WeightWatcher-SVDSharpness-VGG11.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# WeightWatcher - SVDSharpness\n",
    "\n",
    "### Example with the VGG11 model \n",
    "\n",
    "Compare the original (red) vs. smoothed (blue) ESDs\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-05T23:51:16.544327Z",
     "start_time": "2019-03-05T23:51:16.531457Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Suppress the powerlaw package warnings\n",
    "# \"powerlaw.py:700: RuntimeWarning: divide by zero encountered in true_divide\"\n",
    "# \"powerlaw.py:700: RuntimeWarning: invalid value encountered in true_divide\"\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=RuntimeWarning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import tensorflow\n",
    "import torchvision.models as models\n",
    "from tqdm import tqdm\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-06T00:16:43.249725Z",
     "start_time": "2019-03-06T00:16:43.240611Z"
    }
   },
   "source": [
    "### Import WeightWatcher\n",
    "\n",
    "set custom Logging at WARN Level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import logging\n",
    "logging.basicConfig(level=logging.WARNING)\n",
    "logger = logging.getLogger(__name__)\n",
    "logger.setLevel(logging.WARNING)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.5'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import weightwatcher as ww\n",
    "logger = logging.getLogger(ww.__name__)\n",
    "logger.setLevel(logging.WARNING)\n",
    "\n",
    "ww.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### PyTorch Example\n",
    "\n",
    "VGG16 has 16 layers\n",
    "\n",
    "- The last 3 are dense"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Assuming nested distributions\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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HP/gBq1atYo899uC0005j+PDhPP/88wwcOJC1a9cC8PWvf5099tiDQw45hEmTJjFjxgwAJk+e3HT7/8CBA5k6dWrTMLnLly8HSg/Fa3WsJX3Fq13X/dFtK7iEXmDJkiVcf/31PPjgg0QEBxxwAIcddhgrVqzgpz/9KQceeOBm6RctWsSdd97Jo48+ysaNGxk9ejT77rtv0W336dOHhx9+mCuvvJIZM2ZwzTXXlByK18ysuRzQCyxYsIDjjz++aUTEE044gQceeIDdd999i2AO8Mc//pHjjjuO7t270717dz784Q+X3PYJJ5wAJEPh/vKXvwRKD8VrZtZcrnKpUnbI263VOBxu165dtxiK9/HHH+fXv/5109C5ZmbN5YBe4NBDD+Wuu+5iw4YNvP7668ycOZNDDz20ZPqxY8c2BeL169c3u1dKqaF4zcyaq66rXGrZzbBao0ePZvLkyey///4AnHXWWey8884l0++3335MnDiRvffem3e/+92MGDGCnj17Vr2/Cy64gNNPP51vfOMbfOhDH2px/s2s86rrgN5ezj//fM4///zN5j3++OObTTc+jg7gS1/6EtOmTWPDhg2MGzeuqVE0W+LOph8zZgzz5s0D4KCDDuLpp59uWvaNb3wDgPHjx2/2JCQzs0oqVrlIuk7SakmPl1guSf8raaWkpZJG1z6b9W3KlCmMHDmS0aNH89GPfpTRozvdKTCzOlBNCf0G4HLgxhLLjwEGp68DgB+lfzuNW265pb2zYHlV6YEWnemBF1ZRxRJ6RMwH/lYmyXHAjZFYCPSS9N5aZdDMzKpTi14u/YDnM9MN6bwtSJoiabGkxWvWrKnBrs3MrFGbdluMiKsiYkxEjOnbt29b7trMLPdqEdBfAHbLTPdP55mZWRuqRbfFWcB5km4jaQx9LSJeqsF2a9/Q0w4NRwMHDmTx4sX06dOnzfdtZp1LxYAu6VZgPNBHUgMwFegGEBE/BmYDxwIrgQ3AJ1srs22tcajcLl18Q62Z1b9qerlMioj3RkS3iOgfEddGxI/TYE7au+XciPi3iBgREYtbP9utp3Co3DPPPJMxY8YwbNgwpk6d2pSu1HC469at46ijjmLYsGGcddZZRLxzt2vhsLyN+xs6dCiTJ09myJAhnHzyycyZM4exY8cyePBgHnrooTY9fjPruFz0LGLFihV85jOfYdmyZXz3u99l8eLFLF26lPvvv5+lS5c2pWscDvecc85pGgN9+vTpHHLIISxbtozjjz+ev/zlL8Dmw/IuXLiQq6++mj/96U8ArFy5ki9+8YssX76c5cuXc8stt7BgwQJmzJjBt771rbY/AbZ1Cscwd99wa2MO6EVkh8q9/fbbGT16NKNGjWLZsmU88cQTTemyw+E23to/f/58TjnlFAA+9KEPNY0Dkx2Wt0ePHk3D8gIMGjSIESNG0KVLF4YNG8aECROQxIgRIzYbMsDMrByP5VJE41C5zz77LDNmzGDRokXsvPPOTJ48ebPhbYsNh7s1GrcD0KVLl6bpLl26tGi7Zta5uIRext///nd22GEHevbsycsvv8w999xTcZ1x48Y1DQVwzz338MorrwDNH5bXzKy56ruE3s51kPvssw+jRo1i6NCh7LbbbowdO7biOlOnTmXSpEkMGzaMgw8+mAEDBgDFh+UdNWqUq1TMrGbqO6C3g4EDB242VG6ph06UGg63d+/e3HfffUXXKTYsb7n9FS4zMyvHVS5mZjnhgG5mlhN1V+USEUhq72x0eNkbmqyCrR1TvJr1SqWp9TjmpbZvnUpdldC7d+/OunXrHIxaKCJYt24d3bt3b++smFkbqqsSev/+/WloaMBjpbdc9+7d6d+/f3tnw8zaUF0F9G7dujFo0KD2zoaZWYdUV1UuZma29RzQzcxywgHdzCwnHNDNzHKirhpFzepKtX3FW9IHfGv7i7ufuRXhErqZWU44oJuZ5YQDuplZTjigm