colab-notebooks/12_InitializationActivationFunction.ipynb

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            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "071a4d9d6eec405ea791b8b52fd4984d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "fc71630fafb447dca64ec78854bc7249": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
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            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
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            "grid_auto_columns": null,
            "margin": null,
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            "left": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/satyajitghana/PadhAI-Course/blob/master/12_InitializationActivationFunction.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DWAFa7iTGYaY",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.colors\n",
        "import pandas as pd\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score, mean_squared_error, log_loss\n",
        "from tqdm import tqdm_notebook \n",
        "import seaborn as sns\n",
        "import imageio\n",
        "import time\n",
        "from IPython.display import HTML\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "sns.set()\n",
        "\n",
        "from sklearn.preprocessing import OneHotEncoder\n",
        "from sklearn.datasets import make_blobs"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7byiI1taGhoJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "my_cmap = 'inferno'"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qiUvSiAQGkKt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "np.random.seed(0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "1Yum3QoCRDku"
      },
      "source": [
        "## Generate data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D9ae2UDKGrXl",
        "colab_type": "code",
        "outputId": "2a45d6d0-2d5f-4b4a-8a2d-ce04cff13cd4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "data, labels = make_blobs(n_samples=1000, centers=4, n_features=2, random_state=0)\n",
        "print(data.shape, labels.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(1000, 2) (1000,)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "teNFIujUGrxb",
        "colab_type": "code",
        "outputId": "7f7aaaa6-24da-433b-8604-33975bd4e9c8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        }
      },
      "source": [
        "plt.scatter(data[:,0], data[:,1], c=labels, cmap=my_cmap)\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SyxxMNnMY0djywttG5Zjxuje8z044gEoktpxk6ylBSn7AAUMg2Gtg2/UglQozheuq3r4+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\nZDJHfX0EVfV/2LW3Zzllyg0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cf/33uPjifys75777/sbkyZMxDINYLEZDQ4Ov/Rpg6FD/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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "51Kko6X2Gs3o",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "labels_orig = labels\n",
        "labels = np.mod(labels_orig, 2)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "rLpsoFqkPWCA"
      },
      "source": [
        "## Multi class classification"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WXfuN8HyGxwd",
        "colab_type": "code",
        "outputId": "8348923b-e226-48c8-feb7-2c79f5b2446e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "X_train, X_val, Y_train, Y_val = train_test_split(data, labels_orig, stratify=labels_orig, random_state=0)\n",
        "print(X_train.shape, X_val.shape, labels_orig.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(750, 2) (250, 2) (1000,)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s0x3Va-4GyHe",
        "colab_type": "code",
        "outputId": "35748a86-7af9-4f41-afea-54b80f535c49",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "enc = OneHotEncoder()\n",
        "# 0 -> (1, 0, 0, 0), 1 -> (0, 1, 0, 0), 2 -> (0, 0, 1, 0), 3 -> (0, 0, 0, 1)\n",
        "y_OH_train = enc.fit_transform(np.expand_dims(Y_train,1)).toarray()\n",
        "y_OH_val = enc.fit_transform(np.expand_dims(Y_val,1)).toarray()\n",
        "print(y_OH_train.shape, y_OH_val.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(750, 4) (250, 4)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "3e_XHuXLuiIr"
      },
      "source": [
        "## FF Class"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YizBY3SfGzHG",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class FFNetwork:\n",
        "  \n",
        "  def __init__(self, init_method = 'random', activation_function = 'sigmoid', leaky_slope = 0.1):\n",
        "        \n",
        "    self.params={}\n",
        "    self.params_h = []\n",
        "    self.num_layers=2\n",
        "    self.layer_sizes = [2, 2, 4]\n",
        "    self.activation_function = activation_function\n",
        "    self.leaky_slope = leaky_slope\n",
        "    \n",
        "    np.random.seed(0)\n",
        "    \n",
        "    if init_method == \"random\":\n",
        "      for i in range(1,self.num_layers+1):\n",
        "        self.params[\"W\"+str(i)] = np.random.randn(self.layer_sizes[i-1],self.layer_sizes[i])\n",
        "        self.params[\"B\"+str(i)] = np.random.randn(1,self.layer_sizes[i])\n",
        "        \n",
        "    elif init_method == \"he\":\n",
        "      for i in range(1,self.num_layers+1):\n",
        "        self.params[\"W\"+str(i)] = np.random.randn(self.layer_sizes[i-1],self.layer_sizes[i])*np.sqrt(2/self.layer_sizes[i-1])\n",
        "        self.params[\"B\"+str(i)] = np.random.randn(1,self.layer_sizes[i])\n",
        "        \n",
        "    elif init_method == \"xavier\":\n",
        "      for i in range(1,self.num_layers+1):\n",
        "        self.params[\"W\"+str(i)]=np.random.randn(self.layer_sizes[i-1],self.layer_sizes[i])*np.sqrt(1/self.layer_sizes[i-1])\n",
        "        self.params[\"B\"+str(i)]=np.random.randn(1,self.layer_sizes[i])\n",
        "        \n",
        "    elif init_method == \"zeros\":\n",
        "      for i in range(1,self.num_layers+1):\n",
        "        self.params[\"W\"+str(i)]=np.zeros((self.layer_sizes[i-1],self.layer_sizes[i]))\n",
        "        self.params[\"B\"+str(i)]=np.zeros((1,self.layer_sizes[i]))\n",
        "    \n",
        "    self.gradients={}\n",
        "    self.update_params={}\n",
        "    self.prev_update_params={}\n",
        "    for i in range(1,self.num_layers+1):\n",
        "      self.update_params[\"v_w\"+str(i)]=0\n",
        "      self.update_params[\"v_b\"+str(i)]=0\n",
        "      self.update_params[\"m_b\"+str(i)]=0\n",
        "      self.update_params[\"m_w\"+str(i)]=0\n",
        "      self.prev_update_params[\"v_w\"+str(i)]=0\n",
        "      self.prev_update_params[\"v_b\"+str(i)]=0\n",
        "  \n",
        "  def forward_activation(self, X): \n",
        "    if self.activation_function == \"sigmoid\":\n",
        "      return 1.0/(1.0 + np.exp(-X))\n",
        "    elif self.activation_function == \"tanh\":\n",
        "      return np.tanh(X)\n",
        "    elif self.activation_function == \"relu\":\n",
        "      return np.maximum(0,X)\n",
        "    elif self.activation_function == \"leaky_relu\":\n",
        "      return np.maximum(self.leaky_slope*X,X)\n",
        "      \n",
        "  def grad_activation(self, X):\n",
        "    if self.activation_function == \"sigmoid\":\n",
        "      return X*(1-X) \n",
        "    elif self.activation_function == \"tanh\":\n",
        "      return (1-np.square(X))\n",
        "    elif self.activation_function == \"relu\":\n",
        "      return 1.0*(X>0)\n",
        "    elif self.activation_function == \"leaky_relu\":\n",
        "      d=np.zeros_like(X)\n",
        "      d[X<=0]=self.leaky_slope\n",
        "      d[X>0]=1\n",
        "      return d\n",
        "\n",
        "  def softmax(self, X):\n",
        "    exps = np.exp(X)\n",
        "    return exps / np.sum(exps, axis=1).reshape(-1,1)\n",
        "  \n",
        "  def forward_pass(self, X, params = None):\n",
        "    if params is None:\n",
        "        params = self.params\n",
        "    self.A1 = np.matmul(X, params[\"W1\"]) + params[\"B1\"] # (N, 2) * (2, 2) -> (N, 2)\n",
        "    self.H1 = self.forward_activation(self.A1) # (N, 2)\n",
        "    self.A2 = np.matmul(self.H1, params[\"W2\"]) + params[\"B2\"] # (N, 2) * (2, 4) -> (N, 4)\n",
        "    self.H2 = self.softmax(self.A2) # (N, 4)\n",
        "    return self.H2\n",
        "  \n",
        "  def grad(self, X, Y, params = None):\n",
        "    if params is None:\n",
        "      params = self.params \n",
        "      \n",
        "    self.forward_pass(X, params)\n",
        "    m = X.shape[0]\n",
        "    self.gradients[\"dA2\"] = self.H2 - Y # (N, 4) - (N, 4) -> (N, 4)\n",
        "    self.gradients[\"dW2\"] = np.matmul(self.H1.T, self.gradients[\"dA2\"]) # (2, N) * (N, 4) -> (2, 4)\n",
        "    self.gradients[\"dB2\"] = np.sum(self.gradients[\"dA2\"], axis=0).reshape(1, -1) # (N, 4) -> (1, 4)\n",
        "    self.gradients[\"dH1\"] = np.matmul(self.gradients[\"dA2\"], params[\"W2\"].T) # (N, 4) * (4, 2) -> (N, 2)\n",
        "    self.gradients[\"dA1\"] = np.multiply(self.gradients[\"dH1\"], self.grad_activation(self.H1)) # (N, 2) .* (N, 2) -> (N, 2)\n",
        "    self.gradients[\"dW1\"] = np.matmul(X.T, self.gradients[\"dA1\"]) # (2, N) * (N, 2) -> (2, 2)\n",
        "    self.gradients[\"dB1\"] = np.sum(self.gradients[\"dA1\"], axis=0).reshape(1, -1) # (N, 2) -> (1, 2)\n",
        "    \n",
        "  def fit(self, X, Y, epochs=1, algo= \"GD\", display_loss=False, \n",
        "          eta=1, mini_batch_size=100, eps=1e-8,  \n",
        "          beta=0.9, beta1=0.9, beta2=0.9, gamma=0.9 ):\n",
        "      \n",
        "    if display_loss:\n",
        "      loss = {}\n",
        "      Y_pred = self.predict(X)\n",
        "      loss[0] = log_loss(np.argmax(Y, axis=1), Y_pred)\n",
        "\n",
        "    for num_epoch in tqdm_notebook(range(epochs), total=epochs, unit=\"epoch\"):\n",
        "      m = X.shape[0]\n",
        "      \n",
        "      if algo == \"GD\":\n",
        "        self.grad(X, Y)\n",
        "        for i in range(1,self.num_layers+1):\n",
        "          self.params[\"W\"+str(i)] -= eta * (self.gradients[\"dW\"+str(i)]/m)\n",
        "          self.params[\"B\"+str(i)] -= eta * (self.gradients[\"dB\"+str(i)]/m)\n",
        "          \n",
        "      elif algo == \"MiniBatch\":\n",
        "        for k in range(0,m,mini_batch_size):\n",
        "          self.grad(X[k:k+mini_batch_size], Y[k:k+mini_batch_size])\n",
        "          for i in range(1,self.num_layers+1):\n",
        "            self.params[\"W\"+str(i)] -= eta * (self.gradients[\"dW\"+str(i)]/mini_batch_size)\n",
        "            self.params[\"B\"+str(i)] -= eta * (self.gradients[\"dB\"+str(i)]/mini_batch_size)\n",
        "            \n",
        "      elif algo == \"Momentum\":\n",
        "        self.grad(X, Y)\n",
        "        for i in range(1,self.num_layers+1):\n",
        "          self.update_params[\"v_w\"+str(i)] = gamma *self.update_params[\"v_w\"+str(i)] + eta * (self.gradients[\"dW\"+str(i)]/m)\n",
        "          self.update_params[\"v_b\"+str(i)] = gamma *self.update_params[\"v_b\"+str(i)] + eta * (self.gradients[\"dB\"+str(i)]/m)\n",
        "          self.params[\"W\"+str(i)] -= self.update_params[\"v_w\"+str(i)]\n",
        "          self.params[\"B\"+str(i)] -= self.update_params[\"v_b\"+str(i)]  \n",
        "          \n",
        "      elif algo == \"NAG\":\n",
        "        temp_params = {}\n",
        "        for i in range(1,self.num_layers+1):\n",
        "          self.update_params[\"v_w\"+str(i)]=gamma*self.prev_update_params[\"v_w\"+str(i)]\n",
        "          self.update_params[\"v_b\"+str(i)]=gamma*self.prev_update_params[\"v_b\"+str(i)]\n",
        "          temp_params[\"W\"+str(i)]=self.params[\"W\"+str(i)]-self.update_params[\"v_w\"+str(i)]\n",
        "          temp_params[\"B\"+str(i)]=self.params[\"B\"+str(i)]-self.update_params[\"v_b\"+str(i)]\n",
        "        self.grad(X,Y,temp_params)\n",
        "        for i in range(1,self.num_layers+1):\n",
        "          self.update_params[\"v_w\"+str(i)] = gamma *self.update_params[\"v_w\"+str(i)] + eta * (self.gradients[\"dW\"+str(i)]/m)\n",
        "          self.update_params[\"v_b\"+str(i)] = gamma *self.update_params[\"v_b\"+str(i)] + eta * (self.gradients[\"dB\"+str(i)]/m)\n",
        "          self.params[\"W\"+str(i)] -= eta * (self.update_params[\"v_w\"+str(i)])\n",
        "          self.params[\"B\"+str(i)] -= eta * (self.update_params[\"v_b\"+str(i)]) \n",
        "        self.prev_update_params=self.update_params \n",
        "        \n",
        "      elif algo == \"AdaGrad\":\n",
        "        self.grad(X, Y)\n",
        "        for i in range(1,self.num_layers+1):\n",
        "          self.update_params[\"v_w\"+str(i)] += (self.gradients[\"dW\"+str(i)]/m)**2\n",
        "          self.update_params[\"v_b\"+str(i)] += (self.gradients[\"dB\"+str(i)]/m)**2\n",
        "          self.params[\"W\"+str(i)] -= (eta/(np.sqrt(self.update_params[\"v_w\"+str(i)])+eps)) * (self.gradients[\"dW\"+str(i)]/m)\n",
        "          self.params[\"B\"+str(i)] -= (eta/(np.sqrt(self.update_params[\"v_b\"+str(i)])+eps)) * (self.gradients[\"dB\"+str(i)]/m)\n",
        "      \n",
        "      elif algo == \"RMSProp\":\n",
        "        self.grad(X, Y)\n",
        "        for i in range(1,self.num_layers+1):\n",
        "          self.update_params[\"v_w\"+str(i)] = beta*self.update_params[\"v_w\"+str(i)] +(1-beta)*((self.gradients[\"dW\"+str(i)]/m)**2)\n",
        "          self.update_params[\"v_b\"+str(i)] = beta*self.update_params[\"v_b\"+str(i)] +(1-beta)*((self.gradients[\"dB\"+str(i)]/m)**2)\n",
        "          self.params[\"W\"+str(i)] -= (eta/(np.sqrt(self.update_params[\"v_w\"+str(i)]+eps)))*(self.gradients[\"dW\"+str(i)]/m)\n",
        "          self.params[\"B\"+str(i)] -= (eta/(np.sqrt(self.update_params[\"v_b\"+str(i)]+eps)))*(self.gradients[\"dB\"+str(i)]/m)\n",
        "      \n",
        "      elif algo == \"Adam\":\n",
        "        self.grad(X, Y)\n",
        "        num_updates=0\n",
        "        for i in range(1,self.num_layers+1):\n",
        "          num_updates+=1\n",
        "          self.update_params[\"m_w\"+str(i)]=beta1*self.update_params[\"m_w\"+str(i)]+(1-beta1)*(self.gradients[\"dW\"+str(i)]/m)\n",
        "          self.update_params[\"v_w\"+str(i)]=beta2*self.update_params[\"v_w\"+str(i)]+(1-beta2)*((self.gradients[\"dW\"+str(i)]/m)**2)\n",
        "          m_w_hat=self.update_params[\"m_w\"+str(i)]/(1-np.power(beta1,num_updates))\n",
        "          v_w_hat=self.update_params[\"v_w\"+str(i)]/(1-np.power(beta2,num_updates))\n",
        "          self.params[\"W\"+str(i)] -=(eta/np.sqrt(v_w_hat+eps))*m_w_hat\n",
        "          \n",
        "          self.update_params[\"m_b\"+str(i)]=beta1*self.update_params[\"m_b\"+str(i)]+(1-beta1)*(self.gradients[\"dB\"+str(i)]/m)\n",
        "          self.update_params[\"v_b\"+str(i)]=beta2*self.update_params[\"v_b\"+str(i)]+(1-beta2)*((self.gradients[\"dB\"+str(i)]/m)**2)\n",
        "          m_b_hat=self.update_params[\"m_b\"+str(i)]/(1-np.power(beta1,num_updates))\n",
        "          v_b_hat=self.update_params[\"v_b\"+str(i)]/(1-np.power(beta2,num_updates))\n",
        "          self.params[\"B\"+str(i)] -=(eta/np.sqrt(v_b_hat+eps))*m_b_hat\n",
        "          \n",
        "      if display_loss:\n",
        "        Y_pred = self.predict(X)\n",
        "        loss[num_epoch+1] = log_loss(np.argmax(Y, axis=1), Y_pred)\n",
        "        self.params_h.append(np.concatenate((self.params['W1'].ravel(), self.params['W2'].ravel(), self.params['B1'].ravel(), self.params['B2'].ravel())))\n",
