Multi_Class_Text_Classification_Model_Comparison_and_Selection.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Multi-Class Text Classification Model Comparison and Selection.ipynb",
      "version": "0.3.2",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "PptECX0_LsEU",
        "colab_type": "code",
        "outputId": "514d8ed6-ab5f-494a-e592-72796987297b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 851
        }
      },
      "source": [
        "import nltk\n",
        "nltk.download(\"popular\")\n",
        "\n",
        "import logging\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from numpy import random\n",
        "import gensim\n",
        "import seaborn as sn\n",
        "#import nltk\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
        "from sklearn.metrics import accuracy_score, confusion_matrix\n",
        "import matplotlib.pyplot as plt\n",
        "from nltk.corpus import stopwords\n",
        "import re\n",
        "from bs4 import BeautifulSoup\n",
        "%matplotlib inline"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading collection 'popular'\n",
            "[nltk_data]    | \n",
            "[nltk_data]    | Downloading package cmudict to /root/nltk_data...\n",
            "[nltk_data]    |   Package cmudict is already up-to-date!\n",
            "[nltk_data]    | Downloading package gazetteers to /root/nltk_data...\n",
            "[nltk_data]    |   Package gazetteers is already up-to-date!\n",
            "[nltk_data]    | Downloading package genesis to /root/nltk_data...\n",
            "[nltk_data]    |   Package genesis is already up-to-date!\n",
            "[nltk_data]    | Downloading package gutenberg to /root/nltk_data...\n",
            "[nltk_data]    |   Package gutenberg is already up-to-date!\n",
            "[nltk_data]    | Downloading package inaugural to /root/nltk_data...\n",
            "[nltk_data]    |   Package inaugural is already up-to-date!\n",
            "[nltk_data]    | Downloading package movie_reviews to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package movie_reviews is already up-to-date!\n",
            "[nltk_data]    | Downloading package names to /root/nltk_data...\n",
            "[nltk_data]    |   Package names is already up-to-date!\n",
            "[nltk_data]    | Downloading package shakespeare to /root/nltk_data...\n",
            "[nltk_data]    |   Package shakespeare is already up-to-date!\n",
            "[nltk_data]    | Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]    |   Package stopwords is already up-to-date!\n",
            "[nltk_data]    | Downloading package treebank to /root/nltk_data...\n",
            "[nltk_data]    |   Package treebank is already up-to-date!\n",
            "[nltk_data]    | Downloading package twitter_samples to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package twitter_samples is already up-to-date!\n",
            "[nltk_data]    | Downloading package omw to /root/nltk_data...\n",
            "[nltk_data]    |   Package omw is already up-to-date!\n",
            "[nltk_data]    | Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]    |   Package wordnet is already up-to-date!\n",
            "[nltk_data]    | Downloading package wordnet_ic to /root/nltk_data...\n",
            "[nltk_data]    |   Package wordnet_ic is already up-to-date!\n",
            "[nltk_data]    | Downloading package words to /root/nltk_data...\n",
            "[nltk_data]    |   Package words is already up-to-date!\n",
            "[nltk_data]    | Downloading package maxent_ne_chunker to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package maxent_ne_chunker is already up-to-date!\n",
            "[nltk_data]    | Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]    |   Package punkt is already up-to-date!\n",
            "[nltk_data]    | Downloading package snowball_data to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package snowball_data is already up-to-date!\n",
            "[nltk_data]    | Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Package averaged_perceptron_tagger is already up-\n",
            "[nltk_data]    |       to-date!\n",
            "[nltk_data]    | \n",
            "[nltk_data]  Done downloading collection popular\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5mqMtpvTLtoY",
        "colab_type": "text"
      },
      "source": [
        "# Multi-Class Text Classification Model Comparison and Selection\n",
        "inspired by https://towardsdatascience.com/multi-class-text-classification-model-comparison-and-selection-5eb066197568\n",
        "\n",
        "dataset used for multiclassification task : large data set of Stack Overflow questions and tags, publicly available at this Cloud Storage URL: https://storage.googleapis.com/tensorflow-workshop-examples/stack-overflow-data.csv."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pxrBCMT2Ax3u",
        "colab_type": "text"
      },
      "source": [
        "## Dataset preparation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AgkeYAVCAYqm",
        "colab_type": "text"
      },
      "source": [
        "### loading dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tzauinpnAT0Q",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        },
        "outputId": "2c787aa1-41cd-463d-a83a-6caed9580078"
      },
      "source": [
        "df = pd.read_csv('https://storage.googleapis.com/tensorflow-workshop-examples/stack-overflow-data.csv')\n",
        "df = df[pd.notnull(df['tags'])]\n",
        "print(df.head(10))\n",
        "print(df['post'].apply(lambda x: len(x.split(' '))).sum())"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                                                post           tags\n",
            "0  what is causing this behavior  in our c# datet...             c#\n",
            "1  have dynamic html load as if it was in an ifra...        asp.net\n",
            "2  how to convert a float value in to min:sec  i ...    objective-c\n",
            "3  .net framework 4 redistributable  just wonderi...           .net\n",
            "4  trying to calculate and print the mean and its...         python\n",
            "5  how to give alias name for my website  i have ...        asp.net\n",
            "6  window.open() returns null in angularjs  it wo...      angularjs\n",
            "7  identifying server timeout quickly in iphone  ...         iphone\n",
            "8  unknown method key  error in rails 2.3.8 unit ...  ruby-on-rails\n",
            "9  from the include  how to show and hide the con...      angularjs\n",
            "10286120\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EiShZ53C_kao",
        "colab_type": "text"
      },
      "source": [
        "### exploring the dataset\n",
        "- Is dataset balanced ?\n",
        "- Dataset content"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pFXVE8ZkL7UP",
        "colab_type": "code",
        "outputId": "d40ffa6c-2e2a-4e52-dfdb-a49cbe333ec7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 322
        }
      },
      "source": [
        "my_tags = ['java','html','asp.net','c#','ruby-on-rails','jquery','mysql','php','ios','javascript','python','c','css','android','iphone','sql','objective-c','c++','angularjs','.net']\n",
        "plt.figure(figsize=(10,4))\n",
        "df.tags.value_counts().plot(kind='bar');"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmAAAAExCAYAAADbUR4fAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n+395etpuqZM5jgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "izIygn2tMMEZ",
        "colab_type": "code",
        "outputId": "e81eda08-c14f-4c18-d97f-05b8fc6e7511",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "def print_plot(index):\n",
        "    example = df[df.index == index][['post', 'tags']].values[0]\n",
        "    if len(example) > 0:\n",
        "        print(example[0])\n",
        "        print('Tag:', example[1])\n",
        "print_plot(10)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "when we need interface c# <blockquote>    <strong>possible duplicate:</strong><br>   <a href= https://stackoverflow.com/questions/240152/why-would-i-want-to-use-interfaces >why would i want to use interfaces </a>   <a href= https://stackoverflow.com/questions/9451868/why-i-need-interface >why i need interface </a>    </blockquote>     i want to know where and when to use it     for example    <pre><code>interface idemo {  // function prototype  public void show(); }  // first class using the interface class myclass1 : idemo {  public void show()  {   // function body comes here   response.write( i m in myclass );  }  }  // second class using the interface class myclass2 : idemo {  public void show()   {   // function body comes here   response.write( i m in myclass2 );   response.write( so  what  );  } </code></pre>   these two classes has the same function name with different body. this can be even achieved without interface. then why we need an interface where and when to use it\n",
            "Tag: c#\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WgaGwgJBMRGQ",
        "colab_type": "code",
        "outputId": "643e42f5-e83c-4300-88f0-6ab34501fe67",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "print_plot(30)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "how to chain expressions inside ngclass when using the {...}[] form  how can i add another expression to an <code>ng-class</code> directive that uses this form:   <pre><code>ng-class= {true: loading   false: loading-done }[data.loader===null]  </code></pre>   i d like to add something like this to the list:   <pre><code>{highlight:isspecial} </code></pre>   is it possible without expanding the first expression     thanks.\n",
            "Tag: angularjs\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PSflhp5jAOly",
        "colab_type": "text"
      },
      "source": [
        "### cleanning dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cduP-qwEMZB9",
        "colab_type": "code",
        "outputId": "009c9146-4e53-4507-db4c-8f0f450abf40",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "REPLACE_BY_SPACE_RE = re.compile('[/(){}\\[\\]\\|@,;]')\n",
        "BAD_SYMBOLS_RE = re.compile('[^0-9a-z #+_]')\n",
        "STOPWORDS = set(stopwords.words('english'))\n",
        "\n",
        "def clean_text(text):\n",
        "    \"\"\"\n",
        "        text: a string\n",
        "        \n",
        "        return: modified initial string\n",
        "    \"\"\"\n",
        "    text = BeautifulSoup(text, \"lxml\").text # HTML decoding\n",
        "    text = text.lower() # lowercase text\n",
        "    text = REPLACE_BY_SPACE_RE.sub(' ', text) # replace REPLACE_BY_SPACE_RE symbols by space in text\n",
        "    text = BAD_SYMBOLS_RE.sub('', text) # delete symbols which are in BAD_SYMBOLS_RE from text\n",
        "    text = ' '.join(word for word in text.split() if word not in STOPWORDS) # delete stopwors from text\n",
        "    return text\n",
        "    \n",
        "df['post'] = df['post'].apply(clean_text)\n",
        "print_plot(10)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "need interface c# possible duplicate would want use interfaces need interface want know use example interface idemo function prototype public void show first class using interface class myclass1 idemo public void show function body comes responsewrite myclass second class using interface class myclass2 idemo public void show function body comes responsewrite myclass2 responsewrite two classes function name different body even achieved without interface need interface use\n",
            "Tag: c#\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tuZVqZpEMemq",
        "colab_type": "code",
        "outputId": "f16f3cc5-d738-4ab9-bf2d-63756d234a78",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "print_plot(30)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "chain expressions inside ngclass using form add another expression ngclass directive uses form ngclass true loading false loadingdone dataloadernull like add something like list highlightisspecial possible without expanding first expression thanks\n",
            "Tag: angularjs\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M7RNWHVBQ-i0",
        "colab_type": "code",
        "outputId": "6beefe56-59fe-4119-c64d-58d909f83b27",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "df['post'].apply(lambda x: len(x.split(' '))).sum()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3424297"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CpbXpizgAkv8",
        "colab_type": "text"
      },
      "source": [
        "### splitting dataset for training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LhvsSbvARDLl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X = df.post\n",
        "y = df.tags\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state = 42)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "msiIGjeWA6fz",
        "colab_type": "text"
      },
      "source": [
        "## Naive Bayer Classification"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IWJi7KkkRGyJ",
        "colab_type": "code",
        "outputId": "640ee246-0b8d-4cff-91ae-68cbf243f344",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 503
        }
      },
      "source": [
        "from sklearn.naive_bayes import MultinomialNB\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.feature_extraction.text import TfidfTransformer\n",
        "\n",
        "nb = Pipeline([('vect', CountVectorizer()),\n",
        "               ('tfidf', TfidfTransformer()),\n",
        "               ('clf', MultinomialNB()),\n",
        "              ])\n",
        "nb.fit(X_train, y_train)\n",
        "\n",
        "from sklearn.metrics import classification_report\n",
        "y_pred = nb.predict(X_test)\n",
        "\n",
        "print('accuracy %s' % accuracy_score(y_pred, y_test))\n",
        "print(classification_report(y_test, y_pred,target_names=my_tags))\n"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "accuracy 0.7395\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "         java       0.63      0.65      0.64       613\n",
            "         html       0.94      0.86      0.90       620\n",
            "      asp.net       0.87      0.92      0.90       587\n",
            "           c#       0.70      0.77      0.73       586\n",
            "ruby-on-rails       0.73      0.87      0.79       599\n",
            "       jquery       0.72      0.51      0.60       589\n",
            "        mysql       0.77      0.74      0.75       594\n",
            "          php       0.69      0.89      0.78       610\n",
            "          ios       0.63      0.59      0.61       617\n",
            "   javascript       0.57      0.65      0.60       587\n",
            "       python       0.70      0.50      0.59       611\n",
            "            c       0.79      0.78      0.79       594\n",
            "          css       0.84      0.59      0.69       619\n",
            "      android       0.66      0.84      0.74       574\n",
            "       iphone       0.64      0.83      0.72       584\n",
            "          sql       0.66      0.64      0.65       578\n",
            "  objective-c       0.79      0.77      0.78       591\n",
            "          c++       0.89      0.83      0.86       608\n",
            "    angularjs       0.94      0.89      0.91       638\n",
            "         .net       0.74      0.66      0.70       601\n",
            "\n",
            "     accuracy                           0.74     12000\n",
            "    macro avg       0.74      0.74      0.74     12000\n",
            " weighted avg       0.75      0.74      0.74     12000\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rTBD7SdYQUhE",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "outputId": "e22e76e0-b3cd-42da-ae0d-0039d466f5cb"
      },
      "source": [
        "df_cm = pd.DataFrame(confusion_matrix(y_test,y_pred),index=my_tags, columns=my_tags)\n",
        "plt.figure(figsize = (20,10))\n",
        "sn.set(font_scale=0.8)#for label size\n",
        "sn.heatmap(df_cm, annot=True,annot_kws={\"size\": 8})# font size\n"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2a20f463c8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABDkAAAJGCAYAAABRKl46AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nERGRpKAkh4iIiIiIiIgkhf8HfuuXMACPawgAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7XNssE4uA_T-",
        "colab_type": "text"
      },
      "source": [
        "## Linear Support Vector Machine"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uW79J-RXRPHk",
        "colab_type": "code",
        "outputId": "1e738d89-1bd3-4dcb-c517-7d0c04bf0318",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        }
      },
      "source": [
        "from sklearn.linear_model import SGDClassifier\n",
        "\n",
        "sgd = Pipeline([('vect', CountVectorizer()),\n",
        "                ('tfidf', TfidfTransformer()),\n",
        "                ('clf', SGDClassifier(loss='hinge', penalty='l2',alpha=1e-3, random_state=42, max_iter=5, tol=None)),\n",
        "               ])\n",
        "sgd.fit(X_train, y_train)\n",
        "\n",
        "\n",
        "y_pred = sgd.predict(X_test)\n",
        "\n",
        "print('accuracy %s' % accuracy_score(y_pred, y_test))\n",
        "print(classification_report(y_test, y_pred,target_names=my_tags))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "accuracy 0.7895833333333333\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "         java       0.73      0.67      0.70       613\n",
