DS39213.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "DS39213",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyM67uEPKxILbg+5qA64RtrN",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/bmreiniger/datascience.stackexchange/blob/master/DS39213.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1u51g8-vGWPU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "from matplotlib import pyplot as plt"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8HQiYkHHGhz_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "np.random.seed(314)\n",
        "X = np.random.normal(size=100).reshape(-1, 2)\n",
        "X[:, 0] += 4\n",
        "X[0, :] = [4,0]\n",
        "y = np.ones(shape=(X.shape[0], 1))\n",
        "# comment the next line out to get a separable dataset\n",
        "# (assuming the normal sampling didn't give you an unlucky pull)\n",
        "y[0] = -1  \n",
        "\n",
        "X = np.vstack((X, -X))\n",
        "y = np.vstack((y, -y))\n"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "guwFRppQHScE",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "0d803a2a-ca9d-4e20-c767-875d4fb7af4d"
      },
      "source": [
        "plt.scatter(x=X[:, 0], y=X[:, 1], c=y);"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Sgo0t11gHXCb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "c228716b-918d-404f-c54f-50623833e328"
      },
      "source": [
        "eta = 0.01\n",
        "w = [1, 10]\n",
        "w /= np.linalg.norm(w)\n",
        "for iter in range(1000):\n",
        "  error = sum(max(0, -y[i]*np.dot(w, X[i, :])) for i in range(len(y)))\n",
        "  print(w, error)\n",
        "  w += eta * sum([y[i]*X[i,:] if y[i]*np.dot(w, X[i,:]) < 0 else 0 for i in range(len(y))])\n",
        "  w /= np.linalg.norm(w)\n"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0.09950372 0.99503719] [26.58413396]\n",
            "[0.9391015 0.3436399] [7.51281196]\n",
            "[0.92847695 0.37139003] [7.4278156]\n",
            "[0.91608542 0.40098318] [7.32868332]\n",
            "[0.90166513 0.43243495] [7.21332107]\n",
            "[0.88492727 0.46572924] [7.07941816]\n",
            "[0.86555741 0.50080971] [6.92445928]\n",
            "[0.84321899 0.53757021] [6.74575194]\n",
            "[0.81755922 0.57584453] [6.54047375]\n",
            "[0.78821804 0.61539607] [6.3057443]\n",
            "[0.75484069 0.65590817] [6.03872555]\n",
            "[0.7170942  0.69697626] [5.73675359]\n",
            "[0.67468772 0.7381033 ] [5.39750179]\n",
            "[0.62739641 0.77870004] [5.01917124]\n",
            "[0.57508742 0.81809196] [4.60069938]\n",
            "[0.51774642 0.85553413] [4.14197138]\n",
            "[0.45550161 0.89023496] [3.64401285]\n",
            "[0.38864228 0.92138872] [3.41942203]\n",
            "[0.42005811 0.90749721] [3.36046492]\n",
            "[0.35089425 0.93641509] [3.55142005]\n",
            "[0.38153634 0.92435384] [3.44487616]\n",
            "[0.41281746 0.91081378] [3.33066056]\n",
            "[0.44465202 0.8957034 ] [3.55721619]\n",
            "[0.37706259 0.92618778] [3.46075569]\n",
            "[0.40825626 0.91286737] [3.34766668]\n",
            "[0.44001658 0.89798965] [3.52013267]\n",
            "[0.37212187 0.92818388] [3.47816281]\n",
            "[0.4032166  0.91510457] [3.36631552]\n",
            "[0.43489229 0.90048248] [3.47913834]\n",
            "[0.36666473 0.93035315] [3.49723188]\n",
            "[0.39764733 0.91753834] [3.38675299]\n",
            "[0.42922636 0.90319695] [3.43381085]\n",
            "[0.36063639 0.93270649] [3.51810602]\n",
            "[0.3914917  0.92018164] [3.40913481]\n",
            "[0.42296009 0.90614831] [3.38368068]\n",
            "[0.3539762  0.93525443] [3.54093686]\n",
            "[0.38468674 0.92304719] [3.43362633]\n",
            "[0.41602822 0.9093517 ] [3.3282258]\n",
            "[0.34661698 0.93800675] [3.56588401]\n",
            "[0.37716256 0.92614707] [3.46040208]\n",
            "[0.4083582  0.91282177] [3.34728791]\n",
            "[0.44012021 0.89793886] [3.52096169]\n",
            "[0.37223228 0.92813961] [3.4777753]\n",
            "[0.40332924 0.91505493] [3.36590029]\n",
            "[0.43500686 0.90042714] [3.48005489]\n",
            "[0.36678668 0.93030507] [3.49680752]\n",
            "[0.39777182 0.91748437] [3.38629808]\n",
            "[0.42935305 0.90313673] [3.43482439]\n",
            "[0.36077112 0.93265438] [3.51764166]\n",
            "[0.39162931 0.92012308] [3.4086368]\n",