5nlhAO6mVlOOKCbmeWEuy2a5VGxbo3u6ph7LqGbmeWEA7qZWU44oJuZ5URVAV3S0ZKekrRS0oVFlg+QNFfSnyQtlXRs7bNqZmblVAzokroCVwDHAHsBkyTtVZDsa8DtETEKOAm4stYZNTOz8qopoe8PrIyIZyLiLeA24LiCNAHslL7vCbxYuyyamVk1qgno/YDnM9MN6bysacApkhqA2cBni21I0hRJiyUt9nNDzcxqq1b90CcBN0TEdyUdBNwkaXhE/CubKCKuAq4CGDNmTNRo39aZVDukbbH1tnbdWmjpPt2H3KpQTQn9BWC3zHT/dF7WmcDtABHx/4DuQJ9aZNDMzKpTTUBfBAyWNEjStiSNnrMK0vwFmAAgaU+SgO46FTOzNlQxoEfEJuA84F7gSZLeLMskXSppYprsi8DZkh4FbgUmR4SrVMzM2lBVdegRMZuksTM775LM+yeAsbXNmpmZNYfvFDUzywkHdDOznHBANzPLCY+Hbp1HtX25C9O1Z/91s2ZwCd3MLCcc0M3McsIB3cwsJ1yHbnVF09X0Pqb63jSz5nAJ3cwsJxzQzcxywgHdzCwnXIdu+VDYV7w1+oy7H7rVOQd0K8qNk2Ydj6tczMxywgHdzCwnHNDNzHLCAd3MLCcc0M3McsIB3cwsJ9xt0erS1LlATGvbscjdz9w6OJfQzcxywgHdzCwnHNDNzHLCAd3MLCcc0M3McsIB3cwsJxzQzcxyoqp+6JKOBn4IdAWuiYjLiqQ5EZgGBPBoRHyihvm0ZsoOfwu1GwK3cLvFbNW+GvuAV9588fVKTduW2rJvv7WpigFdUlfgCuBIoAFYJGlWRDyRSTMY+AowNiJekbRra2XYzMyKq6bKZX9gZUQ8ExFvAbcBxxWkORu4IiJeAYiI1bXNppmZVVJNQO8HPJ+ZbkjnZQ0Bhkj6o6SFaRXNFiRNkbRY0uI1a9ZsXY7NzKyoWjWKbgMMBsYDk4CrJfUqTBQRV0XEmIgY07dv3xrt2szMoLpG0ReA3TLT/dN5WQ3AgxGxEXhW0tMkAX5RTXJpHVapRtS2fE7ptHnT33k/fmqb7desrVVTQl8EDJY0SNK2wEnArII0d5GUzpHUh6QK5pnaZdPMzCqpGNAjYhNwHnAv8CRwe0Qsk3SppIlpsnuBdZKeAOYCX46Ida2VaTMz21JV/dAjYjYwu2DeJZn3AZyfvswqc19os5rznaJmZjnhgG5mlhN+BJ21i8aeJ9OnT29Rj5dSPViy8806C5fQzcxywgHdzCwnHNDNzHLCAd3MLCfcKNoBZW+nr7ZBsZp1qhnrvFmmTWPqPJh+eA02VdDIOX16Mu0b+c3e4RK6mVlOOKCbmeWEA7qZWU44oJuZ5YQbRetYcxsy23KM8bYwbd70Nm38rOauU4+nbvXMJXQzs5xwQDczywlXuVibmTq3cp/0qXPLT1sLFI49X2naOhyX0M3McsIl9E6u5neHbmUeps5r+XbaeshcN5ZavXEJ3cwsJxzQzcxywgHdzCwnHNDNzHLCjaLtpD3v8GzthtDG7deiobO9+Jmk1hE5oFuzNfYNL9WnvFzf8Vr1K3f/dLMtucrFzCwnHNDNzHLCAd3MLCeqqkOXdDTwQ6ArcE1EXFYi3UeBO4D9ImJxzXJp7XpHZz3cTdpa2qvxs7l3mbZ2esuHiiV0SV2BK4BjgL2ASZL2KpJuR+DzwIO1zqSZmVVWTZXL/sDKiHgmIt4CbgOOK5Lu68C3gTdrmD8zM6tSNQG9H/B8ZrohnddE0mhgt4j4TQ3zZmZmzdDifuiSugDfAyZXkXYKMAVgwIABLd21tbNq+4K3Rb90q4HG8dA9LnqHVU1AfwHYLTPdP53XaEdgODBPEsB7gFmSJhY2jEbEVcBVAGPGjMnXAzBLaMs7QvPceNmRtKSh1Y2Z1hLVVLksAgZLGiRpW+AkYFbjwoh4LSL6RMTAiBgILAS2COZmZta6Kgb0iNgEnAfcCzwJ3B4RyyRdKmlia2fQzMyqU1UdekTMBmYXzLukRNrxLc+WmZk1l+8UNTPLCY+22Aqa2zjpxsy209I7Q0utX6uGULOWcAndzCwnXEK3JoV9wkuNd25m9ckldDOznHBANzPLCVe5VKGauz3dsGltpV7uJm3P5+JacS6hm5nlhAO6mVlOOKCbmeWEA7qZWU50+kbRljTs+I5Qa2/VNJA2uxF12rTN15kXTfM3+1sFN5y2LZfQzcxywgHdzCwnHNDNzHLCAd3MLCc6faOoWb1q7WF16+WOU6sdl9DNzHLCAd3MLCdc5ZJzjWOcFxvbvHD880rrVkpvOdWMfufWvlxCNzPLiU5TQvcda5Z31TSitlZDq/+/6oNL6GZmOeGAbmaWEw7oZmY54YBuZpYTnaZRtBp+dqh1VuUaSwuXTZ9evmHV/yPtp6qALulo4IdAV+CaiLisYPn5wFnAJmANcEZEPFfjvFoNbE1fcvc/N+sYKla5SOoKXAEcA+wFTJK0V0GyPwFjImJv4A7gf2qdUTMzK6+aOvT9gZUR8UxEvAXcBhyXTRARcyNiQzq5EOhf22yamVkl1QT0fsDzmemGdF4pZwL3tCRTZmbWfDVtFJV0CjAGOKzE8inAFIABAwbUctc154Yds9ry3aStr5oS+gvAbpnp/um8zUg6AvgqMDEi/llsQxFxVUSMiYgxffv23Zr8mplZCdUE9EXAYEmDJG0LnATMyiaQNAr4CUkwX137bJqZWSUVA3pEbALOA+4FngRuj4hlki6VNDFN9h2gB/ALSY9ImlVic2Zm1kqqqkOPiNnA7IJ5l2TeH1HjfFmNuS+5Wf75TlEzq3tuUK2Ox3IxM8sJB3Qzs5xwQDczywkHdDOznMhdo6jv8DTrWEo1eM5bdT8Ahxf8T7uBtDSX0M3MciJ3JfTOorFf+fTDy0+btbbCz561H5fQzcxywgHdzCwnHNDNzHKiU9ahuyeMWfvy/2DrcAndzCwnHNDNzHLCAd3MLCc6ZR16R1DYj9x9fK1elLrHYercyvdB+HPcujp8QHfjill+ZP+f5/arzXaaOzxARx5awFUuZmY54YBuZpYTDuhmZjnhgG5mlhMdslHUDaFmBs2PBR25wbMaLqGbmeVEhyyhd2aF/XsrTZu1pUqfv2rvr5g6Fwb+O6zqVZNsdRouoZuZ5YQDuplZTrjKxcxyrVTDaTUNqoVpWnLXaUu2Uy2X0M3McqKqgC7paElPSVop6cIiy7eT9PN0+YOSBtY8p2ZmVlbFgC6pK3AFcAywFzBJ0l4Fyc4EXomIDwDfB75d64yamVl51ZTQ9wdWRsQzEfEWcBtwXEGa44Cfpu/vACZI8t0/ZmZtSBHlK+clfQw4OiLOSqdPBQ6IiPMyaR5P0zSk039O06wt2NYUYEo6uQfwVAvz3wdYWzFVffMx1AcfQ33IwzFA6x7H7hHRt9iCNu3lEhFXAVfVanuSFkfEmFptrz34GOqDj6E+5OEYoP2Oo5oqlxeA3TLT/dN5RdNI2gboCayrRQbNzKw61QT0RcBgSYMkbQucBMwqSDMLOD19/zHgD1GpLsfMzGqqYpVLRGySdB5wL9AVuC4ilkm6FFgcEbOAa4GbJK0E/kYS9NtCzapv2pGPoT74GOpDHo4B2uk4KjaKmplZx+A7Rc3McsIB3cwsJzpUQJf0HUnLJS2VNFNSrxLpVkl6TNIjkha3cTbLasYxlB1uoT1J+g9JyyT9S1LJrll1fh2qPYZ6vg67SPqdpBXp351LpHs7vQaPSCrs0NAu8jCcSBXHMFnSmsy5P6vVMxURHeYFHAVsk77/NvDtEulWAX3aO79bewwkjc9/Bt4PbAs8CuzV3nnP5G9PkhvD5gFjyqSr5+tQ8Rg6wHX4H+DC9P2FZf4f1rd3Xpt7XoHPAD9O358E/Ly9870VxzAZuLwt89WhSugRcV9EbEonF5L0ie9QqjyGaoZbaDcR8WREtPQu33ZV5THU9XVg8yE3fgp8pP2y0ix5GE6kLj8bHSqgFzgDuKfEsgDuk7QkHW6gXpU6hn7A85nphnReR9NRrkMp9X4d3h0RL6Xv/wq8u0S67pIWS1oo6SNtk7WyqjmvTWnSAtBrQO82yV11qv1sfDStXr1D0m5FltdU3T3gQtIc4D1FFn01In6VpvkqsAm4ucRmDomIFyTtCvxO0vKImN86Od5SjY6hXVVzDFWo++tQ78odQ3YiIkJSqT7Iu6fX4f3AHyQ9FhF/rnVebQu/Bm6NiH9K+hTJL44PtuYO6y6gR8QR5ZZLmgz8OzAh0oqqItt4If27WtJMkp9HbRZIanAM1Qy30KoqHUOV26jr61CFur4Okl6W9N6IeEnSe4HVJbbReB2ekTQPGEVS/9temjOcSEOdDidS8RgiIpvfa0jaPFpVh6pykXQ0cAEwMSI2lEizg6QdG9+TNEI+3na5LK+aY6C64RbqWr1fhyrV+3XIDrlxOrDFrw5JO0vaLn3fBxgLPNFmOSwuD8OJVDyG9Eu20UTgyVbPVXu3FjezZXklSb3VI+mrsRX8fcDs9P37SVqcHwWWkfy8bve8N+cY0uljgadJSlL1dgzHk9QZ/hN4Gbi3A16HisfQAa5Db+D3wApgDrBLOn8McE36/mDgsfQ6PAac2d75LnVegUtJCjoA3YFfpP8vDwHvb+88b8Ux/Hf62X8UmAsMbe08+dZ/M7Oc6FBVLmZmVpoDuplZTjigm5nlhAO6mVlOOKCbmeWEA7qZWU44oJuZ5YQDujWRtL5G27lO0mpJjxfMrzi2eMHY3Y9k00n6v7XIX0vU6hyV2f67JN0vqWs6PUHSz1pxfyMkPSfpnMy8bSXNT2+5tw7EAd1aww3A0dkZaYC6AjgG2AuYJGmvIuu+EREjM6/LGhdExMGtmOd6cQbwy4h4O53eh+SO4lYREY+R3LZ+WmbeWyR3oH68tfZrrcMB3cqSdL6kx9PXf2bmX5yWthdIulXSlxqXRTKi4t8KNtXi8aOzpeNS+5d0iqSH0tL9TyR1lTRQ0pOSrlbylKL70pLwZZLOzWxzWmY7d6XD/i4rNvRvus3HM9NfkjQtM10sHztI+o2kR9PzWSxgnszmY7LsQ3LrOJKGSvpDus056dgsSNozLVEvlfRlSSubc15JBvUaVjDvrjQv1oE4oFtJkvYFPgkcABwInC1plKT9gI+SBJtjSMYOqaTa8aPfVVDlskXQK7V/SXuSlCrHRsRI4G3eCUqDgSsiYhjwarr+z4ETM5s+MZ0HcEZE7Jtu+3OSqh6Lu0w+jgZejIh9ImI48NuC9bYlGbNkVWb2PsAj6QBbdwLnp9v8HfCFtFrkZuDzEbE3yRg6zR0E7TJgO0m7Z+Y9DuzXzO1YO3MdmZVzCDAzIl4HkPRL4FCSgsCvIuJN4E1Jv67hPt9IA1Y5Y0vsfwKwL7BIycNt3kVS+pwPPBsRj6TplgADI+JnknaV9D6gL/BKRDR+6XxO0vHp+91IvhCqHb61VD5uAb4r6dvA3RHxQMF6fUi+bACQ1A3oGRFr0i+2BZljeIJkBL8TgEcj4k+Z+auVjH3+1XT9j6Xb2wG4EngLmBcRN0s6BtgB+A1JKf05gIh4W9JbknaMiH9UedzWzhzQra20xdjiAn4aEV/ZbGbygOF/Zma9TRJkIRnR72MkD5H4eZp+PHAEcFBEbFAyhnj3gn1tYvNfuNnlRfORbns0ySh935D0+4i4NLP4jYLt7Mk7Q67uRTJaYqMRJMF7bzavYx8O/DYingHOlHRHZtkJwB0R8WslD2C+k+S5thNJfokNB2Zn0m8HvFl4DFa/XOVi5TwAfETS9mnp7vh03h+BD0vqLqkHycM6Kqnl2OKl9v974GNKnpCEpF0KqhGK+Xmal4+RBHdIHqbwShrMh5JUNxV6GdhVUu+0OiR7DormI/0lsCEifgZ8Bxid3WBEvAJ0ldQY1Jvqz0m+/PZKt/d+4FTgRpJfDUPS+SOBUzLrFOrPO9VebwNfA25Mq3geIwnopNvqDayNiI0ltmV1yCV0y9peUkNm+nskPVYeSqevafxpL2kWsJQksD1G8sxH0mW3AuOBPun2pkbEtZLOA+4leWL6dRGxrEge3iXpkcz0byNisy6OEbGo2P4j4glJXyN5jmkXYCNwLsnzNouKiGVKHsTxQrzzfM7fAp+W9CTwFMnDvAvX2yjp0vTcvAAszywrlY+ewHck/Sudd07hdoH7SKq65pAE9EXp/JuAYyU9RlKSPyMi1km6CfhNOn8esCotnRfTQBLUHyH5hXIkSfUVJOfwokzaw0mqYawD8XjotlUk9YiI9ZK2J6mjnhIRD3eW/beWtErmCxFxapXpe0TE+vT9l0nqzL+WlrC/SRK0r4mI/05/ZV1OUo2yICJKPs82bS+5MCKebuEhWRtyCd221lVK+pF3J6kvbutg2t77bxUR8bCkuZK6Zvqil/MFSSeRlPj/CJyfbmcd8OmCbb9OUldeVloldpeDecfjErqZWU64UdTMLCcc0M3McsIB3cwsJxzQzcxywgHdzCwnHNDNzHLCAd3MLCf+P4TasJ7i+izIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+bmi1+731G+MSQFPcABEfp+G9q078h+KuV9THJZf/AXV88xcBN+FaHjTGXRt4zhf7yd76Rbi62U34Li7G7etk3NlVPe/1sbjSVwvcWJa9cv0982LZy/f4A25s1Ga+Ze7EtV7ZA3dG8wHeheZU1k+wz/uAy7zni4HdqjiWA4CeuGqwElzf6k/71v8UaIX7wf4Q+L1v3cXEXRT13u+ZeBeJvf/VLNyFz3re60NwdeY73X86v6+4s5ZNQMOa/v8z+Qg9gFx54LpZ/Qw3iLLiSuYtAmynspRQiju9rnwM9OZPAG7xLd8EN7LOJuBr4Pwqtn8rrpSzHFfH3NSb3hNvwF5c/fRt3vN+/Dhw8nG4MUXBlWynpOF922n8/uP1ksUa7/2YAPwkbtmO3vu+BpeMX8AboBh3djIdVzWx1vsCnpgkpt1wAxGfGDf9z16Mo3EJMOffs7jpw9ixlUsxrrnnWlxV1oP4WpJUtX6CZd4DjsANDfhlCsdyKK5QsQE3tux4vO8N27dyWYsr3db3rbuYxK1cmuAuglb+MLXA/QB+6302pviWTbr/dHxffcuNIm5g8Vx8WG+LCYjIJbiSTzdV/TrseFLh1XF+o6ovicj1wDxVfV1Efour95skIlcAbVT1BnE3s+yrqiPCjDtM9p5llogsxjUzfSfsWGoLq0NPQFX/hrvwckzYsVRDB1yLBHB1sv7nn/iWqSsi7+IuTt6Xxfhykb1nJq9YCb0WEZGJwMmqGgs7lqiw9yw4K6Fnnw1BV7uUWGKqNnvPAlLVNmHHUNtYCd0YY/KE1aEbY0yeCK3KpWnTptqmTZuwdm9McsuWQYtq32xoTFbMnDnze1VtlmheaAm9TZs2zJgxI6zdG5PczJnQuXPYURiTkIh8lWyeVbkYY0yesIRuTLwuXcKOwJhALKEbY0yesHboxphQlJeXs2TJEkpLS8MOJSfVrVuXVq1aUVyc+iiYltCNiXfHHWFHUCssWbKEhg0b0qZNG1wPtqaSqrJq1SqWLFlC27apD4FrVS7GxBs2LOwIaoXS0lJ23313S+YJiAi77757tc9eLKEbE8/aoGeNJfPkgrw3ltCNibd8edgRGBOIJXRjjMkTkU/oq+du