            "         html       0.84      0.94      0.89       620\n",
            "      asp.net       0.88      0.95      0.92       587\n",
            "           c#       0.81      0.80      0.80       586\n",
            "ruby-on-rails       0.73      0.89      0.80       599\n",
            "       jquery       0.77      0.39      0.52       589\n",
            "        mysql       0.81      0.69      0.74       594\n",
            "          php       0.71      0.95      0.81       610\n",
            "          ios       0.83      0.57      0.67       617\n",
            "   javascript       0.72      0.58      0.64       587\n",
            "       python       0.71      0.65      0.68       611\n",
            "            c       0.79      0.88      0.83       594\n",
            "          css       0.77      0.79      0.78       619\n",
            "      android       0.84      0.86      0.85       574\n",
            "       iphone       0.82      0.81      0.81       584\n",
            "          sql       0.70      0.68      0.69       578\n",
            "  objective-c       0.81      0.90      0.85       591\n",
            "          c++       0.84      0.96      0.90       608\n",
            "    angularjs       0.87      0.96      0.91       638\n",
            "         .net       0.78      0.88      0.83       601\n",
            "\n",
            "     accuracy                           0.79     12000\n",
            "    macro avg       0.79      0.79      0.78     12000\n",
            " weighted avg       0.79      0.79      0.78     12000\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-Sg-G-HnQ9jU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "outputId": "467bcbe3-4012-4967-a74c-36eb81149d68"
      },
      "source": [
        "df_cm = pd.DataFrame(confusion_matrix(y_test,y_pred),index=my_tags, columns=my_tags)\n",
        "plt.figure(figsize = (20,10))\n",
        "sn.set(font_scale=0.8)#for label size\n",
        "sn.heatmap(df_cm, annot=True,annot_kws={\"size\": 8})# font size"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2a20f25320>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABDkAAAJGCAYAAABRKl46AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZJBDCCGEEEIIIYQQhcL/AZIjcUTzC7oUAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ANPSWkdJBQeA",
        "colab_type": "text"
      },
      "source": [
        "## Logistic Regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hkOc6Gw9RV8L",
        "colab_type": "code",
        "outputId": "8aa086ca-0be8-468a-8eb3-44ef22594acb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        }
      },
      "source": [
        "from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "logreg = Pipeline([('vect', CountVectorizer()),\n",
        "                ('tfidf', TfidfTransformer()),\n",
        "                ('clf', LogisticRegression(n_jobs=1, C=1e5)),\n",
        "               ])\n",
        "logreg.fit(X_train, y_train)\n",
        "\n",
        "y_pred = logreg.predict(X_test)\n",
        "\n",
        "print('accuracy %s' % accuracy_score(y_pred, y_test))\n",
        "print(classification_report(y_test, y_pred,target_names=my_tags))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
            "  FutureWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
            "  \"this warning.\", FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "accuracy 0.78175\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "         java       0.70      0.62      0.66       613\n",
            "         html       0.91      0.91      0.91       620\n",
            "      asp.net       0.97      0.94      0.95       587\n",
            "           c#       0.77      0.77      0.77       586\n",
            "ruby-on-rails       0.77      0.81      0.79       599\n",
            "       jquery       0.59      0.58      0.59       589\n",
            "        mysql       0.78      0.75      0.76       594\n",
            "          php       0.82      0.85      0.83       610\n",
            "          ios       0.69      0.71      0.70       617\n",
            "   javascript       0.61      0.59      0.60       587\n",
            "       python       0.64      0.63      0.63       611\n",
            "            c       0.82      0.83      0.83       594\n",
            "          css       0.78      0.78      0.78       619\n",
            "      android       0.84      0.85      0.84       574\n",
            "       iphone       0.80      0.83      0.82       584\n",
            "          sql       0.65      0.64      0.65       578\n",
            "  objective-c       0.82      0.85      0.83       591\n",
            "          c++       0.91      0.91      0.91       608\n",
            "    angularjs       0.96      0.94      0.95       638\n",
            "         .net       0.78      0.83      0.80       601\n",
            "\n",
            "     accuracy                           0.78     12000\n",
            "    macro avg       0.78      0.78      0.78     12000\n",
            " weighted avg       0.78      0.78      0.78     12000\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hXCdip_iRHoC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "outputId": "33cf30a8-78dd-4320-e648-774943239ce9"
      },
      "source": [
        "df_cm = pd.DataFrame(confusion_matrix(y_test,y_pred),index=my_tags, columns=my_tags)\n",
        "plt.figure(figsize = (20,10))\n",
        "sn.set(font_scale=0.8)#for label size\n",
        "sn.heatmap(df_cm, annot=True,annot_kws={\"size\": 8})# font size"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2a4dc5d668>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABDkAAAJGCAYAAABRKl46AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzs3Xd8zWf/x/FXck4OMUIVKR3qbmvH\nqN27NrFiVNGqVRRdtL/qpNWhrS5ddxe1RykaghiJRHAXQe3as0JJiQyyx++PVG5KlnG+54r38/E4\nj8cZzvf7PpfrO/I51/c6bhkZGRmIiIiIiIiIiBjO3eoAIiIiIiIiIiI3goocIiIiIiIiIlIgqMgh\nIiIiIiIiIgWCihwiIiIiIiIiUiCoyCEiIiIiIiIiBYKKHCIiIiIiIiJSIKjIISIiIiIiIiIFgooc\nIiIiIiIiIlIgqMghIiIiIiIiIgWCihwiIiIiIiIiUiCoyCEiIiIiIiIiBYKKHCIiIiIiIiJSINit\nDuDqzr/cxeoI+XLb15utjnBLqFaqgtUR8mVv9HGrI+Tbv7zKWR0h3w7H/ml1hHxJS0+3OkK+2d1t\nVkfIl/QM89o4IyPD6gj5ZreZdTqTkpZqdYRbgrubm9UR8sXEbc+8xOoXzuDubt736EmJ5p0r50fK\nmcNOW5dH6X85bV3ZMa8HioiIiIiIiIhchVlffYiIiIiIiIhI3qWnWZ3AqTSSQ0REREREREQKBI3k\nEBERERERESmoDJwj7HpoJIeIiIiIiIiIFAgqcoiIiIiIiIhIgaDLVUREREREREQKqnRdriIiIiIi\nIiIiYhwVOW4wjyad8XxubL7f5+ZVisJPj8Hz+Y+xPVArc1ltHsPz+Y8zn7u/5o2OmmfVq1dmzeoA\nVoX6M/HHzy3LkR+mZH6oRUMm+n/DRP9vWLl9ES3aNaX/s08wNeB7Pvz2bex2m9URs+XpWZiFC6YS\nFDSX+fMm4XA4rI6UrS49OzB5/rdMW/A9Ze8ow+vv/R8zFk3gjfdfsjpajnzbNCcoaC5BQXM5emQz\nnTu1tTpSrhrUr8Pa1QGsXrWAcZ++Y3WcPLHZbEyf/g0rVszhgw9GWh0nT/r0fpTly+cQHDSP8uXv\nsDpOrkzZJ5crV5Z16wI5d24fNpuNatUqsWqVPytXzmP8+E+tjpcjE7c9gHGfvkNYqD+fj3vX6ih5\nom3v5jOxL6tf3HwmnXe6ooyMdKfdXIGRRY6//vqLcePGWR3jSjY77ndWzNM/LfTY8Msee7R4lOTl\ns0iY8DaO1j0ASP1tFQnfvEbCxPdw+D5+w+Pm1b59h2jarAstWnYDoF7dWpZlyStTMq9bFc5T3Z7n\nqW7Pc+rEafbs3Ef9fz/Ik12e4cCeQ7Ro39TqiNny9W3Oxk1b8fXtyabN22jr29zqSFdV9o4y1G/8\nIAO7P0f/R56hdJlSFCnqSd/OQ3A4PKhRu6rVEbMVFByGr29PfH17cvz4SUJC11odKVfH/oigtW9P\nmrV4hDJlb6dGjSpWR8pVly7t2LlzD23bPo6nZyF8fFy3TwCUL38HTZo0pl27x2nj24OTJ09ZHSlX\npuyTo6Ji6NChFxs3bgVg//7DtGjRjdZ/H5fr1rXuC4fcmLjt1aldg6LFitC8ZTccDofL9ouLtO05\nh2l9Wf3COUw57xTXYGSRo0yZMowYMcLqGFewN2xD6ubQrMeFuj1N4afHUHjQW+BZNMf3uperQPrR\nvZCcSEZSAhTyJCMqMvPF1BTIyLiZ0XOUmpqadT8pKZnjEScty5JXpmW+857ynP0rivur/IvN6zJP\nrjes2UStuj4WJ8ve4cPHKFqkCAAlS3hxNuqcxYmu7uEWjXC3uTN5/reM+vBlatf3Yd3qjQCsW7OR\n2vVct40vqljxHiIjz3DhQrzVUXJ1+vRfJCUlAZCSkkpaWprFiXJXseI97Ny5B4AdO3bTqFFdixPl\nrE2bZths7ixfPocvvhiDu7vrH8pN2ScnJSURHR2b9fifuSMi/rQiVp6YuO01bFiXlSGZxduQ0LXa\n9m4CU7a9S5nWl9UvnMOU806XlZ7uvJsLcP2t8CoiIiIYOnQoU6ZMoV+/fjzyyCP8/PPPAAwbNoyj\nR48CsHXrVt544w2ioqLo378/ffv2pV+/fkRFRd34UO42bPfVIO3gTgBs1eqTHv0XiT+8RcqvgXg0\nbpfj290u2SFmJMTjdklRxNH2cVI2rLjxmfPBz68NW7eGUNa7NGfPmrFTMSlzq47NCF22huJexbgQ\ndwGA87HnKV6imMXJsnfw4BEaNqrL1i0rebBuTdav32x1pKu6vUwpPDw8GNj9ORITEilWvBjn484D\nmW3sVaK4xQlz17VLewIWLbc6Rr74+FSlTOnb2bPngNVRcrV//yGaNGkEQLNmjSlZsoTFiXLmXbY0\nDoeDdu0eJyE+wYjLmMCsffKlOnZszebNQXgbktukba9kSS/iYuMAiI2Jo2RJL4sT5UzbnnOZ0pfV\nL5zDlPNOcQ1GFjkueuyxx5g+fTo///wz06ZNIz09nU6dOrF48WIAFi9eTOfOnSlevDgTJ05kxowZ\ndOjQgfnz59/wLPa6zUndsibrsXvZu7DXboLnM+/jaNUDtyLFcStVFs9n3sfzmfexVX4Qz2fep9Cj\nz2S+4ZLrl9wKFyEjIfMPXVuNRrgV8SJ16xqstGRJMHXqtOJExJ907Nja0ix5ZVLmZr4PE7ZiLefj\nLlC0eGaBq2jxosTFnLc4Wfb69unB0sBg6jzYmuXLQnniiW5WR7qq83Hn2bR+CwAb/rsZNzc3ihXP\nLB4VK16U2Jg4K+PlSYeOrVmyJMjqGHl2220l+frL9xk81PVG3F1NYOBKPD0LsWzZbJKSkomM/Mvq\nSDmKiY1jzdr1AKwK+5UqVe63OFHemLRPvlRg4Erq1fPlxIlTdOjQyuo4OTJt24uJiaW4V2ahubhX\nsctG0bgibXvOY1JfVr9wDlPOO11WRrrzbi7A6CLH0qVL6d27NwMHDiQyMpKYmBiaN2/O6tWrSU1N\nZdu2bTRs2JCYmBheeuklevfuzezZszl9+vQNz+Je9k48HmpP4afext37HkhNyZxT4/s3Sfj2DZKX\nziAjKjLz8fdvkrZvCwnfv0nSL98DkHbyGO4VKoOjEG6FPSEpAfdyFfB4qANJ/j/c8Lz5cenEPrFx\n50lISLQwTd6YlPn2MqVISU4h5lwsv2/bQ93GdQBo1LQ+O7bssjhd9tzc3Ig6Fw3AmbNRlPByzRER\nWzftoHK1zBOOqjUqkZGRQaOm9QBo3LQB239z3TYG8PYuQ0pyMlFR0VZHyRObzcb0qV/z6mtjOH3a\ntYsFF6Wnp/PSS2/Tvn0v0tLSCQ5ebXWkHG1Yvzlr3pBaNatz9OhxixPlzqR98qUuyx3r2rlN3PY2\nbPiNli0eBqBVyyaEh2+xOFHOtO05h2l9Wf3COUw57xTXYLc6wPUYP348gYGBALRr146MjAwcDgdV\nq1bl+++/p1GjRri7u7N48WLq1q3Lk08+yezZszlw4MYPe0sOnJ513/O5saT8dwmOroMp/PQYAFLW\nLCZt98Zs358S5k+hXi/iZneQHDQbAIffANyKl8BzyDtkJMSTOPXDG547L9q2bc6LLwwBMoeKufof\nAGBW5hbtmhC2IvOa5Kgz59iyYRtTA77nzxOnmTnhZ4vTZW/OzwuZNfM7nnjiUVJTUujd5zmrI13V\n3l0HSExMYtqC7zkXFc0rT7/Fy28PZ8aiCezdtZ+dW3dbHTFHnTr5snixOaM4unf3o1692nw0dhQA\no978iA3hv1mcKmfly3szderXpKenM2vWL5w8eeML4TfS9h27SUhIJDhoHmfPRvHV1z9aHSlXpuyT\n7XY7AQHT8PGpxuLFM/jvf8Np3vwhAA4ePMrKldaOqsyJidve1m27SExMJCzUn23bf2fT5m1WR8qR\ntj3nMK0vq184hynnnS4r3bXntrnR3DIyLJzR8hpFREQwZswYypcvz44dO6hUqRJ79uxh8uTJlCpV\nik2bNtG/f3/8/f2pUqUKe/fu5ZVXXqF8+fJ4e3tjt9sZPXp0ntZ1/uUuN/nT3Fi3fa3r05yhWqkK\nVkfIl73Rrv+twj/9y6uc1RHy7XCs605KeDVpLjI5VH7Y3V33Z5WvJt1Fhm3mh4GnBdhtZn1nk5KW\nmvs/kuvm7uZmdYR8MXHbMy+x+oUzmDD56j8lJZp3rpwfycecN1LOUeFBp60rO2adFfwtKSmJwoUL\n8/bbb1/19fr167N79/++na1SpUrWPB0iIiIiIiIitwwDv3S5HsaV2c6dO8dbb71Fp06drI4iIiIi\nIiIiIi7EuJEct912Gz/99JPVMURERERERERcn4GXKF8P40ZyiIiIiIiIiIhcjXEjOUREREREREQk\nbzI0J4eIiIiIiIiIiHlU5BARERERERGRAkGXq4iIiIiIiIgUVJp4VERERERERETEPG4ZGRkZVodw\nZYUK3211hHyJ3Trd6gj5VrRWH6sj5Ju7m5vVEfIlXZu5XEUhu4fVEfItJS3V6gj54ulRyOoI+ZaQ\nkmR1hHxzdzPrO5vU9DSrI+SbWUc9M5l4pDaxX5jYznLzpSafsDrCTZW0/79OW1ehSg87bV3ZMeus\nQEREREREREQkG5qTQ0RERERERKSgMnAE4fXQSA4RERERERERKRA0kkNERERERESkoMrQr6uIiIiI\niIiIiBhHIzlERERERERECqp0jeQQERERERERETGORnKIiIiIiIiIFFSak0NERERERERExDwqcljA\nt01zgoLmEhQ0l6NHNtO5U1unrPfE6TM07/8KA0eNY+jbX1322qRfljNg1Dh6vTyWkA1br2n5gavD\n6fvaJzz//recj0/gQkIiT731BU+O/Izn3/+WCwmJN+Jj5Em5ct5sDF/O+dhD2Gw2p633evTp/SjL\nl88hOGge5cvfYXWcXJnYxg3q12Ht6gBWr1rAuE/fsTpOnpjSzneUK8uv65ZwNmrfZTmff34QwSvn\nWZgsdxUq3MXxP7YSHDSPwMBZVsfJVt16tQhaOY/lQT/z4UejqFDhLpYFzWHpitlMnPwF7u6ue0g3\npY0vstlsTJ/+DStWzOGDD0ZaHSfPTNlfXFS9emXWrA5gVag/E3/83Oo4efbC8MGErVpgdYw8G/fp\nO4SF+vP5uHetjpInJvYL09oYzMts4jmcS0lPd97NBbjuGVE2wsPDee+99y57zt/fn4SEhDwvw8/P\n70bHypeg4DB8fXvi69uT48dPEhK61mnrbly7KpM/GMH4d1+47Pl+Xdow5YMRTBrzf0z2D8p1OQEh\n69i0c1/W45TUNOYuX8uUD0fg17wh81asxW6zMfb/BjL1w5dp3qAmASHrb/jnyU5UVDS+bR8jPHyL\n09Z5PcqXv4MmTRrTrt3jtPHtwcmTp6yOlCvT2hjg2B8RtPbtSbMWj1Cm7O3UqFHF6ki5MqWdz0XF\n0LHDE2zc+L8iqcPhoGbNahamyruQkLW08e1Bx469rY6SreN/nKBTx960832MMmVup/ydd/BY96fo\n0LYXx45F4Nu2udURc2RCG1/UpUs7du7cQ9u2j+PpWQgfn6pWR8oTU/YXF+3bd4imzbrQomU3AOrV\nrWVxotw5HA5q1apudYw8q1O7BkWLFaF5y244HA4j2ti0fmFiG5uY2cRzOLGOcUWOq1mwYEG+ihyu\nomLFe4iMPMOFC/FOW+emnfvo/8ZnzFi08rLnPeyZ3/gkJqdw/z3lAfjjz0iGvv0VA0aNY8LcpTku\n948/T/NAhfLYbTYa1azCjn2HKeTwoEypEpnLt9lwd3e7CZ/o6pKSkoiOjnHa+q5XmzbNsNncWb58\nDl98Mcalv5G9yLQ2Bjh9+i+SkpIASElJJS0tzeJEuTOlnTNzxl72XP8nezJr1nyLEuVPs2YPERry\nC8OHP2V1lGxFRp4hKSkZyOy/UVHRxMae//txCmlprvHtSXZMaOOLKla8h5079wCwY8duGjWqa3Gi\nvDFlf3FRampq1v2kpGSOR5y0ME3eDBzQi+kzXHt02qUaNqzLypDML9NCQtca0ZdN6xcmtrGJmU08\nh3MlGRlpTru5Atf/S+oqjh07xvDhw/Hz82Pjxo3s2bOHZ599lnHjxuHv789zzz3HM888Q5cuXVi6\ndCmDBg2ia9eunDzpWjvJrl3aE7BoudPWV6ZUCRZ99x6T3v8/Nmzfy/6jEZe9/v4PP9H9xTE08KkM\nwH9mBvDu832Z8sEIDh4/yakz57JddtyFBIoV8QSgWFFPYi/8r+gUn5DIvKC1dGja4CZ8qoLBu2xp\nHA4H7do9TkJ8gtMuYbpV+fhUpUzp29mz54DVUQosu91OkyaNWL3aeSO4rtWff0ZSvUYT2vj2pGXL\nJvjUcO1v7atXr0zp0qXYt/cgAHfcUZYWLR4mNMR5owLzy7Q23r//EE2aNAKgWbPGlCxZwuJEBZef\nXxu2bg2hrHdpzp7N/jzDFdjtdpo2a0xY2K9WR8mzkiW9iIuNAyA2Jo6SJb0sTpQ3JvULE9vYxMwX\n6RxO8sLIIkd8fDxfffUVH3/8MTNmzKBq1ap89913jBgxAoDChQvz/fff061bNxYvXsykSZPo3bs3\nixcvtjj55Tp0bM2SJblfGnKjODw8KFK4EHabjab1fDhw7PKiz5tPP0HAN+8ycf4yAI6eOM3IL6cw\ncNQ4jhw/RWRUND8vW83AUeOY5L+CTybNY+CocYRs2EqxIp6cj88sbFyIT8SraGbBIyMjg9H/mc6w\n3l3wKlbEaZ/VNDGxcaxZm/nH4KqwX6lS5X6LExVct91Wkq+/fJ/BQ0dYHaVAe+KJR5g7d5HVMfIk\nOTmZ+PgE0tLSWLp0JdWrV7Y6UrZuu60En37+Ds8/+zqQOXT+hwmfMnzYSJf+VsukNgYIDFyJp2ch\nli2bTVJSMpGRf1kdqcBasiSYOnVacSLiTzp2bG11nBz16f0oc+aYMxcHQExMLMW9igNQ3KvYFSPu\nXJVJ/cLENjYxM+gcTvLOyCJHlSpVcHNzo1y5ckRHR1/xetWqmd8QeXt7X3b/av/WKt7eZUhJTiYq\nynmZLp34c9veQ9xdrkzW4+SUFAAKOzwoWqQwAPfe6c3HI55i8gcjmDNuJDXur8Bj7Zsx+YMRDOrW\nllcH9WDyByNo1agOFcp7c/CPk6SlpbNh+x58KlUE4NufFlO76n00rKnr5nKyYf3mrGu+a9WsztGj\nxy1OVDDZbDamT/2aV18bw+nT+qPlZnrggfsY/FQfFgZMo2rVSjz9dH+rI2WrWLGiWfcfalyfQ4eP\nWZgmezabjQkTP+fNkWOJjDwDwFf/+YAfJ8zMGtXhqkxp44vS09N56aW3ad++F2lp6QQHr7Y6UoHk\ncDiy7sfGnSfBiROUX4tKle9j6JB+LFk8k2rVKvHcswOsjpSrDRt+o2WLhwFo1bKJEfO1mNYvTGxj\nEzPrHO46ZaQ77+YCjCxyuLldPreDh4fHZd9gXfr6P/+tq+jUyZfFi503igNgy+8HeOylD+n72ieU\nLVWSmpUqMnbCHAA+njiXgaPGMfDNz3myqy8Aw/p0YfQ30xn01hc8N+YbEv++FvxqPOw2Hm3zME+O\n/IxFqzbQo21TIqOimbxgBaEbtjFw1Dh+Xua8k0S73c6KZXOoWbMaywJ/okH9Ok5b97XYvmM3CQmJ\nBAfNo169WvziH2h1pFyZ1sYA3bv7Ua9ebT4aO4qQ4Hk0auj616Ca0s52u50lS2bi41OVRYumE7Bo\nOV269KNrl/7s2bOfH36YZnXEbD38cEM2rF/K6rCFnDx5ik2bru0Xpm62rt068GBdH957/zWWLJtF\n/QZ16NTZl2eee5Ily2bh18nX6ojZMqWNLypf3pugoJ9Zvnw2GzZs5uTJ01ZHyhNT9hcXtW3bnJCV\n8wlZOR/vsqVdvpg0cuSHdPTrjV+nPuzevZ9vv5tidaRcbd22i8TERMJC/UlLS2PT5m1WR8qVaf3C\nxDY2MbOJ53BiHbeMjIwMq0PkR3h4OCtWrGD06NFERUXxwgsv0K5dO4KDg3nooYcoXbo0586dY9Cg\nQSxfvpwDBw4wbNgw1qxZw/r163nttdfw8/NjyZIleVpfocJ33+RPdGPFbp1udYR8K1qrj9UR8s3d\nRYtn2Uk3azMXJylk97A6Qr6lpKXm/o9ciKdHIasj5FtCSpLVEfLN3c2s72xS01330qLsmHXUM5OJ\nR2oT+4WJ7Sw3X2ryCasj3FSJW5x3CXHhBzs7bV3ZMa7I4Wwqctx8KnLcfCpyyNWoyHHzqcjhHCpy\n3HxmHfXMZOKR2sR+YWI7y82nIseN4wpFDrvVAURERERERETkJnGRuTKcxayvPkREREREREREsqGR\nHCIiIiIiIiIFlYGXSV4PjeQQERERERERkQJBIzlERERERERECirNySEiIiIiIiIiYh6N5BARERER\nEREpqNI1kkNERERERERExDgaySEiIiIiIiJSUN1ic3KoyJGLdMOG9hSt1cfqCPl24fd5VkfIt2LV\ne1gdQeS6paSlWh0h39zc3KyOkC8XkhOtjnBLSM8w66fxzOrFmWzuNqsj5FvqLfaTiVbIsDrALcDE\n/YX6hVhNRQ4RERERERGRgsqwL+6vl+bkEBEREREREZECQUUOERERERERESkQdLmKiIiIiIiISEGl\ny1VERERERERERMyjkRwiIiIiIiIiBVSGYb9Cdr1U5BARERERERERp6pduzY+Pj4ADB48mAYNGvD6\n668TGRnJAw88wNtvv427uzs7duzgww8/JCMjg6effpoWLVrkuFwVOUREREREREQKKhedk+Ouu+5i\nxowZWY9nzZpFjRo1eOqpp3j33XdZu3YtzZo1Y+zYsXz11VcUK1aM3r1707RpU2w2W7bL1ZwcIiIi\nIiIiInLdYmNjiYiIuOIWGxt7xb/9888/6d27NyNGjODcuXNs3rw5a5RG8+bN2bRpE0lJSaSlpeHt\n7U3RokW59957OXr0aI4ZVOSwyAvDBxO2aoHVMfKsXDlvNoYv53zsoRyrZjfSidNnaN7nBQa+/hFD\n3/rsitczMjLoMWw0v6xYfU3LD1y1nr4vv8/z737J+fgELsQn8NTIT3jytbE8/+6XXIhPuN6PkG+m\n9Ytxn75DWKg/n4971+ooeWZaZtPyAvTp/SjLl88hOGge5cvfYXWcXPm2aU5Q0FyCguZy9MhmOndq\na3WkXFmxT75epvVl09q4evXKrFkdwKpQfyb++LnVcfLEZrMxffo3rFgxhw8+GGl1nDwxrR+DeZkb\n1K/D2tUBrF61gHGfvmN1nFyZlhfM3F+Y2M4uJSPdabdp06bRqlWrK27Tpk27IlZwcDCzZs2icePG\nfPHFF8TExODl5QWAl5cXMTExREdHU7x48az3XHw+J7dUkSMiIoLVq6/tD+IbyeFwUKtWdatj5EtU\nVDS+bR8jPHyLU9fbuHY1Jn/0OuPHvHzFa2Ebt3FbieJXedeVAlb+l0079mY9TklNZe6yVUz5+A38\nWjRm3rIw7HY7Y18ewtSP36B5wzoEhPx6wz5HXpjWL+rUrkHRYkVo3rIbDoeDenVrWR0pV6ZlNi0v\nQPnyd9CkSWPatXucNr49OHnylNWRchUUHIavb098fXty/PhJQkLXWh0pV1btk6+ViX3ZtDbet+8Q\nTZt1oUXLbgBGtHGXLu3YuXMPbds+jqdnIXx8qlodKUcm9mMTMx/7I4LWvj1p1uIRypS9nRo1qlgd\nKUem5QUz9xcmtvOtqn///oSEhFxx69+//xX/tlSpUgB07NiRPXv24OXllTXiIy4ujhIlSlCiRAni\n4uKy3nPx+ZzcUkWOEydOuESRY+CAXkyfMc/qGPmSlJREdHTOFbObYdOOvfR/9UNmLFxxxWvLwjbQ\nrmnDrMd/nDzN0Lc+Y8DrHzFhzqIcl/vHydM8cO9d2G02GtWuzo69Bynk8KBMqZIAeNhtuLs7d/Mw\nrV80bFiXlSGZfwyGhK6lUaO6FifKnWmZTcsL0KZNM2w2d5Yvn8MXX4xx+nZ0PSpWvIfIyDNcuBBv\ndZRcWbVPvlYm9mXT2jg1NTXrflJSMscjTlqYJm8qVryHnTv3ALBjx26X7xcm9mMTM58+/RdJSUkA\npKSkkpbm2r8KYVpeMHN/YWI7u5T0dKfdvLy8uOuuu664XRyhcVF8fHzW/+PGjRupUKEC9evXZ82a\nNQCsWbOGevXqUbhwYWw2G5GRkcTHx3Ps2DEqVKiQ48e19OwzKiqK/v3707dvX/r160dUVBSjRo2i\nV69e9O3bl99++43w8HCefPJJnnnmGbp27cqGDRsuW0ZERAQ9e/ZkxIgRdOrUicDAQCCzoDF48GD6\n9evH8OHDSUpKYvr06QQHB9O3b18OHz5sxUfGbrfTtFljwsKcO0rARGVKlWDRhI+YNPY1Nmzbzf4j\nx7NeW7dlF3V9KmO75A+o/8z4hXeHD2DKR69z8I+TnDoTle2y4y7EU6yIJwDFinoSe8kfNfEJicxb\nFkaHZo1uwqe6OhP7RcmSXsTFZlZVY2PiKFnSK5d3WM+0zKblBfAuWxqHw0G7do+TEJ9gxKUfF3Xt\n0p6ARcutjlEgmdiXTeTn14atW0Mo612as2fPWR0nV/v3H6JJk8xjbbNmjSlZMudv5qxmYj82MfNF\nPj5VKVP6dvbsOWB1lDwxLa9p+4uLTGtnyd7hw4d59NFH6dOnD9OmTeOll16iW7dubNu2jd69e5Oc\nnEzTpk0BeP311xk+fDgDBgzgueeew27P+fdTLP11leLFizNx4kQ8PDyYM2cO8+fPZ/fu3fzyyy+4\nu7uTnp7Opk2biI2NZdKkSZw9e5Znn32W+fPnX7acM2fOMHPmTM6fP89TTz1Fx44d+fTTTxkxYgRV\nqlRhxowZLFiwgH79+rFixQpGjx5t0SfOvFZ9zhxz5lywksPDA4dH5v2mDWpx4FgElSreDYB/0Bo+\neGkwy9eEZ/37oxGnGDnuRyCziBF59hyrN25jxZqNnImOoZCHB8WLFqF35zZUuPMOzv8958aF+AS8\nihYBMuf5GP3VZIb164ZXsSJO+6wm9ouYmFiKe2VeLlTcqxjR0VdOJuRqTMtsWl6AmNg41qxdD8Cq\nsF+p+2BNCLA4VB516Niaxx7qfa5hAAAgAElEQVQbbHWMAsnEvmyiJUuCWbIkmC+/GEPHjq0JCHDt\nol1g4EpatPg3y5bN5tix40RG/mV1pByZ2I9NzAxw220l+frL93n8iaetjpInpuUF8/YXYGY7u4wM\n1/t1lRo1arBw4cIrnv/qq6+ueK5WrVrMmTMnz8u2dCRHTEwML730Er1792b27NmcPn2awYMH89pr\nr/HWW2/x11+ZB7tq1aphs9koW7Zs1jClS91///04HA5KlSpFcnIyAIcOHeKDDz6gb9++LF68mLNn\nzzr1s2WnUuX7GDqkH0sWz6RatUo89+wAqyO5rEsn/ty2+wB3lyub9fjYiVO88P7XTFuwnJkBwRw5\n/if33nUHH7/6NJM/ep05X75DjQcq8liHlkz+6HUGde/Iq4OfYPJHr9PqobpUuNObg8dOkJaWzoZt\nu/GpfB8A385cQO2q99OwVjWnflYT+8WGDb/RssXDALRq2cSI69ZNy2xaXoAN6zdnXVdfq2Z1jh49\nnss7XIO3dxlSkpOJioq2OkqBZGJfNo3D4ci6Hxt3noSERAvT5E16ejovvfQ27dv3Ii0tneBg6y8p\nzomJ/djEzDabjelTv+bV18Zw+rRrF77AvLxg5v7CxHYW61g6kmPx4sXUrVuXJ598ktmzZ7N3715a\nt25Nhw4dCAgIYNasWfz73/9m9+7dpKenExUVddlGeZGbm9sVz1WsWJEXX3yRf/3rXwAkJyeza9eu\ny65Bs8LIkR9m3Q9btYBvv5tiYZq8s9