{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0u1ezfX3zhEe"
      },
      "source": [
        "# Download data and libraries"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 209,
      "metadata": {
        "id": "YVage4fCRGtX"
      },
      "outputs": [],
      "source": [
        "!pip install -Uqq underthesea"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Install PyDrive\n",
        "!pip install -U -q PyDrive\n",
        "\n",
        "from pydrive.auth import GoogleAuth\n",
        "from pydrive.drive import GoogleDrive\n",
        "from google.colab import auth\n",
        "from oauth2client.client import GoogleCredentials\n",
        "\n",
        "# Authenticate and create the PyDrive client\n",
        "auth.authenticate_user()\n",
        "gauth = GoogleAuth()\n",
        "gauth.credentials = GoogleCredentials.get_application_default()\n",
        "drive = GoogleDrive(gauth)\n",
        "\n",
        "file_ids = {\n",
        "    'word2vec.txt': '1L9DdOOeonW_PpZ7ixuS-WtgXhE7GbOwA'\n",
        "}\n",
        "\n",
        "# Download file\n",
        "for filename, file_id in file_ids.items():\n",
        "    downloaded = drive.CreateFile({'id': file_id})\n",
        "    downloaded.GetContentFile(filename)\n",
        "    print(f\"Downloaded {filename}\")\n"
      ],
      "metadata": {
        "id": "lSRqE1L6PPzF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "10084439-af3a-4655-9621-16fd5bb951d3"
      },
      "execution_count": 210,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloaded word2vec.txt\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "snMOKwOyIdKW"
      },
      "source": [
        "# Load pretrained Vietnamese word2vec"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 211,
      "metadata": {
        "id": "2eTR2kPh4RJ4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "440b9bef-1a10-4291-8ace-88d3584f6f2c"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Size([6250, 100])"
            ]
          },
          "metadata": {},
          "execution_count": 211
        }
      ],
      "source": [
        "import torch\n",
        "import torchtext.vocab as vocab\n",
        "\n",
        "word_embedding = vocab.Vectors(name = \"word2vec.txt\",\n",
        "                               unk_init = torch.Tensor.normal_)\n",
        "\n",
        "word_embedding.vectors.shape"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "WuS_afJUHYE2"
      },
      "execution_count": 211,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "word_embedding.vectors.shape\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "21JO2BJZHYKZ",
        "outputId": "0dc5f5d3-b39d-4cde-f98e-c0b1637c19df"
      },
      "execution_count": 212,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Size([6250, 100])"
            ]
          },
          "metadata": {},
          "execution_count": 212
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Lưu ma trận word embeddings vào một tệp bằng torch.save()\n",
        "torch.save(word_embedding, 'word_embeddings.pt')"
      ],
      "metadata": {
        "id": "K9skF9B1H_RZ"
      },
      "execution_count": 213,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "HLlGJZx8H_UD"
      },
      "execution_count": 213,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "word_vectors_loaded = torch.load('word_embeddings.pt')"
      ],
      "metadata": {
        "id": "KyZ9o6NcH_Xk"
      },
      "execution_count": 214,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "word_embedding= word_vectors_loaded"
      ],
      "metadata": {
        "id": "Dll1g_BbDcVU"
      },
      "execution_count": 215,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "word_vectors_loaded.vectors.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fY1PtdgUHYNx",
        "outputId": "75b64255-5f8f-408d-be57-202807be8b92"
      },
      "execution_count": 216,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Size([6250, 100])"
            ]
          },
          "metadata": {},
          "execution_count": 216
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Q7zEHgAFJH0K"
      },
      "execution_count": 216,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 217,
      "metadata": {
        "id": "8vVipzI7jKlR"
      },
      "outputs": [],
      "source": [
        "def get_vector(embeddings, word):\n",
        "    \"\"\" Get embedding vector of the word\n",
        "    @param embeddings (torchtext.vocab.vectors.Vectors)\n",
        "    @param word (str)\n",
        "    @return vector (torch.Tensor)\n",
        "    \"\"\"\n",
        "    assert word in embeddings.stoi, f'*{word}* is not in the vocab!'\n",
        "    return embeddings.vectors[embeddings.stoi[word]]\n",
        "\n",
        "def closest_words(embeddings, vector, n=10):\n",
        "    \"\"\" Return n words closest in meaning to the word\n",
        "    @param embeddings (torchtext.vocab.vectors.Vectors)\n",
        "    @param vector (torch.Tensor)\n",
        "    @param n (int)\n",
        "    @return words (list(tuple(str, float)))\n",
        "    \"\"\"\n",
        "    distances = [(word, torch.dist(vector, get_vector(embeddings, word)).item())\n",
        "                 for word in embeddings.itos]\n",
        "\n",
        "    return sorted(distances, key = lambda w: w[1])[:n]\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "gsKkpc6wJq3V"
      },
      "execution_count": 217,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "get_vector(word_embedding, \"=))\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6ftyufxcJsEp",
        "outputId": "ccf876f7-ca02-487a-8baf-715cdc0ee6b4"
      },
      "execution_count": 218,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([-0.0524,  0.2198,  0.0341,  0.0667,  0.0685, -0.3448,  0.2243,  0.5017,\n",
              "        -0.3036, -0.0485, -0.0718, -0.3842, -0.1026,  0.1339, -0.0350, -0.1742,\n",
              "         0.0753, -0.2906, -0.0184, -0.3389,  0.0839,  0.0182,  0.0064, -0.2174,\n",
              "        -0.0853,  0.0883, -0.1861, -0.1856, -0.0943, -0.0368,  0.3119,  0.0282,\n",
              "         0.1105, -0.1238, -0.0523,  0.3661,  0.1174, -0.1860, -0.1242, -0.4322,\n",
              "         0.0259, -0.2256, -0.0914,  0.1299,  0.2600,  0.0305, -0.2786, -0.0546,\n",
              "         0.1725,  0.1289,  0.1099, -0.2924, -0.1014,  0.0305, -0.3265,  0.1585,\n",
              "         0.1648, -0.1246, -0.3224,  0.0570, -0.0238,  0.1210, -0.0639, -0.0445,\n",
              "        -0.2806,  0.1889,  0.0547,  0.2162, -0.2127,  0.2026, -0.4158,  0.1253,\n",
              "         0.2521, -0.1904,  0.3012,  0.1421, -0.0155,  0.1912, -0.3584,  0.1201,\n",
              "        -0.0571,  0.0419, -0.2927,  0.2666, -0.0123,  0.0570,  0.0271,  0.2038,\n",
              "         0.2482,  0.0273,  0.2204,  0.1571,  0.0307, -0.0453,  0.3166,  0.1144,\n",
              "         0.0649, -0.1665,  0.1764, -0.0072])"
            ]
          },
          "metadata": {},
          "execution_count": 218
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "D6cm01PKJsIE"
      },
      "execution_count": 218,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "fLcFpGVtJ03V"
      },
      "execution_count": 218,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "word_vector = get_vector(word_embedding, 'vl')\n",
        "closest_words(word_embedding, word_vector)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WJ-BygyzQFT1",
        "outputId": "78f8a585-0ab0-429e-ac83-f9c61db91974"
      },
      "execution_count": 219,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('vl', 0.0),\n",
              " ('porto', 0.08383642137050629),\n",
              " ('tư', 0.08441320806741714),\n",
              " ('🤣🤣🤣', 0.08574710041284561),\n",
              " ('đôi', 0.08643840253353119),\n",
              " ('ác', 0.08719383180141449),\n",
              " ('ngu', 0.08817220479249954),\n",
              " ('Khánh', 0.08846817910671234),\n",
              " (':)', 0.08860653638839722),\n",
              " ('bình', 0.08883475512266159)]"
            ]
          },
          "metadata": {},
          "execution_count": 219
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_Bj5im3czmtH"
      },
      "source": [
        "# Vocabulary.py"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 220,
      "metadata": {
        "id": "JDWkevH2VdBn"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "from underthesea import word_tokenize\n",
        "\n",
        "\n",
        "class Vocabulary:\n",
        "    \"\"\" The Vocabulary class is used to record words, which are used to convert\n",
        "        text to numbers and vice versa.\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(self):\n",
        "        self.word2id = dict()\n",
        "        self.word2id['<pad>'] = 0   # Pad Token\n",
        "        self.word2id['<unk>'] = 1   # Unknown Token\n",
        "        self.unk_id = self.word2id['<unk>']\n",
        "        self.id2word = {v: k for k, v in self.word2id.items()}\n",
        "\n",
        "    def __getitem__(self, word):\n",
        "        return self.word2id.get(word, self.unk_id)\n",
        "\n",
        "    def __contains__(self, word):\n",
        "        return word in self.word2id\n",
        "\n",
        "    def __len__(self):\n",
        "        return len(self.word2id)\n",
        "\n",
        "    def id2word(self, word_index):\n",
        "        \"\"\"\n",
        "        @param word_index (int)\n",
        "        @return word (str)\n",
        "        \"\"\"\n",
        "        return self.id2word[word_index]\n",
        "\n",
        "    def add(self, word):\n",
        "        \"\"\" Add word to vocabulary\n",
        "        @param word (str)\n",
        "        @return index (str): index of the word just added\n",
        "        \"\"\"\n",
        "        if word not in self:\n",
        "            word_index = self.word2id[word] = len(self.word2id)\n",
        "            self.id2word[word_index] = word\n",
        "            return word_index\n",
        "        else:\n",
        "            return self[word]\n",
        "\n",
        "    @staticmethod\n",
        "    def tokenize_corpus(corpus):\n",
        "        \"\"\"Split the documents of the corpus into words\n",
        "        @param corpus (list(str)): list of documents\n",
        "        @return tokenized_corpus (list(list(str))): list of words\n",
        "        \"\"\"\n",
        "        tokenized_corpus = list()\n",
        "        for document in corpus:\n",
        "            tokenized_document = [word.replace(\" \", \"_\") for word in word_tokenize(document)]\n",
        "            tokenized_corpus.append(tokenized_document)\n",
        "\n",
        "        return tokenized_corpus\n",
        "\n",
        "    def corpus_to_tensor(self, corpus, is_tokenized=False):\n",
        "        \"\"\" Convert corpus to a list of indices tensor\n",
        "        @param corpus (list(str) if is_tokenized==False else list(list(str)))\n",
        "        @param is_tokenized (bool)\n",
        "        @return indicies_corpus (list(tensor))\n",
        "        \"\"\"\n",
        "        if is_tokenized:\n",
        "            tokenized_corpus = corpus\n",
        "        else:\n",
        "            tokenized_corpus = self.tokenize_corpus(corpus)\n",
        "        indicies_corpus = list()\n",
        "        for document in tokenized_corpus:\n",
        "            indicies_document = torch.tensor(list(map(lambda word: self[word], document)),\n",
        "                                             dtype=torch.int64)\n",
        "            indicies_corpus.append(indicies_document)\n",
        "\n",
        "        return indicies_corpus\n",
        "\n",
        "    def tensor_to_corpus(self, tensor):\n",
        "        \"\"\" Convert list of indices tensor to a list of tokenized documents\n",
        "        @param indicies_corpus (list(tensor))\n",
        "        @return corpus (list(list(str)))\n",
        "        \"\"\"\n",
        "        corpus = list()\n",
        "        for indicies in tensor:\n",
        "            document = list(map(lambda index: self.id2word[index.item()], indicies))\n",
        "            corpus.append(document)\n",
        "\n",
        "        return corpus\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "OUPIwl8VNm2o"
      },
      "execution_count": 220,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "oew13bY-Nm83"
      },
      "execution_count": 220,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def indices2embeddings(tensor, word_embedding):\n",
        "    for sentence_tensor in tensor:\n",
        "        sentence_embeddings = []\n",
        "        for index in sentence_tensor:\n",
        "            if index < len(word_embedding.vectors) and index >= 2:\n",
        "                word_embed = word_embedding.vectors[index-2]\n",
        "                sentence_embeddings.append(word_embed)\n",
        "            #else:\n",
        "                #print(f\"Index '{index}' out of range of the embedding vocabulary.\")\n",
        "        sentence_embeddings_tensor = torch.stack(sentence_embeddings)\n",
        "        print(sentence_embeddings_tensor)\n",
        "        print(\"Size :\", sentence_embeddings_tensor.size())"
      ],
      "metadata": {
        "id": "cs0J-e5O_Irv"
      },
      "execution_count": 221,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 222,
      "metadata": {
        "id": "r4oM-dAhOuZb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b07523b0-9e49-4222-d7bf-5a0cf041cca6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['iu', 'nhất', 'thế_giới', '😊'],\n",
              " ['béo', 'có', 'tội_gì', 'chứ', '😞'],\n",
              " ['tao', 'hiểu', ':))', 'và', 'tao', 'đã', 'chấm_dứt', 'ngay', '😏']]"
            ]
          },
          "metadata": {},
          "execution_count": 222
        }
      ],
      "source": [
        "corpus_sample = [\"iu nhất thế giới😊\",\n",
        "                 \"béo có tội gì chứ😞\",\n",
        "                 \"tao hiểu :)) và tao đã chấm dứt ngay😏\"]\n",
        "\n",
        "Vocabulary.tokenize_corpus(corpus_sample)"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "92F39QYXbD7u"
      },
      "execution_count": 222,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Ac4Od2rqeTL4"
      },
      "execution_count": 222,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 223,
      "metadata": {
        "id": "AjQyzXf-mKt5"
      },
      "outputs": [],
      "source": [
        "vocab = Vocabulary()\n",
        "\n",
        "# create vocabulary from pretrained word2vec\n",
        "words_list = list(word_embedding.stoi.keys())\n",
        "for word in words_list:\n",
        "    vocab.add(word)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "vocab.__len__()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QnVnzcCrUcuh",
        "outputId": "3ed8ef6b-613a-4dbe-961b-ac0cd8eca0a9"
      },
      "execution_count": 224,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6252"
            ]
          },
          "metadata": {},
          "execution_count": 224
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Check if a word is in vocab\n",
        "\n",
        "vocab.__contains__(\"'cộng_đồng'\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0Xht6ttlY91n",
        "outputId": "e5edf5a9-7721-4e21-f835-6793a0b02508"
      },
      "execution_count": 225,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 225
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "QDJo3ifKUc0D"
      },
      "execution_count": 225,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# test the vocabulary\n",
        "tensor = vocab.corpus_to_tensor(corpus_sample)\n",
        "corpus = vocab.tensor_to_corpus(tensor)\n",
        "\" \".join(corpus[0])\n",
        "# >> 'Với cộng_đồng người Bách Việt trước đây , việc <unk> mèo cũng có_thể theo cách_thức như_vậy .'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "eVfQj7qiUZVC",
        "outputId": "8ebf480e-1648-47c4-b56b-8742071a36df"
      },
      "execution_count": 226,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'iu nhất <unk> 😊'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 226
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tensor"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z1-UIJ8E50Oo",
        "outputId": "b00edabe-197a-40ba-deb4-dd002140cb38"
      },
      "execution_count": 227,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[tensor([ 672,  153,    1, 1850]),\n",
              " tensor([   1,    4,    1,   35, 1011]),\n",
              " tensor([ 187,  179,   49,   41,  187,   60,    1,  473, 3662])]"
            ]
          },
          "metadata": {},
          "execution_count": 227
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "indices2embeddings(tensor, word_embedding)"
      ],
      "metadata": {
        "id": "bEtM7v_N6KAv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "166c075d-988c-4f62-e6dd-3ea8ddda27f7"
      },
      "execution_count": 228,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[-0.0442,  0.1712,  0.0355,  0.0547,  0.0596, -0.2660,  0.1879,  0.4132,\n",
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            "          0.0334, -0.0593,  0.0762,  0.0068]])\n",
            "Size : torch.Size([3, 100])\n",
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            "          5.8969e-02,  2.8114e-02, -8.1219e-02,  8.8379e-02,  1.1699e-02]])\n",
            "Size : torch.Size([3, 100])\n",
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            "         -0.0796,  0.1020, -0.2147, -0.1780, -0.0947, -0.0237,  0.3142,  0.0339,\n",
            "          0.1332, -0.1274, -0.0669,  0.3816,  0.0962, -0.1899, -0.1100, -0.4487,\n",
            "          0.0496, -0.2343, -0.0892,  0.1315,  0.2779,  0.0383, -0.2885, -0.0747,\n",
            "          0.1611,  0.1508,  0.1031, -0.3107, -0.1054,  0.0358, -0.3287,  0.1544,\n",
            "          0.1675, -0.1273, -0.3386,  0.0547, -0.0353,  0.1244, -0.0555, -0.0535,\n",
            "         -0.3052,  0.1904,  0.0531,  0.2353, -0.2211,  0.2134, -0.4268,  0.1449,\n",
            "          0.2787, -0.1834,  0.3236,  0.1544, -0.0069,  0.1901, -0.3726,  0.1100,\n",
            "         -0.0506,  0.0497, -0.3141,  0.2794, -0.0116,  0.0642,  0.0357,  0.1898,\n",
            "          0.2649,  0.0222,  0.2273,  0.1448,  0.0565, -0.0423,  0.3393,  0.1240,\n",
            "          0.0650, -0.1698,  0.1901, -0.0064],\n",
            "        [-0.0813,  0.2440,  0.0357,  0.0711,  0.0783, -0.3449,  0.2588,  0.5278,\n",
            "         -0.3154, -0.0822, -0.0561, -0.3899, -0.1095,  0.1353, -0.0148, -0.1824,\n",
            "          0.0838, -0.2838, -0.0454, -0.3615,  0.0798,  0.0096,  0.0131, -0.2390,\n",
            "         -0.0854,  0.0953, -0.2104, -0.1948, -0.0813, -0.0306,  0.3158,  0.0211,\n",
            "          0.1259, -0.1431, -0.0702,  0.3769,  0.1079, -0.1649, -0.1061, -0.4315,\n",
            "          0.0519, -0.2282, -0.0755,  0.1237,  0.2865,  0.0243, -0.3060, -0.0491,\n",
            "          0.1685,  0.1385,  0.1202, -0.3062, -0.0850,  0.0289, -0.3373,  0.1567,\n",
            "          0.1637, -0.1074, -0.3370,  0.0673, -0.0234,  0.1093, -0.0516, -0.0356,\n",
            "         -0.2998,  0.1879,  0.0480,  0.2557, -0.2218,  0.2081, -0.4191,  0.1431,\n",
            "          0.2796, -0.1882,  0.3301,  0.1404, -0.0013,  0.2044, -0.3578,  0.0921,\n",
            "         -0.0581,  0.0367, -0.3342,  0.2873, -0.0095,  0.0705,  0.0576,  0.1837,\n",
            "          0.2665,  0.0366,  0.2240,  0.1646,  0.0584, -0.0297,  0.3480,  0.1288,\n",
            "          0.0685, -0.1460,  0.1859, -0.0028],\n",
            "        [-0.0491,  0.1954,  0.0367,  0.0630,  0.0532, -0.2751,  0.1888,  0.4393,\n",
            "         -0.2372, -0.0526, -0.0500, -0.3434, -0.0976,  0.1092, -0.0081, -0.1511,\n",
            "          0.0568, -0.2519, -0.0159, -0.2826,  0.0684,  0.0223,  0.0052, -0.1953,\n",
            "         -0.0548,  0.0864, -0.1636, -0.1423, -0.0793, -0.0293,  0.2507,  0.0152,\n",
            "          0.1132, -0.1218, -0.0485,  0.2979,  0.0920, -0.1584, -0.0927, -0.3595,\n",
            "          0.0255, -0.1867, -0.0642,  0.1005,  0.2370,  0.0251, -0.2341, -0.0605,\n",
            "          0.1381,  0.1130,  0.0981, -0.2516, -0.0841,  0.0328, -0.2654,  0.1291,\n",
            "          0.1458, -0.0964, -0.2806,  0.0527, -0.0087,  0.0970, -0.0606, -0.0326,\n",
            "         -0.2415,  0.1702,  0.0389,  0.1887, -0.1694,  0.1657, -0.3554,  0.0995,\n",
            "          0.2187, -0.1690,  0.2462,  0.1355, -0.0055,  0.1548, -0.3057,  0.1012,\n",
