZGolBWJQjmRmkrVdeQW4DUz+xcwFfg3kEfQ6f8woGcN198cmGpmsbL82d3/bmbzgb+Y2eXAJ8DAGq5HqiBLW6mUlSxUWVaUE8lyyopEoZxIjaT6wZp/m1kP4BfAWUAz4HNgJvC/7v55TVbu7h8DxUmGfw6cXpNlS25RViQK5USiUlYkCuVEairlD9a4+xfAr8KHiIiIiIhEUGlF28wOAYrd/eXw+Y3l5rlXv4SUXrVxQWe6TuFnaRcTEZGM0/ZRRCB1i/a1wC7g5fD5jQR9tQEKgP2Am9NTNBERERGR+itVRXsA0C/h+U53vwTAzPIJ+mqroi0iIiIVUgu/NFSpKtot3L004fnDsX/cvTSsbItIhmXinvEiIlIz2ibnvpQXQ5rZEe6+DsDdr08cns6CiUhu0I5EREQaqlQV7VeBYcCYJOOGAa/Xeokk52ThvZarLcprUety9ej9yC659L0VEcmUVBXtXwP/NLMWwDN8/YM1FwCXAaelt3giIlLf6SBKRBqqVD/BvpDg50a7A7OB94FZQA+gn7vPT2/xRERERETqp1Qt2quBx4GfAMsJfnZ9g7tvS3fBRERERETqs1QV7auAHwLzgPeACcCfAVW0RUSkVqmLiUjDlovbgEq7jrj7dHcfSNAv+yHg+0CpmT1rZhea2X51UUgRERERkfom5e39ANx9I0FF+yEzKwAuAe4OhzVLX/FyVy4etYlI1WRiO6Btj2Qz3e1GoqhP27FUF0OWYWaNgOOAE4DmwLvpKJSIiIiISH0XqaJtZr3M7GFgLXAH8AbQ3t1PTWfhRERERETqq0q7jpjZbQTdRJoCT1NLSQMAACAASURBVAL93f3V2lq5mbUCHgO+BewBHnb3P4brvRJYF056o7vPrK31Sv3TkLNSn06RZZpyUjHlpKyGnJX6ri6zrpxITaXqo90TuAmY5u7b07D+XcA17r7QzA4C3jKzF8Nxd7v7XWlYp9RPyopEoZxIVMpKLWgAB3jKidRIpRVtd++XzpW7+xpgTfj/FjN7D2iZznVK/aSsSBTKiUSlrEgUyonUlLl7pssAgJm1Bl4GOgO/AC4FNgMLCI4mNySZZzgwHKB58+bdp0yZUmb8u6s3VbrOwpaH1Pp0mVhnqukysc6qlq28U0899S1375FsXLZmJZPvczZ/trW9zkT1MSe1PV1DWWfidNWRrVmp77I5d9WhnGRWNmwroqosK4myoqJtZgcCLwG/dfdnzKw5sB5w4HYgz90vq2wZPXr08AULFpQZFvWUVm1Ol4l1ppouE+usatnKM7OkAc7mrGTyfc7mz7a215moPuaktqdrKOtMnK46sjUr9V025646lJPMyoZtRVQVZaW8SPfRTqfwR2+eBia5+zMA7r42YfwjwN8yVDzJIsqKRKGc5L7auteyslI53dM6oJxITVTpPtq1zcwMGAu85+7/mzA8L2GyAcDiui6bZBdlRaJQTiQqZUWiUE6kpjLdon0Swe0D3zWzt8NhNwKDzawLwSmZEuBHmSmeZBFlRaJQTiQqZUWiUE5qSTZ098iEjFa03f0VwJKM0r0opQxlRaJQTiSq+pSV2q6gNNQKT3XUp5xIdsp0i7aIiIiISK3LhoPKjPbRFhERERHJVWrRFhERyQHZ0HonImWpoi0iIpIhuoVe+ujAQ7KBKtoiIiIiUi06oKmcKtoiIiIiOUCV3uyjiraIiIhIFstEBVqV9tqhiraIiIiINFjpvFZCt/cTEREREUkDtWiLiIiINCC6203dUYu2iIiIiEgaqKItIiIiIpIGqmiLiIiIiKSBKtoiIiIiImmQtRVtM+tnZh+Y2TIzG5Xp8kj2UlYkKmVFolBOJCplRVLJyoq2me0D3AecBXQCBptZp8yWSrKRsiJRKSsShXIiUSkrEkVWVrSB44Fl7v6xu38FTAHOy3CZJDspKxKVsiJRKCcSlbIiKWVrRbslsCrheWk4TKQ8ZUWiUlYkCuVEolJWJCVz90yXYS9mNhD4rrtfET6/BDje3X9abrrhwPDwaQfggzotqKTTUe7+/9u79/Coynvv/++volKPgBUEQiXIwQBJEMOhiAIqCmItICpsK4gHZFfYv237oFTbWlt7Ybn81Z8+VazKqTxsaLECPhUUC0LFEwcFy0kEiZqAikAhioQkfH9/zDBNSMiskEzm9HldV65k3et0z8wna+65515rnRdtIWUl7QXKCQTLinKS0nRMkSB0TJGgAmUlUe8MWQC0KjedAew8diF3fxZ4tr4qJQlJWZGgomZFORF0TJHgdEyRqBJ16MhqoJ2ZZZrZqcBw4KU410kSk7IiQSkrEoRyIkEpKxJVQvZou3upmY0DXgVOBqa5+8Y4V0sSkLIiQSkrEoRyIkEpKxJEQo7RFhERERFJdok6dEREREREJKmpoS0iIiIiEgNqaIuIiIiIxIAa2iIiIiIiMaCGtoiIiIhIDKihLSIiIiISA2poi4iIiIjEgBraIiIiIiIxoIa2iIiIiEgMqKEtIiIiIhID9dLQNrNpZvalmW0oV9bEzF4zs4/CvxuHy83MnjSzbWb2gZl1rY86SmJQViQI5USCUlYkCOVEYqW+erRnAAOOKZsILHX3dsDS8DTAQKBd+GcMMKWe6iiJYQbKikQ3A+VEgpmBsiLRzUA5kRiol4a2u/8D2HtM8Q+BmeG/ZwKDy5X/yUPeARqZWfP6qKfEn7IiQSgnEpSyIkEoJxIr8Ryj3czddwGEfzcNl7cEPiu3XEG4TNKXsiJBKCcSlLIiQSgnUmsN4l2BKlgVZV7lgmZjCH1tw3e+851LWrVqFct6ST3JzMxkx44dZQEWVVbSmHIiQSkrEoRyIjWxdevWr9z9vGjLxbOh/YWZNXf3XeGvXL4MlxcA5ZOYAeysagPu/izwLEBeXp6vWbMmlvWVepKfn09mZmZJuSJlRSpRTiQoZUWCUE6kJszskyDLxXPoyEvAqPDfo4CF5cpHhs/q7QnsP/rVjaQtZUWCUE4kKGVFglBOpNbqpUfbzOYAfYHvmlkB8BDwKPAXM7sD+BS4Mbz4IuBaYBtwEBhdH3WUxDBixAiWL18OcJqyIsejnEhQyooEoZxIrJh7lcOKko6+kkktZrbW3fNisW1lJXUoJxKUsiJBKCcSVNCs6M6QIiIiIiIxoIa2iIiIiEgMqKEtIiIiIhIDamiLiIiIiMSAGtoiIiIiIjGghraIiIiISAyooX2M+fPnY2Zs2bIl3lWpkUmTJtG2bVs6dOjAq6++WuUy7s6DDz5I+/btycrK4sknnwRg9uzZ5OTkkJOTQ69evVi/fn1knVdeeYUOHTrQtm1bHn300Uj5LbfcQocOHejcuTO33347JSUllfaX6lI5K5dddhldunShS5cutGjRgsGDBwOwcOFCcnJy6NKlC3l5eaxcuTKyzqeffsrVV19NVlYWHTt2JD8/H4DbbruNzMzMyPbWrVsX88eYSFI5J0uXLqVr16506dKF3r17s23bNgCKi4u5+eabadu2LT169IhkYdWqVZEc5ObmMn/+fAAOHTpE9+7dyc3NpVOnTjz00EP18hgTTTpmZcaMGZx33nmRXDz//PMArFu3ju9///t06tSJnJwc/vznP1fa5vjx4znzzDNj98ASVDrm5N57741kpH379jRq1CiyzvHee46Ke07cPSV+LrnkEq8LN954o/fu3dsfeuihOtne8ZSWltbZtjZu3Og5OTl+6NAh//jjj71NmzZVbn/atGl+6623ellZmbu7f/HFF+7u/uabb/revXvd3X3RokXevXv3SB3btGnj27dv9+LiYs/JyfGNGze6u/vLL7/sR44c8SNHjvjw4cP96aefrrPH4+4OrHFlxd3jk5Xyhg4d6jNnznR396KiIj9y5Ii7u69fv947dOgQWa5Pnz6+ZMmSyHLffPONu7uPGjXK582bV2ePoTzl5N/ikZN27dr5pk2b3N39qaee8lGjRkX+vvvuu93dfc6cOX7TTTe5u/s333zjJSUl7u6+c+dOP++887ykpMSPHDniRUVF7u5++PBh7969u7/99tt19njclZXyEikr06dP93vuuafS8h9++KFv3brV3d0LCwv9/PPP93379kXmr1692n/0ox/5GWecUWePxV05KS+RclLek08+6aNHj45MH++9xz12OXEPnhX1aJfz9ddf8+abbzJ16lTmzp1bYd7kyZPJzs4mNzeXiRMnArBt2zauuuoqcnNz6dq1K9u3b2f58uVcd911kfXGjRvHjBkzAGjdujW//vWv6d27N/PmzeO5556jW7du5ObmcsMNN3Dw4EGKiorIzMyM9BAfOHCA1q1bV9tjvHDhQoYPH85pp51GZmYmbdu2ZdWqVZWWmzJlCr/85S856aTQy960aVMAevXqRePGjQHo2bMnBQUFQKj3qW3btrRp04ZTTz2V4cOHs3Bh6A601157LWaGmdG9e/fIOuki1bNyVFFREcuWLYv0aJ955pmYGQDffPNN5O9NmzZRWlpK//79I8udfvrpNXlKU1Kq58TMOHDgAAD79++nRYsWkfVHjQrduXrYsGEsXboUd+f000+nQYPQDYkPHToUyY+ZRXqcSkpKKCkpicxLF+maleNp37497dq1A6BFixY0bdqU3bt3A1BWVsaECROYPHlytdtIRcoJzJkzhxEjRgDVv/ckSk7U0C5nwYIFDBgwgPbt29OkSRPee+89ABYvXsyCBQt49913Wb9+Pffddx8QGj5xzz33sH79et566y2aN28edR8NGzZk5cqVDB8+nKFDh7J69WrWr19PVlYWU6dO5ayzzqJv3768/PLLAMydO5cbbriBU045hWeeeYZnnnmm0jYLCwtp1apVZDojI4PCwsJKy23fvp0///nP5OXlMXDgQD766KNKy0ydOpWBAwcG3m5JSQmzZs1iwIABUR97Kkn1rBw1f/58rrzySs4+++wKZRdddBGDBg1i2rRpAGzdupVGjRoxdOhQLr74YiZMmEBZWVlknQcffJCcnBzuvfdeiouLoz72VJHqOXn++ee59tprycjIYNasWZE39/LrN2jQgHPOOYc9e/YA8O6779KpUyeys7N55plnIg3vsrIyunTpQtOmTenfvz89evQI/DyngnTNCsBf//pXcnJyGDZsGJ999lmldVetWsXhw4e58MILAfjDH/7A9ddfH+gxp5p0zgnAJ598wo4dO7jiiiuA6t97EiUnamiXM2fOHIYPHw7A8OHDmTNnDgB///vfGT16dORTUpMmTSgqKqKwsJAhQ4YAoWAG6cG7+eabI39v2LCByy67jOzsbGbPns3GjRsBuPPOO5k+fToA06dPZ/To0QCMHTuWsWPHVtpm6BuMiqrqDSouLqZhw4asWbOGu+66i9tvv73C/Ndff52pU6fyu9/9LvB2f/zjH3P55Zdz2WWXVfu4U02qZ6X84zzac3DUkCFD2LJlCwsWLOAXv/gFAKWlpbzxxhs89thjrF69mo8//jjSQzJp0iS2bNnC6tWr2bt3byRf6SDVc/L444+zaNEiCgoKGD16ND/5yU+irt+jRw82btzI6tWrmTRpEocOHQLg5JNPZt26dRQUFLBq1So2bNgQ9bGnknTNyg9+8APy8/P54IMPuOqqqyLfhBy1a9cubr31VqZPn85JJ53Ezp07mTdvHuPHj4/6eFNRuubkqLlz5zJs2DBOPvlk4PjvPYmUkwbxrkCi2LNnD8uWLWPDhg2YGWVlZZgZkydPxt0rBaKq0ECo9+bIkSOR6aNvIkedccYZkb9vu+02FixYQG5uLjNmzGD58uUAXHrppeTn57NixQrKysro3LlztXXPyMio0AtQUFBQ5dctGRkZ3HDDDUCosXT0HwPggw8+4M4772Tx4sWce+65gbb78MMPs3v3bv74xz9WW79Ukw5ZOfo4V61aFTlh7ViXX34527dv56uvviIjI4OLL76YNm3aADB48GDeeecd7rjjjkhvwmmnncbo0aN57LHHqq1jqkj1nOzevZv169dHep5vvvnmyDdbR9fPyMigtLSU/fv306RJkwrrZ2VlccYZZ7Bhwwby8vIi5Y0aNaJv37688sorUeuZKtI5K0ffbwDuuusu7r///sj0gQMHGDRoEI888gg9e/YE4P3332fbtm20bdsWgIMHD9K2bdvISXOpLJ1zctTcuXN56qmnKmy3qvee888/P2Fyoh7tsBdeeIGRI0fyySefkJ+fz2effUZmZiYrV67k6quvZtq0aRw8eBCAvXv3cvbZZ5ORkcGCBQuAUG/xwYMHueCCC9i0aRPFxcXs37+fpUuXHnefRUVFNG/enJKSEmbPnl1h3siRIxkxYkSFxvDxXH/99cydO5fi4mJ27NjBRx99RPfu3SstN3jwYJYtWwbAihUraN++PRA6Y3fo0KHMmjUrUgbQrVs3PvroI3bs2MHhw4eZO3cu119/PRD6eufVV19lzpw5kTHf6SIdsgIwb948rrvuOho2bBgp27ZtW+Tg/d5773H48GHOPfdcunXrxr59+yJjKJctW0bHjh2BUI8UhA76CxYsSJvGU6rnpHHjxuzfv5+tW7cC8Nprr5GVlRVZf+bMmZHn4YorrsDM2LFjB6WlpUDoK+APP/yQ1q1bs3v3bv71r38B8O233/L3v/+diy66KGo9U0U6Z+Xo8QHgpZdeipQfPnyYIUOGMHLkSG688cbIMoMGDeLzzz8nPz+f/Px8Tj/99LRoZEN65wTgww8/ZN++fXz/+9+PlB3vvSehchLkjMlk+Knt2bx9+vTxxYsXVyh74oknfOzYse7uPmnSJM/KyvLc3Fz/2c9+5u7uW7du9X79+nl2drZ37drVt2/f7u7uEyZM8Pbt2/ugQYN8yJAhPn36dHd3v+CCC3z37t2R7T/99NPeunVr79Onj48bN67C2bW7du3yhg0bVjjLesqUKT5lypQq6//II494mzZtvH379r5o0aJI+cCBA72wsNDd3fft2+fXXnutd+7c2Xv27Onr1q1zd/c77rjDGzVq5Lm5uZ6bm+vln8uXX37Z27Vr523atPFHHnkkUn7yySd7mzZtIus8/PDDwZ7ogEjgM7/TISvHe5yPPvqod+zY0XNzc71nz57+xhtvROYtWbLEs7OzvXPnzj5q1CgvLi52d/d+/fp5586dvVOnTn7LLbdEri5RF5ST+ObkxRdf9M6dO3tOTo736dMnUt9vv/3Whw0b5hdeeKF369YtUv6nP/0pkp+LL77Y58+f7+6hK9h06dLFs7OzvVOnTnV+PHFXVhI1KxMnTvSOHTt6Tk6O9+3b1zdv3uzu7rNmzfIGDRpE3mNyc3P9/fffr7TvdLrqSDrnxN39oYce8vvvv7/Sdo/33lNePK86YqFlk19eXp6vWbMm3tWoMy+88AILFy5k1qxZ8a5KXJjZWnfPi75kzSkrqUM5CS6dcwLKSk2kc1aUk+DSOScQPCtxHaNtZh2A8lehbwP8EmgE3AXsDpc/4O6L6rl6cTN+/HgWL17MokVp85CjUlaqpqxUpJxUTTmpTFmpmrJSkXJSNeUkuITp0Tazk4FCoAcwGvja3QOfNZVqnxTTXXWfFJUVOUo5kaCUFQlCOZGggvZoJ9JZbFcC2939k3hXRBKesiJBKCcSlLIiQSgnUmOJdHm/4cCcctPjzGwksAb4qbvvO3YFMxsDjAFo1qxZ5LIzR/2zcH+VO8pueU7d1Fjipc6zIilJOZGglBUJQjmRGkuIoSNmdiqwE+jk7l+YWTPgK8CB3wDN3f326rZR1VcyrSe+XOWy+Y8OqotqSwwd7yuZWGVFkpNyIkEpKxKEciJBJdvQkYHAe+7+BYC7f+HuZe5+BHgOqPpCv5KOlBUJQjmRoJQVCUI5kROSKA3tEZT7OsbMyt+YfgiQXvfileooKxKEciJBKSsShHIiJyTuY7TN7HSgP3B3ueLJZtaF0Fcy+cfMkzSlrEgQyokEpaxIEMqJ1EaNGtpm1gA4ej/Mze5eWtsKuPtB4Nxjym6t7XYl9SgrEoRyIkEpKxKEciK1Ue3QETN71Mw6h//uDHwIvBH+2WxmWdWtLyIiIiKSrqKN0b4d2Br++0lgirs3cvdGwNPAU7GsnIiIiIhIsorW0G5Ybpls4P8rN+8JoGssKiUiIiIikuyiNbRX8O8B/quBK8rN6wvsjkGdRERERESSXrSTIf8LeM3MhgKfAP/XzFYSOsu2J/CjGNdPRERERCQpVduj7e47CF1l5P8AJcByoAh4C+jq7gtiXUERERERkWQU9fJ+7l5C6K5Hz8W+OiLx0Xriy1WW5z86qJ5rIiIiIqnihO8MaSGX12VlRERERERSRW1uwX4q8HpdVUREREREJJVUO3TEzEZWM/vUOq6LiIiIiEjKiDZGezqwFiiuYp7