vtBC6eSc2a1VgW+BNvvvURGzdtvanr3PL7fr6ZuQCHh50H\nq1eiZuX7GPvDTN54ug/z/vMekDmhaGpaGhXvLsewvo8y+qvJJKek4GGz8fnI5yniWfiqy/aw23m0\nbTOefO1DvIoV5aNXhhJ59hyTf1lK7Sr3E7p+C22bNuCxDi1v6me8yMR+sXXbLhITEwkL9Wfb9t/Z\ntHmb1ZFyZVpm0/ICbN+xm4SERIKD5nH2bBRfff2j1ZHypFMnXxYvDrI6Rp5ZsU++Hib2ZdPauG3b\n5rz4whAADh484vIFA4Dy5b2ZOvVr0tPTmTXrF06ePG11pByZ2I9NzNy9ux/16tXmo7GjABj15kds\nCP/N4lTZMy0vmLm/MLGdXUq6643kuJncMjIyMqxa+d69e3nllVcoX7483t7e2O129u3bh7u7Oykp\nKYwePZq4uDgmTpyIzWbj1KlTvPbaazRu3JgJEybQunVrHA4HY8aMYfz48QD4+fmxZMkSTpw4wZgx\nY4iPz5xr4ZlnnsHHx4chQ4ZQunRpXnnlFe6+++5cM3o47rypbXCjWfafeR0u/G7OZJsXFavew+oI\n+WJiv5Cbz/0qBWJXd7WititLu8VOKiRvzOrFmWzurv8zuv+Umq6JCcV8Ju4vTDzvTE0+YXWEmyoh\n6DunrcvT91mnrSs7lhY58iI8PNzSeTRU5Lj5VOS4+UzsF3Lzqchx86nIIVdjVi/OpCKHiDVM3F+Y\neN5Z4IscK75x2ro82z7vtHVlx5zf9hMRERERERERyYGlc3LkRcOGDWnYsKHVMURERERERETExbl8\nkUNERERERERErtEtdvmsLlcRERERERERkQJBIzlERERERERECiqN5BARERERERERMY9GcoiIiIiI\niIgUVBkaySEiIiIiIiIiYhyN5MjFXcVLWx0hXyLizlgdId+K1+hpdYR8i/3uMasj5EvxZ3+2OkK+\nFbY7rI6Qb4mpyVZHyBc3NzerI+RbIZuH1RHyJT49yeoItwTTenKG1QGugYn7C3fDMqdnmNczzGrh\nTOa1ssgNoDk5RERERERERETMo5EcIiIiIiIiIgWV5uQQERERERERETGPRnKIiIiIiIiIFFSak0NE\nRERERERExDwaySEiIiIiIiJSUGlODhERERERERER82gkh4iIiIiIiEhBpTk5RERERERERETMoyKH\nkw18ug9zA6fStOVDzA6YyOyAiYT/vpI2HVpYHS1b1atXZs3qAFaF+jPxx8+tjpMnFSrcxfE/thIc\nNI/AwFlOX/+MzYd58qd1lz331tLt9Jn5K4PmrGfp7hPXtNzA3SfoN+tXhv2yifNJKVxITmXIzxsY\nOHs9w37ZxIXk1BsRP8/GffoOYaH+fD7uXaeuN7/uKFeW/65bzJmovdhsNlq3acqy5bNZtnw2Bw+H\n49epjdURs1WunDcbw5dzPvYQNpvN6ji58vQszMIFUwkKmsv8eZNwOBxWR7qqO+4oy5pfFxF5dg82\nmw2bzcaUqV+xZOks3nv/Navj5cq0fmFaXjDv2Negfh3Wrg5g9aoFjPv0Havj5KhcubKsWxfIuXP7\nsNlsVKtWiVWr/Fm5ch7jx39qdbwcWX1+kV8mbnsXvTB8MGGrFlgdI09MOR/6J5Pa2KR9nFjvlihy\nnD17ltGjR3PkyBE++eQTy3I4HB5U86kMwJrQdfTq8hS9ujzFyROn+HX1Bsty5WbfvkM0bdaFFi27\nAVCvbi2LE+VNSMha2vj2oGPH3k5db3JqGvsiY6/62ocdazPp8cZ0qHZnrssJ2HWcTX+czXqckpbO\n/G3HmNyrMX7V72T+9j+wu7vxQcfaTO7VmOb3e7No1/Eb9jlyU6d2DYoWK0Lzlt1wOBwu3S/ORUXj\n16E3mzZuBWBl8Brat+tF+3a9OH78JKtCf7U4YfaioqLxbfsY4eFbrI6SJ76+zdm4aSu+vj3ZtHkb\nbX2bWx3pqs6di6Zzxz5ZfaJTZ1927tqLX4feeBYuTA2fKhYnzJlp/cK0vGDese/YHxG09u1JsxaP\nUKbs7dSo4bp9OCoqhg4derHx7+1v//7DtGjRjdatewBQt25NK+Plyqrzi2th4rYH4HA4qFWrutUx\n8sSk86FLmdTGYNY+ziWlpzvv5gJuiSLHrl27qF69Ort27aJGjRqW5ejZ5xF+mbP4sufurnAnZyLP\nEn8hwaJUuUtN/d/ogKSkZI5HnLQwTd41a/YQoSG/MHz4U05d74Kdx+lc/a4rnndzgzeXbmO4/yZO\nxsQD8Me5Czw9N5xBs9fz4/oDOS73j3MXuL9Mcezu7jSsUJodJ89RyG6jTLHCANhtbri7ud34D5SN\nhg3rsjJkLQAhoWtp1Kiu09adX0lJyURHX1l4uvfeu4mMPMOFC/EWpMqbpKQkoqNjrI6RZ4cPH6No\nkSIAlCzhxdmocxYnurp/9ol7K97D7zv3ArBjxx4aNnTd/gzm9QvT8oJ5x77Tp/8iKSkJgJSUVNLS\n0ixOlL3M/vC/7e+fbR0R8acVsfLMqvOLa2HitgcwcEAvps+YZ3WMPDHpfOhSJrUxmLWPE+sVuCLH\nRx99xOOPP07fvn35/fffefXVV/nkk08ICgrim2++YdGiRSxZssTpuex2O43+XY/1azde9nw7v1as\nWBrq9Dz55efXhq1bQyjrXZqzZ13zj5ZL/flnJNVrNKGNb09atmyCT42qTllvSlo6m49H0aBC6Ste\nG9G8KtN7/5sBDe7j87A9AHyzdh/vtKvJpF6NOXTmPKfjsi92xSWlUMzhAUCxQnbikv53UhifnMov\n2/6gfdXcR4jcKCVLehEXGwdAbEwcJUt6OW3dN0rnLu1YvGiF1TEKlIMHj9CwUV22blnJg3Vrsn79\nZqsj5cmB/Yf5d5MGADRt1ogSBvZnufFMO/YB+PhUpUzp29mzJ+fCuavp2LE1mzcH4e3ibW3V+cWt\nxG6307RZY8LCXHeU5aVMPB8yrY0vZeo+znIZGc67uYACVeRYtWoVMTExzJkzhxkzZlClShU++eQT\nKlSowMSJE7nvvvv44Ycf8PPzc3q2R3r6EfDLsiueb9W2GSuXhTk9T34tWRJMnTqtOBHxJx07trY6\nTq6Sk5OJj08gLS2NpUtXUr16ZaesN3D3CdpXLX/V10p4Zs5NUOeuUpy5kFmJPhp1gVFLtzFoznoO\nnz1PZFwic7ceY9Cc9UwJP8SnobsZNGc9oftPUayQB+eTUwC4kJRK8UKZP46UkZHB28t38HyTyngV\n9nDCp8wUExNLca/iABT3KnbVkRKurkOHViwNXGl1jAKlb58eLA0Mps6DrVm+LJQnnuhmdaQ8WbY0\nBM/ChVkUOJOkpGQiI89YHUlcgGnHvttuK8nXX77P4KEjrI6Sb4GBK6lXz5cTJ07RoUMrq+Nky6rz\ni1tJn96PMmeOGfNEgJnnQ6a18UUm7+PEuQpUkePgwYM0bNgw6/GKFSt44okn2L59O7169WLHjh30\n7duXxMREp2f71wP30mdAT6bO/Y5KVe6j/+BelC57OykpKUSfc+1hhJdOHBgbd56EBOe3X34VK1Y0\n6/5Djetz6PAxp6z3aNR55m07xrPzNnLoTByztxzJeu18UkrWvyleKLMYcW+ponzkV4dJjzdmdr+H\nqV6uJD3rVGDS440Z0PA+XmlZjUmPN6ZlpTuocFtRDp05T1p6BhuOncGn3G0AfPfrfmrfedtVR4/c\nTBs2/EbLFg8D0KplE+Ou9y3rXZrk5BSioqKtjlKguLm5EXUus03PnI2ixN8nfq4uPT2dV15+l84d\n+5CWlkZI8BqrI4nFTDv22Ww2pk/9mldfG8Pp039ZHSdfLmvrWNdua6vOL24llSrfx9Ah/ViyeCbV\nqlXiuWcHWB0pRyaeD5nWxmD2Ps4l3GJzctitDnAjPfDAAwQHB9O1a1cA2rVrR9myZdm5cycVKlQg\nKiqK7t27W5Lt43e/zLo/N3Aq036cTa/+3Qk2YBRH27bNefGFIUDmUPTg4NUWJ8rdww835J23XyYp\nKZlff93Ipk1bnbLeF5v9b9jqkz+to02lcvy4/gCDGz/AyMBtxCam4AaMauMDwPNNKvPO8h0kp6Vj\nd3djXJe6FHFcfbP0sLnTrebdDJi9Dq/CHoz1q0Pk+USmhB+i1p23EXrgFG0rl6dnnQrO+Khs3baL\nxMREwkL92bb9dzZt3uaU9V4Lu93OgoVTqOFTlYBF03jnnc+oWbMqgYHBVkfLld1uJ3DxTGrWrMay\nwJ94862P2Oik/nwt5vy8kFkzv+OJJx4lNSWF3n2eszrSVdntdn75u08sWDSNj8d+zchRL5Kekc7s\nnxbw55+nrY6YI9P6hWl5wbxjX/fuftSrV5uPxo4CYNSbH7Eh/DeLU12d3W4nIGAaPj7VWLx4Bv/9\nbzjNmz8EwMGDR1m50nWLjFadX1wrE7e9kSM/zLoftmoB3343xcI0uTPpfOgi09oYzNrHifXcMjJc\n5MKZG2Ts2LFs374dh8PBq6++yqZNm6hRowbr1q2jbdu2VKmSv5l4K95uxgzJF0XEmTfE2s2Jk2Xe\nKDHf9rQ6Qr4Uf/ZnqyPkW2G7a/70aE4SU5OtjpAvNnfzBvMVsjnvkqwbIT4lyeoItwTTjiImnnh5\n2Mz7Xiwt3ayJCdMNPCU3bdsD87Y/tbFzpCafsDrCTZUw6y2nrcuz9xinrSs75h2xcvHGG29c9vji\nr6nUr1/fijgiIiIiIiIi4iQFrsghIiIiIiIiIn/LcI25MpzFvLHKIiIiIiIiIiJXoZEcIiIiIiIi\nIgWVi/zqibNoJIeIiIiIiIiIFAgaySEiIiIiIiJSUBn4603XQyM5RERERERERKRA0EgOERERERER\nkYJKc3KIiIiIiIiIiJhHIzly8eeFc1ZHyBcTr7bKMPAaseLP/mx1hHw5v/5bqyPkW7HGz1kdId+8\ni5a0OkK+nL4QbXWEfEtIT7I6grggd3ezvrNJM/AbtZS0VKsjiNwQNu0v5FZ0i/Ujs7ZyERERERER\nEZFsqMghIiIiIiIiIgWCLlcRERERERERKagydLmKiIiIiIiIiIhxNJJDREREREREpIDKSDfvhx6u\nh0ZyiIiIiIiIiEiBoJEcIiIiIiIiIgWVfkJWRERERERERMQ8GskhIiIiIiIiUlDp11XkZihXzpv1\n6wOJjt6PzWa74rGrK1fOm43hyzkfe8iIvADjPn2HsFB/Ph/3rtVR8sSKvCf+iqLF02MYNGY8Q8dO\nvOy1H34Jpu/ob+k7+lvCdx28puWH/36QvqO/ZdD74zl9NhqAYZ9O5cl3v2fwBxOynnMWU/px5ar3\nE7BiJv5Lp/P5N+/jWcST6T9/x7zFU5g86z84HB5WR8xWg/p1WLs6gNWrFjDu03esjpMn1atXZs3q\nAFaF+jPxx8+tjpMrE9sYzNsn+7ZpTlDQXIKC5nL0yGY6d2prdaRcmdbGYF5m07Y/U457V/PC8MGE\nrVpgdYxcmbivAPO2PTAzs1jjuoscERERDB069EZkuWH27NnDtGnTAOjbty9RUVEWJ4KoqGjat3+C\njRu3XvWxq4uKisa37WOEh2+xOkqe1Kldg6LFitC8ZTccDgf16tayOlKOrMzbyOcBJr01lPFvPHXZ\n835N6jLjvef49rWB/OC/MtflbNp9iIDVmy97bsKCEH544yleeLw9kxaFAfBa/85MffsZBnZuzoxl\n/71hnyMvTOnHhw4cpUvbPnTr0A+AAYOfYMvmnfToNIBtW3bSvNXDFifM3rE/Imjt25NmLR6hTNnb\nqVGjitWRcrVv3yGaNutCi5bdAFx+f2FiG5u2TwYICg7D17cnvr49OX78JCGha62OlCMT29jEzKZt\nf6Yc9/7J4XBQq1Z1q2PkiWn7CjBz2zMxs0tJz3DezQXkq8iRlpZ2s3Jck+zyVK1alf79+zs5Tc6S\nkpKIjo7J9rGrMy1vw4Z1WRmSeZAJCV1Lo0Z1LU6UMyvzbtp9iCff/Z4ZSy8/KN9VthQADg87bn8/\nFxV7nuGfTWXQ++P5YHLO364kJCVT2MODop6FqHn/PRyKOH3Zcu02GzZ35w4mM6Ufp6amZt1PTk5m\ny6btFCnqCYBXieKcO+e6n+H06b9ISkoCICUl1eWOG1dzaXsnJSVzPOKkhWlyZ2Ibm7ZPvlTFivcQ\nGXmGCxfirY6SIxPb2MTMpm1/phz3/mnggF5MnzHP6hj5Ysq+Aszc9kzMLNbJ9S+M8PBwhgwZwrBh\nw6hVqxY7d+4EYNKkSfj7+wNw9uxZhg8fziOPPMKSJUtITU2lW7duWTv+7777jkWLFl223Pj4eIYN\nG0afPn0YNGgQZ86cAaBNmzaMGjWKbt26MWnSpCvy+Pv78+KLL/LMM8/g7+/PlClT6NevH4888gg/\n//xzVub33nvvsvdt376d7t2707dvX9588838tpMYpmRJL+Ji4wCIjYmjZEkvixPlzKq8ZUp6sWjc\nK0x8cwjhuw6y/48/r/g33/8STPdWDQGYvCiMQZ1bMOnNoRTxLMT2/ceyXXZcfCJFPQtlPU67ZFbn\ntPR0flwQmrVcuVKb9i0IWbeQ0mVu5/dde6lbvxah6wKoVbsGm8NdfwSYj09VypS+nT17DlgdJU/8\n/NqwdWsIZb1Lc/bsOavj5IlJbWzaPvlSXbu0J2DRcqtj5MrENjYx80UmbX+msdvtNG3WmLCwX62O\nki+m7CvAzG3PxMwuJT3deTcXkKeJR8+cOcO8efMYNWrUVV8/deoUM2bMAKB79+60b9+ehx56iF9/\n/ZWmTZsSGhrKzJkzL3vP3LlzqVOnDgMHDmTp0qVMmDCBkSNHcubMGV555RWKFClCp06dGDRo0BXr\nS05O5vvvvwcyiyUDBgwgOTmZrl270qNHj6tmDAsLY8iQIfj6+pLuIo0vN09MTCzFvYoDUNyrGNHR\nsRYnyplVeR0edi5O79C0ThUOHj9FpXvKZb0esmkXMXHxdPh3HQCOnIjkqznLcHNzIz4xCZ/77iZk\n0y5+Wv4rcfEJJCWnsmjNb7RtVBO/JnW5kJCUtaxLR22Mm7mETk0e5G7v253yOU0UvGwVwctWMebj\nkfQf9DjBy8P44T9TGPr8kzzasxPzf16U+0IsctttJfn6y/d5/ImnrY6SZ0uWBLNkSTBffjGGjh1b\nExDg2ieqprWxafvkS3Xo2JrHHhtsdYxcmdjGJmYG87Y/0/Tp/Shz5rj+XBz/ZMq+Aszc9kzMLNbJ\n01hxHx8fbDYbbm5uWc9lZPzvepsHHngAT09PPD09KVu2LOfOnePRRx9l4cKF/Pbbb1SvXp3ChQvz\nxhtv0LdvXxYuXMiRI0eoVSvzWqoHH3yQI0eOAFC+fHlKliyJw+HAwyPzr69L3wdQu3btrHUvXbqU\n3r17M3DgQCIjI4mJufqQvN69e7Nx40ZGjBiRtRwpuDZs+I2WLTLnLWjVsonLX4tqVd5LixBb9x/j\nrkuKDvv/+JOfg9YzckDXrOfuLV+Gl/v4Memtocz+YDjN61ajVf0aTHprKK/07cTAzs2Z9NZQerZp\nTJHCDhJTUohPTGLnweP8686yAPiv2oibmxudmmqYYXYunVj0fNx54mLPE/33JSrnzkZT3KuYVdFy\nZbPZmD71a159bQynT/9ldZw8cTgcWfdj486TkJBoYZrcmdjGpu2TL/L2LkNKcjJRUc6dJPlamNjG\nJmY2cfszTaXK9zF0SD+WLJ5JtWqVeO7ZAVZHypVJ+wowc9szMbNLucVGcuSpyHFxNmYvLy9On868\nrn7Pnj1Zrx88eJDExEQSExOJjIzktttuo2LFikRHRzNt2jQeffRRAMaOHcuMGTPo2rUr9957L9u3\nbwdgy5Yt3HvvvQCXFVIuuvR9l+YBGD9+PFOmTGHy5Ml4eXldVny5VNGiRXnzzTf57LPPGD9+PMnJ\nyXn56DeM3W5n6dKf8PGpxpIlM6lfv/YVj12Z3W5nxbI51KxZjWWBP9Ggfh2rI+Vo67ZdJCYmEhbq\nT1paGps2b7M6Uo6syrtl7xEeH/k1/d7+lrKlvKh5/z2MnRoAwOezAjkbe55nPprEC+MyJ/Id1KUF\nExaG8tT7ExjywY+cjsr5Ot/BXVoy9MOJfDlnKQM7NwfgwykL+f1wBIPGjOe7+UE39fP9kyn9uHmr\nh5m/ZCrzl0yldJnbCfhlGZ26tmPe4ik80qMjC+YFWh0xW927+1GvXm0+GjuKkOB5NGro+sWstm2b\nE7JyPiEr5+NdtjTBwautjpQjE9vYtH3yRZ06+bJ4sXP3U9fKxDY2MbNp258px71LjRz5IR39euPX\nqQ+7d+/n2++mWB0pVybtK8DMbc/EzGIdt4zsqgJ/Cw8PZ8WKFYwePZoDBw4wYsQI7rrrLgoXLszD\nDz9MgwYNGDFiBHfccQfHjh1j4MCBdO7cGYAFCxYwadIklixZcsVyL1y4wCuvvEJMTAyFChXi448/\npkyZMvj5+WX9+0vvX+Tv78+5c+eyLmN599132bFjB5UqVWLPnj1MnjyZAwcOZGXu27cvX331FYsW\nLSIoKIiMjAyqV6+e53k5Che+J0//zlWkprv2BFhijfPrv7U6Qr4Va/yc1RHyzbtoSasj5MvpC2Z8\n43SpK8vgrs015hgv+Jw9ifH1SnORb7pErpdp+2QAd+0v5CpSk09YHeGmiv/Seb+GWuTF8U5bV3Zy\nLXJcj4ULFxIdHc2TTz55s1Zx06nIIQWBihzOoSLHzWfaCbWKHM6hIoeINUzbJ4OKHHJ1KnLcOK5Q\n5MjTxKPXYsKECYSFhTFhwoSbtQoRERERERERkSw3rcgxZMgQhgwZcrMWLyIiIiIiIiK5ucVGBJk1\nXktEREREREREJBs3bSSHiIiIiIiIiFgs/daaJUwjOURERERERESkQNBIDhEREREREZGCKkNzcoiI\niIiIiIiIGEcjOUREREREREQKqltsTg4VOXJxX4lyVkfIlwPRJ6yOkG8ZGeZtdCU9i1kdIV+8m42w\nOkK+7bi7ttUR8q3l2cNWR8gXN6sDXAO7zazDVkpaqtURbgnli5ayOkK+RMSdsTpCvtncbVZHyLcM\nzDu/MI2bkUcSs7i7mdfG7m66WECsZdbZooiIiIiIiIjkWUa65uQQERERERERETGORnKIiIiIiIiI\nFFS32JwcGskhIiIiIiIiIgWCRnKIiIiIiIiIFFQZmpNDRERERERERMQ4GskhIiIiIiIiUlBpTg4R\nEREREREREfOoyCEiIiIiIiIiBYKKHE7UuUd7Js3/hin+31GvcR1mLvmR6QHjef/Lt6yOlqMKFe7i\n+B9bCQ6aR2DgLKvj5En16pVZszqAVaH+TPzxc6vjZKtK1QcIDJrN4mWz+PrbDwEY8+EbLF42iw8+\nGmVxuqurW68WQSvnsTzoZz78O+PwFwazPOhnfpz0OXa7c6+CK1SpAvfO+4x753xM+Y9fzPf77WVL\nUWHmh9w77zOKPlQbgNLDemUuc95nFH2o1o2OnKsqVR9g8YqfWLh0Bl9++0HW80Oe7U/AsplOz3Mt\nXhg+mLBVC6yOka1y5cqybl0g587tw2azUa1aJVat8mflynmMH/+p1fFy1KB+HdauDmD1qgWM+/Qd\nq+PkSbly3mwMX8752EPYbDar4+Rq4NN9mBs4laYtH2J2wERmB0wk/PeVtOnQwupo2TLluAeZ/WH9\n+kCio/djs9mueOzKfNs0JyhoLkFBczl6ZDOdO7W1OlKOPD0Ls3DBVIKC5jJ/3iQcDofVkbJ1tX7w\nySejCQmZz2efvWNtuKswuR8D9On9KMuXzyE4aB7ly99hdZxsmdYvXFZ6uvNuLsDlihx//fUX48aN\nszrGDVf2jjLUe+hBBnV/ngHdnmXbph308RtMvy5DAahRu6rFCXMWErKWNr496Nixt9VR8mTfvkM0\nbdaFFi27AVCvrvP/UM2LgweO0NG3F53aZ7brg3VrUrRYETq1742Hw4PaD/pYnPBKx/84QaeOvWnn\n+xhlytzOvx9uQJOmjWjn+xi/79qLX6c2Ts2TdDiCoz1e5ujjrwFQ2OeBHP99+U/+77LHtz/dg8gv\nZnCs/5uUfu4xAGIWhHK0x8v8MfBtSg974uYEz8HBA0fo1PYJunboC0DtOjVwODyo4VPF6VmuhcPh\noFat6lbHyFFUVAwdOvRi48atAOzff5gWLbrRunUPAOrWrWllvBwd+yOC1r49adbiEcqUvZ0aNVy/\nX0RFRePb9jHCw7dYHaOHb6UAACAASURBVCVXDocH1XwqA7AmdB29ujxFry5PcfLEKX5dvcHidNkz\n5bgHmf2hffsnsra/fz52ZUHBYfj69sTXtyfHj58kJHSt1ZFy5OvbnI2btuLr25NNm7fR1re51ZGy\n9c9+ULt2DYoVK0qrVt1xODxcbr9scj8uX/4OmjRpTLt2j9PGtwcnT56yOlK2TOsX4hpcrshRpkwZ\nRowYcUOXmZaWdkOXdy3+3aIRNnd3Js3/hpEfjiD9kslfkpOTOXXitIXpctes2UOEhvzC8OFPWR0l\nT1JTU7PuJyUlczzipIVpsndZzuQUmjZvzOpV6wBYE7aO+vVrWxUtW5GRZ0hKSgYgJSWVqlUf4L9r\nwwEIW7WO+g3qODdQ6v+27/TkFFJPneGO956lwswPuXviO7h7Fcvx7YUr30vCb3vIiE8k/UIC7sU8\nSYnI3B4zklMgw/kTNf2z/544cYon+nbn59kLnZ7lWgwc0IvpM+ZZHSNHSUlJREfHZj3+Z5tHRPxp\nRaw8OX36L5KSkoDMbdAVjnG5yWzvGKtj5EnPPo/wy5zFlz13d4U7ORN5lvgLCRalyp0pxz24sj+Y\n1D8uqljxHiIjz3DhQrzVUXJ0+PAxihYpAkDJEl6cjTpncaLs/bMfNGhQh5CQzCJSaOh/adiwrlXR\nrsrkftymTTNsNneWL5/DF1+Mwd3d5f4kzGJav3BZ6RnOu7kAl+vRERERDB06lE2bNtG1a1eefvpp\nhg4dyvLly7Neu8jPzw+AEydOMHjwYPr168fw4cNJSkoiPDycIUOGMGzYML7//nu6deuWdSL43Xff\nsWjRIqd+rtvLlMLD4cGg7s+TGJ9Iy3ZNadG2CQtX/8TtZUoRfc51d4p//hlJ9RpNaOPbk5Ytm+BT\nw7VHnVzk59eGrVtDKOtdmrNnXfeg3rZ9S9asX0yZMrdjt9uJiz0PQGxsHF4lvCxOl73q1StTunQp\noqNjiYuLAzIzl7Agc7FWDfnXsm+xly5JYZ8HSDn5F8f6jOTcjMXc9kT7nN98yYE9LS4e9+L/K4qU\neaE352Yvu1mxc+TbvgVh6xZRpmxpzkVF89DD9fl1TbglWfLDbrfTtFljwsJ+tTpKvnXs2JrNm4Pw\ndvF9xkU+PlUpU/p29uw5YHWUAsNut9Po3/VYv3bjZc+382vFiqWhFqXKO1OOewVB1y7tCVi03OoY\nuTp48AgNG9Vl65aVPFi3JuvXb7Y6Up79P3t3HhZV9cdx/A0zDLKKG6Tl1uICrqGi5YqKe7kvuVdq\nmlqp5VKaS6XmUmrZT7PFNUxDDXABQdRMwd3c09xwQ0UY1gFm5vcHQZqypcydi9/X88zzzMwd73zu\n9dxzLmfOPdfNzRW9/p/zCzc36z0nUhsP99LodDratu1NSnKK1V92dS8pFyI/rK6TI8vnn3/OkiVL\n+Oabb0hJyf2Xkzlz5jB27FhWrFhB/fr12bAh8zrw27dv8+WXXzJy5Eheeukl9uzJPOkODw/Hz8+v\n0LfhXon6RPb/njnMKvK3AzxbpRI7tu2mc7PXuHk9hmatG1s0T0GkpaWRnJyC0Whk8+bteHlVVTpS\nvgQFhVK3bkuuRl+nQ4dWSsfJ0bYt4TRt1Inr125gNBpx+XvkgYuLM/p4fR7/WhklShRnzvypjBwx\nAb0+ARcXFyAzc7wCmRPDIvmr3dtk3LiD/fMVKN6xKRVXz6T0iF5o3Fywe8aDiqtnUnH1TJybelNx\n9UzKfjIy8x/fc+2gxtkRU0JmJ5OLXyM0bi7oA3dafHsAQrbsoPlLr3D92g3efKsfAeuDFclRUP36\ndsPf33rn4shNcPB26tXz4+rVG7Rv31LpOLkqUcKNhV9+wpBhj3fk45OuS8+ObPrlwY7Nlm2asX1L\nhOUDFZBa2r2ioH2HVgQFhSgdI0/9+/Vgc3AodV9sxdYt4bz2WlelI+VbfHwCrq7/nF/cO/pOPJp4\nfQK7du8FYEfEHqpVe17hRPkn5eI/Mpss97ACVtvJkZqaioeHBzY2NtSqlXmtlY2NzX2fMf89jPz8\n+fN8+umn9O/fn8DAQO7cuQNAzZo1syeo6datGxs3buTgwYN4eXlRrFgxC24NHNl/jKqemRVItRpV\nuHktJntZYkIShlSDRfMUhLOzU/bzlxrV5/xflxRMkz/3TqylT0gkJSVVwTQ50+nssp8nJCRiNptp\n0qwhAE2bv8SB/UeUipYjjUbD0mXz+WjSTGJibnPo0B+83LgBAM1bvGzxzDa6fyY6NSYmY/grmrgN\n4VzqO5GLvT4gZu5y0qNvcqnvRC71nUjiroNc6juR6x99BUDqmYs41K2GjYM9ts4OmBJTsK9aiRL9\nOnJj6mKLbkuW+8qFPpFXOrdl4Ou9WbN+KVWrP88bQ613bpwqVZ9j2NABBAWuwtOzCm+PGKx0pHy5\nr87QW2+dAZnH4IofF/LB+BncvHlL6ThFyrMvVKLf4J78+PNiqlR7joFD+lDavRTp6elWPeIS1NPu\nFQUeHmVIT0sjNjZO6Sh5srGxIfZuZs7bd2Ip/vcfh2oQGXmIFi1eBsDXtzFRUdY/p49a7Nt7gJo1\nM0dm167lxcWLVxROlH9SLkR+WG0nh729PTExMZjNZo4fPw6Aq6srN29mXit/4cKF7BEelStXZtq0\naaxcuZKff/6ZIUOGANw3s3HlypWJi4tj+fLldOvWzcJbA6dP/ElqqoEfAhZTo44nen0iP274hh83\nfEOpMiXZE2G9w9AbN/Zh397N7IzYyLVrN9i/3/onVGrTpjlh29cTtn09Hu6lCQ1V5tf4vPi2asqm\n4JVsCl5JGffSLJi/FENqGoFbVmMyGjl86A+lIz6gc9f2vOhdk+mfjCdoy2oqV67A73ui2Bqylpq1\nqhMUGGrRPE5N61FxzSwqrpmFtpQbieFR6J7xoOKqz6i46jOcm9XL9d/fWboe97EDqLjiU25/8zMA\nHhNeR1vajQo/zKD8/yx/96MWrZqwIXgFG4JXUMa9NB1a96FPtyG81n0oZ06d47ul1nuXo0mTPqND\nx7507NSPkyfP8vXiH5SO9FBarZbg4NXUrOlJYOBKxo0bTkjIWkJC1uLuXprt23cpHTFH3bt3pF69\nOsya+SFhoetoqILrkbVaLdu2+FOrlidbgtfQoL6F5+7Jp9nTvmRgj+EM6jmCs6fPs/zbn2jdrgWh\nKhjFoZZ2DzLLw+bNa6hZ05OgoFXUr1/ngdfWrFMnPwIDrX8UB4D/2o1079aJkJCf6dO7Mz/5W+/c\nTv8uF3Z2WlJTDYSFrcdoNHLgwFGlI95HzeX46LGTpKSkEhqyjnr1avNLgPWOFlVbubBaT9icHDZm\nswKz6uUiOjqaGTNm8PrrrzNz5kzc3d3R6XR07NiRtm3b8sknn3D8+HHq169PeHg4wcHBXL16lRkz\nZpCcnDn50/Dhw7G1tWXbtm1MmTIle90bNmzgu+++IygoKN95vDx8Hvs2FqY/464qHaHArKwI5oub\nQ+6TWVqbNGNG3h+yMns9rP+OEf/me+cvpSMUyJ1k9Q3x1Gose4viR5WuwmNPjcq7lFY6QoFEJ9xW\nOkKBaWyt/5aY/2ZGfecXamODTd4fEo/EZCXD/wvC1sZqf0fPUWrqZaUjFKqkD3tY7LucPlV+8nmr\nO1s0GAwUK1YMHx8fNm7M7G1etGhR9vKPPvoo+3nWXViefvpp/ve//z2wLh+f+zsobGxs6N69e2HE\nFkIIIYQQQgghrI7ZpL7OskdhVd1sd+/eZfLkyXTq1Omxr3vp0qX8/PPP0skhhBBCCCGEEEIUUVZ3\nuYq1kctVCp8ai6BcrlL45HKVwieXqxQ+uVzFMuRylcInl6uIh5HLVQqfXK5iGUX9cpXE8Za7s5Lz\n7ACLfVdO1FcChRBCCCGEEEIIIR5COjmEEEIIIYQQQoiiyorvrnLgwAGqVq1KbGwssbGxvPnmm/Tp\n0+e+eTl37NhBr1696N27N8eOHctzndLJIYQQQgghhBBCCItbvnw5NWrUAODbb7+lW7du/PTTT/zx\nxx+cO3cOo9HIggUL+O6771iwYAEzZ87Mc53qurhZCCGEEEIIIYQQ+WfBuV30ej16/YPzvrm6uuLq\n6nrfezt27MDb25u4uDgADh06xDvvvANA8+bN2b9/PzY2NlSqVAlnZ2ecnZ3JyMjAYDBgb2+fYwYZ\nySGEEEIIIYQQQohHtnz5clq2bPnAY/ny5fd9zmQysWbNGvr06ZP9XnJyMsWKFQMyO0Xi4+OJj4+/\nr3PE1dU1u1MkJzKSQwghhBBCCCGEEI9s4MCBdOnS5YH3/z2KIzAwEF9f3/tGZDg4OGSP0khISKB4\n8eIUL16chISE7M8kJCTg5uaWawbp5MjD9eRYpSMUiEmFt2NVo7spiUpHKJD6ZaooHaHA6kQfVTpC\ngcV93lHpCAXi+n6g0hEKTG7JKh7mRnLuv+iIR5dhMiodociztVHf7VjVeHtTG5XtZzWe25vMUl9Y\nnf8wIeh/9bDLUh7m7NmznDhxgu3bt3PmzBnGjRuHt7c3O3fuxM/Pj127djFmzBgqVqzIxYsXSU5O\nJikpCY1Gk+ulKiCdHEIIIYQQQgghhLCg999/P/t5//79mTt3LgAffPABP/zwAw0bNuSFF14AYOTI\nkQwePBgbGxsmTpyY57qlk0MIIYQQQgghhCiizBYcyfFfrFy5Mvv5smXLHlieNa9HfsnEo0IIIYQQ\nQgghhCgSZCSHEEIIIYQQQghRVFn5SI7HTUZyCCGEEEIIIYQQokiQkRxCCCGEEEIIIURRZVLfnZAe\nhYzkEEIIIYQQQgghRJEgIzmEEEIIIYQQQoiiSubkEEIIIYQQQgghhFAf6eSwEO96tdm6fS2bQ37i\n05mTAGje4mU2Bq3g182rqF3HS+GEuZs3ZyoR4QHMnzdN6Sj5prbMZct6EBW5lUT9eTQajdJxcmRf\nzJ65K2by9bovmP39J9jp7GjX3Y9Fa+fx9bovKPNUaaUj5qhixWe4cvkwoSHrCA5ebfHv19ZtiX2P\ncQ8u0Njh8OZsbMtX+2/rfbE19j3GoWvzOtjaYuNaCvvuY7HvPhZd29fBxuYRkxeM2o69BvXrsnvn\nJnbu2MC8OVOVjpMnteXNooZyUbasO7//Hszdu2fQaDR4elZhx44Atm9fx5Ilc5SOlysvr6rs2rmJ\nHeEBLPt2vtJx8k0N5eJeammr79Wvbze2bvUnNGQd5co9pXScfHtn9BAidmxQOka+qG0fq7EcqzGz\nVTGZLfewAk9cJ0dAQADfffedxb/3yuWrvNqhP+39+lC6TCmqe1Zh0Ou96frKIF5p34+jR05YPFN+\n1a1TAydnR5r7dkWn01HPu7bSkfKkxsyxsXH4telFZOQhpaPkqmGLBpw8dIq3e7zHySOnaP2qL3Ub\n1mZUr7G83eM9bt24rXTEXIWF7aa1Xw86dOhr2S/WaLEt/cxDF2lrvIzpzrV8rcbOpyM2LqX+ecPB\nBU35qhjWzcV0OxrNs3UwG1Iw/Po1hvXzMMffQVOpxuPYgnxR47F36XI0rfx60qxFF8q4l6JGjf/W\n2WQpassL6ikXsbHxtG/fh6iowwCcPfsXLVp0pVWrHgB4e9dSMl6uzpw5T9Nmr9LCtyuA1e7je6ml\nXNxLLW11lnLlnqJJk0a0bdub1n49uHbthtKR8kWn01G7tnX/AJhFjftYbeUY1JlZKOeJ6+RQSkzM\nbQyGNADSMzJo9FI9TCYT6wK+45ulc3B0dFA4Yc58fLzZHrYbgLDw3TRs6K1worypMbPBYCAuLl7p\nGHm6eukaxRyLAeDi6sxTT3tgq7Fl0dp5jJkxCltb665WmjV7ifCwXxg9+k2Lfq/W62UyTu17cIGt\nBtunnsV07fw/b3lUwr7bGOx7vI/Gs1Gu67X1qIgx+iwAxiunsS37LBiSIS018wMmI2az5XrV1Xjs\n3bx5C4PBAEB6egZGo1HhRLlTW15QT7nIrIf12a8zMjLuWZZGdPR1JWLly7+zXonOX8epktRSLu6l\nlrY6S+vWzdBobNm61Z8vvphh9W10ltcH92HFynVKx8gXNe5jtZVjUGdma2I2my32sAZWeRRGRkYy\nePBgRo0aRfv27dmyZQtvvfUWHTt25ODBg4wZMyb7s2+88QbXr19n4cKF9OzZkwEDBrBt2zYAZs+e\nTe/evZk4cSJt2rRRanPu4+lVldKlSxIXp8fjqTL06PoGUZGHGfR6b6Wj5cjNzZUEfQIA+vgE3Nxc\nFU6UNzVmVosrf0VTw9uT1eE/UK12VYwmI3Z2dozqNZbUFANN2rysdMQcXb8eg1eNJrT264mvbxNq\n1qhumS+2tcX26SqYos88sEjj2YiM05H3vWfXqBOGwMUY1s1BW7UB2OY8LNPG3gHSUjJfGFIyX2ct\ncyqObYXqmC6dfDzbkQ9qPvZq1qxOmdKlOHXqT6Wj5Iua8qq5XHTo0IoDB0Lw8CjNnTt3lY6Tq44d\nW3P4cBjuKsgK6i4XauHhXhqdTkfbtr1JSU7hlU7WcT6cG61WS9NmjYiI2KN0lHxR4z4Woqizyk4O\ngNTUVBYuXMiYMWNYunQpixcv5sMPP2TTpk3cunULvV7P9evXsbW1pWzZsoSHh7Nq1SpWrFhB69at\nOXnyJBcuXMDf35/hw4dz584dpTcJtxLF+Xzex4weMRG9PoF9ew9iMpnYvWsvVao+p3S8HMXH63Fx\ndQEyf7m/91cua6XGzGrRvmcb9oTupa/vYH7fvg+NrYbD+44CcHDPYSq9UEHhhDlLS0sjOTkFo9HI\n5s3b8fKqapHv1VRriPFM1IMLbGzRVPTEdOn+y9VsSz+DfacR2Hcbg42jKzYOLtg17Ih9tzFoPBuh\na/cG9t3GYPtUZcyGFND93bGhK5b5GkCjRec3iLSwVWC23L3R1XrslSjhxsIvP2HIsLFKR8kXteVV\na7kACA7eTr16fly9eoP27VsqHSdXQUGh1K3bkqvR1+nQoZXScfKk5nKhFvH6BHbt3gvAjog9VKv2\nvMKJ8tavbzf8/dUxFweocx+LJ5DMyWEdqlWrho2NDR4eHlSpUgVbW1vc3d2Ji4ujU6dOBAcHs3Hj\nRrp06QLA+++/z+TJk5kwYQIXLlzg4sWL1K6deW1nhQoVKFGihJKbg0ajYcm3c5ny4SxiYm5z+NAf\n2R0bNWtW59KlaEXz5WbfvoP4tmgMQEvfJqq4Fk6NmdXCxsYGfVzmL