            "         -0.0349,  0.0330, -0.2579,  0.2390, -0.0227,  0.0556,  0.0199,  0.1655,\n",
            "          0.2105,  0.0192,  0.1798,  0.1226,  0.0330, -0.0257,  0.2635,  0.1110,\n",
            "          0.0497, -0.1406,  0.1442, -0.0026],\n",
            "        [ 0.0021,  0.0247, -0.0007,  0.0008,  0.0092, -0.0418,  0.0151,  0.0515,\n",
            "         -0.0233, -0.0041, -0.0048, -0.0497, -0.0159,  0.0147, -0.0123, -0.0205,\n",
            "         -0.0020, -0.0226, -0.0031, -0.0307, -0.0011, -0.0030,  0.0061, -0.0171,\n",
            "         -0.0121,  0.0160, -0.0244, -0.0088, -0.0115, -0.0084,  0.0254, -0.0040,\n",
            "          0.0141, -0.0205, -0.0035,  0.0415,  0.0192, -0.0104, -0.0160, -0.0443,\n",
            "         -0.0040, -0.0318,  0.0014,  0.0067,  0.0347,  0.0113, -0.0380,  0.0040,\n",
            "          0.0240,  0.0134,  0.0077, -0.0252, -0.0059,  0.0076, -0.0254,  0.0100,\n",
            "          0.0207, -0.0071, -0.0399,  0.0044, -0.0045,  0.0037, -0.0150,  0.0036,\n",
            "         -0.0276,  0.0156,  0.0025,  0.0317, -0.0249,  0.0294, -0.0503,  0.0065,\n",
            "          0.0317, -0.0189,  0.0320,  0.0075,  0.0036,  0.0175, -0.0383,  0.0142,\n",
            "          0.0021,  0.0015, -0.0360,  0.0325, -0.0032,  0.0012,  0.0035,  0.0189,\n",
            "          0.0314, -0.0053,  0.0300,  0.0084,  0.0134, -0.0104,  0.0259,  0.0041,\n",
            "          0.0159, -0.0123,  0.0221,  0.0024]])\n",
            "Size : torch.Size([8, 100])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JqryaYlKzrUC"
      },
      "source": [
        "# Dataset"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "7ISVBtofEt2s"
      },
      "execution_count": 228,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 229,
      "metadata": {
        "id": "uRlIfvhsXqKL"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import torch\n",
        "from torch.utils.data import Dataset\n",
        "\n",
        "\n",
        "class Dataset(Dataset):\n",
        "    \"\"\" Load dataset from file csv\"\"\"\n",
        "\n",
        "    def __init__(self, vocab, csv_fpath=None, tokenized_fpath=None):\n",
        "        \"\"\"\n",
        "        @param vocab (Vocabulary)\n",
        "        @param csv_fpath (str)\n",
        "        @param tokenized_fpath (str)\n",
        "        \"\"\"\n",
        "        self.vocab = vocab\n",
        "        self.pad_idx = vocab[\"<pad>\"]\n",
        "        df = pd.read_csv(csv_fpath)\n",
        "        self.sentiments_list = list(df.sentiment)\n",
        "        self.reviews_list = list(df.vi_review)\n",
        "\n",
        "        sentiments_type = list(set(self.sentiments_list))\n",
        "        sentiments_type.sort()\n",
        "\n",
        "        self.sentiment2id = {sentiment: i for i, sentiment in enumerate(sentiments_type)}\n",
        "\n",
        "        if tokenized_fpath:\n",
        "            self.tokenized_reviews = torch.load(tokenized_fpath)\n",
        "        else:\n",
        "            self.tokenized_reviews = self.vocab.tokenize_corpus(self.reviews_list)\n",
        "\n",
        "        self.tensor_data = self.vocab.corpus_to_tensor(self.tokenized_reviews, is_tokenized=True)\n",
        "        self.tensor_label = torch.tensor([self.sentiment2id[sentiment] for sentiment in self.sentiments_list],\n",
        "                                         dtype=torch.float64)\n",
        "\n",
        "    def __len__(self):\n",
        "        return len(self.tensor_data)\n",
        "\n",
        "    def __getitem__(self, idx):\n",
        "        return self.tensor_data[idx], self.tensor_label[idx]\n",
        "\n",
        "    def collate_fn(self, examples):\n",
        "        examples = sorted(examples, key=lambda e: len(e[0]), reverse=True)\n",
        "\n",
        "        reviews = [e[0] for e in examples]\n",
        "        reviews = torch.nn.utils.rnn.pad_sequence(reviews,\n",
        "                                                  batch_first=False,\n",
        "                                                  padding_value=self.pad_idx)\n",
        "        reviews_lengths = torch.tensor([len(e[0]) for e in examples])\n",
        "        sentiments = torch.tensor([e[1] for e in examples])\n",
        "\n",
        "        return {\"reviews\": (reviews, reviews_lengths), \"sentiments\": sentiments}"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "metadata": {
        "id": "lFJialcPBws6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "outputId": "754c9ff3-900d-4f6b-c3fc-d1d8e542b6e0"
      },
      "execution_count": 230,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-abefebd9-0b64-433e-8a90-12d87a199317\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-abefebd9-0b64-433e-8a90-12d87a199317\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving Dataset.csv to Dataset (2).csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 231,
      "metadata": {
        "id": "5BzdXxCpAeAX"
      },
      "outputs": [],
      "source": [
        "dataset = Dataset(vocab, \"Dataset.csv\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 232,
      "metadata": {
        "id": "4h1FtIow6AGa"
      },
      "outputs": [],
      "source": [
        "torch.save(dataset.tokenized_reviews, \"tokenized.pt\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "fA72kB3-rODP"
      },
      "execution_count": 232,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LS2X1qbk_p3o"
      },
      "source": [
        "# Split data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 233,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KFonmRJB3B-c",
        "outputId": "68de5000-b9bb-46e7-fe7b-223f65beb277"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5125, 1050)"
            ]
          },
          "metadata": {},
          "execution_count": 233
        }
      ],
      "source": [
        "from torch.utils.data import random_split\n",
        "\n",
        "\n",
        "split_rate = 0.83\n",
        "full_size = len(dataset)\n",
        "train_size = (int)(split_rate * full_size)\n",
        "valid_size = (full_size - train_size)\n",
        "\n",
        "train_dataset, valid_dataset = random_split(dataset,\n",
        "                                                          lengths=[train_size, valid_size])\n",
        "\n",
        "len(train_dataset), len(valid_dataset)"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "5VKmWZw8DLG8"
      },
      "execution_count": 233,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "wwDxxRdkCJ53"
      },
      "execution_count": 233,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from torch.utils.data import DataLoader\n",
        "\n",
        "BATCH_SIZE = 100\n",
        "train_dataloader = DataLoader(train_dataset,\n",
        "                              batch_size=BATCH_SIZE,\n",
        "                              shuffle=True,\n",
        "                              collate_fn=dataset.collate_fn)\n",
        "valid_dataloader = DataLoader(valid_dataset,\n",
        "                              batch_size=BATCH_SIZE,\n",
        "                              shuffle=True,\n",
        "                              collate_fn=dataset.collate_fn)\n"
      ],
      "metadata": {
        "id": "RGVzmSwI7VkA"
      },
      "execution_count": 234,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "\n",
        "# Save train_dataloader\n",
        "torch.save(train_dataloader, 'train_dataloader.pth')\n",
        "# Save valid_dataloader\n",
        "torch.save(valid_dataloader, 'valid_dataloader.pth')"
      ],
      "metadata": {
        "id": "cnVuWdXPksDt"
      },
      "execution_count": 235,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Q7vsJDE4ksPr"
      },
      "execution_count": 235,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "1YrAt_R6r13W"
      },
      "execution_count": 235,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IbrDDCwvA1QS"
      },
      "source": [
        "# Convolutional Neural Network model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 268,
      "metadata": {
        "id": "bKebhWVcY4ZT"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "\n",
        "class CNN(nn.Module):\n",
        "    def __init__(self, input_dim, embedding_dim, hidden_dim, n_layers, bidirectional, dropout, pad_idx):\n",
        "        super().__init__()\n",
        "\n",
        "        self.embedding = nn.Embedding(input_dim, embedding_dim, padding_idx=pad_idx)\n",
        "        self.conv = nn.Conv1d(in_channels=embedding_dim, out_channels=hidden_dim, kernel_size=3)\n",
        "        self.fc = nn.Linear(hidden_dim, 1)\n",
        "        self.dropout = nn.Dropout(dropout)\n",
        "\n",
        "    def forward(self, text, text_lengths):\n",
        "        # text = [sent len, batch size]\n",
        "        embedded = self.embedding(text)\n",
        "        # embedded = [sent len, batch size, emb dim]\n",
        "        embedded = embedded.permute(1, 2, 0)\n",
        "        # embedded = [batch size, emb dim, sent len]\n",
        "        padded_embedded = F.pad(embedded, (0, 0, 3, 0), mode='constant', value=0)\n",
        "        conved = self.conv(embedded)\n",
        "        # conved = [batch size, hidden dim, sent len - filter_size + 1]\n",
        "        pooled = F.max_pool1d(conved, conved.shape[2])\n",
        "        pooled = pooled.squeeze(2)\n",
        "        # pooled = [batch size, hidden dim]\n",
        "        return self.fc(pooled)"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "hfR8B5DXxmJo",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3028a8b4-c141-4b3b-cbc7-dd67cd9a76cd"
      },
      "execution_count": 286,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Lớp Embedding đứng trước lớp Convolution.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X2W8eI0y99PO"
      },
      "source": [
        "# Train the model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 237,
      "metadata": {
        "id": "QY0P8iXT_kic"
      },
      "outputs": [],
      "source": [
        "import torch.optim as optim\n",
        "\n",
        "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "6mfuURfO6TRw"
      },
      "execution_count": 237,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 269,
      "metadata": {
        "id": "IZRefC7b_xz7"
      },
      "outputs": [],
      "source": [
        "def binary_accuracy(preds, y):\n",
        "    \"\"\"\n",
        "    Returns accuracy per batch, i.e. if you get 8/10 right, this returns 0.8, NOT 8\n",
        "    @param preds (torch.Tensor): shape = [batch_size]\n",
        "    @param y (torch.Tensor): shape = [batch_size]\n",
        "    @return acc (torch.Tensor): shape = [1]\n",
        "    \"\"\"\n",
        "    #round predictions to the closest integer\n",
        "    rounded_preds = torch.round(torch.sigmoid(preds))\n",
        "    correct = (rounded_preds == y).float() #convert into float for division\n",
        "    acc = correct.sum() / len(correct)\n",
        "    return acc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 271,
      "metadata": {
        "id": "rW_HPt7s_2J6"
      },
      "outputs": [],
      "source": [
        "def train(model, dataloader, optimizer, criterion, device):\n",
        "    \"\"\"\n",
        "    @param model (CNN)\n",
        "    @param dataloader (DataLoader)\n",
        "    @param optimizer (torch.optim)\n",
        "    @param criterion (torch.nn.modules.loss)\n",
        "    @param device (torch.device)\n",
        "    @return epoch_loss (float): model's loss of this epoch\n",
        "    @return epoch_acc (float): model's accuracy of this epoch\n",
        "    \"\"\"\n",
        "    epoch_loss = 0\n",
        "    epoch_acc = 0\n",
        "\n",
        "    model.train()\n",
        "\n",
        "    for batch in dataloader:\n",
        "\n",
        "        optimizer.zero_grad()\n",
        "        reviews, reviews_lengths = batch[\"reviews\"]\n",
        "        reviews = reviews.to(device)\n",
        "        predictions = model(reviews, reviews_lengths).squeeze(1)\n",
        "        sentiments = batch[\"sentiments\"].to(device)\n",
        "        loss = criterion(predictions, sentiments)\n",
        "        acc = binary_accuracy(predictions, sentiments)\n",
        "\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "\n",
        "        epoch_loss += loss.item()\n",
        "        epoch_acc += acc.item()\n",
        "\n",
        "    batch_num = len(dataloader)\n",
        "    return epoch_loss / batch_num, epoch_acc / batch_num"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 273,
      "metadata": {
        "id": "9TViPLND_4WS"
      },
      "outputs": [],
      "source": [
        "def evaluate(model, dataloader, criterion, device):\n",
        "    \"\"\"\n",
        "    @param model (CNN)\n",
        "    @param dataloader (DataLoader)\n",
        "    @param criterion (torch.nn.modules.loss)\n",
        "    @param device (torch.device)\n",
        "    @return epoch_loss (float): model's loss of this epoch\n",
        "    @return epoch_acc (float): model's accuracy of this epoch\n",
        "    \"\"\"\n",
        "    epoch_loss = 0\n",
        "    epoch_acc = 0\n",
        "\n",
        "    model.eval()\n",
        "\n",
        "    with torch.no_grad():\n",
        "        for batch in dataloader:\n",
        "\n",
        "            reviews, reviews_lengths = batch[\"reviews\"]\n",
        "            reviews = reviews.to(device)\n",
        "            predictions = model(reviews, reviews_lengths).squeeze(1)\n",
        "\n",
        "            sentiments = batch[\"sentiments\"].to(device)\n",
        "            loss = criterion(predictions, sentiments)\n",
        "            acc = binary_accuracy(predictions, sentiments)\n",
        "\n",
        "            epoch_loss += loss.item()\n",
        "            epoch_acc += acc.item()\n",
        "\n",
        "    batch_num = len(dataloader)\n",
        "    return epoch_loss / batch_num, epoch_acc / batch_num"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 274,
      "metadata": {
        "id": "ns4tZi3gPqwE"
      },
      "outputs": [],
      "source": [
        "import time\n",
        "\n",
        "def epoch_time(start_time, end_time):\n",
        "    elapsed_time = end_time - start_time\n",
        "    elapsed_mins = int(elapsed_time / 60)\n",
        "    elapsed_secs = int(elapsed_time - (elapsed_mins * 60))\n",
        "    return elapsed_mins, elapsed_secs"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "XJxTObSH5s_m"
      },
      "execution_count": 241,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Q14hMdccl1ck"
      },
      "execution_count": 241,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Tuning RNN : optim, loss function, lr"
      ],
      "metadata": {
        "id": "Mkfq9gfkl2YK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "learning_rate = [0.001, 0.005, 0.01]\n",
        "\n",
        "criterias = [nn.BCEWithLogitsLoss(),\n",
        "            nn.BCELoss()]\n",
        "\n",
        "optimizers = {\n",
        "    'Adam': optim.Adam,\n",
        "    'SGD': optim.SGD,\n",
        "    'RMSprop': optim.RMSprop\n",
        "}\n"
      ],
      "metadata": {
        "id": "xGvqjgEUl1fb"
      },
      "execution_count": 275,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "htjL05nZl1iC"
      },
      "execution_count": 242,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "bestModelCNN = []"
      ],
      "metadata": {
        "id": "rTYx-jqk_UD_"
      },
      "execution_count": 276,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "bu_AYdLe_UHP"
      },
      "execution_count": 277,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def Tuning_model_CNN(learning_rate, criterias, optimizers, train_dataloader, valid_dataloader, device, num_epochs=5):\n",
        "\n",
        "  best_valid_loss = float(\"inf\")\n",
        "\n",
        "  for criteria in criterias:\n",
        "    for lr in learning_rate:\n",
        "      for optimizer_name, optimizer_fn in optimizers.items():\n",
        "\n",
        "        print(f\"Training with criteria = {criteria}, optimizer = {optimizer_name}, lr = {lr}\")\n",
        "\n",
        "        # Initialize model\n",
        "        INPUT_DIM = len(vocab)\n",
        "        EMBEDDING_DIM = 100\n",
        "        HIDDEN_DIM = 256\n",
        "        N_LAYERS = 2\n",
        "        BIDIRECTIONAL = True\n",
        "        DROPOUT = 0.3\n",
        "        PAD_IDX = vocab[\"<pad>\"]\n",
        "\n",
        "\n",
        "        model = CNN(INPUT_DIM,\n",
        "                    EMBEDDING_DIM,\n",
        "                    HIDDEN_DIM,\n",
        "                    N_LAYERS,\n",
        "                    BIDIRECTIONAL,\n",
        "                    DROPOUT,\n",
        "                    PAD_IDX)\n",
        "        # model.embedding.weight.data.copy_(word_embedding.vectors)\n",
        "        # model.embedding.weight.data[UNK_IDX] = torch.zeros(EMBEDDING_DIM)\n",
        "        # model.embedding.weight.data[PAD_IDX] = torch.zeros(EMBEDDING_DIM)\n",
        "\n",
        "\n",
        "        # Define criterion\n",
        "        criterion = criteria\n",
        "\n",
        "        # Define optimizer\n",
        "        optimizer = optimizer_fn(model.parameters(), lr=lr)\n",
        "\n",
        "        train_losses = []\n",
        "        train_accs = []\n",
        "        val_losses = []\n",
        "        val_accs = []\n",
        "\n",
        "        # GPU\n",
        "        model = model.to(device)\n",
        "        criterion = criterion.to(device)\n",
        "\n",
        "        for epoch in range(num_epochs):\n",
        "\n",
        "          start_time = time.time()\n",
        "\n",
        "          train_loss, train_acc = train(model, train_dataloader, optimizer, criterion, device)\n",
        "          valid_loss, valid_acc = evaluate(model, valid_dataloader, criterion, device)\n",
        "\n",
        "          train_losses.append(train_loss)\n",
        "          train_accs.append(train_acc)\n",
        "          val_losses.append(valid_loss)\n",
        "          val_accs.append(valid_acc)\n",
        "\n",
        "          end_time = time.time()\n",
        "\n",
        "          epoch_mins, epoch_secs = epoch_time(start_time, end_time)\n",
        "\n",
        "          if valid_loss < best_valid_loss:\n",
        "              best_valid_loss = valid_loss\n",
        "              torch.save(model.state_dict(), \"BestModelCNN.pt\")\n",
        "              bestModelCNN.append(f\"criteria = {criteria}, optimizer = {optimizer_name}, lr = {lr}\")\n",
        "\n",
        "\n",
        "          print(f\"Epoch: {epoch+1:02} | Epoch Time: {epoch_mins}m {epoch_secs}s\")\n",
        "          print(f\"\\tTrain Loss: {train_loss:.3f} | Train Acc: {train_acc*100:.2f}%\")\n",
        "          print(f\"\\t Val. Loss: {valid_loss:.3f} |  Val. Acc: {valid_acc*100:.2f}%\")\n",
        "\n",
        "\n",
        "\n",
        "        # Vẽ biểu đồ\n",
        "        plt.figure(figsize=(10, 5))\n",
        "        plt.subplot(1, 2, 1)\n",
        "        plt.plot(range(1, num_epochs + 1), train_losses, label='Train Loss')\n",
        "        plt.plot(range(1, num_epochs + 1), val_losses, label='Val Loss')\n",
        "        plt.xlabel('Epochs')\n",
        "        plt.ylabel('Loss')\n",
        "        plt.title(f\"Training with criteria = {criteria}, optimizer = {optimizer_name}, lr = {lr}\")\n",
        "        plt.legend()\n",
        "\n",
        "        plt.subplot(1, 2, 2)\n",
        "        plt.plot(range(1, num_epochs + 1), train_accs, label='Train Acc')\n",
        "        plt.plot(range(1, num_epochs + 1), val_accs, label='Val Acc')\n",
        "        plt.xlabel('Epochs')\n",
        "        plt.ylabel('Accuracy')\n",
        "        plt.title(f\"Training with criteria = {criteria}, optimizer = {optimizer_name}, lr = {lr}\")\n",
        "        plt.legend()\n",
        "\n",
        "        plt.tight_layout()\n",
        "        plt.show()\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "oG9vjs1El1k2"
      },
      "execution_count": 278,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Tuning_model_CNN(learning_rate, criterias, optimizers, train_dataloader, valid_dataloader, device, num_epochs=5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "eYtnG1i8l1nl",
        "outputId": "1bf3239f-fb41-4f3c-f4af-e0a8c99a5908"
      },
      "execution_count": 279,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = Adam, lr = 0.001\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.584 | Train Acc: 68.63%\n",