        "    \n",
        "    if display_loss:\n",
        "      plt.plot(list(loss.values()), '-o', markersize=5)\n",
        "      plt.xlabel('Epochs')\n",
        "      plt.ylabel('Log Loss')\n",
        "      plt.show()\n",
        "      \n",
        "  \n",
        "  def predict(self, X):\n",
        "    Y_pred = self.forward_pass(X)\n",
        "    return np.array(Y_pred).squeeze()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9bir1hpUG8bM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def post_process(scatter_plot=False, gradient_plot=True, plot_scale=0.1):    \n",
        "    Y_pred_train = model.predict(X_train)\n",
        "    Y_pred_train = np.argmax(Y_pred_train,1)\n",
        "    Y_pred_val = model.predict(X_val)\n",
        "    Y_pred_val = np.argmax(Y_pred_val,1)\n",
        "    accuracy_train = accuracy_score(Y_pred_train, Y_train)\n",
        "    accuracy_val = accuracy_score(Y_pred_val, Y_val)\n",
        "    print(\"Training accuracy\", round(accuracy_train, 4))\n",
        "    print(\"Validation accuracy\", round(accuracy_val, 4))    \n",
        "    \n",
        "    if scatter_plot:\n",
        "      plt.scatter(X_train[:,0], X_train[:,1], c=Y_pred_train, cmap=my_cmap, s=15*(np.abs(np.sign(Y_pred_train-Y_train))+.1))\n",
        "      plt.show()\n",
        "      \n",
        "    if gradient_plot:\n",
        "      h = np.asarray(model.params_h)\n",
        "      h_diff = (h[0:-1, :] - h[1:, :])\n",
        "      for i in range(18):\n",
        "        plt.subplot(6, 3, i+1)\n",
        "        plt.plot(h_diff[:, i], '-')\n",
        "        plt.ylim((-plot_scale, plot_scale))\n",
        "        plt.yticks([])\n",
        "        plt.xticks([])\n",
        "      plt.show()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d7cYxAgQG-Bq",
        "colab_type": "code",
        "outputId": "604c179c-01a7-45f0-d396-81653e1a3e8d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 603,
          "referenced_widgets": [
            "203d866641ec42c0bf64dd402a6c762b",
            "e51f2aff89aa4fdb8903bb702f17f615",
            "b3f3591e72ee45298fc026d289835589",
            "19527cf51ded48acad3c7c706c93d9e4",
            "4f783b3e4fd945a789e69f3deb8e5094",
            "55ffec7f5f3840018dde869ed695904f",
            "e91b35d4dd504c57a5b543297494b131",
            "9479a4361ec940c19ee93fb6ecfed17a"
          ]
        }
      },
      "source": [
        "model = FFNetwork(init_method='xavier', activation_function='sigmoid')\n",
        "model.fit(X_train, y_OH_train, epochs=10, eta=1, algo=\"GD\", display_loss=True)\n",
        "post_process()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "203d866641ec42c0bf64dd402a6c762b",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=10), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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mwp5DjvXPFHIRydowpOrCkaYPR6o+HJqIIWzKE3kRA4R8wsi0aKTpL11GZepN\nKc4eiN1uR3PrOVTUt6G8rg3l9W3YeaAWW79zbISlClYgTR+ONJ0jUFJ14X6zzAqRL2KAkE+4eBmV\nGmM7Ei8zC0sQBGgig6GJDMY4gxYA0G21obapwxkqFfVtOFRmwvnHRWPVwY4RSs9IJSlWBYW89xPy\nNpsdB8tNMB2oQ/RFy7cQUd8YIOQzzi+jkjU0xuX3yGUikuPCkBwXhttGO5b7P9vZjcqGdpTXtaKi\nvh1Hq1qw94gRACATBSRpVUjVOUIlJS4M7287fsnIh7O/iK6OAUJ+JzhIDkOyGoZktfNYS3tnz22v\nVlTUtWHP4QZs/6H2kvd2Wqwoq23FwbJmZA3TeLNsokGHAUIBQR0WhLHpGoxNd4SCzWZHvakDG78s\nx/7jzb3O7eq2Yc3HRzA0PsIxutGGISUuDBp1MEQ26YmcGCAUkERRQLxGhUmj9CiubOk1+0suE5Ce\nGAnzWQu2fVeDbqujozJEKUOS9kKgJMWFQRcVwltdFLAYIBTQrjT7a/GMURBFAd1WG+qaO1DV0I4q\nYzuqGtrxxYFabO22AXBMNU6MVSFZG+Ycrehj+IwKBQYGCAW0vjbRAhxN+iRtGJK0YZjU8x6rzYYG\n05meQDGjqqF3T0UuE5GgCXU295O1YUjQhF5x9hfX/qLBigFCAe9qm2j9lEwUEa9RIV6jwk03OI7Z\n7HY0tpztNVL5tqQRXxyo63mPAH1MqHOkkhirwj92laOyvp2zv2jQYoAQDQBREBAXFYK4qBCMH+F4\nRuX8g48Xh8qBE83Yfaj+kvd3Wqw4UduKb482Ot9P5OsYIEQecvGDj9kZsQAcodLS3okNO09gX3Fj\nr/Mt3Tb88Z9H8I9d5T3NehWS4xy3z8JDlFJcAlGfGCBEXiQIAqLCh2D8iDgcOG7qNftLIRORnaFB\nV7cNlfVt+O7ohYBRhwX1atQnaVVQhwVx7S+SFAOESAJXmv31yF0jnD2QjnMWVBvNqGpoR7XRcRvs\nxxPNzmVawkIUzlA5P2LRRAYzVMhrGCBEEnBl7a/QIYpLnqg/19WNk40djp6KsR3VDe34175qWG2O\nWAkOkiMpVnVhpHKFZ1W4/hcNBAYIkUTcWftriFKOoQkRGJoQ4Txm6bahttnsHK1UGduxY38tLOef\nVZE7nlVJ6gmVRI0KG3aeQAVngNE1YoAQDXIKuYiUuHCkxIUDoxzHLnlWxdiOrw83YMcV1v86UduK\n74814mcZnAFGrmOAEPmhKz2r0nT6LDZ+UYZvjzb1Ot/SbcOaTUewMaoCyVpVz8OTKs4Aoz4xQIgC\nhCgI0KpDMOEGHQ6WnbpkBni2VXsAAA7xSURBVNjYdE3PasRt+Kak9wywpFiV84n8ZK0K0dz9kcAA\nIQo4V5oB9ujUCzPAzGctqDG2o8poRnVjO6qNZhwsN8HeMwUsdIjc0VfRXphWHBcdApnINcACCQOE\nKMBcbf0vwLE9sCElCoaUKOexTosVJ5sczfpqo2Nq8cXNeoVcRIJGddEtMMcaYErFhTXAuP6Xf/Fa\ngBQUFOCzzz5DbW0tPvnkEwwfPvySc/7+97/j3XffhSiKsNlsmDFjBubMmQMAWL16Nd5//33Exjqe\n6B0zZgyWLVvmrfKJ/Ep/1/8CgCCFDNfpI3Cd/sIMMKvNhnrTmZ5AcQTLNyWN2NmzBpgoCNBFhyBJ\nq0JCrAr7io0wnjqDLouNs7/8gNcCJDc3F3PmzMGsWbOueM6dd96Je+65B4IgwGw2Y9q0aRg3bhwy\nMjIAAPn5+ViyZIm3Siaiq5CJjlFHwkXN+vNrgF08UjlafRpf92wrfF6nxYpjNafxj13luHWUnn2V\nQchrAZKdnX3Vc1QqlfPX586dg8Vi4V8ookHm4jXAzu8ACQAbdpzAp/uqe51rtdlR+HUVCr+uQnBQ\nT18lVuXsr+hjQqGQs6/iq3yuB/L5559j5cqVqK6uxjPPPIP09HTna4WFhdi9ezc0Gg0WLFiA0aNH\nS1gpEfXHsMRIbP+httfsryCFiOmTUjFEKUdNT8N+18F65zky0XELLDFWhcTYMCRqHQETxqnFPkGw\n28/Pq/COnJwcrF279rI9kIvV1dXhySefxIoVK5CWloampiZERkZCoVBgz549ePbZZ7Flyxao1eo+\nfw4R+QarzY5l675CaVULOrusCFLKkJ6sxsvzb4Lsoh6IzWZHg6kD5XWtqKhrQ3ltKyrqWmFqPec8\nJzpiCFL1EUjVhyMtPgJp+gjERYeyl+JlPjcCOU+v1yMzMxM7d+5EWloaNJoLQ+GJEydCp9Ph+PHj\nGDdunMs/02Qyw2brf172p9HoL3jNgcHb17zgF5mXrP91ymS+5DwFgHR9ONL14UB2AgCg/UwXahod\ns8BqGs2oaWzH/tJG5zpgQQoZEmJDkRTr2LArUevozQT1zAJzrv9l7gq49b/c/XMWRQHR0aorvu5T\nAVJWVobrrrsOAHDq1Cns27cPd9xxBwDAaDRCq3Uss1BSUoLa2lqkpqZKVisR9Z8763+dFxaixIiU\nKIy4aGqxpduxZ311YztqeoJlb7ERO/Y7lmwRBECrDkFibCgqG9pxur0L3VYblAoRafoIzgC7Rl4L\nkOXLl6OoqAjNzc2YO3cuIiMjUVhYiHnz5mHhwoXIzMzEhx9+iD179kAul8Nut2P27Nm4+eabAQAr\nV67EkSNHIIoiFAoFXn/99V6jEiIKPAq56Nx7/jy73Q5T6znHaKXRMROstPo02s5YnOd0Wmw4Wt2C\nNzYewujhMUiKDYM+JuSSfeupb17vgUiJt7Bcx2sODIFyzf/cU4FNuyouOS4TBectMFEQoI0KRmKs\n49ZXYs9sMH/YuCsgbmEREXlCkjYMQQrZT2aAyTB/2gjoY0J7eipmnGwyo7yu91pgIUFyJMReCJQE\njQrxMaEIUnK0wgAhIr93pfW/Rg2NgSgK0EaFOPetB4Cznd042WTGyUYzapo6cLLRjN2H6tHZ5Qgg\nAUBsVAgSNaGOcNE4nrSPuczDkP68fAsDhIj8nivrf10sOEiOYQmRGJYQ6Txm63nC/mRjT7D09Fi+\nL21ybjM8RCnrFSjxMaH4x5flqGzwz827GCBEFBDcWf+r1/sFAbGRwYiNDMaY4Rcm8Jzr6kZtc4fj\nFljPf3uLjTi7/wqbd508jS8O1OLWrPhBHyIMECKiazBEKb9kkUm73Q5T2zls/KIce4t7rwFmsdrx\np6Jj+Ov2E9DHhCJBE+pcTywhVoWI0MHzlD0DhIhogAmCgJiIYIwbocX+4829mvdKuYhbs/QQBAG1\nTWYcLj+FPYcanK+HhSguBEpPj0UfE+p8INKXMECIiDzkSs37mTnDet2+ajvThdpGM042daCmyYza\nJjO++LEWXRbHXisCgFh1sGMGmCbUORtMExnc520w59P3B+o88vQ9A4SIyEMubt5fvHzLT7/Ew0OU\nCP/JBl42mx1NrWcdfZWmDuessB+OXWjaK+Ui4jWhiO8ZsSRqQhEfq0J4iBI2mx0rPjxwSXgNZAOf\nAUJE5EHuLt8iio497LXqEIy9sCg5Oi1W1DV39AqWH080Y/fBeuc54aFKRIYqUNt8xvmgZKfFivK6\nNhwsN7m1lMzlMECIiAaRIIUMqbpwpOrCex1v7ejCySYzahvNqGky43DFKWd4nNdlsaLG2M4AISKi\nCyJClYgIjcL1PbfBDpxoxh8/PozOnj4KACgVMiRqw670I/qNW30REfkhRwM/AkEKGQQ4Ri5p+nCM\nTIsesM/gCISIyA/19+l7dzBAiIj81LU+fX/Vnz/gP5GIiAICA4SIiNzCACEiIrcwQIiIyC0B1US/\nltkHg33ZZXfwmgMDrzkwuHPNV3tPQO2JTkREA4e3sIiIyC0MECIicgsDhIiI3MIAISIitzBAiIjI\nLQwQIiJyCwOEiIjcwgAhIiK3MECIiMgtDJCrqKiowMyZM3HnnXdi5syZqKyslLokj2ppacG8efNw\n5513Ytq0aXjqqadw6tQpqcvyijfeeAPp6ek4duyY1KV4XGdnJ5YtW4Y77rgD06ZNw4svvih1SR63\nY8cO5OfnY/r06bj77rtRVFQkdUkDrqCgADk5OZf8PfbY95id+vTggw/aN23aZLfb7fZNmzbZH3zw\nQYkr8qyWlhb73r17nb//7W9/a/+P//gPCSvyjsOHD9sfeeQR++23324vLS2VuhyPe/XVV+3//d//\nbbfZbHa73W5vamqSuCLPstls9uzsbOefbUlJiT0rK8tutVolrmxgffvtt/a6urpL/h576nuMI5A+\nmEwmFBcXY+rUqQCAqVOnori42K//RR4ZGYnx48c7f5+VlYW6ujoJK/K8rq4uvPLKK3jppZekLsUr\nOjo6sGnTJixatAiC4FgsLyYmRuKqPE8URbS3O3bla29vR2xsLETRv74Cs7OzodPpeh3z5PdYQK3G\n21/19fXQarWQyWQAAJlMhtjYWNTX1yMqKkri6jzPZrPhgw8+QE5OjtSleNSqVatw9913IyEhQepS\nvKKmpgaRkZF44403sG/fPoSGhmLRokXIzs6WujSPEQQBv//97/HEE08gJCQEHR0dWLdundRleYUn\nv8f8K35pQL366qsICQnB7NmzpS7FY/bv34/Dhw/jl7/8pdSleI3VakVNTQ1GjBiBjRs34tlnn8WC\nBQtgNpulLs1juru78cc//hFvvfUWduzYgTVr1mDx4sXo6OiQurRBjQHSB51OB6PRCKvVCsDxP15j\nY+MlQ0R/VFBQgKqqKvz+97/3u2H+xb799luUlZUhNzcXOTk5aGhowCOPPILdu3dLXZrH6HQ6yOVy\n5y2NUaNGQa1Wo6KiQuLKPKekpASNjY0YO3YsAGDs2LEIDg5GWVmZxJV5nie/x/z3m2EAREdHw2Aw\nYPPmzQCAzZs3w2Aw+P3tq5UrV+Lw4cN48803oVQqpS7Ho+bPn4/du3dj+/bt2L59O+Li4vDOO+/g\n5ptvlro0j4mKisL48eOxZ88eAI4ZOiaTCcnJyRJX5jlxcXFoaGhAeXk5AKCsrAwmkwlJSUkSV+Z5\nnvwe44ZSV1FWVoalS5eira0N4eHhKCgoQFpamtRleczx48cxdepUpKSkYMiQIQCAhIQEvPnmmxJX\n5h05OTlYu3Ythg8fLnUpHlVTU4P//M//xOnTpyGXy7F48WLceuutUpflUf/85z/x9ttvOycOLFy4\nEJMnT5a4qoG1fPlyFBUVobm5GWq1GpGRkSgsLPTY9xgDhIiI3MJbWERE5BYGCBERuYUBQkREbmGA\nEBGRWxggRETkFgYIkY9LT09HVVWV1GUQXYJrYRH1U05ODpqbm51rCwHAL37xC/zXf/2XhFUReR8D\nhMgNa9euxU033SR1GUSS4i0sogGyceNG3H///XjllVcwduxY5OXl4euvv3a+bjQa8dhjj2HcuHGY\nMmUK/va3vzlfs1qtWLt2LSZPnozRo0fjnnvuQX19vfP1r776CnfccQeys7Px8ssv4/zzv1VVVZg9\nezbGjh2L8ePHY/Hixd67YAp4HIEQDaCDBw8iLy8Pe/fuxdatW/HUU0/h888/R2RkJJ5++mkMGzYM\nu3btQnl5OebOnYvExERMmDAB69evR2FhIdatW4fU1FSUlpY6l5IBgJ07d+Kjjz6C2WzGPffcg9tv\nvx233HILVq1ahYkTJ+K9996DxWLBoUOHJLx6CjQcgRC54cknn0R2drbzv/OjiaioKPz7v/87FAoF\nfv7znyM1NRU7d+5EfX09fvjhBzz77LMICgqCwWDAjBkz8PHHHwMANmzYgEWLFiEtLQ2CICAjIwNq\ntdr5efPmzUN4eDj0ej3Gjx+Po0ePAgDkcjnq6urQ2NiIoKAgv97Tg3wPA4TIDW+++Sa+++4753/3\n3XcfAECr1ToX6wMAvV6PxsZGNDY2IiIiAiqVqtdrRqMRANDQ0NDnyrAajcb56+DgYOc+Fs899xzs\ndjvuvfde3HXXXfjoo48G9DqJ+sJbWEQDyGg0wm63O0Okvr4eOTk5iI2NRWtrK8xmszNEzu8UBziW\nG6+uru73KsAajQbLly8HAHz33XeYO3cufvazn/n10uzkOzgCIRpAp06dcvYjPv30U5SVleHWW2+F\nTqfD6NGjsXLlSnR2duLo0aP46KOPcPfddwMAZsyYgVWrVqGyshJ2ux1Hjx5FS0vLVT/v008/RUND\nAwAgIiICgiD49QZg5Fs4AiFyw2OPPdbrOZCbbroJubm5GDlyJKqqqnDjjTciJiYGf/jDH5y9jJUr\nV2LZsmWYNGkSwsPDsWDBAudU4Llz56KrqwsPP/wwWlpakJaW5tIeLIcOHcJvfvMbmM1mREdH49e/\n/jUSExM9c9FEP8H9QIgGyMaNG7FhwwZ88MEHUpdC5BUc6xIRkVsYIERE5BbewiIiIrdwBEJERG5h\ngBARkVsYIERE5BYGCBERuYUBQkREbmGAEBGRW/4/Odxwg4+/9iwAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.376\n",
            "Validation accuracy 0.384\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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0H8wqYerR8zB+QibbmqtH25q2ydH8bT+ORPs1UnIxUhrHudPjHe2NVoC1rSZW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\nl4goQwxdIqIM/X8eoRYIfUxb7wAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qvHmwRYOG_lR",
        "colab_type": "code",
        "outputId": "41bc069e-c4c4-41a2-8c6e-6ca15cdf5590",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "5bbadcd695454280a8c834aadddf7b7c",
            "eea48b196c06463e8968e18c96b62958",
            "3584624017b64172bdb8f38219f49f0a",
            "c7a92f4a19624686b2c7e3425cc1f155",
            "daf43dfa583f403c9f6a8f6fba7e71a0",
            "e5e7b5c1e41b4da0bf8a97da9cabb705",
            "ec3d049b1b3646f181d876d8a7155865",
            "6aea7882347c4a06bef31eab7a835ed6",
            "4ccf9a3fe6914b0fac769b8ac7a174f8",
            "752c0a03d514479ebe91803345157f9e",
            "bf6c354678dc4e09a99338f991ab67b7",
            "e8c257f5dac1477ba7d8554bbecb960e",
            "95dd1da146da4c438bfd599884e7643e",
            "e61f1723b59d43d9ace671986fd3131c",
            "7fd87c1c151940919cb011efeede908d",
            "7978959626704de5a849847633f03fb0",
            "01eb8931bb684fdbbf1028bc049dbf8b",
            "1b831707739d4c2d994446d2edf666c7",
            "2ec6c3973e834e609289a10cfad3fd24",
            "3978b86a7ad743299b78fda5d3207055",
            "dc32144e78344f2e90a6a9096395c9cd",
            "7ebf5a0cef7b41248ba37506c49e2294",
            "5fee6fb57a104660a880d0919042641d",
            "4954519ec20743259dda362565ed325b",
            "9b1549e0686343d989e744b8f298e1ae",
            "1e8c66ffb33241539e76bc0ca20774a4",
            "8ae5b4b915ac4df9825c95cc19dade43",
            "a105be39e735457a9a83f20f0b6e71e2",
            "13ad2c26cae24025af1ad09a02a6a7a8",
            "b75ee26519dd4737a9d4d704a5962259",
            "3303eb98632a4d2586d9f6dd6174ba24",
            "f2bbf572a84741b792020d2c97cad1e0"
          ]
        }
      },
      "source": [
        "for init_method in ['zeros', 'random', 'xavier', 'he']:\n",
        "  for activation_function in ['sigmoid']:\n",
        "    print(init_method, activation_function)\n",
        "    model = FFNetwork(init_method=init_method, activation_function=activation_function)\n",
        "    model.fit(X_train, y_OH_train, epochs=50, eta=1, algo=\"GD\", display_loss=True)\n",
        "    post_process(plot_scale=0.05)\n",
        "    print('\\n--\\n')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "zeros sigmoid\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "5bbadcd695454280a8c834aadddf7b7c",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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jI5GYmAiVSoWKigocOHAAERERpgqVyKa03b1XEIAmlQq9eba6zTNKF1Z8fDxSU1NRVlaG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\nECIi0sn/A77AQnfA51gvAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.528\n",
            "Validation accuracy 0.54\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5m+WjyQ2u3cuQLdRQgInhBN96Z4KXTnfTnwrv+3IoitIa53V7GFu2g8wtIETn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\nhK4QQrSRhK4QQrTR/w8o6d4fWt01AAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "random sigmoid\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4ccf9a3fe6914b0fac769b8ac7a174f8",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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YUGFRhvoprwqn8mtQe+0Gz7joBpcMXCcnJ2PTpk0YOHCgzXtiY2PxwQcf4IUX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\nEkREZBOTBBER2fT/AV8T5dBPB13lAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.5827\n",
            "Validation accuracy 0.568\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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XxegqQ9cYysUZusm8G64XUKy2KJRbFCo2a+UmhUqL1VKL05eL/M2bS1fdP5Mw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\nSUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "xavier sigmoid\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "01eb8931bb684fdbbf1028bc049dbf8b",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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DFAUMD/PtUceQiQK07RLqmm4YrrVpdSjkam8il2ZRknjvvfewZcsWKJVKLFmyBABQVFRk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\nRGYxSRARkVlMEkREZNb/B+sgPRw3cI4yAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.8747\n",