3PYwJi06dQo7ApMHNm/eTI8ePdi6dSsAn376Ka1bt+bRRx/dtkxZWRndu3enoqIiLfu0Vi7GxJs5M+wIaqV0F8qatG+Q1u1V15NPPskZZ5xBYWEhAB06dGDs2LFce+21XH755QCUlJTQq1cvnn/+eQYOHFjjfUa+hG5M2g0dGnYEJsseeeQRDjnkEFq3bs1DDz2Ulm0+++yz9O/ff7tpe+yxB3Pnzt1u2umnn86zzz6bln1aQjcm3mOPhR2ByaKXXnqJiRMnMnv2bKZMmcLw4cNrXAVSVlbGokWLiO9R9qabbmLLli189dWP/WsdcsghTJ8+vUb7q5QXCb3e/bfT6MxjYO3asEMxxkTMgw8+yMiRIykuLqZ58+YUFxcTi9VskKrvv/+exo0bbzdtwoQJbNq0id69e29XSi8sLKSkpIQNGzbUaJ+QBwldNqyjzvNPENurJfzpT2GHY4yJkPLycj7++GPatWsHwPLly7fd7HTLLbdwzTXXcNVVV/Htt9/So0cP7r33Xi6++GJGjRrFWWedxWeffcaKFSvo1KkTN998M2eccQaxWIx69eptd1NQaWkpN954I4888ggdOnTgs88+2y6OLVu2ULdu3RofT+QTetHH09h60GFsvnoYPPkkeFeUjQls6dKwIzBZMm/ePNavX8+iRYuIxWLcfPPNXHXVVYwePZrNmzfTuHFj1q1bx5w5cxg4cCA33HAD69atY8iQIZx99tl89dVXTJ8+nQEDBnD33Xezxx57sGrVKnbbbTe2bt26LamPGDGCiy66iDZt2uyQ0FetWkXTpk2r1WdLMpFP6IWfz2XrAR3Y2q497LYbTJsWdkgm6qyVS60xe/ZsBg4cyIABAzj00EPZZ599GDp0KLNnz+aee+5h2LBhPP3008yZM4fu3btTXl7O7rvvTkFBAZ999hkdOnRg+vTpHHbYYQCsW7eOZs3cYEInnXQSH374IQsWLGDixIlcc801ADsk9EmTJtG7d++0HE/kmy0WfjmfisOPdi9694bXX4ejjw43KBNt/fqBDZ6edWE0M5wzZw59+vTh3HPP3W56//79GTRoEHvvvTc9e/bkiy++oF27dnzyySccdNBBACxevJh99tmHBQsWsGHDBl555RV+/vOfb9vGL3/5S+6//37GjBnD1KlTt00/4IADmDVr1rbXzz33HPfcc09ajifyCb3gu+XEmrdyL3r3hquvhhEjwg3KGBMJc+bM2dYm3K9v37707dt32+tTTjkFgI4dO9KxY0cAxowZA0BRURF//OMfd9hGp06d+OlPf8rWrVu3tUWPV1ZWxumnn76tDr+mIp/Q5ftviTXdy7046ihYuBDWrHHVL8YYsxOTJ0+u8TYqE3sil1566U7XLSkp4aKLLqpxDJUiX4desPJbYs32dC+Ki+HII+HDD8MNykTbqFFhR2BMINFO6Fu2IJs2oo13B9ytwz8ceBSbX34n5MBMpNmdoiaiop3Qv/sObdIUCn48jIou3Sie8VGIQZnIsz66TURFO6GvWUNs1ybbTaro0IXCL/8LabjryhhjoiTaCX39erRBw+2n1alLxcGHwZQp4cRkjEmZWvPQpIK8N9FO6OvWoQ0a7TC54vCj7cKoCa5Pn7AjqBXq1q3LqlWrLKknUDlIdHW7A4h2s8X16xMn9E5Hw4sPhxCQyQuvvRZ2BLVCq1atWLJkCStXrgw7lJxUt25dWrVqVa118iChN9xhckXHI+GGQVBe7poyGlMdfftaUs+C4uJi2rZtG3YYeSXaVS5JSujaqDEVLdqw7qWPbGg6U33jx4cdgTGB5GVCB1ftUjzrP1kOyBhjwhP9hL7LjlUu4BJ6kSV0Y0wtEv2EnqAOHVxLl6LZ/7Fe80z12WfGRFS0E/qmTWj9xF1uxpq3QuvUo+CrhVkOykTe6NFhR2BMINFO6KWlUFIn6eyKTkdTNPPfWQzI5IXLLgs7AmMCiXZC37wZrZO84X1Fp2Monm316MaY2iHaCb20FOpUUUKfZV0AGGNqh8gndC1JXkLfut+ByNrV8O23WQzKRN64cWFHYEwgkU/o7KTKhYICKjp2hY+sO11TDZ07hx2BMYGklNBF5BQRWSAiC0XkpgTz9xGRSSIyW0Q+EZHT0h9qAlXUoYPXr4t11GWqo2XLsCMwJpAqE7qIFAIPA6cCBwMDROTguMVuA15Q1cOB84BH0h1oQqWlltCNMcaTSgm9K7BQVRepahkwFugft4wClffg7wosS1+IO1HFRVGAikM6w/z5sNH6dDHG5LdUEnpL4Bvf6yXeNL9hwAUisgR4A/hVWqKrShUXRQHXTv3ww23AC5O6IUPCjsCYQNJ1UXQA8JSqtgJOA8aIyA7bFpGhIjJDRGbUuA9k1aovilY69lirdjGpsztFTUSlktCXAnv7XrfypvkNBl4AUNX/AHWBpvEbUtXRqtpFVbs0a9YsWMSVysuhsNA9qmIJ3VSHtXIxEZVKQp8O7C8ibUWkBHfRM76h7tdALwAROQiX0DM7DElpKaQ6PNMxx8DUqe5HwJiqzJoVdgTGBFJlQlfVCuBK4C1gPq41y1wRuVNE+nmLXQcMEZGPgX8AgzTTAwVWJ6Hvthu0aQMff5zRkIwxJkwpDUGnqm/gLnb6p93uez4P6Jbe0KpQjYS+eu5G6rc/iq3/fJct9Q6kSfvEPTQaA0Dz5mFHYEwg0b1TdPPmKpss+lV0Oppi63nRpGJZdlrdGpNu0U3o5eXVTuhFs2zAC5OCYcPCjsCYQKKd0ItSqjECINZ8b7SkDgVff5nBoExeGD487AiMCSTaCb24uFqr2IAXxph8Ft2EXlFR7YRefmQPiqdMzkw8xhgTsugm9GpWuQBUHNOT4v+8B7FYhoIyeWHGjLAjMCaQaCf0apbQY833Rhs3gTlzMhOTMcaEKLoJPUCVC0D50b1g4sQMBGTyRpcuYUdgTCDRTegBqlwAyo/pCW+/nYGAjDEmXNFO6EFK6F2Pg2nTYNOmDARljDHhiW5Cr6gIVEKnfgPo1Anefz/9MZn8cMcdYUdgTCDRTegBS+gAnHSSVbuY5OxOURNRtTehv/lmeuMx+aNFi7AjMCaQ6Cb0oFUu4AYwWLsWFi5Ma0gmTyxfHnYExgQS3YRekxJ6QQH06QOvvZbemIwxJkS1MqGvnruRDYedQPnYf7F67sZtD2MAd9HcmAiKbkKvSZULUH7UTymaOxtZtyaNQZm8MHNm2BEYE0h0E3pNqlwA6tWnvEs3ij96J30xmfwwdGjYERgTSHQTesBb//3Kjz+V4skT0hSQyRuPPRZ2BMYEEt2EHvDWf7+yHqdS/OE7blvGGBNx0U7oNSyh6x7NibXej6IZH6YpKGOMCU90E3oaqlwAyk7sT8nbr6QhIJM3li4NOwJjAoluQk9DlQtA2UmnU/LOOPcDYQxYKxcTWdFO6GkoocdatSHWsg1F0z9IQ1AmL/TrF3YExgQS3YSepioX8Erpb72clm0ZY0xYopvQ01TlAl5Cf/c1q3YxxkRadBP61q1QWJiWTVVWuzB5clq2ZyJu1KiwIzAmkOgm9FgsbQkdXCmdsWPTtj0TYXanqImo6Cb0rVtdr4lpsuW0s4m9+DKrZ660jrpqO5GwIzAmkOgm9DSX0HWvlmxtfzglk95I2zaNMSabopvQ01xCB9jSbwAl455L6zaNMSZbIpnQV8/dSNnaMjYsS28fLGW9+lL08TTk+++sn/TarE+fsCMwJpBIJnQgIyV06u9Cec/e1Hn9hfRu10SLjWRlIiq6CV1j6U/owJZ+51PyqlW71Gp9+4YdgTGBpJQRReQUEVkgIgtF5KYky5wjIvNEZK6IZD4jZqKEDlR0ORbZtIHCz2