pytorch_BinaryClassifierModel.ipynb

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              "device(type='cpu')"
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      "source": [
        "#USE TENSORFLOW PLAYGROUND TO SIMULATE BEST PARAMETERS/HYPERPARAMETERS FOR MODEL (https://playground.tensorflow.org/)\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import torch\n",
        "from torch import nn\n",
        "import sklearn\n",
        "from sklearn.datasets import make_circles\n",
        "\n",
        "device=torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
        "\n",
        "device"
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      "source": [
        "n_samples = 1000\n",
        "\n",
        "X, y = make_circles(n_samples, noise = 0.03, random_state=42)\n",
        "\n",
        "len(X), len(y)"
      ],
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            "text/plain": [
              "(1000, 1000)"
            ]
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          "execution_count": 2
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      "source": [
        "print(f\"First ten values of X: \\n{X[:10]}\")\n",
        "print(f\"First ten values of y: \\n{y[:10]}\")\n",
        "#looks like binary classification"
      ],
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          "text": [
            "First ten values of X: \n",
            "[[ 0.75424625  0.23148074]\n",
            " [-0.75615888  0.15325888]\n",
            " [-0.81539193  0.17328203]\n",
            " [-0.39373073  0.69288277]\n",
            " [ 0.44220765 -0.89672343]\n",
            " [-0.47964637  0.67643477]\n",
            " [-0.01364836  0.80334872]\n",
            " [ 0.77151327  0.14775959]\n",
            " [-0.16932234 -0.79345575]\n",
            " [-0.1214858   1.02150905]]\n",
            "First ten values of y: \n",
            "[1 1 1 1 0 1 1 1 1 0]\n"
          ]
        }
      ]
    },
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      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({\"x1\": X[:, 0],\n",
        "                   \"x2\": X[:, 1],\n",
        "                   \"label\": y})\n",
        "df"
      ],
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              "           x1        x2  label\n",
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              "997 -0.136900 -0.810012      1\n",
              "998  0.670362 -0.767502      0\n",
              "999  0.281057  0.963824      0\n",
              "\n",
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ePSbnqnCrad5YlQmTrue+e+dw7GjeMRlCwM+/3Urz5uXyPH/3HT8weVLehqA/EotEkZriznPe9TfUYca3WwLK+G52XzpdWc3vGNO0eeXF3xg96i/S0sJbnyYURj7VjpFnxB2B1wPYsskYDh5M8fn7E8Jr/Py99pBPg8kwNLpfXZOvJt+QfWzd34foefVkjmduvUnpNQqlhPdHdWPQ4MbheWOK/wSqq7RCkQ9Onszgzdd/p37tjyie8CY1q37Ai88t4nCQ8Rr/e2c5/frkbKZ3rjD8NP3LwrJsoqMDh70Zhsb07/r4NFyklDw04qc8S/PbtvfY448uYNGSwVSrVjTX/Ph4BzNm9fVpuBw7msaUrzeEbLhUrlKERb8P5qpuNXJkClWuUoSPP7uaG2+qH1CGw6HRuEnZgOMMQ+O5Fy9n2+77+GZmHx5+9FK0MFxdg2kTcCavvfI7b72Rsx/UtCkb2bc/2e/vT0pYs9q34QJeA23p76fTsVNT3fS6dgonT2RkN6sEsj8H990zh6W/q9IVishwXhWpUyjOFUcOp9Kl00R27TyZfQM+fCiVd99exoTxf/PTL7fkuPFKKflnyzFOnXJRtWpRTp7MyG6mdy5iWLIqshqGRrXqRdm+LXCsRFSUQd/+lzBh/N9+b2xjxl5L+8sq+zy/ZvUhNm086vO8lLB3TxJ79pxizYY7+XPFPqZP3UR6mknnq6rTs1dthJ885FWrDuarAeQLL11BjRrFmDK9Nwf2J7Njxwni4500bFQGTRNcd/XkgDJu7FPPZwxOXsTHO+lyVQ26XFWDQ4dSmTxpfXbsSH7QNKhWvRjbt50IurDeS88vpkXL8tnVe7//bksw4T1BcWbtmWlTNno7k/sQrOuC9/+3gjbtLozAc8WFhTJeFArgwRHz2L3rZC7Dw7Ikx46lc8fQWcz/5RYAZs7YzEsvLOafLV4DQdMEVaoWOWdxLK++3gkEJCZGcXnHqjRp8HHAWAkh4JPPrqFp87J8M20TaWmeXLrruqBJ07L0uqGODyle9uw+GZSee/acor2oTKvWFWnVumJQc7J0DYYsAy4hwckb/9eZG/ucTjMuVz6BcuVPBxX/uzcpR2qyLwqSYTP8/lZM+XoDQsh8x8KYpmTkU+2JjXXwyIM/sX9/SsA5mg4fffBntvGSkuoOWyxO1WqnvW8LftqBJgS2D+GmKVnw0448zykUBUUZL4r/PPv3JTP7+60+PSamabN82T5WrzrA52NW8+W4v3Oct23Jzh0nQ1pT1wWly8Rx6GBqvj01miaoWas4997fMttzsXfPKawAT/pCeEvQX39jXQBmzx3ALQNmsGf3KXRDgPQabZd3rMrY8T3Rdf/7H8WD9EzkN4W3RcvyOKN03C7L77j7H2xFw4ZluKZnLZ8ZN1n8uzdwDzRdFxw5nBaSrmdS/5JSTJ7em0EDZpCW5smM/xGYpk1iopMGDctw5Egq27Yez9O40DRBseLR9LqhLk6nzvHj6Qy/e07AdW0L/jhju6ZhozKs/HN/gTxAWaxefYh1fx+iYaMymKYd8LNrmjZSSr+eNYUiPyjjRfGf5++/DwVlQPToOonUlPAEY9atV5JatYsza+Y/+Zqvad403fc+6JrjxlCseEx2aqu/uY2bno7jaNqsLH9vvIuFC3ayetUBnA6dq7rVoP4lpYLSpU3bSpQtG8fBg75jg4oWi86zCWEwFC0azaBbGzH2szV5/p10XdCte01efDl3WQZflCgZ2JCybRm0YeaLLldVZ8uO4Uz5egOrVh7A4dDo3KU63a+uicOhk5bmoWePr/lzxf4cBoxuCByGzsSvr8fp9PY+6n1TfZ4e+UtwfYzOsBWG3taEzz5ZVaD3kYXbbXFtj8msXHsHTZqVZc6P23x6dTTN67lThosiEqiAXcV/nqybQyDCZbg8+Ehrfl1yK+0vq5xvr0uz5mX5YW7/XLEo8fFOel1f129fHNuW9Ot/SY5jmiboclV1HnuiHQ88fGnQhgt4g1VfeMW/4fDs8x2IKkCzxVde78RlHbzvNeu9ZQWzNmhYmlGf9AhJXs1axWnYqLTfgFiHQ+fa62rnU+PTJCZGcfudzRj96dW8P6o7PXvVyW7GGBvrYNac/rzyWieqVi2CEBAb52DAwIYsWTaEdu1P/31jYx1MnnYjDof/y7ZhaHTsdDo7qkHD0txxV7MCvw8AJJw4kc7LLy5mzMer/G5H2bbk7ntbAJCW5mHWzC2MG7uGnxfuxLLCWxtH8d9DpUor/vOkpLipWeV90tLMQlnvtmFNaHdZZS5tW5FWTceQmuoJKibB6dSZ8HUvatYsTq3aJXyO2/rPMS5vN5709NxxLAD3P9CKl1/rVJC3kCfjv1jLk48vJDnZnR1/Ehvn4LkXLs++iRUE07T5cfZWxo9by57dpyhbNp6Bgxpy/Q1182UYzf9pB717TQXyDoR9bGRbnn62Q0HVDolgtlhWrzzAlVdM8BvE/NPCm7m07em4ou5dvuL3JeHL/BHCWwHZn/E9eGhj3vugK6NHreTVl34jOdmdfa58hQTe+6Ar3brXDJtOigsfVedFGS+KIDiwP5kxn6xiy5ajbNl8LDsAt7CIjja47vo6fPvNJmxbBoxVefaFDjzyWHAVTtevO8y9d/3I6lWnewrFxzt58JFLeeSxNhFz5aene/hx9jYO7E+mdJk4rr62VnZ5/fOR77/bwv3D53L8WHq2weWM0rj/IZMHHl+PrsXg0K7CoV2LELHnWt1sfv1lF31vnI7LbWFbpyvh2pbk/969itvvPO1p2bbtOM0aflqo+j37QgcefrQNo97/kyefyF2cMMv4mTGrb763ExUXH8p4UcaLIgCPP7qA0R/+5XdMVvZQVJSOK0CwKHi3MRwOgdsdXOG3LAYNboQzymDmjM2kprjxeOwcJedjYw0eH9meBx5uHbLRse7vQ2zZfIy4eCeXX1ElRyl4hRe322LenG3s3nWK+KJ/0qn7hxQpagIWWT0EBGWJc0xEF9XPsban2b8vmS/GrmHenO14PBZt2lVi2O1Nc235zZu7nT7XTwsoLyHBmcM7kl8MQ+OOu5rx1LOXUbPKB6Sn5+3R1DTvltaSZUMLvKbi4kAZL8p4+c+RVSnWX3G29HQPU77ewGsvL+HAgcAppzVqFuPt967i41F/MX/+joCeEV0XvP7mlTz15C9Yph102rSuCzb+c092Kq9p2ixcsJM9u09RvHgMXbvXID7+/PVeXCx47F9IM2/zcVZHUJYEx88IcWEZgMv++JerrpwYcNz9D7Tiw/f/LHCdIl0X9O1/CVd0qsodQ2cHHP/n6mHUqVuyQGsqLg5CuX+rbCPFBc2C+Tt4/93lLFq0G2lDw0alGTKsCXXrlkAIQaPGZUhIiOLYsXSu6TaJDeuPBC17+7YTVKiQwLA7mzF3zna/YxMTnXz6+bX0uKYWrS6tyIvPLWLhgp1BrSMlfDNtE8NHtAK8BljXbjWC1lMRHlzWJ3hzGPKKJbGQ7MOU83GI0IKDzzUtWpUPmA0WHW3w6BNt6XhlNZ4e+XNI35O8qFqtKEcPpwVV+2jfviTW/X2YBfN34PHYNG9Rjv4DG1KsWHSBdFBc3CjjRVHoJCW5+Pqr9XwzbSNJp1zUrV+SocOaclmHyiFti4we9RePP7LA20sl836z7u/DPHT/T9ljYmIMBg9twq5dJ9m8yXcV2LzQdcHXX63nuRcvp9cNdfjORx+cFi3LMWf+wOyg0Zq1ilG2XDyGoQVVGVbXhbdSqeKcIaULS64IMErHYy/CoV1YxothaDz1bAfuu8d3jZj7H2xFkSLRXNm5Gp2uHMqWzUf5asJ6Zn3/T1DdwM/EtiUDb2nIhHH+KzdncdftP3LwQEp2Ftn0qRt54dlFjJvYi+49VECvIm/UtpGiUNmx4wQ9unyVvW3j3eoRmKZkyG1NePf9rkH1c/lnyzFaNh0TVGxJsGXV8+LGPvV4+70uNLnkE06edOUp2+nUWbZyGDVqFMPlMunW+SvWrD4Y9LaREPDWO124467m+VNSUWCkTCfJc0mAUToOrSexxtuFolO4+fB/K3j+2UV4PFZmU07v53P4/S158ZWOPr93yckuJn+1nocfnB/UOs8834F9/yYx9rM1fsdpGui65g1WP+u7IoT33IcfdWfhwp2sWXWQmFgH111fh8FDGlOqdFxQuiz9fS+ffLySFcv3extL9qjJHXc3p0aNYkHNVxQuKuZFGS/nJbYtadVsDNu3nfB5Y/+/d4O7iT/x6AI+Gb0y4uX4y5WPJy3Vw6lTuQ2XLHRdcPudzXjz7S5MGL+We+8KXAX1TJxOnX92Ds93BVpFwZFSkuLpjM0ufHcBEkTrzxGlDypEzcLL8ePpTJ+6kX3/JlOqVCw39qmXo22CL/5YspduXb4KOO65FzsQHx/Fow/5N3SE8Aa4+/v+Zj10nOnBFJltML7/sT9Nm/lvmPnm67/z8gu/ZT8cgfe7qusaX025QW3Nnoco40UZL+clCxfs5Pprp/gdU6lyIus23R3Q+9K188QcHW7PNeXKxbNlx3CuvPxLVv51IKSgx1de68h9D7QOqz5SZiA5haAIQhRe7IAt/8VtTcGS/yBENA6tK4bockEEubqsiWRYz5G38SKAaBIdSxHiv3ddkVLSrNGn7NyRu/8XeA2R1pdWYM78gTSoOzpg+wVNI2D/LX9ERxu8/1E36tYtSeMmZXJtNy+Yv4Mbek7Nc64Q4IzS2bD5HkqXCc6DoygcVMCu4rzkt0W7A8aB7N2TxPSpG5k96x/WrztCYmIUN/auy823Ns4RwBcdbRRoOyjcpGd400H//TcpaMOlbNk4nnq2A7cOaRw2PSy5E5f5Ph75A2ACDhziGqKM+9FF/psMBoPLGk+G9SLeoFcLpI7HnoVGNeIcE9FEuXzLllJiyXXYciPgxNAuQxPBVwEOBqfWH9Nejil/IGfgrg5oxBqjgDg89kIs+28QBobogKGF7+93viKE4ONPr+aa7l9jnpVJp+uC2FgH733QlT17TgXVN6oghgtARoaZnclUu04J3ny7M52uPF1VeNT7f/oMFpYSPG6b8ePW8ujjwdVNUpx/qPYAikIj2Jv6sCGzmPX9P2zbepxVKw/w9FO/0KLJp2zZfDrg9uprakVKzZDRdUHDhqUBKF06zm8XZCGg/iUlmbdgIBu33htew8XeRIrnOjxyNl7DBcCDR35Piuc6LLk1LOtI6cGy/8GyNyOldzvNYy8kw3oBr9ciqyaO9/82e0j1DEbK/N2xLLmdFLMnqWYv0q0nSbceIdnThjTPE9j2CdzWd2RYH+G2piDlqXy/LyF0Yo3/EaO/jS4aAtFAERziRuKNWWiUINlzOWnm7bjs0bis90k1ryfFcxO2LFh2zoVA6zYVWfDrLXTpWiP7M67rguuur8Ovvw/m8OFUbh8yq9D12vrPMW7oOZWf5p3OCPzjj71+t6RsW/L7b3sKQz1FhFDbRopC48fZW+nX55t8zdV1QcVKiaxZfye6rpGU5KJRvdEcPx5Ek7pMyldIYP++5OxKquFkwqReXHd9XT4ZvZLHHp7v1yM0eszVDLy5YVjXB0j29MSWmzhtPJyJji4aEe/I3+8fQEoLtz0Gl/U5kmOZRxOJ0m7BY/+Ozd/knWbsJdb4Aod2eUhr2nI/KZ5rkCST+32JzB8br3fEBhxE6fcRpd0T1irCttxHsqc7kEbu96ijUZN4x/cXxPZYODh+PJ3jx9MpVSqWIkWi+WriOu6544eAcSyRQgioUrUoazfciRCCsiXeJi3Nfy+yK7tUY8b3fQtJQ0UwhHL/Vp4XRaHRtXsNKlZK9Ns00BeWJdm96xTzzqi3Eh0d3K6nEN5GfL8vH8JHn/Sg9aUVqFqtKO0vq0STpmXypc+ZDLylIT171cn+d81axfOUqeuCho1Kc2PvegVaLy8sewO2XE/ehguAhSVXk+S+ilTP3Xjsn0PyhEgpSTcfI8N68wzDBSAJl/0RNmvwZ7iAgWn/EvR63jVt0s0XkJwk7/clz1jTynztxmW9jdv+JKS1AuGyxgLp+KoBY7MFUwaXjXMxULx4DDVrFqdIkWiOHE7lvrvnICXnxHAB71bQrp0nWb50H7YtKVosyu94IeDyyyO7jaqILMp4URQauq4x9ZveJBaJynFzD9Z4MBwaixftBmDil3+zf3/gKrkAUVEGM2f3ZcniPcybux2nU+fKztV49Y0rmTWnPy1blc+hh78qvWeSmOjkg4+6M+rjHtlP+fHxTubOH0jHM/bfwXux7Na9JrPm9A/a6AqFYLeEJNsw5QLSzGGkmcOyt338zpESt/0FHjnDp9Tg1g6+9LyUHtLMe/NtEGRYHyCl76Jslr2fVM+DJLnbk+RuTYr7Vjz2Lz4NOo89E9+GIYCG25qNlGm4rSmkmY+RZo7Ebc1CyoKX3D+fmfjlurB7MvPLjz9s5euv1rF/n/9rQ3S0wS23NiokrRSRQAXsKgqVBg1Ls2LlMD7/bDXTpmwkJdlNnboluKF3PR64b57fuYLTAboTxv8d9JoOh0a/Pt+w7u/D2UF8S5bs4fMxq7n73ub8+NMAFszfydTJGzl2NI2q1Ypy86CGvP7K7yxcsDPXhVnTBM4onYWLBuVZ1rxU6Ti+nXkT27YdZ9kf/yIEtLusMlWrFg1a51AJrWmg9yZsykVkWG8SYzzjc6QtT5Jm3okl/yyghia6yLuOii2P4LbG4ranIzmBoAhQDMmOAqyXjsf+Fad+de4z5nu47fdzHLM4Qpr5GzodiXOMRoic7RgkgQxlG1vuJcnTFkjCu40FHqaQYZUlzvgCXatTgPdz/rJhwxG/cV6FyehRf1GjRrGA2Uz9BjSgRMnzp9GmInRUzIvivMC2JQ3rjWbvHv+ZClmxJZXKvuu39koWQkBsrIOMDNOnS/utd7pw5925a8ukprq5bfD3/Dh7W7YsKaFixQS+mNCL1pdWCOKdFQ5SppDkaY13ayMUokh0rECI3LU+pJSkmn2x5Gr8ex0CIYAYEh3LECI+xxlb7iHF0wfJ8QKukRuHNoBofUSOrCS3NZl060m/85zaHcQYT2S/ljKZFE9PbPbg28ukZ40m760lB7H6+zj0rqG8hQuC+++dw8Qv1wVVTTrSBJOBKAT0ur4u47/qVSg6KYJHxbwoLjg0TTD8/lY+n+B0XVChQgJXX1s7+3UwSAmpqR6/e/HvvbMMy8p94Z39/VZ+mrsjt04CSpYq3Kc2Kd1Y9jpMe22e2yFCxBOlDcuHZBemXJPnGUv+iSX/omBGhQ7oxBrv5zBcpEzFbX1Nsud6JEcLuEbeeOxJJHvakuZ5GCmTkdIiwwpcHddtf4mUqVhyG6mee0nyNMNmN/63x6zMH183cA9p1t1kmO8CXsPQY88nxXMzp9xNSXK3Jt18Bkv676F1PtLjmlp+DRdvsL3XOA52Sza/BFOdW9MEeoT1UEQetW2kOG+48+7mrFp5gClfb8hRo0HTBImJUUz9tnf2xS8+wRlUplGFCgkcPJji13jZ928y27Yez7EFtHzpv9xx26wcT3FZ/z6wP4WePb5m1d93ZPczihRSWrjs0bitsZmBqwAxGKKDd3tFuNFEDQxxBR77r3yukrfh4LHn4r1EmHmeD0wUBlegadWw7DXYch8O7RpsuZs0cwiS/Kc1B4+FR87ENncQpY08K9jYFxm4rCm47HcAF+E0rFz2B+hWUzxyAR57El7jzvKGGtuTcdtTiTU+DSory5K7sOxd2HIbllyJzQE0SuPUb8QQVyJE4Vzeu1xVnUsalGLz5qO5Oq9neUI+H9cTt9vi8zGr2bTxKIlFoujdpz6lS8Xy2ZjV/L5kb9j0SUx0kpzs9umBsSxJ56uq5X1SccGgjBdFoZKU5MLtsiheIibXU5KmCUY+3Z60VA+Lft1NerqHhMQoBt7ckBEPts6uhrlwwU727A5cCKts2Tj6DWzA/95ZTqCgUo8n55Pj/95bjqaLXBdj8F789u5J4vvv/qFP3/oB9cgv3gyfR/DI78mpfzqmzIwPkhogcfE2+XOk6uiiQd7rh7wFdRpBCZz6rbis98G2yLpJe4vY6eTfIMoPNpZciyl/DnqGy345YtqkW88iyaoOfaZh5PXcpJl3k+D4A00UzXO+ZW8m3Xo+z0aSNhqmuQBdtCTOGIsQka8gq+saM77vyw3XTWX9usMYhoZEYlsSp1Pn4zHX0KZtJQAuv6Jqrvk33lSfB++fx/gv1mSX8c8vliVJSvIdIK3rglKl4rjhxvBn/CkKF2W8KAqFOT9u4523lrJ82T4AypSJ4467m3P/A62yvRfTp27k9ttmwRkplydPZPDpJyu5vGMVrurq7UXy+itLglrz3fe7Yjh03jaX+h0XF+eg+hmN2qSUzP1xe56GSxa6Lpjz47YCGS+mvRa3PRlb7kRQFId2LQ7tquxaIZZcikfODCDF9vHvYNBxiGvRxGmPk5TpgIYQUeiiJp58ex1sXNY7Z7zOMlaytlcKGw3TXnYO1s3NacMl77OQgcf+hij9ttNHpY3kAJbcQZp5N16PUF54PwOW/ItU817ijC/CWu/GF2XLxbNk2RB+XriTH2ZvJSPdpEHD0vQf2CConl33PdCKyV+vR6bnjk3TdYEQAsuyC1xRu0SJWGb+0DciGX+KwkX9BRUR55PRK3n0ofk5PC2HDqXyyou/seiXXXwz8ya2bT3O7UNn5bpw2bbE7bIY2Pfb7G2aLAPIH23bVeTqa2tjWTaVKieyf19ynltHui4YPLQJsbGni4vZtgwYfOjVK3/eAylt0q3n8dgTyfJIgIZp/YTLqkucYwKaKIHLmnzG+XDi/Tto1CLGeB4pbTz2VDKsMUh2AqCLZji1gXgvEf6LfeVGQ+I7TfncYCM5jiEuw5S/nWtlAuK2ZxCl35aZpj4Bl/VZAKPnbCSWXEyq52biHJ8hROSbfmqaoHOX6nTuUj3kudWrF2PWj/25ud+37N+f4vXeSG+36TbtKvHIY224pf8M0tL8x6/5onjxaJ55/nJu6lefhAT/NWAUFwbKeFFElL17TvH4IwuA3O0BbFvy2+I9fPbp6hyl/89GSjBNmy8+X4PhCLw1ouuC5i2yardofDX5Bq7p9jWpqe7sC1/Ww2iz5uV4+rnLzpqvUa9eSTZvPurzSU8IQaMmZQLqkhdue1ym4QKnDRM7879bSTPvJd4xOTNINDyGi6AsghhsjqFRHqfeD6fWB4gm1XMzFjm9U5ZcTbq1CofogUf+GNJK3rL6aWHRO3wINFGGaOMFUjy98KYzn7/YciMuawaWXJkZG5M/LJaS6hmMrtVE4kGjIpqoiBAJGKIVQhQJo9YFo0XL8qzfcg8/zd3OqlUHcDp1rupagyZNvd2jl/55G5+MXsm0KRtJSnIRF+egeIkYLNNm+/YTfr0yx49nsHjRbm9xvVrFaNCwdNAeKSkly/74l4kT1rHv3yTKlI2nb/9LuKJj1aAChBWRQaVKKyLKKy/9xv+98YfPpyUhoGrVorg9Fvv+TfYrq0HDUmzbeoKMjMAej/dHdWPw0CbZr/fsPsVHH/7J1MkbSEp2U7VKEYbe3pShw5rm6UL+4vM1jBg+16d8w9DY+M89lC0X73NMXkhpkuxpj+Sw33HxxiwyrLcw5RJC3w46Gx1DXEWcY1SuM2nmSDy2/07fkAD4/9ucphRR2iBcduCsntBw4vUA5f9yFaO/jlO/CVvuJd18E1POoeC/28ghKJmZiRUOstonnPn7c+LU+hGtj0SIC9cb8ehD8xn72epccWv+qFW7OC+/1onuPWr6HefxWNxx22y+mbYJwxCYpkQ3vLFwV3auxqSpNxAT899oCVEYqFRpxXnDpg1H/FbflBJ27jwZVI2I48fTcQWxVRMTY3Bjn5wBeZWrFOH1tzqzY+8Ijp58lL/W3sE9w1v63PseNLgR113vLSp25gOabgiEgFGf9AjZcAGw5KaAhgvoeORiHFovwnNztXDqfXIdteXBIAwXCN5wgRj9SQytfQi6+UdQlGj9WRIdm0hw/F4ASbEIyiOljSYqEef4gETHWuD8fcDxGi7hukRntU84EzdueyJp5n1cyM+w1aoXxcyj1IE/tm09Tr/e05k5Y7PfcS89v5hvp28CyA4mzoqF++XnXTzy4E/50FgRDpTxoogYlmUTHW2gBajJ4nBotGtfyW8NCF0XlCuXEFSdiMeeaFfgfW1d1xg34Tr+92E36mamUBuGRtduNZg7fyD9B+SdoeMPl/UlqWb/IEdbOLTuaNTmdAG0/CAwxOUYokMe+uT2xBQUj/0TumiERk18X16yPg9nnvf+26kNI86YRazxIbHGeBIcy4jSByOEQFAM75ZUfkgjzRpEsudyPLa35YAQcURpAyjY7zfSRNozZGPKBVjy/Ahmzg99+12CoYd2K5PS+/PQiJ/wePLemk1OdvHpxyt9bkfZtmTSxPUcOhhcmxJFeFHGiyLsLF+2j359plOyyFtMnbLRb9aOt3R+Je66u7lf74ttSzpeWTWoJ6x+A/IuQx8quq4x5LYmLF81jBMpj3Es6VEmT+tNm3aVQpblssaRYT1PcLEgFrpojBBRxDkmoouWIa93JtH6Mwhx+qtu2mtJ9lyD2/6qQHLzQpKMEIIY43XAQW7DQAecRGkj0UVzsgwZXTQkRv+AaH0khnYJDq0HDu2yHGX6hYjCEJ0KqN9+0sy7sg0Yp34bglJ56AkgEOQvrunCQsdtTz/XSuQLj8fitVd/z3d13yNH0lgwf2ee55Yv20damn9Pr2VJfv1ld77WVhQMZbwowkJKipvPPl1F88af0qXjBH6cvS2orAAp4defd/P2W8t47gWvd+BM74phaN5tmo97cNfdLdD8BNlpmqBd+0pUqBj+rQBd14IK8JPSxrTX4rEXZVdLlTKNDOv/gl0JQWUM0Q4ATZQkzvgKQel8ai7w2KcbKlr2RlLN/thyUz7l+UNHF94YAkNrRrwxFV20zaGLIdoRb3xDtHE78Y4pJDr+IdGxlXjHDJz61X5/x7Y8lBkDVBC8n8l088XMLaQSxDumY+TQEyAap3Y7DjG0AGsVJJhTR1C9gDKCxcKWBwphnfBz/71zGePHOxIIIbxJBXnhcQcXLO/Lc6OILCrbSFFg9u45RY+uk9i9K/8VU+f/tIPEIlHMWzCQ0R/9xZLFexEaXNm5Onff24KmzbwZBw88dClvv5W7boumCTRN8NwLgSuTRgqXOYMM+yXIroQLggo4xY0En30jiTX+L4enxGW9E0ScjC9sLHl6Xz/DehNvjZBIxDhYOLSbsl/pWkPitfHY8ghSHkWIkjn6DAEIEfyWjduaAAEbJAaDRLIPS/6FIVqhifLEOcZjyz1YciPgzMzEicey/8FtvhaC7DNT2yWnnw9tThsiMvPfgry3hXQglljjXVLNO4DDRObvdXo9TZT1edabSj8HlzUKm/1AFBqVsTkJHEGjOA69N1HaQIQogi2P4bGn4bG931NDa4VTuynX376g/LPlGF9NWFcgGVJ6a79ksWf3KQ4cSKF0mTgaNS4TVK+krGuTonBRxosi32RkmBw/lka/Pt/w796CpZ7atmT61I08+0IHvvzqep/jnnm+A84onXf/bxkZGWb2xaVsuXg++qQHl7atWCA98ovLnECG/Vyu45J9uOT7ZPbEDkqW25qOobUAvI0LXfZHBdBMy84kseWRzBonkbsRuqx30MWo7EJ7gPemFYYbl9v+Dv8xIIJQqvfaMqdBqInKaKLyWSJDuUSWIl6fQ4rVEziYqeuZ+mpALFHa7dhsBTQE5bHkX2d07dYwRBeijUfwblt5Ta3gyTKeQmnrYOHUbszzjJRuUj39sVid47jNkTP+nYTLege39TXR+qOkWyOBDLI+Z5b1Oy7rQ2KNj4NqexAsU6fkbCOSH2LjHHTrUYNVKw/w1BM/52hT0KJlOdq0rcjyZft81ohq0ao8lzTIr1dUURCU8aIImb17TvH6q78zZfIG3K7wukznzdnOHXfl7vCchaYJRj7VnnuGt2DenO0kJbmoVr0YV3Ssgh5i0F64kDKDDPvFQKOClGbjkTOQciRCFMFtfYP3ppf/SreG6Jyp59EQ9PBHSfCRwmvKhbis/2XefMOLDOh1kWjUI0q/g3TrvoDyNBH4pqNRAYglGM9ZnPEelpwP7PcxwgJSgXRijf/lOGPLQ0h5AiHKoIliSOki2dM5xFRpQaz+JYbWAIjBbU/MbMeg4dvo09CojWmvw5YHcWhdEOL0tmu69WwuwyVvvBWA060HM1/LHOfATZp5JwmOn3IbiPnk2LF0NK1gxsvTz1zGhvVHuLrrpFxxM6tWHgQhKV06nsOHUnNkTeq6oGTJWMaMvTbfaysKhop5UYTEjh0n6NBuHJO+Whd2w0XTBBnpwT0tFikSzU39LmHYHc24snO1c2a4gNdTEt4quB6szJgUO6SqqmejI6iIQ+sOgBAlCqyZUxuEL8PFi8RlT0DKwE0zQ0UTVfF/yfLG3Di0bgFjhATl0EWLgGsKEYVT6xtgXXCIARhaG9z2D/iPU7Fx27lbPmiiDLpWF01421R47LlI9uH/c5XladIABzH62zj0NgiRgBAGUfpgYo3PMgOjfc0Hm8247P8j3XqUJE9rXNanSCmRMhWP/Y3f9332e/MaLXkZExKwcFkT8ziXPypXKhKy4ZIVUhUb6+CV1zpy7/0teWjEPDweO8/q3tI+3XOtQkVvtmOZMnE8+PCl/L58KFWrFg3Tu1GEivK8KLKxLJuf5m7n+5n/cPJEBmlpbvbuTSbpVAaVqxRl6LAmTJ28gZMnMgr0tON7fcklDc8fF6yULtzWd5hyDjZH0aiAQ+uGQ+uRo6iXxZoIrO6NBREUJfSgTe/WgUYF4hxfZuuqidJo1MdmY8jaaFxGtDEMW/6D/yd5gGQsuRlDNAl5HX9EaQNJtx73M8LCqfdDCJ0Y41nSzOE+R8YYT+eIK/JHtD4C0/4Dm3/I68bs0G4iRn8JILNTtv/vRmAPEplNJAP9nsEhrkPX6uLQbsw2fHLq1gmkgzTrDnL3QzrT0Mhax0WG5c0U00VdwmuUW5j2QuDJsEjrN+ASXnx+kc/zmgY1axWnYaMyVKteFIAli/eQlOSmZq3iVKtejLVrDvH3Wt/xZFLC/n3JXHJJKTZtvTcseivCgzJeFAAcOpjC9T29XWF1HayzrllHj6bz15++3OEFR9MEFSom0LFT1YitEQoe+xfSzPs4c7vAZiOmNZ8M6xXijPHomjcl27bDVQU1i3h00RAAh9YTt/1FCHM1HNr1OLSOGKIL4qyYjRj9ZVKtG4KWBQZxxlcYmvfp3WVtCXJu+I1bh9YLtz0zsyZJ7pu6Q+uX7U1xaD2I0T8gw3opR7CzoAwxxjPZ3qhgECKReMc0XNYY3PZEJCcADZ0WROuPYejNssfq1Mw0Dn3d9DV0Ebj3j5RuAv8OJTHGG36Dnk17LWnW4CBk5STDehenNjikOcEgQ+6T5Zty5RN48pnLeOn5xbnO6bqgeIkYvpvVjwoVE3js4QV8MnpldpXcLZuP8v13W7KNmkCMfGwB1/SsHTbdFQVHtQdQIKXkivbj+XvtoYh4VILB6dSY+m0fOl1Z7ZysfyYeaxVpVh/8X/CLkOBYiJQHSTGvCePqAqd2B7qojMeehyTVGw/BvgD6gPfGeAnxDv+dqF3Wl5k1Z/yjizZE649jaI2yj5n2WlJN3wHVXmJIdPyJELEBxoWOlC5c1ge47Ilk9ScSlCFKvx2nNjiXN0VKC0suw5ZH0ERpdNE6pAyn3OtLvBlP0TmCkrMw7b9INW/KdfxMYvS3cOp5B8hmkWF9iMt6D9+eF4FGTRKc8/zKSXHfisX50ohSxyGuJtbxXvYRS+7GY03BkjsQIh6H1h1DXBH030hKybixa3ntlSUcPOD1aAkBXbvX5K13OlOlSlFGffAnIx9bmOd8TQM7yBIxl7apwKDBjSlZKpbGjctQrnxCcBMVQRPK/VsZLwoW/bqLa7tPDqtMTRPYtiQ21ghY6OlM2rStyCOPt6XLVaF3pg0HUtoke9ohORRgpCBKexTLXoPJAsJVCVUXV2TGuxzidIZS4O2DLGL0/8OpB/asmNbfZFgvYrEq84iBQ/TCqffDmzpbGk2Uy3NuiqcXltxA3t4FDac2hBjjqaD0zS9SurDlbhAGGlUKZJCEEyllZsfwCXmcFRiiA7HGmFwesbOx5WGSPe3xlzEUo7+CU/ddsVnKZJI8jYPUPBwE/pzGGdMxNK+nKsMajcv6P04HpGdud4r6xBnj0ETJoFe2LJvVqw6SmuqmZs3i2bWeTNOmXs1RHDoU3i7nmibo2as277zXlZKlThvp6eketv5zHF0X1K5TAofj/PhcXigo40UZLyHxxKML+PTjVfmuUnk2pUrHUqt2CW4b1pTLOlSibs2P/PY3OpOs1MezGysWFi7zSzLs54Mc7QTcYVw9ASgCHMDXtoNGU2xWk/NG4Y2JMUQPYo3/BR3LASBlEpJTCEoE7Smx5T5SPH2RHOC0N8irjy7aEmd8fkE3+isoUkrc9gRv4Gtm5pGgGE59EFHa3TmqBvvDbX1HuvUwObPNvAatIboRa3zg12iz5f5MA6iwKIFTDMAtPyBnvRvvv6P0R4jW7wHAbc0i3RrhQ46OLhoTZ0wLuvOzL9avO0zbVmMLJMMXmuZNHHj0ibbc2Kc+H4/6i88+XUVysveaUKpULPeNaMX9D7ZW3aeDRBkvyngJiQdHzOPLL9aG1JU1L4SAe+9ryatvXJnj+GMPz+fjj1aGJMswNDZtvYcyZUNvflgQktydkOwq1DWDR0MT9YnWH8JlfYIll2cerYZTH4JT619oHggpk3DbU3Fb3yA5gSaq4NT649CuznM75b+IlDY2e/EGT1fK1+/FtP/CZY3JDOC10KhFlD4Yh3ZTwL+1lC6SPI0gjHEm/tHQRTuitNtx2+Mw5VK8hlZrnPpQHNplmXpJUjzdsNmGv63QM700+WXVygNc0X683zEFrRUDp7OYzr6bCgH9BzZg9Kf+q0crvIRy/1YBuwoaNSqDJwxel34DGvDiKx1zHX/l9U6kpLiZ+OU6dN3bldn00+8IvGmKEyes4+FH2xRYr2CRMuM8MFzOfGI9GxtbrscQzXA4vkZKF17vS3ShXxiFSCRKH0aUPqxQ172QEEJDp0qBZBhaCwytRWasjR2ScepN8+6N2/66QDoEj40lfwNxC3GOz3yOkhzKLNLnDx3T/rnAxkut2sWJiTFI91OCwbIkHS6vxOJFe32OCYQvF4CUMGniegbc3JAOlxfss6DIiarzouD6G+sQG1MwO1bT4MPR3fPs+uxw6Hz0ydX8teZ2Hn6sDQNubhhQnhCweVO4s3gCrlrI6529dnBeJplp3AgRhRAx6onuP4AQIl9etSh9BFDw+j7Bo+O2puQ6atp/k2GNIsP6ANP+PQg5AhmGLdmEhChuubURuo/O9rouqFa9KF9P603RopHZ6tR1wbixayIi+7+MMl7+w6Sne3j91SU0bzQmpKDas9F1Qc9edQIGp9WuU4Knn+3Au+93DbgHLIQgNrZwtx+EiEKjVqGueRqJQ3QhUFEyQcXM2i8KRWA0UZoEx/fo5PaIRgYLm33Zr2x5hBTPTaSavXBZ7+Gy3ifdepTADwomughPd/jnXrycho1KI8Tp7R3wXrfi451M/Pp6EhKimDy9d0RiUyxLsm3r8bDL/a+jto3+o2RkmPS6ZgrLl+3zGUzrdGq43f63k4TwRt4/9Ij/7Z2t/xxj9EcrmfXdFlwuk6LFojl5IsPn2qZpc+11hV9XwSa5kFf0bhM5tduI0h7EYy7Em4qb9+89Sh+iPC2KkNBEOeKdn2PLY1j2dgSgicZ47Jlk2E+EezU0vH2spHSR6rkZmx2Z54IteKchSMShdQuLRgkJUcxdcDNjx6zmszGr2bvnFAkJUfQbcAn3DG9J5SpFAGjbrhKTp9/IHbfN4uSJswv65R9NExQrHhM2eQovynj5jzL6w7/8Gi6A3wBeh0PD47EpWiyaseOvo0lT351VFy7YSd/e07EsGysz1sVffQVdFzRoWLrQa75Y9ia8DfUKShTeLCRfv1sBFEcXVdGogVPvj6F5U1rjjE9INYfgDbLMuth7M3kM0TWzPL9CETqaKIGmn95CitJuwuX+EFmgFhRnY+PQegPgsef4iW3x9d3QAZ1YY1RYM9ZiYx0MH9GK4SNa+R3XrXtNtu68j48+/ItXXvwNj8cK2FU6ELYtiYtzsHHDEerVL6kePsKEyja6yNn3bxKzZ20lJcVNzZrF6H51LRwOjXq1PmL/vvx7GbpcVZ1+AxrQs1dtoqJ828CnTmVQt8Yo0tM9fotBZcXKmKZN0+Zlmf5tH0qVjsu3fvkh3XwGt/1VgeU4xC145ET8ZVLEGp/i0Drnec6SO3Fb4/HYPyDJQBe1cWq34NCuPW/qmSguDpLdXbDZHiZpOhr1idKH4bFnYsoVEEQrBCgKnASicIhriNKHoWt1wqRT/tm27Thvv/EHU6dsLHAmZhZVqhbhuRcup/dN9cMi72JDpUor4wWPx+KxhxfwxedrkFKi6xqmaVO8RAz/+7Abt/SfUSD5pcvEsW1X4M69H3/0F48/ssDn04sQULZsPN2vrkl0tMHV19ai/WWV/T6dSHkKtz0TW24DYnFoPXJUgc0vKZ4+WDK0lO6zcWpDiNYfIcVzY+ZT59muci2zFsoXyhBRnHPSzVdw2+MoeA8jgSE6Y8l9yJB7ZwlitZlIsQO3/Q1SHkCIcji13t4mm+c49d7ttkhOdvPbol0MGui/enWwvPpGJ4bf798L9F9EGS/KeOHeu35g4pfr8jQaQimJ7Y91m++iSpWifsfcNvh7vp2+KWAdhSMnH/HrwcnCbX1LuvUU3m0ZnaxutYa4jFjjQ4TIf8nuVM9gTJm7T0pwxBCtPUuU0RfwGljp5nN45GxOx684cWh9idFHIkR0vvVUKMKFJXeT4rkKbyXfUG8F8RiiFYbWGYd2Gameu7FZn09Nzq4mnVX0sBlxxjiEKNx6T3mxdetxmjf6NCyydF2w8Z97VIuBswjl/q2yjS5Cduw4wYTxeRsu4DVcDENDK+Bf/9jR9IBjfKUonk0wUf4e+7fMTAUX3gudSdYToyn/yGykGDxSWpxpu4fSrA80DNGVaP15Yo2PSXSsyjZcAIQoQqzjPRIcS4k1xhBrfE6iYzmxxgvKcFGcN+iiCrHGR3jDH4O/IERpj5PoWEms8Q6QTIrnhgIYLpC7u7X3/5ZcQ7r5XAHkho9atYpTsVJ4jA0p4auJ68Ii67+KMl4uQr6dvimg0WCadoG9LxUqBP4id7yyml+vi64L2rWvFFQPEJf1Pr5TLC1MuRjL9n8BldJFuvkmSe5WJHlqkeSpR6rnASx7ozemhHJ4PTqBkMQYTxGlD8KhXeUzuFATpXBoV+LQOiJEkSDkKhSFi0O7kgTHr0Rp96LTjMCffw2n3gvJMZI915JhvY7kSIS0s/HI77FlpOSHRutLK4ZFjqYJdmw/EdIct9vC4yno9t7FgzJeLkJOnsgIul5BVFT+4i6u6lo9qNL9199QlzJl43waU5Yluf/B1gHl2PJ4ZjyKP4tLw2VNQsq8a9Z4rA0keVrhtj9GklUAz40pZ5Ni9sKUK4hzTEKjUua5vHT2fmWi9SfRRHguZArFuUYT5Yg2HiTeOZ1o/XF/I3GIG9FEGdLMhzN7N0U68sDCkn9GeI3gaNiwdNhqwSQmBs6mklIy5esNXNbmC0oWeYsSiW/RpeMEZs3cEhYdLmSU8XIRUrVa0aCi43VDcFO/0KPe4+IcvPxap6DGRkcbfDerL8WKx+QoEqUb3n+8+PIVdO9RMwhJgbeovE9pk0nytCTFcyOpngdIN98i3XyOU+4mpFnXQp51XGzAJM28D41SxDvmE2uMwakNRBONgNNZT7poQKzxMVH6bUHoo1BceDi123BqWW0fdLy3CW88miGuJMZ4EUtuw5JLKXig74VFrxvrBt1k1h+maXND73p+x0gpefyRBdw+dBbr/j6cffzPFfsZ2G8Gr72ypMB6XMiogN2LkJMnM6hZ5f2ABeYcDo2Onary07wdfsedSd16Jfniy55c0qB0SDqdOpXBpInrmT3rH9LTTJo0K8uw25tS/5JSQc33NplrAYS3tf3ZxOiv4dT75jgmpZXpqXGiiWIRXV+hOF+w5A481jRs9iEogUPrlV2PyG1NId0aWUiaCBIcv6GJ8oW0nn/uufMHJk1cn28jRtcFHTtV5ZuZN/nNqpz/0w5uvG6qX1m//HYrzVuUy5ce5yOqMeN/nKJFo3n1jSt55MH5fsd5PHZ2dclg0DTB5k1H+fqr9UF7XrIoUiSau+9twd33tghpXhbeJnM34ba/JHJPexqW3JDrqOQ4bmsCbnsakhMISuPU+xOl3YIQ/00DWXHxo4vq6IavLaTCSvPXMUTnXIbL6QcKB5ooXki6eHnvg27ousaX49YGXcDO63UW2LakW4+ajBl7bcBidWM+XoluiOzCnmejG4LPPl1F8xZXh/oWLgrUttFFyh13NafH1b63Y4TwbukcOhS8JyPrSeP991bwy8+7CqpiyETrI9CoRuQunBJw5jhiy72keK7FZX+SGZRoItmPy3qXFM91500goUJRmBhaGyLbyFQAAo0axBivZh+V0k2G9RHJnrYke9qQ7GlBsuca3NYPEdQlJ06nzgcfdWf95rupW7cEgQrmFisWzaNPtOXZ5zvw5+phfD31RuLjnf4nAWvWHPJpuABYpmT1ygOhqn/RoIyXi5gxX1xLw0a5A8yygmczMkzm/LAtZLm6Ifj044IVc8sPQiQS75iOUxtCsB2YQ0Pi0K7McSTNfBDJMXJ7e2xs/iXdfDYCeigU5zeaqIAhuhL8g8SZt5ozr0c6pzcAdAQVEJRCE/WJ1l8g3jEje6tWSg+p5m24rLdzZDfZciPp1n1kWKPy/4byQaXKRXjk8bZ+vS+6LrjtjmY8/WwHHnq0DSVLxvLBe8u5fegsht/9Iz/M+gfTzHt7Pzo68MZIdMy5LeB3LlHbRhcx3oZkA3nvneV8PmY1x4+lIwS0vrQCf/zu7Wfi64vjD8uUrDqHFr8mquCgGx6+x1usLkxyqYUuLs1+bdmbseQqPzMsTDkfWx5EE757OykUFyOxxuukmvux5N+cLi7nbTQqqIxDXIOht0ZKE7c9BksuA8js5zUYjdqYch6QhiZq4NBuQBNFc60jpQu3PZ4MazRwyqc+LuttHFpXdBFMAkB4uO76Orzzf0vZsvlYrpIQui4oUjSaO+5sBsA30zZx57DZeDxW9gPll+P+pmzZOKZ+04cmzbzXECklixftDpgJqmmCnuegee35gjJeLkKOHU1j3BdrmT51I8eOplGqTByDhzZhyNDGlC4Tx5OP/8zy5fv8uiQDEUw13HDjsiaSYb1MOA2W00QR55iQYx/ae1EOhI0lNyjjRfGfQ4hE4oxpeOyf8NjTsTmCRgWc+k0Y4ooc7S+cekek9DYrPbMmkgP/MXBSukg1b81MlQ58vUrx3IZOTTStHLq4BF1UQRetECIy16uoKINZP/Zn0M3f8ftve7O92pYlqV6jGF9NvoGy5eJZvvRfbhv8ffbW+5mGzsGDqXRoN45bhzTm1Tc6cdftPzBr5j9+a3XpuiAhIYpbhzTOcTwr/+a/0PxRGS8XGRs3HOHqbpM4fiw925158GAq69Ye5n/vLOOxke34bdHuAhkuul74Fr/b+p4MK3JbNDHal2ji7AyqwPvSoY1TKC4uhHDg1K/GqQcOGhUi9O+Jyx6DJf8i+Foye7HYi2V7+7J7ScSpDSJaHxGRfmKlSscx56eBrF1zkF8W7sK0bFq2Kk+Hy6tkGxHvvrMsYGzMl+PW8vtve9ix4ySA3+KeRYtF8+3MvpQoGYtl2UwY/zeffLSSjRuP4HTq9LimFvc/0PqiykQ6G5UqfRFhmjaN63/Mvn1JfqvnligRw7FjgeumaJrIlQ6oaQKnU2fF6mFUrVq0gBoHh5SSZE9HJHsitkaM/h5OvWeOY7Y8RLKnHf4L48WQ6FiBEIXbAVuhuBix5UkkRxEUQ1CMZM+lZxSULCgJxOgjcer9wiQvOGxbUiLxzYD93YJBCHjl9U4MHdaU2FgHpmkzaMAMfpi9FSD7gdUwNKSUfPHldfS6oW6B1y0sVG+j/yhzf9zG3r3+DReA48eDKfgGsbEGCK/BomkCIbzHps3oXWiGC4AtN0fUcPGS+8KiiTI4RC98f00EUdogZbgoFAXEkttJ9dxNsqcFKZ6rSPa0ItW8OYyGC0Ay6daTuKzwNFcMFtO0w2K4gNc4KV06jthYb6DuF5+v4YfZW5GSHIHD3vYvktuHzgrqQfVCRG0bXUT8vmSv37oAWQghCORw03VB3/6X0LBRGRb/uhspoU27ivQf2IAiRQq3saDMsypuKGR1rPV93tDy3nuPMV7CNg9jySVkBSNm/d8QPYjSHyqgbgrFfxvL3kKK2RvI4LSXU2LJFRFZL8P6PxzajWiiRETkn43TqVO9elF27jwZdF0Yf3w+ZjWt21SgSpWijB7lu22ClN5aXpMm/M19DwRuwXKhoYyX/yB5bQedjRACy5IMHdaUocOaFpJmeaOJygQ2QPzMpzE268i7uJ2OITqiiQp5zhUihjhjHKb8HY89A1seQRPlcWp90EXz/0RgnEIRSdKtZ/AaLrnLEUQGG4/9PVH6kAjJz82d97TgiUcXhEXW8mX/0qHtOH78aQDbtgZu7rh69aGwrHu+obaNLiLaX1YpqEBc25bExfmvD2BZdsgtACKFJspiiCvyPT9KH4ImsvqIiBz/9xbBesPvfCE0HNplxBrvEO+YQKzxBobWQhkuCkUBseSOzIDcwuyRJLDl/kJcD4bd0ZQrO1cLiyzbhqRTLh5/aEHAIGBNA6fz4rzNX5zv6iLEsmzmzd3OyMcW8tjD8/lm2ibc7pxf+K7da1KpcuAgZSHgtjua+uyOKoQ3BbDfgEvCons4iDbym2kUg0O7inhjGjH6a+iiCYKy6KIh0frLOYpgKRSKwsWWO8/FqohCbingcOhM+aY3Tz7d3m8KdLBYlmTx4j1c2raiX3mmKenWvfDq3hQmhWK8jBo1iqpVqxIdHU3r1q1ZscL3Xua4ceMQQuT4iY4u3BiL843t20/Qsuln9Ll+Gp+MXslnY1YzZNBM6tf6iL/+PP0EYRga02f0oWhR/63WHxvZjqeeuYyWrcrnWX1XCMGnn19T6LEt/vDWa2gX8rwo7VGEiPL2RtL7Eu/4hkTnH8Q7viNKH4AQMRHQVqFQBIMgIchxeW/r5g+JIVqFUV5wOBw6TzzVnr833sVV3aqHRabbbfkMBtZ1QZWqRbj62lphWet8I+LGy5QpU3jooYd47rnnWLVqFY0bN6Zr164cPnzY55zExEQOHDiQ/bN79+5Iq3nekpLi5ppuk9i5w7u3aZo2pse7F3zsWBrXdv+aJb/t5s8V+/hjyV6KFIlm9bo7ufve5sTE5Axpio4xqFuvJBvWHWb61I1Mnn4jzz7fgXLlvaX2hQZXdavBvAUDz8v0umj9npDGO7SBRBuDI6OMQqEoMLpohiBQ4Gw08cZMYvT/QxctgYI/cKSaN2PafxRYTn6oVLkI02fcxKat9/DBR90LJGvN6oPZW0dZ/896IC1fIYGZP/TD4SisJpqFS8TrvLRu3ZqWLVvy4YcfAmDbNpUqVeK+++7jiSeeyDV+3LhxPPDAA5w8eTJf611sdV4+H7OaB++fF/R4IaDLVdV58dVO7Nl9kj9X7OfvNQeZ/9NOpJRIeTpgt3SZOL7/oR/16pckNdWD06njdEb+g27LE7jtyXjsH0CmoYk6ROk3o4u2CCEw7bV47KlYci+aKI5Duw6kA5f9FpZcl9e75nQwr0CjPtH60zj0iy/CXqG42HBZk8iwnvZ5Pkq7n2jjgezXye7rMgPwC4IAYkhw/HZOt42TklxUrfC/fLVpyYumzcpSrVpRelxTi+uur3NOKqEXhFDu3xF9Z263m5UrVzJy5MjsY5qm0blzZ5YuXepzXkpKClWqVMG2bZo1a8arr77KJZfkHX/hcrlwuVzZr5OSksL3Bs4DZnyzCSEIOsVOSlgwfwfzf9rhc05WptGxo2n07DGZtRvvDKrLaTiw7C2kmgORnCDL4LDlXkxzHg4xACk9mEwjKx3Zkjoe+/vM2Xnt7QoM0Y0ofTiaKIEgFiEi0bRRoVBEgih9AJBMhvU23sBdg6wAXqc2jCj9/rNmxIZhVQmk47GnE6XfHgZ5+SMxMYoGDUuxJgwZQUJAaqqbLyZc959IJojottHRo0exLIsyZcrkOF6mTBkOHjyY55w6deowduxYZs6cycSJE7Ftm7Zt2/Lvv//mOf61116jSJEi2T+VKlUK+/s4lyQnu0OuDWDbwRk7liU5fDiV6VM35U+5AEjpwm1NJtnTiyR3a5LdPUgx+yI5Sc60Z++FyiMnZRoup4/lzELI600JJAcxtHpoorQyXBSKC5Ao/U4SHMuJ1p/DqQ0hWn+CBMfvxBhPIETO25Sh1SXvB5lQkZi274fowiJcWUhSwj9bjrNtW+D06YuB8y7bqE2bNgwaNIgmTZpw+eWX8+2331KqVCk++eSTPMePHDmSU6dOZf/s3bu3kDWOLJdcUgrDiJwVLQTMm7Mt7HKlTCLVvIl060lsuQ7JEWw2A0mEt36DjSVXY8kdYZSpUCgKG00UI0ofRIzxBFH6MDRRJs9xTq0v+a35lBuJlKdwW9/jtqZg2isDFvAMN916hDegNjUlEo1rzz8iaryULFkSXdc5dCinS+zQoUOULRtcF16Hw0HTpk3Zti3vG2xUVBSJiYk5fi4mBt/WBLMATRQDISVkuMJfYyHdfAlLbshaJezyz8a0lkV8DYVCce7RtbpEafeFRZaU6SR5WpNuPUC6NZJUsw8pnq6YdjAd5cNDq9bladwkb0MtVBwOjSqF2LrlXBJR48XpdNK8eXMWLlyYfcy2bRYuXEibNm2CkmFZFuvWraNcuYu3O6Y/DEPD4Yisg6xataJhlWfLo3jkTCJXITM3Hvu7QltLoVCcW6KNB4nR3wHy21dMABoWfwI5PRU2O0g1+2PJrQXUMkhNhGDi5OsDFpwLhK4Lbuhdj2LFzp8SF5Ek4ttGDz30EGPGjGH8+PFs2rSJu+++m9TUVIYM8ZZmHjRoUI6A3hdffJGffvqJHTt2sGrVKm6++WZ2797NsGHDIq3qeYdp2vTv803YItF9Ee4MI29GkBlWmQHX5C9sGc4mbgqF4nzGqffCKfJT4l/gDQq2ydsrbANuMsz3C6JeSFSpUpRL21TMtwGj64Jy5eJ56ZWO4VXsPCbieVR9+/blyJEjPPvssxw8eJAmTZowd+7c7CDePXv2oGmnbagTJ05w++23c/DgQYoVK0bz5s35448/qF+/fqRVPe+Y88NWDhxIiegaui7IyAi3oXFuIt2lPAKi5DlZW6FQFD4OvRtu88MQZ0kc4jo8cga+2xJYmHIuUqYhRDiymwJzz/AWLP0j78QUf8TGGgy4pRFPjGxH6TK5PVFHj6Rx5EgqpUrFUbJU4byXwqBQksCHDx/O8OHD8zz366+/5nj97rvv8u677xaCVuc/f67Yj8Oh4fGE7nkJJb06q0hduDBEU8DJ2e7YSFPYJb8VCsW5xdsXKVQ0LLYR+CHLQnIKEZbU7MD07FWHATc3YNLE9UHPiYtzMPCWhox4sHUuw2X9usO88Owifpq3HSlP1wB77sXLadgoPDE255LzLttIcRpd10JKkzYMja8mX8+8hQNp1jy4GCHblvTr3yCfGuaNEEVwaH0ovI+Xhi4u9ZmdoFAoLk6kPELoz+AaAkHgZpAagsIrYCeE4KNPrqbTlVWDnpOa6uHzMatp13os69edrlq/auUBrrz8SxbMP13vS0pYuGAnV14+IUdbmQsVZbycx1zZpVpI8S5RUTrXXleHNm0r8ctvt/Ln6mF89EkP4uMdaD7+0iMebE3lKkXCpPFpYvSn0Aulf4gGaETrjxbCWgqF4nxCiFKE3pHaRJO1CJwFaWcW0yw8NE2wZcuxkOZYliQ52c2ggd9lVlGXDL97Tp59jyxL4nZb3HfPnEJPCQ83yng5j2nXvhKNGpdGD6LOi2FodLiiSo5jdeqW5OZBjfjlt1tpfWnFHOeKFInixZev4IWXrwinyoC3OJ3HnoklI19zR1CeOGM8htY04mspFIrzC4d2Nd5q3KHh4dugxpn2ryHLLihpaZ6Q51iWZNvW4/zy8y7WrjnE+nWHfTZstG3JhvVHWL0q70KxFwoXVuODi5DkZBcTv1zHpInrOHYsnapVizB4aBOuv7EuDofO5Gm9uab71+zY7v8JwDRt7r2vZZ7n6tQtybyFN7Nl81G2bD5GXLyTdu0rER0d/j+/lMmkmrdgyXDXSRAIyqOL2miiHhoV0LWq6KJ1rgqcCoXiv4EmShCl34/LeifEmcEkKWhIMvKjVoGoV78Uy5f+69P48Ef/Pt/Q/eqaQY3dvu1E0OEF5yPKeDmH7N+XTPervmLXzpOAd09y/75klvy2ly/HrWXajD5UrJTIsr9u45vpmxjz8UpWrzqYIw4mq8niy692pMPlVfJeKJM6dUtSp27BsnGklFjybyy5FtAxtPbookr2uVTzHh/NEwuKRLIPm2I4tX44tC4RWEOhUFxoRGn3Iogmw3oXSA+jZBtd1A2jvOC4/Y5m/LEkf17r9HSTb6dvDmpsQmLh9LOLFBHvKl3YXEhdpbteOZEVK/Zh+aigW6xYNHcPb8Ftw5pSqnQc27ef4MaeU9ix42SOcZUqJ/Ld7H7UqhXZbBtL7iTNvB9bbuDMSH1DdCFGf5pU8x5sgo+Uzx8aYBOtv0iUfnOE11IoFBcKUrpw29/gsedgyU3A8QJK1EkwNqFphfuMb9uSoYNmMuPbzSH3tQuWxMQotu2+LyLe94IQyv1bGS/niHV/H6Jd6y8CjtM0QZGiUUyZfiO3DpzJ4cOpudyJui4oWTKW5auGUbx4TET0teURUjw9Mpsqnh0gpwEOwJVrXuQwSHD8gabquigUijw45a5LQcs1xDsWoIvq4VEoBCzL5uOPVvLRh3+yd08SAKXLxHL4UFpY5L/yWkfue6B1WGSFk1Du3+eX2XWRs3nTUZb8tgeAff8mBVWLxbYlSadc3HTDdE6dcuU53rIkR46kMWHc34x4KDIfSLc13ofhAt6KlIVpuHjX9NjfEqXfUcjrKhSKCwFDtMaUfxB6NtKZhL/vWzDousa997Xk7ntbcPRIGrouKFosmsceXsCYT1blQ543vEDXNR59oi3DRxRGJmhkUZ6XQuDQwRRuGzKLxb/uzi7/HInfeoOGpfljxdDwCwaS3G2QHAo8sNAwcGg3EGu8fq4VUSgU5yEeezFp5uACSHAQpT2IUxuEpp0uVCelG3AgCtqMKJ+sWX2Qrp0nkp4WWmX09pdVYtyE6yhdJrxFScNJKPdvlaYRYVJT3XS/ahK/Z3pcpIyM4QJw6lTkIuO9XpfzC8H5+yVUKBTnBikllr0BcOHQ+mcezU//Ng8u+02SzYakuO8lxXMHp9wNSPLUJclTjzTPo1hyWxg1D44mTcty190t0PXQjKclv+1l5crT6dF/rz3E228t5bVXljB3zjYsq/Aa6YYDtW0UYb7+aj3bthY0cCwwui6oU6dExORrlMNmV5ikBds6QOC7kJSJQ+sRJn0UCsXFgGmvIN18Fpt/zjhaEo1q2GwBkvIhVWIx56xLkRuP/BaPZzZxxpcYWt5lKiJBeroHwxAhF5nTdcEnH/1Fq9YVuPXm71j86250XSCEwDRtKlZKZOLX118w6dPK8xJhJk1cX+BW58FgWZKhwyJXqM2pD6AgDRc12hFn/EiCYyWJjuUE9yQkfKypo4s26EIVplMoFF5MewWp5s3YnO0NOYrNn0RrT2OIKzKP5ccTczYScJFm3oeU4W5umzfp6R6uu3oyb7+1DDtER4llSRYv2kOzRp+wZPGe7GNZVdz370vi6q6T2JlZuuN8RxkvEebIkdSIbRNlIQRcd30delxTK2JrOLX+aNQm9C+9hibqE+8YjaHVRRPFvL2PxPV+ZGkIKhGjjwaymo05sscboh1xxuhztuesUCjOP9Ktl/AmD+R9V3fZrxKjf0is8QmGuAxB2bCsKzmMKX8Ji6xAvP3WUlYs349t5++mYpo2J45n5Dnftr29kl56flFB1SwUlPESYapULYqmRe4mW6pULM8834EvvrwuYutYcgcu61N00RCNugS/2xhHlD6CeGMKQuSMT4k2nkSjKrk/gjoQQ5zxIU69C4mO5cTob+HUBhOl3UO8MZs4xziEOD+CsRUKxbnHsv/JrD/l2x0hOYnFEhxaF+IcY9FFPcLjgdGw7EjXt/IaHp99ujrfhkuwfDNtEydOFH5l4VBRMS8R5rpedVj86+6IyI6NdbBlx3AMIzI2qJQm6dazeOzJeL/kAu/FQaLRA5sl+N5Drkys7vW25OUh0URR4h3f4LK/wG1NQnIEiMGp9cKp344uqgIgRAxO/cZIvD2FQnGRYAeZCemyJuK2pgDRmHIp4UmFliCiwiDHP4cPpXL8WDgrCOeNlPDVl3+f9+nUyniJEPN/2sGrL/3Gyr8ORES+YWh061EjYoYLQIb1Bh57SuarnF9ymx8DzN5DmnU1mlWHaOMRHNqVuUYIkUi0PoJofUTmnrGutoIUCkXIaARXrNKSf+B9ANPw56UJDYlD5L6+hZuoqHB4iYJjxozN573xoraNIsDkr9fTu9fUiHbttCybe++L3IfLlidw218SuG18ADn8Q5p5O27rO7/jhDCU4aJQKPKFJuqiUZPASQX2Wf8PB5XRtTphlJc3JUrG0qx52aATQAwj/9fT1JTQO1sXNsp4CTPJyS5G3DsXKYnY3qSmwegxV9OyVfmIyAcw7UVAOD7A3t9BuvU0UoantLVCoVCciRCCaOOprFeFvPoebJm/Roqh8shjbYNOAHn6+cuIjQ19c0U3BA0blQ55XmGjjJcw8820TWRkRC5tTtMEN9/SiAEDG0ZsDQBJuA2NNDz2vDDLVCgUCi8O7XJijU8RFP6NN83zILbcH/F1rulZmzf+r3NA70uZsnGMeOBSbrm1ccjF7CxTMuz2878MhTJewsy2rccjGoei64KYWEfE5GevI2qGWaKBzZ4wy1QoFIrTOLQrSXAsIc74khj9NWL0/xXKuharSfZ0xbTXRnytu+9twfrNd1Onru+ipIcOpvLu28t45vkONGhYOncmah72jJZ52xrxYGtat6kYRo0jgzJewkxikaiIprJ5PDatWleImPwsdNESjWqE7yNiISgSJlkKhUKRN0LoGFp7nHpfHNo1CCoS+a0kCaSTZg7L7H0UWTRN8M+WY37HvPT8Ypo2+JgqVYswZGhjKlbylpeIjXMweEhjRj7dnho1i2WPr1e/FJ+OvYYXX7kikqqHDdWYMcz8s+UYLZqM8Xle0wT16pVgw4aj+ZIfG+dg974RREVFLlFMSgubnVj2BtKtJwCTgqcUaiQ4fkcTZcKgoUKhUASHy/qCDOtlCpp8ECyG6IFT7+MthCci4x8Y/8Va7rtnTnD6GALTlLz25pXcfW+LHF4YKSUnTmSgaYKiRaMjomsoqMaM55DadUpwY+96eRaME8L7YXnx1U6UKBmTL/ket0V6emRiaqS0cVmfkexpR4rnKtKtBwEHgqoFlm2IK0g3nyPZcy2pnqG4rR+Q8vyPaFcoFBc2Tu0WDNEp81Xkg3lNOYc0cwjJnisyG0SGH5fLDDrryDS9RtvIxxbmKt0hhKB48RgSE6OY/f0/3NhrKk0bfMKVV3zJmE9WkZISeS9SflHGSwT46NMe3HBjXcAbo+JweH/NsXEOxo6/jis6VqFb9xr5ku3x2Hz/3Zaw6ZqFlJJ0cyQZ1qtIDp9xJgXJjhAkJWT+XyOrN5GgPKb8GVMuxJYbMOVi0q37SDX7ImVy2N6DQqFQnI0QBrHGaGL0V89ocRKT+W8Iv0EjM/+7nxSzP7b8N8zyoXGTsiG3nTEMjU9Gr8x13O226H/TNwzo+y0/L9jJ9u0n+GvFfh558CfathrL/n3n5zVaFamLADExDsZ+eR0jn27PzO+2kJzkpmatYtzQux5Hj6bRsuln7Nh+ItMTc3re2a/zwjA0jhwJf8qxJVfgkdN8nA32WxKPRk1sVnNmHQVJVhR+1taTnbnm36SZTxLn+CAfGisUCkVwCGHg1Pvh1PtlH5NS4rG/w2WNPqOZo05WFfGCYwPpuKyxxBjPhkHeaerULU75Cgkc2J8ctBFjmjaLft2V/To11c1nn6zm/978g1OnXIC3USOcvg/t3XOKQTd/x4Jfbgmn+mFBxbwUIh6PRcumn7F718nsD0l++OTza+g/oEEYNYM0zwN45A8ULLYly9sSigxBgmMxmoh8ELJCoVCcjZQSyVHAxJYppJn9kZwiPK0DQFCUROeqs9a0sOQqJCfRqISu1Q1a3ofvr+DF5xbnuyRHx05VefCR1jw98hfWrzscVHfqRb8Ppmmz8DSy9Eco92/leSlEfpy9lR3bTxRIhsOh0fO62oEHhojFdgr+Zc1P1UqJaS/Hqd9QwLUVCoUidIQQCEoBoAmId/yI2xqH2/4WyXG8CQv5R5KS47XbmkGG9SbyjH5MmriEGP1FDM1/fZXPPl3Fk4//XCB9Fi/aza+/7EIIgjJcNE2wZPHuQjFeQkHFvBQCaWkeDh5IYfasrQUq2QwQn+AkLs4ZJs3OQJ7LNObwPOEoFApFQdFEaaKNx0h0LiPRsR5dNCH/t0qBxumaKW5rMunWwzkMFwBbbiLV7O+3TozbbfHSC4vzqcdpLEtmVoAPfs75uD+jPC8RZOOGI7zx2u98/90WLEuiaYKC7tKdPBneVuWW3IXbmoUk/EHAwaJrzc7Z2gqFQuELIZzEGeNJ8QzFJnewa2AkTn2A918yjXTrZR/jbMAkw3qNeG1yniMWL9rNieOBr/9ZqdHhwrYlbdtXCpu8cKGMlwjx54r9XNNtEm63lR3fEo7idYmJ4Wm9LqWbdPNpPHI63jiVYHSLh7NcoAVDRxet0UX+Mq8UCoUi0giRQIzxAKlmfoJWDRyiLwAe+yfw23bFxpIrsOVeNJHbWAjGcAFo1Lgsq1YeCDwwCHRd0KhxGZq3KBcWeeFEbRtFACkltw+dhctlFSgw92x0XdCvf3gCddOt5/HIbzJfBatjOA0XgaACscbbYZSpUCgUBUNKmasGlS4uBfKzXW9is9krl0N4s5n8Y8uDeR6vWq1oUCuGy3ABKFc+gQmTrkcEW1SmEFHGSwT4fcledmw/EdY2AbouiItzMnxEywLLsuV+PPYUwl9x0tcHXKBRA406QBE0qhOtP06C43tVcVehUJwXWPZGUj0jSPLUJclThyR3B1zWGKR0IYSOLvJ37c0K2BWUJJj4PiFK5nm8Rcty1K5TPM8CqOEmIcHJq290YumfQ6lc5fxs66K2jYJg44YjfDZmNcuX/othaHTtXoMhQ5tQrnxCnuM3bTwaVM2WYMiSU7lKESZMup4qVYoWWKbXfRkJJIKymWmG6ZnHYnFqA4nWH0KI8Gx5KRQKRTjx2ItIM2/H+0DnNTAk/5JhvYHH/ok4YwLR+oOkmr+HLFsTVTL/n1Ugz5cBo6GLBuiiWp5nhRC8/2F3ru3xNVDwMIQGDUuxft0RDEPDNG10XWBZkpatyjP9u5soVuzctwvwhzJeAvDJ6JU89vB8dN37BwZYu+YQ77+7gmkzenNZhyq55sTGOcIWnT10WFOuva42V3SsGjaLW5KK90sU7jYDGrpoSKzxDpb0ukp1UQ8hYsO8jkKhUIQHKdNJM+/Ha1ScfeG2seRqXNZoovQH0MVlWPK3ICXr6KIpGhUy62h9jz/vNEC0/oRfiW3bV2LO/IE8+9Qv/PF7/iv3XtuzNuO/6sX6dYcZP24tO7efoHiJWPr0rc9VXauj6+f/powqUueHP5bspVuXr/I8p2mCmBiD9ZvvpkTJnDfnI4dTqVNjVLaxE4i8vDRCwMBbGjLq4x5h32/02D+SZg4Pq8wsYvQPcOpXR0S2QqFQhBu3NY1063G/YwTFSHAsByDVczMWK4KQHEO88S0uazQeORt/dbAE5YkxXsGhXR603rt3n6R1s89ISwv+IVTTBK+83ol7hrdg+dJ9bNhwhJhYgy5dqlOqdFzQciKFKlIXJj78YAW6IbDySDuzbUl6usnEL9cx4qHWOY6XLBXL0NubMubjlQE9MLoO1asXZ/fuU7jdXndi0WLR3DeiFQ89cmlEAqUM0RlBMSQFK5iXEx2Nmji0LmGUqVAoFJHFkhvx3gp9GwGSE0iOoIlyRBuPkGreFFCuUxsMwpHpcfGFNx4w3jE35A7UVaoUpXTpOHbtOuVbuoDSZeJo2rQszVqU49bBjTl0KJWWTT/jny3HsscZhsaQYU147Y0rcTpzBhW73RZ/rthHaqqHOnVLhCV0IRyc/76hc8ivP+/O03DJwrYlv/y8E8uy+XLcWtq0/Jxi8W9Qsshb/Lv3FJ27VA+4hpW5/fnPzuHM/KEvjz7ehmbNyzFv7nYevH8eq1flHXkeClIm4bF/wm39gCV3I4STGOPNAsv14jWudNGMOMcEhIhAAT2FQqGIGMFes7LGBfNAKdBEKTz2HPxnGElstiE5EqQOORk4qJHfcAIp4dRJF5WrFGHAwIakpLjpftVXbN92PMc407T57JNV3HPnD2fMlXz4/gpqV/+Q7l0m0bvXNBrV+5gbek5h166T+dI3nKhtIz+ULfE2aWkev2Muv6IKxYvHMOPbzTm2f3RDYFuSYsViOH483a+MOnVL8M13N3F1t0ns3nUKTRPYtswOpHrgoda88PIVIXthpHSTYb2B2/4KON3aXBftiTVex23/iMt6NSSZudGI0d9U5f0VCsUFiWmvINXs52eEhi4uId4xE/DGyCR5WgGpfuXGG3Nw2zNw218A/u8j8Y75+ap3dexYOu1aj+XQwRS/ZTl0XZCQ4KRN20r8NG+737F/rBhK7ToluOfOH5g6eWOesooXj2HxH4OpUDG8/QNDuX8rz4sf2rariK77Nhg0TRAf72DGt5l5/Gd8HizTW4L5xIl0vzJ0XXBl52r0uWEa/+5NAk5HkWfFzLz3znK+mrAuJN2llKSZI3Db4zjTcAGw5FJSPL1xiF4YomtIcnMj8Ng/FlCGQqFQnBt00RJdNMK3h8QmSr/n9Cu5E0O09jE2i2LY8jC2/JdAhgs40MhfyYgSJWKYt3AgzVuW9zvOsiRJSS7m/LjNr+FiGBpPPLqAGlXez9NwyZJ1/EQ6b73xR750DhfKePHDPfe19PmHFsL7h9669TiBHCJSkucYIbzpb40al2HTxqN+13r37WUhtRaw5F+Ych5513KxkBzGY48n1nifKO1O4MygYwOd9kAwqc0WpvwFKcNZwE6hUCgKByEEscaYzFRm8BoxAu/tURCtP4VD64plbyLZ05MU8xpMGag54gnSrFsxZaAHOx2H6IUQ8fnWv0qVoiz45RZmz+nn914UTC8j27ZZvGgPp066/I6zTMmkieuz4zTPBcp48UPnLtUZ+XR7gBwNFXVDoOsaX0y4jn+2HA8YlNukaRk0TaCd8dvWdYFhaIyfeB2bNh7FMHz/KaSErf8c5+CB4A0Et/0t/vdabVz2F6SbT2PKTejUQaM+DtGTWP1rdK1OgPk5NMxMv1YoFIoLD02UIt74nlhjDA7N65GO0u4hwbGIKP02LLmDFLMvttwUxlV1BKWINh4OjzghClyiI5RmjRkZJidPhLfXXiiobKMAjHyqPZd1qMwno1d6i9Q5dLr3qMmddzenVu3i2XEp/li/7kh2Y8aixZyULRtP9x61GHp7E6pUKcofv/8b0HsDBJ16DSDlIQJXc0zDI6flOGLLzXisrHoEwX4TYhEUC1o3hUKhON8QQschrsShXZnrnMt8H2/hzXB5GgQal2RmZ/r3cgSL0xHsw2Z4MAyNxCLnrvCoMl6CoP1llWl/WeU8z3XrUcO7j+gjK0lKsl1rti1JTnKTkX6Krt1qZKectWxVnlEf/OlXhzJl4ihfIe+KvnkhRGmQ/qo5+iLLQArWcNFxan1UlpFCobgokTIdj/yR8Bku4M0yWofLXofLfgdDdCfWeAMhQqu1IqVk8aLdTPxyHbt2nsTh0PB4QnCf5BNNE1x/Q12io8+dCaG2jQrIiAdaY4fQfNGyJG63xeBbZmZ7UmrVLp4rt/5MhIA772keUtVDp3YD4f2y5YWOoCxR+r0RXkehUCjODd52J+GuRu6VnPVjyrmkmneHFNfo8VgMGvgd13afzPSpG1m+bF9I3vkzCdUIcTg0HhvZNl9rhQtlvBSQ1m0q8snn12AYGpomEIIcsS15YduSgwdTGD9uLa+9soSOHb70+6G7qmsNRjwYKLo9J7poiSGuIrJ/4jhi9DfQfDQSUygUigsZKVOx7A0EH/+XX2wsuQRL+vfAn8nLL/zG999tAchO9jjT9gmlskbRolEhjb+pb33q1D23131V5yVMHDzgNUbWrj5IapqHXxbu8js+2MaNlSonMnl6bxb/uhvbsmnZqgKt21QIquaLlC4yrNdw218TOF0vP+hANPGOmegicEE+hUKhuBCQ0kOG9TZuewKnm8xGGh2ndhMxxisBR6akuKlZ5YOAdciaNC3DmtWHwqVgNpddXpkf5g4Iu1zVHuAcULZcPI+PbAfAls1Hadn0M7/jgzUZ9+5Jol2rsdlVFG1bckmDUnw56Xpq1Srud64QUcQYzxMlH8C0l2T27wjnF9ECMnCZo4h1vB1GuQqFQnFu8NbIegBTziX42L9wYGPL4Fq2rPxrf0DDBeC225vy9lvL2LP7VJ5dqHVd0L5DZRb9sjskTc1CiKsJhNo2igC1apegaJjbidu2zP7wbd50lG5XTuTwoeDSkzVRFCEMIvMEYeGRs5EyPBHzCoVCcS6x5HJMOYfgDJdw9p7T0ETFoEaaftrWnIltw5ix1+J06rmKpeq6wBmlExfrIC7OEbSWui5o1bpC0OMjhTJeIoBp2ngiWLzHsiTHj6cz5tNVwc+RO4ncvq0HSXKEZCsUCkXh4bamEehaKShJlP4Y4fXMWDj1wA0fARo1Ku23cnsWLVuVp/WlFfjlt0Fce13t7Dm6LrzJIy6LeXO3k54efFiBlDBkWJOgx0cKZbxEgFV/HSA1NRIxJqexLMmkEFoGCBLw15K9YEQhKLz4IoVCoYgUNvsIlKnpfViThP5AaODLW+PUhqGLmkFJKVU6jhv71PNpwBiGoNWlFWjQsDQAlzQozZdfXc+/hx7k1sGNsgN8LUtiWTJHcTpf4ZSGoSEEjPq4O9Wrn/u6Xsp4CSNbNh9l0a+72LbtWODBYeBECNUNvcWQwunizELHqd2g6rwoFIqLAkFJAnteiiPQCd7zIojT5xKrj0FQ4qxzOhqNkWTgssYj5amgJL75dhdq1ymRy9jQNEGpUnF8Pu7aXHMyMiy+nrTer1xNExQvHk2p0rFUrpJIdLRBQqKTa6+rzYJfBzHwlkZB6RdpVMBuGFjy2x5GPr6QtWGK6s7KRPKXkSQEVKlaJGiZmiiDQxuIx56Iry+cRkNs/sHbyDGYL6WOIDFH0zKFQqG4kHHq12Oa/noSaTi13hiiPfB6kFIlqVYPfPWas1mLba/Hg02G9Rox+ms49ev9SixePIaFiwYx7vM1jP1sNfv2J1OyRCw339qI2+9oRslSsbnm/LxgJ263fw+8ZUm+mNCLjp2qBvnezg3KeCkgv/6yi+t7TkGGYUdGCChbNp4772lO9RrFGDTgO7/jhw5rGpL8GP1pwMRjT8brhdHxFl9yEq2PJEofhMf+mTTzLrxfsizXqYZ3y8ngzGJNumhFjPEKmjj3wVsKhUIRDgxxBbpohSX/IvdWu46gJE59EJoogS5aYslVBFcQNNBNIkuGm3TrEYQoiUO7zO+M+Hgnw0e0YviIVkGsDxkZwYUzZIQQA3OuUMZLAZBS8uD985A2eaahhYLDoTHwloa89uaVxMU5kVLSt/8lTJ28IZf3RdcFTZuV5ZZb/bvvLLkDtzUB0/4FiYUhWuLUbyVavxuPPRtbnkQTlXFq1yCEN2bFoXUi3vgelzUWj5wLuNFEbaK0QRiiBzarkGSgiZroomqB3rNCoVCcbwihE2d8Tpo5ElP+wJneEl00JtZ4D014t35ijQ9J9dyMzdZwa4HL+iCg8RIqDRqWCWpcvUtKYduSeXO3M/6LNezcfpKSpWLpN+ASet9Un5iY4LOTIoUqUlcAli/9ly6dJhZIRp26JXj5tU60aFmeEiVicpyzLJu331rKh+//md29MybG4OZBjXjh5SuIj/cdZ+KxfyLNHE5OD4q311G0/iRR+jCktPHYP+KyPsv88kXh0K4hSh/st+iclOnYHEaQgCb815pRKBSKCxVb7se0/wAsdNEIXauXa4yULlLNO7Dkb2FfP8HxV9ivse0v/YIN6w9nB+2eia4LLr+iClO/7cOggTP4cfa27MwkTRPYtqRuvRLMnjOA0mVC68MUDKHcv5XxUgCmTdnIbYO/z/d8TRM88VQ7nniyvd9xLpfJ+nVHME2bevVLkpjov5OnLfeT7OmId4sn7z9vrD4Jl/0Zlvw5j7MGccYXGFq7s+QeJsN6D489g6xOqLpoQ7Q+AkMLzm2pUCgUFxNSppHkaUkk6mglOH4Ly7a8y2Uy+/utbN9+nLRUD2M+WUVauidHQ2FdF5QoEcvCxbfwxWdreO+d5T4L27W7rDKz5/QvsF5noyrsFhIlSsYEHuQDISAqSmfwkCYBx0ZFGTRvUS5o2W5rMl5viy+7VCfdegbJdh/nTVLNYSQ6/srucmrLw6R4eiE5wpn7u5ZcTqo5gFhjdGZGk0KhUPx3sOV2IlMANC4z86lgzJq5hXvvnsPJExnZ3hOAxEQn6ekmHo9NXLyDWwY14sGHL6VI0Wg+/XiVz1AIy5Is/nU3Gzccof4lpQqsX35RqdIF4LIOlSlZMndEdyA0TRAVZTDlm96ULRcfdr1MuRT/wWGWH8MlC1dmsSYvGebruQwXLzYgSTMfVVV2FQrFf5BI+AB0nFo/hPDvZQ/Eol93ccuA77LDDs40SJKS3Hg8NoMGN+Lfgw/y5ttdKFc+gXVrD5GS4vYrVwhY9GtoLQXCjTJeCoDDofPCy5cHPV7ToGmzMjw2si1rN9zJFR2r+hxrWTbHjqXjcuWnFXt46rl45BwApEzCI2fjO6JeAkl47HlhWVehUCguFDRRM4/aLYEQ+L79CgRFcWr9CqgZvPT8YgJFhnw57m/GfrYm+3UwgSRCiIByI40yXgrILbc25t33u/oNns3CtqFU6XiefPoyypVPyHPMsWPpPD3yZ6qU/x/VKv6PsiXe5pYBM/h7bfA1ZAzRFv9/2uD+7DLTFWrLfZyZIu1j1Uz3qUKhUPx3EMJBlD4slBlAIoKSCKojqJXrvOQEKWZXMqzR+dZr379JrFi+Pyhj5H/vno5vuaRhKWJi/HuTbFvSpm2lfOsWDpTxEgZuu70p23bfR7nygbeAFvy0w2c30KNH0ujUYTyjPviTpCTvFoxlSWZ//w+dLv+SxYuCc9M59f6AA98emOCK0ujUB8iOe/GPjRDh3wJTKBSK8x2ndjsO0TfzVSDPtwROITmMZDcyV5q1nf3jst7CbU3Jl04nTwZfgX3P7lPs3eut7JuQEMWtQxqjaXm/D10XtGhZnqbNyuZLr3ChjJcwERvrICXZ/z4heC3WbVuP53nu2ad+Yc/uU7lS2CxLYnpshg76Ho8ncDEkTZQh1vgIrwFzZplrHRBEay8AgQOtovQHABBUQqMO/r+UEofWNaBMhUKhuNgQQiPGeJU4YxrBXFtPE/h6nmG9i8xHFdTyFRKDat6YRbtWYylf6h2u6TaJ1pdW4NI23iyns40YKSW7d53kwfvnsWXz0ZD1ChfKeAkjMbHBFe5xOnP3zTh5MoOpUzbmmXsPXqPn8OFU5s0JbmvGoXUkwbEAp3YbGrXRqI5Tu4l4YzYIN3AkoAxL/gp49zejjQfxnb2k4RC90ETloHRTKBSKiw0hBIbWHKfWmdAbNvpGchhbbgx5XrFi0VzSoHTQ45OS3KSkuPl9yV6GDPqeuvVKMvrTHrRoWZ7YWO82khDe8IcjR9IY98Ua2rYay5wft4WsWzhQxkuYSEpy4XEHtqKLFo2mVu3cRYd27jiJO8B8w9DYuDGw0ZGFJioSYzxBgnMuCc4FxBivIDlGhvVKUPPTracw7ZUAOLSriNFfA5x4PTAGWV9Qh7iGGOPVoPVSKBSKixWHdhPBtQsIHkvuytc8wwg9eSPrAXrsZ2uIjnYw4sFWpKV5Yx7PjJ+xTIlp2gwaOIMjh1PzpV9BUHVewsQXn60JqsvzI4+3Qddz24xZlq0/bFsSW8CyzC5rDFmVdgOj4bI+x9CaA+DU++LQuuGyvsOSa0DYOERHHNq1CBG+Jw2FQqE435AyGY+9AMlxNFEeQ3TKM5XZ0Brh0AbgsSeFcfWUfM3y5ckPBl0XjB71J4ahZVfZPRspweO2mTD+bx56tE2+18oPyngJE+O+WBPUuEqV8q4aWLtOCapVL8rOHSd9zrVtSfdrzo5MDx4pJaZcRvBPBRbmWSWvLbkNj5yKLTeBBJNZZFhvEK0/jlPvlW/dFAqF4nxESonL/hiX9T7eyuLeRrWCIkTrz+PUr8s1J0Z/EV1UxGWNQXKiwDqIfLYIaNS4DBvWe6uzh4plSVatPJj9b1/YtmTZ0n/zpV9BUNtGYeLggeAs4yceXcjGDbm3foQQPP5kuzxmnKZzl2rUqFEsX/qdJtQP8WlDx7TXkGoOwJZbcoyQHCLdeijfUfEKhUJxPmLLPaRbj+Ky3iKrJUrWNVRyinTrwTzrWwmhEaXfRYJjKXHGDGL1yWjUJH+xMA4M0Tpf+g+7o1m+DJcsTNPGtPzPF4I8dxMijTJewkSpUsFV2j1wIIVLW3zOh++vyHWuWNFov3M3bToaVLaRL4QQ6KIpwf/ZdXTRLPtVhvUyXmMm7w9zuvUKUkaiTLZCoVAUHrbcS4pnEMmeK/DY3/oZKcgw3/BZsE0IJ4bWGIfeiljHxwiKEupt16H1Q4giIc3JommzstkPxb5SnwMSxM7TFZ2q5k92AVDGS5i4+dZGIY1/8vGfWbhgZ45j7769zG9q275/k/lhVnCt16VMx219Q7r5Ehnmm5j2KqSUROlDCd774u2PZNorMO1dWHJVgLkpeOwFQcpWKBSK8w9bHiLFcyOWXBrEaInNLmy5IeBIXVQn3jGHKG04EGxbmeJ47LmccjchxdMLtzUNKfOuE+aLp565jPETe1G7Tu6tJ00TaAWwAjRNkJgYRf+BDfIvJL9rF8Yio0aNomrVqkRHR9O6dWtWrMjtdTiTadOmUbduXaKjo2nYsCE//vhjYahZIIbd0Yyixfx7Ts5E0wTvv7c8+3V6uodlS/f53Vs0DI0F83cElO2xF5HkuZR061Hc9gRc9hhSzd6kmjeh0QIts/hcMFhyBalmPzKsp4MYrSE5GLRshUKhON9wWR9nxqkE7+W2g4xr0URJoo0HcGo3EdwW0nG8ZS2SsOTfpFuPk2reFnIfuarVirJr56lcD8dSSux87ippmiAuzsE3M28iMbFgPZjytX6kF5gyZQoPPfQQzz33HKtWraJx48Z07dqVw4cP5zn+jz/+oH///tx2222sXr2aXr160atXL9avXx9pVQtE8eIxLPz1FqKigtvTtG1vZ84sd2MwUeFSyoD7l5a9gTTzdk5Hp5tkfQktuYY0sz82odQMyJr7RxBj7bB0QVUoFIpzgZQWbnsaoaY6a6JCSOMd2nUhr5GFJf/AZY0Kac5jD8/H7bFy3Wek9MasxMU5gqqYKwSUKx9P60sr8OzzHVi74S5atQ7tvYeLiBsv77zzDrfffjtDhgyhfv36fPzxx8TGxjJ27Ng8x//vf/+jW7duPProo9SrV4+XXnqJZs2a8eGHH0Za1QJTq3aJPF1zvrClzM6bj4tzUKNmMYSfbUnbljRvUd6vzAzrY7yblHkZQxZ2wG7SBSEGh9YlgvIVCoUikqRl/gSLhi6aoovqIa2ii0YY4krydwu2cdsTgva+bNt2nOXL9mH7eECWElJTPfS5KTiP/PD7WjL/l1t46NE2lAwy1jMSRNR4cbvdrFy5ks6dO59eUNPo3LkzS5fmvZ+4dOnSHOMBunbt6nO8y+UiKSkpx8+5YseOE6z7O/gico0alckOohJCcM/wlj7Hapq3BUHf/pf4HCOljSnnEe4CScESrT+o+hspFIoLmFgg2C0QDXAQrT8X8ipCCGKND3CI6/AW/QwtmFZyClsG1+tu757A90RN8z7uBgp9kBJ++XlXdu+9c0lEjZejR49iWRZlypTJcbxMmTIcPJh3bMTBgwdDGv/aa69RpEiR7J9Klc5dp8sd20PL569dJ2cb9aHDmnBD73pAzshwwxAYhs6Er68PsLfoIXD353Bw9hctgWj9WZzabYWwtkKhUEQGIXQcohfBxKPoojnxxlQMzX+yhpQSj72YVM+dJLs7kezpicv6DHAR63ibBMdiovUXEJTwKye3ssGVaStePHAspm1DmTJx3DO8hV/vP3iNlxuvm1qgFOxwcMFnG40cOZJTp05l/+zdu/ec6RJq0FJ8fM5qubqu8fm4nowZey3NmpcjNtZB8eLR3HJrY5YsG0LnLoFck04EZQKMCQeSaP0NYvTXiDU+JtGxnCh9MCLQp16hUCjOc6KNe4A4fBkwOu2Id/xCvGMKutbQrywpbdLNx0gzB2PKnzMzk9aTYb1GsucqTHsZpr0CQTSaqEawt2RBGTSqBDW2UeMyAUMSHA6NKzpV5ZHH2mY/QPvCsiTLl+3jx9nBZb5GiohW2C1ZsiS6rnPo0KEcxw8dOkTZsnkHB5UtWzak8VFRUURFFX6kc140b1GOUqVjOXI48J6pEFC0aEyu45om6Nv/Er/bQ75lCpz6Lbisdwi9GF1oOLTWqhGjQqG46NBEJeKNqaRZD5+VAu3Aqd1MtP4EQgTXpsVtj8cjv8l8deZ2vkRylFRzQL50jNJvD7olixCCl17pyIC+vuvVeDw2/XpPZ9ac/owd35Olf/zL/n3JfmTC668uoUXL8pSvkBCy/uEgop4Xp9NJ8+bNWbhwYfYx27ZZuHAhbdrk3QehTZs2OcYDzJ8/3+f48wld17jjruZBjZUSbuzj38LND1HaEHTRgEj+aTUqIzh323MKhUIRSXStNgmOWcQbM4nR3yRGf58Ex3JijGeCNlyktDO3h3yOyJduDq0fTm1wSHOu6VmbMWOv9VuobvWqg7z43GKEEKSmuP3KkxLWrztC/dofce9dP5CRURjhCjmJ+LbRQw89xJgxYxg/fjybNm3i7rvvJjU1lSFDhgAwaNAgRo4cmT1+xIgRzJ07l7fffpvNmzfz/PPP89dffzF8+PBIqxoW7r2vJQ5H4F9ri5blaNQ4/Fs8QsQQZ0zCIa4Ju+wsDK2j2iJSKBQXPbrWEKfeG6d+DZooGtJcyQEkB/K58tn3kKIYXE2cMZkY/RWECP3WXbpMHLbt22CyLMlnn67iy3Frg84ism3JVxPWM3TQTJ9VhiNFxBsz9u3blyNHjvDss89y8OBBmjRpwty5c7ODcvfs2YN2Rom/tm3bMmnSJJ5++mmefPJJatWqxXfffUeDBoVfwS8/xMc7GTy0CWM/W+2zdktMjMHMH/pFTAchYok2Hsfj+T4i8t32VzjlIHRRLSLyFQqF4kLHkpvzPVdQmRjjKUCii8ZoolSB9Vn51350Q2CZvo0Mj8dm+N1zQpJr25LZs7ay8q8DtGjpv5RHOBGysM2lCJOUlESRIkU4deoUiYl5d3CONKdOZdDjqklsWH8kh6WraeB0Gsya05/Wl0a+sE+q5zZMuZjwp07rOLVbiDGeDbNchUKhuHCR8hSmvZYM6y1sArcM8E0RijhXh00vgPfeXsbzzy7y633JL4ahcdvtTXnrnYLV+Qrl/n3BZxudjxQpEs28hTfz1LOXZQczxcQY3DyoEb+vGFoohgtAjPF8vhqBBcbCtH8Os0yFQqG4MLHlEdI8D5PkaUmaNbiAhotAo1zYdANvuvahQ6kRMVyy5B87VrhNeSO+bfRfJT7eyaOPt+XRx9tiWTa6rrFt23HGjlnNihX7iXLqdO1Wg4GDGlGiRO6so3CgiUrEO74jxdMPyb6wypaFUk9GoVAozm9seYwUz42Z8S3h8XI79fCGFbz5+h+M+uDPsMo8m8qVC3enQxkvhYCua4wbu4YRw+cihMi2fpf8toc3X/+Db7+/KWL9ITRRAcmpMEvV0UVwWVUKhUJxMeOyPgrRcDHQqIjNbnJnHOlo1MKp9QmbfseOpvHGq7+HTV5eWJZk4CD/xfrCjdo2KgSW/fEv9w+fi5TkcNtJCUlJLm64bionT2ZEZG1v+/Rwe0ksovRbwyxToVAoLiyk9OC2pxKax8UiRh+LQ7sZcJ5xXMchribe8TVChM8b/830TVhWZOt+3f9AK2rVCr6vXzhQnpdC4K03/vCb0p90ysXXX63j7nt99zbKD7bcS6pnEBAuw0gHLKL1xzC0ZmGSqVAoFBcmXq92asizUq0uOLQ+xBvfY7MfsNBFo7BkFZ3NoUOpGIaGxxN+A6ZEiRgefrQN994f3ntXMCjjpQBYls2fy/dzKslF9RrFfFqev/y8K6Csl15YzBuv/UFcrIMbetfjjruaUalykXzrJqWbFM8tYYh1ceKt1isRlCdKv5co/aYCylQoFIoLH0E83g2MUA0DC489DdP+iXjHtxGtVl6uXHzY+hAJAQ88dCmdOlclOsqgWYtyOBzBVfoNNypVOp9MGL+Wl174jYMHUrKPtWlbkXff70r9S3Jaz4kxr4ckW9cF0TEGM2f3y3csjNuaTbp1f77m5qER3i+nBlg4tdszS2SrQnUKheK/g2VvwpQrAIkhWqFr9Un13IUpF5K/YF0dXbQh3vFlmDU9zfHj6dSu9iFud976aRo4owwy0oMLL+javQbTvg1fTM6ZqFTpCDPqgz+59645OQwXgBXL99H5igls2niEw4dSOXEig127ToYs37IkGekmfXtPx+XKX7yKKRcQTGdU35xpmFh49728H363PQa3ffrLZsuTWHIHtjxZgPUUCoXi/MSWh0nx9CPFvJoM60UyrJdIMa8hxdMHp96fnNfLULCw5BJsGbmGwsWLx/D0s5fleU7XBU6nQf8BDTCM4N7DH0v2UrLIW1Qs+y733zuHf7YcC6e6QaM8LyFy4kQGtap+4NOKFQKcTh2XKzwpc2P+v73zDo+i6uLwe2dmd9NIQg+9d1GaIoIURSmiVLGAgIIdP7H33nvBLooNBVSKoqLSRJDepEtHSugJ6dmdud8fSxZiNtuymwL3fZ4oO3Pn3rs7uzNnzj3ndz69PKQije6ngd8JrX6GO7bFF4IqxBifkmO+eeKpQwICQ1xMlH4PutYkhHEVCoWidCFlJunOPlj8S8Hroo6gBjoNcRG69lWM8Qk2rVuR5ukLKSUff7iS559ZwNGjJ/VYWp5dhbff7cXSJXt56P7ZQevA6IbA0DW+nz6Yzl0Cq3Lti2Du38p4CZJPPl7F3Xf+SnF8ajabxrDrz+GNt3oE1F5KiSmXkWtOxCUXITng/6B8CDTqo4kWuOSP+Dd8HLgzmU79QeuAnThjot9y8QqFQlHayTG/Itv0pyYuCLXQIkCs8TWGdn7IxwdKbq7JH/N2cjw1h0aNK3rq6yXvT6dZo3cLLWnjC00TxMc72Lz9dqKjAytaWRhq2SiC7N1zHMMono9NStB9VAHN39Yky3UfGa6rccofQzBcACQW23HJHwjsh+ik4JOICeSQaT7kpb1CoVCULZzWVPwvCxXlaTYWSx7BZS1HysilNM/8ZSv9L5/EoP7fcv2wH7jjtl+YPHE9UkqSqsVx+x3nEkoYo2VJUlKymfJ96LWcQkEZL0FSsVJMSNZpKLhcFt0uqhtQ2xzrI5xyyolXRVmyCua9FfZDs7DkBkxrXRHmoVAoFCWPJY9SNOPEHxlkmXeQ4RpMmrMLTmtm2Ed449XFDB7wHX8t/Jc8+2jN6gOMuv5H7rv7d6SUPP1cN+6653zs9vyxkoE8rNtsGiuWh1pBOzSU8RIkAwc1C8k6DRYhIC7OxrZtxzhyONNnWymd5JqfRH5SHgL7AEy5I8LzUCgUisiii9oU161SspdM123kmjPC1ufavw/wxGPzAPI9eOfFt3z0wUp+nbkNTRM8+UxXNm8fzXsf9ub5ly5i4rcD2bjlNv/zlmC3Fa85oYyXIEmqFsedd7WP+DhSQlaWi8cfmUeTBu8y4cu/C21ryX+QHPXTowbYKPopF0BgQkpCxBVxLIVCoShZ7PpVBK/jUjSyzadOqKMHj5SSWb9vZ/CAb2lY520uvegrnw/cui54+YW/GHL1FGpXe5M2LT9k5i/baNu2Gr37NCIhMYoaNXxfy10ui0t7NghpvqGiAnZDwLIkL72wkDdeXUx2dvEUKBQCpvxwFRd3r1dgn8v6mwxXP389nPh/OE53IMFp5Yi3LUUIRxjGUygUipJBSpNM10hccgEFjZiiBer6Isb4FJvWNahjpJQ88uAc3nl7GbohMF2Bz03Xhcczk/fvZ57rxo8/bGbpkn2FHmcYgkaNK7Jo2Ui0AGM0C0NlGxWDSJ17rBx+m7mN48dz0HXBPWN+w+WysCJgpOu6oP35NZg5a2iBfVJmctx5LlC8Jcl9EaU/hEO/saSnoVAoFEVGyhyyzTfItb4C8pbxozG4HBeTIzJmtP7CCa9P4Ez9fhPDh04L6zw0TfhMoa5XP5EZv1xTJEX4PIK5f6vyAEUgPt7BoMHNPa9r1Ixn2JBppKflouvuEx4u09A0JX8t3MOxY9mULx+Vb58QMdi1q8m1Pse7e9O/bkv40HBot2PXRhXTeAqFQhFZhHAQbTxIlPwfptwASHTRHKf1My4zMsaLEJWCPubdsUv9GhvB4q+vN97uERbDJVhUzEsY6X5JfbbsGM0No1rhcBj5DJc2bZMYOqxlkYN9s7O8r4NG6feii9YnXp06iIYgAUEtQleBDJxo/XWijLtU6QCFQnHaYMnD5JgfkmU+htOaiiQTiMYimUj5AAzhXRW30DlakmXL9oXVcPGHrgvWrApFlqPoKM9LmHn80Xl8Om51ge2rViazaeMRypWzk5HhLJBuLQR+vTSJiQ4qVY7xuk+IaGKNr8i1vifX+hpL7kYQj10biF0fitP6mWzz6VDfVhCcVquQCoXiDCfXnEKW+RAnvdeCXOsbBE1xaP2IhFdbUAEh7MEdI0AgkAFcgzVNIGXRVwakJOCyAuFGeV7CyPSpm/j4g5Ve97mzh5w0aVqJ6jXKAWDYNE8Off0G5YmKMgr1zOi64IZRrX1W8BTCgUO/lnK2GSTY/ybevoAo4y40URm7djW6aEPBUy5O/PfsoN5rYUSyOqpCoVAUJy7rL7LM+3ALclon/tzGimQTOdanBH8b9XezFyHFCwohuLBzbXTdd/+tWieRlBQblpAGy5J0u7hgEklxoDwvYUJKyQP3zfLTBpYt3cfaTbewYf1hFi38F00TdO5ah67d6jJ96mauHzYdTcufj69pghZnVeae+zuEPD8hHMQaX5Bjvk2O9TWQ5t5OTaL0W8m1fqVo2nsCjXroolVROlEoFIpSQ7b5ns/9koMEexuN0l/EZS3AJWdQ0FOtoVEfu3ZtUH3mcceY8/hj3i6v+9wy/nZM02LfvnSvbYJB1wUdL6zNWS2rFLmvUFDZRmFiyz9HaHvOxwG1nfn7EC7oVCvfsZMnbeDIkSwsl8WWLUdZ8OdupIQKFaMZeWNr7rrnfOLignMjFoaUOSeKjNnQqIUQGhnO23DJ3whNz0ADNGKNLxAkYso1gIahXYAmaoRlzgqFQlGcSJnFcWfwRXELR0MX7Yk1PgMEOeZb5FifARkn9uvYxGVEGU+gifIhj/Lma4t5/NF5GIaGy+W+nmuaIC7OTr16CaxZc7CI78NNo8YV+HXW0EJDGUJBZRuVACkpOQG3rVAxGgCn02TMHTP58vO16LpA09y59ULAgw935Mab21C+QjS6Ht7VPSEc6DTMt82mXYLLDE2WWhfnYNdGkW2+jimXn9xhCgzRmxjjeYQoV5QpKxQKRbEiZYb/RgETi10bQpR+F0K4ixdGGffgkLdhyjVInOiiGVoIGUb/Zcw953NR93qM+2glK5bvx+Ew6HN5I+o1SGT4kOlF7h/cxtB57auH1XAJFuV5CRMHD2TQqN5Yv+uINWqWY8M/tyGE4P57fufD91cUesybY3tww6jW3neGGSlzSHNegmQ/vgPQdDRqEG18ChxBiCoI4kl3XobkkJdjNXTRmljjG4RQtrJCoSj9SHmcdOcwLApXNvePQBcXEK0/gCYaIER02OYXCrfcOINJ36wPW22+mFgbyYfvCUtfeaiq0iVAlaqx9O7TyG8q9Muvdmfpkn0Muep7PnivcMMF4MXnF2KaxSNLLTmMIc6n8GyhvMDeJGJtX2Bo9TG0c9FFHXKtr06s/XozeixMuQKXnBuhmSsUCkV4yXTdi8X6IvYiMeViNNGwxA0XgKNHssJaVDgzw0lJ+j6U8RJGnnvxIhISHYUaMLff0Y5tW49xSbcv+WnGVr/9Je9PZ+WK5DDPsiCmtZY0Zy+ccioFY17KoXM+hriEaP1Vytl+L5BRlGt+6+W4U9HINb8P86wVCoUi/JhyJy45i/CkQJvIE8kRJU3tOgkBVYgOlLp1E0pUz0sZL2Gkfv3yzFswgiv6NUE75ZOtUiWGUTe3pkrVWB5/dB7gX7Uwjz17jkdgpieR0iTDdQtuyWtvP9Y0NFGFWNsH2PUBCBFVoIXkmJ9RrBNLSgqFQlG6cVkLCZ+gZzSCRJ8tpJS4rKXkmBPINadiSX/X09AYNuIcTwBvURECRt3UJix9hYoKQggz9euX58uv+3P4UAavvLSIzz5dzcGDmYz7cFVI/T147yw6XViLX37ayvp1h4iJsXHZ5Y1o265aWKxel5x3Is6lcJzyB1JzZ6OJ2ti1q7FrV+YzYjSqYrGDwpecdAQ1izxXhUKhiDzhEp3TsWuDPAG63nBZa8hy3X3i+pk3vIFdG0aU/qDfOEGn0+SHaf/w5edr2LMnjerV4xhy3dn0H9gUu92tCbbn3+NM+Gotu3am0LJlFdauLXq2Uf0G5bnxlpI1XlTAboR449XFPPHYvLD2abNpSOkuP96pc22++qY/FSoUbS012/U6OdYHQCDVsd0VVHVxNrHGVwjhLpOeY44j23wBX+q6scYXGFqnIs1VoVAoIo3LWkOGq38RexEIqhJnm44mKnttYVr/kO7qB+TirVq1TVxJjO3FQkdIT89lYN/JLPprj6cKdF5do7btqjFtxlV8/OFKnnlyPpomPCrupimx2TScztC9MB+N68PVQ84K+fjCUAG7JUxqajbPP/tn2Pt1Oi2P22/Rwn+5etB3RQ+YEjqBa7u4xzLlOrJcz3m22rVrEBSm5yIwxKXoomORpqlQKBTFgS7ORhNn4S5oG2IfXEKcbUqhhgtAtvk2J5V7/4vEKSdjym2FHn//Pb+zZPFe4KSoaV44wupVyfTrM5Gnn5jvMVhcLulp53JZVK0amy+8IVCEgAu7lLySujJeIsCMH7eQkxPZKs6mKVm8aC8LF/xbpH4M0ZngheksnHIKUqYC4JJ/IdlTSFsdh3abKtSoUCjKBEIIYoy3EZQn1FukoTVGE0mF7pcyE5f8FX+yFE7Tuy7L4UOZTPx6faGxk6YpWbG88GQPKeHAgQysIC/9ui64ol8TatQsuVWNPJTxEgHm/L7Df6MwYBgaU7/fVKQ+dNEKQZ0QjnRiyg1I6STL9RCFB7hJsq0XijBDhUKhKF50UZc42884tNsRVMMdeFsXCEyULdf6Cimdhe53ZyD5e8AVSI543bNk8Z4iB98KAdHRBprm/8FSCEBA02aVeOudnkUaN1wo4yXMHD2axdQpG4ttvIyM3CIdL4QgRvddv6Mwsl3v4rR+R3KUwuNdTEy5BEvuDnmOCoVCUdxoohJRxl3E2xeSYF9PvH0OcbYfEVT0e6wk5YT2lXfcGUj+yr1YCFHde/9hiFTVdcGQ61oSE2vLZ8DkpVP36NmAVq2TqJoUyzmtknjjrR7M/mNYkeMsw4XKNgozX3+1NqxCQL6wLEmTJkWXk5YiNMPC5C+yzLXkBfL6wpL/qorTCoWiTKOLeti1QeRY4/DnOXFZK7Hr3mMBhXBgE/1wyu999mPXBnjd3u7c6p7g3FBxuSSX9mzAAw91ZPynq5nxwxayspy0bVedUTe15rz2pbsunTJewszGDYfRdS1s+fT+SCzvICfHhcMR+qmUMrMIMwhMgMmf1oFCoVCUBQztInKsD/22yzLvRJKGQ/deITrK+B8u5ywkqXgzYBza7Wiimtdjk6rF0X9gU6ZN2RTSw7KmCZKSYrnk0vrousaDD3fiwYfLVjaoWjYKM9HRoRkR48ZfzsArmwL4LTFwKneO/pXG9d/hpx//CWlcAF009N8oZAQaddFE8wiOoVAoFMWDLtqh0ZJAbp/Z5hNY0ruOliaqE2ebgiEu4NSYQUEFovQncOhjfPb9+ls9aN6iMkIEd8/QdYHNpvHJ51eEvehvcVJ2Z15K6XNF45C8Lq1aJ/HJZ30Z+14vmjZzLwUJDbp0rUP/gU2Jj3cUOCbPZZhyLJshV0/lz/m7QpqzJs5CE82IzNdBEmXcp7KNFApFmcdlLSTDNQyLtQSWpSnJNScVulcTtYm1fU452x/EGOOJNSZSzrYIhz7c7zWzfPkoZs27jjfH9qRV6yQMw/81VtPgin5N+Pm3a9m/L5333lnGtCmbyM4OROerdKFE6sKMlJJuF37OmjUHMF2BfbS6Ltix504SE0+q1jqdJpomPJbxP5uP0K7Vx4X2oWmC8zvUYOasoSHN27Q2kO4aDOQQPoXJOKL1J7Bpl+L+occrI0ahUJRJcs3JZJl5mZWBPqAKDNGDWFtoSRGBsntXKmc1fd9nG10X3PfgBVSsGMOTj80jI+NkNpTDofPQoxdy973nA+77z9EjWcSVsxMb6y+wOHwEc/9WMS9hRgjBd1MHM6j/ZFauSPYoHxaGrguu6Ns4n+ECYLPlF0j66cctPvuyLMlfC/eQvD+dpGpxQc9b15oTZ5tOtuttXPJnim7ARGOIjmSZz5Jl3geAoDYOfSR2bQhCKKefQqEoG1jyIFnmI7gTE4J53te81oMLN1lZhadle2aiCZYv3ccsL1IeOTkmTz42j6WL/6V2nUS+/PxvMjKcCAG9LmvIAw91onWbwnVrSgJ1B4kAlSrHMPfP4fzw89WMvLE1bdp6P+m6LoiNtfPok1389pmSkh1QPn5qanbQ8/XMRzQg1vYW8bY1lLMtROMsQv+KZJ0QYUr1bJHsJtt8gizXvUhZPAHNCoVCUVRyrW8JzmjJw8SmXRLu6RSgVu0Ev/GWTqfFX38VJibq5ueftvHh+ys8Xhkp4ddfttG96xfMnbMzXNMNC8p4iRBCCLp2q8urb1zKvAUjePvdnlStGpuvTYcLajL7j+to1KiC3/7q1kv0G0tjGFpIXpf/IkQMmqhGrO1dBIXLW4eKU07DJWeGvV+FQqGIBJbcHMJROoJ6WDKddOdQ0nJ7kOEcidP6DSnDq8AeE2Nj6LCz0XXvD7iaBnFxNjIz/Hto/htIYprusgKjRvyA0xlZ5fhgUMtGESYnx8UP0/5hyz9HuXZoS2rVKkftOgk0aFSRBg3KB9THmtXJZGU5faZg64ZgwKBmJCSEz0WpiVrE2X4m1/qaHE8djnAgyDG/xKb1DlN/CoVCETncnuLgPC+C2gh0ss0HcPsJLCy5HZdrLoa4kBjjI4QomIgRKo8+0Zn5f+xi65aj+cIL8gya7pc2YNqU0BTZLUty6FAmM3/eyuV9m4RlvkVFGS8RZMGfu7numqkcOZKVryJ023OrMenbQV6P+XvNAd5/ZxmzZu3A6bSwLEnKMd9LQbouqFAhmiee6hz296CJ8kTpt6NR6USwWjiQWDL01G6FQqEoLnLNb3HJXwjGeNHpgBBRuOT8E1vyHjrdnguXXEi2+RLRxuNhm2f58lH8Pvc63nxtMZ+OW0VKSg6aJujZuwF2u1HkUjKGobFx42FlvJzubN50mAFXTCY31/1lPbX8+OpVyfTtM5E/F13vkWIGePG5BTz/7IKgxtF1QZ8rGvPcCxdRq3ZCeCbvBZt2JS5r+QlFSPdTRNGIfBCbQqFQBIOUEottSJmCJmpgyd1kmQ8SnNfFwGGMIdN1lY82FrnWN0TJuxCiXBFnfZLExCiefKYrw68/h9WrD1ChQjS7dqYw+tZfity3ZUliYmxhmGV4UMZLhHj7zaW4XJZX+WbTJVm/7hC//LTFY8V+9unqoA2XF1+5mMFXtaBS5cCKhRUFITSijZexyYvIMT/BlBtw/6AtQllOMrSypeaoUChOb5zWbLJdr2CR5xUWELQyeDSxxlcBepZzMOUaDBG+a+G2bce4585fmTN7p2dbYXEwwSKl5LLLG4elr3CgAnYjxJTvNvoMsNV1wdQp7iCwzEwn9971e9BjfDd5Q7EYLiexcFmrMOVqIBe3CzS0OBib6BXGeSkUCkXo5Jo/kum6CYstp2yVwDEC9brodKGcsRZDax3wMTKkDCbv7NqVwsVdvuCPefnFSsNRa0/TBIMGN6devcQi9xUulPESAaSUZPrJuzdNSXpaDgBTp2zyLC8Fw/Jl+9m+/VhIcwyFHPNVcq1PcHtbLCBUVUYNl1yMaa0N3+QUCoXiFEy5iyzXk6TmtiI1txGpuS1Jyx1IrvlHPqkGKXPIMh/LexX6eCzwVJLWtbYBHKGhET7tlBefXUBqanZECgNf1qcR77xfuh44lfESAYQQ1K9X3me9CV0XNGrsLq2+fm3hpdN9jwPjx60O6dhgseRRcqxPKMqP+ySSXOsT0l19SXcORcrjYehToVAo3LisZaQ7e5FrfQkcx+0lzsBiFVnm9WQ4r8e0tuC0fifbfPtEm6Je20yyXHcBoItG6OJ8QPfR3iLDNRxLnrz+Z2U5mfTNel54bgHvvbOMfXsDK3ybkZHLt5M3BqzqHgyVK8cwYdIAoqNLT7wLKOMlYoy6uY3P/aYpOXo0k6VL9uKIMoIqrJWHlLB0yd4QZxgcLut3Qve0/BdJXtS9KZeQ4bqR06xKhUKhKCGkzCHTdTPuUiferysmf5Lu6kGm62ZyLd+y+sFgsgRLuoXgYow3EFT3PVcOke16FYDvv91Io7rvcOMNP/LKi3/x8ANzaN74Pe4Z85tfja8jh7NC8t4HgmErnWZC6ZzVacCom1rT4YKahariappg0jcb6N71S+bO3llAGChQbPaClv2qlcl8+P4Kxn20ki1bjobW8SlIaZJrTSlyP94xMeUyXNa8CPWvUCjOJJzWz0hSCI+XOHhM+TcAmqiKQ7vJX2uccjq//7qOG4ZPJ+1EKEFesodlScZ9tJIH7p3ls5fE8lEBKbCfiqYJDEP4fHA2DEHnLnWC6re4UNlGEcLhMJj641W8+vIiPv5wZQGtlrwvJrhF6MqXjyI1NRsryAzknj0beP69c2cK1w+bzopl+z1fSCnhkh71+eiTy6lYMTqk95Jjvoopl4V0bKBkmjfhkDfi0O9BCF+uVoVCoSgcd0KBTvgKzAqgCnCIwCQiTt5WJftPvPbltXby9JMLEAKv138p4ZOPV3H3vedTo6a7WGFGRi6TvlnPpG/Wc/RIFg0aladtu2qsXLE/oJgXTcu7B/lu53JJbr41kPid4kd5XiJIdLSNx57ozNadd9C8RaVCLVzTlBw7lk3zFm4p/mCWkPoOcKdaHzmSRc+Lv2LNqmTA/YXP8+bMmbWDvpdNDMmtaMljJ2JdIo1JjvUhWa5HimEshUJx+hLOhx/3xTjGeI4YY3wA7Q10ce4ph8fiz+D5d1cca1an+DUkpk11Z6fu3XOcC877lDH/+5XFi/awefMRfv1lG8uW7kNKAvLA+BsrT3/sldcvod25vpe+SgplvBQDR49ksWH9YZ9LQ7ouuKxPI2bMvIbrR7UKuO/sLLdF/+m4VSQnZ+DyErBlmpK/1xzgh2nB1+fINccTWKxL3lepKJoCEqecjGkp9V2FQhEahnYhRfe65F3PYonW38KmXYRNuxCDy3weY9OuQhMny77YtJ74Nl400lLP8jsbXRekpmYjpWTotVPZvSsVTnlAzfO2WJYkPr5oJQeqJsVy5VXNmbdgeKn1uoAyXoqFjMzAypVnZbno3KUOb77dk6SkWL/HAJQr5/6iTvhyrVdBvFP7/+brdYFN+AQ55jhyrHcCahulPUeM8Q6G6IRGPTQaBjXWSbQIxtcoFIrTHUN0RqMeoT9Inaognk6u9YnngSrG9jK6R1Qu7/apnxi3E9H6o/l60kU9bKIvhd9qJfXrXO9XSM7ptKhXvzwrlu9nxTLfS0MSi4TE0AwYXReMuqkNH47rQ5u21ULqo7hQxksxUL16HDGxvtPMnE6Lps0qeV7fcns7v/22al3VU0X66JEsn20tS3L4UGYAs3XjspaSbT4fcHub3gmb1ptY2+eUs89G19oQWkiVhdP6XWnAKBSKkBBCJ9Y2HkHVEHvI7ykx5TrSXYMx5S6EiCbW+IwY4xMM0RNdtMEQPYkxxhNjfOq10GK08SI20efEKx2w4TasoojWX6Vq5Uvoc0VjnwZMXJydvv2a8Ocfu/0aOqkpuaSl5Qb3lk8ghODggYyQji1ulPFSDERH2xg+4pxCv3RCQFw5OwMGNfNsG3P3+dSuE++z38ef6uL5d+3a8T5jZYSAOnUDr32UY44nsLVjHV1ciCZq/Ge7k1Cj/SU7SHf1JcN5B1Ke/BFKKXFZK3BaP+OyluUTmlIoFIo8NFGbcrbZGGFR8nZrxOS43F5oITRsWjdibe8QZ/uOWNtYbFoXhPB+OxXCQYztTeJss3Dod2LXridaf45421Lsen8Annm+GwmJUQXuEZrmzgZ6c2wPMjOcrF6d7NPDnocVolCdy2VRo0b4ai1FEmW8FBMPPdqJRo0rFPhy6rpA0wQff9LHU/RKSsn6dQd58eXutDircoG+HA6dceMvp/sl9T3bht9wjs+YGimhatW4gOfrkosJbN041mtlVF2cRVGLN7rkz2SZzwHgtOaS5uxKhutKMl2jyXBdRZqzC07r1yKNoVAoTk+EiEYTtXB7OoqKiVP+gJQ5Ifegi/pE6aOJNh7Erl+NECevx3XrJjJvwXAuuzy/B6bl2VX4evJAli7dR+P67zD1+00hy2oEylXXtIjsAGFCpUoXE4mJUfw25zpef2UR4z9ZTWpqDkLARd3rcf8DF9C+Q00A5szewUP3z2bjhsOeYxs2qsD5HWpQqVIMDRtVYMCgZsTF2fP1XyUAw2TmL1t5+bXuiADSmQQiAL9JeeJs36GLegX22LUBZJuv4Esoyj8Sp/UNuWZbssy7vOzdR6brNmKMd7BppUu6WqFQlDyaqED4UqadSI4jKPhAGQ7q1k3kq2/6c+RwJv/+e5yExCjq1