            "Validation accuracy 0.88\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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KVWYTBYqVGmrN+Mj739UT4F/9vQca+Ss0lGGazCznOXPVCtrJhRwmViHDQ7ti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\nrkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "he sigmoid\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9b1549e0686343d989e744b8f298e1ae",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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YUGFRhvoprwqn8mtQe+0Gz7joBpcMXCcnJ2PTpk0YOHCgzXtiY2PxwQcf4IUX\nXnBFSETkZSwHum+ut7jR2oartdehMxghwbwMRbfnkp5EYmLibe8ZMmQIAOCHH36AXq93dkhE5GU6\nlqHqtXpEBMsxLl6JHT+VYHtmqdm9OoOI8mqWoezBMQki8hrtZSiVKgS1tc0AgCFRCqvrLQ5lV+Bk\nfg3qGlmG6orXJQmlMrjbz6pUIT0YSe/ANvsGX25zkjIYh89VoqCsATq9iEC5HyIjgnC91YCKuuum\n+3UGESVVTSjTtGDiL6LcFfYdccZ79rokodFou7WApuNvHr6CbfYNbDOw5LGxFrOhdvxUiu2Z5tuU\nt+pF5BbWYIgyqNeVobr7ngVB1uUv116XJIiIOrM2G2pIlPVtPzJzqnC6oAY1DSxDAS6a3ZSeno6p\nU6eiuroaqampmDVrFgAgLS0Nubm5AIBTp05h6tSp2LBhAzZv3oypU6fiyJEjrgiPiHyQtdlQ0cog\n6PRtuFLD2VDtZJLU+VDB3o3lJvuxzb6BbbbNaJQsylDfHS3Bd0dLLe59bEoc5kyOc0K0PYPlJiKi\nHmatDDU02vpsqNySevy/kSrUNrb2qrGKO8UkQUTUgbVDkEKC5CirasI7fzsBQZDBaJQQ6CNjFUwS\nREQd2NobKuuCGp/vvgjxVjm740l53ryBIJMEEVEn1spQtY03LMY7dQYjDp2pwC+GhONCWYNXlqGY\nJIiI7DA4MgTyTmMVMhmQU6zBkj8dgQQJoih53ZRZnkxHRGQHayfljRocjjkPDEWbaESbKHnllFn2\nJIiI7GBrrGLnsVKLe3UGEfllDV6xgSCTBBGRnayNVVgrQwHA96eu4HRBDbQ3DL165TbLTUREd8Ba\nGWrEwFAkxIZB06Tr9Su32ZMgIroDXZWh8suvmd2rM4i4om7uVVNmmSSIiO6QrTKUtZXb5y5rkDhq\nANQNN3rFWAWTBBGRE1hbua3oJ8eVmma8/X9Z8BNkEHvBym0mCSIiJ7BVhjp2vhob9vSeldtMEkRE\nTmKtDKVpaoVkNL9PZzDi3OU6j5wyyyRBRORCtqbMHs6uxNlLdWjVt8HgQVNmOQWWiMiFrE2ZTYgN\nw4SRKjRd10PvYVNm2ZMgInKhrqbMni6sNbtXZxBR7uYps0wSREQu5siU2TOFtUhMGICoiCC3jFcw\nSRAReQBrU2bDggNR03ADv/tbFkKDA9HS6votPpgkiIg8gK0ylLbVgP/bcQHnS+pN93Ycr3B2KYpJ\ngojIQ1grQymC5BgxKNQsSQA/b/HRPm1Wk10JZbC8x8tQTBJERB7O1nhF9qU65BRrcLXm+q0SVc+X\noTgFlojIw1lOmxWgCuuDK9wwiKMAAAmISURBVDVaFFU0QWcQnTZtlj0JIiIPZ2u8YtvhIuzNKje7\nV9/DO826pCeRkZGBpKQkJCQkoLCw0Oo9oihi5cqVmD59OmbMmIGtW7e6IjQiol6hfbxizuQ4jB/e\nH4Igw8jYMAQG+JndJw/wQ2xkSM99bo/9pC4kJydj06ZNGDhwoM17duzYgfLycuzfvx9btmzBxx9/\njKtXr7oiPCKiXsna6u34GAXGxSt77DNcUm5KTEy87T27d+/Gk08+CUEQEBERgenTp2Pv3r1YvHix\nCyIkIup9Opah6rV6RHjz7KaqqirExMSYvo6OjkZ1dbUbIyIi8nztZSiVKgS1tc09/vM9Jkn0FKUy\nuNvPqlQ9V8frLdhm38A2+wZntNljkkR0dDQqKysxbtw4AJY9C3tpNFoYbx3m4QhnZWFPxjb7BrbZ\nN3S3zYIg6/KXa49ZJ5GSkoKtW7fCaDSivr4eP/zwA2bOnOnusIiIfJpLkkR6ejqmTp2K6upqpKam\nYtasWQCAtLQ05ObmAgDmzp2LQYMG4eGHH8ZTTz2FV155BbGxsa4Ij4iIbJBJkuR4bcaDNTRc71a5\nSakMhkajdUJEnott9g1ss2/obpsFQYbw8H42v+91SYKIiHqOx4xJEBGR52GSICIim5gkiIjIJiYJ\nIiKyiUmCiIhsYpIgIiKbmCSIiMgmJgkiIrKJSYKIiGxikgBQUlKCp59+GjNnzsTTTz+N0tJSd4fU\no2wdH+vN7W5oaEBaWhpmzpyJOXPm4NVXX0V9fT0AIDs7G48++ihmzpyJRYsWQaPpuUPj3e3ll1/G\no48+innz5uHZZ5/FxYsXAXj3uwaATz75xOzvtze/YwBISkpCSkoK5s6di7lz5+LIkSMAnNRuiaTn\nnntO+vbbbyVJkqRvv/1Weu6559wcUc86efKkVFlZKT300ENSQUGB6bo3t7uhoUE6fvy46es//OEP\n0v/8z/9IoihK06dPl06ePClJkiStW7dOeuutt9wVZo9ramoy/fn777+X5s2bJ0mSd7/rvLw86YUX\nXjD9/fb2dyxJksW/ZUmSnNZun+9JaDQaXLhwAbNnzwYAzJ49GxcuXDD91ukNEhMTER0dbXbN29sd\nFhaG++67z/T1+PHjUVlZiby8PAQGBpqO1H3mmWewd+9ed4XZ40JCfj50RqvVQiaTefW71uv1eO+9\n9/Duu++arnn7O7bFWe32mEOH3KWqqgqRkZHw8/MDAPj5+WHAgAGoqqpCRESEm6NzHl9qt9FoxJdf\nfomkpCSLw6wiIiJgNBpx7do1hIWFuTHKnvP222/j6NGjkCQJf/3rX736Xa9duxaPPvooBg0aZLrm\nC+8YAN544w1IkoQJEyZg2bJlTmu3z/ckyPu9//77CAoKwoIFC9wdikt88MEHOHToEJYuXYpVq1a5\nOxynOXv2LPLy8vDss8+6OxSX27RpE7777jt8/fXXkCQJ7733ntM+y+eTRHR0NNRqNURRBACIooia\nmhqL8oy38ZV2Z2RkoKysDH/6058gCILpmNx29fX1EATBq37DbDdv3jxkZWUhKirKK9/1yZMnUVRU\nhOTkZCQlJaG6uhovvPACysrKvP4dt787uVyOZ599FmfOnHHa322fTxJKpRKjR4/Gzp07AQA7d+7E\n6NGje303/HZ8od1r1qxBXl4e1q1bB7lcDgC466670NrailOnTgEANm/ejJSUFHeG2WOuX7+Oqqoq\n09cHDx5EaGio177rF198EZmZmTh48CAOHjyIqKgo/O1vf8PixYu99h0DQEtLC5qbb55lLUkSdu/e\njdGjRzvt7zYPHQJQVFSEt956C01NTVAoFMjIyEB8fLy7w+ox6enp2L9/P+rq6hAeHo6wsDDs2rXL\nq9t96dIlzJ49G0OHDkWfPn0AAIMGDcK6detw5swZrFixAjqdDgMHDsQf//hH9O/f380R37m6ujq8\n/PLLuHHjBgRBQGhoKJYvX44xY8Z49btul5SUhPXr12PkyJFe+44B4MqVK1iyZAlEUYTRaMSwYcPw\n29/+FgMGDHBKu5kkiIjIJp8vNxERkW1MEkREZBOTBBER2cQkQURENjFJEBGRTUwSRB4gISEBZWVl\n7g6DyILP791EZE1SUhLq6upM+x0BwGOPPYbf/e53boyKyPWYJIhsWL9+PR544AF3h0HkViw3ETng\nm2++wTPPPIP33nsPEyZMQEpKCo4dO2b6vlqtxksvvYSJEydixowZ+Oqrr0zfE0UR69evx/Tp03HP\nPffg8ccfN9tG46effsLDDz+MxMRErFy5Eu3rXMvKyrBgwQJMmDAB9913H/77v//bdQ0mn8eeBJGD\ncnJykJKSguPHj+P777/Hq6++igMHDiAsLAzLli3DiBEjcOTIERQXFyM1NRWxsbGYNGkSNmzYgF27\nduGzzz5DXFwcCgoKTFuGAMChQ4ewbds2aLVaPP7443jooYcwdepUrF27FpMnT8YXX3wBg8GA3Nxc\nN7aefA17EkQ2vPLKK0hMTDT9194riIiIwH/+538iICAAjzzyCOLi4nDo0CFUVVXhzJkzeOONNxAY\nGIjRo0fjySefxPbt2wEAW7duxeuvv474+HjIZDKMGjUK4eHhps9LS0uDQqFATEwM7rvvPuTn5wMA\n/P39UVlZiZqaGrNDZYhcgUmCyIZ169bh1KlTpv+eeuopAEBkZCRkMpnpvpiYGNTU1KCmpgahoaEI\nDg42+55arQYAVFdXY/DgwTY/T6VSmf7ct29fXL9+HQDw5ptvQpIkPPHEE5g1axa2bdvWo+0k6grL\nTUQOUqvVkCTJlCiqqqqQlJSEAQMGoLGxEVqt1pQo2k+FA4CoqCiUl5dj5MiRDn2eSqVCeno6AODU\nqVNITU3FvffeiyFDhvRgq4isY0+CyEH19fWm8YE9e/agqKgIDz74IKKjo3HPPfdgzZo10Ol0yM/P\nx7Zt2/Doo48CAJ588kmsXbsWpaWlkCQJ+fn5aGhouO3n7dmzB9XV1QCA0NBQyGQyCAL/6ZJrsCdB\nZMNLL71ktk7igQceQHJyMsaNG4eysjLcf//96N+/Pz766CPT2MKaNWuwYsUKTJkyBQqFAkuWLDFN\no01NTYVer8eiRYvQ0NCA+Ph4rFu37rZx5Obm4ve//z20Wi2USiXefvttxMbGOqfRRJ3wPAkiB3zz\nzTfYunUrvvzyS3eHQuQS7LMSEZFNTBJERGQTy01ERGQTexJERGQTkwQREdnEJEFERDYxSRARkU1M\nEkREZBOTBBER2fT/AV8T5dBPB13lAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.5827\n",
            "Validation accuracy 0.568\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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XxegqQ9cYysUZusm8G64XUKy2KJRbFCo2a+UmhUqL1VKL05eL/M2bS1fdP5Mw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\nvWVudknGt3RVJiydRGzzerx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            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "frrbqilqHB9F",
        "colab_type": "code",
        "outputId": "a0854220-5d79-4d44-ea1c-d832f31e1b24",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
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            "c8e71fabe11f4b6482ce81295d7f4a67",
            "ab64ea213dd64aa897146054fd4e3163",
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            "9eed7cfa0ff84b2786151cb6c99cfd09",
            "3271816a055a448cbdb2fdb387b014bf",
            "c3c365330d2747fe9cd523e8de940038",
            "a45e242ea68a4092b5434e665a41889e",
            "45867639030445d189a582adc63bdc02",
            "ce57ba559cd946009f32100ecd9e4ee4",
            "6f7a1b3c9dce4053ac3cbf6d2c8adc74",
            "500162369d56486a802f1c21f13033bd",
            "4dd041cce55c4ad1819e40a0e5adeb1f",
            "b35d0e9092c64212ab8816c30bcb95b2",
            "f441f15d0e454820a8efcd47eb8f37f8",
            "c77005c91f3b4dd0b6a8d242ad07fd52",
            "12298841899f46e39b668d2a9f5a291f",
            "7e2a5bb87f3744329b33001669aa4f8f",
            "568a697eed3d4e379ef9142141f6d8fb",
            "7d7f8516b044460d84842cf2cf4e8313",
            "9465c2a6eaf94a84b20888cb53c6eebd",
            "97ca87c3af3346e792a226425eb329de",
            "9c6b28ca18114dbdb780c361093ee26e",
            "670cec140a8a46e5a635c9ef11de516e",
            "39ef5b0f58544f779785d1a9d47f4463",
            "0f291ecedf1948cbbe58dc460821069c",
            "d064dbbc7d4e48f398e9ca7eb98e0bdc",
            "2d454bb0c2e740a3b1dd8d5420a68f49",
            "4188dedd0d0d47ec88bbb84171db47d5",
            "1c03d9b11a654981b7956d64de2a4973",
            "839590cbe93e41f380c31c22b060c208",
            "b5b2cc79ab6f498a8ed50cd081e39b46"
          ]
        }
      },
      "source": [
        "for init_method in ['zeros', 'random', 'xavier', 'he']:\n",
        "  for activation_function in ['tanh']:\n",
        "    print(init_method, activation_function)\n",
        "    model = FFNetwork(init_method=init_method, activation_function=activation_function)\n",
        "    model.fit(X_train, y_OH_train, epochs=100, eta=0.5, algo=\"NAG\", display_loss=True)\n",
        "    post_process(plot_scale=0.05)\n",
        "    print('\\n--\\n')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "zeros tanh\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "682208cb65ae4b3c9212d6ef3d192a16",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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I0FvXzLo1zOhwONi6dWuXbW+88YZ/mLC1tbVP9UwinS3+7z0zEZFI0K0K9NOf\n/pQHHniAq666yv+k6U8++YTly5cDsGfPHu68885eDVS6b0CsipmIRJZuFbMbb7yRV199lTfffJOG\nhgYmTZrEpEmT/Ms53Xjjjdx44429Gqh03+lrZp+rmIlIhOj22KDdbmf8+PHU19eTnJzsL2TS90Rb\nLfTvZ1HPTEQiRreKWUNDAw8//DC7d+9m4MCBNDU1ce2117Js2bI+NSVd/s4WG62emYhEjG5NAFm4\ncCEjR47k3XffZfv27bz77rukp6dTXFzc2/HJRdL6jCISSbpVzP7yl7/w6KOPEhsbC0BsbCw/+clP\n2LVrV68GJxdvQFw0zSdUzEQkMnSrmA0YMIADBw502VZZWYnNFvr3MIUrW1w0n7eomIlIZOjWNbPZ\ns2fzve99j+985zukpKRQW1vLSy+9xAMPPNDb8clFssVFc6K1g/YOH9aogDzpR0QkaLpVzG6//XZS\nU1MpKytj//79JCUlsXTpUjIzM3s7PrlIA76Ynn/shJa0EpHw1+2p+ZmZmV2Kl9frZfny5eqd9VFn\n3mumYiYi4e6ix5+8Xi/PPfdcT8YiPWhAXD9AN06LSGS4pIsp3VijWILEFmcFtKSViESGSypmJpOp\np+KQHjZAS1qJSAQ55zWzt99++yvb2tvbezwY6TnWKAv9+0WpZyYiEeGcxeyxxx4758FOp7NHg5Ge\npVVARCRSnLOY/eMzzCS0DIi1aphRRCKC7qYNY7b4fuqZiUhECFgxq6qqoqCggJycHAoKCqiurj5r\nH6/XS0lJCVlZWWRnZ1NaWhq0thUrVnDrrbeSn5/P9OnT2bZtm7/t5MmTPPjgg2RnZ5Obm8vrr7/e\nU6epRw2I1TCjiESGbt80famKi4uZOXMmLpeLDRs2UFRUxNq1a7vss3HjRmpqati8eTNNTU1MmzaN\nzMxMhg4dGvC2jIwM7rnnHvr378++ffuYNWsW27dvJyYmhueff574+HheffVVqqur+e53v8vmzZuJ\ni4sL1Ok8L5/P4Pipdk60dvCX/Q1846pEzGbNPhWR8BSQnpnH46GiooK8vDwA8vLyqKiooLGxsct+\n5eXlzJgxA7PZjN1uJysri02bNgWlbeLEifTv3x+AESNGYBgGTU1NALzyyisUFBQAMHz4cEaNGsWb\nb77Zm6fwgvh8BkvX7Wbn/gYA/mtjBUvX7cbn032BIhKeAlLM3G43ycnJWCwWACwWC0lJSbjd7rP2\nS0lJ8b93Op3U1dUFpe1M69evZ9iwYQwePBiA2tpahgwZct7jgmVvpYfK2mY6vJ3Fq63DR2VtM3sr\nPUGOTESkdwRsmDFUvfvuu1IoNrwAABRISURBVCxfvpzf/OY3Pfq5Dkf8RR+bmJhwznbP7lra2r1d\ntrW1e2lsaTvvsX1VqMZ9KZRzZFDOPSMgxczpdFJfX4/X68ViseD1emloaDjrPjWn00ltbS0ZGRlA\n155ToNsAdu3axSOPPMLKlStJS0vzb09JSeGzzz7Dbrf7j5swYcIFnROPp+Wihv0SExM4fPjYOfdx\nxEcTbbXQekZBi7ZasMdHn/fYvqg7OYcb5RwZlHP3mc2mc3YCAjLM6HA4SE9Pp6ysDICysjLS09P9\nxeC03NxcSktL8fl8NDY2smXLFnJycoLStnfvXh566CGeeeYZrrnmmrPiXLduHQDV1dV88MEHTJw4\nsZfO3oXLSHOQlmKjn7Xzx2sxm0hLsZGR5ghyZCIivSNgw4wLFy6ksLCQlStXYrPZWLJkCQBz5sxh\n/vz5jB49GpfLxZ49e5g6dSoA8+bNIzU1FSDgbSUlJZw6dYqioiJ/Dk8//TQjRozg3nvvpbCwkOzs\nbMxmM0888QTx8Rc/bNjTzGYTCwrGsLfSw29e/phke38WFIzRbEYRCVsmQ0vfB0VvDjOeaem63Zw4\n1c7jd193wd/VV2goJjIo58gQ0sOMEjwOWz88za3BDkNEpFepmIU5uy2G5uNttHd4z7+ziEiIUjEL\ncw5bDACNx9Q7E5HwpWIW5uyni9nnp4IciYhI71ExC3MOWz9APTMRCW8qZmFuUEJnz8zTrJ6ZiIQv\nFbMwZ40yMyAumkYVMxEJYypmEcCu6fkiEuZUzCKA3RajnpmIhDUVswjgsMXgaT6FFnsRkXClYhYB\n7LYY2tp9HD/VEexQRER6hYpZBDg9Pd+je81EJEypmEUA/43Tx1TMRCQ8qZhFAP+SVprRKCJhSsUs\nAiTEWomymHXjtIiELRWzCGAymXDY+ml6voiELRWzCGH/Ynq+iEg4UjGLEHZbP10zE5GwpWIWIewJ\n/Th6rJX12yrZ/ekRfD7dQC0i4SNgxayqqoqCggJycnIoKCigurr6rH28Xi8lJSVkZWWRnZ1NaWlp\n0Nq2b9/O9OnTGTVqFEuWLOkS5y9/+UsyMzNxuVy4XC5KSkp64hT1Gp/PYOf+wwD831vV/GrDRyxd\nt1sFTUTCRlSgvqi4uJiZM2ficrnYsGEDRUVFrF27tss+GzdupKamhs2bN9PU1MS0adPIzMxk6NCh\nAW9LTU1l8eLFbNq0iba2trPymTZtGo8++migTt8l2Vvp4cgZN0y3tnuprG1mb6WHMVdeFsTIRER6\nRkB6Zh6Ph4qKCvLy8gDIy8ujoqKCxsbGLvuVl5czY8YMzGYzdrudrKwsNm3aFJS2yy+/nPT0dKKi\nAlbve01N/THaO3xdtrW1ezlUfyxIEYmI9KyAFDO3201ycjIWiwUAi8VCUlISbrf7rP1SUlL8751O\nJ3V1dUFpO5+XX36Z/Px87rnnHnbt2tWtY4JlWHIC/axdf9TRVgupyQlBikhEpGeFfrcjCO644w7u\nu+8+rFYrb731Fj/84Q8pLy9n0KBB3f4MhyP+or8/MfHCitBkRzx/2lPL3k+PYBgQE21hxOWDmDxh\nOBaz6aLjCKQLzTkcKOfIoJx7RkCKmdPppL6+Hq/Xi8Viwev10tDQgNPpPGu/2tpaMjIygK49p0C3\nnUtiYqL/9Q033IDT6eSTTz5h/Pjx3T4nHk/LRU3ASExM4PDhCx8evP+fRrN03S4q3ceYe9s1ZKQ5\naPS0XPDnBMPF5hzKlHNkUM7dZzabztkJCMgwo8PhID09nbKyMgDKyspIT0/Hbrd32S83N5fS0lJ8\nPh+NjY1s2bKFnJycoLSdS319vf/1xx9/zGeffcYVV1xx6SeqF5nNJkalOWht83LV0AGYQ6RHJiLS\nHQEbZly4cCGFhYWsXLkSm83mn+4+Z84c5s+fz+jRo3G5XOzZs4epU6cCMG/ePFJTUwEC3rZz504e\nfvhhWlpaMAyDl19+mcWLFzNx4kSWLVvGRx99hNlsxmq18vTTT3fprfVVQy6LA+Czw8e5OnVgkKMR\nEek5JkOPHw6KQA8zAhz5/CQ/WfU2d+WO4OYxQy7qM4JBQzGRQTlHhpAeZpS+wW6LoZ/VQu3h48EO\nRUSkR6mYRRCzyUTKZbHUelTMRCS8qJhFmBRHHJ8dUTETkfCiYhZhUhLj+LyljeOn2oMdiohIj1Ex\nizApjs4ZjbXqnYlIGFExizCnp+ermIlIOFExizD2ATFEW826biYiYUXFLMKYTSZSHHG4VcxEJIyo\nmEUgpyOW6rpj/N9bVXrqtIiEBa2aH2F8PoMDnzVz/FQH67dV0c9qIS3FxoKCMVqvUURClnpmEWZv\npYejx1r978986rSISKhSMYswNfXHaPfqqdMiEl5UzCJM51OnLV226anTIhLqVMwiTEaag7QUm/8J\n0/2sZtJSbGSkOYIcmYjIxVMxizBms4kFBWPInTAMgLxvDtfkDxEJeSpmEchsNvH/JgzDZIL2Dp8K\nmYiEPBWzCBUbY2X4YBsVB48GOxQRkUumYhbBvj58EFW1zZxs7Qh2KCIil0TFLIKlXz4Ir8/gr4ea\ngh2KiMglCVgxq6qqoqCggJycHAoKCqiurj5rH6/XS0lJCVlZWWRnZ1NaWhq0tu3btzN9+nRGjRrF\nkiVLuh1nKLlyyACiLGY+1lCjiIS4gC1nVVxczMyZM3G5XGzYsIGioiLWrl3bZZ+NGzdSU1PD5s2b\naWpqYtq0aWRmZjJ06NCAt6WmprJ48WI2bdpEW1tbt+MMJdFWC1cOsfGX/Q3ExkQxLDmBjDSHJoSI\nSMgJSM/M4/FQUVFBXl4eAHl5eVRUVNDY2Nhlv/LycmbMmIHZbMZut5OVlcWmTZuC0nb55ZeTnp5O\nVNTZ9f5cx4USn8/A03wKT3Mr67dV8asNH7F03W4tPCwiIScgxcztdpOcnIzF0rnyhMViISkpCbfb\nfdZ+KSkp/vdOp5O6urqgtJ0vn4s5rq/ZW+mhqeXvvU6t0ygioUqr5geJwxF/0ccmJvbM0lOe3bV0\ndJy9TmNjS1uPfUdP6WvxBIJyjgzKuWcEpJg5nU7q6+vxer1YLBa8Xi8NDQ04nc6z9qutrSUjIwPo\n2gMKdNv58rmY487k8bRc1HBeYmIChw/3zKLAjvhooq0WWtu9/m3RVgv2+Oge+46e0JM5hwrlHBmU\nc/eZzaZzdgICMszocDhIT0+nrKwMgLKyMtLT07Hb7V32y83NpbS0FJ/PR2NjI1u2bCEnJycobedy\nscf1NafXaexn7fw1MJnQOo0iEpICNsy4cOFCCgsLWblyJTabzT/dfc6cOcyfP5/Ro0fjcrnYs2cP\nU6dOBWDevHmkpqYCBLxt586dPPzww7S0tGAYBi+//DKLFy9m4sSJ5zwulJxep3FvpYc/7f6MPZ96\nSB82kLK3qzWzUURCiskwDE1dC4K+MMx4plOtHdy/fBuGYWAYncONfeUJ1BqKiQzKOTKE9DCj9H37\nvlgFxGeAgWY2ikho0WxGATqfQO39h55ia7uXV9+rAdCQo4j0aSpmAvz9CdRnzmwE+PhgEwc+ayZp\nUH/GjkgiNTkekwGHDrcwNCkwrxt31zIoztrjnz8sOYFRw+18WN1ITf2xgOUTzJz78nkJZs7BOi99\nPefeOC+Nu2txxEf3+D+QVcwE+PvMxsra5rMKWluHj78dPs7fDldh+uJ3zzDo3msA05e8vtDP6eHX\nGGCNMhNlMeP1+Wht9wU9pr7wWudF56W3zwtG71yT1wSQIOlrE0Cgc3mrvZUeXn2vho8PaiV9Eek9\n/awW/sV1DWOuvKxb+2sCiHSb2WxizJWXkX3dMPpZLcEOR0TCWFu7l0P1PfcPcxUzOcvfb6ZWQROR\n3hFttZCa3HPLWumamZzlzJupa+qa2bn/MIebTobVdQJdA9F50XkJznk585pZT642pGtmQdIXr5l9\nldPX0g7VH2PIFzOS/na4JWCvj55oZ+AXM7568vNTz5iFFazcAp1zXz4vwcw5WOelr+fcG+fl6Il2\n7Bcxm/F818xUzIIklIpZsCnnyKCcI4NWABEREfkKKmYiIhLyVMxERCTkqZiJiEjI09T8ILmUJVwi\nccFf5RwZlHNkuJicz3eMZjOKiEjI0zCjiIiEPBUzEREJeSpmIiIS8lTMREQk5KmYiYhIyFMxExGR\nkKdiJiIiIU/FTEREQp6KmYiIhDwVsxBSVVVFQUEBOTk5FBQUUF1dHeyQetTRo0eZM2cOOTk55Ofn\n86Mf/YjGxkYAdu/ezW233UZOTg733HMPHo8nyNH2vGeffZYRI0bw17/+FQjvnFtbWykuLmbq1Knk\n5+fz+OOPA+H9O/76668zbdo0XC4Xt912G5s3bwbCJ+clS5YwefLkLr/DcO78ejR3Q0LGnXfeaaxf\nv94wDMNYv369ceeddwY5op519OhR45133vG///d//3fjX//1Xw2v12tkZWUZ7733nmEYhrFixQqj\nsLAwWGH2ig8//NC49957jVtuucXYv39/2Oe8aNEiY/HixYbP5zMMwzAOHz5sGEb4/o77fD5j3Lhx\nxv79+w3DMIyPP/7YGDNmjOH1esMm5/fee8+ora31/w6fdq78ejJ3FbMQceTIEWPs2LFGR0eHYRiG\n0dHRYYwdO9bweDxBjqz3bNq0ybj77ruNPXv2GLfeeqt/u8fjMcaMGRPEyHpWa2urcfvttxuHDh3y\n/yEI55xbWlqMsWPHGi0tLV22h/PvuM/nM8aPH2/s3LnTMAzDePfdd42pU6eGZc5nFrNz5dfTuWvV\n/BDhdrtJTk7GYrEAYLFYSEpKwu12Y7fbgxxdz/P5fPz+979n8uTJuN1uUlJS/G12ux2fz0dTUxMD\nBw4MYpQ9Y/ny5dx2220MHTrUvy2ccz506BADBw7k2WefZceOHcTFxfHAAw8QExMTtr/jJpOJ//zP\n/+SHP/whsbGxHD9+nNWrV4f9/9fnys8wjB7NXdfMpE9atGgRsbGxzJo1K9ih9Kpdu3bx4YcfMnPm\nzGCHEjBer5dDhw7x9a9/nZdeeokf//jH3H///Zw4cSLYofWajo4OfvWrX7Fy5Upef/11Vq1axYMP\nPhjWOQeaemYhwul0Ul9fj9frxWKx4PV6aWhowOl0Bju0HrdkyRIOHjzIc889h9lsxul0Ultb629v\nbGzEbDaHfA8F4L333uPAgQNMmTIFgLq6Ou69917uvPPOsM3Z6XQSFRVFXl4eANdeey2DBg0iJiYm\nbH/HP/74YxoaGhg7diwAY8eOpX///vTr1y9sc4Zz/90yDKNHc1fPLEQ4HA7S09MpKysDoKysjPT0\n9LAYijjTsmXL+PDDD1mxYgXR0dEAjBo1ilOnTrFz504A/vCHP5CbmxvMMHvM3Llz2b59O1u3bmXr\n1q0MHjyY559/ntmzZ4dtzna7nQkTJvDWW28BnTPaPB4Pw4cPD9vf8cGDB1NXV0dlZSUABw4cwOPx\ncPnll4dtznDuv1s9/TdND+cMIQcOHKCwsJDm5mZsNhtLliwhLS0t2GH1mE8++YS8vDyGDx9OTEwM\nAEOHDmXFihW8//77FBcX09raypAhQ/j5z3/OZZddFuSIe97kyZN57rnnuPrqq8M650OHDvFv//Zv\nNDU1ERUVxYMPPsikSZPC+nf8//7v//iv//ovTKbOJybPnz+frKyssMn5ySefZPPmzRw5coRBgwYx\ncOBAXn755XPm15O5q5iJiEjI0zCjiIiEPBUzEREJeSpmIiIS8lTMREQk5KmYiYhIyFMxE5FuGzFi\nBAcPHgx2GCJn0QogIiFs8uTJHDlyxL++HcA//dM/UVRUFMSoRAJPxUwkxD333HN885vfDHYYIkGl\nYUaRMPTSSy9xxx138MQTTzB27Fhyc3N5++23/e319fXcd999jB8/nuzsbF544QV/m9fr5bnnniMr\nK4tvfOMbTJ8+Hbfb7W//85//zNSpUxk3bhwlJSWcXnfh4MGDzJo1i7FjxzJhwgQefPDBwCUsEU89\nM5EwtXfvXnJzc3nnnXd49dVX+dGPfsRrr73GwIEDefjhh7nqqqvYtm0blZWVfP/73yc1NZXMzEzW\nrFnDyy+/zOrVq7niiivYv3+/f3kxgDfeeIMXX3yRlpYWpk+fzi233MJNN93E8uXLueGGG1i7di3t\n7e188MEHQcxeIo16ZiIhbt68eYwbN87/3+lelt1u5+6778ZqtfKtb32LK664gjfeeAO3283777/P\nj3/8Y/r160d6ejozZsxgw4YNAJSWlvLAAw+QlpaGyWRi5MiRDBo0yP99c+bMwWazkZKSwoQJE9i3\nbx8AUVFR1NbW0tDQQL9+/Rg3blzgT4ZELBUzkRC3YsUKdu7c6f/v9ttvByA5Odm/qC1ASkoKDQ0N\nNDQ0MGDAAOLj47u01dfXA52PoRk2bNhXfl9iYqL/df/+/Tl+/DgAjzzyCIZh8J3vfIdbb72VF198\nsUfzFDkXDTOKhKn6+noMw/AXNLfbzeTJk0lKSuLzzz+npaXFX9BOPxEYOh9XUlNTw9VXX31B35eY\nmMiTTz4JwM6dO/n+97/Pddddx+WXX96DWYl8OfXMRMJUY2Oj//rVK6+8woEDB5g0aRJOp5NvfOMb\nLFu2jNbWVvbt28eLL77IbbfdBsCMGTNYvnw51dXVGIbBvn37OHr06Hm/75VXXqGurg6AAQMGYDKZ\nMJv1J0YCQz0zkRB33333dbnP7Jvf/CZTpkwhIyODgwcPcv3113PZZZfxzDPP+K99LVu2jOLiYiZO\nnIjNZuP+++/3T+///ve/T1tbG/fccw9Hjx4lLS2NFStWnDeODz74gJ/97Ge0tLTgcDh47LHHSE1N\n7Z2kRf6BnmcmEoZeeuklSktL+f3vfx/sUEQCQmMAIiIS8lTMREQk5GmYUUREQp56ZiIiEvJUzERE\nJOSpmImISMhTMRMRkZCnYiYiIiFPxUxERELe/wdlyqQ3GhtGuwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.2507\n",
            "Validation accuracy 0.248\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAADnCAYAAAC9roUQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBQgSXYAg0QUIEl2AoP8AlKyHqg+v+2QAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "random tanh\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "45867639030445d189a582adc63bdc02",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ebXjrTzdumNCbsdHQoSFobTV5vkE+JJPJEBM5BEmjIjArdQTiNKGQATDU34Clh78kwSKi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\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.8547\n",
