{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Topics in this Notebook\n",
      "\n",
      "1. Convolutional Neural Networks in Pytorch\n",
      "2. ConvNet2d Class\n",
      "3. Try it on MNIST\n",
      "4. Compare Time on CPU vs GPU\n",
      "5. Now let's look at the weights and outputs of convolutional layers\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import banner\n",
    "\n",
    "topics = ['Convolutional Neural Networks in Pytorch',\n",
    "          'ConvNet2d Class',\n",
    "          'Try it on MNIST',\n",
    "          'Compare Time on CPU vs GPU',\n",
    "          'Now let\\'s look at the weights and outputs of convolutional layers']\n",
    "\n",
    "banner.reset(topics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "banner.next_topic()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Convolutional Neural Networks in Pytorch\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-24T16:54:35.353920Z",
     "start_time": "2022-10-24T16:54:33.824625Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.4.0.post300\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "import torch\n",
    "print(torch.__version__)\n",
    "\n",
    "import time\n",
    "\n",
    "import gzip\n",
    "import pickle\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's define our `pytorch` version with a contructor that is called like\n",
    "```python\n",
    "    nnet = ConvNet2d(input_shape=(1, 28, 28), \n",
    "                     conv_specs=[(20, 4, 1), (10, 3, 2)],\n",
    "                     fc_specs=[20],\n",
    "                     n_outputs = 10,\n",
    "                     device='cpu')               \n",
    "```\n",
    "`conv_specs` has a sublist for each convolutional layer, specifying `(n_units, kernel_size, stride)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "banner.next_topic()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# `ConvNet2d` class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting convnet2d.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile convnet2d.py\n",
    "import numpy as np\n",
    "import torch\n",
    "\n",
    "class ConvNet2d(torch.nn.Module):\n",
    "    \n",
    "    def __init__(self, input_shape, conv_specs, fc_specs, n_outputs, activation_function='tanh', device='cpu'):\n",
    "        '''Example for MNIST:\n",
    "        ConvNet2D((1, 28, 28), [(20, 3, 1), (10, 4, 2)], [20], 'tanh', 'cuda')\n",
    "        '''\n",
    "\n",
    "        super().__init__()\n",
    "        \n",
    "        self.input_shape = input_shape\n",
    "        self.device = device\n",
    "        print('ConvNet: Using device', self.device)\n",
    "        self.activation_function = torch.nn.Tanh() if activation_function == 'tanh' else torch.nn.ReLU()\n",
    "        \n",
    "        # Create all convolutional layers\n",
    "        n_in = input_shape[0]\n",
    "        # input_hw = input_shape[1]\n",
    "        self.conv_layers = torch.nn.Sequential()\n",
    "        for nh, patch_size, stride in conv_specs:\n",
    "            self.conv_layers.append( torch.nn.Sequential( torch.nn.Conv2d(n_in, nh, patch_size, stride),\n",
    "                                                          self.activation_function) )\n",
    "            n_in = nh\n",
    "            # Calculate number of outputs of convolutional layers\n",
    "            # conv_layer_output_hw = (input_hw - patch_size) // stride + 1\n",
    "            # input_hw = conv_layer_output_hw  # for next trip through this loop\n",
    "\n",
    "        # Or we pass some zero input samples through the conv_layers and see how many values result\n",
    "        z = self.conv_layers(torch.zeros([1] + list(input_shape)))\n",
    "        z = z.reshape(1, -1)\n",
    "        n_in = z.shape[1]\n",
    "        \n",
    "        # Create all fully connected layers.  First must determine number of inputs to first\n",
    "        # fully-connected layer that results from flattening the images coming out of the last\n",
    "        # convolutional layer.\n",
    "        # n_in = input_hw ** 2 * n_in  # n_hiddens_per_fc_layer[0]\n",
    "        self.fc_layers = torch.nn.Sequential()\n",
    "        for nh in fc_specs:\n",
    "            self.fc_layers.append( torch.nn.Sequential( torch.nn.Linear(n_in, nh),\n",
    "                                                        self.activation_function) )\n",
    "            n_in = nh\n",
    "\n",
    "        output_layer = torch.nn.Linear(n_in, n_outputs)\n",
    "        # Notice, no softmax function applied here.  It is internal to torch.nn.CrossEntropyLoss!\n",
    "        self.fc_layers.append(output_layer)\n",
    "        \n",
    "        self.Xmeans = None\n",
    "        self.pc_trace = []\n",
    "        self.best_pc_val = None\n",
    "        self.to(self.device)\n",
    "\n",
    "    def _forward_all_outputs(self, X):\n",
    "        n_samples = X.shape[0]\n",
    "        Zs = [X]\n",
    "        for conv_layer in self.conv_layers:\n",
    "            Zs.append( conv_layer(Zs[-1]) )\n",
    "\n",
    "        # Flatten outputs from last convolutional layer.\n",
    "        Zs[-1] = Zs[-1].reshape(n_samples, -1)\n",
    "        for fc_layer in self.fc_layers:\n",
    "            Zs.append( fc_layer(Zs[-1]) )\n",
    "\n",
    "        return Zs\n",
    "    \n",
    "    def forward(self, X, keep_all_outputs=False):\n",
    "        if not isinstance(X, torch.Tensor):\n",
    "            X = self._X_as_torch(X)\n",
    "        Zs = self._forward_all_outputs(X)\n",
    "        \n",
    "        if keep_all_outputs:\n",
    "            self.Zs = Zs\n",
    "            \n",
    "        return Zs[-1]\n",
    "    \n",
    "    def _X_as_torch(self, X):\n",
    "        if isinstance(X, torch.Tensor):\n",
    "            return X\n",
    "        else:\n",
    "            return torch.from_numpy(X.reshape([-1] + list(self.input_shape)).astype(np.float32)).to(self.device)\n",
    "\n",
    "    def _T_as_torch(self, T):\n",
    "        if isinstance(T, torch.Tensor):\n",
    "            return T\n",
    "        else:\n",
    "            return torch.from_numpy(T.astype(np.int64)).to(self.device)\n",
    "\n",
    "    def percent_correct(self, Yclasses, T):\n",
    "        if isinstance(T, torch.Tensor):\n",
    "            return (Yclasses == T).float().mean().item() * 100\n",
    "        else:\n",
    "            return (Yclasses == T).mean().item() * 100\n",
    "    \n",
    "    def train(self, Xtrain, Ttrain, Xval, Tval, n_epochs, batch_size=-1, method='sgd', learning_rate=0.01, verbose=True):\n",
    "        \n",
    "        # Assuming Ttrain includes all possible class labels\n",