VfXVERERERFJDtIb2R8D97l5piIiZNQQOxqRWIiIiIiJJLsgNay46zryy8HwRERERETlGtT3a7n53NfNKgH51XiMRERERkRQQ9TrasWZm+YRuglMGlLp7npk1Af4MtAbygZvcfV+86iiJQVmRIJQTCUpZkSCUE6mNaoeOmFkHM7un3PQrZras3E+HOqpHP3fv4u554emJwFJ3bwcsDU+LgLIiwSgnEpSyIkEoJ3JCoo3Rvh/4utx0L2B2+GcjsQvWD4GZ4b9nAoNjtB9JfsqKBKGcSFDKigShnEgg0YaOXA78d7npMnefCmBmZwHv1UEdHFhiZg780d2fBZq5+y4Ad99lZk3rYD+S/JSVOpTCt51XTiQoZUWCUE7khEVraDd19wPlpiM3sHH3IjNrVgd1uNTdd4ZD+pqZbQm6opmNAcYANGvWjOXLl1eY/9Ps0irXO3a5E/HPwv1Vlme3PKfW266NRK1XHUnKrCSqFH7MMctJiv9/pSNlRYKIWU4k9Zm7H3+mWSGhgOVXMa8NsNLdW9RZZcx+RWioyl1A3/CnxObAcnevdjx4Xl6er1mzpkJZLHvsErU3MFHrVVNmtrbcWLiq5v+KJMlKokqFx6ycSFDKigRR3zmR5BUtK0dFG6P9MvCb48x7ODz/hJnZGeEhKJjZGcDVwAbgJWBUeLFRwMLa7EeSn7IiQSgnEpSyIkEoJ1Jb0YaO/BJ4y8zeB+YDnwPNCQ36bwz0rOX+mwHzzexoXf7H3V8xs9XAX8zsDuBT4MZa7keSn7IiQSgndSyFe2aVFQlCOZFaiXbDms/NLA/4CTAQ+C6wB1gE/N7d99Rm5+7+MZBbRfke4MrabFtSi7IiQSgnEpSyIkEoJ1JbUW9Y4+57gZ+Hf0QkDaRwL6aIiEi9qbahbWbnALnu/o/w9APHrPO/dSekmovWiEnHkzhFREREUk20Hu3/BZQC/whPP0BorDZAJnAK8IvYVE1EREREJHlFa2gPAQaUmy5x91sBzCyD0FhtNbRFRNKUviUTETm+aA3tFu5eUG762aN/uHtBuLEtKUJvmMnleK8XxP41U1aSi14vEZH4iHoypJmd5+67Adz9/vLlsayYiNSOGlciIiLxFe2GNW8Co48zbzTwdt1WR0REREQkNUTr0X4YeN3MWgAv8u8b1gwFbgeuiG314ks9ggLRh2jE8yoyIiKJQse6movnEECpH9Ea2u8Rut3oZGAcoR7wI8C7wAB3Xx3b6omISKzFqoGkRoQcpUa4pKtoDe1CYBbwY2A7oduu73P3g7GumIiIiIhIMovW0B4L/AhYBWwGZgD/A6ihnYbUI1H/9JxLEOo5FhFJTNWeDOnuC939RkLjsv8I3AQUmNlLZnaDmZ1SH5UUEREREUk20a46AoC7/8vd/+juvYEsYA3wOLArlpUTEREREUlWUa+jXZ6ZnQZ0A3oAzYC3YlEpqV4yDidIxjrXBz0vlaXyc5LKj01ERCoL1NA2s97ASEJDR74kfIKku38Sw7qJiIhIPdKHQZG6VW1D28x+BdwKNAHmAYPc/c262rmZtQL+BJxP6LKBz7r7E+H93gXsDi/6gLsvqqv9SvJRViQI5USCUlYSS6I28JWTupdu956I1qPdE3gQWODuh2Kw/1Lgp+7+npmdBaw1s9fC8x5398disE+JkRj/cygrSSSOB0rlRIJSViQI5URqpdqGtrsPiOXO3X0X4RMq3b3IzDYDLWO5T0lOyooEoZxIUMpKzaVaT2MQyonUVqCrjtQHM2sNXEzorpMA48zsAzObZmaN41YxSTjKigShnEhQyooEoZzIiTB3j3cdMLMzgRXAb939RTNrBnwFOPAboLm7317FemOAMQDNmjW7ZO7cuRXm/7Nwf5X7y255Tq3nx2vdVK3Xsfr167fW3fOOLY9HVo43L+hjq+/XK971CjK/OjVZN5FyUhfzT1SiZiFavepTomUlUSXq+0t9SZScQOJn5UQlSxaiOV5WjhX3hnb4pjd/A151999XMb818Dd371zddvLy8nzNmjUVymo74L66+fFaN1XrdSwzqxTgeGUl2l33Eu31ine9gsyvTk3WTaSc1MX8E5WoWUikO1YmWlYSVaK+v9SXRMkJJH5WTlSyZCGaqrJSlRpdR7uumZkBU4HN5cNrZs3D46IAhgAb4lE/SRzKigShnEhQyooEoZxULVkaw4kgrg1t4FJClw/8p5mtC5c9AIwwsy6EvpLJB+6OT/UkgSgrEkTS5iRVenmSSMJmRa91QknYnEhyiGtD291XAlbFLF2LUipQViQI5USCUlYkCOVEaivePdoiIiIikkJi+a1Msn3jo4a2iIgknWR7s61L9XWysYjUnhraIiIiktD0AUGSVcLcsEZEREREJJWoR1tEROIinXsp6/ua6unwnIokIjW0RURERJKQTjpMfGpoi4iISMpSg1HiSQ1tEalXetMTEYk9HWsTg06GFBERERGJAfVoi4hIQlKPnEjs6P+rfqhHW0REREQkBtSjLSIiIpKA1OtcM4l411Q1tEVERCRpqTEqiUxDR0REREREYkANbRERERGRGEjYhraZDTCzD81sm5lNjHd9JHEpKxKUsiJBKCcSlLIi0STkGG0zOxl4CugPFACrzewld98U35pJolFWJChlRYJQTiQoZSX5xGM8f6L2aHcHtrn7x+5+GJgL/DDOdZLEpKxIUMqKBKGcSFDKikRl7h7vOlRiZsOAAe5+Z3j6VqCHu487ZrkxwJjwZAfgw3qtqMTSBe5+XrSFlJW0FygnECwryklK0zFFgtAxRYIKlJWEHDoCWBVllT4RuPuzwLOxr44kMGVFgoqaFeVE0DFFgtMxRaJK1KEjBUCrctMZwM441UUSm7IiQSkrEoRyIkEpKxJVoja0VwPtzCzTzE4FhgMvxblOkpiUFQlKWZEglBMJSlmRqBJy6Ii7l5rZOOBV4GRgmrtvjHO1JAEpKxKUsiJBKCcSlLIiQSTkyZAiIiIiIskuUYeOiIiIiIgkNTW0RURERERiQA1tEREREZEYUENbRERERCQG1NAWEREREYkBNbRFRERERGJADW0RERERkRhQQ1tEREREJAbU0BYRERERiQE1tEVEREREYqBeGtpmNs3MvjSzDeXKmpjZa2b2Ufh343C5mdmTZrbNzD4ws671UUdJDMqKBKGcSFDKigShnEis1FeP9gxgwDFlE4Gl7t4OWBqeBhgItAv/jAGm1FMdJTHMQFmR6GagnEgwM1BWJLoZKCcSA/XS0Hb3fwB7jyn+ITAz/PdMYHC58j95yDtAIzNrXh/1lPhTViQI5USCUlYkCOVEYqVBHPfdzN13Abj7LjNrGi5vCXxWbrmCcNmuYzdgZmMIfZrkO9/5ziWtWrWK8Wd5zgAAGddJREFUbY2lXmRmZrJjx46yckXKilSinEhQyooEoZxITWzduvUrdz8v2nLxbGgfj1VR5lUt6O7PAs8C5OXl+Zo1a2JZL6kn+fn5ZGZmlgRYVFlJY8qJBKWsSBDKidSEmX0SZLl4XnXki6NftYR/fxkuLwDKf+TLAHbWc90ksSgrEoRyIkEpKxKEciK1Fs+G9kvAqPDfo4CF5cpHhs/q7QnsP/rVjaQtZUWCUE4kKGVFglBOpNbqZeiImc0B+gLfNbMC4CHgUeAvZnYH8ClwY3jxRcC1wDbgIDC6PuooiWHEiBEsX74c4DRlRY5HOZGglBUJQjmRWDH3KocVJR2NfUotZrbW3fNisW1lJXUoJxKUsiJBKCcSVNCs6M6QIiIiIiIxoIa2iIiIiEgMqKEtIiIiIhIDamiLiIiIiMSAGtoiIiIiIjGghnbY/PnzMTO2bNkS76rUyKRJk2jbti0dOnTg1VdfrXKZ2267jczMTLp06UKXLl1Yt24dAPv37+cHP/gBubm5dOrUienTp0fW+fTTT7n66qvJysqiY8eO5OfnV9jm+PHjOfPMM2P2uBJZKmflsssui+SkRYsWDB48GIDZs2eTk5NDTk4OvXr1Yv369ZF1br/9dpo2bUrnzp0rbGvevHl06tSJk046iXQ80z6Vc7J06VK6du1Kly5d6N27N9u2bQOguLiYm2++mbZt29KjR4/IcePw4cOMHj2a7OxscnNzj15GDYAHH3yQVq1ape3xBNIzKzNmzOC8886LHG+ef/75yDozZ86kXbt2tGvXjpkzZ1ba5vXXX1/peJMO0jEnAH/5y1/o2LEjnTp14j/+4z8i5ffddx+dOnUiKyuL//qv/+LoVfTmzJlDdnY2OTk5DBgwgK+++iq2DzAad0+Jn0suucRr48Ybb/TevXv7Qw89VKvtRFNaWlpn29q4caPn5OT4oUOH/OOPP/Y2bdpUuf1Ro0b5vHnzKpX/9re/9fvuu8/d3b/88ktv3LixFxcXu7t7nz59fMmSJe7uXlRU5N98801kvdWrV/uPfvQjP+OMM+rssRwLWOPKSp1tK2hWyhs6dKjPnDnT3d3ffPNN37t3r7u7L1q0yLt37x5ZbsWKFb527Vrv1KlThfU3bdrkW7Zs8T59+vjq1avr7LGUp5zEJyft2rXzTZs2ubv7U0895aNGjYr8fffdd7u7+5w5c/ymm25yd/c//OEPftttt7m7+xdffOFdu3b1srIyd3d/++23fefOnTE9nrgrK+6JlZXp06f7PffcU2n5PXv2eGZmpu/Zs8f37t3rmZmZkWOPu/tf//pXHzFiRKXjTV1RThIrJ1u3bvUuXbpEMvDFF1+4e+g9qVevXl5aWuqlpaXes2dPf/31172kpMTPO+883717t7u7T5gwIWbPV9CsqEcb+Prrr3nzzTeZOnUqc+fOrTBv8uTJkV6YiRMnArBt2zauuuoqcnNz6dq1K9u3b2f58uVcd911kfXGjRvHjBkzAGjdujW//vWv6d27N/PmzeO5556jW7du5ObmcsMNN3Dw4EGKiorIzMykpKQEgAMHDtC6devIdFUWLlzI8OHDOe2008jMzKRt27asWrUq8OM2M4qKinB3vv76a5o0aUKDBg3YtGkTpaWl9O/fH4AzzzyT008/HYCysjImTJjA5MmTA+8nlaRLVoqKili2bFmkR7tXr140btwYgJ49e1JQUBBZ9vLLL6dJkyaVtpGVlUWHDh2qezpTVqrnxMw4cOAAEPpmrEWLFpH1R40K3Uhv2LBhLF26FHdn06ZNXHnllQA0bdqURo0aRb7l6NmzJ82bN6/xc5wq0jUrx/Pqq6/Sv39/mjRpQuPGjenfvz+vvPJK5Ln6/e9/z89//vMoz2rqSdecPPfcc9xzzz2R95+mTZtGlj906BCHDx+muLiYkpISmjVrFmncfvPNN7g7Bw4ciJq5WFNDG1iwYAEDBgygffv2NGnShPfeew+AxYsXs2DBAt59913Wr1/PfffdB8Att9zCPffcw/r163nrrbcCvUk0bNiQlStXMnz4cIYOHcrq1atZv349WVlZTJ06lbPOOou+ffvy8ssvAzB37lxuuOEGTjnlFJ555hmeeeaZStssLCykVatWkemMjAwKCwur3P+DDz5ITk4O9957L8XFxUDon2zz5s20aNGC7OxsnnjiCU466SS2bt1Ko0aNGDp0KBdffDETJkygrKwMgD/84Q9cf/31afvGmA5ZgdBXlFdeeSVnn312pXlTp05l4MCBUR9HOkv1nDz//PNce+21ZGRkMGvWrMibe/n1GzRowDnnnMOePXvIzc1l4cKFlJaWsmPHDtauXctnn31Ww2c1NaVrVgD++te/kpOTw7BhwyJ5qG67v/jFL/jpT38a6fhJJ+mak61bt7J161YuvfRSevbsGfnQ9f3vf59+/frRvHlzmjdvzjXXXENWVhannHIKU6ZMITs7mxYtWrBp0ybuuOOOGj7bdUsNbULjeYYPHw7A8OHDmTNnDgB///vfGT16dOSfukmTJhQVFVFYWMiQIUOAUDCD/NPffPPNkb83bNjAZZddRnZ2NrNnz2bjxo0A3HnnnZFx0tOnT2f06NBdXceOHcvYsWMrbTP0zUVFZlapbNKkSWzZsoXVq1ezd+9efve73wGhnoMuXbqwc+dO1q1bx7hx4zhw4AClpaW88cYbPPbYY6xevZqPP/6YGTNmsHPnTubNm8f48eOjPt5UlepZKf84R4wYUan89ddfZ+rUqZEMSdVSPSePP/44ixYtoqCggNGjR/OTn/yk2vVvv/12MjIyyMvL47//+7/p1asXDRo0iPoY00G6ZuUHP/gB+fn5fPDBB1x11VWRb0KOt91169axbdu2yGNPN+mak9LSUj766COWL1/OnDlzuPPOO/nXv/7Ftm3b2Lx5MwUFBRQWFrJs2TL+8Y9/UFJSwpQpU3j//ffZuXMnOTk5TJo0Kepjj6W0P9Lt2bOHZcuWsWHDBsyMsrIyzIzJkyfj7pUCUVVoINR7c+TIkcj0oUOHKsw/44wzIn/fdtttLFiwgNzcXGbMmBE5MejSSy8lPz+fFStWUFZWFvVkj4yMjAq9QgUFBVV+RXL0k+xpp53G6NGjeeyxx4DQP8nEiRMxM9q2bUtmZiZbtmwhIyODiy++mDZt2gAwePBg3nnnHc4//3y2bdtG27ZtATh48CBt27atcNJCKkuHrBx9nKtWrWL+/PkVyj/44APuvPNOFi9ezLnnnlvt/tJZqudk9+7drF+/nh49egChN+cBAwZUWD8jI4PS0lL2799PkyZNMDMef/zxyDZ69epFu3btqq1LOkjnrJQ/htx1113cf//9ke2WP1m2oKCAvn378vbbb7N27Vpat25NaWkpX375JX379q2wbKpK55xkZGTQs2dPTjnlFDIzM+nQoUOk4d2zZ8/ISdQDBw7knXfe4Tvf+Q4AF154IQA33XQTjz76aLV1jLW079F+4YUXGDlyJJ988gn5+fl89tlnZGZmsnLlSq6++mqmTZvGwYMHAdi7dy9nn302GRkZLFiwAAidZX/w4EEuuOACNm3aRHFxMfv372fp0qXH3WdRURHNmzenpKSE2bNnV5g3cuRIRowYEfmUWJ3rr7+euXPnUlxczI4dO/joo4/o3r17peV27doFhP75FixYEPnH+N73vhep5xdffMGHH35ImzZt6NatG/v27WP37t0ALFu2jI4dOzJo0CA+//xz8vPzyc/P5/TTT0+bRjakR1YgdLWQ6667joYNG0bKPv30U4YOHcqsWbNo37591P2ls1TPSePGjdm/fz9bt24F4LXXXiMrKyuy/tGrRLzwwgtcccUVmBkHDx7km2++iSzfoEEDOnbsGOTpTGnpnJWj70sAL730UqT8mmuuYcmSJezbt499+/axZMkSrrnmGv7zP/+TnTt3kp+fz8qVK2nfvn1aNLIhvXMyePBgXn/9dQC++uortm7dSps2bfje977HihUrKC0tpaSkhBUrVpCVlUXLli3ZtGlTpP1SfltxE+SMyWT4OdGzefv06eOLFy+uUPbEE0/42LFj3d190qRJnpWV5bm5uf6zn/3M3UNnwfbr18+zs7O9a9euvn37dncPnd3avn17HzRokA8ZMsSnT5/u7u4XXHBB5AxYd/enn37aW7du7X369PFx48ZFzq51d9+1a5c3bNjQ9+3bFymbMmWKT5kypcr6P/LII96mTRtv3769L1q0KFI+cOBALywsdHf3fv36eefOnb1Tp05+yy23eFFRkbu7FxYWev/+/SPzZs2aFVl/yZIlnp2d7Z07d/ZRo0ZFrkZSXrpddSQdsnK8x3nHHXd4o0aNPDc313Nzc738czh8+HA///zzvUGDBt6yZUt//vnn3d39xRdf9JYtW/qpp57qTZs29auvvrr6J/gEKCch9Z2TF1980Tt37uw5OTnep0+fSH2//fZbHzZsmF944YXerVu3SPmOHTu8ffv2ftFFF/mVV17p+fn5ke1OmDDBW7Zs6WbmLVu2jPsVAk7kR1mpeVYmTpzoHTt29JycHO/bt69v3rw5sv7UqVP9wgsv9AsvvNCnTZtWab87duxIq6uOpHNOjhw54vfee69nZWV5586dfc6cOe4eujLKmDFj/KKLLvKsrCy/9957K9Tloosu8uzsbL/uuuv8q6++Cv5k10DQrFho2eSXl5fnqXCt3hdeeIGFCxcya9aseFclrsxsrbvnxWLbykrqUE6iU05ClJXolBXlJAjlJCRoVuI6RtvMOgB/LlfUBvgl0Ai4C9gdLn/A3RfVc/Xq3fjx41m8eDGLFqX8Q60xZaUiZaVqyklFysnxKSsVKStVU04qUk5qLmF6tM3sZKAQ6AGMBr5298eCrp8qnxQlpLpPisqKHKWcSFDKigShnEhQQXu0E+lkyCuB7e7+SbwrIglPWZEglBMJSlmRIJQTqbFEamgPB+aUmx5nZh+Y2TQzaxyvSklCUlYkCOVEglJWJAjlRGosIa6jbWanAtcDPwsXTQF+A3j49/8L3F7FemOAMQDNmjWrdKmffxbur7Sv7Jbn1F3Fpd4pKxJErHIiqUdZkSCUEzlRCTFG28x+CNzj7ldXMa818Dd3r/aq6FWNfWo98eVKy+U/Oqg2VZV6cryxT8qKlFffOZHkpaxIEMqJBJVsY7RHUO7rGDNrXm7eEGBDvddIEpWyIkEoJxKUsiJBKCdyQuI+dMTMTgf6A3eXK55sZl0IfSWTf8w8SVPKigShnEhQyooEoZxIbcS9oe3uB4Fzjym7NU7VkQSmrEgQyokEpaxIEMqJ1EbgoSNmdpaZNTMzi2WFRERERERSQbUNbTM72cweMrNPgH8BO4FvzexNM7uyXmooIiIiIpKEog0deQK4BJhIqFE+HpgP7AOmm9l97j43tlUUEREREUk+0RraI4D27r4HwMyWAivdva2ZfQBMB9TQFhERERE5RrQx2oeA0nLTpUBDAHd/B2gVo3qJiIiIiCS1aD3afwFeMrMnAQP+H+BFiFxDcndsqyciIiIikpyiNbTvJ3S70YmEGtqLgd+G5xkwMnZVExERERFJXtU2tN39MPBw+OfYeTsJXYVERERERESOccK3YLeQy+uyMiIiIiIiqeKEG9rAqcDrdVUREREREZFUUu3QETOrbgz2qXVcFxERERGRlBHtZMjpwFqguIp5uhW7iIiIiMhxRGtofwTc7+6VhoiYWUPgYExqJSIiIiKS5KKN0V4BXHSceWXh+SIiIiIicoxol/e7u5p5JUC/Oq+RiIiIiEgKiDZ0JObMLB8oItRDXurueWbWBPgz0BrIB25y933xqqMkBmVFglBOJChlRYJQTqQ2qh06YmYdzOyectOvmNmycj8d6qge/dy9i7vnhacnAkvdvR2wNDwtAsqKBKOcSFDKigShnMgJiTZG+37g63LTvYDZ4Z+NxC5YPwRmhv+eCQyO0X4k+SkrEoRyIkEpKxKEciKBRGtoXw7MLzdd5u5T3X0q8ADQuw7q4MASM1trZmPCZc3cfRdA+HfTOtiPJD9lRYJQTiQoZUWCUE7khEUbo93U3Q+Um47cwMbdi8ysWR3U4VJ332lmTYHXzGxL0BXDgR8D0KxZM5YvX15h/k+zSyutc3SZfxburzQvu+U5wWsdwPH2UdNyiaj3rCTqa5Ko9UoQMcuJnveUE7OsSEpRTuSEmbsff6ZZIaGA5Vcxrw2w0t1b1FllzH5FaKjKXUBfd99lZs2B5e5e7XjwvLw8X7NmTYWy1hNfrrRc/qODos6rK8fbR03L05GZrS03Fq6q+b+iHrKSqK9JotarviVKTiTx1XdWJDkpJxJUtKwcFW3oyMvAb44z7+Hw/BNmZmeY2VlH/wauBjYALwGjwouNAhbWZj+S/JSV2mk98eVKP6lIOZGglBUJQjmR2oo2dOSXwFtm9j6hsdqfA80JDfpvDPSs5f6bAfPN7Ghd/sfdXzGz1cBfzOwO4FPgxlruR5KfsiJBKCcSlLIiQSgnUivRbljzuZnlAT8BBgLfBfYAi4Dfu/ue2uzc3T8Gcqso3wNcWZttS2pRViQI5USCUlYkCOVEaivqDWvcfS/w8/CPHCPeYzaTbWyxVBbP10o5SW16fUVE4qvahraZnQPkuvs/wtMPHLPO/9adkEREREREKovWo/2/gFLgH+HpB/j3dbUzgVOAX8SmaiIiIiIiyStaQ3sIMKDcdIm73wpgZhmExmqroZ1E9FWyiFRHw9Hqhp4vEYHol/dr4e4F5aafPfpHuDwjJrUSEREREUlyUU+GNLPz3H03gLvfX748lhUTEZFg1HsqIpKYojW03wRGA5OrmDcaeLvOa5Sg9EZWe6n0HNbHXUfj/XzFe/8iIiLJLlpD+2HgdTNrAbzIv29YMxS4HbgittUTERGRRKMP4iLBRGtov0fodqOTgXGExnQfAd4FBrj76thWT0RqQm9+IiIiiSNaQ7sQmAX8GNhO6Lbr+9z9YKwrJv+mxpOIiIhI8onW0B4L/AhYBWwGZgD/A6ihLSKSpOryw7s6AkREjq/ay/u5+0J3v5HQuOw/AjcBBWb2kpndYGan1EclRURERESSTdTL+wG4+78INbT/aGaZwK3A4+Gy78auelJf1CslUju60YskM+VUJDYCNbSPMrPTgG5AD6AZ8FYsKiUiIiLJRw12kYoCNbTNrDcwktDQkS8JnyDp7p/UZudm1gr4E3A+oauZPOvuT5jZr4C7gN3hRR9w90W12ZckN2UlcSTyG6lykjgSOSegrEgwyonUVrUN7XCQbgWaAPOAQe7+Zh3uvxT4qbu/Z2ZnAWvN7LXwvMfd/bE63Jckt6TPSqI3PFJE0udE6o2yEoCOW8qJ1E60Hu2ewIPAAnc/VNc7d/ddwK7w30VmthloWdf7keSnrEgQyokEpaxIEMqJ1Fa1DW13H1BfFTGz1sDFhG6GcykwzsxGAmsIfZrcV191kcSmrEgQqZgT9S7GRipmReqecnJix6B0P26Zu8e7DpjZmcAK4Lfu/qKZNQO+Ahz4DdDc3W+vYr0xwBiAZs2aXTJ37twK8/9ZuL/SvrJbnlPtvLoqT4d91FRNttOvX7+17p53bHl9ZyXZXpN47qMuBd1HouSkunl1+Twm4usez5zURCJlJRGl6uteU/Wdk2RTl8etZHe8rBwr7g3t8LW4/wa86u6/r2J+a+Bv7t65uu3k5eX5mjVrKpRV9ymqppfiOpFLd6X6PmqqJtsxs0oBjkdWku01iec+6lLQfSRKTqqbV5fPYyK+7slyWcNEykq8pOPrXlP1nZNkox7tf6sqK1Wp0eX96pqZGTAV2Fw+vGbWPDwuCmAIsCEe9ZPEoaxIEMqJBKWs1L9kbHDFOifJ+JxIzcS1oU1ojNOtwD/NbF247AFghJl1IfSVTD5wd3yqJ9Wp5wOEsiJBKCcSVFyykkjfCEkgOqZIrcS1oe3uKwGrYpauRSkVKCsShHIiQSkrEoRyIrUV7x5tERGRtJfOvdDp/NjTWbq87mpoS51Ll38ekVjQ/4+ISOpQQ1tEREREIvSBv+6ooS0iIiIiJ0wN8+NTQ1tE6oQOtCKxkarXrBZJB2poi4iIiEhCSLUPkGpoi4hIUkq1N2SRIOoy9/ofir2T4l0BEREREZFUpB5tERERkSSn3unEpIa2iIiISIpSAzy+1NAWkZiq7iCvN4D0pNddJDr9n6QGNbRFRCShqcEhtaUMJb9kfQ11MqSIiIiISAyoR1tEREQSTrL2YEryikXm1NAWEZGEoIaViKSahB06YmYDzOxDM9tmZhPjXR9JXMqKBKWsSBDKiQSlrEg0CdmjbWYnA08B/YECYLWZveTum+JbM0k0yooEpaxIEMpJ4kuUKxkpK4kjkb8NS8iGNtAd2ObuHwOY2Vzgh4DCK8dSViQoZUWCUE4kKGUlSdVnwzxRG9otgc/KTRcAPeJUF0lsyooEpaxIEMqJBKWsJLhE6Ok2d6/XHQZhZjcC17j7neHpW4Hu7j7+mOXGAGPCkx2AD+u1ohJLF7j7edEWUlbSXqCcQLCsKCcpTccUCULHFAkqUFYStUe7AGhVbjoD2HnsQu7+LPBsfVVKEpKyIkFFzYpyIuiYIsHpmCJRJepVR1YD7cws08xOBYYDL8W5TpKYlBUJSlmRIJQTCUpZkagSskfb3UvNbBzwKnAyMM3dN8a5WpKAlBUJSlmRIJQTCUpZkSAScoy2iIiIiEiyS9ShIyIiIiIiSU0NbRERERGRGFBDW0REREQkBtTQFhERERGJATW0RURERERiQA1tEREREZEYUENbRERERCQG1NAWEREREYmB/x+QJifzKxuerwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 32\n",
    "identifieer = 'LRS'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 128\n",
    "identifieer = 'LRS'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "batch_size = 512\n",
    "identifieer = 'LRS'\n",
    "cols = ['{} Filtersize'.format(col) for col in reversed(['Full','Halfed', 'Quartered', 'Eigth', 'Sixteenth'])]\n",
    "rows = ['{}'.format(row) for row in ['VGG11', 'VGG13', 'VGG16', 'VGG19']]\n",
    "\n",
    "fig, axes = plt.subplots(nrows=4, ncols=5, figsize=(12, 8))\n",
    "for ax, col in zip(axes[0], cols):\n",
    "    ax.set_title(col)\n",
    "\n",
    "for ax, row in zip(axes[:,0], rows):\n",
    "    ax.set_ylabel(row, rotation='vertical', size='large')\n",
    "\n",
    "    \n",
    "\n",
    "#fig.tight_layout()\n",
    "for i,net in enumerate([11, 13, 16, 19]):\n",
    "    for j,filterstack in enumerate(reversed(['', '_S', '_XS', '_XXS', '_XXXS'])):\n",
    "        filename = join('.','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "        #print(filename)\n",
    "        df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "        plot_saturation_level_ax(df, axes[i][j], acc)\n",
    "plt.show()\n",
    "#plt.savefig('collage_cifar.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7229 47.221111111111114\n"
     ]
    }
   ],
   "source": [
    "net = \"11\"\n",
    "batch_size=512\n",
    "identifieer = 'ADAM1'\n",
    "filterstack=\"_XXS\"\n",
    "\n",
    "filename = join('C:\\\\','Users','Mats Richter','Documents','delve','delve-deep-dive','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "plot_saturation_level(df, 'VGG-Network with too low learning rate')\n",
    "print(acc, np.mean(df.values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7162 47.22333333333333\n"
     ]
    }
   ],
   "source": [
    "net = \"11\"\n",
    "batch_size=512\n",
    "identifieer = 'ADAM'\n",
    "filterstack=\"_XXS\"\n",
    "\n",
    "filename = join('C:\\\\','Users','Mats Richter','Documents','delve','delve-deep-dive','logs','VGG{}{}'.format(net, filterstack),'Cifar10','VGG{}{}_bs{}_e20_id{}.csv'.format(net, filterstack, batch_size, identifieer))\n",
    "df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "plot_saturation_level(df, 'VGG-Network with too low learning rate')\n",
    "print(acc, np.mean(df.values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "invalid literal for int() with base 10: 'saturation_conv1'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-73-df7aa1b91f15>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0midentifier\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'ADAM'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mfilename\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mjoin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'.'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'logs'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'ResNet{}'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnet\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'Cifar10'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'ResNet{}_bs{}_e20_id{}.csv'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnet\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0midentifier\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0macc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mextract_layer_saturation\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msep\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m';'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mepoch\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m19\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0macc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[0mplot_saturation_level\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'ResNet-Network with too low learning rate'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-53-be36cf661c22>\u001b[0m in \u001b[0;36mextract_layer_saturation\u001b[1;34m(df, excluded, epoch)\u001b[0m\n\u001b[0;32m      9\u001b[0m     \u001b[1;31m#print(cols)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m     \u001b[0mtrain_cols\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mcol\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mcol\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcols\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;34m'train'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcol\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mexcluded\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcol\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;34m'accuracy'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcol\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;34m'loss'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcol\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 