alfdsmIsaPDzsCYwKpMiOKSCHwMHAqcDAwQEQOjltmf+BmoJuqtgeuSX+ocWIxkAycYBQUsOXMi6nz4pPp37YxxmRQKhmxK7BQVRepahkwFugft8wQ4GFVXQOgqivSG2YCqmlttui35YyLKJn4KrJhXUa2b4wxmZBKQm8JfON7vcSb5tcOaCciH4nIFBE5JV0BJiMZqnIB0KZ7Un70TykZ/3xGtm9ynGrYERgTSLoyYhGwP3A8MAB4TEQaxy8kIkNFZIaIzFi5cmXN9qgxtCAzJXSALecMps4LT9qXuzYaPTrsCIwJJJWEvhTY2/e6lTfNbwkwTlXLVfV/wOe4BL8dVR2tql1UtUuzZs2CxuxksIQOUNG1O1K+haI5UzO2D5OjLrss7AiMCSSVjDgd2F9E2opICXAeMC5umX/hSueISFNcFcyi9IWZgMYggyV0RNhy9qXUGWsjwBtjoqHKhK6qFcCVwFvAfOAFVZ0rIneKSOXQLm8Bq0RkHjAJuF5VV2UqaMAroWe2E6Utp19A8QcTbYxJY0wkpDRChKq+AbwRN+1233MFrvUe2RHLcAkd0F13o6zPudT9y1/g7rszui+TQ8bFn4AaEw2RvVNUYjE0g3XolUovuBweeww2Wp8utUbnzmFHYEwgkU3o2SihA8T22Re6d4enn874vkyOaBnfKteYaIhwQs9sK5ftXHcdPPCAq7c3xpgcFeGEnt4BLnbqmGOgSROrWzXG5LQIJ/StmenLJRERuOkmGDHCbjSqDYYMCTsCYwKJcELPYgkdoH9/KCuDCROyt08TDrtT1ERUZBO6xGJoNgfzLSiA226Du+6yUnq+s1YuJqIim9CzelG00llnwZo18O672d2vya5Z1he+iaYIJ/TMdZ+bVGEh3HqrK6UbY0yOiXBCz+JFUb8BA2DZMiul57PmzcOOwJhAIpzQs3xRtFJRkSuh33yz1aXnq2XLwo7AmEAim9AlrBI6wDnnQEUFvPxyOPs3mTVsWNgRGBNIZBM6sRgaRgkd3MXYu+929ekVFeHEYDJn+PCwIzAmkJR6W8xJGR7gwm/13AQdc7U8hibNm8NTT8HPf56VOIwxZmeiW0LXWPabLfqJwD33uNPzH34ILw5jjPFEN6FvDTmhAxx5JHTrBiNHhhuHSa8ZM8KOwJhAolvlkukh6FKweu5GCoYMo9FZ3Vh/7LnEWuwDQJP2DUKNyxhTO0W2hC5bt2ZlgIuqxJrvTenAy6n3x9vCDsWkS5cuYUdgTCDhZ8SgcqCEXqn0kqsp+nQmRdM+CDsUY0wtFt2EnsVWLlWqV58frhtB/XtugIoKVs/duO1hjDHZkiMZMYCw7hRNovyk09HGTajz3F/DDsXU1B13hB2BMYFEN6FrLLw7RRMRYdPtD1Bv9H0ULPs67GhMTdidoiaicigjVo/kUpWLJ9Zmf0ovvJL6I661fl6irEWLsCMwJpDcyoipqkyWOZbQAUovvZqCZV9T8tYrYYdiglq+POwIjAkk9zJiKnKkyWJCxSX8cMeD1B95I7JuTdjRGGNqkRzNilVQdbfe56iKw4+irFdf6o+8MexQTBCdOoUdgTGBRDOhk9sJHeCHa++iaPZU+Ne/wg7FVNfMmWFHYEwg0UzoqkBuJ3Tq78Km3/0VLr8cVqwIOxpTHUOHhh2BMYFEN6HneAkdoKLT0XDxxXDZZdbqJUoeeyzsCIwJxBJ6pg0fDl9+Cc88E3Ykxpg8Zwk90+rUgTFj4Prr4Ysvwo7GGJPHIprQc6Av9Oo47DB3O/m558KWLWFHY6qydGnYERgTSISyok8ULorGu+IKaNvWldRNbrNWLiaiopvQo1LlUkkEnngCXnvNmjLmun79wo7AmEAimdAligkdoHFjGDvWtXpZvDjsaIwxeSalhC4ip4jIAhFZKCI37WS5M0VERSSzQ76oolFM6ODGIb35ZjjjDBtc2hiTVlUmdBEpBB4GTgUOBgaIyMEJlmsIXA1MTXeQO4hqCb3S1VfDwQe7G1isfXruGTUq7AiMCSSVEnpXYKGqLlLVMmAs0D/BcncBI4HSNMaXRMQTugiMHg3z5sGf/xx2NCae3SlqIiqVhN4S+Mb3eok3bRsR6QTsraqvpzG25CLUyiXZcHSr/xdj7T1jiI24GyZNCik6k1CUCwumVqvxRVERKQD+BFyXwrJDRWSGiMxYuXJl8J2qRiWf71SsZWs23vsknH8+LFoUdjjGmIhLJaEvBfb2vW7lTavUEDgEmCwii4GjgHGJLoyq6mhV7aKqXZo1axY86qjXoftUHNkDfvtb6N0b1lj/6caY4IpSWGY6sL+ItMUl8vOA8ytnquo6oGnlaxGZDPxGVWekN1QfJZIJPb7aZZsrroCFC+HMM+HNN6GkJLuBme316RN2BMYEUmUJXVUrgCuBt4D5wAuqOldE7hSRcO7AyKMS+jb33QeNGlnLl1zw2mthR2BMICnVoavqG6raTlX3U9XfedNuV9VxCZY9PqOlc7cX8qIS3a+wEJ59FubOhREjwo6mduvbN+wIjAkklSqX3JOPJXSAXXZhzR/G0uj8nmxmdxr89oqwI6qdxo8POwJjAonkrf+oRqu3xWrQpnuyYdQr1H/wTnjllbDDMcZESDSzYiyWnyV0T6xtOzY88k/X58t774UdjjEmIiJZ5RLZzrmSSNT6ZevBHeHFF+Hss+GNN6BLZrvHMT52UdpEVDRL6CiabxdFE+nRAx5/3F2kmz8/7Ghqj9Gjw47AmECimdDzrIS+U/36wb33woknwoIFYUdTO1x2WdgRGBNIJKtcalVCB7jwQjZ+tZH6PXqy/onxxNrsv21Wk/YNQgzMGJNLLKFHRNnPLoRYjIaD+7LhyfHEWv8k7JCMMTnGEnqElJ15MaKVSf11YvvsG3ZI+WncDvfLGRMJltAjZstZl0BMaTi4DxseHwftO4YdUv7p3DnsCIwJJJoJPR9v/a+GLedcCgUFNLrkNHjnLejQIeyQ8kvLltZ00URSNBN6LS6hV9py1iC0fgManHiiqyLo2jXskIwxIbNmixFWdtpZ8Nhjri/1//u/sMMxxoQswgk97CAyL9nwddvp2xeef97dUTphQvaCy2dDhoQdgTGBRDih14KMnqqePV21y6BB8Pe/hx1N9NmdoiaiIpzQoxl6xhx1lOvI69ZbYeRIu6hXE9bKxURUJC+K5lvnXDXhr45p0r49fPQRnHYaLFkCDzzgBs4w1TNrVtgRGBNINIu5qqgl9MRatYIPPnAjH51zDmzeHHZExpgsiWxCtxL6Tuy6q7tAWlLiOvVavTrsiKKlefOwIzAmEEvoeWr1wnJW3zKKzft3dvXrn38edkjRsWxZ2BEYE0h0E3ptaLdYUwUFbP7N7+D66+G442z0o1QNGxZ2BMYEEs2EjpXQq2XIEBg7FgYMsCZ5qRg+POwIjAkkmgndqlyqZfXcjaze4wjW/u0t+OMf4de/hq1bww7LGJNmltBrkVjrn8CUKfDpp24kpPXrww7JGJNGltBrm912cy1g9tnHLpYmM2NG2BEYE4gl9NqouBgefRSuuQaOPRZefz3siIwxaRDdhG6tXGpu6FB49VU3KPJdd0EsFnZEuaFLl7AjMCaQaCZ0a+WSPkcfDdOnw5tvwhlnWL26MREWzYRuVS6BJeySt3lzmDQJWrSAI4+E//43ta57jTE5JboJvcASelqVlMAjj8BvfgPdu1P87mthRxSeO+4IOwJjAolmb4uxmJXQM2XwYOjQgfqnn0XZnKlsvqoWJje7U9REVGRL6GoXRTOna1fWv/gBhV/Mo+Hg3rWvb5MWLcKOwJhAopnQ7aJoRvjrzbXx7mx85J+UdzvRtfp4992ww8ue5