            "[0.42310022 0.90608289] [3.38480174]\n",
            "[0.35412507 0.93519807] [3.5404292]\n",
            "[0.38483888 0.92298377] [3.43308162]\n",
            "[0.41618326 0.90928076] [3.32946608]\n",
            "[0.34678148 0.93794595] [3.56532957]\n",
            "[0.3773308  0.92607854] [3.45980684]\n",
            "[0.40852977 0.912745  ] [3.34665035]\n",
            "[0.44029461 0.89785336] [3.52235686]\n",
            "[0.3724181  0.92806506] [3.47712299]\n",
            "[0.40351882 0.91497134] [3.36520133]\n",
            "[0.43519967 0.90033397] [3.48159734]\n",
            "[0.36699193 0.93022413] [3.49609316]\n",
            "[0.39798134 0.91739351] [3.38553231]\n",
            "[0.42956626 0.90303534] [3.43653006]\n",
            "[0.36099786 0.93256664] [3.51685997]\n",
            "[0.39186091 0.92002447] [3.40779847]\n",
            "[0.42333604 0.90597273] [3.38668833]\n",
            "[0.35437559 0.93510317] [3.53957458]\n",
            "[0.38509493 0.92287697] [3.43216463]\n",
            "[0.41644416 0.9091613 ] [3.33155329]\n",
            "[0.34705831 0.93784355] [3.56439617]\n",
            "[0.37761393 0.92596313] [3.45880478]\n",
            "[0.40881849 0.91261572] [3.34557704]\n",
            "[0.44058808 0.89770939] [3.52470465]\n",
            "[0.37273079 0.92793952] [3.47602481]\n",
            "[0.40383784 0.91483058] [3.36402462]\n",
            "[0.43552412 0.90017706] [3.48419295]\n",
            "[0.36733733 0.93008778] [3.49489047]\n",
            "[0.39833391 0.91724048] [3.3842431]\n",
            "[0.42992504 0.90286459] [3.43940029]\n",
            "[0.36137944 0.93241884] [3.51554386]\n",
            "[0.39225063 0.91985838] [3.40638704]\n",
            "[0.42373287 0.9057872 ] [3.38986298]\n",
            "[0.35479718 0.93494329] [3.53813563]\n",
            "[0.38552579 0.92269706] [3.4306207]\n",
            "[0.41688319 0.90896007] [3.33506549]\n",
            "[0.34752418 0.93767102] [3.56282449]\n",
            "[0.37809037 0.92576869] [3.45711752]\n",
            "[0.40930431 0.91239793] [3.34376987]\n",
            "[0.44108189 0.89746686] [3.52865512]\n",
            "[0.37325699 0.92772799] [3.47417561]\n",
            "[0.40437466 0.91459343] [3.36204327]\n",
            "[0.43607004 0.89991273] [3.48856034]\n",
            "[0.36791855 0.92985802] [3.49286518]\n",
            "[0.39892717 0.91698261] [3.38207218]\n",
            "[0.43052871 0.90257688] [3.44422966]\n",
            "[0.36202152 0.93216974] [3.51332743]\n",
            "[0.39290639 0.91957847] [3.40401017]\n",
            "[0.42440056 0.90547455] [3.39520445]\n",
            "[0.35550659 0.93467378] [3.53571214]\n",
            "[0.38625077 0.92239381] [3.4280205]\n",
            "[0.41762185 0.90862093] [3.34097478]\n",
            "[0.34830807 0.93738012] [3.56017723]\n",
            "[0.37889202 0.92544089] [3.45427571]\n",
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            "[0.41636849 0.90919595] [3.33094795]\n",
            "[0.34697802 0.93787326] [3.56466693]\n",
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            "[0.41675586 0.90901845] [3.3340469]\n",
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            "[0.43124975 0.90223259] [3.44999803]\n",
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            "[0.42519804 0.90510034] [3.40158432]\n",
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            "[0.40861059 0.91270882] [3.34634996]\n",
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            "[0.37250562 0.92802993] [3.47681565]\n",
            "[0.40360812 0.91493196] [3.364872]\n",
            "[0.43529049 0.90029006] [3.48232391]\n",
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            "[0.42966669 0.90298756] [3.4373335]\n",
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            "[0.39197  0.919978] [3.40740347]\n",
            "[0.42344712 0.90592082] [3.387577]\n",
            "[0.3544936  0.93505844] [3.53917189]\n",
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            "[0.41656706 0.90910499] [3.33253645]\n",
            "[0.34718872 0.93779528] [3.56395634]\n",
            "[0.3777473  0.92590873] [3.4583326]\n",
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            "[0.40953313 0.91229524] [3.34291822]\n",
            "[0.44131447 0.89735252] [3.53051573]\n",
            "[0.37350483 0.92762823] [3.47330408]\n",
            "[0.4046275 0.9144816] [3.36110948]\n",