11\u001b[1;33m     \u001b[0mtrain_cols\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0morder_columns\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtrain_cols\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     12\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     13\u001b[0m     \u001b[1;31m#print(list(train_cols))\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-53-be36cf661c22>\u001b[0m in \u001b[0;36morder_columns\u001b[1;34m(column_names)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0morder_columns\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn_names\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m     \u001b[0mcolumn_names\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn_names\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m100\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;34m'classifier'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32melse\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m     \u001b[0mcolumn_names\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mcolumn_names\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-53-be36cf661c22>\u001b[0m in \u001b[0;36m<lambda>\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0morder_columns\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn_names\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m     \u001b[0mcolumn_names\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn_names\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m100\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;34m'classifier'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32melse\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m     \u001b[0mcolumn_names\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mcolumn_names\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: invalid literal for int() with base 10: 'saturation_conv1'"
     ]
    }
   ],
   "source": [
    "net = 34\n",
    "batch_size=512\n",
    "identifier = 'ADAM'\n",
    "filename = join('.','logs','ResNet{}'.format(net),'Cifar10','ResNet{}_bs{}_e20_id{}.csv'.format(net, batch_size, identifier))\n",
    "df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "print(acc)\n",
    "plot_saturation_level(df, 'ResNet-Network with too low learning rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "invalid literal for int() with base 10: 'saturation_conv1'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-80-67bfc7397c9f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0midentifier\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'ADAM'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mfilename\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mjoin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'..'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'Documents'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'delve'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'delve-deep-dive'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'logs'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'ResNet{}'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnet\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'Cifar10'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'ResNet{}_bs{}_e20_id{}.csv'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnet\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0midentifier\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0macc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mextract_layer_saturation\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msep\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m';'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mepoch\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m19\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0macc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[0mplot_saturation_level\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'ResNet-Network