29xd+MxY+b56s8C8ILXc1y/\nbL3Xojo7O2U/f6lRfc7/dcki32tbwgNtrabYvzoK25Jl0dZuDpDZgeFSEvtXR6Gp1gC7lzuDvSOm\nW1cwbPoKwy/zSf3pU8xJcaTvC8Lwy3yMJ/eStuU7DL/Mx3TjAqabl9A8/QIAmgrVMd24AIDOty8Z\nRyMwx1p2eL0ajz2NRsOKHxfywfgZ3Lx5S+k4eVJbXlBnuYDMeQGy6PWJpKSkKpgmd/dlTbDurFnU\nWi7UZN/eA9SsmTlqsXYtLy5evKJworxVqfocw4YOIChwFZ6eVXh7xGClI+VKjftYiKLOajs5bO65\nG4DNv+4MkHUJS0REBK1aZf5S8eKLLzJ79my6d+/O4sWLqVixIseOHQPgypUr3L2r7LDNV7u0o653\nLabO+IBfN6/i2Wcr8PtvUQRtXcNr/brxw3c/KZovN4ePHCc1NZWI8ACMRiP7DxxROlKe1JhZq9Wy\nbYs/tWp5siV4DQ3q11U60kOFbNiOb6fmfL3uC9p0acUvP27EkGrg63VfUL1ONcKDdyodMUeNG/uw\nb+9mdkZs5Nq1G+zff9gi35u+ZwOGjYswbFqEKfY6GX8eQlu/HeakOAz+szBsWoTxdBTpezaCIZn0\nfUHYvzIC+67voWuXx9whKQkYr/6JfY9x2JZ5BuP5I9g+VRnN83Uz7+bSbQya5+pYZDtBncde9+4d\nqVevDrNmfkhY6Doa+lj3vABqywvqKRdarZbg4NXUrOlJYOBKxo0bTkjIWkJC1uLuXprt23cpHTFH\nbdo0J2z7esK2r8fDvTShodZbF2dRS7m4l1ra6ixHj50kJSWV0JB11KtXm18CgpWOlKdJkz6jQ8e+\ndOzUj5Mnz/L14h+UjpQrNe5jtZVjUGdmoRwbs7XMDnKPyMhItm3bxpQpU/jjjz9YvXo1s2bN4vz5\n8yxYsICFCxcyceJEHBwcmDJlCpA5N0daWhppaWmMGjWKxo0bM2vWLI4cOUKVKlWIiopi69atBAQE\ncPfuXd544418ZSnp8kJhbupjpzckKx1BWKH6ZaooHaHADt62/nkG/i3u845KRygQ1/cDlY4gxGNh\np9EqHaFAMowZeX/IyljdyWIRZGvh230/Dlb4Z0Se/v3jqbUzqXAfq1FG2lWlIxQq/RutLfZdrt+F\nWuy7cmKVnRz5MWnSJPr164enp2e+Pt+xY0eCgoIK/D3SySGKAunksAzp5BBCGdLJUfhUebKoMtLJ\nYRnSySEeRjo5Hh9r6ORQ11nB39577z3s7Ozy3cEhhBBCCCGEEEI8icxWMiGopaiyk+OLL74o8L/5\nL6M4hBBCCCGEEEIIoR6q7OQQQgghhBBCCCFEPjxhIzms9u4qQgghhBBCCCGEEAUhIzmEEEIIIYQQ\nQoiiyqR0AMuSkRxCCCGEEEIIIYQoEmQkhxBCCCGEEEIIUUQ9aXdXkZEcQgghhBBCCCGEKBJkJEce\nEgzJSkcQ4pHtv3VW6QhPBNf3A5WOUCBJJ9YpHaHAnm0wROkIBXYzKU7pCEVeujFD6QhFnpOumNIR\nCiwpLVXpCAViMj9Zv7QqxSz7WTyJZCSHEEIIIR4H6eAQQgghhLAsGckhhBBCCCGEEEIUVXJ3FSGE\nEEIIIYQQQgj1kZEcQgghhBBCCCFEESV3VxFCCCGEEEIIIYRQIenkEEIIIYQQQgghRJEgl6sIIYQQ\nQgghhBBFlUw8KoQQQgghhBBCCKE+MpJDCCGEEEIIIYQoomTiUSGEEEIIIYQQQggVkk4OhbwzeggR\nOzYoHSPfypb1ICpyK4n682g0GqXj5ElteUGdmefNmUpEeADz501TOkq+qS2zEnmv3rxN837v8PqE\nWQybPPeB5WazmR6jpvDLtp3/af3BO/bSf9wnjJz2JYnJKSQlp/DmpM8ZNH4mI6d9SVJyyqNuQp6q\nVn+eTdtWEbB5BfO/+gQHRwdWrF3MusAf+H71InQ6u0LP8CjUVo5BMluCGvJ616tNyPZ1bA1Zy2ez\nPqRixWfYEuLP5m0/sez7L7C1te5TU2mrC5/sY8uQzE8YkwUfVsC6W5L/oH///sTGxiodI1c6nY7a\ntb2UjlEgsbFx+LXpRWTkIaWj5Iva8oL6MtetUwMnZ0ea+3ZFp9NRz7u20pHypLbMSuZtVMeT72dN\nYMmMcQ8si4g6QoniLvlaz6btv7H/2Ons1+kZGfy8ZQc/zJ5IxxaNWLclAq1Wy8xxQ/lx9kSa+9Rl\nU9iex7YdOTn/50VebdOPru0HADB4yGscOvAHPToN5sihP2jesnGhZ/iv1FaOQTJbglryXrl8lU4d\n+tLWrxdlypSi3NNP0av7m7Rv04dLl6Lxa9Nc6Yi5kra68Mk+LnySWRR1Ra6TQw1eH9yHFSvXKR2j\nQAwGA3Fx8UrHyDe15QX1Zfbx8WZ72G4AwsJ307Cht8KJ8qa2zErm3X/sNAM/+IyVG7c9sGxLxD7a\nNvXJfn352k2GTZ7L4AmzWOr/a67rvXztJi9UegatRkPDOl4cO30Oe50dZUq6AWCn1Vjkl9yMjIzs\n52lpaRzafxRHJwcAXIu7cPeu9R6LaivHIJktQS15Y2JuYzCkAZCenkFsbBx6feLfr9MxGq3kZ8Ac\nSFtd+GQfFz7J/OQxmyz3sAaq7uSIjIxk0KBBDB8+nM6dO7Nv3z4AlixZwoABAxg1alSun1OCVqul\nabNGREQU/i+VQhQmNzdXEvQJAOjjE3Bzc1U4Ud7UllmpvGVKFufXpbP4buZ49h05ydkLV7KX/X7o\nON41q6K5pyNi0cpfmDZ6MD/MmsC5y9e4cTvn0XQJSck4O2Z2Jjg7OaBPSs5elpySyrotEbRv1rAQ\ntupBrdu1IOz3jZQuU4oTx0/jXb824b9vonadGhyIPGyRDP+F2soxSGZLUFteL6+qlC5dkjOnzwHw\n1FPutGjRmPC//4gRj4fayoUaqXEfS2ZR1Kn+7ip6vZ7vvvuOO3fuMGLECBwcHGjSpAkTJ07krbfe\n4syZMw/93Pr16xXJ269vN/z91TMXhxA5iY/X4+KaecmCi6szcXF6hRPlTW2Zlcqrs7Mja0qKpg1q\n8+elaKpULg9AQMguPh0zhK27IrM/fzH6BpPmfQtkdmLE3LnLzqgjbNsVxe24eOzt7HBxcqTvK62p\n+PRTJP4950ZScgquTo5A5jwfUxZ8z6gBXXF1drTIdoZu2UHolh3MmD2JgW/0JnRrBP9b9APDRg6i\nW89OrF+b+6gUpaitHINktgQ15S1Rojhz5k9lUP/MH6N0Oh3/WzqH0aMmYTQaFU5XtKipXKiVGvex\nZH4CWckIC0tR9UgOAE9PTzQaDe7u7hgMhuz3AMqVK0d8fHyOn1NClarPMWzoAIICV+HpWYW3RwxW\nLIsQj2LfvoP4tsict6ClbxNVXDurtsxK5b134s8jJ/+kfFn37NeXrt7gnU8WsnzDVlZtCuXCletU\neuYpZn/wFt/PmoD/l1Op8UJlerX35ftZE3ijewc+GPIa38+aQMuXvKn4tAfnLl3FaDSx78hJalZ9\nDoCvV22gTvXn8antaZFtvHdi0cSERBL0icT9fYnK3TtxuLg6WyTHf6G2cgyS2RLUklej0bB02Xw+\nmjSTmJjbACxY9CnfLl2VPapDPD5qKRdqpsZ9LJlFUaf6To6TJ09iMpm4ffs2Op3ugeVmszlfn7OU\nSZM+o0PHvnTs1I+TJ8/y9eIfFMtSEFqtlm1b/KlVy5MtwWtoUL+u0pFypba8oL7Mh48cJzU1lYjw\nAIxGI/sPHFE6ayZl/QAAIABJREFUUp7UllmpvIdOnKXXO1PpP+4T3EuVoFbV55j5v1UArFs0nf9N\nH8vALm3p92prKpcvy6j+3Ziy4HvemDSbt6fOJ/Xv6+0fxk6rpVubZgwa/xm/hu2hR7vmxNy5y/e/\nbCZ87yFenzCLtZvDC30bm7dszPqgH1kf9COly5Ri0y9b6NS5LesCf6BLjw5sWBdc6Bn+K7WVY5DM\nlqCWvJ27tudF75pM/2Q8QVtWU79BXTq94sfwtwcRtGU1HTv5KR0xV9JWFz7Zx4VPMj95nrQ5OWzM\nWb0AKhQZGcmyZcvQaDTcuHGD8ePHs3jxYhYsWEDJkiWZPn06bdq0AXjgc40aNcrXd9jpni7MTXjs\nVPufKYSwuKQT6poAGeDZBkOUjlAgN5PilI4gxGPhpCumdIQCS0pLVTqCEEIlMtKuKh2hUN1u18xi\n31V6y06LfVdOVD8nR/ny5ZkyZUr263s7L7Lej4yMfOBzQgghhBBCCCFEkWclIywsRfWXqwghhBBC\nCCGEEEKAykdy+Pj44OPj89g+J4QQQgghhBBCFCXWMleGpchIDiGEEEIIIYQQQhQJ0skhhBBCCCGE\nEEKIIkHVl6sIIYQQQgghhBAiZ3K5ihBCCCGEEEIIIYQKyUgOIYQQQgghhBCiiJKRHEIIIYQQQggh\nhBAqJCM5hOK0thqlIxSYvdZO6QgFkpSWqnQEYYX6tpqldIQCO+HnrnSEAim9IU7pCE8EG6UDFJBG\nhe2eh0MJpSMU2F9p15WOUOSp7XwIwJCRrnQEISzPrLaW8tHISA4hhBBCCCGEEEIUCTKSQwghhBBC\nCCGEKKJkTg4hhBBCCCGEEEIIFZKRHEIIIYQQQgghRBFlNsmcHEIIIYQQQgghhBCqIyM5hBBCCCGE\nEEKIIkrm5BBCCCGEEEIIIYRQIRnJIYQQQgghhBBCFFFms8zJIYQQQgghhBBCCKE60smhAC+vquza\nuYkd4QEs+3a+0nHypWxZD6Iit5KoP49Go1E6To7KlvVg795g4uLOZuf8/PMphIWtZ+7cqcqGewjv\nerUJ2b6OrSFr+WzWhwCMfmcIW0PW8u1389FqrXewVYP6ddm9cxM7d2xg3pypSsfJt3lzphIRHsD8\nedOUjpIvSh17JdxL8nnwF6w5sx5bzf1NxdDPRvDJL7OZsX4WFatV+k/rb9K5GZ8GzGbi95NxcHag\nmJMDH6+ZwfSfZzLx+8kUc3Io0Ppsy1fCefoinKcuwGH4B/ctc3xnMs5TvsB5xle4zP72P+W1a9wK\n5+mLcPrgM3BwhGIOOH00D+epX2a+V6xgeR+VWurke6nt2FNLW/3vdu9h7aA1ebp8WX4/sY2VG5fw\n/c9fUb1GFVZuXMLKjUsIO7CJgcP6KB0xV2pr+9RUVzxV1p09vwdxJ/YMGo2GChWe4cKF/WzZ6s+v\nv65QOl6u1LSfs6itTgZ1ZrYWZpPlHtagSHVy3Lp1i3nz5ikdI09nzpynabNXaeHbFYB63rUVTpS3\n2Ng4/Nr0IjLykNJRchUbG0e7dq8RFXUYgDp1auDs7ETLlt3R6ezw9q6lcML7Xbl8lU4d+tLWrxdl\nypTi5cYNaNK0IW39enHi+Gk6dmqtdMQcXbocTSu/njRr0YUy7qWoUaOa0pHyVLdODZycHWnu2xWd\nTifHXi4S4xOY1ucj/jx85oFlG7/5hY+6jefrcQvo8W7vPNfVvLsvXg1rZL/WaDX49W3L5B4T2Rmw\ng9Z922LMyGDBu/OZ0nMi+0MiadHDt0B5TdeukDhlFIlT38n8jueqZi9LXjCDxOnvYfjVn/RDe/Nc\nl65ZG7Se95QNjQb7Vp1InPoOabtDsW/VCYwZJH/1KYlT3yX9wB50zdsWKO+jUkudnEWNx55a2up/\nt3v/fm2N9uyMpH/nYbzecySnjp+lf+dh9O88jDMnz7EjZLfS8XKltrZPTXXF3dh4OrS/v+yGh/9G\nu7a9eeWVAQomy5ua9jOos05WY2ahnCLVyVGmTBnGjh2rdIw8ZWRkZD83GNK4En1NwTT5YzAYiIuL\nVzpGnv6ds0GDuoSFZZ4whYf/ho+Pt1LRHiom5jYGQxoA6ekZVK/+Ar/tjgQgYsfv1G9QV8l4ubp5\n8xYGgwHIzG40GhVOlDcfH2+2/10ewsJ307ChdZWHh1Hq2Es3pJOkT3rospgrNwEwZhgxGTO77J+q\nWJbJK6cxbe1ndBvVM9d1l61cjktnLmEymjj221GqvliNdEM6cTF3gcw6Mmu9+XZv+UtPx3Q75oGP\n2DVoQnpU5v+/rUc5nCZ9jvPHX2LftV+uq7Z96hmMVy6AyUTGHwfRVPGE9HTMcbF/f3cGmCz704Va\n6uQsajz21NJW/7ssqKFsNGxcjzWB3zJo2GvZ7zk4FqOMeykuX4hWMFne1Nb2qaE8ZMnMqr/vvabN\nGhES+jMjR76hUKr8UdN+BnXWyWrMLJRTpDo5oqOjGTZsGAcPHqRXr1707t2bhQsXAnD06FG6d+9O\n//79+eijjxROCh07tubw4TDcPUpz585dpeMUWW5uruj1CQDo9Qm4ubkqnOjhvLyqUrp0SeLi9CQk\n/JO3eHHrzHuvmjWrU6Z0KU6d+lPpKHlyc3MlIas8xFtveVCLvh8MYPMPgQD0eb8fiz9YxMe9JlH+\nhQqUfKpUjv/OydWJlIRkAJITknB0dcpeVsyxGK37tmX3pl0FzqP1fgmXud9jU7wE5sT7T5TRaLAt\nXxnjhcxyWqz3myQvmUPitHfRPFMJm5Klc1yvjZMz5uTMDh9zciI2js7/LLQvhq5VJ9J/217gvE8S\ntR570lY/fjE3b+PXsCv9O7/FS80aUNXzeQCatnyZ3eG/K5wu/9TU9qnVjRsx1K7VgnZt+9DC92Wr\nHzWjJmqsk9WY2ZqYTTYWe1gD673g/xHMnDmTr7/+Gg8PD4YOHcqpU6eIiIhg6NCh+Pn5YbLwL24P\nExQUSlBQKF9+MYMOHVqxadNWpSMVSfHxCbi6ugDg4uL8wC8E1qBEieLMmT+VQf1HUaduDZ5+uiyQ\nmTc+3vry3qtECTcWfvkJvV97S+ko+RIfr8clqzy4Wmd5UIsOr79C9LkrnD5wCoByzz7N6C/eA8DR\n1YlST5WiXqsGvNyxMW5lSpBmSCNZn0TwD4Fc++sqDi6OmZ91diT5nhEjI+aM5qc5q+57L78yDv5O\nwsHfcRg8CrsXG5G+/7fsZVrPOmScPJL9WlOuPE5vTwIyOzFsS5ZB4/0SukYtsHErCelpmJMSMWz5\nBeP1aGwcMztibBycMCcnZq/Hcfh4Uv2/y+4EEQ+n1mNP2urHLz0tnfS0dAB2hOzmhWrPcebkOVq3\nb86yr6x73oUsamv71CotLY20zMGubNkSjqdnFY4fP61sqCJCjXWyGjML5RSpkRxZDAYDHh4eANSp\nU4cLFy7Qt29foqKiGDt2LBs3blQ0n06ny36uT0gkJSVVwTRFW2TkIVq0eBkAX9/GREVZ17WSGo2G\npcvm89GkmcTE3ObQoT94uXEDAJq3eJkD+4/ksQblaDQaVvy4kA/Gz+DmzVtKx8mXffsO4tuiMQAt\nfZuo5tpZa1O7SR2qeldj/cK12e9d++sqX4yey8e9P2R8xzGcO/onIau28HHvD9nwzXp+nL6Mj3t/\nSNS2fVy/cI0KVSpia2tLzca1OXsoc96P3mP7cvrAKY7/fqzgobR22U/NycmY0wz3LbZr0OS+Tg/j\ntSskLcycqyNhwjCM50+TFvpr5twdm9aQsvwrEqe/R/r+3zBdv4KmfCWwsUVb0xvjn5kdO8V6Dibj\nzHEyTljv3AfWQo3HnrTVhcPJyTH7+YsNanP5YjRarYbnqlTm9AnrHxWhxrZPrZyd/xnl16ihN39d\nuKxgmqJFjXWyGjNbE7PZcg9rUCQ7Oezt7bl5M/Oa8SNHjlC5cmWcnJz46KOPmDt3LkuWLCEtq2tY\nAW3aNCds+3rCtq/Hw700oaE7FcuSX1qtlm1b/KlVy5MtwWtoUN8654rQarVs3ryGmjU9CQpahZ2d\nltRUA2Fh6zEajRw4cFTpiPfp3LU9L3rXZPon4wnasprKlSvw+54otoaspWat6gQFhiodMUfdu3ek\nXr06zJr5IWGh62hoZfOdPMzhI8dJTU0lIjwAo9HI/gPW24mURaljT6PVMGX1dCp6Vmbyyml4+njR\ndWQPAF6fNhT38h5M8/+UoZ+NAOCnOat4e85oPv7pEyb9OAV7B/sc123MMLL9p23MWD+T5t19CV2z\nlRLuJXn1ra74tGnINP9P8evXrkB5tXUa4Pzxlzh//CU2biUwXv4L+y59/9meFzwxnv4j+3Wq/zIc\n3/oAp8nzcJo4C3Q558VoxBAWjPO0BeiatcEQGohNiVLYv9oHXf3GOE/5Al3rVwqU91GppU7OosZj\nTy1t9b/bvfr16zzw2prUa1SXgO0r8Q/+jpvXb3Hs0AkaNqnPvt37lY6WL2pr+9RUV2i1WoKCVlGz\nZnV+/XUFo0a/yW97AgkL/4Vr125a9Q8/atrPoM46WY2ZhXJszGZr6W95dNHR0cyYMYMhQ4bw+eef\nY2NjQ8OGDXnvvff48ccfCQkJwWw24+Xlle95Oex0Txdy6sdLjf+ZWlt13GrrXvb3/GqsBklp8guk\neFDnstZ9cv4wyxomKB2hQEpvOKt0hCeCdVwBnH8aFbZ7FVzclY5QYH/FX1c6QpGntvMhAENGutIR\nhBXKSLuqdIRCdenFVhb7roqHlJ+nrEh1chQG6eQofNLJUfikk0M8jHRyFD7p5LAM6eQofNLJIR5G\nbedDIJ0c4uGkk+PxsYZOjiI58agQQgghhBBCCCGwmrueWEqRnJNDCCGEEEIIIYQQTx4ZySGEEEII\nIYQQQhRRT9oEFTKSQwghhBBCCCGEEEWCjOQQQgghhBBCCCGKKJmTQwghhBBCCCGEEEKFZCSHEEII\nIYQQQghRRJnNMpJDCCGEEEIIIYQQQnVkJEcebG3V1Q9kVuHUuRkmo9IRCsyYpq7Mauy7VV9JVp+g\nm0eUjlBgZTao69iL7e+pdIQCaxacrHSEAjsee1HpCAWixnbvQvx1pSMUmNravrqln1c6QoEdun1O\n6QgFprZyoUZyDmd9zCalE1iWuv6CF0IIIYQQQgghhMiBdHIIIYQQQgghhBCiSJDLVYQQQgghhBBC\niCLKJBOPCiGEEEIIIYQQQqiPjOQQQgghhBBCCCGKKLmFrBBCCCGEEEIIIYQKyUgOIYQQQgghhBCi\niDKbZCSHEEIIIYQQQgghhOrISA4hhBBCCCGEEKKIMpuVTvCg27dvM3LkSLRaLUajkWnTplGhQgUm\nTJhATEwML7zwAh9//DG2trYcO3aMzz77DLPZzFtvvUWLFi1yXbeM5FCAX+vmhIT8TEjIz1y8cIBX\nOrVROlKuKlZ8hiuXDxMaso7g4NVKx8mXsmU9iIrcSqL+PBqNRuk4+eLlVZVdOzexIzyAZd/OVzpO\nvr0zeggROzYoHSPf5s2ZSkR4APPnTVM6Sr6opSyXLevB3r3BxMWdzc75+edTCAtbz9y5U5UNlwel\njj3bpyvhOPFLHMfPp9jgcfct09ZritOHi3D6cCHaOo3+0/p1bXrgOOELHIZMAI0Gm9JP4Th+Po7j\n5+EwZCLYFO4pwEstfPg2YBHfBiwi5OgmWnVszo+B/2PZhq/4cvls7IvpCvX7Hwe11W9qqS+yqLHd\nU0tmewd75q+YxTfrv2TOD59ip7Pjvalvs3TDIsZMH6V0vFyprRxnUVN9oZZyfC+1lguRsxIlSrBm\nzRpWrVrFu+++y9KlS/nll1+oUaMGa9aswdbWlt27dwMwc+ZMFixYwPfff8+CBQswGo25rrtQznBu\n3brFvHnzCmPVeVq6dCl//fVXjssDAgJISUmxYKIHhYRG4OfXEz+/nly5co2w8N2K5smPsLDdtPbr\nQYcOfZWOki+xsXH4telFZOQhpaPk25kz52na7FVa+HYFoJ53bYUT5U2n01G7tpfSMfKtbp0aODk7\n0ty3KzqdThX7WC1lOTY2jnbtXiMq6jAAderUwNnZiZYtu6PT2eHtXUvhhDlT6tgz3bhC8sx3SZ49\nBgDbSlWyl+ladyVpzjiSPh+Hzq97nuuyf6U/NqU8sl/buLihqVaH5FnvYYy+gLbuy5iTE0le+BHJ\ns8diun0Dba0Gj3+j7vH7jkiGdB3FkK6juHH1Jvt27mfwK8N5s8tITh47TZPWLxfq9z8qtdVvoJ76\nIosa2z21ZG7UvAEnDp9iePd3OXn4FANHvoaDkyNDu4zCzs6O6rWrKR0xR2orx6C++kIt5fheaiwX\n1sRssrHYQ6/XEx0d/cBDr9ffl0mj0WBrm9kdkZCQQLVq1Thw4ED2KI3mzZuzf/9+DAYDRqMRDw8P\nnJycqFSpEhcvXsx1ewulk6NMmTKMHTu2MFadK6PRyNChQ3n22Wdz/MyGDRsU7+TIUrlyBWJibpOU\nlKx0lDw1a/YS4WG/MHr0m0pHyReDwUBcXLzSMQokIyMj+7nBkMaV6GsKpsmf1wf3YcXKdUrHyDcf\nH2+2h2V2KoaF76ZhQ2+FE+VNLWX53zkbNKhL2N/7Ojz8N3x8rHdfK3bs3fsrREY65thb2S9Nt65j\noyuGjb0D5pQkADSVq+H4/lwcJ3yJ3cu5jwDUVKqC8czRzFWfPITmueqQnAgpf7c3xgwwmR7v9uTg\n6QrliL11l8SEJMx/j5fVaDRc/ivaIt//X6mtfgP11BdZ1NjuqSXz1UvXcHAsBoBzcWfMZojadQCA\nqN0HqFnPev8gV1s5BvXVF2opx/dSY7l4Ui1fvpyWLVs+8Fi+fPkDnz137hy9e/dmxowZNGjQgPj4\neFxdXQFwdXUlPj6euLg4XFxcsv9N1vu5KZROjujoaIYNG8YPP/zAgAED6NKlC2vXrgVg1KhR2T0v\nhw8fZuLEicTGxjJw4ED69+/PgAEDiI2NBeDDDz+kT58+9O/fn4MHDwIwa9YsevfuTf/+/Tlx4gQB\nAQG8++67DB8+nICAACZMmMAff/xBZGQkgwYNYvjw4XTu3Jl9+/YRFRXFqVOnGDFihGIjTe7V+dV2\nbPp1q9Ix8nT9egxeNZrQ2q8nvr5NqFmjutKRiqyOHVtz+HAY7h6luXPnrtJxcqXVamnarBEREXuU\njpJvbm6uJOgTANDHJ+Dm5qpwoqLLzc0Vfda+1lv/vlbq2NPWboTT9KXYuLphTvrnF46MQ3tw+vgb\nnKb+j7TwTQDYdx5I8qIpJM96F7uGvqDJZVotRyfMf3domFOSsHF0zl5k41YKjac3GScOFM5G/Ytv\nh2aEb9kJgFfd6qze9h31X36Ra5et96RajfWbWqmp3cuihsyXL0RT09sL/x0/Ur1WNYwZRhITMjtM\nExOScHF1zmMNIr/UWl+ooRyLx8dktrHYY+DAgYSFhT3wGDhw4AO5nn/+efz9/VmyZAkzZszA1dU1\ne8RHQkICxYsXp3jx4iQkJGT/m6z3c1OoF+T26tWLFStWsHbtWpYvX47JZKJTp04EBgYCEBgYyCuv\nvIKLiwvLli1j5cqVtG/fnvXr15Oens7JkydZvXo1K1eupG7duuzYsYP4+Hj8/f1ZuXIl1aplDrVL\nS0vjm2++oUePHvd9v16v56uvvmLp0qXMnTuXBg0aUL16dRYvXqzISJN/a9+hFUFBIUrHyFNaWhrJ\nySkYjUY2b96Ol1dVpSMVWUFBodSt25Kr0dfp0KGV0nFy1a9vN/z91XHtaZb4eD0urpk9wS6uzsTF\n6fP4F+K/io9PwDVrX7tY/75W6tjLOLqXpClDMd+9jbZWw+z37Tv1I3HymyR+9Ab2nfoBYFv+WRxH\nTcfx/bnYFC+BjUtx7F8dgOP7c7F72Q+HYR/i+P7czFEbKUnYODgCYFPMEXNyYuaKtXY4vP4+qcvn\nW2wkRzO/l9m57TcAThw+Rd82b7Bjyy5e7dPRIt//X6ixflMrNbV7WdSQuWOPtuwO/Z3eLQaxJ2wv\nWjsNzi5OADg5O5KgT1Q4YdGh1vpCDeVYqJOrqyvPPPPMA4+sERpZ0tLSsp+7uLhQrFgx6tevz65d\nuwDYtWsX9erVo1ixYmg0GmJiYkhOTubSpUtUrFgx1wyF2smxefNm+vbty+uvv05MTAzx8fE0b96c\nnTt3kpGRwZEjR/Dx8SE+Pp4xY8bQt29ffvrpJ27evImdnR1Dhgxh/PjxTJ48mVu3bnHu3Dl8fHyy\n15816UydOnUe+v2enp5oNBrc3d0xGAyFuakF5uFRhvS0NGJj45SOkidnZ6fs5y81qs/5vy4pmKbo\n0un+mYRPn5BISkqqgmnyVqXqcwwbOoCgwFV4elbh7RGDlY6Up337DuLbojEALX2byHWdhSgy8hAt\nWmTOueDr25ioKOvd14ode1q77KfmlGTM6fe0UxlpkJYKhlRs/h6xYbp8juQFH5E8ZxxJ04ZjjruD\nYdMKkueMI31PCClLPiV5zjiM509hvHAWTdXMeVC0ni9iPH8KgGID3iVtx6+Yrl+2yCaWKlOS9LQM\n4u/q0dr9M/IkMSEJQ6p1tcv3UmP9pkZqa/dARZltbND/3bkcF5s5rLte4xcBaNCkHscPnlAsWlGj\nxvpCNeVYPDZms43FHvl14sQJ+vXrR//+/ZkwYQITJkyga9euHDlyhL59+5KWlkbTpk0BmDBhAqNH\nj2bw4MG8/fbbaLW53yS2UG8hu2TJEoKDgwFo27YtZrMZnU5H9erV+eabb2jYsCG2trYEBgbi7e3N\noEGD+Omnn/jzzz8xGo20atWK9u3bs2nTJlavXs2LL75IaGgonTt3BsD0969QOc2we/LkSUwmE7Gx\nsdkHs52dXZ6zsVpCp05+BAZa/ygOgMaNfZj68TgMhjT27Ili//7DSkfKk1arJThwFbVqebIleA0f\nTZ5FlJXnbtOmOe++MxSAc+cuEBq6U+FEuZs06bPs5xE7NvD14h8UTJM/h48cJzU1lYjwAI4cPcH+\nA0eUjpQntZRlrVbLr7+uoGZNT4KCVjFlymxSUw2Eha3n6NETHDhwVOmIOVLq2NPWqJc9qajp5lVM\n0RfQdXiNtOA1pEUE4TTxSwDSdm0GIHXTChxHTwcbG8xJCaQsnp7jus0JcRjP/oHjhC8w34khLTQA\nzXPVsfNujG0pD3StupK2fQMZhwt3eHXztk2I2JY5N0vVGi/w3pS3MZnM6O/q+WhUzvmVpsb6DdRT\nX2RRW7sH6sm8bcN2Pvvfx7Tr5kdGhpEP35rKm2MGsXTDIs6eOMfJI6eVjpgjtZVjNdYXainH91Jb\nuRB5q1u3LqtWrXrg/QULFjzwXu3atfH398/3um3M5sd/19zo6GhmzJhBuXLlOHbsGFWqVOHUqVN8\n//33lCxZkv379zNw4EACAgKoVq0ap0+f5v3336dcuXJ4eHig1Wqz59mwtbUlPT2dKVOm4OnpycyZ\nMzl69Cg6nY4PPviAs2fPcvfuXd544w0gs5enb9++JCcns2zZMjQaDTdu3GD8+PE0atSI1atXExoa\nyksvvcTQoUPz3Bb7YuUf9+4pVIXw31noTCrMnP8+SvFfqa9UqI/WVn23YDOalO+kLog7/T2VjlBg\nzYKtfzLsfzsee1HpCAWixvpN2r3CV7f080pHKLBDt88pHaHApCwXPjXWcRlpV5WOUKiOVepkse+q\ndTHQYt+Vk0Lp5Dh//jwLFy58aC+MpURGRrJt2zamTJnySOuRTo7CJ50c4mHUVyrURzo5Cp90cliG\ndHIUPmn3Cp90cliGlOXCp8Y6Tjo5Hh9r6OR47HNy3L17l8mTJ9Opk+V2pBBCCCGEEEIIIcRjn5Oj\nRIkSrFmz5nGvtsB8fHzum6RUCCGEEEIIIYR40pgKMCFoUVCod1cRQgghhBBCCCGEsJRCvbuKEEII\nIYQQQgghlFOQW7sWBTKSQwghhBBCCCGEEEWCjOQQQgghhBBCCCGKKBXezPKRyEgOIYQQQgghhBBC\nFAkykkMIIYQQQgghhCiinrS7q0gnRx7MKhvbY2OjvgJso7J9rEayh0VRobY67qOwkkpHKDB/N/Wd\nGnjFKp2gYNRVijOp7dgD9Z3DmVXYWmts1Tco3GgyKR2hQNR35IGtCusLUbSo70xGCCGEEEIIIYQQ\n+SJ3VxFCCCGEEEIIIYRQIRnJIYQQQgghhBBCFFFP2pwcMpJDCCGEEEIIIYQQRYKM5BBCCCGEEEII\nIYoo9U1r/GhkJIcQQgghhBBCCCGKBBnJIYQQQgghhBBCFFEyJ4cQQgghhBBCCCGECslIDiGEEEII\nIYQQoogyy0gOUdgqVnyGK5cPExqyjuDg1UrHyZNf6+aEhPxMSMjPXLxwgFc6tVE6Ur69M3oIETs2\nKB0jX7y8qrJr5yZ2hAew7Nv5SsfJl3lzphIRHsD8edOUjpIvDerXZffOTezcsYF5c6YqHSdf1LKP\ny5b1YO/eYOLizqLRaAD4/PMphIWtZ+7cqcqGy4d+fbuxdas/oSHrKFfuKYt8p6t7Cd4PmsW8Myux\n1dzfHDsWd2LwV+8ycs1k/N7u8p/W7zu0E++sm8aAL0dhq9VQ8pkyvPPzVEavncqABaOwsS3YCY/u\nhYpU+Gke5VfN4anP3rtvWclhvXlu1ypKvzPgP2UFKPF6N8qvnkvZOR+AVoPd0x6UXzWH8is/p+zc\nD8DWsqcsaqsv1NiGgDLH3qNSw7lFo+YN+N/6Bfxv/QK2HN5Ai3ZNmb7oI5YELOLrtfMpXrK40hFz\npLbzTrXVFaDO+kJtfz8JZamqk2P79u3cvHkTgMjISKZPn65wov8uLGw3rf160KFDX6Wj5CkkNAI/\nv574+fXkypVrhIXvVjpSvuh0OmrX9lI6Rr6dOXOeps1epYVvVwDqeddWOFHu6tapgZOzI819u6LT\n6aw+L8Cly9G08utJsxZdKONeiho1qikdKVdq2sexsXG0a/caUVGHAahTpwbOzk60bNkdnc4Ob+9a\nCifMWbmhs1WwAAAgAElEQVRyT9GkSSPatu1Na78eXLt2wyLfmxyfyFevzeDi4T8fWNb23e4Ef/Ez\nX702g5Cv8/5jqt273Sn5TJns186lXHmhkRcLenzMtdOXqOVXnxR9MkvemM3CXlO5cyUGrxZ1C5Q3\n7UI0l/uM5Uq/9wEoVqNK9rL49Vu59v7n+V5XqZF90T7tnv1aU7I4jj61udJ3HIYzF3Bu2QhjQhJX\n3/qYK/0/ID36Jk7N6hco76NSW32htjYElDv2HoVazi32RkTxVvd3eKv7O9y4epO42HjS09MZ1nUU\ngf5baNeltdIRc6S280611RWgzvoC1PX3k1CW6jo5YmJilI7xWDRr9hLhYb8wevSbSkfJt8qVKxAT\nc5ukpGSlo+TL64P7sGLlOqVj5FtGRkb2c4MhjSvR1xRMkzcfH2+2h2WeeISF76ZhQ2+FE+Xt5s1b\nGAwGANLTMzAajQonyp2a9rHBYCAuLj77dYMGdQn7O3t4+G/4+Fhv9tatm6HR2LJ1qz9ffDEDWwuN\nGMgwpJOiT3rosrJVyuM3ogujfppCpRdfAKBinecZ5T+Fd9dPx6dH81zXXaHms5zbdxKAM7/9QeUX\nXyBFn0RqQgoApgwjJqOpgIH/OV7Maemk37iV/dp4Jw7M99+grlitqpRfMZsKa+bi2jX3P6iK1ahC\nStQxAJL2HsahbnVM+kRMiZntjTkjAwqa9xGprb5QWxsCyh17j0Jt5xZPVyhL7O27XDp/GVvbzFF2\nLsWdib8bn8e/VJ5azjvVVleAOusLUOffT9bCZMGHNbCK1iQyMpJBgwYxfPhwOnfuzLZt2+jfv3/2\n8g8//JCoqCh2797Nxx9/zMSJEwG4dOkSo0ePpmPHjkRFRQFw8OBBevXqRe/evVm4cCEAAQEBjBo1\nihEjRvDKK69w7tw5y2/kPa5fj8GrRhNa+/XE17cJNWtUVzRPfnV+tR2bft2qdIx80Wq1NG3WiIiI\nPUpHKZCOHVtz+HAY7h6luXPnrtJxcuXm5kqCPgEAfXwCbm6uCifKv5o1q1OmdClOnXrwF3RrouZ9\n7Obmij4ru966s3u4l0an09G2bW9SklOsYmh0Ze+qhC7eyI+jFvDqxH4AtB/Tk2/fnMOX3adQ79XG\naOw0Of57B1cnUv/uIEhJSMbB1Sl7mat7Cao2rsXp3ccKnMuphQ+Vfv0GTakSGOP0uX629Oj+XB0+\njcuvjcO1Ywuwy3kaMFtXJ4x/5zUlJKFxcc5epnEvidNLdUnac7DAeR8HtdQXoK42BKzz2MuNGs8t\nWrRvRsSWXcTFxmNfTMfPO1fSbcCrhG/ZpXS0PKnpvBPUVVeA+uoLtf79JJRhFZ0cAHq9nq+++oql\nS5fy7bffUrp0ac6fP09qaipnzpyhQYMGNGnShGnTpjFz5kwAkpOTWbBgAbNnz2blypUAzJw5k4UL\nF+Lv78/x48c5deoUkDm8cPHixYwcOZL169crtp0AaWlpJCenYDQa2bx5O15eVRXNk1/tO7QiKChE\n6Rj50q9vN/z9rft62YcJCgqlbt2WXI2+TocOrZSOk6v4eD0uri4AuLg6E5fHHzzWokQJNxZ++QlD\nho1VOkqe1LqPAeLjE3DNyu5i3dnj9Qns2r0XgB0Re6hW7XmFE8GtC9e5ef4qCbfjMZsyR0g8Xb0i\nQ5a9zyj/KbiUccO5pCvt3uvBKP8pNOjejEGL3mGUf+bIj5SEZIo5OwJQzNkxe8SIVqel37wR+E9Y\nUvCRHEDSjkguvjKcjJu3cW7uk+tn7atW5ulvPqb8itloS5dAW6I4pUb1o/yK2RTv0ppy8yZSfsVs\nitWpltmx8XdeW2dHjAmJANjY2VF25lhuTF5o8ZEcoK76AtTVhoB1Hnu5UeO5RZPWL7ErZA8Nm9Un\nLjaens36s3TeD/R/q7fS0fKkpvNOtdUVoL76Qq1/P1kLMzYWe1gDq+nk8PT0RKPR4O7ujsFgoHv3\n7mzYsIGQkBD8/Pwe+m+qVauGjY0NZcuWJS4uDsgcMu3h4QFAnTp1uHDhAgDVq2f29pUtW5b4eGWH\n6Dk7//OL2kuN6nP+r0sKpskfD48ypKelERsbp3SUfKlS9TmGDR1AUOAqPD2r8PaIwUpHypNOp8t+\nrk9IJCUlVcE0edu37yC+LRoD0NK3CZGRhxROlDeNRsOKHxfywfgZ3Lx5K+9/oDA17uMskZGHaNHi\nZQB8fRsTFWW92fftPUDNmpltRO1aXly8eEXhRBDz13Vcy7ihc7BHo81sqqNPXGDJ4Nks6j2dzzuM\nJ/7mXbZ8sY5FvacTtX4nP45awKLe07l46E8uHzvP8z6Z21S1cc3seT96zRzK7pXbuHHuaoEz2djZ\nZT83JSZjSjXk+vnUU+eJHvZ/9u48LqqqDwP4AzMMoIC4IGKLmrmDS+CWOwaiopa5YEpmlpa5ZPa6\nV6aVtqC5ZIu7aJqYiooiCLjkCrmhoua+g8q+DTAz7x8EiQoDCnPmDM/3/fCJmcF7n7nv79575sy5\n536OG29PwtW+o5ET9wAPFq7BjbcnIWlzKG5PmI0bb09C5olzyIy+AOuWLgCAim1bIPPEOQCA46yx\nSPx9O7IuXS9x3mcl2/FCtnMIYJz7XlFka1tUdaiC7OxsJCUkA2ZmSE7I7WxOjE+CzUOjpYyRTO1O\