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            "[0.36819231 0.92974966] [3.49191061]\n",
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            "[0.43081302 0.90244121] [3.44650414]\n",
            "[0.36232394 0.93205223] [3.5122827]\n",
            "[0.39321524 0.91944645] [3.40288986]\n",
            "[0.42471501 0.9053271 ] [3.39772007]\n",
            "[0.35584072 0.93454662] [3.53456973]\n",
            "[0.38659222 0.92225076] [3.42679484]\n",
            "[0.41796972 0.90846096] [3.34375776]\n",
            "[0.34867729 0.93724284] [3.55892923]\n",
            "[0.37926957 0.92528622] [3.45293606]\n",
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            "[0.44230387 0.89686526] [3.53843094]\n",
            "[0.3745593  0.92720296] [3.46959229]\n",
            "[0.40570314 0.9140049 ] [3.35713275]\n",
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            "[0.36935701 0.92928758] [3.48784476]\n",
            "[0.40039529 0.91634252] [3.37669118]\n",
            "[0.43202243 0.90186286] [3.45617945]\n",
            "[0.36361057 0.93155105] [3.50783238]\n",
            "[0.39452912 0.91888344] [3.39811785]\n",
            "[0.4260526  0.90469839] [3.40842082]\n",
            "[0.35726222 0.93400412] [3.52970273]\n",
            "[0.38804472 0.92164054] [3.42157353]\n",
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            "[0.38087563 0.92462628] [3.4472284]\n",
            "[0.41214396 0.91111874] [3.33317932]\n",
            "[0.44396771 0.89604279] [3.55174166]\n",
            "[0.37633296 0.92648449] [3.4633349]\n",
            "[0.40751217 0.91319978] [3.35042942]\n",
            "[0.43926017 0.8983599 ] [3.51408135]\n",
            "[0.37131602 0.92850655] [3.48098911]\n",
            "[0.40239437 0.91546642] [3.3693441]\n",
            "[0.434056   0.90088589] [3.47244803]\n",
            "[0.36577458 0.93070348] [3.50032675]\n",
            "[0.3967386  0.91793163] [3.39007075]\n",
            "[0.42830155 0.90363587] [3.42641241]\n",
            "[0.359653   0.93308613] [3.52149228]\n",
            "[0.3904872  0.92060836] [3.41276661]\n",
            "[0.42193716 0.90662508] [3.37549725]\n",
            "[0.35288965 0.93566495] [3.5446386]\n",
            "[0.38357616 0.92350925] [3.43759849]\n",
            "[0.41489649 0.90986862] [3.32286854]\n",
            "[0.44676414 0.89465178] [3.57411313]\n",
            "[0.37931513 0.92526755] [3.45277434]\n",
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            "[0.44235108 0.89684197] [3.53880861]\n",
            "[0.37460961 0.92718263] [3.46941502]\n",
            "[0.40575446 0.91398212] [3.35694282]\n",
            "[0.43747312 0.89923149] [3.49978493]\n",
            "[0.36941258 0.92926549] [3.48765056]\n",
            "[0.40045201 0.91631773] [3.37648304]\n",
            "[0.43208014 0.90183522] [3.45664108]\n",
            "[0.36367196 0.93152708] [3.50761979]\n",
            "[0.39459181 0.91885652] [3.39788991]\n",
            "[0.42611642 0.90466834] [3.40893136]\n",
            "[0.35733005 0.93397818] [3.52947022]\n",
            "[0.38811403 0.92161136] [3.42132411]\n",
            "[0.41952003 0.90774608] [3.35616022]\n",
            "[0.35032296 0.93662897] [3.55335763]\n",
            "[0.38095226 0.92459471] [3.44695572]\n",
            "[0.41222208 0.9110834 ] [3.33288732]\n",
            "[0.44404708 0.89600345] [3.55237663]\n",
            "[0.37641758 0.92645011] [3.46303591]\n",
            "[0.40759847 0.91316126] [3.35010915]\n",
            "[0.4393479  0.89831699] [3.51478324]\n",
            "[0.37140948 0.92846917] [3.48066149]\n",
            "[0.40248974 0.9154245 ] [3.36899302]\n",
            "[0.43415301 0.90083915] [3.47322404]\n",
            "[0.36587782 0.93066289] [3.49996802]\n",
            "[0.396844   0.91788607] [3.38968617]\n",
            "[0.42840882 0.90358502] [3.42727057]\n",
            "[0.35976705 0.93304216] [3.5210998]\n",
            "[0.39060371 0.92055893] [3.41234566]\n",
            "[0.42205581 0.90656985] [3.37644648]\n",
            "[0.35301568 0.93561741] [3.54420958]\n",
            "[0.38370498 0.92345573] [3.43713811]\n",
            "[0.41502776 0.90980875] [3.32237567]\n",
            "[0.44689749 0.89458517] [3.57517994]\n",
            "[0.37945738 0.92520922] [3.45226937]\n",
            "[0.41069811 0.91177139] [3.33857756]\n",
            "[0.44249846 0.89676926] [3.53998767]\n",