            "Validation accuracy 0.86\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Uuy3L/hqeCZFYgu/++hR6jYovPbR60a/3dDMj98JsyyIa9Rpqih0T5sYqikLy\nUhk6tUrKCOsz3WivsOAXQuRmgkqS+MhtVXzrF8f5l1+f4uGbK7EYtQQjcYKRBNFYEllRkAC1WkKt\nUiFJKTdTUlFIJBVi8SThaIJwNEkwEscfiuMPxfAFY3iDqX+vTOG5kmK3hXVV2ayqyKIsz7oogb2B\nkdTso5vX5vPOiR4Kc1JTUR1mHWdaPXzktkpePdTBP/7yODvWFjDij6LTqtm1rYwhX5S//vfDPHxL\nBfffWJb2vu8+0ok/FMuocqaKovDvr5yndzjE1x5dl5YYSqax6NkLkiShUV9/Qns5o5buxpoc6kqd\nY7NeFpOV5Vl88u5afv76Bf7iiUNzakutkrAYtVhMWmwmHVVF9ktvRHps5tRnFpMW46W8aY8/SnO3\nl5PNQ7ywr5Xn97aiVknku0yU5lopL7BRVWinyG2Z8WuprCjE4zIJWSYpKyiygqxA8tLf8YRMPCET\niSZo7fPzXwfaAbhtfREFLjNl+TZqih1E40neO9nDzWsLqC5y8PRbzby47/1i9G8d7xp7g3v67Yt4\n/FF2binBPccg8EyIxpM8t6eVPJeJrfWZ4SZ642gX+8/28dCOclaUTV0dcDkiKYpyzWrHQ0MBURB5\ngfnRSw28d7KHD9xUyoduvnplC5VKwuWa35SY6Y6rxx/lfIeHWFzGpNdgNmox6NRjYpeQZZJJhdHL\nSKWS0KhV6LRqDFo1JoMGg0496zeYQDjO+fYRWnt9tPcFaOv14QvFAbCZtKyrzmFtlYuyPBt2i45k\nUmEkEKVvOETXYJCeoSD9njDDvij+cIxwNDmrfnz/j269ZkwhKcv8zX8cIRRNUp5vpW84TEuPD7NB\nQyiaAAXMRi3f+v1tY+0sxLjC+2OblGX++t+PEI4m+JvPb110v+nxpkG+8/Qp1lS6+P2HVy96fxaK\nqcZ10S1dwfuW7pVuhkzAadUvqpVkMWrZWJszlvesKApD3gjnO0Y4dXGIAw19VwUir9w/N8tIWX7K\nR2zSa9Dr1KhVKtQqCZUEkkpCLUmo1RI6jRqNWoVeq0KtVrH3dC+hSHzKIK5apeJPPrGRRFLGqNeQ\nSMo8ubuRHWsKcDuNhKMJ2nr98x4MnqpPOzcX84Pnz3KuzTMujzydKIrCeyd7+I9Xz1OSa+FzH7y+\nAmdXIkQ3AxgVWzEZYWokSSLbYSTbYWTb6nziCZmL3V46B4IEwnHUKgmbWUeu00h+thmbaW7BuJnU\n6NBqVGMPUI1axSd3vr/OnVGvWRT/5abaHH72moY9p3rSLrqyrHC6ZYiX97dzvmOEFaVOfvfBVRj1\n17fsXN+/PkMYs3TTnCq2HJwENJoAACAASURBVNBqVNSWOMW05UnQatSsqczmZPMgSVle8LxrRVFo\n6fFz6FwfBxv68fijOCw6PnFXDbeuF3nfIEQ3IxCiK1hI1lVns+9ML81dvnkvaQqp4GRTp5cj5wc4\neqGfIV8UtUpidYWLj91Rzbrq7LS6VTIdIboZQCb7dAVLn5VlWahVEieaB+dNdBVFoa3Pz97TvRw+\n189IIIZGLbGyLIsHd1Swrjob8zTry15vCNHNAN736QrRFcw/JoOGigIbDa2eObcVjSXZe7qHN491\n0zkQQKNOWbSb69ysrcq+7v2100GcoQxgLPgiRFewQKwodfL8nlaCkfisLNBILMFrhzt59WA7wUiC\n0lwrj91dy5YVbmHRzhAhuhmA8OkKFpr6siye29PKuTYPG2vd095PURQOnO3jF2804Q3GWFvp4r4b\nS6kqtF+Xs0fnAyG6GcBoqpjw6QoWiooCG3qtmoYZiG4gHOfHLzVwrHGQ8nwrX/rQ6hktBCuYGCG6\nGYDNlHo9s5rEa5pgYdCoVVQX2TnXPjKt7TsHAnz7VycZCUR55LYqdm4uFkV75okpRVec6IWnrtTJ\n3/3eTZPOy1+IMRDjuvgs1BhM1u6mOjcv7W8jGIljvcakkbY+P4+/0IDdqufLH15LSe7SWZUhE5hq\nXKesvSAQCASC+UM4EQUCgSCNCNEVCASCNCJEVyAQCNKIEF2BQCBII0J0BQKBII0I0RUIBII0MmWe\nrscTnPVyPS/sbeWdE9189M5qNlTnzKoNQSrvz+k0z2ubcxlXwfywEOMKYmwXm6nGdUrRlWVl1gO4\nc3Mxp5qH+O4zp/naR9ctSC1PweyYy7gKMhsxtpnNgroXNGoVv/fQKrLtBv75Vydp6fEt5OEEAoEg\n41lwn67VpOMPH12H2aDh/zx5nPPtc6/pKRAIBItJPCEjz3Iyb1oCaS67ga9/fAMOi45/+MVx3j05\n+eqtAoFAkMnIisI3vr+PVw92zGr/tFUZc9kNfOOTG/nXZ0/z45fOcb59hE/cVSMqzS8z4gkZXzCG\nPxwjHEkQTcjIsoJKktBpVZgNWhxWPTaTVtRjFWQksqyw51QPG2vdmAwpfRryRvAGY3QOBPAGYwz7\nojR3eWfVfloVz2LU8tVH1/Lce628sK+VhjYPH7+zhg012eIGXEJE40k6BwL0DIbo84To94QZ9IYZ\n9Ebwh+LTakOvU1OUbaa8wMaKEicrypwYdOIBLFgcXjvcgd2s442jXRRmm3nzWBcv7W/jz397C8Fw\nnP949Tzn2j2gQCwhA9A7HJrVsaasMjY0FFiQSGhzt5efvHyOzoEgdSUOPnRzJVVFmVkgWVEUgpEE\nw77U0y4QjhOJJognZJKKgsWgHfdUnG9UKgmXa37L6810XBVF4eiFAXYf6aSx00vy0r4qSSLbbiDH\nYcBlN5Jl0+Ow6LEatZgMGnRaNSpJQlYUYvEkgXACjz9C33CYjn4/rb1+YgkZrUbF+ups7tpUTOV1\nUih7IcYVFu6eXW40do5wsKGfrStz+fufHyOZVMau61EsRi3haALgqu8AchwGPnt//bjMrKnGddFE\nFyApy7x1rJvn9rTgD8WpK3Fw56Zi1la5UKsWZ95GLJ6kvS9Aa6+P9v4AXQNBeodDYyd+MnQaFZ+6\np5abVuXPe58WW3STsszjLzSw/2wfboeRjXU5VOTbKcwxk203zGl57URSprHTy9HzA+w/20swkmBT\nnZtP3lWDzTx5zdflgBDdxeVfnz3NoXP9qFXSVYJaXWRPrSu3txW1SkUiKeO06lFJMOSLjtv2plV5\n/M4H6sf+zmjRHSUaS/LW8S5eO9zBsC+Kzaxjc52bDTU5VBfZ53RTT4U3GKOxY4QLnSM0d3lp7wuM\nDYDVpKUw20x+thm3w4jLZsBu0WExajHpNWg1KiRJomcoxPefP4PToufrn9gw731cbNH92esXeP1w\nJw9uL+cDN5UtWPHtSCzBq4c6eGFvG2aDZtkvDyNEd3H5sx8dpKM/MPa3Xqsm22GgayDIrm1lPLij\ngnA0wX8dbGfPqV7+4re3IEnwtz89gl6nprkrlQJr0mv4py9vH9OpJSG6oyRlmZNNQ+w53cvJ5iES\nSRmdVkVlgZ2yfCtFORbysky47AasxpkHYhJJme7BIC09Ppq6vDR1eunzhIGUpVqeb6Oy0E5lgY2y\nfBsOi27ax/jB82e40OHl73/vphn/7qlYTNHt6A/w5z8+yK3rCnns7tp57cO1jvmdZ07i8cf4wq76\nGS2kuJQQort4yLLC733rbXasLeBgQx9mg5b/9pE1WI1a9pzqZUt9LvZLb1qKoqCQcqVBSkdC0QT/\n/dvvoVGnrOC//O0tFLlTY7mkRPdyIrEEDa0ezrZ6aOry0jkQGPcKoFGrcFp1ZFkNZNn02C/5EXVa\nNZKUiqKHowl8oTgeX4T+kTD9nvBYGxajlqpCO9XFdmqKHJTmWedkUT/zzkVe3NfKv33t1nm3zBdT\ndL/77GkaWof52y/ciMWYvjXc/KEY3376JBe7fXz6njp2rC1I27HThRDd9CIrCkPeCAfO9vHMOxcB\n+NQ9tWRZ9agkiVUVrhm119rrozDbTEuPn8pC25hLdKpxzdhwsUGnYX1NDutrUjUbEkmZvuEQfZ4w\nQ74IHl8UTyDKsC/ChQ4v3mCURPLqC81s0OC0GsjLMrGuOptit4XyPBtup3FeMyZy7AYUBTz+KCaD\nBqNeM/ZkvBxFUXjqzWZKci1sXZlHNJ7kvZM9bF+Tj16rxuOPMugNU120+FOmQ5E4xxsHuXVdQVoF\nF1KTar726Hq+8+tT/Pjlc4RjSXZuLk5rHwRLg0A4zsBIGI8/ii8UIxiOE4omCEUSBMNxAuE4I4EY\nI4EokVhy3L75WSZqS5yzOm5Zng1gxuUNMlZ0r0SjVlGYY6EwZ+IniKIoRONJYnEZBdCqJQw6TdoW\nYMy+tKjkvtO9PPteC7993wq2r7k6qLbnVC+vHGwH4OiFAZq7fXj8UfRaNWuqXPztT49gMmj4889s\nSUu/r8Xh8wMkkjI3rspblOPrdWq+/PAavv/cGZ7c3UgsnuQDN5UtSl8EmYGiKHQNBjnVPMT5jhFa\ne3z4JkhT1KgljHoNZoMWi0lLkdvCyvIsCrPNqFUSP375HAB5rvkvODQVS0Z0p0KSUiJrWKSAd7bd\nAMCz77UAcOR8P2sqXeMi8PvP9PLEpcGGlKiN0tTlZf/ZXrzBGF98YFWaen1tTl0cwmXTU5ZnXbQ+\naDUqvvjgSn70YgPPvHORWELmoR3lGZHXHY0nae7ysqLUOWl/ZFnh0Ll+NtbmLGhAeLmTSMrsPd3L\n64c76BwIApDvMrG60kVhtoVcpxGnTY/NlAp067Tqa7aXm2XiQEMfNlN63+BgGYnuYpNl04/9P9tu\n4ETzEF/5v++xc0sxzV0+vvLIWp58o4nyfCtf2LWSb3x/P9VFdv7oY+v51i9P8M6J1NToT99bR0WB\nbbF+xhiKonChY4TVFa5FFzi1SsVn769Ho1bxwt5WYvEkj95etaj9GvZF+P5zZ7jQ6eWDN5Xx0M0V\nE253rHGAf3vuDJ++t46bl6FfOh209vr4wfNn6RkKUZJr4ZM7a1hfnYPTqp9650moKXYsWtVDIbrz\nhFql4saVeZTnW1EU+PnuRhTgvy7Nz37qrWZ8wRi/fd8Ksh1G/vDRdeRmmZAkiWK3hTMtw5TlWdkx\ngUtiMegeCuEPxanNkHKcKpXEb91bh16r5tVDHfhCMT5z7wq0mvRZj+Fogp+8co62Xj/9I2FUkkRd\niYPn97YiSfDA9nIAfKE4ZoOGvuEQe0/3AvDUm0109AX46J1Vi5aDvhQ5dmGAf/3NGWxmLV9+eA1r\nqxbfCJgrQnTnkc99MJUg3dbrB8Bm0o75m9461kW23cCqiiwA6krfd95vrnPz6sEOPnFXTcZcUI0d\nIwDUlmSG6EIqZedjd1ZjM+t45p2L9HvCfPGBlWTbjQt63B++cJZhX4R4Uqa1x8+66mxuqM9l++p8\nnDY9P3nlPM/taaWpy0vXYBBvIEaJ20L7pRxQSYJgJMHxpkE+flf1gvZ1rsQTSRraRmjq8tI7FGQk\nECMcS6TqZ6gkdBoVJr0Gi0mH3azDZTfgdhjJc5nIsRvnNYbS0Obhu8+epjTPypc/vAabaXlMlhGi\nuwCU5ln5q89uwe00crbVw9NvN9M5EGTH2oIJMxrK82384I9vzRjBBWjr82M2aMhxLKygzRRJkvjA\nTWXkZZl4/KUG/vTxg+zcXMz66hxsZh2xeJKRQJSRQIxgJE4snponr9WoMOjUmA1abGYdDosOu0U3\npdXZORAYs1YNOjVf2LWSTXXj84Y/fW8dWo2K442D1BY7sBi1vHG0C5dNj82s594bSjjY0MeHb63M\nqDG+nEA4zkv723j7eDfhaAKVJJHjMOC06nE7jKjVKhRZIZpIEo4kGBjxMRKIjtUhgFSue9Gl7KDK\nQhs1xQ6ybIZZ9WfYF+Ffnz2N22nkq4+sxWRIv+91oRCiu0CMZlmsrcrmdMswXYNBtl0jCyDTbsb2\nvgAludaM69com+rclORZefL1Rp7b08pze1pn3IZKksiy6clxGMnLMpHvMlGYbaYgxzKWGP/S/jZ0\nGhVf/8QGsmyGsc+vbOexnbU8tjM1eURRFEpyrVQW2inMNo/1N91c7Pbx3J4WPP4o66uz+cBNZRMG\n8040DfKjlxoIhOJsXuFm2+p8aood6KcIRimKgj8Up98TpmcoSOdAkPY+P++d6mH30U4gFezaWJvD\nresKpy3AsqLwwxfOEk/I/MHDa5aV4IIQ3bSwa1sZm+vcs37qp5ukLNM5EOC29YWL3ZVr4nYY+fKH\n1zDsi9DU5SUUSaDTqrCb9TgsOiwmHbpLPt94UiYSTRAIJ/AFUzmbw/4IgyMR+jxhDpztI3RZfQ27\nWUfs0gSbe7eWUJ4//eCmJEkZETQ7cr6f3uEQWVY9z+1ppa3Xz5c+tHpMeBVF4ZUD7fzqrWaK3Bb+\n8NF1lOROP1NFkiRsZh02s25csaqkLNPZH+R8u4eTF4d4cV8brxzo4IM3lXL/jVNPI3/1YAfn2kf4\nzL115GWZZvfjMxghumnAatJhXUL+qL7hMPGETEnu/M+WWgiybAa2TPFAMwI2kw73JHnwiqLgDcbo\nGgjSOZAqdHSxx4fZoOEDN5bNe5/TwUduq+Ijt1UB8MbRTn766gWeePkcn71/RSrY+3oju492srnO\nzWfvXzFlmtV0UatUlOZZKc2zsnNLCYPeML96q5lfv9tCS4+fL+xaiV438bGau708/XYzG2pyJsxz\nXw4I0RVcxWgRkGL34uXnphtJknBYUmUpV5angp2KoiAryrLINrh9QxGBUJxn32thJBAlFEnQ2uvn\n7i3FfOS2qgljDfNFtt3IF3atpKbYwX++doH/8+Qx/mCCwNjgSJh/eeYUTqueT99bl7Gurbmy9K8m\nwbzTORBArZLIdy2/V7uZIEnSshDcUT64rYyP3VlNe1+AUDTB53fV8+jt1QsquKNIksTtG4r4vQdX\n094f4K9/cpiG1mFGS780d3v53z87Sjwh8+WH16R92nk6EZau4Co6+gPku0xiBtUyQ5Ik7tpUzF2b\nFq+GxcbaHL5u3cD3fnOav3/yODkOAzqtmq6BIFk2PV/76Pqxal3LFSG6gqvoHAgs2mwdwfKnosDG\nX332Bvae7uFsq4dEUmZrfS63rS9cdpkKEyFEVzCOYCTOsC9K0SSFhQSC+UCvU3PbhiJu21C02F1J\nO+L9UTCOzktBtKKc9FdfEgiuB4ToCsYxWsHpespcEAjSyZTuhXTVoxVMzkKMwWRteoMxyvJtZNn0\nyzZlJ1NYqHtL3LOLy1Tnf8rlegQCgUAwfwj3gkAgEKQRIboCgUCQRoToCgQCQRoRoisQCARpRIiu\nQCAQpBEhugKBQJBGpszT9XiCyPLss8o6+gO8eqiD8+0ezEYtN68tYGt9Hkb97Gp3+sNxfv7aBZq6\nvHzqnjpWXSrDN1MC4Tjff+4MA94IH7+jmtWVrlm1kw5UKgmnc35niF0+ri/ua6Mg28T66px5PYbg\n2izEuMLc71nB3JhqXKfM0x0aCszLADZ1efnNey2caRlGr1VzQ30uW+tzqSqyT1nNKpGUae7ycvj8\nAHtO9RBPyHz63jq2rZ5bkeNAOM4//+oEzV0+7r+xlAe2l2dkZS2VSsLlmt9aCJeP63eeOUVDm4f/\n/cUbl3VJvUxjIcYV5u+eFcyOqcY1baI7Sluvn9ePdHDoXD+xuIxBp6Y830a+y4TDokevVSMrCqFI\ngmFfhO6hEB39ARJJGY1aYkNNDg9sLyffNT8WQjyR5D9fu8A7J3oocVt47O5aKgvtU++YRhZadDsH\nAvzZ4wd5YEc5u7aVz+txBJMjRHd5knGiO0o0luR0yxBnWz209vroHQ4TvmyNKklKrVOVl2WiJNdK\ndZGD+jInRv3CFEY7cr6fn752AW8gxvrqbO7bWkpFgS0jpsIutOgC/NVPDqFRq/jGJzfO63EEkyNE\nd3ky1bguWmlHvU7Nxlo3G2vfXyU1nkgSjcuoJAmDTp3WOeQba93Ul2Xx6qEOXjvUwbHGQQpzzGxZ\nkcvaShdFbktaKuwvFnWlTl492EE0lpx0/SqBQDB3Fs3SzWTC0QQHzvax53QPzV0+AEx6DWX5Vopy\nLOS5TOQ4jLhsBhwWHQbdwj670mHpnmkZ5h9+cZyvPLKW1RWZG1RcTghLd3mSsZZuJmPUa7h1fSG3\nri9kJBDlTMswjZ1e2nr9vHmsi3hCHre9XqfGYU6t+Gsz68i2G3A7jWTZDORnmXBYU77qTKaqyI5a\nJXG+fUSIrkCwgAjRnQKHRc+21fljmRKyojDsizA4EmHYH2EkEMMbiOENRvGH4vQMBTl9cYjYZcIs\nAdkOAxajjsIcM3lZJopyzMQTCkU5ZjovrQ/1+uFOjHo1/SNhvvrIurT+Tr1WTVmelQudI2k9rkBw\nvSFEd4aoJIlsu5Fsu3HSbWRFwRuIMeSN0OcJMTASps8TxheMcbxxkEA4ftU+apVE8tIr4b1bSxas\n/9eiutjB64c7iCeSaDWZbZkLBEsVIboLgEqScFr1OK16qorGp58pikI0nqSpy4takmjs9OIJRHn7\neDcP7kjlCd+zZXFEt6bIwSsH2rnY7aO2xLkofRAIljtCdNOMJEkYdBpWlaf8pivKslAUhQ/eVEaW\nzbCofasptqOSJM60DgvRFQgWiMybfnUdIknSogsugMmgparIzsmmocXuypJHVhSeerOJzoHAYndF\nkGEI0RWMY02li/b+AMO+yGJ3ZUnTPRDk5QPtvLy/DUi5lUQalwCE6AquYGNNDhLw1vGuxe7KkqOp\n08vpi6m3hNEskONNQ1zoGOGbPzjAl//5XRJJ+VpNCK4DhE9XMI7cLBMbanPYfaSLOzYWYzfrZt1W\nIinT0R+gtcdH92CIAW8qgyMcTZBIykiShE6rxmzQ4LDocTuNlOZaqS1xYDXN/rjzSb8nRDCSoDzf\nNuW2P3v9AsO+COtrcnj7eDcSqYk2//9/HiXbbuBT99RmZEElQXoRoiu4ige2l3Pq4hD//NQJ/uhj\n62dU7yIYiXP0/ADHGgdpaPcQjSUBMOjU5DiMY+KqVauQFYjFkwTCcdr6/By9MEBSVpAkqC/L4o4N\nRaytci1q/Ys/+bf9APzoT26/5nbRWJL2vgCyovD28W4glYJXnm8lFpe5/8bSjPDbCxYfIbqCqyjK\nsfDFXav4zjOn+M4zp/hvH16D7hoz6hRF4Wybh7ePd3O8cYBEUsFl03PjyjzqShxUFNhw2QxTimc8\nIdPe7+dE0yB7TvXy7adPUppn5WN3VFNT7Jjvnzkl8mUz5BVFuWb/L3Z7x21/x4Yitq3JoyxvagtZ\ncH0hai8sAdJRe2Ei9p3u5YcvnKWu1MmXHlqFyTC+1m4oEmfv6V7eONpF73AIi1HL1pW53Lgyj7I8\n65ws1ERSZv+ZPp597yLDvijbVufx6O3Vaav32zUY5FBDH8/taQXg2/9tx7hjD4yE+Zdfn+LLD6+h\nrdfP/33mFADFbgsOi56vPLJ2ymOI2gvLE1F7QTBrblyVh6woPPHyOf7n4we5c1MR+VlmRgJRzrYO\nc7I5Nd25osDG73xgBZvr3PM2k02jVrF9TT6bV7h5YW8rrxxo5/TFYT51T+28rnARjia42O2jtddH\nR3+A3qEQfZ4wsUSSy80Rjz/KT14+x5pKFzvWFtDQ5qG9L8DZVg97TvUAsG11Hh+/s2ZZV6PLNJKy\nTDSWJCkrqFUSWo0ajVqa1gM/HE0w5ItQmG1OqwtLWLpLgMWydEdp7vLy5O5Gmrt9Y5/ZzTo21OZw\n85oCSvOs89q3iWjv8/P4iw109AfYssLNo7dX47TqZ9yOLCs0d3s52TzEmZZh2vr8Y+LqshnId5nI\nc5kw6TXsP9tHvycMwO98YAU/fKGBmmIH3mAMvUZFe3+ArfW5HGjo4/4bS/nQzZUz6ksmWLqKoqDA\nknlQ9HlCHGro51y7h66BIL5gjCt/qUYtYdJrsJh02M06nFY9WTYDuU4jOY5UsDYST/L02828d7KH\nVRVZOMx68l0m7rmhZM4CnLFFzAXTZ7FFdxSPP8pIIIrVqMVln9pHO98kkjIv7W/jhb2tqFUqbt9Y\nyB0biqYMUEVjSc62DnOscZDjTanaFypJoqLQRn2pk+oiB2X5VsxXuE9Gfcz/69+PsKnOzeFz/ZMe\n408/vWnG/tvFFN1wNMEzb19k75leorEkOU4jVYU2qoscFLstuOwGLAbtpDWtR8UaBRQUFAWSskIy\nqZBIysQTMomkjKwo6LVq7BYdatXsMzcudvt4bk8LJ5tTKXnFbguluVaybHpMeg0qlYQsK8QSMuFY\ngmA4QSAcxxuMMuxLXbeXK51GLaFWqYjGk2Of6bQqnBY9H9xWxk2rZr8UmBDdZUCmiG6m0O8J8cw7\nFznU0A8SVBc5WFHqpDDbjM2sQ5YVRoJRugeDNHV6aerykkgqGPUa1la6WFedzaryrKt81BORSMp8\n/u/fQqNWTZpjW+K28Gef2Tzjh9Biia6sKHz7Vyc5dXGIrfW5ZNkMdA8Gaez0XlWMafRVXVFSwipf\n+nemaNQSFQV2NtbmsGVF7rRTEVt7fTy/p5VjjYNYjFru3FTEjjUFM37LSSRlBkbC9A6FONUyzFvH\nUnnoX3xgJT97vZFkUiYYSa1cY9RrcNn03LGxiFvWFc7shyJ8uoJliNtp4osPrOLhW8LsOdXD8cZB\nnnuv5arXTJUkUeQ2c8fGIlZXuKgpdsw4T1ajVmE1afGHrq4MN/r5fTeWZsSyTtNlz8keTjYP8Ym7\narhjY9HY54qi0O8J0zkQZNgXIRRNjPm2JSl1PiUJJC79K0lIAJf+r5JS50ujVqHVqNCqVUgSROJJ\n+oZDnGkZ5uevN/Lk7kYqCmyU5lqxGLWoJImELBOOJglHE8QTMrF4kp7hEP2eMEa9mge3l3PX5uJZ\nL9elUavId5nJd5lZX5OD61Ip1XVV2eQ4UhUDe4dCNLR5eO9UD50DCX7yynnsZj3rqrPn4ay/j7B0\nlwDC0p2acDRBvydMIBJHBVjNOnKdxnkJ7H35n98lEI5TU2TnQqeXohwzPUMhvvzhNWjVKmpLHLMS\n3cWwdGVZ4Zs/PIBBq+ZPP70p7Q+L0ayQM63D9AyGCF1aF1GSwKDTYNJrUoKtUZFtN7CqPIutK/Pm\nfW3EUcv9SveJPxTjL544xEM7KnhxX2oK99c/sWFGk4SEe2EZIER3cXnnRDf9njD331jK//fDA+za\nVsamOvdVPuCZshiie+riEP/4yxN8YddKbqjPnfdjz5RR8Ru1nDOJk81DfPtXJzEZNPzN57eOSxlU\nFIWX9rexuc6N22kat99U4yrmJAoEU3Dz2gI+fGslRr2Gf/jSNm5eWzBnwV0sjl4YQK9Ts6Fmfl+Z\nZ4skSahU00vxSjdrKl1847ENBMJxvvvrU7x3sodRG7XPE+bpty/y0v52QpHEFC2NR4iuQDBDMlEg\npoOsKBxrHGR1hUusDDJNKgvsrCh1cq59hB+91MC/PXeGRFKmtSeVPvnOiW7+4J/eoXc4NO02RSBN\nILhOaO/z4wvGWD/PgaHlzm/dW8f5Ng/eYIxn3rlIIqmMy57Q6dTkOKZfV0OIrkBwndDU6QWgdhHq\nWCxl3A4j7ksZDnqtmp/vbgQg32WiNM/KfVtLZ5SDPKXoTpYcLUgfCzEGYlwXn4Uag8naHfRFqS52\nkO2YfFFVwbW5+4YStBoVrxxsZ2t9Hg/sKL9qm6nGdcrsBYFAIBDMHyKQJhAIBGlEiK5AIBCkESG6\nAoFAkEaE6AoEAkEaEaIrEAgEaUSIrkAgEKSRKfN0PZ7gtAqjxBIyz757kcPn+inNtfLwLZXkuUxT\n7jcVoUiC0y1DHLswQHO3D5UksbI8i22r8yjPt2XklMyeoRD/+Mvj5LvM9AwFyXEYGRgJc+PKPB66\nuQKAv/zJYVaVZ7H/TC/bVuWz53QPX9i1kspC+1XtqVQSTqd5Xvs43XFNF8FwnG89dQKrQcuXP7wa\n1RTJ5mdbPTzxcgOfuKuGtVVLc4bVQowrZN7YXm9MNa5Tiq4sK1MOYEuPjx+91ED3QJD7byrjge1l\nqFWqeRl4g07Nplo3m2rd9HlCvH2sm3dPdrP7SCclbgt3bS5my4r5W5trrgx6w/QOBen3hBnyRkjK\nCt5AjGg8yQt7W+n3hHFa9Vzs8nKxKzVD6NfvXhz796uPrEtLP6czrukikZT57rOnaevx8c3HNgHS\nlH2rKbaTTCq8cqCd1RWu9HR0iZBJYyu4mjlNA77Y7eOXbzRyodOL3azjK4+sZdUC3gC5ThOP3F7F\nAzvK2Xeml9cPd/L4iw384o0mblqVxw31uXNehXYuNLQO8/dPHqcoJ/WUS1668EeXBEnKCvvO9E66\n/5mWYUKRBCbD9TM7x4lX8wAAHfpJREFUO5GU+eELZznTMsyn762b9nprKkni5rX5/PrdFvo8IXKd\nc3+rEgjSwazr6Q77IvzFE4fQqFXcsbGIW9cVpl0sFEWhoc3Dm8e6ON44SFJWsJt1VBbayXeZsJl0\naNQS8YRMKJogFEkQjiaIxlOrh6okCa1WhUmvwWrS4bDoyLYbycsykWXTz1i8v/69vQyMRCb8zu00\nji1yOBkqSaI0z8I3H9s0birhcq2nGwjH+ddnT9PQ5uEjt1Zy79bSGe3v8Uf5o+/u5e4txXzktqoF\n6uXCkQkLUwrmnwVbrueFfW1EYkn+/DMbyHfNv19qOkiSRH1ZFvVlWQTCcU40DXKmZZiWHh/HGweR\nr3ieGPVqTHoNOq0atUpCUVJWaDiaGFsf6fJtS3OtVBc5qC9zUllov+ZSL4qi4PFHJ/2+It+GPxQn\nHJ249qbFqOUjt1by45fPcb7dw4qyrBmciaVHc5eX7/3mDN5glM/ev4Jtq2e+EKDTqmdtlYv3TvXw\n4I4KtBoRFxZkPrMS3XA0wb4zvWypcy+a4F6Jxahl2+r8sZtXlhVC0QTJpIxGo8Ko01yzEEUiKTMS\niDI4EqF3OERH//9r77yj4y7PfP/5Te+j0YxGo95sFcuSJdvY4IINgdBNCAQIISSbsKScDem52SQ3\nZ/fmnL3JuXt3k83ekCxLSAIpLMlSHIzpBhdc5C5bzVaxetf0Pr/7x1iDjYssW83S+znHxxpNe4/e\n3+/7Pu/zPO/z+Gjt8fDX99vZvKsdg1ZFbamD1UsyWVKQftZndQ/6iMQSxOIXti5MBjVFWWaOt49e\ncPyrlmTyh7da2NMwMG9FN5GQeXVPBy9ub8Nm1vL3D6+gKGtyXXTP5CMrcjnYMsTOo71srJ18E0GB\nYKa5LNHd09BPOBJn4/K5e5ErFNJZ7TUmQqVU4LDqcVj1lBfYUr8PhGI0dCTbdx9oHmTn0T4cVh1r\nlrr46DX56LVK/udTeyf8fLNBw6dvyWXHkd5U76UzMenVaNVKli/OoLlz7JLHfTUxNBbkP19poLlz\njJXlTj57a9kldeS9GBUFNoqyLGzZ3cHaKtecCagKBBfiskR3d30fWXYDxVdgoVwtGHQqVpQ5WVHm\nJBqLc7BliO2He9i8s52Xd7ajUZ+9pb1Y59hMm4GlRem88n4HCkli9RInbb1e+kYCqQXi4Y+WMjh2\ncd/v1YYsy7x7uIfn3j6BBHz+jgrWLHVNScBTkiTu3VDMP//pEC/taOe+jSVXPuB5RiyeYNgTwmHV\nTaruq2B6mLToDo0Fae5yc8/1xXMyR3Y6UauUrKrIZFVFJh19XnbW9/JmXddZr3GlG/AG3KnHkgSy\nDObTomo53VXUatLwt3dV8tzbLfTtDWDUJ6dCr1WRn3lpEfyrgYHRAL/d2kRDxygVBTb+5vZyHNap\nree6pDCddVVZbNndQaZNz/pl2VP6+VczwXCMH/22jr6RAIUuM3/38SrSLZfe5UAw9UxadN893IMk\nwZpK13SM56qhwGWmwGWmvdfLie4PRDYz3UBLlxu9VkkwHCfTZqBvJIDZcFpsjck2H+MibPrQ//OF\neCLB6/s6eWl7GwqFxCO3lLGhJnvaFupP31LKiDfE0682sq9xgJXlTrLtRiwmDSadGr1WueCMBEjm\nfvePBNi0tpA36jr5v88d4rufWp66Hjv6vOyq76OhY5RBd5BYLIFeqyLdrCUz3UCOw0hOholshwGn\nTS8s5SlgUqIbjcV591APNYsc2K1itQT4zkO1vFHXyfPvnASSli7AyjIni3Kt9I8E2bK7IyWqeq0S\ntUqB+bTFOx9F91S/l6e3NNLR76V2sYNP3Vw67daVWqXka59Yxuv7OnmzrpP6tpGznlcpJaxGLekW\nLQ6rDodVj9OmJzPdgCvdMK/+/uOEI3HeO9TDmioXH1tfTHm+jX/5r8P872cPsKrCyfH2UU50u1Ep\nJcry0igvSEOjUhIIxxh2h2jv81DXOMB4eFipkHCk6clI02G36LCZtFhMGsx6DWaDGqNOhUGnxqBT\noVEpFuQidylMSnS3HerBF4xy04rc6RrPVYdKqTirSd14kr7FqGF9dTbvHOhCIUlYTUmRlSSJTJsh\n1XNp/GY3zoObPhZPsHlnO1t2d2DUq/nyx5ayoixjxm4+lVLB7dcWcOvqfAZGgwyMBvD4o/iCUTyB\nCG5fmBFPmOZON7uP93NmRqHZoCbHYSTPaSY/00RJjhWnTY/iKhaOwyeHiMQSrF2azOgpL7DxzQeW\n8dQrDby8s51sh5EHP7KYdVWuCwY0w5E4PcN+eob89Jw+aTnkDtHR5z1v7GIcpULCqFNh1KuxGDTY\nrToKXGaqS+wL/iDLpER3y/sdlOennRXdF4BZr0n97EpPiqnx9EW8tiqLomxL6jHAtx6sSeWUpizd\nK4zizzbdQ36efPkYpwZ8XFfp4pM3LZ4161EhSbhOW7AXIhZPMDgWpH80SN9wgJ5hP92Dft491E0k\nlgCSQlyam8aiXCu3rMqfqeFPGYdPDGM1aig9oxFlWb6Nn3zxOiKxBFr1xJkeWo2SoizLedP6YvEE\nHn8EbyC5sPlDUfyhGIFQNHUYyReM4vFHONY+wq76Pv74Zgsl2RbWVmexssw5L3cYEzEp0d1Qk821\nlVMTdZ5PjF84KqVElt3IDctzWLYoeRxao1ZS6Dr7gh0PpgEUZ1v46DV5LLlK83JlWebdQz388a0W\ndBolX/l4FbWlGbM9rAlRKRVk2Y3JPPMzDrMlEjI9w35aezzUtw7T1uthf/Mgo94wmekGlpXYr5pA\n1PXLslhb5TonP12SpEsS3IlQKRWkW3SX/PcYHAuyv2mQHUd7+d3WJp55rYm8DBN5mSZyHCbynCYK\nXOZ5L8SXfQxY8AHD7hDffmIXFoOanz6+fso/f64eAw5H4vx2ayO7j/dTWZTOo3cuwXrGgjIfSCRk\nfvnyMeoaBwDItOm547pCaksdZ+1eLoeFegxYlmU6+r0cahniZLebrkE/bn8k9XxuhonlpQ6uqcgk\n226YNiOv9/Tiel2li70N/VhNWnIyjBh1KobdITLS9Jf13dN2DFjwAakg2VXuIpgMQ+4gP//LUboG\nfNyzvog71hRe1f7PC6FQSHz5Y0vxBaOc6HLz878c4ddbGig9YiXXaeKe64uvWHwXGpIkUeiynLUD\n9AWjnOr30tbrob51JJUHn27Rku80YzVpUCkVxBMy0ViydopEcidp0quxW3RkphvIzTCmMjMm4r/f\na2V/02CyfED7CFajllFfmNpFDnYf7+e21fnTUtNDiO4UoFErUKuShXMWAu19Hn76/BGisThfu3/Z\ngiitaNKrqVns4AefWUl92wgvvNdKc5cbk17NprVFFz1iDkmLuXfYT07G1Fu28wGTXp2qo3LHdYWM\n+cIcbBmisWP0tLvHnSxSpZBQKRWolMnaKZFoHF8wdladFbtFS3G2lcW5Vkrz0sh1ms5rEIx4krVS\n6poGAQiGAwDsPt4PwKt7TrGuOmvKSx0sDJWYZiQpeeR4IZRkPNY+wr//5SgmvZpvf7KWHMfcqL0x\nUxRlWSh0makosPHS9lZe3tnO5p3tVJXYefTOJWjVinOOIscTCXYf6+fpLY38+9fXo9PM/+vkSkkz\nabmhNocbLqGeRiIhM+YL0zucrJnS1uvhZI+bfaddQia9mtK8NJYWp1OcZcGVbmDIHWJgNEBuhomu\nQd85n6nTKIknZF7e2c69G4pJyODxRViUm2wyUNc4QH6mCedlZGKI2Z8iSvPSUmlg85WDzYM88VI9\nrnQD33ighjSTduI3zUMkSWJRjpX7b1zMc2+3kJVu5O2DXTz+s+0szrXyhU2V6DRKOgd8SJLEj39/\ngJwMI0qlhGYKAliCs1EopFRAr7Log4D0kDtIc+cYDR2jNHaMcaB58Jz33n5dJq/sCqFRK7CatKhV\nCk50uVlZ7kSlVLDtYDd1jQPkOU30DPv57K3lGHRqfvFiPVq1kie+uWHS4xWBtKuAuRBIq2sc4Fcv\nH6PAZebr9y8TfswPsf1wD0+/2ph6bLdoGfacXeozx2HkR4+uTj1eqIG02UCWZfpGAhw+McyW3R34\ngskc48fvq6ZvOIBCIfHRa/LwBaP84MndfPb2CoqyLDz7WhP7zyPW43zrwRoqCmxnBdwmmlchulcB\nsy26dY0D/PKlYxTnWPj6J5ahXyC+68nSPxLg7/9j9wWfr13s4Cv3VqceC9GdPT7347cB+KfHrr1o\nPrcsy3zvyT30ny5KNS7WZ7KxJptP31KWEt6J5lUcpBbQ0DHKsPv8HS8ONg/yq5ePUZwtBHciMtMN\n5DsvfLNlzHP309XEutN1tx0TlDOQJIl1VS7sFi0/enQ133ww2cPQlW7g25+s5YbaHLYd6qF/gq4w\nZyLuIAF/3nYChULiew+vOGubtL8paeGOuxSE4E7MNx6oYdQb5h9/s++c5zJtQnTnCp+9rZz7b1x0\n0W4w49x+bQG3rS5AoZCwGGw4rDrKC2xUFNgoz0/jhuU5k5pbYekKWLM0i5PdHho7Puhq8c7Bbn7x\nYj2FWWa+cX+NENxLxGLUUOAyc9OKXMyGs/3eGUJ05wyTaXIgSVIqJVCSJH742Wt44MZFqce5GaZJ\nHaIQd5KA9dVZbN3Twa82H+futYXUtyU7ZVSX2Pni3ZUixekyeOjmUpRKidf2dpJp01OUbaEk2zrb\nwxJMAVd6TFlYugI0aiXfeKAGtVLimdebaegY5b6NJTx+b7UQ3CtgvHZyXqaZx+6qFLsFASAsXcFp\nsuxGfvKlNQyOBbFbdJfk6xJcnDTTeOH6+VWPQnBlCNEVpFCcrvUrmBqspw+PWIToCs5AmDMCwTSR\nbkmKbrp5YZ7cE5wfYekKBNNEps3AV++rZkmhKPov+IAJRXei6kmC6Wc65kDM68xwsYLu0zUHYm5n\nl4n+/hMeAxYIBALB1CF8ugKBQDCDCNEVCASCGUSIrkAgEMwgQnQFAoFgBhGiKxAIBDOIEF2BQCCY\nQSbM0x0d9Ysq9LOMQiFhs01tA8gPz2s0luCHv97D+qpsbr+uYEq/S3B+pmNeQdyzs81E8zqh6CYS\nspjAeciH51WpkDBoVRxoHuTW1fmzODLBlSLu2bmNcC8IUizOSaO9z0M0Fp/toQgE8xYhuoIUi3Kt\nxOIybb3e2R6KQDBvEaIrSFGal4YENJ4anfC1AoHg8hCiK0hh0qvJzzRzvF2IrkAwXSwY0fUFoxxt\nHabp1Oic9FkGw7HZHgIAS4psnOx2E4rMjfEIBPONeV9PNxyJ8+KOVt7a30UsnozomvRq7riugJtW\n5qJUzP66c7x9hH/9r8P8w+dWkeOY+hSiybC0MJ1Xd5/iyMlhVlVkzupYBILpRJZlwtE4WrWSXfV9\npJm0KBQSeU4TSoWETqOcVJffS2Vei25z5xhPvXKcwbEQ66qyWFvlIhCO8faBbp57+wR7GwZ4bNOS\nWW1R0z3oY8fRXuIJmR1HeijKssyq2JXl27BbtLx3uEeILjDiCRGMxGd9MRRMPS9sb+WvuzpYUmij\nuXMMjUpJIBxjca6V1h4P1SV2HttUiVatPOe90ViC//PHg9y5ppDqEvukvndeim4iIfPSjjb+uqsd\nu1XH/3iolrL8D6r31yxysK9xgN9tbeIfnt7HwzeXsmapa1pWtQtxrH2E7kE/f3qrJfW71/Z2ApCR\npqcoyzJjYzkThUJi/bJsXtzeRueAjzynaVbGMVf41i92AfDr7944yyMRTBXxRAJvIMqB5iGAVAwj\nFk+61Fq63AAcbBnixe2t3Luh5JxGrW29Hk50u3lt7yk8/girKpxoziPO52Peia7bF+ZXLx+j8dQY\na6tcfOrm0nPaiEuSxKqKTEqyrTy5+RhPvdJAXeMAn7q5FEeafnrH54+w+1gfz719AgCDVkUgHEv9\nD/BGXSeP3VU5reO4GDcuz+XNui6eea2J7z68HMUMLkYCwWRJyDJef4QxXwRvIIIvFCUYihEIJ/8F\nw3ECoSihSBxfMIo3EGFwLATAx68vZvuRHrRqFRUFNhIJmbcOdLGxJpt4Qua1vZ3sPNrHAzcuon80\nwB3XFqLVKGnpGgOgoWOUho5RyvLTyLhE7ZhXotvcOcYTL9UTDMX43O0VrKvOuujr7VYd33loOW/U\ndfLC9la+9+QeNtZmc8s1+dituikbVzAco+nUGG29Hl7f10k4Gqc8P43qEgfLyzIw6lR0D/p59vUm\nFucmDyjMJia9mgduXMRTrzTw3qEeNtbmTMnnxhMJBkaD9I8EGfaE8AYiBMIxYrEEMqdPxelUpFt0\n5DlNFGSaZ7UV/JgvnPo5Eo1PaMn4glHiCRmrUUM8keA/Xj7OzSvzWJRrne6hLijCkTiHTw5xrG2E\ntl4v/aMBorHEeV+rVEjotSoMOhU6tRKjXk3sDCOsqtjOmqUuANItOhIJmXSrlmuXuDDoVOQ6Tfzp\nzRaeeqUBgDfqurhpRS6dAz40KgWRWILqEvslCy5MUnQPtQxxvGOEDTU5c87Htf1ID7/b2oTdquMb\n99dc8rZYoZC4ZVU+15Q7eWF7K2/v7+at/V1UFdtZVeGkusSBSa++rDH1DvvZVd/HvsYBBkaDSMCy\nRQ7uWFNAoct8VhCvNC+N//X51ciyTHwOHOFcs9TFrvo+nt92guoSO+mWyS9C0ViC5q4xjreN0NLl\npqPfe9bNIQFajRKNSgGSRDyeIBCOMd5ASq9VcU25k5tX5pKTMTNujlg8QXufl131fWw72J36vccf\nmXAX9PSWBjz+CN9/ZCX9I0H2NQ7gSNPNSdF1+8K8sL2V1h4PmTYD65dlU1WcPqMutsniD0V5dfcp\n3jnYTfD07rA4x0JlkQ2HVU+aSYvZoMakV2PQqTBoVRdcKPc1DrDjSC95maazdnIKhcRtqz+oPXLz\nyjxautwcaBrkM7eVceTkMK+834EkwfrqbGoWO6gomFzj0Ql7pA0P+5JnuWWZr/98B75AFINOxfcf\nWYkrffYCUGfy6u4Ont92kspCG1/62FIMussTSYAhd5B3D/Wwq76PUW8YCch1mijJtpCXaSbbbsBu\n1ZFm0p7Xz9M54KN/JMC2Qz0EwzEUkkS6RctDN5VSlGXGapp8O26FQsJun1rRGZ/XizEwGuCHv95L\naV4aX/vEsktyM8TiCerbRth7vJ9DJ4YIReIoFRJFWRaKsy3kOU247AYcFh1mg+acJn6JhMyIN0R7\nr5eDLUPsbxogEkuwqsLJfRtLcFin3v0TjsY5enKY/c2D1LcO4w+dmy73/UdW8O6hHioL01m9JBNZ\nluke8pN7ejGQZZmv/tsOQpE4v/zmBvY3D/LEi/WsqnDyxbuXAklL/8yFdjrmFSae23A0zo+fPUD3\nkJ+KAhun+r24/RFKsi18fEMJ5flpc0589zUO8OzrTfgCUVaWO7lxeQ6Lc9NmpAlnOBJnyB0kJ8NE\nQpb587aTRKJxNq0twmLUnPP6ieb1kkUXkjfUiCfEP/6mjkKXmW89WDOrk5OQZf78zkm27j3Fqgon\nj965ZMq2owlZpr3XS33bMM2dY7T1es/JpdWqlahVCmRZJiGfnWtbs8jB4lwra6uyzjsxk2G2RBfg\nnQNdPPN6M3etKeSe64sv+LreYT/bD/eyq74XTyCKSa+mdrGD2tIMKvJtaDWXFmT4ML5glNf2nuKN\nfckg493rivjoqrwrTvVLyDJNp8bYdbSXuuZBwpE4ZoOa6mI7NYsdZDuMdA/6eedgNw0do/ztXUt4\ncvNxVpZl8OV7qmg6NcpP/nCQHzyykuJsC0PuIN954n0AHFYdQ+6kz7A428IPHlnJzqO9/OmtFn72\n1fWpxWu2RPevu9r57/daefy+amoWOYjFE+w42svmne2MesMUZVlYvyyL2kWOyzISppJAKMbv32ji\n/WP9FGWZ+cyt5eRnmmd1TBMx0bxOyr2gUipw2gzct6GYZ15vZm/DAKuXXDitKBiOsb9pkOMdI/QO\nB/AHo8hycktp1quxmjSkm3XYzFrSLVpsZh1pJg0Wo2ZC8ewd9vOHN5o51j7KDctz+NRNpVO66ikk\nieLspHUGSUtm2BNK+SPHfGECoRjRWAJJAhnIthtZVmLHbNBctsjMNTbW5tDW62XzrnYCoRj3XF+M\nQZe8bNy+MAdPDPF+fR8tXW6UConqEjvrqrOoKrZPyQJo0qu5d0MJG2ty+MObzTy/7SR7jvfzmdvK\nLyvDw+2PsONID9sP9zIwFkSvVbKq3MnqJZmU5aedJeZZdiPF2Ra+9YtdHG8bAaBz0M8P/nMPmbak\nxd095MOkV/Hs682p940L7vjPwXCM57edJMdhZLbtx2gswVv7u6gsSqdmkQNI3tcba3JYu9TFjiO9\nvLm/i99tbeJ3NOFKN1DgMpOVbsCRpkvdo+Nb+AstfrIsE4snCEXiRGMJlAoJo159yddEPJFgX+MA\nz79zkjFfmE1rC7lrbeGcyKu/UiZl6Y6TSMj86Ld1eAIRfvT51ambcJxINM7WPafYuvcUoUgcq1FD\nntOE2aAGJMLRON5ABLcvwog3TCx+rhPcpE/6Zoz6pANcrVIiScmLZtgTonc4gEat4MGPLGbDsuw5\ntx2aSmbT0oXkfP/prRbe3N+FSqkg06YnGIkx4kkGmrLsBtZWZbF2qWvaLaP9TQM8+3ozHn+E62uy\nuXtdEWkTfGc8keBY2wjbD/dy6MQQ8YRMWV4a1y/LZnlZxnnzMMeJxhJ84Z+3YTVqcPsj5zx/55oC\nTvX7OHJy+IKfkec00TXg43ufXkFJzgf+3dmwdPc3DfL/XjjK1z6x7IL5pbIs0zngo75thBNdbjoH\nfAx7Qud9rVqlQKNSoFRIIEkkEkmxjUQTJD4kLRLgTDdQ6DJTkGnGadNj0KpQKCQisTi+QJTBsSCd\ng36aT43iCUTJc5r4zK3lKePnamBK3Qtn0trj4Z+e2c/K8gwe21SZ2jI1tI/w261NDIwFWVGawS2r\n8ynJtlxQFGVZxhuMMuoJM+oNM+YL4/ZH8PgjeINRgqEowdOrpSzLqFUKrEYti3KtrJuCrfvVwGyL\n7jjtfR72HO9ncCyEVq0g12liaZGd3AzjjC56gVCMF3e08s6BbpQKiWsrXVxXmUlxtgW1Kimg3kCE\nk90ejrQOc6BpAE8gitmgZs1SF9cvyybLfumB4K/89L3z+nkBVpY7aWgfwR+KcdeaQjbvagcgx2HE\nbFDTeCqZWvTFuyvPOWwyG6L7m1cb2Nc4wM8eXz+pnUg0FmfIHWLMG8YdiOALRAmEYoSicaLRBPFE\nMgNFoZBQKRRo1Ap0GmXKBZdIyIz6InQP+mjv8zLqDV/wuxxWHSU5VlaVO1m22HHVpSxOqXvhTIqz\nLdxzfRF/ebeVWFxmRVkGB5oH2d80iNOm59ufrL2kqJ4kSVgMGiwGDQWuue2rWegUuiwUumbf4jDo\nVDx0UykfWZHLlvc72H2sj/cO9yBBMiXo9LYWQKNWUF1sZ/USF8sWXZ7LY1y/JAk+bKLUNQ4A8KWP\nLeWacidKpYRWreSWVfk0d47x498fAJgTp/tkWeZo6wiVhemT/juoVUqy7MZJLVYXwxeMMuQOEgzF\nSABqpQKTXo3dops3rrkLcUV5urdfm0yt2LyznQPNgxi0KjatLeS2awsuumUTCKaCTJuBv7m9gk/e\ntJiG9lE6+r14g1GUCgm7RUehy0xxthW16sr8gGV5aRw6McR9G0p4ftvJc55XKRVUFiYNjE1ri1K/\nz80wYjVpePjmsiv6/qmiZ8jPqDdMVfHkjq1OB+Puw4XIFYmuJEnccV0hN9TmMuYL47DqLvkonEAw\nVeg0KmpLM6gtzZiWz3/0ziVA0tJ9fttJSnIsnOz2YDNrGfWGuaY847xpigadmn/9u3XTMqbLYbw4\n/VzMG15ITMmJNINOdU4wTSCYL5x5bX9hUyWLc6209XoxG9Q88VI9d68rusi75w4dfV60GiWZcyS/\nfqEilFIgmATjKZLjJ/TmkiU7Ee39HgqcpqsuMDXfuPqT3gQCwYTEEwk6+30UzIFA6EJHiK5AsAAY\nGA0SiSXIz1zYpTrnAkJ0BYIFQM9QAIDsOVaoaiEiRFcgWAD0DvsB5kyRqoWMEF2BYAHQM+zHbtGi\n14rY+WwjRFcgWAD0DgWm7DSZ4MqYcNmbiXqVgoszHXMg5nX2ma45OKdGsSwTkxOU5tvEvM8AE/2N\nJyx4IxAIBIKpQ7gXBAKBYAYRoisQCAQziBBdgUAgmEGE6AoEAsEMIkRXIBAIZhAhugKBQDCD/H8a\nVXv5+95sEAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "xavier tanh\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "12298841899f46e39b668d2a9f5a291f",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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7ZLgpNjYWarUagtD1j0MQBNTW1iI2Ntbiuri4OGRkZCAoKAghISFIT09HUVGR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\nQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.88\n",
            "Validation accuracy 0.88\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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AmKeStrVUueQCaYNWFz9+5iytPVY+sC2HO3bkLnh9VJkgUJQVS1FWLNfNINn/SqB30EF5\nfT8f2J4zJ77QhBgt5VOsARCsMjVadINCa3VOILr28OyGpFgtRp2SN463cLauj+88ugWvT+Rnz5eT\nGq/nxs2ZvHiogSPnuwCGa/4KfOFDq2nustA9YMfq8HC2vp/d69O5aUtAmJLjdFQ0DjBkc2Gxe2jv\nDVT3qhn22Vc2m8hKMkS0yBeD23fkMmh18frxFt480YooBqq5bStJ4cM3Fs37fXj3tXkcv9CDz++n\na8DOHC5mW1AuKUt3wOzkB0+dZsjq5vP3rmF1/uIHkCTBHZ8Dp9sRhECQci5IHq4B4HB50aonvgzd\nXj9ymTDGQjSEit54IEL9VKvDg16jCCXCG3Wq0Mqkzn47DR1mHG4v5xsHON84wFunAiuqbtqSRVKs\nlprWQbauTGFVXjyrhmMEoihS2zYUtuhg17p0dq1LDwnX429U4/X5OXq+C5VShtvj5+o1aUvq+pIJ\nAh+9uZhtJamcbxxALhNYnR9P7ogVbPPJrVtzuHVrDr944VwgrbNraqvklhrzGkh7en8t165Nm5Np\n8qDVxQ+eOo3F7uZL96+9ZP2cVwIer5/D5Z2sK5x6NbHJSB4ujNJjckyYM2u2uWntsY7r259KTV2r\n3Y1Rr8Lj9eP2+onSKbl5Sxbvnm7H6xP57nDtVZVCxjc/uonTtb043T4+sC0HlVLOznEeMoIgRFws\nIAgCAvDRm5fj8/vJSDSwIieWw+WdbCtZmoG2ZZkxky5+mE8eubUYn1/k8z85DAKXnMU7b+4Fv1/k\n3dPt+EWRB69bNu0DG0mPyc6Pny1nyObmy/etnVUkXGL+Ka3uwerwsHPd3Fi5EJjmQ6AI+kSi+/T+\nWs419BOlG+s+CNbUtdoji67F7iFKq8Tt8dFvdmHUq9i+KpW7d+bzblk771d00dBhJj1RT1qCftYZ\nDSORy2Qh98ND11/+izFmSnCmo9cq0WuVdA/YEZhZzYXFwOcXp5WCOGXRlckE8lKN1LZObfngeIii\nyMGzHfz1nToUMoEv3LtGEtxLgANnOkiK0VKcEzv5xlMkaOl2T7LUs7k7MOUc7ZuFi5auZSJL1+Eh\nOU6Hy+un3+wK5frKBIE9GzK4dm0afzvcyIaimbevkZgbPn5rMX5R5GfPnwsURZpG+c/Fxun2YdBO\nTXSnFRFZlhlDS48ltGxvOticHn72/Dkef6OavFQj//bRTYs6pZGYGp39NmpaB7l2bdqcBoHUw4W1\newYi10r1eH10D0QWZa1agUwQsDoir2CyDPdQe/iGIrKSDGQlh1ucCrmMe3bmL5gfUyIyawoSKM6O\nRaOSkz/sL59t/zv5cDAw+FMhD/xUKQPSp1LIxiy6mQ7BW2I6ft1pi64oMuViGUH6hhz8xxOlnGvo\n54E9hXzp/rUz7tgpsbAcPNOBXCawfRpLQadKSpyOrglEt6PPPmF9VpkgYNAqIroXRFHEavcQpVOS\nl2bkW49snjRoJ7G4aFQK/vuz20OurGDHC/kUMimCRkGwCJNWrQjNhoKr6kI/dYGf0QYVGpUcpUI2\naXdquUwIiXXwOooaHsc5jQyGaYlu0BponEaUsXfQwfefLGPQ6ubL96/l+k2ZSyptRiIyHm8g+r6u\nMGHaS0GnQmq8no5+O2IEYR2ZPB9p/wadKqJ7wTZc5S1K6hZ8SaFRKSjKiuHvbljGquGMpmCnkPG0\nIyiEwXq/Bq0yJKJBcR3zc/h6itarUSnlqJXykFWtVQfENyjeQV+tQatEp1YglwlEjxLvebN0dRoF\nSTFaWrqnJroDZic/fOo0TrePrzywjqKsufMJSsw/ZTW9WB2eOUsTG01qvA6Hy8uQbXz3QGuPFYVc\nxi+/eA0/fGzruNsYtMqIhcxPVnYDXBEVxS435DIZu9dnoBu2KIN52Fq1POQOCFqm+uH3gt1EDDol\n6hFCKhCwaOFi3Y+kWC1ymUBempH0BD0qpSw0TnCfQfENBnENOiVqlQK1Uh4S7ZiowM9g+dGpMO25\nVlZKFE2dkxegHrK5+eHTZ7A5PfzTA+ukC/8S5OCZdhKiNXMaQBtJMFOgs8827sqwymYThRMUN4KA\n6HaP00NLFEVeO9ZCfrpRih1cwug1AdGM0inpGgjEAuQyAbfXj06jwOn2oVMrMFlcIWs41qDG6fKS\nGKMlNkrN+mWJLMuMISclil3rAsWwCjKi2bUuncKMwLXxvSfLiDOqae62oFUrARdatYJBqxu9JtDT\nz6hT4XB5EUUlycOifdPmLFblxpOXNvWEgGmLbnaygVNVPdidnoirgMx2Nz96+jQmi5Mv3beWnBQp\nSHGp0dlvo6plkLuvzZs3d1Aw37uj305xTninAbM9kJ/7wWvyJhzDoFVS3z7W0jXb3PSbndy4OXNJ\nLUiQmB5bV6aQEqfj3dPtKOSy0D+z3TPsV3WhHRbbuCg1rQoZ9+0pwOX2kRqvRxAuugeCxdzXFAQe\n8EHBBfjCh9bg94scq+gOuSmCP6N0SgQB7ttdgMfrD9XwiB42FFbkTK1LRpAZiG7AYm3ptrI8e6wF\nZLK4+O9nztBjcvD5e1aH/WESSxO704tKKQvLM3y3rB25TGDH6rR522+MQYVWLaejzzbmvarmQEnP\nyS7oKF2ggI0oimHiGqxgligFbC9p1Co5y7Njee9cJ0qFgFIuQz6cgRAMZsUMT/Vv3JLFnVfnhdIR\np7WfYf/twzcsQ62SU9M6SKxBjQBsWZFMYox2TObLTJm26AafFq29Y0W3pdvCz54vx+r08o/3rB5j\nvUgsTX741GkKM6J58PrAoheHy8t75zrZXJwUChjMB4IgkBavp7N/rOi2dFuRywSyUyYuNmTQKvH5\nRRyjit4ERTchenZVsiSWBlq1Ao1KgXy4O4xcJpBg1GCN83Ddxkx2r88gfxpT/EjsWp8RWo68uTiZ\n27blkJUcxTVr5s74mFR0Rxe9iIlSk5tmZGi4rzwE/GfHLvTw8pFG4qK1fPG+5aQnXtoVtZYS81F4\nZOSYhZkxgRYpQiA6fKq6F6NexS1bc+a96ElRdixVzaYx+3F5/RRlxYxp0TOalHgdSbFa7G4fBt3F\nB4TT7SUpVktSnG7BCyhNlfk6rqX6986GO67OZdf6dF4+0oRSLuD0BNwHn7qzZM73lZ0axd/fvpJ1\nyxJnVFp2su9fECPl60hISEhIzDmLX9hTQkJC4gpCEl0JCQmJBUQSXQkJCYkFRBJdCQkJiQVEEl0J\nCQmJBUQSXQkJCYkFRBJdCQkJiQVk0sURJpMNv3/+Unnbeq389LlyHriukHWF4dX73yvv5OUjjXz9\n4Q3EGNRUNA3wp9erANhcnMQ9OwuAQKHqb//fSQB+8Ni20Od//OxZjHoVj9xSHHrt7VOt7DvZijCq\nF9PNW7J4/XgLAHddk8+Lh+onPXadRondeXHd/327C0iK1ZGRqOdsXT/7TrXSN+jgtm057D3aFNpO\npZTjnqD+5mfuWhVWIEgmE4iNndvFJvN9XiUmZz7OK0jndrGZ7LxOKrp+vzivJ7C8rj/QnDA5asx+\nUuN19JgcVLcMsml5Eq+934zH62dVXhxvHG9hz4ZMovUqHE4PPcNtX0aO0dxlYWVOXNhru9dnYLF7\neOm9xrB9mSyu0BhDFmfo/xOhVrnD6mj+7PlzQEA0f/HiudDrPSZ72HhymYBvgu/U7vTM+00z3+dV\nYvGQzu3SZtHdC1UtJlLidOOW9stMMqBUyKhtHaSt10pF4wDXrk3jhk1ZeH0i75/vAgLFtkcjiiIW\nu5so/dhKaMGamiNxey6O4fGNHW88PJ7xt3v1/aaw362O8PZGEwnuVN6XkJC4dFlU0fX5/dS2DbI8\na/xKZAq5jFV58Rw408ETb1ajUcnZvT6DtAQ9+elGDpd3IIriuKLrcPnw+kSitGMLtsQbxwq8a8R0\nf7zxxmN0Kxn1cFHlplGdNSIV2Y44riS643KhaYAf/KWMg2faF/tQJCRmzKKKbl3bEA6Xb8LyfXde\nnYvX56e2bYibt2SFWmpctSKFzn47vYOOcUXSYg90IzCOY+nGjVN5yj0D0R1NJLG0Oacnul5JdMfg\nF0V++eJ56tqHePyNas439i/2IUlIzIhF7dJXVtOHQi6jJC+y6GYkGviHu1ejVMhYMaKDQWFGoIxb\nQ4c5VEx4JMG+WYZxLN24qLGi6xohtO65Fl3H9LonS5buWDr7bNhdXj58YxEvHWnkwOkOSnLjF/uw\nJCSmzaJZun5RpKyml5U5sRO2YwFYW5jAyty4sCLV6Yl61Eo5pTW9NI7TPsg53CZeN073V6VCRkF6\neO3NubB0I/lip2vpSqI7loaOwDkuyophU1ES5fX9OFxTe5jZnB5efb8Jj9eHdZquHgmJuWbRRPdC\n0wD9Ziebi5Nn9Hm5TEZijIbS6l6eOxBI7xrZVsY5nFUQqa3y1x/ewLrChNDv4aI79SZzU2G6Iu71\nz0z0L2fqO8zoNQqS43RsKk7C6/NzprZv0s+JosgP/nKa5w828OuXKviHnxzm9WPNC3DEEhLjs2ii\n+05pO1E6JRuXJ814jNGCrZBfFN1gYEw9QS/7ke/NJJA2VbxTzIYIIlm6Y2nutpCTEoVMEMhPjyY2\nSs3Jqp5JP9fUZaG1J9DK/fSwSD97oJ5zDf34pIebxCKwKKJb2zbImbo+dq/PmFFl9iC3bs3m9u05\nod9H9vgKWroTia5qRFeCkSljXt/MRW+89jZTTUELIqWMjcVkcRE/HACVCQIbi5I439iP3Tmxi6G6\nZTDs98KMaOKMav7nmbN87TfH6BuaPB9bQmIuWXDRdbl9PP5mNbFRam7anDWrsQRBIDbqYhBNoRgp\nuoGbUaOcwNJVjm/pumfhXhgv39g3TRFfDNH1iyInKrvpH+4ttpTw+f1YbG6i9Re/203Lk/D6xEmz\nGOrah0iM0VA03IY9N9XIY3eWcPv2HOxOL99/soxuk52WbktE37vP78dkcY07AxlvFiPNVCQmYkGz\nF1xuH7966TwdfTa+cO+aCa3QqRJMIQNQjnIvyARhQktarbr43lwE0gCiDSroDn9tuiK6GDft429U\ncehsJyqFjC8/sG5MoHExMds8iAS6BwfJSzOi1yg43zAQMS4giiJ17UOszIlDrZJT3TpIeqKe/LRo\n8tOiWVeYyH/99Qzff7KMQasblVLGg9ctozg7lsPlHaxflohOo+SJN6qoaDKxuTiJR24pRqmQMWRz\n09Zr5b//epb79xTS0WcjPVFPbdsQp2t6WVuQwCfvWInZ5kavVdLZbyMrKeqy7F8mMT3mTHS9Pj9u\njx+lQjZG6OxOD2fr+nnpSCO9gw4evrGIkry5SfcZKbph7gWXD7VKHpbxMJow98IIoZ2N6I4Uhpmy\n0JZuffsQh852smt9OmXVvbxwsJ6vPLh+QY9hIsy2QM71yNRAmUygOCeO8439Y9qvQ+B6/PVLFZht\nblbkxIYyHTISL3YXzk6J4pN3rOS/nj5DRqIBo17J/71ehVGvwmxzs/doMwq5gNcnEm8M+JBPVvaw\nblkiZTW9IVfS0/trUSlluD1+BGDj8iROVvXwlV8dZdDqDo2Rn2bkqw+tD7tOJa48Ziy6oihS0zrI\n4fJOKptNmCyui4PKZeg1ChRyGW6vD4s9MG1Ljdfx5fvWzmlrdv0I0R1pRTg9voiZC0FGuhdG+nGn\n64MdSew4OcDTZbruiNny1qlWtGoF9+7MJzlWx9P7a6lvHyJ/CVi7dqc30KmY4VnECFblxnGqqoeG\nTvOY9tsvHGygrKaXe3fms7UkBbvTi88vhhUSAliZE8c/P7SelDgdeq2C379aybGKbu7dlY9Bo+SF\nww24PX6+8KG1fPP3J/ATSHUEGBp+GKwtSOAjNxXR0mPF7xdZU5DA5upeDpxu46oVKVgdHtIT9WEd\ntCWWLl6ff14fjDMS3Z5BB39+s5rzjQPo1ApK8uJISwjkzXq8fuxOL3aXF6/Pj0ohIz5aQ2FGDAUZ\n0WFpXXPBSEt35Kpcl9sXJqrjoVJe/GJH+uYi1VSYCnFGNY/dWcJL7zXS0Web0RijlxfPN34Rbt+e\ng0al4OrVqTx/sJ6jFV1LQnT/7Q8n6DcH/Myjg5Qblyfx9Dt1vHm8hU/ftSr0+pDVxb6TrVyzJpWb\nr8oGAtfJjRFiCMsyLy5Df/S2Fdy+PZeUOB0Axdmx2F1e0hL0fOm+NdS2D/G3wxeLJW1Zkcwnb18J\nwKoRlviGokQ2FIVXzbuSsG0OHHcAACAASURBVDo8VLcEjDGNSsGq/Phxg8xT4b3yTt461Upagp7V\nefFctTJ5whnsbDDb3fzzr9/n0dtWsH7Z/Jy/aYluTesg5fX9vF3aikwQuH93ATvXpaOaRNzmk3DR\nvShWTvf0LN2RzMbSlcsENi1P4sDp9jDRDU4/p4JvFvufCZ++syT0f61awdqCBE5W9vDAnsJFnQq3\n9lhDgguEBdIgcKy716fz2vvNdA/YSR4WyvcruvGLYkSRnQiZIIQEFyAhRhv6f3FOHHnp0TR3WbA4\nPNS1DZGROPelGS9lRFFk79Em9g5XBAyiVSt47I6V03Yr1rcP8ac3qoiP1lDTOsjxC9109Nu4YVMm\nWnVgNu0XxTkx5oZsbioa+3G6fVQ0Dsyb6E75jhJFkZ8+V85rx5pZnRfPdx7dwg2bsxZVcCHcjzvS\nPnS5vTMW3Ylq3U5GcPo42q890n88GYudMrZ9VWBKfKyie/KN54neQUdYeUwY+50CXLcxE7lcxitH\nm3B5fLxwqJ4XDjWQn24kNX7uBVGtlPO5u1dz3YYMIFAJT+IiLxxq4MXDjawtSODrD2/gJ/+wg3/7\n6CbijRp+9VIFPYNTT9Ebsrn5+YvniDOq+dePbOSHj21j+6oUXnu/mc//9D1ePNxAz6CDx/7rIPUd\nQ5OO19ZjDc0ig5Z4EIfLy7/89hi/21sJQFPX2FWuc8WURVcQBH7w2DZ+/o9X8+m7VhE3TnnExSbM\n0vVMxb0wH5Zu4CtVjrIQp5OPvNDuhdGsyosnOzmKl480hlLvFhJRFPnTG1VY7B6+/ncbJtw2Wq/i\n6jWpHD3fxT/98ih7jzazKi+OT3xg5bwe4/pliXzs5uWszJ27+MRc4/H6FzQTpq59iNfeb2bH6lQ+\ndcdKCtKjidKpyE6J4h/uDrh//vBqZej6HjA7qWgaiDje/tI2zDY3n/3gavQaJTKZwAN7CjEOuynO\n1vVT3zaEx+sfk48N8MqRRg6cDlSkq2ga4Jt/OMHBMx30mOz8dX8tP3jqNGabm3MN/Xzn8VPYRuR8\nt/ZYqe8Y4pUjjZyo7OYPr1WG9OWdsjaqW0zUtA7idHupax+a1j07LfeCTrOo9XEmZbRPVzNO3YWR\nRHQvzCJ7ITjNGWvpTl10FzqQNhpBELhvdwE/fPo0v3zxPH9/+8owN858c7aunwtNJh68rpCCjGg+\ndcfKCc/JA3sKWZ4Vy1/fqSVGruLR21agneTczxaFXMbVa9LmdR+z5an9tVS3mPjnh9YTpZt9Vs1k\nvHCwHqNexQN7Csf4XBNitDywp5A/vFbJ/tI2rt+Yyb/87jhOt4/ff3XXmO19fj/vlXewKi8+bDah\n0yj5949v5pl36jhd20drb2C1YdvwqsMg3SY7f3uvEZ1agV8UeftUGwBPvV0bFr85cq6TFw414POL\nZCUbaOm2kp0cRXO3he8+Xho25oZliZisLv68rwaNSo7T7SM2So3J4uK7n9gy5ZnV0lbRaTJSdJ3T\nDKRFGme6yIfdCwrFaEv30nEvACzPjuUjNy3niTer+cqvjrKmIIHs5CgSojVE6ZToNEp0agV6rWLS\ngkXTweP18/Q7taTG69i5Lh0Yu9x7NAq5jE3LkyjJjcPj9c+74F4qbF2ZzJFznfzxtSr+4Z7V87qv\nurYhqloGuX93QcTvf/uqFE5V9/D8gXr0GkVo1ajN6R3zUK9oNDFodfPQ9WMfbEadioKMaI6e7+Js\nXWBpd2uvldO1vbz6fjO5qUb2l7aFxv7zvhr0GgVr8uM5W98fatWlkMt49kA9cpnAp+8sYVlmTCj2\n8rPny1mWFYPJ7OJ4ZTeiCD95rhwIpIUOWt3IZQImi4vi7NiwOMBkXBZX548+vY3f7b0Q5i+absrY\naFQK2bglHhOiNXz2g6v4wV9OYx+nylUkn+603AtLQHQBrlmTRl6qkX0nWznf2M/xC+P7eLVqOekJ\nBkpy47h6TVrYKsHpsu9kCz0mB1/80JppB/G0agXame/6sqMwI4bbt+fw/MEG6tqGKMiYv2yUt0tb\n0akVXLs2PeI2giDw0ZuX84sXzoV8pxDINhktuicru9GqFazOHz/wlpUUSP3r7LcD0NVvZ+/RZho7\nzTR0mMlJiWL7qlQOnukgKVbLp+8qwe3x8dqxZq7bmInX6+eN4y28XdrGA9cVhtWA0ajgGx/eCAQs\n7juvyWP/qTZOVnXzdzcUUZwdy5naPtIT9Ryv7Gbn2vRpZVNcFqIbZ9SQEKOlO9gnTRRxT8HS1WkU\nCIQH4IKolPKQ6GrVchyuwFNZIZeRlRx5ZVHQ0h3t05XLhDG90YqzY7E6PKGCLEGWgqUbJCPJwCO3\nBhp72pweBswuzHY3dqcXh8uLzRF4ranLzEvvNfLqsWY+sC2Hm7ZkTVs0O/psvHKkiQ3LEuds8cyV\nznUbMtl3spU3TrTw2YxVk39gBgxaXZRW97JnQ8akq0xjDGq+8uB6PvmjAxc/b3OTPiJRwOP1U1bb\nx/rChIjGSrC0q8vjIycliqYuC42dZuKManx+kS/etxaDVsnOdWmhOItGpeCD1+SHxrh3VwG378id\n0HUml8lIitFy354C7ttdELrvt5akAJCVHBXxs5G4LEQXCIjnsF/A7fEhAhr1xBdAlE7F1x7ewB9e\nraRrwB723siT/c2PbGLfyVbePd0eElV5BNGNZOnKZAJyebjofvzWYl59v3lJi+5I9Bolek3kC7Rn\n0MFz79bxwqEGTlb18OEbi6ac69s/5OTHz55Fo1bw4PXL5uqQr3jUKjlbV6awv7QNq8MzL775g2c6\n8PlFdq2PbOWORKmQ8Y/3ruap/XV0D9gZsrrC3q9rG8Th8rJ+gjxntVLOtx7ZxPEL3exYlcqLhxo4\n1zjANx7eiEGrCLnzgoIb6TimOgOVCUJAZOaAy2Y9oiAIIYs12KF3omI3QQrSo8e1iEeejKRYbchP\nFRTb6Vq6MmHsBRC0fkezVNwL0yUpRsun71rFZ+4qwerw8N0nSvnTG1VhberHo73Pxn8+WYrN6eHz\n96yelXtCYizbSlLw+UVOVs59CqDX5+fgmXZK8uJIjp26X3N1fgLf/EhgCj9odYe9V9liQiYILM+K\nHe+jIZJjddy+PZc4o4aP37aCH39uB7FR6mnFTxaDy0Z0ZcLFAJhzOM92qjnEQS0cOR0OiqZcJiAI\nQkhkZTO0dOUyIazeb3Db8cT7Uq/zuqEoKZDHvSmTw2c7+cbvjnP0fOe4D5Oa1kG+9+dSfD6Rrz64\nntxU4yIc8eVNZpKBpFgtZ+vnvq/cyaoeBq1udq/PmPZntWoFapWcwVGWbmWzidzUqMs2IHrZiC6C\nEHIvBJfxTubTDRJM8xopinKZgEwQxrgT5PKJRTdS9oJMJhvzGfmwy2E0S9W9MB20agX37ynkXz+y\nkRiDmt/treTrvz3Gu2VtON1e/H6Rd8ra+NHTpzHoVHz94Q0z8o9JTI4gCKzKjaeq2TSnXVFEUeT1\nYy2B5bkRAl6TEaNXMTTC0nW4vDR2WFiePbGVeylz2TxKhBGWbjAANlV/jRAUSrkMCFyUQSs0KIoh\nC1eY2L0QKU93PPeC7DJzL4xHdkoU//qRjZRV9/L68Wae2FfDU/vrUCtl2JxeVubG8ckFzgO+EinJ\ni2N/WRs1rUNztqDjZFUPbb1WPn5r8YyX4UYb1GE+3QtNJvyiSMkSXnQyWy4f0eViIC34NJ+Wk5xh\nVwKBbAa5XBj2uV50MwDI5eG/jyaiT3cc98LI8UdyOVi6I5EJAhuXJ7GhKJH6djNlNb3YXV5KcuPY\nUJQ4b8VLJC6yPCsWuUygstk0J6Lr8fp4/mA9GYl6tq5MmfE4sVFq6tsvLuE919CPRiVfEsWW5ovL\nR3RH3LjB1UtTrXcQ1M+gdevzi8iH/bihwNkoCzeipTuBT1c+jhCP79O9vEQ3iCAIFGREz2u+qMT4\nqFVyclKiqGkbu1x2JrxxvIXeQSdfun/trMpVZiUbOH6hG4vdjUGr5HxjPyty4i7rmsOTiu6lUv/T\naFARH60ddgnISIrVotcqp3T88dEakmK1xBrUaNRyfD6R+GgNbp+ISiFDJhMw6lUkxWqJj9Ygkwkk\nxmhDK2pGolbJkckEooa3DxJr1OD1iWFLEBVyGdGjtgMw6lVhxz0f5+BSOa+XM/N1DiKNu6EoicPl\ngfSu2fQm7Oy3c6yyhz0bMlg1y3zqFTlxJMV20N5vD9Xg3r4q5ZK+Pic7dkEUF7m6ioSEhMQVxOVr\nw0tISEgsQSTRlZCQkFhAJNGVkJCQWEAk0ZWQkJBYQCTRlZCQkFhAJNGVkJCQWEAmzdM1mWwzXpba\n2mPlFy+cY21hAvfvKZzRGNPlWEU3Lxyq5+sPB3pr/ccTpdx5dR7bSma+amaxkckEYmPntsnibM5r\nELvTy2/3XqBrwMZjd5RMuXZC35CDH/7lNLs2ZHDTDDr2Xi7Mx3mFuTm3EjNnsvM6qej6/eKMT2B6\ngp7NxUm8fKSJ/LRoNkxQH3OuaO2x0D/kxKBRIggBYahsGuCqFRO3fLnSmM15BegasPOz58vpHXTw\nmbtWkZFomPJ4cVEaMhINvHS4kW0rU6S6C3PMbM+txPwy7+6F27blkJVs4PE3qzDb3ZN/YJb0m53E\nRqmRDZdkzEwy0DKqSLjE7DhV1cO3/3QSi93Dl+5by5qChGmPcefVuTjdXl56r3HMez6/H7NtZtfK\n2bo+nnmnjucP1o9pVighsRSY99oLCrmMR29bwf/7v5P8+c1qPn3X/LQMCTIw5AxrD5+dHMXbpa14\nff7Lej33QuD3izzzbh37TraSl2bksTtKiI/WTP7BcUhPNLBzXTrvlLaxtjCBlTlxiKLI0fNdPPNu\nHRa7h7UFCdyxI5djF7qQCQL37iqYcMzzDf389PlyBAT8osi5+n7SEvTcsjWbjETDhJ+VkFgoFqTg\nTUaigTt25PL8wQZOVfWENYGba/rNTpZlXqzFmZ0Shdcn0tZrJSdFKpA9U3x+P79+qSLQC2t9Bvft\nKZj1Q+xDOwuoajbx8+fP8cFr8qjvGOJEZQ+FGdFcvTqGg2fa+d6TZbiGi9JPJLqd/TZ+9dJ50hMM\nfP3h9Ry70M3jb1TT0mMlIUYria7EkmHBTL8bN2eRnRzFn9+qmbR9y0wRRZFBq5s448V2L4XDFa1q\n24YifUxiCjzxZg2l1b3ct7uAh25YNiezBrVKzj89sI70RD1P7a+ltLqXO3bk8tUH13PPzny+dP/a\nkOBOxtP765DLZHz+ntVoVAq2l6SyrjDg9pipq0JCYj5YMNFVyGV89OblWOxunjvYMC/7cLi8+Pwi\nUSMCM3FGDfFGNXWS6M6Yk1U9HDrbwa1bs7lxjrMNYgxqvvHwBr77iS389PNXc8eO3FCVppwUI9kj\nMiIi1WbqGrBzrqGfPRsyQu4OpULG5+5eTV6akd5Bx5wes4TEbFhQJ2d2ShR7NmRw8HQ7zV2WOR/f\n4ghY0AZdeDS8ICOG2rbBiDfteFxoGqC8vm9Oj+9SxOP18fT+WrJTorhjR+687EMQBFLj9eP2xPro\nzctZnhUDBB6q4/FOWRtymcDOtWlj3kuM0U5LdHsHHfzvKxWhfbk9voj7lZCYCQseWbpzRy4GnZKn\n9tdOSwSngtU+LLpaVdjrBenRDFrdmCyu8T42hqYuMz96+gw/frZ8To7L7xfnzaUy3xw624nJ4uLe\nnfmLEojMToli+6pU4OJDdSQuj4+j57rYUJRItGFsF+HEGA0DZldYHePRvHConprWQHHvvx1u4FhF\nN6XVvQzZ3Hzn8VK+/MujoW1FUeRMXR82p4fjF7rxT3AN17YN4nR7GbK5EUVxTKtxiYu8fqyZI+c6\nF3SfLo9vTFPMSHh9/jH3sM/vx+P1c76xf1patuCdI3QaJXfuyOWJfTWcre9n7QzSjSIRsnRH5X0G\nO8w2dJjDMhsi8dbJttD/7U4vOs3svqY3TrTw3IF6vvWxTZdc88WDZ9rJTTVSvIiNAqOGZy5Wh4fk\nUYdRWt2D3eVl17r0cT+bEK3FL4r0m5243L4x339Hn429R5upaDQRF6WmrLYXgD+8VolCLuD1iaF9\n9w85qe8Y4s/7akKfV8hlofxzvyiCGEiOb+gw859/LiMzyUBbj5XCjGjq2s3871d2zrif2OVKY6eZ\nZw/Uo1LIWJkbR8w4D8+5ZsDs5N//7yRen5///swO1KqLXWacbi9qpTzUjWbA7OR/nj2L2ebmGw9v\noLSml45eG8cre1AqBBwuH9/71FaSYrSRdhfGouRQXb0mjaRYLS8crJ/QUpgutgjuhcwkA3KZQGOn\neUrj9A9dnI5+78kyDpd3zOq4KhoHAPjNyxWzGmehaem20NZrY/uqlEXtY6YffogGZzIjqWgcwKhT\nsiwzZtzPJg7fCL944Tzf+uNJugfsYe+XVvcAgRu/rKaXHatSWZETUPag4AIcPd/Fd584FSa4ALYR\n1s/vXrnAD546Tc+ggyffCmzX2mNFBGrahlhXmCAJ7jg8d6AevUaBzy/y7T+doqrZNCfjiqLIWydb\nQ+P1Djr4y1s1NHdZ+NXfzmOxe3C4fHz/L2WU1QQetma7m3/82XucqOwJjfG7vRfoH3Li9Yl87TfH\nePbdespq+1iVF0dxdhyfuWvVlAUXFqlHmkIu466r8/jNyxUcq+hiW0lqxG1bui0cON1OS4+VKK2S\nnevSIybjW4ZvyqhRlq5SISMr2TBl0R2wuFieFUNVyyBtvVb2l7Zx9eqx/sLRmCwu9BoFqlGt393D\nEfjOfjvHKrpIjddT1z5EfrpxSaexnazqQS4T2DSPKX5TIXg+raPcC6IoUtlsYnl2bMSHQnayAYVc\noK03sFCi3+wkOU4HBATx0NlOEmM09A062bE6lY/dUkxbr5U3jrdw3cYMugcc/OblCp7eX4tGJeeq\nFUk43F5KqwM3af+QM3RsJ6t68PlF/u0PJ/D5RO7bXUBZTS9rCxI4WdXDPTvz5+X7uZS50DRAZbOJ\n+3cXkBSn44k3q3n5SOOUWrDbnV40KjkVTQOsyIlFLpOxv7SN07W9fOqOEt4+1crLR5rQaxTcuDmL\nN0+0YHN6ebs0MJP9+9tX8PyBBpq6LPz8hXOsyotHIRdwe/yUVvdQnB3L4fIOqloGefjGIvLTjJys\n6iE7OWpWaa+L1phyU3ESb55o4dkD9awrTBwTRHF7fDzzbh3vlrWjUsrJSzPS1mvjJ8+Vc/e1edy6\nNWfMmFaHB7lMQKMa25AyLy2aw+UduNy+sKnEaPx+EZPFxebiZKpaAn6+1m4rVodnwuWqoijypV8c\nIVqv4r8+sz2sT1LvoINlGdHUtA3xv69cCL1elBnDVx9aHzaGzy8umUUcF5oGyE0zEqVTTb7xPBL0\n0Y8W3W6Tg0Grm+VZkW9QnUZJSW48Z+oCQdGgX18URX754jk8Xh+P3VmCWiUnPSGwXj4j0cCjt60A\nAhkUbxxvobnbwodvLOKqlSmYLC66Buy099roNzvZX9oWsmzlMgGfT+SbH91IRqIhlO1x81XZc/iN\nXD4cLu/EqFOya306SoWc5i4LL7/XSN+Qg4ToyNaj0+3lK786SlFWDKdr+0Kzk6rmQfyiyBd/fgSv\nz09JbhxVLSZeONRAcXYsd12dR2OnmeQ4LavzE8hIMPBOWRsHznRwrqE/NP6p6l5ODT9YNyxL5No1\nachkwpy4BxdNdGWCwMM3FvGdP53iiX3VfOK2FWE+lJ8+X05Lt5XrNmZw5448dBoFXp+fP7xayfMH\nG0iK1YVZYE+8Wc27p9uJ1qvGtXo2FiWGnoJXRWgZLYoivYMOfH6ReKOa6zZm0N5ro7LZxNd+8z6f\n+MAKXjzcyCduW0Fagp7OfhttvbbhQF3gZh6yuXn1/SY+sD2XAbOTV442YbZ7uG5jPDWj0taqWwf5\nxm+PccOmTP76Th07VqVy7EI33//U1nEj+QuJ3emhqcvCB7blLOpxAGjVcuQyYYzoBqeNk1lFV61M\nDonugNmJ1eGhumWQbpODD99URNEEog3wubtX4fOLIVdFbJSab398C//x51K6BuyU1wdu1pU5sWwr\nSUWhkEmLMaZI14CdrOQolMOdu69amczLRxr5l98e58sPrKMgQiv22rYh7C4vp2sD5/VCkwmdWsGy\nzEC36YYOM7dclU1xdizdJgcKmUDC8Pkb2Y06I8nAg9cvo6ymF/Mo91WUTsnHby1mVV78nLrXFvXO\nzk01cufVubx4uBGFXMbt23LoNjn43d4LuDw+Pn/P6jBXgkIu45Fbi+kddPDH1ypJjtWSlRxFW6+V\nd0+3Axf9f6MpzIwhzqjm/YruiKK772Qrf32nDgh07921PgOvz88XfvYeNqeX37xcgcPlY9/JFm7f\nnsv/PHOWviEnCdEa+oanmbFRav52uJHGTguCQOiiSIrVcueOXI5WdNFjcqCQy/D7RTr77Tz+ZjWi\nSGjac6auj60RjnGhqG4ZRBRZ1ABaEEEQ0GuVY0S3unWQaIOK5NiJ/WmblicRZ9Tw0+fKMVlc/PG1\nytB5WTeFQG6k4GuCUcOxC90AfOWBdVOaEkuE02tykJd20cWWHKvja3+3gZ8+V87bp1ojim7lKL+v\nUa/isTtWjvsATRl2J0VCIZfxlQfX0z1g52cvnGNzcRI6tYKbr8oOPWjnksU1p4Bbt+Xg9vp59f1m\n3isPpIwkxWj58v1rSR/HWlDIZTx2ZwnffaKUHz51mg1FiWEnIFJamEwQ2FiUxDtlbTjdXjSq8D/d\n4fKy92hT6Pe4KHVof9/5xFX878sVof0cOtvJobMX01uCggvwLx/eyCtHmzh+oTssvzMxRsvm4mRu\n2ZrNZ398iLxUI4/etoKn99eGpjFBTlb2LLro1neYkcuEsBtiMYnSKkM+ewjMSqpaTBRlxkxqhQiC\nQEF6NHFGNQMWVyg9bG1BwrhpZlMlKMZZSQaKssYP5ElExurwYHd5xwShCtKj2VKczP6yNgatZXzu\n7lXoNReNKVEUqWwyIQggirCtJIVHbi2eVZAyLUFPSryO7SUp7FidOunsZzYsuvNQJgjcfW0+//H3\nV/HQ9ct45JZivv3o5nEFN0icUcNXHlxHRqKBYxe6SYjW8tD1y4DICfQAa/Lj8frEMU9JgDO1fdic\nFz87spBLtF4VSm3LTo4a49sd6UOOjVLz4RuL+OTtK4mNUoemmcEnpkIu4+O3ruDua/OJM2rYNpyD\nujo/HpVCxjVrUqecTzyftHRbSEvQh6Z9i02MQRX2vfSYHAxZ3dO6OeKiNNS3D+F0+3jwukI+e/fs\nii8p5IGbfPvq1EXN7rhU6TEFsoTGi/xfuy4QuK5pHeTgmY6wxVSHyztp7rZw3YZMZIJAUWbMnGSF\nyASBj9+2Yl4FF5aApRskJU436TRgJMmxOr760HpEUQxd8HXtQ6yYYIpXmBmDWiXnbF0/6wrDa/v2\nDaeJ3bQli6PnOtGN8qmuzI0DYPf6dK5ek8Z//LmUurYhvnT/WtLi9XzpF0dQj8haWJ0fz48+vQ2/\nKNJjcoQJ9Uhf9Jr8eL74oTWsyInD4/WjUsrwLXItVFEUae62sDo/flGPYyRxRg1t9RcDHXXtAf94\nYcb408/xiDWqQw/W/PToWd+o123MRK2UR8wRlpiYnsFA+l7iOO6hjEQDv//qLr72m2M8d6Ce56hn\nTX48VoeHjn4bxdmx3Le7gN3r0+fFBTCfLBnRnSkjLYxP3r5ywm0VchkbliVy9HwXN27OJDX+YnX3\nfrMLo17Fh3YV8KFxqlmlJej51sc2hSzXPeszcHt8FGXGoJDL+PajW9CMShUTBAH58BLXiY6/JC8g\nbsGsiqAFtVgMWt1Y7J4ltZAjPlrDkM2Nx+tDqZDT2GlGrZKTNsF3O5rE4Wi4WiUnM2n2gS6DVnlZ\nZSWIohh6KOk1inm33nuHLd1IoikIAttXpfDi4UDN5bMjHrr37spHJhNC6X+XEpe86E6Xe3fmc6a2\nj+cO1PO5u1eHXh8wO4k3TuzfGylCW1Yks2VEN4pgutHlQEt3YCqXvZREd9h/OmBxkRyro7HTTG5K\nVFhq3mRcuzaNxBgtGUn6JZOWtxRo67Hy5skWztb1h4KVUTol6woTuPmqbJJj50fYOvvtxBnVYTPE\n0dy6LYfNxcn8+a0aqltMZCQaMOpVSzq/fTKuONGNNqi5Zk0ab51qxWJ3E6VTMWR10W92knYZCeds\n6OizAZCRuHS+j2DQqn/ISVyUhpZuKzdsypzWGFq1YkFaRi0VzDY3xyq66Bqwk5kcxY5VKWE+eo/X\nz/MH63nrVCsqpZz1hYlkJxsQgeZuC8cudHP0fBcPXr+MnWvn3oXS0mMlK2niB7tMCFizH7mpiP4h\nJwUZ0Qhc2v7zK050IRDtfONEC7/623m2laTyx9cqEYFVeUvHh7mYdPTbiNar0GmWTu+yYGCz3+xE\n0WnG5xfJS5u6P/dK5LmD9bxX3olWreDAmQ7eK+/g8/eswahX0Tfo4Jd/O09Tl4Vd69L54LV5YRkC\nAINWF394rZLH36jG5xPZsyFjzo7N7fHR1W9n/bKpPQQTorUTLpa4lLgiRTcjycCO1amcquoJrTqD\nyPmYVxqd/XZS45eWryzWoEYgYOn2DToRBCjOltK0JuKh65dx19V5xBhUlNX08ttXLvC9J8tYW5jA\nwTMdgMjnPriKdRGEL8ag5vP3rOaXL57nL2/XkJMSRX6EvNnp0t5nwy+KZM2Bb/1S44p1bD1ySzEf\nvrEo7DWtemmkRy0moijS2W8jdYm5WpQKGXFGNa09Vi40DZCXalxSlvhSRK2UExulRhAENhQl8cX7\n1uJwe3njeAuFGdF862ObIwpuELks0OMwLkrN71+tnLBE5lTx+0VOVAYWlWQmX3mie0VaukE2r0jG\n7vISZ9Tw21cuLInVV4vNoNWNw+UjdQlGhTcUJbHvZCsAt2/PWdyDuQRZlhnDf39mO26vf8Lg1Wi0\nagUP3VDET58r5/DZLuY5sQAAIABJREFUDnatn52b4bkD9bx5opXV+fGXXLrXXHDFWroQcNLvXp/B\n2oIEfvGFay4bn9Fs6OgPBNGWmqULgZKgQXbP8sa/UhEEYVqCG2RNfjxFmTG8fKQJj3dqfevGo6ym\nlzdOtLBzXTqfv2f1FVnq8ooWXYmxtHYHSiDORR7rXJOeoOfR24r5zqNbMOoXt/LZlYYgCNy+PYch\nm5sj57pmNEZLt4X/fbmCvDQj9+8uuGJX8UmiKxFGS4+F2Cg1xkUu5xiJbSWpUmrfIrE8O5bc1Cje\nPNk67VZbdqeXX/7tPDqNgs/dvXpMzekrCUl0JcJo7bZekRFlickRBIE9GzLoHrCHZf1Mhn9E94VP\n3VFC9BU+S5k0kDadFT8S88N8nIPxxvR4/fj8IsW5cdJ5XwDm6zuez3O3ZUUKb59q40xdX6geyWTs\nO9FKR7+NR24tviLKX072/QviXLfklZCQkJCIiORekJCQkFhAJNGVkJCQWEAk0ZWQkJBYQCTRlZCQ\nkFhAJNGVkJCQWEAk0ZWQkJBYQCbN0zWZbPiHe3b5/H7kssXX6br2If735Qp2rk3nlq2XT7uUSMhk\nArGxc7sKa+R5fWJfDbWtg3z94Q1hTTYXmtO1vTz1di2fv2cN6SMKqAfP96fuWDlhDd0n9tXQ2DHE\nv3xkY2hN/8+eP4dWLefR21bM+/FPl/k4rxB+biUWnsnO66Si6/eLoRMoICyJk5mXaqQoM4bnDtSz\nMjduSdYJWOqMPK/bViaz/1QrB8+0c/3G6XVjmEvK6/sZsrpJitWEXWcyIdA5dtDijnj9mW1uDpS1\nBQrhiIFVUAB+v5+mzitLhEaeW4mlx+KbrTPk3l0F6DQKHn+jSrrAZkluqpGUOB0VjQOLehx1bUPk\npRnHzKa0qoBt4HB7I372yPlOfH6RnevSwl6PMagZtLrn/mAlJGbIJSu6Bq2SB64rpL7DzBsnWhb7\ncC55irJiqG0bXLQHmMPlpa3XOm5LdY06ILpOV2TRrWwykZGoH9N5Odqgwurw4PH66R9yzu1BS8wZ\nflHklSONVLeYFvtQ5p1LVnQBrlqRzIaiRP52uIG2HutiH84lTVFmDA6Xj9Y5+h4bOsz8+qXzPL2/\nFpPFNen21S2DiGLgOEajHfYzO9zj13EVRZHGTjN5aWM7xMYYAh2e//h6Jf/0q6MMmCXhXYq8eKiB\nFw838vtXKxf7UOadS1p0BUHg4RuL0KkV/PyFc3Sb7It9SJcsy4bFbi4sjZZuC9//SxkVjQO8U9bG\nv//xBHXtQxN+pqJpAJVCRkHGWNFVKmTIBAFHBEu3d9CBzeklJ3U80Q1UtDpWEWgP02NyTPfPkZhn\nRFEc7tkGJosr4nm+XLikRRfAqFPx2btXY3N6eHJfzWIfziVLnFFDQrSG2knEcTL8fpHf7r2AXqPg\nu5+4im99bDMatYIfPXWahg5zxM9daBpgWWYMSsXYS1IQBLRqOU7X+JZuY6cFgNyUsaI7uh3MgCXc\n0hVFkcffrA75s00WF88eqJtVdwSJ6dE35MTq8LC5OAmfX6Sq+fJ2MVzyogtQkB7NVStTqG0bmpPG\neVcqhRkx1LYOTrtA9UhOVHbT3mvj/j2FGPUq0hL0fP3vNhClU/Hrl85jd461Ytp6rXT22ynJi484\nrkaliBhIq20bRKWUhaWZBUmN1/PNj27kY7csB2DAHO7qqGw2ceB0O795uYLmLgvf+uMJXj/WQkVj\n5Bvf45WusbmksTPwML5+UyZqpZyKpsUN6M43l4XoAhRmROPyzJ1P8kqkMDMa8/9v7zwD46jP/P/Z\nXrTqvfdqS+7dBmwwYEwLHUIICaRwuZDkUi7/u5S75JLcJZe7NFKPEDoxYKrBBtxwl4tsSbZ671rV\nlbaX+b9Y7VorraSVLcmSmc8bW6uZ2dHOznee31NN9ktegrtcAm8faSQpOoiVeTHe10OClHzpjkX0\nGay88EHVOFE/WNKOXCZh3aLYCY+tUcn8LjsFQaC0rpeC1AjkMv9f57S4EDYVJaDTKOgb5V8urevh\nlb21AAyb7fzobycZMtkBOFOj51xtDy6X4COyzV1DfO03h/jjW+V8//9OiMG5GaChw4BcJiU1Npis\nxBCqWwJvkL4QuYpE1+0LrLnKL9hs4gliXbhES6O4oovOPhO3b0gfN3AwKzGUOzamcfxCF28cqvcK\nb1e/icNlHazMiyF4khFBQWoFRrN93OudfSZ6Bi0UZkzdUDs8WEWfwUJDh4HjFzp55v1Keg0Wrz9b\nAH7+5XVkJoZwuLSDX79Wyld//TE/f+kMAINGG396+zxWm5Piim7aeoxT+qpFpqa1e5ik6CDkMik5\nyWG06o0M+7nWVwtXzQj28GAVkSFq6jsm9hv2DJg5XNZBq96IRiWjIC2C5dnRqK5gFdZ8Ii5CS2y4\nhjM1PdMes22zO9n5cT1J0TqW50b73Wb7+jT0gxbePdpEVfMAi9MjOFzWgVwm4e5rMic9frBWQVuP\ncdzrFxrdboDJXBMeIoJV9Bqs7DxYx4XGfgTg0W155KaE8f/+dJzkGB1RYRpiwjTUtRlQyKWYrU7q\n2g1YbU7+++USegctfP2+JbTpjezYXysGb2cAg8lOZIgagNyUcKCBmpYBluX4/x4tdK4a0QVIiAqi\ns9f/TXDiQhd/e78Sm91JXKSWIZOdI2WdaFVyVufH8KlrMia1tD4JSCQSludE88HJFowWO0FqRcD7\nvne8iZ5BC99+YOmEY7WlEgmf25ZHRnwIu4418cahBuIitHz17iIiQ9WTHl+nVTJkGr+KadMPE6SW\nEzXF/uAOFla1DKAfMONxcCxKiyAyVM1j2/NZPDJ+5pZ1achkUj61KYN9Z1pHzrWeth4j/3DnYgoz\nIinMiOSj0y109ZkwGG109pm8FrOHwWErwUHKT+SY8ekwbLaTGhsMQHp8MFKJhIZOgyi6C4H4SC1V\nzf24BMHni77/TCvPf1BNVlIoX7ytgKhQDS5BoKZlgANn293Wb4+Rbz+wzG/0/JPE6vxY3j/RzHvH\nmrh3c1ZA+9S1DfLu0SbWLoolP23yZb5EIuG6ZYlcuzQBm8OFUi4NaBR3sEaB0WLH5RJ8ZlC19hhJ\njAoK6BiRoWosI7m+cpmE6DCNV+w3FMZ7t0uMCuLzt+QDsG5RHLuONfHByRaSonWsGGXFx4Zrae4a\n5hevlNCmN1KUGUl0qIZP35jDsfOd/OWdC9y+IY3lOdEkx+g+sSPHJ0MQBIbNdnRa9wNeIZcRF6ml\ntXv8qmaucAkCR8o6WFsQi0I+86vgq0p04yK02Bwu+g1W783U0GHgpY9qWJIZyVfuKvQGW6QSCbkp\n4eSmhFNcEcUf3zrPK/tqWJQWwfIZesIKgoDZ6kDrx2IUBIHOPhPnanuJClXT1W8iOkzDwJCV9YXx\n6DSBW5kzSWpcMBuL4tlT3MLq/FhS44In3V4/YOa3O8uICFHx8NacgN9HIpGgmsYYbp1WgSCA0WL3\nrkgEQaBdb2RNwcQBuNGsXxzHawfqAPjnh5YH9BnHRlxMOdu2NsVHOOMitFQ09SORuN1bpXW9AIQE\nKXjjUAMAbx9p5O0jjaxfHIcgwOe3582LplHzBZvdhd3hInjUtUiO0VHbGriv3GSxs7u4ma0rk2dk\ntVrZ1M8z71XS2DHEZ27KvezjjeWqEt34SC0AHX1GIkPVOJwunnmvgpAgJY/fVjBhdHt1fixnqvXs\nP9PG/jNt/OtnVpCZeLEc1WJzcKSsk/BgFS6XQGl9Lw0dBnKSwnC6BJo6h9CoZNy5KYMLjX30DFo4\nW9NDqE5Jd7+Zf31kBWlxITR0GHhlbw0WmxOjxT4ufclDcWU333tk5cx/QAFy3+Ysyup6eea9Cr73\n2ZUTfm6dfSZ++UoJTqeLrz24zO/DZaYIHrGEhs0XRXdg2IbJ6iAhKrBOXWE6Fd9+YCkVzf0+13cy\nRgvkqlEZGaPPaU1BLPdcm8mRsg7eONTAG4caWJYdxbY1qfzni2dQKWUcLe8kJVYnuhrGMGR298UY\n/QBMig7ixIUuTBYHWvXUElXR1M+7R5v48FQrv3ly02WvVs0j+eDlDb2XdZyJuKpEN26k7r6jx8Ti\n9EgOnm2nVW/kK58qnNI/+fCNuSTH6Hj9YD17TrbwxbhgOnpNHC3v4Gh5pzeVCEApl5IUo+NIeQdq\npZwQrZL6DgP/+eIZJBJ3TmlWYijVrQM4XQJ/31uLRiXnbG0PIVoFMRFawoNVbF+XRkFaOPp+MzER\nWvT9ZoK1iiueB6rTKHjkplx+u7OM1w/Wcf+W7HHbnK3t4el3LyCVSvjWA8tIDFD4LpVgjVtoh0x2\n4kdiZq16d3rgdN47Py1iShfIWH746CpcgjDu4bNuURydfSYeuiEHnUbBzWtSvBbup7fmEBGi5pf/\nuAG7w8l7x5q4bUO66GIYgydLweNeALxdA1v1w+P85P7w3JtWm5Oa1gEKpnl9x2Iwuo0h/YBlnKty\nJriqRDdEqyAiREVpXQ8bCuN5+0gDeSlhLM+JmnJfnUbB9nVpmK1O3jveRGOHgZ5BC1KJhGU5Udyw\nIglBAJVSRlK0btzTtM9goalryB0BD724JN11rJHXD9ajlEu5+9oMNi9LGvf0jg13W+gxY6qnriTL\ncqLZvCyRPcUt6DQKtq1NRSqR0Dto4c1D9Rwp7yQlRsdX7iocV/U1G3isytEPv4Z2AxIgJXZyF8jl\nMpGLJTZCy5fvWOz9WSGXsX1dKkq5lIiRaHxokPth8cjNebN6jvMFQRBwusY/oCZieOR6eh6qgDeo\nVt9uCEx0R6WXVTZfvuiO7kpX3TxAXmr4ZR1vLFeV6EokEq5bmsjOj+v531fPYjQ7uHdz1rSsi9s3\npHG+sY+OXiOP3JRLQVo4MSOiOBkRIWrvjTaabWtTWZEbQ4hWGdBSaT7x4A3ZDJntvH6wnoNn29Gq\n5bR0DyOVSLhlbSp3bEyblUCDPzzLT89yFKC2fZCE6KB59bnefe3kqW9XK1a7k50H6zlU2o7d4aIo\nM5LPbssjZAof65AfSzdUpyIuQktlcz83r0mZ8r2HTDbUShlxEVrePdqIXCbh9g3pl/y3DBqtqJQy\ntCo5L35Yzc1rUogJ19DaPcx1yxIve7Uyf76tM8Q1SxPYfaKZhvYhHr4xh3Q/TVAmQ6mQ8d2HlmOy\nOggPVl32+UglEuIiphbt+YhcJuWJOxZxIieKU5V6bHYnt61PY1NRwpQpXjON16c7Yhm5BIG6NsM4\nP6vI3ON0ufjDm+WU1fWyZlEsIVol+8608YuXSvjBo6sm9bF6rufYoGZeShjHL3QFNK1m2GQnWKsg\nOymMxs4h3jzUwLLs6CmHG+w708ruE81sXZXsbd5/4GwbtW0GYsM03L4xnT++dd6n85nBZOeOjene\n4p76dgMpscHT8iNfdaIbolXyv1/diEsQphUdH41KKRMLJkaQSCSsLYhjbUHcFT0Phdx9TTzuhY5e\nE2arg8zE6T1URWaevafbKK3r5TM35bJ5WSIABWnh/OrVUnYda+TOTRkT7jtktiORMG61kpcazoGz\n7TR3DU9pOA2ZbARrldy6PpWIEBU79tVypKyDB64fH4sYTXFFNz2DFnbsqyUpKgiFXMZzu6sAKMyI\nZHlONL9+ciPf+cNRjBYHMqmEtw43oFRI+fhcBxHBKiqa+lm3KI7Hb80P2AK+KnNXFHLpJQuuyPwl\nTKfydglr6nRXHk53JSMysxgtdt4+3MCi9AiuW3pxakdRZhQrc6P56FQrNvvEHduGze4iHH9l48Ck\nqWMul8Bbhxto7h4mWKMgWKvkptUprMiN5uC5djp6jVQ199PZ5y6YEgSB6pYBHE4Xw2Y7TZ1D5CS7\nM5B+8cpZfvrCae+xPb54jUrOLWtTiQ3X8LuvX0NRZiSv7q+jq89ERVM/KoWMY+c7ve8RCFedpSty\n9RIXrqFr5Mvd0j2MXCb1pgmKTB+XIGCzO1ErL10GDpS0YbI6uPe6zHGW3pblSZyq0nOqqpv1i+P9\n7m802wnyky8dEaImPFhFXfsgW/E/t6+ufZC3DruzRUb7hB+4PpvKZ07yp7fP09zlznD5zy+vo11v\n5Devl6JSyrCOFMlcsyQeo8VOm963GGN0U6Zta1PZttY9APfxWwv46fOnyU4KJSJEzcq8GCw2x7Rc\niKLoiiwYYiO0XGhyVxw2d7mbpIiFBpfGkbIO/r6vlmGznfhILTesTGZTUXzAWQcADqeLvadbKUgL\n95tBkpsSRkyYhuMXuiYUXbPNgVblf1WamRhK3SQNhSqbL5aFjy6KiAhRc/uGNF76qMb72k+eO+WN\n0VhHTSBJjw/h/316Of1DVr7/dDGhQUoGjTaUE7gXdRoFP358NVKJ5JIDauI3VmTBEBehxe5w0Wew\n0NI9POupYlcrp6v0PL2rgoRILZ/alI5aKef5PVV8/+liztX2BNxP+VRlNwPDNm5c5d8SlUgkFGVG\nUt08MGFTeLPVgUbl3/bLSgih12CdcMTS6