            "\t Val. Loss: 0.537 |  Val. Acc: 70.55%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.450 | Train Acc: 79.88%\n",
            "\t Val. Loss: 0.493 |  Val. Acc: 73.82%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.362 | Train Acc: 85.25%\n",
            "\t Val. Loss: 0.455 |  Val. Acc: 77.27%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.287 | Train Acc: 89.33%\n",
            "\t Val. Loss: 0.447 |  Val. Acc: 78.45%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.231 | Train Acc: 91.83%\n",
            "\t Val. Loss: 0.443 |  Val. Acc: 79.91%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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kScTHx6fYh/vevXvodDri4+OpXbs2oaGh7N+/n/nz57N37159vp4+fTpxcXGsWLGC6tWrM336dGbOnEnz5s0pX748T58+1cf13XffAe+Xrx89esTgwYMZPHgwAQEBrF+/nrFjx1KtWjUmTJhAVFRUqvn6TWNZlClTBp1Ox/79+2ndujWQfL7etm0bAI0bNzbY3tbWlvz586NWq+ncufMb87VarWb69OkG+fqXX34BEj4P1KxZk7t37/Lo0SMqVqyo3y4xXz99+hQzMzNmz56dYr4+d+4cN27ckHydCsnXkq8lX0u+Tk5my9fJPfcLFy7E3d2dFi1aYGJiwl9//cXgwYPR6XQMGTLEYN3r16/TpUsXBgwYQLdu3fT5etGiRYwfP15flJg+fTodOnTgypUrqNXp135j8ODBODk56fP1m6R13ClbW1vMzc1TvD+x8PRqHgXImzcv+fPnT7UwdfbsWaytrSlVqpTB8sqVK+vvTylfv7rujh070nQ87+Rdm+Yk17y2Tp06CqAsWrQoyfrJNUcbMGCAYmVlZdAvt2fPnoqrq6v+78Qmp7ly5VKePn2qX759+3YF0DdNVZTkm5EBipmZmUGzxPPnzyuAMnfuXP2y5s2bK1ZWVsrdu3f1y65du6bvX/wmWq1WsbOzU8aMGaMoSkIzqly5cint27dXNBqN8vz5c0VRFGX27NmKWq1Wnj17ZhDfq02kUmtinZZjSc7y5csVQJk9e3aS+xKb3CY+13Z2dsqjR48M1km8b8WKFfplKTWx9vPzM+jnnWjnzp1Jlru6uiqAsnPnziT7eb25XXR0dJJ+tLdu3VLMzc2VKVOmpHzw/y/x/ZnaLS19MlPaV6lSpZSbN2/q10t8n86ZMyfVfSYez5ti8/f316/75ZdfKoBy584dRVEUZf369YqFhYUSExOj7NixQ9FoNPp+s4lNv48cOaLf/vVzLbUm1kCS57l8+fKKl5eXwTJSaWK9bds2BVCmTZtmsLxdu3aKSqXSv79Pnz6tAMrw4cMN1uvVq1eSOFesWJHkvEmpia+np6fSrFmzFONTlLQ1sS5Xrpzi7OysPHnyRL/s/PnzilqtVnr06KFfZm9v/8bn4+zZswqgbNq0KcV14uLiFJVKpYwaNSrFdRo1aqSUKlUqxfvfpFWrVoqZmZlBE+179+4ptra2Su3atfXLEp9nLy8vg+4CP/30kwIo27dv1y9L6fnfv3+/Aij79+/XL0s8n9atW6dfdvnyZX23kmPHjumX79q1K8m1KLnX/1WhoaFKwYIFFQ8PD30T3fS6TiUn8f2T2u3V8+9NNm/erADKtWvXFEVRlIiICMXCwiLJdaVVq1aKhYWFQVPdgIAARaVSJblW16pVK0m+9vb2VooUKWKQrxOPvVWrVvp8nfgaaDQaJX/+/Pp1E8fqsLOze+d8rVar9deAxNcVUH7++Wf9eqnl67TcmjRpoihKyvm6efPmCqBcvHjRIL6JEycqlSpVUqpWrZpqvua1LhGJ+RpQxo4dqyiKopw8eVIBlNWrV+vXS8zX9erVUwCDz0iJ+Trx+mhubi75+h33Jfla8rXk6wSSrzNPvtZoNEmu1cl9h07M169KPPajR4/qlyW+Bq9341m8eHGS1/ZtvH7NT3xda9asadCF6E3Smq9fff8kJzEXBwcHJ7kvMV+/SbNmzZI8l4qS0E08tXydKPEan9y4funRJSrdW9iYm5vTu3fvJMstLS31/3/+/DkxMTHUqlWLxYsXc/nyZTw9Pd+4344dOxpUNmvVqgUk/IqTmgYNGhj8IlW2bFns7Oz022q1Wvbu3Uvr1q0NfvUpWrQoTZo04a+//nrj/tVqNdWrV+fQoUNAwujRT548YezYsWzZsgV/f38aNmyIn58fZcqUwcHBIdWY3/VYUrJlyxYcHR0ZNmxYkvteb0Letm3bNLUsSsmmTZuwt7enYcOGBtVTLy8vbGxs2L9/P126dNEvL1y4MN7e3qnu99XqqlarJSwsDBsbG0qUKGHQXDUls2bNStJ0Mjmp/fKXqFChQixduhSA+Ph4rly5wk8//USTJk3w8/PDycmJiIgIgLf6tQ6gf//+tG/fPsny0qVL6/9fs2ZNZsyYgZ+fH506deLIkSN4eXlhZmZGtWrV9M2qGzZsyJEjR7CwsEi2Kvw2Bg4caPB3rVq1kv3F9k127NiBRqPh888/N1g+atQoNm/ezL///svQoUP1Xf1ebaIIMGzYsPeazcDBwYFLly5x7do1ihUr9k77uH//PufOnWPMmDHkzJlTv7xs2bI0bNjQoMru4ODA8ePHuXfvXrLvrcRf5Hbt2kXTpk2xsrJKss7Tp09RFOWNv+7kyJHjnZq3arVadu/eTatWrShSpIh+uYuLC126dGHp0qVERERgZ2env69///4Gv2YNGjSI8ePHs2PHDlq0aPHWMQDY2NgYzKZRokQJHBwcyJcvn8Evhon/T8u1P/H4OnfuzPPnz9m3bx/W1tZAxl2nAHr06JHir+OvejUvvsnatWupWLGi/ldIW1tbmjVrpv81M/E4d+3aRatWrQya6pYqVYqCBQsSFBRksE+1Wq3P14mtGerUqcOuXbuIjY3Vx6bT6ShevDjt2rVj27ZtXL58Wf8auLi4oNFo9PssV64ckPAcvmu+dnFxSdKNwNLSUt98Pi35OrXuEuPHj+fRo0dAyvn6+vXrAAa/8CaysLDQX9vfxNraOtl8HRERwcuXLwH0/76a3xLzdfXq1dm/fz8vX77U3/96vi5VqpTk6zSQfC35WvJ1AsnXhjJbvvb29k7SUuPVx349X4eHh+vfl5Bw3alWrZr+78TX4JNPPjF4rFdfm8QucOmhX79+Bp8L3iStXRvd3d3feH9yeTRRWvL1qzn29W1f3X9qj/Omfb2vdC/Y5MuXDzMzsyTLL126xDfffMO+ffuSPHGv9vtMyatvMkB/IUxLQn9928TtE7d99OgRL1++TNIkD0h2WXJq1aqlb2bp5+eHi4sLFSpUwNPTEz8/Pxo2bMjhw4fp0KFDmvb3rseSkhs3blCiRAmDvn0pKVy48DvHBwnNisPDw5P9oAvoPyi/7ePpdDp+/vlnFixYwK1btwz6Yr+pO1giLy+vND1OWllbW+v7IkNC0/maNWtSsWJFfvjhB2bNmqVPms+fP3+rfRcrVsxg38mpUaMGKpWKI0eO6D8AJjYRdnBwoHTp0vplR44coVKlSsmem2llYWGR5ItBWt57rwsKCiJv3rxJPhQnNkVM/GIZFBSEWq1O8v5I6zmZkilTptCyZUuKFy9OmTJlaNy4Md27dzdoTp6WYwCSbWZbqlQpdu3aRVRUFNbW1vz000/07NmTAgUK4OXlRdOmTenRo4f+w1bhwoUZOXIks2fPZu3atdSqVYsWLVrQrVs3gyQMJBkz4PX7Uhu/IzmhoaG8ePEixWPR6XSEhIQYJMzXPzjb2Njg4uKSZLytt5E/f/4k8dvb21OgQIEkyyBt135An3f++ecfgy/PGXWdAihSpIjBh+n3ERYWxo4dOxg6dKi+iAAJ5/+WLVu4evUqxYsXJzQ0lJcvXyb7pcbBwSFJwSY8PBy1Wk2OHDmSNAc/efIk8+fPN8jX3bp102+X+BpYWVkRExOj3y7xevf6B9u3ydeJH9BfZW9v/1b5OrVr54kTJ1LN14ljxLx6fImio6PT9OE9uWbmDg4ORERE6LdP/PfVx0nM17GxsQbrJOd9fgACydeSr99M8rXk6+RIvk5eeuTrEiVKJCnYHDlyhIkTJ+Lv758kX79esHn9e2Life/72qTV2zz3qV030yq5PJooLfna0tIyxW1f3X9qj/PqOukt3Qs2yQUaFhZGnTp1sLOzY8qUKbi5uWFhYcGZM2f46quvkvS3Tk5K1bo3XRDTY9u0qlmzJnFxcfj7++Pn56f/RbFWrVr4+flx+fJlQkND9cvf1Yc4lvd9s+l0OpydnVMcZOv1DxFpfbzvv/+eb7/9lj59+jB16lRy5syJWq1m+PDhaXoPPX36VP8B+E0sLS2TJN608vLywt7eXt/aqmTJkkBCX9X0litXLkqWLMnhw4eJjIzkwoULTJw4UX9/9erVOXz4MHfu3CE4OJiuXbu+1+OltWKe2dWuXZsbN26wfft2du/eza+//sqcOXNYtGgRffv2TffH69ChA7Vq1eKPP/5g9+7dzJgxgx9//JGtW7fSpEkTIOHX5F69eulj+vzzz5k+fTrHjh0jf/785MyZE5VK9cbE+uzZM/04GllRSu+v97nmbdu2jR9//JGpU6cmGYsko65TAJGRkURGRqa6nkajSbV1xKZNm4iJiWHWrFnMmjUryf1r165l8uTJaY4NEgoC58+fx9zcnDlz5lCgQAHMzMzYsWMHc+bMoUOHDjg4ODBlyhS+++47ihQpQps2bZLk65T6vaf0RSQtr1ly26pUqrfKcQ8ePHjj/aVKlUo1Xyf2vb9//36SD7r379/X921/k8QBil89psTCReKv9y4uLvp9vu7+/fvkzJnzjb/WpTYmUGokX0u+zswkX2dOkq+Tl1H5un79+pQsWZLZs2cnydevX08z4rV5G2/z3KeWqxPZ29u/cb+v5tF3ydcuLi7s378/Sb5OzMvpla/fR7oXbJJz4MABnjx5wtatWw0G3L1169aHePhUOTs7Y2FhYVANTZTcsuQkzgLg5+eHn5+ffvaI2rVrs3TpUnx9ffV/v8m7VNzTws3NjePHjxMXF/feH/ASpRSrm5sbe/fupUaNGulaady8eTP16tVj2bJlBsvDwsLSlPjatGnDwYMHU12vZ8+e79WEV6vV6i/+xYsXp0SJEmzfvp2ff/45TYMjvo2aNWuyfPlydu/ejVarpXr16vr7qlevzvr16/Wjw6fW5DOj3nuvc3V1Ze/evTx//tzgV7vLly/r70/8V6fTcevWLYNfIdJ6Tr7peHLmzEnv3r3p3bu3fiDwSZMmpfkDYGKMV65cSXLf5cuXcXR0NGgp4OLioh9I9dGjR1SoUIHvvvtO/wEQwMPDAw8PD7755huOHj1KjRo1WLRoEdOmTcPExAQ3N7c3XjNv3bqVatfS5Dg5OWFlZZXisajV6iQJ8Nq1a9SrV0//d2RkJPfv36dp06b6ZR/q/ZSSq1ev0rNnT1q1aqWfrfBVGXWdApg5c2aaPpS5urqm+ivn2rVrKVOmjMGXu0SLFy9m3bp1TJ48GScnJywtLbl27VqS9V6dEQngr7/+QlEUChYsyIABA/TL9+/fDyR8mdi2bRu1a9fWD6iblsEWP4S05OvED1VvYmJikmq+Bjh16pTBh73nz59z584d+vfvn+p7PD4+nsDAQIOuMYm/zCV2H8uXLx9OTk6cOnVKv05ivn706JF+vfcl+Tp5kq/fTPK15OsPQfL1/7z+2v7111/ExMTw559/GrSeSczXWVlacjUkTIbz6oxhr0vMk6/n63v37unz9ZuUK1eOX3/9NUm+Pn78uMH+k8vXiU6cOJFu+To5H6Rgk1jVe7WKFxsby4IFCz7Ew6dKo9HQoEEDtm3bZtBv9fr16/z7779p2oeFhQWVKlVi/fr1BAcHG/xi9/LlS3755Rfc3NxSfXMmJo3XP2C/r7Zt2/LPP/8wb968JKPSv2vTzFdjfbVZdocOHViwYAFTp07l+++/N9gmPj6eyMjId2rGrdFoklSCN23axN27d9PU7Da9+8QnZ//+/URGRhok4smTJ9OpUyf69u3Lb7/9lqRb2u7du4mNjX3rqUIh4UPd0qVLmTlzJsWKFTOo/levXp3IyEgWLFigH2fpTRL7Yqf3e+91TZs2ZcmSJcybN49x48bpl8+ZMweVSqX/UOTt7c3XX3/NggULDGaimDt3bpoex9raOtljefLkiUGTfBsbG4oWLUpISEiaj8HFxYVy5cqxatUqxo0bp38///fff+zevVvffSTxy8CrvwA7OzuTN29e/Re3iIgIrKysDN4XHh4eqNVqg2aX1apVM5ha81Xh4eHcuHHjrWb/SKTRaGjUqBHbt2/n9u3b+tkyHj58yLp166hZs6ZBf3iAJUuW0Lt3b33xd+HChcTHxxt8oE3p+f8QIiMjad26Nfny5WPVqlXJXt8y6joF6dcnPiQkhEOHDjF58mTatWuX5P7Y2Fi6du3K8ePHqVKlCt7e3mzbto3g4GD9B7vAwEB9955Eyf3SFh4ezooVK/R/v3qt1el0WSpfp6Vf/Pjx41PN16ampixZsoQBAwbon7OTJ0+iUqlo166dvqAQEhJCdHQ0Li4uBue6Wq1mwYIFzJs3D0h4Tp8/f46VlZXB9bht27asWrWKkJAQChQooM/Xjx8/NphqPHEfkq//R/J12FvH8TYkX0u+zmiSrw3z9a5duwy2S+479Ov5OqtKrzFs3N3dKVmyZJJ8vXDhQn2+ThQeHs79+/cN8nXLli0ZMWJEkny9aNEi8uXL98Z8DeDr68vVq1ffada3tPogBZvq1auTI0cOevbsyeeff45KpWLNmjXp3gzrfUyaNIndu3dTo0YNBg0ahFarZd68eZQpU4Zz586laR+1atXihx9+wN7eHg8PDyDhYl+iRAmuXLnyxupgosR+219//TWdOnXC1NSU5s2bJ9uv/2306NGD1atXM3LkSE6cOEGtWrWIiopi7969DB48mJYtW771PhNj/fzzz/H29kaj0dCpUyfq1KnDgAEDmD59OufOnaNRo0aYmppy7do1Nm3axM8//5zsxSw1n376KVOmTKF3795Ur16dixcvsnbt2jT3PU3vPvHh4eH89ttvwP8GMVy4cCGWlpaMHTtWv17Hjh25ePEi3333HWfPnqVz5864urry5MkTdu7cia+vL+vWrTPY95kzZ/T7fpWbm5vBYGKJScbf3z/J+6t48eI4Ojri7++Ph4dHqsnM0tKS0qVLs2HDBooXL07OnDkpU6YMZcqUeZunBUiock+bNi3J8rp169K8eXPq1avH119/ze3bt/H09GT37t1s376d4cOH6/ste3l50bZtW3x8fHjy5Il+mtCrV68Cqf8i5OXlxcKFC5k2bRpFixbF2dmZTz75hNKlS1O3bl28vLzImTMnp06d0k/j+brZs2cnGVRQrVYzfvx4ZsyYQZMmTahWrRqfffaZfppQe3t7Jk2aBCT8Gp8/f37atWuHp6cnNjY27N27l5MnT+qby+7bt4+hQ4fSvn17ihcvTnx8PGvWrEGj0dC2bVv947Zs2ZI1a9bo+0C/au/evSiKkuQ87tWrF6tWreLWrVv6D3bJmTZtGnv27KFmzZoMHjwYExMTFi9eTExMDD/99FOS9WNjY6lfv75+SsgFCxZQs2ZNgwEMU3r+P4TJkycTEBDAN998w/bt2w3uSzyHMuo6BenXJ37dunX6aXWT07RpU0xMTFi7di1VqlRh8uTJ7Ny5k1q1ajF48GDi4+OZO3cuOXPm5MmTJ/rtGjVqhEqlIigoiPnz5xMZGcnSpUtxdnbm/v372Nvb6/N1REQER44ceeexzW7fvv3e46K9LrV8nZZ+8b6+vqnm67Zt29KiRQsaNWqkH2DTz8+Pfv36UapUKX3LjKFDh3LhwgUGDhzIzJkz9fna09OT+fPnExcXR6VKldi2bZt+woVXi2bjx49n06ZN1KtXjy+++IKIiAhMTEyIj49n37596HQ6fb4uVaoUjo6O3Lt3D0gYMDLxWtu9e3d9a4LXSb6WfJ0SydeTAMnXkq/fT3rla3d3dy5cuKDfrlGjRpiZmdG8eXMGDBiQJF+np8R8/b4tF9MqvcawAZgxY4ZBvv7vv/+YN28effv2NZiu+48//qB3794GrXby58/P8OHDmTFjhkG+9vPzY+3atW/M15GRkcyYMQMPD48kky6tWbOGoKAg/bhDhw4dSlO+Tta7Ti+V0rTe7u7uya5/5MgRpWrVqoqlpaWSN29eZcyYMfqpxl6dUiylab1nzJiRZJ+8NkVWStOEJjdF3+vTkSmKovj6+irly5dXzMzMFDc3N+XXX39VRo0apVhYWKTwLBj6559/FF6ZLjRR3759FUBZtmxZqsegKIoydepUJV++fIparTaY+u5tjiU5L168UL7++mulcOHCiqmpqZInTx6lXbt2+qkB3/RcJzdNaHx8vDJs2DDFyckp2WljlyxZonh5eSmWlpaKra2t4uHhoYwZM0a5d++eQewpTdmY3DSho0aNUlxcXBRLS0ulRo0air+/v1KnTp1kpyPMSK9PE6pSqZScOXMqLVq0UE6fPp3sNr6+vkrLli0VZ2dnxcTERHFyclKaN29uMLViatOEJvc6582bVwGUJUuWJLmvRYsWCqAMGjQoyX2vn2uKoihHjx5VvLy8FDMzM4P3Zs+ePRVra+sk+0jpnEvpNnXqVEVRFOX58+fKiBEjlLx58yqmpqZKsWLFlBkzZuinrE0UFRWlDBkyRMmZM6diY2OjtGrVSrly5YoCKD/88IN+veSmiXzw4IHSrFkzxdbWVgH075Fp06YplStXVhwcHBRLS0ulZMmSynfffWcw7eWbpnnUaDT69fbu3avUqFFDsbS0VOzs7JTmzZsrAQEB+vtjYmKUL7/8UvH09FRsbW0Va2trxdPTU1mwYIF+nZs3byp9+vRR3NzcFAsLCyVnzpxKvXr1lL179xo8FzExMYqjo6P+OXxVx44dlZo1ayZZ3rZtW8XS0lJ59uxZkvted+bMGcXb21uxsbFRrKyslHr16hlMDfnq83zw4EGlf//+So4cORQbGxula9euBtOlvun5T2ma0ORyR0rXh9evha+//onT2qblHHrf61RG8vDwUAoWLPjGderWras4OzsrcXFxiqIoysGDB/XncJEiRZRFixYplSpVSnKelilTRjE3N1csLCyUQoUKKT/++KN+OunNmzfr87VGo1GKFCmSJF8DSsmSJQ2uIYlTr776XF28eFH/3KclX5coUUL/d+Lr6uLiYrR8/ccffyjlypVTzM3NFUCpVauWwbVi6tSpSo4cOfTH+Gq+Hjx4sPL9998rrq6uipmZmeLu7q44Ojomex3/77//lEaNGilWVlaKg4OD0rFjR2X48OFJ8nXlypVTfG8nvjaSrw1Jvk4g+VryteTrjJNe+Tq58/TPP/9UypYtm2y+fvU8SutroCjJf+dLzNeJ01i/SUrTep88eTLVbTPKq/k6f/78yjfffGNwrVCU/8X5+lThWq02Sb7+7bffkn2c1/N1165dlQcPHiRZ7/Xck1y+Tqt3LthkFy1btlSKFi1q7DCEEP/v7NmzCpDihfRjNmXKFKVw4cJKfHy8ftn9+/cVCwsLZdu2bUnWd3Z2VkaPHp1uj58ZErLIWubPn69YW1sn+2EmvUm+FiJzkXwt+VpkHR8yX4u3k/wUD9lU4vzqia5du8aOHTvSdX56IUTavX5OAvj4+KBWq1MdwPtjNGLECCIjI/n999/1y3x8fPDw8EjSvPrSpUu8fPmSr7766kOHKYTe/v37+fzzz8mdO3e67lfytRCZi+RrQ5KvRVaTUflavL8PMoZNVlGkSBF69epFkSJFCAoKYuHChZiZmTFmzBhjhyZEtvTTTz9x+vRp6tWrh4mJCf/++y///vsv/fv3TzITQnZgY2PDo0ePDJb98MMPya7r7u5ORETEhwhLiBRt2rQpQ/Yr+VqIzEXytSHJ1yKryah8Ld6fFGxe0bhxY9avX8+DBw8wNzenWrVqfP/99wZTFAohPpzq1auzZ88epk6dSmRkJAULFmTSpEl8/fXXxg5NCGFEkq+FyFwkXwshRMZQKUommqpJCCGEEEIIIYQQQiBj2AghhBBCCCGEEEJkMlKwSaP58+dTqFAhLCwsqFKlCidOnHjj+mFhYQwZMgQXFxfMzc0pXrw4O3bseK99CiGEEEIIIYQQInuQMWzSYMOGDYwcOZJFixZRpUoVfHx88Pb25sqVKzg7OydZPzY2loYNG+Ls7MzmzZvJly8fQUFBODg4vPM+X6fT6bh37x62traoVKr0PFwhhBAiVYqi8Pz5c/LmzYtaLb//vInkbCGEEMYi+TprkzFs0qBKlSpUqlSJefPmAQkfvAoUKMCwYcMYO3ZskvUXLVrEjBkzuHz5Mqampumyz9fduXMnW466L4QQInMJCQkhf/78xg4jU5OcLYQQwtgkX2dN0sImFbGxsZw+fZpx48bpl6nVaho0aIC/v3+y2/z5559Uq1aNIUOGsH37dpycnOjSpQtfffUVGo3mnfYZExNDTEyM/u/EOltISAh2dnbpcahCCCFEmkVERFCgQAFsbW2NHUqml/gcSc4WQgjxoUm+ztqkYJOKx48fo9VqyZ07t8Hy3Llzc/ny5WS3uXnzJvv27aNr167s2LGD69evM3jwYOLi4pg4ceI77XP69OlMnjw5yXI7Ozv58CeEEMJopItP6hKfI8nZQgghjEXyddYkndgygE6nw9nZmSVLluDl5UXHjh35+uuvWbRo0Tvvc9y4cYSHh+tvISEh6RixEEIIIYQQQgghMhNpYZMKR0dHNBoNDx8+NFj+8OFD8uTJk+w2Li4umJqaotFo9MtKlSrFgwcPiI2Nfad9mpubY25u/p5HI4QQQgghhBBCiKxAWtikwszMDC8vL3x9ffXLdDodvr6+VKtWLdltatSowfXr19HpdPplV69excXFBTMzs3fapxBCCCGEEEIIIbIPaWGTBiNHjqRnz55UrFiRypUr4+PjQ1RUFL179wagR48e5MuXj+nTpwMwaNAg5s2bxxdffMGwYcO4du0a33//PZ9//nma9ymEEFmRTqcjNjbW2GGIdPB6S1GRseTcyXrkHBFCCJHRpGCTBh07diQ0NJQJEybw4MEDypUrx86dO/WDBgcHBxvMaV+gQAF27drFiBEjKFu2LPny5eOLL77gq6++SvM+hRAiq4mNjeXWrVsGrQtF1ubg4ECePHlkoMIMJudO1iXniBBCiIykUhLnhxZZSkREBPb29oSHh8uME0IIo1MUheDgYOLi4sibN69BEVtkPYqi8OLFCx49eoSDgwMuLi5J1pE8lHZveq7k3Mma0nKOCCFEZiD5OmuTFjZCCCHeW3x8PC9evCBv3rxYWVkZOxyRDiwtLQF49OgRzs7O0vUjg8i5k3XJOSKEECKjyc84Qggh3ptWqwUSBmoXH4/EAkJcXJyRI/l4ybmTtck5IoQQIiNJwUYIIUS6kXEcPi7yen448lxnTfK6CSGEyEhSsBFCCCGEEEIIIYTIZKRgI4QQQqSjQoUK4ePjY+wwhMhy5NwRQgghDEnBRgghRLakUqneeJs0adI77ffkyZP079//vWKrW7cuw4cPf699CJFRMvO5k2j9+vVoNBqGDBmSLvsTQgghjEFmiRJCCJEt3b9/X///DRs2MGHCBK5cuaJfZmNjo/+/oihotVpMTFJPm05OTukbqBCZTFY4d5YtW8aYMWNYvHgxs2bNwsLCIt32LYQQQnwo0sJGCCFEtpQnTx79zd7eHpVKpf/78uXL2Nra8u+//+Ll5YW5uTmHDx/mxo0btGzZkty5c2NjY0OlSpXYu3evwX5f79ahUqn49ddfad26NVZWVhQrVow///zzvWLfsmUL7u7umJubU6hQIWbNmmVw/4IFCyhWrBgWFhbkzp2bdu3a6e/bvHkzHh4eWFpakitXLho0aEBUVNR7xSOyl8x+7ty6dYujR48yduxYihcvztatW5Oss3z5cv055OLiwtChQ/X3hYWFMWDAAHLnzo2FhQVlypTh77//fvcnTAghhHhHUrARXHv4nDX+t40dhhDiI6IoCi9i441yUxQl3Y5j7Nix/PDDDwQGBlK2bFkiIyNp2rQpvr6+nD17lsaNG9O8eXOCg4PfuJ/JkyfToUMHLly4QNOmTenatStPnz59p5hOnz5Nhw4d6NSpExcvXmTSpEl8++23rFy5EoBTp07x+eefM2XKFK5cucLOnTupXbs2kNAyonPnzvTp04fAwEAOHDhAmzZt0vU5E+9Hzh1D73LurFixgmbNmmFvb0+3bt1YtmyZwf0LFy5kyJAh9O/fn4sXL/Lnn39StGhRAHQ6HU2aNOHIkSP89ttvBAQE8MMPP6DRaN7vCRFCiLdw/VEkv/rdNHYYIhOQLlHZ3J1nL2g29zBxWh0lXeyoVCinsUMSQnwEXsZpKT1hl1EeO2CKN1Zm6ZPepkyZQsOGDfV/58yZE09PT/3fU6dO5Y8//uDPP/80+IX+db169aJz584AfP/99/zyyy+cOHGCxo0bv3VMs2fPpn79+nz77bcAFC9enICAAGbMmEGvXr0IDg7G2tqaTz/9FFtbW1xdXSlfvjyQULCJj4+nTZs2uLq6AuDh4fHWMYiMI+eOobc9d3Q6HStXrmTu3LkAdOrUiVGjRnHr1i0KFy4MwLRp0xg1ahRffPGFfrtKlSoBsHfvXk6cOEFgYCDFixcHoEiRIu/yFAghxFuJ1+rYG/iQNceCOHL9CQA1izlSMo+dkSMTxiQtbLK5/DmsaFUuL4oCozaeJyom3tghCSFEplGxYkWDvyMjIxk9ejSlSpXCwcEBGxsbAgMDU20lULZsWf3/ra2tsbOz49GjR+8UU2BgIDVq1DBYVqNGDa5du4ZWq6Vhw4a4urpSpEgRunfvztq1a3nx4gUAnp6e1K9fHw8PD9q3b8/SpUt59uzZO8UhxJsY69zZs2cPUVFRNG3aFABHR0caNmzI8uXLAXj06BH37t2jfv36yW5/7tw58ufPry/WCCFERgt9HsNc32vU+mk/A387w5HrT1CroGHp3KhQGTs8YWTSwkbw7aelOXL9CcFPX/DDv5eZ2qqMsUMSQmRxlqYaAqZ4G+2x04u1tbXB36NHj2bPnj3MnDmTokWLYmlpSbt27YiNjX3jfkxNTQ3+VqlU6HS6dIvzVba2tpw5c4YDBw6we/duJkyYwKRJkzh58iQODg7s2bOHo0ePsnv3bubOncvXX3/N8ePH9a0PhHHJuWPobc+dZcuW8fTpUywtLfXLdDodFy5cYPLkyQbLk5Pa/UIIkR4UReF00DNW+wfx73/3idMmdEnNZW1Gx0oF6FKlIPlzWBk5SpEZSMFGYGthyk/tytL11+OsORaEt3seahZzNHZYQogsTKVSpVvXiszkyJEj9OrVi9atWwMJrQZu3779QWMoVaoUR44cSRJX8eLF9eNsmJiY0KBBAxo0aMDEiRNxcHBg3759tGnTBpVKRY0aNahRowYTJkzA1dWVP/74g5EjR37Q4xDJk3Pn3T158oTt27fz+++/4+7url+u1WqpWbMmu3fvpnHjxhQqVAhfX1/q1auXZB9ly5blzp07XL16VVrZCCHS3YvYeLafu8dq/yAC70fol5cv6ECPaq409XDB3ETGzBL/8/F9IhDvpEZRR3pUc2W1fxBjNp9n54ja2FmYpr6hEEJkI8WKFWPr1q00b94clUrFt99+m2EtZUJDQzl37pzBMhcXF0aNGkWlSpWYOnUqHTt2xN/fn3nz5rFgwQIA/v77b27evEnt2rXJkSMHO3bsQKfTUaJECY4fP46vry+NGjXC2dmZ48ePExoaSqlSpTLkGIRI9CHOnTVr1pArVy46dOiASmXYjaBp06YsW7aMxo0bM2nSJAYOHIizszNNmjTh+fPnHDlyhGHDhlGnTh1q165N27ZtmT17NkWLFuXy5cuoVKp3GnNKCCEAbj2OYo1/EJtOh/A8OmEICnMTNS3L5aVHtUKUyWdv5AhFZiUFG6E3tklJDl4NJejJC6b+FcCM9p6pbySEENnI7Nmz6dOnD9WrV8fR0ZGvvvqKiIiI1Dd8B+vWrWPdunUGy6ZOnco333zDxo0bmTBhAlOnTsXFxYUpU6bQq1cvABwcHNi6dSuTJk0iOjqaYsWKsX79etzd3QkMDOTQoUP4+PgQERGBq6srs2bNokmTJhlyDEIk+hDnzvLly2ndunWSYg1A27Zt6d69O48fP6Znz55ER0czZ84cRo8ejaOjI+3atdOvu2XLFkaPHk3nzp2JioqiaNGi/PDDD+kaqxDi46fVKey7/IjV/rfxu/ZYv9w1lxXdq7rSzis/DlZmRoxQZAUqRebyzJIiIiKwt7cnPDwcO7v0Gzn81O2ntF/sj6LAsp4VqV8qd7rtWwjx8YqOjtbPwmJhYWHscEQ6edPrmlF56GP0pudKzp2sTV4/IcTrnkTGsOFUCGuPBXM37CUAKhV8UsKZ7tVcqV3MCbX6ww0mLPk6a5MWNsJAxUI56VerCEsO3WTs1ovsHp6DHNZS+RVCCCGEEEKI5CiKwtmQMNb4B/HPhfvEahO6fOawMqVDpQJ0q+JKgZwyiLB4e1KwEUmMbFicfZcfcf1RJBP+vMTczuWNHZIQQgghhBBCZCrRcVr+PHeP1cdu89/d/3Xz9MxvT/dqhfi0rAsW6TgDn8h+pGAjkrAw1TC7gyetFxzlr/P3aOyeh2ZlXYwdlhBCCCGEEEIYXdCTKH47FsTGU3cIfxkHgJmJmuZl89KjmiueBRyMG6D4aEjBRiSrbH4HhtR145d91/lm20UqF86Jk625scMSQgghhBBCiA9Oq1M4ePURq/2DOHg1lMSRYPPnsKRbVVc6VCxAThlKQqQzKdiIFA39pBh7Ax8RcD+CcVsvsrSHV7IzLwghhBBCCCHEx+hZVCwbT4Xw2/EgQp6+1C+vW8KJ7lVdqVvCGc0HHERYZC9SsBEpMjNRM7ujJ83nHmZv4EO2nrlLW6/8xg5LCCGEEEIIITLU+ZAwVvsH8deFe8TGJwwibG9pSoeK+elW1RXXXNZGjlBkB1KwEW9UMo8dwxsUZ8auK0z66xLVi+bCxd7S2GEJIYQQQgghRLqKjtPy94X7rPG/zfk74frlZfLZ0aNqIZp75sXSTAYRFh+OFGxEqgbULsKegIecCwljzOYLrO5TWbpGCSGEEEIIIT4KIU9f8NvxIDaeDOHZi/8fRFijpllZF7pXc6V8AQf5/iOMQgo2IlUmGjWzOnjS9Gc//K49Zt2JYLpWcTV2WEIIIYQQQgjxTnQ6hUPXQlnjH8S+K4/0gwjnc7CkS5WCdKxUAEcbmXRFGJcUbESauDnZMKZxSab+HcB3/wRSq6gTBXNZGTssIYQwurp161KuXDl8fHyMHYoQWYqcO0IIYwh/Ecem0yH8diyI209e6JfXKuZIj2qF+KSkDCIsMg+1sQMQWUfv6oWoUjgnL2K1jN58Hp1OMXZIQgjxzpo3b07jxo2Tvc/Pzw+VSsWFCxfe+3FWrlyJg4PDe+9HiMziQ507iV6+fEnOnDlxdHQkJiYm3fYrhMhe/rsbzlebL1Bl+l6m/RPI7ScvsLUwoU+NwuwbVYc1n1WhYencUqwRmYq0sBFpplarmNneE2+fQ5y49ZQVR2/zWc3Cxg5LCCHeyWeffUbbtm25c+cO+fMbzoC3YsUKKlasSNmyZY0UnRCZ14c+d7Zs2YK7uzuKorBt2zY6duyYbvsWQnzcYuK17Lh4nzX+QZwJDtMvL+ViR49qrrQslxcrM/lKLDIvaWEj3kqBnFZ83awUAD/tvMyN0EgjRySEEO/m008/xcnJiZUrVxosj4yMZNOmTXz22Wc8efKEzp07ky9fPqysrPDw8GD9+vXpGkdwcDAtW7bExsYGOzs7OnTowMOHD/X3nz9/nnr16mFra4udnR1eXl6cOnUKgKCgIJo3b06OHDmwtrbG3d2dHTt2pGt8QrzuQ587y5Yto1u3bnTr1o1ly5Yluf/SpUt8+umn2NnZYWtrS61atbhx44b+/uXLl+Pu7o65uTkuLi4MHTr0neIQQmQdd8Ne8tPOy1Sfvo8RG85zJjgMU42KFp552TywGjs+r0nnygWlWCMyPXmHirfWpXJBdv73AL9rjxm18TybB1bDRCO1PyHEKxQF4l6kvl5GMLWCNMzkYGJiQo8ePVi5ciVff/21fvaHTZs2odVq6dy5M5GRkXh5efHVV19hZ2fHP//8Q/fu3XFzc6Ny5crvHapOp9MXaw4ePEh8fDxDhgyhY8eOHDhwAICuXbtSvnx5Fi5ciEaj4dy5c5iamgIwZMgQYmNjOXToENbW1gQEBGBjY/PecQkjknPHwI0bN/D392fr1q0oisKIESMICgrC1TVh8oO7d+9Su3Zt6taty759+7Czs+PIkSPEx8cDsHDhQkaOHMkPP/xAkyZNCA8P58iRI+/w5AghMjudTuHIjces9g/CN/AhiaM3uNhb0KVyQTpVLoiTrQwiLLIWKdiIt6ZSqfipXVkazTnEuZAwFh+6yZB6RY0dlhAiM4l7Ad/nNc5jj78HZtZpWrVPnz7MmDGDgwcPUrduXSChS0fbtm2xt7fH3t6e0aNH69cfNmwYu3btYuPGjelSsPH19eXixYvcunWLAgUKALB69Wrc3d05efIklSpVIjg4mC+//JKSJUsCUKxYMf32wcHBtG3bFg8PDwCKFCny3jEJI5Nzx8Dy5ctp0qQJOXLkAMDb25sVK1YwadIkAObPn4+9vT2///67vpBZvHhx/fbTpk1j1KhRfPHFF/pllSpVSvPjCyEyv/CXcWw5fYffjgVx83GUfnl1t1z0qOZKg1K55cdlkWXJO1e8Exd7SyY1dwfAZ+9VAu9HGDkiIYR4eyVLlqR69eosX74cgOvXr+Pn58dnn30GgFarZerUqXh4eJAzZ05sbGzYtWsXwcHB6fL4gYGBFChQQF+sAShdujQODg4EBgYCMHLkSPr27UuDBg344YcfDLp6fP7550ybNo0aNWowceLEdB3oVYg3+RDnjlarZdWqVXTr1k2/rFu3bqxcuRKdTgfAuXPnqFWrlr5Y86pHjx5x79496tev/z6HKoTIpALvRzBu60Wqfu/LlL8DuPk4ChtzE3pWc2XvyNqs61eVxmVcpFgjsjRpYSPeWZsK+dh56QF7Ah4yauN5tg2pgZmJXBCFECR0rRh/z3iP/RY+++wzhg0bxvz581mxYgVubm7UqVMHgBkzZvDzzz/j4+ODh4cH1tbWDB8+nNjY2IyIPFmTJk2iS5cu/PPPP/z7779MnDiR33//ndatW9O3b1+8vb35559/2L17N9OnT2fWrFkMGzbsg8Un0pmcO3q7du3i7t27SQYZ1mq1+Pr60rBhQywtLVPc/k33CSGypth4HTsvPWCN/21O3n6mX14ity3dq7nSunw+rM3lK674eMi3a/HOVCoV37f2IIeVKQH3I5i375qxQxJCZBYqVULXCmPc0jAGx6s6dOiAWq1m3bp1rF69mj59+ujH5Dhy5AgtW7akW7dueHp6UqRIEa5evZpuT1OpUqUICQkhJCREvywgIICwsDBKly6tX1a8eHFGjBjB7t27adOmDStWrNDfV6BAAQYOHMjWrVsZNWoUS5cuTbf4hBHIuaO3bNkyOnXqxLlz5wxunTp10g8+XLZsWfz8/IiLi0uyva2tLYUKFcLX1/etHlcIkfncD3/J7N1XqP7DPj5ff5aTt59holbRrKwLG/pXZefwWnSr6irFGvHRkYKNeC9OtuZMa5UwdsL8Azc4HxJm3ICEEOIt2djY0LFjR8aNG8f9+/fp1auX/r5ixYqxZ88ejh49SmBgIAMGDDCYwSmttFptki+dgYGBNGjQAA8PD7p27cqZM2c4ceIEPXr0oE6dOlSsWJGXL18ydOhQDhw4QFBQEEeOHOHkyZOUKpUwW9/w4cPZtWsXt27d4syZM+zfv19/X3Y1f/58ChUqhIWFBVWqVOHEiRMprhsXF8eUKVNwc3PDwsICT09Pdu7c+V77zE4y8twJDQ3lr7/+omfPnpQpU8bg1qNHD7Zt28bTp08ZOnQoERERdOrUiVOnTnHt2jXWrFnDlStXgIQWarNmzeKXX37h2rVrnDlzhrlz56b3UyGEyACKonD0+mMGrjlNzR/388u+6zyOjMHZ1pzhDYpxZOwnzO9SgSpFcumLxUJ8bKRgI95bs7IuNPfMi1anMGrTeaLjtMYOSQgh3spnn33Gs2fP8Pb2Jm/e/w34+s0331ChQgW8vb2pW7cuefLkoVWrVm+9/8jISMqXL29wa968OSqViu3bt5MjRw5q165NgwYNKFKkCBs2bABAo9Hw5MkTevToQfHixenQoQNNmjRh8uTJQEIhaMiQIZQqVYrGjRtTvHhxFixYkC7PSVa0YcMGRo4cycSJEzlz5gyenp54e3vz6NGjZNf/5ptvWLx4MXPnziUgIICBAwfSunVrzp49+877zG4y6txZvXo11tbWyY4/U79+fSwtLfntt9/IlSsX+/btIzIykjp16uDl5cXSpUv1Y9r07NkTHx8fFixYgLu7O59++inXrkmLYCEys+fRcaw6epuGcw7R5dfj7Lz0AK1OoUrhnMzvUoEjYz9heIPi5LazMHaoQmQ4laIoirGDEG8vIiICe3t7wsPDsbOzM3Y4PIuKpZHPIUKfx9C/dhHGN83ev/AKkd1ER0dz69YtChcujIWFfID6WLzpdc1seQigSpUqVKpUiXnz5gEJ06YXKFCAYcOGMXbs2CTr582bl6+//pohQ4bol7Vt21ZfDHiXfSbnTc+VnDtZm7x+QqSfqw+fs9r/Nn+cuUtUbMIPwNZmGtpUyE+3qq6UyGNr5AizpsyYr0XaSSc/kS5yWJvxQxsPPlt1iqV+N2lYOjeVCuU0dlhCCCGyidjYWE6fPs24ceP0y9RqNQ0aNMDf3z/ZbWJiYpJ8yba0tOTw4cPvvE8hhBBpF6fVsfvSQ1b73+b4raf65UWdbejx/4MI21oknQVOiOxCCjYi3dQvlZv2XvnZdPoOozed598vamFlJm8xIYQQGe/x48dotVpy585tsDx37txcvnw52W28vb2ZPXs2tWvXxs3NDV9fX7Zu3YpWq33nfUJCISgmJkb/d0RExLselhBCfJQeRkSz/kQw608E8zAi4XqpUatoVDo33au5Uk3GpRECkIKNSGffNi/NkeuPCXrygh/+vcyUlmWMHZIQQgiRrJ9//pl+/fpRsmRJVCoVbm5u9O7dm+XLl7/XfqdPn64fZ0gIIUQCRVE4fuspa/yD2HXpAfG6hJE5HG3M6VK5AJ2rFMTF3tLIUQqRucigwyJd2VmY8lM7TwBW+wdx+NpjI0ckhBAiO3B0dESj0SSZiejhw4fkyZMn2W2cnJzYtm0bUVFRBAUFcfnyZWxsbChSpMg77xNg3LhxhIeH62+vTtsuhBDZTWRMPGuOBdHYx49OS47xz8X7xOsUKhXKwS+dy3N07CeMbFRCijVCJEMKNmn0NlN6rly5EpVKZXB7vY98r169kqzTuHHjjD6MD6JmMUe6V3UFYMzm80RExxk5IiGEEB87MzMzvLy88PX11S/T6XT4+vpSrVq1N25rYWFBvnz5iI+PZ8uWLbRs2fK99mlubo6dnZ3BTQghspvrj54zcft/VP3el2+3/ceVh8+xNNXQpUpB/v2iFpsGVqeFZ17MTOQrqRApkS5RaZA4peeiRYuoUqUKPj4+eHt7c+XKFZydnZPdxs7OjitXruj/Tq4PZuPGjVmxYoX+b3Nz8/QP3kjGNinJoWuhBD15wbS/A/StboQQHzeZePDjotPpjB3CWxk5ciQ9e/akYsWKVK5cGR8fH6KioujduzcAPXr0IF++fEyfPh2A48ePc/fuXcqVK8fdu3eZNGkSOp2OMWPGpHmf6UXOnawpq50jQmS0eK2OvYEPWe0fxNEbT/TLizhZ072qK2298mMngwgLkWZSsEmD2bNn069fP/2Hs0WLFvHPP/+wfPnyFKf0VKlUb2wuDQkFmtTWyaqszU2Y2d6TDov92XjqDt7ueahfKnfqGwohsiRTU1NUKhWhoaE4OTnJQIFZnKIoxMbGEhoailqtxszMzNghpUnHjh0JDQ1lwoQJPHjwgHLlyrFz5079oMHBwcGo1f/7JTc6OppvvvmGmzdvYmNjQ9OmTVmzZg0ODg5p3uf7knMna8qq54gQGSX0eQy/nwhm3Ylg7odHA6BWQYNSuelRrRA1isogwkK8C5UiP+m8UWxsLFZWVmzevJlWrVrpl/fs2ZOwsDC2b9+eZJuVK1fSt29f8uXLh06no0KFCnz//fe4u7vr1+nVqxfbtm3DzMyMHDly8MknnzBt2jRy5cqVbBzJzThRoEABwsPDM3VT6+/+CWCp3y2cbM3ZPbw2OazlA40QH6vIyEju3LkjLQU+IlZWVri4uCT7ZTQiIgJ7e/tMn4cyg9SeKzl3sq43nSNCfOwUReF00DNW+wfx73/3idMmXMNyWZvRqXIBulRxJZ+DjEtjbJKvszZpYZOKd5nSs0SJEixfvpyyZcsSHh7OzJkzqV69OpcuXSJ//vxAQneoNm3aULhwYW7cuMH48eNp0qQJ/v7+aDSaJPvMqjNOjGpUgv1XQrn+KJKJf17il87ljR2SECKD2NjYUKxYMeLiZNyqj4FGo8HExER+Ef0A5NzJmuQcEdnVi9h4tp29x5pjQQTej9Avr1DQgR7VCtHEIw/mJkm/zwgh3p60sEnFvXv3yJcvH0ePHjUYYHDMmDEcPHiQ48ePp7qPuLg4SpUqRefOnZk6dWqy69y8eRM3Nzf27t1L/fr1k9yfVVvYAJwPCaPNwqNodQrzu1SgWVkXY4ckhBDiPckvdmknz5UQ4mNwMzSSNceC2Hz6Ds+j4wGwMFXT0jMf3au5UiafvZEjFMmRHJS1SQubVLzrlJ6vMjU1pXz58ly/fj3FdYoUKYKjoyPXr19PtmBjbm6eZQcl9izgwOC6bszdd51vtl2kcuGcONlmzWMRQgghhBAiu9DqFHwDH7LmWBB+1x7rlxfKZUW3qq609yqAvZUMIixERpE51FLxPtOEJtJqtVy8eBEXl5Rblty5c4cnT568cZ2sbNgnxSjlYsezF3F8/cdF6acvhBBCCCFEJqUoCuuOB1P7p/30X3Mav2uPUamgQSlnVvWpzL5Rdelbq4gUa4TIYNLCJg3edprQKVOmULVqVYoWLUpYWBgzZswgKCiIvn37AgmDC06ePJm2bduSJ08ebty4wZgxYyhatCje3t5GO86MZGaiZnYHT1rMO8zugIf8cfYubSrkN3ZYQgghhBBCiFfcC3vJV1su6FvU5LAypWOlgnStUpACOa2MHJ0Q2YsUbNLgbacJffbsGf369ePBgwfkyJEDLy8vjh49SunSpYGEQeouXLjAqlWrCAsLI2/evDRq1IipU6dm2W5PaVHKxY7hDYozY9cVJv55iWpuuXCxl5HjhRBCCCGEMDZFUdh65i6T/rrE8+h4zE3UfOldgm5VXbEwlUGEhTAGGXQ4i8qqg0fFa3W0XeTP+ZAwahd3YlXvSjK7ghBCZEFZNQ8ZgzxXQojM7nFkDOO3XmR3QMK4neUKODCrgyduTjZGjky8L8lBWZuMYSM+KBONmlntPTE3UXPoaijrT4QYOyQhhBBCCCGyrZ3/3afRnEPsDniIqUbFl94l2DywmhRrhMgEpGAjPriizjZ86V0CgGn/BBDy9IWRIxJCCCGEECJ7CX8Rx/DfzzLwtzM8jYqlZB5btg+pyZB6RTHRyNdEITIDOROFUfSpUZjKhXPyIlbL6E3n0emkZ54QQgghhBAfwoErj2jkc5Bt5+6hVsGQem5sH1qD0nmly4wQmYkUbIRRqNUqZrbzxMpMw/FbT1l59LaxQxJCCCGEEOKjFhkTz7itF+m14iQPI2Io4mjNlkHV+dK7JOYmMrCwEJmNFGwEGGnc6YK5rBjftBQAP+68zI3QSKPEIYQQQgghxMfu2M0nNPY5xPoTwQD0rlGIfz6vRfmCOYwcmRAiJVKwEbB9CGwdAKFXP/hDd61SkFrFHImJ1zFq43nitboPHoMQQgghhBAfq+g4LVP/DqDz0mPcefaSfA6WrOtXhYnN3bE0k1Y1QmRmUrDJ7iLuw/nf4cLvML8ybOoNDy99sIdXqVT82LYsthYmnAsJY4nfzQ/22EIIIYQQQnzMzoeE0ewXP5YdvoWiQKdKBdg5vBbV3RyNHZoQIg2kYJPd2blA3z1QoimgwKWtsLA6/N4V7p37ICHkdbBkUnN3AObsucrlBxEf5HGFEEIIIYT4GMXG65i1+wptFh7lRmgUzrbmrOhViR/alsXWwtTY4Qkh0kgKNgLyeUHn9TDwMJRuCajg8t+wpA6sbQ8hJzM8hDYV8tGgVG7itAojN5wnNl66RgkhhBBCCPG2Lj+IoNX8I8zddx2tTqGFZ152j6hNvZLOxg5NCPGWpGAj/iePB3RYDYOPgUcHUKnh2m5Y1gBWt4TbRzLsoVUqFd+3KUMOK1MC7kcwb//1DHssIYQQQgghPjZancKCA9dpPvcwAfcjyGFlyvwuFfilc3kcrMyMHZ4Q4h1IwUYk5VwS2i6FoaegXDdQm8DNA7CyKSxvAjf2ZcjMUs62Fkxr5QHA/P3XuXAnLN0fQwghhBBCiI/NzdBI2i06yk87rxCnVWhQypldI2rTrKyLsUMTQrwHKdiIlOVyg1bzYdgZ8OoNGjMIPgprWsOvDeDqrnQv3DQr68KnZV3Q6hRGbjxPdJw2XfcvhBBCCCHEx0KnU1h55BZNf/HjbHAYtuYmzGhXlqU9KuJsa2Hs8IQQ70kKNiJ1OVyhuQ98fg6qDAQTC7h7CtZ1SBjnJvAv0KXfmDNTW5bB0cac648imbPnw081LoQQQgghRGZ359kLui07zqS/AoiO01GjaC52jqhN+4oFUKlUxg5PCJEOpGAj0s4+HzT5Eb64ANWHgak13D8PG7rBohpwcTPo3r9FTA5rM35ok9A1aonfTU7dfvre+xRCCCGEEOJjoCgKG0+F0NjHj6M3nmBpqmFKS3fW9KlCPgdLY4cnhEhHUrARb882NzSaBsMvQq1RYGYLjwJgy2cwvwqcWw/a+Pd6iAalc9POKz+KAqM2nedF7PvtTwghhBBCiKzuUUQ0fVedYszmC0TGxOPlmoMdX9SiR7VCqNXSqkaIj40UbMS7s84F9SfAiItQdxxY2MOTa7BtIMzzgtOrID72nXc/oXlp8tpbEPTkBT/+ezkdAxdCCCGEECJr+fvCPRr5HML38iPMNGrGNinJxgHVKOxobezQhBAZRAo24v1Z5oC6Y2H4f1B/Iljlgme34a/PYW4FOLEU4qLferd2Fqb81M4TgFX+QRy5/jidAxdCCCGEECJzexYVy9B1Zxi67ixhL+Jwz2vHX8NqMrCOGxppVSPER00KNiL9WNhBrZEJXaUafQc2uSE8BHaMhp89wX8+xL54q13WLOZIt6oFARiz+QIR0XEZEbkQQgghhBCZjm/gQxr5HOLvC/fRqFV8Xr8YfwyuQYk8tsYOTQjxAUjBRqQ/M2uoPhS+OA9NZoBdPoh8ALvGg48HHJ4DMc/TvLtxTUpRMKcVd8NeMu3vgAwMXAghhBBCCON7Hh3HmM3n+WzVKUKfx1DU2YY/BldnZMPimJnIVzghsgs520XGMbWEKv3h87PQ/GdwcIUXj2HvpITCzcGf4GVYqruxNjdhZntPVCrYeOoO+y4/zPDQhRBCCCGEMIaj1x/T2MePjafuoFJBv1qF+XtYTcrmdzB2aEKID0wKNiLjmZiDVy8YdhpaLYRcReHlM9j/XULhxncqvHjz1N2VC+fksxqFAfhqy0WeRb37YMZCCCGEEEJkNi9jtUz68xJdfj3O3bCXFMhpye/9qvJ1s9JYmGqMHZ4QwgikYCM+HI0plOsCQ05A22XgVApiIsBvJswpA7u/hchHKW4+2rsEbk7WhD6PYeKflz5g4EIIIYQQQmSc00HPaPqLHyuP3gaga5WC7PyiNlWK5DJuYEIIo5KCjfjw1BrwaAeDjkKHNZDHA+Ki4Ogv4FMW/h0LEfeSbGZhqmFWh3Jo1Cr+PH+PHRfvGyF4IYQQQggh0kdMvJYfd16m/aKj3HocRR47C1b1qcx3rT2wNjcxdnhCCCOTgo0wHrUaSreAAX7QeQPk84L4l3B8YcKsUn+PgLBgg03KFXBgcF03AL7Z9h+hz2OMEbkQQgghhBDv5dK9cFrOO8LCAzfQKdCmfD52Da9NneJOxg5NCJFJSMFGGJ9KBSUaQ19f6LYVClYDbSycWg6/lIftQ+DJDf3qwz4pRikXO55GxfL1HxdRFMWIwQshhBBCCJF28Vodc32v0XLeES4/eE4uazMWdavA7I7lsLcyNXZ4QohMRAo2IvNQqaBofeizE3r9A4XrgC4ezv4G8yrC1v4QegUzEzWz2ntiqlGxO+Ah287dNXbkQgghhBBCpOr6o0jaLjzKrD1XidcpeLvnZteI2jQu42Ls0IQQmZAUbETmVKgm9PwTPtsDRRuCooMLG2B+FdjYk9LqYIY3KA7AhO2XuB/+0sgBCyGEEEIIkTydTmHZ4Vs0+8WP83fCsbUwYU5HTxZ188LRxtzY4QkhMikp2IjMrUBl6LYZ+u2Hkp8CCgRsg0U1GHT/W9rkCeV5dDxfbZGuUUIIIYQQIvMJefqCzkuPMfXvAGLiddQu7sTuEbVpXT4/KpXK2OEJITIxKdiIrCFfBei0FgYeAffWgAr11R3MDvuCVWY/EXntCL+fDDF2lEIIIYQQQgCgKArrTwTT2OcQx289xcpMw3ety7CqdyVc7C2NHZ4QIguQueJE1pKnDLRfCXWvgN8suLiJOupz1DE/h/8/m3lkMRnnsg2MHaUQQgghhMjGHoRH89WWCxy8GgpA5UI5mdnek4K5rIwcmRAiK5EWNiJrcioBbZbA0FMo5bsTj4Zqqv9w3toWZXljuO4L0kVKCCGEEEJ8QIqisO3sXRrNOcjBq6GYmaj5plkp1vevKsUaIcRbk4KNyNpyuaFqOY8HPf1ZrzQkRjFBFewPv7WBXxvAlZ1SuBFCCCGEEBnuSWQMg9eeYfiGc0REx1M2vz07Pq9J31pF0KhlrBohxNuTgo34KOQvXAJtk1nUjvFhla4JOo0F3D0F6zvC4toQ8CfodMYOUwghhBBCfIR2X3qAt88h/v3vASZqFSMbFmfLoOoUdbY1dmhCiCxMxrARH42uVQqy61JxJl7LyX7nbiwvdhz1qWXw4AJs7A5OpaD26IRBi9UaY4crhBBCCCGyuPCXcUz+6xJbz9wFoHhuG2Z3KEeZfPZGjkwI8TGQFjbio6FSqfixbVlszU04cEfFIvOeMOI/qP0lmNtBaCBs+QzmV4Zz60AbZ+yQhRBCCCFEFuV3LZTGPofYeuYuKhUMqFOEv4bVlGKNECLdSMFGfFTyOlgysYU7AD57rnE5wgQ++QaGX4R6X4NlDnhyHbYNgrlecHolxMcaN2ghhBBCCJFlRMXE8822i3RfdoL74dEUymXF5oHVGNekFOYm0opbCJF+pGAjPjptK+SjQSlnYrU6Rm08T2y8DiwdoM6YhMJNg8lg5QhhQfDXF/BLOTi+BOKijR26EEIIIYTIxE7efkrTX/z47VgwAD2rubLji1p4ueY0cmRCiI+RFGzER0elUvF9Gw8crEy5dC+Cefuv/+9Oc1uoOTyhcOM9HWzyQMRd+PdL+LksHJ0HsVFGi10IIYQQQmQ+0XFavt8RSIfF/gQ9eUFeewt++6wKk1uWwcpMhgUVQmQMKdiIj5KzrQXTWpUBYP7+61y8E264gpkVVBsMX5yHpjPBLj9EPoTdX4OPB/jNhugII0QuhBBCCCEyk4t3wmk+9zBLDt1EUaC9V352jqhNzWKOxg5NCPGRk4KN+Gh9WjYvn5Z1QatTGLnxHNFx2qQrmVpA5X7w+VloMRdyFIIXT8B3ckLh5sAP8PLZB49dCCGEEEIYV5xWh8/eq7RecIRrjyJxtDFnaY+KzGjviZ2FqbHDE0JkA1KwER+1qS3L4GhjzrVHkczZczXlFU3MoEIPGHoaWi+GXMUgOgwOTAefsuA7BaKefLC4hRBCCCGE8Vx9+JzWC47gs/ca8TqFph552D2iNg1L5zZ2aEKIbEQKNmk0f/58ChUqhIWFBVWqVOHEiRMprrty5UpUKpXBzcLCwmAdRVGYMGECLi4uWFpa0qBBA65du5bRh5Ht5LA2Y3obDwCW+N3kdNDTN2+gMQHPTjDkOLRbDs6lISYC/GYltLjZ/Q08f/gBIhdCCCGEEB+aVqew5NANPp17mP/uRmBvacovncszv0sFclqbGTs8IUQ2IwWbNNiwYQMjR45k4sSJnDlzBk9PT7y9vXn06FGK29jZ2XH//n39LSgoyOD+n376iV9++YVFixZx/PhxrK2t8fb2JjpaZipKbw1L56adV34UBUZtPM+L2PjUN1JroExbGHgEOq4FF0+Ii4KjcxMGJ94xBsLvZnzwQgghhBDig7j9OIqOi/35fsdlYuN11CvhxO4RtWnhmReVSmXs8IQQ2ZAUbNJg9uzZ9OvXj969e1O6dGkWLVqElZUVy5cvT3EblUpFnjx59Lfcuf/XfFJRFHx8fPjmm29o2bIlZcuWZfXq1dy7d49t27Z9gCPKfiY0L42LvQW3n7zgx38vp31DtRpKfQr9D0KXTZC/EsRHw4nFCdOB/zUcngWlthchhBBCCJFJKYrCmmNBNPnZj1NBz7A20/BjWw+W96pEbjuL1HcghBAZRAo2qYiNjeX06dM0aNBAv0ytVtOgQQP8/f1T3C4yMhJXV1cKFChAy5YtuXTpkv6+W7du8eDBA4N92tvbU6VKlRT3GRMTQ0REhMFNpJ2dhSk/ti0LwCr/II5cf/x2O1CpoHgj+GwPdN8GrjVAGwunV8DcCrBtCDy5kf6BCyGEEEKIDHMv7CU9lp/g223/8TJOS9UiOdk5vDYdKxWUVjVCCKOTgk0qHj9+jFarNWghA5A7d24ePHiQ7DYlSpRg+fLlbN++nd9++w2dTkf16tW5c+cOgH67t9nn9OnTsbe3198KFCjwvoeW7dQu7kS3qgUBGLP5As+j495+JyoVuNWD3jug1w4oUhd08XDuN5hXEbb0g9Ar6Ru4EEIIIYRIV4qisOX0Hbx9DuF37THmJmomNi/Nur5VKZDTytjhCSEEIAWbDFGtWjV69OhBuXLlqFOnDlu3bsXJyYnFixe/8z7HjRtHeHi4/hYSEpKOEWcf45qUomBOK+6GvWTa34Hvt7NCNaDHdvhsLxTzBkUHFzfC/CqwsQc8uJg+QQshhBBCiHQT+jyGAWtOM2rTeZ5Hx1OugAM7vqhF7xqFUaulVY0QIvOQgk0qHB0d0Wg0PHxoODPQw4cPyZMnT5r2YWpqSvny5bl+/TqAfru32ae5uTl2dnYGN/H2rM1NmNGuLCoVbDgVwr7L6TDjU4FK0HVjwjg3JT8FFAjYDotqwvrOcPfM+z+GEEIIIYR4b/9evI+3zyF2BzzEVKPiS+8SbB5YDTcnG2OHJoQQSUjBJhVmZmZ4eXnh6+urX6bT6fD19aVatWpp2odWq+XixYu4uLgAULhwYfLkyWOwz4iICI4fP57mfYp3V6VILj6rURiAsVsuEvYiNn12nLccdFoLg46CextABVd2wNJ68FtbCD6ePo8jhBBCCCHeSviLOL74/SyD1p7haVQsJfPYsn1ITYbUK4qJRr4SCSEyJ7k6pcHIkSNZunQpq1atIjAwkEGDBhEVFUXv3r0B6NGjB+PGjdOvP2XKFHbv3s3Nmzc5c+YM3bp1IygoiL59+wIJM0gNHz6cadOm8eeff3Lx4kV69OhB3rx5adWqlTEOMdsZ7V0CNydrHj2PYeKfl1Lf4G3kdof2K2DoSfDsDCoNXN8LyxvByk/h1iFQlPR9TCGEEEIIkaz9Vx7RyOcg28/dQ62CofWK8ufQmpTOKy3WhRCZm4mxA8gKOnbsSGhoKBMmTODBgweUK1eOnTt36gcNDg4ORq3+X+3r2bNn9OvXjwcPHpAjRw68vLw4evQopUuX1q8zZswYoqKi6N+/P2FhYdSsWZOdO3diYSFTB34IFqYaZnUoR5sFR9h+7h6N3fPQxMMlfR/EsRi0XgR1xsDhOXBuPdz2S7gVqAp1vgS3+gkDGQshhBBCiHQVGRPPd/8EsP5EwtiPRRytmdXBk/IFcxg5MiGESBuVoshP/VlRREQE9vb2hIeHy3g272HmrivM23+dnNZm7B5RG0cb84x7sLAQOOIDZ9aANiZhWd4KUGsUlGgCak3GPbYQQqQzyUNpJ8+VEB/esZtPGL3pPHeevQSgT43CfOldAksz+bwlshfJQVmbdIkS2drn9YtRMo8tT6NiGb/1Ihlav3QoAM1mwRfnoeoQMLGEe2dgQ1f42RP8ZkPU44x7fCGEEEKIj1x0nJapfwfQeekx7jx7ST4HS9b3q8qE5qWlWCOEyHKkYCOyNTMTNbM7lMNUo2J3wEO2nbub8Q9q5wKNv4fhF6HmSLDMCeEh4DsZZpeCrQPgzumMj0MIIYQQ4iNyLiSMpr/4sezwLRQFOlUqwM7htajmlsvYoQkhxDuRgo3I9krnteOL+sUAmLj9Eg/Coz/MA9s4QYOJMDIAWi2EvOVBGwsXfodfP4EldeHsWoh7+WHiEUIIIYTIgmLjdczafYW2C49yMzQKZ1tzVvSqxA9ty2JrYWrs8IQQ4p1JwUYIYGAdNzzz2xMRHc9XWy5kbNeo15laQrku0P8A9N2XMLOUxhzunYXtgxNa3eyZAM9uf7iYhBBCCCGygMD7EbScf4S5+66j1Sm08MzL7hG1qVfS2dihCSHEe5OCjRCAiUbNrA6emJmoOXg1lN9PhhgnkPxeCTNLjQyA+hPBvgC8fAZHfoafy8G6jnBtL+h0xolPCCGEECITiNfqWHDgOi3mHSbwfgQ5rEyZ36UCv3Quj4OVmbHDE0KIdCEFGyH+X1FnW8Z4lwBg2t8BhDx9YbxgrB2h1siEAYo7rQe3TwAFru6EtW1hnhf4z08o5gghhBBCZCM3QyNpv9ifn3ZeIU6r0KBUbnaPqEOzsi7GDk0IIdKVFGyEeEXvGoWpXCgnUbFavtx8Hp3OyLPeqzVQsil0/wOGnoYqg8DcHp7ehF3jYVYp+HMY3L9g3DiFEEIIITKYTqew8sgtmv7ix9ngMGzNTZjZ3pOlPbxwsjU3dnhCCJHupGAjxCs0ahUz2pfF0lTDsZtPWeV/29gh/Y9jUWjyQ0J3qU/ngLM7xL+EM6thcS1Y5g0XN0N8rLEjFUIIIYRIV3eevaDbsuNM+iuA6DgdNYrmYueI2rTzyo9KpTJ2eEIIkSGkYCPEa1xzWTO+WSkAftx5mZuhkUaO6DXmNlCxDww6Ar3/Bfc2oDaBkGOw5TOY4w77voOIe8aOVAghhBDivSiKwsaTITT28ePojSdYmmqY0tKdNX2qkM/B0tjhCSFEhpKCjRDJ6FalILWKORIdp2PUpvNojd01KjkqFbhWh/YrYMQlqDsObPJA1CM49BPMKQMbusOtQ/AhZ70SQggjmj9/PoUKFcLCwoIqVapw4sSJN67v4+NDiRIlsLS0pECBAowYMYLo6Gj9/ZMmTUKlUhncSpYsmdGHIYQgYbruERvOMWbLBSJj4vFyzcGOL2rRo1oh1GppVSOE+PhJwUaIZKhUKn5sWxZbcxPOBoex5NBNY4f0ZrZ5oO5YGPEftF8JrjVA0ULgn7CqOSyoCieWQsxzY0cqhBAZZsOGDYwcOZKJEydy5swZPD098fb25tGjR8muv27dOsaOHcvEiRMJDAxk2bJlbNiwgfHjxxus5+7uzv379/W3w4cPf4jDESJbex4dR5+VJ9l27h4mahVjm5Rk44BqFHa0NnZoQgjxwUjBRogU5HWwZELz0gDM2XOVKw+yQLFDYwruraH3Dhh0NKHrlKk1hF6GHaMTBin+ZzSEXjF2pEIIke5mz55Nv3796N27N6VLl2bRokVYWVmxfPnyZNc/evQoNWrUoEuXLhQqVIhGjRrRuXPnJK1yTExMyJMnj/7m6Oj4IQ5HiGzr0fNoOi4+xuHrj7Ey07C8VyUG1nFDI61qhBDZjBRshHiDdl75aVDKmVitjpEbzxGn1Rk7pLTL7Z4wOPGoQGj8I+QqBrHP4eRSmF85oeVNwJ+gjTd2pEII8d5iY2M5ffo0DRo00C9Tq9U0aNAAf3//ZLepXr06p0+f1hdobt68yY4dO2jatKnBeteuXSNv3rwUKVKErl27EhwcnHEHIkQ2dzM0kjYLjhJwPwJHGzN+71+V2sWdjB2WEEIYhRRshHgDlUrF9208cLAy5dK9CObtu27skN6ehT1UHQhDT0L3bVDyU1CpE8a22dgdfi4Lh2ZAZPJdBoQQIit4/PgxWq2W3LlzGyzPnTs3Dx48SHabLl26MGXKFGrWrImpqSlubm7UrVvXoEtUlSpVWLlyJTt37mThwoXcunWLWrVq8fx5yq0uY2JiiIiIMLgJIVJ3NvgZ7Rb5c+fZS1xzWbFlUHXK5ncwdlhCCGE0UrARIhXOthZMbVkGgHn7r3PxTriRI3pHKhW41YNOa+GLC1BzJFjlgoi7sG8azC4NW/pCyAkZpFgIkS0cOHCA77//ngULFnDmzBm2bt3KP//8w9SpU/XrNGnShPbt21O2bFm8vb3ZsWMHYWFhbNy4McX9Tp8+HXt7e/2tQIECH+JwhMjS9l1+SJelx3kaFUvZ/PZsGVQd11wyXo0QInuTgo0QadDcMy/Nyrqg1SmM2nSO6DitsUN6Pw4FoMFEGBkIrZdAvoqgi4OLm2BZQ1hcG86shtgXxo5UCCHSxNHREY1Gw8OHDw2WP3z4kDx58iS7zbfffkv37t3p27cvHh4etG7dmu+//57p06ej0yXfBdbBwYHixYtz/XrKLS7HjRtHeHi4/hYSEvLuByZENrDxVAj9Vp/mZZyW2sWdWN+vKo425sYOSwghjE4KNkKk0dSWZXC0MePqw0jm7L1q7HDSh4k5eHaEfr7Q/wCU6wYmFvDgAvw5DGaXgl1fw9NMPkuWECLbMzMzw8vLC19fX/0ynU6Hr68v1apVS3abFy9eoFYbfhTSaDQAKCm0NIyMjOTGjRu4uLikGIu5uTl2dnYGNyFEUoqiMNf3GmM2X0CrU2hTIR/LelbE2tzE2KEJIUSmIAUbIdIop7UZ09uUBWDJoZucDnpq5IjSWd7y0Gp+QqubhlPAwRWiw8B/HvxSAX5rB1d3QQq/OgshhLGNHDmSpUuXsmrVKgIDAxk0aBBRUVH07t0bgB49ejBu3Dj9+s2bN2fhwoX8/vvv3Lp1iz179vDtt9/SvHlzfeFm9OjRHDx4kNu3b3P06FFat26NRqOhc+fORjlGIT4WWp3Ct9v/Y9aehB/BBtV1Y1Z7T0w18vVECCESSflaiLfQsHRu2lbIz5Yzdxi18Tw7vqiFldlHdhpZ5YQaX0C1oXB9L5xYCtf3/O+WoxBU/AzKd0tYVwghMomOHTsSGhrKhAkTePDgAeXKlWPnzp36gYiDg4MNWtR88803qFQqvvnmG+7evYuTkxPNmzfnu+++069z584dOnfuzJMnT3BycqJmzZocO3YMJyeZtUaIdxUdp2X47+fYeekBKhVMau5Oz+qFjB2WEEJkOiolpTa/IlOLiIjA3t6e8PBwaWr9gYW/jKOxzyHuh0fTq3ohJrVwN3ZIGe/JDTi1HM6ugej/H3TZxALKtIPK/SBvOaOGJ4T48CQPpZ08V0L8T/iLOPquPsnJ288w06jx6VSOph4pdzEUQrwfyUFZm7Q5FOIt2Vua8mPbhK5RK4/e5uj1x0aO6API5Qbe38HIy9BiLuTxgPhoOPcbLKkDvzaA8xsgPsbYkQohhBAik7oX9pL2i49y8vYzbC1MWNWnshRrhBDiDaRgI8Q7qF3cia5VCgLw5eYLPI+OM3JEH4iZFVToAQP8oM9u8GgPalO4cxL+6J8wNbjvFAiTGVGEEEII8T9XHjynzYKjXH0YSW47czYNrEY1t1zGDksIITI1KdgI8Y7GNy1FgZyW3A17yXf/BBo7nA9LpYKCVaDtrzAyAD75BuzywYvH4DcLfi4Lv3eFmwdAel0KIYQQ2drxm09ov+goDyKiKepsw9bBNSiZR7pmCCFEaqRgI8Q7sjY3YWY7T1Qq+P1kCPsvPzJ2SMZh4wy1v4QvLkCHNVC4Nig6uPw3rG4J8yvD8cUQHWHsSIUQQgjxge387z7dl58gIjoeL9ccbB5YjXwOlsYOSwghsgQp2AjxHqoUyUWfGoUB+GrLBcJexBo5IiPSmEDpFtDzLxh8HCr1AzMbeHwV/h0Ds0rC3yPhUTZrjSSEEEJkU2v8bzNo7Rli43U0LJ2btX2r4GBlZuywhBAiy5CCjRDv6UvvEhRxsubR8xgm/XnJ2OFkDs4lodlMGHUZms4ExxIQFwWnlsGCqrCiGVz6A7TZZOwfIYQQIhtRFIUZuy7z7fZLKAp0qVKQhV0rYGGqMXZoQgiRpUjBRoj3ZGGqYVZ7T9Qq2HbuHv9evG/skDIPc9uEab+HHE9oeVOqBag0EHQYNvUCHw848CM8f2DsSIUQQgiRDuK0OsZsvsD8/TcAGNmwON+1KoOJRr52CCHE25IrpxDpoHzBHAyq6wbA19v+43GkTG9tQKVKGNum4xoYfjFhzBtrZ3h+Hw58D3PcYVNvCDoqgxQLIYQQWdSL2Hj6rT7FptN3UKvghzYefF6/GCqVytihCSFEliQFGyHSyef1i1Eyjy1Po2L55o//UKTwkDz7fAmzSo24BG2XQYGqoIuHS1thRRNYVBNOrYDYKGNHKoQQQog0ehIZQ+elxzlwJRQLUzVLulekU+WCxg5LCCGyNCnYCJFOzE00zOrgiYlaxc5LD9h+7p6xQ8rcTMzAox18tgsG+EGFHmBiCQ//g7+Hw6xS8O9YeHzd2JEKIYQQ4g2Cn7yg3SJ/zoeE4WBlytq+VWlQOrexwxJCiCxPCjZCpCP3vPZ8Ub8YABO2/8eD8GgjR5RFuJSFFnNhVCB4fw85CkNMOBxfCPO8YE1ruLwDdFpjRyqEEEKIV/x3N5w2C49y63EU+Rws2TywOl6uOYwdlhBCfBSkYCNEOhtU1w3P/PZERMczdusF6Rr1NixzQLUhMOwMdN0CxRsDKrixD37vDD+Xg8NzIOqJsSMVQgghsj2/a6F0XOzP48gYSrnYsXVwdYo62xg7LCGE+GhIwUaIdGaiUTOrgydmJmoOXAllw8kQY4eU9ajVUKwBdNkAX5yD6p8nFHPCg2HvJJhdCv4YCHdOGztSIYQQIlvadvYuvVecJCpWS7UiudgwoCq57SyMHZYQQnxUpGAjRAYo6mzLl41KADD17wBCnr4wckRZWI5C0GgqjAyElgvApRxoY+D8evj1E1hSD86tgzjpfiaEEEJ8CEsP3WT4hnPE6xQ+LevCyj6VsLMwNXZYQgjx0ZGCjRAZpE/NwlQqlIOoWC1fbj6PTiddo96LqSWU7wr9D0BfXyjbCTRmcO8MbBuU0OpmzwR4FmTsSIUQQoiPkk6nMPXvAL7bEQhAnxqF+aVTecxNNEaOTAghPk5SsBEig2jUKma298TSVMOxm09Z7X/b2CF9HFQqyF8R2ixOaHVTfwLYF4CXT+HIz/CzJ6zrBNf3gk5n7GiFEEKIj0JMvJbhG86x7PAtAMY3Lcm3n5ZCrVYZOTIhhPh4ScFGiAzkmsua8U1LAvDDzsvcDI00ckQfGWtHqDUKvjgPndZBkXqAAlf/hd/awryK4L8AXoYZO1IhhBAiy3oeHUfvFSf58/w9TNQqfDqWo39tN1QqKdYIIURGkoKNEBmsaxVXahZ1JDpOx+hN59FK16j0p9ZAyWbQYxsMPQVVBoK5HTy9AbvGJXSX+vNzeHDR2JEKIYQQWcqjiGg6LD7G0RtPsDbTsLxXJVqVz2fssIQQIluQgo0QGUytVvFju7LYmptwJjiMpX43jR3Sx82xGDT5MaG71KdzwLk0xL2AM6tgUU1Y3hgubob4WGNHKoQQQmRqN0IjabPwKIH3I3C0MWPDgGrULu5k7LCEECLbUCmKIj/3Z0ERERHY29sTHh6OnZ2dscMRabDxVAhjNl/ATKPmr2E1KZHH1tghZQ+KAkFH4eRSCPwLdPEJy21yJ3Shsnb8/5sTWP3/v9a5Ev41szZu7EJkYpKH0k6eK5EVnQ1+Rp+VJ3n2Io5CuaxY1acyrrkkLwqR1UgOytpMjB2AENlFe6/87PrvAb6XHzFy4zm2DamBqUYauWU4lQoK1Ui4RdyH0ysTbpEP4MLvb97WxPJ/BZzXiznJ/W1m9SGOSAghhMhQvoEPGbLuDNFxOjzz27OsVyUcbcyNHZYQQmQ70sImjebPn8+MGTN48OABnp6ezJ07l8qVK6e63e+//07nzp1p2bIl27Zt0y/v1asXq1atMljX29ubnTt3pikeqZRmTY8iomnkc4iwF3EMb1CM4Q2KGzuk7EkbB9d2w+NrEBUKL55A1ONX/h8K8dFvv19T6+QLOvr//39rHqv//9fUMv2PTYgPRPJQ2slzJbKSjSdDGPfHRbQ6hbolnJjfpQLW5vIbrxBZleSgrE2uvmmwYcMGRo4cyaJFi6hSpQo+Pj54e3tz5coVnJ2dU9zu9u3bjB49mlq1aiV7f+PGjVmxYoX+b3Nz+eXiY+dsZ8GUlmX4fP1Z5u27Tv2SufHIb2/ssLIfjWnCIMUpURSIjTIs4Lxe0Hn9b20sxEVBWBSEBactDjObVwo4qbTesXYEE7lGCCGEyBiKojBv33Vm7bkKQNsK+fmhrYe0BhZCCCOSgk0azJ49m379+tG7d28AFi1axD///MPy5csZO3ZssttotVq6du3K5MmT8fPzIywsLMk65ubm5MmTJyNDF5lQ87Iu7PrvAf9cvM+oTef4a1hNzE00xg5LvEqlAnObhFvOwqmvrygQ8xxePP7/Qk5iMecNf+viIDYy4fbsdtriMrcDq1zJtNZJ5m+rXGBi9l5PgxBCiOxBq1OYsP0/1h5P+MFhSD03RjcqIdN2CyGEkUnBJhWxsbGcPn2acePG6Zep1WoaNGiAv79/ittNmTIFZ2dnPvvsM/z8/JJd58CBAzg7O5MjRw4++eQTpk2bRq5cuZJdNyYmhpiYGP3fERER73hEwthUKhVTW5Xh+K0nXH0Yyew9VxnXpJSxwxLvQ6UCC7uEW84iqa+vKBATkUwxJxSiniQt7rx4nDBYckxEwu3ZrbTFZWH/v9Y5iUUcfXHntb+tciW0PBJCCJGtRMdp+Xz9WXYHPESlgknN3elZvZCxwxJCCIEUbFL1+PFjtFotuXPnNlieO3duLl++nOw2hw8fZtmyZZw7dy7F/TZu3Jg2bdpQuHBhbty4wfjx42nSpAn+/v5oNElbW0yfPp3Jkye/17GIzCOntRnft/ag/5rTLD54E2dbCz6rmYaWHOLjoFIlFFMs7CGXW+rrKwpEhxkWcJIUd179+wkoWogOT7g9vZG2uCwcUm6983qxxzInaCSFCCFEVhb2Ipa+q05xKugZZiZqfDqWo6mHi7HDEkII8f/k03Y6e/78Od27d2fp0qU4OjqmuF6nTp30//fw8KBs2bK4ublx4MAB6tevn2T9cePGMXLkSP3fERERFChQIH2DFx9UI/c8DKnnxvz9N5j6dwDRcVqG1Ctq7LBEZqRSgWWOhJtjsdTX1+leKfAk01pHPwbP///94gko/79NdBg8uZaWoBLiSVPrHUewyglq6fonhBCZxb2wl/RcfoJrjyKxtTDh1x4VqVIk+ZbeQgghjEMKNqlwdHREo9Hw8OFDg+UPHz5MdvyZGzducPv2bZo3b65fptPpADAxMeHKlSu4uSX9Rb1IkSI4Ojpy/fr1ZAs25ubmMijxR2h0oxKYaTTM2XuVGbuuEBOvY0SDYtJnXLwftTqhQGKVE5zSMBOZTgsvw15rrfNqgee1Ys+Lp4ACL58m3B5fTUNQqoR4EgdRtrAHM+uEm7lNwgDMZtb//+//jx+UeL+Z7Sv/t5GWPUII8Z6uPHhOz+UneBARTR47C1b2qUTJPDJ7jBBCZDbyqTcVZmZmeHl54evrS6tWrYCEAoyvry9Dhw5Nsn7JkiW5ePGiwbJvvvmG58+f8/PPP6fYKubOnTs8efIEFxdphpqdqFQqvmhQDHNTNT/8e5lffK8RE6dlbJOSUrQRH45a8/8zUqXxl1WdNqFok2xxJ5liz8v/L/C8eJJwe18mFobFHX3R57XiTnKFoOSWm1olFLmEECIbOHbzCf1Wn+J5dDxFnW1Y3acyeR0sjR2WEEKIZEjBJg1GjhxJz549qVixIpUrV8bHx4eoqCj9rFE9evQgX758TJ8+HQsLC8qUKWOwvYODA4B+eWRkJJMnT6Zt27bkyZOHGzduMGbMGIoWLYq3t/cHPTaROQys44aFiZpJfwWw+NBNouO0TGzujlotRRuRCak1YOOUcCMNA2Zr4xOKNq9Ohx7zPGHq9NgoiP3//8dE/v/f/z97VuL9Mc8T/tbFJ+wvPjrhlh7Fn0RmNoateJIUgl4r8iS3/NVCkIlFQlc2IYTIRP69eJ8vNpwjNl5HRdcc/NqzIg5WMqOgEEJkVlKwSYOOHTsSGhrKhAkTePDgAeXKlWPnzp36gYiDg4NRv8WvsxqNhgsXLrBq1SrCwsLImzcvjRo1YurUqdLtKRvrVaMw5qYaxv9xkVX+QcTE6/iutQcaKdqIrE5jAjbOCbf3ER/7v2JOssWdV5ensRCEkrDvxPvSi0rz5qJPktY/bygEmVmDua3M4iWEeC+rjt5m0l+XUBRoVDo3v3Quj4WpjC0mhBCZmUpRFMXYQYi3FxERgb29PeHh4djZSZ/jj8nWM3cYvek8OgVal8/HjHZlMdFIdw0h0p2iQNzLNBR33qIQFPci4+LVmBl2+3pTcSfF1kI2CTN8pbX72xtIHko7ea6EMSmKwszdV5i/P2HGwK5VCjKlZRn5QUiIbEJyUNYmLWyEyGTaVMiPuYmGL34/yx9n7xITr8WnY3nMTKRoI0S6UqnAzCrhhlP67FOnfaWw80pxR9+1KyqFQtDrrX8i/7dMG5uwb20svIyFl8/eL8biTaDL7+9/rEKITC9Oq2Pc1otsPn0HgFENizP0k6IyTp4QQmQRUrARIhNqVtYFMxM1Q9aeYcfFB8TGn2ZelwrSdFmIzE6tAQu7hFt6iY+FuKjkW/m8SyEoPWMTQmRaUTHxDFl3hgNXQtGoVXzfugwdKxU0dlhCCCHeghRshMikGpbOzdKeFem/+hR7Ax/Rb/UplnSviKWZFG2EyFZMzBJuljmMHYkQIot4EhlDn5UnOX8nHAtTNfO7VKB+qdzGDksIIcRbkj4WQmRidYo7saJ3JazMNPhde0zvlSeIjIk3dlhCCCGEyKSCn7yg7cKjnL8TTg4rU9b1qyrFGiGEyKKkYCNEJlfdzZHVfSpja27CsZtP6bHsOBHRccYOSwghhBCZzH93w2mz8Ai3n7wgfw5LNg+qToWC0jpPCCGyKinYCJEFVCyUk7X9qmBvacqZ4DC6Lj3Os6hYY4clhBBCiEzC71ooHRf78zgyllIudmwdVB03JxtjhyWEEOI9SMFGiCyibH4H1verSi5rMy7eDafz0mM8jowxdlhCCCGEMLI/zt6h94qTRMVqqe6Wi40DquJsZ2HssIQQQrwnKdgIkYWUzmvH7/2r4mxrzuUHz+m42J8H4dHGDksIIYQQRqAoCksO3WDEhvPE6xSae+ZlRe9K2FqYGjs0IYQQ6UAKNkJkMcVy27JhQDXy2ltwIzSKjkv8ufPshbHDEkKId1KoUCGmTJlCcHCwsUMRIkvR6RSm/h3I9zsuA/BZzcL83LEc5iYym6QQQnwspGAjRBZU2NGaDQOqUTCnFUFPXtBx8TGCnkQZOywhhHhrw4cPZ+vWrRQpUoSGDRvy+++/ExMj3T2FeJOYeC2f/36W5UduAfB101J8+2lp1GqVkSMTQgiRnqRgI0QWVSCnFRsHVKOIozV3w17SYbE/1x9FGjssIYR4K8OHD+fcuXOcOHGCUqVKMWzYMFxcXBg6dChnzpwxdnhCZDoR0XH0Wn6Svy/cx1SjwqdjOfrVLmLssIQQQmQAKdgIkYXlsbfg9wFVKZ7bhocRMXRa4s/lBxHGDksIId5ahQoV+OWXX7h37x4TJ07k119/pVKlSpQrV47ly5ejKIqxQxTC6B5GRNNhkT/+N59gbaZhRa/KtCqfz9hhCSGEyCBSsBEii3O2teD3/tVwz2vH48hYOi05xsU74cYOSwgh3kpcXBwbN26kRYsWjBo1iooVK/Lrr7/Stm1bxo8fT9euXY0dohBGdSM0kjYLjnL5wXMcbczZMKAaNYs5GjssIYQQGcjE2AEIId5fTmsz1vWrSs/lJzgXEkaXX4+xsndlvFxzGDs0IYR4ozNnzrBixQrWr1+PWq2mR48ezJkzh5IlS+rXad26NZUqVTJilEIY1+mgZ3y26iRhL+Io7GjNqt6VKZjLythhCSGEyGDSwkaIj4S9pSm/9a1C5UI5eR4dT49lxzl284mxwxJCiDeqVKkS165dY+HChdy9e5eZM2caFGsAChcuTKdOnYwUoRDG5Rv4kK6/HiPsRRye+e3ZPLCaFGuEECKbUCnSKTxLioiIwN7envDwcOzs7IwdjshEXsTG03/1aQ5ff4yFqZol3StSu7iTscMSQnxk0isPBQUF4erqmo6RZT6Ss8W7+v1EMOP/uIhOgXolnJjftQJWZtJAXgiRdpKDsjZpYSPER8bKzIRfe1bkk5LORMfp6LvqFL6BD40dlhBCJOvRo0ccP348yfLjx49z6tQpI0QkhPEpisLPe68xdmtCsaadV36W9KgoxRohhMhmpGAjxEfIwlTDom5eNHbPQ6xWx4A1p9lx8b6xwxJCiCSGDBlCSEhIkuV3795lyJAhRohICOPS6hS+3vYfc/ZeBWBovaLMaFcWU418bBdCiOxGrvxCfKTMTNTM61KeFp55idcpDF13hm1n7xo7LCGEMBAQEECFChWSLC9fvjwBAQFGiEgI44mO0zLwt9OsOx6MSgVTW7oz2rsEKpXK2KEJIYQwAinYCPERM9GomdOxHO298qNTYMTGc2w4GWzssIQQQs/c3JyHD5N227x//z4mJtL9Q2QfYS9i6frrcfYEPMTMRM2CLhXoXq2QscMSQghhRFKwEeIjp1Gr+LFtWbpVLYiiwFdbLrLa/7axwxJCCAAaNWrEuHHjCA8P1y8LCwtj/PjxNGzY0IiRCfHh3A17SbtF/pwOeoadhQm/fVaFJh4uxg5LCCGEkclPV0JkA2q1iqkty2BhouHXw7eYsP0SMXE6+tUuYuzQhBDZ3MyZM6lduzaurq6UL18egHPnzpE7d27WrFlj5OiEyHiXH0TQc/kJHkbEkMfOglV9KlMij62xwxJCCJEJSMFGiGxCpVLxdbNSWJhqmLf/Ot/tCCQ6Tsuw+sWMHZoQIhvLly8fFy5cYO3atZw/fx5LS0t69+5N586dMTU1NXZ4QmSoYzef0G/1KZ5Hx1PM2YZVfSqT18HS2GEJIYTIJKRgI0Q2olKpGO1dAgtTNTN3X2XWnqtEx2sZ3UgGNBRCGI+1tTX9+/c3dhhCfFD/XLjPiA3niNXqqFQoB7/2qIS9lRQphRBC/I8UbITIhoZ+UgwLUw3T/glk/v4bRMfp+KZZKSnaCCGMJiAggODgYGJjYw2Wt2jRwkgRCZFxVh65xeS/A1AU8HbPzc+dymNhqjF2WEIIITIZKdgIkU31rVUEcxM1326/xLLDt4iO0zK1ZRnUainaCCE+nJs3b9K6dWsuXryISqVCURQAfQFZq9UaMzwh0pWiKPy06woLD9wAoHtVVya1cEcjuVcIIUQyPtpZokJCQrhz547+7xMnTjB8+HCWLFlixKiEyFy6VyvET23LolLB2uPBjNlyAa1OMXZYQohs5IsvvqBw4cI8evQIKysrLl26xKFDh6hYsSIHDhwwdnhCpJs4rY5Rm87rizWjGxVnSksp1gghhEjZR1uw6dKlC/v37wfgwYMHNGzYkBMnTvB/7d13dBRVH8bx7+6mhySUQAqEDgk90kIVlC4iiAV8kSaCUlTEigrYUWyoICDSUUERsCEIUXrvoBB6J6GnQerO+0c0GmkBksxu8nzO2aM7e2fy7CjczW9vefnll3n99ddNTifiOB6sF8LoLuHYrBbmbDrG07O3kppuNzuWiBQQa9as4fXXX8ff3x+r1YrVaqVJkyaMHDmSJ5980ux4IjkiMTmNPtM2MnfzcWxWC6Puq8mgOytpKrKIiFxTvi3Y7Ny5k/r16wPwzTffUL16dVavXs2XX37J1KlTzQ0n4mA6hpdkzEO34Wqz8MO2Ewz6ajMpaSraiEjuS09Px8cnYwtjf39/Tpw4AUCZMmWIiooyM5pIjjiTkMxDE9eyfM9pPFytTOxRhwfrhZgdS0REnEC+Ldikpqbi7u4OwJIlSzIXLQwLC+PkyZNmRhNxSO1qBDH+4Tq42aws+iOGx2ZsJClVa0eISO6qXr0627ZtAyAiIoJRo0axatUqXn/9dcqXL29yOpFbc/hsIveNW832Y7EU8XLl674NuDMswOxYIiLiJPJtwaZatWqMHz+eFStWsHjxYtq2bQvAiRMnKFasmMnpRBxTiyoBTOpVFw9XK79HnabPtA1cTEkzO5aI5GOvvPIKdnvGiL7XX3+dgwcP0rRpUxYsWMAnn3xicjqRm7fjWCz3jVvN4bMXKVXEk+/6N+K20kXMjiUiIk7EYvy9HUM+s3TpUu69917i4uLo2bMnkydPBuCll15i9+7dzJ071+SEtyYuLg4/Pz9iY2Px9fU1O47kM+sOnOWRqRtITEmnftmiTOpVFx8PV7NjiYgDyc1+6Ny5cxQpUiTfrO+hPrvgWb7nNI/P3MTFlHSqBvky9ZF6lPDxMDuWiBRA6oOcW74t2EDGvPi4uDiKFPnn24xDhw7h5eVFiRIlTEx26/QHT3Lb5iPn6Tl5PfFJadQKKcz03vXx81LRRkQy5EQ/lJqaiqenJ1u3bqV69eo5nNBxqM8uWOZtOcZz324nzW7QuGIxxj9cR196iIhp1Ac5t3w7JerSpUskJydnFmsOHz7M6NGjiYqKcvpijUheqF26CF/3bUBhL1e2Hb3AQxPXci4xxexYIpKPuLq6Urp0adLTtV6WOD/DMBi/bD9Pz95Gmt3gnlrBTOlVX8UaERG5afm2YNOxY0emT58OwIULF4iIiOCDDz6gU6dOjBs3zuR0Is6hekk/ZvVrgH8hN/48GUfXz9dwKj7J7Fgiko+8/PLLvPTSS5w7d87sKCI3zW43eP2nP3nnl90A9G1ajtFdwnFzybcftUVEJA/k215k8+bNNG3aFIA5c+YQEBDA4cOHmT59uhYxFLkBYYG+zOrXkABfd/bEJNB1wlpOxl4yO5aI5BNjxoxh+fLlBAcHExoaSu3atbM8RBxdclo6T8zawpRVhwB4pX0VXm