SpotMicroESP32-Leika/simulation/notebooks/training_and_converting.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.onnx\n",
    "import onnx\n",
    "import onnxruntime as ort\n",
    "from onnx_tf.backend import prepare\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2 * np.pi, 1000, dtype=np.float32)\n",
    "y = np.sin(x)\n",
    "\n",
    "x_train = torch.tensor(x, dtype=torch.float32).view(-1, 1)\n",
    "y_train = torch.tensor(y, dtype=torch.float32).view(-1, 1)\n",
    "\n",
    "model = nn.Sequential(\n",
    "    nn.Linear(1, 16),\n",
    "    nn.ReLU(),\n",
    "    nn.Linear(16, 1)\n",
    ")\n",
    "\n",
    "criterion = nn.MSELoss()\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "for epoch in range(1000):\n",
    "    optimizer.zero_grad()\n",
    "    output = model(x_train)\n",
    "    loss = criterion(output, y_train)\n",
    "    loss.backward()\n",
    "    optimizer.step()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "with torch.no_grad():\n",
    "    y_pred = model(x_train).numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_pred(x, y, y_pred):\n",
    "    plt.plot(x, y, label='True')\n",
    "    plt.plot(x, y_pred, label='Predicted')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "plot_pred(x, y, y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert model to ONNX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_size = (1, 1)\n",
    "batch_size = 1\n",
    "channels = 1\n",
    "\n",
    "def convert_torch_to_onnx(model, onnx_model_path = 'model.onnx'):\n",
    "\n",
    "    dummy_input = torch.tensor(np.linspace(0, 2 * np.pi, 1, dtype=np.float32).reshape(-1, 1))\n",
    "\n",
    "\n",
    "    sample_input = torch.rand((batch_size, channels, *data_size))\n",
    "    torch.onnx.export(\n",
    "        model,\n",
    "        dummy_input, \n",
    "        onnx_model_path,\n",
    "        verbose=False,\n",
    "        input_names=['input'],\n",
    "        output_names=['output'],\n",
    "        opset_version=12\n",
    "    )\n",
    "\n",
    "onnx_model_path = 'model.onnx'\n",
    "convert_torch_to_onnx(model, onnx_model_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RaM4m8G+q9sJa9DL82ludmPCKVjU8mT+oFY62BjafuMDrv+6j0GTWLrcQwuIGDBiATqdDp9Nha2tL7dq1+eCDDygstOwo7l9//cWHH354W/ver6KkNEmBIzSVnp3PpGnf83XW2/xi+wlNTIfVUY6QgfDaXugxBSrV0jpm6fFtcGU0590rozkr4ftQiPq1aDQnpJonP/Rrga1Bz6rDybz9xwF5hFyIcq5r164kJiZy4sQJRo8ezXvvvccXX3xx3X75+fml9jM9PT1xcXEptfNZGylwhDYUhbxDSzn/TRs+yn6fEP0JFIMdtHoZRuyHxyaCRzWtU1qGwaj2w3p5EwQ0U0dzFr9SbDSnbW0vvnu+GQa9jr/2neOj5dEahxZCWJKdnR1+fn5Uq1aNoUOHEh4ezpIlS4ouK3388ccEBARQr149AOLj43n22Wdxd3fH09OTHj16cPr06aLzmUwmRo0ahbu7O5UqVeLtt9/mfxsX/O8lqry8PN555x0CAwOxs7Ojdu3azJo1i9OnT9OpUycAPDw80Ol0DBgwAACz2cyECROoUaMGDg4OBAcH88cffxT7OStWrKBu3bo4ODjQqVOnYjktSQoccf+YzZCwD6J+RZnWDrs/+lK78ASXseNik8HoRh6A7p+DW2Wtk94fvg1g0FroPA4MtteN5jzc0I+vnlFvpJ69NZZ5205rm1eIskRRID9bm6UUOiA5ODgUjdZERERw7Ngx1qxZw7JlyygoKKBLly64uLiwefNmtm7dirOzM127di065quvvmLu3LnMnj2bLVu2kJqayqJFi0r8mf369ePXX39l0qRJREdHM336dJydnQkMDOTPP/8E4NixYyQmJvLtt98CMGHCBObPn8+0adM4fPgwb7zxBn379mXjxo2AWog9+eSTPPbYY0RFRfHSSy8xZsyYe/58bofMgyPuD7MJfnoKTq0HQAdkKfb8rHQh9Pl3aRpUR9t8WjEYof1oqNsN/n5VLQAXvwKHF8Fj39KzWWXOpV3mi1XHeH/pYap4ONC5/o27lgsh/qUgBz4J0OZn/ycBbJ3u6lBFUYiIiGDVqlW89tprnD9/HicnJ2bOnImtrS0AP/30E2azmZkzZxY1G54zZw7u7u5s2LCBhx9+mIkTJzJ27FiefPJJAKZNm8aqVatu+nOPHz/Ob7/9xpo1awgPDwegZs2aRds9PT0B8PHxwd3dHVBHfD755BPWrl1LWFhY0TFbtmxh+vTpdOjQgalTp1KrVi2++uorAOrVq8fBgwf57LPP7urzuRMygiPuj4O/FxU3F9wa8W3hk7TL+5aApz6tuMXNv/3vaM6JVVdGc37h1Q416d0yELMCw3/Zx6Fz6VqnFUKUsmXLluHs7Iy9vT3dunWjV69evPfeewA0bty4qLgB2L9/PzExMbi4uODs7IyzszOenp7k5uZy8uRJ0tPTSUxMJDQ0tOgYo9FIixYtbvrzo6KiMBgMdOjQ4bYzx8TEkJOTw0MPPVSUw9nZmfnz53Py5EkAoqOji+UAioohS5MRHGF5pgLY8CkAsU3fJHxnCCazwuiH6vJYsEa/YVmjq6M59brD4lchYS8sHoru8GI+7P4159Ius/nEBV6cu4slw9vh5yYdk4W4KRtHdSRFq599hzp16sTUqVOxtbUlICAAo/Ha17OTU/HRoKysLEJCQvj555+vO4+3t/ed50W9JHansrKyAFi+fDmVKxe/tcDOzu6ucpQmKXCE5e3/FS7FYnKoRK+oJpjMCk82q8zwB2trncw6+dSHQWtg2yTYMAFOrMJmWhtmdP6InunVOJaSxSs/7WHhy62lpYMQN6PT3fVlIi04OTlRu/bt/T+xefPmLFy4EB8fH1xdXW+4j7+/Pzt27OCBBx4AoLCwkD179tC8efMb7t+4cWPMZjMbN24sukT1b1dHkEyma3NzNWjQADs7O+Li4m468lO/fn2WLFlSbN327dtv/SZLgVyiEpZVmA8b1UcdfzD3ICXXSItqHkx4qnHRtWNxAwYjtB8FL2+GgOaQl47DitdY7PEtdewziIpP470lh7VOKYTQQJ8+ffDy8qJHjx5s3ryZ2NhYNmzYwOuvv87Zs2cBGDFiBJ9++imLFy/m6NGjvPrqqyXOYVO9enX69+/Piy++yOLFi4vO+dtvvwFQrVo1dDody5Yt4/z582RlZeHi4sKbb77JG2+8wbx58zh58iR79+5l8uTJzJs3D4BXXnmFEydO8NZbb3Hs2DF++eUX5s6da+mPCJACR1javvmQHkeaoRLfpD+Aj4sd3/eVZpK3zSdIHc0Jfw8MtjicieAfm7d4xrCRX3fG8cuOOK0TCiHuM0dHRzZt2kTVqlV58sknqV+/PoMGDSI3N7doRGf06NG88MIL9O/fn7CwMFxcXHjiiSdKPO/UqVN5+umnefXVVwkKCmLw4MFkZ2cDULlyZd5//33GjBmDr68vw4cPB+DDDz/k3XffZcKECdSvX5+uXbuyfPlyatSoAUDVqlX5888/Wbx4McHBwUybNo1PPvnEgp/ONTrlfx+MrwAyMjJwc3MjPT39psN7ohQU5MKkZpCZwLiC/vyidGXhy60JqeapdbKyKeWo+qTVuT0ArDM1ZZx5MN8OeYSQah4ahxNCW7m5ucTGxlKjRg3s7eX+tLKspL/LO/n+lhEcYTl75kBmAomKJwtMD/Luow2kuLkXPkHw4moIfw/FYMuDhihWGN9ixfwvuJiZq3U6IYSwKlLgCMvIz8G8SZ33YHLhEzzSrDr9wsrpzMT3k8EI7d5A9/JmTP7NcdXl8K5pCmenPIo57azW6YQQwmpIgSMswrzzB/Q554k3e7PPszufPCE3FZcqnyAML60hOfQ/5Ck2BOfuonByKOz9sVRmURVCiLJOChxR+vIyyd/4NQDfK0/xTZ9WONjKTcWlzmDEt9s7rH7gd/aZa2NryoIlw+HnpyH9nNbphBBCU1LgiFKXvGYS9gVpnDL70bDbEIL85EZuS3r0wY7MqjuNTwqeIw8biFkL34dBQpTW0YQQQjNS4IhSlZ2eisPu7wFY7zeQPmE1b3GEuFc6nY5Pnm7KP27P0j3vE87Y14O8dFj6ulyuEhVOBXwwuNwprb9DKXBEqdr60/u4ksUpXSBP9Rsh993cJ672Nkzq3YzTuio8kfYGJoM9JO6HUxu0jibEfWFjYwNATk6OxknEvbr6d3j17/RuSasGUWrW7TtK65SFoANT+3dwd77z3ibi7jWr6sGwjrWYtC6GhaZOPM8/sHUi1OqkdTQhLM5gMODu7k5KSgqgToYnv2CVLYqikJOTQ0pKCu7u7hgM93bv5n0pcKZMmcIXX3xBUlISwcHBTJ48mVatWt1w344dO7Jx48br1nfv3p3ly5cDMGDAgKJpoK/q0qULK1euLP3w4rakZudzesmnPKi7TLJjbep07KN1pArptc51WH/sPN8ndKWX3SoMpzZAwj4IaKZ1NCEszs/PD6CoyBFlk7u7e9Hf5b2weIGzcOFCRo0axbRp0wgNDWXixIl06dKFY8eO4ePjc93+f/31F/n5+UV/vnjxIsHBwTzzzDPF9uvatStz5swp+rM1dC6tyD77cwvjzCtABx7d3wO9XP3Ugo1Bzze9gnlkUiZLTa3padgGW7+FZ+ZqHU0Ii9PpdPj7++Pj40NBQYHWccRdsLGxueeRm6ssXuB8/fXXDB48mIEDBwIwbdo0li9fzuzZsxkzZsx1+3t6Fp/pdsGCBTg6Ol5X4NjZ2ZVKhSfu3dL9CdQ6PhMnYx45Xk1wbPio1pEqtNo+LrzTNYjpyx+jp2EbypG/0aWeAk+54VtUDAaDodS+JEXZZdFfs/Pz89mzZ0+x1ut6vZ7w8HAiIyNv6xyzZs2id+/eODkVb3u/YcMGfHx8qFevHkOHDuXixYulml3cnpTMXL5dvJl+htUAOHYZB3LdW3MD2lTHo2ZzNpiC0SlmlG3faR1JCCHuK4sWOBcuXMBkMuHr61tsva+vL0lJSbc8fufOnRw6dIiXXnqp2PquXbsyf/58IiIi+Oyzz9i4cSPdunXDZDLd8Dx5eXlkZGQUW8S9UxSF//x1iD4Ff2KvK8BcpSXUDr/1gcLi9Hodnz/dhDm6HgCY9v4EWec1TiWEEPePVd8oMWvWLBo3bnzdDcm9e/fm8ccfp3HjxvTs2ZNly5axa9cuNmzYcMPzTJgwATc3t6IlMDDwPqQv/1YcTOJw9BH6GCIA0D/4Xxm9sSJVPBzp9PATRJlrYTTnkblJRnGEEBWHRQscLy8vDAYDycnJxdYnJyff8v6Z7OxsFixYwKBBg275c2rWrImXlxcxMTE33D527FjS09OLlvj4+Nt/E+KG0nMKGL/kMMONi7HVFUK1dlCjg9axxP94oU0NVns8B4B+90yUXBm9FEJUDBYtcGxtbQkJCSEiIqJondlsJiIigrCwsBKP/f3338nLy6Nv3763/Dlnz57l4sWL+Pv733C7nZ0drq6uxRZxbz5dGY19djy9jBvUFZ3+I6M3Vsig1/Hkc4M5pfjjZM7i8LLJWkcSQoj7wuKXqEaNGsUPP/zAvHnziI6OZujQoWRnZxc9VdWvXz/Gjh173XGzZs2iZ8+eVKpUqdj6rKws3nrrLbZv387p06eJiIigR48e1K5dmy5dulj67Qhg+6mL/LozntcNizBigpodoXpbrWOJm6jt505sXXUk1PvQTC6mZ2qcSAghLM/iBU6vXr348ssvGTduHE2bNiUqKoqVK1cW3XgcFxdHYmJisWOOHTvGli1bbnh5ymAwcODAAR5//HHq1q3LoEGDCAkJYfPmzTIXzn2QW2DiP4sOUl2XyFPGLerKTv/VNpS4pfZPDeeizhNfUlm9QO7FEUKUfzqlAnYmy8jIwM3NjfT0dLlcdYe+Xn2MSeti+N5hGt2VTVDnYejzu9axxG1IWP4pAbsmcMJcmYv9N9K6lrfWkYQQ4o7cyfe3VT9FJazLieRMpm48SS3dObopm9WVnf6jbShx2wI6DyVX70Qd/TlW/DGHApNZ60hCCGExUuCI26IoCu/+fYgCk8IEj2XoUCDoUelxVJbYu6Fr8SIAj2f/zuwtsRoHEkIIy5ECR9yWZQcS2X4qlSbGeFrlXGmG2vH6m8OFdbNrPxyT3oYW+uNsWruUhLTLWkcSQgiLkAJH3FJ2XiEfL48G4Guff9SVDZ8Av0YaphJ3xcUPfbA6L85AFvPB0iMaBxJCCMuQAkfc0uR1MSRl5NLZPYHaqRtAp5fRmzJM13YECjrCDfs4eWQ364+maB1JCCFKnRQ4okQnz2cxa8spAD7zWKqubPwMeNfTMJW4J1610dVXO76/bFzG+CWHyS24cR83IYQoq6TAETelKArvLTlMgUnhpern8UrcCDoDdHhH62jiXrV9A4Cehq0UpMYzS244FkKUM1LgiJtadTiJzScuYGvQM9rmD3Vl0+egUi1tg4l7VyUEqrfHiIlBxhVMWR9DSkau1qmEEKLUSIEjbii3wMSHy9Qbiz9omoZD/GbQ28ADb2ucTJSatiMB6GNcj01+Op+vOqZtHiGEKEVS4Igbmr01lnNpl/F3teOZjPnqyuYvgEc1bYOJ0lO7M/g2xoFcXjCs4Y89ZzlwNk3rVEIIUSqkwBHXOZ+Zx/frTwLwRcglDPHbwGAL7UdrnEyUKp0O2o4A4GX7NdiRzwdLj1ABu7cIIcohKXDEdb5ec5ysvEKaVHalbdx0dWXIQHCrom0wUfoaPgFuVXExpdHHdhO7z1xi6YHEWx8nhBBWTgocUczRpAwW7ooD4IumKejO7QKjPbQfpXEyYREGI7QZDsAIx1UYMPHpimgu58tj40KIsk0KHFFEURQ+Xh6NWYFuDX2pd2SSuqHlS+Dip204YTnN+oKDJ2655+jjso+E9Fx+2HxK61RCCHFPpMARRTYcP1/0WPj7QWcgMQpsnKDdG1pHE5Zk6wShLwMw2vEfQGH6xpOcz8zTNpcQQtwDKXAEAIUmc1G/qQFtquKz+2t1Q+jL4OSlYTJxX7QaAjaOuKVH088nlux8E5MiTmidSggh7poUOAKAX3fFE5OShYejDSMCoiH5ENi5QpvXtI4m7gdHT2jeD4BRjisA+HVnHKfOZ2mZSggh7poUOIKsvEImrjkOwKjwWjht/Vzd0PpV9YtPVAxhw0BnwD1pGwNrpFFoVvhCJv8TQpRRUuAIZm4+xcXsfGp4OfGc4y64cAzs3SHsVa2jifvJvSo0fhqANxxWoNfBP4eS2Bt3SeNgQghx56TAqeAuZOXxwyb1iZm3wmth3HRl9KbNa2DvpmEyoYkrE/+5xq7g5UbqqgkromXyPyFEmSMFTgX33boYsvNNNK7sRjfzBkg9CY6VIPQVraMJLfg2hDoPg2JmuP1K7G307Dp9ibXRKVonE0KIOyIFTgUWn5rDzzvOADDmoZroro7etB0Jds7aBRPautKE0+nIQl5r6QrAp/9EU2gyaxhKCCHujBQ4Fdg3a45TYFJoV9uLtlkrIS0OnHzUif1ExVWtDVRpCaY8XrJbjYejDSfPZ/P7nrNaJxNCiNsmBU4FFZ2YwaKocwC8E14NNn2pbmg/CmwdNUwmNPevJpx2e+cw6gF/ACZFnCC3QFo4CCHKBilwKqgvVx1DUeCRxv40Tv4bMs6BS4DaVFOIeo9ApTqQl05vQwT+bvYkpufy8444rZMJIcRtkQKnAtp1OpWIoykY9Dre7BQIm79SNzwwGmzstQ0nrINeD21fB8Bm5zRGdqwGwPfrY8jOK9QymRBC3BYpcCoYRVH4fOVRAHq1DKTG6QWQlQxuVaFZP43TCavSpBe4+ENmIk/ZRlKtkiMXs/OZu+201smEEOKWpMCpYDaduMCu05ewM+oZ2T4AtkxUN3R4C4y2mmYTVsZoB62Hqi8jJ/FG59oATN94kvTLBVomE0KIW5ICpwJRFIWvr7RkeKF1NXyi50HOBfCoAcHPaZxOWKWQgWDnBheO85jDfur4OJORW8jMzae0TiaEECWSAqcCWX8shf3xaTjYGBga5gPbJqkbOo4Bg4224YR1sneFli8CYNj6LaMfqgPA7C2xXMzK0zKZEEKU6L4UOFOmTKF69erY29sTGhrKzp07b7rv3Llz0el0xRZ7++I3viqKwrhx4/D398fBwYHw8HBOnDhh6bdRpv179KZ/m+pUOjgLLl8Cr7rQ+BmN0wmrFjoUDHZwdiddXGJpVNmV7HwT0zae1DqZEELclMULnIULFzJq1CjGjx/P3r17CQ4OpkuXLqSk3Hzqd1dXVxITE4uWM2fOFNv++eefM2nSJKZNm8aOHTtwcnKiS5cu5ObmWvrtlFmrjyRz6FwGTrYGXm7lCZFT1A0dx4DeoG04Yd1cfKGpeglTt/VbRj9cD4D5kWdIzpD/5oQQ1sniBc7XX3/N4MGDGThwIA0aNGDatGk4Ojoye/bsmx6j0+nw8/MrWnx9fYu2KYrCxIkT+e9//0uPHj1o0qQJ8+fPJyEhgcWLF1v67ZRJZrPCN1dGbwa2rYFH1HTISwefhtDgCY3TiTKhzeuADk6soqP7eVpU8yCv0MzkdTJyKoSwThYtcPLz89mzZw/h4eHXfqBeT3h4OJGRkTc9Lisri2rVqhEYGEiPHj04fPhw0bbY2FiSkpKKndPNzY3Q0NASz1mR/XMoiaNJmbjYGRkS4gY7pqkbOo1V5zsR4lYq1YIGjwOg2zqJN7uoozgLd8Vz9lKOlsmEEOKGLPrtduHCBUwmU7ERGABfX1+SkpJueEy9evWYPXs2f//9Nz/99BNms5k2bdpw9qzaB+fqcXdyzry8PDIyMootFYXJrDBxrTp6M6h9DVz3ToH8LPAPhqBHNU4nypQr7Rs49AetPXNoU6sSBSaFqRvkXhwhhPWxul/fw8LC6NevH02bNqVDhw789ddfeHt7M3369Ls+54QJE3BzcytaAgMDSzGxdVt2IIETKVm4OdgwqKkj7PxB3dDp/9SeQ0LcrsohUL09mAshcgqvd1afqPptdzwJaZc1DieEEMVZtMDx8vLCYDCQnJxcbH1ycjJ+fn63dQ4bGxuaNWtGTEwMQNFxd3LOsWPHkp6eXrTEx8ff6VspkwpNZr5dq94jMeSBmrjs+g4KL0PlFlDnYY3TiTKp3Uj1n3vn0dpPR2gNTwpMijxRJYSwOhYtcGxtbQkJCSEiIqJondlsJiIigrCwsNs6h8lk4uDBg/j7qx2Na9SogZ+fX7FzZmRksGPHjpue087ODldX12JLRbBkfwKnLmTj4WjDgEY2sPvKjd2d/iOjN+Lu1OoMfo2hIAd2zWREuDqKs2BnPEnp8kSVEMJ6WPwS1ahRo/jhhx+YN28e0dHRDB06lOzsbAYOVLtW9+vXj7Fjxxbt/8EHH7B69WpOnTrF3r176du3L2fOnOGll14C1CesRo4cyUcffcSSJUs4ePAg/fr1IyAggJ49e1r67ZQZJrPCd+vVUa/BD9TEace3YMqDqmFQ60GN04kyS6eDtiPV1zumERboQMvqHuSbzDKKI4SwKkZL/4BevXpx/vx5xo0bR1JSEk2bNmXlypVFNwnHxcWh/9eTPJcuXWLw4MEkJSXh4eFBSEgI27Zto0GDBkX7vP3222RnZzNkyBDS0tJo164dK1euvG5CwIpsxcFETp3Pxs3Bhn719TB9vrpB7r0R96pBT4j4ANLOoIv6hRGdn6DvrB38sjOOVzvWwsdV/jsUQmhPpyiKonWI+y0jIwM3NzfS09PL5eUqs1mh27ebOZacycjwOozMmQx750ONB6D/Uq3jifJg5w+w4k1wr4ry2l6enrGLPWcu8WLbGox7rMGtjxdCiLtwJ9/fVvcUlbh3q48kcyw5E2c7I4PqA/t+Vjd0+q+muUQ50rQPOFaCtDh0R/5mxJUnqn7ecYaUTLkXRwihPSlwyhlFUfhuvfrkVP821XDZ+TUoJqgdDlVDNU4nyg1bRwh9RX29ZSLta1eiaaA7eYVmftgkncaFENqTAqec2XDsPIfOZeBoa2BwfRMcWKhu6PQfbYOJ8qflS2DjBMkH0Z1aV/RE1Y/bz3BBOo0LITQmBU45oigKk670BurbuhruO78CxQz1uquTtAlRmhw9IaS/+nrLRDrW9Sa4ihu5BTKKI4TQnhQ45cjWmIvsi0vDzqjn5fq5cOgvdYOM3ghLaf0q6I1wejO6hL3FRnEuZedrHE4IUZFJgVOOXB29ea5VVSrt/ApQoEEPdWI2ISzBPRAaPa2+3jKRTvV8aODvSk6+iXmRpzWNJoSo2KTAKSd2nLrIzthUbA16htXPhuilgA46jr3lsULck6tNOKOXort4klc71QJgztbTZOUVahhMCFGRSYFTTkxep85a/HSLKnjv+kpd2fhp8KmvYSpRIfg2gDpdAAW2TaJbI39qeDmRfrmAX3fEaZ1OCFFBSYFTDkTFp7El5gJGvY4R9dLh+ErQ6aHDGK2jiYriahPO/b9iyE7hlQ41Afhh8ynyCk3a5RJCVFhS4JQDUzeoozc9mlbGd8+V0Zvg58CrtoapRIVSNQyqtAJTPuyYyhPNquDvZk9KZh5/7jmndTohRAUkBU4ZF5OSyarDyQC8Ue8CnFynPtXywFsaJxMVik53bRRn12xsC7MY3F4dxZm28SSFJrN22YQQFZIUOGXc9I3qfCMPN/Clyr5v1JVN+4BnDQ1TiQqpbjfwqgd56bBnDr1bBeLhaENcag7LDyZqnU4IUcFIgVOGJaRdZnGUOvz/Zt1kOL0ZDLYyeiO0oddD29fV15Hf46g38WJbtdD+fv1JzOYK19dXCKEhKXDKsJmbYykwKbSu4UHdw5PUlc37q3OTCKGFxs+CSwBkJcGBhfQLq46znZFjyZmsO5qidTohRAUiBU4ZdSk7n193qo/g/qdeIsRvB6M9tB+tcTJRoRltIexV9fXWSbjZG+jTuioAUzbEoCgyiiOEuD+kwCmj5kWe5nKBiYb+LjQ+/p26ssUgcPXXNpgQIQPAzg0unoBjyxnUrga2Rj374tLYfipV63RCiApCCpwyKCe/kLnbTgMwPigeXcJesHGEdm9oG0wIADsXaDlIfb1lIj7OdvRqoV42/f7KlAZCCGFpUuCUQQt2xpOWU0B1T3taxk5VV7YaAs7e2gYT4qrWQ8FgB+d2w5mtDHmgJga9js0nLnDwbLrW6YQQFYAUOGVMfqGZmZvVR8M/rHcaXdJBsHW