n2Y4VgJzHCxk/P5E4RnML2bNnz0Kr1SI+Ph4qlQpt27bFwoULERMTkz9yw8LCosB1bmZmj/cUWVpa\nIjY2Fo6Ojjhx4gS6dOmCmJiYAn+re+S6YUNr3741ZnzxKdTqLBw4cBSRkceF5imOXr08sW2bHL3p\nADB16jf5v++J2IyfFq8QmKZ4unXrjI/HjQAAXLx4BaGhewUnKtrxE6eRmZmJPeGbcOLkGURGnRAd\nSa9+/bzh5tYcc2ZPAwBMmz4Hh4+IGQJfHDJtY6VSia1bV8PFpTG2b1+Dzz//FpmZaoSFbcTJk2cQ\nFXVSdMRCnTx1FhkZmQgNCcCDB/GYv2CJQdZrrlTgw5VT8FyjWvhw9VTsWvAnXnJriJCfNmPnvA0Y\nunAsLKxUCP4xd/ThjnkBGLFsIszMzJCWmIrlHxY+I37qg2RcOhqDcQFfIuH2fexZHoTar9RDs26t\nUOW5auj8bg/sXbETp3ZFFjtvxQ6uqDwsd5K6rKu3oL5wBVVG+iD+1/Wo9KYn7N/yhnklW5jb2SBu\n1mI8WLgGz/08A2ZmZtAkpeD22K8LXbYmPgkZUafxwtofkHMnDvGrt8CqeUPYerwKi5rVUXno60hY\nHYjU3QeLnfdZyXa8kO0cAojb956WbG2Ljt3aY++u3EtrjuyNRG+fHvhl43yYmZtj5vjZgtMVTaZ2\np2zHCkDO44WMn5+MiVbsx1+DM9OJ/sSP3Dk5li5dCoVCgbt372LSpElo27YtFi1ahOjoaPz6668A\nciceXblyJZo0aQJ3d3fs2rULn3/+OeLj4zFu3Dj4+/sjKioK3333HczMzNCmTRuMHz8emzZtQkJC\nAoYPH47o6GisXbsWc+bMKVY2leXzZfnWS92TOn6MnVZrLFPUmC7hOzkZJaV54XM6GCutTq7jxQdO\n7URHKLGPrIz30qLCNLlc8vlFRJLvTC1n+8IImrgl0rxaXdERSuxU/BXREUpMI1m7U749T87jRZb6\npugIZWqPY3+DratzrPjJmY2mkyOvw+JhP/30E+rXrw8PD3G3uWInR9ljJ0fZE76Tk1FiJ0fZYyeH\nYbCTo+zJ2L4wgiZuibCTwzDYyVH2ZDxemHonR7jjAIOtyz12g8HWVRijmZPjUd988w1OnDgBd3d3\n0VGIiIiIiIiISAJGMSdH69at0bp1wVnap06dKigNERERERERkWkwlrueGIrRjuQgIiIiIiIiIioJ\noxjJQURERERERESlT66ZaJ4dR3IQERERERERkUngSA4iIiIiIiIiE8U5OYiIiIiIiIiIJMSRHERE\nREREREQmqrzNycFODj2slCrREUokI1stOkKJ6UQHeArmZnIN+apgYSk6Qompc7JFRygxpblCdIQS\nyczJEh2hxGTb9xbf/kt0hBJbLDrAU0hZ9Z7oCCViN3Sp6Ajlgplkx4sT9y+JjlBilpK1kwFAq5Xr\n3CdjOxk6KVOTCeHlKkRERERERERkEjiSg4iIiIiIiMhElbfLVTiSg4iIiIiIiIhMAkdyEBERERER\nEZko3kKWiIiIiIiIiEhCHMlBREREREREZKK05WsgB0dyEBEREREREZFp4EgOIiIiIiIiIhOl5Zwc\nRERERERERETyYSeHgdSoUR37DmxF3IMYKBQKKBQKrFg5H9t3rMXMryaJjlekJk0aYN/eQESEb8LS\nJXNFxymWVi1bYP/eQOyN2Ay/72eIjlMsQwa/ieDg9QgNCUDNmjVExymUq1szhOwOQHDIH/hmzjQo\nlUqEhgXg1t1TeOmlWqLjPZGTkyMOHQpCYuIFKBSKxx4bmxpO1fHXwW24H38uP9+gt/pie9Aa7Axe\nB6eajoITFs3v+xnYE74Jc/2+FB2l2GTZ//I4OTni6JFgpCZfMsoafhKRdeF/6DzeWba7wHOTAg5i\n+IowvL00FAN+Dn6q5Qaduoq3l4ZizNp9SM3MRpo6GyNWhePd5WEYs3Yf0tTZpRG/RMaNfR97IjYb\nfL1Po1at53Hj+nGEhgQgKGit6DjFIltmmdpwj577XvPoiJ3B67AzeB0uXj4C714eoiMWSaZ9T8Z2\nsky1bIx0BvwxBuzkMJCEhET07jkEkUePAwB69fZE9Olz8O4xGNZWVnB2aSg4YeHOn7+Ejp36oIt7\nXwCAm2szwYn0u3b9Jl7zHIBOXd6AQ/WqcHY23u0LADVr1kCHDm3h5eUDD8/+uH37ruhIhbpx/RZ6\n9RwML8+BcHCoivoNXsJbgz5A4Jan+5BgCPHxieje/S0c/Xf/e/SxsUmIT4R3j8H5xwunmo5o36EV\nvHsOQXevQbhzO1ZwwsK1aO6MijYV0Nm9L1QqlRTHC5n2vzzx8Ynw7DYQR44cEx2lWETWRVaOBufv\nJjz2/Lf9X8WyYV3xTrtG6Fi/pt7lBB6/jMgr/+172RotNkZdxPJhXeHdrDY2/n0RSnNzfN23LZa/\n2xWdGz6HrSeulOp70UelUqFZsyYGXeezCgvbDw/P/ujZc7DoKMUmU2aZ2nCPnvt2h+5Dd69B6O41\nCDdu3EZE+AHBCQsn274nWzsZkKuWSTx2chiIWp2FxMTk/Me167yIM9HnAACnTsWgdWtXUdH0ysnJ\nyf9drc7CjZu3BaYpntjYe1Cr1QCA7OwcaDQawYmK5uHRCQqFOYKD12PevFkwNzfeXTMu7j7U6iwA\nedtWi3txDwSnKpparUZiYlKhj43No8eL117rCIW5AtuD1uAHvxlGXR+tW7tid9h+AEBY+H60aWO8\nx7Y8Mu1/eYy9hh8lsi42H7uM3s3qFPp6eMxNdG30PADg+oMUfLA6AsNXhGHJ3jNFLvf6gxS8XN0e\nSoU5Wr/kiFM3HsDSQgEHW2sAgNLcDOZmhr0G+t1hg7DaP8Cg63xWnTq9ivCwPzF27HuioxSbTJll\nasM9eu7LU7v2C4iLu4+0tHQBqYpHtn1PtnYyIFctGyOtAX+MgfG35ErRnDlz4OPjA19fX5w5U3Tj\npaz9c+Ey2nVoBQDo2KkNKtnbCc2jj7e3B44fD0N1x2p48ODxb8SMlYtLIzhUq4qYmH9ERymSY/Vq\nUKlU8PLyQUZ6Bnr36iY6kl5NmjRAtWpVcP7cRdFRTF716tWgUlnAu+cQpKdnGPWQXXt7O6QkpwAA\nkpNSYG/kxzZAzv1PNqLqIlujRdTVOLR66cmXeGVrtPgnLhGNalYBACwKP4UZfVph2bCuuHQvCbFJ\nhX+oSsnMho2lBQDAxtICKZlZ+a+lq7Px59+X0N3FcJfwKZVKdOzUFnv2GO+33Y+6cycOTZw7wMNz\nANzdO8DFuZHoSHrJmFnWNlye3n28sG3rLtExCiXjvpdHlnZyHtlrmQyn3HRyREREICkpCevXr4e/\nvz8aNhQ7LGvnjjBYW1lha9AaqNVZiIu7LzSPPtu3h6JFi664dfMOevZ8TXScYqlc2R4LfvwK74+c\nIDqKXknJKdi3/xAAIGLPATRs+LLgREWrXLkSvp87A6NHTRYdpVxITk7BX38dAQDs3XsIDRoYb30k\nJSXD1s4WAGBrZ/PEb+WMjWz7n4xE1UXQyatFdjREXY2DW+3q+Y+v3k/BtE2HMXxFGC7fS0ZcSgY2\nRP6D4SvCsOKvGHwffBzDV4QhPOYmbKwskPrvnBtp6mzYWqkAADqdDl8EHsVo96aws1aV7Rt8yJDB\nb2L9ejnmA8iTlZWF9PQMaDQa7NixG02aNBAdSS8ZM8vYhntYjx5dsSNot/4/FETGfQ+Qq52cR/Za\nFklrZmawH2NQbjo5Ll68iNatW+c/Fj1Rm1arxf8+/RK9ew6BRqNBWOg+oXmKolL910hLTklFRkam\nwDTFo1AosHrlAkycNAuxsfdEx9Hr8KEouLjkfhvUrGkTXL16Q3CiwikUCvy2dC6mT51t9J1zpuLw\n4b/h/O+3hU2bNjLq+jh8+G+4d2kPAOjq3kGKOSNk2v9kJaourj5IRkDURYzy34NL95Kw7siFAq+H\nx9yEe8Pn8x/XrmaLOf1y5+pYN9ITTWpWwYCW9bBsWFcMa98I//NqgWXDusK90fOoVdUWl+KSoNFq\ncfhyLFyerwoAWBwRjeYvVit09EhZqd+gLkaOeBvbt61B48b18dGoYQZd/9OwsamY//urbVvi0uVr\nAtMUj2yZZWzDPay6YzVkZWUjPj5RdJRCybjvydZOBuSvZTKsctPJUa9ePURGRuY/1moNe8WQUqlE\n4HZ/OLs0wuatq9CufSsE7fwd23aswZEjx3DnjvFOJNitW2eE7d6IsN0b4Vi9GkJD94qOpFe/ft5w\nc2uOObOnISw0AG2MeM4TADh56iwyMjIRGhIAN7dm+HNTkOhIhXq9bw+84uqCmV9Nwvada9GyVQus\nXL0A7l3b4+dfv0cPI+xZVyqV2LHjd7i4NMb27WvQsmXzxx4bE6VSiW3/Hi8Ct66CpaUlMjIysTN4\nHVxdm2HL5p2iIxbq+InTyMzMxJ7wTdBoNIiMOiE6kl4y7X95lEoldu1cj6ZNG2Nn0O9o1bKF6EhF\nElUXH3s0x8++nbHYtzPqOlSCR+MXsGRf7uWqOp0Op27eR4sXHfL/frR7U8wIPIr3V4Zj9Np9yMzO\nKWzRsFCYo6/rSxi2PAzbTl5BP7e6iEvOwIq/ziE85iaGrwjDhkjDDQGfOvUb9PQeDO9eQ3D27AX8\ntHiFwdb9tNq3b43Dh3Zg754tuH37LiIjjXMy6IfJllmmNtyj5z63ls3h7e2BoKBQ0dGKJOO+J1s7\nGZCrlo1Rebu7iplOpzOWLGVu9uzZOHnyJFQqFSZOnAhnZ2e9/8au4ksGSFZ6MrLVoiOUmIwFaOjJ\n5J6VtYWl6Aglps4x/K0Xn5XSXI5beebJzMnS/0dGRrZ9T1t+TrFCpawy/gkgH2Y3dKnoCCVmJtm+\nJyMZm+SWSsNdklVa1JKd++SrCkDGo0V21i3REcpUgJPh7gbV/47422srRQcwpClTpoiOQERERERE\nRERlpFx1chARERERERGVJ8Zya1dDKTdzchARERERERGRaeNIDiIiIiIiIiITpZVxopRnwJEcRERE\nRERERGQSOJKDiIiIiIiIyERppbznzdPjSA4iIiIiIiIiMgkcyUFERERERERkonSiAxgYR3IQERER\nERERkUngSA491Jps0RFKRMZeuooqK9ERSixHqxEdoUTUOXLVMQBodfLd0VudI1ddKM0VoiOUWPUK\nlURHKJE7qfGiI5QLdkOXio5QInF96omOUGJvHJKvyXggLkZ0hBKRsQ2nMJfv+1IzM7nmJtDpZKwM\nMja8uwoRERERERERkYTk65YnIiIiIiIiomKRb3z0s+FIDiIiIiIiIiIyCRzJQURERERERGSiytvM\nLhzJQUREREREREQmgSM5iIiIiIiIiEwU765CRERERERERCQhdnIQERERERERkUng5SpERERERERE\nJoq3kKUy5+nRGSEhGxASsgFXr0Shd69uoiPp5eTkiKNHgpGafAkKhUJ0nCdydWuGkN0BCA75A9/M\nmQYAGDvufQSH/IEly+ZCqTS+Pr0aTtVx4OB2PIg/X2C7jh49HKG7AwQm00+hUGD16kXYtWs9vv56\nqug4xTZk8JsIDl6P0JAA1KxZQ3ScIjVp0gD79gYiInwTli6ZKzpOkZycHHHoUBASEy/k1/J3332O\nsLCN+OGHGWLDFWH4h774c8cq1G/0MjYF+2Nj0Er8sGiW6FhFkqku8siYGQDGjX0feyI2G3Sd5i/U\nge1Xi2AzcwEqjJpU4DUzG1tUHP8FbL6YC6u+Q55q+Za9B8J21kJUGDsNUChgXr0GbGYugM2X81Fx\n3HTAvGybhgqFOT7/aRrmbfgBI6e9DwDYfjYQPwb44ccAP9ja25bp+kuDiLp4Fn7fz8Ce8E2Y6/el\n6CiFerQNp1QqERoWgFt3T+Gll2qJjqeXTG0LQI52fWFk2/9IDHZyCBASugeengPg6TkAN27cRlj4\nftGR9IqPT4Rnt4E4cuSY6CiFunH9Fnr1HAwvz4FwcKiKdu1boUPHNvDyHIgzp8/Bu5eH6IiPSYhP\nQs8eb+Ho0eP5z6lUKjRt2lhgquLp08cL0dEx6NbNB9bWlnBxaSQ6kl41a9ZAhw5t4eXlAw/P/rh9\n+67oSEU6f/4SOnbqgy7ufQEAbq7NBCcqXHx8Irp3/6+Wmzd3ho1NRXTt2g8qlQVcXZsKTvg4lcoC\nTZwbAAAu/3MVfb180a/nOwCApi2aCExWNJnqIo+MmVUqFZo1M3wdaG9fR8r00Uj9fCwAQFG3Qf5r\nVv2HIuOPFUj98hNkblqjd1lW/d+BucN/H7jM7Oxh0aQFUj4bA821y7Bo2R66tFSkzpmC1C/GQRN3\nBxYtWpf+m3pIe6/2uHj2MsYP+BSWVpao2+glXDl3BR/3n4CP+09ASmJKma7/WYmqi6fVorkzKtpU\nQGf3vlCpVEa77z3ahqvf4CW8NegDBG4JFh1NL9naFoAc7fonkW3/MyZaA/4YA3ZyCFSnzouIi7uP\ntLR00VH0UqvVSExMEh2jSHFx96FWZwEAsrNz0KhRPfy1/wgAYE/EQbRs1UJkvCfK3a7JBZ4b+s4A\nrF27UVCi4qtT50VER8cAAE6dOos2bVwFJ9LPw6MTFApzBAevx7x5s2Bext9YPqucnJz839XqLNy4\neVtgmqI9eoxo1aoFwsJyO3DDw/9C69bGVx8Dh/TFxvVbARTc1lnqLNy5ZbyNVJnqIo+Mmd8dNgir\n/QWMqNNo/vs9OxvaB/fyHypeqAOrvoNh88U8KOrndoYrXm4Emxk/wnbWQqg6exW5aEXdBsg+cwIA\nkBP9N5QNmkCXlgqkp+X+QY4GOm3ZNlFr1nLC5ZjLAICLZy6iiVsTvFjvRSz4cx5GTHmvTNddGoTV\nxVNq3doVu/89FoeF7zfac/WjbTiNRot7cQ8Epyoe2doWgBzt+ieRbf8jcYx/LyymOXPmwMfHB76+\nvjh58iT69esHX19fTJ8+HQCwYMECDBgwAG+//TZ27dolOG2u1/t0R+BW4++hlk2TJg1QrVoVJCYm\nIyUl9xuh5OQUVKpkJziZfkqlEh06tMHevYdER9HrwoVL6NChDQCgU6e2sLevJDiRfo7Vq0GlUsHL\nywcZ6RlSXCrm7e2B48fDUN2xGh48SBAdp9js7e2QnPzf/mdvb1z7n1KpRNv2LXFw/9H85zy8OiP0\nwCZUc6iKhHjjbvzJWBcyZVYqlejYqS327DkgZP0Wbq/Czm8FzOwrQ5fyXy0qGzgjc/NapP04ExV8\nPwQAWA8chtRvpyLlszFQdfAAirg006yiDXQZuV+s6NLTYFbB5r/XKleFRVNX5JyMKqN3levGpRto\n1jZ3ZFeLV5vDxs4GQzoMxdg3x8Omkg1e9Whbput/FqLr4mnY29shJe9YnGR8x+JH5bXhzp+7KDpK\nscnYtpCRjPufMdGZGe7HGJhEJ0dERASSkpKwfv16+Pv7IyIiAiNGjIC/vz9mzpwJAAgPD8eaNWuw\nevVqeHgYx2ULPXq+hu3bQ0THMCmVK1fC93NnYPSoyUhOToGtbe61vba2NkhKStbzr8V76603sGHD\nVtExiiUoaDesrS2xc+c6qNVZiIu7p/8fCZaUnIJ9+3M7kCL2HEDDhi8LTqTf9u2haNGiK27dvIOe\nPV8THafYkpJSYGf33/736Igl0foO9MaWjTsKPBcavAce7frizu1YdO3WUVCy4pGxLmTKPGTwm1i/\nXtw139lRB5E8YRi0D+7BwvW/D/2a2zegvXUduqSE/BEXitovw2bSN7CZ8SPM7avAzM4eVgPegc2M\nH6Hq7IWKH38Omxk/QlG/cW7HhnUFAICZdQXo0lNzF6y0QMXRU5D26w+AVvNYntJ0MPQwLK0s4bf+\nO2RlZSPhfkL+JSp/7TqAOg1ql+n6n4XoungaSUnJsM07FtsZ37H4YQ+34WQiY9tCRjLufySOSXRy\nXLx4Ea1b/3cN6ZAhQ3D06FFMmDABW7ZsAQD873//w2effYbJkyfjypUroqLmc3R0QHZWFuLjE0VH\nMRkKhQK/LZ2L6VNnIy7uPo4di0a79q0AAJ27tENU5AnBCfWrV68u3n9vCLYErkKjRvXxwQdDRUcq\nlFarxSeffIHu3QdBo9EiNHSv6Eh6HT4UlT93SLOmTXD16g3BiYqmUqnyf09OSUVGRqbANCVz5Mgx\ndOnSDgDg7t4eR48a13W/dV+uA993B2B1wM+o3/BlvDtycP5rqSmpyMxUC0xXNBnrQrbM9RvUxcgR\nb2P7tjVo3Lg+Pho1zHArV1rk/6rLSIMuKyv/sfbOTZjZVwEsrWD272SBmiv/IHX2ZKTO+BjJE9+D\nLlKQAJ0AACAASURBVP4+MjesROqMj5G1JxhpP85E6oyPoblwFpqL52DRJHdOBqWLK3IunAUAVBg5\nAergLdDevFbmb0+r1WLBZ4swwWcitBotIvdG5g/vd3Fzxu1rd8o8w9MSWhdP6fDhv+HepT0AoKt7\nB6Odg+HRNpxMZGtbyErG/c+YlLc5OYzvdhNPoV69eggNDcXrr78OAKhYsSKmT58OnU4HLy8veHt7\n45VXXkG7du0QFRWFxYsXw8/PT2jmXr08sW2bPKM4lEolgratQdOmjbEz6HdM/2wOjkYe1/8PDej1\nvj3wiqsLZn6VOxv9l1/8gIMHjiI45A/cvHkbi39aITjh45RKJbZsWQkXl0bYunU1vpjxPT77bA4A\nIHR3AH75ZZXghIWrWdMRK1cugFarxdq1f+L27VjRkfQ6eeosMjIyERoSgAcP4jF/wRLRkYrUrVtn\nfDxuBADg4sUrRt2RpFQqsXXrari4NMb27Wvw+effIjNTjbCwjTh58gyiok6KjljA7C/n5f/+545V\nuHH9NjZsyz1GXLl8DfvCD4qKppdMdZFHtsxTp36T//ueiM34abHhzh8WzVvBsld/AID2zi1orl2C\nVd8hyNy0BhkbVqDix5/DTKVCRkDu+SFjwwrYTP4GgBl0qclI8/ui0GXrkhORffYUbGcthPZ+LNJ2\nbISifmOoWneEuUMNWPbsB/WOjcg++leZvb9qNapi+sKp0Gq1CNkYCvsq9vhmxVfISMvAnRt3scLP\neM97IuviaR0/cRqZmZnYE74JJ06eQWSUcX7h86Q23Eejh6FNWzfUrVsb83/8DTuCdgtO+WSytS0A\nOdr1j5Jx/yNxzHQ6nU50iNIwe/ZsnDx5EiqVCp07d8bu3buh0+nQpEkTTJ8+HcOHD0dWVhaysrIw\nZswYtG/fvljLtbR6oYyTly5NGU8YVhYqqqxERyixnDIezlvaZKwLrU6+zLIdThXmct02DgCqVzD+\nuV8edic1XnQEMkJxfeqJjlBibxyS73uxA3ExoiOUiFxnkFwytuEyso13pN6TaCVrWwCAkUzLUCLZ\nWbdERyhTi154utuOP43RN/Tf/ausyXfGKsSUKVMKPH733XcLPF62bJkh4xARERERERGRgZlMJwcR\nERERERERFSTfeKBnYxITjxIRERERERERcSQHERERERERkYnSyjhRyjPgSA4iIiIiIiIiMgkcyUFE\nRERERERkouS7Z+GzYScHERERERERERnM8ePHMWfOHFhYWKBChQr44YcfkJOTg4kTJyItLQ2vvvoq\nxowZAwCIiIjAL7/8AjMzM0ydOhVNmzYtctns5CAiIiIiIiIig6lZsyZWrlwJa2trrFu3DmvXrkVy\ncjLefPNNdO/eHSNGjMDFixdRp04dzJ8/H2vWrEFaWho+/vhjrFu3rshls5ODiIiIiIiIyEQZ8nKV\n5ORkJCcnP/a8nZ0d7Ozs8h87Ojrm/25hYQGFQoFjx45h3LhxAIDOnTsjMjISZmZmqF27NmxsbGBj\nY4OcnByo1WpYWloWmoETjxIRERERERHRM1u1ahW6du362M+qVaue+PcJCQn4/fff0a9fP6Snp8PK\nygpAbqdIUlISkpKSCnSO2NnZITExscgMHMmhh0Zb3qZpMbwsTY7oCCWm1clVF6xjehJbS2vREUos\nUZ0mOkKJ6EQHIKP0QtA10RFK7N6GMaIjlJht3xjREUxeWlam6AhkhHjuMz6G/P9k6NCheOONNx57\n/uGOijwZGRkYN24cpk+fjipVqsDa2jp/lEZKSgoqVaqESpUqISUlJf/fpKSkwN7evsgM7OQgIiIi\nIiIiomf26GUphcnJycH48ePh6+uLV155BQDg6uqKvXv3wtPTE/v27cMnn3yCWrVq4erVq0hPT0da\nWhoUCkWRl6oA7OQgIiIiIiIiMllaM9EJHrd9+3ZERUUhLS0Nq1evRqdOnfD+++9j4sSJWLFiBdq0\naYN69eoBAEaPHo1hw4bBzMwMU6ZM0btsM51OxxFFRVCqnhMdweRZKOTra+PlKmQKKlvbiI5QYuqc\nbNERSiQ9Wy06AhkhK6VKdIQSk/NyFT/REYhIEjlZt0RHKFPf1RpisHVNvLbGYOsqjHyfLomIiIiI\niIioWMrb1528uwoRERERERERmQSO5CAiIiIiIiIyUeVtfgqO5CAiIiIiIiIik8CRHEREREREREQm\nSlvOxnJwJAcRERERERERmQR2cgji9/0M7AnfhLl+X4qOUiyy5HVyqo6DB4OQkHAeCoUCLVs2R0TE\nJoSFbcR3330mOl6RPD06IyRkA0JCNuDqlSj07tVNdCS9ZKmLPE5Ojjh6JBipyZegUChExykWWTI3\nbFQPQSHrsG3nWiz46RsAwKxvpmDbzrX4es40wekeV6NGdew7sBVxD2KgUCigUCiwYuV8bN+xFjO/\nmiQ6nl6y1MXDZDteAHJkruFUHX8d3Ib78eegUCjwmkdH7Axeh53B63Dx8hF49/IwSA7/vafwzsLA\nAs+FnLyEwT9uwpD5mxFx+upTLXdlxAm8szAQU9aEIVujwa0HyRi2KBDv/hSIyWvCDH6LdBlq4mEy\nHitatWyB/XsDsTdiM/y+nyE6TrHIVhcAM5c3WgP+GAOpOjlu3ryJkSNHFvvvf/vtN1y+fPmx5729\nvUszVom1aO6MijYV0Nm9L1QqFdxcmwnNo49MeePjk9CjxyAcPXocAHD9+i14eQ1C16794OBQDU2a\nNBCcsHAhoXvg6TkAnp4DcOPGbYSF7xcdqUgy1UWe+PhEeHYbiCNHjomOUmyyZL74zxX09ByEXt0H\nAwBecW2KijYV0Kv7YFioLND8FRfBCQtKSEhE755DEPnvsaJXb09Enz4H7x6DYW1lBWeXhoITFk2W\nusgj4/FClswJ8Ynw7jE4v5Z3h+5Dd69B6O41CDdu3EZE+IEyz5CVo8H52w8ee37N3mgsHdULS0f1\nwpq9p/Qu5+ddUbgVn5L/OD4lA5EXb2PlmD6oX7MqIk5fha21JRYM98Lyj/rguSq2+Cvmeqm+l6LI\nUhMPk+1YAQDXrt/Ea54D0KnLG3CoXhXOzsZ9PJaxLpiZTJ1UnRxPotPpoNM9+RqjESNG4KWXXjJw\nIv1at3bF7rDcD7Bh4fvRpo2r4ERFkymvWq1GYmJy/uPY2HtQq9UAgOzsbGg0xtK/WLg6dV5EXNx9\npKWli45SJJnqIk9ufSSJjlEismTOycnJ/12dlY2Ondtib8RBAMC+PQfRsmVzUdGeSK3OKnCsqF3n\nRZyJPgcAOHUqBq1bG3c9y1IXeWQ8XsiS+dFazlO79gsGO5dsPnIOvd3qP/b8C9XskJGVg3R1Nipa\nWQAAoq/FYvjirRi6cAu2HD1X5HLP3LwHt7o1AQCt6z2HU1djYVfBErbWlgAApcIc5uaGa8rKUhMP\nk+1YATzadsuBRqMRnKhoMtYFM5c/OgP+GANhnRzx8fEYOnQofH198fbbbyM+Ph49e/bE7Nmz4ePj\ng6+//hoAkJaWhpEjR2LYsGH47bff8v+9r68vvv32WwwbNgwJCQmYN28efHx84OPjg+PHc7/NmDx5\nMqKjo6HVavHpp5/C19cXc+bMEfJ+H2Zvb4eU5NxvKpKTUmBvbyc4UdFky/skzs4NUa1aVZw794/o\nKHq93qc7ArcGi46hlynUBZWubt3dse/QNjg4VIVSqURKcioAIDk5BXaVjLs+/rlwGe06tAIAdOzU\nBpVYz6VKxuOFjJkf1ruPF7Zt3VXm68nWaBB16TZa1XvusdfcnWvDZ+6fGOi3ET7tnQEAi4OjMP9d\nL6wc3Qc7j11Edk7hH2BTMtSwsVIBAGysVUjJyMp/LS4pDYcv3ETb+s+X8jsqnOw1IRsXl0ZwqFYV\nMTHG3XaTsS6YmUydsE4OW1tbLF26FP7+/ujRowc2btyIjIwM+Pj4YP369Thy5AhSU1MREBCA1q1b\nY8WKFWjRokWBZbi6umLlypW4e/cuzp8/j/Xr12PevHn45ptvCvxdWFgYKlWqBH9/f7i7uxvybT5R\nUlIybO1sAQC2djZP/AbGmMiW91GVK1fCvHkz8eGHE0VHKZYePV/D9u0homPoJXtdUOnbtTMcHdv2\nwp3bd6HRaGBrZwMAsLW1QXKScdfHzh1hsLaywtagNVCrsxAXd190JJMi4/FCxswP69GjK3YE7S7z\n9QRF/YPuLV5+4mu/hh7DpokDsHnSQPwWknu5xIU7DzBueTDe+3kb7qekIz4tE4uDIzF88VZsjTyP\nyf67MXzxVpy8ehc2ViqkZuZ2bKRlZsHWOrfDIytHg8/WReDz/p2gVBiuKSt7TcikcmV7LPjxK7w/\ncoLoKHrJWBfMTKZOWCdHUlISPvnkEwwePBjr1q1DbGwsrK2tUadOHQCAk5MTkpKScOXKFTRrlnvN\nVdOmTQsso3nz3OHPV69ezf8bJycnZGZmFvi7h5eR91+RDh/+G+5d2gMAurp3MPrrJGXL+zCFQoHl\ny+djypSvERt7T3QcvRwdHZCdlYX4+ETRUfSSuS6o9KlUFvm/p6SkQqfToUOnNgCAjp1fRVTkCVHR\nikWr1eJ/n36J3j2HQKPRICx0n+hIJkXG44WMmfNUd6yGrKxsg5xLrt5LRMDBsxj1WxAuxcZj3f7T\n+a+plApYWShhrVIi+99LDho+Vw2LhnfHslG9sf6TN+FYqSJGebXEslG90btlA8zxfQ3LRvVGs9o1\n4PxCdfx9+Q4A4PCFW3Cp5QgAmBmwDwPbNUHdGpXL/P09TOaakIlCocDqlQswcdIsKdpuMtYFM5c/\nnHjUQLZt2wZXV1esXbsWPj4+0Ol0MDMzK/A3Op0OtWvXRnR0NADk/zdP3nWYtWrVwsmTJwEAd+7c\ngZWVVYG/q127Nk6dyp3wKu+/Ih0/cRqZmZnYE74JGo0GkVHG3fiXKa9SqURQ0Fq4uDTGtm3+mDRp\nNFxdm+Lrr6dg1671aN36FdERi9Srlye2bTP+URyAXHWRR6lUYtfO9WjatDF2Bv2OVi1b6P9HgsmS\n2f21jggM8kdgkD8cqlfD/Lm/QZ2ZhW0710Kr0eD4sWj9CzEgpVKJwO3+cHZphM1bV6Fd+1YI2vk7\ntu1YgyNHjuHOnVjREYskS13kkfF4IUtmpVKJbf/WcuDWVXBr2Rze3h4ICgo1yPo/9m6Dn0f2xOIR\nPVHXsQo8mr2EJbtzP3z0b9sY7ywKxNCFgXizTSMAwAfd3DB2eTDeW7wNk/3Dilx2FVtruL7khHcW\nBuL87Qdwd66Nk1fvIjz6Ctbuj8bwxVsRHn2lzN9jHllq4mGyHSsAoF8/b7i5Ncec2dMQFhqANkY+\nR5KMdcHMZOrMdIXN2lnGzp07h//973+oWbMmHB0doVQqcfToUWzfvh0AMHLkSHz22Wewt7fH+PHj\nkZ2djZdffhk3btzAr7/+Cl9fX8yfPx9VqlQBAPj5+SEyMhI6nQ4TJ06Eq6srJk+ejMGDB6Nx48aY\nOHEi4uLi0KxZM+zZsyd/PfooVY9fY0qly0KhFB2hxLQ6Y+mnLB5D32KP5FDZ2kZ0hBJT52SLjlAi\n6dlq0RHICFkpVaIjlNi9DWNERygx275+oiMQkSRysm6JjlCmPq892GDrmnl1rcHWVRhhnRyyYCdH\n2WMnR9ljJwc9CTs5yh47OehJ2MlhGOzkIKLiYidH6TGGTg75Pl0SERERERERUbFojebmroYhbE4O\nIiIiIiIiIqLSxJEcRERERERERCaqfI3j4EgOIiIiIiIiIjIRHMlBREREREREZKLK2y0IOJKDiIiI\niIiIiEwCR3IQERERERERmSjeXYWIiIiIiIiISEIcyaGHmegAJSRjH122Jkd0BKJyKSEjVXQEonIp\nMydLdIQSs+3rJzpCiaVsmiA6QonIuI2V5grREUosR6sRHcHktahWV3QEeoSMnxGfBUdyEBERERER\nEZFJ4EgOIiIiIiIiIhPFu6sQEREREREREUmInRxEREREREREZBJ4uQoRERERERGRieItZImIiIiI\niIiIJMSRHEREREREREQmqnyN4+BIDiIiIiIiIiIyERzJQURERERERGSieAtZKnNNmjTAvr2BiAjf\nhKVL5oqOUyx+38/AnvBNmOv3pegoxeLk5IijR4KRmnwJCoVCdJxikS1zq5YtsH9vIPZGbIbf9zNE\nxyk22WpZtryy1XEe2bazbHkB+TLLWMuybWNAbGb/vafwzsLAAs+FnLyEwT9uwpD5mxFx+upTLXdl\nxAm8szAQU9aEIVujwa0HyRi2KBDv/hSIyWvCoNEa9uOGbHWhUCiwevUi7Nq1Hl9/PVV0nGKRbRvL\n0oZr27kVftk4H79snI+dxzejk1d7fPrVOPyycT4+mzsJ5ub8KEtPZjSVce/ePfj5+T3xtSNHjmDm\nzJkGTlR2zp+/hI6d+qCLe18AgJtrM8GJitaiuTMq2lRAZ/e+UKlURp8XAOLjE+HZbSCOHDkmOkqx\nyZb52vWbeM1zADp1eQMO1avC2bmh6Eh6yVbLsuUF5KtjQL7tLFteQM7MstWyjNtYZOasHA3O337w\n2PNr9kZj6aheWDqqF9bsPaV3OT/visKt+JT8x/EpGYi8eBsrx/RB/ZpVEXH6KmytLbFguBeWf9QH\nz1WxxV8x10v1vRRFxrro08cL0dEx6NbNB9bWlnBxaSQ6UpFk3MaytOEO7TmKD/qNwwf9xuHurVgk\nxSfDwsICH/Qbh8vnr6K9x6uiI0pDZ8D/GQOj6eRwcHDAhAkTRMcwiJycnPzf1eos3Lh5W2Aa/Vq3\ndsXusP0AgLDw/WjTxlVwIv3UajUSE5NExygR2TLHxt6DWq0GAGRn50Cj0QhOpJ9stSxbXkC+Ogbk\n286y5QXkzCxbLcu4jUVm3nzkHHq71X/s+Req2SEjKwfp6mxUtLIAAERfi8XwxVsxdOEWbDl6rsjl\nnrl5D251awIAWtd7DqeuxsKugiVsrS0BAEqFuUG/fZaxLurUeRHR0TEAgFOnzhp9Zhm3sWxtuOde\ndEL8/QQ41KiGizGXAAAXzvyDpm7OgpORsTKaTo6bN29i5MiR8PX1xcyZM/H2229j/Pjx+TvdtWvX\nMHbsWHh7e+Po0aMAgL///hsDBw6Ej48PFixYAADYtGkTxowZg1GjRqF37964ePEiAODQoUMYPHgw\n3nrrLSxatEjMm3yIt7cHjh8PQ3XHanjwIEF0nCLZ29shJTn3W4rkpBTY29sJTkTGxMWlERyqVUVM\nzD+io+glWy3LlldWsm1n2fICcmaWjYzbWFTmbI0GUZduo1W95x57zd25Nnzm/omBfhvh0z73A9Ti\n4CjMf9cLK0f3wc5jF5GdU/gHwpQMNWysVAAAG2sVUjKy8l+LS0rD4Qs30bb+86X8jgonY11cuHAJ\nHTq0AQB06tQW9vaVBCcqmozbOI8sbbguPTphz859uHbpOlq0yR0p49buFdja2QhOJg+tAX+MgdF0\ncjysbdu2WL16NapWrYqwsDAAQHp6OubPn49vv/0W/v7+AIDZs2djwYIFWL9+PU6fPo2YmNxeX5VK\nhcWLF2P06NHYuHEjdDodfvjhByxZsgS///47Lly4gMuXLwt7fwCwfXsoWrToils376Bnz9eEZtEn\nKSkZtna2AABbOxskJiYLTkTGonJleyz48Su8P1KOUViy1bJseWUl23aWLS8gZ2bZyLiNRWUOivoH\n3Vu8/MTXfg09hk0TB2DzpIH4LST3UqULdx5g3PJgvPfzNtxPSUd8WiYWB0di+OKt2Bp5HpP9d2P4\n4q04efUubKxUSM3M7dhIy8yCrXVuh0dWjgafrYvA5/07QakwXPNbxroICtoNa2tL7Ny5Dmp1FuLi\n7omOVCQZtzEgVxuug8er2BdyABfOXMTl81fwc8CPqGhbEfH340VHIyNllJ0cTZs2zf/v1atXAQAN\nGzaEmZkZnJyckJiYCCB3KKmjoyMAoHnz5rhy5QoAoFGj3Gv3nJyckJSUhISEhAIjRa5du4Y7d+4Y\n+F39R6VS5f+enJKKjIxMYVmK4/Dhv+HepT0AoKt7B2muT6aypVAosHrlAkycNAuxscbdAMkjWy3L\nlldWsm1n2fICcmaWjYzbWFTmq/cSEXDwLEb9FoRLsfFYt/90/msqpQJWFkpYq5TI/nc0ccPnqmHR\n8O5YNqo31n/yJhwrVcQor5ZYNqo3erdsgDm+r2HZqN5oVrsGnF+ojr8v57YxD1+4BZdaue3UmQH7\nMLBdE9StUdkg7zGPjHWh1WrxySdfoHv3QdBotAgN3Ss6UpFk3MYyteGqOlRBdnY2khJyO4+WzluF\nD/t/jKSEZPy1+5DgdPLQQmewH2NglJ0c0dHRAIDTp0+jVq1aAAAzM7PH/s7S0hKxsbEAgBMnTqBO\nnTqP/a1Op0PlypVRu3ZtLFmyBP7+/ti8eTPatGlT1m+jUN26dUbY7o0I270RjtWrGf3B+/iJ08jM\nzMSe8E3QaDSIjDohOpJeSqUSu3auR9OmjbEz6He0atlCdCS9ZMvcr5833NyaY87saQgLDUCb1sZ/\nDapstSxbXkC+Ogbk286y5QXkzCxbLcu4jUVl/ti7DX4e2ROLR/REXccq8Gj2Epbszv1g2r9tY7yz\nKBBDFwbizTa5X5p90M0NY5cH473F2zDZP6zIZVextYbrS054Z2Egzt9+AHfn2jh59S7Co69g7f5o\nDF+8FeHRV8r8PeaRsS5q1nRESMgfCA5eh8OHo3D7dqzoSEWScRvL1Ibr2K099u46ACD3M94vG+dj\n8R/zkJ2VjTPHYwSnI2NlptPpjKK75ebNm5g1axbS09PRqFEjxMTEoEqVKvDz88Pff/+NXbt24fPP\nP0d8fDzGjRsHf39/REVF4bvvvoOZmRnatGmD8ePHY9OmTUhISMDw4cMRHR2NtWvXYs6cOTh06BAW\nL14MILfh8sMPP6Bq1ap6c1moHr9e05gZxf+ZRERERIKlbDL+YfgPs+375LsMGjOluRy3V35Yjta4\nJ9k0BS2q1RUdocQib+8THaFMfVh7gMHW9fPVDQZbV2GMppMjj6+vL+bPn48qVaqIjgKAnRxERERE\nMmInR9ljJwc9CTs5jE956+