cvDjsCYQKKZ0O2iaHYUFFB62fUwZgxceCGMGGFNG43JYSkldBE5RUQWiMhCEbkpwfxrRWSeiHwiIu+KSOv0h+pjCT27evVyd0++/Tb07g3ffx92RJnVqVPYERgTSJUXRUWkEHgYOBFYAkwXkXGqOs+32Gygi6r+ICKXA/cC52YiYAAUS+gJVLeJYarLu+UawUPjaPLc3W7Mzeefd10H5KOZM8OOwJhAUimhdwUWquoiVS0DxgL9/Quo6iRV/cF7OQVold4w41gJPRxFRW4A6ocecp17/fnP+TkY9dChYUdgTCCpJPSWwDe+10u8ackMBibUJKiq2a3/oerXz/XaOGaMG7d03bqwI0qvxx4LOwJjAknrRVERuQDoAtyXZP5QEZkhIjNWrlwZfEdWQg/fvvvChx/CHnu4VjBz5oQdkTG1XioJfSmwt+91K2/adkTkBOBWoJ+qbkm0IVUdrapdVLVLs2bNgsRbuSFL6Lmgbl14+GG48043GPXjj+dnFYwxEZFKQp8O7C8ibUWkBDgPGOdfQEQOB0bhkvmK9IcZxxJ6bhkwAD74wNWpX3wxbNoUdkQ1s3SH8ooxkVBlQlfVCuBK4C1gPvCCqs4VkTtFpJ+32H1AA+BFEZkjIuOSbC49LKHnhO068DrwQJg6FQoKoGtXmD8/7PCCs1YuJqJEQzpF7tKli84IODLM6pkrkY3r0aZ7pjkqU5Um7Rtse+5v9uifzpNPwo03uhL7+ednM7z0ELGqI5OzRGSmqibstD+SnXNRtx5at17YUZhkLr3UXSg96yx4/3144AFX326Myaho3vpvct+hh7q7S1evdoNofPll2BEZk/csoZvMadTI3VE6eLBL6i+/HHZEqRk1KuwIjAnEErrJLBG48ko3EPV118Gvfw1lZWFHtXN2p6iJKEvoJi38LV4SDl93xBGu9cjChdCjB3z9dXjBVsVaUJmIsoRusqdJE3j1VTcYddeuMCHDPUQYU8tYQjfZVVAA118PL74IQ4bArbdCRUXYURmTF6LZbNGEprpd9CZbt8lxx8GsWTBwoOs24B//gL32SkeINdenT9gRGBOIldBNePbYA95809WpH3GEa+aYC157LewIjAnEEroJV2EhDBsGDz4Ip57qSuph69s37AiMCcSqXExu+NnPYL/9oH9/+PRTN35pQUjljfHjw9mvMTVkJXSTOw49FKZNg48+gtNPhw0bwo7ImEixhG5yS7NmMHEiNG8OxxwD33xT9TrGGMASuslFJSXw17/CoEHQrZurgskm62nRRJQldJObRFxXASNHwgknwOTJ2dv36NHZ25cxaWQJ3eS2AQNcy5dzznEdfWXDZZdlZz/GpJm1cjG5r2dPeOcdOO00N7zdpZeGHZExOckSusmomtxZup1DD4X33oNevaC83ErRxiRgCd1ER7t2ri69Z0/X/8svf5mZ/YzL7JC4xmSKJXQTLfvt92NSLy7OTN/lnTunf5vGZIEldBOKZFUxKQ1C3bYtvP226wOmaVPXHW86tWxpTRdNJFlCN9G0//6uE61TTnH9rB9/fNgRGRM6a7ZooqtzZxg7Fs49142EZEwtZyV0k1NSaRWz3TJ7HUmdITdS59R+FM2eBg0aJF8xVUOG1HwbxoTASugm8racN4Sth3SGwYPTU/dtd4qaiLKEbqJPhE2/vR/mzYMxY2q+PWvlYiLKqlxMJFRZFVOnLuuGjaLhkH6sb9GVxiccWOV2tms54zdrVmrLGZNjrIRu8sbWAw+ldODl1L/7N2GHYkwoLKGbvFJ6ydUUfj4XJk0KvI1YsxwZrNqYarIqF5Nf6tTlh1/fSb0rr2X98++7bnhTsF2VzqQvMhScMZllJXSTd8pPOh22lFI0ZXKg9es9/Pu0xmNMtlhCN/lHhNJBV1H3mb8EWr3eo3enOSBjssMSuslLZaecSdGcqciqlWGHYkzWWB26yU/16lN+3EmUvDOOLecOTrhIkL7a09WcMdl2wmouac0084OV0E3eKu/Wi6LpH1R7vXXPv5+BaIzJvJQSuoicIiILRGShiNyUYH4dEXnemz9VRNqkPVJjqqmi45EUzZkadhjGZE2VVS4iUgg8DJwILAGmi8g4VZ3nW2wwsEZVfyIi5wEjgXMzEbAxqYrtvS8Fq1fC5h+gXv2U19v13O6s/mzDttfJqmZSqbJJVp2SippUy6TS33xN1ahP+yTbyefqnmwcZyol9K7AQlVdpKplwFigf9wy/YGnvef/BHqJpNgA2JhMKSgg1rwVBd8tDTsSY7IilYuiLYFvfK+XAEcmW0ZVK0RkHbA78H06gjQmqHX/mgbFJWGHYUxWZLWVi4gMBSoHgdwoIguqsXpT8uMHIl+OA/LnWHY8jkMahhNJzeXv/yS60n0srZPNSCWhLwX29r1u5U1LtMwSESkCdgVWxW9IVUcDgTqbFpEZqtolyLq5JF+OA/LnWPLlOCB/jiVfjgOyeyyp1KFPB/YXkbYiUgKcB4yLW2YccLH3/CzgPVUbZdcYY7KpyhK6Vyd+JfAWUAg8qapzReROYIaqjgOeAMaIyEJgNS7pG2OMyaKU6tBV9Q3gjbhpt/uelwJnpze0HeTLuGD5chyQP8eSL8cB+XMs+XIckMVjEasZMcaY/GC3/htjTJ7I+YReVbcDUSEiT4rIChH5LOxYakpE9haRSSIyT0TmisjVYccUhIjUFZFpIvKxdxzDw46pJkSkUERmi8j4sGOpCRFZLCKfisgcEZkRdjw1ISKNReSfIvJfEZkvIkdndH+5XOXidTvwOb5uB4ABcd0ORIKIdAc2As+o6iFhx1MTItIcaK6qs0SkITATOD1q/xfvbuZdVHWjiBQDHwJXq+qUkEMLRESuBboAjVS1T9jxBCUii4Euqhr5dugi8jTwgao+7rUSrK+qazO1v1wvoafS7UAkqOr7uBZAkaeqy1V1lvd8AzAfd7dwpKhT2cFGsffI3RLOTohIK6A38HjYsRhHRHYFuuNaAaKqZZlM5pD7CT1RtwORSxz5zOtZ83Agkt0aetUUc4AVwERVjeRxAA8ANwCxkONIBwXeFpGZ3t3lUdUWWAn8zasKe1xEdsnkDnM9oZscJiINgJeAa1R1fdjxBKGqW1W1I+4O6K4iErnqMBHpA6xQ1Zlhx5Imx6pqJ+BU4JdedWUUFQGdgEdV9XBgE5DR64C5ntBT6XbAhMCrc34JeFZVXw47npryToUnAaeEHEoQ3YB+Xt3zWKCniPw93JCCU9Wl3t8VwCu4qtcoWgIs8Z31/ROX4DMm1xN6Kt0OmCzzLiY+AcxX1T+FHU9QItJMRBp7z+vhLr7/N9SgAlDVm1W1laq2wX1H3lPVC0IOKxAR2cW70I5XPXESEMmWYar6LfCNiBzgTeoFZLThQE6PKZqs24GQwwpERP4BHA80FZElwB2q+kS4UQXWDbgQ+NSrfwa4xbujOEqaA097rakKgBdUNdJN/vLAnsAr3nAKRcBzqvpmuCHVyK+AZ70C6SLgkkzuLKebLRpjjEldrle5GGOMSZEldGOMyROW0I0xJk9YQjfGmDxhCd0YY/KEJXRjjMkTltCNMSZPWEI3xpg88f+EkWePXipV6wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vgg11 = models.vgg11(pretrained=True)\n",
    "watcher = ww.WeightWatcher(model=vgg11)\n",
    "details = watcher.describe()\n",
    "esd = watcher.get_ESD(model=vgg11, layer=8)\n",