CknwVpfa3n94niUCikxYRp+8oU1yKQSmruGWZoVxe//\n6Rq+fMciFqVHEBuhRatWkBit48Hrs/nKXYX8w52LJ23AJJMGVro+EaLoiiwYPEu4srpehs32KaPT\nIuOxO5z8fV8NSdFBfOvBZdy2IZ3vPbKCJ+8uAuDXr5Xyi5dLpizDFQSBD0+1EhuumbTD2+KMCGwO\nF9Ut/o9nsTq9057HsiTLnV//8bn2cb9zulw+5zh2qohWLefx7QV85uZc4iODePzWAsDdY0OtlLM6\nP5Zv3u/bnGnrqmSyEkNZmRczq2mIouiKLBhiR0T3+Q+qkcskLMueuuhFxBdPxP6+zVleV4JEImFp\ndhQ/fmw1D92QTXuPkZ++cJpfvFwyYUPxszU9NHQYuHF1yqQVW7nJ4chlEu84pLGYJrF0YyO0FGVG\nsr+kbdxEmD6DFZvDxebl7myJvJTxRRQr82JYNFIoUZAWwe++fk1AhVKzjejTFVkwhOmUJMfoaOke\nZlNRgt9iFJHJOVreSUyYhkXp46u25DLpiG83gf0lbewubuY/XzzDorRw7ro205spYjDZeHlvDfGR\nWjYV+ffVelApZWTEh1A1gXhbbA7UE/h0ATYVxVNa10td2+BIr103PSMTO1bkRPPQDdkB+fbnSxHN\n/DgLEZEAkEgkfO+RlVQ09QVUHiriS5/BQmVTP3dsnLwHhEop4+Y1KWxensiBkjZ2HWvix8+eIj81\nnIyEEE5WdDNotPHtB5cFFHjLSQnnvWNNboEd5UpwCQIWqxPtBJYuuPN1JRJ3Uxsf0R1wj5SKCtMs\nuGDqwjpbkU88CrmUosyoy0pz+qRSVt+LAKwIsIpPpZBx0+oU/uvL67j72gz6DBZ2HWtCqZDxjXuX\neHNppyI3OQyXIIwbbWS1ORFg0msZpFaQGhtMxZgJwfpBCxKJexrIQmPKb+7ohtEiV4bZuAbidb3y\nzNY1mOi4rd1GspPDSIoOrOm7hyCNgts2pHPbBnf563Qj9zkpYcRHamnTmyjKvOhTtTtdxIRriApT\nT/pZrF0cx/4zrZyp1nsHnjqcLnKSwlDOwyKoqa6rRLicedsiIiIiItNCdC+IiIiIzCGi6IqIiIjM\nIaLoioiIiMwhouiKiIiIzCGi6IqIiIjMIaLoioiIiMwhU+bp9vcbcbkmzipzulz88a3zdPSaePKe\nomkNVxQEgb+9X0ldu4Fv3b+UsAWY6DwXSKUSwsNndtruVNf1UjlZ2cWr++t4fHsBOX7q4QEOlXbw\nzpEG/vGuIlJiJ29a850/HAXgMzfm8vwHVXz93iXjRq6bLA7+/W/FbFmexE2rfWdq9Q6a+a+XSgBQ\nKKQ47C4kEgkuP5mSKoWMHz++hurmAV7aW4NKLqV/2Eq4TkX/sJWfP7F+3D6/fb2Mlu4hCjMiaeke\nZshsJ0gt53uPrPRu43S5KK3rZWlWlE+O62xcV5i9aysSGFNd1ylF1+USJryAgiDwwgfVnKzo5ok7\nFxMVop72xd6+NpXvPX2C/9t1gW/cu0QcUT1HTHZdLxWH08Wr++tQKWRkJoZMePzl2VG8/GE1rx2o\n5Wv3FCGRSLDanSjk0nHNU7r73eWevQYL3f1mFDLpuOOqlTJCtUoOnWvnhhVJPt+hviGr9xiebaUS\nCSarw++5/frVc8RGaGnsMIw/h0GLz9w8g8nG6apuAC409tFnsGIdmZLgcglYbA5+/lIJRZmRvH2k\nkR88upK0uNmfdDEb11Zk5risWsp3jjSyv6SNbWtSLnlAYFSYhnuuzeSlj2o4fqGLdYuu7CwukUvn\n0Ll2uvvNPDkipBOhUcm5dX0aO/bX8ud3LuB0uiip6SEkSMlj2/O9I7RHW6Mmi1skJ2pasnZRHM/t\nqaKyqZ/8kf07eo3ewYceVAoZMtnEoltS0zPheZ+p1nP9iiTAbb1eGNU5Sz9gxuG8eL7//UoJ6fEh\nNHYO4Xl12Ox7LiKfTC7Zp3v8QidvHm5gw+I47r7u8sZOb1mRRHp8CH/fV4t5gptBZH4zbLbzxqEG\ncpLDWJI5cX9VDzetTuam1cmU1Oipahng2qUJqJUynnqjjJpWd0eqgSGrd3ujxY5UIkE9QUf/DYVx\nhOqUvH+iGXD3jf3Xv5zg92+W+2ynUsimnJ8nl/k+MDyTXsvrewFo6zHyhZ8f4Nj5Lu82owUX4EJj\nP7uONQEXm7N4Hhwin2wu2dLde7qV+Egtn7slf9J+moEglUh48IZsfvr8aY6Wd3qtCZGFw6v7azFZ\nHDy8NScgF5FEIuH+LdncfW0mUqkEqURC76CFX7xSws9fKiEpRkdT55B3e6PZjlYtn/DYCrmMdYvi\n+OhUC3aHk0GjDQC7w7cPq0opG9VHFvwVwY8VUM8xmrvd87ZqRx4KZSMiPBXGEbEVRXdiuvpM2J0u\n4iO1C65r2HS5pL+uvcdIXZuBTUUJM9a0IysxlPT4YPadaQ14XIjI/OBCYx+HSju4cXUySdOc5iCX\nXfTjRoaq+cFnV7IoPcJHcAEGjbZJWwAC5CSF4XAK1LcbGBy2+d1GpZB5reXoaQR9FXIp/UNWztb2\neAV9ukzk0hCBX71Wyg+eLuYLPz/A3tOtV/p0ZpVLEt3iii4kwLpFsTN6MluWJ9HRa+J8o/8u8yLz\nD5PFwV/fqyA2QsudG9Mv+3hatYIn7yni50+s83ndYLRN2YQ6K8ndavC/Xirh6V0VPr8LGtlXpZCi\nVspQyKU8clMuy3OiAzqvnJFj/+a1Ut481OB9XTYNo8NoEX26/hg22+nqMxER4g5SeoKTVyuXJLqn\nq/RkJ4cRqpvZFK81BbGE6pTsKW6Z0eOKzA6CIPD8B1UMDNn4wq0FM9ZmTyqREBXqa4UOBiC6Oo0C\nzcgUgs6RUe2jfwegVMjQquUEaxUUpEX4naDgj6wk/+lvaqVswnEzYzGL7gW/NIxkijy2vYCbVidT\n2zbozQK5Gpm2T7ej10hbj5EHb8ie+ZORSblhRRKvH6ynrm2QzACbJItcGQ6XdXDiQhefuiaDjISZ\nT4X62RfX8tJHNZTV9zJktgc0/fdfPrOSZ9+vHNcwW6dR0NVvRq2Ucdv6NDYVJQCgGXE1qJQyrl2S\nwMFz7T4juj1EharJSwnzGfvt2U8mlQQUAL5S7oXatkH2nWklMSqIrSuTvQ9Ho8XO0bJOSmr0tOqN\nWGzueWXxEVpyU8JZlR9DUvTsD/+sbzcgAdLigrE7XOwpbqG2dTDgB+JCY9qW7pGyTqQSCStzLy1F\nbCquX5FESJCSHftrRd/uPKZVP8yLH1STnxrO9rWps/IesRFarwvLanOiVEz9dU2MChrnMlDIpV6h\nUSlkxIRrveN+1CNWqk6t4IHrs0mI1Po9rlop4zsPLWdplu9gQ5VCRpDad/y3ZoKZX8YrYOn2Dlr4\nxcslnKvt4fWD9fz3K2c5XaXn5Y9q+Nbvj/Ly3hqGzQ5W5kazdVUyy7KjsTsF3j3WyA+eLuaXr5TQ\nqh+e1XNs6DAQHxWERiUnNzkMjUrGvjNXr193Wpauw+niSFkHRZmRPkniM4laKefOTek8t7uKo+Wd\nbCicfPCdyNxjtjp46o1yNCo5X7ytYFanUIyewaWUB+a+iA33dU0o5VKUI2lfY10gHkvXI5QTuQpU\nI9uNrZpUKmQEaXxF97ufXkFZfS+vHajzef1KZC/s/LgegB99fg0NHQb+790LPPVGGTKphFX5Mdy8\nOsXvCsJgsnGktIP3TzTz78+c5JGbc72rg5mmo9foHXqpUsq4ZW2qe7XbPkhmwtW32p2W6B4738mg\n0cZ1y2bnw/dwzZIEjpZ18vJHNeSlhBMZKk59nS8IgsD/vXsBfb+Zbz+4dMb9+mORy0eLbmALs5gI\nX2tVqZChGBHbsXm+HpEd++9Y1Ar36+E6pc/rKoXM6y/2HlMp8+t/nmv3gsni4GRlF9cuTSQyVE1k\nqJpF6RG06Y3ER2nHWeijCdEq2bY2lY1F8fzp7fM8814lCLBpycze+3aHi55Bi09R1OZlSew8WM/5\n+r6rUnSn5V5492gjaXHBFGZMnfx+OUglEh67NR+XIPD7N8sXtFPdbHUEnI0hCAJ2x/z+W9873kRJ\nTQ/3bc70mc46WyhGW7oBBupiwtSMtr2VChmqEcEeWxihHiO2nrS0woxIVudfdKF5xDpszEPG7V5w\n7+PJZFCr5H4FzTTH2Qtna/U4nAJrCi5mGWlUcrKSQicV3NEEa5V8/d4lLE6P4NndVVRPMEr9Uunu\nNyEIEDfqQalVy0mICqKu3TDJnguXaYludlIYD9+YOyf9EWLDtXzh1gIaOww8tbNsRoW3pnWA9h4j\nzV1Ds1IBd/xCJ81dQ/zkuVO8caieX75ylhc/rOZnL5z2buNwunAJAm09RgaGrTzzXgV7ilv45lNH\n/QZy5gPl9b3sPFjPmoJYtq5KnpP3HF0dFqilq5C7p9h63AwqhdRr6U7sXvAV32XZUXz5jsVekfa4\nF8a61VQKKXmMkwrEAAAgAElEQVQp4RRlRnqtW7VSNi6nWKWQYbI45jROUd7QR3iw6rKDnHKZlC/f\nsZjoMDV/eLP8kvOU/eHJMokb40vPSAihvn3wqozrTMu98PitBbN1Hn5ZlhPNo9vy+NvuSn72/Gm+\ndMci4iOn35XJJQjY7S4+Ot1CV5+Z8419xIZrqG0b5Nb1aSzJjCI5VhdwZZ3bInVhtDjQD5jp6jfh\ncgkYTHa0KjkvflhNVKiankELLSNBiMNlHdhsTg6da0ejkrNjfy0FaREcOtdOalwwjZ1DqBQyrHYn\ntW3zL3KrHzDzp7fPkxgdxKM3581ZYyIf98I0UtLu25KFTCbxjgxXTmTpKv1bumrVRXeE1e686NPV\njffprsyLYWVeDN/94zEsNidymdQrwKE6JYPDNqLC1LTpjdjsLu+xZpsbViSzZXnSZVeMgtv6/Mqn\nCvnxc6d4+t0LfOO+mWlO5RHd2HBf0c1MDOVQaQeNnUNef+/VwmU1vJkLNi1JIFSn5C/vXOCHfy1m\n68pktq1NHedH84fT5aKyeYCWrmF2HWtELpdiMNoQBBgctuESBE5X6XnzUANfvmMREomElFgdDe0G\nkmN02BwulAoZOrWc+nYD4SEqfrezjE1FCew+0UxOchiVzf3oNApsdicmi8P7RewZtABgs7tLSD3W\n6/MfVKFWyhk22zlU2o4ANI5UX3ms+crm/nklunaHk9+/WY5LgK/cVThnogFj3QvTS7bxWqlyqbd/\nwlifrkIuJUSrIGLEgvVavCNirFLKwHjRIo4O15AUrcNosdM/ZPURcbVS5t3O43KIDdMwOGwjKVpH\ne48Rp8sFzM3nN9NpfEkxOu7bnMWLH1bz8bl2rl2aeNnH7OozE6pTjvOlF2ZEEqSW8z9/P8tPvriW\nEK1ygiMsPOa96AIUZUbxH4+vYcf+OnafaGbvmVbWLYpj/eI4MhNDfZ7kA8NWXC6B/9lxjuQYHScu\ndKGUS7GNqcH3dLBqGamn33mwnu4BM9lJodS2DpKeEILR4sBmdxIVqqamdZAwnZKBYRvvHm3E6RK8\ntff9oxqzTLUccjgFb7epiTatbO6f3gc0y7yyt5amziG+enfhOItkthm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dyNIF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\ncjwokie2AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "he tanh\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "39ef5b0f58544f779785d1a9d47f4463",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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C+4y7xq8K14IgoLS0FNu3b4fJZMLq1asRGxuLRYsWufw1ukvEnqjVob1+7UDF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\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.8547\n",
            "Validation accuracy 0.86\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Uuy3L/hqeCZFYgu/++hR6jYovPbR60a/3dDMj98JsyyIa9Rpqih0T5sYqikLy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\nVXv5+95sEAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cu35X9TzHEMk",
        "colab_type": "code",
        "outputId": "9c9befd0-51d7-4176-91f2-2c987e5661af",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "0cf80e2bcee942e186dd9384441d3369",
            "d5e6036b7bbe42bca02c1bc3e2d288de",
            "c9ae4a4895454bbebce10b5d120c5c45",
            "6126e7705e9244c9a7012b53233bd916",
            "40537732eea34217a785de7065559447",
            "228a05dbea464fe0896e5cdabc8f8060",
            "fe3bd2aec2294483abd8d5c3e581e856",
            "020497da5c744dd38f215b2349b318df",
            "90244bc48de24e2bb1e5ae4257f15689",
            "7eb935de69c8461d90c9eb8cf870ea9e",
            "51dd942e1b394da28ece0967c9282d3b",
            "fd0f0b4d52ec40fc974410267af8a75d",
            "b778851198e44c2cbc5b2d2e026f984a",
            "f6907ba042044be89db547d5f88a9c45",
            "c0d712d79d6c48f5846b352c71ba9f29",
            "6ba08e5130454b43bbc8db1848991cef",
            "fc80d99f2b5e48e4850f27ef628047da",
            "348f9972a07d424fb708f8e10f2e8cce",
            "3dd43f7c32f6437f855976584ce03905",
            "c19fdd635b764cd5a82c951df239b949",
            "7e01023b21e0402ea6f5b0f6a5de47db",
            "33cf453237ff457e9b725c20fc381da3",
            "bbb82f794e5546429850a9727fb024de",
            "7a51237dd39840bcb8aeb662dba887d2",
            "6430023b9ec048f98435d04eefe98fef",
            "37da6eb327664b69a1709c5da5242b4e",
            "6962d2208e2f4abfb2261a45e0ddf87b",
            "d78aa8af7fdf45a28998a934cc570551",
            "f3736b3924fb4820930021941f2cb525",
            "73ee72310cdf42b385e8ddd9e1c97ff0",
            "1e0fd4ca40b64c1bbffface16e42d8d6",
            "4ede5413a9074477ada1de5a01c8956f"
          ]
        }
      },
      "source": [
        "for init_method in ['zeros', 'random', 'xavier', 'he']:\n",
        "  for activation_function in ['relu']:\n",
        "    print(init_method, activation_function)\n",
        "    model = FFNetwork(init_method=init_method, activation_function=activation_function)\n",
        "    model.fit(X_train, y_OH_train, epochs=50, eta=0.25, algo=\"GD\", display_loss=True)\n",
        "    post_process(plot_scale=0.05)\n",
        "    print('\\n--\\n')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "zeros relu\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "0cf80e2bcee942e186dd9384441d3369",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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UIYTocbIFTB81MnIgPho1a7ZWAZf2PpOtYYQQfZW0zPogm03h9Q/2YLPZqDI28nbxPhav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\nPJ4kMyGEEB7v/wFvbiN41RmwAgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.2507\n",
            "Validation accuracy 0.248\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAADnCAYAAAC9roUQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n0H8ATb9DYGiUqCEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "random relu\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "90244bc48de24e2bb1e5ae4257f15689",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fnmbCoWMNaPdwkL0g04y9JRa38s5J0NmXg5/LuYJftXTp0qUev1MAtbba4M0Q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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.9067\n",
            "Validation accuracy 0.92\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/W+bCfIXZhSozC1WKFXvF8cmYQTphkoxLKyWfjknrw9KxDA3T0DFbBE8IEZhr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\nTYRFDwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "xavier relu\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "fc80d99f2b5e48e4850f27ef628047da",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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v8G6f38gvqsXXP5xneBAFEFlCwmQy4fjx41izZg0AYPLkyVi6dCnq6uoQFxcn\nRwnkAU/nMNKSNJgwMhmrNx93CI8whYCb+sfhfE2Ti80IrVi77STMLW3XhMdFhgeRH5MlJCorK5GY\nmAiFQgEAUCgUSEhIQGVlpVNIbN26FXv27IFer8ecOXNwyy23yFEiueGuhwHAZXjM+dUIHCk24Z1N\nBWix2By+jw2Sy51s3/3sGFrbbJCk9mNXhq6+O16FvUeruhQenAsh6lmCJEle3/WtoKAACxYswNat\nW+3HfvGLX+DPf/4zbrrpJvuxmpoaxMTEQKlUYu/evXj++eexbds2xMbGertE6garTcKBk0aUlF9E\nah8tRg5NhEIUYLVJWLz6G5wqrUdLqxXhKgWG9IvF5DvSsPyDA7jc6tj7iFVHoOZCs0fnDFMIyBrb\nD8dL6lBe3YRWy4/f/6WZY7HkvW+dzvvKE7cBAA6cNKK4/CLSrqnV1XEiukKWkDCZTJg0aRK+//57\nKBQKWK1WjBkzBtu3b+90uOmBBx7AwoULMXr06C6cy9yt3U47TuKGCm+2uf0v+mt7H64mtF0NXSkV\nIpL0USitMnt8zjh1OC6YW9Dx41cqROTcmYpDp2txrrrRYbPDZ6fcjL+sP9wjPRV/7sHwZzs0dLfN\noihAp4t2+7wsw006nQ7p6enYsmULsrOzsWXLFqSnpzsFhNFoRGJiIgDgxIkTKC8vR2pqqhwlUg9z\nNb8BoEtDV67CI1wpIr1/HPILa53OebnVimv/PrBYbVj/zyKHYy0WK06W1ePF975HbUMzbLYfj585\nfwHbvjuL/MJanK+9soNu+HVCpTthAyAgA4dCjyw9CQAoKirCwoUL0dDQAI1Gg9zcXKSlpWHWrFmY\nO3cuhg8fjgULFuDYsWMQRRFKpRJz587FuHHjunQe9iQ8509tvtGeR7hSgXt+moLt+8859kjCRKQa\n1Dh97qLTOV3tbdWZ6MgwNF1uQ8d/MQpRwJC+MTh97gLarD8+oQoTMf2ewdhbUIWzlQ1O27W7a5s3\nejcmc6vDbr+hEEL+9LMtF2/1JGQLCbkwJDwXCG3uSni4+wXblVBRhYkY0EeDE6UXnGpRRyrR2Gy5\nofYIAHrHRUGpFHG+2uzQ81GIAn7SPxYnSuudAmfahEH4tqAKZUbPhsx6stfT1R6PP/SQAuFnu6cx\nJDzEkPBcILfZVXh0/EUkV6iEK0Vk3pqMrw+cR2vbj1dzhSkEpCREo6TS+f+vXhsBi9WGC+bWG/7/\nEBmuwOUWq8N9p0QB6KPvhYraS7B2+LcQphAwLDUOBSV1TiH0UOZAfHfMiLKr8zbhShFpSdoeC6HO\nwskbQeRp7ymYelUMCQ8xJO5wLtgAAArSSURBVDwXSm1u/2XQcSuSngqVrobNb7KvXNH3zqZjToEz\nLqMPdh0qdwgcpUJASqIaxRWOixcBQNNLiYYm595NmEJwCILuChMFh21ZAEAQrlwkUN/Y4tQT6p+o\nxlljo1M4DU/ToaDYBEuHmpRhIh68awB+0i8W//PFSZRVm+0BlWrQYP5DGV4NKH/sVXUWWl0NRk8x\nJDwUSr8w27HN7nWlp9LVsOnOnETXejduhtKUIn4+Igm7D1c4hVDf3mqnFfQAEHs1DK4VqVKgudV5\nPkcQAG//RomODENTc5tT7ykhNhLV9c3OwWVQ42ylc3Dd1D8Ox8469qqUYSLuu60fDpyuRUVtEyxt\nNvsOA7Pu/Qne33YCZcZGtMjc2wK6PoflaVAwJDzEX5ihQe42uwuVzp7zZu/GmyH04/Eyh4WUKqWI\nO4YZsOdo5TXhJOKenybDWN+MH07VOP2/02nCYWpwDih3c0MqpYjWDuf1tajwMDS3OIZZey+srrHF\nIUxFAUiK74UK0yWH318KUcDIwXqIooD9J6s9Crr23uq1Vxa64xeXwBKFKneXAnf2XFcuH3a3It7d\nbr9dXUF/3239cab84g0fnzZ+ECrrLjkd/+WdA3Ck2ISjxXVOgXPbMIPLILrrlj49Elwue1VhIga6\nuXDBEBeFyrpLTsfdhVmYQsC1f65KEnCppc2pt2WTgKq6S05/4FptEvaddLzXS7s2q4TDRSan460W\nK84ZGz0OiethSBAFiK6Giqvdfjt7fXdD6EaPu9sfrKcCyt3xqXcPREVtk8teVXFFo1PYjBqa4DKE\n3IXZuAzXYTZhZNd6Z7+5/yewSRLe3Xzco6BTKRVISVRf/wfKQwwJIgLQ/RDqieM9HUSe9J581avq\n6vERA+Kv1qT1OOja29ETOCdxFcfnQwPbHBputM09ceFCTx73pKZrg9FTnLj2EP8hhQa2OTSwzZ67\nXkiIN1IUEREFN4YEERG5xZAgIiK3GBJERORW0F0CeyObcwXqxl43gm0ODWxzaOhOm6/3nqC7uomI\niHoOh5uIiMgthgQREbnFkCAiIrcYEkRE5BZDgoiI3GJIEBGRWwwJIiJyiyFBRERuMSSIiMgthgSA\nkpISTJ06FZMmTcLUqVNx9uxZX5fUo3Jzc5GZmYkhQ4bg9OnT9uPB3O76+nrMmjULkyZNwn333Ydn\nnnkGdXV1AID8/Hzcf//9mDRpEh577DGYTM73CQ5Us2fPxv3334+cnBw8/PDDOHHiBIDg/qwB4K9/\n/avDz3cwf8YAkJmZiaysLGRnZyM7Oxu7d+8G4KV2SyQ98sgj0saNGyVJkqSNGzdKjzzyiI8r6ln7\n9++XKioqpLvvvls6deqU/Xgwt7u+vl767rvv7I//67/+S/rd734nWa1WacKECdL+/fslSZKkVatW\nSQsXLvRVmT2uoaHB/vVXX30l5eTkSJIU3J91QUGB9Pjjj9t/voP9M5YkyenfsiRJXmt3yPckTCYT\njh8/jsmTJwMAJk+ejOPHj9v/6gwGo0aNgsFgcDgW7O2OiYnBmDFj7I8zMjJQUVGBgoIChIeHY9So\nUQCAadOm4YsvvvBVmT1OrVbbvzabzRAEIag/69bWVixZsgQvv/yy/Viwf8bueKvdQbcLbFdVVlYi\nMTERCoUCAKBQKJCQkIDKykrExcX5uDrvCaV222w2rFu3DpmZmaisrERSUpL9ubi4ONhsNly4cAEx\nMTE+rLLnLFq0CHv37oUkSXjvvfeC+rNeuXIl7r//fiQnJ9uPhcJnDADPP/88JEnCyJEjMX/+fK+1\nO+R7EhT8li5diqioKEyfPt3Xpcjij3/8I3bt2oVnn30Wr732mq/L8ZpDhw6hoKAADz/8sK9Lkd0H\nH3yAzz77DP/3f/8HSZKwZMkSr50r5EPCYDDAaDTCarUCAKxWK6qrq52GZ4JNqLQ7NzcXpaWl+O//\n/m+IogiDwYCKigr783V1dRBFMaj+wmyXk5OD77//Hr179w7Kz3r//v0oKirC+PHjkZmZiaqqKjz+\n+OMoLS0N+s+4/bNTqVR4+OGHcfDgQa/9bId8SOh0OqSnp2PLli0AgC1btiA9PT3gu+HXEwrtXrFi\nBQoKCrBq1SqoVCoAwLBhw3D58mX88MMPAIB//OMfyMrK8mWZPaapqQmVlZX2xzt37oRWqw3az/qJ\nJ57Anj17sHPnTuzcuRO9e/fG+++/j5kzZwbtZwwAly5dQmNjIwBAkiRs27YN6enpXvvZ5k2HABQV\nFWHhwoVoaGiARqNBbm4u0tLSfF1Wj1m2bBm2b9+O2tpaxMbGIiYmBlu3bg3qdhcWFmLy5Mno378/\nIiIiAADJyclYtWoVDh48iMWLF6OlpQV9+vTBn//8Z8THx/u44htXW1uL2bNno7m5GaIoQqvVYsGC\nBbjpppuC+rNul5mZiby8PAwePDhoP2MAOHfuHObMmQOr1QqbzYYBAwbgxRdfREJCglfazZAgIiK3\nQn64iYiI3GNIEBGRWwwJIiJyiyFBRERuMSSIiMgthgSRHxgyZAhKS0t9XQaRk5Dfu4nIlczMTNTW\n1tr3OwKAX/7yl3jppZd8WBWR/BgSRG7k5eXhtttu83UZRD7F4SaiLvjkk08wbdo0LFmyBCNHjkRW\nVha+/fZb+/NGoxFPPvkkRo8ejYkTJ+Ljjz+2P2e1WpGXl4cJEybglltuwQMPPOCwjcY333yDe+65\nB6NGjcIrr7yC9nWupaWlmD59OkaOHIkxY8bgP//zP+VrMIU89iSIuujIkSPIysrCd999h6+++grP\nPPMMvv76a8TExGD+/PkYNGgQdu/ejeLiYsyYMQMpKSkYO3Ys1qxZg61bt2L16tVITU3FqVOn7FuG\nAMCuXbuwYcMGmM1mPPDAA7j77rtx5513YuXKlbj99tuxdu1aWCwWHD161Ietp1DDngSRG08//TRG\njRpl/6+9VxAXF4f/+I//gFKpxC9+8QukpqZi165dqKysxMGDB/H8888jPDwc6enpmDJlCjZt2gQA\nWL9+PebNm4e0tDQIgoChQ4ciNjbWfr5Zs2ZBo9EgKSkJY8aMwcmTJwEAYWFhqKioQHV1tcNNZYjk\nwJAgcmPVqlX44Ycf7P899NBDAIDExEQIgmB/XVJSEqqrq1FdXQ2tVovo6GiH54xGIwCgqqoKffv2\ndXs+vV5v/zoyMhJNTU0AgN/+9reQJAkPPvgg7r33XmzYsKFH20nUGQ43EXWR0WiEJEn2oKisrERm\nZiYSEhJw8eJFmM1me1C03xUOAHr37o2ysjIMHjy4S+fT6/VYtmwZAOCHH37AjBkz8NOf/hT9+vXr\nwVYRucaeBFEX1dXV2ecHPv/8cxQVFWHcuHEwGAy45ZZbsGLFCrS0tODkyZPYsGED7r//fgDAlClT\nsHLlSpw9exaSJOHkyZOor6+/7vk+//xzVFVVAQC0Wi0EQYAo8p8uyYM9CSI3nnzySYd1ErfddhvG\njx+PESNGoLS0FD/72c8QHx+PN954wz63sGLFCixevBg///nPodFoMGfOHPtltDNmzEBraysee+wx\n1NfXIy0tDatWrbpuHUePHsWf/vQnmM1m6HQ6LFq0CCkpKd5pNNE1eD8Joi745JNPsH79eqxbt87X\npRDJgn1WIiJyiyFBRERucbiJiIjcYk+CiIjcYkgQEZFbDAkiInKLIUFERG4xJIiIyC2GBBERufX/\nAaFPSAi26riTAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.9053\n",
            "Validation accuracy 0.924\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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XOp73+pAxGC+YuJ5P/2gJgEeePs9//srBpWymRLIqmHWcLtREt2blqqrA9eRC2krGn7aQ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\na/mxyAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "he relu\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "6430023b9ec048f98435d04eefe98fef",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fnmbCoWMNaPdwkL0g04y9JRa38s5J0NmXg5/LuYJftXTp0qUev1MAtbba4M0Q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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.9067\n",