    "        self.classes = np.unique(Ttrain)\n",
    "\n",
    "        if self.Xmeans is None:\n",
    "            self.Xmeans = Xtrain.mean(0)\n",
    "            self.Xstds = Xtrain.std(0)\n",
    "            \n",
    "        XtrainS = (Xtrain - self.Xmeans) / self.Xstds\n",
    "\n",
    "        if method == 'sgd':\n",
    "            optimizer = torch.optim.SGD(self.parameters(), lr=learning_rate, momentum=0.9)\n",
    "        else:\n",
    "            optimizer = torch.optim.Adam(self.parameters(), lr=learning_rate)\n",
    "\n",
    "        loss_f = torch.nn.CrossEntropyLoss()\n",
    "        # loss_f = torch.nn.NLLLoss()\n",
    "        \n",
    "        if batch_size == -1:\n",
    "            batch_size = Xtrain.shape[0]\n",
    "\n",
    "        self.batch_size = batch_size  # remember this for use in forward functions\n",
    "\n",
    "        for epoch in range(n_epochs):\n",
    "\n",
    "            for first in range(0, Xtrains.shape[0], batch_size):\n",
    "                Xtrain_batch = Xtrains[first:first + batch_size]\n",
    "                Ttrain_batch = Ttrain[first:first + batch_size]\n",
    "\n",
    "                # Set data matrices to torch.tensors if not already.\n",
    "                Xtrain_batch = self._X_as_torch(Xtrain_batch)\n",
    "                Ttrain_batch = self._T_as_torch(Ttrain_batch)\n",
    "\n",
    "                Y = self(Xtrain_batch)\n",
    "                loss = loss_f(Y, Ttrain_batch)\n",
    "                loss.backward()\n",
    "\n",
    "                optimizer.step()\n",
    "                optimizer.zero_grad()\n",
    "\n",
    "            with torch.no_grad():\n",
    "                pc_train = self.percent_correct(self.use(Xtrain), Ttrain)\n",
    "                pc_val = self.percent_correct(self.use(Xval), Tval)\n",
    "                self.pc_trace.append([pc_train, pc_val])\n",
    "\n",
    "                if self.best_pc_val is None or pc_val > self.best_pc_val:\n",
    "                    self.best_pc_val = pc_val\n",
    "                    self.best_epoch = epoch + 1\n",
    "                    # Save weights to be restored when done training\n",
    "                    self.best_parameters = [p.clone() for p in self.parameters()]\n",
    "\n",
    "            if verbose and (epoch + 1) % max(1, (n_epochs // 10)) == 0:\n",
    "                print(f'{method} Epoch {epoch + 1} % Correct: Train {self.pc_trace[-1][0]:.1f}'\n",
    "                      f' Val {self.pc_trace[-1][1]:.1f}')\n",
    "\n",
    "        # Restore weights that resulted in best_pc_val\n",
    "        for p, bestp in zip(self.parameters(), self.best_parameters):\n",
    "            p.data = bestp.clone()\n",
    "\n",
    "        return self\n",
    "\n",
    "    def _softmax(self, Y):\n",
    "        '''Apply to final layer weighted sum outputs'''\n",
    "        # Trick to avoid overflow\n",
    "        maxY = torch.max(Y, axis=1)[0].reshape((-1,1))\n",
    "        expY = torch.exp(Y - maxY)\n",
    "        denom = torch.sum(expY, axis=1).reshape((-1, 1))\n",
    "        Y = expY / denom\n",
    "        return Y\n",
    "\n",
    "    def use(self, X, return_probs=False, keep_all_outputs=False):\n",
    "        \n",
    "        classes = []\n",
    "        probs = []\n",
    "        return_numpy = False\n",
    "        \n",
    "        X = (X - self.Xmeans) / self.Xstds\n",
    "\n",
    "        for first in range(0, X.shape[0], self.batch_size):\n",
    "            X_batch = X[first:first + self.batch_size]\n",
    "\n",
    "            if not isinstance(X_batch, torch.Tensor):\n",
    "                X_batch = self._X_as_torch(X_batch)\n",
    "                return_numpy = True\n",
    "\n",
    "            with torch.no_grad():\n",
    "                \n",
    "                Y = self(X_batch, keep_all_outputs=keep_all_outputs)\n",
    "                class_index = torch.argmax(Y, axis=1).cpu().numpy()\n",
    "                classes.extend(self.classes[class_index])\n",
    "                \n",
    "                if return_probs:\n",
    "                    probs.extend(self._softmax(Y).cpu().numpy())\n",
    "                \n",
    "        if return_numpy:\n",
    "            classes = np.array(classes) # .cpu().numpy()\n",
    "            probs = np.array(probs) # .cpu().numpy()\n",
    "                    \n",
    "        if return_probs:\n",
    "            return classes, probs\n",
    "        else:\n",
    "            return classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-24T16:56:43.189091Z",
     "start_time": "2022-10-24T16:56:41.955714Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "farley has an available cuda GPU.\n",
      "Using device cuda\n"
     ]
    }
   ],
   "source": [
    "import platform\n",
    "\n",
    "node = platform.node()\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    print(f'{node} has an available cuda GPU.')\n",
    "    \n",
    "if torch.backends.mps.is_available():\n",
    "    print(f'{node} has an available mps GPU.')\n",
    "    \n",
    "device = 'cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu'\n",
    "\n",
    "# device = 'cpu'\n",
    "\n",
    "print('Using device', device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-24T16:56:43.864031Z",
     "start_time": "2022-10-24T16:56:43.699629Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tue Nov  5 12:08:47 2024       \n",
      "+-----------------------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 550.127.05             Driver Version: 550.127.05     CUDA Version: 12.4     |\n",
      "|-----------------------------------------+------------------------+----------------------+\n",
      "| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |\n",
      "|                                         |                        |               MIG M. |\n",
      "|=========================================+========================+======================|\n",
      "|   0  NVIDIA GeForce RTX 3090        Off |   00000000:02:00.0 Off |                  N/A |\n",
      "|  0%   45C    P8             21W /  350W |     380MiB /  24576MiB |      0%      Default |\n",
      "|                                         |                        |                  N/A |\n",
      "+-----------------------------------------+------------------------+----------------------+\n",
      "                                                                                         \n",
      "+-----------------------------------------------------------------------------------------+\n",
      "| Processes:                                                                              |\n",