Utk5Igf+G7yhogbLeBOoc5Lxy7tCHmaSZseP36chIQEUlNTiY8vnSfB5bI4djSLmFgbsbEnjZCPPljBfXf/XuBLqmnutcjvpw/moosLGgoADz8wm/ffXe43x3/T1tupHoBbMMN5By45k8J/+BoObTRRxphC+3Bas8h03cbJWkihIaiI5CiFGUGCKpSzLVT6MAqFIh+W3EuaszPhEayzEW/722tcS6RYszqZCzt8Fpa+YuNsZKQXnjwiBLQ7txqz/xgelvFCIZj7t1o2KgEMQ6NylViP4XLkcCa9e0zg3rsKGi7gzsm3LMndd/5WqIy+lCACyO8P1FZ16CMo3HARgA27fo3PPmxad+KMaRiid0BjFobkCL4uPpKDmHJxkcZQKBSnB1K6cFozyXT9j0zXI4Dd7zH+0bGJK4rVcAGY9M16j+ZKUfFluID7HnLb6PPCMlZxoIyXEsbpNOnbZxJ/LfjXZzspYfu2Yyxdss/r/g4X1MTl9O3dqFGzHNWqBxaMZWhtidKfwm2onOrRcEfLxxjvoQn/0fy61pwY4xU0OvltWxQseSCi/SsUitKPJQ+T5uxDpus2nNYMTDkf99J1UdCBGBzG6DDMMDgOHcostrpvjRpXYMCgpsUyVjhQxksJ8/OMLfy95kDAZQH2/Ou9AnPvPo2oUaOcz4ym2+84N6j6Fw79OuKMGdi1wWjUR6Mxdm0k5WyzsGndAurDtNaS5uyExYKAxz1l1ggCq6shRGTWoRUKRdlASkmG8wYkoYpcFnLtpBpxxrfoovhq/EgpmfLdRv6Yt8tvKIC/1OlAcbmsgOIhSwsqYLeE+f67jei6CKgeBUClyvnrE+3fn8Y7by3lx+lbOHw4E8uSCHFSeTGv70GDm3NrANox/0XXmhGtPee3nZSZOK0fcclVCHQMrTMaLUl3DQVC1Q0wiNHfJ9O8Eck+Co95qYQhOoQ4hkKhOB1wWauwCE6IMz+FLMmzB1NuQadxEfoOYhZS8tD9s3nvneV+S8XoumD49efwy09b2b8/vUjj2kpp9ejCUMZLCXP0aHbAhktSUiwdO9UG4PChTB64b5bXKHQh3F/qChWiOevsKtx4Uxt692kUdNXRQHFZf5HhugVIJ+8rlWt9A8Sf2BaK21Ng167F0JsSLR49EfjrnSj9EYRQX2WF4kwmVwZSe8gbOu5rVOHu7xzzFWxa72LxTMz6fQfvvbMcwG9JmcqVY3nw4U689ualnNt6HFu3HC3QTgioUCGalJTC7zW6LujZK1RV9JKhbJlapyENG5ZHNwL7QTz9fDcMQ+Po0Swu7vpFoelzedtq1opn+oyr6XNF44gZLqbcToZrJCe9Ky5O1kI6TlHSpO36MABsWg9ijHcKKGYKKhGtv4Fd7xviGAqF4nTBsnaGeKQDf9mQFrux5IYQ+w+OD99bHtBS0EXd6zH7j+tIqhaHrmssX30jDz3Skbi4k7o2drvO9SNb8cPPV6PrmldPjhCgGxojb2oTzrcRcdTjagkz/PpWfDputd92MTE2Jk5YR0JCFF9+tpod21N8tjdNyaqVyaxcsT+iNSpOFm4Mb1CZRkNyzPfRRTPs2gBsWi8M26WYcjGWPIAQlTFEB+VxUSgUAAiRGOJlKLCyKRLv8YbhZuWKZL/e+GbNK/H9tMH5tmma4KFHL+S+Bzuybu1BcnNNmjStSEJCFAATJg1g6DVTcOZaHpVeTRPY7BpffTOAevUSI/J+IoW68pcwrdskccttbfngvRU+22VmOvlj3i7mzN4ZcN9CwPJl+yJqvDitXwifCBS4g+YkFjuwrB04+Z5s82VijNewab0xRMcwjqVQKMoqltyDy1oOSAytHTatF6a5MGLjudV6I4/d7n9BxFflaMPQaNU6qcD2Hj0bsG7jrXw2fg3z/9gFwIWdazPi+laeGnllCWW8lAJeerU79eqX583XF7N/X+FBV4HGxpxKuDQCCkOSXaTjo7XxaFo8ptxMjvkWkkO4H59ONYhyyHT9j1ijOobWqkjjKRSKso0lU8hy3Y9LzsbjajEFOl2AaMB3kdpQENRFEzXD3q83+lzRmE/GrcJ0eb/ea5rgsj6NQuq7alIcDzzUkQceKvsPgSrmpRQghODW29ux4Z/bWLJiJLfe3g4tTGem60V1w9NRIeiiMcF/jdwLr3ZtBDa9M4bWGk1URHKAwteeLTJdo5EyrQizVSgUZRkpc8hwDcEl55J/jUhi8gcU8WGqMOxa/4j0641bbm/nMz4lKkrnysHNi20+pZWIGi9Hjx5lyJAhxMfHk5iYyMiRI0lP953O1bVrV4QQ+f5uueWWSE6z1KDrGs2aV+bf3alFrmOhaW7tl/r1y4dncoVg14YRrPS/RkOi9ZeJ0h/zRO87rd/w93WU7CPNORSnOYdcczJOa06+qtMKheL0xmlNx5Ib8b5ULQl37J0bA7s+NAL9eqdhwwpM/HYgUVFGAQNGSsjMdHFe23GMfXNJsQnYlUYiarwMGTKE9evX8/vvvzNjxgzmz5/PTTfd5Pe4G2+8kf3793v+Xn755UhOs9Sh60U/LQ6HQacLa+N0hjMepSA27fKg5P9j9M+Js83Erg/yGC4uaw0u608CMYIka8k0R5FlPkimaxRpzg7kmt+GOn2FQlGGyLW+ozAxueBxX2dt2pU+2ggc2ig0EdmHwP/S/ZL6bNx6O7fc1g7h5XaQlpbLIw/N5dWXFxXrvEoTETNeNm7cyMyZMxk3bhzt27enU6dOjB07lokTJ7Jvn3eJ+zxiYmJISkry/JXWAouRoutFdYvsecnKcvHQ/bMZ1O9bcnLcqcvZ2S4mfLWWkSN+YMTQaYx9cwlHjxZtfVgInRjjLQxxaYDto/NpJTit+WS4rjwR6xI8kmNkmQ8oA0ahOAOw5EHC5V3RRTtijE+IMV4iWn8JiDmxxyCvLIpduxGHfm9YxvPFoYMZLFu6j382H0FKiZSS9esOMn3qJp9v99mn5rN0qe/76elKxKpKf/rpp9xzzz0cO3bMs83lchEVFcW3335L//7e1xC7du3K+vXrkVKSlJTE5ZdfzmOPPUZMTIzX9jk5OeTknKxdcfz4cWrVqlWqq0r7Iy0th5ZN3yc1NSekIN1TEQIeeLgj/fo3pV+fSSQnp6PrAilBInHYDT6f0I9evYsmUOSyVpPhGuCnVRTxtqUI4Y5slzKHNOcFSFIo6gVJUJ5ytkUIEY4ibAqFojSS7rwGUy6jKFXqATTaUc4+Od82KTNwWjOx2IOgPDatF1qEy47s3JnCIw/O4acft3jSlxs1Lo8Qgn82FxSc80ZUlMGCxdfTuEnFSE61WCgVVaWTk5OpUqVKvm2GYVChQgWSk5MLPe7aa6/lq6++Yu7cuTz00EN8+eWXDB1a+HrjCy+8QEJCguevVq3iSWeLJOXKOZjyw1WUK+fI5zI0DIEQ0G9AE5+pcqciJbzx6mLOb/cJycnueCPTlFiWRFqQk+Ni6NVT2LA+NM9HHro4B02cRf4ijqeiYdcGewwXAKc1C8kxwvEkJTmGS/5Z5H4UCkXpxa5dRVENFwBNJBTYJkQsdn0gUfqdOPRhETdcdu1KoduFn/PzjJOGC8CWf44FbLiA+xr+wL2zIjHFUk3QxsuDDz5YIKD2v3+bNm0KeUI33XQTPXr0oGXLlgwZMoQvvviCqVOnsm3bNq/tH3roIVJTUz1///7ruzpzWaFN22qsWnczzz7XjY6datG2XTVuGNWaJStG8cWE/mzZOZo33g5sqSYnp/C4Fyndf++9s6xI8xVCEGu8g6AS+b9W7iUiXbQiSr8/3zGW3EI4s/WlPBy2vhQKRenDpvVGo2WR+xGUvFf+iUfnkXIs8PIwhSElzJm9o9CivacrQd857rnnHkaMGOGzTf369UlKSuLgwYP5trtcLo4ePUpSUkEBncJo3749AFu3bqVBgwYF9jscDhyOwLwQZY2KFaO5Y0x77hjTvsC+6GhbkeNi8nC5LCZ9s56RN7ahdZvAz81/0URt4mw/k2t9jdP8HkkKQtTEoQ3BpvVDiPznSYgYwvEUdbK/yInxKRSKkkcIOzH6F6SbrYvQi4auhaaTEi6OHctm+tTNRTZc8pASdu9KpWatkjfKiougjZfKlStTubJ/d1qHDh1ISUlhxYoVtG3bFoA5c+ZgWZbHIAmE1atXA1Ctmrox/ZfsbJf/RgGSk2PSpeNn3HJbW156tXvIBcg0UZ4o/Xai9Nv9tjW07mC+GNI4/0VQGUNcEJa+FApF6aXotRE1bNqgcEwlZPbtPR42wyWPhMTT8yG+MCIW89KsWTN69uzJjTfeyNKlS1m4cCGjR4/m6quvpnr16gDs3buXpk2bsnTpUgC2bdvGM888w4oVK9i5cyc//PADw4YNo3Pnzpx99tmRmmqZZe+e8Au2ffDeCj5833epgnChi/on0qwDuRo58PV1NbQuqs6RQnGaY8nDZLpGhHi0+/oRrT+NJiqFbU6BkpPjYsP6Q2zedJi4cuE1NBo2qkDzFpGN0SltRPRqP2HCBEaPHs3FF1+MpmkMHDiQt99+27Pf6XSyefNmMjPdhbHsdjuzZs3izTffJCMjg1q1ajFw4EAeffTRSE6zTCKl5Ndftkak7zdfX8KNN7cJi96MP6L150lz/Q44fbZziFvJlTOReI+nclrfkekC01qFxT4E5bFrA9G19risn3DJDQhisGk9sGv9EaJcBN6NQqGIFFJaZDivw2JLQO0N0QtT/oUkFQBdtMah345N6xrBWRYkJ8fFSy/8xccfriA1xZ0ZW7VqLLVqxbN3b1q+YN1QefLpLiF7y8sqEUuVLimCSbUqy2RlOala4bWI9b9s1SiaNI3804kl95LmvDCMPboLO+b/t45bkVOc2FqJWNsEdOE7PVxKE1OuRHIMjRpoovkZd4FQKIobKXPINX/BaU3C4iCaqIohuuG0pmCxOeB+NJqhieoIUQWbNgibVpQ4mdBwuSwG9ZvMvLm7wmKkeOPSng34bqovob2yQzD3b+VnL6MYhrv2RaRMT6czfyBtTo6LP+fv5nhqDg0bVeDsc6qGaaRw67JIL/82872WHCXDOYJytrkIYfPaS675A9nmCyfqLbnRaEy08TSGdl6Y56xQKExrEznWOJzWDOBk2Q9T7sCUi4Puz2Kju5SA1HFa3+DQ7sChjynWB5APP1jBnNk7fbaJijbIzgo9fvGNtwLLOj3dUMZLGcVm0+nStQ5/zt/tM/ArLs5Oenpw9X9iY23Ub+CWw5ZS8t47y3np+QWkpJwUA6xcOYYXX+nOlVc1Z/WqZCZPXM+RI1nUrBXP0GFnU69eYkBjCSqhiWZYchORqUviDRPJPlzyd2xeShvkmt+RZd5fYLvFVjJc1xFrfI2htS2OiSoUZwTZ5rvkmJHyJLsfXnKssWiiBnZ9cITGyc8vP23h4ftn+2xjGIKmTSuyetUBn+0Ko32HGtSqXVCz5kxALRuVYebM3kG/PpO87tN1Qc1a8Tz2ZGdGjfgx4D6FBrfdfi4vvHwx69Ye5OEHZjNv7q5C21dNiuVAcgaGoSGRIMGyJHff24HHn+oc0FOO0/qZTNfogOcYHgzs2pVEG8/l2yplDsed5wGFBUNr6KIlcbapEZ+hQnEmkGN+TLb5QrGMpVGbONvciHpfFi38l9dfW8yvv3jXJvsvdeomsGtnatDjnE7KunmoZaMzhIsursebY3tw952/IYRbOVfTBJYlqV69HF9M6M8l3b4Iqk9pQbl4O/2vmMTs33f4bX8gOQNwr+2eymuvLKJylRhuG32u3z5sWm+i9AfJNl/CnREQ2WKSbiSSgq5al5xN4YYLgIUp12DK7eiifsRmp1CcCeSYH5EdJrmEQLDYjcUudOqGdPzOnSl89slq/v77IDHRBr36NGLAwKYndLckTz3+B6+/ujiodO6aNctx7Gg2x4/n+G2bd32vVz+RTz/ve1oZLsGiPC+nAbt2pfD5p2tYu/Yg0VHuH1T/AU15/NG5fPBuaGnPui6KrENQuXIMm7bdjs1WWMmA/JhyF05zEi5rDSaRr5Yarb+AXb8q37Yc81OyzefxJ54Xo3+CTe8WwdkpFKc3TutPMl3Di33cOGMmutY46OPGfbSSe8b8hqaJfA+K1arF8fXkgezalcKIodOD7jch0UH782vw28ztftt27VaHe+7vQOcudU7L5IFg7t/KeDmNaVR3LAcOZJToHH6fex3tz68R1DFSWqQ5uyDZG6FZCcAGJADHAA1BBezalQhRmWzzcb896JxHrO2b0/IColCEiiUPkWt+hdOajiQNTdTHrg3BpvUpoMOU7hyOKf+ieDytecQQb1uOEFFBHeVriT6PqCid7OzQ3oumCSpUjCblWHYBL/apCAGr1t1M/frlQxqntFMqCjMqSp5gA3UjQXa2b/0WbwihEaX/z1eL0CfkSZ/OBQ4BLiAXSTI51liyzedwC+L5xmQpplxThHkoFKcXprWJdGcPcqx3sdiN5BimXEmWeTfHnU05nnsZueYkpHRfE9wZRMVpuGjYtauDNlzAXdxW131fd0I1XMAdJ3j0SCb+fAmaJvj6q7Uhj3M6oYyX05g6dRNLdHxNEzRuHNqarF2/kij9AdxfUQ13eJZ7+UmnNxBqqnaMn/05BFZvycBpBe8iVihOR6Q0yXDdjCSN/L+fvJuxhWQjWeZDZLiuR8ocIptd+N9bm0AXLYjS7wq6J6fTZP4fu8Iu5/9fLAv/YwjOuAKMhaGMl9OYUTcVvyhTHrou6N2nIdWqh65k69BvppxtIQ79HuzalTi0G4kzfibOPhZB8G5TQ/QBAllGC8RbJJGkFNwqLVzWYnLNb3Fav5+4SCsUpzcu+SeSfwnEk2LKxeSY76GLtgR+C3JgEyNwaA/iXxvKhk30I+9BRVCDKP0BYo2JCBEb4HgncbmsiOlpBYtAUKmSvwewMwOVbXQaM+S6lnzx2RrWrD4QkR+fprmfFv4b3KvrgqpJcbzy2iVFH0NUJUq/1cueo0H0Eo1Dvw1p5eC+WAbiWclT5fUxN2rle+20/iTL9QiSPadsLUeUPga7NkLFxyhOW0xrBe7bSSBiaxY51jvodMH3b1Fg5xFsxlno4mzPco8w5YnMxEKO0YYTbTwMvIqUFkIU7Rk9KsqgYaMKbNt6tFiMGF/JEi6XxVXXtIj8JMoAyvNyGhMdbWPGzGsZOqwlhhH8qfZ2r83b5ojSGTbiHKbNuIorr2qBzebuPzbOxs23tmX+whHUqBnJgOlACptFEWO8Q7xtKVH67QhNJ3BXdRx5y1TesbDrJyW5XdZSMl03eAkyTiPbfIZca1yA4yoUZQPT2kSuOQOnNQcZdOyKxGQ+vn9jklzeQqNhvjgVu3YTdu0m3PFrOqcuKdvElUTpJwUmi2K4HD6Uyd497urPt97eLuR+giE+3k5UlOE1vkbTBIMGN6Pl2eFSNy/bqGyjM4QjR7L4e80BDh5I58YbZhTaTgho0rQid97VnldeWsT2bccAiIkxuG74OTz0aCd0XRAXZ89XuNHpNElPdxIfby+Wgo4ZzjtxyZ/w9eRmiIuItZ00GlzWCjJcgdYA0YBKwBG8eWAc2h1EGSfXz9NyL8Nio4/+HMTblqqCkIoyj2ltJst8AFP+fcpWO6dK+ocTQUPi7b8V2G7Jf8k1v8ciGY1K2PT+6KJBkcf7cfpmXnnpL4/qbYUK0Yy8sRUbNx5mxg+BFYX0hhDQrHklNm06glWIZ+WJp7tw0cX1GHX9D2z556inBIyuC64f2YoXX+mO3R6Y9ERZRKVKK+PFJ6Ou/4HvJm8stFDYFxP6cUW/JqxelczmzUdIqhrLeefXIDY23HWIQsdlLSPDdZXPNrHGFxhaJ89rKSXpzr5YrAtwFAOdjpgs5KQ7vAIaNYFchIjDpl2GTisyzP5+e4vWX8GuDwxwbIWi9GHKHaQ7+wJZFGemUJwxD12rHfFx3h27jIfun+3RcMlD0wTnnleda4a04K7//RbU8lHeMtCAQU15c2xPrrtmKn/M2+XZbhgaLpfF9SNb8cbbPdA0gZSSRQv3sGHDIaKjDS7t0YDKVYKP1ylrKIVdhU/GvteL3FyTaVM2YxgCIQQu08LQNV58pTtZ2S5aNnuff3e7o9qFgIu71+Pl1y+hYcMKJTx7N4Z2Lg7tFnKsD8gfx+L+t127AV10zHeMEIJY24ekOTsT2IXXRAhJOWMJprWdXOtzXHIGFqnu46XANFfgP4MJQCA5FPgbVChKITmutyluwwXAKaeh40s+oejs3pXKww+4axH998HOsiTLlu6jz+WNqVw5hoMHMwPq027XueTS+owY2YpLe9RHCMEPP1/NH/N2Memb9Rw5nEmt2gkMG3E257RK8hwnhOCCTrW4oFMtH72f2SjPyxnM+nUHmfL9JlJTsqlXvzxXX9OCyZM28MC9swq01XVBfLyDuQuGlxqBJCklTutncq2PPS5sTbTAoY3EpvUtNED2eO75SA4GOIqgnG05LmsmWeYjRZqvLs4nxngHTZQOA1ChCAYpszjuPIfAgnLDi127k2jjzoiO8ezT83nt5UU+05Vr1Y7HdFns25cecL8Hjt5DdLT36vWK/CjPiyIgWpxVhRZnVfG8PnYsm8cenuu1rWlKjh/P4c7bZ1KhYjRLFu/FMDR69mrAzbe2pVEIei6WJdnyzxEyM13Ub5BIQkJw4lFCCOz6Zdj1yzwpyUL4D+QVVAzCeJFY8ig55kecFLgLDVMuJcM5gFjbVDRROgxAhSJQ3NIAxW+4ANi0HhEf459NRwpdSs/j393H6dS5NsnJGX7b5lEcMYBnIsp4UXj4bvIGnM7C3cGmKfOt1QJ8Mm4V4z9ZzZdf96d3n0YcPpTJrzO3kp7upEnTinTuUgdNK+gBmfDVWl56fiE7d6QAbvfq4Kub88xz3agYgo5BIEZLHjatOzmWr+DaU9ERSCwKr6wdOBYWe8kxxxJt+C9BoFAUJ1JKTLkSp/UbkIUmGmPX+nqCzAUJBJ4OHT4ENTC0phEfJzbOjqYLTJdvo+SSS+uxYP5uv/3puuC89jVO6wDbkkQtGykA2Lc3jQF9J7NhffBxGUKAzaZz9bXN+fqr9bhclidKvnadBMZ9ejnnX1DT0/71Vxbx5ON/FOhH1wV16iYyZ/4wKlSILtL78YUlk0lzXoj/dXuBIS4nSr+XdFfnMM4ghnjbSoQoPQHQitMTl/U3Tus7LJmMEBWxa/3RxbkFllQtmUKm62ZMuQx32rHA/ftwEGO8ik3rDUCmcwxO+ROBx7zkKWS7TnmdF58WiCfTRpzxG7pWJ8DxQueXn7dy1cDv/LZLSHDQqnUSf87f7df7Mum7gfS6rFG4pnjao2obKYJiz7/H6dLxMzZuDC2gVEp3qvQXn631FBXLM4n3/Hucy3t/w9q/D3heP/VEQcMF3J6dXTtTeOPVxSHNI1A0kUS0/koALeOIMu4i23wvzDPIRHIszH0qFCeR0iTTeT8Zrn7kWt/gkrNwWt+R4bqaTNcopMw+pa0k03UTplx5YouJ29iQQA6Zrv/hspYC4DD+B0ThW5/lVCwgFod2J7H6t9jEIDTRFF2cg127G0PkZd8V9M4K6hKrLygWwwXg0h71aXl2Fa+e4lNJT8+lTdsk7r6vA3FxBR9AtBMfzVPPdFWGSwRRnhcF1107lRk//BOx2h26Luh1WUO+njSQF59fwEvPL/Q5VkKCg137xvi9iBSVXHMuWeZo3NkT+dFoQ4ztZQDSnd3DPLIg3ra6gOaLaW06EXhsx9A6oonKgPvmYrEVKTPRRG0VL3OGIGUqudY0LLkDQSw2rTe6Fpi6arbrDXKsd/Du2dAwGECM7QWE0HFZS8lwXe2jNx1DdCTW9hkAprWRLPNBTBlogUANiCLONr2ADos76H4yOeY4LLadaN0Ahz4Kmza42FWpDx7IoHXLD0lL861ZU7t2POs230Z2tosVy/fx68ztLF+6l5wck3NaJzFyVKt88YSKwFABu4qAOXQwI6KGC7g9Kj/P2EpaWg47tqf4LQqdmprD8eM5JCYGX/01GOx6N2zaSpzWr7jkcqQ8iiYaYdf6omt1AfdNIJBSAYGjYYhO+QwXS+4m03X3KU++gKlhEwPQaEeufB/pibkxsIneRBkPoYn8SptS5mDKVUgy0UVDNBF5XQxFeHHHnSwmx/wKl/wN9/fOACQ51vsY4mJijLcQovC4MCmzyLE+pfAlGQsX33Hc+R2aaHGiTpiv77iJS85HyiyEiEbXmhGnTce0NuC05uK0pnkMj8LGgxyyXWOJtb2Zb4876P4qbNpgJKnubSSUWCmNKlVjqd8gkTWrfQf05xk3UVEGHTvVpmMn9VsrbpTxcoazY0dKxKulgjuzKDXFbZAIP2vdhqERE1M8qYVCOLDrV2DnCq/7JYfxa20FhVuDxvNKHiLdeSWyQK0mC6f8DvjvGrwLp/wJl3MZcbZpaKIyUkpyrU/IMd/LVyxSFx2JNp5FF8Xjds9Dyhyc1nRyrUlYcj9CVMauDcKuDfR50z3TMa1/yHTdhsX2/+w5GSDrknPJdN1FrO3DwvuRKwisAClYcn3A8zvuvBC76I/DGIYmaqFrzdG15kRxO5mux3FaX1O44rWJS/6MlC/mk/rPQwiBIDHguYTCln+O8PGHK1kwfzdCE1zcvR433NiaunXzj9u0WWXWrzvsWQL/L5omaNhYyR2UNMp4OcPxtmYbLHnBub6wO3QqVopm4JXNeP/d5YW203XBFf0al5oIfSGqElghx8Cx2Aq4A4BzzfEnDJdgPDsmkoMnspaeJsd8lRzr/YKt5GIynAOJs01HEzXCMnd/SJlGhuu6E8tf7uBMKQ+Qba4j1/ySWNvXaKJSscyltCLlcZzWL1gcRiMJm9YDSToZrquQ+NMPsXDJ3zGtf9C1xt77D6gqeigcJVd+Qq7zE6L0p3Do13n2CEz8Fz11ITmOILIeVW98PWEtt930M0LgeVjbsP4Q745dxhcT+nHZ5Sc/yxtGtmLSN4UbdZYl6XNFYx5/ZC47tqeQWD6Krt3qUK9+eZKS4qheQ5UAKQ5UzMsZjpSSc1p8wM4dqQEfoxsn0wl1XWCz6eTmurAKuW7phuDqa85ixA2tSDmWxcsv/MXy5fsKGDxCgM2uM3f+sFJTfMySe04o8oYPXXQkzvYlAMdzzzvh3QmFKOKMGaS7LqFwT5aOXRtMtPFciGMER6bzPpxyGt6NMR1DdCbW9kmxzKW04faQfUS2+QbuOkB5SzVR6KINplxCYEasjkO/gyjdu+KsJfeT5uxEUTSJAiHG+BybdiEA2eZYcsy38T1/O/G2NUHJGoSDtX8foNP5470+YAnh9vSuXHsTdeokAu7zdPedv/HJx6u89lepUjSHD2cV+tDWuUttnn6uG23aVgvjuzgzUNlGioARQtC3X5OA2mqa4KKL6zJ8xDk0b16Js8+pyt33dWDV2pt45HHvN3hdF0RH25j1+3Yu6fYlVw74jmXLChou4L4QjL7j3FJjuAAIqgPhrilyMhiw4HJRMGSTa03E98/YJNea4hHxiySWPIJTTsd37MRcTBkOzZyyR641nmzzJU6e/7zPKRtT/kUw6cdSFi5PL6gARPrBTSPH/MDzyq4NwL+H0sCUmyI6K2988N6KQoXipHR7Uj79eLVnmxCCV17vzq23t6NixZOSDQkJDmw2jcOHszzHemPhgn/pcfFXLFm0J2zvQVEQtWykYOOGw2gahXpO8rAsSd/+Tbl+ZKsC++69vwMVK0bz4nMLSE52r7cLAY2bVGTjhsOk+4nez+Pdd5Zx173nB622GyksdhNo/EBgaOii9Smvo4DA6qQURCDlMfzH5OSccNdXDnGcwDDlGgIRMDOt5eh68cbhlDRSZpNtvhWm3pyFVk92B38/CATuSQ0NC1MuQspchLCjiRo4tJtP1BorjCwyXEOIs/2ILupFdHYrV+znx+n/kJGRyw/TNxcavwLuZaTJk9bTuEkFLu5enz/n7+axh+fkKwFQp04Chw9n4nT6X0I2TYmUFv8bPZPFy0eWWPDx6Y4yXhSsXpXs13ABqFgxmsFXN8+3LS0thzmzdpCenstZLauw/p/bWLUymYwMJ9WrxdGl0+dBzSU3x2TyxA3ceHObQtts2XKUL8avYcuWI8TFOejXvwk9ezfEMCLhSAxvvAuAQ7/W82+BHRmS8eJeghEEEpNjICiHJY/hsmYhOY4m6mKILggRzktAoBfpM+9i7pILgLQw9CSAGGzaZQX25JoTyTIfJRLf2cJxAe64OYd+H5KUE95Ab7h1Y3LNcSEvY1qW5NeZ2/j6y7Xs3ZtGjRrluPa6llzaoz66rpGams2wIdOYO3unp+hsIAbH3j1p3HoiJsabR2X37tSgKklblmTjhsOsXJFM23Zq+SgSKONFgd3h/2ug64KpP15FbKz7QmVZkocemMXHH6zEdYqcdvXqcXzxdX+6XVSXCV/+TVZW8MGDTzw6jw/fX84VfZsw8sbW1Kh50gX+8osLefapPz1xN7oumDxxPWe1rMK0H6+iStXwLvFo1EJQPmyicjbRl1xzEogYDHFJkaISBBXIlV/i+2alYYhe5Jhvk2N9AjjJC6wUVCbaeBGb1q0IsziJLlrhXz5eYGjnhWW84sAdXPvziaypiti0y9CE7zpeLmslueaXuORKBHYM7WK/xwQxIxzaKE/WlmltxJR/Y8o95FrvhmmMwNCoA5xcVhFCIP0G7prkWtOIks8G7ZHIzHRy9aDvmDf3ZImSVSsF06dtpmu3Okz8biBDr5nqke53X5eC+4UVZqCEGhm6Y/sxZbxECBWwq+DB+2bx4fsrCk2ZFgIeeKgjDz92oWfbDcOn891k7/WBNE0w/6/h/PLzNl56fqFPl60vNM0dwPvkU10YMuxsfv1lGzfe8KPXtrouaNO2GrPmXRd2N222+daJYERvn48A4tFpj8lsAotbME70Fap2jEBQBckhAnnK1rkIk7kUnL8ABLHG1xjaeUjpRLIfsCFICulzzHQ9jNOaXMi8NDTOwaZ1BKFjiAvRRetS61bPMT8n23yR/MG1Og7tVhz6GK/zzjbfIcd8nfy6KTruG3o4soDcMgN27QZMuRJTrg5Dn6Hh0J4gyhieb1uG8xZc8nf8GQ3xtn+C9vr97/Zf+OKzv71K8muaoFfvBvw0Y2tQfUaa76cP5pJL65f0NMoMwdy/lfGiYPv2Y7RvMw6n0ypwYdB1QVycndXrbvYUTNy65Qhtzv7YZ5/Nz6rEjTe15e47fw35qeVU7HaNmFg7qSnZPvv7fc5Q2neoWXiDEJAyl0zXzbjkH+R/qtQQlCPW+NqT6hp5BIJ6J0TrwiGcp6HRCpvWgVzrK49QmFvl9Dbsev+gepMykwzX9Sdq5OR9Vnn/t+G+gZ803nRxDjHGh2iidKmR5prfkmU+UOh+h34PUfrt+bY5rT/IdF3vo9c8Y6cwI1gQ3JKPv9TkyBJnLEXX8qe9Z7meJ9caj6/vpqAK8fbgSoAcPpRJ4/rv+HwQEsLt/Qm02nOkKV8+in92jMYRgGdb4UYp7CqCon798nw79UquHfw9GRlOzxOlZUkSEqOYMn1wvkrPzzz1p98+N6w7TLdudTAMLaA1Z3/k5lrk5mb7bGMYGr/O3BZ240UIOzHGxzitH8m1vsKU2xHEYdf6YdeHoomqSCnRxQWYcjGRvaFIJLsJn+KvhcVKcqzVnDpvi+1kmfdgsZso/U73NnkAKVPRRBJCeL+wCBFDrPEVTutXcq3JSLkXSMBiEyc9DyeXlUy5jgznEOJsM4o9hbYwpHSRZfqufZVjvodDG44Qcads+wTfSrUSt8HhzUgJfomjJA0XACEKzteuDybXGufjKA27PsRv3y6XxW8zt7F82T50Q8Nu0/x6cKV0pzn7o2rVGA4cCDVIPnAefuxCZbhEEPXJKgDo2q0uG7fezjcT1rF40V40TdClax0GDW7miXPJ45/NRwLq8+ixbO594AJeeHZBoW3y1q7DgRCQkxOum/p/+zaw6/0L9UQIIYg1PiDTdRcuOZuTlXn9Z98EhvumaNduJNfy7fUKDW83U8gx30JQE6c18YRyq3suhuhNtHG/V/E7IWzY9T7Y9T4AZLleINdai/ebuonFNpzWL9j1fuF6M0XCZS0Dv9o7WTitORjiPCQ5aKJSgDotFRDEIwuo6JYtBNUQFIzj0UXDE1lH3hSAdTTq49BG+Ox71cpkrhn8Pfv2pmGzaUhJyEvP/yUhwcHb7/bimsFTgvbQ5AXzapp3746muffb7DqPPnYhN91SeNKBougo40XhISEhiltua8ctt7Xz2a5cgKq8lSvH8ODDHbHZNF596S8yM0/eyKtVj2PAwKYIIXjn7WVFmnceTqdFq9ZJYekrFISII9b2Mab1D045C2QOQlQl23w0xB7t5D2tG6ITDn0UgvgIGS+FoZFt3k/+DCG31Hu6cyFxtqloopbPHpzWNHzf1DWc1ozSY7zI+QG1yzLHnPIq0CWcw0gCkw0oPnyX6/DW3qGPQAjv2X0O/X6EqE6O+T6S5BNb7di1gUTpDxQoSHoqu3el0qfn12Rmur104fDa5qHrgq4X1Q3ZcBFC8MDDHZk/byd/LXRruJzTqio3jGqFlHDgQAZJSXH0G9CU8uVLh9TD6YwyXhRBc92Is1m8eK/PNvHxdmrXcRdYu/f+C7j51rb8NnM7qanZ1K2XSJeudTzCUYv+2sOqlclFXqs2DMFZLStx8EBG2LOOgkHXGqPjlhuX0km2+QLBa8Xo2LURRBsP5tsqpYkg6ZSbQqTJu3n899yYSFJJd47CpnVEE1WxaX3RREHjMRDJe8lxLCsFF8tApqGJKujiPITwbii7rOXkmONPpCBb6LTF0C9E4EAQhaF18VTlDhZTeldW9fceAud4CP1HCh1BDTQaYzIH3+/DbeQYojt2rfDYHiEEDv067Nq1WHILklx0Uc+n0ZLHB+8tJzPTGfZ6a5omaNioPGtWJwe0tGS36+TmnjS4q9coxxtv96Bnr4Y8/GgnXC4LKSU2W+koY3ImogJ2FUHjclnUr/UWKSmFq7Y+83w37ryrfUD9Tf1+E8OHTgvT7Ny0PLsK9z1wAf0GNA1rv6GQ5XqWXOtzglFQhWjK2WZ6XZbJMSeQbT4WzikWEYO8m55Duw2HfpcnbsqU20l39sJ3po0OJEABteF4ovR7cehD8211v//HcX9OhX2mOjbtKqL1x4KOpUnLvRyLwAsWlk5O9QTleVbyAqbzPCYWumhDjDEWKQ+T7hqI+/P0HlCscRYOfTg2rS9CROam3bDuWA4eCKco5EmqVY9j/z5/hjRcfU0Lrrm2BRMmrCczM5cOF9TkttHnFqrSqwgfKttIGS8RZ8s/R+h24eccP17QBT5sxNmMfa9XwCmwP0zbzNBrpoZ1fnnr0s8+343/BWhERQpLppDh7I/FHgq/2eY5QV0IKhFjfIyhneO1pZSSHPMNcqx3OXmT8v8zFtRC8m/wbyBIovSHceijsKw00l1di6yRY9dGEaU/iBAaptxCurMngS1zaBiiJ7G2dwIax1176IsTnrLStrSTh/sG6tYeSqHg90lgiD7EGG8iOYDTmgNkoomGGOJCLLkZl1yC24NyHrp2ludIpzWHTNeduL2EJ7+PumhNjPFRyFo1liVZv+4g6Wm57uKF1eIKtNm08TCfj1/D++8uj1i2UCAq4gA1a5Vjz79p6IZAIHC5LJo0rcjXkwfSqJGqJh1JlPGijJdiIS0thwlfruXLz//2KOzefW+HoEWZOp3/KevWHorIRUsIWLPhlgJl74sbSx4lx3ydXOt7wO2x0miKQ78DIaJxWSeWP0QbbNqlhS6XnIopd+E0v8Ull5wSTOsdnW5EGy+R7ioOgbh4yhlzSHddhWRbmPpMIkofjSk347S+Jphsqzjjh3w36cLIcr1IrvVREeYYaSpi1/pj169FEEuW6/ETmip5d+QYHNrwE56v0CICpMzEac3AlBsBBzatO7poG7IWz6Rv1vPs0/PZtdOdgi8E9OzdkJde7U7duolIKXn6ifm89soiDEPkE7wsKbwZObouqFQphsUrRuWrd6QIL8p4UcZLmWHf3jSaNoycMqiuC+6653wef6pLxMYIBikzsNiHIAZB9bAItEnpJN3ZA4t/8X5TF8Qa36CJGqQ5L/SyP/wImiDZHIF+KyIJLNvNjY5dG0a0cXKZTUoTl5xDrjkRS+5GiIoY2oXkmK+Ffb7hJMZ4B5vWO982SyZjyg2ADUO09SjvlgY+fH8F9939e4Htui5ILB/FHwtGMGf2Dv53+8wSmF3waJrg8Sc7c/d9HUp6KqctSudFUWbIDKF8QDBYlmTzpmBudpFFiFh0GoW5Txuxti/IcF6HxS7cMSR5zyQa0fpLJxR0c4FyhKfGjm8iYbi4+w32XMp8lbvdgoO34pJz8WiyyO2Y5tJwTjPMaAgqYohLCu4RSV6DpEuaI0eyeOTBOV73maYkJSWbZ56az+JFewqtJxRJQhnTsiQTv1mvjJdSgjJeFCVKzZrxxMbayMiIjBGjaYLYOFtE+i5NaKImcbbfcMlZOK3ZQA6aaIZdu/KUrBsbdu2aEyJiJStwFjq+VGq9t9eo7nmVbb6OS8478SrPS1XanM+nBtvqQDQxxkcIUXa+x99N3oDTWfjSnumSfP/txrDptwSDYWhUrhzD/v0ng3crV45B0wUHkn0HC6em+hbKVBQfynhRlChRUQbDrz+HD95bHlAwXbCYpqRff/8ZRy6XhaYJNK101tkJBCFs2EQvbFovzzZLHiHb9Sq51iQkRxAkAuUhaA9GaSFPpTbv3/4wMbR+OK3ZmNa2E9L1oRorweqhBI/G2QihY8ptCGKwaVfg0K/zmnVWmtm5IwVN8y1AWRKGi64Lrh16Fm+905M/5+9m3740qlSJpUvXOgy7dhozZ27FLCTuRteFCtgtRSjjRVHiPPRoJ+bN3cmmjYfDasDouqBZ88r06NXA637Lknz5+d+8/84yNmw4jKYJLr6kHnfe1Z7OXeqEbyIlhCX3ke4cdKKAo/sp2J2houG/+nNpRUcXnTDlUiAb/8aEgwzXQCCdohsfBuEprlgYArt+BQ79hgiOEXk2bTzMV1/8HZBWS0yMkU+8MhQCXQLKi7V54KGO6LpG12518+2/flQrfpqxpdDjTVNy/cjWRZqrInyoxHVFiZOQEMVvc67j7vsuICa2aK5xm03DMNxf61Ztkpj241Ve9RksSzLq+h+447Zf2LjxsGfbnFk7uLzXN3z26eoizaM0kOV6KJ/hchKLk4USfVEwpbXkMXHoN1DONh+7Npr8yr/eyAGPSF5RvSaRjc+CKOzaoAiPEVmOHs2id4+vSUsrXAMK3IZEt4vqcv3I1uh6aN7OPC9poEJxF3Ssxew/hlGrdoLX/ZdcWp9Bg5vhLYZeCOjZqwH9BjQJaa6K8KM8L4pSQXy8g8ef7Myjj19I8v50Jk9az+OPzAv4eE2Dvv2aklQtDodDp2evhnToWBMhBFJKli7Zx5TvNpKSkk29+omUi7Pz3eSNQP6ntrynxTF3/MpFF9ejdh33hS4z08mcWTtIPpDOkUNZJFWLpX6D8nTsVLtULjWZchcu6auAptuA0WhRiCBbReKML3Baf5JjvRihWeYRhU27Aqf1A25vSmHo6KIVhuiIEBo2rSO51tgIzy0UtBN/wXgUNGKNjwoteFlW+PKzvzlyONOvJ0QIwcOPXUiLsyqz6K9/WbUyOeAAWk0TVKwYzcArm3FJjwa8/cZi/pi32+9xvfs0on798j7n9PGnl3PWWVV4d+wyDh1yF28sXyGKm29ty30PXKCE6koRynhRlCo0TVC9RjnG3H0+q1cdYPrUTQFKhQvad6jBbaPPzbc1PT2XIVd9z9w5uzzu5f/+32tvAj4bv4bHnriQd8cu44VnF5CWVlC4rHadBMa+14tuF9UN/s1GEEsGphDr0EehixbkWJ9jye0IKmLTumDT+iCEA11rhm7WI9McjdvzIPBeFflUAmmTh51Y4wsMrR1SPo0lt2PKTWSZLwEHOKnea6FxFlH6feR5W6QsjZcvDUNcQpRxH9mul08U6fSnSWMnxhiPoZX9LJYvv1jj1wjRdcG3U6+k/fnuOJ6ffxtC65Yf+lW/zdNfOfe86kz8dqCn0v2/u1P9Gi+aJli/7qDf+eu6xt33deCOMeexdctRpISGjSpgt6syAKWN0vjrVygAeOf9XqQcy2LO7J1+21qW5JIeBWNbhl4zhblzdgEnDZX//t8bpilZvSqZN19bwhOPzSu03b+7UxnQdxI//XItF3TyXaCweAmseKYQdnStITHaM4W2semXUE5bgtP6Hpe1EiF0NJqTa41Dkkr+m7P7yTRafx2n9QMu6T1dNo9YfQKG1vbkXERTdJpi0y7HJf/Aaf2Gy/oDyQEs1pDhutpdmVh/+ERWVTjI85zZCF1ZVyCoTpztBzThfrqPNp4m3bn+RB0q7waMIS4iyngUXdQNcdyiIaVk0cI97NhxjISEKC7qXo+YmNCWbp9/5k/+2fzfEg8FqVI1lou71/O8NgzNr+EiBDRqXJF33uvFeefXyKePNPDKZoy541efx2uaICo68Pdls+k0ax5abSxF8aBE6hSlGiklfy38l8cfmceypfu8ttF1waU9GzDpO3e8wKGDGXzx+d/M+m07CxeELoefd3309wvRNEG7c6sxa96wkMcKN1Ie57izPXlqvt6xUc62BE0khjSGJfeS7XoNp5xB3hKJLtoTpY/B0NojpSTL9SRO+SX503/d/3bodxOljy60f5e1jAzXUNw3/lO9OMGmS/uiHBrVsesDsaxD5MpPCC2NXBClP4pDz1+w0JJHyTXHkWtNPBEsHYNNuxhD9MLQ2qCJKmF4D4Gzft1BnnnqT7ZsPoIlJceOZnH06Mmlurg4Ow8+3JE7xpwXlIDi2LeWFqrrcipCuL2V308bTOMm7nIDubkmlRJe8XmcrgvO71CThEQH+/elU6NmPNcNa8mlPRug6xq9L53AwgX/+vytTptxFRddXK/wBooSRynsKuPltENKyQP3zuKD91Z4ZMR1Q2C6JOd3qMG3U68kISGKX37awrAh03A6rYjVSCmMNRtuoV69xGId0xdZrufItT6lsEJ7Nm0oMcZTRR5HyjQsDiKIL1DJWUqJ0/qZXGscplwDCHRxLg79RmzaxT77TXP2wZKbiJwmTRzxtqUIEQWAJfeT5uyK2xAL5rujoYuziDUmevr6L+7LbC5gD4uqcrCYpsWwIdP4cfo/AbV/9IkLuf/BjgG13bEjhVYtPggiZsW9/HPb6HY8/9LFaJqge9cvWLF8v98lYl13p1/n/f+ii+vyzbcDWbpkL1f0nuh1DrohaNGiMvP/ur5UxqcpThLM/VtFHynKBEIIXn7tEhYuuZ4bRrWmR88GXDm4Od9PH8zMWUNJSIhi86bDDL1mKrm5ZrEbLgDTpmxk4YLdJaJf4Y0o/X4MkScnr+f7vyEuJVp/OCzjCFEOXTQoYLi49wns+mXE2aYSb9tCvG0LcbaJfg0X09qIJTcQSTG9aP3xfMaGJqoRY7yHezX91BgHHRBEac8RpT+OoOqpvWDXhhFrTCjUcAH35yCEo0QMF4C7/vdrwIYLwEvPL+TIkayA2o4ftyqoueTJIbz3znLefmMJAP8b075Qw+XUjyyvTd7/583dxcMPzKFL17q899Fl2GwamibQdeHJOmzevDLfTxusDJfTDOV5UZw23PW/X/l8/JqgjYdwy5MnJcXy+FNdGDrs7PB1GiJSSky5Cqf1PZY8gBBVsGv90UW7EruRBoLTmk2m68YIjpBIgn2l1z2W3EOO+RUu6w/cInftsWtD0TV3mqyUJpbcBrjQRN1SVU/IG0cOZ9KgztigDHoh4PW3enDDqFbs35eOaVpUr1HOa7ZN7x5fs2C+/2wfbySWj2LLjtE4HAbPPfMnLz2/MF+Bxrzq8L6w23X+2TGaChWiOXwokwlfrmX9+oPExNjoc0VjLrq4njJcyghq2UgZL2ckjeuNJdmPvPd/iY2zcd2wlnzwnvcbWVG4fmQroqMN9uw5TpUqsXS7uB6X9qiPw6Hi5P3hslaT4RoQsf4F1Yi3L4xY/6WJr774m9tu/jmoYwxDcEmPBvyz+Qjbth4D3Eb5Lbe1444x52GaEtO0iImxMeCKycyetSPk+f3827V0urA2AMuX7ePjD1eyemUyUTEG9eqVZ8p3G/32Mem7gfS6LLw1wxTFjyrMqDgjyXUGv8Rw3wMdWb5sbwRmA+M/WZ3v9biPVlGunJ1nX7iI60e2isiYpwu6OBtBTSR7fLQqLCXbn5KujiE6FXWKZYbUVN+Ccd5wuSS//LQ135JNcnIGTz3xB6++/Bfp6W7BvsREB23bVS+S9zI7+6QeTrtzq9Pu3JO1qCZ+sy4g4yUwOQXF6YSKeVGcNrRtVy0otc4evRpwy21tmDNrZ+Qm9R/S0nK5c/RMPvk4uDiB7duP8eZri3nmqfl88/U6siJcjbukEUIj2njIZxuHdieap0K3wclnscrkxal4x8KhDw/LPMsCDYtQj+e/BomUeAwXgJSUHGbP2oEQodUFEwKaNatU6P5zz/Nf00nTBG3aVgt6bEXZRhkvitOGm29t6/cJTNOgxVmVGfteLyZ+O5AN6w+TmRmcISAE1KnrXWI8UJ54dF5ABkhOjoubR86g9Vkf8uTjf/Dma4u5eeQMGtV9h+lTNxVpDqUdm9aLaP1NBHmqqHk3x1ii9CeIMv5HnO1nYo0JOLSbcGgjiTE+It62kBhjLG4DpmDgbbT+IrrWvDjfSonS/ZJ6VKgYHdExLEt6AmQDRdcFvS5rSI2ahS8PNGhQnu6X1Cv0oUTXBVf0a0z1GuWCGltR9lExL4rTBikljzw0h3feWuZJpQQ8KdUvv9adW25rl++YJYv2cMlFXwU9Vs2a5dizJ61I861bL4GEhCjOa1+DG29uQ1MvT6Cjrv+BbydtKPAELIQ7g2X6T1fRpWvdIs2jtCNlLi75B5bcf0IB+CKE8H8zNuVOcs2vcFl/AhaG1uFE4G3jyE+6GJBSkpHhJCrK8Gs4zJm9g359JkV0PoYhuPu+Drz8wl9+2woB1auXY9a863waLwAHktO59OKv2LkzBWmdPB6gcZOKzPx9iEdtV1G2UTEvijMSIQTPvXARHTrU5N2xy1i6ZB+6Luh6UV3uuPM8r5WimzavhMOhk5PjT8LdjaYJWrWqysqVyUWe784dqUAq69cdZNxHK3n1jUu58eY2gPvG9MpLi5g8cYPXY/PKGzz/zAKP8ZKV5eTAgQzKlXNQMcJP2sWJEHZs4pKgj9NFXaKNRyMwo5Ll+PEcxr61lE8+WsXhw5kYhkbf/k24574OnNXSu+jdju0phfYXG2sjI6Poy5Aul6RV66SA2p7XvgYTJg6gStVYv22rJsUx/68RfP7pGj7/bA0HD2RQrXo5hl9/DsOvP4e4uMDUpBWnF8rzojjjuet/v/LZp6v9LjnZbBpdutZh06bD7Pm3aF6Xwpj5+xAu6FSLF59fwPPPLAjomEVLb+Djj1by9VfrPMGPXbrW4eFHO9GhYy1M0+L337YzZ9YOcp0mSUlxXHhhHc5pXVVd+MsYKSnZ9Oz+FZs2HsmXQmwYAk3X+H7alQU8cQcPZNC04buFSgiEUyrgtzlDuXnUDHbuSPHZ5/y/RgRs6CjOHFSqtDJeFEGQlpZDn57fsHqV25uS94vQdUF8goOHH+1ErVoJ7N2Xxr1jfsvXJpwYhkaPXg146ZXutGz2fsBjVE2K5fChzHzGV16MwOtvXcrbby5l29ZjBTQzHA6dkTe25vGnunjq2Rw9mkVGei5VqsaqlG4fSCmZO2cnn45bzT+bDpNYPoorr2rB1de2oFw5R8TGvfeu3/jk41VeDW1NE5SvEMXmbaPzFRJ849XFPPXEHxEXbtQ0wY49dzLjh83cfssvXtvouuD8C2ryy29DIjoXRdlELRspFEFQrpyDmbOG8Pn4NXz68Sp27U6lfPlorh3akptvaUPVpDjS03NpVHdsRIyWPFwui7mzd/LVl3+jaSKg9E+hUcBwAXfqqBAw5o5fPfEB/7155eSYvP/uclatTOa+Bzvw+iuLWfCnuxZUXJydYSPO5v6HOlKhwumzBBUOTNPi1pt+YuLX6z3xVELAksV7efP1xfz827XUqZMY1jHT0nL4+MOVfPzhykK/g5YlOXI4ixk//MOAQc0827dsOYI4tbRUhLjs8oaULx/F0GFns3NnKq+8+Jfn88mLQWt5dhW++rp/ZCeiOCNQnheFIgC+/HwNo2/9JWDjpc/ljVixYr/farn/JSrKoN+AJnw7aYNf40VoJ1ROwnRT+q9nRtcF9eqXZ9a86844A8ayJHNm7+CnGVvIynTSokVlrh3akoqVYnj7jSU89shc73V0dEGz5pVYuOSGsCkYHzmcSc9LJrB50xG/bW02jTvvPp/Hn+zs2Xb/Pb8z7qNVfpWn82oOhULNWuVYuGQk5cufLJGwedNhPh+/hm1bj1Eu3sHAQU09hRQVCm8oz4tCEWa2b0vBMDScfoTwhIAxd5/Pk890AaD/5ZOYN3dXQC57oUGTphVJTIw6cePzfUzFClEcPpzts00w/HeOpinZsf0YLz63gJdfCz5gtqxyIDmdgf0m8/eagxiGhpQSy5I89cR83n63J2PfXlqoEWuaknVrDzH/j11kpDv599/jVKwYTc/eDYmLs7N82T7eHbuM33/bjmVKzmtfnVtHn0uPng0Knc+do2eydcvRgOZuWZKoKD3ftlq1E3waLrou6NylDvv3p7Fp4xEMQ8OyrIANmb79G/PuB5cRH59/uaxJ00o8/5LvGlYKRagoz4tCEQBvvraYJx/3HzcwZ/51tDv3pLDW3Dk76XvZxKDGqlI1hoMHMn22qV0ngU/GXx5SmnewxMTa2LnnTqKiiv6s43Sa/DxjCyuW78cwNC7qXo+OnWqVmjpLliXpfMF41q87FLJqq6YJHA6drCyXx5sVE2ujV68GfP/dJgxD8xgTecsp99zXgSee7lKgrz3/HqdFk/eCWq78a+kNnqyj995ZxoP3zS60rRDu+f425zratE3it1+38/OMLcyetYN9e9P8ft9vGNWKN97uUWrOn6Jso6pKKxRhpu+Apviy8zVNcO551fMZLgB79xwPeqyDBzI9N5WC44AjSufryQNYsWI/Nlvkf8KZGU727w9u+csby5fto0Xj97nu2mm8O3YZb76+hN6Xfk3nCz4L6XM6ldxck28nbeDqQd/R4+KvGH3rzyxbui/ofubM3sHfaw4GVOG4MCxLkpXl8vwb3J/h99+5RQVP9YLkjfPaK4v4/bftBfpauWJ/wIaLrgu6X1rfY7hs+ecID91fuOEC4HAYTJg4gHPPq46ua/Tq3ZCx7/WifPkov4ZLbJxNGS6KEkMtGykUAVCvXiJDh7VkwpfrClzU3ammkkcevzDfdtO0ePrJ+SGPWblyDAcPZiCEQAj3ja5atXJ8PP5yHn94LnPn7PR5YwtnCmxcrK1Ix+/alcIVvSd6VIVPXX5bt/Ygl/eeyKJlN4SU4XTwQAaX9/6GjRsOezwdy5bu5YvP/ubGm9vw6huXFLjBSimZ+cs2Pv5gBWv/PkhUtEG//k3Zvz89n2fkv0TKT63rgg/eXc4ll9YvsD1Qzu9Qk/FfXOF5/cnHq9B0d8CsN4SAs1tVoXefggUNK1SI9lvROSkpThkuihJDGS8KRYC88XZPNCH44vO/EUKg6wKn0yIuzs7Y93px0cX18rVfvnQfySF6LKSEAwcymL9wOIsW7SU7y0XzsyojpeTmUTP4d7d/T0X/AU2pXTeRN19bHNIc4KRHqXIV/2Jivnj/neVkZTm9ejRMU7J1y1GmTtnE1decFXTfQ6+dyj+b3cGseTdb14kb9scfrqRBw/LcNvpcT3spJWPu+JXxn6zOp8T8zttLEQKsElhJN03J0iUFC4Se36EmNpvvWCsh4Muv+3F53yb5jInVq5ILNVzA/R3bsO6w131XXdOCP+btKvRYTRNcMyT4c6VQhAtlvCgUAWK364x9vzf3PngBP0zdzPG0XBo0LE/ffk2Iji7omUg9Hnw13/8SG2fn1tvdJQ2+m7yBkSN+8Pv0LwQMH3EOb7/XiyNHMnn7jcV+gy8Le8qWUvLAwx0LbF+5Yj9Ll+xF1zW6XlSXRieK//27O5Xvv93IkSNZ1KwVz6DBzalYMZpvJ/vOntI0wdTv3caLlJIli/by68xt5OaatGqdRIOG5fnzj924TIu27arRpWsdhBCsWL6fxX/5qjwNb72+hI6darFjewrxCQ527kjxVPw+dU556eUlFQWoe5H4r1AxmkGDmzPx63WFzqtylRiys01cLgub7WSwblSU4ff92B261+0Dr2zGm68vYdvWowXOm64LKlWKYeSo1v7flEIRIZTxolAESZ06idwxpr3fdvUblPfbxhdCwyOfnpnp5H+3zwzoOClhf3I6a1Ync8+Y3wLKGmnUuAKbN7kzTYRwx2XYHTpvvdOT7pecXMrYsSOFEddNY9WKZE/8h5Rwac/61KgRz2efrvZ4pUzT4uEHZvPUs13JSPctP29ZktSUbA4eyODqK79n+bJ9nno9eUs4eXFApilp0LA8EyYOYO6cHfm8J97Yvz+dCzt85nntq/pxyRkugosvrsuEL/9m//50KlWK4fjxHD4dt5rt24552nkzRg4fymLU9T/y1ON/MOqm1lx5VQtq1oqnd59GzJ2zs9AxDUPj8iu813mKjrbx08xruG7INBb/tcezfGWakqbNKvHlN/1VPSFFiaKyjRSKCNKz+1csWbw3pMyVs1pW5q+lIwH4esJabhn1U0DHaZqgY6daLFmyF5fTCihN+/W3LuXc86ozfepmjh/PoUnTSgy+ujkJCSd1O44czqTDuZ9y6FBG0O+nZs1y7NuXVqghJQTUrh1PRqaLY0ez/Pafp3489Lqzef/d5X41TIIhzwsVihcmLs5GZqYraDVbIdyevZxcE70QgcJA5yME3HhzGx5+7ELObf0xR48U/DyFcBsvCxZfT7PmlX32t3pVMvPnudP9259fg/MvqKliXRQRoVTovDz33HP89NNPrF69GrvdTkpKit9jpJQ88cQTfPzxx6SkpNCxY0fef/99GjUqGFCmUJQFXn+rB927fUlWpvd4D188+Ww3z7+3bzvmN/YhD8uSbFh/KGDDBeCi7vWoX78857QqvN7Mxx+t5ODBjJBk5tPTc316gKSEXbsCzzgyTcnx1Bz+3Z0aVsMF3MbLxZfUY/eu1ICE4U7F5ZLYbO6A31PPd57hERXlNlDyqiPrukBK9znLKw5a2PckUENKSnesj2Fo/PjzNfTtM5EDyRmesaSUOBwGn0/o59dwAWjVOknVIVKUOiKWZ5mbm8uVV17JrbfeGvAxL7/8Mm+//TYffPABS5YsITY2lh49epCdHT4hLoWiOGneojJz5w+j12UN8y1XNGpcwedxHS+sxaWnZJ4kJkQFZPzouqBKlViOHMkK2MioUDGa+vVPLnFlZOTy+fg1XDv4ey4471N6dv+Kxx6Zy+efrg65Pk5KSg5t2lbzuWQTLKYp+euvf6lbLzGorBx/uFwWg69qwcxZQ4NORc/OdjFh0gDatM1/sy9fIZr3PuzFxq2jeebZbnS9qC6dLqzN/8acR+IpqrThQkr48P0VVKwYzdqNt/LhJ30YMKgZ/fo34bkXL2LTttvp1bth2MdVKIqLiC8bffbZZ4wZM8av50VKSfXq1bnnnnu49957AUhNTaVq1ap89tlnXH311QGNp5aNFKWVI4czSU5Op2LFGKomxfLs03+667/o7mWKvHiODhfUZPKUQfmWbHbvSg2oWGO9+om0O7c6307aEPC8WrdJ4o+FIwBYsXw/A66YyLFjRQ82/i/fTh3EhK/WMu37zWHrMyrK4M672/PyCwvDEq+i64JKlWNYt+lWHA6D115ZxFOP/xFUH5UqRWOz6ezfn+7xdoDb+/LiK925+da2gNvQ+enHLVw/bHrRJ+4FIeC1Ny9l1E1tItK/QhFuSsWyUbDs2LGD5ORkunfv7tmWkJBA+/btWbRoUcDGi0JRWqlYKSZfkONjT3TmmiFn8cX4NezYnkJCooNBg5t7MmlOpXadBIZffw6fj19T6E36/gcvoH2HmgzqNzngOem64Lz2bmG9Qwcz6HvZRNLSwm+4gFsufu+/aX71Q4LBbtd46fmFYelLCEhIjGLK9MEevZm77z2fqCiD556eT7qfoOM8Dh/O8vz7v96y++7+nZgYg5Urkpnw5Vqys11hmbs3dF3jeGpkzqVCUdKUGuMlOTkZgKpVq+bbXrVqVc8+b+Tk5JCTc/IHevx40ZQ6FYripGHDCjz9XDf/DXE/RQN8Pn5NAZ2Zt97pyaDBzejYfnxQ41uWZOSN7pTXz8avIS0tJyIZN23aJlGtWlxIqre+CNSgCAQp4YaRrWh59slrkBCC2+84l6uubkGjemNDLhlwsj93pW9LSp8aLOHA5bKKnPGmUJRWglrQffDBB0+ofRb+t2nTpkjN1SsvvPACCQkJnr9atWoV6/gKRXFhs+m8/W4v1m68lWee68pd957PB+MuY+uuO7jyquZs3nSEdWsPBpyRAu5ljKbNKgHw4/R/ImK4CAHvfXRZRPoOlwcnjzdeW8yRwwXrSlWqHMPlfb2nFQeDlG514aIYLoHE9wjhjmXypp6rUJwOBOV5ueeeexgxYoTPNvXr1/e5vzCSktwBbgcOHKBatWqe7QcOHKBVq1aFHvfQQw9x9913e14fP35cGTCK05radRK86swcOpQR0PFCwEUX1+N/d7Wn20V1PdvzpPsD4VRtFV9y+uBeeml+IqulxVmV2bjhUMAViwtDCChfIYqjR8IbzG+akinfb+LGm/PHibz52mKmTQlfrE6olCtn56ffrmXVimQ+HbeKtX8fKPBZ5gVFv/t+L+x27yJ0CkVZJyjjpXLlylSu7D+1LhTq1atHUlISs2fP9hgrx48fZ8mSJT4zlhwOBw6Ho9D9CsWZQrXq5QJq9+kXVzBwUPMC29u0rcbWLUcwTf99fDVxAAkJDgxdo2nzitz1v9/4/tuNGIaGJS2QYFlw1z3n8/hTJ6slj/7fudx6089++69TJwGXy2Lv3rSCO4XbgDt6JKvgvjCw5Z/86dGTJ67n8UfnRWSsYDAMjfl/jaBBwwq0apXE9SNbsWNHCk8+Opcfpv/jMSbPPa86jz3Zmc5d6pTwjBWKyBGxmJfdu3dz9OhRdu/ejWmarF69GoCGDRsSFxcHQNOmTXnhhRfo378/QgjGjBnDs88+S6NGjahXrx6PPfYY1atXp1+/fpGapkJx2tCwYQXOa1+dFcv3FxqbER/v4LI+3pc/bry5Dd9MWOd7EAE1a8RzaY/6Hil6p9OkX/8mpKbksHXrEaKjbFxwYS3+N6Y99eol5jv82qEtWbZ0H5+OW+1VGbdKlRgcDoPdu1O9Dl+rVjw339qWxk0qMHjg977nGiIJiSezvKSUvPziwmItG3Cq9gu4PSl2u8433w6kQcP8Kfb16iXy+YT+HD2axb69aZQvH0WNmirLUnH6EzHj5fHHH+fzzz/3vG7d2h0UOHfuXLp27QrA5s2bSU09eZG6//77ycjI4KabbiIlJYVOnToxc+ZMoqLCr4OgUJyOvPByd3pdMgEpvQvUvfTqxURFef/Ztzu3Og8+0pEXn/ORvSNhz57jtGj8Hrfefi5XXtWcgf0ms3HDYY8xouuCjRsPU6NGOe69/4J8hwsheOPtHvTs3ZCPP1jJmtXJREXb6NuvMTfc2Jovxv/NW28s8WooaJogJ8fk1tHtmPHDlqA+l2AYNuIcz7937Urln81Hw9KvrruDrHNzfRdZnD1vGLNmbefPP3YjBHTuWofhI87xWRyzQoVoKlSIDss8FYqygCoPoFCcZixZvJd7xvzK32sOerbVqFmOp5/txpVXFVwu+i8zfviHV15ayKqVB3y2E8LtyUlLz8EqZKnp08+vYNBg95gbNxxi9eoD2G06XS+qS8WK+W+2OTkuGtQZ6ze994sJ/aheoxzdu37p970ES9t21Zj753DP600bD3Nem3FF7rdCxWhG3dSaWrXiueM27zWqNE1w9bVn8cHHlxV5PIWiLFImdV4UCkV4aH9+DRYsvoF1aw+ye1cqFStGc277GgGr2/a5ojF9rmiMy2Xx5/xd9L1sktd2UkKqD0ND0+D1VxfTum0St970c77qzzabxogbWvH8Sxd5NFV270r1a7jYbBqrVibTt38TGjQsz/ZtxwJeztF1QVSUQUamE7wcU6FiNJO/H5RvW+06CcTEGGRm+tZjaXFWZTasP+SZS1K1WB56pBNXX3sWOTkm8fEOz+efkeHk0YfmYlnSI1BompIBg5ry1js9AnszCsUZjjJeFIrTlLNaVuGsllVCPt4wNCZ+vR7DELhCSO21LFi39iDdu3xJSkr+rCCn0+KTj1eRnJzOV9+4Y95sAWTGSCmxO3SEELz25qUM7DsZy5L5DJi8NPDhN5zDogV72LUrlfh4O1dfexa33t6OnTtTeOn5hcybuwsAh0PnuuFn88hjFxaolBwTY+O64ecw7qOVXuOINE1QvkIUfywc4cm6stm0fCKD0dG2fMfcNvpcrhzcnIlfr2PHzlTKl49i0JXNAqozpFAo3KhlI4VCUSidLxjP6lW+l4/8oWn4TI3+fe51tD+/BlJK2pz9kV9vypz5w2h3bnUA5s7ZyYP3zWLjhsOe/Y2bVOD5ly7m0h4NfM4rJSWb9LRcKp8IEi6M1NRsenafwMYNh/PFEem6QDc0vp92JV261vU5lkKh8I9aNlIoFGEhPt5RpEwbIXwbLoah8c2EtbQ/vwZCCO69v0OhqdS6Lmh3XnXatjupA9XtorosXj6StX8fZN++NJKS4jinVdUC5RW8kZgYRWKi/2SAhIQofp09lHfeXsq4D1dx+HAmhqHRt38T7r73/HyKvAqFonhQxotCoSiUAYOaMf+P3SEdG0gNI5fLIjk53fP62qEt2bEjhZdf+MuzXJWXxdS8RWW+njiggGEihODsc6py9jmRMyLi4x08/OiFPPRIJzIznTgcBoYRXMVphUIRPpTxolAoCmXw1S149aW/2L8/vUDMh64LHA4Dp8tEWtITF5NnW3S4oCYbNxzi6NHCVXANQ8snrieE4NHHO3Pl4OZ89ukatm45Srl4BwMGNqVn74YlbjAIIYiNtZfoHBQKhYp5USgUftixI4XBA75l86YjGIaGEO6A26SkOCZ9P4joaIO331zClO83kZXppEGD8tx4S1tuGNWKF55dwFtvLPFZ0HDun8PzLQUpFIozk2Du38p4USgUfrEsydw5O5k3ZyemadH+/Br07tPIo7Kbh5Qy37LO4UOZdOowngPJBT03QsCVVzVn3PgriuU9KBSK0o0yXpTxolCUGvbuOc4dt/3C7Fk7PIG/0TEGt9zajsee7FziS0EKhaJ0oLKNFApFqaFGzXim/HAVO3emsHbNAewOgws61qRcOVVQVaFQhIYyXhQKRbFQt24idesmlvQ0FArFaYDy1yoUCoVCoShTKONFoVAoFApFmUIZLwqFQqFQKMoUynhRKBQKhUJRplDGi0KhUCgUijKFMl4UCoVCoVCUKZTxolAoFAqFokyhjBeFQqFQKBRlCmW8KBQKhUKhKFOcdgq7eaWajh8/XsIzUSgUCoVCESh59+1ASi6edsZLWloaALVq1SrhmSgUCoVCoQiWtLQ0EhISfLY57apKW5bFvn37KFeuHEKIkp4Ox48fp1atWvz777+qynUpR52rsoU6X2ULdb7KFiVxvqSUpKWlUb16dTTNd1TLaed50TSNmjVrlvQ0ChAfH69+sGUEda7KFup8lS3U+SpbFPf58udxyUMF7CoUCoVCoShTKONFoVAoFApFmUIZLxHG4XDwxBNP4HA4SnoqCj+oc1W2UOerbKHOV9mitJ+v0y5gV6FQKBQKxemN8rwoFAqFQqEoUyjjRaFQKBQKRZlCGS8KhUKhUCjKFMp4USgUCoVCUaZQxkuYee6557jggguIiYkhMTExoGOklDz++ONUq1aN6OhounfvzpYtWyI7UQUAR48eZciQIcTHx5OYmMjIkSNJT0/3eUzXrl0RQuT7u+WWW4ppxmcW7777LnXr1iUqKor27duzdOlSn+2//fZbmjZtSlRUFC1btuTnn38uppkqILjz9dlnnxX4HUVFRRXjbM9c5s+fz+WXX0716tURQjBt2jS/x8ybN482bdrgcDho2LAhn332WcTn6QtlvISZ3NxcrrzySm699daAj3n55Zd5++23+eCDD1iyZAmxsbH06NGD7OzsCM5UATBkyBDWr1/P77//zowZM5g/fz433XST3+NuvPFG9u/f7/l7+eWXi2G2ZxaTJk3i7rvv5oknnmDlypWcc8459OjRg4MHD3pt/9dff3HNNdcwcuRIVq1aRb9+/ejXrx/r1q0r5pmfmQR7vsCt3nrq72jXrl3FOOMzl4yMDM455xzefffdgNrv2LGDyy67jG7durF69WrGjBnDqFGj+PXXXyM8Ux9IRUQYP368TEhI8NvOsiyZlJQkX3nlFc+2lJQU6XA45DfffBPBGSo2bNggAbls2TLPtl9++UUKIeTevXsLPa5Lly7yzjvvLIYZntmcd9558vbbb/e8Nk1TVq9eXb7wwgte2w8ePFhedtll+ba1b99e3nzzzRGdp8JNsOcr0GukIrIAcurUqT7b3H///bJFixb5tl111VWyR48eEZyZb5TnpYTZsWMHycnJdO/e3bMtISGB9u3bs2jRohKc2enPokWLSExMpF27dp5t3bt3R9M0lixZ4vPYCRMmUKlSJc46l/7euwAABQhJREFU6yweeughMjMzIz3dM4rc3FxWrFiR73ehaRrdu3cv9HexaNGifO0BevTooX5HxUAo5wsgPT2dOnXqUKtWLfr27cv69euLY7qKICmNv63TrjBjWSM5ORmAqlWr5ttetWpVzz5FZEhOTqZKlSr5thmGQYUKFXx+9tdeey116tShevXq/P333zzwwANs3ryZKVOmRHrKZwyHDx/GNE2vv4tNmzZ5PSY5OVn9jkqIUM5XkyZN+PTTTzn77LNJTU3l1Vdf5YILLmD9+vWlsrjumUxhv63jx4+TlZVFdHR0sc9JeV4C4MEHHywQWPbfv8J+oIriJ9Ln66abbqJHjx60bNmSIUOG8MUXXzB16lS2bdsWxnehUJzedOjQgWHDhtGqVSu6dOnClClTqFy5Mh9++GFJT01RBlCelwC45557GDFihM829evXD6nvpKQkAA4cOEC1atU82w8cOECrVq1C6vNMJ9DzlZSUVCCY0OVycfToUc95CYT27dsDsHXrVho0aBD0fBUFqVSpErquc+DAgXzbDxw4UOi5SUpKCqq9InyEcr7+i81mo3Xr1mzdujUSU1QUgcJ+W/Hx8SXidQFlvARE5cqVqVy5ckT6rlevHklJScyePdtjrBw/fpwlS5YElbGkOEmg56tDhw6kpKSwYsUK2rZtC8CcOXOwLMtjkATC6tWrAfIZn4qiYbfbadu2LbNnz6Zfv34AWJbF7NmzGT16tNdjOnTowOzZsxkzZoxn2++//06HDh2KYcZnNqGcr/9imiZr166ld+/eEZypIhQ6dOhQQHagxH9bJRYqfJqya9cuuWrVKvnUU0/JuLg4uWrVKrlq1SqZlpbmadOkSRM5ZcoUz+sXX3xRJiYmyunTp8u///5b9u3bV9arV09mZWWVxFs4o+jZs6ds3bq1XLJkiVywYIFs1KiRvOaaazz79+zZI5s0aSKXLFkipZRy69at8umnn5bLly+XO3bskNOnT5f169eXnTt3Lqm3cNoyceJE6XA45GeffSY3bNggb7rpJpmYmCiTk5OllFJed9118sEHH/S0X7hwoTQMQ7766qty48aN8oknnpA2m02uXbu2pN7CGUWw5+upp56Sv/76q9y2bZtcsWKFvPrqq2VUVJRcv359Sb2FM4a0tDTPvQmQr7/+uly1apXctWuXlFLKBx98UF533XWe9tu3b5cxMTHyvvvukxs3bpTvvvuu1HVdzpw5s6TeglTGS5gZPny4BAr8zZ0719MGkOPHj/e8tixLPvbYY7Jq1arS4XDIiy++WG7evLn4J38GcuTIEXnNNdfIuLg4GR8fL6+//vp8huaOHTvynb/du3fLzp07ywoVKkiHwyEbNmwo77vvPpmamlpC7+D0ZuzYsbJ27drSbrfL8847Ty5evNizr0uXLnL48OH52k+ePFk2btxY2u122aJFC/nTTz8V84zPbII5X2PGjPG0rVq1quzdu7dcuXJlCcz6zGPu3Lle71N552f48OGyS5cuBY5p1aqVtNvtsn79+vnuYSWBkFLKEnH5KBQKhUKhUISAyjZSKBQKhUJRplDGi0KhUCgUijKFMl4UCoVCoVCUKZTxolAoFAqFokyhjBeFQqFQKBRlCmW8KBQKhUKhKFMo40WhUCgUCkWZQhkvCoVCoVAoyhTKeFEoFAqFQlGmUMaLQqFQKBSKMoUyXhQKhUKhUJQplPGiUCgUCoWiTPF/9OfMOZY4JEsAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(X), X.dtype\n",
        "\n",
        "X=torch.from_numpy(X).type(torch.float32)\n",
        "y=torch.from_numpy(y).type(torch.float32)\n",
        "\n",
        "X[:5], y[:5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7AcMoE8NKX3U",
        "outputId": "0a6eff0a-7284-4ecc-d987-f109ff252af3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(tensor([[ 0.7542,  0.2315],\n",
              "         [-0.7562,  0.1533],\n",
              "         [-0.8154,  0.1733],\n",
              "         [-0.3937,  0.6929],\n",
              "         [ 0.4422, -0.8967]]),\n",
              " tensor([1., 1., 1., 1., 0.]))"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state=42)\n",
        "X.shape, y.shape\n",
        "X_train.to(device)\n",
        "y_train.to(device)\n",
        "X_test.to(device)\n",
        "y_test.to(device)\n"
      ],
      "metadata": {
        "id": "Y07HEkNkUz8B"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#build model\n",
        "\n",
        "#more verbose definition, allows for more flexibility and customization\n",
        "class ToyCircleClassificationModel(nn.Module):\n",
        "  def __init__(self):\n",
        "    super().__init__()\n",
        "    #create 2 nn.Linear() layers to handle data shapes\n",
        "    self.layer1 = nn.Linear(in_features=2, out_features=5) #we have 2 input features, x1 and x2, and will upscale to 8 output features = 8 neurons in hidden layer\n",
        "    self.layer2 = nn.Linear(in_features=5, out_features=1) #8 new inputs from learning patterns, 1 output feature: binary classification\n",
        "\n",
        "  def forward(self, x: torch.Tensor) -> torch.Tensor:\n",
        "    return self.layer2(self.layer1(x))\n",
        "\n",
        "model_2=ToyCircleClassificationModel().to(device)\n",
        "print(f\"{model_2} currently on: {device}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EtOPs-MiX1KQ",
        "outputId": "15898d11-81e2-44e1-8d8f-03ee11d8bd70"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ToyCircleClassificationModel(\n",
            "  (layer1): Linear(in_features=2, out_features=5, bias=True)\n",
            "  (layer2): Linear(in_features=5, out_features=1, bias=True)\n",
            ") currently on: cpu\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#overriding model_2 with simpler, concise model definition, same functionality as prior model if model is relatively simple\n",
        "model_2=nn.Sequential(\n",
        "    nn.Linear(in_features=2, out_features=8),\n",
        "    nn.Linear(in_features=8, out_features=1)\n",
        ")\n",
        "model_2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zmLLnwzPcJiK",
        "outputId": "53a4e752-5008-450e-e44a-fa474b47ee73"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sequential(\n",
              "  (0): Linear(in_features=2, out_features=8, bias=True)\n",
              "  (1): Linear(in_features=8, out_features=1, bias=True)\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model_2.state_dict()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CeKgvayufaHV",
        "outputId": "7d94e139-a296-4e4c-c8e3-f4262f7a8eb4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "OrderedDict([('0.weight',\n",
              "              tensor([[-0.4207, -0.5175],\n",
              "                      [-0.2912,  0.6842],\n",
              "                      [-0.5860, -0.3092],\n",
              "                      [-0.6306, -0.0744],\n",