RQig5ARERERERERGXDWObKMBSj6+TIu3MKEREREREREVFJGOXEo0RE\nREREREREJWV0IzmIiIiIiIiIqHRoRQcwMI7kICIiIiIiIiKTwJEcRERERERERCZKV84mHuVIDiIi\nIiIiIiIyCRzJQURERERERGSiytucHOzk0MPcXK7BLhpteSthMcxEByghawtL0RFKLCNbLTpCiSkV\nch1SNVqN6AglptPJNdzSzaG+6Agldj09TnSEErufkSw6QonwXG0Ydn39REcokfv9G4iOUGLVAs6L\njlBisrXh5Drr5Tp+/5LoCFTOydUiJyIiIiIiIqJi45wcREREREREREQS4kgOIiIiIiIiIhNV3i6S\n5EgOIiIiIiIiIjIJHMlBREREREREZKK0kk3c/qw4koOIiIiIiIiITAJHchARERERERGZqPI1joMj\nOYiIiIiIiIjIRHAkBxEREREREZGJ0pazsRwcySGAtbUVtmxeiZCQDdgYsAwqlUp0pCK1atkC+/cG\nYm/EZvh9P0N0nGLz+34G9oRvwly/L0VHKbZxY9/HnojNomMUqUaN6th3YCviHsRAoVBAoVBgxcr5\n2L5jLWZ+NUl0vGIx9u3s5FQdBw8GISHhPBQKBVq2bI6IiE0IC9uI7777THS8ItWq9TxuXD+O0JAA\nBAWtFR2nRIy9LiytLPHD6tn4KWAevl3+FSxUFujezxML//DDTwHz4FCjmuiIBTRo9DICd63Bph2r\nMXfRV1AqlVi87HsEbF2BaV9OEB1PL9nO1YB85z1Z2xcijhXmz9eGzRcLYfPZj7AeMbHAaxVGT4fN\ntLmwmbEQtt/89lTLt3i1K2y+WIiKn34NWFcArKxRccoPsPnsx9znrKxL420UC+ui7Dk5OeLokWCk\nJl+CQqEQHadYZK0LEqPcdXJ4e3uLjgBPz844Gnkcnp4DEBl1At08O4uOVKRr12/iNc8B6NTlDThU\nrwpn54aiI+nVorkzKtpUQGf3vlCpVHBzbSY6kl4qlQrNmjURHUOvhIRE9O45BJFHjwMAevX2RPTp\nc/DuMRjWVlZwdjHu+pBhO8fHJ6FHj0E4+u82vn79Fry8BqFr135wcKiGJk0aCE5YtLCw/fDw7I+e\nPQeLjlJsMtRFmy6tcPZYDD7qPx5nT8TAo487WrRphjEDJ+Cj/uNx7+590RELuPTPVfTpNgR9e7wN\nAHjvQ1+cPX0e/XsPg5WVJRo7G3cdy3aulvG8J2P7QtSxQnvnBlK/HIPUWR8DABQv/bf/pC/6Cqlf\nfwL19j+Qffyw3mWpOnaDstFD9aFQwLJrL6TOGoesv0Jh6d4L0OQg/edvkDrrY2T/fRCqjl6l/p4K\nw7ooe/HxifDsNhBHjhwTHaXYZKwLEqfcdXIYg8uXr6FihQoAAPtKdngQnyA4UdFiY+9BrVYDALKz\nc6DRaAQn0q91a1fsDtsPAAgL3482bVwFJ9Lv3WGDsNo/QHQMvdTqLCQmJuc/rl3nRZyJPgcAOHUq\nBq1bG/e2lmE7q9XqAtu44D6YDY1GKypasXTq9CrCw/7E2LHviY5SbDLUxa1rt2FVwQoAYGtngxrP\nOcJcYY6Ff/jhk1ljYG5uXKf0nJyc/N+zsrJgbW2FmDMXAABnos/BrVVzUdGKRbZztYznPRnbF8KO\nFQ9vm5wsaB/EPfYnFm7tkR2ZWwPmjjVRcfJ3sJk+D5avDyly0eY1nofmxhVAq0XO6WNQ1GsMZGdD\nlxj/77pzAK3h/r9hXZS93HZGkugYJSJjXRgTnQH/ZwyMq0X0DG7cuIGBAwfC19cXH3zwAS5evIj+\n/fvj/fffx9ixY7Fs2TLREfNdvHgFrdu44vix3XjFtSkOHYoSHalYXFwawaFaVcTE/CM6il72fdeW\ncwAAIABJREFU9nZISU4BACQnpcDe3k5woqIplUp07NQWe/YcEB2lxP65cBntOrQCAHTs1AaVjHhb\ny7ydAcDZuSGqVauKc+eMdx+8cycOTZw7wMNzANzdO8DFuZHoSHrJUhc3Lt+Es2tjrA1fgYbNGkCj\n1cDCwgJjBk5AZoYaHbq1Ex3xMR7duyDs4BZUc6iKf85fQpt2LQEAr3ZoBbtKtoLTFU22c7Vs572H\nydK+EH2sUL7yKmznLIOZXRXoUpMLvqhQwPyFOtBczd2GVgOGI/2375H61XgonqsNsyqFX85mVsEG\nuox0AIAuPRVmFWz+e9HSCip3b2QfDCv196MP64KeRJa6ILFMppPjyJEj8PLygr+/PxYvXgw/Pz98\n8cUXWLJkCSpWrCg6XgG+Q/pjR1AoWrzyGoJ3huOtt/qKjqRX5cr2WPDjV3h/pPFfRw0ASUnJsLXL\nbUDb2tkU+FbcGA0Z/CbWr5fjOs5H7dwRBmsrK2wNWgO1OgtxccY1ZP5hMm/nypUrYd68mfjww4n6\n/1igrKwspKdnQKPRYMeO3UZ/aQ0gT130GNANB0IPYbD7MBzcfRgKcwWOHz4JAPj7wHHUrvei4ISP\nC90Zga6vvo47t2Oh1epgZWWJP7YsQ5Y6C/fiHoiOVyTZztWynffyyNS+EH2syDl2ECmTh0MXfw8W\nLdoWeE3ZqDlyYk7mP1Y4vYCKH06BzbS5UDz3IswrV4Oqa2/YTJsLy16DYO37EWymzYWFW3vo0tNg\nZp07asnMuiJ06an5y6kwYiIyNyyHLj3NMG/yX6wLehKZ6sLYaA34YwxMppOje/fuePDgASZMmIDl\ny5fj5s2bcHZ2BgA0bdpUcLqCzMzMEJ+QCAC4/yAeleyM+9sshUKB1SsXYOKkWYiNvSc6TrEcPvw3\n3Lu0BwB0de9g9Ncc1m9QFyNHvI3t29agceP6+GjUMNGRik2r1eJ/n36J3j2HQKPRICx0n+hIhZJ1\nOysUCixfPh9Tpnxt9Pugjc1/ncqvtm2JS5evCUxTPLLUhZmZGZITc7+pT0xIgg46vNzoJQBAvSZ1\ncef6XZHxHqNSWeT/npqSivT0DHw26RsMfH04NBot9oYb97eesp2rZTvvAfK1L4QeK5T/7U+6jDTo\nstQFXrZwa4/sqL/yH2vu3EDaT7lzdaRM+wCay+eRFbY1d+6ObeuQ4f8TUr/+BNlRf0F79wYUL9QB\nzMyhdH4FmotnAQBW/YYh58Jp5Jw9bpj3+C/WBT2JbHVBYpnpdDrjuHDmGWVkZMDaOnfm53feeQcW\nFhYYP348GjdujClTpuDll1/G8OHD4e3tje3btxd7uZZWL5R61kqV7LB2zWKoLFXIyc7G4CEfIeHf\nhtSz0mhLv/9s4MA++HHuLJw9ex4AMG36HBw+8nepr6e0zfX7Eq+0cMGJk2fw8fjSvSOFWakuraA9\nEZvRucsbpbpMawvLUluWUqnEn1tWoHlzZ5w8eQbfzl6AqdM+hlanxbrfN+P3NX+WynoystX6/+gZ\nlMV2VipK567cSqUSgYGr0KKFC06cOI2//jqCDz4YipiY3PkMPv/8u1L5AKMpg2usvbzcMeOLT6FW\nZ+HAgaOYOu2bUl1+WZ+ySrsu3Bzql9qybOwqYtbPX0ClskBOTg4++3Amho4ZjIZNGyAxIQlffPQV\ncrJz9C9Ij+vpj1/r/zQ8u3fBiI+GAgCuXLoGvzk/YeFv30Kn1WHj+q3YsG5LqawHAO5nlP6oBdnO\n1UDZnvfKQlm3L2Q7V9/rX/jIN6Xrq7Dq3h8AoLl7E5kbV0LVyQvqwNy7WNl8/StSp38A/HuMNHes\nCeuhYwClCtDkIO3HLwB1JoDciUe19+4WGPlh0d4Dll17Q5eWgrSfvoaZpRXs5v8OzYUzAICsw3uQ\nFbb1sVzVAs6Xzpt/COuioLI46ymVSgRtW4NXXnHB8eOnMf2zOTgaadjOrJIq67rIybpVassyRv1r\n9THYugKuBRpsXYUxmU6OHTt2wN/fHwqFAg4ODvjwww8xdepU2Nvbw97eHo0aNTKaTo6yVFYNJyqo\nLE+QZaE0OzkMpaw7OcpCaXVyGEpZdHKUNdlOWaXZyWEopdXJYUhl0clRlniuNgzZztVFdXIYq7Lo\n5ChrstWFXGc9ebGTo/QYQyeHXC3yIvTo0QM9evQo8NzGjRsBAJs2bUJCQu6s6CXp4CAiIiIiIiKS\nmbHc9cRQTGZODiIiIiIiIiIq30xmJEdR+vY17hnRiYiIiIiIiMpCebtIkiM5iIiIiIiIiMgklIuR\nHERERERERETlkWwTtz8rjuQgIiIiIiIiIpPAkRxEREREREREJkrLu6sQEREREREREcmHIzmIiIiI\niIiITFR5u7sKOzlIOHMzM9ERSky2yXsyc7JERygxMwnrQqPViI5QIjJuY2sLS9ERSiTy3gXREcoF\n2SrZUmkhOkK5oDRXiI5QItUCzouOUGIpS3xFRyixyiN/Fx2hRLQ6+T6eytZOJtPDy1WIiIiIiIiI\nyCRwJAcRERERERGRidJx4lEiIiIiIiIiIvlwJAcRERERERGRieItZImIiIiIiIiIJMSRHERERERE\nREQmqrzd8YYjOYiIiIiIiIjIJHAkBxEREREREZGJ0ooOYGAcyUFEREREREREJoGdHAJ4enRGSMgG\nhIRswNUrUejdq5voSHr5fT8De8I3Ya7fl6KjFNuQwW8iOHg9QkMCULNmDdFx9GrSpAH27Q1ERPgm\nLF0yV3QcvWrVeh43rh9HaEgAgoLWio5TLLJlli0vIM/xzdWtGUJ2ByA45A98M2caAGDsuPcRHPIH\nliybC6XSuAc6Ojk54uiRYKQmX4JCoRAdp1hkPI+MG/s+9kRsFh2jSDWcquPAwe14EH++QC2MHj0c\nobsDBCYr3KOZX3zxeVy5Eomdweuxdetq0fEe8+jxolat57EzZD127FqHpcvnwdzceJvTrVq2wP69\ngdgbsRl+388w+Pr9j17EO6v3FnguKSML/9t0FO+v3Y8lB84/1XJXHr6Ad1bvxZTASGRrtLiVmIZh\nq/fhXf99mLwlEhqt4eYfUCgUWL16EXbtWo+vv55qsPU+CxnbF3lkOC4bI50B/1dc2dnZ8PHxgZub\nG4KDgwEA8fHxeO+99zBo0CAsXLgw/28jIiIwcOBA+Pj44NSpU3qXXepHZW9v78eei4mJwapVq0q0\nnN27dyM2NhYAcO/ePfj5+ZVKPmMQEroHnp4D4Ok5ADdu3EZY+H7RkYrUorkzKtpUQGf3vlCpVHBz\nbSY6kl41a9ZAhw5t4eXlAw/P/rh9+67oSHqdP38JHTv1QRf3vgAgxXYOC9sPD8/+6NlzsOgoxSZb\nZtnyynJ8u3H9Fnr1HAwvz4FwcKiKdu1boUPHNvDyHIgzp8/Bu5eH6IhFio9PhGe3gThy5JjoKMUi\n43lEpVKhWbMmomPolRCfhJ493sLRo8fzn1OpVGjatLHAVEV7Uubw8L/Q3csHvXu/LTDZkz16vKj5\nXA0M7PceenQbhGvXbsKzW2fREQt17fpNvOY5AJ26vAGH6lXh7NzQYOvOytHgfGziY8//sv8cRnVs\nhCWDO+D9dg30LufnfTG4lZiW/zg+TY3Ia/ex8u1OqF+9EiIu3IGtpQUWDGiL5b4d8Zx9Bfx1yXDt\nvj59vBAdHYNu3XxgbW0JF5dGBlv3s5CtfQHIc1ym4lEqlViwYAGGDh2a/9ySJUvw5ptvYt26dYiO\njsbFixeh0Wgwf/58LFu2DPPnz8fs2bP1LtsgXc+NGjUqEL44du/ejbi4OACAg4MDJkyYUBbRhKpT\n50XE/b+9O4+P6ez7OP6ZzMhCRKxBtahaIgua2qX2vYpSUgxqp7hpi9BWa2u1VV1vLbUvN7VEFa0t\n9pagltBGiT1oqMhCkolkzvNHnkyzSkJmzpz4vfvyaiYzOfM9Z67lzDXXuebWP9y/H692lIdq2NCP\nXcGpb1SCdx+gUSM/lRPlrm3b5uj1DmzbtobPP59h15+ypElOTrb8bDIlcS3ihopp8qZ58ybsDt7A\n2LFD1I6SZ1rLrLW8aey9fbt16x9MpiQAHjxIxtOzOgcPhACwd89v1G9QT814uTKZTERHx6gdI8+0\n2I8Mev01lq+wz5kQ6aWWhdgMvxswsBerVq1XKVHussv8YvPG7Ni5ltGjB6uUKmeZ24uoqGhiY+/9\n/+0HpKTY79XukZG3MZlMQGr2lJQUmz33xlNXeNmncpbfX7gdy6Lf/mLIygOcirgDwOnrUQxeeYAB\ny/fx46krD93uHzfv8sIzZQBoWKUsodfv4ObiSHHnIgAYHBxw0OkKeG9yVrXqM5w+HQZAaOifmmjf\nQJvnF1ppl+2RGcVm/2JjY4mIiMjyLzY2Y7uv0+koV65cht8dP36cli1bAtCiRQuOHj3K5cuXqVKl\nCq6urnh4eJCcnGxp13LyWO/8zGYzU6ZMoW/fvhiNRi5duoSiKEyfPp3XXnuNDz/8EICQkBCmT58O\nwKFDh+jbty99+vThm2++ASA6OppRo0ZhNBoZMGAAFy9e5MCBA7z//vtMnjyZiIgIhg8fzt27dzEa\njZbnnzp1KkePHuX69esMHTqU/v37M3bs2Gx3evHixfTq1Quj0ci+ffuy3K+Gbl07sumnbWrHyJW7\nuxtxsXEAxMbE4e7upnKi3HmUK4OjoyMdOgSQEJ9gt1PmM3vppbacOBFMOY8y3LlzV+04D3Xz5i28\nvP1p264XrVr54+Nt/59caC2z1vKmp5X2zcurJmXKlCI6Opa4uP9v52LjKFHC/ts5LdFaP2IwGHix\neWP27v1V7Sj5ZjAY8PdvxL59h9SOkmd//32LOr4t6djhNVq2amrT2Qb5kdZe/HU2HIDy5cvRsmUz\ndgfb54y19Hx8PClbpjRhYedt8nwPUswcu/IPDaqUzXLfqet3GNSkBh93q8/nu88AMG9/GF++2oil\nxhf55Y9rPHjIwFGc6QGuTqkDGq5ORYhLfGC571ZcAocv36Lxs+Vy+vMCd+7cBfz9GwHQvHlj3N1L\n2Oy5H5UWzy+03C4/aZYtW0br1q2z/MvLlR3x8fE4OzsD4ObmRkxMDDExMbi5/Xve4ObmRnR01lli\n6T3WRcfBwcG4uLiwatUqQkNDmTNnDgkJCfTs2ZPatWszatQo/vjjD8vjFUVhzpw5rFixgqJFizJ2\n7FguXrzIunXraNeuHd26dcNsNuPg4IC/vz99+/bFx8eHiIgIAEqWLImrqyvXrl2jfPnynD59mmnT\npjF+/HjeeustatWqxYoVK9i4cSMBAQGW5z137hwHDx5k9erV6PV6m45iP0ynzm3o3Xuo2jFyFRMT\nS3G34gAUd3PN8umLPYqJjWP/gdQTvD17f8XveV/YpHKoPNiyZSdbtuzki89n0LlzGzZtst83iUlJ\nSSSlfrDFzz/vwsurJqfPhKkbKhday6y1vOlpoX0rWbIEn879gIHGMdSt581TT1UAoHhxV2Ji7L+d\n0xKt9SP9+vZgzRptXvPdp0931q79Se0Y+ZK+rfvll93Url2DM2fOqhsqk/TtBaROm/9uwaeMHTPF\nbs4rc1KypDtffTGTgD4jbPacW89cpaNXpWzvq1zKlWfLpL5hSZtxce5WDP9ZdxiA6HgTUfEmNpy4\nzO9X/+FGTDy/XYzE0aBnbIvauDoVITI2AYD7ScmWGRxJySm8t/l3pnash8GGM3i3bt1Fy5ZN+eWX\n1Vy5co1bt27b7LkflRbPL7TcLtsDRbHdOjUDBgyge/fuWX6ffqAiJy4uLphMJpycnIiLi6NEiRKU\nKFHC8kEUQFxcHO7u7g/dzmO1AJcuXaJOndTran19fbl69SoGg4HatVOvA/Xx8eHKlX+nnN29e9cy\nK8NoNHLlyhVu3rxJeHg4DRs2TA2US6PUpUsXNm/ezP79+/H390en03HhwgVmzZqF0Whk8+bN3Llz\nh2XLlmE0Gpk9ezbh4eH4+flZFuSyh0XaPDzK8iApiaioh49C2YPDh3+nVctmALRu5a+Ja8APHzpm\nuSayjq8Xly9fUzlR7hwdHS0/x8bdIyEhUcU0uXN1LWb5uUnj+ly4+PDppfZAa5m1ljeNFto3vV7P\ngoVzeXfKR9y69Q/Hj5+mabMGALRo2ZRjR0+qnLBw0Vo/UqNmNYYP68+WzSupXbsGb4x6Xe1IeVa9\nejWGDunHj5uW4elZgxEj8ne5sBrSt3WNG/lx8dJVFdNklbm9APjy61l8v2ClZVaHvdLr9Sxf+hUT\nJ80gMtJ2b74v37nHuuOXGLXmVy78E8fqoxcs9z1TypXb9xJJSEom+f8XCK3l4c43vRqzqJ8/awa3\nwqO4C6Ne9GRRP39e9nmG2d3qs6ifP3Uqlca7Qkl+v5r6Ohy+dAufiqUAmP7LCXr7PUu1sradKWY2\nm3nzzffp2PE1UlLM7NxpHzPGH0aL5xdabpefNG5ublSqVCnLv7wMcvj5+Vmuuti/fz8vvPAClStX\n5vLly8THx3P79m30ej1OTk4P3c5jzeSoUqUKISEhvPzyy4SGhvL0009z9uxZzp49S61atThz5gz+\n/v7cv5+6WFDJkiWpUqUK33//Pc7OzpjNZhRF4eDBgxw5coSuXbtaZnIUKVIk25Hx1q1bYzQaOXfu\nHKNHjwagatWqjBs3jmeffRZIHZ10dHS0rANy7tw5NmzYYNl22v/V1KVLOzZv3qFqhrw6cfIMiYmJ\n7N0dxMlTf3D0mP2f/J8K/ZOEhER27ljHnTtRfPnV92pHylX79i0Y959hAISHX7L7TrJZs4Z88P7b\nmExJ/PrrEY4ePZH7H6lMa5m1ljeNFtq3bq904nk/H6bPnATAtPfn8NuvR9i24wciIm4w779LVE74\ncAaDga2bV+LrW5tftv6Pd9+bzRE7Lh9a60emTPnQ8vPePRv57zz7LQ8Gg4Eff1yKj48nP/20nPc/\n+JT33psNwM5d6/juu/wt/G4LmTMf/PUInTu3wWRK4rdfj9rdIGN27UWXl9vx9DMVGfnGQL6bt4wt\ndtrm9ez5Ei+8UJfZH6V+i9Q7787mcMjvVn/eca28LT8PXL6Ptp5P8f2vfzG0aU1G+nsS+ONRTMkp\nDG+WemnSiBdrMXbdIRQFSrg48lmPhjluu1QxJ/yeKcPA5fso71aUfg2e41TEHXb/dZObMQmsOnqB\nvvWr0apmRavvJ0DFih4sXfoVZrOZVas2cONGpE2e93Fo8fxCS+2yPTLn41tPbOk///kPZ86coWjR\nooSGhjJ06FAmTpzIkiVLaNSoEdWrVwdg9OjRvP766+h0OiZPnpzrdnXKY8xdSVuT4+rVq+h0OqZP\nn87YsWNp2rQpoaGheHt78+677xISEsL27duZOnUqhw4dYt68eUBqJzdnzhz0ej2TJ08mLi4OvV7P\nwoUL2bdvH0uXLsXLywuj0ciMGTOYP38+AJMnT+b8+fOsX5+6qNb169eZMWMG8fGpC9yNHDmSxo0b\nZ8i6aNEitm/fjrOzM4MGDaJFixZ52kcn56cf9fCoIsVsv4tf5cSWi0MVFFtO+SoIOg0eY2F9WiwX\nzgbH3B9kR+4n2feMrMJCayXZ0VBE7QhPBIOD+jN380OL7UXc98bcH2RnSg7/n9oR8sWsaO/cXmvn\nyQAPkq6rHcGqWlay3bfG7YnYabPnysljDXLk1f79+zl8+DATJ0609lMVOBnksD4Z5LA+Lb6ZFdan\nxXIhgxwiO1oryTLIYRsyyGF9MshhfTLIYRuFfZCjRaU2NnuuvRG7bPZcObH6NRsXLlxg3rx5tG+v\njW+3EEIIIYQQQgghhDY91poceVGtWjXWrFlj7acRQgghhBBCCCHEE87qgxxCCCGEEEIIIYRQh1mD\nlxA9DnW/YkQIIYQQQgghhBCigMhMDiGEEEIIIYQQopB6suZxyEwOIYQQQgghhBBCFBIyk0MIIYQQ\nQgghhCikzE/YXA6ZySGEEEIIIYQQQohCQWZy5EJ5wlaiVYMWj7FOp1M7Qr4U0WuvqpuSH6gdId8c\nNFYuzGaz2hHyLTE5Se0Iwg5prU1O0mD7pr2eGsx6baXWVilOVXL4/9SOkG/RO2epHSFfXFsHqh0h\n3wwOerUjiExkJocQQgghhBBCCCGEBmnv410hhBBCCCGEEELkiRZnzj8OmckhhBBCCCGEEEKIQkFm\ncgghhBBCCCGEEIWUrMkhhBBCCCGEEEIIoUEyk0MIIYQQQgghhCikFJnJIYQQQgghhBBCCKE9MpND\nCCGEEEIIIYQopOTbVYQQQgghhBBCCCE0SAY5VFC5ciWuXT3Bzh3r2Lp1ldpx8qRCBQ+OhGzjXuwF\n9Hq92nHy7D9jh7J3z0a1Y+RJv7492LZtDTt3rKNixfJqx8lR+Qrl+PW3LdyJ+itDWRg9ejA7d61T\nMVnutFiOtVIuMtNS3WvXtgU7dqxlx461XL50jJe7tFc70kM1qF+PA/s2sW/PRj779AO14+SJFuue\nFvtq0Fbd00pZrlChHL/9tpW7d1P7vdq1a7BnTxC7dq1j/vxP1Y6XJ1ooFxUqeHDo0Faio89Z2olP\nPplKcPB65sz5wOrPf/2faFqO/5zBnyxn+NyMdX7jwZN0DPyayd//+Mjb33r4NP0/Wsror9ZwL8HE\n/UQTQ+es5PWPlzH6qzXcTzQ97i7kmVbqHmQtF9mVEyEyk0EOlQQHH6Btu1fp3Lmv2lHyJCoqmnbt\nexMSclztKHnm6OhInTpeasfIk4oVy+Pv35gOHQJo2+5Vbtz4W+1IObobFUPnTn04cuSE5XeOjo74\n+tZWMVXeaK0ca6lcpKelugewY+de2rXrRbt2vbh27QbBuw+oHemhrlyNoE27XjRv2Z2y5Urj7V1L\n7Ui50lrdS6O1vlprdU8rZTkqKoZOnV6z9Hvnzl2kZctXaNPmVQD8/HzVjJcrrZSLqKhoOnb89/yi\nbl1vXF2L0bp1Txwdi9jkODeqXZVFE/sz/82Mdb5FnRrMH5/3dmDTr6c4evay5faD5BTW7TvO4on9\neamRD+v3Hceg1/PhkK4smTSAlnVrsOnX0ILajVxppe5B1nKR+bbIGzOKzf7Zg0I1yGE0GnO8LzAw\nkIiICBumebjmzZuwO3gDY8cOUTtKnphMJqKjY9SOkS+DXn+N5Svse2ZBmrZtm6PXO7Bt2xo+/3wG\nDg72WzVTy0Jsht8NGNiLVavWq5Qo77RWjrVULtLTUt1Lr2rVZ7h16x/u349XO8pDRUbexmRK/cTv\nwYNkUlJSVE6UO63VvTRa66u1Vve0UpYz93vJycnp7ksiIuKmGrHyTCvlInM70aBBPYKDUwedd+8+\nSMOGflbPcPSvKwz8eBkrdoRk+H3J4kXR6zP2wVcjoxg+dxWDPlnOgi0PHxy/eiuK6k+Vw6B3oFHt\nqpy6EIFTEQNl3YsDYNDr0TvoCnZnHkIrdQ+ylgut9ifCtrRxxpzJ7NmzCQgIwGg08scff6gdJ99u\n3ryFl7c/bdv1olUrf3y8PdWOVOgYDAZebN6YvXt/VTtKnniUK4OjoyMdOgSQEJ9g99Pl0zMYDPj7\nN2LfvkNqRyl0tFgutFb30uvWtSObftqmdow88/HxpGyZ0oSFnVc7SqGktb5ay3VPi2W5c+c2HDu2\nAw+PMty5c1ftODnScrlwd3cjNjYOgNjYONzd3az6fGVLuPLTrJEsfNtISNglzl2LfOjjv964l2kD\nX2LxxP5cuHGbyKjYHB8bF59IMWcnAFxdnIlLSLTcF5+YxPp9x+nY0LtgdiQftFj3xKNRFMVm/+yB\n5r5dZc+ePcTExLBmzRoAux55zElSUhJJSak///zzLry8anL6TJi6oQqZfn17sGaNfV97ml5MbBz7\nD6QOEuzZ+yt+z/vCJpVD5VGfPt1Zu/YntWMUSlosF1qre+l16tyG3r2Hqh0jT0qWdOerL2YS0GeE\n2lEKLa311Vqte1oty1u37mLr1l3MnTuNTp1a89NP29WOlC2tlguAmJg43NxSZzoUL+6aZRZpQXMs\nYsDx/39+0bc64TduU+NpjxwffyXyDu8sTO2U4xJMREbHse/UebYf/YN/Yu/jVMRAcRcn+rRpQGWP\n0pY1N+4nmCju4gykvvF8f+lmRndvgVtRZ6vuX2ZarXtC5IXmZnKEh4fTsGFDy+1z585hNBoxGo2E\nhYVl+Bmw3D5w4ABvvvkmRqORoKAgteID4OpazPJzk8b1uXDxioppCqcaNasxfFh/tmxeSe3aNXhj\n1OtqR3qow4eO4eOT+ilhHV8vLl++pnKivKtevRpDh/Tjx03L8PSswYgRA9SOVGhosVxore6l8fAo\ny4OkJKKiotWOkiu9Xs/ypV8xcdIMIiNvqx2n0NJaX63FuqfVsuzo6Gj5OTb2HgnpPpW3N1osF2lC\nQo7TsmVTAFq1asaRI9Zd0yf9wp8nwq9RqWzJhz6+skdpZg/rzqKJ/Vn93mC8q1SkV0s/Fk3sz6CO\nTZjQuy2LJvan9fO1qOxRivDrt0gxmzkcdgnfZ58C4L+b9lH3uadp6FnVqvuWmVbrnnh0T9qaHDrF\nXuaU5NHevXvZuXMns2bNAsBsNluuUzcajaxYsSLbvwsMDGT06NFUqlQpX8/n6JS/x+dFhw6t+OD9\ntzGZkvj11yNMeefDAtu22Uovp8FgYOvmlTz/vA8nTpzh3fdmc+RowSz4Y+0rEPfu2UiLlt0LdJs6\nXcGnnj37Xfyer8OdO1EY+4/mwYMHBbbtIvqCm7RlMBj48cel1K3nw6mTZ3j/g085dvQkADt3raPt\n/y/E9rhMyQW3/2msWY4BHDRWLqzd/Fuj7llrXZIhQ/pSxGDg2++WFeh2U8zmAt0eQO/eXfli7gz+\n/PMvAN55dzaHQ34v8OcpSFqse9bsq7VY96yR2NpluaD6PoPBwKZNy6hXz4eTJ89w8GAILVo0ASA8\n/DJvvBFYIK9pckpy7g96DNYoF3qHgvt2C4PBwE8/Lbcc56lTP6Z3727Uq+fNqVN/8OYMtmRHAAAg\nAElEQVSb7xfI80TvnJXt7w+EhvPfH/fiWMRAvepPM75naz763zYm9+nAvlPnWfzLr0TcjqZOtUrM\nHdWTq5FRzF69naTkZAx6PXNH9qSoc+oA2KZfT1GxdAnq16pi2f7mQ6Gs23sct6LOfDS0GwlJD+g4\n6WvqVkt9r9G+vhe9WmZdd8S1dWCB7Hd61q57BiuXi2nTJma4ffT/z0MfR2Li1QJIa7/qlG9is+c6\n9fdvNnuunGhukAPgo48+4tSpUzg6OjJx4kS8vVOvYdPKIIc1WWuQw5pst8xSwbHGIIc1FeQgh61Y\nY5DD2qzxRsuaNNj8a2bx1TTWGOQQWUndsz7tJdZe32ftQQ5rKMhBDlvJaZDDXlljkMPaCnKQw1YK\n+yCHb/nGNnuu0L/VX6dPk4MctiSDHNanrVPTVDLIYX0yyGF9Wmz+ZZBDZEfqnvVpL7H2+j4Z5LAN\nGeSwPhnksD9P2iCHtlp/IYQQQgghhBBC5JkWPwh/HNr6SEwIIYQQQgghhBAiBzKTQwghhBBCCCGE\nKKQUTV50+OhkJocQQgghhBBCCCEKBZnJIYQQQgghhBBCFFKyJocQQgghhBBCCCGEBslMDiGEEEII\nIYQQopCSNTmEEEIIIYQQQgghNEhmcuTiSbt+SQ16B73aEfLNrJjVjpAvpuQHakd4ImitvdCpHeAR\n6DSW2uCgJ9mconaMfNHWEU6ltbqnRQYN9tWKxsqFttKmStFY+wbg2jpQ7Qj5knDjgNoR8q3YUy+q\nHUE84WSQQwghhLASrQ1wCCGEEKLwedI+DJDLVYQQQgghhBBCCFEoyEwOIYQQQgghhBCikJKFR4UQ\nQgghhBBCCCE0SGZyCCGEEEIIIYQQhZSsySGEEEIIIYQQQgihQTKTQwghhBBCCCGEKKRkTQ4hhBBC\nCCGEEEIIDZKZHEIIIYQQQgghRCGlKGa1I9iUzOQQQgghhBBCCCFEoSCDHCpoUL8eB/ZtYt+ejXz2\n6Qdqx8mTChU8OBKyjXuxF9Dr9WrHyZVer2f58m/Yvn0Ns2ZNUTtOnlSuXIlrV0+wc8c6tm5dpXac\nXGmtTIBktgUvr5rs37eJPbuDWPj9XLXj5KhCBQ8OHdpKdPQ59Hp9ltv2TsqFbXz26Qfs3R3E3M+m\nqR0lT7RSLrRW/7LL98knUwkOXs+cOR+oGy4XWjzn1GJ7oUbdu34zkhdfeo2BoycydFzGc93ZX3zH\nwNETGTh6Ik06vPpI2w/5/SR9h43n9dGT+PvWbQDemPg+/Ue+zeCxgZbf2YrWzpPtjRnFZv/sgeYG\nOSIiIhg+fHieH79gwQIuXrxoxUT5d+VqBG3a9aJ5y+6ULVcab+9aakfKVVRUNO3a9yYk5LjaUfKk\na9cOnD4dRvv2Abi4OOHj46l2pDwJDj5A23av0rlzX7Wj5EprZQIksy389dcFXmzelZatXgHgBb86\nKifKXlRUNB079uHIkRPZ3rZ3Ui6sr15db4q5FqVFq1dwdHTURGatlAut1b/M+erW9cbVtRitW/fE\n0bEIfn6+KifMmRbPObXYXqhV9xrXr8fSbz7h+y8+zPD7wHEjWPrNJ0waOwz/xvVz3c6R46H8uHVn\nht99t2Q1Cz6fxfiRr7NwxVoAJo8byfJv5zC4Xy9W/PBjwe1IHmnpPFmoS3ODHPmRkpLCsGHDePbZ\nZ9WOkkFk5G1MJhMADx4kk5KSonKi3JlMJqKjY9SOkWdVqz7D6dNhAISG/kmjRn4qJ8qb5s2bsDt4\nA2PHDlE7Sq60ViZAMttCcnKy5WeTKYlrETdUTJOzzMdVa8dZa3m1Ui7Sa9jQj13BBwAI3n1AE/2I\nVsqF1upf5nwNGtQj+P/Lxu7dB2nY0H7LhhbPObXYXqhVho8eD6X/yLdZvmZjtvcH7/uNNs2bAhB1\nN5rREz/g9dGTmDHnm4duNyExEWcnR4oVK4qvVy3CL10BoFLF8gAYDAYcHGz/NlJL58n2RlEUm/2z\nB1YtnVFRUQwYMACj0Uj//v2Jioqic+fOfPTRRwQEBDBr1iwA7t27x5AhQ3j99deZNWuWZaaG0Wgk\nKioKgOnTpxMSEpJh+0uWLKF///50796dH374AYCgoCDGjRvHyJEjCQoKIjAwkNOnT3Pt2jV69+6N\n0WhkxIgR1tztPPPx8aRsmdKEhZ1XO0qhc+7cBfz9GwHQvHlj3N1LqJwodzdv3sLL25+27XrRqpU/\nPt7amH0iRGYvvdSWEyeCKedRhjt37qodR9gJrZULd3c34mLjAIiNicPd3U3lRMJeuLu7EZtWNmK1\nUTa0ds6ptfZCDWVLl2TLmoUs/vpjDh07wV/hl7I85mDI7zT7/wHaRSvXMaR/b5Z88zHFirpw8kxY\njtuOi7tPsWJFLbfNKf8uWpmSksKCZat5tWvHAtyb3Ml5ssgPqw5yFC9enIULF7JixQo6derE+vXr\nSUhIICAggDVr1hASEsK9e/dYu3YtzZo1Y8mSJdSuXTvP2+/duzfLly/nhx9+YNmyZZjNqRUwKSmJ\nb7/9lldf/fcatJCQEDp06MCKFSuYN29ege9rfpUs6c5XX8xk6PC31I5SKG3dugsXFyd++WU1JlMS\nt2x83eCjSEpKIj4+gZSUFH7+eRdeXjXVjiTEI9myZSf16rXmesRNOnduo3YcYSe0Vi5iYmIp7lYc\ngOJurkRHx6qcSNiLmJg43NLKRnH7LxtaPOfUWnuhBkdHR4q6OGMw6GnetAHhFy9nuP/KteuUK1sa\nF2dnAC5evsoX3y5m4OiJHD52itu377Br368MHD2Rj7+cz6KVaxk4eiJrNm7B1bUY9+/HW7bloP/3\nLeOnX39Plw6teaZSRZvsZxo5T348T9qaHFb9CtmYmBimTZtGVFQU9+7d44UXXsDFxYWqVasCUKFC\nBWJiYrh8+TJdu3YFwNfXl23btmXZVnZTX37++Wc2btyITqfj1q1bxMSkThOrW7dulsd27NiRb7/9\nlrfeegtPT0+GDFFvmpNer2f50q+YOGkGkZH2/+Zbi8xmM2+++T4A//3vbHbu3Kdyoty5uhbj3r37\nADRpXJ//zluiciIh8s/R0ZGkpCQAYuPukZCQqHIiYQ+0WC4OH/6doUONrF+/mdat/Fm+fK3akYSd\nCAk5zpAhfdmwYQutWjVjxYp1akfKkRbPObXYXqjh/v14y2yLE6F/0rfnyxnuD97/G61fbGK5XeWZ\nSrzUvhVetaoDkJycgsGgp03zphw5HsqNm5F069zW8vhEU+qgwoXLV6lW5RkANmzejk6no2tH2w88\nyXmyyA+rzuTYvHkzfn5+rFq1ioCAABRFQafTZXiMoihUrlyZM2fOAHD69GnLfSVKlCAyMhJFUTh7\n9myW7c+fP58lS5awePFi3NzcLAMh2a1q7ODgwNtvv81nn33GwYMHuXQp65QuW+nZ8yVeeKEusz96\nh+Cd62hkx9dypjEYDGz/ZQ2+vrX5Zev/aFC/ntqRHqpiRQ927PiBbdtWc/jwMW7ciFQ7Uq6aNWvI\n4UM/s2/vj9y48TdHj9rnAmxptFYmQDLbQvv2LQjetZ7gXevxKFfGbgcYDQYDP//8P3x8arNly0rq\n16+b5bY9k3JhfSdOniExMZG9u4NISUnh6LGTakfKlVbKhdbqX+a8RYoYSEw0ERy8npSUFI4dO6V2\nxBxp8ZxTi+2FGnXv91Nn6DVoDH2Hv4lH2dL4etXiw7n/zlbf9+sRWjRtaLk9tH9v5i9bzaAxgQz5\nz2Qib//z0O0PGxDA0HFTmDtvMUP69QJg5mff8MfZ8wwcPZFvFq6wzo7lQGvnyUJdOsWKq4OcPXuW\nCRMmULFiRTw8PDAYDBw5coQtW7YAMHz4cN577z1KlCjBuHHjSElJoUqVKvzzzz988803HD58mJkz\nZ1KtWjUSExMZNGgQTz31FDNmzGD+/PlMmzaN0NBQatSoQVhYGIsXL2bv3r3cvXuXwYMHAxAYGEjf\nvn25du0aK1asQK/XU7ZsWT799FMMhtwnshgcn7LW4RH/z+Bgf18XlxuzYs79QXbEbCeLAAn7osv9\nIXZHr7H2Itls/4v8ZabFciEtnPVpsa/WGmkvbENr7UXCjQNqR8i3Yk+9qHaEfEsyRagdwaqeKull\ns+e6fvcPmz1XTqw6yJFXiqKQkpKCwWBg48aNhIeHM2HChALZ9vjx43njjTd47rnnHunvZZDD+rR4\n4iSDHKIw0OLJqQxyWJ8Wy4W0cNanxb5aa6S9sA2ttRcyyGEbMshRcOxhkMOqa3LkVXJyMgMGDECn\n0+Hg4MCcOXMKZLsrV67k3r17ljVAhBBCCCGEEEKIJ8mT9oGnXczksGcyk8P6tPjpkMzkEIWBFj+B\nk5kc1qfFciEtnPVpsa/WGmkvbENr7YXM5LCNwj6To4J73r/B9HHdjP7TZs+VE7uYySGEEEIIIYQQ\nQoiCp2hueO/xWPXbVYQQQgghhBBCCCFsRWZyCCGEEEIIIYQQhdSTtkKFzOQQQgghhBBCCCFEoSAz\nOYQQQgghhBBCiELKLGtyCCGEEEIIIYQQQmiPzOTIhYNOW