51g9ICGvg7ANNn1dfb5lIoKcjjzVRL59O33RSw2BCiIpCCpwyZsn+BBLSc/F1NtL27Ax1Zeuh4OipbTAh/leb19SWITFrIOkQQx5Qm3CuOJhIfGqOxuGEEOWdFDhliNmsMG2j+tvvx3Vj0J8/CvZuEDZM42RC3EClWlD/cfX1tkk0CHClfR0vzApFo5BCCGEpUuCUIWujk4lJycLdXseDSbPUlWGvgYO7prmEuKmr7RsO/gFpcbzSQR3FWbg7ntTsfO1yCSHKPSlwyghFUZh6ZfTmk1rR6FNPgoMHtH5F42RClCCgGdToAIoJIqfQplYlGga4kltg5sfIM1qnE0KUY1LglBG7z1xiX1wajkYzXS7MU1e2HaE+kiuENbs6irN3PrrLl3j5yijOvMjT5BaYtMslhCjXpMApI2ZsUu9Z+KjaAQzpZ8DJW300XAhrV7MT+DWBghzYOYPujfyo4uFAanY+v+85q3U6IUQ5JQVOGXDyfBZro5OxpYDH0n9SV7Z7A2ydtA0mxO3Q6a6N4uyYjtF0mZfaqU04Z24+hUmacAohLEAKnDJg1pZYFAXGV96NTVYCuPhDixe1jiXE7avfAzyqw+VU2PcTz7YMxN3RhjMXc1h1OEnrdEKIckgKHCt3ISuPP/ecxY58nsn5TV3ZfjTYOGgbTIg7YTBC2HD19bbvcDQo9GtdDYDpG09KE04hRKmTAsfK/Rh5hrxCM29V2obt5WRwrQLN+2kdS4g716wvOHpBehwcXkS/NtWxM+rZfzadHbHShFMIUbqkwLFil/NN/Lj9DA7k8kLhn+rKDm+B0U7bYELcDRsHCL0yrcHWb/FysuXpkCrAtZvohRCitEiBY8X+3HuW1Ox8XnfZgF3eRfUehqZ9tI4lxN1rOQhsnCD5EMRE8FL7muh0sO5oCseTM7VOJ4QoR+5LgTNlyhSqV6+Ovb09oaGh7Ny586b7/vDDD7Rv3x4PDw88PDwIDw+/bv8BAwag0+mKLV27drX027ivTGaFWVticeIyA1miruzwDhhstA0mxL1w9ISQAerrrROp4eVE14Z+gIziCCFKl8ULnIULFzJq1CjGjx/P3r17CQ4OpkuXLqSkpNxw/w0bNvDcc8+xfv16IiMjCQwM5OGHH+bcuXPF9uvatSuJiYlFy6+//mrpt3JfrY1OJvZCNkPt12BfkAaVakPjZ7WOJcS9C3sV9EY4vRnO7mHIAzUB+DvqHEnpuRqHE0KUFxYvcL7++msGDx7MwIEDadCgAdOmTcPR0ZHZs2ffcP+ff/6ZV199laZNmxIUFMTMmTMxm81EREQU28/Ozg4/P7+ixcPDw9Jv5b76YdMpXMnmJcNydUXHseqTKEKUdW5VrhXrW7+hWVUPWtXwpMCkMGdbrLbZhBDlhkULnPz8fPbs2UN4ePi1H6jXEx4eTmRk5G2dIycnh4KCAjw9PYut37BhAz4+PtSrV4+hQ4dy8eLFm54jLy+PjIyMYos123PmErvPXGKIzT/YmzLBuz40fFLrWEKUnrYj1H9GL4MLJxjcXh3F+XVHHNl5hRoGE0KUFxYtcC5cuIDJZMLX17fYel9fX5KSbm9yr3feeYeAgIBiRVLXrl2ZP38+ERERfPbZZ2zcuJFu3bphMt24r82ECRNwc3MrWgIDA+/+Td0HMzefwp1MXrJZqa7oNBb0cj+4KEd8gqBuN0CBbZPoHORD9UqOZOQW8oe0bxBClAKr/tb89NNPWbBgAYsWLcLe3r5ofe/evXn88cdp3LgxPXv2ZNmyZezatYsNGzbc8Dxjx44lPT29aImPj79P7+DOnbmYzcrDSbxsXIa9OQf8GkPQY1rHEqL0XW3fsH8B+uxkBl1p3zB7a6y0bxBC3DOLFjheXl4YDAaSk5OLrU9OTsbPz6/EY7/88ks+/fRTVq9eTZMmTUrct2bNmnh5eRETE3PD7XZ2dri6uhZbrNXMzbFUUtJ50WaNuqLjf2T0RpRPVVtDYGsw5cP273kqpApuDmr7hrXRybc+XgghSmDRb05bW1tCQkKK3SB89YbhsLCwmx73+eef8+GHH7Jy5UpatGhxy59z9uxZLl68iL+/f6nk1oraXTmeV4xLsFNyIaA51OumdSwhLOfqvTi75+BozqZPaFUAZm2Wm42FEPfG4kMDo0aN4ocffmDevHlER0czdOhQsrOzGThwIAD9+vVj7NixRft/9tlnvPvuu8yePZvq1auTlJREUlISWVlZAGRlZfHWW2+xfft2Tp8+TUREBD169KB27dp06dLF0m/Hon7afgbXgou8YLxSEHb6P7UTsxDlVd2u4B0EeRmwezb921THxqBj5+lU9senaZ1OCFGGWbzA6dWrF19++SXjxo2jadOmREVFsXLlyqIbj+Pi4khMTCzaf+rUqeTn5/P000/j7+9ftHz55ZcAGAwGDhw4wOOPP07dunUZNGgQISEhbN68GTu7stvCILfAxPzI0wwzLsaOfAgMhdqdtY4lhGXp9dDmdfX19qn4OsBjwQEAzNoiozhCiLunUypgG9+MjAzc3NxIT0+3mvtxftsVz8Q/17HBfhS2FEK/JVCzg9axhLC8wnyY1BQyzsFjkzjs35NHJm3BoNex+e1OBLg7aJ1QCGEl7uT7W+5etQKKojB7ayzDjYvV4qZ6eyluRMVhtIXWr6qvt02ioZ8zbWpVwmRWmLvttKbRhBBllxQ4VmDbyYtkJ8fwjGGjuqLT/2kbSIj7LaQ/2LvBxRg4upyX2quPjP+6I44smfhPCHEXpMCxArO2xPK6YRE2OhPUehCq3fwJMyHKJTsXaDlYfb11Ih3reFPT24nMvEJ+22W981YJIayXFDgaO3U+izPH9vGkYbO6QkZvREUV+goY7eHcHvRxW2XiPyHEPZECR2Nztp5mtPF3DDoF6j0CVW49748Q5ZKzNzTto77eOpEnm1XBw9GGs5cus/rw7bV2EUKIq6TA0VB6TgFH92ygu2EnCjro/K7WkYTQVpvXQKeHmLU4pB6hb+tqAMyUR8aFEHdIChwN/borjhH8ov4huDf41Nc2kBBa86wBDXqqr7d+ywth1bA16Nlz5hJ74y5pGk0IUbZIgaORApOZI1v+pp3hMCa9DbqOY295jBAVwtX2DYf+wqcwmcebysR/Qog7JwWORlYeTGRQ3o8AKCEvgkc1jRMJYSUCmkLNjqCYIPK7opuN/zmYSHxqjqbRhBBlhxQ4Gjmy7ieC9afI1ztg7PCW1nGEsC5tR6r/3Psj9V3zaVfbC7MC82TiPyHEbZICRwN7Ys/zdNocAApavao+PSKEuKZmR/APhsLLsHMGg65M/LdgVzyZuQXaZhNClAlS4GggeuU0aukTyTa44dRxpNZxhLA+Ot21UZydM+hQzZHaPs5k5RWyUCb+E0LcBilw7rNzF1LpnDQbgMyWI8DeOpp9CmF1GvQAjxpw+RL6qJ94sa06ijN322mZ+E8IcUtS4Nxn0X9/jb8ulQsGb/w6D9M6jhDWS29Q58UBiPyOJ4N9ZOI/IcRtkwLnPspOT6VFvHrvTUrzUWBjr3EiIaxc0+fByRvS47E/9rdM/CeEuG1S4NxHMX9PwJ0szuiqENRlsNZxhLB+Ng5qjypQJ/4LrYqNQceeM5eIik/TNJoQwrpJgXOfmDOSqXtqPgCxwW+gN9ponEiIMqLlILB1hpTD+CRv5rFgmfhPCHFrUuDcJ2eXfIgDuRykFi279tc6jhBlh4MHhAxQX2+dWDTx34qDiSSkXdYulxDCqkmBcz9cOk1AzK8AHAx6Ayd7Gb0R4o60fhX0NnBmKw1Nx2ld0xOTWWFe5GmtkwkhrJQUOPdB2ooPMFLIZnNjOnZ9Wus4QpQ9bpWhybPq660TGdSuJgC/7ogjO69Qw2BCCGslBY6lJR/B9cRfAERWH0aAu4PGgYQoo6424Ty6nM5eaVSv5EhGbiF/7j2rbS4hhFWSAsfC8la/hx6F5aZWhId31TqOEGWXdz2o1x1Q0EdO4sUr9+LM3hKLWSb+E0L8DylwLCluB3YnV1Go6Fnh/RLNq3ponUiIsu1q+4b9C3m6jgFXeyOnL+YQcTRF01hCCOsjBY6lKArmNeMB+N3Uga4d2mscSIhyoGooVA0DcwGOe2fwXGhVAGZtOaVxMCGEtZECx1Ji1qKPjyRPsWGB43N0a+SndSIhyoerozi75zCgmQcGvY7tp1I5nJCuaSwhhHWRAscSzGaUte8BMNf0MN3btsBokI9aiFJR52Hwrg/5mfif+IXujf0BmfhPCFGcfOtawuG/0CUfIkNxYK7uCXq3rKp1IiHKD73+2hNV26fyUmu1wFm6P4GUjFwNgwkhrIkUOKXNVADrPgJgRuGjPNSiPm6OMrGfEKWq8dPgWgWyUwi++A8tqnlQYFL4cfsZrZMJIayEFDilbe98uBTLecWV2aZuDGxbQ+tEQpQ/BhsIG6a+3jaJQW3VUdKftp8ht8CkYTAhhLWQAqc05efAxs8AmFz4BGFBVanh5aRxKCHKqeb9wN4dUk/xsH43VTwcuJRTwF97z2mdTAhhBe5LgTNlyhSqV6+Ovb09oaGh7Ny5s8T9f//9d4KCgrC3t6dx48asWLGi2HZFURg3bhz+/v44ODgQHh7OiRMnLPkWbs+OaZCVzFnFm19NnYuaAgohLMDOGVoNBsCwbSIDwqoBMHtrLIoiE/8JUdFZvMBZuHAho0aNYvz48ezdu5fg4GC6dOlCSsqNJ+batm0bzz33HIMGDWLfvn307NmTnj17cujQoaJ9Pv/8cyZNmsS0adPYsWMHTk5OdOnShdxcjW8wrNmBc+4t+LLgGWr5eRBWq5K2eYQo71q9DEZ7SNjH8z6ncbYzEpOSxcbj57VOJoTQmE6x8K86oaGhtGzZku+++w4As9lMYGAgr732GmPGjLlu/169epGdnc2yZcuK1rVu3ZqmTZsybdo0FEUhICCA0aNH8+abbwKQnp6Or68vc+fOpXfv3rfMlJGRgZubG+np6bi6upbSO4UCk5kHPltHYkYunz8dzLMtAkvt3EKIm1g+GnbNhFoP8oH7x8zeGkv7Ol78OChU62RCVEhZeYVsP3mRB4N80Ot1pXruO/n+tugITn5+Pnv27CE8PPzaD9TrCQ8PJzIy8obHREZGFtsfoEuXLkX7x8bGkpSUVGwfNzc3QkNDb3rOvLw8MjIyii2WsPJQEokZeXg52/F4cIBFfoYQ4n+EDQedHk6uY0jdLPQ62HziAseTM7VOJkSF9PvueF6av5uX5u/WNIdFC5wLFy5gMpnw9fUttt7X15ekpKQbHpOUlFTi/lf/eSfnnDBhAm5ubkVLYKBlRlZyC0x4OdvSJ7Qa9jYGi/wMIcT/8KwBDZ8AwO/gdB5uoM4aPlsm/hPivjOZFeZuOw3Ag0E+mmapEE9RjR07lvT09KIlPj7eIj/nmRaBbHnnQYY8UNMi5xdC3MTVif8O/8WrTY0A/LXvHBez8jQMJUTFs+5oCmcu5uDmYMOTzStrmsWiBY6XlxcGg4Hk5ORi65OTk/Hzu3FvJj8/vxL3v/rPOzmnnZ0drq6uxRZLsbcx4GRntNj5hRA34B8MtR4ExUzjuB8JruJGfqGZn3fEaZ1MiArl6sjpc62q4mir7XehRQscW1tbQkJCiIiIKFpnNpuJiIggLCzshseEhYUV2x9gzZo1RfvXqFEDPz+/YvtkZGSwY8eOm55TCFEBXGnCqdv3E6+0dANgfuQZ8gpl4j8h7ofDCelEnrqIQa+jf5tqWsex/CWqUaNG8cMPPzBv3jyio6MZOnQo2dnZDBw4EIB+/foxduzYov1HjBjBypUr+eqrrzh69Cjvvfceu3fvZvjw4QDodDpGjhzJRx99xJIlSzh48CD9+vUjICCAnj17WvrtCCGsVY0HIKAZFF7m4ay/8Xez50JWHkuiErROJkSFMGfraQC6N/bH381B2zDchwKnV69efPnll4wbN46mTZsSFRXFypUri24SjouLIzExsWj/Nm3a8MsvvzBjxgyCg4P5448/WLx4MY0aNSra5+233+a1115jyJAhtGzZkqysLFauXIm9vb2l344QwlrpdEWjOIZdP/BiS/UGx1lbZOI/ISztfOa1XyZebFtd2zBXWHweHGtkqXlwhBAaM5vguxaQeorLD35E8zV1uFxg4peXQmlT20vrdEKUWxPXHmfi2hM0q+rOolfbWuznWM08OEIIcV/pDdDmNQAcdk/j2ebqgwez5JFxISwmr9DET9vPAPCiFTWYlgJHCFG+BD8PTj6QcZZhXvvQ6SDiaAqnzmdpnUyIcmnp/kQuZOXj72ZP10Y3fppZC1LgCCHKFxt7aP0KAD4HphNeT700dfUGSCFE6VEUpejR8H5h1bExWE9ZYT1JhBCitLQYBLYucD6aUTXUuXD+2HOWtJx8jYMJUb7siE3lSGIG9jZ6nmtlXf0XpcARQpQ/Du7QYgAAQSdnUd/fVb3ZeKdM/CdEabp6f9tTzavg7mircZripMARQpRPrV8FvQ26uEjeapAOwPxtZygwmTUOJkT5cOZiNmuj1a4CA63k0fB/kwJHCFE+uQZAcC8AOpz/GS9nO5IycllxMPEWBwohbsfcbadRFOhQ15vaPi7XNmSdhxVvQeaNG2DfL1LgCCHKrzYjAB2G4ysYEayO3MjEf0Lcu8zcAn7ffRaAQe3+59HwTV/Azhnwx4saJLtGChwhRPnlXReCHgHgmby/sDPqOXA2nd1nLmkcTIiy7bfdZ8nKK6S2jzPt6/xrEs3UWNg9W33d4R1twl0hBY4Qony70r7B/sgfDGhkA8CszTLxnxB3y2RWmLtN/W/oxbY10Ol01zau/xjMBVCrM9TsoFFClRQ4QojyLbAlVGsL5gJesVsNwOojScRdzNE4mBBl09roZOJTL+PuaMMTzSpf25C4Hw7+rr4Of0+TbP8mBY4QovxrOwIAj+if6VrbHrMCc7bJKI4Qd+PqxH7Pt6qKg63h2oa176n/bPws+De5/8H+hxQ4Qojyr87D4NMA8rN4p9IWAH7bFU9GboHGwYQoWw6dS2dHbCpGvY4Xwqpd23ByPZxcB3obePD/tAv4L1LgCCHKP52uaBSnesyPNPS2ITvfxG+74jUOJkTZMnurOnrTvbE//m4O6kqz+droTctB4FFdk2z/SwocIUTF0OgpcAtEl32e96oeANT+VIUy8Z8QtyUlM5el+xMAePHfj4YfWQSJUWp7lAfe0ibcDUiBI4SoGAw2EDYMgJCEn/ByNHAu7TKrjyRrHEyIsuGnyDMUmBSaVXWnaaC7utJUABEfqq/bvg5OXjc9/n6TAkcIUXE07wcOHugvxTK+9kngWi8dIcTN5RaY+HH7GQBealfz2oY9c+FSLDj5qO1RrIgUOEKIisPWCVoNAaBr+kJsDTr2nLlEVHyatrmEsHJ/7T3HpZwCqng40KWhr7oyLws2fqa+7vgO2DlrF/AGpMARQlQsrV4GowM2yfsZVUvtlSOjOELcnNmsMGvLKQAGtq2B0XCldIicAtnnwbMmNO+vYcIbkwJHCFGxOFWC5i8A0Nf0FwArDiZyLu2ylqmEsFobj5/n5PlsXOyMPNuiiroy6zxsm6S+fvBd9R43KyMFjhCi4gkbDjoDzuc281yVVExmhfnbTmudSgirNPPK6E3vVoG42F8pZDZ9AflZENAMGvTULlwJpMARQlQ8HtWg0ZMAjHBYAcAvO+PIzivUMpUQVudwQjpbYy5i0Ovo36a6uvLfDTXD3we9dZYS1plKCCEs7crEf75nV9LWM4PM3EL+2HNW41BCWJer96d1a+RHFQ9HdaUVNdQsiRQ4QoiKya8x1OqMTjEzrtI6AOZsjcVsVjQOJoR1SM64NrHfS+2vPBpuZQ01SyIFjhCi4mo3EoC6iUuoYZ/D6Ys5RBxN0TaTEFZifuRpCkwKLat7XJvYr6ih5jNW0VCzJFLgCCEqrurtIaA5usJcPgrYClD0OKwQFVlOfiE/74gDYNDVif3+3VCzk3U01CyJFDhCiIpLpysaxQm7+Beu+jy2n0rl0Ll0bXMJobE/954jLaeAqp6OPNTA9/qGmp41SjzeGkiBI4So2IIeBc9a6PPSea/ybgBmy8R/ogIzm5Wi/wZebFsdg14HRxZbZUPNkkiBI4So2PQGtUkg8GjOX9hQyNIDCaRk5GocTAhtRBxNIfZCNi72Rp5pEXiloeYH6kYra6hZEilwhBCiSW9w9sU2O5HXfaIoMCnMjzyjdSohNDFzs3of2vOhVXGyM1p1Q82SWLTASU1NpU+fPri6uuLu7s6gQYPIysoqcf/XXnuNevXq4eDgQNWqVXn99ddJTy9+PVyn0123LFiwwJJvRQhRntnYQ+uhAAxgCTrM/LzjDLkFJo2DCXF/HTybzo7YVIx6HQPaVC/eULPD21bXULMkFi1w+vTpw+HDh1mzZg3Lli1j06ZNDBky5Kb7JyQkkJCQwJdffsmhQ4eYO3cuK1euZNCgQdftO2fOHBITE4uWnj17WvCdCCHKvRYvgp0rLhkxPOt6hEs5Bfy195zWqYS4r64+RfhoE3/83RyKN9QMGaBtuDukUxTFIrNaRUdH06BBA3bt2kWLFi0AWLlyJd27d+fs2bMEBATc1nl+//13+vbtS3Z2NkajUQ2t07Fo0aK7LmoyMjJwc3MjPT0dV1fXuzqHEKIcWjMOtn5LkltTWie/TW0fZ9a88QA6nU7rZEJYXGL6Zdp/tp5Cs8LS4e1o7J4Pk5qqPaeenlPU3kRLd/L9bbERnMjISNzd3YuKG4Dw8HD0ej07duy47fNcfRNXi5urhg0bhpeXF61atWL27NmUVKfl5eWRkZFRbBFCiOuEDgWDLX7pUbS3iyEmJYuNx89rnUqI+2LetjMUmhVCa3jSuIobbP7S6htqlsRiBU5SUhI+Pj7F1hmNRjw9PUlKSrqtc1y4cIEPP/zwustaH3zwAb/99htr1qzhqaee4tVXX2Xy5Mk3Pc+ECRNwc3MrWgIDA+/8DQkhyj9Xf2jSC4B33VcD13rxCFGeZecV8ssO9cb6l9rXVBtq7pqlbrTihpoluePEY8aMueFNvv9ejh49es/BMjIyeOSRR2jQoAHvvfdesW3vvvsubdu2pVmzZrzzzju8/fbbfPHFFzc919ixY0lPTy9a4uPj7zmfEKKcajsC0FE3fQv19GfZfOICx5IytU4lhEX9vjuejNxCqldypHOQT5lpqFmSOy5wRo8eTXR0dIlLzZo18fPzIyWleE+XwsJCUlNT8fPzK/FnZGZm0rVrV1xcXFi0aBE2NjYl7h8aGsrZs2fJy8u74XY7OztcXV2LLUIIcUNedSDoEQDeqxQByMR/onwrNJmZeeXf8UHta6JPPvCvhprjNUx2b4y33qU4b29vvL29b7lfWFgYaWlp7Nmzh5CQEADWrVuH2WwmNDT0psdlZGTQpUsX7OzsWLJkCfb29rf8WVFRUXh4eGBnZ3f7b0QIIW6m3RtwdBmhWRH48SiLovS81bUeXs7y/xhR/qw4lMTZS5ep5GTLMyFVYMFIdUPjZ8A/WNNs98JiF9Xq169P165dGTx4MDt37mTr1q0MHz6c3r17Fz1Bde7cOYKCgti5cyegFjcPP/ww2dnZzJo1i4yMDJKSkkhKSsJkUuejWLp0KTNnzuTQoUPExMQwdepUPvnkE1577TVLvRUhREVTpQVUa4deKWSMxzryC838vD1O61RClDpFUZi+8SQA/cKqYx+/uUw11CyJRe8a+vnnnwkKCqJz5850796ddu3aMWPGjKLtBQUFHDt2jJycHAD27t3Ljh07OHjwILVr18bf379ouXrfjI2NDVOmTCEsLIymTZsyffp0vv76a8aPL7vDaEIIK3SlCeejBatwJYsft58hr1Am/hPly7aTFzmckIGDjYF+rQNhzZXv0jLSULMkFpsHx5rJPDhCiFtSFJjWDpIPMc3wPJ9mP8oXTzdRe/MIUU68MGsHm09cYECb6rxX8xj8MVBtqDkiyip7TlnFPDhCCFGm6XRXnqiC/vp/sCOfWVtiS5xzS4iy5EhCBptPXECvg0FhVcpkQ82SSIEjhBA30/BJcKuKQ8ElnrfdzNGkTLadvKh1KiFKxYxN6r03jzQJIDD2tzLZULMkUuAIIcTNGIzQZjgAr9n/gwET0zed0jiUEPfu7KUclh5IBGBomG+ZbahZEilwhBCiJM36goMnnvkJPGLcxabj5zl0Ll3rVELck9lbTmMyK7StXYkGp38ssw01SyIFjhBClMTWCVqp7WLecvoHUGQUR5Rp6TkFLNilTnswrJU7bJukbnjwXTCUPLFuWSIFjhBC3EqrIWB0IDDvBO30h1h+IIEzF7O1TiXEXflpxxly8k0E+bkQdnZ2mW6oWRIpcIQQ4lacKkHzfgCMdV2JWYEfNssojih7cgtMzNl6GoBRLWzR7Z6tbgh/r0w21CxJ+Xo3QghhKWHDQGegYe4+GulO8dvus5zPvHH/OyGs1aJ957iQlUeAmz3hST9caaj5INTsqHW0UicFjhBC3A6PatDoKQDGuK4iv9DMnK3ShFOUHWazwg9X7h97Ozgf/aE/1A3h72kXyoKkwBFCiNt1ZeK/tnlbqapL5sftZ8jMLdA4lBC3Z010MqcuZONqb+TR89PVlWW8oWZJpMARQojb5dcIaj+EDjNvOa8iM7eQX3ZIE05h/RRFYeoGdWK//9RPwRi7vlw01CyJFDhCCHEnrjTh7G5ahxfpzNoSK004hdWLPHWRqPg07I3wVOoP6spy0FCzJFLgCCHEnajWFiq3wGDOZ7jTWlIy81i095zWqYQo0ffr1dGbD2rHYJO8H2ydof2bGqeyLClwhBDiTuh0RaM4z+lW48RlZmw6hcksTTiFdYqKT2NLzAXs9SaevHTlsfA2r4Ozt7bBLEwKHCGEuFP1HoFKtbErzORF+42cupDN6sNJWqcS4oa+Xx8DwMdV92JMPw1O3uq0B+WcFDhCCHGn9Hr1N2BgiO1KbChk2saTKIqM4gjrcjw5k9VHknHS5dIj/Sd1ZYd3yk1DzZJIgSOEEHcjuDc4++GSn8IzttvYfzadyJMXtU4lRDFXn5ya4L8Z4+Xy11CzJFLgCCHE3TDaQeuhALzh8A86zHx/5ctECGsQn5rDkv0JeJLBI5m/qSvLWUPNkkiBI4QQd6vFQLBzxTvvDF0M+9gSc4G9cZe0TiUEANM3ncRkVpjgtRJDQTb4Ny13DTVLIgWOEELcLXs3aPEiAGPcVgHw3boYLRMJAUBKRi6/7T5LoC6Zh3KWqysfer/cNdQsScV5p0IIYQmth4LBluo5h2ilP8q6oykcOpeudSpRwc3aEkt+oZmP3f5GX44bapZEChwhhLgXLn4Q/BwA4zzWADKKI7SVlpPPT9vP0FB3mgdyN6gry2lDzZJIgSOEEPeqzeuAjkbZkdTTx7PycBLHkjK1TiUqqHnbzpCdb+J9pyvdwstxQ82SSIEjhBD3yqs21H8MgPcrRQAwZb2M4oj7LyuvkDnbYmmjP0SLwr3lvqFmSaTAEUKI0nClfUNo1joCuMCyAwmcOp+lbSZR4cyPPE16Th7j7ReqK1q8WK4bapZEChwhhCgNlUOgent0SiHv+2zArCDz4oj7KjuvkB82naK7fif1zCfVhpoPvKV1LM1IgSOEEKXlyijOgzkrcSOLRfvOEZ+ao20mUWH8uP0MmTmXGWv3u7qiAjTULIkUOEIIUVpqdQbfxhgKc3jXZwsms8LUjTKKIywvJ18dveltWE8VJbHCNNQsiRQ4QghRWnQ6aDsCgB55y7Anjz92nyUx/bLGwUR59/P2OC5nZ/CGzSJ1RQVpqFkSKXCEEKI0NXwC3Ktik5fKWz67yDeZmb7xlNapRDl2Od/E9E0nGWRYQSXSwKNGhWmoWRKLFjipqan06dMHV1dX3N3dGTRoEFlZJT9V0LFjR3Q6XbHllVdeKbZPXFwcjzzyCI6Ojvj4+PDWW29RWFhoybcihBC3x2CEsNcA6GNeigETv+6MIyUjV+Ngorz6eccZzFkXGGqzTF3RueI01CyJRQucPn36cPjwYdasWcOyZcvYtGkTQ4YMueVxgwcPJjExsWj5/PPPi7aZTCYeeeQR8vPz2bZtG/PmzWPu3LmMGzfOkm9FCCFuX7O+4FgJ+6x4hvkeIq9QOo0Ly8gtMDF90yleMy7CkdwrDTWf0DqWVbBYgRMdHc3KlSuZOXMmoaGhtGvXjsmTJ7NgwQISEhJKPNbR0RE/P7+ixdXVtWjb6tWrOXLkCD/99BNNmzalW7dufPjhh0yZMoX8/HxLvR0hhLh9to7Q6mUAhuiXAgq/7IiTe3FEqftlRxz2WXH0NaoTTFa0hpolsdinEBkZibu7Oy1atChaFx4ejl6vZ8eOHSUe+/PPP+Pl5UWjRo0YO3YsOTnXHrOMjIykcePG+Pr6Fq3r0qULGRkZHD58+Ibny8vLIyMjo9gihBAW1Wow2DjifOkILwWcJt9kltmNRanKLTAxbeNJRhn/wIbCCtlQsyQWK3CSkpLw8fEpts5oNOLp6UlSUtJNj3v++ef56aefWL9+PWPHjuXHH3+kb9++xc777+IGKPrzzc47YcIE3NzcipbAwMC7fVtCCHF7HD2heX8AXrNV741YuCues5dkXhxROhbsjMM76xhPGLaqKypgQ82S3HGBM2bMmOtuAv7f5ejRo3cdaMiQIXTp0oXGjRvTp08f5s+fz6JFizh58u6vX48dO5b09PSiJT4+/q7PJYQQty1sGOiNuCVF0ifwIgUmRUZxRKnILTAxdeNJ3jYuUFc0erpCNtQsifFODxg9ejQDBgwocZ+aNWvi5+dHSkpKsfWFhYWkpqbi5+d32z8vNDQUgJiYGGrVqoWfnx87d+4stk9ycjLATc9rZ2eHnZ3dbf9MIYQoFe6B6hfPgQWMdlzBz7zA77vPMrRDbapWctQ6nSjDfow8Q62sPXSwPYCit0H34H+1jmR17ngEx9vbm6CgoBIXW1tbwsLCSEtLY8+ePUXHrlu3DrPZXFS03I6oqCgA/P39AQgLC+PgwYPFiqc1a9bg6upKgwYN7vTtCCGEZbV9HQDPMyt5pkYehWaFyetOaBxKlGVZeYVM23CCMcZfAdBV4IaaJbHYPTj169ena9euDB48mJ07d7J161aGDx9O7969CQgIAODcuXMEBQUVjcicPHmSDz/8kD179nD69GmWLFlCv379eOCBB2jSpAkADz/8MA0aNOCFF15g//79rFq1iv/+978MGzZMRmmEENbHtyHUeRhQeMd1NQB/7TtH7IVsbXOJMmv2llha526hiT4WpYI31CyJRZ8l+/nnnwkKCqJz5850796ddu3aMWPGjKLtBQUFHDt2rOgpKVtbW9auXcvDDz9MUFAQo0eP5qmnnmLp0qVFxxgMBpYtW4bBYCAsLIy+ffvSr18/PvjgA0u+FSGEuHttRwLgFfMXPWsbMZkVJkXIKI64c2k5+czZdJw3jQsB0FXwhpol0SmKomgd4n7LyMjAzc2N9PT0YnPsCCGERSgKzHoIzu4iJfhVWu1oh04Ha954gNo+LlqnE2XIZyuPkrl5Gh/ZzEFx8kb3elSF6jl1J9/fMhuQEEJYmk5XNIrjc/RnHgtyRlHg6zXHtc0lypSUzFx+23qUEca/ANBJQ80SSYEjhBD3Q73u4FUX8tJ5128nOh2sOJjE/vg0rZOJMuL79Sd53rwUb106ikeNonmWxI1JgSOEEPeDXg9t1CeqfA7P4ulg9b6Jz1fd/bxhouI4l3aZf3Yc4mWjOmmkrvO7YLTVOJV1kwJHCCHulybPgos/ZCYytvJBbA16tsZcZPOJ81onE1ZucsQJXtH9ibNOGmreLilwhBDifjHaQetXAfCMmkqf0CoAfL7yGGZzhXveQ9ym2AvZRO7ZSx/DWnWFNNS8LfIJCSHE/RQyAOzc4OIJ3giMwcnWwMFz6fxz6OY9+kTF9sWqo4w0/IatziQNNe+AFDhCCHE/2btCy0EAuO6ZwuD26gy0X64+RoHJrGUyYYX2xl3izKHt0lDzLkiBI4QQ91voK2Cwg7O7GFI9mUpOtsReyOb33We1TiasiKIoTFgRLQ0175IUOEIIcb+5+ELT5wBw3DmZ4Q/WBmDi2uNczjdpmUxYkTVHkrGJ20wHg9pQE2moeUekwBFCCC20eR3QwYnV9KmRRRUPB1Iy85i9NVbrZMIKFJrMfPpPNO9cGb2Rhpp3TgocIYTQQqVa0OBxAGy3T+bNh+sB8P36GM5n5mmZTFiBhbvjCUpdR7D+FIqtkzTUvAtS4AghhFautG/g4B88Xq2Q4CpuZOebpIVDBZedV8ik1dG8VdRQc4Q01LwLUuAIIYRWKjeHGg+AYkK/Yyr/fbQBAAt3xXEsKVPjcEIrP2w+xUO5K6mhT0Zx8oawYVpHKpOkwBFCCC1dHcXZO4+WPtCtkR9mBT5eEa1pLKGNlMxcftp0RBpqlgIpcIQQQku1HgS/JlCQAzt/YEy3IGwMOjYdP8+GYylapxP32ZerjvGcSRpqlgYpcIQQQks6HbQdob7eOZ1qLjoGtKkOwMfLoymUyf8qjINn04nYc0QaapYSKXCEEEJrDXqCezXIuQj7fmJ4pzq4O9pwIiWLhbvjtU4n7gNFUXh/6WGGGRZLQ81SIgWOEEJozWCENq+pryMn42anY2TnOgB8vfo4mbkFGoYT98PSA4kkxR2jr2GNuiL8PWmoeY/k0xNCCGvQrC84ekFaHBxeRJ/W1ajp5cTF7Hwmr4vROp2woMv5Jj5dEc1o4+9qQ82anaBWJ61jlXlS4AghhDWwcYDQl9XX6z/GxpTLu4+pj43P3hJLTIo8Nl5eTd90Eo+Mo9JQs5RJgSOEENYi9BVwCYBLsbDhEzrV8yG8vi+FZoX3lhxBURStE4pSlpB2mWkbTxZvqBnQVNNM5YUUOEIIYS3sXeGxierryClwdg/jHm2ArVHPlpgLrDyUpGk8Ufom/HOUZqaD0lDTAqTAEUIIa1K3CzTpBYoZ/h5GVTcDr3SoBcCHy45It/FyZGvMBZbuP8dY46+ANNQsbVLgCCGEten6KTh5w/lo2PwVQzvUorK7AwnpuXy/QW44Lg/yCk28u/gQ3fU7aKI/BbbO0lCzlEmBI4QQ1sbRE7p/ob7e/BUOqUd490qfqukbT3H6QraG4URp+GHTKeIupDPG9jd1RZvXpKFmKZMCRwghrFGDnhD0KJgL4e/hdKlfifZ1vMg3mXl/6WG54bgMi0/NYfK6GHob1lOVJHW0ThpqljopcIQQwhrpdPDIV2DvDolR6CK/473HG2Jj0LH+2Hn+kRuOyyRFURi/5DCGwhzetFusruzwDti5aJqrPJICRwghrJWLH3SdoL5eP4FaukRe7VgbgPFLDpN+WWY4LmtWH0lm3dEUhtj8g7v5EkhDTYuRAkcIIaxZ8HNQOxxMefD3cF7tWIOa3k6cz8zjs5VHtU4n7kBOfiHvLzmMJxkMtV2urpSGmhYjBY4QQlgznQ4enag+ZRO/Hbu9s/nkicYA/LIjjl2nU7XNJ27bl6uOk5CeyxinZdiZcsA/WBpqWpBFC5zU1FT69OmDq6sr7u7uDBo0iKysrJvuf/r0aXQ63Q2X33//vWi/G21fsGCBJd+KEEJoxz0QHnpffb32fVp7ZNG7ZSAAY/86SF6hzI1j7fbGXWLOtliq6FJ4Wlmlrgx/XxpqWpBFP9k+ffpw+PBh1qxZw7Jly9i0aRNDhgy56f6BgYEkJiYWW95//32cnZ3p1q1bsX3nzJlTbL+ePXta8q0IIYS2Ql6Eam2hIBuWvs7YrkF4OdsSk5LFtA2ntE4nSpBXaOKdPw6gKPCtz3L05gJpqHkfWKzAiY6OZuXKlcycOZPQ0FDatWvH5MmTWbBgAQkJCTc8xmAw4OfnV2xZtGgRzz77LM7OzsX2dXd3L7afvb29pd6KEEJoT6+HxyeD0R5ObcDt2ALGPdYQgCnrY4hJufnouNDWlPUnOZGSRRunc4Skr1FXSkNNi7NYgRMZGYm7uzstWrQoWhceHo5er2fHjh23dY49e/YQFRXFoEGDrts2bNgwvLy8aNWqFbNnzy5xToi8vDwyMjKKLUIIUeZUqgWd/k99veq/PFYDOtbzJt9k5s3f91NoMmubT1wnOjGD79ers09P9FqirpSGmveFxQqcpKQkfHx8iq0zGo14enqSlHR78zfMmjWL+vXr06ZNm2LrP/jgA3777TfWrFnDU089xauvvsrkyZNvep4JEybg5uZWtAQGBt75GxJCCGsQNgwqh0BeOrplo/ikZyNc7IxExacxY7NcqrImhSYz7/x5gEKzwus1EvBJ3gzSUPO+ueMCZ8yYMTe9EfjqcvTovT+6ePnyZX755Zcbjt68++67tG3blmbNmvHOO+/w9ttv88UXX9z0XGPHjiU9Pb1oiY+Pv+d8QgihCb0BekxRvyiP/0PA2RWMe0xt4zBxzQmOJWVqHFBcNX3TKQ6cTcfF3sBr5p/UlS0GSkPN++SOC5zRo0cTHR1d4lKzZk38/PxISUkpdmxhYSGpqan4+fnd8uf88ccf5OTk0K9fv1vuGxoaytmzZ8nLy7vhdjs7O1xdXYstQghRZvnUv9aY8Z+3eTrIns5BPuSbzIz6LYoCuVSluUPn0vlmzXEAZoScwyY56kpDzbe1DVaBGO/0AG9vb7y9b90QLCwsjLS0NPbs2UNISAgA69atw2w2ExoaesvjZ82axeOPP35bPysqKgoPDw/s7Oxu/QaEEKI8aPcGHPkbUg6jW/kOE578noe+2cThhAymrI9hZHhdrRNWWLkFJt5YGEWhWaF7Ay9ax165JCUNNe8ri92DU79+fbp27crgwYPZuXMnW7duZfjw4fTu3ZuAgAAAzp07R1BQEDt37ix2bExMDJs2beKll1667rxLly5l5syZHDp0iJiYGKZOnconn3zCa6+9Zqm3IoQQ1sdoCz2ngM4Ah/7EJyGCD3qoT1V9ty6Gg2fTNQ5YcX2x6hgnUrLwcrbji5pR6FJPSUNNDVh0Hpyff/6ZoKAgOnfuTPfu3WnXrh0zZswo2l5QUMCxY8fIyckpdtzs2bOpUqUKDz/88HXntLGxYcqUKYSFhdG0aVOmT5/O119/zfjx4y35VoQQwvoENFNHBQCWjeLxeo50b+xHoVlhxIJ9ZOcVapuvAtoWc4FZW2IB+KpHTZwiv1Q3SEPN+06nlPR8dTmVkZGBm5sb6enpcj+OEKJsK7gM09rBxRho1pdL4d/Q7dvNJGXk8myLKnz+dLDWCSuM9MsFdJu4iYT0XJ5rVZUJlVbC+o/AozoM2yU9p0rBnXx/yxzRQghRltk4wOPfATrY9xMeSVv4pldTdDr4bfdZluy/8cSqonQpisLYvw6QkJ5LtUqO/LeTN2z9Vt34oDTU1IIUOEIIUdZVC4NWV9rgLBlBWBU7hneqDcD//XWQ+NScEg4WpeGnHXGsOJiEUa/j297NcNo+EfIz1YaaDZ/UOl6FJAWOEEKUB53HgXtVSI+DiPcZ0bkOzau6k5lXyOsL9smj4xZ0OCGdD5cdAWBMtyCaOqfBrpnqRmmoqRn51IUQojywc4bHrlwS2TkD49kdfNu7GS52RvbFpfHl6mPa5iunsvIKGf7LPvILzXQO8mFQuxqw7mOQhpqakwJHCCHKi1oPQrO+6uslwwl00fHpU00AmL7xFCsPJWoYrvxRFIX/W3SQ2AvZBLjZ8+UzweiSDsLB39UdpKGmpqTAEUKI8uThj8HZT32qasMEHmnir44qAG/+foCT56XreGmZs/U0f0clYNDrmPRcMzycbCHifUCBRk9JQ02NSYEjhBDliYM7PPqN+nrbZDi3lzHdgmhV3ZOsvEJe+XGPzI9TCradvMDHK6IB+E/3+rSo7gmnNkLMWtAbpaGmFZACRwghypug7uoIgmKGv4djoxTyXZ9m+LjYcSIli3f+PEAFnAKt1JxLu8zwX/ZhMis80awyL7atDooCa69MONviRfCsqWlGIQWOEEKUT90+B8dKkHIYtnyDj4s9U/o0x6jXsexAIlPWx2idsEzKLTDx8o+7Sc3Op1FlVyY82RidTgdHFkPCPmmoaUWkwBFCiPLIyUstcgA2fQHJR2hZ3ZP3r/Sr+nL1cZYdkEkA74TZrPDWHwc4dC4DTydbpvUNwd7GAKYCiPhA3UkaaloNKXCEEKK8avQU1OuuPrL89zAwFdIntBovtlVvOh79236i4tO0zViGfLn6GEv3J2DU6/ju+WZU8XBUN+ydD9JQ0+pIgSOEEOWVTgePfA12bpCwF7Z/D8D/PVKfB4N8yCs089K83ZxLu6xxUOv3y444vt9wEoBPn2pCm1pe6oa8LNjwqfr6gbeloaYVkQJHCCHKM1d/6PKR+nr9x3DxZNFjzUF+LlzIymPA7J2k5eRrm9OKbTiWwrt/HwJgROc6PB1S5drG7VMhO0VtqBkyQJN84sakwBFCiPKu2QtQsyMU5sLfw8FsxtnOyKwBLfF1VZ+sGjBnlzw+fgP749MY9vNeTGaFJ5tXZmR4nWsbsy9IQ00rJgWOEEKUdzodPDYJbJwgbhvsngVAZXcHfhwUirujDVHxabzy0x7yCk0ah7Uex5Iy6T9nJ9n5JtrUqsSnTzZRn5i6atOX0lDTikmBI4QQFYFHNQi/Mk/L2vcgLQ6Aur4uzBnQEkdbA5tPXGDUwv2YzDJHzukL2fSdtYO0nAKCA92Z0a8FtsZ/fWVeOi0NNa2c/I0IIURF0XIwBLaG/CxYOkKdnA5oVtWD6S+EYGPQsfxgIm/+XrGLnHNpl+kzcwfnM/MI8nNh3sCWONsZi++0/hNpqGnlpMARQoiKQq+HHt+BwQ5OroOoX4o2ta/jzeTnmmHU61i07xxvLIyi0GTWMKw2zlzM5tlpkZxLu0wNLyfmD2qFu+P/3FuTeAAO/Ka+loaaVksKHCGEqEi86kCnserrVWMhM6loU9dG/nz3vDrb8ZL9CYxYEEVBBSpyYlKyeHa6WtzU9HLil8Gh+LjYX7+jNNQsE6TAEUKIiibsNfBvCrnpsHx00aUqgK6N/Jja99rlqpd/3ENOfvl/uio6MYPeMyJJzsijrq8zC15ujb+bw/U7SkPNMkMKHCGEqGgMRvVSld4IR5fB4UXFNj/UwJcZL7TAzqhn3dEUnvthBxez8jQKa3mbT5znmWmRXMjKp4G/KwuGhN145EYaapYpUuAIIURF5NcY2o9WX694C7IvFtvcKciHXwa3xt3Rhv3xaTw9LZIzF7M1CGpZv+2OZ+CcXWTlFRJaw5NfB7fG0+km89lIQ80yRQocIYSoqNq/Cd71IecCrBxz3eaQah788UobKrs7EHshmx5TtrL5xHkNgpY+k1nhi1VHefuPAxSaFXo0DWD+oFa4Odrc5IACiPhQfS0NNcsEKXCEEKKiMtpCjymg08PB3+DYyut2qe3jzKJX2xAc6E5aTgH9Z+9k+saTKErZfYw8NTufAXN2MmW92ltqWKdaTOzVFDuj4eYH7Z0PqSfB0UsaapYRUuAIIURFViUEWr+qvl72hnrj8f/wcbVn4ZDWPBNSBbMCE/45yqs/7y2T/aui4tN4bPIWNp+4gIONgW97N+WtLkHFZyj+X/9uqNnhHWmoWUZIgSOEEBVdp/9Tb5jNTIDV795wF3sbA58/3YQPezTEqNfxz6Ekuk7czLaYC/c57N0pMJn5Zs1xnpq6rWiOm8XD2tKjaeVbHywNNcskKXCEEKKis3WEx79TX++dB6c23HA3nU7HC2HV+XNoG2p6OZGUkcvzM3fwwdIjZFlxo84TyZk8+f02vo04gcms8EgTf/4e3pZ6frcxEpN+VhpqllE6pSxfSL1LGRkZuLm5kZ6ejqurq9ZxhBDCOiwbpTbidK8Gr0aCrdNNd83JL+Tj5dH8vEPtaeXnas+7jzage2O/ki/33EfZeYVMXhfDrC2nKDApuDnY8GHPRjweHHDrgy+dhh0z1IIvPwsCmsFL66TnlMbu5PtbChwpcIQQQpWbAd+HQcZZCB0K3T695SEbjqUw7u/DxKXmANCuthfvdA2icRU3S6e9qUKTmcVRCXy56hhJGbkAdA7y4ZMnG+PreoP5ba5SFDizVb0kdWwFKFdmcfaqC71/UWeBFpqSAucWpMARQoibOLEWfn4K0MGLq6Bq6C0PyS0w8f2Gk0zbcJL8K60dujb04/XOdWgQcP/+H1toMrP8YCLfRpzg1Hl1zp6qno6Mf6wBnev7lnBgHhz6E7Z/D0kHr62v9aB6A3atzjJyYyXu5PvbYn9jH3/8MW3atMHR0RF3d/fbOkZRFMaNG4e/vz8ODg6Eh4dz4sSJYvukpqbSp08fXF1dcXd3Z9CgQWRlZVngHQghRAVUJxyCnwcUWDIcCnJveYi9jYFRD9VlzagHeKJZZXQ6WHk4ie6TNtN7RiSrDidZtHFnanY+32+IocMXGxixIIpT57PxcLRhTLcgVr/xwM2Lm8xkWD8BvmkIi4eqxY3RAUIGwqs74IVFUOchKW7KKIuN4IwfPx53d3fOnj3LrFmzSEtLu+Uxn332GRMmTGDevHnUqFGDd999l4MHD3LkyBHs7dVhxW7dupGYmMj06dMpKChg4MCBtGzZkl9++eUWZ79GRnCEEKIEOakwJVR9csivCTTsqY5m+AXf1pf98eRMJkWc4J9DSZjM6ldMJSdbujf259Em/jSv5oGN4d6KhvScAiKOJrPsQCKbT5ynwKT+HE8nWwa2qc7AdjVwtjPe+OCEKNgxTR21MV151N21MrQaDM37g6PnPWUTlmNVl6jmzp3LyJEjb1ngKIpCQEAAo0eP5s033wQgPT0dX19f5s6dS+/evYmOjqZBgwbs2rWLFi1aALBy5Uq6d+/O2bNnCQi4jRvHkAJHCCFuKWYt/Po8mP7Vg8qxEtTspBY7tR4EV/8ST5GQdpkft59h4a54UrOvzZnjZGugVQ1PWlT3JMjPhXp+Lvi52mO8SdGTW2Di5PksTiRncTghnchTFzmckPHvHqE0ruxG/zbVebSJP/Y2N5iwz2yCo8vVwubM1mvrq7SC1kOh/mNguMksxsJq3Mn3903K2/svNjaWpKQkwsPDi9a5ubkRGhpKZGQkvXv3JjIyEnd396LiBiA8PBy9Xs+OHTt44oknbnjuvLw88vKu/UeakZFhuTcihBDlQe1weH0vHPsHTq6H2E2QcxEO/aEuAD4NrhU71dqATfHu2wHuDrzTNYhRD9Vla8wFluxPYP3RFC7lFLD+2HnWH7vW9kGnAw9HW9wdbTDodOh0kFtgJjU7/6aPoNf2ceaRxv48FuxPbZ+bPPJ9OQ32/Qg7Z0Ca+sQXeiM0fEK9kbpKyL1+UsJKWU2Bk5SUBICvb/Frpb6+vkXbkpKS8PHxKbbdaDTi6elZtM+NTJgwgffff7+UEwshRDnnVkW9bNNqsNqL6ewuOLkOYiLUppMpR9Ql8jsw2KlFTu3OasHj00CtWgAbg56O9XzoWM8Hs1khOimDbTEXOZSQzrGkTE6ez6LApJCanV9spKdYFAcb6vo6U9fXhZbVPQmrVankJ6IunlRHa/b9DAVXmoQ6eEKLgdDyJXC9vRF/UXbdUYEzZswYPvvssxL3iY6OJigo6J5ClbaxY8cyatSooj9nZGQQGBioYSIhhChjDDZqAVOtDTz4X/U+nVMb4GSEOsKTcQ5OrVcXAGe/a6M7NTsWNafU63U0DHCjYcC1x8hNZrW4uZCVR1pOQVGfK1ujHk8nWyo52eHqYLz1/DqKombaPhVOrLq23ru+ehmqybPXjTKJ8uuOCpzRo0czYMCAEvepWbPmXQXx8/MDIDk5GX//a9d1k5OTadq0adE+KSkpxY4rLCwkNTW16PgbsbOzw87O7q5yCSGEuAFHT2j0pLooClw4ro7snFwHp7dAVhLs/0VdAPyDrxU8ga2LzQhs0OvwdrHD2+Uu/z9dcBkOLITt0+B89LX1dbtC6CtqgWUlkw+K++eOChxvb2+8vS3TIr5GjRr4+fkRERFRVNBkZGSwY8cOhg4dCkBYWBhpaWns2bOHkBD1uum6deswm82Eht56rgYhhBAWoNOBdz11CXtVfbQ8frta7Jxcpz5+nbhfXbZ8AzZOUL2dWuzU7gyVat9dAZKRADt/gD1z4XKqus7GCZr1gVYvg1ftUn2bomyx2D04cXFxpKamEhcXh8lkIioqCoDatWvj7OwMQFBQEBMmTOCJJ55Ap9MxcuRIPvroI+rUqVP0mHhAQAA9e/YEoH79+nTt2pXBgwczbdo0CgoKGD58OL17977tJ6iEEEJYmI29OmpSsyM89IE638ypDdcKnuwU9RLS1ctIboFQq5M6oV7NDuDgUfL5z+5WL0MdWQzmKzcgu1dVi5pmfcHB3WJvTZQdFntMfMCAAcybN++69evXr6djx47qD9fpmDNnTtFlL0VRGD9+PDNmzCAtLY127drx/fffU7du3aLjU1NTGT58OEuXLkWv1/PUU08xadKkoqLpdshj4kIIoRGzGVIOX7tZOS7y2lw0ADo9BDS/drNy5RZgMKo3OUcvUQubs7uu7V+trXp/Tb3uoL/B4+GiXLGqeXCskRQ4QghhJfJz4My2Kzcrr4PzR4tvt3NVG11eOAGZCeo6gy00ehpav6Le2yMqjDI5D44QQogKyNZRbQ9R58ocaOnnrl3KOrUeLl+C2I3qNidv9RHvFi+Cs8/NzykEUuAIIYSwJm6VofkL6mI2QWIUnIkE90D1qSijPBErbo8UOEIIIayT3gCVQ9RFiDskLVKFEEIIUe5IgSOEEEKIckcKHCGEEEKUO1LgCCGEEKLckQJHCCGEEOWOFDhCCCGEKHekwBFCCCFEuSMFjhBCCCHKHSlwhBBCCFHuSIEjhBBCiHJHChwhhBBClDtS4AghhBCi3JECRwghhBDlToXsJq4oCgAZGRkaJxFCCCHE7br6vX31e7wkFbLAyczMBCAwMFDjJEIIIYS4U5mZmbi5uZW4j065nTKonDGbzSQkJODi4oJOpyvVc2dkZBAYGEh8fDyurq6leu6yTj6bksnnUzL5fEomn8/NyWdTsrL0+SiKQmZmJgEBAej1Jd9lUyFHcPR6PVWqVLHoz3B1dbX6f1G0Ip9NyeTzKZl8PiWTz+fm5LMpWVn5fG41cnOV3GQshBBCiHJHChwhhBBClDtS4JQyOzs7xo8fj52dndZRrI58NiWTz6dk8vmUTD6fm5PPpmTl9fOpkDcZCyGEEKJ8kxEcIYQQQpQ7UuAIIYQQotyRAkcIIYQQ5Y4UOEIIIYQod6TAKUVTpkyhevXq2NvbExoays6dO7WOZDU2bdrEY489RkBAADqdjsWLF2sdyWpMmDCBli1b4uLigo+PDz179uTYsWNax7IaU6dOpUmTJkWTkIWFhfHPP/9oHcsqffrpp+h0OkaOHKl1FKvw3nvvodPpii1BQUFax7Iq586do2/fvlSqVAkHBwcaN27M7t27tY5VKqTAKSULFy5k1KhRjB8/nr179xIcHEyXLl1ISUnROppVyM7OJjg4mClTpmgdxeps3LiRYcOGsX37dtasWUNBQQEPP/ww2dnZWkezClWqVOHTTz9lz5497N69mwcffJAePXpw+PBhraNZlV27djF9+nSaNGmidRSr0rBhQxITE4uWLVu2aB3Jaly6dIm2bdtiY2PDP//8w5EjR/jqq6/w8PDQOlrpUESpaNWqlTJs2LCiP5tMJiUgIECZMGGChqmsE6AsWrRI6xhWKyUlRQGUjRs3ah3Fanl4eCgzZ87UOobVyMzMVOrUqaOsWbNG6dChgzJixAitI1mF8ePHK8HBwVrHsFrvvPOO0q5dO61jWIyM4JSC/Px89uzZQ3h4eNE6vV5PeHg4kZGRGiYTZVF6ejoAnp6eGiexPiaTiQULFpCdnU1YWJjWcazGsGHDeOSRR4r9P0ioTpw4QUBAADVr1qRPnz7ExcVpHclqLFmyhBYtWvDMM8/g4+NDs2bN+OGHH7SOVWqkwCkFFy5cwGQy4evrW2y9r68vSUlJGqUSZZHZbGbkyJG0bduWRo0aaR3Hahw8eBBnZ2fs7Ox45ZVXWLRoEQ0aNNA6llVYsGABe/fuZcKECVpHsTqhoaHMnTuXlStXMnXqVGJjY2nfvj2ZmZlaR7MKp06dYurUqdSpU4dVq1YxdOhQXn/9debNm6d1tFJRIbuJC2Gthg0bxqFDh+Q+gf9Rr149oqKiSE9P548//qB///5s3Lixwhc58fHxjBgxgjVr1mBvb691HKvTrVu3otdNmjQhNDSUatWq8dtvvzFo0CANk1kHs9lMixYt+OSTTwBo1qwZhw4dYtq0afTv31/jdPdORnBKgZeXFwaDgeTk5GLrk5OT8fPz0yiVKGuGDx/OsmXLWL9+PVWqVNE6jlWxtbWldu3ahISEMGHCBIKDg/n222+1jqW5PXv2kJKSQvPmzTEajRiNRjZu3MikSZMwGo2YTCatI1oVd3d36tatS0xMjNZRrIK/v/91vyTUr1+/3FzGkwKnFNja2hISEkJERETROrPZTEREhNwnIG5JURSGDx/OokWLWLduHTVq1NA6ktUzm83k5eVpHUNznTt35uDBg0RFRRUtLVq0oE+fPkRFRWEwGLSOaFWysrI4efIk/v7+WkexCm3btr1uSorjx49TrVo1jRKVLrlEVUpGjRpF//79adGiBa1atWLixIlkZ2czcOBAraNZhaysrGK/NcXGxhIVFYWnpydVq1bVMJn2hg0bxi+//MLff/+Ni4tL0X1bbm5uODg4aJxOe2PHjqVbt25UrVqVzMxMfvnlFzZs2MCqVau0jqY5FxeX6+7VcnJyolKlSnIPF/Dmm2/y2GOPUa1aNRISEhg/fjwGg4HnnntO62hW4Y033qBNmzZ88sknPPvss+zcuZMZM2YwY8YMraOVDq0f4ypPJk+erFStWlWxtbVVWrVqpWzfvl3rSFZj/fr1CnDd0r9/f62jae5GnwugzJkzR+toVuHFF19UqlWrptja2ire3t5K586dldWrV2sdy2rJY+LX9OrVS/H391dsbW2VypUrK7169VJiYmK0jmVVli5dqjRq1Eixs7NTgoKClBkzZmgdqdToFEVRNKqthBBCCCEsQu7BEUIIIUS5IwWOEEIIIcodKXCEEEIIUe5IgSOEEEKIckcKHCGEEEKUO1LgCCGEEKLckQJHCCGEEOWOFDhCCCGEKHekwBFCCCFEuSMFjhBCCCHKHSlwhBBCCFHuSIEjhBBCiHLn/wGgvkXu0uMHsAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def test_onnx(onnx_model_path = 'model.onnx'):\n",