    "analyzed = watcher.analyze(plot=True, layers=[8], randomize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>layer_id</th>\n",
       "      <th>name</th>\n",
       "      <th>M</th>\n",
       "      <th>N</th>\n",
       "      <th>layer_type</th>\n",
       "      <th>num_evals</th>\n",
       "      <th>rf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>None</td>\n",
       "      <td>3.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>27.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>None</td>\n",
       "      <td>64.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>576.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>None</td>\n",
       "      <td>128.0</td>\n",
       "      <td>256.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>1152.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>256.0</td>\n",
       "      <td>256.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>2304.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>None</td>\n",
       "      <td>256.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>2304.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15</td>\n",
       "      <td>None</td>\n",
       "      <td>512.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>4608.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>18</td>\n",
       "      <td>None</td>\n",
       "      <td>512.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>4608.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>20</td>\n",
       "      <td>None</td>\n",
       "      <td>512.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>4608.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>25</td>\n",
       "      <td>None</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>25088.0</td>\n",
       "      <td>LAYER_TYPE.DENSE</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>28</td>\n",
       "      <td>None</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>LAYER_TYPE.DENSE</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>31</td>\n",
       "      <td>None</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>LAYER_TYPE.DENSE</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   layer_id  name       M        N         layer_type  num_evals   rf\n",
       "0         2  None     3.0     64.0  LAYER_TYPE.CONV2D       27.0  9.0\n",
       "1         5  None    64.0    128.0  LAYER_TYPE.CONV2D      576.0  9.0\n",
       "2         8  None   128.0    256.0  LAYER_TYPE.CONV2D     1152.0  9.0\n",
       "3        10  None   256.0    256.0  LAYER_TYPE.CONV2D     2304.0  9.0\n",
       "4        13  None   256.0    512.0  LAYER_TYPE.CONV2D     2304.0  9.0\n",
       "5        15  None   512.0    512.0  LAYER_TYPE.CONV2D     4608.0  9.0\n",
       "6        18  None   512.0    512.0  LAYER_TYPE.CONV2D     4608.0  9.0\n",
       "7        20  None   512.0    512.0  LAYER_TYPE.CONV2D     4608.0  9.0\n",
       "8        25  None  4096.0  25088.0   LAYER_TYPE.DENSE     4096.0  1.0\n",
       "9        28  None  4096.0   4096.0   LAYER_TYPE.DENSE     4096.0  1.0\n",
       "10       31  None  1000.0   4096.0   LAYER_TYPE.DENSE     1000.0  1.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "details"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "sharper_vgg11 = watcher.SVDSharpness(model=vgg11, layers=[8])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Assuming nested distributions\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "watcher_sm = ww.WeightWatcher(model=sharper_vgg11)\n",
    "analyzed_sm = watcher_sm.analyze(plot=True, layers=[8], randomize=True)\n",
    "esd_sm = watcher_sm.get_ESD(model=sharper_vgg11, layer=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(np.log10(esd),bins=100);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(np.log10(esd_sm[esd_sm>0.00001]),bins=100, alpha=0.4);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Layer 8 Eigenvalue,  $\\\\lambda>0.0$')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(np.log10(esd),bins=100, label='vgg11 layer 8');\n",