            "[0.37476671 0.92711915] [3.46886147]\n",
            "[0.4059147  0.91391097] [3.35634979]\n",
            "[0.43763604 0.89915221] [3.50108833]\n",
            "[0.3695861  0.92919649] [3.48704415]\n",
            "[0.40062909 0.91624033] [3.37583313]\n",
            "[0.43226028 0.90174888] [3.45808225]\n",
            "[0.36386363 0.93145223] [3.50695597]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sSIJhXRyJA_q",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "0092b92a-55f5-486c-8494-b897367f8a0e"
      },
      "source": [
        "xx = np.arange(-6, 6, 0.1)\n",
        "yy = -w[0]*xx/w[1]\n",
        "plt.plot(xx, yy)\n",
        "plt.scatter(X[:, 0], X[:, 1], c=y);"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cok2g8zINs_L",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "68c8f121-d83d-41be-fc7c-025d0b83cd7c"
      },
      "source": [
        "import matplotlib.animation as animation\n",
        "\n",
        "eta = 0.001\n",
        "n_iter = 100\n",
        "w = [1, 10]\n",
        "w /= np.linalg.norm(w)\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "line, = ax.plot(xx, -w[0]*xx/w[1])\n",
        "plt.scatter(X[:,0], X[:,1], c=y);\n",
        "\n",
        "def init():  # only required for blitting to give a clean slate.\n",
        "  global w\n",
        "  line.set_ydata(-w[0]*xx/w[1])\n",
        "  return line,\n",
        "\n",
        "def animate(i):\n",
        "  global w\n",
        "  # hack to make the saved gif delay between plays: don't update for a few frames\n",
        "  if i < n_iter:\n",
        "    w += eta * sum([y[i]*X[i,:] if y[i]*np.dot(w, X[i,:]) < 0 else 0 for i in range(len(y))])\n",
        "    w /= np.linalg.norm(w)\n",
        "  line.set_ydata(-w[0]*xx/w[1])\n",
        "  return line,\n",
        "\n",
        "ani = animation.FuncAnimation(\n",
        "    fig, animate, init_func=init, interval=200, repeat_delay=5000, blit=True, save_count=n_iter+10);\n",
        "\n",
        "# To play the animation in the notebook:\n",
        "# from IPython.display import HTML\n",
        "# HTML(ani.to_jshtml())\n",
        "\n",
        "# or see below to save the animation to gif.\n",
        "# (Be careful not to run both, or the gradient descent will have already started.)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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+1IZxoCriPOoksoNTgesEJPPKqD0UKrwRVXIiGBtBhQEB2/ZI7rROfwecKonmyHUg7yA+j5/Tt7mYkrVlhENhAKx2K1uMHMz9X92CiHDSkPNYt6LxaSeH286ji+5msy2aLveplOKkIeezfmX0OU0mYc/jd+Wq6Re1/g1pGqB8n6DKLwfVxHSKOJGcRyKde2oYJadD4FuimyfbwX0GpsxL2mW86a5dFztF5GVgHrCViKwWkTOScd6u5ItXvqGypKouiAME/UH++nFlXa3yM24/MaZ0bkPhkEFWfkazrlm2sYKStWUxxw1DsfCjxS0YvaYloCqJWzcl5nlelPf1TX80PHGCOIAfvG8kc4TdQlLmyJVSE5Nxnq5s6YJlcSsiKkPx148r2XaXrdjzuHEYhsFTV7/EhlVF1PWKq2G1Wxl94A5k5TVv04/DbY+kv8ThztYV5rQksO2cYONMHCoQydDyf4KqeprYIF77vDjNn7VGdc5s/C5owNb9sMdpwmyymOhXb5pk74m78eKKR/ko/BqTp5yEw23HleXEarcycr/hXPHsBc2+ptPtYOdDRmK1R39e2112jrzkoASv0rTmE3MfcJ9BZD68sSe6EOehqKr7UWX/B6GFCZ5oAcd+zbq2UgbKNxuj9DyM0otQ/i/ipvJ2B0mbI2+JdJkjL9tYzruPf8wfC5YzZPtCDjlnPHm9c1t1rqqyak4acj7VZZ66HzazxUyfwT156tf7MZnif6b6PH5WL11Dbu8c8vu0/NrV5dXccPgUfv9+GRabhaA/yPhT9uTC/52Z8Jqa1lLKPw/lfRUML5g3A+/rQBgIAi6w7wJZN8LGfYguRFWfE0y5SMGbiCmv8esphSq7uKawVW0xOyc4j8CUfWNy3lQn1O6LnS2RDoF89Z9ruXDnqwh4AwR8Qax2K1a7hQe+uY3Cbfu36px///4v9535KL999ydiEkZP2IFLp51Dbs/sJI8+1j9L/2X9qiIGDRvQqg8ETWsJFfoH5X0bVAVi3zPS3s3/Bar8MlBVsS8w9UIyLgLnwYg0cXcPqMB8VOmZkfKyURxI/gzEmqBUbppLFMh10awEHrno6ai756A/SNAf5IFzpzF1zi2tOueArftx/9e3EvAFEJNgtVmbflGS9N+qH/236pe08xmGgVKqrumGptUnlv5IZvQ0oDLlAfF62prAvjvian6/TuX/Kk4QJ3L+wDfQRQN5Ivq7dQI/fP5L3Pm2JXOXYhiNN1iuTynFkrlL+fiFL1nx8yoAbA5bhwbxZCrdUM5NR9/DgY4TONBxAlfufwvrVsaW9tW0GNbhNY0jGoYdW8sLUUkm8Rs4W0Cal9XVleg78gTsTlvcjj0WqyWmMUQi5UUVXDzumkgetwgmkzBiz225ceYV2OzJDeShYIiZD77Pu49/TNAXZLejd+bEa49qdoZLc4TDYS7d7TrWrdhQl0b5w6c/c+HOV/P88odxuh1Ju5bW9YgI5D2LKj0XQn9FWrthgqybEevQlp3LeQiq6qE4DyhwjE/OgNOIviNPYP/T9sLmiA62VruVfSft3uxAfvG4a/j3z3WEgmFCgRABX5BFn/zMS7fNSPp4bznuPp674VXWLFvHxtXFzHpkNheMvgq/N3ET6JZa+NFPlKwrjcqFNwyFr9rHF698k7TraF2XmPtgKngLKZiF5L2A9JyHydnyDCox90Zy7gNxRe7AJQMkE8l5HDFltcPIO7e0CuQduTB7+m0TGbb70Jp+m07sLjtbj96cc6c2r+Xab9/+wb9/xjaSDYfCdc2ak2XFz6tYOPvHqHotwUCI0vVlfP7K3KRdZ/XSNXHb0fmq/az6renyAppWSywDEet2iDS+Aa7Rczj2RXp+i+Tcj+Q8hPSch9h3TuIo00daTa3c8cHvvL34Xwrz3Qzu4aYw301hgZtBBW4G5LlwWJO38GZ32rnzw2tZueQfVi35h8226suQEYXNfv2cGfMSPuat9CV8rDWWzl+OmGK/Jfiq/fw851cOOG2vpFyncLv+kRTGBlNOjgxHi/7faFqyiDjAvnvTT+zi0iqQb98/h+KqACuLq5m9ZD0l1ZvuQEWgb7aTQQVuCgtcFOa7a/7bTf9cFzZL6758FG7bv