    "    ort_session = ort.InferenceSession(onnx_model_path)\n",
    "\n",
    "    onnx_y_pred = np.zeros(y.shape)\n",
    "    for idx, _x in enumerate(x):\n",
    "        x_train_np_reshaped = np.array([[_x]])\n",
    "\n",
    "        ort_value = ort.OrtValue.ortvalue_from_numpy(x_train_np_reshaped)\n",
    "\n",
    "        input_name = ort_session.get_inputs()[0].name\n",
    "        inputs = {input_name: ort_value.numpy()}\n",
    "        outputs = ort_session.run(None, inputs)[0][0][0]\n",
    "        onnx_y_pred[idx] = outputs\n",
    "\n",
    "    plot_pred(x, y, onnx_y_pred)\n",
    "    \n",
    "test_onnx(onnx_model_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert model to tensorflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: model_tf\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: model_tf\\assets\n"
     ]
    }
   ],
   "source": [
    "def convert_onnx_to_tensorflow(onnx_model_path = 'model.onnx', tf_model_path = 'model_tf'):\n",
    "    onnx_model = onnx.load(onnx_model_path)\n",
    "    tf_rep = prepare(onnx_model)\n",
    "    tf_rep.export_graph(tf_model_path)\n",
    "\n",
    "tf_model_path = 'model_tf'\n",
    "convert_onnx_to_tensorflow(onnx_model_path, tf_model_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert model to tensorflow lite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_tensorflow_to_tensorflow_lite(tf_model_path = 'model_tf', tflite_model_path = 'model.tflite'):\n",
    "    def representative_dataset_gen():\n",
    "        for i in range(1000):  # Generate 1000 samples\n",
    "            yield [np.array([x[i]], dtype=np.float32)] \n",
    "    converter = tf.lite.TFLiteConverter.from_saved_model(tf_model_path)\n",
    "    converter.optimizations = [tf.lite.Optimize.DEFAULT]\n",
    "    converter.representative_dataset = representative_dataset_gen\n",
    "    # converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]\n",
    "    # converter.inference_input_type = tf.int8\n",
    "    # converter.inference_output_type = tf.int8\n",
    "    tflite_model = converter.convert()\n",
    "\n",
    "    with open(tflite_model_path, 'wb') as f:\n",
    "        f.write(tflite_model)\n",
    "\n",
    "tflite_model_path = 'model.tflite'\n",
    "convert_tensorflow_to_tensorflow_lite(tf_model_path, tflite_model_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4vF8Z23JwKWyYBonHlSrEmz5WXhzaCyYdg/+Lg0cWKDVvily7bw1aV2Xcz/XK6m0qRXhoXRaO6Yyzg4Ytp5N58ccoCvSGSgxSCFHVjBo1CpVKhUqlwsHBgcaNG/Pee+9RUFB2AdHK8NtvvzF16tQKtbVWUlKZpP9b2FTmud24rX2BkQAOcGXQ/dRNPaLMjipyaq2yARz7A1LOFp9zCzS/4ENz4OIe0DhA/U4Wjv46KpVSLDD9uinkl/eDi7cyDscnTGkHkHoBsq+AV6hyO61Qh4ZezHqiI0/O38Pao/G8/uthPhnSuuLrbAkhqp0BAwYwb9488vLyWLNmDePHj8fe3p7JkyebtdPpdDg43GCCRAV5eXnduFE1Jj04wmZydHoW/77C7FjdlaNhdh/libqU/DvpOOh1yn7PN+CO69aTcnBWZjE1jACNDfJ3F+/ifdcA5XHDBzCrJ3zbBTZ+pBw7vx2+bKkcn94Z9Plml+nexJuvH2uHRq3i1/0X+XDNcSu9ASGELWi1Wvz9/WnYsCHjxo0jMjKSFStWmG4rffDBBwQGBtKsWTMALly4wCOPPIKHhwdeXl7cf//9xMTEmK6n1+uZNGkSHh4e1K1bl9dee43rl568/hZVXl4er7/+OkFBQWi1Who3bsycOXOIiYmhd+/eAHh6eqJSqRg1ahQABoOBadOmERISgpOTE23atOGXX34x+zlr1qyhadOmODk50bt3b7M4LUkSHGETer2BqK8e4ZmMr81PFBXlq+MPfadAxyeVMTbezczbhfaG3pNBW8c6AVdUxyeVGVsNu8Ogz8GrkRJ/0YysoplWlw8UvyYjTpmNdZ3+d/jzyZDWAMzeGs3CHTEWDl6IGsRoBF2WbbZKWMPayckJnU75Y279+vWcPHmSdevWsWrVKvLz8+nfvz+urq5s2bKFbdu2UadOHQYMGGB6zWeffcb8+fOZO3cuW7duJSUlhd9//73cnzlixAh+/PFHvvrqK44fP87MmTOpU6cOQUFB/Pqrsg7fyZMniYuL43//+x8A06ZNY+HChcyYMYOjR4/y0ksv8fjjj7Np0yZAScQefPBB7r33XqKionjqqad44403bvvzqQi5RSWsL3YnR1Z8RUTmP8XHujwHO79V9t3qwQsHSk6tXvwInP5L2Q+50zqx3qwOI80HJBfN2jq3ERbeD2mXlOfXDzzOSgKPoBKXe7B9feLScvnkr5O8s+Io9Tyc6NvczzKxC1GT5GfDh4E3bmcJ/7lcdqHQGzAajaxfv56//vqL559/nqSkJFxcXJg9e7bp1tSiRYswGAzMnj0bVeEt73nz5uHh4cHGjRvp168fX375JZMnT+bBB5Ve7hkzZvDXX3+V+XNPnTrFsmXLWLduHZGRkQCEhoaazhfdzvL19cXDwwNQenw+/PBD/vnnHyIiIkyv2bp1KzNnzqRnz5589913NGrUiM8++wyAZs2acfjwYT7++ONb+nxuhiQ4wnr0+XBxD9lLRtImLxGAOP8+BAz9AjyDIfwZyElVKhOXVjdm6CJIOqGMr/FpVvJ8VeZWOL08+aRSSyfz+gSn7IHIz/VqROyVbH7ae4HnfzzAsmciShY+FEJUa6tWraJOnTrk5+djMBh47LHHeOeddxg/fjytWrUyG3dz8OBBzpw5g6urq9k1cnNzOXv2LGlpacTFxREeHm46Z2dnR8eOHUvcpioSFRWFRqOhZ8+eFY75zJkzZGdnc9ddd5kd1+l0tGunlOc4fvy4WRyAKRmyNElwhPVs+BC2fo4zkG505kjwSLoOmVi8uKVnMHiW83o7B2WhzOro2jo4s/uWPF/OVHKVSsX7D7TkUmoOW88k8+T8PayY0L3sGkFCCKV0xH8u2+5n36TevXvz3Xff4eDgQGBgIHZ2xV/PLi7mvUGZmZl06NCBxYsXl7iOj49PiWMV4eTkdNOvyczMBGD16tXUq2de60urLbu4qbVIgiOsJuf8Xor+F/oz4DkeGfVm8Yyims7eCe58FQ7+BGnXrETu6A65abDyRVjzSvFxrRsMWwz1Oyov16j59vH2DPluO6cSMhm3eB9Ln+4iSzoIURaV6pZvE9mCi4sLjRs3rlDb9u3b89NPP+Hr64ubW+n1vgICAti1axd33qnczi8oKGDfvn20b9++1PatWrXCYDCwadMm0y2qaxX1IOn1xbW5WrRogVarJTY2tsyen+bNm7Nihflkkp07d974TVYCGWQsrCIrr4CkS+cAmOI5jcFP/cd077jW6PMmPLVOqbYMYO8CXQpXMzfkK2MGirbM+OKp8YXcHO35fkRH3BztOBCbyjsrjln5DQghqoLhw4fj7e3N/fffz5YtW4iOjmbjxo288MILXLyolKl48cUX+eijj1i+fDknTpzgueeeK7eGTXBwMCNHjuTJJ59k+fLlpmsuW7YMgIYNG6JSqVi1ahVJSUlkZmbi6urKK6+8wksvvcSCBQs4e/Ys+/fv5+uvv2bBggUAPPvss5w+fZpXX32VkydPsmTJEubPn2/pjwiQBEdYgVFfwLyFc2hgUP7He2Fwr9rb8+DqDy8fhxcPwSunoNfr8Mpp5XnRFjFBaVvKbauGdV346tF2qFTw4+5YluyKLdFGCFGzOTs7s3nzZho0aMCDDz5I8+bNGTNmDLm5uaYenZdffpknnniCkSNHEhERgaurKw888EC51/3uu+8YMmQIzz33HGFhYYwdO5asrCwA6tWrx7vvvssbb7yBn58fEyYov6emTp3KW2+9xbRp02jevDkDBgxg9erVhISEANCgQQN+/fVXli9fTps2bZgxYwYffvihBT+dYipjWSOOarD09HTc3d1JS0srs3tPVJ4NP39D76P/B4ARFar/i1Nu2YjS7ZkDqycpq58PK3mPHWD6hjN88tdJ7DUqlj4dQYeG5Q1eEqLmy83NJTo6mpCQEBwdZXxadVbev+XNfH9LD46wqJ3nrnD60A7Tc9Vd70lycyMuhYMEyxl4/FyvRgxs6U++3sj4xftJydJZKTghhKgeJMERFnMlM48XfjyAP1cAMPZ7H7q9YOOoqoGiBCf+CPzwoLJtNK8ZoUo8ztfqz/jJ5VPaZ27klZ8Pljn9UwghaiOZRSUswmg08srPB2metZv7HJQeHJV7yUJ2ohReIaDSQH4WnF2vHDu7HjqMAtfCIn9752J3ajXhQID9Re480YU5W6N5qkdoWVcVQohaRXpwhEXM2xZDwqk9LHC4pufBo4HtAqpOXP2V2VYPzFQ2Rw/leGZCcZu8dNNuoJ2y//HaE0RdSLVenEIIUYVJgiMq3ZFLaXz05wmaqK5ZVbvHyxDYznZBVTf1OkCbYcrmXlgF+doxObos066dPpfBd7iTrzfy/I/7ScvJRwghaju5RSUqVd7u+WjWfsMPGg3aOl6QDbQeBn3ftnVo1VfRCuWLHoTA9uDZUFnS4hrvRfqz97KOCyk5TPnjCF8Ok2RS1E4yFq36q6x/Q0lwRKXKWvcRzQ1xSt9gduHBoh4IcWtcrim9fnm/sl3Hbf93LGvuwcxdySyLupPVLfwZ1DrAikEKYVv29vYAZGdn39KyA6LqyM5WvjyK/k1vlSQ4otL8cyyBcF0qXF+g2DPYBtHUIG4VWBF5z2wCgXftwQD833JXOgV74usm9UBE7aDRaPDw8CAxUVnI19nZufZVS6/mjEYj2dnZJCYm4uHhgUZzewVhrZLgTJ8+nU8++YT4+HjatGnD119/TefOnUtt26tXLzZt2lTi+N13383q1asBGDVqlKkMdJH+/fuzdu3aEq8T1nE1S8f//XqAXaoc5UC/9yH5NDjXhTvKr54pbiD8WdAXKGvrXD4A57cVn+v/IVw5Awa90rMTf5h2rmn8kJrPa78eYt6oTvJLXtQa/v7Kwr1FSY6onjw8PEz/lrfD4gnOTz/9xKRJk5gxYwbh4eF8+eWX9O/fn5MnT+Lr61ui/W+//YZOV1y07MqVK7Rp04aHH37YrN2AAQOYN2+e6XlVWLm0Nnt7xVHys65CUYdBl+dAXUuXY6hsboEwoLC0+fLnzBOc4O4QUbie1bb/QfxhIhuocMhUs/FkEkt2xzI8vKH1YxbCBlQqFQEBAfj6+pKfL4PtqyN7e/vb7rkpYvEE5/PPP2fs2LGMHj0agBkzZrB69Wrmzp3LG2+8UaK9l5eX2fOlS5fi7OxcIsHRarWVkuGJ27f7r8W0PrqKSPs05YDWXZIbS3G6bkkG+2tWSy4cq+OmT+W1/s14f/Vx3l91nG6NvAn2rj6rKgtxuzQaTaV9SYrqy6LTxHU6Hfv27TNbel2tVhMZGcmOHTvKeWWxOXPmMGzYMFxczH9Bb9y4EV9fX5o1a8a4ceO4cuVKpcYuKibpahptdrzIWLs13K8p7Flw8rBpTDVaUU2cIg7OxftFg5FTY3my/mVG1buEc34Kr/96CINBZpYIIWoXiyY4ycnJ6PV6/Pz8zI77+fkRHx9/w9fv3r2bI0eO8NRTT5kdHzBgAAsXLmT9+vV8/PHHbNq0iYEDB6LX60u9Tl5eHunp6WabuH1Go5Evf9uIluu6gq/vZRCV5/rk0eHaHpzC6eRXzqBeMIh3rrzKP9rXiIqO58c9suq4EKJ2qdKzqObMmUOrVq1KDEgeNmyYab9Vq1a0bt2aRo0asXHjRvr27VviOtOmTePdd9+1eLy1zdoj8Zw7exIcIL9OIPYBLSH1gjIoVlhGs7vhyG+QnQyhvcDRvficXytocT8kHleeXzmDJxn4q1L4aM0J+oT5EuAu02eFELWDRXtwvL290Wg0JCQkmB1PSEi44fiZrKwsli5dypgxY274c0JDQ/H29ubMmTOlnp88eTJpaWmm7cKFCxV/E6JUaTn5/L58GfPtlaUY7H2bwfCfYfxOaPuojaOrwdzrwZN/woQ9cPcn5uc0dvDIQuXchD1QuPZXhL+BjLwC3vz9iBRBE0LUGhZNcBwcHOjQoQPr1683HTMYDKxfv56IiIhyX/vzzz+Tl5fH448/fsOfc/HiRa5cuUJAQOmFzbRaLW5ubmabuD0frz3B8/lz0aoKlAPeTW0bkCipcEzO8+Ee2GtUrD+RyMpDcTYOSgghrMPia1FNmjSJ77//ngULFnD8+HHGjRtHVlaWaVbViBEjmDx5conXzZkzh8GDB1O3bl2z45mZmbz66qvs3LmTmJgY1q9fz/3330/jxo3p37+/pd+OAHZHp7BkVyzuFK6H1HII9HzdtkGJkgoTnHp2GUzo3QSAd1ccJSVLV96rhBCiRrD4GJyhQ4eSlJTE22+/TXx8PG3btmXt2rWmgcexsbGo1eZ51smTJ9m6dSt///13ietpNBoOHTrEggULSE1NJTAwkH79+jF16lSphWMFeQV6Jv92CAAPBz0UAN0ngkvdcl8nbKBo0PGql5jQ4UnW+D3AyYQMPlh9nM8eaWPb2IQQwsJUxlp4Uz49PR13d3fS0tLkdtVN+vKfU3z5z2m862jZox6FSpcBz++Huo1sHZq43uFf4NfCMWxOnhx49AAPfrcdoxGWPRNB5xCv8l8vhBBVzM18f1v8FpWoOc4kZvLthrMAvHNfC1QFhcsy2MvMnCqp1RB48aCyn3OVdvXqMKxTAwDeWn6EfL3BhsEJIYRlSYIjKsRoNDJlxRF0egO9m/kwqIU3GAoHGEuCU3W5NwBV4f/m2Vd4rX8zPJ3tOZmQwfxtMTYNTQghLEkSHFEhaw7Hs+3MFRzs1Lx7X0tUBbnFJ+0kwamy1GplwVOArGQ8XRyYPLA5AF/8c4q4tBwbBieEEJYjCY64oWxdAe+vPgbAuJ6NaFDXGfKLvhhVYCeDu6u0oiUcZnSDc5sY0qE+HRp6kq3TM3XVMdvGJoQQFiIJjrihb/49Q1xaLvU9nRjXq3AwcX628mjvDCqV7YITN+YTVry/YzpqtYqp97dErVJ65jadSrJdbEIIYSGS4IhynUvK5Pst5wB4+54WOOalwJWzkJuqNJDxN1Xfvf+D9iOV/UylqniLQDdGdQ0BYMofR8grKH0dNyGEqK4kwRFlMhqNvLvyGPl6Iz2b+nCX43H4tAl83R5m9VIaSYJT9Tm6FSc4Wcmmwy/d1QRfVy0xV7KZuzXGNrEJIYSFSIIjyrTuWAKbTiXhoFHzzn13oDq/HbiubJIkONVDUdG/jMuwbCR80xnXZQ/zn771APjm39MkZuSWcwEhhKheJMERpcrN1/Ne4QDUp3qEEOLtAmkXSzaUNaiqh6IEx2iAY8sh+SSc28B9rqdoU9+dLJ2eT/86adMQhRCiMkmCI0o1f3sMF6/m4OemZUKfxpB+GY79oZy8/1sY8w+M/hMemmPbQEXFOLiAU8nKxercVN6+twUAP++7yJFLadaOTAghLEISHFFCcmYe0/89A8Br/cNwzroEX7aC/MLFNT0bQlAnaNgV7B1tGKm4KUPmQpfn4M5XoUnhwrS5qXRo6MV9bQIxGuG9lceohau3CCFqIElwRAlf/nOKjLwCWtZz44F29SAuqrhqceNIqN/JpvGJW9SoNwyYBn3eBK9Q5VjOVQDeGBiGo72a3TEprDkcb8MghRCickiCI8ycSshgya5YAN4c1AK1WgVpl5STdzwAj/8qhf1qAicP5XHfAlj5IoF7pvFChDJO58M1x8nNl2njQojqTRIcYebDNccxGKH/HX50Ca0LqbGwb55y0q2ebYMTlcfJU3nMSYF982Hb/3jKbRcB7o5cSs1hdmHtIyGEqK4kwREmm04lsfFkEvYaFW8MbA656TCjBySfUhq4B9k2QFF5Shlw7JCTxBsDlarHMzad40pmnrWjEkKISiMJjgCgQG/gg8L1pkZEBBOy/yP4b6hSsVjrBo36Qov7bRukqDxNIqHpAKjfGRp0VY7lXOXe1oG0qudOZl4BXxcONBdCiOpIEhwBwLK9FzmVkImHsz0v9GkCB5eCIV852edNeOI3cAuwbZCi8jh5wmM/wVProOWDyrGcq6jVKiYX9uIs2nmemOQsGwYphBC3ThIcQVZeAf/7+zi91Qf4X4tTuGecgqxE5eSEvRD+jG0DFJbl6KE8Fq4v1rWxNz2b+lBgMPLJ31L8TwhRPUmCI5izNZpuOf8yz+ETeh75P/iu8JaFnRPUbWzb4ITlFQ04TrsIeqUcwBsDw1CpYPWhOKIupNouNiGEuEWS4NRyKVk6Zm0+R31VcsmT7vVApbJ+UMK6iqaMp5yDz5pBRjzNA9x4sF19AKatOS7F/4QQ1Y4kOLXc9A1nyMwrIMi18IBKA6rC/yya32ezuIQV+TYHz2BlPzsZYncC8HK/pjjYqdkVncK/JxJtF58QQtwCSXBqsUupOfyw4zwAEQ1clIPdX4L/S1C2yCk2jE5YjYMLPH8Amt2tPE9XCjsGejgxulswAB/9eYICvcFGAQohxM2TBKcW++qvo/joE+gT7Eg9l8JbEPZOYOcga0zVNmo11G2k7J/fDgU6AJ7r1RgPZ3tOJ2by6/5SVpMXQogqShKcWupU3FWePTqcbY4vMjtxKKrYHcoJeyfbBiZsx00Zc8OJVfBtOOgLcHeyZ0JvZaD5//45TV6BLOEghKgeJMGppWas3UuIWllUUW3IhyunlROS4NReTe4qrladcg4yEwB4vEtD/N0cuZyWy4+F65QJIURVJwlOLbTvfAo7T14u/aS9s3WDEVVH3Ubw0hFw8VGeF6407mivYUIfpRfnmw1nydYV2CpCIYSoMElwahmj0ch/157EUaUrvYH04AjTQpxXTYce6RhEkJcTyZl5LCwcmC6EEFWZJDi1zLYzV9gVnUIdTRljKaQHR1xX2RjAwU7NxL5NAZix6SzpufnWj0sIIW6CJDi1iNFo5PN1Sun9+1qWXE0akB4cUWoPDsDgdvVo5ONCanY+c7ZE2yAwIYSoOElwapFNJxNpfWkpUx0W8rhhRemN7CTBqfWKEpwVz0PMNtNhjVrFpLuaAcryHlezyrjNKYQQVYAkOLWE0Whk+do/ecd+IU+o1+J4amXpDV3qWjcwUfW4BRbv/zHe7NTAlv60CHAjM6+AGZvPWjkwIYSoOKskONOnTyc4OBhHR0fCw8PZvXt3mW3nz5+PSqUy2xwdzYvOGY1G3n77bQICAnByciIyMpLTp09b+m1Ua+uPJ5KUGF/yRL2OcO9XcOer8NCc4pL9ovaKmADhzyr7qedNC3ACqNUqXu6njMVZsD2GxPRcW0QohBA3ZPEE56effmLSpElMmTKF/fv306ZNG/r3709iYtlr27i5uREXF2fazp83n7Xx3//+l6+++ooZM2awa9cuXFxc6N+/P7m58su2NAaDkc/XncKRUm4p2DtBh5HQ501oNcT6wYmqx6Uu9J8GanswGiDTPDHuE+ZLuwYe5OYbmL7hjI2CFEKI8lk8wfn8888ZO3Yso0ePpkWLFsyYMQNnZ2fmzp1b5mtUKhX+/v6mzc/Pz3TOaDTy5Zdf8uabb3L//ffTunVrFi5cyOXLl1m+fLml30619PexeI7FpeNhX8rMKTut9QMSVZ9aDW4Byv7KifDrWFj9MmQkoFKpeLWfMhbnx90XuJyaY7s4hRCiDBZNcHQ6Hfv27SMyMrL4B6rVREZGsmPHjjJfl5mZScOGDQkKCuL+++/n6NGjpnPR0dHEx8ebXdPd3Z3w8PAyr5mXl0d6errZVlsYDEa+WKfcvruriVvJBnay5pQog7eSxHBmHRxeBntmw8ElAHRt7E14iBc6vYEZm2QsjhCi6rFogpOcnIxerzfrgQHw8/MjPr6U8SBAs2bNmDt3Ln/88QeLFi3CYDDQtWtXLl5UFvoret3NXHPatGm4u7ubtqCgoNt9a9XG6sNxnEzIwNXRjp4hriUbSA+OKMu9X8KAj6H/hxDcQzl2zdTxF/s2AWDp7gvEp8ntYSFE1VLlZlFFREQwYsQI2rZtS8+ePfntt9/w8fFh5syZt3zNyZMnk5aWZtouXLhQiRFXXXqDkS//OQXA2B6hOKlLKc4mPTiiLO71ocuzEDEeGnRRjumyTacjGtWlU7Cn9OIIIaokiyY43t7eaDQaEhISzI4nJCTg7+9foWvY29vTrl07zpxRBjMWve5mrqnVanFzczPbaoNVhy5zNikLdyd7RncLhvxSxkpIgiMqoqjCdX5xgqNSqXixsLrxj7tjZUaVEKJKsWiC4+DgQIcOHVi/fr3pmMFgYP369URERFToGnq9nsOHDxMQoAx4DAkJwd/f3+ya6enp7Nq1q8LXrA0MBiPf/KskhWN7hODqaA8FecpJ52tq3Vxb80SIsji4KI+6LLPD3RrXpX0DD/IKDMzcfM4GgQkhROksfotq0qRJfP/99yxYsIDjx48zbtw4srKyGD16NAAjRoxg8uTJpvbvvfcef//9N+fOnWP//v08/vjjnD9/nqeeegpQ/mqcOHEi77//PitWrODw4cOMGDGCwMBABg8ebOm3U22sPRrP6cRMXB01jGzjooydKCjswWk9DB79CR5eoNx+EOJGSunBgcJenEilF2fxrvMkZeRZOzIhhCiVnaV/wNChQ0lKSuLtt98mPj6etm3bsnbtWtMg4djYWNTq4jzr6tWrjB07lvj4eDw9PenQoQPbt2+nRYsWpjavvfYaWVlZPP3006SmptK9e3fWrl1boiBgbWU0Gvm6sPfmR58fcP16lXJCba88OrhAswE2ik5USw6FCY4uu8SpO5t40zbIg6gLqczafJb/G9SiRBshhLA2ldFoNNo6CGtLT0/H3d2dtLS0Gjke559jCTy1cC8uDhoOu72I+rpCbfR5C+58xTbBierp5Fr4cSgEtoOnN5Y4veFEIqPn78HJXsOW13vjXUdm5wkhKt/NfH9XuVlU4vYovTdK3ZsnujREnX2lZCNZMVzcrKIenLxM2DcftnwGZ4rHwfVq5kPr+u7k5Ov5fouMxRFC2J4kODXM5tPJHLyYhqO9mrGd64KhlKnhjh5Wj0tUc/aFg4yvnIaVL8L692DJI6a6OMqMKqUuzg87zpMiK40LIWxMEpwaxGg08vV6pfdmeHhD6lJYsVnrBg/MhHZPQPeXoMV9NoxSVEtFs6iuZSiAzOI15fqE+dKynhvZOunFEULYniQ4NciOc1fYe/4qDnZqJjQ4D990UE64eEObYXD/NxD5DmhLqWgsRHnqNobQXkqJAd87imdVXVPZWKVS8UKf4l6ctOxSeg+FEMJKJMGpQYrq3gztGITnyWXFJ/xb2ygiUWNo7GDEH/DaOXhuO/iEKcdzUs2aRTb3I8zflcy8AhbuiLF6mEIIUUQSnBpi3/kUtp+9gr1GxbO9GhXXK2k/Ah783rbBiZrHyUN5vKYHB0CtVjGuVyMA5m6LJltXYOXAhBBCIQlODfHVeqX35qH29ann4VSc4IT0BDsHG0YmaiQnT+XxugQHYFCrABp4OXM1O5+lu2vHum9CiKpHEpwa4PDFNDadSkKjVvFcr8bKwfzCdYFkrSlhCUUz8da/Bx8HwydN4MBiAOw0ap7tqfTifL/lHLoCg21iFELUapLg1AAzNp1FjYFvAv+mwZZXYdtXxT04UvNGWEL9TspjQY7Si5OVCAd/NJ1+qEM9fF21xKXlsvzAJRsFKYSozSy+VIOwrOjkLNYciaOD6hQDk+dB8nUNima7CFGZ2j4KIXcqi29e2gvLx0FW8X98WjsNY3uE8sGa43y36SwPdaiPRq2yYcBCiNpGenCquZmbzmI0Qq/6mtIbSA+OsBT3euDTFALaKM+zksxOPxbeAHcne6KTs/jzSJwNAhRC1GaS4FRj8Wm5/Lr/IgCDwuqU3kgSHGFpLj7KY/YVMOiLD2vtGNU1GIBvN5ylFi57J4SwIUlwqrG526LJ1xvpHOxFSFlrjkmCIyzNyQtQAUZY9BCkxppOjeoajLODhmNx6Ww8lVTmJYQQorJJglNNpWXns37nPoZoNjEl9ARklvHlIWNwhKVp7MArRNk/twH2zjOd8nRxYHh4AwC+3XDGFtEJIWopGWRcTf2wM4bP+Jy29mdhezkNpQdHWMPwX+DHYZB8yqwHB+CpHqEs2H6ePTFX2R2dQucQLxsFKYSoTaQHpxrK0emZty2GQNWVGze2kwRHWEHdRtBrsrKfdtHslJ+bIw91qA/AtxulF0cIYR2S4FRDP++7wJUsHU6qUhYzbDpAWT0coOlAUMs/sbAS9yDl8cJO2LfA7NSzPUNRq2DjySSOXk6zQXBCiNpGvv2qmXy9gZmbzgHgrC4lwQntDa+fh7euwGNLrRydqNXqNkIZbAysfQN2zTSNDWtY14VBrQMB+H7zORsFKISoTSTBqWZWH4rjUmoO3s52aAy6kg2cPJVeG40MrxJW5uwFz+1U9vOz4c/XYP27ptPP3BkKwMpDcVy8mm2LCIUQtYgkONWIwWDku41nARjbNbD4RL/3ofVQiJgAYYNsFJ0QgG8YjP6z+Hn6ZdNuy3rudGtcF73ByNytMdaPTQhRq8if+dXIrj3bef/qy3hoc2iQM7D4RPg46bERVUfDrvDID7DsCWUph2s8fWcjtp25wtI9sbzYtwnuzvY2ClIIUdNJD041cn7zEjqpT9FEdQHtvlnKQbWdJDei6nFwUR51mWaH72ziTZi/K9k6PYt2nbdBYEKI2kISnGpi3/mrpKddLXlCpoGLqkjrqjzmZZgdVqlUPNNTGYszb1sMufn6618phBCVQhKcamL2lnO4kFvyhJ3W+sEIcSMOhWujXXeLCuCe1oEEujuSnJnH7wcuWTkwIURtIQlONXD+ShZrj8bjosopeVIqFYuqqIxbVAD2GjVPdleWdvh+8zkMBlmEUwhR+STBqQbmbI3GaISGdUr5IrBztH5AQtxI0S2qglzQF5Q4PaxzA1wd7TiXnMW64wlWDk4IURtIglPFXc3SsWzvBQBC3UpJcOwlwRFVUNEtKoCTq+H0P5B43HSojtaOJ7o0BGCWFP4TQliAJDhV3KKd58nNN9CynhtumsLCfipNcQN7F9sEJkR57BxAUzg+bNkIWPwQfNsFEo6ZmozqGoyDRs2+81fZG5Nio0CFEDWVJDhVWG6+ngU7YgAY2yMUVdF4hu4vQf1OENgeuoyzXYBClKfX6+DfWtmKEvGUs6bTvm6OPNi+HgAzpRdHCFHJJMGpwpYfuERypo4G7vbcE/8tJJ9STjS/B576B57eAHcMtmmMQpSpx8vw7BZlC+qkHNOZL9HwVA9lyvi6YwmcSSw5IFkIIW6VVRKc6dOnExwcjKOjI+Hh4ezevbvMtt9//z09evTA09MTT09PIiMjS7QfNWoUKpXKbBswYICl34ZVGQxGvt+i/FU7uXkSmp3fKCdUanANsGFkQtyCoh6cfPNp441963BXCz9AKYUghBCVxeIJzk8//cSkSZOYMmUK+/fvp02bNvTv35/ExMRS22/cuJFHH32UDRs2sGPHDoKCgujXrx+XLpnXyxgwYABxcXGm7ccff7T0W7GqDScTOZuUhaujHb0bXDPmZsQf4Opvu8CEuBUOzsqjruQim0WLcP62/xKJ6aXUehJCiFtg8QTn888/Z+zYsYwePZoWLVowY8YMnJ2dmTt3bqntFy9ezHPPPUfbtm0JCwtj9uzZGAwG1q9fb9ZOq9Xi7+9v2jw9PS39VqyqaGbJY+ENcNQXdt2H3QMhd9owKiFukX1hgpNfMsHpGOxF+wYe6PQG05gzIYS4XRZNcHQ6Hfv27SMyMrL4B6rVREZGsmPHjgpdIzs7m/z8fLy8vMyOb9y4EV9fX5o1a8a4ceO4cuVKmdfIy8sjPT3dbKvKDl5IZVd0CnZqFaO7hhSXu9e62TYwIW6VqfBfycrGAE8X9uIs3hVLjk6WbxBC3D6LJjjJycno9Xr8/PzMjvv5+REfH1+ha7z++usEBgaaJUkDBgxg4cKFrF+/no8//phNmzYxcOBA9PrSfzFOmzYNd3d30xYUFHTrb8oKisbe3Nc2EH93R8gtTMgcJcER1VQ5PTgAd7XwJ8jLidTsfH7df9GKgQkhaqoqPYvqo48+YunSpfz+++84OhYXtBs2bBj33XcfrVq1YvDgwaxatYo9e/awcePGUq8zefJk0tLSTNuFCxes9A5u3oWUbNYcjgPgmc51Ie0i5BTWCJEeHFFdlTMGB0CjVvFkN2X5hrlbo2X5BiHEbbNoguPt7Y1GoyEhwbwUe0JCAv7+5Q+U/fTTT/noo4/4+++/ad26dbltQ0ND8fb25syZM6We12q1uLm5mW1V1dxt0RiM8EzQBZotaANf3AH75isnpQdHVFdlzKK61sMdg0zLN2w4WfokBCGEqCiLJjgODg506NDBbIBw0YDhiIiIMl/33//+l6lTp7J27Vo6dux4w59z8eJFrly5QkBA9Z4+nZadz097lN6l4b7nwXjdLbei9X2EqG6KenDOrIcZPWDmnbBrplmTOlo7HuvcAIDZW6KtHaEQooax+C2qSZMm8f3337NgwQKOHz/OuHHjyMrKYvTo0QCMGDGCyZMnm9p//PHHvPXWW8ydO5fg4GDi4+OJj48nM1OZSZSZmcmrr77Kzp07iYmJYf369dx///00btyY/v37W/rtWNTi3efJ1ukJ83clSFPKoGnvptYPSojKULeJ8piXDvGHIO4gbPq4RLORXYPRqFXsOHeFI5fSrBykEKImsbP0Dxg6dChJSUm8/fbbxMfH07ZtW9auXWsaeBwbG4taXZxnfffdd+h0OoYMGWJ2nSlTpvDOO++g0Wg4dOgQCxYsIDU1lcDAQPr168fUqVPRarWWfjsWoyswMH9bDADPd3ZFtfkv5cT908E9CJw8wb+V7QIU4nY06ALPbIHMRMhLg1+ehOwUZaVxTfGvoUAPJwa1CmDFwcvM3RrN50Pb2i5mIUS1pjIajbVuNF96ejru7u6kpaVVmfE4v+2/yKRlBwl3TWKp/hVUhnzlxOg/oWFX2wYnRGXSF8BUb8AIr5yGOr5mpw9dTOW+b7Zhp1ax9fU+ykxCIYTg5r6/q/QsqtrCaDQyZ8s5PrGbwQLj20pyY+8CwT2gXgdbhydE5dLYgXNdZT8rqcTp1vU96BzsRYHByEIp/CeEuEUWv0Ulbmx3dApJcbE87LgZCgoPPrIAmtxl07iEsBgXH8hOVsbhuAYWH3cLgC7jGdMjhN0xKSzeFcuEPo1xdpBfVUKImyO/NWxJXwCX9rFl3REaqa8ZVPz8fqjbyHZxCWFpHg0g6Tgc+6PkOb+WRDbvQ8O6zpy/ks2v+y7yRESw1UMUQlRvkuDY0vp3YftXvALgUHgsKFySG1Hz9f8QAtuCoaD42OFfIPU8ZF9Bo1YxpnsIb/9xlDlboxke3hC1WmWzcIUQ1Y8kOLaUdKLkMbd61o9DCGvzbgy9/2N+LPG4kuAUrlc1pEN9Pvv7FDFXsll/IpG7WviVciEhhCidDDK2oYKcUup8hPSwfiBCVAXXrVfl7GDHY+FFhf/O2SoqIUQ1JQmODaVfVcbdvOH8LsYXomDSCej4pG2DEsJWSlmvamREMHZqFbuiUzh8UQr/CSEqThIcG9EbjORnpwLQu21TVF4hygwSIWqrUtar8nd35N42yiyrOVulF0cIUXGS4NjI30fjcTIof6n2ai2DioUoa8XxMd2VVcZXHYojLi3H2lEJIaopSXBsZN7Ws9RB+WWtreNp42iEqAJMY3DMVxxvWc+dLqFK4b8F28/bIDAhRHUkCY4NHD6fSPDF5ahVhatkyCrhQoBD4S2q7KtwaBnsnQdXzgLwVPdQAJbsOk9WXkFZVxBCCBNJcGzg6J8z+a/998oTOyewk7V2hDD14JxcDb+NhVUTYclQAPqE+RLi7UJ6bgG/7LtouxiFENWGJDhWFp+WS9qlU8UHBn0KKilgJoSpB+da6ZcBUKtVPNktGIB526IxGGrdGsFCiJskCY6VLdwRg6sxQ3nS+/+g3eO2DUiIqqJBF3AtnElYp7CoX342GJVk5qEO9XF3sjcV/hNCiPJIgmNFOTo9S3bH4q4qHETpJIOLhTBxrw8vn4B30mDC3sKDRijIA5TCf492lsJ/QoiKkQTHWnTZ/LNlC3bZyfjbF051dfSwaUhCVFn2TsX7+dcU/uva0FT478glKfwnhCibJDjWUJCH8esO3LvlfnZrn6OD4bByXHpwhCidxh7UhUvlFeSaDge4O3F3K+U21tyt0baITAhRTUiCYw1XY1BlFA6WVF0zOFISHCHKZqqLY17c76keSuG/lYcuk5iee/2rhBACkATHOtIumHaNFM6YsnMCrxAbBSRENVB0myrfvLJx6/oedAr2JF9vZOEOKfwnhCidJDiWpssmbe8yADbq2xA/YhuMXgsvRoGzl21jE6IqMyU4JZdnKFq+YfGu8+Tm660ZlRCimpAEx9IWD8H9xE8AqD2DCAi9AxpGgKu/jQMTooqzKzvBuauFP0FeTlzNzue3/ZesHJgQojqQBMfCDPHKgOIcowN1uz9p42iEqEaKenBWvgD/DYUfHwODAQCNWsWorkovztxt0RiNUvhPCGFOEhxL0hegzksH4Cmv+bTo1MfGAQlRjRQNMr4aA9lXlCUc0ouXaXikY33qaO04k5jJplNJtolRCFFlSYJjQbqsq6b9R7q3RCVLMghRcXV8Sx7LSjbtujraM7RTEABzZMq4EOI6kuBY0MaDyppTmTgxsE2QjaMRoprpNxXumgp3vVdcFPOaBAdgVNdg1CrYcjqZk/EZ1o9RCFFlSYJjIUajkbV7jgNg0HrgYCcftRA3xb0+dHsBur0I9Toox7LMb0UFeTnT/w5lwL4U/hNCXEu+dS3k2J5/eSftTQCc3b1tHI0Q1ZyLj/L4x3Nw7A+zU0VTxn+PukRyZp61IxNCVFGS4FiIfuPHuKmU6a12daWgnxC3pW7j4v21k81OdWjoSZsgD3QFBhbvjLVyYEKIqkoSnMpUkAc5qcQmpeOYqcz2yGh8Pwz6zMaBCVHNRTwHke8q+5kJpuniACqVytSL88PO8+QVSOE/IYQkOJUragl83BC37zvRVK0UH3Md8Fbps0GEEBXn4AJdnlP2DQWQm2p2emBLfwLcHUnOzGNF1GXrxyeEqHKskuBMnz6d4OBgHB0dCQ8PZ/fu3eW2//nnnwkLC8PR0ZFWrVqxZs0as/NGo5G3336bgIAAnJyciIyM5PTp05Z8CzfFQxdf/MStnu0CEaImsXMAR3dl/7rZVPYaNSO7BgPKlHEp/CeEsHiC89NPPzFp0iSmTJnC/v37adOmDf379ycxMbHU9tu3b+fRRx9lzJgxHDhwgMGDBzN48GCOHDliavPf//6Xr776ihkzZrBr1y5cXFzo378/ubk2Xlm4/Qj2Nhpvemr0CgUHZxsGJEQNUzTYeM9s2DEd9i8EnbIY56OdGuBkr+FEfAY7zl6xYZBCiKpAZbTwnzrh4eF06tSJb775BgCDwUBQUBDPP/88b7zxRon2Q4cOJSsri1WrVpmOdenShbZt2zJjxgyMRiOBgYG8/PLLvPLKKwCkpaXh5+fH/PnzGTZs2A1jSk9Px93dnbS0NNzc3CrpnYLeYKTvJ+sITtvDmM6+9Oh9N7hLD44QlWb+PRCzxfxY/w8hQvnD4u0/jrBwx3n6hvkyZ1QnGwQohMjWFXDwQhpdQr0qvcDtzXx/W7QHR6fTsW/fPiIjI4t/oFpNZGQkO3bsKPU1O3bsMGsP0L9/f1P76Oho4uPjzdq4u7sTHh5e5jXz8vJIT0832yxh3bEEYq7mc9CxE50GPSnJjRCVre8UaPMYtHoE/Foqx67GmE6P7haCSgXrTyRyNinTNjEKUcv9tv8Sj36/k3GL9ts0DosmOMnJyej1evz8/MyO+/n5ER8fX+pr4uPjy21f9Hgz15w2bRru7u6mLSjIMlWFr2Tl4aq147HwBjjaayzyM4So1YI6wQPfwUPfQ7snlGOZxbe7Q7xd6BumDOqft00K/wlhbQaD0fT/XpdQL5vGUitmUU2ePJm0tDTTduHCBYv8nOHhDdnxn748fWcji1xfCHENl8ICmtcNOH6ycMr4r/sukZqts3ZUQtRqm04ncTYpC1etHUM62naJIosmON7e3mg0GhISEsyOJyQk4O/vX+pr/P39y21f9Hgz19Rqtbi5uZltllJHa4e7k73Fri+EKFQ04Dj9Ilzar2w5V4kIrUvzADdy8vUs2S2F/4SwpqIlU4Z2CqKO1s6msVg0wXFwcKBDhw6sX7/edMxgMLB+/XoiIiJKfU1ERIRZe4B169aZ2oeEhODv72/WJj09nV27dpV5TSFEDVSU4FyNge97K9tX7VEV5PJUYS/Owu3nydcbyr6GEKLSnErIYMvpZNQqTGUbbMnit6gmTZrE999/z4IFCzh+/Djjxo0jKyuL0aNHAzBixAgmTy4uvf7iiy+ydu1aPvvsM06cOME777zD3r17mTBhAqBULZ04cSLvv/8+K1as4PDhw4wYMYLAwEAGDx5s6bcjhKgqfJpBs0HgHqRsqCAnBTLiuLdNID6uWuLTc1lzOM7WkQpRK8zbFgNAvxb+BHnZvkSKxfuPhg4dSlJSEm+//Tbx8fG0bduWtWvXmgYJx8bGolYX51ldu3ZlyZIlvPnmm/znP/+hSZMmLF++nJYtW5ravPbaa2RlZfH000+TmppK9+7dWbt2LY6OjpZ+O0KIqkKtgUeXFD//pLGy2rguGwc7NSO6NOSzdaeYszWa+9oEVvp0VSFEsatZOn7bryxRVDQOztYsXgenKrJUHRwhhA192RpSz8OYdRDUmZQsHRHT1pNXYODnZyPoFGzbGR1C1GTTN5zhk79O0rKeGysndLfYHxRVpg6OEEJYjYOL8qjLAsDLxYEH2yu1qOZskSnjQlhKvt7Awh0xADzZLaTK9JZKgiOEqBnsC+/552ebDj3ZTekq//tYPLFXskt7lRDiNq05HEdCeh4+rloGtQ6wdTgmkuAIIWqGonXfdMWJTBM/V+5s6oPBCPO2Sy+OEJXNaDSapoY/0aUhWruqU+RWEhwhRM1gX3iLKj/L7PCYwgGPy/ZcID0339pRCVGj7Y9N5eDFNBzs1DwW3sDW4ZiRBEcIUTNc24NTkKdswJ1NvGniW4csnZ5leyxTxVyI2qqo92Zw20C862htHI05SXCEEDVD0Ricf6bA+77wvh9s/RKVSmWatjpvWwwFUvhPiEpx8Wo2fx5R6kyN7lY1poZfSxIcIUTN4FBHedQXrT9lhFNrAXigXT28XBy4lJrD38cSSn+9EOKm/LDjPAYjdG2kLI9S1UiCI4SoGTxKuf9fuNK4o72GxwvHB8zZKoONhbhdWXkF/Fi41tuYKlLY73qS4AghaoZOY2DYEnhgFgz/VTl2zUrjj0c0xEGjZt/5q0RdSLVNjELUEL/tv0h6bgHBdZ3p3czX1uGUShIcIUTNYKeFsEHQZijUa68cy0szDTb2dXXk3jaBgPTiCHE7DAajad2p0d1CUKurRmG/60mCI4SoeRw9QF241N63XSDhGFDclb7mcByXU3NsFJwQ1dumU0mcS87C1dGOIR3q2zqcMkmCI4SoedRq8G2u7Kecg6jFALQIdCMitC56g5EFhaXlhRA3Z+42pQd0WKcgXLQWX7P7lkmCI4SomUasgOAeyv41Y3GKenGW7IolK6/AFpEJUW2dSshgy+lk1CoYERFs63DKJQmOEKJmcvaCto8p+1lJpsN9wnwJ8XYhI7eAX/ZdtFFwQlRPRYX9+t/hT5CXs42jKZ8kOEKImsvFR3nMSjQdUqtVjO4WDMC8bdEYDEYbBCZE9XMlM4/fDlwCMBXPrMokwRFC1Fwu3spj/GHY+iXolbWoHmpfHzdHO2KuZLP+RGLZrxdCmCzZFYuuwECreu50bOhp63BuSBIcIUTN5VYPKJzC+s8UOL0OABetHY+FNwRgztZzNgpOiOojr0DPwp3nAXiyezAqVdWcGn4tSXCEEDVXHV94ZEHx8/RLpt2RXRtip1ax81wKRy+n2SA4IaqPFVGXScrIw9/NkUGtAm0dToVIgiOEqNla3A8dxyj71ww2DnB34u5WAYAU/hOiPEaj0fT/yMiuwTjY3SB1WPUSTGsAaydbIbqySYIjhKj5TIONk8wOF00ZX3nwMonpudaOSohqYduZK5yIz8DZQcNjnUtZ8+1aBj3sW6BUEc+Is06AZZAERwhR8xUNNt4711TVGKBNkAcdG3qSrzfyQ+H4AiGEudmF49Qe6RiEu7N9+Y0z4sGoV/YHfGThyMonCY4Qouar41e8P6snXC1OZop6cRbtPE9uvt7akQlRpZ1OyGDjySRUKkzlFcqVqqwwjnsDcPW3aGw3IgmOEKLma9wX7nhAuVWl18H/WsMvyricfnf4U9/TiavZ+fy2/9INLiRE7VK0LEO/Fn40rOtSfuPNn8K8Acq+u+3XqJIERwhR8zm4wMPz4Z4vio8dWw4GAxq1ilFdgwHll7nRKIX/hAClsN+vhUn/Uz1Cb/yCg0uL95v2s1BUFScJjhCi9mh+L7xWOGPKUAC5qQAM7RREHa0dZxIz2XQqqezXC1GLLNqpFPZrU/8Ghf102XBgEVw5rTwfvwe6v2SdIMshCY4QonZx9gKtu7JfuAinq6M9j3QMAmTKuBAAufl6ftgZA8CYHqHlF/bb/hX8MV7Zd/IC7yaWD7ACJMERQtQ+RbOqrpk2PrpbMGoVbDmdzKmEDBsFJkTVsCLqMsmZOgLdHRnY8gaDhS/uKd4f9ClUkSrHkuAIIWqforo48++Gk38CEOTlTP87lF/kc6UXR9RiRqPRNDV8VLdg7DVlpApZV+DHx+DMP8rzJ/+Glg9ZKcobkwRHCFH7+DYv3t/yuWm3aMr4bwcucSUzz9pRCVElbD6dzKmETFwcNAztVE5hv6O/wcnVyr6DK/i1sE6AFSQJjhCi9un/IfQqLCOfdsF0uENDT9rUd0dXYGDxrlgbBSeEbc3eovTeDO3UAHenMgr75WXA8RXKvndTeGYTaF2tFGHFWDTBSUlJYfjw4bi5ueHh4cGYMWPIzMwst/3zzz9Ps2bNcHJyokGDBrzwwgukpZkvhKdSqUpsS5cuLeOqQghxHQdn6Piksp8RD/p8QPnd8mRhL87CHefJK5DCf6J2ORmfwZbTyajLK+yXkwpf3AHRm5Xnd74KdRtZK8QKs2iCM3z4cI4ePcq6detYtWoVmzdv5umnny6z/eXLl7l8+TKffvopR44cYf78+axdu5YxY8aUaDtv3jzi4uJM2+DBgy34ToQQNY6zN2gcACNM7wzfdIKtX3B3qwAC3B1JzsxjRdRlW0cphFXNKRx7M6ClP0FezqU3SjgKuYUdD753QKO+Voru5lgswTl+/Dhr165l9uzZhIeH0717d77++muWLl3K5cul/9Jo2bIlv/76K/feey+NGjWiT58+fPDBB6xcuZKCggKzth4eHvj7+5s2R0dHS70VIURNpFZDYHtlP+UcJJ+CrV9gr1EzIiIYUKaMS+E/UVskZeSx/IDy/TymezmF/dIuKo/BPeC57eBS1wrR3TyLJTg7duzAw8ODjh07mo5FRkaiVqvZtWtXha+TlpaGm5sbdnZ2ZsfHjx+Pt7c3nTt3Zu7cueX+EsrLyyM9Pd1sE0IIHv8VRv8Jjy1TnuemQYGOxzo3wMlew4n4DHacvWLbGIWwkh92nkenN9CugQcdyirsl5MKR39X9t2DrBbbrbBYghMfH4+vr6/ZMTs7O7y8vIiPj6/QNZKTk5k6dWqJ21rvvfcey5YtY926dTz00EM899xzfP3112VeZ9q0abi7u5u2oKCq/Y8ihLASbR1o2BUa3wUqjXIsOxl3Z3uGdFDW0pHCf6I2yM3Xs2insgjtU2X13ugLlMVqTymlFXCvZ6Xobs1NJzhvvPFGqYN8r91OnDhx24Glp6czaNAgWrRowTvvvGN27q233qJbt260a9eO119/nddee41PPvmkzGtNnjyZtLQ003bhwoUy2wohaiG1ukTxv6IBlutPJHIuqezJEULUBL/tv0RKlo56Hk70v8OvZIPd38PnYXA1Rhm7FtC2StW8KY3djZuYe/nllxk1alS5bUJDQ/H39ycxMdHseEFBASkpKfj7l18VMSMjgwEDBuDq6srvv/+OvX0Z09QKhYeHM3XqVPLy8tBqtSXOa7XaUo8LIYSJiy9kJsCykTB0EaH+Lekb5sv6E4nM2xbD1MEtbR2hEBahNxhNU8Of7B6CXWmF/Q78UFz5O/xZ6DfVihHemptOcHx8fPDx8blhu4iICFJTU9m3bx8dOnQA4N9//8VgMBAeHl7m69LT0+nfvz9arZYVK1ZUaPBwVFQUnp6eksQIIW6dZ0NIOAxXo+Hf9+GxpYzpEcL6E4n8su8iL/drioezg62jFKLSrTuWwLnkLNwc7RjWqYwhHDlXlcfBM6DNMOsFdxssNganefPmDBgwgLFjx7J79262bdvGhAkTGDZsGIGBgQBcunSJsLAwdu/eDSjJTb9+/cjKymLOnDmkp6cTHx9PfHw8er1Sj2LlypXMnj2bI0eOcObMGb777js+/PBDnn/+eUu9FSFEbTBgmjIrBCD9EgARoXVpHuBGTr6eH3fLrW1R8xiNRmZuPgvAExENcdGW0e+Rk6o81u9UZdaauhGL1sFZvHgxYWFh9O3bl7vvvpvu3bsza9Ys0/n8/HxOnjxJdnY2APv372fXrl0cPnyYxo0bExAQYNqKxs3Y29szffp0IiIiaNu2LTNnzuTzzz9nypQplnwrQoiazqNBcbd74SrjKpXKtHzDgu0x5OsNtopOCIvYe/4qB2JTcbBTM7JrcOmN9AWQVzj72KmM2VVV0E3foroZXl5eLFmypMzzwcHBZtO7e/XqdcOaEwMGDGDAgAGVFqMQQpgULcKZlQRGI6hU3NsmgI/+PEF8ei5rDsdxf9uqPXNEiJsxc5My9uah9vXwdS1jSEjuNasJOLpbIarKIWtRCSFEEefCmVSGfIhaAgV5aO00jIhoCEjhP1GznEnM4J/jCahU8FSPMqaG67Jh3zxlX+sGGov2i1QqSXCEEKKIvWPxX6h/PAd7ZgMwPLwBDnZqDl1MY+/5qzYMUIjKM2uz0ntzV3M/GvnUKb3Rls/g38Jbt85Vs2JxWSTBEUKIa/WfVryfcAyAunW0PNReuTVV1KUvRHWWkJ5rWpbhmZ7lLJR5cXfxfmT1GusqCY4QQlyr3XBlKixA+kXT4ad6hKJSwT/HEzidkGGj4ISoHPO2xaDTG+jY0LP0ZRmykpWaUEUrho/dAHc8YN0gb5MkOEIIcb2iEvTnNsKR38BgoJFPHfq3UIqUzpBeHFGNZeTms3iXsixDmb03R3+HY8uVfa0b+IRZJ7hKJAmOEEJcz6Nh8f4voyFG+Sv22V7Kl8EfUZe4nJpji8iEuG1Ld18gI7eARj4u9A3zLb1RWmHdJxdfGPsvODhbL8BKIgmOEEJcz7Mh9Pug+HlqLABtgzyICK1LgcHI7C2yCKeofnQFBuZuU/7bffrOUNTqMor2pSnFLun6PHg3sVJ0lUsSHCGEKE3XCdB6qLJfVMUVGFfYi7N0TyxXs3Q2CEyIW7fy4GXi0nLxcdUyuF0pNZ30+fDzKDjyi/K8iq8YXh5JcIQQoixFVVtziqeG92jizR2BbmTr9Czccd5GgQlx84xGo2lq+OhuwWjtNCUbXdqnjL8BQAX+bawXYCWTBEcIIcri6KE85qaaDqlUKp4tHJg5f3s02boC68clxC3YeCqJkwkZuDhoGB7esPRGacUzB5mwB7wbWyc4C5AERwghylJKDw7AwJb+NPBy5mp2Psv2yCKconqYsVFZVPPRzg1wd7IvvVFRgtN6aLUde1NEEhwhhChLUYJz9Hf48VEw6AGw06h5+k6ltP33W6JlEU5R5e07n8Ku6BTsNSrG9AgxP7lrFnzREj5vAZs/UY65Vd+xN0UkwRFCiLL4twIKZ5mcXANJJ0ynhnSoj3cdBy6l5rDq0GXbxCdEBX27Qem9eah9fQLcncxP7pmtTAtPvwS6TOVYUGcrR1j5JMERQoiy+LWASceKnxdNnQUc7TWM7qb8JTxj4zlZhFNUWccup7P+RCJqVRmF/bKSlMdHFsLTm+DFg9BsoHWDtABJcIQQojxugdC08Jf9NUs3ADzepSF1tHacTMhgw8lEGwQnxI19t0npvbm7VQAh3i7mJ/UFkJOi7DfsBoFtwTPYqvFZiiQ4QghxI+71lcdVL8Hv44oPO9kzPLwBAN8VDuAUoiqJSc5ideEt1Od6lTIjKjtZeVSpi8ec1RCS4AghxI2E9MA0FufgEvj1KbiwB4Anu4fgoFGzJ+Yqe2NSbBejEKWYufksBiP0CfOlRaCb+UmjEf58Tdl3rgvqUuriVGOS4AghxI20uB9ePQOhvZXnh3+G9e8C4OfmyIPtlRkn30ovjqhC4tNy+WWfclv1uV7Xjb1JjYWtX8CxP5TnntfNrKoBJMERQoiKcPGGB2ZAq4eV56nFVYyf6dkItQr+PZHIkUtpNgpQCHPfbzlHvt5I5xAvOgZ7FZ8wGmHe3aYkHa0bPDjLNkFakCQ4QghRUa7+EPmOsp9+2VQXJ8TbhXtaBwIwfcMZGwUnRLGULB1LdimLxI7vfd3Ym9y04tXCQ3rCM5vAq+b14NjZOgAhhKhW6vgrAzINBfDDYFDbQx0/Xuj+FisOXubPI/GcSsigqZ+rrSMVtdj8bdHk5OtpWc+NO5t4m59MLyx34OQFI1dYPzgrkR4cIYS4GRo78Gmu7EdvhrPr4eASGqduZ8Ad/oD04gjbyswrYP72GECZOaVSqYpPpsfBvx8o+9V4pfCKkARHCCFu1mM/wQOz4IGZENBWOZaXzoQ+yq2AlQcvE52cZbv4RK22eOd50nMLCPVxoX9h0m3yx3g4uVrZ9yhjwc0aQhIcIYS4WR5B0GYotBlWvCChLpuW9dzpE+aLwQjfSi+OsIHcfD2zt0YDMK5nIzTqa3pvjEa4tFfZ92kOd75igwitRxIcIYS4HfbOymN+NoCpF+f3A5e4kJJtq6hELbVkVyxJGXnU83Di/rbX3IK6fAC+6agMMFZplIHFge1sF6gVSIIjhBC3w6Gw9L1OuSXVvoEn3Rt7U2AwMmOT1MUR1pObrzf9N/dc70Y42F3zFb9vAVwp7FWs1wHstDaI0LokwRFCiNtxXQ8OFPfi/Lz3IvFpubaIStRCS3fHkpiRR6C7Iw93CDI/WbSgZtOByhiyWkASHCGEuB0OhQmOrjjB6RJal87BXuj0BmZtPmejwERtkpuvNy2qOa53Y/PeGyhOcNo+Bs5e1AaS4AghxO2wL7xFlW8+a6qoF2fJ7vMkZ+ZZOypRyyzbe4GE9DwC3B15pGP9kg2KEhwXH+sGZkOS4AghxO0opQcHoEcTb9oEeZCbb2D2lmgbBCZqi7wCvWk1+3G9GqG1u2bRzPxc2PI5pBT2JNbxtUGEtmHRBCclJYXhw4fj5uaGh4cHY8aMITMzs9zX9OrVC5VKZbY9++yzZm1iY2MZNGgQzs7O+Pr68uqrr1JQUGDJtyKEEKUrGoOTEQcx25QtNw2VSsXzhSXyf9gRQ0qWzoZBiprs570XiUvLxc9NyyMdrxt7c+yP4jWn1Pa1KsGx6FINw4cPJy4ujnXr1pGfn8/o0aN5+umnWbJkSbmvGzt2LO+9957pubOzs2lfr9czaNAg/P392b59O3FxcYwYMQJ7e3s+/PBDi70XIYQolbZwSYb4QzD/bmXfuxlM2E3f5r7cEejG0cvpzNp8jjcGhtkuTlEj6QoMxb03PRvhaK8xb5ByzUy+RxYW//daC1isB+f48eOsXbuW2bNnEx4eTvfu3fn6669ZunQply9fLve1zs7O+Pv7mzY3NzfTub///ptjx46xaNEi2rZty8CBA5k6dSrTp09Hp5O/kIQQVtawK4T2hrpNwKuRciz5JBTkoVKpmHRXUwAWbI+RsTii0v2y7yKXUnPwddUyrHODkg3SCted6v0mhN1t3eBszGIJzo4dO/Dw8KBjx46mY5GRkajVanbt2lXuaxcvXoy3tzctW7Zk8uTJZGcX39vesWMHrVq1ws/Pz3Ssf//+pKenc/To0VKvl5eXR3p6utkmhBCVQusKI5bD83thwl5QF3aMZyUD0CfMlzb13cnJ1zNT6uKISqQrMJjWPXv2+t4boxG2fAZRi5Tn7qUMPK7hLJbgxMfH4+trfq/Pzs4OLy8v4uPjy3zdY489xqJFi9iwYQOTJ0/mhx9+4PHHHze77rXJDWB6XtZ1p02bhru7u2kLCgoqtZ0QQtwWtRqcC1duLpy1olKpeKmwF2fhjvMkpktdHFE5ftuv9N74uGp5LPya3pu0S7Dtf7C+eKgH3k2tH6CN3XSC88Ybb5QYBHz9duLEiVsO6Omnn6Z///60atWK4cOHs3DhQn7//XfOnr31v3wmT55MWlqaabtw4cItX0sIIcpVNA23aFou0LOpD+0beJBXYODbjdKLI26frsDAN4W9N8/cGVrce2M0wuxI+GeK8jzkThgyD+q1t1GktnPTg4xffvllRo0aVW6b0NBQ/P39SUxMNDteUFBASkoK/v7+ZbyypPDwcADOnDlDo0aN8Pf3Z/fu3WZtEhISAMq8rlarRaut+WWphRBVgEthD87iITDxCHgEFY7Facbjc3axZHcsz/QMJcDdybZximrtpz2xXLyq9N4MD79mVfC8dMgoHOca3APu/Qq8QmwTpI3ddA+Oj48PYWFh5W4ODg5ERESQmprKvn37TK/9999/MRgMpqSlIqKiogAICAgAICIigsOHD5slT+vWrcPNzY0WLVrc7NsRQojK1bhv8X70ZtNut8aF1Y0LDHy7QXpxxK3L0en5+l+l9+b5Po1xcrhm7E3h2C8cXGHUqlqb3IAFx+A0b96cAQMGMHbsWHbv3s22bduYMGECw4YNIzAwEIBLly4RFhZm6pE5e/YsU6dOZd++fcTExLBixQpGjBjBnXfeSevWrQHo168fLVq04IknnuDgwYP89ddfvPnmm4wfP156aYQQttf1eWh+n7Kffsl0+NqxOEv3xHIpNccW0Yka4IedMSQWrhg+rNN1M6dMFYu9rR9YFWPRQn+LFy8mLCyMvn37cvfdd9O9e3dmzZplOp+fn8/JkydNs6QcHBz4559/6NevH2FhYbz88ss89NBDrFy50vQajUbDqlWr0Gg0RERE8PjjjzNixAizujlCCGFTfncoj/GHQF9chDSiUV0iQuuSrzfyTeFf4ELcjMy8AlPdmxcjm5Rccyr5tPJYi5ZkKIvKaDQabR2EtaWnp+Pu7k5aWppZjR0hhKgU+3+AFROUfc8QGL8L7JQe5j0xKTw8Ywd2ahUbXulFkJdzORcSwtxX60/z+bpThPq48PfEO7HTXJPgrHwR9s1X9psNgkfLL6pbHd3M97esRSWEEJUttGfxX9BXo+HqedOpTsFe9GjiTYHByBf/nLJRgKI6Ss3W8X3h6vQvRTYtTm4u7YeF98OBwpo3GodaV9SvNJLgCCFEZfNoAK+cVh4Bcq6anX6lXzMAfj9wiZPxGdaOTlRTMzefIyOvgOYBbgxqFVB8YvcsOLcRDAUQ2A7+LwHaPV7mdWoLSXCEEMISVCpw8lL2c1PNTrUJ8uDuVv4YjfDJX7deN0zUHokZuczfFgPAy3c1Ra1WFZ9MLazt1mIwDP9FKTgpJMERQgiLcfJUHq/rwQF4uV8zNGoV/xxPZG9MipUDE9XNtxvOkpOvp22QB32bX7ciePpF5TH8WZk9dQ1JcIQQwlLKSXAa+dThkY7K+kAfrz1BLZzvISroUmoOS3bFAvBq/2aoVIW9N1fPw5x+cDVGee5ezzYBVlGS4AghhKU4eSiPa9+A8zvgwm74513Y/Clkp/Bi36Zo7dTsibnKhpOJ5V5K1F6f/30Knd5ARGhdujaqW3ziyC9woXDx6jr+4BpomwCrqJteqkEIIUQFXfuF8/Mo0NhDWuF4CYMe/16vM6pbMDM3neO/a0/Sq6mv+dgKUesdu5zObweUW1BvDAwr7r1Ju6SUIwBo1BcenAUa+Uq/lvTgCCGEpXR8Ero8p+xnxhcnNwCZyhp643o2wtXRjhPxGfxx8FIpFxG12UdrT2A0wr1tAmkT5KEcvHIWvmqrlCAA6Py0jL0phSQ4QghhKS51YcA00JZSkEyXBYCHswPP9mwEwGd/n0JXYLBmhKIK23I6ic2nkrDXqHi1sLQAy5+DWb1Ar1P+uwrpCSE9bBpnVSUJjhBCWJp7/ZLHdJmm3Se7heDrquXi1RwW7Txfsq2odQwGI9PWKCUEHu/SkAZ1nZXB6lGLlRXDAR6YCSNXgIOLDSOtuiTBEUIIS6vbuOSxvOICf04OGiZGKgtx/m/9aVKzddaKTFRRfxy8xLG4dFy1djzfp4lyMO1icYOJR6Ra8Q1IgiOEEJbW/wPoOwX6vg0DPlKOFd6iKvJIx/o083MlLSefr2UhzlotN1/Pp38py3iM690ILxcH5URa4RitgDbgEWSj6KoPSXCEEMLSPBpAj0nQ42XwbaEcu+YWFYCdRs1/BjUHYOGOGGKSs66/iqglFu6I4VJqDv5ujjzZLUQ5eOUs/DhU2Xcr5ZanKEESHCGEsCZtHeVRVzKB6dnUh55NfcjXG/noT1nCoTZKzdbxTWEP3qR+TXG01ygnzm0sbtSot/UDq4YkwRFCCGtycFUec67CwZ+U7XKU6fT/DWqOWgVrj8az69wV28QobObLf06TnltAMz9XHmp/TU9N0Xpmze6GzmNtElt1IwmOEEJYk6O78qjLhN+fVrbZkZClJDNN/VwZ1llZhfyDNccxGGQJh9ridEIGPxTOonvrnhZori36WLTch1eoDSKrniTBEUIIa3L1g56vQ2hvZdM4gCEfMuJMTV6KbEodrR2HLqZJ8b9awmg08t6qY+gNRu5q4Uf3JtcV7stJVR6Llv8QNyQJjhBCWFvv/8CI5crmVricwzVjcnxctYzrpRT/++/ak+To9NaPUVjVvycS2XI6GXuNiv+7u3nJBkU9OEULuIobkgRHCCFsyb6wSFu++aDjMd1DqOfhRFxaLjM2nbVBYMJadAUG3l99HIAnu4cQ7H1d4b4z6+HEKmXf0cO6wVVjkuAIIYQtOTgrj7pss8OO9hom3x0GwIxNZ7mQkn39K0UNsWB7DNHJWXjX0TKh93VFIa+chUUPFj+v42vd4KoxSXCEEMKW7AsTnPySCcygVgFEhNYlr8DA1FXHrByYsIbkzDy+Wn8agNf6N8PV0d68weUDxfvdXoQGXa0YXfUmCY4QQthS0TpCpdTFUalUvHv/HWjUKv4+lsDGk4lWDk5Y2qd/nSQjr4CW9dwY0uG6An4bPoRfxyj7HUbBXe+Bxs7qMVZXkuAIIYQtldODA8q08VFdgwF4d+Ux8gpkwHFNsT/2Kj/tvQDAlHvvQH3ttPC8DNj0cfFz6bm5aZLgCCGELZUxBudaEyOb4F1HS3RyFnO3xlgnLmFRBXoDb/5+BKMRHmpfn07BXsUnDXo4/Evx86f+hdaPWD/Iak4SHCGEsKUyZlFdy9XRnv8UDjj++t/TxKXlWCMyYUE/7DzPsbh03J2K/21Nlo+DVROV/dDeUL8DqFQlriHKJwmOEELYUlEPzu7v4YuW8GVr2L+wRLMH2tWjY0NPsnV6PiicUiyqp8T0XD77W1kt/LUBzahbR2ve4NK+4v2OT1oxsppFEhwhhLAlvzuUR10mpF2A1PNKsnOdogHHahWsOhQnA46rsamrj5OZV0CbIA+GdWpQskFWkvI4fg+0uM+6wdUgkuAIIYQttXwInt8PYzfAkLnKsfTSl2e4I9Cd0d1CAHhz+RGydQXWilJUkq2nk1l58DJqFbx/f0vz9aYACnSQm6bsu3iXvICoMElwhBDC1uo2gnrtoVEf5Xn2FcgvfZzNpLuaUs/DiYtXc/jyn9NWDFLcrrwCPW//cQSAJ7o0pFV995KNspOVR7WdVC2+TZLgCCFEVeHoUTzo+AN/OP1PiSYuWjveH9wSgNlbznHkUpoVAxS3Y/qGs5wrrFg8qV+z4hNJp+DLVvBhPfi6g3LM2RvU8hV9Oyz66aWkpDB8+HDc3Nzw8PBgzJgxZGZmltk+JiYGlUpV6vbzzz+b2pV2funSpZZ8K0IIYXkqFYT2LH5+5Bf45134dSxs+QyMRgB6h/kyqHUABiNM/u0wBXqDjQIWFXU8Lp1vN5wB4J37WuDudE3F4jP/QGqsMg6rqB5SwwgbRFmzWLQk4vDhw4mLi2PdunXk5+czevRonn76aZYsWVJq+6CgIOLi4syOzZo1i08++YSBAweaHZ83bx4DBgwwPffw8Kj0+IUQwuqGLlYKvG36CA7+aH6u+X3g3QSAKfe2YPOpJA5fSmP+9hie6hFqg2BFRRToDbz+6yEKDEb6tfBjUKsA8wZFg4rbDoc7X1USXfdSBh+Lm2KxBOf48eOsXbuWPXv20LFjRwC+/vpr7r77bj799FMCAwNLvEaj0eDv72927Pfff+eRRx6hTp06Zsc9PDxKtBVCiGpPrYbgbrCplHM5V027vq6O/Ofu5kz+7TCfrztF/zv8CfJytl6cosLmbYvh0MU0XB3tmDq4Jarra9oUJTheIcomKoXFblHt2LEDDw8PU3IDEBkZiVqtZteuXRW6xr59+4iKimLMmDElzo0fPx5vb286d+7M3LlzMRZ23ZYmLy+P9PR0s00IIaost3qlH79uvaqhHYPoHOxFtk7PG78dwmAo+/egsI2Y5Cw+W3cSgDcHNcfPzbFko6zCgcUuPlaMrOazWIITHx+Pr6/5su52dnZ4eXkRHx9foWvMmTOH5s2b07Wr+Roc7733HsuWLWPdunU89NBDPPfcc3z99ddlXmfatGm4u7ubtqCgoJt/Q0IIYS0eDcFPGUiMvTPYOSn7161XpVar+HhIaxzt1Ww7c4XFu85bOVBRHqPRyBu/HSI330C3xnV5pON13z36fFjzKpz6U3kuCU6luukE54033ihzIHDRduLEidsOLCcnhyVLlpTae/PWW2/RrVs32rVrx+uvv85rr73GJ598Uua1Jk+eTFpammm7cOHCbccnhBAWo7GDZ7bA6+fh9RgI6qQcj94Me+fCiTWmAcch3i68PkAp9f/hmhOcv1L2kg/CuhbtPM/Ocyk42WuY9kBr81tTcQdh3RTYPav4WN3G1g+yBrvpMTgvv/wyo0aNKrdNaGgo/v7+JCaaV9osKCggJSWlQmNnfvnlF7KzsxkxYsQN24aHhzN16lTy8vLQarUlzmu12lKPCyFElaVWg5OHsl80dXzXjOLzI/6A0F4AjIwI5q+j8ew8l8KrPx9i6dNdzFemFlZ3LimTD9YoS2q8NqAZDeoWjo8yGpWK1fPuVmZNgTJ4PPxZ8GlWxtXErbjpBMfHxwcfnxt3o0VERJCamsq+ffvo0EGZ1//vv/9iMBgIDw+/4evnzJnDfffdV6GfFRUVhaenpyQxQoiayaGUwcOpxT3RarWKT4a0of+Xm9kdk8K87TGM6S6DVW2lQG/gpWUHyc030L2xNyMjgotPrnwR9i9Q9p29oWl/iHwX6sjtqcpmsTE4zZs3Z8CAAYwdO5bdu3ezbds2JkyYwLBhw0wzqC5dukRYWBi7d+82e+2ZM2fYvHkzTz31VInrrly5ktmzZ3PkyBHOnDnDd999x4cffsjzzz9vqbcihBC2ZV9KgpNnPlkiyMuZ/9zdHID/rj3BmcSya44Jy5q+4SwHL6Ti5mjHJw+3Nu9NO3NN8ca73oPB30pyYyEWLfS3ePFiwsLC6Nu3L3fffTfdu3dn1qzi+435+fmcPHmS7GzzgXNz586lfv369OvXr8Q17e3tmT59OhEREbRt25aZM2fy+eefM2XKFEu+FSGEsB0Hl5LHckvOBh0e3oAeTbzJKzDw4tID5BXorRCcuNbBC6l89a+yhMbUwS0JcHcqPqkvgIzCWm8vn4R2w20QYe2hMpY3v7qGSk9Px93dnbS0NNzc3GwdjhBClO+fd2Hr5+bHuoyHAR+WaBqflsvA/23manY+T3UP4c17WlgpSJGj0zPo6y2cS8rintYBfPNYe/MGMVth/iBQ28ObibIUwy24me9v+XSFEKKqK60HJ6/0Naj83R35ZEgbAGZvjWbjycRS24nK996qo5xLysLPTWtaL8xk21dKcgPgFiDJjRXIJyyEEFVd0wHg1Uipj9PyIeVYKbeoikS28GNkREMAXvn5IIkZudaIslb7I+oSP+6+gEoFnz/SFg9nB/MGF68Za9rxSesGV0tJgiOEEFWdf0t4YT9MPARNCscmxkXB328qW/TmEi+ZfHdzwvxdSc7U8fKyg1Ll2IKik7P4z2+HAXi+d2O6NfYu2aioWvHDC6D7S1aMrvaSBEcIIaqTOn7KY2osbP9a2X4pWRDV0V7D14+2w9FezZbTyczcfM7KgdYOufl6xi/eT5ZOT+cQL17o26T0hpmFtwqlWrHVSIIjhBDVScidMOBj6PoCdBqrHMtKMlU2vlYTP1em3HsHAJ/8dYLtZ5KtGWmt8OGa4xyLS8fLxYGvhrXDTlPG16qsN2V1kuAIIUR1otZAl2eh31SIfKfwoLHEOlVFhnUKYkiH+hiM8PyPB7icmmO1UGu63/ZfZOEOZf2vzx9pg797KQtpJp6AL1oWDwp3KeX2lbAISXCEEKK6cnABCovI6Upfg0qlUvH+4Ja0CHDjSpaO5xbvl/o4leDwxTQmF467eaFPY3o18y294am1ytIMAN5NwdHDOgEKSXCEEKLaUqnAoY6yn5ehPF45qyzGeXGv6baVo72GGY93wN3JnqgLqby38piNAq4ZrmTm8cwPe8krMNA3zJeJkU3LbpyVpDw2HQDPbpXp4VYkn7QQQlRnRTVydJmQdQVm9IClj8LsvhCzxdSsQV1nvhzWFpUKFu+KZdHO8zYKuHrL1xsYv2Q/l9NyCfV24Ythbctf2LRo7E3DrmAn6yVakyQ4QghRnWkLe3B+exo+CYX8a25VpZjPnOrdzJdX+ikrVk9ZcZQtp5OsFWWNYDQaeW/lMXaeS6GO1o5ZIzrg5mhf/ouKenBkcLHVSYIjhBDVWVEPTtKJkud0JQceP9erEQ+2q4feYOS5xfs5k5hh4QBrjjlbo/lh5/nCYn5taOzrWnZjfT78+QacXa88lwTH6iTBEUKI6szhui/Z12Og3RPKfn7JgccqlYppD7WiU7AnGbkFjJ6/hyuZeZaPs5r783AcH6w5DsD/3d2cfnf4l91YlwW/joFd3xUf8wq1cITiepLgCCFEdebkUbwf2B6cPK8Zl1P61HGtnYaZT3SkgZczF1JyeGrhXrJ1BZaPtZrad/4qE3+KwmiEkRENGdM9pPwXbPkcjv2h7De/D0auhLqNLB+oMCMJjhBCVGfdXoSwe6DZ3RA5RTlm76w8llEbB8DLxYG5ozri7mTPgdhUnl20H12BwQoBVy9nkzIZu1CZMRXZ3Je3770DlaqcQcUAidfMUrvnC6U4o7A6SXCEEKI6C+oMwxbDoz9CaC/lmENhglNGbZwijX1dmTuqE072GjafSmLSsij0smaVyYWUbB6fvYuULB2t6rnz1aPt0JQ3Y6pI2kXl8dGfpLCfDUmCI4QQNY194S2qnKuwb4GyXtXlqFKbdmjoyYwnOmCvUbHqUBxTVhzBWMqyD7VNYnouj8/ZRVxaLo196zB/dCecHezKf5E+Hw4shvhDynP3+pYPVJRJEhwhhKhpisbgnFgFK19QVhxf/HCZzXs29eHzR5QaOYt2xvL+6uO1OslJydLxxJzdnL+STZCXE4vGhFO3TgVq2Bz9Hf54rvCJShIcG5MERwghapqiBOdaWYlgKHuJhnvbBPLB4FaAMh363ZXHamWSk5SRx6OzdnIyIQM/Ny2Lx3QpfY2p0lzaX7x/7//MB4ALq7tBf5sQQohqp2iQ8fV0WeDoVubLHgtvgEoFk387zPztMegNRt69747yK/XWIPFpuTw2eyfnkrKU5OapLjSoW8Znea38HPhlDJxcrTy/fzq0e9yywYobkgRHCCFqGu8mxfsaLegL69zE7oALu8HeEdqPgjoli8892rkBGpWK1387xA87z5Ot0/PRQ62w19TsDv8LKdkMn72L2JRs6nk4sWRsOA3rltITdr2zG+DAouLkRqWGoC6WDVZUiCQ4QghR03g3gef3Q/ol8AyGbyOUtap+Hl1c/C8vA+56r9SXP9IpCDuNild/OcSv+y+SnJnHt8Pb46KtmV8Zhy6m8uT8vSRn5tHAy5klY8Op71mBnht9Pix9rHg6fodR0PUFqXlTRdTslFwIIWqruo2U+iseDa6pi3PNtPHM8teherB9fb4f0QFHezWbTiXx6Pc7Sa6BFY/XH09g6EzlvYX5u7LsmYiKJTcAGXHFyU2PV+CuqZLcVCGS4AghRE3nUMoXdinLOFyvT5gfP47tgqezPYcupnHf11s5fDHNAgFan9FoZP62aMYu3EtOvp4eTbz5+dmIig8ohuJ6N57B0Petcsc3CeuTBEcIIWo6+1LGkpSxjMP12jXw5NdxXQnxduFyWi5DZmznt/0XKzlA68rWFTDxpyjeWXkMgxGGdgxi7qhOuN5oZfBrXdgDPz6q7LsHWSZQcVskwRFCiJqu1B6ciiU4AKE+dVg+vht9wnzJKzAwadlB3v7jCLn5ZU87r6qik7N4YPp2/oi6jEat4q17WtzaIOpVEyE3VdmX21JVkiQ4QghR05U2bfwGyzhcz93JntkjOvJCn8YALNxxnnu/3srRy9XjlpXRaGTRzvMM+moLJxMy8HHV8uPYLozpHnLjtaWuV5AHSSeU/c7PQK/JlR+wuG2S4AghRE1XWuG/m+jBKaJWq5jUrxnzR3fCx1XL6cRMHpi+ne82niVfX3UX6oxPy2XkvD28ufwI2To9XUK9WP18dzqHeN38xY78Bu/7gqEAtO4w8GNw9a/8oMVtkwRHCCFqugbX1GWp31l5zMuAdW/Dr09B7M6bulyvZr6sfbEHd7XwQ6c38PHaEwz6agu7o1MqMejbl683MGdrNHd9vonNp5LQ2ql5+54WLHmqC75uNzGY+FqHfirebzYAbrb3R1iNylgLa3Gnp6fj7u5OWloabm4y6l0IUQtkFi7VkJcO0zubnwsKhzF/3/QljUYjv+6/xIdrjpOSpQPgwXb1eOmupgR5VXCqtQUYjUY2n07mw9XHOZmQAUCbIA