with too low learning rate'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-53-be36cf661c22>\u001b[0m in \u001b[0;36mextract_layer_saturation\u001b[1;34m(df, excluded, epoch)\u001b[0m\n\u001b[0;32m      9\u001b[0m     \u001b[1;31m#print(cols)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m     \u001b[0mtrain_cols\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mcol\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mcol\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcols\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;34m'train'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcol\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mexcluded\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcol\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;34m'accuracy'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcol\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;34m'loss'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcol\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 11\u001b[1;33m     \u001b[0mtrain_cols\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0morder_columns\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtrain_cols\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     12\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     13\u001b[0m     \u001b[1;31m#print(list(train_cols))\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-53-be36cf661c22>\u001b[0m in \u001b[0;36morder_columns\u001b[1;34m(column_names)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0morder_columns\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn_names\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m     \u001b[0mcolumn_names\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn_names\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m100\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;34m'classifier'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32melse\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m     \u001b[0mcolumn_names\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mcolumn_names\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-53-be36cf661c22>\u001b[0m in \u001b[0;36m<lambda>\u001b[1;34m(x)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0morder_columns\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn_names\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m     \u001b[0mcolumn_names\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumn_names\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m100\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;34m'classifier'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32melse\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'-'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m     \u001b[0mcolumn_names\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mcolumn_names\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: invalid literal for int() with base 10: 'saturation_conv1'"
     ]
    }
   ],
   "source": [
    "net = 18\n",
    "batch_size=128\n",
    "identifier = 'ADAM'\n",
    "filename = join('..', 'Documents', 'delve', 'delve-deep-dive','logs','ResNet{}'.format(net),'Cifar10','ResNet{}_bs{}_e20_id{}.csv'.format(net, batch_size, identifier))\n",
    "df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "print(acc)\n",
    "plot_saturation_level(df, 'ResNet-Network with too low learning rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "net = 18\n",
    "batch_size=128\n",
    "identifier = 'ADAMHIGHREZ'\n",
    "filename = join('..', 'Documents', 'delve', 'delve-deep-dive','logs','ResNet{}'.format(net),'Cifar10','ResNet{}_bs{}_e20_id{}.csv'.format(net, batch_size, identifier))\n",
    "df, acc = extract_layer_saturation(pd.read_csv(filename, sep=';'), epoch=19)\n",
    "print(acc)\n",
    "plot_saturation_level(df, 'ResNet-Network with too low learning rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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