    "plt.hist(np.log10(esd_sm[esd_sm>0.00001]),bins=100, alpha=0.7, label='sharpened');\n",
    "plt.title(\"VGG11 Layer 8, top eigenvalues (ESD)\")\n",
    "plt.xlim([0,1])\n",
    "plt.legend()\n",
    "plt.xlabel(r\"Layer 8 Eigenvalue,  $\\lambda>0.0$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>layer_id</th>\n",
       "      <th>name</th>\n",
       "      <th>M</th>\n",
       "      <th>N</th>\n",
       "      <th>layer_type</th>\n",
       "      <th>num_evals</th>\n",
       "      <th>rf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>None</td>\n",
       "      <td>3.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>27.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>None</td>\n",
       "      <td>64.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>576.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>None</td>\n",
       "      <td>128.0</td>\n",
       "      <td>256.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>1152.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>256.0</td>\n",
       "      <td>256.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>2304.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>None</td>\n",
       "      <td>256.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>2304.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15</td>\n",
       "      <td>None</td>\n",
       "      <td>512.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>4608.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>18</td>\n",
       "      <td>None</td>\n",
       "      <td>512.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>4608.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>20</td>\n",
       "      <td>None</td>\n",
       "      <td>512.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>LAYER_TYPE.CONV2D</td>\n",
       "      <td>4608.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>25</td>\n",
       "      <td>None</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>25088.0</td>\n",
       "      <td>LAYER_TYPE.DENSE</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>28</td>\n",
       "      <td>None</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>LAYER_TYPE.DENSE</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>31</td>\n",
       "      <td>None</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>4096.0</td>\n",
       "      <td>LAYER_TYPE.DENSE</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   layer_id  name       M        N         layer_type  num_evals   rf\n",
       "0         2  None     3.0     64.0  LAYER_TYPE.CONV2D       27.0  9.0\n",
       "1         5  None    64.0    128.0  LAYER_TYPE.CONV2D      576.0  9.0\n",
       "2         8  None   128.0    256.0  LAYER_TYPE.CONV2D     1152.0  9.0\n",
       "3        10  None   256.0    256.0  LAYER_TYPE.CONV2D     2304.0  9.0\n",
       "4        13  None   256.0    512.0  LAYER_TYPE.CONV2D     2304.0  9.0\n",
       "5        15  None   512.0    512.0  LAYER_TYPE.CONV2D     4608.0  9.0\n",
       "6        18  None   512.0    512.0  LAYER_TYPE.CONV2D     4608.0  9.0\n",
       "7        20  None   512.0    512.0  LAYER_TYPE.CONV2D     4608.0  9.0\n",
       "8        25  None  4096.0  25088.0   LAYER_TYPE.DENSE     4096.0  1.0\n",
       "9        28  None  4096.0   4096.0   LAYER_TYPE.DENSE     4096.0  1.0\n",
       "10       31  None  1000.0   4096.0   LAYER_TYPE.DENSE     1000.0  1.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
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  {
   "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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