1XphjZH4juNQcMHtmosifQcUBA3kNscVvpunryu5NvvvR19Bvfin9//rQvmZouZzFw3exwzNmnX0TStZdI6j7zcG2RlUTUri6tZUVTNyqJqVhR7WLGxigrfprtGs0nolxMJ8oMK3BTmu+ru5PvlOLGYkz/DtOLnVZw/+iqC/tjtxo8tvpshwwuTdi3DMDhliwvZ8HcRRnhTRo0zw8EzSx9Mat54dXk1j1/+Al+8+g1GWDH20FGce98prd4opWla83WrDUFKKUo9wbrgXhvoa/9cHdi0WGc1C/1zNwX2wgI3g/Ijd/V9s52Y4tzpNtfLd7zJCze/QTgcBqUQk4nzHzydQ85O/qr6xtXF3H7i/fz+3TLEJPTcLJ8rnr+QoTtvmfRraVqtTts8uR0o5UV53oLAl5ENTK4TI709O1C3CuSNUUqxscrPyiJPzR18zZ18TcD3BTfd0dosJgbmuTbdyRe466ZsemXZm5W9smb5Oua9swCz1cyuR46hoG/jW4/bqqK4koA/SH6f3GZn12haSyn/3Eg/y/DySE63+1TEfR4YGyC8HiybI6bm53Or8DpU1f/A/zWY8xH3mYjjgHZ8By2jjCpU8dEQXgt4ieSJ2CD7LkzOCR02ji4dyJVS/PbdnyxbtII+g3uy437DW7Xj0DAU6yt9NXfunqgpm1XFHgL1py2sZgbmu2IWXQvz3RRk2HQQ1bosFfgRVXISUH/R3gGmPDCKQayRiogZkxH3+U3+LqjwBlTRwTVb92unRM3gmIBkT0Ek9Ut5RtWjUPUIMXViJDOSLdOG7JuW6LJb9P1eP1dNuJ0/Fy7HCCvMVjM5PbKY+tUtLZ4bNpmEPtlO+mQ72WVI9GNhQ7GmzMvKujv4SKD/fW0lHy1ZT8jY9IGYabcwsP6Ca71An+uy6iCvpTVV9TDRQZzIn401NU+oCXbVT4C5EJwHN36+6qdrGlPUz4YKg+9dVGgV5L+U+o5BvtnEL/ZlQOj3yK7VFEr7QP7irTNY+v2fBHw1i4o+8Hv83H3qw9w5+7qkXcdsEvrnueif52K3LaJbpIXCBqtLvXXTNLWLrj+tLuf9n9dSL8aT7bRSmO/aNB9fL9BnO9Nz277WzYSWNe95youqfhJpIpATmEekSmK8ay1FeV5B3M3bv9FuEm0yUuFOURIg7QP57Gc/3xTEaxhhg8VfLMFb7euQbeMWsykyf17ghq2iHwuEDP4p9UTNw68s8jB/ZSlv/7gmqu9DnttWE+QzGFTgipqTd9vT/q9K6yqsW4F/Dc3qDGQUN/0cc7/IXW3c8wXA+w50QCBXygf+L8GoBvsuiLl33WPimoQK/tigUJcJzP0Ry+B2H1tT0j46hILhuMcFMELxH+tINouJIT0yGNIj9lPbFwzzd4knJrvmm2VFzFgU/dW1R6adQfVy4+sH+mRuhNK0pkjGhSj/PCKLfo0xgW2Xps/nPjNSzTBRnfIOmFZRgUWRsri1zaIrQqiMszFlXBh5gn0/cE4Cz3MgtshzTLlI7mPtPrbmSPtAvtuRY5j9zOdRAV0ksunGne1O4cia5rCa2bJXJlv2ii1s5QmEYhZcVxZX8+nv6ymqCkQ9t0+2I3Ln3qM2dTIS6PvnubBbdJDXkkus20LeU6iK2yC0FEzZYN0V/LXzyIpIFUIXkhnd4FuF/gb/F5Fg6BiPmPIQ246orNug4gpiy9w6EVf7dpJUKoAqPTu2TnrVkyjbzohtJ0QEyboc5T4Fgj+AqQCsO3aa9a60z1opL6rggjFXUbaxAl+VD7srUiJ26le3tLoBRGdX6QuyssjTYE4+EvDLPJummUwCfaM2Qm26o98s14m1HTZCad2XCvyAqn4Cwv+AbUwkhbDe9IRR9T+oqr2DFSAEtr0Q90Sw7YIKLoWSkyLHMQAFzoOQrDvaNWAq/9eosoviNLwQcByGKWdKu127pbp0+mHAF+DL1+bx23d/sNmWfdnv5D3IzE39AkQqlHkCdXPxK2py5VcWV7NiYzWV9QpeWUzCZrnOugXX+oG+b44Tcxs2QmlaQyr4C6r4BGKzXQCcYB2O5D0V+aP/CzBKwLYTYhkS5/k15zTKwKgEc782bUpSvk9R5ZfH71xk3x9TbpxyuSnSpQO51jSlFMXVgZhF19r/9tTb7WoxwcC8mqmaqN2ubnpnOdq021XrnoyK28HzPPE7BAE4IPMKTO5JTZ5LGRWo8v8D/zcgNVM4WTcjzWzaHHu+StSGccR8yIgLyb4DcUQ2/CgVgNCfIBmIJbn1kpqry+aRp5PitaU8fc1LfDtrITanjYMm78txVxzWId2CRISCDDsFGXZGFUbvLlVK8fmHP3LH5S/izXDjz86gKDeL0HaFfPVnEf7Qpl8+h9UUCfL1F11r5ud7ZDRvt6vWDamaqZKEfOCdCc0J5KXnQnAxEAQVjKQ5ll0G+S9H5u9bSEyZqKwboOKmyDkJR+qcW3cCe6SchuH9ECquAQxQYZSlEMl9FDEnr31iW+g78g5SXeHh9G0uoXxjRV1jBrvTxo77Defmt/6b0rFVFFdyYuG5+KqjswYcbjsvrHyEarN10518veyav0s8BMObfn7cNjMD891RJQ1qA32eW+927cqUMiC4EIwKsO2ImKI346nAAlTJGTSa6WIdgSn/9cavE1oV2QUak+FiAseBmHLua9X4I+dehvK+CUYFYt8H7HsgYkIFl6KKjyH6jr0m9bDgow79udZ35Cn20bOfU13uiequ4/cGWPjxT6z69R8GDk3dwuyXr81FGbEf6ErBV69/yyHnjKdfjpNxmxdEPV6727V2euavjZF/L1lTzodL1hGuv9vVYYmah68/ZZPt0huh0pkKLUeVnAaqEhBQAVTGxZgyztr0JOtIcB4F3jdINE8uzmObvpixPpLxohoGciOyyNoW5gFgGgiBt1HhfxDlQTkORHleInbDkgHGxsg3A9sOcU+njBJU9VOR3HRTAeI+HWmn2uk6kHeQX75Zit8TmydrtphYvnhlSgN5RUlVTLMIgKA/SGVJnAWgGvV3u+5O9G7XYNjgnxJPzKLrwlWlzPopeiNUrstaF9SjdrwWuMnQG6E6NaWMyJ22sZ6oqZOqh1HW4Yh9DBCZ2pPs61GuI1DVL4PvHSKFp0KAFezjwHlk0xe0bBkniAPYwNb67kB17yP0U92mHxVYDIGvIFwCxNuTYgKjKP75jBJU0SFglBH5EPgjktWTeQkm92mtHmci+rekgwzYph9WuzW2PrmC3oN6pmZQNXbYZxiv3DkzZmrF5rCywz7DWnVOq9nE4B4ZDE6wEeqfEk9Mds28v4p584d/o55bkGGvm55pmGHjtOkc+ZQL/gyqjNj5by/K82JdIK8l1mFIzjCUcQ34P47s/LSOQmwjmnU5MeWgXKeC5wU2TdOYQdyIqw27PwNzIPRzg52bXvC+D65TIfAdMdNCKgDW7eOeTlU/D0Y50XfyXqicinIei5iSu8dFB/IOctDk/Zhx37tRgdxsFXoPymabFNcM32bMFoyesCPff7CoLpg73HbGHLQjW4/ePOnXc1jNbNErky3ibITyBsKbCpPV5cl7+OKPjWxcGN0XtHeWg8ICV0z6ZP8kt/3TGqGqSNj6V5UnfJmY3OA8vNmXKV5byvwPfsBsNTP24HNwZ28ZmbYwSsG+O5JxAWIuaPpECSj/N6A88R4BUw6Ye9WUsK252REnOE9EzD3ivIbIdAqB2ONiiZQjsI1s9VjjScpip4gcADwAmIEnlVJ3Nvb87rjYCbB0wXLuOe1+Vv+xFoCRe1Zx2X3rye47Dsl5AJHUBR/DMPjytXnMfvZzRGD/U/di92PGYjJ1nk1DVf5QVF58XaAv9jTa9q+udk1+JMjrjVDJo4wq1IZdiJ33dkLmlZjcbd+V+dbD7/PEFdMxmU2ICEbY4KoXL2bc4aPbfO5aRtVjUPUwMcFX3EjWrWDfA+V5LlIFUTIR98lgH59wodMoPQf8n8V5xIEUzGp1+mK75ZFLJPr8AewHrC0U2UEAACAASURBVAbmAxOVUr8mek13DeQARtEhVBUvw2I1cLhq/987a3JoT0zp2NJZuScY0ySk9r8btv3bLNcZteg6sKYaZXu1/evqjOpXoPJ2IkHQAJxgGYTkv9rm8rOrfv2H83a6koA3OsDanTZe+ucxsvJiv9W1hgqvQ20cT2wueRbS8+tIk+eWnC/wParkzAbns4B1O0z5r7V6nO2ZtTIaWKaU+qvmQq8AhwEJA3kyKaXwVfuwu+xJuXsM+AJ4Kr1k5Wcm/W5UhddAaCUZ2Q0XTrzgfQV0IG+1bJeV7V05bN8/J+r4prZ/VXVz8bUBf8HKkrht/+q6QSWx7V9XZnIfj7INjWR3hEsQx3hwHpKUGuKfvfw14WDsQryYTcx7ZwH7n7pXm68ROV9vyP0fquxS6soDSAaS+1iLgziA2Eajsq6ByjsAUyTf3bodkvu/pIy3oWQE8n5A/byf1cCYhk8SkcnAZIABAwYk4bLwziMf8twNr1FdXo0ry8Wk64/miAsPbFVeZ8Af5JFLnubj575EKcjMdXP+g6ez+9FJ7A6vAkRqTCR6LDnWrljPV298SygYZpfDduqyNWeaQ0TIc9vIc+cxcmDsRqiNVX5WbIwtafDN8qK4bf/ilTRobtu/rkysw5Hs5DdXCPiChMOxu0GVoQj6YwN8W4h9N+g5D4K/RLocWYa2aeu/yXUcynl4zW7QHMSyWRJHG63DFjuVUtOAaRCZWmnr+T585jOmXTG9LqWvsqSKZ65+GavNwiHn7N/i8009+3HmvD6vrrZ5yboyppz6P3J6ZjN896FtHW6EeSCYcsFY2+ABOziaKL7fTLMem81j/3kOw1AoQ/HSbTM46rJDOO3m45Ny/q5EROiZ6aBnpoMxg/OjHmus7d+XSzfGbftXP3VSt/1Ljl2PGMOsRz+KSd1VhsGYg3ZM+vVErAnzwlt3PjtYt0va+RJJRiD/F6h/y7dZzbF29fwNr8X85fo8fqbf/Eajgbx0fRkfPPUpq35dzdZjtmD8KXtihA3mvDY3pkGF3+PnpdtmJC2Qiwjk3IcqPSPSWQQ/4AJLf8R9epvPX7SmhEf/8xzBeu8jHAoz495Z7HbkGDbfflCbr9FdNNX2b225ty6w17b9W7quko9/jW77l2G3UFiz0Dq43pTN4AI3Oa6O6fPYEiq8AeV9G4yNiG1sJCMkhYvwQ8duyb4n7c6n0+cwdvw6Jv1nPfm9g1RX96eg5yogv8lzdAfJCOTzgS1EZBCRAH48cEISztuo4rWlcY+XrCtDKRX3Lmj5jyv5zx7XEwqECPiCfPPW97xyx0yufPFiLFZLTCAHWLN8fZvGqZRi3jsLmP3s5xiGwX4n7cG4w2Yj/rcgvAaxjQbHfklp3vrtrIVx53GDgRBfvfGtDuRJElkwdbFZbvy2f/+WefmrqLrJtn85LmskPz6/wZRNgZssR8fvdlX+uaiyc2tuMgIoz2tgHQp5z3ZYc+GGRISLHzmLY84toyDnB6y2yO+o070KVXIq5L3Q7Bz0rqzNgVwpFRKRC4DZRNIPn1ZKLWnzyJrQd/PerF66JuZ470E9E36VvfeMR/BUbErq93sChAIh3pv2MYYROw9nMpvYZuct2jTOe898lC9fm1uXn734s1+Yc9COXPPypc3+yh3wBfjl699BhGG7bZ2wyFbkdPHPqb/edwyL2cTAfDcD82Pb/vlDYf4p8UbVq1lZXB237V++21av1V8khbL2zr492v4pFY4s9EVtiPFA8BeU53UkpQvxYfr0ejWyYBjFh6q6F8l7PiWj6kyS8hOhlHofeD8Z52quyVNO4rbjp+Kvl5Zkd9mYPOWkuM/3Vvv466dVMcfDIYMFHy5m4lVH8PLtM/HVTNeIgM1pY9J1R7d6jMt+WMEXr36D37NpjL5qP9+9t4hf5/3Btrts1cirI77/4AdumzgViNzdK0Nx2PkT2P+0Pem/VXTltbGHjuKRS56JOYfVZmGPY5O4aKu1it1iZvOeGWzeM3Hbv9p6NbWpk18v28iMRdFTiD0z7VGlheunUbZ6I1ToV+JuYMEHvrdSm1FllCROBgj+3rFj6aTSdmfn2ENGcf0b/8dTV73Iv8vW0XdIL067dSJjD4lJsQTAbDEnvCu1OaxMvOpIemxWwCt3zaR0fTlDx27JGXecGBMsW2LRJz/F7Snq9wRY+PGPTQbyknWl3HzMPVEfBACvTnmLmQ++xy6H7cSV0y/CbI788ub1zuWiR87iwfOeAKibYpp49ZEMGpaa+sla8zSn7d+K+nfyRbFt/0SgT5YjZsG1sMDNgDwXNktjGRgWEpeZTXFRM1MOCXePmrtvRlZ9aRvIAUZP2IHRE5q3wmyzWxl94I58//6iqOBqc9o48Mx9EBH2O3kPdj5kJHPfnk/AG8CV6WzT+DJy3FitFsINgrnVbiEjp+laC1+8Gr8qIUTSsubNWsC7j33EYedPqDu+/6l7seO+w/n6ze9q0g9H0W/zPm16H1pquWwWhvbNYmjfrJjHKnzBeiWGN2XXvPfz2pi2f/3qbYSq3+N1s1wnZsvWIDmx29TFibiOa++32CgRG8p1UoP6KgCOmJ6g3VW3qkdeXlTB5fvexLq/NkR6ZRsGw3bbhpve+i82u5V5sxZw2/FTEZOgDIVSihOvPYoTrj6qVderLK3ihAHnxBSjsrtsPL/sYfJ65yZ4ZcTzN73G9JvfoLG/o4FDN+PJX6a2anxa11bmCcQsutb+d8O2f/3zXBTmGQx0f0ZhThGDctYzKKeYPj1GY8md0qZ86mRQKoyqeijSxV75wZQXKQHgTE7abrrQrd5qKKVYMncpa/9az+DhAxkyohCA6vJqjus3OWYaw+6yMXXOLWyx4+BWXe+Hz37m5qPvjVpMveblS5v1TWLJ3KVcuf8tMR8E9fUq7MH0vx5p1di07qm27d+KmGYhHlYWVeGtvxHKbGJAvqtu0bX+tE2vzI5v+6dUOLIgK+5uuYCvG0vUEBG2G7c1243bOur4d+//gClOnY2AL8gn0+e0OpDvsPcwXlv3BL98/TvKUGy32zbY7PHnHMPhMH8s+AsR2GLkYIaO3ZIxB43k23cXxHzAAFhsFnY/uvU1mLXuqX7bv53itP3bUOmPCvK1c/Nz/txIoEHbv0j65KZuULXZNe3V9k/EDNL5G6ur4O+RphOmXmDfDZH2DbXdLpAnEg6GifvlRKm4TRdawmqzssPejdf1/vmr37jp6HsI+oIoIguwN755OVe/dDHfvDWfGVNn8du3fyIihENhHG47eb1zmHjVpmL8SikWfPQjX70xD7vLzvhT9mz1B5DWPYkIvbIc9MpysHOc3a5rK3zRlSeLqvljQyWf/r4+qu1fht3CwNr8+AbZNbkua5e9m1YqhCq7BPxzIgdqP3jyXkQsySlNEk+3m1rxVnnZ8HcRBZvl485y1R0v3VDOpMJzYzYFOdx2bn33Kkbs0fKmrs1VUVzJiYPOw1fVsPIaXPDQGRx23gEAbPiniPef+IQ1y9ezw97bsdfEXXG4IoWJlFLcNvF+vntvIb5qP2ISbHYrh56/Pxv+Lmbp/GX027w3J157NMN226bd3ovWPdVuhNo0VbMpy2Z1qTeq7V9Wbdu/OK3/sp3p3fbPqH4BKu8mpr+nZWtMBW+1+fzdfo7cMAyeuvol3n7oA0wWE+FgmAln7sO5U0+tS9+b9dhsHr/seULBMOFwGIfLzl4Td+XSx89u1zuIWY/O5vHLn084fXLRI2cy4fR9Gj3Hwo9/5MYj7447n167eAuROf8rX7iIXY+IqWumae0iEDJYXerZNF1TXF2XTrmm3Bv1TTjPbdu00zU//dr+GRsPhPCyOI/YkR4fR6ostkG3nyN/8/73ePvhD6M2EH349Gdk5mZwyk2R9KpDztmf7ffajs9e+hq/N8C4w0czdOyW7f41sKK4Km55AIBQIMRz17/aZCD/+s3vEi6K1k9h9HsC/O/ipxl3+Ogu+/VW61xslua1/aufJz93WTFvLoou2dQj015XVnhgfnSufOdp+5eoiqkktcJpQ90mkL9+zzsxRbb8ngBvPvAeJ994bF1Q679Vv7rA3lFG7DkUu9OWMBAXrynFMIxG66Pb3XZMZhNGnJKfDZWtr6CqrJrM3M6/aKR1bY21/fMEQqwq9sRk13z2+0aKqhK3/as/XdPhbf8cB0P1k8QEdFN+u25e6jaBvKI4fjd4T4UXwzDqpldSYdtxW7PDPsOYN2tB3M11Bf3ymmxyMf7kPXn30Y+ivnEkYrKYcLjbXvRf09qTy2Zhmz5ZbNMndiNUpS9YF+TrNwuZvWR9o23/Ggb5ZLf9E/eZKP/HEPoX8AB2EDOSc2+7fgPuNoF8yA6FLP0+du5qwDb9UhrEIZIpcMOM/+ORS55l1qOzo6ZC7C47p93WdN/DwcMHcuZdk3jiihfqyhEE/EHEJFFlbe1OGwecsXfCwlualg4yHVa265fNdv2yYx4r9wQj8/DF1VG1a95evIbKRtr+1c7NDy7IoF+uE3MrcuTFlAH5M8H3ESrwHZj7Ic6jEjdpTpJus9i5ZO5S/jv+ZgLeYE0Nksj2/Jvf+i877pv8ziat9eVrc3nq6pdYt3IDPfsXcOotx7HvpD2a/frSDeUs/OhH7E4bI/cfwZv3v8crd76FyWwiHAyx1wm7cvEjZ+lArqU9pRSEfoHwRrAOazJYNtb2b2VRdWzbvzxX3YJr7eLroB5u+mR1/EaoWt0+awVg2eIVTL/5DZb/uJKBQzdj0nVHs/XotpWpTQc+j5/1qzaS3ye3WTVeNK01lPKhKqeC943INnrbzkjWda3uGN/otcIbUCUnQngNkYJaClwnIplXtmoKo7btXySbpiqq7d/K4uqotn92iymSI5/vjkqjHNzDTc/M9m37pwO5pnVTSinwfYDyPAtGOdj3RjLOQkx5Tb62JYySMyDwPZHOVwACkon0+Cip11JKoTbuCsbGBo/YkezbEechSbsWxLb9qwv0xdX8XeyJavvnsplrMmpc9Xa8Rv7Jd7e97V+3Tz/UtO5KVU2tKTZVUznQ8zzK9y4UvIuYYueYW3WN4J8QmM+mIA6gQPlRnleQjPOSch0A5XsnThAH8KOqn016IG+q7d+aMm/dPHxtkbLf1lby0ZLotn+ZdguFBW6uP2RoTGmEttKBXNO6MGWUQPUzRAfYIBhlNQH27ORcKLwssh095gu+H4I/J+catbyzEj9mbGjRqZQKQGglmHJbtSBprqkc2T8vtu1fMGzwb6m3bh6+No3SbUt+2NWBvJ1VlFRSUVxFn0E9MVs6y6YFrdsI/gpii8xZR/GD/ytIViA3F9b0+mzIBpZkl4RopE+Adftmn8XwvAmVtwEGqCDKNhrJmZq0bylWs6luobRh279kS22R4S7MU+nlxqPu5vh+Z3PujpdzdM8zmP3c5206Z8AfxO9NXNJW02KYCkDFK/pmAnPru181JNZtwDoMaNCkWWyI6/ikXQdAXIfFXqdW1tXNOocKzIeKG0FVgqoGAhD4DlV6QbKG2aF0IG8nd5z4AN+/v4igP4iv2k9VWTUPnf8Uiz//pcXnKl1fxnWH3smhWSdxaNbJXLzrNfz9+79Nv1Dr9sS6NVgKif3ybUPcpyT3WrnTwHkokSArYB2J5L2CmHsm9TrY9wbHfkDtpjYBzJB1NyZz87phqaoniS5sBRCE4GJUaHW8l3RqOmulHZSsK2XSoPMJ+mPrp4zafwR3fHBts88VDoc5fZtLWL9yI+FQ5KuriJCR6+b5ZQ/rdEKtSSpchCq7KDJXLWbAClm3YHIe0D7XUwpQ7dpVSCkFwUUo/5eRzBjnIS0qSGUUHQah32IfkAwk92nE1vwpmo6ks1Y6UMm6Mqx2S9xAvn5VUYvOteiTnyldV1YXxCHyQxzwBfn0xTlR/To1LR4xFyD5L6HC68CoBMugdm10EEmxa98NMyICtpGIbWTrTmAbC6FlQIPfURUCS/rtLdFTK+1gsy37xi1eZbaaGbHn0GafZ+1f6/no2S8IxPlA8Hv8rPotMr3iqfTy+Svf8NFzX1C6vqz1A9e6NDH3RqxbJCWIK6VQ4fUoo2N+3pRSGJ63MTZOwFi/E0bJmZEuPK0k7jNBMom6lxUnZFyEmNLvW66+I28HDpedk288ludueK2u4qLJbMKZ4WDilUc06xxPXf0ib97/HkopwsHYbABHhoOtRg1h/oc/cPPR9yJmQSkwQmEmXn0kdqcdT6WH0RN2ZOvRm+uStVrSqMBCVPkVEN4AGCjbKCT7nlal70WmYfxA4zsiVfUTUPU/oCYXPvAVqmQB5L+BWDZv8XXFXAAF76CqHoPAV2DqgbjPQByNl4vurPQceTv6euZ3vDrlbUrWlrLDPsOYdN3R9C5seuHnxy+XcO1Bd+DzxM9QMVvM5PfN5aFvb+fkzS+MKc8LYLGaCYcMbE4bexwzlv97+jwdzLU2U+E1qKIJmzYXAWAB80Ck4P0W/YwZ3veh8s5I7re4wX0W4p4cM7eulB+1YQwoT4MzmMA+HlPug61/Q2lGz5GnwK5HjGlVJ57Zz3yeMM3Q7rKz+9E7c9Zdk1j0yc8Ji/eEau7i/R4/c96Yxx7H7sLoCTu0eCyaVp/yvBInnTEExloILoJmzlkr/xdQfiV1mSOqEqoeQFVNQ1kGIu4zwHFQ5IMh/C/x59yN5G82SlN6jrwTCviDcRtBu7KcXDX9Iq549gJye+UQ8AVozjcqX7WfT6bPaYeRat1OaCUxC4QASE0Bq+ZRlfcTm/4XBqogtARVcQ2q+uHIYVMPUPE7aGFpv2YN6UQH8k5o7+N3xeF2xBwPBcNsv/d2dX/e6YDtm9URCCJz9JrWZradgNifTVQIrNvFHk8k3ESutvJC1TSUUYmYMmvy0xte14m4k1fDJZ216bdbRI4RkSUiYohIzLyN1jo7HzKSnQ7Yvq6Lj9lqxua0cem0s3FnueqeV9Avn1NuPh6709ZofWSH2874k5tf01zTEhHnEWDKBerXs3eAfR/EMijua5RRgvJ9ggp8j6rdxt+sBcoAquQElP8bJOtGcB5JZBOQLXKXnn0HYt+5Te+nq2jTYqeIbAMYwOPA/ymlmrWC2V0WO9tCKcXiz3/h21kLcGe72WfSbvTbPP6utWWLV/DJC3PwewP0HFDA9FteR8REOBTGbDYx4cx9OO/+0/Rip5YUyihBVT4M/o8iKXuuExHXpLhpjUbVNKh6CMQKqMiGm7xnwChFlZxG4mbF9Tkg+y5MzgmRIleqCiSnXTccdVbtWo9cRL5AB/JOo6K4kq9mfIun0sfoCdszcKieR9Q6nvJ/hyqdTF3KIAACpj5Ij89QvtlQfglxG9U2ZOqJ9Piq29+MpDxrRUQmA5MBBgwY0FGX7Zay8jM5aPJ+qR6G1s0pz4tEB3GI1Cgvh+BPmJwTMLwvQ2ABEK+wVz1GaSSzRWIbMWvNmCMXkU9E5Jc4/xzWkgsppaYppUYppUb16NG+jUibI+AP8sLNr3PCwHM4ts+ZPHTBk1QUV6Z6WJrWdajyBA9IZHoEkJwHwDqCyEJmIzsqxRKZxtHiavKOXCm1b0cMpKNdd8id/PLN7wS8kTm695/8lPkfLuaJn+/F7rQ38WpN05pkPwACi4m5K1ehurrhYspF8l/G8H4ElTeD4SF2qsUBzhMRaX3DcGV4UN7XwPcxmPIQ98mIbadWn6+z6X6rBcDS+ctYMndpXRAHCAVClG4o58vX5qVwZJrWdYjrSLAMrncnbQIckHUNYsqoe54ySqDivzXdfRoGcQHn0Ujmf1o9DmV4UMVHQeV9EJwP/tmokjMxqp9t9Tk7m7amHx4hIquBscB7IjI7OcNqX38uWkG8BRZflY9f5/3R8QNqxPIfV3LdYXdxXL/JXLLrtSz46MdUD0nTmkXEjuS/imReD/a9wHkEkv8iJtdxUc9TnpmgEmWvWBD7bm0q9KW8r9fsDq2/AckLlfeijK4xndqmxU6l1ExgZpLG0mF6FfaIu0HG5rTRd/Pm1zRub38u+ov/7H49fq8fpaBkbSk3HjmF/zxxDntP3C3Vw9O0JonYwHUU4joq8ZPCq4m/WxQgiAr+hDj2inlEqUBkEdSU1/i0i+8TYneREkmJDP4E9nGNvYW00C2nVnbcdxjZBVkxwdxiNbP/qXumZlBxPHnli/g8/qjt+n5PgMf+8xyG0bwdnZrW2YltFAlbt+FAzH2jjiilMKoeQm3YCbVxP9SG0RhV0xKXqzDlkbBWS5L6c6ZatwzkZrOZqXNuZvjuQ7HYLFhsFgYNG8C9X9xEdkHnSW9aumBZ3ONVZdVUllR18Gg0rZ049gNzgr0OYgNHdPMUVf0kVD1ZU4HRF+m5WfUwqvwaVPVTqMCCqKAu7pPY1BaulimyO9SybVLfSqp02+qHBf3yufvTG6guryYcMsjKz0z1kGIU9M2juqxh6c5I3RRXlk7F0roGERvkv46qnALeGUSmWUxgGozk3h+1MApA9RPE5qf7wDcD5TNHgr9lOOQ9iYgNsY1CZV4OlXdH0hgxIhuMcp/sMhuMuuUdeX3ubHenDOIAR116cMz0j9Vh5eDJ+2G1tT4VS9M6GzFlYMq+GVPvJUiPb5AeX2Lq+T5i3TLqeUqFQSXqSqSAUKRueXAxqvqZukdM7pOQnnORnIeRvBeRgkhehlH2H4wN4zCKDkV5321WNdHOqNvekXd2SineffzjmB8sFTY44pKDUjQqTWt/jXUaEjGjzAMg/HcTZ/GB9w3IOHvTa00ZYN8FABVajSo+IjItgwHGRlT5NRD+B8k4NwnvomN1+zvyzuqPBcv5+7fVKCM6kIvJxOxnPk/RqDQt9STzGuKW0o2ROCFAVU+r6ThU/zleqHoUZVS3cYQdTwfyTurfZesQU+xfT9AfZOUv/yTtOqFgiGdveIWjepzOBMdELt/3Jlb80tTdjqaljjj2QnIfB+sOILnED+p2cBya+CSB+UQaWTQ8uQXCK5Mz0A6kA3knNXj4QIxQ7A+a3Wlj6zFbJO06U079H2/cM4uK4kpCgRCLP/uFS8Zdy4a/NybtGpqWbGIfiyn/VUy9vkPyXwHJBGoSAMQFliGI+6zEJzBvFv+4CoCp6b66nY0O5ElWXV7NF69+w2cvf01laetTBAu37c/wPbfF5ti0qGkyCQ63gwln7J2MobJxdTHfzPwOvzd6V13AF2TG/e8l5Rqa1t7EOhTp8TmS9V9wT0ay70Xy30BMrsSvyTib2Dt5O9h3b3SOvrPSi51J9PXM77jzpAfrMk3CQYNLnzibfU/cvVXnu/HNy5l+8+u8/+SnBLwBdpqwA2fffRKZuRlNv7gZ/vn9X6x2KwFf9K66UDDE0vnxc9g1rTMSUxa4Toi77Sfu822jUNl3QMXNNfnoBjj2RbJua89hthsdyJOkdEM5d0x6MKoQF8DUsx5j2K7b0Gtgyz/lbXYrp992AqffdkKyhhml7+a9Cfpjt0abLWaGjChsl2tqWjIoZYD/U5T3bcCMuI4A2x4tygs3