8+e7gNjX3r3NpFDXo4twEWPaQ8f2gOtHxIEhwru5nv75pZtUkIIYS5Or7KY2pByXMX90J+rlLh+CaoVCqGdKhPZHNfPl57kqV7YvntwCVWHrrMsE4NeK53IwLcnSoh+IoxGo3sOHeFL9adYk/MVQA8ne15fUAYj3QMur0lJ46vgJ9HFT9v1EeSmyrOYreoPvjgA7p27YqzszMeHh4Veo3RaOTtt98mICAAJycnIiMjOX36tFmblJQUhg8fjpubGx4eHowZM4bMzEwLvAMhhKiBShuPY9TDB35wfNUtXdLD2YFpD7Zi+XPd6N7Ym3y9kR92nqfHxxt4/scD7I+9atGFO3Pz9fyy7yL3fbONx77fxZ6Yq2jt1IzpHsKGV3oxrHOD219P68rZ4v3Id8D5FsbvCKuyWA+OTqfj4YcfJiIigjlz5lToNf/973/56quvWLBgASEhIbz11lv079+fY8eO4eio/GUxfPhw4uLiWLduHfn5+YwePZqnn36aJUuWWOqtCCFEzeHoAfU7wcU94FBHqeGSdFw5d24DNL/nli/dJsiDRU+Fs+PsFb785xS7olNYefAyKw9epolvHe5rE8g9bQIJ8a7AGk83UKA3sPNcCqsOXWbt0XhSs/MBcLBTM6xTEON7N8bvVsfZlCZH6RGi6/PQ/aXKu66wGIuPwZk/fz4TJ04kNTW13HZGo5HAwEBefvllXnnlFQDS0tLw8/Nj/vz5DBs2jOPHj9OiRQv27NlDx44dAVi7di133303Fy9eJDAwsEIxyRgcIUStZjQqs6g0DqCxh82fwr9ToeUQGFKxP0gr4silNOZvj2HFwcvoCopnWdX3dKJbI286BHvS3N+NJn51cLTXlBOukeRMHacTMjhyOY2d51LYHZ1CZl7x7bZAd0cej2jIsE4N8HJxqLT3YPLHeGVRzT5vwZ2vVP71RYVUyzE40dHRxMfHExkZaTrm7u5OeHg4O3bsYNiwYezYsQMPDw9TcgMQGRmJWq1m165dPPDAA6VeOy8vj7y84jVU0tPTLfdGhBCiqlOpzG9VuRX+cZhzFfIylQJ2zt43PSbnei3rufPpw214+94W/HUknhUHL7Pz3BUuXs3hp70X+GnvBVM4dV0c8K6jxcPZHo1ahQoVufl6UrJ0JGXmkZFbcuyQp7M9A1sFcE/rAMJD6qK53dtQ5clJVR6dPC33M0SlqjIJTnx8PAB+fn5mx/38/Ezn4uPj8fX1NTtvZ2eHl5eXqU1ppk2bxrvvvlvJEQshRA1R9KV9+QB80hgKcsDFF17YD1rX2768m6M9D3cM4uGOQWTlFbA7JoXtZ5I5cimdkwkZpGTpSM5UtrKoVNDAy5mmfq50DvYiolFdmge4WTapuZYpwfGwzs8Tt+2mEpw33niDjz/+uNw2x48fJyws7LaCqmyTJ09m0qRJpufp6ekEBcnaIUIIARQnODnX1LHJSoQrZyCwXaX+KBetHb2b+dK7mfLHqtFo5EqWjoT0XK5k6kjNycdoNGI0KuNpvFwcqOviQH1PZ5wcyr6NZTEFOvj9aTi/VXkuPTjVxk0lOC+//DKjRo0qt01oaOgtBeLvr1SCTEhIICAgwHQ8ISGBtm3bmtokJiaava6goICUlBTT60uj1WrRarW3FJcQQtR4ZX1pFw2stSCVSoV3HS3edaro7+iLu+Ho78q+Sg11G9s2HlFhN5Xg+Pj44OPjY5FAQkJC8Pf3Z/369aaEJj09nV27djFu3DgAIiIiSE1NZd++fXTo0AGAf//9F4PBQHh4uEXiEkKIGs/FB1AB1805KbotU5tlXvNH9fjd4NHAdrGIm2KxOjixsbFERUURGxuLXq8nKiqKqKgos5o1YWFh/P67khmrVComTpzI+++/z4oVKzh8+DAjRowgMDCQwYMHA9C8eXMGDBjA2LFj2b17N9u2bWPChAkMGzaswjOohBBCXMfZCwZ/Cx2fhJ6vQ+O7lONW6MGp8rKSlccW94N3E9vGIm6KxQYZv/322yxYsMD0vF075T7uhg0b6NWrFwAnT54kLa14JdrXXnuNrKwsnn76aVJTU+nevTtr16411cABWLx4MRMmTKBv376o1WoeeughvvrqK0u9DSGEqB3aPqZsAMvHK4+5qSXb5VyFHx+DtItQtxEMWwIOtluWweKykpRHF8vcvRCWI2tRSR0cIYQw99f/wY5vlAHGQV3Mz105A2fWFT8Pu0cpFlhTxWyFhMPQazL0esPW0dR61bIOjhBCiCrCrZ7yePmAspXGvQGkxcKJW1veodqpyUlcDSUJjhBCCHPtHgdDPuSmlX7eyVNps28+5GVYNTSbcPKClg/aOgpxk+QWldyiEkIIIaqFm/n+ttgsKiGEEEIIW5EERwghhBA1jiQ4QgghhKhxJMERQgghRI0jCY4QQgghahxJcIQQQghR40iCI4QQQogaRxIcIYQQQtQ4kuAIIYQQosaRBEcIIYQQNY4kOEIIIYSocSTBEUIIIUSNIwmOEEIIIWocO1sHYAtFC6inp6fbOBIhhBBCVFTR93bR93h5amWCk5GRAUBQUJCNIxFCCCHEzcrIyMDd3b3cNipjRdKgGsZgMHD58mVcXV1RqVSVeu309HSCgoK4cOECbm5ulXrt6k4+m/LJ51M++XzKJ59P2eSzKV91+nyMRiMZGRkEBgaiVpc/yqZW9uCo1Wrq169v0Z/h5uZW5f9DsRX5bMonn0/55PMpn3w+ZZPPpnzV5fO5Uc9NERlkLIQQQogaRxIcIYQQQtQ4kuBUMq1Wy5QpU9BqtbYOpcqRz6Z88vmUTz6f8snnUzb5bMpXUz+fWjnIWAghhBA1m/TgCCGEEKLGkQRHCCGEEDWOJDhCCCGEqHEkwRFCCCFEjSMJTiWaPn06wcHBODo6Eh4ezu7du20dUpWxefNm7r33XgIDA1GpVCxfvtzWIVUZ06ZNo1OnTri6uuLr68vgwYM5efKkrcOqMr777jtat25tKkIWERHBn3/+aeuwqqSPPvoIlUrFxIkTbR1KlfDOO++gUqnMtrCwMFuHVaVcunSJxx9/nLp16+Lk5ESrVq3Yu3evrcOqFJLgVJKffvqJSZMmMWXKFPbv30+bNm3o378/iYmJtg6tSsjKyqJNmzZMnz7d1qFUOZs2bWL8+PHs3LmTdevWkZ+fT79+/cjKyrJ1aFVC/fr1+eijj9i3bx979+6lT58+3H///Rw9etTWoVUpe/bsYebMmbRu3drWoVQpd9xxB3FxcaZt69attg6pyrh69SrdunXD3t6eP//8k2PHjvHZZ5/h6elp69Aqh1FUis6dOxvHjx9veq7X642BgYHGadOm2TCqqgkw/v7777YOo8pKTEw0AsZNmzbZOpQqy9PT0zh79mxbh1FlZGRkGJs0aWJct26dsWfPnsYXX3zR1iFVCVOmTDG2adPG1mFUWa+//rqxe/futg7DYqQHpxLodDr27dtHZGSk6ZharSYyMpIdO3bYMDJRHaWlpQHg5eVl40iqHr1ez9KlS8nKyiIiIsLW4VQZ48ePZ9CgQWa/g4Ti9OnTBAYGEhoayvDhw4mNjbV1SFXGihUr6NixIw8//DC+vr60a9eO77//3tZhVRpJcCpBcnIyer0ePz8/s+N+fn7Ex8fbKCpRHRkMBiZOnEi3bt1o2bKlrcOpMg4fPkydOnXQarU8++yz/P7777Ro0cLWYVUJS5cuZf/+/UybNs3WoVQ54eHhzJ8/n7Vr1/Ldd98RHR1Njx49yMjIsHVoVcK5c+f47rvvaNKkCX/99Rfjxo3jhRdeYMGCBbYOrVLUytXEhaiqxo8fz5EjR2ScwHWaNWtGVFQUaWlp/PLLL4wcOZJNmzbV+iTnwoULvPjii6xbtw5HR0dbh1PlDBw40LTfunVrwsPDadiwIcuWLWPMmDE2jKxqMBgMdOzYkQ8//BCAdu3aceTIEWbMmMHIkSNtHN3tkx6cSuDt7Y1GoyEhIcHseEJCAv7+/jaKSlQ3EyZMYNWqVWzYsIH69evbOpwqxcHBgcaNG9OhQwemTZtGmzZt+N///mfrsGxu3759JCYm0r59e+zs7LCzs2PTpk189dVX2NnZodfrbR1ileLh4UHTpk05c+aMrUOpEgICAkr8kdC8efMacxtPEpxK4ODgQIcOHVi/fr3pmMFgYP369TJOQNyQ0WhkwoQJ/P777/z777+EhITYOqQqz2AwkJeXZ+swbK5v374cPnyYqKgo09axY0eGDx9OVFQUGo3G1iFWKZmZmZw9e5aAgABbh1IldOvWrURJilOnTtGwYUMbRVS55BZVJZk0aRIjR46kY8eOdO7cmS+//JKsrCxGjx5t69CqhMzMTLO/mqKjo4mKisLLy4sGDRrYMDLbGz9+PEuWLOGPP/7A1dXVNG7L3d0dJycnG0dne5MnT2bgwIE0aNCAjIwMlixZwsaNG/nrr79sHZrNubq6lhir5eLiQt26dWUMF/DKK69w77330rBhQy5fvsyUKVPQaDQ8+uijtg6tSnjppZfo2rUrH374IY888gi7d+9m1qxZzJo1y9ahVQ5bT+OqSb7++mtjgwYNjA4ODsbOnTsbd+7caeuQqowNGzYYgRLbyJEjbR2azZX2uQDGefPm2Tq0KuHJJ580NmzY0Ojg4GD08fEx9u3b1/j333/bOqwqS6aJFxs6dKgxICDA6ODgYKxXr55x6NChxjNnztg6rCpl5cqVxpYtWxq1Wq0xLCzMOGvWLFuHVGlURqPRaKPcSgghhBDCImQMjhBCCCFqHElwhBBCCFHjSIIjhBBCiBpHEhwhhBBC1DiS4AghhBCixpEERwghhBA1jiQ4QgghhKhxJMERQgghRI0jCY4QQgghahxJcIQQQghR40iCI4QQQogaRxIcIYQQQtQ4/w8PGsd0V3H2aAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def test_tf_lite_model(tflite_model_path = 'model.tflite'):\n",
    "    interpreter = tf.lite.Interpreter(model_path=tflite_model_path)\n",
    "    interpreter.allocate_tensors()\n",
    "    input_details = interpreter.get_input_details()\n",
    "    output_details = interpreter.get_output_details()\n",
    "    \n",
    "    tf_lite_y_pred = np.zeros(y.shape)\n",
    "    for idx, _x in enumerate(x):\n",
    "        input_data = np.array([[_x]])\n",
    "\n",
    "        interpreter.set_tensor(input_details[0]['index'], input_data)\n",
    "        interpreter.invoke()\n",
    "        output_data = interpreter.get_tensor(output_details[0]['index'])[0][0]\n",
    "        tf_lite_y_pred[idx] = output_data\n",
    "\n",
    "    plot_pred(x, y, tf_lite_y_pred)\n",
    "\n",
    "test_tf_lite_model()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert tensorflow lite to c++ file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_tflite_model_as_c_header(tflite_model_path = 'model.tflite', output_file_path = \"./src/model.h\"):\n",
    "    with open(tflite_model_path, \"rb\") as f:\n",
    "        tflite_model_content = f.read()\n",
    "\n",
    "    header_content = \"alignas(16) const unsigned char g_model[] = {\"\n",
    "    for i, byte in enumerate(tflite_model_content):\n",
    "        if i % 12 == 0:\n",
    "            header_content += \"\\n  \"\n",
    "        header_content += f\"0x{byte:02x}, \"\n",
    "    header_content = header_content.rstrip(\", \")\n",
    "    header_content += \"\\n};\"\n",
    "\n",
    "    with open(output_file_path, \"w\") as f:\n",
    "        f.write(header_content)\n",
    "\n",
    "save_tflite_model_as_c_header()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = bytes([0x1c, 0x00, 0x00, 0x00, 0x54, 0x46, 0x4c, 0x33, 0x14, 0x00, 0x20, 0x00, \n",
    "  0x1c, 0x00, 0x18, 0x00, 0x14, 0x00, 0x10, 0x00, 0x0c, 0x00, 0x00, 0x00, \n",
    "  0x08, 0x00, 0x04, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, \n",
    "  0x80, 0x00, 0x00, 0x00, 0xd8, 0x00, 0x00, 0x00, 0x3c, 0x02, 0x00, 0x00, \n",
    "  0x4c, 0x02, 0x00, 0x00, 0xf0, 0x06, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, \n",
    "  0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x76, 0xfd, 0xff, 0xff, \n",
    "  0x0c, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x38, 0x00, 0x00, 0x00, \n",
    "  0x0f, 0x00, 0x00, 0x00, 0x73, 0x65, 0x72, 0x76, 0x69, 0x6e, 0x67, 0x5f, \n",
    "  0x64, 0x65, 0x66, 0x61, 0x75, 0x6c, 0x74, 0x00, 0x01, 0x00, 0x00, 0x00, \n",
    "  0x04, 0x00, 0x00, 0x00, 0x9c, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, \n",
    "  0x04, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x6f, 0x75, 0x74, 0x70, \n",
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    "  0x6c, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xea, 0xfe, 0xff, 0xff, \n",
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    "  0x4e, 0xff, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, \n",
    "  0x31, 0x2e, 0x31, 0x34, 0x2e, 0x30, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, \n",
    "  0x00, 0x00, 0x00, 0x00, 0xc0, 0xfa, 0xff, 0xff, 0xc4, 0xfa, 0xff, 0xff, \n",
    "  0xc8, 0xfa, 0xff, 0xff, 0xcc, 0xfa, 0xff, 0xff, 0x7a, 0xff, 0xff, 0xff, \n",
    "  0x04, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x2f, 0x3d, 0x2b, 0x9e, \n",
    "  0xf5, 0xd3, 0xf5, 0x3a, 0xe6, 0x44, 0xd4, 0x5b, 0xcc, 0x81, 0x44, 0xd6, \n",
    "  0x96, 0xff, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, \n",
    "  0xe1, 0x0f, 0x00, 0x00, 0x56, 0xdb, 0xff, 0xff, 0x65, 0xdf, 0xff, 0xff, \n",
    "  0xad, 0x18, 0x00, 0x00, 0x2b, 0x17, 0x00, 0x00, 0x7d, 0xfd, 0xff, 0xff, \n",
    "  0x0c, 0xef, 0xff, 0xff, 0x7b, 0xfe, 0xff, 0xff, 0x0e, 0xf7, 0xff, 0xff, \n",
    "  0xf8, 0xf4, 0xff, 0xff, 0xef, 0x1d, 0x00, 0x00, 0x3e, 0x07, 0x00, 0x00, \n",
    "  0xae, 0x12, 0x00, 0x00, 0x0f, 0x14, 0x00, 0x00, 0x04, 0xf5, 0xff, 0xff, \n",
    "  0x70, 0x22, 0x00, 0x00, 0xe2, 0xff, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, \n",
    "  0x10, 0x00, 0x00, 0x00, 0xf6, 0x26, 0x3d, 0xd4, 0xa3, 0xf8, 0x00, 0x05, \n",
    "  0xf1, 0x0d, 0x6a, 0xfa, 0x96, 0xc8, 0x0a, 0x7f, 0x00, 0x00, 0x06, 0x00, \n",
    "  0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, \n",
    "  0x04, 0x00, 0x00, 0x00, 0xf1, 0xf5, 0xff, 0xff, 0x6c, 0xfb, 0xff, 0xff, \n",
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    "  0x0e, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, \n",
    "  0x04, 0x01, 0x00, 0x00, 0x08, 0x01, 0x00, 0x00, 0x0c, 0x01, 0x00, 0x00, \n",
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    "  0x0c, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, \n",
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    "  0x07, 0x00, 0x00, 0x00, 0xca, 0xff, 0xff, 0xff, 0x14, 0x00, 0x00, 0x00, \n",
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    "  0x1a, 0x00, 0x14, 0x00, 0x10, 0x00, 0x0c, 0x00, 0x0b, 0x00, 0x04, 0x00, \n",
    "  0x0e, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, \n",
    "  0x1c, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, \n",
    "  0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x07, 0x00, 0x06, 0x00, 0x00, 0x00, \n",
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    "  0x08, 0x00, 0x04, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, \n",
    "  0x0c, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, \n",
    "  0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, \n",
    "  0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, \n",
    "  0x09, 0x00, 0x00, 0x00, 0x24, 0x03, 0x00, 0x00, 0xac, 0x02, 0x00, 0x00, \n",
    "  0x34, 0x02, 0x00, 0x00, 0xe0, 0x01, 0x00, 0x00, 0x84, 0x01, 0x00, 0x00, \n",
    "  0x20, 0x01, 0x00, 0x00, 0xac, 0x00, 0x00, 0x00, 0x48, 0x00, 0x00, 0x00, \n",
    "  0x04, 0x00, 0x00, 0x00, 0x16, 0xfd, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01, \n",
    "  0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, \n",
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    "  0xb4, 0xfd, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, \n",
    "  0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, \n",
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    "  0x9a, 0xfe, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01, 0x14, 0x00, 0x00, 0x00, \n",
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    "  0x3c, 0x00, 0x00, 0x00, 0x84, 0xfe, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, \n",
    "  0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x80, 0xff, 0xff, 0xff, \n",
    "  0xff, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, \n",
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    "  0x34, 0x00, 0x00, 0x00, 0xe4, 0xfe, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, \n",
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    "  0xa2, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01, 0x14, 0x00, 0x00, 0x00, \n",
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    "  0x38, 0x00, 0x00, 0x00, 0x8c, 0xff, 0xff, 0xff, 0x08, 0x00, 0x00, 0x00, \n",
    "  0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, \n",
    "  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, \n",
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    "  0x75, 0x6c, 0x5f, 0x31, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, \n",