      "|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |\n",
      "|        ID   ID                                                               Usage      |\n",
      "|=========================================================================================|\n",
      "|    0   N/A  N/A      5695      G   /usr/libexec/Xorg                              11MiB |\n",
      "|    0   N/A  N/A    370769      C   ...e/fac/anderson/anaconda3/bin/python        356MiB |\n",
      "+-----------------------------------------------------------------------------------------+\n"
     ]
    }
   ],
   "source": [
    "!nvidia-smi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "banner.next_topic()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Try it on MNIST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-24T16:56:45.261855Z",
     "start_time": "2022-10-24T16:56:45.258420Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((50000, 784), (50000,), (10000, 784), (10000,), (10000, 784), (10000,))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with gzip.open('mnist.pkl.gz', 'rb') as f:\n",
    "    train_set, valid_set, test_set = pickle.load(f, encoding='latin1')\n",
    "\n",
    "Xtrain = train_set[0]\n",
    "Ttrain = train_set[1] \n",
    "Xval = valid_set[0]\n",
    "Tval = valid_set[1]\n",
    "Xtest = test_set[0]\n",
    "Ttest = test_set[1] \n",
    "\n",
    "Xtrain.shape, Ttrain.shape, Xval.shape, Tval.shape, Xtest.shape, Ttest.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import convnet2d as cnn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ConvNet: Using device cuda\n",
      "adam Epoch 10 % Correct: Train 89.8 Val 91.0\n",
      "adam Epoch 20 % Correct: Train 93.9 Val 94.4\n",
      "adam Epoch 30 % Correct: Train 96.5 Val 96.7\n",
      "adam Epoch 40 % Correct: Train 97.6 Val 97.5\n",
      "adam Epoch 50 % Correct: Train 98.2 Val 97.8\n",
      "adam Epoch 60 % Correct: Train 98.6 Val 98.0\n",
      "adam Epoch 70 % Correct: Train 98.9 Val 98.2\n",
      "adam Epoch 80 % Correct: Train 99.2 Val 98.3\n",
      "adam Epoch 90 % Correct: Train 99.3 Val 98.4\n",
      "adam Epoch 100 % Correct: Train 99.5 Val 98.4\n",
      "% Correct Test 98.3\n"
     ]
    },
    {
     "data": {
      "image/png": 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HbOUPzSN9IIWUqfyDv+LDNtoTAsKq8ZHjbVmo1FpTeQyJ2eLbihAWXv7cVvWcNdo3gIQdFlpNYb6BwBoF4bZDwSIs3PM4/IM9LPzILSP1TZi56j2rjpQU/17nBwo7IhI0OUVONv5RwMY/8tn0Rz4b/yhgZ04Rf+Q6/nT9F3OYidRGEbSMj6RlfCTJsXaSYm0kxUWQFBNBaqMIGkUeZ6BxFh0KI8XZlQZblrdkOPKrjq2oaEGpaN0w8Pyru+LDFhMUHfS8p8txfHVV5nJU733C7Yc+tEuLy8dsHOX7Du+OsDf2tEhYozzhwBrpCQLhEYcFDduhEFHRalQ53Fjsf94aJfXXOedA8+YYu3Z5xugczmSC5s091wWJwo6I+E2x08XO7CIys4vIPFjMzuwidmYXk1n+9VizlEwmSIyxkRxnp0VjOy3iI2nROJIW8XZaxkeS2siOpTqr6JYWQ95uyNsFubs8XyueFx/0bTUoc3qOOQv8eBeOwhoD0U0hKhGiEiA6EaKaegJHZeFWz/GoxPLrm3paciqPSXG7fMNHmAUsEZ6gcaR/iVfMxjEM3xYRBRIJBLMZ/v53uOIKDEyYKo39MUwmz1ieadOCNjgZFHZEpIZKXW62Hyhiy74Ctuwv9HzdV8i2A0XsL/jzlodmjey0SYqmbVIMbRKjyYi3kWotoqkpF0vJASj+w/OB7Z1pYoHsMsiqNNjVWejb0lKc7en2ySsPNMfDbPMEEHvjQ10ZFV0k1mjP8cpjK6p0kYQdaglyOT1dT/b4Q8HGYj++uvzBHA7muND9fGl4hgzBOXtOlXV2jGbNMP3df+vsVJfCjhzRueeey6mnnsq0adMASE9PZ+zYsYwdO/ao32MymZg/fz6XX375Cf1sf72PnJhip4st+z1B5vd9BWzKKmDTH/ls3V9Iqevo87FjIsJp0TiStMZW2kU7aBVZSHNrIcnmPJqQg61wj6eVJXMX/Lrb081ztFkfx8sSCbHNIK4ZxDaH2FTP86im5WM7Ks1IsTf2tKDYYtXSIeJHrssH80ZsJ58VlAfdeRWRdlvQa1HYqYcuueQSiouLWbRoUZVz3333HT179mTlypWcfvrp1X7PFStWVNkp/URNmDCBDz/8kNWrV/sc37NnD40bN/brz5IjMwzPwOBNfxSweV8Bv2cVsDmrgC37CsqnaxvEUkSsqZAoSojCwRmmEhpbSmkbU0KryCKaWwpoGpZHnDsXuysfsyMXCnMgO78GlZggssmhlpWKtUUqWknCwquOCzl8rElkk0MBJ6KRgotILWCYzezs0uPQgSB2XVWmsFMP3XTTTQwZMoTt27eTlpbmc+7NN9/k1FNPrVHQAWjatKk/Szym5OTkoP2shsQwDDIPFrN2dy5rd3ke23ftIaJ4Dy1NWbQ0ZZFuyuIc0z6amnJIsOWSYMrDylFm+hSVP47FFOYJIRXjT6KTPIEkNhXiyltcopM915j1vyMRCQz936Ueuvjii0lMTGTGjBk89thj3uNFRUXMmTOHe++9l2uvvZYlS5Zw8OBBTjrpJB588EGuvfbao77n4d1YmzZt4qabbmL58uW0atWKv//971W+54EHHmD+/Pns3LmT5ORkhg0bxqOPPorFYmHGjBk8/vjjAN6F16ZPn87IkSOrdGOtWbOGMWPG8N133xEZGcnQoUOZOnUq0dHRAIwcOZKcnBx69erFc889h9Pp5JprrmHatGlYLIevWdFAuN04Dmxj2+Z17N6+mZw/tuPKyaRR2X5STbmcYsqjKbnYTKVQnRblymt1VLSuRDbxdAtFJ3rCTGQT33EtFS0uxzN1VUTEjxR2asowPAt3hYIlslpN8+Hh4QwfPpwZM2bw6KOPesPEBx98gNPp5Oabb+a9997jgQceIDY2lk8++YQbbriBVq1a0aNHjz95d3C73QwZMoSEhAS+//578vLyjjiWJyYmhhkzZpCamsqaNWu45ZZbiImJ4f777+fqq69m7dq1fPbZZ97utri4qgMoi4qKGDBgAGeeeSYrVqwgKyuLm2++mbvuuosZM2Z4r/vqq69ISUnhq6++YvPmzVx99dWceuqp3HLLLX/6+9RZhgGOvPIZR7tx7NvMgS2rMfauJb5wM3ajmHZAu8rfc4TcYUQ0whSfAY3TPY9GaRCTcmgmUFSiZ6aPiEgdpbBTU6VFMCk1ND/7wd2ef1FXw6hRo3j22Wf5+uuv6du3L+DpwhoyZAjNmjVj3Lhx3mvvvvtuPvvsMz744INqhZ1Fixaxfv16tm3bRvPmzQGYNGkSAwcO9Lnu4Ycf9j5PT0/n3nvvZc6cOdx///3Y7Xaio6MJDw8/ZrfVu+++S3FxMW+//bZ3zNBLL73EJZdcwjPPPENSUhIAjRs35qWXXsJsNtO+fXsGDRrEF198UX/CjrMI9q6BPath90+w5xfc2dsIKy30XmIDKv/NdBjh7DElUmRPxhzXjJikDJo2S8cSm3Jo2nNUU0zWyGD/NiIiQaWwU0+1b9+enj178uabb9K3b19+//13lixZwueff47L5eLpp59mzpw57Nq1C4fDgcPhqPYA5PXr19OyZUtv0AE466yzqlz373//m2nTprF582YKCgooKysjNja2Rr/H+vXr6dKli09tZ599Nm63mw0bNnjDTseOHTFXGviWkpLCmjVravSzapUyB+z4HrZ8DVu+gj0/V9nXp2LFmRwjij1GE3YZTdhjawVJnWh60mm063ga6YlxDW9/JhGRwyjs1JQl0tPCEqqfXQM33XQTd911F//4xz+YPn06aWlpnH/++Tz77LM8//zzTJs2jc6dOxMVFcXYsWNxOqu3M65xhBUxD/9A/f7777nmmmt4/PHH6d+/P3FxccyePZvnnnuuRr+DYRhH/bCufPzwsTkmkwm3+8+3F6g1SvJg14+QuQIyv8fY/h2mw/YZyjIascadwRojgzXuDLaRQnTTNE7JSKV7Rjzd0xtzQVwI13IREamlFHZqymSqdldSqF111VWMGTOGWbNm8dZbb3HLLbdgMplYsmQJl112Gddffz3gGYOzadMmTj755Gq9b4cOHdixYwe7d+8mNdXTcfLdd9/5XPPtt9+SlpbGQw895D22fft2n2usVisu17F3Qe7QoQNvvfUWhYWF3tadb7/9lrCwMNq2bVutemslVylsXwa/fQLblkDWeiqvNWPCE26Wujux1NWJZe6OZJma0DE1jjNbxXNtRhO6p8cTF9lAB2CLiNSAwk49Fh0dzdVXX82DDz5Ibm4uI0eOBKB169bMnTuXZcuW0bhxY6ZOncrevXurHXYuuOAC2rVrx/Dhw3nuuefIy8vzCTUVP2PHjh3Mnj2b7t2788knnzB//nyfa9LT09m6dSurV6+mefPmxMTEYLP5Tg0aNmwYjz32GCNGjGDChAns27ePu+++mxtuuMHbhVVnFO6HbUthw/9g4wLPyr+VZBqJrHS3ZpW7Dd+7O/C7qQWdmzWiR0Y8T6XH0z0jnji7wo2ISE0p7NRzN910E2+88Qb9+vWjZcuWADzyyCNs3bqV/v37ExkZya233srll19Obm5utd4zLCyM+fPnc9NNN3HGGWeQnp7OCy+8wIABA7zXXHbZZfz1r3/lrrvuwuFwMGjQIB555BEmTJjgvWbo0KHMmzePvn37kpOT4516XllkZCQLFixgzJgxdO/e3Wfqea1mGLDvN9j+radraudyOLjF55ICcxyflp7GF2WnstLdln00Ir1JJP07JvNom6ac1rIRUTb9JyoicqJMxpEGYDQweXl5xMXFkZubW2UAbUlJCVu3biUjI4OICE2/rU/8/mfrLISt38Cmz2HTQsjNrHJJTlQrvig9hdn5p7DSaIubMNonx3BR5xT6d0ymbVK0BhSLSL1Q5Czjn4t9/5F3W59WRFr994+4Y31+V6Z/NoqcqINbYMlU+OV9cFXaCDM8AqNFD/6I68LH2S14fUs8fxzwDCCOsIRxZZdmDDuzJac0bxSaukVEGgiFHZHjtX8zLPk/T8gxygdax7WEtv0oyTifD3Na8faKfaxbn+f9lrZJ0QzrkcblpzXT+BsRkSBR2BGpidIS+P1L+GUOrP/o0No3rS+A3vexO+YU3v5+B+99sIPc4t8BsIaHcXHnFK7r0ZKuaY3VTSUiEmQKOyJ/pswJv38Bv86H3/4Hzkq7ebcdiOuccXxXks7spTv4dO3XuNyeYXAt4yMZflYaV3RtTqNIa4iKFxERhZ1q0jju+udP/0zLHPDTO7B0mu9g45hUjA6XsjHlUuZkNua/b+9mX/4P3tNntWrCqF4ZnNc+EXOYWnFEREJNYedPVKzMW1RUhN2u1Wnrk6Iiz4auVXZGLy2GlW/Bt3+H/PLVsqMSodNQHO0uYd6+Zvxr6TZ+X5wD5ADQKNLCRZ1TGNajJR1Tq25oKiIioaOw8yfMZjONGjUiKysL8Kz7ojEXdZthGBQVFZGVlUWjRo189tRiw2fw3zFQsNfzOrYZnD2W3PbXMHNVFtNnbWN/wa+AZ0bVhR2SuaxLKr3bNsUaHnaEnyYiIqGmsFMNFbtyVwQeqR8aNWp0aMd1Rz4seBBWve15HdcCzrmHog5X88rSnbzx3DKKnJ4ZV6lxEdx0Tiuu7t6CaC36JyJS6+n/1NVgMplISUkhMTGR0tLSUJcjfmCxWA616Gz/DubfBjnbAROcdSfGeQ/z8bpsJv39e/bklgDQPjmG2/q04uJTUrGY1YojIlJXKOzUgNls9u3ykLqtzAFfTfKMzcHwrJEz+BV+iziFCdNX8/2WgwA0a2Tn4UEnM6BTsrowRUTqIIUdaZj++BXm3Qp/rPW8PnUYjgsn8tK3Wbz89VJcbgNbeBh3nHsSt/c5iQiLQq6ISF2lsCMNi9sF3/0DvnwSXE6IbAKX/J1fYs7hvtd+YcMfnjV0+ndM4uFBHWgRHxnigkVE5EQp7EjD4Cr1rHy8dBrsWOY51nYgjoue54Ufcnl18TJcboMmUVaevLwTF3VOCWm5IiLiP7V+lGV+fj5jx44lLS0Nu91Oz549WbFihff8yJEjMZlMPo8zzzwzhBVLrWEYkLkcPhkHz7WDWVd5go41Gi55gU3nvcZlMzbxj69+x+U2uPiUFBbe00dBR0Sknqn1LTs333wza9eu5Z133iE1NZWZM2dywQUXsG7dOpo1awbAgAEDmD59uvd7rFYtzd/g5e2G94fDzkPBmKim0GkoRo/bmbUpjCf/8S0lpW6aRFl56vJODFTIERGpl2p12CkuLmbu3Ln85z//oXfv3gBMmDCBDz/8kFdeeYWnnnoKAJvNdmi9lGpwOBw4HA7v67y8vGNcLXXOzpUw+zrPwoCWSDj5EjjlKsg4lxyHm7/NXcNnv3oWDTynTQLPXdWFxJiI0NYsIiIBU6vDTllZGS6Xi4gI3w8iu93O0qVLva+//vprEhMTadSoEX369GHixIkkJiYe9X0nT57M448/HrC6JYR++QD+cye4HJDYAa59DxqnA/DVhiwenLeGPbklWMwm7uvfjpt7tSJM+1eJiNRrJqOW73DZs2dPrFYrs2bNIikpiffee4/hw4fTpk0bNmzYwJw5c4iOjiYtLY2tW7fyyCOPUFZWxsqVK7HZbEd8zyO17LRo0YLc3FxiY2OD9auJP7nd8OUTsPR5z+u2A2Ho62CLISuvhMc/Xscnv+wBICMhiheuOY3OzbWHlYhIoBQ5y/jn4i0+x27r04pIq//aWfLy8oiLi/vTz+9a3bID8M477zBq1CiaNWuG2Wzm9NNP57rrrmPVqlUAXH311d5rO3XqRLdu3UhLS+OTTz5hyJAhR3xPm8121CAkdZCzCObfCuv/63nd6x447xHcmHj3++1M+fQ38h1lhJngpl4ZjL2gLVHa5kFEpMGo9f/HP+mkk1i8eDGFhYXk5eWRkpLC1VdfTUZGxhGvT0lJIS0tjU2bNgW5UgmJgn3w3jWw60cwW+HSl6DL1RwsdHLHzJX8sNWzCnKX5nFMHNyZTs3UmiMi0tDU+rBTISoqiqioKLKzs1mwYAFTpkw54nUHDhwgMzOTlBTNrKn39m+Gd4dC9jaIaATXzIL0s9mcVcCoGSvYcbCIKKuZ+/q344az0jFrbI6ISINU68POggULMAyDdu3asXnzZu677z7atWvHjTfeSEFBARMmTGDo0KGkpKSwbds2HnzwQRISEhg8eHCoS5dA2vYtzBkGxdnQKA2G/RuatmXZ5v3cPnMleSVlNG9sZ/rI7rRJigl1tSIiEkK1Puzk5uYyfvx4du7cSXx8PEOHDmXixIlYLBbKyspYs2YNb7/9Njk5OaSkpNC3b1/mzJlDTIw+4OodVxls+B8sfw22LfEca9YVrp0N0Ym8/2MmD85bQ5nb4PSWjXhteDcSojU2S0Skoav1Yeeqq67iqquuOuI5u93OggULglyRBJ0j3xNwVrwJeTs9x0xmOOVqGPQcrnA7U/63nn9+4xn1f0mXVJ694hRt3ikiIkAdCDvSwOVkwrtXwr71nteRTaDrSOg2CuKak1dSypi3VvDVhn0A3H1ea/56QVutnSMiIl4KO1J77fkZ3r3KsxJydDJc8Bh0HAIWzyKTW/cXcvNbK/h9XyG28DCevbILl3ZJDXHRIiJS2yjsSO208XP4YCSUFkLTk2HYB9Cohff00k37uXPWKnKLS0mOjeD14d20SKCIiByRwo7ULm43/PgGfPoAGC7I6ANXvwMRh4LM/J92Mu6DX3C5DU5r2Yh/3tBVe1uJiMhRKexI7eB2wboP4Zv/g6x1nmOnDoOLp0H4oV3s31i6lSc/9py/7NRUnhmqgcgiInJsCjsSWm4XrJ0L3zwL+zd6jtliofd90PNuMHkGGhuGwbMLNvDy178Dnm0fHrroZA1EFhGRP6WwI6HjyIfZw2DrYs/riDg4807ocRvYG3kvK3O5efjDtcxekQnA/QPacUefkzCZFHREROTPKexIaBQd9Ewp3/UjWKOh11/hjFshwnfX2lKXm7GzV/PJmj2EmWDS4M5cc0bLEBUtIiJ1kcKOBF/+XnhnsGdsjr0xXD/XsxLyYRxlLu589ycWrf8DqzmMF649jQGdkkNQsIiI1GUKOxJc2dvh7csge6tn7ZzhH0LiyVUuKyl1cds7K1m8cR+28DD+eUNXzm2XGPx6RUSkzlPYkeDZt9ETdPJ3ezbvHP4fiM+oclmRs4ybZvzId1sOYLeYeWNEN3q2TghBwSIiUh8o7Ehw7F3rCTpF+6Fpe7jhQ4hNqXLZwUInt779Iz9uzybaFs70G7vTPT0++PWKiEi9obAjgbdrlWeMTkkOJJ/iCTpRTapctn5PHre8/SM7s4uJiQjn7VFncFrLxkEvV0RE6heFHQmsHd97Zl058qB5dxj2b59p5RU+XbOHe97/meJSFy3jI3l9eDfaJccEv14REal3FHYkcDYvgjk3QGkRpJ8D174HNt8A43YbTPtiEy98sQmAXq0TeOm602gUaT3SO4qIiNSYwo74n7MQFk2A5a95Xp90Plw9E6yRPpeVlLq45/3V/G/NXsCzKvL4ge0JN4cFuWAREanPFHbEv7Z9C/8ZDdnbPK+73ggDn4Fwm89luUWl3PL2jyzfdhCrOYxJQzpzRdfmwa9XRETqPYUd8Y/SYlj0OPzwKmBAbHO49AVofX6VS3fnFDPizeVsyiogxhbOP4d3pedJmlouIiKBobAjJ+7A7/D+CPhjjef16cOh31Oeva4O89vePEa+uYK9eSUkxdp4a9QZtE+OrXKdiIiIvyjsyIn59UP4z13gzIfIBLj8FWjb74iX/rjtIDfOWEF+SRmtE6N5a9QZNGtkD269IiLS4CjsyPEpc8LCR8q7rYCWZ8EVb0Js6hEvX7JpH7e+vZLiUhfd0hrzrxHdNONKRESCQmFHai53p6fbatePntdnj4XzHgHzkf86Lfh1L3fP+gmny02ftk159fqu2K3m4NUrIiINmsKO1MyWr+Hfo6DoAEQ0gsGvQruBR738w592ce8HP+NyGwzslMy0a07FFq6gIyIiwaOwI9VjGPDtNPjiCTDcnm0frn4HGqcf5XKDt5Zt4/GP12EYMOT0ZkwZeorW0BERkaBT2JE/V5IHH94Bv33seX3qMBj0HFiOPLi42OnioflrmPfTLgCGn5XGhEs6EhZmClbFIiIiXgo7cmz7N8Psa2H/RjBbYeAU6DoSTEcOLlv3F3LHzJX8tjcfc5iJ+/u349berTAd5XoREZFAU9iRo9u4AObe7NnEMybV023VvNtRL/9s7V7u++Bn8h1lJETbeOm60zizVdXdzUVERIJJYUeqMgxY8n/w5UTA8Ewrv+ptiE484uVut8Hzizby4pebAeie3ph/XHc6ibERQSxaRETkyBR2xJejwDM+Z/1HntfdboIBT0P4kdfEKXKWce/7P/Pp2kObef5tYHssGogsIiK1hMKOHHLgd5g9DPathzALDPo/z/ico9iTW8wtb//I2l15WMwmJg3uzJXdWgSvXhERkWpQ2BGPTYtg7igoyYXoJLjqHWjZ46iX/5yZwy1v/0hWvoP4KCv/vKEr3dPjg1iwiIhI9SjsNHSGAUuf96yfgwHNu3uCTmzKUb/l0zV7GDtnNY4yN+2SYvjXiG60iI8MXs0iIiI1oLDTkJU5PJt4rnnf8/r04XDR/0G47YiXG4bBa99sYfKnvwHQt11TXrj2NGIiLMGqWEREpMYUdhqq4myYcwNsWwImM1w0xTMY+Sjr4ZS63Dz6n7W8tzwTgJE903l40MlaEVlERGo9hZ2GKHs7vHsl7N8A1hi46i1off5RL88vKWX0u6tYsmk/YSZ45OIO3Hh2RhALFhEROX4KOw3NrlUw62oozPIsFDjsA0judNTLc4qcDH9zOb/szCXSauaFa07jgg5JQSxYRETkxCjsNCQbPvXsWF5aBEmdYdj7EJt61MsPFDi4/o3lrN+TR3yUlbdHnUGnZnFBLFhEROTEKew0FMtfh0/v9+xYftL5cOUMiIg96uVZ+SUMe/0HNmUVkBBtY9YtPWibFBO8ekVERPxEYae+c7th4SPw3Uue16cPh0FTwXz0GVR7cosZ9voPbNlfSHJsBLNu6UGrptFBKlhERMS/FHbqs9JimH8brPuP5/V5j8A59x51xhXAvnwH17z2PdsPFNGskZ33bjmTlk20ho6IiNRdtX7ecH5+PmPHjiUtLQ273U7Pnj1ZsWKF97xhGEyYMIHU1FTsdjvnnnsuv/76awgrriXcLnh/uCfohFlgyL+g97hjBp0iZxk3vbWC7QeKaBFvZ85tCjoiIlL31fqwc/PNN7Nw4ULeeecd1qxZQ79+/bjgggvYtWsXAFOmTGHq1Km89NJLrFixguTkZC688ELy8/NDXHmIffkUbPocwu1ww3w45cpjXl7mcnP3rJ/4ZWcujSMtvD2qB80bK+iIiEjdV6vDTnFxMXPnzmXKlCn07t2b1q1bM2HCBDIyMnjllVcwDINp06bx0EMPMWTIEDp16sRbb71FUVERs2bNOur7OhwO8vLyfB71yq8fwtKpnueXvggZ5xzzcsMweOyjX/nityxs4WH8a0R3MhKiAl+niIhIENTqsFNWVobL5SIiIsLnuN1uZ+nSpWzdupW9e/fSr18/7zmbzUafPn1YtmzZUd938uTJxMXFeR8tWtSjnbr/WAcfjvY8P+uuP23RAXhl8e+8+8MOTCb4+zWn0TWtcYCLFBERCZ5aHXZiYmI466yzePLJJ9m9ezcul4uZM2fyww8/sGfPHvbu3QtAUpLvIndJSUnec0cyfvx4cnNzvY/MzMyA/h5BU5wNs6+D0kLI6AMXPP6n3/Kf1buY8tkGAB69uAMDOiUHukoREZGgqtVhB+Cdd97BMAyaNWuGzWbjhRde4LrrrsNsNnuvMR026NYwjCrHKrPZbMTGxvo86jy3C+beDNlbIa4lXDEdzMeebPf9lgPc98EvANzcK0NbQIiISL1U68POSSedxOLFiykoKCAzM5Ply5dTWlpKRkYGycmeVojDW3GysrKqtPbUez+9A5sXeQYkX/MuRDU55uWb/sjn1rd/xOlyM7BTMg9edHKQChUREQmuWh92KkRFRZGSkkJ2djYLFizgsssu8waehQsXeq9zOp0sXryYnj17hrDaICvJ88y+Ajj/UUg55ZiXZ+WVMHL6CvJKyuia1pjnrz6VsLCjt4SJiIjUZbV+UcEFCxZgGAbt2rVj8+bN3HfffbRr144bb7wRk8nE2LFjmTRpEm3atKFNmzZMmjSJyMhIrrvuulCXHjxLnoPCfdCkNZxxyzEvLXSUMeqtFezKKSYjIYrXh3cjwmI+5veIiIjUZbU+7OTm5jJ+/Hh27txJfHw8Q4cOZeLEiVgsnu0O7r//foqLixk9ejTZ2dn06NGDzz//nJiYBrKPU/Y2+P5lz/N+Tx1zGwiX2+CuWatYuyuPJlFWZtzYnfgoa3DqFBERCRGTYRhGqIsItby8POLi4sjNza17g5XfHwHrPvTMvhr+n2OukDx14UZe+GITEZYw3rvlTE5rqSnmIiISGEXOMv65eIvPsdv6tCLS6r92lup+fteZMTtyBNu/8wQdUxj0n3TMoPPNxn28+OUmAJ4ecoqCjoiINBgKO3WV2w0Lxnuen3YDJHc66qV7cosZO2c1hgHX9WjJ5ac1C1KRIiIioaewU1eteR92/wTWGDjv4aNeVlq+59XBQicdU2N59OIOQSxSREQk9BR26iLDgMXPeJ73vheiE4966f8t2MCP27OJsYXz8rDTNfNKREQaHIWdumjHd3BwC1ij4Yxbj3rZonV/8M9vPIPDnr3yFNKaaHNPERFpeBR26qKf3vV87Xg5WI8cYPYXOLh/rmcriFFnZzCgU0qQihMREaldFHbqGkcB/Drf8/zU64962aP/WcvBQiftk2N4YGC7IBUnIiJS+yjs1DXr/+vZ1bxxBrQ884iXfPzLbv63Zi/hYSb+78ou2MI1TkdERBouhZ26ZnV5F9apw464rs6+fAePfLgWgDv7tqZTs7hgViciIlLrKOzUJdnbYNsSwARdrqly2jAMHv5wDdlFpZycEsudfVsHvUQREZHaRmGnLln9nudrqz7QqEWV0x/9vJsFv/5BeJiJ567sgjVcf7wiIiL6NKwr3G74eZbn+anDqpzeX+Dg0f/8CsBfzm9Dh9Q6