1+OpcWvCtXiV6bpHTQ2PqjBciGsT4ul\nQovthdZosVwI69Ni3Xu3Qgu1I+TLzJt71Y4g7JBLRX+1I+Rb9Gg/tSOITGRNDiGEEEIIIYQQQggN\nkpkcQgghhBBCCCFEIaXF2f6PQ2ZyCCGEEEIIIYQQolCQmRxCCCGEEEIIIUQhJWtyCCGEEEIIIYQQ\nQmiQDHIIIYQQQgghhBCiUJDLVYQQQgghhBBCiELK/IR9QbzM5BBCCCGEEEIIIUShIDM5hBBCCCGE\nEEKIQkoWHhVWV7lyJa5dPcHOHevYunWV2nHy5LNPP2Dv7iDmfjZN7Sh5pqXMLi7O/LhxKTt2rGX9\nukU4OjqqHSlPtHSMARrUr8eBfZvYt2cjn336gdpx8qRCBQ+OhGzjXuwF9Hq92nHyRGvlArSXWWt5\nQXuZpe7ZhhqZi5dzZ/jWmbz71xIc9BlPhWt3asDQTdMZ8uM0arb1e6TtNxnemUHrp/LKl6NwMOhx\nf7osr697j9fXvkePr95A56AriN3IM62VCy+vmuzft4k9u4NY+P1ctePkidaOsb2dDxV58WVcRs/O\n99/p3ErhPHImLmM+Rl+9Tuq22gXgMvYTXMZ+gr66b0FHFRrxxA1yBAUFkZCQoHYMgoMP0Lbdq3Tu\n3FftKLmqV9ebYq5FadHqFRwdHXnBr47akXKltczt2rXgyNETtGvXi6PHTtK+XQu1I+VKa8cY4MrV\nCNq060Xzlt0pW6403t611I6Uq6ioaNq1701IyHG1o+SJFsuF1jJrLS9oM7PUPetTK3NCzH2WvfYh\nESfCs9zXeEhHlvaeydLeM2k8pGOu22ox7hXcK5Wx3C5W2o2qjWuzuOd0IsOuUqudH4kx9/nfoDks\n6TWDu9duUb1l3QLdn4fRYrn4668LvNi8Ky1bvQJg95m1eIzt6nxIb8DhqWfz9FCngP9kuF2kdQ+S\nfllFwvz3cWzbC4DkY3tI+GoiCQum4djutQKPq1VmRbHZP3vwxA1ybNy40S4GOZo3b8Lu4A2MHTtE\n7Si5atjQj13BBwAI3n2ARo0e7ZMNW9Ja5osXr1CsaFEA3Eu4cSfqrsqJcqe1YwwQGXkbk8kEwIMH\nyaSkpKicKHcmk4no6Bi1Y+SZFsuF1jJrLS9oM7PUPetTK3Oy6QGJsfHZ3hd15RZFijrhWMwZ073U\n88Wn6lZj4Jp3GLThfeq++uJDt13RtyqXD4UBcPHgGZ72q05ibDymuNRtmR+koJjNBbg3D6fFcpGc\nnGz52WRK4lrEDRXT5E6Lx9iezocMDduSfHS35bZTj5E4j5yJ85D3wKXYQ//WoUJlzJfDICkRxZQA\nTi4oUZGpd6Y8gCdssU3xr0IxyBEYGMjUqVMZMmQIRqPRUmmXLl1Knz596N27N3v27OHIkSOEhYUx\natQoPvvsM9Xy3rx5Cy9vf9q260WrVv74eHuqliUv3N3diIuNAyA2Jg53dzeVE+VOa5nDwy/RsJEf\nJ47v4nk/Xw4dOqZ2pFxp7Rin5+PjSdkypQkLO692lEJHi+VCa5m1lhe0mVlrtHiM7THz2e1HGfHz\nh4z45UOOLN0BQMs3e7J6yFwW95iGb7em6IvkfPmSs1sxy+CIKS4BZ7eilvuKl3PnWX8fLuw/bd2d\nSMcej3FevPRSW06cCKacRxnu3LHvD360eozBDs6HHPTon/MhJTwUAH3t+pijb5P47bs8OLiVIk0e\nPptKp/u3LiqJ8ejSDYo4tn+NB4e2WSe3Bik2/M8eFJqFR728vJg+fTozZ87k119/5ZlnnuH48eP8\n73//w2Qy8dprrxEUFISnpydffvklpUqVUi1rUlISSUmpP//88y68vGpy+kyYanlyExMTS3G34gAU\nd3MlOjpW5US501pmY79X+XnrTuZ+Pp/x44bTp88rrFq1Qe1YD6W1Y5ymZEl3vvpiJgF9RqgdpVDS\nYrnQWmat5QVtZtYaLR5je8zcfOwr/LfNRAD6Lp3AhQOnKe/5DK8tfBOAoqWKU7SUG359WlGlYS3c\nK5XlueZ1SDYlseuTH0iMi8etfOo5plNxF8uMEb2jgW5zR7A5cCHmFNvN5LDHY5wXW7bsZMuWnXzx\n+Qw6d27Dpk32+2ZVq8fYHs6HDC+0JPn4PsttB4+nMdTzx1CzHjjoSblyFl0pD5wDxgKgK1cJl1Gz\nMN++jmndPFD+rUs6JxeUhPsA6H0aoStanOTj+227Q8JuFIqZHACenqmzISpUqEBMTAznz5/nzz//\nxGg0MmTIEOLj47l3757KKVO5uv47ytikcX0uXLyiYprcHT78O61aNgOgdSt/TVyfrLXMOp2OqLvR\nAPxzJ4oS/99Z2jOtHWMAvV7P8qVfMXHSDCIjb6sdp1DSYrnQWmat5QVtZtYaLR5je8ycnPSABwkm\nkuIT0RdJ/Szw5p9XWPX6HJYGzOK7Tu8QF3mXvZ9vYGnALE6u38/6MV+zNGAWEcfDuXHqIpUbpa5v\n8GxTbyKOp6770eWjwRxdvpPb56/bdH/s8RjnJv3i67Fx90hISFQxTe60eIzt5XzIodxTFGnSEedh\nH+BQ/hlIfkDy0T0kzHuHhG8CSdq6AiUqMvX2vHdIOXuchHnvpA5wACk3L+NQuSY4OqFzLgqmBBwq\nVKFI006YNnyn2n7ZI1mTQ6N0un9XqlYUhWeffZY6deqwYsUKVqxYwU8//YSrqytFihRR/Tr8Zs0a\ncvjQz+zb+yM3bvzN0aMnVM2TmxMnz5CYmMje3UGkpKRw9NhJtSPlSmuZ1/zwIz17dGHHjrW8FtCN\n1Wt+VDtSrrR2jAF69nyJF16oy+yP3iF45zoaNbT/62YNBgPbf1mDr29tftn6PxrUr6d2pIfSYrnQ\nWmat5QVtZpa6Z31qZXYw6Om/ajIetSvTb8UkKjeshf/orgAcWxnMoA3vMzjoA35fnbpOwN656+mz\n+C0GrHmHnt+Mfui279+J5UrIWQatn0p5r8qc3XGMSs8/h2eH+jQa1IGBa96hVvsXrL6PabRYLtq3\nb0HwrvUE71qPR7ky7Ny5L/c/UpEWj7G9nA8lbVlG4oIPSFzwAea/r/LgwGZ0pcqlrskxciZ6z4fn\nerA7CMdORlxGzCBp1zoAHLsMRFfcHZfh03Ae9I4tdkPYIZ2i4S/NvX37NsuXL+f27dv07dsXHx8f\nFi1aRMmSJXnllVdYtmwZO3bswMHBgYoVK/Lxxx+zatUqdu7cSZMmTRg2bFiuz+HoVMkGe1Jw7GX0\nrLDTO2hrfDDFhoucCSGEEPbg3Qot1I6QLzNv7lU7Qr7Z9stwC4acKVtf9Gj7/xApM9e5P6kdwaqc\nnZ+x2XMlJl612XPlRNODHLYggxwiOzLIIYQQQtg3GeSwPhnkENmRQQ7786QNchSahUeFEEIIIYQQ\nQgiRkb1864mtaOvjaCGEEEIIIYQQQogcyEwOIYQQQgghhBCikHrSVqiQmRxCCCGEEEIIIYQoFGSQ\nQwghhBBCCCGEEIWCDHIIIYQQQgghhBCFlKIoNvuXH2vXriUgIACj0ci1a9cKbH9lkEMIIYQQQggh\nhBA2Ex0dzbp161i5ciUTJkxgzpw5BbZtWXhUCCGEEEIIIYQopGy57GhsbCyxsbFZfu/m5oabm5vl\ndmhoKA0aNMBgMODr68ulS5cKLIMMcuQiyRShdgQhhBBCCFHIfaB2ACFEoZWcdN1mz/X111/zzTff\nZPn96NGjGTNmjOV2TEwMJUqUsNwuyG+AkUEOIYQQQgghhBBCPLYBAwbQvXv3LL9PP4sj7fZff/1l\nue3gUHAracgghxBCCCGEEEIIIR5b5stSclKnTh3mzZtHSkoKZ8+epXLlygWWQQY5hBBCCCGEEEII\nYTPu7u5069aNvn37YjAYmDVrVoFtW6cU5MUvQgghhBBCCCGEECqRr5AVQgghhBBCCCFEoSCDHEII\nIYQQQgghhCgUZJBDCCGEEEIIIYQQhYIMcgghhBBCCCGEEKJQkEEOIYQQQgghhBBCFAoyyGElt2/f\n5rPPPlM7Rp6FhIQwffr0DL8LCgoiISEhz9t46aWXCjqWzUVERLBv3z5VM9y5c4epU6dy6dIlPvnk\nE6s8R0REBMOHD7fKth9VWFgYy5YtA8BoNBIVFZWnv9NaXbO2oKAgFi1apNrz5+e1U4taZUbNsrpg\nwQIuXryY4/35be/zYteuXURGRgLZ9zHiyZbffiinMvw45x4Pq5OFvcxa65wtu+2m79/zKn37If28\ndRVUXVSTNfowoW0yyGElZcuW5a233lI7xmPZuHHjE9dgXL9+XfVBjjNnzuDl5cWZM2fw9vZ+7O2l\npKQUQKqCk1MeT09PBgwYkO/tWaOu2dsxEwVLrfZZredNSUlh2LBhPPvsszk+xhrt/a5du7h161aB\nblMUboqioChKtvflVoYfRWE4V9OCR+nf07cf9v46GY3GHO8LDAwkIiLChmmsKy/9iRqexPcs4uEM\nagcorCIiIpgxYwaNGjViz549xMXFERAQQO/evRkzZgxvvfUWVapU4cSJE6xdu5YJEyYwfvx4zGYz\nOp2OL774glKlStk085UrVxg7diwXL15k6tSphIWFMWrUKOrXr0/VqlUJDg7GbDZz48YNhg8fzoYN\nG7hz5w7z5s2jYsWKVskUFRWV5bh89tlnXLx4EYPBwLhx40hOTubbb7/FxcWFmzdvEhgYSKNGjSzb\niIiI4M033+Tpp5/m3LlzjBgxgs6dO3P9+nU++OADTCYT7u7ufPrppyxfvpzQ0FDOnz/PtGnTrN6I\nz549m5MnT1KkSBECAwNZtmwZf/zxB+XLlyciIoKqVatiNpvz/YlLSEgIixYtwsnJiT179rB69Wp8\nfHxYtGgRJUuWpEGDBty5c4exY8dy7do1Bg8eTIcOHejVqxfr1q1Dr9czb948KlWqxMsvv2zZbnx8\nPJMmTeLu3bs4OTnx8ccfU6ZMGdq2bUuDBg0ICwujc+fODB48OEOeoKAg9u/fj8lkolWrVty7dy9L\nvQgJCWH79u1MnTrV8nenTp1ixowZuLi4ULlyZWbOnJllX9Pq2pAhQ5g1axbly5dHURS6d++Ot7c3\nM2bMYP78+UDqJ0xbtmzJ9rU/efKk5ZjVrFmT3bt3P/RYPI6QkBC+++47XF1duXDhAmPGjGHTpk1E\nREQwbdo0Vq1axdy5cwEYPHgwM2fOZN26dRw8eBBnZ2f69u1L+/bt+fjjjzlx4gRVq1bl+PHjbN++\nvUDy5Wc/Mtc9gPnz5xMWFkaJEiX4+uuvs31c+jpqa2llZtiwYXzyySfodDqaNGnC2LFj81TmHvd5\nH7dfeOeddzK0gX5+flnakr/++itDnfv999/p27cv8fHxWV4LBweHDO19bm8mMr+eI0eOZOXKlaxY\nsQKAd955h65du3LgwAHOnTtHzZo16datW5Y+pkGDBvz+++9ZXoOgoCD27NlDSkoKERERzJ07l+ee\ne67AXof8yHxcvby8VMmRk/T53n777Sxl96uvvsrSblhDdn210WikWbNmnDp1Ch8fH9555x3u37/P\nm2++SVJSEk8//bTl741GI97e3oSFhTF37lyWLVtGSEgIAJMmTaJevXoEBgbSt29fvLy8mDhxIpGR\nkY/9eqTVyfj4eKpXr054eDilS5dmzpw5QNbzovyW2UOHDvHNN9+gKApNmjRh9OjRj5U3L65du8bb\nb7+No6MjxYoV4+2332by5Mm4u7vj4uJCnTp1svTRj8psNvPuu+9y5coVHBwcmD59OoqiMH36dMLC\nwvDx8WHKlCkZ+vfsjkl0dDRTpkwhLi4OBwcH3n///QztxxtvvMGMGTOYPXs2Y8eOtbQ1U6dOpUuX\nLlSsWDFLn+7k5JQh6+LFi9m2bRtOTk4MGTKE5s2b53t/7aE9yGtdu3fvHuPGjSMlJYXnnnuOq1ev\nMn/+fIxGI19++SWlSpVi+vTptG/fnqeeesqy/SVLlmTpnzKfw6X1J+7u7hnK2nfffVeg+xoYGIij\noyM3btzAZDKxcOFCnJycWLp0KTt27CAlJYURI0ZQrFixfPVh4gmhCKu4du2aMmzYMOX+/fuKoiiK\nyWRSOnbsqKSkpCjbt29XvvrqK0VRFGXatGnKb7/9piQlJSlJSUmKoijK6tWrlfnz59s07+HDh5WA\ngADFbDYrZ86cUUaPHq3069dPuXPnjqIoirJhwwblzTffVBRFUZYuXaqMGDFCURRFWbt2rfLdd98p\niqIonTt3LvBc2R2Xbt26KSkpKYqiKEpKSopy+PBhpXv37kpycrISGRmp9OjRI8M2rl27prRs2VIx\nmUzKnTt3lO7duyuKoij/+c9/lLCwMEVRFGX58uXK6tWrlcOHDyvTpk0r8P3Izu7du5XAwEDL7eTk\nZEVRFGXkyJGK2WxWRo4c+cjbTn9MJk2apISGhiqKoigLFy5UNmzYoFy7dk1p2uKBXOsAAA2oSURB\nVLSpEh8fr8THxyudOnVSkpOTlU8//VTZt2+foiiK0qNHDyUhISHDdpcsWaIsWrRIURRF2bp1qzJr\n1ixFURSlbt26yt27dxWTyaS0a9cuS54NGzZk2J/s6kX6Y59W9r744gtl+/btiqIoltc8s7S61rNn\nT+Xvv/9WzGazYjQalV9++cVyX5q0MprTa592zBRFyfVYPI709W3nzp2WMv3bb78p7733ntKvXz8l\nJiZGuXHjhjJkyBBFURSla9euislkshyLP/74Qxk+fLiiKIpy5coVxc/PT1GU1GO9cOHCAsua235k\nrnv9+vVTDhw4oCiKogwfPlw5e/ZsrnXU1tLKRY8ePZS///5bURRFGTp0qPLnn3/mqcw97vM+Tr+Q\nlJSUpQ3Mri3JXOfS2oGcXov07X1ustvGuHHjlPDwcCUhIcGyzfRtT3Z9jKIo2b4G6fub7du3Kx99\n9NEjHO3Hl1MbbS8y5/v888+zlN3M7Ya1ZFdWW7ZsqVy8eFFRFEXp0qWLEhcXl6EPCQoKsrTP/fr1\nU3bu3KkoipKhbbtx44bSs2dPRVH+LU87duxQpk+friiKooSEhDzWuUdanezXr5+yY8cORVEUZcaM\nGcr27dsfu8yazWbllVdesdT3MWPGKBcuXHjkrHm1bt06ZfHixYqipL7mI0aMUE6fPq0oiqIEBgZa\n+oeCOGdL/1qcOnVKGTVqlNKyZUvljz/+UBQl9XzmzJkzlv49p2Mye/ZsZePGjZbMipKx/Ujfl48Y\nMUK5evWqpS00m83Z9unp/fXXX8rrr79uqcOPUpcf1h7069cvx7+bNGmScu3atXw/X07yWtcWLVqk\nLFmyRFGUrHUtra2fNm2acvjw4QzHN7v+Kaf+JHNZK2iTJk1S1qxZoyhKar0MDg5Wzp8/r4wZM0ZR\nFEVJTEy0nNPnpw8TTwaZyWFlP//8Mxs3bkSn03Hr1i1iYmJo0aIFCxYsYOTIkZw8eZJ3332XqKgo\npk2bRlRUFPfu3eOFF16wedZatWqh0+moUKEC0dHRWe739PQEwMPDI8PP1rwuLyYmJstxGTp0KJMm\nTcLZ2dnyqUjt2rXR6/WUK1cOk8mUZTvPPfccjo6OlCpViqSkJAAuXLjArFmzADCZTDRv3pyqVata\nbV8yCw8Pp2HDhpbb27dvZ+XKlVy5coXXXnuNiIgIjEYj33//Pc7Ozvnevo+PD3q9Hp1OZ/mdkm4a\ncPXq1XFxcQGgXLly3L17lx49evD1119TrFgxvLy8cHZ2ZvLkyURERNCjRw8uXbpkmc3w/PPPs3Hj\nRgAqVqyIu7s7AEWKFAHI8HcAdevWtTx3dvUiO3379uW7775j+/btNG3alFdeeSXH/U1MTMTDwwMA\nX19fgAz7nn7/c3rt044ZkO2xKEhp9c3Dw4MaNWrg4OBAuXLliI6OpkuXLmzdupXo6Gi6d+8OwIQJ\nE3jvvffQ6XQMHTqUy5cvU6dOHQCeeeYZSpYsWaD58ipz3XNxcaF27dpAarlIe21zq6NqMJlMljJT\nt25dLl26lK8y96gep18oUqRIljYwc1uSVobT17n0CuK1yLyNnj17snHjRmrUqEG7du2y/Zvs+pjs\nXgP4t7+pUKFCju2DteV0XO1F5nz9+vXLUnYztxvVqlWzSpbs+moXFxdLn5r2OqbvQ3x9fdm2bZtl\nG2nlNX3bVqFCBRITEzM816VLlyz3p/2/IKT1G76+vpYMj1Nm7969m2Gtg9jYWG7evGn1GaIdO3bk\n22+/5a233sLT05OIiAjLpa++vr7Ex8cX2HOlfy18fX25evUqBoPB0gf4+Phw5coVSpcuDZDjMQkP\nD6d///4AODg8/Er6Ll26sHnzZmrWrIm/vz86nS7bPn3ZsmXs2rULLy8vfH198fPzs9ThR6nLmevb\nuXPn+PDDD4HUNUfSLlmZMmUKnp6eltsXL17k4sWLODk50b1798fuU/Ja1y5fvkzXrl2BrHUtjZLN\npWE5nZ9l159kLmtDhgx5rH3LTuZ6df78ef7880/L8Y2Pj+fevXsF/rxC+2SQw8rmz5/P1q1bAejQ\noQOKouDo6IinpyfffvstjRo1wsHBgc2bN+Pn58fAgQNZvXo158+ft3nWzG8IixQpkmFtgvT3Z36s\ntWQ+LmfPnqVNmzZ06tSJTZs2sWrVKpo2bcqff/6J2WwmKioKR0fHLNvJLm/VqlUZN26c5YQjKSmJ\nM2fOkJycbPX9gtRBhp07d9KtWzcgtXyUK1eO06dPU7lyZaKioujZs+cjbz+tE3dzcyMyMhIfHx/C\nwsJo2rQpkNphp5083rp1i5IlS1KmTBmio6NZtmyZpbP66KOPLNu8e/cup06dws/Pj+PHj1OlShUg\n++Ob/u+CgoIynFRkVy+yU6xYMd59910URaFDhw689NJL2b6+AE5OTty6dYuyZcta1jNJ23dIPRlL\nu14zu9f+xIkTGTJWrVo1y7EoSA+rT506dWLUqFGYTCbLtNznn3+epk2bcuzYMebNm8egQYPYvHkz\nkDo9+e7duwWeMS9yq3tpr21uj1ODk5MTkZGReHh4cPLkSVq2bJmvMveoHqdfSElJydIGPv/88xna\nErPZDOR8Ip/da5G5vc9N5m00btyYr7/+mrCwMEvdf1gfkia71yAsLCzHwVlbytxGm83mXN+A2VLm\nfNmV3czthrUWb8yurGY3yFylShVOnz6Nn58fp0+fznB/2rGtXLkyP/30EwA3b97MMsBcpUoVjhw5\nwssvv0xoaGiB7cPp06fx8PDgzJkz+Pn5AY9XZkuWLEmVKlUsH1SYzWablGUHBwfefvttAAYOHEj5\n8uX5888/qV27NqGhoQV66VeVKlUICQmxvBZPP/00Z8+e5ezZs9SqVYszZ87g7+/P/fv3AXI8JgcP\nHuTIkSN07drVUs9yapNat26N0Wjk3Llzlg+6suvTHR0dLeuAnDt3jg0bNli2/Sh1OXN9q1mzpqV/\nNhqNlp/TpN0ODAxk9OjRVKpUKV/Pl5O81rXKlStbynL6ulaiRAkiIyMpWbIkZ8+epUOHDhn+Nqfz\ns+z6k8xlrXXr1gX+YWHmevXss89Sp04dS1uW9lrntw8ThZ8MclhZs2bNeO2116hRowZubm6W37/8\n8ssMGDCAoKAgABo3bsyECRM4dOgQHh4eGAzqvzStW7dmwoQJNGnShDJlyqiSIbvj8vrrr+Pg4MCD\nBw+YOnUqcXFxlC5dmlGjRvH3338zadIkIHX15zZt2uT4BmXSpEmWa3EBRo4ciY+PD+Hh4YwdO5YJ\nEyZkuGa4oLVo0YJDhw4REBCAo6MjEydO5PTp03h7e/Pbb78V2LXTPXv25K233iIoKCjDyWLFihWZ\nNGkSV65cYfjw4ZYOrEuXLixatMjyqVZ6vXr1YsKECQQHB1vW5HgUOdWLzH744Qd27NiBoij4+/s/\n9M3mhAkTGDZsGOXKlcPV1RWA4sWL88ILLxAQEED9+vUtM1eye+2zO+F52LGwJldXV5566ilcXFws\n+zx69GiSkpJISkpizJgxeHl5UblyZQICAqhRo4ZqdTRz3Zs3b16eHmcPAgMDGTNmDDqdjkaNGuHp\n6Wm51jcvZe5RPU6/cP/+fUt5TWsDa9eunaUteZjsXov07f2wYcNy3YfM23BwcKBZs2acPn2acuXK\nAdC8eXPmzJmDl5cXrVq1ynY72b0GYWFheTqO1pZdG10Qi0EXlMz5WrRowa5duzKU3cGDB2doN6wl\nr+cwr776KuPHj2fv3r05vtn28vKievXqBAQEoCiKZa2fNK1bt2b79u0YjcYCnclx5MgRli1bRqlS\npWjdujW///57to/La5nV6XSMGzeOoUOHAmAwGJgzZ45lVoO17NmzhxUrVqDX6ylbtiwjR45kypQp\nuLu7W2ZcFpQ2bdqwe/du+vTpg06nY/r06ZY1SkJDQ/H29sbb29uyvkpOx2T48OFMnjzZsg7WwoUL\nM7Qf6Rf2dHJyolq1apw/f95ShrLr0xs3bmz5mxo1atCkSRMCAgJwdnZm0KBBtGjRIl/7ai/tQV7r\nWq9evRg3bhx79uyhSpUqllm2/fr1Y8KECVSrVi3b86+8np9B1rJWUOfMt2/fZvny5dneV7NmTXx9\nfenbty8ODg5UrFiRjz/+ON99mCj8dIpaH5EUchcuXOCrr77iyy+/VDtKoZfdgpXi0f34449ER0cz\ncOBAtaPkSXZ17euvv6Z69epZPqHILzWPxZQpU+jXr59l2m9u0hZVtaW81j2po6nsoV8oiNcip238\n97//pUaNGrRt2/ZxYwphU+kXYyzMgoKCuHv3boEtPJpX+/fv5/Dhw7kOwIqCoygKKSkpGAwGNm7c\nSHh4OBMmTCiQbY8fP5433nhDtQWhhcgL9acLFEJ3797lvffeY9CgQWpHESJfFixYwN69e1mwYIHa\nUfLEmnVNzWMxfvx4ihQpkucBDmH/Cnu/8OGHH3Lp0iVGjBihdhQhhB25cOEC8+bNY/LkyWpHeaIk\nJyczYMAAdDodDg4Olm8MelwrV67k3r17Nl3DTohHITM5hBBCCCGEEEIIUSjYzwpaQgghhBBCCCGE\nEI9BBjmEEEIIIYQQQghRKMgghxBCCCGEEEIIIQoFGeQQQgghhBBCCCFEoSCDHEIIIYQQQgghhCgU\nZJBDCCGEEEIIIYQQhcL/AZIjcUTzC7oUAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jZffJ4yBBX15",
        "colab_type": "text"
      },
      "source": [
        "## Word2Vec & embeddings\n",
        "Word2vec is a type of mapping that allows words with similar meaning to have similar vector representation.\n",
        "\n",
        "The idea behind Word2vec is rather simple: we want to use the surrounding words to represent the target words with a Neural Network whose hidden layer encodes the word representation."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h7j4nOMwBdw4",
        "colab_type": "text"
      },
      "source": [
        "### loading precomputed embeddings"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FttqZMv3TM0H",
        "colab_type": "code",
        "outputId": "6af06963-ae93-416f-b578-5e88c3740840",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 124
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=email%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdocs.test%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive.photos.readonly%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fpeopleapi.readonly&response_type=code\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-gSsTgezRfUU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from gensim.models import Word2Vec\n",
        "wv = gensim.models.KeyedVectors.load_word2vec_format(\"/content/drive/My Drive/Colab Notebooks/GoogleNews-vectors-negative300.bin.gz\", binary=True)\n",
        "wv.init_sims(replace=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uJvOq1kOSMkh",
        "colab_type": "code",
        "outputId": "469d470c-8d2c-4084-ca81-0f732a7f16b6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        }
      },
      "source": [
        "from itertools import islice\n",
        "list(islice(wv.vocab, 13030, 13050))"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Memorial_Hospital',\n",
              " 'Seniors',\n",
              " 'memorandum',\n",
              " 'elephant',\n",
              " 'Trump',\n",
              " 'Census',\n",
              " 'pilgrims',\n",
              " 'De',\n",
              " 'Dogs',\n",
              " '###-####_ext',\n",
              " 'chaotic',\n",
              " 'forgive',\n",
              " 'scholar',\n",
              " 'Lottery',\n",
              " 'decreasing',\n",
              " 'Supervisor',\n",
              " 'fundamentally',\n",
              " 'Fitness',\n",
              " 'abundance',\n",
              " 'Hold']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DaER5YrRTn7y",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# BOW based approaches that includes averaging, summation, weighted addition. The common way is to average the two word vectors. Therefore, we will follow the most common way.\n",
        "\n",
        "def word_averaging(wv, words):\n",
        "    all_words, mean = set(), []\n",
        "    \n",
        "    for word in words:\n",
        "        if isinstance(word, np.ndarray):\n",
        "            mean.append(word)\n",
        "        elif word in wv.vocab:\n",
        "            mean.append(wv.syn0norm[wv.vocab[word].index])\n",
        "            all_words.add(wv.vocab[word].index)\n",
        "\n",
        "    if not mean:\n",
        "        logging.warning(\"cannot compute similarity with no input %s\", words)\n",
        "        # FIXME: remove these examples in pre-processing\n",
        "        return np.zeros(wv.vector_size,)\n",
        "\n",
        "    mean = gensim.matutils.unitvec(np.array(mean).mean(axis=0)).astype(np.float32)\n",
        "    return mean\n",
        "\n",
        "def  word_averaging_list(wv, text_list):\n",
        "    return np.vstack([word_averaging(wv, post) for post in text_list ])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z0bVxlbjTwJq",
        "colab_type": "code",
        "outputId": "50bd94f6-8b41-494d-f5eb-26c365f55290",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 124
        }
      },
      "source": [
        "# We will tokenize the text and apply the tokenization to “post” column, and apply word vector averaging to tokenized text.\n",
        "\n",
        "def w2v_tokenize_text(text):\n",
        "    tokens = []\n",
        "    for sent in nltk.sent_tokenize(text, language='english'):\n",
        "        for word in nltk.word_tokenize(sent, language='english'):\n",
        "            if len(word) < 2:\n",
        "                continue\n",
        "            tokens.append(word)\n",
        "    return tokens\n",
        "    \n",
        "train, test = train_test_split(df, test_size=0.3, random_state = 42)\n",
        "\n",
        "test_tokenized = test.apply(lambda r: w2v_tokenize_text(r['post']), axis=1).values\n",
        "train_tokenized = train.apply(lambda r: w2v_tokenize_text(r['post']), axis=1).values\n",
        "\n",
        "X_train_word_average = word_averaging_list(wv,train_tokenized)\n",
        "X_test_word_average = word_averaging_list(wv,test_tokenized)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:9: DeprecationWarning: Call to deprecated `syn0norm` (Attribute will be removed in 4.0.0, use self.wv.vectors_norm instead).\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.6/dist-packages/gensim/matutils.py:737: FutureWarning: Conversion of the second argument of issubdtype from `int` to `np.signedinteger` is deprecated. In future, it will be treated as `np.int64 == np.dtype(int).type`.\n",
            "  if np.issubdtype(vec.dtype, np.int):\n",
            "WARNING:root:cannot compute similarity with no input []\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IoddfH2JCjCb",
        "colab_type": "text"
      },
      "source": [
        "### word2vec & logistic regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o8KVhtHhT5EH",
        "colab_type": "code",
        "outputId": "e8d35ca2-eb0e-4c8d-8e55-abaea8809597",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        }
      },
      "source": [
        "from sklearn.linear_model import LogisticRegression\n",
        "logreg = LogisticRegression(n_jobs=1, C=1e5)\n",
        "logreg = logreg.fit(X_train_word_average, train['tags'])\n",
        "y_pred = logreg.predict(X_test_word_average)\n",
        "print('accuracy %s' % accuracy_score(y_pred, test.tags))\n",
        "print(classification_report(test.tags, y_pred,target_names=my_tags))"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