            "Validation accuracy 0.92\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/W+bCfIXZhSozC1WKFXvF8cmYQTphkoxLKyWfjknrw9KxDA3T0DFbBE8IEZhr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\nTYRFDwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gJUNODKZHFWb",
        "colab_type": "code",
        "outputId": "8e4e05f4-6653-48c4-e359-cb733359e1ca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "f1498b4d8fb94c5abc601f8bf65073d7",
            "5e3194bb7bdd446abfe2450f28416409",
            "e925e7b33eec4dfab50418ece906ee6c",
            "66d419944d4d425fb5c33ac4ad64c3ab",
            "1e6fac99dc5042efac618bd81b959401",
            "77daf3a3060d4a48b9c4ff2049a9ebb1",
            "e1804ecb24a849c194134ad323137dce",
            "45891a23514f4b18b34bf78b8993ab4e",
            "c23b25407ebe4f0c94af1fa695d4535b",
            "ff6364fc04564fef971f430db445ace4",
            "690901620eab4298b55a2724ffbde566",
            "4c7f583b166843dc84f2098427bd5f13",
            "cb1367dd80634c97997019d7054f3c26",
            "76ff97cba95e43cca91a1be6144e7b2f",
            "cfe41b71ae9e44ac82a1353d736b88f5",
            "74a9279693ca48e0a4d658b2caaf9ba9",
            "83e9097cfa00431caa65e95e8a020f02",
            "72fc43fba2a546f399b9572f2799c14a",
            "502b0176276c40d99f9d83cb788ed6f9",
            "d0732595c0564088b3b81d7b9ebade46",
            "e78e9d6aeb544b2586924c2971d5473b",
            "5670c924a04b4f14a69b5a8330d74254",
            "33d681684c6a4e3eb8f4ba9c4c489e0e",
            "9fad6c483afe4a85a3d8ad6120b5f53f",
            "f162e0693d564bd4b37d0e9c8a4851cb",
            "c61d42dd5cd44311ad940bd1954b37ed",
            "1cb05c0f860c4258993540ead7c43c7d",
            "e25b4596b4e4443ca24cf3b78324c3d1",
            "edaeb1555e644303a711362eddb006f6",
            "b736afbf8a9046e0b8b684b33e288f28",
            "071a4d9d6eec405ea791b8b52fd4984d",
            "fc71630fafb447dca64ec78854bc7249"
          ]
        }
      },
      "source": [
        "for init_method in ['zeros', 'random', 'xavier', 'he']:\n",
        "  for activation_function in ['leaky_relu']:\n",
        "    print(init_method, activation_function)\n",
        "    model = FFNetwork(init_method=init_method, activation_function=activation_function, leaky_slope=0.1)\n",
        "    model.fit(X_train, y_OH_train, epochs=50, eta=0.5, algo=\"GD\", display_loss=True)\n",
        "    post_process(plot_scale=0.05)\n",
        "    print('\\n--\\n')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "zeros leaky_relu\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f1498b4d8fb94c5abc601f8bf65073d7",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Yt62K0GAtScYons4Zj6LI9mRCCP+kUdVrL2u79dZb2blzJ4ryzUDO4XBw2223\n8dlnn9Ha2kpqaiqff/55jwbbl/jqmtneIyd5bd0B2i46XWWhwVr+1TyW8SMHdfl9e5JcVwgM0ufA\n0FPXzDyaZtTr9WzZssWtbOvWra5pwpaWFr8ZmQS6mrozbokMoLXNwbG6wPofSgjRt3iUgX7xi1/w\n05/+lJtuusn1pOnDhw+zcuVKAMrKynjwwQd7NFDRPYbERRIarKWl7Zu9NUOCtSTGBd7yYCFE3+FR\nMrvzzjt5//33+eijj6ivr2fq1KlMnTrVtZ3TnXfeyZ133tmjgYrukZKkJ8kYxeHjjVx0qIQEKSQZ\no0hJ0vs6NCGE6DKP5wZ1Oh2TJk2irq6OuLg4VyIT/kVRNDydM57t+6388b2DTDLF8aN/HiOLP4QQ\nfs2jZFZfX89TTz3F3r17GTBgAI2Njdx8882sWLHCb5aki28oioa7bjby/mfHOHn6vCQyIYTf82gB\nSEFBAWPGjGHXrl1s376dXbt2YTKZyM/P7+n4RA9KGaHn8PHTnLtw0dehCCHEDfEomX3++ecsXbqU\n/v37A9C/f39+/vOfs2fPnh4NTvSslBF6HE6V8mr7tRsLIUQv5lEyi46OpqKiwq2ssrKSqKioHglK\neMfIhGj6hwZRVnHS16EIIcQN8eia2fz58/nRj37E97//fYxGIxaLhb/+9a/89Kc/7en4RA/SKgrj\nknTsr7DhVFUUjVw7E0L4J4+S2f33309iYiIlJSUcOnSI2NhYXn75ZVJTU3s6PtHDUkbo2fVVPUdr\nzzDcICNtIYR/8nhpfmpqqlvycjgcrFy5UkZnfm5ckh4NUHbkpCQzIYTf6vKTph0OB6+//np3xiJ8\nIKp/CEnGKPZV2HwdihBCdFmXkxmAB3sUCz+QMkJPde0ZTje3+DoUIYTokhtKZhpZMNAnpIy4tFv+\nvkoZnQkh/FOn18w++eSTq9a1tbV1ezDCN4bERTAgIoR9FTZ5+rQQwi91msyeffbZTg82GAzdGozw\nDY1G41rVeNHhJEh7QwN2IYTwuk6T2befYSb6rpQRg/iozMrhY42Yhul8HY4QQlwXeaKmAOA7wwai\nVWDz58c5fOI0Q+IiSUnSyybEQgi/4LX5pKqqKnJycsjIyCAnJ4fq6up2bRwOB4WFhaSlpZGenk5x\ncbHP6latWsV3v/tdZs2axezZs9m2bZur7vz58zz55JOkp6eTmZnJhx9+2F2nyWdCgrT0Cwli7+GT\nrN9Wxe/Wf8nLa/fidMqKVSFE7+e1kVl+fj5z587FbDazfv168vLyKCoqcmuzYcMGampq2LRpE42N\njWRnZ5OamkpCQoLX61JSUm9I/2gAABmoSURBVHj44YcJCwvj4MGDzJs3j+3bt9OvXz/efPNNIiIi\neP/996muruYHP/gBmzZtIjw83Funs9vtq7TR0ubgcupqaXNQaWliX6WN8SMH+TQ2IYS4Fq+MzGw2\nG+Xl5WRlZQGQlZVFeXk5drv7bu2lpaXMmTMHRVHQ6XSkpaWxceNGn9RNmTKFsLAwAEaPHo2qqjQ2\nNgLw3nvvkZOTA8CwYcMYN24cH330UU+ewh5XU3eGiw73UVhrm4NjdWd8FJEQQnjOK8nMarUSFxeH\nVqsFQKvVEhsbi9VqbdfOaPxmabjBYKC2ttYndVdat24dQ4YMYfDgwQBYLBbi4+OveZw/GRIXSWiw\n1q0sJFhLYlykjyISQgjPyQKQa9i1axcrV67kD3/4Q7e+r14f0eVjY2K6P8FM10fw9zIL5ZV22hxO\nQoIVxgwbyPTJw9D2gkUgPdHn3k76HBikz93DK8nMYDBQV1eHw+FAq9XicDior69vd5+awWDAYrGQ\nkpICuI+cvF0HsGfPHp555hlWr15NUlKSq9xoNHLixAl0Op3ruMmTJ1/XObHZmru0uCImJpKGhp6Z\n+nvivmQ+O1jP70vKGZUwgCfuS8Zua+6Rz7oePdnn3kr6HBikz55TFE2ngwCvTDPq9XpMJhMlJSUA\nlJSUYDKZXMngsszMTIqLi3E6ndjtdjZv3kxGRoZP6vbt28eSJUt45ZVXGDt2bLs4165dC0B1dTX7\n9+9nypQpPXT2vEdRNEz+ThyTTHFUWE7T5nD6OiQhhPCI16YZCwoKyM3NZfXq1URFRbF8+XIAFixY\nwOLFi0lOTsZsNlNWVsbMmTMBWLRoEYmJiQBeryssLOTChQvk5eW5+vDSSy8xevRoHnnkEXJzc0lP\nT0dRFJ577jkiIro+bdjbTEkx8MmXtXxxqIHUcYN9HY4QQlyTRpWt732iN04zXuZUVf7td5+gj+rH\nz+f+U49+lidkKiYwSJ8Dg19PMwr/omg03Jls4GBNI/WN530djhBCXJMkM9GhO5INaIAd+6zXbCuE\nEL4myUx0SBfVj7HDdew4YJUtrYQQvZ4kM3FVd6YYsDe18NXRU74ORQghOiXJTFzVLTcNIrxfENv2\nWXwdihBCdEqSmbiq4CAtt31nMF98fZLm8/JkcSFE7yXJTHTqzhQDFx1O3vl7BX/bUcXeIyflGpoQ\noteRvRlFpxJjIwgN1vLR3ktTjSHBWpKMUTydM14e3CmE6DVkZCY6ta/ShsPpRAVU3J9zJoQQvYUk\nM9Epec6ZEMIfSDITnZLnnAkh/IEkM9GplCQ9ScYoQoIv/aooioYkYxQpSXofRyaEEN+QZCY6pSga\nns4Zz6PmcSQZo0BVeTBjtCz+EEL0KpLMxDUpiobxIwex6L5kFEXhvU+P+jokIYRwI8lMeGxgZChT\nxxv5+EAtDbKbvhCiF5FkJq7LPbcNRaOBdz+p9nUoQgjhIslMXJeBkaFMvTmeHftldCaE6D0kmYnr\ndk+qjM6EEL2LJDNx3WR0JoTobbyWzKqqqsjJySEjI4OcnByqq6vbtXE4HBQWFpKWlkZ6ejrFxcU+\nq9u+fTuzZ89m3LhxLF++3C3O3/72t6SmpmI2mzGbzRQWFnbHKfIr96QOBVSK/u+gbEAshPA5r200\nnJ+fz9y5czGbzaxfv568vDyKiorc2mzYsIGamho2bdpEY2Mj2dnZpKamkpCQ4PW6xMREli1bxsaN\nG2ltbW3Xn+zsbJYuXeqt09frRIeHEBUeypdVp/iy6hShsgGxEMKHvDIys9lslJeXk5WVBUBWVhbl\n5eXY7Xa3dqWlpcyZMwdFUdDpdKSlpbFx40af1A0dOhSTyURQkDxYoCP7Km2cvfDNM85kA2IhhC95\nJZlZrVbi4uLQai/t8afVaomNjcVqtbZrZzQaXa8NBgO1tbU+qbuWd999l1mzZvHwww+zZ88ej47p\nS2rqztDW5nQrkw2IhRC+IsOOLnjggQd49NFHCQ4OZseOHTz22GOUlpYycOBAj99Dr4/o8ufHxPh+\nk9/kUbFs3FnDhVaHqywkRMu4UbE9El9v6LO3SZ8Dg/S5e3glmRkMBurq6nA4HGi1WhwOB/X19RgM\nhnbtLBYLKSkpgPvIydt1nYmJiXH9fMcdd2AwGDh8+DCTJk3y+JzYbM1dWjARExNJQ4PvRz9D9f0Z\nboii0tJES9ulhBYWomWovn+3x9db+uxN0ufAIH32nKJoOh0EeGWaUa/XYzKZKCkpAaCkpASTyYRO\np3Nrl5mZSXFxMU6nE7vdzubNm8nIyPBJXWfq6upcP3/11VecOHGC4cOH3/iJ8iOXNyD+V/NY7psy\nnH8aFUNjcysHa075OjQhRADy2jRjQUEBubm5rF69mqioKNdy9wULFrB48WKSk5Mxm82UlZUxc+ZM\nABYtWkRiYiKA1+t2797NU089RXNzM6qq8u6777Js2TKmTJnCihUr+PLLL1EUheDgYF566SW30Vqg\nuLwB8fiRg2htc5D/h1388b2DPP/IZEJDtNd+AyGE6CYaVVXl5iAf8Pdpxo4cqjnF8j/tIW1iAnPT\nRnXb+/bmPvcU6XNgkD577lrTjLIARHSb0UMGMu2f4tm8+zgDI0JpczgZEhdJSpJe7j0TQvQoSWai\nW82eksS2Mgtvb61ABbmZWgjhFbI3o+hWh0+cRqPRcHkCVW6mFkJ4gyQz0a1q6s5w8aLcTC2E8C5J\nZqJbDYmLJCTYfSVjUJBCYlzg3RgqhPAeSWaiW6Uk6UkyRhH6j4SmARwOJ7EDwnwbmBCiT5NkJrrV\nt2+mfuifx9C/XxCvvLOP5vNt134DIYToAlnNKLrdlTdTAxj14bz05z389u0yZk4awomTZ2XJvhCi\nW0kyEz1uZEI0P75nDP//hnIq1h1AVSFEluwLIbqRTDMKrwgLDUKraHCqoCJL9oUQ3UuSmfCKmroz\n7bbvkiX7QojuIslMeEVHS/Y1GjAOCvdRREKIvkSSmfCKK5fsa4Cgf0w5vv/ZMc5dkFWOQogbIwtA\nhFdcXrK/r9LGsbozJMZFcu5CG2tKD/Lif39O5uSh2JouyCpHIUSXSDITXvPtJfsAkf1D+M/iMt58\n9ytANiYWQnSNTDMKn3I4VYK13/waXlrleFpWOQohroskM+FTNXVnaPvWxsQtbU4OH2v0UURCCH8k\n04zCpy6vcmxpc7iVf7jnBEMHX6qz7bWgjwiRa2lCiKuSZCZ86vIqx0pLE61tDkKCtcTHhNN20cHr\n679E0SA7hgghrslr04xVVVXk5OSQkZFBTk4O1dXV7do4HA4KCwtJS0sjPT2d4uJin9Vt376d2bNn\nM27cOJYvX+5xnOL6XLkxcfaU4fyreSz/37wJmO8c3sGOIXItTQjRMa+NzPLz85k7dy5ms5n169eT\nl5dHUVGRW5sNGzZQU1PDpk2baGxsJDs7m9TUVBISErxel5iYyLJly9i4cSOtra0exymuX0erHI83\nnG23Y0hLm5Md+62MG6bjQLWdmrozspRfCAF4aWRms9koLy8nKysLgKysLMrLy7Hb7W7tSktLmTNn\nDoqioNPpSEtLY+PGjT6pGzp0KCaTiaCg9vm+s+NE9+hwxxDg80MNPL7yI1773wOs31bF79Z/yctr\n97ZLfEKIwOKVZGa1WomLi0OrvfSPk1arJTY2FqvV2q6d0Wh0vTYYDNTW1vqk7lr96cpxwnPf3jEk\nNFjLmKEDyZiUSGubkzaHs930o9OpsvfISf62o4q9R05KghMigMgCEB/R6yO6fGxMTGQ3RtJ7vfj4\nFD4/WEfVidMMj49mwpg4ij/4Gg2XrqNd1tLm5P921fB/u45xtLaJllYHoSFaRg8dSOHC29H66RRk\noHzPV5I+B4ae6LNXkpnBYKCurg6Hw4FWq8XhcFBfX4/BYGjXzmKxkJKSAriPgLxdd63+dOW4K9ls\nzV0aOcTERNLQEDg7zQ+PCWfSdwbT0HAGu60ZfURIu6X8iga+rml0S3AXWh0crD7Flp3VpCTp2Vdp\n86trbIH2PYP0OVB0tc+Koul0EOCVaUa9Xo/JZKKkpASAkpISTCYTOp3OrV1mZibFxcU4nU7sdjub\nN28mIyPDJ3Wd6epx4sZ1NP04eshAMiYNade2pc3B1j3H+ff/+YLfrf9SrrEJ0Yd5bZqxoKCA3Nxc\nVq9eTVRUlGu5+4IFC1i8eDHJycmYzWbKysqYOXMmAIsWLSIxMRHA63W7d+/mqaeeorm5GVVVeffd\nd1m2bBlTpkzp9DjRszrasPjyyOvDPSfa3Xy9r8J9kdGV19jGjxyE06n63ahNCNGeRlVV+RPVB2Sa\n0XOe9NnpVHl57V63m6+TjFEY9P3Z8sWJdu11kaFMMsVyoMpOfeN52tqcbjdmAz5NcvI9Bwbps+eu\nNc0oC0BEn9DZiG3H/lq3EZtW0RASrLDps2Nc+fdES5uDr4818s7fj/D1sdMcb2im1cMkJyM8IXxL\nkpnoMzq6+bqj7bIuJ6b126vY8HG123s4nCrv7TzmVnY5yf3PpkNUWJuotZ2j9aLT9biaJXNu5j+K\nyzr8DLi+5He5XPajFOL6aAsKCgp8HUQgOn++la5M8IaHh3LuXOu1G/YhN9JnjUZD6tjBJMZFYNT3\nZ/qEBO6bkoSiaGhpc7D38EkcVwzPQoMVTMMGUn/qvNv7qCpU157h9NlWV3uHU8V2+gK7vqqjpr6Z\niw6nq/z02VYiwoJ568MjfPD5ccqrTrH38EkO1pxisimOFW+VsXn3ccqr7B2W7/26wVWeOnYwqgpl\nFTZ2fVXH+VYHsQPC0GguJb+eLAd6/DMul392sJ6m5hav9a03nIve3ueeOEff7vP1/L/cv3/I1evl\nmplvyDUzz/VUn692nS1tQgJvbCh3m5oMDVYYO0zHF4dPtnuf0GCFljZnu/KOaDQwKCoUW1OL2xRn\nkKLBNGwgXx09xUXHNxUhQQrfnzaCXeWXEmZrm5PQYIUkY/RVR4TdVX55ZNnROerpz+5t5XIueuYc\nXc/G4de6ZibJzEckmXmuJ/t8eVrvyuts0PH/kB0nOS0zb01k02fH3MqDgxSGxEVQcaKp3WeGhWg5\n3+poV369NP94ooBbGRARFkTz+Ytu991pNBATHcbJ0+fdkqiiAeOgcCy2c26/j1pFQ8qIS+diX4XN\nbfSqVTSMiI+m4sTpduWjEqL5+rh7eZBWw+ghAzhU0+iWqIO0GkxD2yfwIK2GscN0fFlt97h83HAd\nB6ralycn6dhf2VG5nv2VNo/LZ0y4tO/qB58fb1eXkjSIfZUn25XfPGIQZRWBU55+66UV3e9/dqz9\nMSMHUXbE/ZjQYC3/ah7rdlmgM5LMeilJZp7zRZ+vJ8ld7a/O60l+ocEKd91s5O97LbRe8bDSYK3C\n0MGRHDlxul2MuqhQ7E0t7cojwoJpPt/WrrxfiJYLHSTRIK3G7R+ZK8tVFbfEJER30QDZU4Yz647h\nHrXvFTdNC+FvLi8mmXXHcMaPHISiaDp8XM3TOeMJClI6LL955KB2N3gnGaOYdfuwDsqjmXP3SEbE\nR7uVj0yI5p8nDyH0W5suhwZruWOcocPyabfEd1iePjGxw/J/njy0w/LH7ktm0ezkDutm3T6U0GDl\nW+UK99w2pMPyjEmJhHyrPCRYYebEhA7L0yZ0UB6kMGNCAiFB7cunX638n+I7Lr/l+sofnDmKB2eO\n6rBu2i3GDsvvDrDyeek3MS/9po6PGW9oXx6sJTGu+7a1ktWMQlyHjlZMdlbe0e0CV7uN4Mpye3Mr\nun+sZgQ6XJE56/ZhHDlxusfKO//s4Rw50dSuPPvOJKqsZ9qVf++uEdTUNbcr//7dIznWcLZd+f3T\nRnLiZPvynGkjsXRQ/sC0kVg7Kp9+E1bbufblM27Cave8fOr4eAB2H2poV/cvM0ZRaz/frnzujFHU\nBVD53bdcmor9/OuT7Y9JG03dqQtX/R3rDjLN6CMyzeg56XPH055XLuXvqXJvfvaVCdwbfesN56K3\n97knztG3++wpuWbWS0ky85z0OTBInwODX280LIQQQvQkSWZCCCH8niQzIYQQfk+SmRBCCL8nS/N9\n5EY2jw3EjWelz4FB+hwYutLnax0jqxmFEEL4PZlmFEII4fckmQkhhPB7ksyEEEL4PUlmQggh/J4k\nMyGEEH5PkpkQQgi/J8lMCCGE35NkJoQQwu9JMhNCCOH3JJn5kaqqKnJycsjIyCAnJ4fq6mpfh9St\nli9fzvTp0xk9ejRff/21q7wv9/vUqVMsWLCAjIwMZs2axeOPP47dbgdg79693HvvvWRkZPDwww9j\ns9l8HG33eeyxx7j33nvJzs5m7ty5fPXVV0Df/q4BXn31Vbff7778HQNMnz6dzMxMzGYzZrOZbdu2\nAT3Ub1X4jQcffFBdt26dqqqqum7dOvXBBx/0cUTd67PPPlMtFos6bdo09dChQ67yvtzvU6dOqZ9+\n+qnr9b//+7+r//Zv/6Y6HA41LS1N/eyzz1RVVdVVq1apubm5vgqz2zU1Nbl+fv/999Xs7GxVVfv2\nd33gwAH1kUcecf1+9/XvWFXVdv8vq6raY/2WkZmfsNlslJeXk5WVBUBWVhbl5eWuv+L7gokTJ2Iw\nGNzK+nq/BwwYwOTJk12vx48fj8Vi4cCBA4SGhjJx4kQAHnjgATZu3OirMLtdZGSk6+fm5mY0Gk2f\n/q5bW1t57rnnKCgocJX19e/4anqq37Jrvp+wWq3ExcWh1WoB0Gq1xMbGYrVa0el0Po6u5wRSv51O\nJ3/+85+ZPn06VqsVo9HoqtPpdDidThobGxkwYIAPo+w+zz77LDt27EBVVX7/+9/36e965cqV3Hvv\nvSQkJLjKAuE7BvjZz36GqqpMmDCBp556qsf6LSMzIXqJ559/nv79+zNv3jxfh+IVy5YtY+vWrSxZ\nsoSXXnrJ1+H0mD179nDgwAHmzp3r61C87n/+53/429/+xjvvvIOqqjz33HM99lmSzPyEwWCgrq4O\nh8MBgMPhoL6+vt20XF8TKP1evnw5R48e5T//8z9RFAWDwYDFYnHV2+12FEXpU3+xX5adnc3OnTsZ\nPHhwn/yuP/vsMyoqKpgxYwbTp0+ntraWRx55hKNHj/b57/jydxcSEsLcuXP54osveux3W5KZn9Dr\n9ZhMJkpKSgAoKSnBZDL5/fTLtQRCv1esWMGBAwdYtWoVISEhAIwbN44LFy6we/duAP7yl7+QmZnp\nyzC7zdmzZ7Fara7XW7ZsITo6us9+1wsXLmT79u1s2bKFLVu2MHjwYN58803mz5/fZ79jgHPnznHm\nzBkAVFWltLQUk8nUY7/b8nBOP1JRUUFubi5NTU1ERUWxfPlykpKSfB1Wt3nhhRfYtGkTJ0+eZODA\ngQwYMIB33323T/f78OHDZGVlMWzYMPr16wdAQkICq1at4osvviA/P5+Wlhbi4+P59a9/zaBBg3wc\n8Y07efIkjz32GOfPn0dRFKKjo1m6dCljx47t09/1ZdOnT+f1119n1KhRffY7Bjh27BhPPPEEDocD\np9PJiBEj+MUvfkFsbGyP9FuSmRBCCL8n04xCCCH8niQzIYQQfk+SmRBCCL8nyUwIIYTfk2QmhBDC\n70kyE0J4bPTo0Rw9etTXYQjRjuzNKIQfmz59OidPnnTtZwhw3333kZeX58OohPA+SWZC+LnXX3+d\n22+/3ddhCOFTMs0oRB/017/+lQceeIDnnnuOCRMmkJmZySeffOKqr6ur49FHH2XSpEmkp6fz1ltv\nueocDgevv/46aWlp3HLLLcyePdtt+6mPP/6YmTNnMnHiRAoLC7m878LRo0eZN28eEyZMYPLkyTz5\n5JPe67AIeDIyE6KP2rdvH5mZmXz66ae8//77PP7443zwwQcMGDCAp556iptuuolt27ZRWVnJj3/8\nYxITE0lNTWXNmjW8++67vPHGGwwfPpxDhw65ttoC2Lp1K2+//TbNzc3Mnj2badOmcdddd7Fy5Uru\nuOMOioqKaGtrY//+/T7svQg0MjITws8tWrSIiRMnuv67PMrS6XQ89NBDBAcHc8899zB8+HC2bt2K\n1Wrliy++4Gc/+xmhoaGYTCbmzJnD+vXrASguLuanP/0pSUlJaDQaxowZw8CBA12ft2DBAqKiojAa\njUyePJmDBw8CEBQUhMViob6+3u3hi0J4gyQzIfzcqlWr2L17t+u/+++/H4C4uDg0Go2rndFopL6+\nnvr6eqKjo4mIiHCrq6urA6C2tpYhQ4Zc9fNiYmJcP4eFhXH27FkAnnnmGVRV5fvf/z7f/e53efvt\nt7u1n0J0RqYZheij6urqUFXVldCsVivTp08nNjaW06dP09zc7Epol5/yDDB48GBqamoYNWrUdX1e\nTEwML7zwAgC7d+/mxz/+MbfeeitDhw7txl4J0TEZmQnRR9ntdtf1q/fee4+KigqmTp2KwWDglltu\nYcWKFbS0tHDw4EHefvtt7r33XgDmzJnDypUrqa6uRlVVDh48yKlTp675ee+99x61tbUAREdHo9Fo\nUBT5J0Z4h4zMhPBzjz76qNt9ZrfffjszZswgJSWFo0ePcttttzFo0CBeeeUV17WvFStWkJ+fz5Qp\nU4iKiuKJJ55wLe//8Y9/TGtrKw8//DCnTp0iKSmJVatWXTOO/fv386tf/Yrm5mb0ej3PPvssiYmJ\nPdNpIb5FnmcmRB/017/+leLiYv785z/7OhQhvELmAIQQQvg9SWZCCCH8nkwzCiGE8HsyMhNCCOH3\nJJkJIYTwe5LMhBBC+D1JZkIIIfyeJDMhhBB+T5KZEEIIv/f/AI5XwP0ZPqQjAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.2507\n",
            "Validation accuracy 0.248\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAADnCAYAAAC9roUQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "random leaky_relu\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "c23b25407ebe4f0c94af1fa695d4535b",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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httbU7efZK4T6s009er6aejrmvoxj1r5QGy/g25hFUfD4y3SnoTBo0KBOX/ihhx7qUYfa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\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.8933\n",
            "Validation accuracy 0.9\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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eBF3pMF3pmxNeep7PyFSFayNFBifKDE+WGZ+uce56jprlzvpsxFTpiJuk4yap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\nLkEQhIP8D8lCLVK4cR2uAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "xavier leaky_relu\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "83e9097cfa00431caa65e95e8a020f02",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SJPmtXZIkXHvpMKQkDEWSKQyZk5Nx27RU6HSyX9plWUJ81GAcL6lF4zkbnM4L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\nTpvFQ2yN4CEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.8027\n",
            "Validation accuracy 0.812\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5JoTjugyP5+fTLkEFcN3zU3bOZl7UzpY4juty5lx6oUwTCJYN1yG6Dpoq0zY1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\nCEIJiaArCIJQQv8P6cNdCy6XJugAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n",
            "he leaky_relu\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f162e0693d564bd4b37d0e9c8a4851cb",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=50), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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httbU7efZK4T6s009er6aejrmvoxj1r5QGy/g25hFUfD4y3SnoTBo0KBOX/ihhx7qUYfa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\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Training accuracy 0.8933\n",
            "Validation accuracy 0.9\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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eBF3pMF3pmxNeep7PyFSFayNFBifKDE+WGZ+uce56jprlzvpsxFTpiJuk4yap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\nLkEQhIP8D8lCLVK4cR2uAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 18 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "--\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0n7010SFHHNo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}