tseXiIhIgNQ47HzzzTeUlZVVOV5WVsY333zjl6LkCLZ/Czk7wBYL7S+ucvrVr38nt7iUDimx3HHuSSEoUEREpHaqcdjp27cvBw8erHI8NzeXvn37+qUoOYKKgckdB4M10udUVl4J73y/HYAHBrbHYlaDnYiISIUafyoahoHpCLOADhw4QFSUVugNCEc+rPuP5/lpVdfWefnr33GUuema1pjebRKCXJyIiEjtFl7dC4cMGQKAyWRi5MiR2Gw27zmXy8Uvv/xCz549/V+hwG+fQGkRNGkNzbv7nNqbW8Ks5TsAuOfCtkcMoiIiIg1ZtcNOXJxnvRbDMIiJicFut3vPWa1WzjzzTG655Rb/VyiwcYHna4fLq6yt8/LXm3GWuTkjPZ6eJzUJfm0iIiK1XLXDzvTp0wFIT0/nvvvuIzIy8k++Q/zCVQa/f+F53ra/z6ldOcXMXp4JwF/VqiMiInJENR6zM3z4cHbt2lXl+KZNm9i2bZs/apLKdq6AklywN4ZmXX1O/eOrzThdbs5q1YSz1KojIiJyRDUOOyNHjmTZsmVVjv/www+MHDnSHzVJZZs+93xtfQGEHdrjKvNgEe+vONSqIyIiIkdW47Dz008/cfbZZ1c5fuaZZ7J69Wp/1CSVbVro+dr6Qp/DL3+9mTK3Qa/WCZyRER+CwkREROqGGocdk8lEfn5+leO5ubm4XC6/FCXl8nbDH2sAE7Q+/9DhklLm/+TpShxzQZsQFSciIlI31DjsnHPOOUyePNkn2LhcLiZPnkyvXr38WlyDV9Gq06wrRB1aP+d/v+yhpNRN68RouqU1DlFxIiIidUO1Z2NVmDJlCr1796Zdu3acc845ACxZsoS8vDy+/PJLvxfYoFWM12nTz+fwv1fuBOCKrs01A0tERORP1Lhlp0OHDvzyyy9cddVVZGVlkZ+fz/Dhw/ntt9/o1KlTIGpsmMqcsOVrz/M2h8brbN1fyI/bswkzweDTmoWmNhERkTqkxi07AKmpqUyaNMnftUhlmd+DswCimkLKqd7Dc8tbdXq3bUpSbESIihMREak7jmvHyCVLlnD99dfTs2dP75o777zzDkuXLvVrcQ2ad8r5hRDm+WNyuQ3mrjrUhSUiIiJ/rsZhZ+7cufTv3x+73c6qVatwOBwA5Ofnq7XHnyoGJ1fqwvru9wPsyS0hNiKcC05OClFhIiIidUuNw85TTz3Fq6++yuuvv47FYvEe79mzJ6tWrfJrcQ1W9nbY9xuYzHBSX+/hf6/0LCJ46ampRFjMR/tuERERqaTGYWfDhg307t27yvHY2FhycnL8UZNsLm/VadHDs00EnrV1Pvt1LwBXdG0RqspERETqnBqHnZSUFDZv3lzl+NKlS2nVqpVfimrwjtCFVXltnS7N40JUmIiISN1T47Bz2223MWbMGH744QdMJhO7d+/m3XffZdy4cYwePToQNTYsbjdsKx/o3foC72GtrSMiInJ8ajz1/P777yc3N5e+fftSUlJC7969sdlsjBs3jrvuuisQNTYsuTs8U87NVkjsAGhtHRERkRNRo7DjcrlYunQp9957Lw899BDr1q3D7XbToUMHoqOjA1Vjw5K13vM1oS2YPX88C9d5xuqc3TpBa+uIiIjUUI3Cjtlspn///qxfv574+Hi6desWqLoarqx1nq+JJ3sPfb/lIAB92jYNRUUiIiJ1Wo3H7HTu3JktW7YEohYByPrN87U87LjcBiu2esLOma2ahKoqERGROqvGYWfixImMGzeOjz/+mD179pCXl+fzkBNU0Y1VPl5n3e488h1lxESEc3JKbAgLExERqZtqPEB5wIABAFx66aU+s4IMw8BkMuFyufxXXUPjKoP9GzzPy1t2vt9yAIAz0uMxh2kWloiISE3VOOx89dVXgahDAA5uAZcTLFEQ1xI4FHbUhSUiInJ8ahR2SktLmTBhAv/85z9p27ZtoGpquLyDk9tDWBgut8HybZ7xOj1axYewMBERkbqrRmN2LBYLa9euDdqidmVlZTz88MNkZGRgt9tp1aoVTzzxBG6323vNyJEjMZlMPo8zzzwzKPX5nXe8jqcLa/2ePPJLyoixhdNB43VERESOS427sYYPH84bb7zB008/HYh6fDzzzDO8+uqrvPXWW3Ts2JEff/yRG2+8kbi4OMaMGeO9bsCAAUyfPt372mq1Bry2gPC27HgGJ1d0YXXPiCfcXOOx5CIiIsJxhB2n08m//vUvFi5cSLdu3YiKivI5P3XqVL8V991333HZZZcxaNAgANLT03nvvff48ccffa6z2WwkJydX+30dDgcOh8P7utbMIjusZadifZ0eGerCEhEROV41bi5Yu3Ytp59+OrGxsWzcuJGffvrJ+1i9erVfi+vVqxdffPEFGzduBODnn39m6dKlXHTRRT7Xff311yQmJtK2bVtuueUWsrKyjvm+kydPJi4uzvto0aIW7CJeWgIHf/c8T+zgGa+zVYOTRURETlStno31wAMPkJubS/v27TGbzbhcLiZOnMi1117rvWbgwIFceeWVpKWlsXXrVh555BHOO+88Vq5cic1mO+L7jh8/nnvuucf7Oi8vL/SBZ/9GMNxgbwzRSazfnUdeSRnRtnA6pmq8joiIyPGqcdipbOfOnZhMJpo1C8zmlHPmzGHmzJnMmjWLjh07snr1asaOHUtqaiojRowA4Oqrr/Ze36lTJ7p160ZaWhqffPIJQ4YMOeL72my2owahkKm8mKDJxA/lqyZ3S2+s8ToiIiInoMafom63myeeeIK4uDjS0tJo2bIljRo14sknn/SZJeUP9913H3/729+45ppr6Ny5MzfccAN//etfmTx58lG/JyUlhbS0NDZt2uTXWgLusD2xtL6OiIiIf9S4Zeehhx7yzsY6++yzMQyDb7/9lgkTJlBSUsLEiRP9VlxRURFhYb55zGw2HzNUHThwgMzMTFJSUvxWR1BUGpzsdhss36rBySIiIv5Q47Dz1ltv8a9//YtLL73Ue6xLly40a9aM0aNH+zXsXHLJJUycOJGWLVvSsWNHfvrpJ6ZOncqoUaMAKCgoYMKECQwdOpSUlBS2bdvGgw8+SEJCAoMHD/ZbHUFRqRvrt7355BaXEmU106lZXGjrEhERqeNqHHYOHjxI+/btqxxv3749Bw8e9EtRFV588UUeeeQRRo8eTVZWFqmpqdx22208+uijgKeVZ82aNbz99tvk5OSQkpJC3759mTNnDjExMX6tJaBK8iB3h+d50/Z8v8rThdUtPR6LxuuIiIickBqHnS5duvDSSy/xwgsv+Bx/6aWX6NKli98KA4iJiWHatGlMmzbtiOftdjsLFizw688MiX3lm39GJ0NkPD9s3QJoiwgRERF/qHHYmTJlCoMGDWLRokWcddZZmEwmli1bRmZmJv/73/8CUWP9V2lwsmEYrNiWDUCPDA1OFhEROVE17iPp06cPGzduZPDgweTk5HDw4EGGDBnChg0bOOeccwJRY/1XabzO/gInBwudmExofR0RERE/OK51dlJTU/06ELnBq9SysykrH4CW8ZFEWMwhLEpERKR+qHbLzqZNm7j22muPuI9Ubm4u1113HVu2bPFrcQ1GpZadTX8UANAmsQ4NsBYREanFqh12nn32WVq0aEFsbNWulYr9pZ599lm/FtcgFB6AwvK9vJq287bstEmKDmFRIiIi9Ue1w84333zDlVdeedTzV111FV9++aVfimpQ9pW36jRKA1t0pZYdhR0RERF/qHbY2b59O4mJiUc9n5CQQGZmpl+KalAq74kFbMryhJ22SerGEhER8Ydqh524uDh+//33o57fvHnzEbu45E/kbPd8jW/FgQKHdybWSU3VsiMiIuIP1Q47vXv35sUXXzzq+RdeeEFTz49H/l7P15hkb6tO88Z27FbNxBIREfGHaoed8ePH8+mnn3LFFVewfPlycnNzyc3N5YcffmDo0KEsWLCA8ePHB7LW+skbdlLY9IdncHJbzcQSERHxm2qvs3Paaafx73//m1GjRjF//nyfc02aNOH999/n9NNP93uB9Z437CSxaaunZae1ZmKJiIj4TY0WFbz44ovZvn07n332GZs3b8YwDNq2bUu/fv2IjIwMVI31W8Efnq8xKWz6w7MBqNbYERER8Z8ar6Bst9sZPHhwIGppeJyF4ChfpDE6iU1Z2wBoq5YdERERv6nx3ljiRxVdWJYoDpbZ2F/gBDQTS0RExJ8UdkKp0nidzfsKAc9MrCjbcW1ZJiIiIkegsBNKBYdmYm0sn4mllZNFRET8S2EnlCpadqKT2Fy+xk4brZwsIiLiVzUOO2azmaysrCrHDxw4gNmshfBqpPIaO1lq2REREQmEGocdwzCOeNzhcGC1Wk+4oAal0pidjX+oZUdERCQQqj0S9oUXXgDAZDLxr3/9i+joQy0QLpeLb775hvbt2/u/wvqsfMxOoTWBffkOAFqrZUdERMSvqh12nn/+ecDTsvPqq6/6dFlZrVbS09N59dVX/V9hfVbesrOzLA6AZo3sRGsmloiIiF9V+5N169atAPTt25d58+bRuHHjgBXVYOR7Vk/eVBQNFKpVR0REJABq3Izw1VdfBaKOhsdZBI5cANbm24FCDU4WEREJgBqHHZfLxYwZM/jiiy/IysrC7Xb7nP/yyy/9Vly9VrHGTridX/d7Bn231eBkERERv6tx2BkzZgwzZsxg0KBBdOrUCZPJFIi66r/8ig1Ak9mYpd3ORUREAqXGYWf27Nm8//77XHTRRYGop+HI3wNAWVQSf+zxzMRSN5aIiIj/1XidHavVSuvWrQNRS8NS4GnZyQtvAkBKXAQxEZZQViQiIlIv1Tjs3Hvvvfz9738/6uKCUk3lLTv78Mxq00wsERGRwKhxN9bSpUv56quv+PTTT+nYsSMWi29rxLx58/xWXL1WPmZnr7sRABkJUSEsRkREpP6qcdhp1KgRgwcPDkQtDUt5y84el2dBwabRtlBWIyIiUm/VOOxMnz49EHU0POVjdnaWh52EGIUdERGRQKjxmB2AsrIyFi1axD//+U/y8z27de/evZuCggK/FlevlbfsbHPEAtAkSpuoioiIBEKNW3a2b9/OgAED2LFjBw6HgwsvvJCYmBimTJlCSUmJ9seqjtJiKPGsnry52DMwWS07IiIigVHjlp0xY8bQrVs3srOzsdvt3uODBw/miy++8Gtx9Vb5BqBGeATbCj0bqiZEKeyIiIgEwnHNxvr222+xWn27XdLS0ti1a5ffCqvXysfrGNHJlBR4pvAnxKgbS0REJBBq3LLjdrtxuVxVju/cuZOYGO3tVC3l43Wc9qYA2C1mIq01zp0iIiJSDTUOOxdeeCHTpk3zvjaZTBQUFPDYY49pC4nqKl9jp8jmCTtq1REREQmcGjcnPP/88/Tt25cOHTpQUlLCddddx6ZNm0hISOC9994LRI31T/mO5/nlW0UkaI0dERGRgKlx2ElNTWX16tXMnj2blStX4na7uemmmxg2bJjPgGU5hvIBygfDPGGniQYni4iIBMxxrbNjt9u58cYbeemll3j55Ze5+eabAxJ0ysrKePjhh8nIyMBut9OqVSueeOIJ3G639xrDMJgwYQKpqanY7XbOPfdcfv31V7/X4lflYWcfjQBoqm4sERGRgKlx2Jk8eTJvvvlmleNvvvkmzzzzjF+KqvDMM8/w6quv8tJLL7F+/XqmTJnCs88+y4svvui9ZsqUKUydOpWXXnqJFStWkJyczIUXXuhd7LBWKg87FVtFqGVHREQkcGocdv75z3/Svn37Ksc7duzo9wUFv/vuOy677DIGDRpEeno6V1xxBf369ePHH38EPK0606ZN46GHHmLIkCF06tSJt956i6KiImbNmuXXWvyqfMxOZmn5VhHRatkREREJlBqHnb1795KSklLleNOmTdmzZ49fiqrQq1cvvvjiCzZu3AjAzz//zNKlS72zvrZu3crevXvp16+f93tsNht9+vRh2bJlR31fh8NBXl6ezyNoSkugOBuA3x2eqfpNNEBZREQkYGo8QLlFixZ8++23ZGRk+Bz/9ttvSU1N9VthAA888AC5ubm0b98es9mMy+Vi4sSJXHvttYAneAEkJSX5fF9SUhLbt28/6vtOnjyZxx9/3K+1Vlv5goKYbewotAClmo0lIiISQDUOOzfffDNjx46ltLSU8847D4AvvviC+++/n3vvvdevxc2ZM4eZM2cya9YsOnbsyOrVqxk7diypqamMGDHCe53JZPL5PsMwqhyrbPz48dxzzz3e13l5ebRo0cKvtR9V+XgdYpLYn1sKqBtLREQkkGocdu6//34OHjzI6NGjcTqdAERERPDAAw8wfvx4vxZ333338be//Y1rrrkGgM6dO7N9+3YmT57MiBEjSE5OBqp2rWVlZVVp7anMZrNhs4WoNaV8vI47OpncvRVhRy07IiIigVKjMTsul4tvvvmGBx54gH379vH999/z888/c/DgQR599FG/F1dUVERYmG+JZrPZO/U8IyOD5ORkFi5c6D3vdDpZvHgxPXv29Hs9flHesuOMSAQgPMxEnN0SyopERETqtRq17JjNZvr378/69evJyMige/fugaoLgEsuuYSJEyfSsmVLOnbsyE8//cTUqVMZNWoU4Om+Gjt2LJMmTaJNmza0adOGSZMmERkZyXXXXRfQ2o5bedgptCUAEB9lJSzs6F1uIiIicmJq3I3VuXNntmzZUmWAciC8+OKLPPLII4wePZqsrCxSU1O57bbbfFqR7r//foqLixk9ejTZ2dn06NGDzz//vPZuSloednLN2ipCREQkGGocdiZOnMi4ceN48skn6dq1K1FRUT7nY2Nj/VZcTEwM06ZN89l49HAmk4kJEyYwYcIEv/3cgCofs3MgLB6AJhqcLCIiElA1DjsDBgwA4NJLL/WZ8VQxA8rlcvmvuvqovGUny2gEQFO17IiIiARUjcPOV199FYg6Go7ysLOrrHyrCLXsiIiIBFSNw06fPn0CUUfDUOaE4oMA7HDGAgUasyMiIhJgx7Xr+ZIlS7j++uvp2bMnu3btAuCdd95h6dKlfi2u3nEWeJ/uKPZMN9dWESIiIoFV47Azd+5c+vfvj91uZ9WqVTgcDgDy8/OZNGmS3wusVyrCjtnGvkLP2CatniwiIhJYNQ47Tz31FK+++iqvv/46FsuhxfB69uzJqlWr/FpcveMs8ny1RnGgwBMS1Y0lIiISWDUOOxs2bKB3795VjsfGxpKTk+OPmuqv0kIADGskBwo9W20o7IiIiARWjcNOSkoKmzdvrnJ86dKltGrVyi9F1VtOT9hxh0fichuAZwVlERERCZwah53bbruNMWPG8MMPP2Aymdi9ezfvvvsu48aNY/To0YGosf4o78YqNdsBiLNbsIYf1xhxERERqabj2vU8NzeXvn37UlJSQu/evbHZbIwbN4677rorEDXWH+XdWA6TJ+xocLKIiEjg1TjsgGfLiIceeoh169bhdrvp0KED0dHR/q6t/invxirBM05H085FREQCr9p9KEVFRdx55500a9aMxMREbr75ZtLT0znjjDMUdKqrvBuriAhAW0WIiIgEQ7XDzmOPPcaMGTMYNGgQ11xzDQsXLuSOO+4IZG31T3k3VoHb032lrSJEREQCr9rdWPPmzeONN97gmmuuAeD666/n7LPPxuVyYTabA1ZgvVLejZVXHnY07VxERCTwqt2yk5mZyTnnnON9fcYZZxAeHs7u3bsDUli9VN6NlVOmsCMiIhIs1Q47LpcLq9W32yU8PJyysjK/F1VvlXdjZZdW7IulbiwREZFAq3Y3lmEYjBw5EpvtUGtESUkJt99+O1FRUd5j8+bN82+F9Ul5N9bBUs9tV8uOiIhI4FU77IwYMaLKseuvv96vxdR75d1Y+xwVYUctOyIiIoFW7bAzffr0QNbRMJR3Y+VqzI6IiEjQaK+CYCrvxirCRoQljEirZrGJiIgEmsJOMJV3YxUSQUK0DZPJFOKCRERE6j+FnWAq78YqNmzaKkJERCRIFHaCqVI3VlMNThYREQkKhZ1gqrQ3VpMoteyIiIgEg8JOsLhdUFYMQJFhIyFGLTsiIiLBoLATLKVF3qdF2DTtXEREJEgUdoKlvAvLjYkSrBqgLCIiEiQKO8FSPhOrhAjApNWTRUREgkRhJ1i8M7G0erKIiEgwKewES3k3VoE7AoAmUWrZERERCQaFnWCpWFAQT4tOrN0SympEREQaDIWdYKm0oKA1PAyLWbdeREQkGPSJGywV+2IZEdoAVEREJIgUdoKlUjdWlDU8xMWIiIg0HAo7wVKpG8uulh0REZGgUdgJlop9sYwIohR2REREgkZhJ1hK1bIjIiISCgo7weLd8VxjdkRERIJJYSdYKsbsGBFq2REREQkihZ1gqdSNpZYdERGR4Kn1YSc9PR2TyVTlceeddwIwcuTIKufOPPPMEFd9BOXdWMUasyMiIhJUtb6JYcWKFbhcLu/rtWvXcuGFF3LllVd6jw0YMIDp06d7X1uttXDfqfJurEIjgiSbwo6IiEiw1Pqw07RpU5/XTz/9NCeddBJ9+vTxHrPZbCQnJwe7tJqptKhgpLqxREREgqbWd2NV5nQ6mTlzJqNGjcJkMnmPf/311yQmJtK2bVtuueUWsrKyjvk+DoeDvLw8n0fAedfZsWm7CBERkSCqU2Hnww8/JCcnh5EjR3qPDRw4kHfffZcvv/yS5557jhUrVnDeeefhcDiO+j6TJ08mLi7O+2jRokXgi6/oxiJCA5RFRESCqE596r7xxhsMHDiQ1NRU77Grr77a+7xTp05069aNtLQ0PvnkE4YMGXLE9xk/fjz33HOP93VeXl7gA0+lbiwNUBYREQmeOhN2tm/fzqJFi5g3b94xr0tJSSEtLY1NmzYd9RqbzYbNZvN3icdWqRsrSgOURUREgqbOdGNNnz6dxMREBg0adMzrDhw4QGZmJikpKUGqrBrKnOAuBaCICOyWOpMxRURE6rw6EXbcbjfTp09nxIgRhIcfCgoFBQWMGzeO7777jm3btvH1119zySWXkJCQwODBg0NY8WHKu7CgfFFBteyIiIgETZ1oYli0aBE7duxg1KhRPsfNZjNr1qzh7bffJicnh5SUFPr27cucOXOIiYkJUbVHUN6FVYqZMsI1G0tERCSI6kTY6devH4ZhVDlut9tZsGBBCCqqoUoLCgJaZ0dERCSI6kQ3Vp1XaV8sQC07IiIiQaSwEwwV+2IZFWFHLTsiIiLBorATDJUWFAwPM2EN120XEREJFn3qBoPPvljqwhIREQkmhZ1g8NkXS11YIiIiwaSwEwyVurEitcaOiIhIUCnsBENFN5Zh0yagIiIiQaawEwwV3VjaBFRERCToFHaCwVmxzk4EUQo7IiIiQaWwEwwViwpqgLKIiEjQKewEQ6VuLE09FxERCS6FnWCo1I2lsCMiIhJcCjvBULkby6ZuLBERkWBS2AmGir2xsBFpUcuOiIhIMCnsBIPPooJq2REREQkmhZ1gqLSooMbsiIiIBJfCTjB4Z2NpgLKIiEiwKewEg7cbS+vsiIiIBJvCTqAZBpSWD1A2tIKyiIhIsCnsBFppMWAA5YsKaoCyiIhIUCnsBFp5FxZAMVaN2REREQkyhZ1Aq7SgoEGYwo6IiEiQKewEWqV9sQANUBYREQkyhZ1Acx5q2QHUsiMiIhJkCjuBVnpoE9AwE9jCdctFRESCSZ+8gVZpX6woazgmkynEBYmIiDQsCjuBVrGgoGHDri4sERGRoFPYCbSKfbGIIEpr7IiIiASdwk6gVZqNZbeoZUdERCTYFHYCrVI3VpRNYUdERCTYFHYCrVI3ll1r7IiIiASdwk6gVerG0iagIiIiwaewE2jeRQUjtHqyiIhICCjsBJp3UUGbVk8WEREJAYWdQKvUjRWpAcoiIiJBp7ATaJW7sSzqxhIREQk2hZ1Aq9SNpannIiIiwaewE2gV3VhGhLaLEBERCQGFnUBzVmrZ0WwsERGRoFPYCbRK3Vhq2REREQm+Wh920tPTMZlMVR533nknAIZhMGHCBFJTU7Hb7Zx77rn8+uuvIa66kkrdWGrZERERCb5aH3ZWrFjBnj17vI+FCxcCcOWVVwIwZcoUpk6dyksvvcSKFStITk7mwgsvJD8/P5Rle7jKwOUA1LIjIiISKrU+7DRt2pTk5GTv4+OPP+akk06iT58+GIbBtGnTeOihhxgyZAidOnXirbfeoqioiFmzZoW6dG8XFkCxZmOJiIiERK0PO5U5nU5mzpzJqFGjMJlMbN26lb1799KvXz/vNTabjT59+rBs2bKjvo/D4SAvL8/nEZiCPV1YpYYZJ+FaZ0dERCQE6lTY+fDDD8nJyWHkyJEA7N27F4CkpCSf65KSkrznjmTy5MnExcV5Hy1atAhMwc6KHc9tgEkrKIuIiIRAnQo7b7zxBgMHDiQ1NdXnuMlk8nltGEaVY5WNHz+e3Nxc7yMzMzMg9VaeiQVogLKIiEgI1JlP3+3bt7No0SLmzZvnPZacnAx4WnhSUlK8x7Oysqq09lRms9mw2WyBK7ZCeTdWoRGByQQRljqVLUVEROqFOvPpO336dBITExk0aJD3WEZGBsnJyd4ZWuAZ17N48WJ69uwZijJ9VerGirSYj9naJCIiIoFRJ1p23G4306dPZ8SIEYSHHyrZZDIxduxYJk2aRJs2bWjTpg2TJk0iMjKS6667LoQVl/NZULBO3GoREZF6p058Ai9atIgdO3YwatSoKufuv/9+iouLGT16NNnZ2fTo0YPPP/+cmJiYEFR6mMoLCmpwsoiISEjUibDTr18/DMM44jmTycSECROYMGFCcIuqDmcBUN6yY1HYERERCYU6M2anTir1tOx4FhSsE7lSRESk3lHYCaRKs7EitVWEiIhISCjsBFKlbiyFHRERkdBQ2Amkim4sw0akZmOJiIiEhMJOICV14vf4PmwymqllR0REJEQUdgKp+03Maf0M/3OfqbAjIiISIgo7AVbkLANQN5aIiEiIKOwEWJHDBaBFBUVEREJEYSfACstbdrRdhIiISGgo7ARYkbO8ZUdjdkREREJCYSfAKsKOBiiLiIiEhsJOgB0KO+rGEhERCQWFnQA7NBtLLTsiIiKhoLATYGrZERERCS2FnQArcqhlR0REJJQUdgLIMAyKSstbdrTOjoiISEgo7ARQSakbw/A8VzeWiIhIaCjsBFDF4GQAu0UtOyIiIqGgsBNAFYOTIyxhmMNMIa5GRESkYVLYCaCKrSKi1IUlIiISMgo7AeSddq7BySIiIiGjsBNAFTueR1rUsiMiIhIqCjsB5F09WS07IiIiIaOwE0DaBFRERCT0FHYCSFtFiIiIhJ7CTgBpE1AREZHQU9gJILXsiIiIhJ7CTgAVqmVHREQk5BR2Aqi4vGUnSmFHREQkZBR2AswWHkakTd1YIiIioaJP4QB64rJOPHFZJ4yKrc9FREQk6NSyEwQmkzYBFRERCRWFHREREanXFHZERESkXlPYERERkXpNYUdERETqNYUdERERqdcUdkRERKReU9gRERGRek1hR0REROq1Wh92du3axfXXX0+TJk2IjIzk1FNPZeXKld7zI0eOxGQy+TzOPPPMEFYsIiIitUmt3i4iOzubs88+m759+/Lpp5+SmJjI77//TqNGjXyuGzBgANOnT/e+tlqtQa5UREREaqtaHXaeeeYZWrRo4RNk0tPTq1xns9lITk4OYmUiIiJSV9TqbqyPPvqIbt26ceWVV5KYmMhpp53G66+/XuW6r7/+msTERNq2bcstt9xCVlbWMd/X4XCQl5fn8xAREZH6qVaHnS1btvDKK6/Qpk0bFixYwO23385f/vIX3n77be81AwcO5N133+XLL7/kueeeY8WKFZx33nk4HI6jvu/kyZOJi4vzPlq0aBGMX0dERERCwGQYhhHqIo7GarXSrVs3li1b5j32l7/8hRUrVvDdd98d8Xv27NlDWloas2fPZsiQIUe8xuFw+ISh3NxcWrZsSWZmJrGxsf79JURERBqgImcZ05du8zl2Y690Iq3+G0GTl5dHixYtyMnJIS4u7qjX1eoxOykpKXTo0MHn2Mknn8zcuXOP+T1paWls2rTpqNfYbDZsNpv3dUU3llp4REREAufBAL1vfn5+3Q07Z599Nhs2bPA5tnHjRtLS0o76PQcOHCAzM5OUlJRq/5zU1FQyMzOJiYnBZDIdd72Hq0icajEKDt3v4NG9Dh7d6+DRvQ4ef91rwzDIz88nNTX1mNfV6rDz17/+lZ49ezJp0iSuuuoqli9fzmuvvcZrr70GQEFBARMmTGDo0KGkpKSwbds2HnzwQRISEhg8eHC1f05YWBjNmzcP1K9BbGys/sMJIt3v4NG9Dh7d6+DRvQ4ef9zrY7XoVKjVA5S7d+/O/Pnzee+99+jUqRNPPvkk06ZNY9iwYQCYzWbWrFnDZZddRtu2bRkxYgRt27blu+++IyYmJsTVi4iISG1Qq1t2AC6++GIuvvjiI56z2+0sWLAgyBWJiIhIXVKrW3bqOpvNxmOPPeYzGFoCR/c7eHSvg0f3Onh0r4Mn2Pe6Vk89FxERETlRatkRERGRek1hR0REROo1hR0RERGp1xR2REREpF5T2Amgl19+mYyMDCIiIujatStLliwJdUl13uTJk+nevTsxMTEkJiZy+eWXV1ll2zAMJkyYQGpqKna7nXPPPZdff/01RBXXD5MnT8ZkMjF27FjvMd1n/9q1axfXX389TZo0ITIyklNPPZWVK1d6z+t++0dZWRkPP/wwGRkZ2O12WrVqxRNPPIHb7fZeo3t9fL755hsuueQSUlNTMZlMfPjhhz7nq3NfHQ4Hd999NwkJCURFRXHppZeyc+fOEy/OkICYPXu2YbFYjNdff91Yt26dMWbMGCMqKsrYvn17qEur0/r3729Mnz7dWLt2rbF69Wpj0KBBRsuWLY2CggLvNU8//bQRExNjzJ0711izZo1x9dVXGykpKUZeXl4IK6+7li9fbqSnpxunnHKKMWbMGO9x3Wf/OXjwoJGWlmaMHDnS+OGHH4ytW7caixYtMjZv3uy9RvfbP5566imjSZMmxscff2xs3brV+OCDD4zo6Ghj2rRp3mt0r4/P//73P+Ohhx4y5s6dawDG/Pnzfc5X577efvvtRrNmzYyFCxcaq1atMvr27Wt06dLFKCsrO6HaFHYC5IwzzjBuv/12n2Pt27c3/va3v4WoovopKyvLAIzFixcbhmEYbrfbSE5ONp5++mnvNSUlJUZcXJzx6quvhqrMOis/P99o06aNsXDhQqNPnz7esKP77F8PPPCA0atXr6Oe1/32n0GDBhmjRo3yOTZkyBDj+uuvNwxD99pfDg871bmvOTk5hsViMWbPnu29ZteuXUZYWJjx2WefnVA96sYKAKfTycqVK+nXr5/P8X79+rFs2bIQVVU/5ebmAhAfHw/A1q1b2bt3r8+9t9ls9OnTR/f+ONx5550MGjSICy64wOe47rN/ffTRR3Tr1o0rr7ySxMRETjvtNF5//XXved1v/+nVqxdffPEFGzduBODnn39m6dKlXHTRRYDudaBU576uXLmS0tJSn2tSU1Pp1KnTCd/7Wr9dRF20f/9+XC4XSUlJPseTkpLYu3dviKqqfwzD4J577qFXr1506tQJwHt/j3Tvt2/fHvQa67LZs2ezatUqVqxYUeWc7rN/bdmyhVdeeYV77rmHBx98kOXLl/OXv/wFm83G8OHDdb/96IEHHiA3N5f27dtjNptxuVxMnDiRa6+9FtDf7UCpzn3du3cvVquVxo0bV7nmRD87FXYCyGQy+bw2DKPKMTl+d911F7/88gtLly6tck73/sRkZmYyZswYPv/8cyIiIo56ne6zf7jdbrp168akSZMAOO200/j111955ZVXGD58uPc63e8TN2fOHGbOnMmsWbPo2LEjq1evZuzYsaSmpjJixAjvdbrXgXE899Uf917dWAGQkJCA2WyukkSzsrKqpFo5PnfffTcfffQRX331Fc2bN/ceT05OBtC9P0ErV64kKyuLrl27Eh4eTnh4OIsXL+aFF14gPDzcey91n/0jJSWFDh06+Bw7+eST2bFjB6C/1/5033338be//Y1rrrmGzp07c8MNN/DXv/6VyZMnA7rXgVKd+5qcnIzT6SQ7O/uo1xwvhZ0AsFqtdO3alYULF/ocX7hwIT179gxRVfWDYRjcddddzJs3jy+//JKMjAyf8xkZGSQnJ/vce6fTyeLFi3Xva+D8889nzZo1rF692vvo1q0bw4YNY/Xq1bRq1Ur32Y/OPvvsKksobNy4kbS0NEB/r/2pqKiIsDDfjz6z2eydeq57HRjVua9du3bFYrH4XLNnzx7Wrl174vf+hIY3y1FVTD1/4403jHXr1hljx441oqKijG3btoW6tDrtjjvuMOLi4oyvv/7a2LNnj/dRVFTkvebpp5824uLijHnz5hlr1qwxrr32Wk0b9YPKs7EMQ/fZn5YvX26Eh4cbEydONDZt2mS8++67RmRkpDFz5kzvNbrf/jFixAijWbNm3qnn8+bNMxISEoz777/fe43u9fHJz883fvrpJ+Onn34yAGPq1KnGTz/95F1ypTr39fbbbzeaN29uLFq0yFi1apVx3nnnaep5bfePf/zDSEtLM6xWq3H66ad7p0fL8QOO+Jg+fbr3GrfbbTz22GNGcnKyYbPZjN69extr1qwJXdH1xOFhR/fZv/773/8anTp1Mmw2m9G+fXvjtdde8zmv++0feXl5xpgxY4yWLVsaERERRqtWrYyHHnrIcDgc3mt0r4/PV199dcT/P48YMcIwjOrd1+LiYuOuu+4y4uPjDbvdblx88cXGjh07Trg2k2EYxom1DYmIiIjUXhqzIyIiIvWawo6IiIjUawo7IiIiUq8p7IiIiEi9prAjIiIi9ZrCjoiIiNRrCjsiIiJSrynsiIiISL2msCMigmc35g8//DDUZYhIACjsiEjIjRw5EpPJVOUxYMCAUJcmIvVAeKgLEBEBGDBgANOnT/c5ZrPZQlSNiNQnatkRkVrBZrORnJzs82jcuDHg6WJ65ZVXGDhwIHa7nYyMDD744AOf71+zZg3nnXcedrudJk2acOutt1JQUOBzzZtvvknHjh2x2WykpKRw1113+Zzfv38/gwcPJjIykjZt2vDRRx95z2VnZzNs2DCaNm2K3W6nTZs2VcKZiNROCjsiUic88sgjDB06lJ9//pnrr7+ea6+9lvXr1wNQVFTEgAEDaNy4MStWrOCDDz5g0aJFPmHmlVde4c477+TWW29lzZo1fPTRR7Ru3drnZzz++ONcddVV/PLLL1x00UUMGzaMgwcPen/+unXr+PTTT1m/fj2vvPIKCQkJwbsBInL8TnjfdBGREzRixAjDbDYbUVFRPo8nnnjCMAzDAIzbb7/d53t69Ohh3HHHHYZhGMZrr71mNG7c2CgoKPCe/+STT4ywsDBj7969hmEYRmpqqvHQQw8dtQbAePjhh72vCwoKDJPJZHz66aeGYRjGJZdcYtx4443++YVFJKg0ZkdEaoW+ffvyyiuv+ByLj4/3Pj/rrLN8zp111lmsXr0agPXr19OlSxeioqK8588++2zcbjcbNmzAZDKxe/duzj///GPWcMopp3ifR0VFERMTQ1ZWFgB33HEHQ4cOZdWqVfTr14/LL7+cnj17HtfvKiLBpbAjIrVCVFRUlW6lP2MymQAwDMP7/EjX2O32ar2fxWKp8r1utxuAgQMHsn37dj755BMWLVrE+eefz5133sn//d//1ahmEQk+jdkRkTrh+++/r/K6ffv2AHTo0IHVq1dTWFjoPf/tt98SFhZG27ZtiYmJIT09nS+++OKEamjatCkjR45k5syZTJs2jddee+2E3k9EgkMtOyJSKzgcDvbu3etzLDw83DsI+IMPPqBbt2706tWLd999l+XLl/PGG28AMGzYMB577DFGjBjBhAkT2LdvH3fffTc33HADSUlJAEyYMIHbb7+dxMREBg4cSH5+Pt9++y133313tep79NFH6dq1Kx07dsThcPDxxx9z8skn+/EOiEigKOyISK3w2WefkZKS4nOsXbt2/Pbbb4BnptTs2bMZPXo0ycnJvPvuu3To0AGAyMhIFixYwJgxY+jevTuRkZEMHTqUqVOnet9rxIgRlJSU8PzzzzNu3DgSEhK44oorql2f1Wpl/PjxbNu2DbvdzjnnnMPs2bP98JuLSKCZDMMwQl2EiMixmEwm5s+fz+WXXx7qUkSkDtKYHREREanXFHZERESkXtOYHRGp9dTbLiInQi07IiIiUq8p7IiIiEi9prAjIiIi9ZrCjoiIiNRrCjsiIiJSrynsiIiISL2msCMiIiL1msKOiIiI1Gv/Dw994PLAfCWGAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "input_shape = (1, 28, 28)\n",
    "n_outputs = 10\n",
    "\n",
    "conv_specs = [(40, 4, 1), (10, 3, 2)]\n",
    "fc_specs = [20]\n",
    "\n",
    "#batch_size = -1  # means all training samples used in a single batch\n",
    "batch_size = 5000\n",
    "n_epochs = 100\n",
    "device = 'cuda'\n",
    "\n",
    "nnet = cnn.ConvNet2d(input_shape, conv_specs, fc_specs, n_outputs, \n",
    "                 activation_function='tanh', device=device)\n",
    "\n",
    "nnet.train(Xtrain, Ttrain, Xval, Tval, n_epochs, batch_size, method='adam', \n",
    "           learning_rate=0.001, verbose=True)\n",
    "\n",
    "pc_test = nnet.percent_correct(nnet.use(Xtest), Ttest)\n",
    "print(f'% Correct Test {pc_test:.1f}')\n",
    "\n",
    "plt.plot(nnet.pc_trace)\n",
    "plt.axvline(nnet.best_epoch, lw=3, alpha=0.5)\n",
    "plt.plot(nnet.best_epoch, pc_test, 'ro')\n",
    "plt.xlabel('Epochs')\n",
    "plt.ylabel('Percent Correct')\n",
    "plt.legend(('Train', 'Validation'));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compare compute time for training our ConvNet2D on a GPU versus a CPU."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "banner.next_topic()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compare Times on CPU vs GPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ConvNet: Using device cpu\n",
      "adam Epoch 10 % Correct: Train 89.7 Val 90.8\n",
      "adam Epoch 20 % Correct: Train 94.5 Val 95.1\n",
      "adam Epoch 30 % Correct: Train 96.9 Val 96.9\n",
      "adam Epoch 40 % Correct: Train 97.7 Val 97.5\n",
      "adam Epoch 50 % Correct: Train 98.3 Val 97.8\n",
      "adam Epoch 60 % Correct: Train 98.6 Val 98.1\n",
      "adam Epoch 70 % Correct: Train 98.9 Val 98.2\n",
      "adam Epoch 80 % Correct: Train 99.0 Val 98.0\n",
      "adam Epoch 90 % Correct: Train 99.3 Val 98.3\n",
      "adam Epoch 100 % Correct: Train 99.4 Val 98.3\n",
      "ConvNet: Using device cuda\n",
      "adam Epoch 10 % Correct: Train 90.4 Val 91.4\n",
      "adam Epoch 20 % Correct: Train 94.3 Val 95.0\n",
      "adam Epoch 30 % Correct: Train 96.6 Val 96.8\n",
      "adam Epoch 40 % Correct: Train 97.6 Val 97.5\n",
      "adam Epoch 50 % Correct: Train 98.2 Val 98.0\n",
      "adam Epoch 60 % Correct: Train 98.5 Val 98.0\n",
      "adam Epoch 70 % Correct: Train 98.9 Val 98.2\n",
      "adam Epoch 80 % Correct: Train 99.0 Val 98.3\n",
      "adam Epoch 90 % Correct: Train 99.3 Val 98.4\n",
      "adam Epoch 100 % Correct: Train 99.4 Val 98.5\n",
      "Execution time in minutes: cpu 43.80 gpu 0.97  cpu/gpu 45.33\n"
     ]
    }
   ],
   "source": [
    "n_epochs = 100\n",
    "\n",
    "device = 'cpu'\n",
    "start_time = time.time()\n",
    "nnet = cnn.ConvNet2d(input_shape, conv_specs, fc_specs, n_outputs, \n",
    "                 activation_function='tanh', device=device)\n",
    "nnet.train(Xtrain, Ttrain, Xval, Tval, n_epochs, batch_size, method='adam', \n",
    "           learning_rate=0.001, verbose=True)\n",
    "cpu_elapsed_time = time.time() - start_time\n",
    "\n",
    "\n",
    "device = 'cuda'\n",
    "start_time = time.time()\n",
    "nnet = cnn.ConvNet2d(input_shape, conv_specs, fc_specs, n_outputs, \n",
    "                 activation_function='tanh', device=device)\n",
    "nnet.train(Xtrain, Ttrain, Xval, Tval, n_epochs, batch_size, method='adam', \n",
    "           learning_rate=0.001, verbose=True)\n",
    "gpu_elapsed_time = time.time() - start_time\n",
    "\n",