              "                      [-0.3939,  0.1494],\n",
              "                      [-0.5940,  0.2915],\n",
              "                      [-0.3910,  0.5857],\n",
              "                      [ 0.1401, -0.3697]])),\n",
              "             ('0.bias',\n",
              "              tensor([ 0.3901,  0.1827,  0.6809,  0.6906,  0.1711, -0.3105,  0.0125,  0.5344])),\n",
              "             ('1.weight',\n",
              "              tensor([[-0.2392,  0.0808,  0.2234, -0.0490,  0.1240, -0.0022, -0.1472,  0.1465]])),\n",
              "             ('1.bias', tensor([-0.2549]))])"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with torch.inference_mode():\n",
        "  untrained_preds=model_2(X_test)\n",
        "print(\"Untrained Predictions:\",torch.round(untrained_preds[:10]))\n",
        "print(\"Actual labels:\",y_test[:10])\n",
        "#pretty abysmal without training"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o2ablwtoplNz",
        "outputId": "3df8e38e-4dcf-414f-c3bb-d51a934986ff"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Untrained Predictions: tensor([[-0.],\n",
            "        [-0.],\n",
            "        [-0.],\n",
            "        [-0.],\n",
            "        [-0.],\n",
            "        [-0.],\n",
            "        [-0.],\n",
            "        [-0.],\n",
            "        [-0.],\n",
            "        [-0.]])\n",
            "Actual labels: tensor([1., 0., 1., 0., 1., 1., 0., 0., 1., 0.])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#set up loss function and optimizer\n",
        "\n",
        "loss_func=torch.nn.BCEWithLogitsLoss() #combines sigmoid activation function built-in with BCE loss in a single step, torch.nn.BCELoss() requires inputs to have gone through sigmoid activation function before calculating cross-entropy loss\n",
        "\n",
        "optimizer=torch.optim.SGD(params=model_2.parameters(), lr=0.1)\n"
      ],
      "metadata": {
        "id": "4RnebJucqrkj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#accuracy function\n",
        "def accuracy(y_test, y_preds):\n",
        "  correct=torch.eq(y_test, y_preds).sum().item()\n",
        "  return (correct/len(y_preds)) * 100\n",
        "accuracy(y_test, untrained_preds)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mv8xXvnJtMRZ",
        "outputId": "7deef2e9-15ed-4008-d688-09641130f2fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#use sigmoid only for binary classification\n",
        "torch.manual_seed(42)\n",
        "epochs=1000\n",
        "for epoch in range(epochs):\n",
        "  model_2.train()\n",
        "\n",
        "  y_logits = model_2(X_train).squeeze()\n",
        "  y_pred = torch.round(torch.sigmoid(y_logits)) #logits -> pred probs -> pred labels\n",
        "\n",
        "  loss=loss_func(y_logits, y_train)\n",
        "  acc=accuracy(y_train, y_pred)\n",
        "\n",
        "  optimizer.zero_grad()\n",
        "\n",
        "  loss.backward()\n",
        "\n",
        "  optimizer.step()\n",
        "\n",
        "  model_2.eval()\n",
        "\n",
        "  with torch.inference_mode():\n",
        "    test_logits = model_2(X_test).squeeze()\n",
        "    test_pred = torch.round(torch.sigmoid(test_logits)).squeeze()\n",
        "\n",
        "    test_loss = loss_func(test_logits, y_test)\n",
        "    test_acc = accuracy(y_test, test_pred)\n",
        "\n",
        "  if epoch%10==0:\n",
        "    print(f\"Epoch: {epoch} | Training Loss: {loss} | Testing Loss: {test_loss} | Training Accuracy: {acc}% | Testing Accuracy: {test_acc}%\")\n",
        "#our results are not very good, we are losing accuracy as epochs progress past a certain epoch, should we increase layers?"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-v9nAnXtuNb-",
        "outputId": "10fa68d4-c666-4fac-de7f-81900be16841"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 0 | Training Loss: 0.6948879361152649 | Testing Loss: 0.6945173144340515 | Training Accuracy: 50.0% | Testing Accuracy: 50.0%\n",
            "Epoch: 10 | Training Loss: 0.6937289237976074 | Testing Loss: 0.6932328939437866 | Training Accuracy: 50.0% | Testing Accuracy: 50.0%\n",
            "Epoch: 20 | Training Loss: 0.6934133768081665 | Testing Loss: 0.6929444074630737 | Training Accuracy: 50.0% | Testing Accuracy: 50.0%\n",
            "Epoch: 30 | Training Loss: 0.6932942271232605 | Testing Loss: 0.6929439306259155 | Training Accuracy: 50.0% | Testing Accuracy: 50.0%\n",
            "Epoch: 40 | Training Loss: 0.6932271718978882 | Testing Loss: 0.6930339336395264 | Training Accuracy: 50.0% | Testing Accuracy: 50.0%\n",
            "Epoch: 50 | Training Loss: 0.693179190158844 | Testing Loss: 0.6931517720222473 | Training Accuracy: 49.125% | Testing Accuracy: 48.5%\n",
            "Epoch: 60 | Training Loss: 0.6931414604187012 | Testing Loss: 0.693274974822998 | Training Accuracy: 40.875% | Testing Accuracy: 40.5%\n",
            "Epoch: 70 | Training Loss: 0.6931111812591553 | Testing Loss: 0.6933950781822205 | Training Accuracy: 48.25% | Testing Accuracy: 44.5%\n",
            "Epoch: 80 | Training Loss: 0.6930866241455078 | Testing Loss: 0.6935086250305176 | Training Accuracy: 47.625% | Testing Accuracy: 47.0%\n",
            "Epoch: 90 | Training Loss: 0.6930666565895081 | Testing Loss: 0.69361412525177 | Training Accuracy: 49.375% | Testing Accuracy: 45.5%\n",
            "Epoch: 100 | Training Loss: 0.6930503845214844 | Testing Loss: 0.6937116384506226 | Training Accuracy: 50.0% | Testing Accuracy: 44.5%\n",
            "Epoch: 110 | Training Loss: 0.693037211894989 | Testing Loss: 0.6938010454177856 | Training Accuracy: 50.5% | Testing Accuracy: 45.0%\n",
            "Epoch: 120 | Training Loss: 0.6930264234542847 | Testing Loss: 0.6938830018043518 | Training Accuracy: 50.625% | Testing Accuracy: 45.5%\n",
            "Epoch: 130 | Training Loss: 0.6930176615715027 | Testing Loss: 0.6939579248428345 | Training Accuracy: 50.74999999999999% | Testing Accuracy: 45.0%\n",
            "Epoch: 140 | Training Loss: 0.6930105686187744 | Testing Loss: 0.6940261721611023 | Training Accuracy: 50.74999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 150 | Training Loss: 0.6930047869682312 | Testing Loss: 0.6940882802009583 | Training Accuracy: 50.625% | Testing Accuracy: 46.0%\n",
            "Epoch: 160 | Training Loss: 0.6930001974105835 | Testing Loss: 0.6941448450088501 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 170 | Training Loss: 0.6929963827133179 | Testing Loss: 0.6941961646080017 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 180 | Training Loss: 0.6929931640625 | Testing Loss: 0.6942427754402161 | Training Accuracy: 50.74999999999999% | Testing Accuracy: 46.0%\n",
            "Epoch: 190 | Training Loss: 0.6929906606674194 | Testing Loss: 0.694284975528717 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 46.0%\n",
            "Epoch: 200 | Training Loss: 0.6929886341094971 | Testing Loss: 0.6943233013153076 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 210 | Training Loss: 0.6929869651794434 | Testing Loss: 0.6943579316139221 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 220 | Training Loss: 0.6929855942726135 | Testing Loss: 0.6943893432617188 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 230 | Training Loss: 0.6929844617843628 | Testing Loss: 0.6944177150726318 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 240 | Training Loss: 0.6929836869239807 | Testing Loss: 0.6944433450698853 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 250 | Training Loss: 0.6929829120635986 | Testing Loss: 0.6944665312767029 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 260 | Training Loss: 0.6929823160171509 | Testing Loss: 0.694487452507019 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 270 | Training Loss: 0.6929818987846375 | Testing Loss: 0.6945064067840576 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 280 | Training Loss: 0.692981481552124 | Testing Loss: 0.6945234537124634 | Training Accuracy: 51.5% | Testing Accuracy: 45.5%\n",
            "Epoch: 290 | Training Loss: 0.6929811835289001 | Testing Loss: 0.6945388913154602 | Training Accuracy: 51.625% | Testing Accuracy: 45.5%\n",
            "Epoch: 300 | Training Loss: 0.692980945110321 | Testing Loss: 0.6945527791976929 | Training Accuracy: 51.5% | Testing Accuracy: 45.5%\n",
            "Epoch: 310 | Training Loss: 0.6929808259010315 | Testing Loss: 0.6945652961730957 | Training Accuracy: 51.5% | Testing Accuracy: 45.5%\n",
            "Epoch: 320 | Training Loss: 0.6929805874824524 | Testing Loss: 0.694576621055603 | Training Accuracy: 51.5% | Testing Accuracy: 45.5%\n",
            "Epoch: 330 | Training Loss: 0.6929804086685181 | Testing Loss: 0.6945868730545044 | Training Accuracy: 51.5% | Testing Accuracy: 45.5%\n",
            "Epoch: 340 | Training Loss: 0.6929803490638733 | Testing Loss: 0.6945960521697998 | Training Accuracy: 51.5% | Testing Accuracy: 45.0%\n",
            "Epoch: 350 | Training Loss: 0.6929802894592285 | Testing Loss: 0.6946043372154236 | Training Accuracy: 51.5% | Testing Accuracy: 44.5%\n",
            "Epoch: 360 | Training Loss: 0.692980170249939 | Testing Loss: 0.6946117281913757 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 44.5%\n",
            "Epoch: 370 | Training Loss: 0.6929801106452942 | Testing Loss: 0.6946184635162354 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 44.5%\n",
            "Epoch: 380 | Training Loss: 0.6929800510406494 | Testing Loss: 0.694624662399292 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 44.5%\n",
            "Epoch: 390 | Training Loss: 0.6929800510406494 | Testing Loss: 0.6946300268173218 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 400 | Training Loss: 0.6929799914360046 | Testing Loss: 0.6946350336074829 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 410 | Training Loss: 0.6929799914360046 | Testing Loss: 0.6946394443511963 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 420 | Training Loss: 0.6929799914360046 | Testing Loss: 0.6946433782577515 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 430 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946470141410828 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 440 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946502923965454 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 450 | Training Loss: 0.6929799914360046 | Testing Loss: 0.6946531534194946 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 460 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946557760238647 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 470 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946582198143005 | Training Accuracy: 51.125% | Testing Accuracy: 45.5%\n",
            "Epoch: 480 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946603655815125 | Training Accuracy: 51.125% | Testing Accuracy: 45.5%\n",
            "Epoch: 490 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946622729301453 | Training Accuracy: 51.125% | Testing Accuracy: 45.5%\n",
            "Epoch: 500 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694663941860199 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 510 | Training Loss: 0.6929799914360046 | Testing Loss: 0.6946655511856079 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 520 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946669220924377 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 530 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694668173789978 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 540 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946693658828735 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 550 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946704387664795 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 560 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946712732315063 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 570 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946721076965332 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 580 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946727633476257 | Training Accuracy: 51.0% | Testing Accuracy: 45.5%\n",
            "Epoch: 590 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946735382080078 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 600 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946740746498108 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 610 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946747303009033 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 620 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946751475334167 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 630 | Training Loss: 0.6929798126220703 | Testing Loss: 0.694675624370575 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 640 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946759819984436 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 650 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946762800216675 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 660 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946766376495361 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 670 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946769952774048 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 680 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946771740913391 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 690 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946774125099182 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 700 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946776509284973 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 710 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946778893470764 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 720 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946780681610107 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 730 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946781873703003 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 740 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946782469749451 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 750 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946784257888794 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 760 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946784853935242 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 770 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946786642074585 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 780 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694678783416748 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 790 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694678783416748 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 800 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946789026260376 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 810 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946789622306824 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 820 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946790218353271 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 830 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946790218353271 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 840 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946790814399719 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 850 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946790814399719 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 860 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946792006492615 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 870 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946792006492615 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 880 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946792602539062 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 890 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946792602539062 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 900 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694679319858551 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 910 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694679319858551 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 920 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694679319858551 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 930 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694679319858551 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 940 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694679319858551 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 950 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946794390678406 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 960 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946794390678406 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 970 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946794390678406 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 980 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946794390678406 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 990 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946794986724854 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import requests\n",
        "from pathlib import Path\n",
        "\n",
        "#download helper functions from repo if not already downloaded\n",
        "if Path(\"helper_functions.py\").is_file():\n",
        "  print(\"helper_function.py exists already in file path!\")\n",
        "else:\n",
        "  print(\"Downloading helper_functions.py...\")\n",
        "  request=requests.get(\"https://github.com/mrdbourke/pytorch-deep-learning/main/helper_functions.py\")\n",
        "  with open('helper_functions.py', 'wb') as f:\n",
        "    f.write(request.content)\n",