OQ9COQ4AYz1IVmy+ehrRUytJ8vWMb4n3M2QYii9fm9vxA2qG3oU9GbX/9tgc0dujrXYrR116cIpGpWmNU0qhyi9DlV0eaTfn/wBVejGq4qYWn0vEjJj7pnUQBx3Ik8bvDcTtaG+Ewvg8/hSMqHmuefkSJpy5N3anDRFhi5GDufvT6+k7pPMUD9O0KMGF4PsMqL/r2QveN1HBP1M1qpTSUytJMuagHXnm2pdjjlsdNnY+eGQKRtQ8NoeNCx48g/MfOB3DMDCbzakekqY1Svm/Im41Q8IQ+AqsycvqShf6jjxJ+m/VjyMvOQi7y46IIAIOt53xp+7JliOHpHp4TRIRHcS1tCCmLCBOiQqx1KQhdj/6jjyJzrj9RMYeMopPps9BGYq9Ju7KsN22SfWwNK1rcRwElQ8keGz/jh1LJ6EDeZINHbsVQ8dulephaFqXJebeqOx7oeJy6k8qSM7DNXfr3Y8O5JqmpR2Tcz+UYx4EvgfMYBsdKYfbTXWZQL7i51U8fvkLLJm7lKy8DI6+7BAOv2BCl6k3rGlaNBEn2PdI9TA6hS4RyFf/uZaLx12Ltyqyku2r8vHUVS+x8Z8iJk85OcWj0zRNa19dImvllTtnxtQL8Xv8vP3wh1SVpV9JSk3TtJboEoH89+/+jLsZx2Kz8O+ydSkYkaZpWsfpEoG8/9b94s6FB/0heg4oSMGINE3TOk6XCOQTrzoiqtwrgM1pY9cjx5DbMztFo+p4AV+A1X+soboitmGzpmldV5cI5FuOHMKNM6+g75BemC0m7E4bB5y2F//39HmpHlqHUErx6pS3OKrnGZw36r8c0/tM7pv8GMFAbGVDTdO6ni6RtQIwavwInv3jIbxVPuxOG2ZL99lu/sn0OUy/5Q181ZuKc3324lfYHFYuePCMFI5M07SO0CXuyGuJCK5MZ7cK4gAv3zEzKohDpBrjB099pu/KNa0b6FKBvLsqXVcW97gRNvBWxqsSp2laV9KmQC4id4vI7yLyk4jMFJGcZA1Ma76tRm8e93hWfgaZeeldMF/TtKa19Y78Y2A7pdRw4A/gqrYPSWups+6ahMNtR0ybUjDtLhvn3X+6LlGgad1AmwK5UuojpVSo5o/fApu1fUhaSw0ZUchD397BrkeMpueAAkbsuS23zrqKPY4Zm+qhaZrWAUQplZwTicwCXlVKTU/w+GRgMsCAAQNGrlq1KinX1TRN6y5EZKFSalTD402mH4rIJ0C8Bo7XKKXernnONUAIeDHReZRS04BpAKNGjUrOp4emaZrWdCBXSu3b2OMicipwMLCPStbtvaZpmtZsbdoQJCIHAFcAeyil9L5wTdO0FGhr1srDQCbwsYgsFpHHkjAmTdO0DqNUEKUCTT+xE2vTHblSKn4Cs6ZpWienwhtRFdeB/0tAoWw7IVm3IZYBqR5ai+mdnZqmP3/YLwAABglJREFUdTtKhVAlx4N/DhAGDAjMRxUfizLSrxmNDuSapnU//q/AKCGSbFfLAOUF33upGlWr6UCuaVr3E14FKl5BOS8qtLzDh9NWOpBrmtb9WLYEibNEKC7EOrTjx9NGOpBrmtb92HYGcyFQv7OYBSQHHAekaFCtpwO5pmndjogJyZsOzmNBskDc4DgYyZ+BiD3Vw2uxLtMhSNM0rSXElIFk3wDZN6R6KG2m78g1TdPSnA7kmqZpaU4Hck3TtDSnA7mmaVqa04Fc0zQtzelArmmaluZ0INc0TUtzOpBrmqalOb0hKM2Fw2G+f/8Hvv/gB3J6ZjH+lD3pM6hXqoelaVoH0oE8jYWCIa7c/1aWLliOr8qHxWbm9bvf4crpF7HrEWNSPTxN0zqInlpJY59M/4ql85fhq/IBEAqE8XsDTDn1YQL+eCU6NU3rinQgT2OfvjgHX7U/5riI8Nu8P1IwIk3TUkEH8jRmd9riHldKYbXrWTNN6y50IE9jB561Lw53bMlNh9vBVqN1X2xN6y50IE9jYw8Zxf6n7YXNYcXusuPMdJKR4+bWWVdiNptTPTxN0zqIKKU6/KKjRo1SCxYs6PDrdlX/LlvLj58vITMvgzEH7YjNEX/KRdO09CYiC5VSoxoe1xOpXUC/zfvQb/M+qR6GpmkpoqdWNE3T0pwO5JqmaWlOB3JN07Q0pwO5pmlamtOBXNM0Lc2lJP1QRDYCq1r58gKgKInDSSX9XjqvrvR+9HvpnFrzXgYqpXo0PJiSQN4WIrIgXh5lOtLvpfPqSu9Hv5fOKZnvRU+taJqmpTkdyDVN09JcOgbyaakeQBLp99J5daX3o99L55S095J2c+SapmlatHS8I9c0TdPq0YFc0zQtzaVtIBeRC0XkdxFZIiJTUj2ethKRy0REiUhBqsfSWiJyd83fyU8iMlNEclI9ppYSkQNEZKmILBORK1M9ntYSkf4i8rmI/FrzO3JxqsfUViJiFpEfROTdVI+lrUQkR0TeqPl9+U1ExrblfGkZyEVkL+AwYIRSalvgnhQPqU1EpD8wHvg71WNpo4+B7ZRSw4E/gKtSPJ4WEREz8D9gAjAUmCgiQ1M7qlYLAZcppYYCOwPnp/F7qXUx8FuqB5EkDwAfKqW2BkbQxveVloEcOBe4UynlB1BKbUjxeNpqKnAFkNYrz0qpj5RSoZo/fgtslsrxtMJoYJlS/9/e3btWEYRRHP4d1CgoChYiGCERjJWFgdgERYmFaIhtCsWPSsGApRr8F0TBMomNARENaqGIItgZxaD41aUxophGFCyCeCx2gwE1ibshc0fep7o7exnOsuy7M8PevR63PQVcpRgwZMf2B9tj5eevFIViQ9pU1UlqBvYDA6mz1CVpDbATGASwPWX7c50+cy3kbcAOSaOSHknqSB2oKkkHgPe2X6TOssCOAXdTh/hHG4B3M7YnyLj4TZPUAmwDRtMmqeUCxWDnR+ogC6AVmAQul0tFA5JW1umwYf8hSNIDYP0fdvVT5F5LMWXsAK5J2uQGfZZyjmM5S7GskoXZjsX2rfI7/RRT++HFzBZ+J2kVcAM4ZftL6jxVSOoGPtl+JmlX6jwLYCnQDvTZHpV0ETgNnKvTYUOyvedv+ySdAEbKwv1E0g+KF9BMLla+f/G3Y5G0leLu/EISFEsRY5K22/64iBHnbbbzAiDpCNANdDXqjXUW74GNM7aby7YsSVpGUcSHbY+kzlNDJ9AjaR+wAlgt6Yrtg4lzVTUBTNieniFdpyjkleW6tHIT2A0gqQ1oIsM3otl+aXud7RbbLRQnuL1Ri/hcJO2lmP722P6WOk8FT4HNklolNQG9wO3EmSpRMTIYBN7aPp86Tx22z9huLq+RXuBhxkWc8vp+J2lL2dQFvKnTZ8OOyOcwBAxJegVMAYczHP39jy4By4H75Qzjse3jaSPNn+3vkk4C94AlwJDt14ljVdUJHAJeSnpetp21fSdhpvBLHzBcDhjGgaN1Oouf6IcQQuZyXVoJIYRQikIeQgiZi0IeQgiZi0IeQgiZi0IeQgiZi0IeQgiZi0IeQgiZ+wnTeCNY1/Z1NQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1ZOIcBRxVzNW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 164
        },
        "outputId": "e578da55-da4f-4559-97d2-a2019925755d"
      },
      "source": [
        "!apt install imagemagick"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "imagemagick is already the newest version (8:6.9.7.4+dfsg-16ubuntu6.8).\n",
            "The following package was automatically installed and is no longer required:\n",
            "  libnvidia-common-440\n",
            "Use 'apt autoremove' to remove it.\n",
            "0 upgraded, 0 newly installed, 0 to remove and 39 not upgraded.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0X5oxQnuQusB",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "ani.save('small_learning_rate.gif', writer='imagemagick', fps=None)"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ay11ZDcPVCxC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 8,
      "outputs": []
    }
  ]
}