    "print(f'Execution time in minutes: cpu {cpu_elapsed_time/60:.2f} gpu {gpu_elapsed_time/60:.2f}  cpu/gpu {cpu_elapsed_time / gpu_elapsed_time:.2f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "banner.next_topic()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now let's look at the weights and outputs of convolutional layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'cuda'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nnet.device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(784,)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Xtest[0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = Xtest[0].reshape(1, 28, 28)\n",
    "T = Ttest[0]\n",
    "Zs = nnet.use(X, keep_all_outputs=True)\n",
    "len(Zs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nnet.Zs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ws = list(nnet.parameters())\n",
    "len(Ws)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[torch.Size([40, 1, 4, 4]),\n",
       " torch.Size([40]),\n",
       " torch.Size([10, 40, 3, 3]),\n",
       " torch.Size([10]),\n",
       " torch.Size([20, 1440]),\n",
       " torch.Size([20]),\n",
       " torch.Size([10, 20]),\n",
       " torch.Size([10])]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[W.shape for W in Ws]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-24T16:57:12.014125Z",
     "start_time": "2022-10-24T16:57:11.967785Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(-X.squeeze(), cmap='gray')\n",
    "plt.axis('off');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-24T16:57:13.642270Z",
     "start_time": "2022-10-24T16:57:13.159756Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([40, 1, 4, 4])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "W_layer1 = list(nnet.parameters())[0]\n",
    "W_layer1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nnet.Zs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[torch.Size([1, 1, 28, 28]),\n",
       " torch.Size([1, 40, 25, 25]),\n",
       " torch.Size([1, 1440]),\n",
       " torch.Size([1, 20]),\n",
       " torch.Size([1, 10])]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[Z.shape for Z in nnet.Zs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "n_units_layer_1 = 40"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 40, 25, 25])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z_layer1 = nnet.Zs[1]\n",
    "Z_layer1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([40, 25, 25])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z_layer1 = Z_layer1.reshape(40, 25, 25)\n",
    "Z_layer1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 27.5, 27.5, -0.5)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1, 3, 1)\n",
    "plt.imshow(W_layer1[0, 0, :, :].detach().cpu(), cmap='gray')\n",
    "plt.axis('off')\n",
    "plt.subplot(1, 3, 2)\n",
    "plt.imshow(Z_layer1[0, :, :].detach().cpu(), cmap='gray')\n",
    "plt.axis('off')\n",
    "plt.subplot(1, 3, 3)\n",
    "plt.imshow(X.squeeze(), cmap='gray')\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.randint(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 80 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "W_layer1 = list(nnet.parameters())[0]\n",
    "\n",
    "random_digit = np.random.randint(Xtest.shape[0])\n",
    "X = Xtest[random_digit].reshape(28, 28)    \n",
    "nnet.use(X, keep_all_outputs=True)\n",
    "Z_layer1 = nnet.Zs[1].reshape(40, 25, 25)\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "ploti = 0\n",
    "for unit in range(40):\n",
    "    ploti += 1\n",
    "    plt.subplot(10, 10, ploti)\n",
    "    plt.imshow(W_layer1[unit, 0, :, :].detach().cpu(), cmap='gray')\n",
    "    plt.axis('off')\n",
    "    ploti += 1\n",
    "    plt.subplot(10, 10, ploti)\n",
    "    plt.imshow(Z_layer1[unit, :, :].detach().cpu(), cmap='gray')\n",
    "    plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ConvNet2d(\n",
       "  (activation_function): Tanh()\n",
       "  (conv_layers): Sequential(\n",
       "    (0): Sequential(\n",
       "      (0): Conv2d(1, 40, kernel_size=(4, 4), stride=(1, 1))\n",
       "      (1): Tanh()\n",
       "    )\n",
       "    (1): Sequential(\n",
       "      (0): Conv2d(40, 10, kernel_size=(3, 3), stride=(2, 2))\n",
       "      (1): Tanh()\n",
       "    )\n",
       "  )\n",
       "  (fc_layers): Sequential(\n",
       "    (0): Sequential(\n",
       "      (0): Linear(in_features=1440, out_features=20, bias=True)\n",
       "      (1): Tanh()\n",
       "    )\n",
       "    (1): Linear(in_features=20, out_features=10, bias=True)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nnet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[torch.Size([1, 1, 28, 28]),\n",
       " torch.Size([1, 40, 25, 25]),\n",
       " torch.Size([1, 1440]),\n",
       " torch.Size([1, 20]),\n",
       " torch.Size([1, 10])]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[Z.shape for Z in nnet.Zs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "n_units_layer_2 = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "144.0"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1440 / n_units_layer_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(144)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "W_layer2 = list(nnet.parameters())[2]  # skip bias weight in layer 1\n",
    "\n",
    "random_digit = np.random.randint(Xtest.shape[0])\n",
    "X = Xtest[random_digit].reshape(28, 28)    \n",
    "nnet.use(X, keep_all_outputs=True)\n",
    "Z_layer2 = nnet.Zs[2].reshape(n_units_layer_2, 12, 12)\n",
    "n_units = Z_layer2.shape[0]\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "ploti = 0\n",
    "for unit in range(10):\n",
    "    ploti += 1\n",
    "    plt.subplot(4, 6, ploti)\n",
    "    plt.imshow(W_layer2[unit, 0, :, :].detach().cpu(), cmap='gray')\n",
    "    plt.axis('off')\n",
    "    ploti += 1\n",
    "    plt.subplot(4, 6, ploti)\n",
    "    plt.imshow(Z_layer2[unit, :, :].detach().cpu(), cmap='gray')\n",
    "    plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-24T16:57:17.194217Z",
     "start_time": "2022-10-24T16:57:16.256760Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x1000 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "first = np.random.randint(10000 - 20)\n",
    "\n",
    "Xs = Xtest[first:first + 20].reshape(-1, 1, 28, 28)\n",
    "classes, probs = nnet.use(Xs, return_probs=True)\n",
    "\n",
    "plt.figure(figsize=(8, 10))\n",
    "ploti = 0\n",
    "for i in range(10):\n",
    "    ploti += 1\n",
    "    plt.subplot(10, 2, ploti)\n",
    "    plt.imshow(-Xs[i, 0, :, :], cmap='gray')\n",
    "    plt.axis('off')\n",
    "    ploti += 1\n",
    "    plt.subplot(10, 2, ploti)\n",
    "    Yprobs = probs[i, :]\n",
    "    plt.plot(Yprobs, 'o-')\n",
    "    plt.ylim(0, 1)\n",
    "    plt.xticks(range(10))\n",
    "    plt.ylabel('probs')\n",
    "    if i == 9:\n",
    "        plt.xlabel('digits')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.2"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}