        "\n",
        "from helper_functions import plot_predictions, plot_decision_boundary"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u6a6rXCVgytK",
        "outputId": "0d20d662-a19b-4b0e-b324-c76597e7ef3f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading helper_functions.py...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "plt.subplot(1,2,1)\n",
        "plt.title(\"Train\")\n",
        "plot_decision_boundary(model_2, X_train, y_train)\n",
        "plt.subplot(1,2,2)\n",
        "plt.title('Test')\n",
        "plot_decision_boundary(model_2, X_test, y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "td9WRRlUhxjM",
        "outputId": "ae45bc23-0067-44c0-9a2e-106a3210adf4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#improving the model - add layers?\n",
        "\n",
        "class ToyCircleClassificationModelV1(nn.Module):\n",
        "  def __init__(self):\n",
        "    super().__init__()\n",
        "    self.layer1=nn.Linear(in_features=2, out_features=8)\n",
        "    self.layer2=nn.Linear(in_features=8, out_features=8)\n",
        "    self.layer3=nn.Linear(in_features=8, out_features=1)\n",
        "  def forward(self, x: torch.Tensor) -> torch.Tensor:\n",
        "    return self.layer3(self.layer2(self.layer1(x)))\n",
        "\n",
        "model_3 = ToyCircleClassificationModelV1().to(device)\n"
      ],
      "metadata": {
        "id": "yUaf177GlGyL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#initialize loss function and optimizer for new model training\n",
        "loss_func=nn.BCEWithLogitsLoss()\n",
        "optimizer=torch.optim.SGD(params=model_3.parameters(), lr=0.1)"
      ],
      "metadata": {
        "id": "8Wpf1yMpodf5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "torch.manual_seed(42)\n",
        "epochs=1000\n",
        "for epoch in range(epochs):\n",
        "  model_3.train()\n",
        "\n",
        "  y_logits = model_3(X_train).squeeze()\n",
        "  y_pred = torch.round(torch.sigmoid(y_logits)) #logits -> pred probs -> pred labels\n",
        "\n",
        "  loss=loss_func(y_logits, y_train)\n",
        "  acc=accuracy(y_train, y_pred)\n",
        "\n",
        "  optimizer.zero_grad()\n",
        "\n",
        "  loss.backward()\n",
        "\n",
        "  optimizer.step()\n",
        "\n",
        "  model_3.eval()\n",
        "\n",
        "  with torch.inference_mode():\n",
        "    test_logits = model_3(X_test).squeeze()\n",
        "    test_pred = torch.round(torch.sigmoid(test_logits)).squeeze()\n",
        "\n",
        "    test_loss = loss_func(test_logits, y_test)\n",
        "    test_acc = accuracy(y_test, test_pred)\n",
        "\n",
        "  if epoch%10==0:\n",
        "    print(f\"Epoch: {epoch} | Training Loss: {loss} | Testing Loss: {test_loss} | Training Accuracy: {acc}% | Testing Accuracy: {test_acc}%\")\n",
        "#results not very good still. Issue lies in fact that we are trying to code a linear model to train on nonlinear data."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PlrfzLf9pXQ3",
        "outputId": "d517e21f-f379-4423-9052-bcb72995e4f5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 0 | Training Loss: 0.6986392140388489 | Testing Loss: 0.6937922835350037 | Training Accuracy: 47.625% | Testing Accuracy: 51.5%\n",
            "Epoch: 10 | Training Loss: 0.6964757442474365 | Testing Loss: 0.6926801204681396 | Training Accuracy: 48.875% | Testing Accuracy: 51.5%\n",
            "Epoch: 20 | Training Loss: 0.6955786347389221 | Testing Loss: 0.692444920539856 | Training Accuracy: 49.375% | Testing Accuracy: 51.0%\n",
            "Epoch: 30 | Training Loss: 0.6950634717941284 | Testing Loss: 0.6924083232879639 | Training Accuracy: 49.75% | Testing Accuracy: 51.5%\n",
            "Epoch: 40 | Training Loss: 0.6946998834609985 | Testing Loss: 0.6924221515655518 | Training Accuracy: 49.625% | Testing Accuracy: 50.5%\n",
            "Epoch: 50 | Training Loss: 0.6944177746772766 | Testing Loss: 0.6924552917480469 | Training Accuracy: 50.375% | Testing Accuracy: 51.0%\n",
            "Epoch: 60 | Training Loss: 0.694190263748169 | Testing Loss: 0.6925005912780762 | Training Accuracy: 50.375% | Testing Accuracy: 50.5%\n",
            "Epoch: 70 | Training Loss: 0.6940033435821533 | Testing Loss: 0.6925556063652039 | Training Accuracy: 50.5% | Testing Accuracy: 50.0%\n",
            "Epoch: 80 | Training Loss: 0.6938484311103821 | Testing Loss: 0.6926185488700867 | Training Accuracy: 50.24999999999999% | Testing Accuracy: 50.0%\n",
            "Epoch: 90 | Training Loss: 0.6937190890312195 | Testing Loss: 0.6926875114440918 | Training Accuracy: 50.0% | Testing Accuracy: 51.0%\n",
            "Epoch: 100 | Training Loss: 0.6936103701591492 | Testing Loss: 0.6927606463432312 | Training Accuracy: 50.74999999999999% | Testing Accuracy: 50.5%\n",
            "Epoch: 110 | Training Loss: 0.6935189962387085 | Testing Loss: 0.692836582660675 | Training Accuracy: 50.625% | Testing Accuracy: 50.5%\n",
            "Epoch: 120 | Training Loss: 0.6934415698051453 | Testing Loss: 0.6929140686988831 | Training Accuracy: 50.125% | Testing Accuracy: 50.0%\n",
            "Epoch: 130 | Training Loss: 0.693375825881958 | Testing Loss: 0.6929919719696045 | Training Accuracy: 50.5% | Testing Accuracy: 52.0%\n",
            "Epoch: 140 | Training Loss: 0.693320095539093 | Testing Loss: 0.6930694580078125 | Training Accuracy: 50.0% | Testing Accuracy: 53.0%\n",
            "Epoch: 150 | Training Loss: 0.6932725310325623 | Testing Loss: 0.6931459307670593 | Training Accuracy: 50.0% | Testing Accuracy: 54.0%\n",
            "Epoch: 160 | Training Loss: 0.6932318806648254 | Testing Loss: 0.693220853805542 | Training Accuracy: 49.75% | Testing Accuracy: 54.0%\n",
            "Epoch: 170 | Training Loss: 0.6931971907615662 | Testing Loss: 0.6932938098907471 | Training Accuracy: 49.5% | Testing Accuracy: 54.50000000000001%\n",
            "Epoch: 180 | Training Loss: 0.6931674480438232 | Testing Loss: 0.6933647394180298 | Training Accuracy: 50.24999999999999% | Testing Accuracy: 53.5%\n",
            "Epoch: 190 | Training Loss: 0.6931418776512146 | Testing Loss: 0.6934332251548767 | Training Accuracy: 50.875% | Testing Accuracy: 52.5%\n",
            "Epoch: 200 | Training Loss: 0.6931199431419373 | Testing Loss: 0.6934991478919983 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 50.5%\n",
            "Epoch: 210 | Training Loss: 0.6931011080741882 | Testing Loss: 0.693562388420105 | Training Accuracy: 50.74999999999999% | Testing Accuracy: 50.5%\n",
            "Epoch: 220 | Training Loss: 0.6930848956108093 | Testing Loss: 0.6936230659484863 | Training Accuracy: 51.5% | Testing Accuracy: 48.5%\n",
            "Epoch: 230 | Training Loss: 0.6930708289146423 | Testing Loss: 0.6936811804771423 | Training Accuracy: 51.125% | Testing Accuracy: 50.5%\n",
            "Epoch: 240 | Training Loss: 0.6930588483810425 | Testing Loss: 0.6937364935874939 | Training Accuracy: 51.125% | Testing Accuracy: 48.0%\n",
            "Epoch: 250 | Training Loss: 0.6930484175682068 | Testing Loss: 0.6937891244888306 | Training Accuracy: 51.5% | Testing Accuracy: 47.0%\n",
            "Epoch: 260 | Training Loss: 0.6930394172668457 | Testing Loss: 0.6938392519950867 | Training Accuracy: 51.125% | Testing Accuracy: 49.0%\n",
            "Epoch: 270 | Training Loss: 0.6930316090583801 | Testing Loss: 0.6938868761062622 | Training Accuracy: 50.875% | Testing Accuracy: 48.0%\n",
            "Epoch: 280 | Training Loss: 0.6930249929428101 | Testing Loss: 0.6939321160316467 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 48.0%\n",
            "Epoch: 290 | Training Loss: 0.6930190920829773 | Testing Loss: 0.6939749717712402 | Training Accuracy: 51.5% | Testing Accuracy: 47.5%\n",
            "Epoch: 300 | Training Loss: 0.6930140852928162 | Testing Loss: 0.6940155029296875 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 310 | Training Loss: 0.693009614944458 | Testing Loss: 0.6940538287162781 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 47.0%\n",
            "Epoch: 320 | Training Loss: 0.6930059194564819 | Testing Loss: 0.6940901279449463 | Training Accuracy: 51.5% | Testing Accuracy: 47.0%\n",
            "Epoch: 330 | Training Loss: 0.6930025219917297 | Testing Loss: 0.6941244602203369 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 46.5%\n",
            "Epoch: 340 | Training Loss: 0.6929996609687805 | Testing Loss: 0.69415682554245 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 47.5%\n",
            "Epoch: 350 | Training Loss: 0.6929972171783447 | Testing Loss: 0.6941874027252197 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 47.5%\n",
            "Epoch: 360 | Training Loss: 0.692995011806488 | Testing Loss: 0.694216251373291 | Training Accuracy: 51.125% | Testing Accuracy: 47.5%\n",
            "Epoch: 370 | Training Loss: 0.6929931044578552 | Testing Loss: 0.6942434906959534 | Training Accuracy: 50.875% | Testing Accuracy: 47.5%\n",
            "Epoch: 380 | Training Loss: 0.6929914951324463 | Testing Loss: 0.6942691206932068 | Training Accuracy: 51.0% | Testing Accuracy: 47.0%\n",
            "Epoch: 390 | Training Loss: 0.6929899454116821 | Testing Loss: 0.6942932605743408 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 47.0%\n",
            "Epoch: 400 | Training Loss: 0.6929887533187866 | Testing Loss: 0.6943160891532898 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 47.0%\n",
            "Epoch: 410 | Training Loss: 0.6929876804351807 | Testing Loss: 0.6943375468254089 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 46.5%\n",
            "Epoch: 420 | Training Loss: 0.6929867267608643 | Testing Loss: 0.6943577527999878 | Training Accuracy: 51.125% | Testing Accuracy: 46.5%\n",
            "Epoch: 430 | Training Loss: 0.6929858922958374 | Testing Loss: 0.6943767666816711 | Training Accuracy: 51.0% | Testing Accuracy: 46.5%\n",
            "Epoch: 440 | Training Loss: 0.6929851770401001 | Testing Loss: 0.694394588470459 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 450 | Training Loss: 0.6929845213890076 | Testing Loss: 0.6944114565849304 | Training Accuracy: 51.125% | Testing Accuracy: 45.5%\n",
            "Epoch: 460 | Training Loss: 0.6929839253425598 | Testing Loss: 0.6944274306297302 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 470 | Training Loss: 0.6929834485054016 | Testing Loss: 0.6944422721862793 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 480 | Training Loss: 0.6929830312728882 | Testing Loss: 0.6944563388824463 | Training Accuracy: 51.5% | Testing Accuracy: 45.5%\n",
            "Epoch: 490 | Training Loss: 0.6929826140403748 | Testing Loss: 0.6944695115089417 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 45.5%\n",
            "Epoch: 500 | Training Loss: 0.6929823160171509 | Testing Loss: 0.6944820284843445 | Training Accuracy: 51.125% | Testing Accuracy: 45.5%\n",
            "Epoch: 510 | Training Loss: 0.692982017993927 | Testing Loss: 0.6944937109947205 | Training Accuracy: 51.125% | Testing Accuracy: 45.5%\n",
            "Epoch: 520 | Training Loss: 0.6929817199707031 | Testing Loss: 0.6945046782493591 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 46.0%\n",
            "Epoch: 530 | Training Loss: 0.6929815411567688 | Testing Loss: 0.69451504945755 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 46.0%\n",
            "Epoch: 540 | Training Loss: 0.6929813623428345 | Testing Loss: 0.6945247650146484 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 46.0%\n",
            "Epoch: 550 | Training Loss: 0.6929811835289001 | Testing Loss: 0.6945339441299438 | Training Accuracy: 51.37500000000001% | Testing Accuracy: 46.0%\n",
            "Epoch: 560 | Training Loss: 0.6929810047149658 | Testing Loss: 0.6945424675941467 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 46.0%\n",
            "Epoch: 570 | Training Loss: 0.6929808855056763 | Testing Loss: 0.694550633430481 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 580 | Training Loss: 0.6929808259010315 | Testing Loss: 0.6945582628250122 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 590 | Training Loss: 0.6929806470870972 | Testing Loss: 0.6945654153823853 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 600 | Training Loss: 0.6929805278778076 | Testing Loss: 0.6945721507072449 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 610 | Training Loss: 0.6929805278778076 | Testing Loss: 0.6945784091949463 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 620 | Training Loss: 0.6929804086685181 | Testing Loss: 0.6945844292640686 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 630 | Training Loss: 0.6929803490638733 | Testing Loss: 0.6945900917053223 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 640 | Training Loss: 0.6929803490638733 | Testing Loss: 0.6945952773094177 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 650 | Training Loss: 0.692980170249939 | Testing Loss: 0.6946002840995789 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 660 | Training Loss: 0.692980170249939 | Testing Loss: 0.6946049332618713 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 670 | Training Loss: 0.692980170249939 | Testing Loss: 0.6946092844009399 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 680 | Training Loss: 0.6929801106452942 | Testing Loss: 0.6946133971214294 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 690 | Training Loss: 0.6929800510406494 | Testing Loss: 0.6946173310279846 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 700 | Training Loss: 0.6929800510406494 | Testing Loss: 0.6946209669113159 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 45.5%\n",
            "Epoch: 710 | Training Loss: 0.6929800510406494 | Testing Loss: 0.6946244239807129 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 46.0%\n",
            "Epoch: 720 | Training Loss: 0.6929799914360046 | Testing Loss: 0.6946277022361755 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 46.0%\n",
            "Epoch: 730 | Training Loss: 0.6929800510406494 | Testing Loss: 0.6946306824684143 | Training Accuracy: 51.24999999999999% | Testing Accuracy: 46.0%\n",
            "Epoch: 740 | Training Loss: 0.6929800510406494 | Testing Loss: 0.6946334838867188 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 750 | Training Loss: 0.6929799914360046 | Testing Loss: 0.6946362257003784 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 760 | Training Loss: 0.6929799914360046 | Testing Loss: 0.694638729095459 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 770 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946411728858948 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 780 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946433186531067 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 790 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946454644203186 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 800 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946475505828857 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 810 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694649338722229 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 820 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946511268615723 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 830 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946527361869812 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 840 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946542859077454 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 850 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946558356285095 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 860 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946571469306946 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 870 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946585178375244 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 880 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946597099304199 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 890 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946607828140259 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 900 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946619153022766 | Training Accuracy: 51.125% | Testing Accuracy: 46.0%\n",
            "Epoch: 910 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946629285812378 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 920 | Training Loss: 0.6929798126220703 | Testing Loss: 0.694663941860199 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 930 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946648359298706 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 940 | Training Loss: 0.6929799914360046 | Testing Loss: 0.6946656703948975 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 950 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946665048599243 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 960 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946672201156616 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 970 | Training Loss: 0.6929798722267151 | Testing Loss: 0.6946679949760437 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 980 | Training Loss: 0.6929798126220703 | Testing Loss: 0.6946685910224915 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n",
            "Epoch: 990 | Training Loss: 0.6929798722267151 | Testing Loss: 0.694669246673584 | Training Accuracy: 51.0% | Testing Accuracy: 46.0%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "plt.subplot(1,2,1)\n",
        "plt.title(\"Train\")\n",
        "plot_decision_boundary(model_3, X_train, y_train)\n",
        "plt.subplot(1,2,2)\n",
        "plt.title('Test')\n",
        "plot_decision_boundary(model_3, X_test, y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "VucjKMKyii_h",
        "outputId": "b03410a3-1a19-42c0-f6f2-ceeb6e288523"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#we should use a non-linear activation function since our input data is nonlinear: ReLU!\n",