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    "  0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x44, 0x00, 0x00, 0x00, \n",
    "  0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xf0, 0xff, 0xff, 0xff, \n",
    "  0x06, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, \n",
    "  0x0c, 0x00, 0x10, 0x00, 0x0f, 0x00, 0x00, 0x00, 0x08, 0x00, 0x04, 0x00, \n",
    "  0x0c, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, \n",
    "  0x00, 0x00, 0x00, 0x09, 0x0c, 0x00, 0x0c, 0x00, 0x0b, 0x00, 0x00, 0x00, \n",
    "  0x00, 0x00, 0x04, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x72, 0x00, 0x00, 0x00, \n",
    "  0x00, 0x00, 0x00, 0x72\n",
    "  ])\n",
    "\n",
    "file_name = 'model.tflite'\n",
    "\n",
    "# Write the data to a file\n",
    "with open(file_name, 'wb') as file:\n",
    "    file.write(data)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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4pmwRaqa8X0IE72UFuFY5QezlBr5OwPqviMhtiMBbox014wXJMwAWEaMbvhWE8XtYRIxuWESMbgJbRJ5m4UWwPlXJ25mEj0XkPOsuk53jXU32AI+z8GercC66QPfvzjQMaYla3qwcP6/lLpPMwte+0oS0abuHKDDxbRYfyVgzKuuehej2Otz4+eiM/q+3UMbdlsm3youL05eFb8WFsM0oTb7gMitvJGZ2Fl+hZd2P4iIlRjc6WgFbnqscRxv7YaIclbAw05qFJ87WwJo+Os3CjI8hRKTlylpwzZYJt0OpAS1m2Z0pzjKTGYnTnYUnSISXpyPVEZgYKCZKwaLIMbdxkOUxaVaHLJHGNGfhSbjp1vETs8x9GMOdZe4WVmU3Vpvacc7xNlN5O4hmdaQlImiEJUdU05OFT9lRxFbIQwI8d+ZhFp4EuvEaKh0vC/gBnIBldMMJWMbvYRExumERMbrxSkzEL7maXmgfB/5LroSIFs6epWqYqebm8D3cDpmLuEAWUYcYnf1o7mxVw0w1vXeGYQ0OwZK4OFXjXTgmYnTDImJ0wyJidMMiYnTDImJ0wyJidONzEWUd+if++s579umZUtUwDlmHqvBEviowhsAQlqjj7/n47WYx/VcDordXYbuqZ/wDY7mz997Dlb4liFWWxtFK3Weh8p/FM4dGTBItO5EVY6YHY4koPx/LcAkfvyfmS6tQjP/WLNTmZ9G7kS2UUTGEiBK2q5hoH1D9q2fwkajbvjoVoWufUZboGfwkYsRCMcbCQDHRs/gc2djo4JLssZKc/gMvk4ViDIeB3Nl7ePlXJ4QJ0tzWN5YBJGx8Fllao1Oif5yv2kuxcW24nGO8j7FiIlTh2b8DBW88C/zpP1BjyUaJCqz/KupGCeq9Z1Bnb38IvecGVAPjbfhWkACAbwVh/B4WUQBw+949zJrluztHp11EdO8v/YG9w9PqNWc0N8SuDZk3T5W8j1csUbjJhO7bw6rETCW3hBW6gVmYF+giovfmDAcH46oIAJmp44YQUOedezAtWIDQ0FBV632mfXRm486dO+i6dg337tzGLDFiIw8eGsRPgEwGoRvcFiHCDREikJWPjo5WLb7BayKyMTAwgKGhITn0N+qzaHFiqExvdxscHFQ1xoL2XbCw7AuEBQoK8v3YyOsi8gcefvhh+RIKi8WiahhX8BCf0Q2LyAlz5syRroJxDxaRE27fvi1jIsY9WESMblhETqCr7OzO3IdF5AQaQrM7cx8WEaMbFhGjGxYRoxsWkRNsKQXGPVhETqBkMQfW7sMiYnTDImJ0wyJidMMicgJfsfYMFpET+Iq1Z0z7N2D9EdudjXQH5n1kFWP/zk1Yt24dVi34Bhea+1SDC8Q6pSt7Ry2b/dh+7Ny0TvSThOEPP0enqvdH2BJ5SAK+xhuHD+Pw4Xr0Jq0UZVckYGvpfuzPHf1kakJhKR60viH6oH6q0aDq/RUWkYd0fNSADppJWgi0/VubF2JJSJIzkoQkm7Q68HaVEErdVVUmErDS3CsE+Cvs3y8EVrp1AiEaHxbRZCCXVgjUn9IkhKQ45AjrslUIidzU1nSt2jlxiIhdgL5TZIUOo77vR8hx9eoTP4BFNAmylwkBVb2trJCgrQHVoozC/Vh65TCqbOJyylX0DfbiuvrmfsOVq1gQ5d+2iEU0CRpeuz+OyX5sKyCsy9fLNIs0Ph243heHpcr6ZC8TQXy3K9EZHxbRJCCXVVroYD2StmLhlSq8LaxLw2vCIqVnqwbnNLxWD+SKeEjERDmoRzW9X9CP4efOnMDPnXkGWyJGNywiJ3DawzNYRE7gtIdnsIgY3bCIGN2wiBjdsIicwIG1Z7CInMCBtWewiBjdsIgY3bCIGN2wiJzAT8B6BovICfwErGewiBxYuXLlqJeKR0VFIT4+XpWY8WAROdDZ2YmsrCyEhYVh6dKlUlRUx7iGReRAd3c3bty4gfnz50sr1NzcrFoYV7CIxmATzq1bt9gKuYlPPstAB8jIpKSkoK+vD11dXarGWNy8eVOOICl+Cw/3/bdvvSYiEs/1biuC5oQhOHQBZofMVy3GIyhoNoaH76qS8bg9ZMW94TuYde8OgsQUEx0lReUrvCIiElBP/w8IjV6O+dFLVS0zFVi/bsDdIQsWL4pGSEiIqvUuXomJuq5bhYBWsICmAfPSbNybHYr+ft99jXvaRURWKHhumBBQsqphpprwxSsw4MPPak27iCiInj2PUwjTSag5AfSJXbqFxRd4xZ0ZOYhm9MPXiRjdsIgY3fhYRDmofOFJVNunYuxSLc7I3VOMP67R5ncdcL2sZM2jOOrY/4Ec1eALxN9a8ShyVck9JrOO9/G9JRpsxUtPvYhiOVXjuKrWzS+KUb0rDO/b+xbTn+tVIzOV+O4y57ik4Y8HVqD+z/9CHRXJmmzoxm6nAhDLVqwH/vEqnjvvWD4LPBKBxuOvOhclCSwvRhUsOKnEu+vAXsT39CEzQ2trrX0RZW+JGbH80ZhBWDKSIS9UdH4yIkiHvgYvncbuI01yPnfPXvwuQ/va9uClVvu6v3thL3LEdj13nrZ1EzLDaImRbZB/765kyOpOC1phzC9iO+J7SxSWLHbsZN1NE577uA8rMtO04poVWNFzCc9B/I9vUS+FNQY6SHkQB02zTi9disA2++/ORWZkh2a1jrci5pERVxKWEYbP5Tqn0RiZoblV6mu5Wl5M70eu1+qFsH6X/K3dwu4+8i+UPfUJWqXV1QS/6wCJXWsvPj6IDXIbhLB+mQyLEK+s/wqaaA2OsdzZZNzNWx2wJK+QBzs3MxaWr1z3QcvgUqPdQtUduYTWyCgllptofF+tf/5LfNmjzRKD9nWaUN+qvQWW+gqLf8gec22LnwvzA0Igy2PQ+rGypE7JwU/Espm71MlDloe2gU4CYXtOkvUjxN/WqmaNTACMzurxeU8sctakISe5D5/TATjfDUtYmFfOYnJh8gRQk3R/bkEubGS94nJXojM2xhRRJIlCm921QcUHLjj+lXBpGzKFK+tQ1qIeJ8lNjRrZiJGOcBl1jd8CGZn2kV3ungwk93RP6gDWWfqEmxvpy8bxryxIdnCF99MF62AMNuxRbtiGFP/I345fJLA7mxxanGMz9T/pcSO0JJcWH4Evba5IUHfkVbzUGjsSb72QgM/JXZ7/F46RwFS9jF0mO2p7q1qLqey/oS47iPqTPSOx3lEpFrKYVLdXxE3ibyz/RATbm9R6I8uU1Y787dXLRXBP/Rmcab8VhG45vTMvFqbYDFUzDVCA+0vgmB+7BL1899k/kfhAnHyPgLfx85iIhsnijN0Viy//MXMF5GsCwxIxbIkY/4ZFxOiGRcToxisx0eDtYMw12XJVzHQw8H0TkhITfBITeUVE/f39Pn2kZSZAz6IlJSUFrojo0eR58+apGmY6oIctExMTeXTG+CcsIkY3LCJGNywiRjcsIhfk7StDUaoqTDspKCorRZ4q+RN+JaKUHWWoqHCxo1OLUFZRgdL1qqwH0Vda1wmccHjPVd6+0X1r21PhepsccL1+C068aUXajhTV6j/4lYha3qxEeXkValXZXeTBKisS57r75G00o+nNFlsJpeJgr43sV2WBEFlR9DmxPeVubJOb6zefQA0KvGj9pobZycnJB9X8tEDXiOhtrPdfbCTz/Qc8uqQVdV+sFjt5DwqixHxMESr2rsHwmQsIEgf/D7/Zgvz8fCy/ewbWR6icMaYtC1lZW5BL/XwXh9zMJQhdlIUtW0RbVjRaZ+did+4iYO4SPETl7zJQ+v9+jS2izyz6vS+sanscWF+K4lk1OG5va8WFM2dwdUkulg3V4UKb2Pqf5yIj7iHxO/na79RdgpOeFO6vbxW/mVFUgBvnXfV3P3SxkV6bHBTkfbvgQ0vUgvPN/TClrkHK+jQkihpTdCJSYsxARxNq6UzNBC4eE2fq6XYkbirFg9qKgjwUZJrQfprO4nOwmlS1DXFGlx+7iH5TCtZ0VuFoo7AA/RdxtPIEEjeuhqmjRlqASrulcUSIO90qXIuzthESxbZaP6TfL0dNz2oUSDdFJ4bmsqT12ze+k3O+PiHc2mWzQ9n4+NSdtVjEuWYyY40QTnujOOgJaSiINqG/qx2IN8Mk/q0uETHDJpKYGZER2npIXSRK/bDKVyq2w+rgJQirZXwB1F4WfScUyFikzGn8IQ7iu0DBhLGJ7fdVnxKxbmU5mtIrUAQh5FdcOTln6xOaiGvOqqIf4NuY6GyTkEAiVguLY/30mjDfiUhM6EfLp0IEnVaxm/s1SyTjhkrUak/qKEwwy1dMJ8I81hK54myV7I+sk7SCqnoUwpI1RRe4DJbbu8ThflBbOy/drAShWaK0y+VCQsItu7BEztcXrC+A+fIJIUf/wceBtbIi/eTabBbFims0IhIH8kQjNEtEIxjHAyLb+oWLo7a1MI+xRGPRLN5q7BbB9XYxQqL+dpM7/HD8g1X7ShPSXIig5U2xbupu2VcBzqlRnGaJqoQVkYMAF5bI+foiAF/nX1aI8P8ELA3rS1bDKuIjOnhTCcU1BZbKKe93POi61KJ3K0ddVnAXXyZg/VRE5DZ2Y7VyY/2NR8cJkmcOLCJGN3wrCOPXsIgY3bCIGN0EtIg8zcLTaIyuNjOe4VMRaVnssRlwLVnp/GqyB0wiC0/XbqzpniVqGUNaolpUjZvXcp/JZeHdTXkwjvgwiw+Yf5yLh2JDsShri5bNXjGMM+eTRzL6Kru/PV+0qUz+hTlFKJvOLHy3+P/HRSi4dQGXuuXKfsEMzeKP0PKmsAanKTG6dkwMo1klmenuABLT84SFmc4svEbLm00wbxw/5cGMxgAiUrkymXAdi+aGZH4pQRQjF6F9WrPwGik70mB91/VtZswIxomJ5K0fSlA25H1G7ahRlkgyrVl4Ig8F0U2Tyl/NVAwgokQUkLXZlIj+xhoV4CqkddLapSUSPDitWXghoX1r2Qp5SEDnzjzOwouAvCymxi+TuZyAZXTDCVjGr2ERMbphETG68UpMxC+5mn4C/iVXN3t7EBY0S9Uw08H1u8NITEoOXBEF9/di0Rzv/3Ezif+7eQcJib6xRBwTMbphETG6YRExumERMbphETG6YRExuvGxiErxzDvv4a+26Y1nkaVanCOW/59SNc8YBd9bor4GHNucj9+KqcaSjeJD+aqB8RcM5c7+frEZoTG2m6wdrJQzC1VahWccjNL2//knnmD9+QRDiWj76lR0XKwSc/l44o2H8H/KQv323YVsoQyM70UUkY0SZXF+dDEfz0oN5WNZRCoKbJZoe6qDhWKMhnFior83I2Gjg9tyiJXk9J+kLsaIGMedVZXi2BcZmtt6rw1dwkJtnGAglrBaLZD/LHKXabOM9zFUTPTRn/4bV378jAiYq/DsfzUgertyZ2JyDKIlVSfweUyR1r4PuHJF1TNeh28FCRD4VhDGr/GKiG5Pq61jNHx35+i0iygkJAQ3ffgHzgR67w5j1qxZPnFlxLSLKDw8HHfE/9Y7w1oFM+VcF/vWFGH7ZoX38Yo7i4qOhlVYIxbS1PPNrTsYnh0sT1ZfMe2jMxsDAwO4brEgJGgWQu7dwxz2cJPmB7H/hsVRuxck3NecOYhZtMinj2R5TUQ2SEy3bt1SJWMSFxeH3t5eDA4OqhpjQc+YUfwzf/58n1ogG14XkT/w8MMPo729HRZhOZmJ4etEjG5YRE6YI+IMeokm4x4sIifcvn1bxkSMe7CIGN2wiJxAIx92Z+7DInLC3bt32Z15AIuI0Q2LiNENi4jRDYvICZSH4sDafVhETqCvInFg7T4sIkY3LCJGNywiRjcsIifwFWvPYBE5ga9Ye8a0fwPWH7Hd2Tg0NKRqHMgqxv6dm7Bu3TqsWvANLjT3qQYXiHVKV/aOWjb7sf3YuWmd6CcJwx9+Dvs3+/wQtkQekoCv8cbhwzh8uB69SStF2RUJ2Fq6H/tz41RZI6GwFA9a3xB9UD/VaFD1/gqLyEM6PmqA/JJo0kKg7d/avBBLQpKckSQk2aTVgberhFDqrqoykYCV5l4hwF9h/34hsNKtEwjR+LCIJgO5tEKg/pT6MG1SHHKEddkqhERuamu6Vu2cOETELkDfKbJCh1Hf9yPkuH5RpeFhEU2C7GVCQFVvKyskaGtAtSijcD+WXjmMKpu4nHIVfYO9uN6mlRquXMWCKP+2RSyiSdDw2v1xTPZjWwFhXb5eplmk8enA9b44LFXWJ3uZCOK7XYnO+LCIJgG5rNJCB+uRtBULr1ThbWFdGl4TFik9WzU4p+G1eiBXxEMiJspBPao/Ug1+Cj935gR+7swz2BIxumEROYHTHp7BInICpz08g0XE6IZFxOiGRcTohkXkBA6sPYNF5AQOrD2DRcTohkXE6IZFxOiGReQEfgLWM1hETuAnYD2DReTAypUrERoaqkpAVFQU4uPjVYkZDxaRA52dncjKykJYWBiWLl0qRUV1jGtYRA7Qt9lu3LghXzJOVqi5uVm1MK5gEY3BJhx66z9bIffw+p2N9KkDmuiq8Ny5c1WtsUhJSUFfXx+6urpUjbGgfUepmcjISAQF+d4OeE1ENOKxdHVD/Pm4N2sOZgXNRkhYlGo1FkFi24aH76qS8bh7cwjDtwdxa8iKCFM4Fi5cqFp8g1dERK7hmuU6gufHYEGynz9kZSBuDVxHf+cnCJsbBLPZrGq9j1dsYX9/P4aD5rGAppiQ8IVin65DX/+QHBD4Cq+IaGBwCOGLV6gSM5UEzw1HcFg0fvjhB1XjfaZdRBQE3rt3D6Fmf3/i3LjMCTPj5i36SKpv4CF+ABAcEgZfPjzIImJ0wyJidONzEeXu2YvqF560T0f3pKkWZ+Sg8kCONrvmUVS6XFZj14GRvqtf2Is/rlENPoD+1spfqIKbTGYdb2MIS9Ra+yKKn9Km3UeaVK1e0vDHiiexoee0ve/ip17Fc+dVMzNlTPvFRhqddXzTicWrnJ9OdKZts7yKsrdUBfGLYlSi2l6368BexL9PAiBLBJT9uV6zRJlf4iTWowRn7eKj/mTZkonq5R0opmXvgwS2CZlhWmnw0mltfdHn0Q3Al5HJWttgK14q/xfq5PKZQu0RyMygVM1NNB63CdKxLwtOPlWN4zRLVvOFh5As5y1ovGRbV9D5ibZd4u+szouRVfZtEJD13CbvQLmJVkrffTVm/4zhhrUDNy1fIHax1pe3MYQlSs6bvLupO3IJluQVyJWlNOQk9+F9cTB2LY9B61fOBEQHaRNWtNos1CewZKwf+d34WOAfmuU62ZOMbXbtx2CFEKdcp7YPmRs0t7rrwHr78sXHB7FBulsS1kOA3cJW47kjr+KlS0IUVKdOgqMkctn+It6PVNsghLUtUohX1p+FNdKY+UVHDObOJuNu6vF5Tyxy6ACsWYEVPR3KEoxHDn4Sb5FC06jHyUuA+QFV7Lxk34bjXzm+WsZhnbc60CpnqK+5yNylToJdyQiLjEIubYdY4qQL65GbGYuw+IfUyUOWZ67cBin+j8n6EU2ob70p54xMQIzOjn/VhxWZafLAWJT1ae25iZiYiQNv/ZALs50EYpLuzz3IhdnXE5Mrl2VkDCui5OUjo7ANE92hKiyDJTkT24Qr+1wdCOnmMjaNGtnk7ikWLkNYrs4YbLCP7HKwLQOwfqOKHtEF66BjX4rzX+JLEQ2NuML7qbP0ISwjE7tU2QaJ3/63S/fM7mxyvNWIxkhl6n8pAt0J7w0jlxaDmNZGB1dWjzIR78Aebz0pAu5G6aqO/5nioE2qnmKXyY7amvBcuWNftksUov4frYix/3axFEtd47daHcVNb1WLGCkC29R69mWOnB35219YD7MQldHx+ehsaqBAlgLcmTmE59GZTrSLlTTaOjsjBWQEAsQSzWzYEjF+D4uI0Q2LiNGNV2KitvYOhC/2xoW/mcntG33ALSviY5eoGu/iHRG1tRn2GbNAgPYxPYfmq/cGeEVE9ImDiIgIVcNMNfRIFhEbGyv/9zYcEzG6YRExumERMbphETG6YRG5IrUIZfvyVGGqyUNpWRFSVMmf8TMRiR1fUYGyHePt+onaPSNvoxnnXqlVJQGJyt0Df9+y2rZV2LevFlUfmlGwXmv1Z/xMRGLHl5ej8s0WVXYX7QCWenLAhAjSumrEL2qk7ChDhZvidLZs3r61sB4rR7nj9p+tQlN6qdg6/2Z2cnLyQTU/LdBz+PQmVqcXG9eXomLvGgyfuYAgseP/8JsMMW9FVtkf8OiSVtTFFIn27cjPz0dWlCh/sVqIYQ8KHOa3U1tWFrZsoXWvIzp/GULDl4vyFrHectXfDqSJn1+wLB/L756BaUsF9vwyX7VfUPdLO5KCor0ZaH/1XXub9Ys6nKkLRkZuGFrqLsGq6p1x/7J52LzxAcRlb8EWsb20DRfU16hbz5uweV8yLpy/fyvcha7FESaTSf7vbXxric42oR2JSFufgjWptAPMWJSaCLOpHy2fJqJ0UyLaT4uz99hFILMIRanaakTKjrVI7L+Io+LMPjHm1YqmnnPijK9RfbfgRCXNQ/ZV1VmEtQn9uCitQpXd0oxifQHMH47T5gidBNJlkaUrG7V9o0hdJP4ysR1iW+lvMa9zdHO1qOlKG39dP8DH7qwd1n4hnZg1YidfxMUOE1I2pol5K66BdjyQuEnEESWrYRL/zA5X9ROjheh6rolDA7RYRtuF/i6SzDg0n0dLvwmrSyg+GceVuOtmxHLlbwJFFWloKq+8T8yjUNsqf79H1ijyUBDd5Hpdg+NjEbXgfHM/TJmrkSh28vkuMZ+QCFNHE2qbr0mXIS0RncFiqjqrrWUncpE8o1NiPHlLGFkm6s9mqVT1GGrftSJtohiILNEOCAvThDRXloj+loQ0TZSpa8Q2K0EJUnakwfruhDbP0Pg8sLZZkfbLtfZ5zZKIIPq0OMxkiWhUM2ZUVPuKEIFpNXaLtoldgWbxqK/S7WLUJEdJBdId1owVpo3mE6hBgeu+yRJVnhCCoIDflSWivwUooN8tSUGLTTQieC/ycytEBEQCNm9fBQoiRXwkD+hUImKdskWomfJ+CRG8lxXgWqUbsdcE+DoB678iIlciAm+NdtSMFyTPAFhEjG74VhDG72ERMbphETG6CWwRuczC08jLzWQq4xIfi0hLjI7NussE5nhXkz3AdRY+cLLovsaQlqjlzcrx81ru4k4WPkCy6L7Gt1l8JGPNqKx7FqLb63Dj56Mz+r/eQhl3WybfKi8uTlUWfiqy6L5mZmfxFVrW/SguUmJ0o6NdsOW5ynG0sR8myjsJCzNlWXiJ/2fRfY0hRKTlylpwbVR2m6DUgJY7250pzjKTGYlTmYWX+H8W3dcYKCZKwaLIMbdxkOUxaVaHLJHGFGbhBYGQRfc1xnBnmbuFVdmN1aZ2nHO89VXeDqJZHWmJCBphTVUWXvQVCFl0XxPguTNXWfipy6L7Gk7AMrqhD+bRB4UDNgFLb6uYNWsWbt++rWqYqYZO1Hnz5qmS9/FKTETXL27eNP6rdP2R4eFhOc0IEZG59eXHbgMRskC0TxcsWIDQ0FBV632mPSayQd/Fv3btmvzD6cwhgoOD5f+MZ9j2H+1TOkGjo6Nl2Vd4TUQ2BgYGMDQ0JMVk1LenxcXFyVTN4OCgqjEWtO/oBCQLRBbe13hdRP7Aww8/LEeUFovjV4aY8TDExUbGv2EROWHOnDnSVTDuwSJyAl3TopiIcQ8WEaMbFpET6Co7uzP3YRE5gYbQ7M7ch0XE6IZFxOiGRcTohkXkBFtKgXEPFpETKLHJgbX7sIgY3bCIGN2wiBjdsIicwFesPYNF5AS+Yu0ZLCJPySrG/v375VRamKAqJ0Cs4/ayfgiLyEMS8DXeOHwYhw/XozdppSi7IgFbS4XgcuNUOTBhEXlIx0cN6KCZpIVA27+1eSGWhCQ5I0lIskmrA29XCcHVXVXlwIRFNBnIpRUC9ac0CSEpDjmFpdgqhJT92H5sTdeqZwosokmQvUwIqOptZYUEbQ2oFmUU7sfSK4dRZRPXDIFFNAkaXqtGg5q3kf3YVuDUYXy9TLNIMwkW0SQglzVqtJW0FQuvVOHtNhKYsEjp2aphZsDPnTmBnzvzDLZEjG5YRE7gtIdnsIicwGkPz2ARMbphETG6YRExumEROYEDa89gETmBA2vPYBExumERMbphETG6YRE5gZ+A9QwWkRP4CVjPYBE5sHLlylEvFY+KikJ8fLwqMePBInKgs7MTWVlZCAsLw9KlS6WoqI5xDYvIge7ubvmZg/nz50sr1NzMH0JzBxbRGGzCoW+IsRVyD7+9s5E+mUBfLqLvXEz1pwlSUlLQ19eHrq4uVTM10HfJKKVC337z5Qddphq/ExGJ5/r161I49NJyOihG+L6FO5CI6BPvBG33kiVL5Ly/41ciIgHR0JtilsjISFXrn3z//ffyUgJ9LdFfToLx8Kutp8CX3IC/C4hYvHixtEqBcD3Kb0Rk++Ce2WyW/wcC4eHhhv0clif4jYhotBQSEqJKgQFZVBoc2OIkf8Wv3BkFo4EGfWTZ3/HviI4xBCwiRjeBKaLig3j592tVwYv89Gm8fOwYjtH04tPwwRb4BLZEU8jOR4C/lZSgRExVzal43BdC9gF+c7GRrqfQFxHH+3z32t+/jNIH58v5tvY2xHSfwhN/OUctePrFUqwKly04VXIQr8u6QqA5BqvkOkP47MgTeP4DMSus2LHN2rthhj6tUn3sxMFjhZC1A5+h6snnQbUuIWu42LYN49PS0iLvGPDnADswLJFwI48/aBEC0azAZe1wS3Yeehx4TasvOdKLnx3aqVqSkIq/afXvWLBqM9ULsWyGvZ8REabjsqorqV/ghoUR6+TEoPnjCaUWEASEiNY+kgp8ekpYGI3XL7epuZ1IT5yPVXtUnLJnFeZHxalYpQ3/a7MS1ZdFiXgdl9uTUOgYz/x0HVLDRZ0t1hFWan6Uq7dYaZZvQb2ybDOAGRATkQtTVoSmCVzR638Sy7wGPC4EYw/OyYU59vEnm1zHQm5Ps3wHq1XVDCAgRHTuewvmp66zW4+d6TZL0YbegST8zNMA94Pn8cSRzwCyOB9chSV8FQqLVdu42NzezLFANgImsN556BgKE7X50YG1Q1As0IJlyMD66pMUZBNimUPAwT+Jyb6sQ7BNQ3dyhbJe9P+OM0sz+nckbgThgRBYB4yI/BUWkRcxlojutzojlwM8g0XkRUhEdGcg3YcTSFy5ckXejsvXibwA3QZCt4MEEj09PZg7d65fC4jwGxHZbmy3Wq3y/0BgYGBAPuPm7/jVEJ/uaqQ7HOkM9nfoHmu6tzoQnvn3m5jIBj/tYTz87mIjmf/ExERplUhE/ga9cYSerg0UARF+Z4kY4+F3logxHiwiRjcsIkY3LCJGNywiRifA/wda54r/G6jY8AAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}