            "  FutureWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
            "  \"this warning.\", FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "accuracy 0.6380833333333333\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "         java       0.63      0.59      0.61       613\n",
            "         html       0.74      0.76      0.75       620\n",
            "      asp.net       0.65      0.67      0.66       587\n",
            "           c#       0.53      0.52      0.52       586\n",
            "ruby-on-rails       0.70      0.77      0.73       599\n",
            "       jquery       0.44      0.39      0.41       589\n",
            "        mysql       0.65      0.60      0.63       594\n",
            "          php       0.73      0.80      0.76       610\n",
            "          ios       0.61      0.61      0.61       617\n",
            "   javascript       0.56      0.52      0.54       587\n",
            "       python       0.55      0.50      0.52       611\n",
            "            c       0.61      0.61      0.61       594\n",
            "          css       0.65      0.65      0.65       619\n",
            "      android       0.61      0.57      0.59       574\n",
            "       iphone       0.70      0.71      0.70       584\n",
            "          sql       0.43      0.43      0.43       578\n",
            "  objective-c       0.68      0.71      0.70       591\n",
            "          c++       0.76      0.78      0.77       608\n",
            "    angularjs       0.82      0.83      0.82       638\n",
            "         .net       0.65      0.71      0.68       601\n",
            "\n",
            "     accuracy                           0.64     12000\n",
            "    macro avg       0.63      0.64      0.63     12000\n",
            " weighted avg       0.63      0.64      0.64     12000\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R7H58cDVROkU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "outputId": "43b86569-f818-40d8-85ea-d99e4f61437b"
      },
      "source": [
        "df_cm = pd.DataFrame(confusion_matrix(y_pred, test.tags),index=my_tags, columns=my_tags)\n",
        "plt.figure(figsize = (20,10))\n",
        "sn.set(font_scale=0.8)#for label size\n",
        "sn.heatmap(df_cm, annot=True,annot_kws={\"size\": 8})# font size"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f29da054d68>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABDkAAAJGCAYAAABRKl46AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YKy6KRiXCtIH",
        "colab_type": "text"
      },
      "source": [
        "### Doc2Vec & Logistic Regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IEDsaNkIT-nV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from tqdm import tqdm\n",
        "tqdm.pandas(desc=\"progress-bar\")\n",
        "from gensim.models import Doc2Vec\n",
        "from sklearn import utils\n",
        "import gensim\n",
        "from gensim.models.doc2vec import TaggedDocument\n",
        "import re\n",
        "\n",
        "def label_sentences(corpus, label_type):\n",
        "    \"\"\"\n",
        "    Gensim's Doc2Vec implementation requires each document/paragraph to have a label associated with it.\n",
        "    We do this by using the TaggedDocument method. The format will be \"TRAIN_i\" or \"TEST_i\" where \"i\" is\n",
        "    a dummy index of the post.\n",
        "    \"\"\"\n",
        "    labeled = []\n",
        "    for i, v in enumerate(corpus):\n",
        "        label = label_type + '_' + str(i)\n",
        "        labeled.append(TaggedDocument(v.split(), [label]))\n",
        "    return labeled\n",
        "X_train, X_test, y_train, y_test = train_test_split(df.post, df.tags, random_state=0, test_size=0.3)\n",
        "X_train = label_sentences(X_train, 'Train')\n",
        "X_test = label_sentences(X_test, 'Test')\n",
        "all_data = X_train + X_test"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ipqv_CtEUEnw",
        "colab_type": "code",
        "outputId": "8006d882-b800-4f13-e8c2-7d5bb24f6647",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "all_data[:2]"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[TaggedDocument(words=['fulltext', 'search', 'php', 'pdo', 'returning', 'result', 'searched', 'lot', 'matter', 'find', 'wrong', 'setup', 'trying', 'fulltext', 'search', 'using', 'pdo', 'php', 'get', 'results', 'error', 'messages', 'table', 'contains', 'customer', 'details', 'id', 'int', '11', 'auto_increment', 'name', 'varchar', '150', 'lastname', 'varchar', '150', 'company', 'varchar', '250', 'adress', 'varchar', '150', 'postcode', 'int', '5', 'city', 'varchar', '150', 'email', 'varchar', '250', 'phone', 'varchar', '20', 'orgnr', 'varchar', '15', 'timestamp', 'timestamp', 'current_timestamp', 'run', 'sqlquery', 'alter', 'table', 'system_customer', 'add', 'fulltext', 'name', 'lastname', 'except', 'columns', 'id', 'postcode', 'timestamp', 'signs', 'trouble', 'far', 'idea', 'problem', 'lies', 'db', 'configuration', 'php', 'code', 'goes', 'php', 'sth', 'dbhprepare', 'select', 'name', 'lastname', 'company', 'adress', 'city', 'phone', 'email', 'orgnr', 'db_pre', 'customer', 'match', 'name', 'lastname', 'company', 'adress', 'city', 'phone', 'email', 'orgnr', 'search', 'boolean', 'mode', 'bind', 'placeholders', 'sthbindparam', 'search', 'data', 'sthexecute', 'rows', 'sthfetchall', 'testing', 'print_r', 'dbherrorinfo', 'empty', 'rows', 'echo', 'else', 'echo', 'foreach', 'rows', 'row', 'echo', 'tr', 'datahref', 'new_orderphp', 'cid', 'row', 'id', 'echo', 'td', 'row', 'name', 'td', 'echo', 'td', 'row', 'lastname', 'td', 'echo', 'td', 'row', 'company', 'td', 'echo', 'td', 'row', 'phone', 'td', 'echo', 'td', 'row', 'email', 'td', 'echo', 'td', 'date', 'ymd', 'strtotime', 'row', 'timestamp', 'td', 'echo', 'tr', 'echo', 'tried', 'change', 'parameter', 'searchquery', 'string', 'like', 'testcompany', 'somename', 'boolean', 'mode', 'also', 'read', 'word', 'found', '50', 'rows', 'counts', 'common', 'word', 'pretty', 'sure', 'case', 'uses', 'specific', 'words', 'table', 'uses', 'myisam', 'engine', 'get', 'results', 'error', 'messages', 'please', 'help', 'point', 'wrong', 'thank'], tags=['Train_0']),\n",
              " TaggedDocument(words=['select', 'everything', '1', 'table', 'x', 'rows', 'another', 'im', 'making', 'join', 'query', 'like', 'select', 'clothes', 'c', 'join', 'style', 'cstyleid', 'ssylelid', 'clothesid', '19', 'dont', 'want', 'select', 'everything', 'style', 'want', 'select', 'everything', 'clothes', '20', 'rows', 'select', '1', 'row', '10', 'style', 'easyest', 'way', 'without', 'select', 'every', 'row', 'clothes', '20', 'things', 'select', 'like', 'select', 'cid', 'cdescription', 'cname', 'csize', 'cbrand', 'sname', 'clothes', 'c', 'join', 'style', 'cstyleid', 'stsylelid', 'clothesid', '19', 'would', 'fastest', 'way', 'possibillity'], tags=['Train_1'])]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uUqzbnxfUO1e",
        "colab_type": "code",
        "outputId": "73506d61-2a79-49ea-c7dc-bfa9bfdc7751",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 555
        }
      },
      "source": [
        "model_dbow = Doc2Vec(dm=0, vector_size=300, negative=5, min_count=1, alpha=0.065, min_alpha=0.065)\n",
        "model_dbow.build_vocab([x for x in tqdm(all_data)])\n",
        "\n",
        "for epoch in range(30):\n",
        "    model_dbow.train(utils.shuffle([x for x in tqdm(all_data)]), total_examples=len(all_data), epochs=1)\n",
        "    model_dbow.alpha -= 0.002\n",
        "    model_dbow.min_alpha = model_dbow.alpha"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 40000/40000 [00:00<00:00, 2311643.63it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2876406.47it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2249680.33it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2822736.39it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2958840.25it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2625336.98it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2898220.01it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2958109.88it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2828590.02it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2876554.42it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2981768.03it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 3027394.71it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2908116.69it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2909125.21it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2973681.92it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2767284.54it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2914127.70it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2183396.15it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2913469.83it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2864374.79it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2962340.60it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2960354.31it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2243243.21it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2907915.07it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2165640.38it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2969418.76it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2936724.96it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2771993.92it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2490383.56it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 3023085.21it/s]\n",
            "100%|██████████| 40000/40000 [00:00<00:00, 2984367.01it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3q7Fuef7UUyI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def get_vectors(model, corpus_size, vectors_size, vectors_type):\n",
        "    \"\"\"\n",
        "    Get vectors from trained doc2vec model\n",
        "    :param doc2vec_model: Trained Doc2Vec model\n",
        "    :param corpus_size: Size of the data\n",
        "    :param vectors_size: Size of the embedding vectors\n",
        "    :param vectors_type: Training or Testing vectors\n",
        "    :return: list of vectors\n",
        "    \"\"\"\n",
        "    vectors = np.zeros((corpus_size, vectors_size))\n",
        "    for i in range(0, corpus_size):\n",
        "        prefix = vectors_type + '_' + str(i)\n",
        "        vectors[i] = model.docvecs[prefix]\n",
        "    return vectors\n",
        "    \n",
        "train_vectors_dbow = get_vectors(model_dbow, len(X_train), 300, 'Train')\n",
        "test_vectors_dbow = get_vectors(model_dbow, len(X_test), 300, 'Test')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rpYm7lEfUa9b",
        "colab_type": "code",
        "outputId": "e2aa83a9-e385-4866-eb64-c9cbe80c6696",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 642
        }
      },
      "source": [
        "logreg = LogisticRegression(n_jobs=1, C=1e5)\n",
        "logreg.fit(train_vectors_dbow, y_train)\n",
        "logreg = logreg.fit(train_vectors_dbow, y_train)\n",
        "y_pred = logreg.predict(test_vectors_dbow)\n",
        "print('accuracy %s' % accuracy_score(y_pred, y_test))\n",
        "print(classification_report(y_test, y_pred,target_names=my_tags))"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
            "  FutureWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
            "  \"this warning.\", FutureWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
            "  FutureWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
            "  \"this warning.\", FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "accuracy 0.8093333333333333\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "         java       0.70      0.68      0.69       589\n",
            "         html       0.89      0.91      0.90       661\n",
            "      asp.net       0.93      0.96      0.94       606\n",
            "           c#       0.79      0.78      0.78       613\n",
            "ruby-on-rails       0.82      0.90      0.86       601\n",
            "       jquery       0.70      0.69      0.70       585\n",
            "        mysql       0.88      0.80      0.84       621\n",
            "          php       0.83      0.87      0.85       587\n",
            "          ios       0.69      0.67      0.68       560\n",
            "   javascript       0.69      0.65      0.67       611\n",
            "       python       0.67      0.69      0.68       593\n",
            "            c       0.81      0.85      0.83       581\n",
            "          css       0.80      0.77      0.79       608\n",
            "      android       0.85      0.85      0.85       593\n",
            "       iphone       0.86      0.82      0.84       592\n",
            "          sql       0.73      0.66      0.69       597\n",
            "  objective-c       0.85      0.88      0.86       604\n",
            "          c++       0.91      0.93      0.92       610\n",
            "    angularjs       0.95      0.96      0.95       595\n",
            "         .net       0.80      0.85      0.82       593\n",
            "\n",
            "     accuracy                           0.81     12000\n",
            "    macro avg       0.81      0.81      0.81     12000\n",
            " weighted avg       0.81      0.81      0.81     12000\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RgM7Yj6yR1Cu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "outputId": "3dd13dcd-44e0-4194-be3b-ff6447220007"
      },
      "source": [
        "df_cm = pd.DataFrame(confusion_matrix(y_test,y_pred),index=my_tags, columns=my_tags)\n",
        "plt.figure(figsize = (20,10))\n",
        "sn.set(font_scale=0.8)#for label size\n",
        "sn.heatmap(df_cm, annot=True,annot_kws={\"size\": 8})# font size"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f29c6da0ef0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABDkAAAJGCAYAAABRKl46AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niKha+D/0DxMHnyad0gAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "38ZCvS4mC2MS",
        "colab_type": "text"
      },
      "source": [
        "## Keras Bag of words"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cyOq3RDDUjqu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import itertools\n",
        "import os\n",
        "\n",
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import tensorflow as tf\n",
        "\n",
        "from sklearn.preprocessing import LabelBinarizer, LabelEncoder\n",
        "from sklearn.metrics import confusion_matrix\n",
        "\n",
        "from tensorflow import keras\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Dense, Activation, Dropout\n",
        "from keras.preprocessing import text, sequence\n",
        "from keras import utils\n",
        "\n",
        "train_size = int(len(df) * .7)\n",
        "train_posts = df['post'][:train_size]\n",
        "train_tags = df['tags'][:train_size]\n",
        "\n",
        "test_posts = df['post'][train_size:]\n",
        "test_tags = df['tags'][train_size:]\n",
        "\n",
        "max_words = 1000\n",
        "tokenize = text.Tokenizer(num_words=max_words, char_level=False)\n",
        "tokenize.fit_on_texts(train_posts) # only fit on train\n",
        "\n",
        "x_train = tokenize.texts_to_matrix(train_posts)\n",
        "x_test = tokenize.texts_to_matrix(test_posts)\n",
        "\n",
        "encoder = LabelEncoder()\n",
        "encoder.fit(train_tags)\n",
        "y_train = encoder.transform(train_tags)\n",
        "y_test = encoder.transform(test_tags)\n",
        "\n",
        "num_classes = np.max(y_train) + 1\n",
        "y_train = utils.to_categorical(y_train, num_classes)\n",
        "y_test = utils.to_categorical(y_test, num_classes)\n",
        "\n",
        "batch_size = 32\n",
        "epochs = 2\n",
        "\n",
        "# Build the model\n",
        "model = Sequential()\n",
        "model.add(Dense(512, input_shape=(max_words,)))\n",
        "model.add(Activation('relu'))\n",
        "model.add(Dropout(0.5))\n",
        "model.add(Dense(num_classes))\n",
        "model.add(Activation('softmax'))\n",
        "\n",
        "model.compile(loss='categorical_crossentropy',\n",
        "              optimizer='adam',\n",
        "              metrics=['accuracy'])\n",
        "              \n",
        "history = model.fit(x_train, y_train,\n",
        "                    batch_size=batch_size,\n",
        "                    epochs=epochs,\n",
        "                    verbose=1,\n",
        "                    validation_split=0.1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C6tqef3vUtzU",
        "colab_type": "code",
        "outputId": "a12ba0d7-6ee6-48b2-9388-bc661fcee838",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "score = model.evaluate(x_test, y_test,\n",
        "                       batch_size=batch_size, verbose=1)\n",
        "print('Test accuracy:', score[1])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "12000/12000 [==============================] - 0s 36us/step\n",
            "Test accuracy: 0.794\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cAmW749FU74E",
        "colab_type": "text"
      },
      "source": [
        "Notes :\n",
        "* https://towardsdatascience.com/multi-class-text-classification-model-comparison-and-selection-5eb066197568\n",
        "* https://towardsdatascience.com/multi-class-text-classification-with-doc2vec-logistic-regression-9da9947b43f4\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6NVuVpqDU84m",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}