        "# import torch\n",
        "# from torch import nn\n",
        "# import numpy as np\n",
        "# import pandas as pd\n",
        "device = 'cuda:0' if torch.cuda.is_available() else 'cpu'\n",
        "class ToyCircleClassificationModelV2(nn.Module):\n",
        "  def __init__(self):\n",
        "    super().__init__()\n",
        "    self.layer1=nn.Linear(in_features=2, out_features=5)\n",
        "    self.layer2=nn.Linear(in_features=5, out_features=5)\n",
        "    self.layer3=nn.Linear(in_features=5, out_features=1)\n",
        "    self.relu=nn.ReLU()\n",
        "\n",
        "  def forward(self, x: torch.Tensor) -> torch.Tensor:\n",
        "    return self.layer3(self.relu(self.layer2(self.relu(self.layer1(x))))) #outputs of each layer passed to relu activation\n",
        "\n",
        "model_4=ToyCircleClassificationModelV2().to(device)\n",
        "model_4"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6evtaMmoRfNt",
        "outputId": "179307e2-4f7f-4f9f-b34d-5446e8cf43c3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ToyCircleClassificationModelV2(\n",
              "  (layer1): Linear(in_features=2, out_features=5, bias=True)\n",
              "  (layer2): Linear(in_features=5, out_features=5, bias=True)\n",
              "  (layer3): Linear(in_features=5, out_features=1, bias=True)\n",
              "  (relu): ReLU()\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "loss_func = nn.BCEWithLogitsLoss()\n",
        "optimizer = torch.optim.SGD(params=model_4.parameters(), lr=0.1)"
      ],
      "metadata": {
        "id": "yqwx60CkVOAW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "torch.manual_seed(42)\n",
        "\n",
        "epochs=10000\n",
        "for epoch in range(epochs):\n",
        "  model_4.train()\n",
        "\n",
        "  y_logits=model_4(X_train).squeeze()\n",
        "  y_preds=torch.round(torch.sigmoid(y_logits))\n",
        "\n",
        "  loss=loss_func(y_logits, y_train)\n",
        "\n",
        "  acc=accuracy(y_train, y_preds)\n",
        "\n",
        "  optimizer.zero_grad()\n",
        "\n",
        "  loss.backward()\n",
        "\n",
        "  optimizer.step()\n",
        "\n",
        "  model_4.eval()\n",
        "\n",
        "  with torch.inference_mode():\n",
        "    test_logits = model_4(X_test).squeeze()\n",
        "    test_pred = torch.round(torch.sigmoid(test_logits)).squeeze()\n",
        "\n",
        "    test_loss = loss_func(test_logits, y_test)\n",
        "    test_acc = accuracy(y_test, test_pred)\n",
        "\n",
        "  if epoch%100==0:\n",
        "    print(f\"Epoch: {epoch} | Training Loss: {loss} | Testing Loss: {test_loss} | Training Accuracy: {acc}% | Testing Accuracy: {test_acc}%\")\n",
        "#significant improvement!"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "38yRjLiZTzMF",
        "outputId": "77010764-82bf-4a52-d95f-c5b7d4f0991b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 0 | Training Loss: 0.7214900255203247 | Testing Loss: 0.7180036306381226 | Training Accuracy: 50.0% | Testing Accuracy: 50.0%\n",
            "Epoch: 100 | Training Loss: 0.6903275847434998 | Testing Loss: 0.6919379234313965 | Training Accuracy: 56.125% | Testing Accuracy: 55.00000000000001%\n",
            "Epoch: 200 | Training Loss: 0.6886691451072693 | Testing Loss: 0.6899645924568176 | Training Accuracy: 56.875% | Testing Accuracy: 56.49999999999999%\n",
            "Epoch: 300 | Training Loss: 0.6865138411521912 | Testing Loss: 0.6874092221260071 | Training Accuracy: 57.375% | Testing Accuracy: 59.5%\n",
            "Epoch: 400 | Training Loss: 0.6833891868591309 | Testing Loss: 0.6835718750953674 | Training Accuracy: 57.875% | Testing Accuracy: 59.5%\n",
            "Epoch: 500 | Training Loss: 0.6790879964828491 | Testing Loss: 0.6782599091529846 | Training Accuracy: 57.125% | Testing Accuracy: 60.0%\n",
            "Epoch: 600 | Training Loss: 0.6734306812286377 | Testing Loss: 0.6712139844894409 | Training Accuracy: 57.25% | Testing Accuracy: 60.0%\n",
            "Epoch: 700 | Training Loss: 0.6662245392799377 | Testing Loss: 0.6620245575904846 | Training Accuracy: 57.49999999999999% | Testing Accuracy: 62.0%\n",
            "Epoch: 800 | Training Loss: 0.6562811136245728 | Testing Loss: 0.6502735614776611 | Training Accuracy: 59.25% | Testing Accuracy: 65.5%\n",
            "Epoch: 900 | Training Loss: 0.638751745223999 | Testing Loss: 0.6325225830078125 | Training Accuracy: 62.25000000000001% | Testing Accuracy: 68.0%\n",
            "Epoch: 1000 | Training Loss: 0.5998563170433044 | Testing Loss: 0.5946660041809082 | Training Accuracy: 74.75% | Testing Accuracy: 80.5%\n",
            "Epoch: 1100 | Training Loss: 0.5286612510681152 | Testing Loss: 0.5334718227386475 | Training Accuracy: 85.5% | Testing Accuracy: 84.5%\n",
            "Epoch: 1200 | Training Loss: 0.444889098405838 | Testing Loss: 0.4538913667201996 | Training Accuracy: 87.5% | Testing Accuracy: 85.5%\n",
            "Epoch: 1300 | Training Loss: 0.40695881843566895 | Testing Loss: 0.4693610668182373 | Training Accuracy: 79.75% | Testing Accuracy: 79.0%\n",
            "Epoch: 1400 | Training Loss: 0.4132532477378845 | Testing Loss: 0.45846137404441833 | Training Accuracy: 76.0% | Testing Accuracy: 77.0%\n",
            "Epoch: 1500 | Training Loss: 0.4195749759674072 | Testing Loss: 0.4736948311328888 | Training Accuracy: 75.5% | Testing Accuracy: 74.5%\n",
            "Epoch: 1600 | Training Loss: 0.4050354063510895 | Testing Loss: 0.47409531474113464 | Training Accuracy: 75.875% | Testing Accuracy: 73.0%\n",
            "Epoch: 1700 | Training Loss: 0.3667833209037781 | Testing Loss: 0.44958609342575073 | Training Accuracy: 78.875% | Testing Accuracy: 74.5%\n",
            "Epoch: 1800 | Training Loss: 0.20886482298374176 | Testing Loss: 0.271636962890625 | Training Accuracy: 93.625% | Testing Accuracy: 89.5%\n",
            "Epoch: 1900 | Training Loss: 0.12220492213964462 | Testing Loss: 0.1609850823879242 | Training Accuracy: 98.25% | Testing Accuracy: 95.5%\n",
            "Epoch: 2000 | Training Loss: 0.22689460217952728 | Testing Loss: 0.2993292510509491 | Training Accuracy: 89.125% | Testing Accuracy: 85.0%\n",
            "Epoch: 2100 | Training Loss: 0.09618453681468964 | Testing Loss: 0.1381394863128662 | Training Accuracy: 98.25% | Testing Accuracy: 95.0%\n",
            "Epoch: 2200 | Training Loss: 0.07970625162124634 | Testing Loss: 0.1192583441734314 | Training Accuracy: 98.625% | Testing Accuracy: 95.5%\n",
            "Epoch: 2300 | Training Loss: 0.06707644462585449 | Testing Loss: 0.10860340297222137 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 2400 | Training Loss: 0.05945603549480438 | Testing Loss: 0.10173910111188889 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 2500 | Training Loss: 0.05357847735285759 | Testing Loss: 0.09765049070119858 | Training Accuracy: 98.875% | Testing Accuracy: 97.0%\n",
            "Epoch: 2600 | Training Loss: 0.049181848764419556 | Testing Loss: 0.09374409914016724 | Training Accuracy: 98.75% | Testing Accuracy: 97.0%\n",
            "Epoch: 2700 | Training Loss: 0.045752059668302536 | Testing Loss: 0.08963240683078766 | Training Accuracy: 98.625% | Testing Accuracy: 96.0%\n",
            "Epoch: 2800 | Training Loss: 0.043058160692453384 | Testing Loss: 0.08616577088832855 | Training Accuracy: 98.75% | Testing Accuracy: 96.0%\n",
            "Epoch: 2900 | Training Loss: 0.04091441631317139 | Testing Loss: 0.08397538959980011 | Training Accuracy: 98.75% | Testing Accuracy: 96.0%\n",
            "Epoch: 3000 | Training Loss: 0.039137836545705795 | Testing Loss: 0.08223844319581985 | Training Accuracy: 98.75% | Testing Accuracy: 96.0%\n",
            "Epoch: 3100 | Training Loss: 0.03763685002923012 | Testing Loss: 0.08080509305000305 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 3200 | Training Loss: 0.036350689828395844 | Testing Loss: 0.07961146533489227 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 3300 | Training Loss: 0.03523619472980499 | Testing Loss: 0.07861471176147461 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 3400 | Training Loss: 0.034261468797922134 | Testing Loss: 0.0777796059846878 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 3500 | Training Loss: 0.03340226411819458 | Testing Loss: 0.0770801529288292 | Training Accuracy: 98.875% | Testing Accuracy: 95.5%\n",
            "Epoch: 3600 | Training Loss: 0.03263964504003525 | Testing Loss: 0.07649436593055725 | Training Accuracy: 98.875% | Testing Accuracy: 95.5%\n",
            "Epoch: 3700 | Training Loss: 0.03195866942405701 | Testing Loss: 0.07600552588701248 | Training Accuracy: 98.875% | Testing Accuracy: 95.5%\n",
            "Epoch: 3800 | Training Loss: 0.03134729340672493 | Testing Loss: 0.07559812068939209 | Training Accuracy: 98.875% | Testing Accuracy: 95.5%\n",
            "Epoch: 3900 | Training Loss: 0.030795684084296227 | Testing Loss: 0.07526156306266785 | Training Accuracy: 98.875% | Testing Accuracy: 95.5%\n",
            "Epoch: 4000 | Training Loss: 0.030295811593532562 | Testing Loss: 0.07498488575220108 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4100 | Training Loss: 0.029840998351573944 | Testing Loss: 0.0747607871890068 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4200 | Training Loss: 0.029425662010908127 | Testing Loss: 0.07458179444074631 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4300 | Training Loss: 0.029045043513178825 | Testing Loss: 0.0744432657957077 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4400 | Training Loss: 0.02869522012770176 | Testing Loss: 0.07433944195508957 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4500 | Training Loss: 0.02837268076837063 | Testing Loss: 0.07426650077104568 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4600 | Training Loss: 0.028074564412236214 | Testing Loss: 0.07422087341547012 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4700 | Training Loss: 0.02779828943312168 | Testing Loss: 0.07419957965612411 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4800 | Training Loss: 0.027541695162653923 | Testing Loss: 0.07419989258050919 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 4900 | Training Loss: 0.027302835136651993 | Testing Loss: 0.07421938329935074 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5000 | Training Loss: 0.02708004042506218 | Testing Loss: 0.0742560401558876 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5100 | Training Loss: 0.026871835812926292 | Testing Loss: 0.07430825382471085 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5200 | Training Loss: 0.026676930487155914 | Testing Loss: 0.07437395304441452 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5300 | Training Loss: 0.026494119316339493 | Testing Loss: 0.07445249706506729 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5400 | Training Loss: 0.02632242627441883 | Testing Loss: 0.07454181462526321 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5500 | Training Loss: 0.026160890236496925 | Testing Loss: 0.07464151084423065 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5600 | Training Loss: 0.02600873075425625 | Testing Loss: 0.07474993169307709 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5700 | Training Loss: 0.02586514875292778 | Testing Loss: 0.0748656764626503 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5800 | Training Loss: 0.02572956308722496 | Testing Loss: 0.07498642802238464 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 5900 | Training Loss: 0.025601372122764587 | Testing Loss: 0.07510153949260712 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 6000 | Training Loss: 0.025480516254901886 | Testing Loss: 0.0751369297504425 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 6100 | Training Loss: 0.025404302403330803 | Testing Loss: 0.07444718480110168 | Training Accuracy: 98.875% | Testing Accuracy: 96.0%\n",
            "Epoch: 6200 | Training Loss: 0.03837757557630539 | Testing Loss: 0.07981733977794647 | Training Accuracy: 98.25% | Testing Accuracy: 96.0%\n",
            "Epoch: 6300 | Training Loss: 0.2166132777929306 | Testing Loss: 0.25633156299591064 | Training Accuracy: 98.375% | Testing Accuracy: 96.0%\n",
            "Epoch: 6400 | Training Loss: 0.16009922325611115 | Testing Loss: 0.21001626551151276 | Training Accuracy: 98.625% | Testing Accuracy: 95.5%\n",
            "Epoch: 6500 | Training Loss: 0.12467323243618011 | Testing Loss: 0.17320138216018677 | Training Accuracy: 99.125% | Testing Accuracy: 95.0%\n",
            "Epoch: 6600 | Training Loss: 0.10116872191429138 | Testing Loss: 0.14645762741565704 | Training Accuracy: 98.875% | Testing Accuracy: 95.5%\n",
            "Epoch: 6700 | Training Loss: 0.08496502041816711 | Testing Loss: 0.12518948316574097 | Training Accuracy: 99.0% | Testing Accuracy: 95.5%\n",
            "Epoch: 6800 | Training Loss: 0.07494641840457916 | Testing Loss: 0.11331091076135635 | Training Accuracy: 99.0% | Testing Accuracy: 96.5%\n",
            "Epoch: 6900 | Training Loss: 0.06758865714073181 | Testing Loss: 0.10393085330724716 | Training Accuracy: 98.875% | Testing Accuracy: 97.0%\n",
            "Epoch: 7000 | Training Loss: 0.061954155564308167 | Testing Loss: 0.09759405255317688 | Training Accuracy: 98.875% | Testing Accuracy: 97.0%\n",
            "Epoch: 7100 | Training Loss: 0.057480841875076294 | Testing Loss: 0.09246479719877243 | Training Accuracy: 98.875% | Testing Accuracy: 97.0%\n",
            "Epoch: 7200 | Training Loss: 0.05384184420108795 | Testing Loss: 0.08872959762811661 | Training Accuracy: 98.75% | Testing Accuracy: 97.0%\n",
            "Epoch: 7300 | Training Loss: 0.05082312598824501 | Testing Loss: 0.08564247190952301 | Training Accuracy: 98.75% | Testing Accuracy: 97.0%\n",
            "Epoch: 7400 | Training Loss: 0.04828059673309326 | Testing Loss: 0.0830305740237236 | Training Accuracy: 98.75% | Testing Accuracy: 97.0%\n",
            "Epoch: 7500 | Training Loss: 0.04611564055085182 | Testing Loss: 0.08098987489938736 | Training Accuracy: 98.75% | Testing Accuracy: 97.0%\n",
            "Epoch: 7600 | Training Loss: 0.044248007237911224 | Testing Loss: 0.07881750166416168 | Training Accuracy: 98.75% | Testing Accuracy: 97.5%\n",
            "Epoch: 7700 | Training Loss: 0.04262648522853851 | Testing Loss: 0.07721202075481415 | Training Accuracy: 98.75% | Testing Accuracy: 97.5%\n",
            "Epoch: 7800 | Training Loss: 0.041203614324331284 | Testing Loss: 0.07584618031978607 | Training Accuracy: 98.75% | Testing Accuracy: 97.5%\n",
            "Epoch: 7900 | Training Loss: 0.03994574025273323 | Testing Loss: 0.07471528649330139 | Training Accuracy: 98.75% | Testing Accuracy: 97.5%\n",
            "Epoch: 8000 | Training Loss: 0.038826312869787216 | Testing Loss: 0.07379333674907684 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 8100 | Training Loss: 0.03782431781291962 | Testing Loss: 0.07270815223455429 | Training Accuracy: 98.75% | Testing Accuracy: 97.5%\n",
            "Epoch: 8200 | Training Loss: 0.03692568466067314 | Testing Loss: 0.07190340757369995 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 8300 | Training Loss: 0.036114245653152466 | Testing Loss: 0.07117965072393417 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 8400 | Training Loss: 0.03537698835134506 | Testing Loss: 0.0706968829035759 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 8500 | Training Loss: 0.03470570966601372 | Testing Loss: 0.07014254480600357 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 8600 | Training Loss: 0.034091316163539886 | Testing Loss: 0.06972506642341614 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 8700 | Training Loss: 0.03352603316307068 | Testing Loss: 0.0693286657333374 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 8800 | Training Loss: 0.033004578202962875 | Testing Loss: 0.06896450370550156 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 8900 | Training Loss: 0.03252340853214264 | Testing Loss: 0.06860623508691788 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9000 | Training Loss: 0.0320780985057354 | Testing Loss: 0.06840618699789047 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9100 | Training Loss: 0.03166463226079941 | Testing Loss: 0.06816177070140839 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9200 | Training Loss: 0.031279634684324265 | Testing Loss: 0.06796661764383316 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9300 | Training Loss: 0.0309198759496212 | Testing Loss: 0.06783052533864975 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9400 | Training Loss: 0.03058324009180069 | Testing Loss: 0.06765037775039673 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9500 | Training Loss: 0.030268101021647453 | Testing Loss: 0.06752718240022659 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9600 | Training Loss: 0.029972145333886147 | Testing Loss: 0.06742845475673676 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9700 | Training Loss: 0.02969346195459366 | Testing Loss: 0.06735718995332718 | Training Accuracy: 98.875% | Testing Accuracy: 97.5%\n",
            "Epoch: 9800 | Training Loss: 0.029431186616420746 | Testing Loss: 0.06729946285486221 | Training Accuracy: 98.875% | Testing Accuracy: 97.0%\n",
            "Epoch: 9900 | Training Loss: 0.02918406017124653 | Testing Loss: 0.06720712035894394 | Training Accuracy: 98.875% | Testing Accuracy: 97.0%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "plt.subplot(1,2,1)\n",
        "plt.title(\"Train\")\n",
        "plot_decision_boundary(model_4, X_train, y_train)\n",
        "plt.subplot(1,2,2)\n",
        "plt.title('Test')\n",
        "plot_decision_boundary(model_4, X_test, y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "sYXyL1uBe2SN",
        "outputId": "58553c67-f5c0-493b-b441-7b797f4957cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}