5fFas1f6zBJCIi5nExO0BuuXjxIj4+PgD8+uuvdO7cGavVSoMGDTh8+LDJ6UScS8UShfjmsYb8b+I6DpxJ5MEJa/jq0QaEFPUyO5qIOLlOnTqZHUHkpsUlpdJv+kbWHjiHq83C+w/UomN4SbNjiYhIPpFvCzYVK1Zk/vz53HvvvSxatIinn34agFOnTmmxJZGbUKaYN9883pD/TVzL4bMXM4o2fRtQzt/b7Ggi4sRGjBiRo9cbO3Ys7733HtHR0dSqVYtPP/2U+vXrX7X96NGjGTduHEeOHMHf35/777+fkSNH4uHhcdPXlIIhJi6JnpPXszs6nkLuLkzoXofGFf3NjiUiIvlIvp0SNXz4cJ599lnKli1L/fr1adiwIZAx2ua2224zOZ2IcypZ2JNvHmtIheLenIxN4sEJa9gbE292LBERAGbPns2QIUMYMWIEmzdvplatWrRp04ZTp05dsf1XX33Fiy++yIgRI9i1axeTJk1i9uzZvPTSSzd9TSkY9p2Kp/Nnq9kdHY9/IXdm9WugYo2IiOS4fL2td3R0NCdPnqRWrVpYrRm1qfXr1+Pr60tYWJjJ6W6NtmcTM51JSObhL9axOzqeot5uzOhTn2rBfmbHEpE8lFP9kNVqxWK5+lofN7KDVEREBPXq1WPMmDEA2O12QkJCeOKJJ3jxxRcvaz9o0CB27dpFZGRk5rFnnnmGdevWsXLlypu65pWoz85fNh0+T59pG7hwMZVy/t5Mf6S+pgiLiMNSH+Tc8u2UKIDAwEACAwM5duwYAKVKldIQZpEc8Pe3id0nrWfH8Vge+nwtM/pEUCuksNnRRMTJzJs3L8vz1NRUtmzZwrRp03jttdeyfZ2UlBQ2bdrE0KFDM49ZrVZatmzJmjVrrnhOo0aNmDlzJuvXr6d+/focOHCABQsW0L1795u+JkBycjLJycmZz+Pi4rL9PsSxLf4zhie+3kxSqp3wkMJM7lWPot5uZscSEZF8Kt9OibLb7bz++uv4+flRpkwZypQpQ+HChXnjjTew2+03fL2xY8dStmxZPDw8iIiIYP369dk6b9asWVgslssWVTQMg+HDhxMUFISnpyctW7Zk7969N5xLxCyFvdz4sm8EdcoUIS4pjW5frGPjIW3LKyI3pmPHjlke999/P2+99RajRo3ihx9+yPZ1zpw5Q3p6OgEBAVmOBwQEEB0dfcVz/ve///H666/TpEkTXF1dqVChAs2bN8+cEnUz1wQYOXIkfn5+mY+QkJBsvw9xXF+vP8JjMzaSlGrnjtDifNU3QsUaEcl5ly7AnkUQ+QbcxO+tkr/k24LNyy+/zJgxY3jnnXfYsmULW7Zs4e233+bTTz9l2LBhN3Stm52/fujQIZ599tnM7cX/bdSoUXzyySeMHz+edevW4e3tTZs2bUhKSrqhbCJm8vVwZfoj9WlQvigJyWl0n7Se1fvOmB1LRPKBBg0aZJmqlBuWLl3K22+/zWeffcbmzZuZO3cuP//8M2+88cYtXXfo0KHExsZmPo4ePZpDicUsczYdY+jcHdgNeLBuKSb2qIuXW74eqC4ieSXhNPz5PfzyAoxvAu+Wha8ehBXvw+ldZqcTk+XbnmbatGl88cUX3HPPPZnHatasScmSJRkwYABvvfVWtq/14Ycf0rdvX3r37g3A+PHj+fnnn5k8efJV56+np6fTrVs3XnvtNVasWMGFCxcyXzMMg9GjR/PKK6/QsWNHAKZPn05AQADz58+na9euN/GORczh7e7ClF716TdjIyv2nqH31A1M6F6H5qElzI4mIk7q0qVLfPLJJ5Qsmf3tkf39/bHZbMTExGQ5HhMTQ2Bg4BXPGTZsGN27d+fRRx8FoEaNGiQmJtKvXz9efvnlm7omgLu7O+7u7tnOLo7tYkoa7/yyG4C+Tcvx0l1VrrnukojINcUeh8Or4fCqjH+eibq8TdEKUKYRWF3zPp84lHxbsDl37twVFxYOCwvj3LnsT9u42fnrr7/+OiVKlKBPnz6sWLEiy2sHDx4kOjqali1bZh7z8/MjIiKCNWvWXLFgo/nw4sg83Wx80bMuA7/czJJdp+g7fSNj/1eb1tWu/guNiAhAkSJFsvzyaxgG8fHxeHl5MXPmzGxfx83NjTp16hAZGZk5DdlutxMZGcmgQYOueM7FixczNyX4m81my8xxM9eU/GfKqkOcSUimdFEvnmsTpmKNiGSfYcD5g38VaP4q0pw/dHm7ElUzCjRlGkHpRuAblOdRxTHl24JNrVq1GDNmDJ988kmW42PGjKFmzZrZvs615q/v3r37iuesXLmSSZMmsXXr1iu+/ve89xuZEz9y5MgbWnxRJK+5u9j4rFsdnp69lZ93nGTAl5v5qEs4HWoFmx1NRBzYRx99lOUXYKvVSvHixYmIiKBIkSI3dK0hQ4bQs2dP6tatS/369Rk9ejSJiYmZI2R79OhByZIlGTlyJAAdOnTgww8/5LbbbiMiIoJ9+/YxbNgwOnTokFm4ud41JX87n5jC+KX7AXimdWXcXPLtagIikhMMA05H/TN65vBqiD+RtY3FCoE1oUxjKNsYSjcEr6Lm5BWHl28LNqNGjaJ9+/YsWbKEhg0bArBmzRqOHj3KggULcu3nxsfH0717dyZOnIi/v3+OXXfo0KEMGTIk83lcXJwWMRSH4+Zi5eOu4bi7WJm75ThPzdpCcpqd++uUMjuaiDioXr165di1unTpwunTpxk+fDjR0dGEh4ezcOHCzC9Ijhw5kmVEzSuvvILFYuGVV17h+PHjFC9enA4dOmSZNn29a0r+Nm7ZfuKT0wgL9KFDTX0BISL/YU+HmJ0ZhZlDK+HIGrh4NmsbqyuUrP3XCJomEFIfPLS9tmSPxTAMw+wQueXEiROMHTs2cyRMlSpV6NevH2+++Saff/55tq6RkpKCl5cXc+bMybLTU8+ePblw4QLff/99lvZbt27ltttuy/xmDsjclcpqtRIVFYXFYqFChQps2bKF8PDwzHbNmjUjPDycjz/++Lq54uLi8PPzIzY2Fl9f/YEXx2K3G7w0bwezNmQstPn2vTX4X0Rpk1OJSE7KqX5oypQpFCpUiAceeCDL8W+//ZaLFy/Ss2fPW41qOvXZzulk7CWavbeUlDQ7U3rV444wrc0mUuClp8KJrXB4ZUaR5shaSP7PUhUuHlCqHpRtklGkKVkX3LxMiQvqg5xdvh1hAxAcHHzZ4sLbtm1j0qRJ2S7Y3Oj89bCwMHbs2JHl2CuvvEJ8fDwff/wxISEhuLq6EhgYSGRkZGbBJi4ujnXr1tG/f/8bf6MiDsZqtfD2vTVwd7Eybc1hXpq3g+S0dHo3Lmd2NBFxMCNHjmTChAmXHS9RogT9+vXLFwUbcU4fL9lLSpqd+uWK0jy0uNlxRMQMqZfg+CY4tCpjmtOxDZB6MWsbNx8o3eCvETSNIfg2cHEzJ6/kO/m6YJNTbmROvIeHB9WrV89yfuHChQGyHB88eDBvvvkmlSpVoly5cgwbNozg4OAso3hEnJnVauHVe6rh4WpjwvIDvPbjnySl2unfvILZ0UTEgRw5coRy5S4v5pYpU4YjR46YkEgE9p1K4JuNGaNEX2gbqoWGRQqK5Hg4uu6f9WeOb4L0lKxtPItkFGb+XiQ4oAbY9Gu15A79n5UNNzonPjuef/75zK1DL1y4QJMmTVi4cCEeHh658RZETGGxWHixXRgerjY+jtzLuwt3k5SazuCWlfThV0SAjJE027dvp2zZslmOb9u2jWLFipkTSgq8D36Nwm5AyyoB1CmjxUBF8q2L5zKmNf29SPDJbWCkZ21TKOBfBZrGUDwMbvB3P5Gbla/XsLmSbdu2Ubt2bdLT06/f2IFpLqI4m8+W7mPUwigAHmtWnhfbamtUEWeWU/3QCy+8wOzZs5kyZQq33347AMuWLeORRx7h/vvv5/3338+pyKZRn+1cth29QMexq7BYYOFTtxMa6GN2JBHJKfExcGT1PyNoYv4A/vPrcOHSWQs0RcuDE39mVR/k3PLdCJvOnTtf8/ULFy7kTRARyWJA84p4uNh4/ac/mbDsAMmpdobfXRWr1Xk7QBG5dW+88QaHDh2iRYsWuLhkfCyx2+306NGDt99+2+R0UhCNWpSxWcW9t5VUsUbE2V04+ldx5q81aM7uu7xNsUoZxZmyTTK22C6snXjFceS7go2fn991X+/Ro0cepRGRf3ukSTncXa28PG8nU1cfIjktnbc61VDRRqQAc3NzY/bs2bz55pts3boVT09PatSoQZkyZcyOJgXQyr1nWLXvLG42K0+3rGx2HBG5EYYB5w5kFGYO/TXFKfa/a6FZIKD6P+vPlGkEhbQDnDiufFewmTJlitkRROQaukWUwd3FxvNztvH1+qMkp9oZdX9NXGyaCyxSkFWqVIlKlSqZHUMKMMMweHdhxuiabg1KE1LUvG14RSQb7HY4vfuf0TOHV0NCTNY2FhsEh/8zvSkkAry0LpU4j3xXsBERx3d/nVK4u1gZPHsrc7ccJznNzuiu4biqaCNS4Nx3333Ur1+fF154IcvxUaNGsWHDBr799luTkklBs2BHNDuOx+LtZmPgHRXNjiMi/5WeBjE7/hk9c2Q1XDqftY3NDUrW/Wf0TEh9cNfURnFeKtiIiCk61ArGzcXKoK828/OOkySn2Rnb7TbcXWxmRxORPLR8+XJeffXVy463a9eODz74IO8DSYGUmm7n/V8zFsZ/tGl5/Au5m5xIREhLgRNb4PDKvwo06yAlPmsbV6+MoszfiwSXrAuu2nVX8g8VbETENG2qBfJ5j7o8PmMTS3bF0Hf6JiY8XAdPNxVtRAqKhIQE3NzcLjvu6upKXFycCYmkIJqz6RgHzyRS1NuNR5uWMzuOSMGUchGObfhnkeBjGyAtKWsbdz8o3eCfRYKDaoHN1Zy8InlABRsRMdUdoSWY0qsefaZtZPme0/Seup5JPevh7a6/nkQKgho1ajB79myGDx+e5fisWbOoWrWqSamkIElKTWf0kj0ADLqjIj4e+uVPJE8kxcHRdf+sP3N8M9hTs7bxKvbX9KYmGf8MqAZWfbEnBYd+IxIR0zWq6M/0PvXpPWUDaw+co8fk9UzpXQ9ffWgWyfeGDRtG586d2b9/P3feeScAkZGRfPXVV8yZM8fkdFIQTFt9iJi4ZEoW9qRbg9JmxxHJvxLPwpE1/4ygid4Ohj1rG59gKNv4n0WC/SuDRbuJSsGlgo2IOIR6ZYsy89EIekxax6bD53n4i3VMf6Q+hb0unyohIvlHhw4dmD9/Pm+//TZz5szB09OTWrVq8dtvv1G0qHbykNwVeymVz5buB+DpVpW1jppIToqP/mf0zKFVcHrX5W2KlPtn/ZkyjaBIWRVoRP5FBRsRcRjhIYX5ul8Duk9az/ZjsXT9fC0zH43Q4o8i+Vz79u1p3749AHFxcXz99dc8++yzbNq0ifT0dJPTSX42Ydl+Yi+lUqlEIe69raTZcUScl2HAhSN/jZ75a5Hgcwcub1c87J/RM6Ubgp/+3Ilciwo2IuJQqgX7MatfA7p9sY7d0fF0/XwtXz4aQYCvVvwXyc+WL1/OpEmT+O677wgODqZz586MHTvW7FiSj52KS2LyqoMAPNcmFJtV3+qLZJthwNl9cOiv4szh1RB37D+NLBBYI+sIGm9/U+KKOCsVbETE4VQO8GH2X0WbfacS6DJhDV/2bUDJwp5mRxORHBQdHc3UqVOZNGkScXFxPPjggyQnJzN//nwtOCy57pPf9pKUaqd26cK0qhpgdhwRx2a3w6k//5ri9Nc0p8TTWdtYXSD4tn8WCQ6pD56FTYkrkl+oYCMiDql88UJ881hD/vfFWg6dvciD49fwVd8IyhTzNjuaiOSADh06sHz5ctq3b8/o0aNp27YtNpuN8ePHmx1NCoBDZxKZtf4oAC+0DcOiNTNEskpOgOgd/2yzfWQ1JMVmbWNzh1L1/lkkuFQ9cNPnNJGcpIKNiDiskKJeGUWbies4eCaRByes4au+DahQvJDZ0UTkFv3yyy88+eST9O/fn0qVKpkdRwqYDxbvIc1u0Dy0OBHli5kdR8RcSbEZxZkTW+HkNji5Fc7sBYys7dwKQUjEP2vQlKwNLlpnUCQ3qWAjIg4tyM8zc3rU3lMJdJmQsaZNaKCP2dFE5BasXLmSSZMmUadOHapUqUL37t3p2rWr2bGkANh5PJYft50AMtauESlQLp3/qyiz7Z8Czbn9V27rEwzB4f+sPxNYC2z69VEkL+lPnIg4vBK+Hsz6a/eoP0/G0fXzNczoE0H1kn5mRxORm9SgQQMaNGjA6NGjmT17NpMnT2bIkCHY7XYWL15MSEgIPj4qzErOe29RFAD31AqmWrD6EcnHEs9mjJb5e9TMyW1w/tCV2/qFQFAtCArPKNIE1YJCJfIsqohcmcUwDOP6zcTRxMXF4efnR2xsLL6+vmbHEckTsRdT6TFlPduOXsDHw4Vpj9SndukiZscSKZByox+Kiopi0qRJzJgxgwsXLtCqVSt++OGHHLm2mdRnO441+8/y0MS1uFgtRD7TTOuiSf6RcOpfo2a2Zvx77NErty1c5p+iTNBf/9TuTfmW+iDnpoKNk9IfPCmo4pNSeWTqBjYcOo+3m43Jvepp/QERE+RmP5Sens6PP/7I5MmTVbCRHGMYBp3HrWbLkQt0b1CGNzpVNzuSyM2JO5l11MyJrRB/4spti1bIKMhkFmhqgae+7CpI1Ac5NxVsnJT+4ElBdjEljUenbWT1/rN4uFr5okc9mlTSN0MieUn9UPbpXjmGRX9E89iMTXi62lj2XHNK+HqYHUnk2gwD4o5nXQz45DZIiLlCYwv4V8o6aiaoJnho2l9Bpz7IuWkNGxFxOl5uLkzuVY/HZ25iadRpHpm2gXHdatOiSoDZ0URExAGl243MtWseaVJWxRpxPIYBF45kHTVzchtcPHN5W4sV/EP/NXImHAKrg7vW/RLJb1SwERGn5OFqY0L3Ojzx1RZ+/TOGx2du4tOHbqNt9SCzo4mIiIOZu/kY+04l4OfpSr/bK5gdRwo6w4BzB7KOmjm5LWMHp/+y2KBElX9GzQSHQ0A1cNP6SyIFgQo2IuK03F1sjO1WmyHfbOPHbScY+NUWPnzQTsfwkmZHExERB5GUms7oJXsBGHhHBfw8XU1OJAWK3Z6xbfbJbXBiy1/Fme2QHHt5W6trRnHm71EzQeEZxRlXjQgTKahUsBERp+ZqszK6SzhuNivfbT7G4NlbSU6182C9ELOjiYiIA/hy3RGOX7hEoK8HPRqWNTuO5Gf2dDizN+u0pujtkJJweVube0Yx5t8LApeoCi7ueRxaRByZCjYi4vRsVgvv3V8TD1crX647wvPfbSc5LZ3u+mAuIlKgxSelMvb3fQAMblkJD1ebyYkk30hPgzNRWRcEjt4BqRcvb+viAYE1/lkQODgcioeBTaO9ROTaVLARkXzBarXwZqfquLvYmLzqIMO+/4PkNDuPNi1vdjQRETHJxBUHOZeYQvni3txfp5TZccRZpaXA6V1ZFwOO2QlpSZe3dfXOKM5kbqMdDv6VwaZfu0TkxulvDhHJNywWC8PuroKHq5XPlu7nzZ93kZSazqA7K5kdTURE8tiZhGS+WHEAgOdah+Jis5qcSJxCWjLE/JF1QeCYPyA95fK2bj4ZW2f/PWomqBYUqwhWjeQSkZyhgo2I5CsWi4Xn2oTi4Wrjw8V7eP/XPSSl2nmmdWUsFovZ8UREJI+M+W0fF1PSqVnKj7bVA82OI44o9VJGMSZzMeCtcGoX2NMub+vh99eImVr/LAhctDxYVQgUkdyjgo2I5DsWi4UnW1TCw9XK2wt2M+b3fSSlpvNy+yoq2oiIFABHz13ky3WHAXihbZj+7hdISYTonVkXBD69G4z0y9t6Fsm6jXZQLShSDvT/kYjkMRVsRCTf6nd7BdxdbIz44Q++WHmQ5DQ7r91TDatVH7hERPKzjxbvITXdoElFfxpX9Dc7juS15PiMrbP/Pa3pzB4w7Je39fL/1zbafxVo/EJUnBERh6CCjYjkaz0blcXdxcrQeTuYsfYwyWnpjOxcE5uKNiIi+dLu6DjmbT0OwPNtQ01OI7kuKfavwsy/FgQ+uw8wLm9bKDDrqJmgcPANVnFGRByWCjYiku91rV8ad1crz3yzjW82HiM5zc4HD9TSApQiIvnQ+4uiMAxoXyOImqUKmx1HctLFc1lHzZzYCucPXrmtb8nLpzX5aC0jEXEuKtiISIFw722lcHex8eTXW/h+6wmSU+188tBtuLmoaCMikl9sPHSOJbtOYbNaGNK6stlxJCfsXQKbp2UUaS4cuXIbv9IQ/PeCwLdl/LNQ8TyNKSKSG1SwEZEC464aQbjZrAz4cjML/4im7/SNjPnfbfh4uJodTUREbpFhGLy7cDcAD9YtRYXihUxOJLfkzF5Y9BLs/TXr8SLlLp/W5FXUjIQiIrlOBRsRKVBaVg3gi5516TdjI8v2nObez1bzRY+6lPX3NjuaiIjcgt+jTrHh0HncXaw82aKS2XHkZl26AMvfg3XjM7bXtrpCvUchtB0E1czYwUlEpIDQXAARKXBur1ycbx5rSICvO/tOJdDps1Ws3nfG7FgiInKT7HaDUQujAOjVqCxBfp4mJ5IbZk+HjVPg09qwZkxGsaZyWxiwFtq9A+WbqVgjIgWOCjYiUiDVLFWYHwY1oVZIYS5cTKX75PXMWHvY7FgiInITfth2gt3R8fh4uNC/eQWz48iNOrQSJjSDnwbDxbPgXxm6fQf/mw3+Fc1OJyJiGhVsRKTACvD1YHa/BnQKDybdbjBs/k6Gzd9Jarrd7GgiIpJNKWl2PlicMbrm8WYVKOzlZnIiybbzh+GbnjC1PcTsAA8/aPsu9F8NlVqanU5ExHRaw0ZECjQPVxsfdQmncqAP7y2KYsbaw+w7lcBn3WpTxFsf+kVEHN3X649w9Nwlivu407txWbPjSHakJMLKj2DVJ5CeDBYr1OkNd7wM3sXMTici4jA0wkZECjyLxcKA5hX5vHtdvN1srDlwlk6frWJvTLzZ0URE5BoSk9P49Le9ADzZohJebvou0qHZ7bBtNnxaN2Nh4fRkKNsUHlsBd3+oYo2IyH+oYCMi8pdWVQP4bkAjShXx5PDZi9z72Wp+333K7FgiInIVk1ce5ExCCmWKedG1XojZceRajm2Cya1hXj+IPwGFy0CXmdDzRwisbnY6ERGHpIKNiMi/hAX68v3AxtQvV5SE5DQembaBz5fvxzAMs6OJiMi/nEtM4fPlBwB4pnUorjZ9rHVIcSdhXn/44k44tgFcvaHFcBi4Hqp0AIvF7IQiIg5LPVs2jR07lrJly+Lh4UFERATr16+/atu5c+dSt25dChcujLe3N+Hh4cyYMSNLm169emGxWLI82rZtm9tvQ0SyoVghd2b2ieCh+iEYBry9YDfPfrud5LR0s6OJiMhfxi3dR3xyGlWDfLm7RpDZceS/UpNgxQfwaR3Y9lXGsVr/gyc2QdNnwNXD3HwiIk5AE32zYfbs2QwZMoTx48cTERHB6NGjadOmDVFRUZQoUeKy9kWLFuXll18mLCwMNzc3fvrpJ3r37k2JEiVo06ZNZru2bdsyZcqUzOfu7u558n5E5PrcXKy8fW8NQgN8eOPnXXy3+RgHzyQwvnsdSvjoQ6aIiJmOX7jEtDWHAXi+bShWq0ZpOAzDgN0/waKX4ULGfyNK1cvY/alUHXOziYg4GY2wyYYPP/yQvn370rt3b6pWrcr48ePx8vJi8uTJV2zfvHlz7r33XqpUqUKFChV46qmnqFmzJitXrszSzt3dncDAwMxHkSJF8uLtiEg2WSwWejUux9Te9fD1cGHzkQt0GrOKncdjzY4mIlKgfbxkDylpdiLKFaVZ5eJmx5G/Re+EaR1g9sMZxRqfIOg8ER75VcUaEZGboILNdaSkpLBp0yZatmyZecxqtdKyZUvWrFlz3fMNwyAyMpKoqChuv/32LK8tXbqUEiVKEBoaSv/+/Tl79myO5xeRW9e0UnHmD2xM+eLenIhN4oHxa1iw46TZsURECqR9p+KZs+kYAC+0C8OiNVDMl3gWfhoCE5rCoRVgc4fbn4NBG6Hmg2DVrxwiIjdDU6Ku48yZM6SnpxMQEJDleEBAALt3777qebGxsZQsWZLk5GRsNhufffYZrVq1yny9bdu2dO7cmXLlyrF//35eeukl2rVrx5o1a7DZbJddLzk5meTk5MzncXFxOfDuRCS7yhcvxLwBjXni6y0s33OaAV9uZnDLSjx5ZyUNxRcRyUPvL9qD3YDWVQOoXVqjk02VngobvoClIyHpr9GnVTtBq9ehSBlTo4mI5Acq2OQSHx8ftm7dSkJCApGRkQwZMoTy5cvTvHlzALp27ZrZtkaNGtSsWZMKFSqwdOlSWrRocdn1Ro4cyWuvvZZX8UXkCvw8XZncsy5vL9jN5FUHGb1kL3ti4nn/gVp4uemvUxGR3Lb16AUW/hGN1QLPtgk1O07Btm8JLBwKZ/ZkPA+oAe3egbJNzM0lIpKPaHzidfj7+2Oz2YiJiclyPCYmhsDAwKueZ7VaqVixIuHh4TzzzDPcf//9jBw58qrty5cvj7+/P/v27bvi60OHDiU2NjbzcfTo0Zt7QyJyS1xsVoZ3qMqo+2riarOwYEc0D4xfw4kLl8yOJiKSrxmGwbu/ZIxu7ly7FJUDfExOVECd2QdfdYGZ92UUa7yKQYeP4bFlKtaIiOQwFWyuw83NjTp16hAZGZl5zG63ExkZScOGDbN9HbvdnmVK038dO3aMs2fPEhR05W0p3d3d8fX1zfIQEfM8WC+Er/o2oJi3G3+ciOOeMavYdPi82bFERPKtFXvPsObAWdxsVga3rGR2nIInKTZj56fPGsCehWB1gYaD4InNUKcXWC+f0i8iIrdGBZtsGDJkCBMnTmTatGns2rWL/v37k5iYSO/evQHo0aMHQ4cOzWw/cuRIFi9ezIEDB9i1axcffPABM2bM4OGHHwYgISGB5557jrVr13Lo0CEiIyPp2LEjFStWzLLtt4g4tnpli/L9oMaEBfpwJiGZhz5fy3d/LYQpIiI5x243GLUoY3TNww3KUKqIl8mJChB7OmyaCp/UhjVjwJ4KldrAgLXQ5i3wLGx2QhGRfEuLLmRDly5dOH36NMOHDyc6Oprw8HAWLlyYuRDxkSNHsP5r9fvExEQGDBjAsWPH8PT0JCwsjJkzZ9KlSxcAbDYb27dvZ9q0aVy4cIHg4GBat27NG2+8gbu7uynvUURuTqkiXnzXvxFPz97Kr3/G8My329gTE8/zbcOwaTFiEZEcsWDnSXYej6OQuwsD76hgdpyC49AqWPgCRO/IeF6sErQdCZVaXfs8ERHJERbDMAyzQ8iNi4uLw8/Pj9jYWE2PEnEAdrvBR0v28OlvGetQ3RlWgo+7huPj4WpyMpHcoX4o+3Svbk1qup3WHy3n4JlEnm5Zmac0HSr3XTgCi4fDH/Mynrv7QfMXoX5fsKlfE3Em6oOcm6ZEiYjkAKvVwjOtQ/m4azjuLlZ+232Kzp+t5vDZRLOjiYg4tW82HuXgmUSKebvRp2k5s+PkbymJ8NtbMKZeRrHGYoW6j8CTm6HhABVrRETymAo2IiI5qGN4Sb55rCEBvu7sPZVAx7GrWL3/jNmxRESc0qWUdD5esheAQXdWpJC7ZvPnCsOA7d/Ap3Vh+ShIS4KyTeGx5XD3R+Dtb3ZCEZECSQUbEZEcViukMD8MakKtUn5cuJhKj0nrmbn2sNmxREScztTVhzgVn0ypIp78L6K02XHyp+ObYFJrmNsX4k9A4dLw4Azo+SME1jA7nYhIgaaCjYhILgjw9WD2Yw3pGB5Mmt3glfk7GTZ/J6npdrOjiYg4hdiLqYxbmrEu2JBWlXF30bbROSo+GuYPgIl3wrH14OoNdw6DgRug6j1g0cL5IiJm07hSEZFc4uFqY3SXcEIDfXhvURQz1h5m/+kEPutWm8JebmbHExFxaOOW7ScuKY3QAB86hpc0O07+kZoEaz+DFR9ASkLGsVoPQYsR4BtkbjYREclCI2xERHKRxWJhQPOKTHi4Dl5uNlbvP0vHsavYdyre7GgiIg4rOjaJKasOAvBcm1BsVo32uGWGAbt+gs8iIPK1jGJNybrwaCTcO17FGhERB6SCjYhIHmhdLZC5AxpRqognh89e5N6xq/l99ymzY4mIOKRPfttLcpqdumWK0KJKCbPjOL+YP2D6PTC7G5w/BD5BcO8E6LMYStU1O52IiFyFCjYiInkkLNCX7wc2pn7ZosQnp/HItA18vnw/hmGYHU1ExGEcPJPI7A1HAXihXRgWraVy8y6eg5+fgfFN4OBysLlD02dh0Eao1RWs+lVARMSR6W9pEZE8VKyQOzMfjaBrvRAMA95esJtnv91Oclq62dFERBzCB79GkW43uDOsBPXKFjU7jnNKT4W14+GT22DDF2DYoco9MGg9tBgG7oXMTigiItmgRYdFRPKYm4uVkZ1rEBrowxs//cl3m49x8EwCE7rXpbiPu9nxRERMs+NYLD9tP4nFkrF2jdyEfZGwcCicicp4HlAd2r4D5Zqam0tERG6YRtiIiJjAYrHQu3E5pj1SH18PFzYfuUDHMSvZeTzW7GgiIqYZtWg3AB1rBVMlyNfkNE7m7H74qivM7JxRrPEqBnePhseWq1gjIuKkVLARETFR00rFmT+wMeX9vTkRm8QD49fwy46TZscSEclzq/edYcXeM7jaLAxppdE12ZYUC7++AmMjYM8vYHWBBgPhic1QtzdYbWYnFBGRm6SCjYiIycoXL8S8gY1pWsmfS6np9P9yMx8v2avFiEVuwtixYylbtiweHh5ERESwfv36q7Zt3rw5Fovlskf79u0z2/Tq1euy19u2bZsXb6VAMQyDdxdlTOH5X/3SlC7mZXIiJ2BPh83T4dM6sPpTsKdCxVbQfw20fRs8C5udUEREbpEKNiIiDsDP05UpverxSONyAHy0ZA+DvtrCpRQtRiySXbNnz2bIkCGMGDGCzZs3U6tWLdq0acOpU6eu2H7u3LmcPHky87Fz505sNhsPPPBAlnZt27bN0u7rr7/Oi7dToCz6I4ZtRy/g5WZj0J2VzI7j+A6vhs+bww9PQOJpKFYJ/vctPDwHilc2O52IiOQQLTosIuIgXGxWhneoSmhgIV6Zv5Ofd5zk0NlEJvaoS3BhT7PjiTi8Dz/8kL59+9K7d28Axo8fz88//8zkyZN58cUXL2tftGjWHYhmzZqFl5fXZQUbd3d3AgMDcy94AZeWbue9v9au6dOknBZfv5YLR2HxcPhjbsZzdz9o/gLU6wsubuZmExGRHKcRNiIiDqZLvdJ8+WgDinq78ceJOO4Zs4rNR86bHUvEoaWkpLBp0yZatmyZecxqtdKyZUvWrFmTrWtMmjSJrl274u3tneX40qVLKVGiBKGhofTv35+zZ89e8zrJycnExcVlecjVzd18nP2nEyns5Urf28ubHccxpSTC72/DmLp/FWssUKc3PLkZGg5UsUZEJJ9SwUZExAHVL1eU7wc2JizQhzMJyXT9fC1zNx8zO5aIwzpz5gzp6ekEBARkOR4QEEB0dPR1z1+/fj07d+7k0UcfzXK8bdu2TJ8+ncjISN59912WLVtGu3btSE+/+nTFkSNH4ufnl/kICQm5uTdVACSlpvPRkj0ADGxeEV8PV5MTORjDgB1zYEw9WPYupCVBmSYZOz91GA3e/mYnFBGRXKQpUSIiDiqkqBff9W/E4NlbWfxnDEO+2UZUTDzPtwnDZrWYHU8kX5k0aRI1atSgfv36WY537do1899r1KhBzZo1qVChAkuXLqVFixZXvNbQoUMZMmRI5vO4uDgVba5i5trDnIxNIsjPg+4Ny5gdx7Ec3wwLX4Sj6zKe+5WGNm9ClXvAoj5ARKQg0AgbEREH5u3uwoSH6zDojooATFh2gL7TNxKflGpyMhHH4u/vj81mIyYmJsvxmJiY664/k5iYyKxZs+jTp891f0758uXx9/dn3759V23j7u6Or69vlodcLi4plbG/Z9zHp1tWxsNV208DEB8D8wfCxDszijWuXnDnKzBoPVTtqGKNiEgBooKNiIiDs1otPNsmlI+7huPuYuW33afo/Nlqjpy9aHY0EYfh5uZGnTp1iIyMzDxmt9uJjIykYcOG1zz322+/JTk5mYcffvi6P+fYsWOcPXuWoKCgW85c0E1cfoDzF1OpUNybzrVLmh3HfGnJsHI0fFobts4EDKjZFZ7YBLc/B65afF5EpKBRwUZExEl0DC/JN481pISPO3tPJXDP2JWs3n/G7FgiDmPIkCFMnDiRadOmsWvXLvr3709iYmLmrlE9evRg6NChl503adIkOnXqRLFixbIcT0hI4LnnnmPt2rUcOnSIyMhIOnbsSMWKFWnTpk2evKf86nR8Ml+sOAjAc21CcbEV4I+khgG7f4axEbBkBKQkQMk60GcJdJ4AvsFmJxQREZNoDRsRESdSK6QwPz7RhH7TN7LtWCw9Jq3n1Xuq8XADrf0g0qVLF06fPs3w4cOJjo4mPDychQsXZi5EfOTIEazWrIWBqKgoVq5cya+//nrZ9Ww2G9u3b2fatGlcuHCB4OBgWrduzRtvvIG7u7aevhVjftvLpdR0aoUUpk21ArxlesyfsGgoHFia8bxQILR8FWp2AWsBLmKJiAgAFsMwDLNDyI2Li4vDz8+P2NhYzY0XKYCSUtN5fs52fth2AoAeDcsw7O6quBbkb6klT6kfyj7dq6yOnL1Iiw+Xkppu8FXfCBpVKIA7HV08l7FN98bJYKSDzR0aDYImQ8C9kNnpRCQfUR/k3DTCRkTECXm42vi4azihgT68tyiK6WsOs/90AmP/V5vCXm5mxxMRuaqPluwhNd2gaSX/glesSU/NKNL8/jYkXcg4VqUDtHoDipYzNZqIiDgefRUrIuKkLBYLA++oyOfd6+DlZmPVvrN0GruKfafizY4mInJFu07GMX/rcQCebxNmcpo8tv83GN8Efnk+o1gTUB16/ghdZqpYIyIiV6SCjYiIk2tdLZC5AxpRqognh85e5N6xq/k96pTZsURELvPeoigMA9rXDKJGKT+z4+SNs/vh64dgxr1wejd4FoX2H0K/ZVDudrPTiYiIA1PBRkQkHwgL9OX7gY2pX7Yo8clp9Jm6gYnLD6BlykTEUaw/eI7fdp/CZrXwTKvKZsfJfUlxsHh4xu5PUQvA6gINBsCTm6FeH7BpZQIREbk2FWxERPKJYoXcmfloBF3rhWA34K0Fu3huznaS09LNjiYiBZxhGIxauBuALvVCKF88Hy+sa7fD5hnwaR1Y9THYU6FCC+i/GtqOBM8iZicUEREnodK+iEg+4uZiZWTnGoQG+vDGT38yZ9MxDp5JZPzDdSjuo22IRcQcv+0+xcbD53F3sfJUi0pmx8k9h9fAwhfg5LaM58UqQpu3oVJrsFjMzSYiIk5HI2xERPIZi8VC78blmNq7Pj4eLmw6fJ6OY1byx4lYs6OJSAGUbjcYtTAKgN6NyxHg62Fyolxw4SjMeQSmtM0o1rj7Quu3oP8aqNxGxRoREbkpKtiIiORTt1cuzvyBjSnv782J2CTuH7eGhTtPmh1LRAqY77ceJyomHl8PF/o3q2B2nJyVchF+Hwlj6sHO7wAL1OkFT2yGRoPAxc3shCIi4sRUsBERyccqFC/EvAGNaVrJn0up6Tw+czOfRO7VYsQikieS09L5cPEeAB5vXgE/L1eTE+UQw4AdczIKNcvegbRLUKYxPLYMOnwMhYqbnVBERPIBFWxERPI5Py9XpvSqxyONywHw4eI9DPp6C5dStBixiOSur9cd4dj5S5Twcad3o3Jmx8kZJ7bA5LbwXR+IOwZ+peGBadDrZwiqZXY6ERHJR7TosIhIAeBiszK8Q1UqBxRi2Pc7+Xn7SQ6fTWRij7oE+XmaHU9E8qGE5DQ+/W0fAE+1rISnm83kRLcoPgZ+ex22fAkY4OoFTYZkTH1y1d+jIiKS8zTCRkSkAOlavzQz+0RQ1NuNncfjuGfMKjYfOW92LBHJhyatOMjZxBTKFvPiwbohZse5eSkXYcUHGdt0b5kJGFCzCwzaCM2eU7FGRERyjQo2IiIFTET5Ynw/sDFhgT6cjk+m6+drmbv5mNmxRCQfOZuQzMQVBwB4pnUorjYn/MhpT88o0HxaByJfh5R4CK4NfRZD58/Br6TZCUVEJJ9zwt5TRERuVUhRL+b0b0SrqgGkpNkZ8s023vllN+l2LUYsIrfus6X7SUhOo1qwL+1rBJkd58YYBuxdDOObwPcDIf5Exjo1nSfCo5EQUt/shCIiUkCoYCMiUkAVcndhwsN1GHhHxja745ftp9/0jcQnpZqcTESc2fELl5ix5jAAL7QNw2q1mJzoBpzYAtPvgS/vh1N/gkdhaP0mDNoANR8Eqz46i4hI3lGvIyJSgFmtFp5rE8bHXcNxd7ESufsU941bzZGzF82OJiJO6qPFe0hJt9OwfDGaVvI3O072nD8E3z0KnzeHg8vB5g6NnoSntkKjJ8DVw+SAIiJSEGmXKBERoWN4ScoW86bv9I3siUmg49iVfNatDg0rFDM7mog4kT0x8ZlrYj3fNhSLxcFH11w8l7Gg8PrPIT0l41jNLnDnK1C4tLnZRESkwNMIGxERAaBWSGF+GNSEmqX8OH8xle6T1vHlusNmxxIRJ/L+oijsBrSpFsBtpYuYHefqUpNg1cfwSTisGZNRrCnXDB5bnrGgsIo1IiLiAFSwyaaxY8dStmxZPDw8iIiIYP369VdtO3fuXOrWrUvhwoXx9vYmPDycGTNmZGljGAbDhw8nKCgIT09PWrZsyd69e3P7bYiIXFOgnwffPNaQDrWCSbMbvDxvJyO+30laut3saCLi4DYfOc+vf8ZgtcBzbULNjnNldjts/Tpj56fFwyEpFgKqw8PfQY/vIaiW2QlFREQyqWCTDbNnz2bIkCGMGDGCzZs3U6tWLdq0acOpU6eu2L5o0aK8/PLLrFmzhu3bt9O7d2969+7NokWLMtuMGjWKTz75hPHjx7Nu3Tq8vb1p06YNSUlJefW2RESuyMPVxiddwzN/4Zq25jA9p6znwsUUk5OJiKMyDIN3f9kNwP11SlGxhI/Jia5g/28w4XaY/zjEHQPfUtBpXMaomootwdGnb4mISIFjMQxDe7heR0REBPXq1WPMmDEA2O12QkJCeOKJJ3jxxRezdY3atWvTvn173njjDQzDIDg4mGeeeYZnn30WgNjYWAICApg6dSpdu3a97vXi4uLw8/MjNjYWX1/fm39zIiLXsOiPaJ6evZWLKemULebFFz3rUbFEIbNjiQNQP5R9BeFeLY06Ra8pG3BzsfL7s80pWdjT7Ej/OLkdlozIKNgAuPtB0yEQ8Ri4OlBOEZFcUBD6oPxMI2yuIyUlhU2bNtGyZcvMY1arlZYtW7JmzZrrnm8YBpGRkURFRXH77bcDcPDgQaKjo7Nc08/Pj4iIiGxdU0Qkr7SpFsh3/RtRsrAnh85e5N6xq/g96sqjC0WkYLLbDUYtjAKgR4MyjlOsuXAU5j2eMapm/29gdYUGAzN2fmoyWMUaERFxeNol6jrOnDlDeno6AQEBWY4HBASwe/fuq54XGxtLyZIlSU5Oxmaz8dlnn9GqVSsAoqOjM6/x32v+/dp/JScnk5ycnPk8Li7upt6PiMiNqhLkyw+DGtN/5mbWHzpHn6kbeOmuKvRpUs7xd4ARkVz3046T/HkyDh93FwbcUdHsOHDpPKz4ENZNgPS/PjtVvz9j56ei5czNJiIicgM0wiaX+Pj4sHXrVjZs2MBbb73FkCFDWLp06U1fb+TIkfj5+WU+QkJCci6siMh1FCvkzsxHI+haLwS7AW/+vIvn5mwnOS3d7GgiYqLUdDsf/Joxuqbf7eUp6u1mXpi0ZFg9Bj4Oh9WfZBRryjaFvr/D/ZNUrBEREaejETbX4e/vj81mIyYmJsvxmJgYAgMDr3qe1WqlYsWMb5nCw8PZtWsXI0eOpHnz5pnnxcTEEBQUlOWa4eHhV7ze0KFDGTJkSObzuLg4FW1EJE+5uVgZ2bkGlQN8ePPnP5mz6RgHzyQyoXsd/Au5mx1PREwwe8NRDp+9iH8hNx5pYlJBxG6Hnd/Bb6/DhSMZx4pXgVavQ6VWWkxYRESclkbYXIebmxt16tQhMjIy85jdbicyMpKGDRtm+zp2uz1zSlO5cuUIDAzMcs24uDjWrVt31Wu6u7vj6+ub5SEiktcsFguPNCnHlN718fFwYdPh83Qcs4o/T2iapkhBczEljY8j9wLwxJ2V8HY34XvAA8tgYnOY+2hGscYnCO4ZA/1XQeXWKtaIiIhT0wibbBgyZAg9e/akbt261K9fn9GjR5OYmEjv3r0B6NGjByVLlmTkyJFAxvSlunXrUqFCBZKTk1mwYAEzZsxg3LhxQMYvPIMHD+bNN9+kUqVKlCtXjmHDhhEcHEynTp3MepsiItnWrHJx5g9szKPTNnLwTCL3jVvNR13CaVv96iMPRSR/mbLqEKfjkylVxJOH6pfO2x8e8wcsHgH7Fmc8d/PJWEi4wQBw88rbLCIiIrlEBZts6NKlC6dPn2b48OFER0cTHh7OwoULMxcNPnLkCFbrP4OVEhMTGTBgAMeOHcPT05OwsDBmzpxJly5dMts8//zzJCYm0q9fPy5cuECTJk1YuHAhHh4eef7+RERuRoXihZg/oDGDvt7Mir1neHzmJoa0qswTd1bUYsQi+dyFiymMX7YfgGdaV8bNJY8Gbcceh9/fhq1fAgZYXaBuH2j2PHj7500GERGRPGIxDMMwO4TcuLi4OPz8/IiNjdX0KBExVVq6nbcW7GLKqkMA3F0ziPfur4Wnm83cYJKr1A9lX368VyN/2cWEZQcIC/RhwZNNsVpzuUibFAsrR8PazyAtKeNY1U7QYjgUq5C7P1tExInlxz6oINEIGxERuSUuNisjOlQjNMCHYd/v5KftJzl89iKf96hDkJ+n2fFEJIdFxyYx9a8C7fNtQ3O3WJOWAhsnw7J34dK5jGOlG2UsKBxSL/d+roiIiAPQosMiIpIjutYvzcw+ERT1dmPH8VjuGbOKLUfOmx1LRHLYx5F7SE6zU69sEe4ILZE7P8QwYOdcGFsPFr6QUazxrwxdv4beC1SsERGRAkEFGxERyTER5Yvx/cDGhAb4cDo+mS6fr2XelmNmxxKRHLL/dALfbMz4M/1827DcWa/q0Cr4ogXM6Q3nD0GhALh7NPRfA2F3aecnEREpMFSwERGRHBVS1IvvBjSiZZUAUtLsPD17G+8u3I3driXTRJzdh7/uId1u0CKsBPXKFs3Zi5/aDV91hal3wfFN4OoNzV+CJzZD3d5g00x+EREpWFSwERGRHFfI3YXPu9dhQPOMxUDHLd1PvxkbSUhOMzmZiNys7ccu8POOk1gs8Fzb0Jy7cNxJ+OFJGNcQ9vwCFlvGzk9PbYXmL4B7oZz7WSIiIk5EBRsREckVVquF59uG8XHXcNxcrCzZdYrOn63iyNmLZkcTkZvw3qIoAO4NL0lYYA7sNJIcD7+9BZ/Whs3TwLBD2N0wcB3c/SEUyqX1cURERJyExpaKiEiu6hhekjLFvOk3fSN7YhLoOHYlH3e9jdsrFzc7mohk06p9Z1ix9wyuNgtPt6p8axdLT4VNU2HpO3DxTMaxUvWh9RtQusEtZxUREckvNMJGRERyXXhIYX4Y1ISapfw4fzGVHpPX89SsLZyKSzI7mohch2EYvLtwNwDdIsoQUtTrZi8Ef/4AYyNgwbMZxZqiFeDBGdDnVxVrRERE/kMFGxERyROBfh5881hDejUqi9UC3289QYsPljF11UHS0u1mxxORq1i4M5rtx2LxcrMx8I6KN3eRI2thUmv4pjuc2w9e/nDX+xnTn6reo52fRERErkAFGxERyTMerjZevacaPwxqQq2QwsQnp/Hqj3/Scewqthw5b3Y8EfmPtHQ77/2asXbNo03LU9zH/cYucGYvzOoGk9vAsfXg6gW3P5+xoHD9vmBzzfnQIiIi+YTWsBERkTxXvaQf8/o34usNRxi1MIo/TsTRedxqutYrzQttQyns5WZ2RBEB5mw6xoHTiRTxcqVv03LZPzHhVMYaNZumgpEOFivc1h2aDwXfoFzLKyIikp+oYCMiIqawWi10iyhDm2qBvPPLbuZsOsbX64+w6I9oXmwXxv21S2G1apqEiFmSUtMZvWQvAAPvqIiPRzZGwyQnwJqxsOpjSE3MOBZ6F7QYASXCcjGtiIhI/qMpUSIiYir/Qu68/0AtvnmsIaEBPpxLTOH5Odt5cMIadp2MMzueSIE1fc0houOSCPbz4OEGZa7dOD0NNk7J2KJ76dsZxZqSdaDXAnjoaxVrREREboIKNiIi4hDqlyvKT0824eW7quDlZmPj4fPc/elK3vzpTxKS08yOJ1KgxF5KZezv+wEY3KoyHq62Kzc0DNi9AMY1hJ8GQ0IMFCkHD0yFRyOhbOM8yywiIpLfqGAjIiIOw9Vmpe/t5Yl8phl31Qgk3W7wxcqDtPhgKT9vP4lhGGZHFCkQJi4/QOylVCqVKMR9tUtdudGxjTDlLpj1EJzZA17FoN0oGLgeqt2rnZ9ERERukdawERERhxPk58ln3eqwNOoUI374g8NnLzLwq800reTP6x2rU87f2+yIIvnWqbgkJq08CMCzbUKx/XctqbP7IfI1+PP7jOcuHtBwIDR+Cjz88jitiIhI/qURNiIi4rCah5Zg0eDbGdyyEm4uVlbsPUObj5bz4eI9JKWmmx1PJF/69Ld9XEpNJzykMK2rBvzzQuIZWPAcjK3/V7HGArc9DE9shhbDVawRERHJYSrYiIiIQ/NwtTG4ZWV+HXw7t1cuTkq6nU8i99L6o+X8HnXK7Hgi+crhs4l8vf4IAC+0DcNisUDKRVj+PnwcDus/B3saVGoN/VdBx7HgV9Lc0CIiIvmUpkSJiIhTKOvvzbTe9Vi4M5rXfvyTI+cu0nvKBtpWC2R4h6oEF/Y0O6KI0/tw8R7S7Aa3Vy5Ow3KFYfMM+P0tiD+Z0SCoFrR6A8o3MzWniIhIQaCCjYiIOA2LxUK7GkE0rVycTyL3MmnlQRb+Ec3yvad5qkUlHmlSDlebBo+K3Iw/TsTy/dYTgMHrVY7BuCfh9K6MFwuXhhYjoFpnsOrPmIiISF5QjysiIk6nkLsLL91VhZ+fbEK9skW4mJLOyF920/6TFaw7cNbseCJO6b1FUdSwHODXIu9RdlHvjGKNR2Fo8zYM2gg17lexRkREJA9phI2IiDitsEBfvnmsId9tPs7bC3axJyaBLp+vpXPtkrx0VxX8C7mbHVHEKWzZtoXOB4Zzj/sauATY3KHB49DkafAsYnY8ERGRAkkFGxERcWoWi4X765SiZZUSvLcoiq/WH2Hu5uMs+TOG59qG8b/6pS/fllhEMlw8h7FsFNXXTeQ2Wxp2LFhrdYU7XobCIWanExERKdA0rlVERPKFwl5uvHVvDeYNaEz1kr7EJaUxbP5O7v1sFduPXTA7nohjSb0EKz+Cj8OxrBuHK2msNGpy/uElcO94FWtEREQcgAo2IiKSr4SHFOb7gU14vWM1fNxd2H4slo5jVzFs/k5iL6WaHU/EXPZ02PoVfFoHlrwKybHst5aje8qLrG44kWIV65qdUERERP6iKVEiIpLv2KwWejQsS9vqgYxcsJt5W44zY+1hftl5kpfuqsK9t5XEYtE0KSlADAP2R8LiERCzM+OYbynWlx9Il7Uh+Hq6M6ZZBXMzioiISBYaYSMiIvlWCR8PPuoSzld9I6hQ3JszCSkM+WYbXT9fy96YeLPjieSNk9tgRieYeV9GscbdD1q9TvKA9Ty9OwwDK/2bV8DP09XspCIiIvIvKtiIiEi+16iCP788dTvPtw3Fw9XKuoPnaPfxCt75ZTcXU9LMjieSOy4cgbn9YMLtcGAp2Nyg4SB4ais0foovN57i+IVLBPi607NhWZPDioiIyH+pYCMiIgWCm4uVAc0rsmRIM1pVDSDNbjB+2X5afrCMRX9EYxiG2RFFcsal8/DrKxnr1GyfnXGsxgMwaAO0eQu8ipKQnMaY3/cBMLhlZTzdbCYGFhERkSvRGjYiIlKglCrixcQedVnyZwyv/vgHx85f4rEZm7gzrASvdqhG6WJeZkcUuTmpSbBhIix/H5IuZBwrdzu0eh2Cb8vS9IsVBziXmEJ5f28eqFMq77OKiIjIdalgIyIiBVLLqgE0rujP2N/3MWH5fn7bfYpV+84w6I6K9GtWHncXjTgQJ2G3w845EPkGxB7JOFaiWkahpmIL+M8C22cSkpm4/AAAz7QOxcWmAdciIiKOSD20iIgUWJ5uNp5tE8rCwbfTuGIxktPsfLB4D21Hr2DF3tNmxxO5vgNL4fNmMLdvRrHGJxg6fgaPr4BKLS8r1gCM/X0fiSnp1CjpR7vqgXmfWURERLJFI2xERKTAq1C8EDP7RPDj9pO88dOfHDyTSPdJ67m7ZhDD7q5KgK+H2RFFsoreCUtGwL4lGc/dfaHJ0xDxOLhdfVrf0XMX+XJtxiic59uGYrVqe3sRERFHpYKNiIgIYLFYuKdWMM1Di/PR4j1MW32In7afZGnUaZ5uVZmeDcto6oiYL/YY/P42bP0KMMDqCvUehdufA+9i1z199JK9pKTbaVyxGE0rFc/9vCIiInLT9MlTRETkX3w9XBnRoRo/PtGE20oXJiE5jTd++pO7P13JpsPnzI4nBdna8Rk7P239EjCgWmcYtB7avZOtYk1UdDxztxwD4Pk2YbkcVkRERG6VCjYiIiJXUC3Yj+8eb8Q7nWtQ2MuV3dHx3DduDS/M2c65xBSz40lB5BMIaUlQpjE8+hs8MAWKls/26e8tisIwoF31QGqFFM69nCIiIpIjVLARERG5CqvVQtf6pfntmeZ0qRsCwOyNR7nzg6XMWn8Eu90wOaEUKFU7Qs8fodfPUKrODZ266fA5luyKwWrJ2BlKREREHJ8KNiIiItdR1NuNd++vyXf9GxIW6MOFi6m8OHcH941fzR8nYs2OJwWFxQLlbr/izk/XYhgG7/4SBcADdUKoWKJQbqQTERGRHKaCjYiISDbVKVOUn55owrC7q+LtZmPLkQt0+HQlr/34B/FJqWbHE7mipXtOs/7QOdxcrAxuVcnsOCIiIpJNKtiIiIjcABeblT5NyhH5THPurhmE3YApqw7R4oNl/LDtBIahaVJmGjt2LGXLlsXDw4OIiAjWr19/1bbNmzfHYrFc9mjfvn1mG8MwGD58OEFBQXh6etKyZUv27t2bF28lR9jtBqMWZoyu6dWoLEF+niYnEhERkexSwUZEROQmBPp5MOZ/tZnRpz7l/L05FZ/Mk19v4eFJ69h/OsHseAXS7NmzGTJkCCNGjGDz5s3UqlWLNm3acOrUqSu2nzt3LidPnsx87Ny5E5vNxgMPPJDZZtSoUXzyySeMHz+edevW4e3tTZs2bUhKSsqrt3VLftx+gl0n4/Bxd6F/swpmxxEREZEboIJNNt3IN3YTJ06kadOmFClShCJFitCyZcvL2vfq1euyb/Tatm2b229DRERyWNNKxVk4uCnPtKqMu4uVVfvO0nb0ct5fFMWllHSz4xUoH374IX379qV3795UrVqV8ePH4+XlxeTJk6/YvmjRogQGBmY+Fi9ejJeXV2bBxjAMRo8ezSuvvELHjh2pWbMm06dP58SJE8yfPz8P39nNSUmz88GvewB4rFl5ini7mZxIREREboQKNtlwo9/YLV26lIceeojff/+dNWvWEBISQuvWrTl+/HiWdm3bts3yzd7XX3+dF29HRERymLuLjSdaVGLx0824I7Q4qekGY37fR6uPlhG5K8bseAVCSkoKmzZtomXLlpnHrFYrLVu2ZM2aNdm6xqRJk+jatSve3t4AHDx4kOjo6CzX9PPzIyIiItvXNNPsDUc4cu4i/oXceaRJObPjiIiIyA1SwSYbbvQbuy+//JIBAwYQHh5OWFgYX3zxBXa7ncjIyCzt3N3ds3yzV6RIkbx4OyIikktKF/Nicq96jH+4DsF+Hhw7f4k+0zbSb/pGjp2/aHa8fO3MmTOkp6cTEBCQ5XhAQADR0dHXPX/9+vXs3LmTRx99NPPY3+fd6DWTk5OJi4vL8shrF1PS+DhyHwBPtaiIl5tLnmcQERGRW6OCzXXkxDd2Fy9eJDU1laJFi2Y5vnTpUkqUKEFoaCj9+/fn7NmzOZpdRETynsVioW31QBYPacZjzcrjYrXw658xtPpwOeOW7iclzW52RLmCSZMmUaNGDerXr3/L1xo5ciR+fn6Zj5CQkBxIeGMmrzzImYRkShf1oku90nn+80VEROTWqWBzHbf6jR3ACy+8QHBwcJaiT9u2bZk+fTqRkZG8++67LFu2jHbt2pGefuX1Dhzh2zoREck+b3cXhrarwoKnmlK/XFEupabz7sLd3PXJCtbsV4E+p/n7+2Oz2YiJyToFLSYmhsDAwGuem5iYyKxZs+jTp0+W43+fd6PXHDp0KLGxsZmPo0eP3shbuWXnE1OYsOwAAM+0roybiz7uiYiIOCP14LnsnXfeYdasWcybNw8PD4/M4127duWee+6hRo0adOrUiZ9++okNGzawdOnSK17HEb6tExGRG1c5wIfZ/Rrw4YO18C/kxr5TCTw0cS1Pz97KqXjn2GnIGbi5uVGnTp0s04//no7csGHDa5777bffkpyczMMPP5zleLly5QgMDMxyzbi4ONatW3fNa7q7u+Pr65vlkZfGLdtPfHIaYYE+dKgZnKc/W0RERHKOCjbXcSvf2L3//vu88847/Prrr9SsWfOabcuXL4+/vz/79u274utmf1snIiI3z2Kx0Ll2KSKHNKd7gzJYLDBvy3FafLCM6WsOkW43zI6YLwwZMoSJEycybdo0du3aRf/+/UlMTKR3794A9OjRg6FDh1523qRJk+jUqRPFihXLctxisTB48GDefPNNfvjhB3bs2EGPHj0IDg6mU6dOefGWbtjJ2EtMXX0IgBfahmG1WswNJCIiIjdNK9Bdx7+/sfv7w9nf39gNGjToqueNGjWKt956i0WLFlG3bt3r/pxjx45x9uxZgoKCrvi6u7s77u7uN/UeRETEMfh5ufJGp+o8ULcUr8zfyfZjsQz//g++2XiUNzvVIDyksNkRnVqXLl04ffo0w4cPJzo6mvDwcBYuXJg5rfnIkSNYrVm/q4qKimLlypX8+uuvV7zm888/T2JiIv369ePChQs0adKEhQsXZhk160g+XrKXlDQ79csVpXlocbPjiIiIyC2wGIahr/WuY/bs2fTs2ZMJEyZQv359Ro8ezTfffMPu3bsJCAigR48elCxZkpEjRwLw7rvvMnz4cL766isaN26ceZ1ChQpRqFAhEhISeO2117jvvvsIDAxk//79PP/888THx7Njx45sFWbi4uLw8/MjNjY2z4dai4jIrUu3G3y1/gijFu4mPikNiwX+V780z7cJw8/L1ex416V+KPvy6l7tO5VA64+WYTfgu/4NqVOm6PVPEhGRfE39tXPTlKhs6NKlC++//z7Dhw8nPDycrVu3XvaN3cmTJzPbjxs3jpSUFO6//36CgoIyH++//z4ANpuN7du3c88991C5cmX69OlDnTp1WLFihUbRiIgUEDarhe4NyvDbM83pXLskhgFfrjvCnR8sZc6mY+j7FLlRH/wahd2AllUCVKwRERHJBzTCxkmpUioikr+sPXCWYfN3svdUAgD1yxbljU7VCQ30MTnZlakfyr68uFfbjl6g49hVWCyw8KnbHfb/GxERyVvqr52bRtiIiIg4gAbli7HgqaYMbReGp6uN9YfOcdcnK3h7wS4Sk9PMjicObtSi3QDce1tJFWtERETyCRVsREREHISrzcpjzSqw5JlmtK0WSLrd4PPlB2j54TJ+2XFS06TkilbuPcOqfWdxs1l5umVls+OIiIhIDlHBRkRExMGULOzJ+O51mNKrHqWLenEyNon+X26m15QNHDqTaHY8cSB2u8G7CzNG13RrUJqQol4mJxIREZGcooKNiIiIg7ojrAS/Pn07T7aohJvNyrI9p2k9ejmjl+whKTXd7HjiAH7ZGc2O47F4u9kYeEdFs+OIiIhIDlLBRkRExIF5uNoY0qoyi56+naaV/ElJszN6yV7ajF7O0qhTZscTE6Wm23n/1ygAHm1aHv9C2mlSREQkP1HBRkRExAmU8/dm+iP1Gfu/2gT4unP47EV6TdnAgC83cTL2ktnxxARzNh3j4JlEinq78WjTcmbHERERkRymgo2IiIiTsFgstK8ZxJIhzejTpBw2q4UFO6Jp8cEyJi4/QGq63eyIkkeSUtMZvWQPAIPuqIiPh6vJiURERCSnqWAjIiLiZHw8XBl2d1V+HNSEOmWKcDElnbcW7OLuT1ay4dA5s+NJHpi6+hAxccmULOxJtwalzY4jIiIiuUAFGxERESdVNdiXbx9ryKj7alLEy5WomHgeGL+GZ7/dxtmEZLPjSS6JvZjKZ7/vA+DpVpVxd7GZnEhERERygwo2IiIiTsxqtfBgvRB+e6Y5D9UPATLWNrnzg2V8ue4wdrthckLJaROW7ycuKY3KAYW497aSZscRERGRXKKCjYiISD5QxNuNkZ1rMndAI6oG+RJ7KZWX5+3k3nGr2Xk81ux4kkNOxSUxedVBAJ5rE4bNajE5kYiIiOQWFWxERETykdqli/DDoMaM6FCVQu4ubDt6gXvGrGTE9zuJvZRqdjy5RZ/8tpekVDu1SxemZZUSZscRERGRXKSCjYiISD7jYrPSu3E5fnumGffUCsZuwLQ1h2nxwTLmbzmOYWialDM6dCaRWeuPAvBC2zAsFo2uERERyc9UsBEREcmnSvh68MlDt/HloxGUL+7NmYRkvlp/xOxYcpMmrjhAmt2geWhxIsoXMzuOiIiI5DIXswOIiIhI7mpc0Z9fnmrKxOUHaFU1UCMznNSwu6tSuqgXTSr5mx1FRERE8oAKNiIiIgWAu4uNQXdWMjuG3AIPVxuPNatgdgwRERHJI5oSJSIiIiIiIiLiYFSwERERERERERFxMCrYiIiIiIiIiIg4GBVsREREREREREQcjAo2IiIiIiIiIiIORgUbEREREREREREHo4KNiIiIiIiIiIiDUcFGRERERERERMTBqGAjIiIiIiIiIuJgVLAREREREREREXEwKtiIiIiIiIiIiDgYFWxERERERERERByMCjYiIiIiIiIiIg5GBRsREREREREREQejgo2IiIiIiIiIiINxMTuA3BzDMACIi4szOYmIiBREf/c/f/dHcnXqs0VExCzqr52bCjZOKj4+HoCQkBCTk4iISEEWHx+Pn5+f2TEcmvpsERExm/pr52QxVGpzSna7nRMnTuDj44PFYrmla8XFxRESEsLRo0fx9fXNoYR5x5nzK7t5nDm/M2cH587vzNkhZ/MbhkF8fDzBwcFYrZphfS3qszMou3mcOb8zZwfnzu/M2cG586u/lr9phI2TslqtlCpVKkev6evr63R/mf2bM+dXdvM4c35nzg7Ond+Zs0PO5dc3ddmjPjsrZTePM+d35uzg3PmdOTs4d37116ISm4iIiIiIiIiIg1HBRkRERERERETEwahgI7i7uzNixAjc3d3NjnJTnDm/spvHmfM7c3Zw7vzOnB2cP784939DZTePM+d35uzg3PmdOTs4d35nzi45S4sOi4iIiIiIiIg4GI2wERERERERERFxMCrYiIiIiIiIiIg4GBVsREREREREREQcjAo2BcDy5cvp0KEDwcHBWCwW5s+ff91zli5dSu3atXF3d6dixYpMnTo113NeyY1mX7p0KRaL5bJHdHR03gT+l5EjR1KvXj18fHwoUaIEnTp1Iioq6rrnffvtt4SFheHh4UGNGjVYsGBBHqTN6mayT5069bL77uHhkUeJsxo3bhw1a9bE19cXX19fGjZsyC+//HLNcxzhvsONZ3ek+34l77zzDhaLhcGDB1+znaPc/3/LTnZHuv+vvvrqZVnCwsKueY4j3veCzJn7a1CfrT77xjlzfw35q89Wf5131F/LjVDBpgBITEykVq1ajB07NlvtDx48SPv27bnjjjvYunUrgwcP5tFHH2XRokW5nPRyN5r9b1FRUZw8eTLzUaJEiVxKeHXLli1j4MCBrF27lsWLF5Oamkrr1q1JTEy86jmrV6/moYceok+fPmzZsoVOnTrRqVMndu7cmYfJby47gK+vb5b7fvjw4TxKnFWpUqV455132LRpExs3buTOO++kY8eO/PHHH1ds7yj3HW48OzjOff+vDRs2MGHCBGrWrHnNdo50//+W3ezgWPe/WrVqWbKsXLnyqm0d8b4XdM7cX4P6bPXZN86Z+2vIP322+uu8p/5ass2QAgUw5s2bd802zz//vFGtWrUsx7p06WK0adMmF5NdX3ay//777wZgnD9/Pk8y3YhTp04ZgLFs2bKrtnnwwQeN9u3bZzkWERFhPPbYY7kd75qyk33KlCmGn59f3oW6QUWKFDG++OKLK77mqPf9b9fK7qj3PT4+3qhUqZKxePFio1mzZsZTTz111baOdv9vJLsj3f8RI0YYtWrVynZ7R7vvkpUz99eGoT7bTM7eZztzf20Yztdnq7/Oe+qv5UZohI1cZs2aNbRs2TLLsTZt2rBmzRqTEt248PBwgoKCaNWqFatWrTI7DgCxsbEAFC1a9KptHPXeZyc7QEJCAmXKlCEkJOS63zDllfT0dGbNmkViYiINGza8YhtHve/ZyQ6Oed8HDhxI+/btL7uvV+Jo9/9GsoNj3f+9e/cSHBxM+fLl6datG0eOHLlqW0e773Lj8st/Q/XZOctZ+2xn7q/Befts9dfmUH8t2eVidgBxPNHR0QQEBGQ5FhAQQFxcHJcuXcLT09OkZNcXFBTE+PHjqVu3LsnJyXzxxRc0b96cdevWUbt2bdNy2e12Bg8eTOPGjalevfpV213t3psxn/9v2c0eGhrK5MmTqVmzJrGxsbz//vs0atSIP/74g1KlSuVh4gw7duygYcOGJCUlUahQIebNm0fVqlWv2NbR7vuNZHe0+w4wa9YsNm/ezIYNG7LV3pHu/41md6T7HxERwdSpUwkNDeXkyZO89tprNG3alJ07d+Lj43NZe0e673JznLm/BvXZucEZ+2xn7q/Bufts9dfqr8XxqWAj+UpoaCihoaGZzxs1asT+/fv56KOPmDFjhmm5Bg4cyM6dO685P9VRZTd7w4YNs3yj1KhRI6pUqcKECRN44403cjvmZUJDQ9m6dSuxsbHMmTOHnj17smzZsqt+iHIkN5Ld0e770aNHeeqpp1i8eLHDLKSYXTeT3ZHuf7t27TL/vWbNmkRERFCmTBm++eYb+vTpk6dZRLJDfXbOc8Y+25n7a3DePlv9tfprcQ4q2MhlAgMDiYmJyXIsJiYGX19fh/+27krq169v6oeuQYMG8dNPP7F8+fLrVvCvdu8DAwNzM+JV3Uj2/3J1deW2225j3759uZTu2tzc3KhYsSIAderUYcOGDXz88cdMmDDhsraOdt9vJPt/mX3fN23axKlTp7J8O56ens7y5csZM2YMycnJ2Gy2LOc4yv2/mez/Zfb9/7fChQtTuXLlq2ZxlPsuNy+/9degPvtWOGuf7cz9NThvn63+Wv21OAetYSOXadiwIZGRkVmOLV68+JrzcR3Z1q1bCQoKyvOfaxgGgwYNYt68efz222+UK1fuuuc4yr2/mez/lZ6ezo4dO0y591dit9tJTk6+4muOct+v5lrZ/8vs+96iRQt27NjB1q1bMx9169alW7dubN269YofoBzl/t9M9v8y+/7/W0JCAvv3779qFke573Lz8uN/Q/XZNy6/9dnO3F+D8/TZ6q8d5/959ddyTeaueSx5IT4+3tiyZYuxZcsWAzA+/PBDY8uWLcbhw4cNwzCMF1980ejevXtm+wMHDhheXl7Gc889Z+zatcsYO3asYbPZjIULFzp89o8++siYP3++sXfvXmPHjh3GU089ZVitVmPJkiV5nr1///6Gn5+fsXTpUuPkyZOZj4sXL2a26d69u/Hiiy9mPl+1apXh4uJivP/++8auXbuMESNGGK6ursaOHTscPvtrr71mLFq0yNi/f7+xadMmo2vXroaHh4fxxx9/5Gl2w8j4/2LZsmXGwYMHje3btxsvvviiYbFYjF9//fWK2R3lvt9Mdke671fz350bHPn+/9f1sjvS/X/mmWeMpUuXGgcPHjRWrVpltGzZ0vD39zdOnTp1xeyOfN8LKmfur28mv/ps87I7yt9dztxf30x+R7nvV6P+Om+ov5YboYJNAfD3tpn/ffTs2dMwDMPo2bOn0axZs8vOCQ8PN9zc3Izy5csbU6ZMyfPcf+e4kezvvvuuUaFCBcPDw8MoWrSo0bx5c+O3334zJfuVcgNZ7mWzZs0y38vfvvnmG6Ny5cqGm5ubUa1aNePnn3/O2+DGzWUfPHiwUbp0acPNzc0ICAgw7rrrLmPz5s15nt0wDOORRx4xypQpY7i5uRnFixc3WrRokfnhyTAc974bxo1nd6T7fjX//RDlyPf/v66X3ZHuf5cuXYygoCDDzc3NKFmypNGlSxdj3759ma87030vqJy5v/47i/ps9dk3wpn7a8PIf322+uu8of5aboTFMAwj58ftiIiIiIiIiIjIzdIaNiIiIiIiIiIiDkYFGxERERERERERB6OCjYiIiIiIiIiIg1HBRkRERERERETEwahgIyIiIiIiIiLiYFSwERERERERERFxMCrYiIiIiIiIiIg4GBVsREREREREREQcjAo2IiLXYLFYmD9/vtkxRERE5DrUZ4tIfqOCjYg4rF69emGxWC57tG3b1uxoIiIi8i/qs0VEcp6L2QFERK6lbdu2TJkyJcsxd3d3k9KIiIjI1ajPFhHJWRphIyIOzd3dncDAwCyPIkWKABlDn8eNG0e7du3w9PSkfPnyzJkzJ8v5O3bs4M4778TT05NixYrRr18/EhISsrSZPHky1apVw93dnaCgIAYNGpTl9TNnznDvvffi5eVFpUqV+OGHHzJfO3/+PN26daN48eJ4enpSqVKlyz6sioiIFATqs0VEcpYKNiLi1IYNG8Z9993Htm3b6NatG127dmXXrl0AJCYm0qZNG4oUKcKGDRv49ttvWbJkSZYPd+PGjWPgwIH069ePHTt28MMPP1CxYsUsP+O1117jwQcfZPv27dx1111069aNc+fOZf78P//8k19++YVdu3Yxbtw4/P398+4GiIiIOAn12SIiN8gQEXFQPXv2NGw2m+Ht7Z3l8dZbbxmGYRiA8fjjj2c5JyIiwujfv79hGIbx+eefG0WKFDESEhIyX//5558Nq9VqREdHG4ZhGMHBwcbLL7981QyA8corr2Q+T0hIMADjl19+MQzDMDp06GD07t07Z96wiIiIk1KfLSKS87SGjYg4tDvuuINx48ZlOVa0aNHMf2/YsGGW1xo2bMjWrVsB2LVrF7Vq1cLb2zvz9caNG2O324mKisJisXDixAlatGhxzQw1a9bM/Hdvb298fX05deoUAP379+e+++5j8+bNtG7dmk6dOtGoUaObeq8iIiLOTH22iEjOUsFGRByat7f3ZcOdc4qnp2e22rm6umZ5brFYsNvtALRr147Dhw+zYMECFi9eTIsWLRg4cCDvv/9+jucVERFxZOqzRURyltawERGntnbt2sueV6lSBYAqVaqwbds2EhMTM19ftWoVVquV0NBQfHx8KFu2LJGRkbeUoXjx4vTs2ZOZM2cyevRoPv/881u6noiISH6kPltE5MZohI2IOLTk5GSio6OzHHNxcclcJPDbb7+lbt26NGnShC+//JL169czadIkALp168aIESPo2bMnr776KqdPn+aJJ56ge/fuBAQEAPDqq6/y+OOPU6JECdq1a0d8fDyrVq3iiSeeyFa+4cOHU6dOHapVq0ZycjI//fRT5odPERGRgkR9tohIzlLBRkQc2sKFCwkKCspyLDQ0lN27dwMZu0HMmjWLAQMGEBQUxNdff03VqlUB8PLyYtGiRTz11FPUq1cPLy8v7rvvPj788MPMa/Xs2ZOkpCQ++ugjnn32Wfz9/bn//vuznc/NzY2hQ4dy6NAhPD09adq0KbNmzcqBdy4iIuJc1GeLiOQsi2EYhtkhRERuhsViYd68eXTq1MnsKCIiInIN6rNFRG6c1rAREREREREREXEwKtiIiIiIiIiIiDgYTYkSEREREREREXEwGmEjIiIiIiIiIuJgVLAREREREREREXEwKtiIiIiIiIiIiDgYFWxERERERERERByMCjYiIiIiIiIiIg5GBRsREREREREREQejgo2IiIiIiIiIiINRwUZERERERERExMGoYCMiIiIiIiIi4mD+D8jLz/3LY+uCAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = SGD, lr = 0.001\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.696 | Train Acc: 50.58%\n",
            "\t Val. Loss: 0.690 |  Val. Acc: 53.36%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.684 | Train Acc: 55.88%\n",
            "\t Val. Loss: 0.684 |  Val. Acc: 57.91%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.680 | Train Acc: 58.56%\n",
            "\t Val. Loss: 0.681 |  Val. Acc: 58.18%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.675 | Train Acc: 59.87%\n",
            "\t Val. Loss: 0.677 |  Val. Acc: 58.09%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.670 | Train Acc: 61.06%\n",
            "\t Val. Loss: 0.673 |  Val. Acc: 58.82%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = RMSprop, lr = 0.001\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.556 | Train Acc: 72.02%\n",
            "\t Val. Loss: 0.642 |  Val. Acc: 69.73%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.391 | Train Acc: 83.65%\n",
            "\t Val. Loss: 0.465 |  Val. Acc: 76.36%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.308 | Train Acc: 87.60%\n",
            "\t Val. Loss: 0.460 |  Val. Acc: 76.27%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.240 | Train Acc: 91.08%\n",
            "\t Val. Loss: 0.439 |  Val. Acc: 79.09%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.193 | Train Acc: 93.46%\n",
            "\t Val. Loss: 0.452 |  Val. Acc: 79.55%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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yPj4+DB8+HMB+Lho5ciRjxozhmWeeoUaNGkRERLBp0ya2bNlC06ZNU/04lixZQsuWLSlatCgjR44kKiqKzz77jDp16rBlyxb7B/jnn3+e3377jZdeeomyZcty8eJFVq9ezd69e3nooYeIiYmhefPmREdH8/LLL5M3b15OnTrFX3/9xZUrV/D39wds/Z8feuihJGPx9/enWLFirFmzhkGDBqX6MSTYvXs39erVw8/Pj1dffRVXV1e++uorGjZsaP+Ad6uXXnqJHDlyMHLkSPbv38/kyZM5fvy4PVnf6flPzuXLl2ndujXdu3enS5cuTJ48me7du/PTTz8xcOBAnn/+eR577DHGjh1L586dCQ0NTfaY6tixI8WLF3dYt3nzZiZOnOjwgSk9zlNgO36vX79+x8cL4OzsTM6cOVPcLikJH6iTu/1jjz1Gs2bNOHz4sP38/vPPP9O5c+ckc2ZISAjHjx/HMIw75vCnn36aMWPGYLVaWbBgAfXr1+eZZ57hk08+4ZFHHqFRo0YO+034EhoWFoafnx+PPPIIDz30EG+++SZbtmzhqaee4qGHHmLhwoXMnTs3ycdy8OBBdu/eTcOGDfH29ubvv//m1VdfpVatWvZz2v3k8ITz3DvvvEOuXLkYOnQo//vf/9i3b1+yOfzy5cv2x5Zwvm7UqBE7d+5k1qxZjB49mly5cuHm5nbHHP7RRx8RHx+f6P3k5uZG5cqV2bp1q/15TCqHf/PNNwBUq1bN/p779ttviYqKwmKx0KBBAwICAoiLiwOwn5duzeHt2rVjzpw5DmPf3HpsHDp0iOLFi/PTTz8ph6eScriNcrhyuHJ40tIjhy9dupSTJ09SsGDBFO//+++/5+rVq/Tr148bN27Yc/jOnTsdXuu4uDiaN29O3bp1+fjjj/Hy8rqrcwDYCoUzZsygf//+uLu7M2nSJFq0aMGGDRsoX758ap+yFI0ePRo3NzeGDh1KdHR0kkWzBLfm8Dvx8vLCy8sr2et37txJXFwc1apVc1h/ew5PTsL1t9++atWqODk5sXXrVnr27El8fDw7duzgqaeeSrSPGjVqsGjRIq5evXpXeSpV7qkdkpF0t6MGDRoYgPHll18m2j6pJn7PPfec4eXl5dDHunfv3kZISIj9/4RmvLly5XJofjVnzhwDsDf3NYybzftuBRhubm4OTT23b99uAMZnn31mX9emTRvDy8vLOHXqlH3dwYMH7X3F78RqtRp+fn7Gq6++ahiGrUljrly5jC5duhjOzs7G1atXDcMwjPHjxxtOTk7G5cuXHeK7tZlwSs3WU/NYkjJ16lQDMMaPH5/ouoSmaQnPtZ+fn3H+/HmHbRKu+/bbb+3rkut6tmrVKoc++wkWLFiQaH1ISIgBGAsWLEi0n5CQEIemcjdu3EjUjPDo0aOGu7u7MWrUqOQf/H8S3p8pLalpnpfcvsqUKWMcOXLEvl3C+3TChAkp7jPh8dwptnXr1tm3feWVVwzAOHnypGEYhjF9+nTDw8PDiI6ONubPn284OzsbERERhmHcbE6/Zs0a++1vP9ZSarYOJHqeq1SpYlStWtVhHSk0W589e7YBGO+++67D+s6dOxsWi8X+/t68ebMBGAMHDnTYrk+fPoni/PbbbxMdN8k1m65UqVKiJp63S02z9cqVKxuBgYHGxYsX7eu2b99uODk5Gb169bKv8/f3v+PzsXXrVgMwfv3112S3iY2NNSwWizFkyJBkt2nWrJlRpkyZZK+/k/bt2xtubm4Ozd5Pnz5t+Pr6GvXr17evS3ieq1at6tAF46OPPjIAY86cOfZ1yT3/y5YtMwBj2bJl9nUJx9PPP/9sX7dv3z4DMJycnIx///3Xvn7hwoWJzkVJvf63CgsLMwoVKmRUqFDB3mw6rc5TSUl4/6S03Hr8pbSv/fv3G2FhYcaxY8eMqVOnGp6enkaePHkSde8OCQkxHn30USMuLs7ImzevMXr0aMMwDGPPnj0GYKxYscL+fN16/p4yZYp9XcmSJY233nrLWLVqlf2cm5DDE85Rnp6eRs+ePe05fP369QZglC1b1v64Es4bt+fwhHPA7Tm8TJkyibpmJGw3e/Zs+7qE16hixYr2dXeTw29vtr506VIDMPz9/Y3r16+nKocnvCdSWm49TyWVwz/++GMDMAYMGJDote/SpYuRN29ewzCSz+H9+vUznJycHF6bhByeJ08eo3v37oZh3DyfdujQweG2gPHFF18YgLFv3z7DMBIfGwnN1pXDU6YcrhyeFOVw5fD0yOG3dj1LyOFubm5Go0aNEuXwBLfm8IRzj2EY9hw+aNAg+7qE88brr7/usI/UngMM42YO37Rpk33d8ePHDQ8PD4d8dDduz+EJ78miRYumukvhveTwpCR0TV65cmWi627N4cnp16+f4ezsnOR1t+bwhPN7Urny9hx+u/vpepbmLYrc3d158sknE6339PS0X7569SrR0dHUq1ePr776in379lGpUqU77rdbt24OVdeEJntJjfR9uyZNmji0mKlYsSJ+fn7221qtVpYsWUKHDh0cftEqXrw4LVu2TPZXzgROTk7Url3b3oxu7969XLx4kddff53ff/+ddevW0bRpU1atWkX58uXJkSNHijHf62NJzu+//07u3Ll5+eWXE113e9O0Tp06pepX2OT8+uuv+Pv707RpU4df1KpWrYqPjw/Lli3jscces68vUqRIks0ob+fu7m6/bLVauXLlCj4+PpQqVcqhCXByxo0bl6g5alJS+lUzQeHChe2/5sbFxbF//34++ugjWrZsyapVq8iTJ4+92ePdVnj79u1Lly5dEq0vW7as/XLdunUZO3Ysq1atonv37qxZs4aqVavi5uZGrVq17E3VmzZtypo1a/Dw8EhUsb5bzz//vMP/9erVS7JF2Z3Mnz8fZ2dn+vfv77B+yJAh/Pbbb/z999+89NJL9i6VtzfHfPnll+9rJo4cOXKwe/duDh48SIkSJe5pH2fOnGHbtm28+uqrBAQE2NdXrFiRpk2bMn/+fIf7W79+PadPn07yvZXwa+PChQtp1apVkr9cXLp0CcMw7vjLVc6cOVP85SIpVquVRYsW0b59e4oWLWpfny9fPh577DG++eYbIiIiHJrU9u3b1+EXrRdeeIE33niD+fPn07Zt27uOAcDHx8dhJphSpUqRI0cOChQo4PBraMLl1Jz7Ex5fjx49uHr1Kv/88w/e3t5A+p2nwNbkOLlf/m91a15Mye2/flaoUIFvv/022V+6nJ2d6dq1K9OnT+fNN9/kp59+Ijg4mHr16iX53D311FNMnDiR3bt3c+TIEUaPHs3o0aMpWrQoP/zwA7Vr13bYvmXLlrRo0YIff/yRffv2UaNGDWrWrMnevXuTfJ/emsPnz5+Pk5MT8fHxDrHUrl2bvXv32s8BCRK6hCRo3rw5rq6u7Nmzx/6L4P3mcLCdpz09PdmzZ0+KOfynn34iKiqKpk2b8sQTT9CrVy/A9r76+uuv+eGHH8ibN6/DMQWJc3jCr+Pnz59PFJeHhwdRUVFA8jk8KirKITfCzRx+6+1v3LgBOHapuvV+EvaV8BhuPTYMw+DGjRvK4XdBOVw5/FbK4crhGZHDCxQowPjx41m2bBnLli27Yw5v3749BQoUsP+fkMPnz5/P+PHjHba9vcVhas8BCWrVqkXVqlXt/xcqVIh27doxd+5crFYrzs7OST4Hd6t3796pfk0ScnhKbs/ht0vYx+15GBxz+J1un1zLp1tvn9L93LpNWkrzQlGBAgWSfMC7d+/mzTff5J9//knUZ/DWPrzJKVSokMP/CSfb1HxouP22CbdPuO358+eJiopK1MwRSHJdUurVq2dvurpq1Sry5cvHQw89RKVKlVi1ahVNmzZl9erVdO3aNVX7u9fHkpzDhw9TqlSpJD8k3q5IkSL3HB/YmmqHh4c7NA+91e0fiFN7f/Hx8XzyySdMmjSJo0ePOjQZvFO3uwS3nqTSgre3t8P0lS1atKBu3bpUq1aNDz74gHHjxtkT89WrV+9q3yVKlEh2aswEderUwWKxsGbNGvuHzIRm1zly5KBs2bL2dWvWrEm273JqeXh4JCogpua9d7vjx4+TP3/+RB+8y5QpY78+4a+Tk1Oi90dqj8nkjBo1inbt2lGyZEnKly9PixYteOKJJxya6KfmMUDixA/Yxxy5du0a3t7efPTRR/Tu3Zvg4GCqVq1Kq1at6NWrlz35FClShMGDBzN+/Hh++ukn6tWrR9u2benZs6f9A2gC47a+37dfdy/9kcPCwrh+/XqyjyU+Pp7Q0FDKlStnX3/7h3MfHx/y5cuXaCyWu1GwYMFE8fv7+xMcHJxoHaTu3A/Y8868efMcvqCn13kKbB8sUvpwcbd+//13/Pz8CAsL49NPP+Xo0aMpfiB67LHH+PTTT9m+fTs///wz3bt3v+N7JCAggMKFC7Nz5042b97MjBkz+PLLL2ndujWzZ89mwoQJLF26FIBZs2bZpwVPyOElS5Zk48aNDl+GnJ2dsVqtDrnr+PHjFChQgNDQUIfXMaG7dcLxlSCp18jLy4vw8HDCwsIwDOO+czjYvjymNocndE0C2+udcL7etm0bYCsC3DreYoLbc3jCa5jUNMk3btywX59cDvf09CQmJsZhXcJ79dbbJ3yQTOiCdvv93BpLUsfGjBkzmDFjBqAcnhrK4crhyuHK4bfKiBzevHlzmjdvzvXr1xPl8H379jk8V0kVWUuWLJlorBsXF5dEXdlSew5I6b6uX79OWFiYfWy4+3U3r/GtOfx+JLyG0dHRia67NQff6fa35/Ckbp/S/dy6TVpK80JRUkFeuXKFBg0a4Ofnx6hRoyhWrBgeHh5s2bKF1157LdH4N0lJrtp4p5NuWtw2terWrUtsbCzr1q1j1apV9hZP9erVY9WqVezbt4+wsDD7+nuVEY/lft9o8fHxBAYG8tNPPyV5/e0fVFJ7f++//z5vvfUWTz31FKNHjyYgIAAnJycGDhyYqvfQpUuXkj0Yb4/n9uSeWlWrVsXf39/euqx06dKArQ9rWsuVKxelS5dm9erVREZGsmPHDkaMGGG/vnbt2qxevZqTJ09y4sQJ+wB09yqtKv5mq1+/PocPH2bOnDksWrSI//3vf0yYMIEvv/ySZ555Js3vr2vXrtSrV48//viDRYsWMXbsWD788ENmzZpFy5YtAdsv5X369LHH1L9/f8aMGcO///5LwYIFCQgIwGKx3PGD1eXLl+1ftLOi5N5f93POmz17Nh9++CGjR4+mRYsWDtel13kKIDIyksjIyBS3c3Z2TnXrzfr169tf3zZt2lChQgUef/xxNm/ebG8Rc7uaNWtSrFgxBg4cyNGjRx1+XU2Op6cnXl5e1KtXj3r16pE7d27eeecdHn30UfLkycOgQYMYNWoUPXv2pEKFCinmcDc3N6Kiou7rdUyLARlTw2q1pjqHh4WF2QsdkZGRnD17FrhZUAgLC7OPlXPreDm3Pw/58uUDSHI8jDNnzqTYOiZfvnxYrVaHL0UJHzwvXrxov31CS+akClJnzpwBbrbEuf3YaNOmDfXq1ePVV18FlMPTinL4vVEOz5yUw+8so3I4kGQO//vvv+ndu3eqbn8rd3f3ZOPLbO7mNb41h9/J7Tn8dgk5PCGP3upuc/ithbzbc3hAQADu7u7J3g+kvjXt3ciQV3758uVcvHiRadOmMWDAAFq3bk2TJk3ueQCwtBYYGIiHhweHDh1KdF1S65KSMIPFqlWrHD5k1q9fn/Xr19t/hU1uIOsE6fWBuFixYuzfvz9VA0GmVnKxFitWjIsXL1KnTh2aNGmSaEmpm2FyfvvtNxo1asSUKVPo3r07zZo1o0mTJkl+8E1Kx44dyZcvX4rLgAED7im+BFar1Z5gSpYsSalSpZgzZ06qks7dqlu3Ljt37mTRokVYrVaHpqW1a9dm/fr19pkpUmpGm1FfxkJCQjh9+nSiX2j37dtnvz7hb3x8PEePHnXYLrXHZEotJ5588kmmT59OaGgoFStWTDQ7TEqPAWyDI95u37595M6d2948GmyJ4MUXX2T27NkcPXqUXLly8d577zncrkKFCrz55pusXLmSVatWcerUKb788kvA9otOsWLFEj0Xtzp69Kj915y7kSdPHry8vJJ9LE5OTol+ETx48KDD/5GRkZw5c8ahBUVGvZ+Sc+DAAXr37k379u3ts2/eKr3OUwAff/xxqs41t85ccTd8fHwYMWIE27ZtS3FGjR49erB8+XLKlClD5cqV7/q+Erq6REZG2gcNBdt57vYcfuDAgVQNIpxwDrhdQveBhOMrQVLn+NjYWPuH9LTI4WA7zlKbw6tXr27/gDhu3Dj7azpq1CjA9pkgX758fPzxx3e8z4SBPG8f+DgmJoZt27bZX7PkcnjC9Zs2bXJYv2nTJuLj4+3XJ3zQv7XFQMIxun79eooWLWr/dfj2Y8PZ2Zn8+fMrhyuHA8rhyuEZQzncJq1y+O0FhtvfA2B7zpNqCXu71J4DUrovLy+v+xrq5H4k5PCUltTkcBcXl0Q5+PYcnpy7yeEVKlRItB0kzuFpKUMKRQnV5FurxzExMUyaNCkj7j5Fzs7ONGnShNmzZzt8eD106BB///13qvbh4eFB9erVmT59OidOnHD4NTIqKopPP/2UYsWK2T9YJichMaX2g1NqderUiQsXLvD5558nuu5eWyMlF2vXrl2xWq2MHj060W3i4uLu+bE5OzsnivXXX3/l1KlTqbr9uHHjWLx4cYpLwq+m92LZsmVERkY6JKh33nmHixcv8swzzyTZ7H/RokX89ddf93R/devWxWq18vHHH1OiRAmHE27t2rWJjIxk0qRJ9nG07iShn3Rav/du16pVK6xWa6L34oQJE7BYLPZf6BL6kt9+nvjss89SdT/e3t5JPpaLFy86/O/j40Px4sWTbM6ZnHz58lG5cmW+++47h/vYtWsXixYtolWrVoDtC8ftXWsDAwPJnz+//f4iIiISvS8qVKiAk5OTQ0y1atVKMkGArevP4cOHU3yNk+Ls7EyzZs2YM2eOw5fIc+fO8fPPP1O3bl2HsQ0Avv76a4cvrJMnTyYuLs7+2kHyz39GiIyMpEOHDhQoUIDvvvsuyQ+86XWeAtv4Bqk51yT3S2hqPP744xQsWJAPP/zwjts988wzjBgxgnHjxt1xu4RCyO1uHavj1vPvH3/8wSeffGL/f8OGDaxfv95hzIPkJJwDbpcwlfOt7yOwvRdvHcMmNDSU69evkz9/fpydndMkh4Pti0dqc/hPP/1kn477iSeesL+mCWM2TJ48mcWLF9vHLkqOv78/Hh4eHDlyxOFD9w8//EBkZKR9nJuEHP7WW285FJUeeeQRcubMyeTJkx32O3nyZLy8vBLNMHX06FH7eSQhhy9dutRhPB3lcOXwO1EOVw5Pb8rhN6VVDr+9a+Ls2bMdzr0JOfz2/JuU1J4DEqxbty5RDp8zZw7NmjUzraVjQg5PaUlNDm/SpAk//vjjHXM42FoO79u3L1EODwgISFUO79y5Mxs3bnQ4j+zfv59//vknyTHx0kKadz1LSu3atcmZMye9e/emf//+WCwWfvjhhzTtLnW/Ro4cyaJFi6hTpw4vvPCC/QAoX768fcyBlNSrV48PPvgAf39/KlSoANgSSqlSpdi/fz99+vRJcR8JffCHDx9O9+7dcXV1pU2bNg6/bNyLXr168f333zN48GA2bNhAvXr1uHbtGkuWLOHFF190GCg0tRJi7d+/P82bN8fZ2Znu3bvToEEDnnvuOcaMGcO2bdto1qwZrq6uHDx4kF9//ZVPPvmEzp073/X9tW7dmlGjRvHkk09Su3Ztdu7cyU8//ZTqfsRpPb5BeHg4P/74I3BzIMzJkyfj6enJ66+/bt+uW7du7Ny5k/fee4+tW7fSo0cPQkJCuHjxIgsWLGDp0qX8/PPPDvvesmWLfd+3KlasGLVq1bL/n/AL47p16xK9v0qWLEnu3LlZt24dFSpUSHEQdU9PT8qWLcuMGTMoWbIkAQEBlC9f/p6mrty0aRPvvvtuovUNGzakTZs2NGrUiOHDh3Ps2DEqVarEokWLmDNnDgMHDrT3Qa9atSqdOnVi4sSJXLx40T617oEDB4CUf+2qWrUqkydP5t1336V48eIEBgbyyCOPULZsWRo2bEjVqlUJCAhg06ZN9qlvbzd+/PhEAw06OTnxxhtvMHbsWFq2bEmtWrV4+umn7VPr+vv723/ZvHr1KgULFqRz585UqlQJHx8flixZwsaNG+1J/59//uGll16iS5culCxZkri4OH744QecnZ3p1KmT/X7btWvHDz/8wIEDByhZsqRDTEuWLMEwjETHcZ8+ffjuu+84evToHX8levfdd1m8eDF169blxRdfxMXFha+++oro6Gg++uijRNvHxMTQuHFjunbtyv79+5k0aRJ169Z1GAQzuec/I7zzzjvs2bOHN998kzlz5jhcl3AMpdd5CtJnfIPbubq6MmDAAF555RUWLFiQqFl+gpCQkFT90t6uXTsMw8DLy4spU6bY88PcuXOpUqUKx44do3fv3vTs2dN+m4Rj8fvvv2fOnDnkypWLChUqsH79+jveV8I5YNmyZcydO5fAwEAWLVrE7t27ARzGoQBb64HmzZs7TK0LUKVKFfs2I0eO5K+//qJYsWK8884795TDy5Qpw+zZs1OVw5Mbo8jf359PP/2UuXPn0r17dy5cuEBQUNAdc3jOnDk5d+4cDRo0oG/fvpw8eZJx48bRrFkz++vaq1cvPv30Uz788EPmzZvHCy+8YH+NunTpwtdff20vvv3yyy9s3ryZ9957z2GgXrC1Pnj00UcZOnSovbucu7s7ISEh/PLLL/Yc3qJFC8aMGcNvv/3GjRs3WLp0KbVr12bXrl2MGDGCIUOGpOo5vZVyuHK4crhyeGooh990Nzm8SJEitGnThmLFijnk8OrVq9OmTRuH7YsXL07dunV54YUXiI6OZuLEieTKlStVhfbUngMSlC9fPskc/s477zhsZ7FYaNCggb0VZXpKqzGKAN577z1q1659xxwOtmJco0aNGDFihP019fT0ZPTo0fTr148uXbrQvHlzVq1axY8//pgoh7/44ot888039hzu6urK+PHjCQoKSpST586dy/bt2wFbC+wdO3bYz+lt27ZN/Zhu9zRXmpH01OgNGjQwypUrl+T2a9asMR5++GHD09PTyJ8/v/Hqq6/ap0i8dYrF26f7TJjGb+zYsYn2yW3T1iVMQXj7NklNa3n7tK2GYZsit0qVKoabm5tRrFgx43//+58xZMgQw8PDI5lnwdG8efMMwGjZsqXD+meeecYAjClTpqT4GAzDMEaPHm0UKFDAcHJycpgu8m4eS1KuX79uDB8+3ChSpIjh6upq5M2b1+jcubN9Os07PdcJ1906nWVcXJzx8ssvG3ny5DEsFkui5/7rr782qlatanh6ehq+vr5GhQoVjFdffdU4ffq0Q+zJTXOa1NS6Q4YMMfLly2d4enoaderUMdatW5domsSMcPvUuhaLxQgICDDatm1rbN68OcnbLF261GjXrp0RGBhouLi4GHny5DHatGnjMB1pSlPrJvU658+f3wCMr7/+OtF1bdu2NQDjhRdeSHTd7ceaYRjG2rVrjapVqxpubm4O783evXsb3t7eifaR3DGX3JIwzefVq1eNQYMGGfnz5zdcXV2NEiVKGGPHjjXi4+Md9nXt2jWjX79+RkBAgOHj42O0b9/e2L9/vwEYH3zwgX27pKZWPXv2rPHoo48avr6+BmB/j7z77rtGjRo1jBw5chienp5G6dKljffee89hqtg7TY166zSWS5YsMerUqWN4enoafn5+Rps2bYw9e/bYr4+OjjZeeeUVo1KlSoavr6/h7e1tVKpUyZg0aZJ9myNHjhhPPfWUUaxYMcPDw8MICAgwGjVqZCxZssThuYiOjjZy585tfw5v1a1bN6Nu3bqJ1nfq1Mnw9PQ0Ll++nOi6223ZssVo3ry54ePjY3h5eRmNGjUy1q5d67BNwvO8YsUKo2/fvkbOnDkNHx8f4/HHH3eYYvhOz39yU+smlTuSOz/cfi68/fW/dVr2lI6h+z1Ppbc7TfMcHh5u+Pv7O5z/UhNrwvN167E7ffp0I0+ePIarq6vh6elpeHh4GGXLljWGDx9uRERE2HO4h4eHARgNGzY0+vbtawCGq6urUa9ePWP79u0O55XevXsbnp6eSeaVq1evGoDh4+NjPwc0bdo0yfNJhQoVjB9//NEoUaKE4e7ublSpUsUICgpyeC0T9pczZ84Uc3hyU+sOGzbMtBzeokULo3bt2oaHh4eRJ08eo1+/fvap0RMkTPucI0eORDn866+/NooWLWoARq5cuYwJEyY4nE8Tcsu4ceOMzp07G35+foa3t7dRuHBhIyAgIFEOv9MxdOtU8crhyuHK4crhyuHJS88cvnHjRvu66dOnG927dzeKFSuWZA5PcOt3vXHjxhnBwcGGu7u7PYffKrnzhmGk/hyQ8FrfnsNvff8k7A+wTwd/J8nl8F9//TXF26aXVatWpZjDE+K8/TODYdjex6VKlbJ/frk9hycIDQ2153AfHx+jdevWxsGDBxNtd6dj6Nbv8im550JRdtGuXTujePHiZochIv/ZunWrARg//vij2aFkuFGjRhlFihQx4uLi7OvOnDljeHh4GLNnz060fWBgoDF06NA0u/+kPpxI9nKnHxTSQ3LFldvNmzfPsFgsxo4dOxzWK4eLZC7K4crhYp6slsPFXFljGPMMEhUV5fD/wYMHmT9/Pg0bNjQnIJFs7vZjEmDixIk4OTmlODD8g2jQoEFERkbyyy+/2NdNnDiRChUqJGqyvnv3bqKionjttdcyOkyRDLds2TI6d+5s7zIGyuEiZlMOd6QcLpK0ZcuW0b17d4ccLubLkDGKsoqiRYvSp08fihYtyvHjx5k8eTJubm73NTCiiNy7jz76iM2bN9OoUSNcXFz4+++/+fvvv+nbt2+iWTyyAx8fH4dpsAE++OCDJLctV64cERERGRGWiOnGjh1Lvnz5GDZsmHK4SCahHO5IOVwkaWPHjjU7BEmCCkW3aNGiBdOnT+fs2bO4u7tTq1Yt3n//fUqUKGF2aCLZUu3atVm8eDGjR48mMjKSQoUKMXLkSIYPH252aCKSySiHi2QuyuEiIlmXxTAy0dRjIiIiIiIiIiJiGo1RJCIiIiIiIiIigApFIiIiIiIiIiLyH41RlA3Ex8dz+vRpfH19sVgsZocjIiLZnGEYXL16lfz58+PkpN+s7kQ5XEREMhPl8OxBhaJs4PTp09lydgkREcncQkNDKViwoNlhZGrK4SIikhkphz/YVCjKBnx9fQHbwezn52dyNCIikt1FREQQHBxsz0+SPOVwERHJTJTDswcVirKBhKbqfn5++pApIiKZhrpSpUw5XEREMiPl8AebOhWKiIiIiIiIiAigQpGIiIiIiIiIiPxHhSIREREREREREQE0RpGIiGQiVquV2NhYs8OQ++Tq6oqzs7PZYWQrOnayFh0jIiKSmalQJCIipjMMg7Nnz3LlyhWzQ5E0kiNHDvLmzavBLtOZjp2sS8eIiIhkVioUiYiI6RK+6AYGBuLl5aUvTlmYYRhcv36d8+fPA5AvXz6TI3qw6djJenSMiIhIZqdCkYiImMpqtdq/6ObKlcvscCQNeHp6AnD+/HkCAwPVxSad6NjJunSMiIhIZqbBrEVExFQJ46p4eXmZHImkpYTXU+PmpB8dO1mbjhEREcmsVCgSEZFMQV1mHix6PTOOnuusSa+biIhkVioUiYiIiIiIiIgIoEKRiIhIplG4cGEmTpxodhgiWY6OHRERkbSjQpGIiMhdslgsd1xGjhx5T/vduHEjffv2va/YGjZsyMCBA+9rHyLpJTMfOwmmT5+Os7Mz/fr1S5P9iYiIZDWa9UxEROQunTlzxn55xowZvP322+zfv9++zsfHx37ZMAysVisuLimn3Dx58qRtoCKZTFY4dqZMmcKrr77KV199xbhx4/Dw8EizfYuIiGQFalEkIiJyl/LmzWtf/P39sVgs9v/37duHr68vf//9N1WrVsXd3Z3Vq1dz+PBh2rVrR1BQED4+PlSvXp0lS5Y47Pf27jMWi4X//e9/dOjQAS8vL0qUKMGff/55X7H//vvvlCtXDnd3dwoXLsy4ceMcrp80aRIlSpTAw8ODoKAgOnfubL/ut99+o0KFCnh6epIrVy6aNGnCtWvX7iseyV4y+7Fz9OhR1q5dy+uvv07JkiWZNWtWom2mTp1qP4by5cvHSy+9ZL/uypUrPPfccwQFBeHh4UH58uX566+/7v0JExERMYEKRXJ3Lh+DtZ+ZHYWIPMAMw+B6TJwpi2EYafY4Xn/9dT744AP27t1LxYoViYyMpFWrVixdupStW7fSokUL2rRpw4kTJ+64n3feeYeuXbuyY8cOWrVqxeOPP86lS5fuKabNmzfTtWtXunfvzs6dOxk5ciRvvfUW06ZNA2DTpk3079+fUaNGsX//fhYsWED9+vUBW0uQHj168NRTT7F3716WL19Ox44d0/Q5k/ujY8fRvRw73377LY8++ij+/v707NmTKVOmOFw/efJk+vXrR9++fdm5cyd//vknxYsXByA+Pp6WLVuyZs0afvzxR/bs2cMHH3yAs7Pz/T0hIiL34Vp0HDM3hrLvbITZoUgWoq5nknrXL8GX9SA6AnKXhJLNzY5IRB5AUbFWyr690JT73jOqOV5uaZMaR40aRdOmTe3/BwQEUKlSJfv/o0eP5o8//uDPP/90aJFwuz59+tCjRw8A3n//fT799FM2bNhAixYt7jqm8ePH07hxY9566y0ASpYsyZ49exg7dix9+vThxIkTeHt707p1a3x9fQkJCaFKlSqArVAUFxdHx44dCQkJAaBChQp3HYOkHx07ju722ImPj2fatGl89pntB7Hu3bszZMgQjh49SpEiRQB49913GTJkCAMGDLDfrnr16gAsWbKEDRs2sHfvXkqWLAlA0aJF7+UpEBG5L4ZhsOXEZWZsDOWvHWe4HmPlsZqFeL+D8rakjloUSep5BUDV3rbLcwdA1BVTwxERycyqVavm8H9kZCRDhw6lTJky5MiRAx8fH/bu3Ztiq4iKFSvaL3t7e+Pn58f58+fvKaa9e/dSp04dh3V16tTh4MGDWK1WmjZtSkhICEWLFuWJJ57gp59+4vr16wBUqlSJxo0bU6FCBbp06cI333zD5cuX7ykOkTsx69hZvHgx165do1WrVgDkzp2bpk2bMnXqVADOnz/P6dOnady4cZK337ZtGwULFrQXiUREMlrY1Wi+WnGYJuNX0GnyOmZuOsn1GCtFcntTKsjX7PAkC1GLIrk7jYbDvvlw6TAsehPafW52RCLygPF0dWbPKHNaLHq6pl0XEW9vb4f/hw4dyuLFi/n4448pXrw4np6edO7cmZiYmDvux9XV1eF/i8VCfHx8msV5K19fX7Zs2cLy5ctZtGgRb7/9NiNHjmTjxo3kyJGDxYsXs3btWhYtWsRnn33G8OHDWb9+vb21hZhLx46juz12pkyZwqVLl/D09LSvi4+PZ8eOHbzzzjsO65OS0vUiIukhzhrP8v1hzNwUyj/7zhMXb+sK7OnqTKsK+ehWPZjqhXNisVhMjlSyEhWK5O64ekK7L+DblrD1ByjXAYon/cuaiMi9sFgsadaFJTNZs2YNffr0oUOHDoCtlcSxY8cyNIYyZcqwZs2aRHGVLFnSPo6Ki4sLTZo0oUmTJowYMYIcOXLwzz//0LFjRywWC3Xq1KFOnTq8/fbbhISE8McffzB48OAMfRySNB079+7ixYvMmTOHX375hXLlytnXW61W6taty6JFi2jRogWFCxdm6dKlNGrUKNE+KlasyMmTJzlw4IBaFYlIujsSFsnMTSf5fctJwq5G29dXDs5Bt+rBtK6YD18P1zvsQSR5D96nCUl/IbWg5nOw/ktbF7QX14G7mjKKiNxJiRIlmDVrFm3atMFisfDWW2+lW8ugsLAwtm3b5rAuX758DBkyhOrVqzN69Gi6devGunXr+Pzzz5k0aRIAf/31F0eOHKF+/frkzJmT+fPnEx8fT6lSpVi/fj1Lly6lWbNmBAYGsn79esLCwihTpky6PAaRBBlx7Pzwww/kypWLrl27JvrVvVWrVkyZMoUWLVowcuRInn/+eQIDA2nZsiVXr15lzZo1vPzyyzRo0ID69evTqVMnxo8fT/Hixdm3bx8Wi+WexhQTEbnd9Zg45u04w6+bTrLh2M3B+XN5u9GhSgG6Vg+mpLqYSRpQoUjuTeO34cAC2yxoi9+G1hPMjkhEJFMbP348Tz31FLVr1yZ37ty89tprRESkzwwkP//8Mz///LPDutGjR/Pmm28yc+ZM3n77bUaPHk2+fPkYNWoUffr0ASBHjhzMmjWLkSNHcuPGDUqUKMH06dMpV64ce/fuZeXKlUycOJGIiAhCQkIYN24cLVu2TJfHIJIgI46dqVOn0qFDhyS7ZnTq1IknnniCCxcu0Lt3b27cuMGECRMYOnQouXPnpnPnzvZtf//9d4YOHUqPHj24du0axYsX54MPPkjTWEUkezEMg62hV/h1Uyhzt58hMjoOACcLNCiZh27Vg3mkdBBuLhp+WNKOxdC8tg+8iIgI/P39CQ8Px8/PL+12fHQlfNfGdrn3XChSP+32LSLZxo0bN+yzCnl4eJgdjqSRO72u6ZaXHkB3eq507GRtev1E5E4uREbzx5ZTzNwUysHzkfb1Ibm86FotmE4PFSSvf8afO5TDswe1KJJ7V6Q+VHsKNk2FP1+GF9aCm3fKtxMREREREREHcdZ4Vh4MY+bGkyzZe84+MLWHqxOtyueja/VgahYJ0MDUku5UKJL703QUHFxs64K2dBS0/NDsiERERERERLKMYxeu8evmUH7bfJJzETcHpq4UnIOu1QrSplJ+/DQwtWQgFYrk/rj7QptP4MeOsP4rKNveNti1iIiIiIiIJCkqxsr8nWeYuSmU9UdvDkyd08uVDlUK0rV6QUrnVdcuMYcKRXL/ijeGKk/A1h9gTj94fjW4eZkdlYiIiIiISKZhGAbbT4Yzc1Moc7ed5up/A1NbLFC/hG1g6sZlAnF3cTY5UsnuVCiStNHsXTi0BC4dhuXv2/4XERERERHJ5i5di+GPraeYuTGU/eeu2tcHB3jStWownaoWJH8OTxMjFHGkQpGkDc8cti5oP3eFdV/YuqAVrGZ2VCIiIiIiIhnOGm+w8mAYv24KZfGec8RabQNTu7s40bJ8XrpWD+bhIrlwctLA1JL5qFAkaadkc6jYHXb8ArNfhOdWgqumexURERERkezhxMXr9oGpz4TfsK+vWNCfLtWCaVspP/6eGphaMjcViiRttRgDh/+BC/thxYfQZITZEYmIiIiIiKSbG7FWFuw6y4yNoaw7ctG+PoeXK+0rF6BrtWDK5tfA1JJ1qFAkacsrAFqPhxk9Yc0nULYt5K9idlQiIiIiIiJpxjAMdp2KYMamE8zZdpqrN24OTF23eG66VQ+madkgDUwtWZIKRZL2yrSBch1h9yyY3Q/6LgcXN7OjEhHJdBo2bEjlypWZOHGi2aGIZCk6dkTELJevxTB72ylmbAxl39mbA1MXzOlJl6rBdK5WkAIamFqyOCezA5AHVKux4JUbzu+GVePMjkZEJE21adOGFi1aJHndqlWrsFgs7Nix477vZ9q0aeTIkeO+9yOSWWTUsZMgKiqKgIAAcufOTXR0dJrtV0SyF2u8wcoDYfT7eQs131/KO3P3sO/sVdxcnGhbKT8/PVOTla80YkCTEioSyQNBLYokfXjnthWLfnsSVn0MZVpD3gpmRyUikiaefvppOnXqxMmTJylYsKDDdd9++y3VqlWjYsWKJkUnknll9LHz+++/U65cOQzDYPbs2XTr1i3N9i0iD77QS9f5dfNJft98klNXouzry+X3o1v1YNpVKoC/lwamlgePWhRJ+inXwdYNLT7ONguaNdbsiERE0kTr1q3JkycP06ZNc1gfGRnJr7/+ytNPP83Fixfp0aMHBQoUwMvLiwoVKjB9+vQ0jePEiRO0a9cOHx8f/Pz86Nq1K+fOnbNfv337dho1aoSvry9+fn5UrVqVTZs2AXD8+HHatGlDzpw58fb2ply5csyfPz9N4xO5XUYfO1OmTKFnz5707NmTKVOmJLp+9+7dtG7dGj8/P3x9falXrx6HDx+2Xz916lTKlSuHu7s7+fLl46WXXrqnOEQk67gRa2XOtlM8/r9/qffRMj5depBTV6Lw93Sld60Q/nq5LvP616NXrcIqEskDSy2KJP1YLNBqHBxbDWd32Aa3rj/U7KhEJLMzDIi9bs59u3rZzl0pcHFxoVevXkybNo3hw4dj+e82v/76K1arlR49ehAZGUnVqlV57bXX8PPzY968eTzxxBMUK1aMGjVq3Heo8fHx9iLRihUriIuLo1+/fnTr1o3ly5cD8Pjjj1OlShUmT56Ms7Mz27Ztw9XV9qG2X79+xMTEsHLlSry9vdmzZw8+Pj73HZeYSMeOg8OHD7Nu3TpmzZqFYRgMGjSI48ePExISAsCpU6eoX78+DRs25J9//sHPz481a9YQF2cbkHby5MkMHjyYDz74gJYtWxIeHs6aNWvu4ckRkaxg16lwZm4KZfbWU0T8NzA12Aam7lo9mGZlg/Bw1cDUkj2oUCTpyzcIWnwIf/SFFR9C6UchsIzZUYlIZhZ7Hd7Pb859v3Ea3LxTtelTTz3F2LFjWbFiBQ0bNgRsXWc6deqEv78//v7+DB16szj+8ssvs3DhQmbOnJkmhaKlS5eyc+dOjh49SnBwMADff/895cqVY+PGjVSvXp0TJ07wyiuvULp0aQBKlChhv/2JEyfo1KkTFSrYugUXLVr0vmMSk+nYcTB16lRatmxJzpw5AWjevDnffvstI0eOBOCLL77A39+fX375xV5ALVmypP327777LkOGDGHAgAH2ddWrV0/1/YtI5hd+PdY+MPWeMxH29QVyeNK5akE6Vy1IcICXiRGKmENdzyT9VewKJVuANQbm9ANrXMq3ERHJ5EqXLk3t2rWZOnUqAIcOHWLVqlU8/fTTAFitVkaPHk2FChUICAjAx8eHhQsXcuLEiTS5/7179xIcHGwvEgGULVuWHDlysHfvXgAGDx7MM888Q5MmTfjggw8cutT079+fd999lzp16jBixIg0HUBY5E4y4tixWq1899139OzZ076uZ8+eTJs2jfj4eAC2bdtGvXr17EWiW50/f57Tp0/TuHHj+3moIpIJxccbrD54gZenb6X6+0sY8edu9pyJwM3ZidYV8/HD0zVY+WojBjUtqSKRZFtqUSTpz2KB1hPgi3VwajP8+wXUGZDy7UQke3L1srVOMOu+78LTTz/Nyy+/zBdffMG3335LsWLFaNCgAQBjx47lk08+YeLEiVSoUAFvb28GDhxITExMekSepJEjR/LYY48xb948/v77b0aMGMEvv/xChw4deOaZZ2jevDnz5s1j0aJFjBkzhnHjxvHyyy9nWHySxnTs2C1cuJBTp04lGrzaarWydOlSmjZtiqdn8jMT3ek6EcmaTl2J4tdNofy6yXFg6jL5/OhWrSDtKhcgp7ebiRGKZB4qFEnG8MsPzd+DP1+Cf96DUq0gd4mUbyci2Y/FkuouLGbr2rUrAwYM4Oeff+b777/nhRdesI+5smbNGtq1a2dv0RAfH8+BAwcoW7Zsmtx3mTJlCA0NJTQ01N6qaM+ePVy5csXhPkqWLEnJkiUZNGgQPXr04Ntvv6VDhw4ABAcH8/zzz/P8888zbNgwvvnmGxWKsjIdO3ZTpkyhe/fuDB8+3GH9e++9x5QpU2jatCkVK1bku+++IzY2NlGrIl9fXwoXLszSpUtp1KjRfT5aETFLdJyVRbvPMXNTKKsPXcAwbOt9PVxoX7kA3aoHUy6/n/38IyI2KhRJxqnSE3b/AYeXwpyX4Mn54KQB4UQk6/Lx8aFbt24MGzaMiIgI+vTpY7+uRIkS/Pbbb6xdu5acOXMyfvx4zp07d9eFIqvVyrZt2xzWubu706RJEypUqMDjjz/OxIkTiYuL48UXX6RBgwZUq1aNqKgoXnnlFTp37kyRIkU4efIkGzdupFOnTgAMHDiQli1bUrJkSS5fvsyyZcsoU0ZjyEnGSM9jJywsjLlz5/Lnn39Svnx5h+t69epFhw4duHTpEi+99BKfffYZ3bt3Z9iwYfj7+/Pvv/9So0YNSpUqxciRI3n++ecJDAykZcuWXL16lTVr1qiYKpIF7DkdYRuYetsprly/OfNy7WK56FY9mObl8mpgapE7UKFIMo7FAm0+gUm1IPRf2PA1PPyC2VGJiNyXp59+milTptCqVSvy5785kPCbb77JkSNHaN68OV5eXvTt25f27dsTHh5+V/uPjIykSpUqDuuKFSvGoUOHmDNnDi+//DL169fHycmJFi1a8NlnnwHg7OzMxYsX6dWrF+fOnSN37tx07NiRd955B7AVoPr168fJkyfx8/OjRYsWTJgw4T6fDZHUS69j5/vvv8fb2zvJ8YUaN26Mp6cnP/74I/379+eff/7hlVdeoUGDBjg7O1O5cmXq1KkDQO/evblx4wYTJkxg6NCh5M6dm86dO6fNgxeRNBceFcuf204xc9NJdp66eb7I5+9Bl6oF6VItWGMOiaSSxTASGuDJgyoiIgJ/f3/Cw8Px8/MzOxzYNBX+GgQunvDiWgjQTDsi2dmNGzc4evQoRYoUwcPDw+xwJI3c6XXNdHkpE7vTc6VjJ2vT6ydy/+LjDf49cpEZm0JZsOss0XG2wepdnS00K5uXrtWDqVs8N85O6lqWVpTDswe1KJKM91Af2DULjq2CP/tDrz/BSRPwiYiIiIhIyk5fieK3zSf5dXMooZduDkxdOq8vXasF075KAQI0MLXIPVOhSDKekxO0/Qwm17YVizZPherPmB2ViIiIiIhkUtFxVpbsOc+MTaGsOhh2c2BqdxfaVs5P12rBVCzor4GpRdKACkVijoAi0GQk/P0qLB4BJZpBjkJmRyUiIiIiIpnIvrMRzNgYyuytp7h8y8DUDxcNoFv1YFqUy4enmwamFklL6u9jgi+++ILChQvj4eFBzZo12bBhwx23v3LlCv369SNfvny4u7tTsmRJ5s+fn0HRpqPqz0Kh2hATaeuCpuGyRERERESyvYgbsfz473Hafb6aFhNX8e2aY1y+HktePw9ealSc5UMb8kvfWnSoUlBFIpF0oBZFGWzGjBkMHjyYL7/8kpo1azJx4kSaN2/O/v37CQwMTLR9TEwMTZs2JTAwkN9++40CBQpw/PhxcuTIkfHBpzUnJ2j3ua0L2pFlsPUHeKiX2VGJiIiIiEgGMwyDf49c4tdNoczfdYYbsTcHpm5SJoiu1YOpXyKPBqYWyQAqFGWw8ePH8+yzz/Lkk08C8OWXXzJv3jymTp3K66+/nmj7qVOncunSJdauXYurqysAhQsXzsiQ01euYvDIm7DoTVg4HIo1Bv8CZkclIiaIj483OwRJQ3o9M46e66xJr5uIzdnwG/y+5SQzN4Vy/OJ1+/qSQT50rRZMhyoFyOXjbmKEItmPCkUZKCYmhs2bNzNs2DD7OicnJ5o0acK6deuSvM2ff/5JrVq16NevH3PmzCFPnjw89thjvPbaazg7J93MMjo6mujoaPv/ERERaftA0trDL8KeOXByI/w1EB6bCRqETiTbcHNzw8nJidOnT5MnTx7c3Nw0EGUWZhgGMTExhIWF4eTkhJubZp1JLzp2siYdIyIQExfP0r3nmLkplBUHwoj/bwQKH3cX2lTKT9dqBakcnEPnNBGTqFCUgS5cuIDVaiUoKMhhfVBQEPv27UvyNkeOHOGff/7h8ccfZ/78+Rw6dIgXX3yR2NhYRowYkeRtxowZwzvvvJPm8acbJ2do9wV8WQ8OLoLtv0DlHmZHJSIZxMnJiSJFinDmzBlOnz5tdjiSRry8vChUqBBOThoOMb3o2MnadIxIdnTg3FVmbgzlj62nuHgtxr6+RpEAulULpmWFvHi56SuqiNl0FGZy8fHxBAYG8vXXX+Ps7EzVqlU5deoUY8eOTbZQNGzYMAYPHmz/PyIiguDg4IwK+d7kKQUNX4el78CC16BYI/DNa3ZUIpJB3NzcKFSoEHFxcVitVrPDkfvk7OyMi4uLfgnOADp2siYdI5KdxMTFM2vLSX7ZGMq20Cv29YG+7nSuWpAu1YIpktvbvABFJBEVijJQ7ty5cXZ25ty5cw7rz507R968SRdF8uXLh6urq0M3szJlynD27FliYmKSbK7s7u6Ou3sW7Mdbu7+tC9qZbfDXYOj+k7qgiWQjFosFV1dX+3hsIpI6OnZEJDMyDIOFu88y5u999rGHXJwsNC4TSNdqwTQomQcXZ7WoE8mMdGRmIDc3N6pWrcrSpUvt6+Lj41m6dCm1atVK8jZ16tTh0KFDDgMeHjhwgHz58j14fdqdXaD9JHByhf3zYNfvZkckIiIiIiJ3aefJcLp9/S/P/7iF4xevk8fXnTdalWbdsMZ89UQ1GpcJUpFIJBPT0ZnBBg8ezDfffMN3333H3r17eeGFF7h27Zp9FrRevXo5DHb9wgsvcOnSJQYMGMCBAweYN28e77//Pv369TPrIaSvoHJQ/xXb5fmvQGSYufGIiIiIiEiqnAmPYvCMbbT5fDUbjl7Cw9WJ/o8UZ/nQhvStX4w8vlmw14NINqSuZxmsW7duhIWF8fbbb3P27FkqV67MggUL7ANcnzhxwmFQw+DgYBYuXMigQYOoWLEiBQoUYMCAAbz22mtmPYT0V28w7J0L53bC/KHQ9TuzIxIRERERkWRci47jqxWH+XrVEW7E2npCdKxSgKHNS5E/h6fJ0YnI3bIYhmGYHYSkr4iICPz9/QkPD8fPz8/scFLn9Db45hEwrND1eyjbzuyIREQkjWTJvGQSPVcikplZ4w1+33ySsYv2E3Y1GoAahQN4s3UZKhbMYW5wki6Ul7IHtSiSzCl/Zag7CFZ9DPOGQOF64BVgdlQiIiIiIgKsPXSB0fP2svdMBACFArx4o1VpmpfLqxn9RLI4FYok82rwKuybB2F74e/XoNM3ZkckIiIiIpKtHQ6LZMz8vSzZex4AXw8XBjQuwRO1QnB3cU7h1iKSFahQJJmXizu0/wL+1wR2zoTyHaFUS7OjEhERERHJdi5fi+GTpQf58d/jxMUbODtZeOLhEPo3LkGA9wM2G7NINqdCkWRuBapC7ZdhzScwdyAUqgWeOcyOSkREREQkW4iOs/LDuuN8uvQgETfiAGhSJpDXW5aheKCPydGJSHpQoUgyv4bDbF3QLh6ChcNtrYxERERERCTdGIbBwt1nGfP3Po5fvA5AmXx+vPloGeoUz21ydCKSnlQokszP1RPaTYKpzWHbj1CuA5RoYnZUIiIiIiIPpB0nr/DuX3vZcOwSAHl83XmlWSk6VS2Is5MGqhZ50KlQJFlDoZrw8Avw7ySY2x9e/Bc8NB2jiIiIiEhaOX0lio8X7mfW1lMAeLg60bdeUZ5rUAxvd311FMkudLRL1vHIW7D/b7h8FBa/DW0mmh2RiIiIiEiWdy06jq9WHObrVUe4ERsPQMcqBRjavBT5c3iaHJ2IZDQnswMQSTU3L2j7me3y5m/hyApz4xERkQfKF198QeHChfHw8KBmzZps2LAh2W1jY2MZNWoUxYoVw8PDg0qVKrFgwYL72qeISEazxhvM3BhKw4+X8+k/h7gRG0+NwgH8+VIdxnerrCKRSDalQpFkLUXqQfVnbJf/fAmiI82NR0REHggzZsxg8ODBjBgxgi1btlCpUiWaN2/O+fPnk9z+zTff5KuvvuKzzz5jz549PP/883To0IGtW7fe8z5FRDLSmkMXaP3Zal79fQdhV6MJyeXFlz0fYsZzD1OxYA6zwxMRE1kMwzDMDkLSV0REBP7+/oSHh+Pn9wCM6xMdCZNqQfgJqNEXWo01OyIREbkLmTEv1axZk+rVq/P5558DEB8fT3BwMC+//DKvv/56ou3z58/P8OHD6devn31dp06d8PT05Mcff7ynfSYlMz5XIpK1HQ6LZMz8vSzZayta+3q4MKBxCZ6oFYK7i7PJ0Ulmp7yUPahFkWQ97j7Q9lPb5Q1fw7E15sYjIiJZWkxMDJs3b6ZJk5szajo5OdGkSRPWrVuX5G2io6Px8PBwWOfp6cnq1avveZ8J+42IiHBYRETSwqVrMYyYs4vmE1ayZO95XJws9KldmBWvNOKZekVVJBIROxWKJGsq1gge6mW7/OdLEHPd3HhERCTLunDhAlarlaCgIIf1QUFBnD17NsnbNG/enPHjx3Pw4EHi4+NZvHgxs2bN4syZM/e8T4AxY8bg7+9vX4KDg+/z0YlIdhcdZ+WblUdoMHYZ3607Tly8QZMyQSwcVJ+RbcsR4O1mdogiksmoUCRZV7N3wa8AXDoCy94zOxoREclGPvnkE0qUKEHp0qVxc3PjpZde4sknn8TJ6f4+Wg0bNozw8HD7EhoamkYRi0h2YxgGf+88Q9PxK3lv/l6u3oijTD4/fn6mJv/rXY1ieXzMDlFEMikXswMQuWce/tDmE/ipM6z7Asq2g+AaZkclIiJZTO7cuXF2dubcuXMO68+dO0fevHmTvE2ePHmYPXs2N27c4OLFi+TPn5/XX3+dokWL3vM+Adzd3XF3d7/PRyQi2d320Cu8O28PG49dBiCPrzuvNC9Fp4cK4uxkMTk6Ecns1KJIsrYSTaHSY4ABc/pB7A2zIxIRkSzGzc2NqlWrsnTpUvu6+Ph4li5dSq1ate54Ww8PDwoUKEBcXBy///477dq1u+99iojcq9NXohg0YxvtvljDxmOX8XB1on/jEiwf2pCu1YJVJBKRVFGLIsn6WrwPh5fChQOw4gNoMtLsiEREJIsZPHgwvXv3plq1atSoUYOJEydy7do1nnzySQB69epFgQIFGDNmDADr16/n1KlTVK5cmVOnTjFy5Eji4+N59dVXU71PEZG0ci06ji9XHObrlUeIjosHoONDBXileSny+XuaHJ2IZDUqFEnW55kTWk+AXx6DNZ9CmbZQ4CGzoxIRkSykW7duhIWF8fbbb3P27FkqV67MggUL7INRnzhxwmH8oRs3bvDmm29y5MgRfHx8aNWqFT/88AM5cuRI9T5FRO6XNd7gt82hfLzoAGFXowGoUSSANx8tQ8WCOcwNTkSyLIthGIbZQUj6ioiIwN/fn/DwcPz8/MwOJ/389jTs+g0Cy0Lf5eCiMR5ERDKjbJOX0oCeKxFJzppDFxj91x72nb0KQEguL4a1LEPzckFYLOpiJulDeSl7UIsieXC0/AiOroDze2Dlx/DIcLMjEhERERFJU4fORzJm/l6W7jsPgJ+HC/0bl6BXrcK4uWgIWhG5fyoUyYPDOxe0+hh+7Q2rx0OZNpCvotlRiYiIiIjct0vXYvhkyQF+XH8Ca7yBi5OFng+HMKBxCXJ6u5kdnog8QFQokgdLufawqy3s/RPmvAjPLgNnV7OjEhERERG5J9FxVr5fe5xP/znI1RtxADQpE8SwVqUplsfH5OhE5EGkQpE8eB4dB8dWw9mdsHoiNHjF7IhERERERO6KYRgs2HWWMX/v48Sl6wCUzefHm4+WoXbx3CZHJyIPMhWK5MHjE2gbr2jWM7DiQyj9KASVNTsqEREREZFU2R56hXfn7WHjscsABPq6M7R5KTo9VBBnJw1ULSLpS4UieTBV6Ay7Z8H++bYuaE8vAWe93UVEREQk8zp9JYqxC/fzx9ZTAHi4OtG3fjGeq18Ub3d9lhWRjKGzjTyYLBZ4dDwcXwOnt8K6z6HuQLOjEhERERFJJDI6ji+XH+abVUeIjosHoONDBXileSny+XuaHJ2IZDcqFMmDyy8fNB9ja1G07H0o1QrylDQ7KhERERERAKzxBr9uCuXjRQe4EBkNQI0iAbz1aFkqFPQ3OToRya5UKJK7YhgGRy9co2hWmWGh8mOw+w84tBjm9IOnFoCTs9lRiYiIiEg2t/rgBd6dt4d9Z68CEJLLi2Ety9C8XBAWi8YhEhHzqFAkqRYeFcuAX7ay+fhl/h5Qj4I5vcwOKWUWC7SZCF88DCc3wPovoVY/s6MSERERkWzq0PlIxszfy9J95wHw83Chf+MS9KpVGDcXJ5OjExEBnYkk1bzdnImIiuXqjTgGz9yONd4wO6TU8S8Izd+1XV46Gi4eNjceEREREcl2Ll2L4e05u2g+cSVL953HxclCn9qFWfFKI56pV1RFIhHJNHQ2klRzcXZiQrfKeLs5s+HoJb5amYUKLg/1hiINIC4K/nwZ4uPNjkhEREREsoHoOCtfrzxMg7HL+H7dcazxBk3LBrFoUH1Gti1HTm83s0MUEXGgQpHclZBc3oxoWw6A8YsOsPNkuMkRpZLFAm0/A1dv20xom6aYHZGIiIiIPMAMw2D+zjM0Gb+C9+fv4+qNOMrm8+PnZ2vyTa9qWWfMTxHJdlQokrvWpWpBWpbPS1y8wYAZW4mKsZodUurkDIGm79guLx4Bl4+ZGo6IiIiIPJi2hV6hy5frePGnLYReiiLQ152xnSsy9+W61C6W2+zwRETuSIUiuWsWi4X3O1QgyM+dI2HXeHfeHrNDSr1qT0NIHYi9Bn/2ByOLjLMkIiIiIpneqStRDPxlK+2/WMOm45fxcHViQOMSLBvakC7VgnF20mxmIpL5qVAk9ySntxvjulQG4Kf1J1iy55y5AaWWk5OtC5qLJxxdAVu+MzsiEREREcniIqPj+Hjhfh75eDmzt50GoNNDBVk2tCGDmpbE212TTYtI1qFCkdyzuiVy80zdIgC89vsOwq5GmxxRKuUqBo3fsl1e+CaEnzQ3HhERERHJkqzxBr9sOEHDscv5fNkhouPiqVkkgLkv1WVc10rk8/c0O0QRkbumQpHcl1dalKJ0Xl8uXovh1d+2Y2SVrlw1n4eCNSDmKswdoC5oIiIiInJXVh+8wKOfruL1WTu5EBlN4VxefPVEVX7p+zAVCvqbHZ6IyD1ToUjui7uLM5/2qIKbixPL9ofxw7/HzQ4pdZycod0X4OwOh5bAtp/NjkhEREREsoBD56/y1LSN9Jyynn1nr+Ln4cJbrcuyaFADmpfLi8WicYhEJGtToUjuW8kgX4a1LA3Ae/P2cvDcVZMjSqU8JaHRMNvlhcMg4oy58YiIiIhIpnUxMpq35+yi+cRV/LPvPC5OFp6sU5gVrzTi6bpFcHPRVysReTDobCZpok/twtQvmYfouHgG/LKN6Dir2SGlTq2XIf9DcCMc5g1WFzQRERERcRAdZ+XrlYdp+PFyvl93HGu8QdOyQSwaVJ8RbcqR09vN7BBFRNKUCkWSJiwWCx93rkiAtxt7zkQwfvEBs0NKHWcXWxc0J1fYPx92/mZ2RCIiIiKSCRiGwfydZ2gyfgXvz9/H1RtxlM3nx8/P1uSbXtUomsfH7BBFRNKFCkWSZgL9PPigYwUAvl55hHWHL5ocUSoFlYUGr9ku//0KRJ43Nx4RERERMdW20Ct0+XIdL/60hdBLUQT6ujO2c0XmvlyX2sVymx2eiEi6UqFI0lSzcnnpUSMYw4DBM7cRfj3W7JBSp+5AyFsBoi7D/KFmRyMiIiIiJjh1JYoBv2yl/Rdr2HT8Mh6uTgxoXILlrzSkS7VgnJ00ULWIPPhUKJI091brshTJ7c2Z8BsMn70TIyuM++PsCu0mgZML7JkDu2ebHZGIiIiIZJDI6DjGLtzHIx8vZ8620wB0eqggy4c2YlDTkni5uZgcoYhIxlGhSNKcl5sLE7pVxtnJwl87zvDH1lNmh5Q6+SpC3cG2y/OGwLUs0nVORERERO6JNd5g+oYTNBy7nC+WHSY6Lp6aRQKY+1JdxnWtRF5/D7NDFBHJcCoUSbqoHJyDgY1LAPD2nN2EXrpuckSpVP8VCCwL1y/A36+aHY2IiIiIpJNVB8N49NNVDJu1kwuR0RTO5cXXT1Tll74PU6Ggv9nhiYiYRoUiSTcvNipOtZCcREbHMWjGNuKs8WaHlDIXN9ssaBYn2PUb7JtndkQiIiIikoYOnb/Kk99u4IkpG9h39ir+nq683bosiwY1oFm5vFgsGodIRLI3FYok3Tg7WZjQrTI+7i5sOn6ZycsPmx1S6hR4CGr3t13+a7BtgGsRERERydIuRkbz1uxdNJ+4imX7w3BxsvBkncKseKUhT9UtgpuLvhqJiIAKRZLOggO8GNWuHAATlx5kW+gVcwNKrYbDIHdJiDwLC94wOxoRERERuUex1ni+XnmYhmOX88O/x7HGGzQtG8SiQfUZ0aYcObzczA5RRCRTUaFI0l2HKgVoXTEf1niDgb9s5Vp0nNkhpczVw9YFDQts/xkOLjY7IhERERG5S9tCr9Dms9W8P38fV6PjKJffj+nPPsw3vapRNI+P2eGJiGRKKhRJurNYLLzXvgL5/T04dvE6o//aY3ZIqRNcA2r1s12eOwBuhJsbj4iIiIikyrXoON6Zu5sOk9aw7+xVcnq58lHnisx9qS61iuUyOzwRkUxNhSLJEP5erozrWhmLBX7ZGMqCXWfNDil1Gg2HgKIQcQoWvWV2NCIiIiKSgmX7ztNswkq+XXMMw7C1bl8yuAFdqwXj5KSBqkVEUqJCkWSYWsVy0bd+UQCGzdrBuYgbJkeUCm5e0PZz2+Ut38HhZebGIyIiIiJJCrsazcvTt/LktI2cuhJFwZyefPdUDSZ0q0wuH3ezwxMRyTJUKJIMNaRpKcrl9+Py9ViG/rqd+HjD7JBSVrgO1Ohru/xnf4i+am48IiIiImJnGAYzN4XSZPwK5m4/jZMFnq1XhEWD6tOgZB6zwxMRyXJUKJIM5ebixCfdK+Pu4sSqgxf4bt0xs0NKncYjIEcIhJ+AJSPNjkZEREREgGMXrvH4/9bz6m87CI+KpVx+P+b0q8vwR8vi5eZidngiIlmSCkWS4YoH+vLmo2UAGPP3PvafzQItdNx9oO2ntssb/wfHVpsbj4iIiEg2FmuNZ9LyQzSfuJK1hy/i4erEsJalmdOvDhUK+psdnohIlqZCkZii58MhPFI6kJi4eAb8spXoOKvZIaWsaEOo2sd2ec5LEHPdzGhEREREsqXtoVdo+/kaPlqwn+i4eOoWz83CgfV5rkExXJz19UZE5H7pTCqmsFgsfNipIrm83dh39ipjF+w3O6TUaToa/ArC5aPwz2izoxERERHJNq5FxzFq7h46TFrD3jMR5PByZVyXSvzwdA1CcnmbHZ6IyANDhSIxTR5fdz7qXBGA/60+yuqDF0yOKBU8/KDtJ7bL/06GE/+aG4+IiIhINrBsv23K+6lrjhJvQPvK+Vk6uAGdqhbEYtGU9yIiaUmFIjFV4zJBPF6zEABDft3G5WsxJkeUCsWbQOWegAFz+kFslNkRiYiIiDyQLkRG03/6Vp781jblfYEcnkx7sjoTu1fRlPciIulEhSIx3ZuPlqVoHm/ORUTzxh87MQzD7JBS1vxd8MkLFw/B8jFmRyMiIiLyQDEMg1//m/L+z/+mvH+mbhEWD65Pw1KBZocnIvJAU6FITOfp5swn3arg4mTh711n+XXzSbNDSplnTmgz0XZ57WdwcrOp4YiIiIg8KI5fvEbPKet55bcdXLkeS9l8fszuV4c3W2vKexGRjKBCkWQKFQr6M7hZSQDe+XM3xy9eMzmiVCjVEip0BSMe5rwIcdFmRyQiIiKSZcVa45m8/DDNJqxkzaGLuLs48XrL0sx5qQ4VC+YwOzwRkWxDhSLJNJ6rX4waRQK4FmNl4IxtxFnjzQ4pZS0/BO88ELYPVo41OxoRERGRLGnHSduU9x8u2Ed0XDy1i+Vi4cD6PN+gGK6a8l5EJEPprCuZhrOThQndKuPr4cLWE1f47J9DZoeUMq8AeHSc7fKq8XBmu7nxiIiIiGQh12PiePevPbT/wjblvb+nK2M7V+SnZ2pSOLemvBcRMYMKRZKpFMjhybvtywPw2T8H2Xz8sskRpULZdlC2PRhWmN0P4rLAzG0iIiIiJltxIIxmE1byv9W2Ke/bVsrP0iEN6FItWFPei4iYSIUiyXTaVS5A+8r5iTdg0IxtREbHmR1Sylp9DF654NxOWD3B7GhEREREMq2LkdEM/GUrvadu4ORl25T33/apzqc9qpBbU96LiJhOhSLJlEa1L0+BHJ6cuHSdkX/uNjuclPnkgZYf2S6vHAvnskDMIiIiIhnIMAx+33ySJuNXMHubbcr7p+oUYdGg+jQqrSnvRUQyCxWKJFPy83BlQrfKOFngt80nmb/zjNkhpax8JyjdGuJjYfaLYM0CLaFEREREMsCJi9fpNXUDQ37dzuXrsZTO68sfL9bh7TZl8XbXlPciIpmJCkWSadUoEsALDYsBMGzWTs6G3zA5ohRYLLaBrT1ywJltsPZTsyMSERERMVWcNZ6vVhym2cQVrDp4AXcXJ15tUYq5L9elUnAOs8MTEZEkqFAkmdrAJiWpWNCf8KhYhvy6jfh4w+yQ7sw3L7T4wHZ5+RgI229uPCIiIiIm2XUqnHZfrGHM3/u4ERtPraK5WDCwPi82LK4p70VEMjGdoU3wxRdfULhwYTw8PKhZsyYbNmxIdttp06ZhsVgcFg8PjwyM1lyuzk5M6FYZT1dn1hy6yNQ1R80OKWWVukOJZmCNgTn9IN5qdkQiIiIiGeZ6TBzvzdtD289Xs/u0bcr7jzpX5Odna1JEU96LiGR6KhRlsBkzZjB48GBGjBjBli1bqFSpEs2bN+f8+fPJ3sbPz48zZ87Yl+PHj2dgxOYrlseHN1uXAeCjBfvZczrC5IhSYLFA64ng7gcnN8K/k82OSERERCRDrDwQRvOJK/lmlW3K+zaV8rNkcAO6asp7EZEsQ4WiDDZ+/HieffZZnnzyScqWLcuXX36Jl5cXU6dOTfY2FouFvHnz2pegoKAMjDhzeKxGIZqUCSLGGs/AGVu5EZvJW+n4F4Bm79ou/zMaLh42Nx4RERGRdHTpWgyDZmyj19QNhF6KIr+/B1P7VOOzHlXI46sp70VEshIVijJQTEwMmzdvpkmTJvZ1Tk5ONGnShHXr1iV7u8jISEJCQggODqZdu3bs3n3nqdejo6OJiIhwWLI6i8XCh50qkNvHnQPnIvng731mh5Syh3pB0UYQdwPmvATx8WZHJCIiIpKmDMNg1paTNB63nD+2nsJigT61C7NocAMeKZ39ftwUEXkQqFCUgS5cuIDVak3UIigoKIizZ88meZtSpUoxdepU5syZw48//kh8fDy1a9fm5MmTyd7PmDFj8Pf3ty/BwcFp+jjMksvHnbFdKgIwbe0xVhwIMzmiFFgs0PZTcPOBE2th4zdmRyQiIiKSZkIv2aa8Hzzz5pT3s16ozci25fDRlPciIlmWCkWZXK1atejVqxeVK1emQYMGzJo1izx58vDVV18le5thw4YRHh5uX0JDQzMw4vTVqFQgvWuFADD01+1cjIw2OaIU5CgETd+xXV4yEi4fMzMaERERkfsWZ43n65WHaTrBNuW9m4sTrzS3TXlfpVBOs8MTEZH7pEJRBsqdOzfOzs6cO3fOYf25c+fImzdvqvbh6upKlSpVOHToULLbuLu74+fn57A8SIa1KkOJQB/Crkbz+qydGIZhdkh3VvUpKFwPYq/Dny9DZo9XREREJBm7ToXTftIa3p9vm/L+4aIBLBhQj36NNOW9iMiDQmfzDOTm5kbVqlVZunSpfV18fDxLly6lVq1aqdqH1Wpl586d5MuXL73CzPQ8XJ2Z2L0yrs4WFu85xy8bM3mLKScnWxc0Vy84uhI2f2t2RCIiIiJ3JSrGyvvz99LuizXsOhWBn4cLH3aqwPRnH6ZoHh+zwxMRkTSkQlEGGzx4MN988w3fffcde/fu5YUXXuDatWs8+eSTAPTq1Ythw4bZtx81ahSLFi3iyJEjbNmyhZ49e3L8+HGeeeYZsx5CplAuvz+vNC8FwKi5ezgSFmlyRCkIKAqN37ZdXvQ2XMnkxS0RERGR/6w6GEaziSv4euURrPEGj1bMx5IhDehWvZCmvBcReQBplLkM1q1bN8LCwnj77bc5e/YslStXZsGCBfYBrk+cOIGT08363eXLl3n22Wc5e/YsOXPmpGrVqqxdu5ayZcua9RAyjWfqFmX5/jDWHr7IoBnb+O2F2pm7yXON52D3bAj9F+b2h56zbANei4iIiGRCl67F8O68PczacgqAfP4evNu+PI3LaDYzEZEHmcXI9AO8yP2KiIjA39+f8PDwB268ojPhUbSYuIrwqFhealScof+1Msq0LhyCL+tA3A1o9wVU6Wl2RCIiGe5BzktpTc+VmMEwDOZsO82ov/Zw6VoMFgv0rlWYoc1LaTYzkWxOeSl7yMTNL0RSls/fk/c7VABg0vJDbDx2yeSIUpC7ODR6w3Z5wRsQcdrceERERERuEXrpOr2/3cjAGdu4dC2GUkG+/K4p70VEshUViiTLe7RiPjo9VJB4Awb+so2IG7Fmh3RntV6CAlUhOhz+GqRZ0ERERMR0cdZ4/rfqCM0mrGTlgTDcXJwY2qwkc1+uy0Oa8l5EJFtRoUgeCCPbliU4wJNTV6IYOWe32eHcmZMztJsEzm5wYAHsmGl2RCIiIpKN7T4dTodJa3l33l6iYq3UKBLA3wPq8dIjJXBz0dcFEZHsRmd+eSD4ergyoWtlnCwwa+sp5m7P5F26AktDg9dsl/9+Fa6eMzceERHhiy++oHDhwnh4eFCzZk02bNhwx+0nTpxIqVKl8PT0JDg4mEGDBnHjxg379SNHjsRisTgspUuXTu+HIZJqUTFWxvy9l7afr2HnqXB8PVwY07ECvzz7MMU05b2ISLalQpE8MKoVDuClRsUBGP7HTk5fiTI5ohTUGQB5K8KNKzB/iLqgiYiYaMaMGQwePJgRI0awZcsWKlWqRPPmzTl//nyS2//888+8/vrrjBgxgr179zJlyhRmzJjBG2+84bBduXLlOHPmjH1ZvXp1RjwckRStOXSBFp+s5KsVtinvW1XIy9LBDehRoxBOTpqVVUQkO1OhSB4oLzcuQaXgHETciGPwzG1Y4zNx8cXZFdpPAicX2DsXdv9hdkQiItnW+PHjefbZZ3nyyScpW7YsX375JV5eXkydOjXJ7deuXUudOnV47LHHKFy4MM2aNaNHjx6JWiG5uLiQN29e+5I7d+6MeDgiybp8LYYhM7fz+P/Wc/zidfL6efBNr2pMerwqgX4eZocnIiKZgApF8kBxdXbik26V8XJz5t8jl/hm1RGzQ7qzvBWg3lDb5flD4doFc+MREcmGYmJi2Lx5M02aNLGvc3JyokmTJqxbty7J29SuXZvNmzfbC0NHjhxh/vz5tGrVymG7gwcPkj9/fooWLcrjjz/OiRMn0u+BiNyBbcr7UzQZv4Lft5zEYoFetUJYPLg+TcsGmR2eiIhkIioUyQOncG5vRrQpC8C4RfvZdSrc5IhSUG8IBJaD6xdt4xWJiEiGunDhAlarlaAgxy/LQUFBnD17NsnbPPbYY4waNYq6devi6upKsWLFaNiwoUPXs5o1azJt2jQWLFjA5MmTOXr0KPXq1ePq1avJxhIdHU1ERITDInK/Tl6+zpPTNjLgl21cvBZDySAffnu+NqPalcfXw9Xs8EREJJNRoUgeSF2rBdO8XBCxVoMBv2wlKsZqdkjJc3GD9l+AxRl2/Q57/zI7IhERScHy5ct5//33mTRpElu2bGHWrFnMmzeP0aNH27dp2bIlXbp0oWLFijRv3pz58+dz5coVZs5MfrbLMWPG4O/vb1+Cg4Mz4uHIA8oabzBl9VGaTVjJ8v1huDk7MbhpSf56uR5VQzTlvYiIJE2FInkgWSwWPuhYkUBfdw6HXeP9+XvNDunO8lexDW4N8NcguH7J3HhERLKR3Llz4+zszLlzjjNQnjt3jrx58yZ5m7feeosnnniCZ555hgoVKtChQwfef/99xowZQ3x8fJK3yZEjByVLluTQoUPJxjJs2DDCw8PtS2ho6L0/MMnW9pyOoOOkNYz+aw/XY6zUKBzA/AH16N9YU96LiMidKUvIAyuntxvjulYC4Id/j/PPvkw+BX2D1yB3Kbh2HhYMMzsaEZFsw83NjapVq7J06VL7uvj4eJYuXUqtWrWSvM3169dxcnL8GOXs7AzYxoJJSmRkJIcPHyZfvnzJxuLu7o6fn5/DInI3bsRa+XDBPtp8vprtJ21T3r/foQK/9H2Y4oGa8l5ERFKmQpE80OqVyMNTdYoA8OpvO7gQGW1yRHfg6mGbBc3iBDt+gQMLzY5IRCTbGDx4MN988w3fffcde/fu5YUXXuDatWs8+eSTAPTq1Ythw24W8du0acPkyZP55ZdfOHr0KIsXL+att96iTZs29oLR0KFDWbFiBceOHWPt2rV06NABZ2dnevToYcpjlAff2kMXaDFxJZOXH8Yab9CyvG3K+8dqasp7ERFJPRezAxBJb6+2KMXawxfYd/Yqr/62gym9q2GxZNIPSwWrQa1+sPYzmDsQ+v0LHv5mRyUi8sDr1q0bYWFhvP3225w9e5bKlSuzYMEC+wDXJ06ccGhB9Oabb2KxWHjzzTc5deoUefLkoU2bNrz33nv2bU6ePEmPHj24ePEiefLkoW7duvz777/kyZMnwx+fPNiuXI/hvXl7+XXzSQDy+nkwql05mpVLuuukiIjInViM5NpHywMjIiICf39/wsPDs20T9n1nI2j7+Rpi4uIZ3b48TzwcYnZIyYuNgsl14NJhqPIEtPvc7IhERNKU8lLq6bmSOzEMg7k7zjBq7m4uRMZgsUDPmiG82qKUZjMTkXShvJQ9qOuZZAul8/rxWovSALw3bw+HzkeaHNEduHpCuy8AC2z9AQ4tTfEmIiIikr2cuhLFU9M20n/6Vi5ExlAi0Iffnq/F6Paa8l5ERO6PCkWSbTxZuzD1SuTmRmw8A2dsJSYu6VlpMoWQWlDzOdvluQMg+qq58YiIiEimYI03mLr6KE3Hr2DZf1PeD2pSkr/616VqSIDZ4YmIyANAhSLJNpycLHzcpRI5vFzZdSqCCUsOmB3SnTV+G3KEQHgoLB5hdjQiIiJisr1nIug4eS2j/pvyvnrhnMwfUJcBTUrg7uJsdngiIvKAUKFIspUgPw8+6FgBgC9XHObfIxdNjugO3Lxvjk+0aQocXWluPCIiImKKG7FWPlqwjzafrWZ76BV83V14r0N5ZvStRfFAX7PDExGRB4wKRZLttCifj67VCmIYMHjGNsKjYs0OKXlF6kO1p2yX/3wZYq6ZG4+IiIhkqLWHbVPeT1p+mLh4gxbl8rJkSAMerxmiKe9FRCRdqFAk2dKINuUIyeXF6fAbvDV7l9nh3FnTUeAfDJePwdJRZkcjIiIiGSD8eiyv/baDx75Zz7GL1wnyc+erJ6ry5RNVCfLzMDs8ERF5gKlQJNmSt7sLE7tVxtnJwp/bTzN76ymzQ0qeuy+0+cR2ef1XcHydufGIiIhIujEMg792nKbx+BXM2BQKQM+HC7F4cAOal8trcnQiIpIduJgdgIhZqhTKSf9HSjBhyQHemr2LqiE5CQ7wMjuspBVvDFV6wtYf4afO4JsPXD3B1cv21837v/9vWWf/e/s6r+Svc9YpQURExCynr0Tx1uxdLN13HoBiebz5oFNFqhfWbGYiIpJx9K1QsrV+jYqx8mAYm49fZsjM7Uzv+zDOmbW/f7P34MhKCD8BFw+mz304uToWke66AJXUdrdt7+IOlkz6HIuIiJjAGm/ww7pjjF24n2sxVlydLbzYsDgvNiqm2cxERCTDqVAk2ZqLsxMTulam1aer2HDsEl+uOEy/RsXNDitpnjnghTW2IlHsDYi9/t8SlcTfJNbFXE/+egzbfcTHQnS4bUkvFqc7FJuSW3enQtRt69y8wMUTnNSzVkREMr99ZyN4/fedbAu9AkDVkJx80LECJYI0m5mIiJhDhSLJ9grl8mJk23IM/XU7ExYfoF6J3FQsmMPssJLm4QcFqqbtPg0D4qKTKCLdobCUVFEq2ULUf5fj/5tdzoiHmEjbkp5cPO6xAJXMdm7/XfYJsrW0EhERuQ83Yq18/s8hvlxhm83Mx92F11qW5vEahTSbmYiImEqFIhGg00MFWLbvPPN2nmHgL9v4q39dvNyyyeFhsYCrh21JT9bYJApRqShAORSiUtguLurm/cXdsC1Rl9P4gVggoCjkLQ9B/y15y9tmplOXOhERSYV/j1zkjVk7OXLhGgDNygYxql158vprNjMRETFfNvkmLHJnFouF9zqUZ/Pxyxy5cI3Rf+1lTMcKZof1YHF2tS0eful3H/HxtuJQbBTEXkt9t7zYKIi5fftkilgxkXDpsG3ZM+fmfXv4OxaOgspBYFlbKyQRERFsU96P+Xsvv2y0zWYW6OvOqHblaFE+n8mRiYiI3KRCkch/cni5Mb5rJR6fsp7pG07QqFQemmka2qzFycnWRczNC8iVPvcRGQbndsK53XB2F5zbBWH74EY4HF9jWxJYnCBX8VuKRxVsf33zqfWRiEg2s2j3Wd74YxcXIqMBeKxmIV5rURp/T1eTIxMREXGkQpHILWoXz82z9Yry9cojvD5rJ5UL5SDQV83A5RY+ecDnESj2yM11cTFwYf/NwtHZnba/1y/ChQO2Zfesm9t7BthaHOWtcLOIlKe0bUY4ERF54Ow5HcHzP24m3rBNeT+mY0VqFNGU9yIikjmpUCRymyHNSrLq4AX2nonglV93MO3J6ljU+kPuxMXNVvTJe0t3RcOAyHP/FY923iwiXTgIUZfg2CrbksDJBXKXdOy6FlQBfIMy/vGIiEiaGrtwH/EGNCkTyBePP6Qp70VEJFNToUjkNu4uznzSvTJtPlvNigNhfLf2GH3qFDE7LMlqLBbwzWtbSjS5uT72BoTt/a9wtPtmC6QbV+D8Htuyc+bN7b3zJO66lrukbbwnERHJ9NYfuciy/WG4OFl489GyKhKJiEimp0KRSBJKBvkyrGVpRs7dw5i/91G7eG5KBvmaHZY8CFw9IH8V25LAMCDiVOLWRxcPw7UwOLLMtiRwdoM8pW4bPLsCeKfTuEySfcRcg/BTEB7633LyliUUgh+Gjl+ZHaVd4cKFeeqpp+jTpw+FChUyOxyRRAzD4KOF+wHoVj2Ywrm9TY5IREQkZSoUiSSjd+3CLNsfxooDYQz4ZRuz+9XWr4CSPiwW8C9oW0q1uLk+5jqc3+tYPDq3G6IjbK2Qzu503I9vvlsKR/8tuYqDs071gm1WwGthSReBrpyw/Y26dOd9eAdmTKypNHDgQKZNm8aoUaNo1KgRTz/9NB06dMDdXeN9SeawdO95Nh+/jIerE/0blzA7HBERkVSxGIZhmB2EpK+IiAj8/f0JDw/Hzy8dpyZ/AJ2/eoMWE1dx6VoMfesX5Y1WZcwOSbI7w4Arx2/puvZfEeny0aS3d/GwDZR9a9e1oHLgmTNj45b0Fxt1s+VPUkWgiFNgjUl5P+5+4B98s3jpXxByFLr51y//fYea1nlpy5YtTJs2jenTp2O1Wnnsscd46qmneOihh+5732ZTDs+6rPEGLT9ZyYFzkbzQsBivtShtdkgiIvdNeSl7UKEoG9DBfH8W7znHs99vwmKBn56uSe3iuc0OSSSx6Ktwbs9trY/2QOy1pLf3D/5vwOxbuq4FFAEntZrLlAzjltZACQWg21oGXb+Q8n4sTuCb/7YiULBjYcjDP90fTnrlpdjYWCZNmsRrr71GbGwsFSpUoH///jz55JNZdlIC5fCs6/fNJxny63b8PV1Z+Woj/D01tpyIZH3KS9mD+iOIpKBp2SB61CjE9A0nGDxzOwsG1iOHl5vZYYk4cveFQjVtS4L4eFtLo3O7bhaPzu6C8BM3ux8dWHBze1cvCCzr2HUtqBx46ENAuou9YWvxEx76XwHoZOLWQdbolPfj5uNY9Lm9COSb74EcCD02NpY//viDb7/9lsWLF/Pwww/z9NNPc/LkSd544w2WLFnCzz//bHaYko1Ex1kZv/gAAC80LKYikYiIZCkqFImkwluty7D+yEWOXLjG8D928fljVbLsr9OSjTg5Qa5itqVsu5vro67cnHEtoXh0fg/EXodTm2zLrXKEQN4KjuMf5Qix7V9SZhhw/eIdikChttZCKbLYCj3JFYH8C4JHDtuYV9nEli1b+Pbbb5k+fTpOTk706tWLCRMmULr0zS4+HTp0oHr16iZGKdnRz+tPcOpKFEF+7vSuVdjscERERO6KCkUiqeDl5sLE7pXpOGkt83aeodGWQDpXLWh2WCL3xjMHFK5jWxLEW22zrN3ade3sLrh62jYm0pXjsO+vm9u7+UJQWceua0FlwS0bzugTF33b7GAnSTRgdNyNlPfj6nWz8JMjoQB0a2ug/OCi1oy3ql69Ok2bNmXy5Mm0b98eV9fErTaKFClC9+7dTYhOsqvI6Dg+/+cQAAMal8TTTV16RUQka1GhSCSVKhbMwaCmJRm7cD8j5uyiRuEACuXyMjsskbTh5Ax5StqW8p1urr9+6bauazshbB/EXIXQ9bbFzgIBRRMPnO0fnHVbuRiG7TkIv70l0C3/R55L3b588iZfBPIPtg0wnlWfJ5McOXKEkJCQO27j7e3Nt99+m0ERicD/Vh3h4rUYiuT2pks1/agkIiJZjwpFInfh+QbFWLE/jA3HLjFwxlZmPlcLF2d1v5EHmFcAFKlvWxJYY+HCQceua+d22Qomlw7blj1zbm7v4X9zzKOErmuBZcDVM+Mfz+3iYv4bGyiZIlD4SVuXvJS4eN65COSXH1w0ZXtaO3/+PGfPnqVmzZoO69evX4+zszPVqlUzKTLJri5GRvPNyiMADG1WCld9RhARkSxIhSKRu+DsZGF8t0q0nLiKLSeu8MWywwxoUsLssEQylrPrf93OygJdb66PDEvcde3CfrgRDsfX2JYEFifIVcLW4ujWFki++dKuVY1hQNTlOxeBrp4FUjH5p3dgMuMC/fe/V4BaA5mgX79+vPrqq4kKRadOneLDDz9k/fr1ydxSJH18seww12KsVCjgT8vyec0OR0RE5J6oUCRylwrm9GJ0+/IMnLGNT/85SL2SuXmoUE6zwxIxn08e8HkEij1yc11cjK1YdGvXtXO7bIM7X9hvW3bPurm9Z0Dirmt5SifdGscaCxGnHQeFdpg6/iTEXks5bhcPxwGh/W9rFeRXAFw97v/5kTS3Z88eHnrooUTrq1Spwp49e0yISLKzk5ev8+O/xwF4tUUpnJxUPBYRkaxJhSKRe9Cucn6W7jvP3O2nGTRjG/P618PHXYeTSCIubrYZ0/JWuLnOMGwteeyFo/9mYLtwEKIuwdGVtiWBkwvkLmkrGhnxN4tAV8+QqtZAXrmT6BJ2y1/v3GoNlEW5u7tz7tw5ihYt6rD+zJkzuLjonCwZa+KSg8RY46ldLBd1i+c2OxwREZF7pk9RIvfAYrHwbvvybD52ieMXrzNq7m4+6lzJ7LBEsgaLBfzy2ZYSTW+uj70BYXsdu66d22nrunZ+j225nbNb8i2B/IPBv0DmGAtJ0kWzZs0YNmwYc+bMwd/fH4ArV67wxhtv0LRp0xRuLZJ2Dpy7yqwtJwF4tUVpLCo+i4hIFqZCkcg98vd0ZXy3yvT45l9mbjrJI6UDaVE+n9lhiWRdrh6Qv4ptSWAYtsGmz+6C87vB2d2xGOSdB5w0WGx29fHHH1O/fn1CQkKoUsX2vtm2bRtBQUH88MMPJkcn2cnYhfuJN6Bl+bxUDs5hdjgiIiL3RYUikfvwcNFcPFe/GF+uOMzrs3ZSpVBOgvw0lolImrFYbrYYKtXC7GgkkylQoAA7duzgp59+Yvv27Xh6evLkk0/So0cPXF1dzQ5PsonNxy+zeM85nCwwpFkps8MRERG5byoUidynwU1LsvpQGLtORTD01+1892QNDWApIpJBvL296du3r9lhSDZlGAYfLtgHQJeqwRQP9DE5IhERkfunQpHIfXJzcWJityq0/mwVqw5e4Nu1x3i6bhGzwxIRyTb27NnDiRMniImJcVjftm1bkyKS7GLFgTA2HL2Em4sTA5qUMDscERGRNKFCkUgaKB7ow/BHy/LW7F18uGAfdYrnonReP7PDEhF5oB05coQOHTqwc+dOLBYLhmGbBS9hIGGr1WpmePKAi483+GjBfgB61wohfw4NnC8iIg8GjQCaSqGhoZw8edL+/4YNGxg4cCBff/21iVFJZtKzZiEalw4kJi6eAdO3cSNWX1BERNLTgAEDKFKkCOfPn8fLy4vdu3ezcuVKqlWrxvLly80OTx5wc3ecZs+ZCHzdXXixYXGzwxEREUkzKhSl0mOPPcayZcsAOHv2LE2bNmXDhg0MHz6cUaNGmRydZAYWi4UPO1ckt48b+89dtf/KKCIi6WPdunWMGjWK3Llz4+TkhJOTE3Xr1mXMmDH079/f7PDkARYTF8+4RQcAeK5BUXJ6u5kckYiISNpRoSiVdu3aRY0aNQCYOXMm5cuXZ+3atfz0009MmzbN3OAk08jt487YzpUAmLrmKCsPhJkckYjIg8tqteLr6wtA7ty5OX36NAAhISHs369ivaSfGZtCOXHpOrl93HmyjsYlFBGRB4sKRakUGxuLu7s7AEuWLLEPkFm6dGnOnDljZmiSyTQqHcgTD4cAMPTX7Vy6FpPCLURE5F6UL1+e7du3A1CzZk0++ugj1qxZw6hRoyhatKjJ0cmD6npMHJ8uPQhA/8bF8XbXkJ8iIvJgUaEolcqVK8eXX37JqlWrWLx4MS1atADg9OnT5MqVy+ToJLN5o1UZiuXx5vzVaIbN2mEfYFVERNLOm2++SXx8PACjRo3i6NGj1KtXj/nz5/Ppp5+aHJ08qL5dc4ywq9EUCvCie/VCZocjIiKS5lQoSqUPP/yQr776ioYNG9KjRw8qVbJ1L/rzzz/tXdJEEni6OfNJ9yq4OltYuPscMzeFmh2SiMgDp3nz5nTs2BGA4sWLs2/fPi5cuMD58+d55JFHTI5OHkRXrsfw5YrDAAxpVhI3F32UFhGRB4/ayqZSw4YNuXDhAhEREeTMmdO+vm/fvnh5eZkYmWRW5Qv4M6RZKT74ex/vzN1DjSK5KJLb2+ywREQeCLGxsXh6erJt2zbKly9vXx8QEGBiVPKgm7z8MFdvxFE6ry9tKuY3OxwREZF0oZ9BUikqKoro6Gh7kej48eNMnDiR/fv3ExgYaHJ0klk9W68oNYsEcD3GysAZ24i1xpsdkojIA8HV1ZVChQphtVrNDkWyiTPhUUxbewyA11qUxsnJYm5AIiIi6USFolRq164d33//PQBXrlyhZs2ajBs3jvbt2zN58mSTo5PMytnJwvhulfH1cGF76BU++2/wSxERuX/Dhw/njTfe4NKlS2aHItnAp0sPEh0XT43CATQslcfscERERNKNCkWptGXLFurVqwfAb7/9RlBQEMePH+f777/XgJlyRwVyePJehwoAfL7sEJuO6QuNiEha+Pzzz1m5ciX58+enVKlSPPTQQw6LSFo5HBbJzE0nAXitZSksFrUmEhGRB5fGKEql69ev4+vrC8CiRYvo2LEjTk5OPPzwwxw/ftzk6CSza1spP8v2neePracYOGMbfw+oh6+Hq9lhiYhkae3btzc7BMkmxi3ajzXeoEmZIKqGaBwsERF5sKlQlErFixdn9uzZdOjQgYULFzJo0CAAzp8/j5+fn8nRSVbwTrtybDh6iZOXoxj55x7Gda1kdkgiIlnaiBEjzA5BsoHtoVeYv/MsFgu80ryU2eGIiIikO3U9S6W3336boUOHUrhwYWrUqEGtWrUAW+uiKlWqmBydZAV+Hq5M7F4ZJwv8vuUk83acMTskERERScHYhfsB6FClAKXy+pocjYiISPpToSiVOnfuzIkTJ9i0aRMLFy60r2/cuDETJkwwMTLJSqoXDuDFhsUBeOOPnZwJjzI5IhGRrMvJyQlnZ+dkF5H7tfrgBVYfuoCrs4VBTUqaHY6IiEiGUNezu5A3b17y5s3LyZO2wQwLFixIjRo1TI5KspoBTUqw6mAY20+GM2Tmdn58uqam2BURuQd//PGHw/+xsbFs3bqV7777jnfeecekqORBYRgGHy3cB8DjNUMIDvAyOSIREZGMoUJRKsXHx/Puu+8ybtw4IiMjAfD19WXIkCEMHz4cJyc1zpLUcXV2YkK3yjz66WrWHr7I/1YfoW/9YmaHJSKS5bRr1y7Rus6dO1OuXDlmzJjB008/bUJU8qD4e9dZdpwMx9vNmZceKW52OCIiIhlG1Y1UGj58OJ9//jkffPABW7duZevWrbz//vt89tlnvPXWW2aHJ1lM0Tw+vN2mLGAb+2D36XCTIxIReXA8/PDDLF261OwwJAuLs8bz8X9jEz1Tryi5fdxNjkhERCTjqFCUSt999x3/+9//eOGFF6hYsSIVK1bkxRdf5JtvvmHatGlmhydZUPfqwTQtG0Ss1WDAL9u4EWs1OyQRkSwvKiqKTz/9lAIFCpgdimRhv20+yZEL1wjwduOZekXMDkdERCRDqetZKl26dInSpUsnWl+6dGkuXbpkQkSS1VksFj7sVJFtoSs5dD6SMfP38k678maHJSKSZeTMmROL5eYYb4ZhcPXqVby8vPjxxx9NjEyyshuxViYuOQhAv0bF/9/efYdHUa5vHP/ubnpIQkkhQOiQAAKhC0jvIoogTaTZjogKIhbOUdBjQf2hogcEC1hQ6cVKr9JrKAKhk9ASahqQhOz8/liMRlqAJLOb3J/r2ovNm9nZeyeEZ3n2nXfw83I3OZGIiEjeUqMom2rWrMnYsWP55JNPsoyPHTuWGjVqmJRKXF1RXw9Gd6tJv0kb+GbtEZpHBNMiPNjsWCIiLuGjjz7K0iiyWq0EBQXRoEEDihQpYmIycWXfrj3MycRLlCzsTe8Gpc2OIyIikufUKMqm999/n44dO7J48WIaNmwIwNq1a4mNjeW3334zOZ24smaVg+jfqCxfrznMizO2M39IE62FICKSDf379zc7guQzCRfTGbfsAABDWlfCy91mciIREZG8pzWKsqlZs2bs3buXBx98kPPnz3P+/Hm6dOnCH3/8weTJk29pX+PGjaNs2bJ4eXnRoEEDNmzYkK3HTZ06FYvFQufOnW/jFYgze6VDBJVDCnE6OZVXZm3HMAyzI4mIOL2vvvqKGTNmXDU+Y8YMvvnmGxMSiav7fOUBEi6mUym4EF1qlzI7joiIiCnUKLoFJUqU4O2332bWrFnMmjWLt956i3PnzjFx4sRs72PatGkMHTqUkSNHsmXLFmrWrEm7du2Ij4+/4eMOHz7MsGHDaNKkyZ2+DHFCXu42xvSohYfNyuLd8fywIcbsSCIiTm/UqFEEBgZeNR4cHMw777xjQiJxZfGJl5i06jAAL7YLx2a13PgBIiIi+ZQaRXnsww8/5IknnmDAgAFUrVqVCRMm4OPjw6RJk677mIyMDHr37s0bb7xB+fLl8zCt5KWqJfx5sV04AG/+sosDp5JNTiQi4txiYmIoV+7qK1KVKVOGmBg13OXW/G/pfi6mZ1CrdGHaVA0xO46IiIhp1CjKQ2lpaWzevJnWrVtnjlmtVlq3bs3atWuv+7j//ve/BAcH89hjj+VFTDHRY/eUo3HFYlxKtzNkahRpl+1mRxIRcVrBwcFs3779qvFt27ZRrFgxExKJqzpyJoUpV2bzvtw+Issi6SIiIgWNGkV56PTp02RkZBASkvVTqpCQEE6ePHnNx6xatYqJEyfyxRdfZPt5UlNTSUxMzHIT12C1WhjdrSYB3u7sOJbAmMV7zY4kIuK0evXqxXPPPceyZcvIyMggIyODpUuXMnjwYHr27Gl2PHEhHyzcy2W7QbPKQdxdXk1GEREp2HTVs5vo0qXLDb9//vz5XHvupKQk+vTpwxdffHHNNRiuZ9SoUbzxxhu5lktyV2iAN6O6VOfp77cwfsUBmocHU79cUbNjiYg4nTfffJPDhw/TqlUr3Nwcb2nsdjt9+/bVGkWSbX8cT+CnbccBeKl9uMlpREREzKdG0U0EBATc9Pt9+/bN1r4CAwOx2WzExcVlGY+Li6N48eJXbX/gwAEOHz5Mp06dMsfsdsepSG5ubkRHR1OhQoWrHjd8+HCGDh2a+XViYiJhYWHZyijO4d7qoTxUpxQzNx/l+WlRzBvSBH8vd7NjiYg4FQ8PD6ZNm8Zbb71FVFQU3t7eVK9enTJlypgdTVzI/y2IBuD+miWoVuLG7/tEREQKAjWKbuKrr77KsX15eHhQp04dlixZknmJe7vdzpIlS3jmmWeu2j4iIoIdO3ZkGXv11VdJSkri448/vm7zx9PTE09PzxzLLeZ4/f5qbDh0lpizFxgxdydjetYyO5KIiFOqVKkSlSpVMjuGuKB1B8+wPPoUblYLQ9tUNjuOiIiIU9AaRXls6NChfPHFF3zzzTfs3r2bgQMHkpKSwoABAwDo27cvw4cPB8DLy4u77rory61w4cL4+flx11134eHhYeZLkVxWyNONj3pEYrNamBt1nB+jjpkdSUTEqXTt2pX33nvvqvH333+fbt26mZBIXIlhGLw/fw8APeuHUTbQ1+REIiIizkGNojzWo0cPRo8ezYgRI4iMjCQqKor58+dnLnAdExPDiRMnTE4pzqJOmSI806IiAK/O3cnRcxdMTiQi4jxWrlzJvffee9V4hw4dWLlypQmJxJUs2hXHlpjzeLvbeK6lZqSJiIj8SaeemeCZZ5655qlmAMuXL7/hY7/++uucDyRO7dmWFVm57xRbY84zdPo2pjxxNzarLtsrIpKcnHzN2bXu7u664qfcUIbdyFyb6NF7yhLs72VyIhEREeehGUUiTs7NZmVMj0h8PWxsOHSWz1YeMDuSiIhTqF69OtOmTbtqfOrUqVStWvWW9zdu3DjKli2Ll5cXDRo0YMOGDTfcfsyYMYSHh+Pt7U1YWBjPP/88ly5duqN9St6Ys/UY++KTCfB258mmV18YREREpCDTjCIRF1CmmC8j76/GSzO3838Lokm4mM4LbcLxcFOvV0QKrtdee40uXbpw4MABWrZsCcCSJUv44YcfmDlz5i3ta9q0aQwdOpQJEybQoEEDxowZQ7t27YiOjiY4OPiq7X/44QdeeeUVJk2aRKNGjdi7dy/9+/fHYrHw4Ycf3tY+JW+kXs7go0V7AXi6eQUCvHVVURERkb/T/zJFXES3OqXo36gshgGfrTjIg5+uZn98ktmxRERM06lTJ+bOncv+/ft5+umneeGFFzh27BhLly6lYsWKt7SvDz/8kCeeeIIBAwZQtWpVJkyYgI+PD5MmTbrm9mvWrKFx48Y8/PDDlC1blrZt29KrV68sM4ZudZ+SN75fF8Ox8xcJ8fekX6OyZscRERFxOmoUibgIi8XC6/dXY8IjtSns484fxxPp+Mkqvl17GMMwzI4nImKKjh07snr1alJSUjh48CDdu3dn2LBh1KxZM9v7SEtLY/PmzbRu3TpzzGq10rp1a9auXXvNxzRq1IjNmzdnNoYOHjzIb7/9lrm49u3sEyA1NZXExMQsN8k5SZfSGbtsPwBDWlfGy91mciIRERHno0aRiItpf1coC4Y0pUmlQFIv2xnx4x88+vVGTiWlmh1NRMQUK1eupF+/fpQoUYIPPviAli1bsm7dumw//vTp02RkZGRegfRPISEhnDx58pqPefjhh/nvf//LPffcg7u7OxUqVKB58+b8+9//vu19AowaNYqAgIDMW1hYWLZfh9zcl78f4mxKGuUDfelWp5TZcURERJySGkUiLijE34tvBtRnZKeqeLhZWRZ9ivZjVrJ4V5zZ0URE8sTJkyd59913qVSpEt26dcPf35/U1FTmzp3Lu+++S7169XL1+ZcvX84777zDp59+ypYtW5g9eza//vorb7755h3td/jw4SQkJGTeYmNjcyixnE5O5cvfDwIwrF04bja9DRYREbkWVUgRF2W1WhjQuBw/P3MPEcX9OJOSxuPfbuLfc3ZwIe2y2fFERHJNp06dCA8PZ/v27YwZM4bjx4/zv//977b3FxgYiM1mIy4ua7M9Li6O4sWLX/Mxr732Gn369OHxxx+nevXqPPjgg7zzzjuMGjUKu91+W/sE8PT0xN/fP8tNcsa4ZftJScugeskAOtx1/Z+BiIhIQadGkYiLCy/ux4/PNOaJJuUA+GF9DPd9sortR8+bG0xEJJfMmzePxx57jDfeeIOOHTtis93ZOjMeHh7UqVOHJUuWZI7Z7XaWLFlCw4YNr/mYCxcuYLVmfRv1Zw7DMG5rn5J7Ys9e4Pt1MQC83D4Ci8ViciIRERHnpUaRSD7g6WbjPx2r8v3jDSju78XB0yl0+XQNY5fuI8Ouha5FJH9ZtWoVSUlJ1KlThwYNGjB27FhOnz59R/scOnQoX3zxBd988w27d+9m4MCBpKSkMGDAAAD69u3L8OHDM7fv1KkT48ePZ+rUqRw6dIhFixbx2muv0alTp8yG0c32KXlnzOJ9pGXYaVyxGPdUCjQ7joiIiFNzMzuAiOScxhUDmT+kCf+Zs5Nfd5xg9MK9LI8+xUc9Igkr6mN2PBGRHHH33Xdz9913M2bMGKZNm8akSZMYOnQodrudRYsWERYWhp+f3y3ts0ePHpw6dYoRI0Zw8uRJIiMjmT9/fuZi1DExMVlmEL366qtYLBZeffVVjh07RlBQEJ06deLtt9/O9j4lb0SfTGL21qMAvNQuwuQ0IiIizs9i6Lra+V5iYiIBAQEkJCRorYMCwjAMZm05xsgfd5KSlkEhTzf++0A1HqxVUtPtRcR0uVGXoqOjmThxIpMnT+b8+fO0adOGn376KUf2bSbV8Dv3+DebWLw7jnurF+fT3nXMjiMikjMMA9JS4OI5uHgWLpz925/nrx6rch/c8/wdP63qUsGgGUUi+ZDFYuGhOqWoX7Yoz0+PYvORcwydvo0le+J5p3N1AnzczY4oIpKjwsPDef/99xk1ahQ///wzkyZNMjuSOIHNR86yeHccNquFF9qGmx1HROTaMtIdDZ8szZ5sNIAy0rL/HEH6N1CyT40ikXysdDEfpj15N58uP8DHS/bx6/YTbDlyjg+616RRBa3RICL5j81mo3PnznTu3NnsKGIywzB4b140AN3qlKJCUCGTE4lIvmcYcCnhSjPnSqPnpg2gc5CWdPvPafMA76LgXQR8/v7nP+4Xq5Bzr1PyPTWKRPI5N5uV51pVomnlIIZM3crhMxfo/eV6nmxSnqFtK+PpdmdXCxIREXFGy/eeYsPhs3i6WRncupLZcUTE1aRf/KuZc81mzz/Hrsz4MTJu8wkt4BXwV2PnqmbPdRpAHr6gpSUkh6lRJFJARIYV5tfnmvDWr7uYsiGWz1Ye5Pd9p/m4ZySVQm5t0VcRERFnZrcbvD/fMZuof6OyhAZ4m5xIRExjz7hBY+cGDaDLF2//Od19rjR7ijiaOn9v/PzZ9PnnmFcAWPUBrjgHNYpEChBfTzdGdalB8/BgXpm1nV0nErnvf6sY3iGCfo3KaqFrERHJF37efpzdJxLx83JjYHOdbiGSLxgGpCVnc2bP38YuJdz+c1ps12ns3KQB5O6Vc69bxARqFIkUQO2qFadWWGFenLmdFXtP8frPu1gWfYr/e6gGwf4qbCIi4rrSLtv5YOFeAJ5qVoHCPh4mJxKRq1xOu8nMniuncf2zKWRPv/3n9PTPespWdhpAnv46rUsKJDWKRAqoYH8vvh5Qj2/XHuGd33azYu8p2n/8O+92qU7basXNjiciInJbpm2MIebsBQILeTKgcVmz44gUbHY77J0PW7+DhNi/rtqVlnz7+7R5/mOtniLXWdPn72OFwaar/opklxpFIgWYxWKhX6OyNKxQjMFTo9h9IpEnJ2+mZ70wXruvKr6e+idCRERcx4W0y3y8ZD8Ag1tVxMdDdUzEFOmXYPtUWDMWzuy7zkYWRwPnqtO3btIAcvfRLB+RXKbqKSJUDvFj7qBGfLhwL5//fpCpG2NZd/AMY3rWIjKssNnxREREsmXSqkOcTk6lTDEfetYvbXYckYLnwlnYOBE2fAYppxxjnv5Qpz+UvSfrKV9ehcFqNTOtiFyHGkUiAoCnm43h91ahWXgQL0zfxuEzF+g6fg2DW1Xi6eYVcLOpkIuIiPM6l5LGZysOAjC0TWXcVbdE8s7ZQ7DuU8cpZukXHGP+peDugVC7L3j5m5tPRG6JGkUikkWjCoHMH9yUf8/dwa/bT/Dhor2s2HuKMT0iCSvqY3Y8ERGRaxq/4gBJqZepEupPpxolzI4jUjAc2wyrP4HdP4Fhd4yFVIfGz0G1B7UukIiLUqNIRK4S4OPO2F61aBURzIgf/2DzkXN0+Ph3Xr+/Gl1rl8Si88JFRMSJnEi4yNdrDgPwUvtwrFbVKZFcY7fDvoWw5hM4svqv8QotodFzUL651hAScXFqFInINVksFrrULkW9skUZOj2KjYfPMWzGNpbtieftB+/S5YZFRMRpfLx4H2mX7dQvV5TmlYPMjiOSP11Ohe3THAtUn452jFnd4K6HoNGzUPwuc/OJSI5Ro0hEbiisqA9Tn2zIhBUH+GjRXn7dcYLNR87xQfeaNK4YaHY8EREp4PbHJzN9UywAL7eP0KxXkZx28dyVBao/h+Q4x5iHH9TtDw2egoBSpsYTkZynRpGI3JTNamFQi4rcUzGQ56dFcfB0Cr2/XM8TTcoxrF04nm42syOKiEgB9cHCaOwGtKkaQp0yRcyOI5J/nDviWKB6y2RIT3GM+ZVwLFBdpx94BZibT0RyjRpFIpJtNcMK88tz9/DWr7v5YX0MX/x+iN/3nebjnrUIL+5ndjwRESlgtsWeZ97Ok1gs8GK7cLPjiOQPx7c6FqjeNfevBaqDq11ZoLoLuGn5AZH8To0iEbklPh5uvPNgdVqEB/PyrO3sOZlEp7GreKV9BP0bldUCoiIikmfeX7AHgC61SlE5RB9YiNw2w4B9ixwLVB/+/a/x8s0dC1RXaKkFqkUKEDWKROS2tKkaQs2wJrw8czvLok/x3192sSw6ntHdahLi72V2PBERyedW7TvN6v1n8LBZeb5NJbPjiLimy6mwY4ZjgepTux1jFhvc1dWxQHVoDXPziYgp1CgSkdsW7OfFpP71+G7dEd76dTe/7ztN+zErGdWlBu3vKm52PBERyafsdoP35jtmEz1ydxlKFfExOZGIi7l4HjZNgvWfQfJJx5hHIajT37FAdeEwM9OJiMnUKBKRO2KxWOjTsCwNKxRj8NQo/jieyFPfbaZ73VKM7FQNX0/9MyMiIjlr3s6T7DiWgK+HjUEtKpgdR8R1nI+BdRNgyzeQluwY8wt1NIfq9AfvwmamExEnof/BiUiOqBjsx5ynG/PBomg+X3mQ6ZuOsv7QWcb0iKRWaV2FRkREckZ6hp3RC6MBeKJpeYoV8jQ5kYgLOLEN1vwPds4GI8MxFlzVcXrZXQ9pgWoRyUKNIhHJMR5uVoZ3qELzysG8MD2KI2cu8NCEtTzXshKDWlTAzWY1O6KIiLi4mZuPcuh0CkV9PXi8SXmz44g4L8OA/UscC1QfWvHXeLmm0GgwVGylBapF5JrUKBKRHNewQjHmDW7Kqz/u5Odtx/lo8V5W7I3nox6RlCnma3Y8ERFxUZfSMxizeC8Az7SoSCGd3ixytctpsHOmYwZR/C7HmMUG1R50zCAqEWlqPBFxfqquIpIrAnzc+V+vWrSKCOa1uTvZEnOeez/+nZH3V6NbnVJY9AmWiIjcoq/XHCYuMZWShb3pfXdps+OIOJdLCbD5a8caREnHHWPuvlCnn2MNoiJlTI0nIq5DjSIRyVWda5WkbtkiDJ22jQ2Hz/LSzO0s2xPPOw9Wp4ivzocXEZHsSbiQzqfL9gMwtE1lPN1sJicScRIJR2HdeNj8DaQlOcYKhTiaQ3UHgLfWihSRW6NGkYjkulJFfJjy5N18tvIAHy7cy7ydJ9kSc47R3WrSpFKQ2fFERMQFfLbyAImXLlM5pBCda5U0O46I+U7uuLJA9SywX3aMBUU4Ti+r3g3ctNC7iNweNYpEJE/YrBaebl6RJhWDGDxtKwdPpdBn4gYebVyOl9qH4+WuT4ZFROTa4hMvMWn1IQBebBeBzarTl6WAMgw4sNTRIDq47K/xsk0cDaKKbcCqi4eIyJ1Ro0hE8lT1UgH8+mwT3v5tF9+ti2HS6kOsOXCaMT0jiSjub3Y8ERFxQp8s3celdDt1yhShdZVgs+OI5L2MdMel7df8D+J2OMYsVqja2dEgKlnb1Hgikr+oUSQiec7bw8ZbnavTIjyYl2ZuZ8/JJO7/32peah/Oo43LYdUnxSIicsXh0ylM3RALwMvtI3QxBClYLiXClm8caxAlHnOMuftA7b5w90AoUtbUeCKSP6lRJCKmaVUlhPlDmvLyrO0s3RPPW7/uZnn0KT7oXpMQfy+z44mIiBP4YNFeLtsNWoQHUb9cUbPjiOSNhGOwfoLjKmapiY4x32Bo8C+o+yj46HdBRHKPGkUiYqogP08m9qvLd+tjePvXXazaf5p2Y1Yy6sHqdKgeanY8EREx0c5jCfy8zXGZ7xfbRZicRiQPnNwJa8fCjhl/LVAdWBkaPgM1eoC7PkgTkdynRpGImM5isdDn7jI0LF+MIdO2svNYIgO/30K3OqUYeX81CnnqnyoRkYLo/xZEA/BAZAmqltA6dpJPGQYcWgGrP4EDS/4aL9PYsf5QpXZaoFpE8pT+9yUiTqNicCFmD2zMmMV7Gb/iADM2H2X9obN81COSOmWKmB1PRETy0NoDZ1ix9xRuVgtD21Q2O45IzstIhz/mwppP4OR2x5jFClXuh0bPQak6psYTkYJLjSIRcSoeblZeah9Bs8pBDJ2+jZizF+j+2VqeaVGRZ1tWxM2mT9RERPI7wzB4b/4eAB5uUJoyxXxNTiSSg1KTYMu3jgWqExwLtePmDbX7OBaoLlre3HwiUuCpUSQiTqlB+WL8NrgJI3/cydyo43y8ZB8r9p5iTI9IygbqPwwiIvnZwl1xRMWex9vdxjMtK5odRyRnJJ5wLFC96StITXCM+QQ6Fqiu97gWqBYRp6FGkYg4rQBvd8b0rEWLiGBenbuTqNjz3PvJ74zsVJXudcN0iWQRkXwow25krk302D3lCPbT4r3i4uJ3w5r/wfbpYE93jBWr6FigumZPcPc2N5+IyD+oUSQiTu+ByJLULVuUodOiWH/oLC/P2sHSPfGM6lKDor4eZscTEZEcNHvLUfbHJ1PYx50nm+kUHHFRhgGHf3csUL1/0V/jpRs6Fqiu3EELVIuI01KjSERcQsnC3vzwxN188ftBPlgYzYI/4tgas5LR3WrStHKQ2fFERCQHXErPYMzifQA83bwC/l7uJicSuUUZl2HXXMcC1Se2XRm0QJVOjgWqw+qZmU5EJFvUKBIRl2GzWniqWQXuqRjI4KlbOXAqhb6TNtC/UVle6RCBl7vN7IgiInIHvlt3hGPnLxIa4EXfhmXNjiOSfanJsHUyrP0UEmIcY27eUKs33P00FKtgbj4RkVugRpGIuJy7Sgbwy7NNGDVvN9+uPcLXaw6z5sBpPu5Ziyqh/mbHExGR25B0KZ1xy/YDMKR1JTX/xTUknYT1n8GmiXDpzwWqi0H9KwtU+xYzN5+IyG1Qo0hEXJK3h43/PnAXLcKDeXHmNvbGJfPA2NW81D6cRxuXw2rVQtciIq7ki98Pce5COuWDfOlau5TZcURuLH4PrL2yQHVGmmOsaHnHAtWRD2uBahFxaWoUiYhLaxERzPwhTXll1nYW747nrV93syw6ntHdahIaoDdpIiKu4HRyKl/+fhCAF9uG42bTIr/ihAwDjqx2LFC9b8Ff46XqQ+PnIPxesGomnIi4PjWKRMTlBRby5Iu+dflhQwxv/rKL1fvP0H7M77zzYHU61gg1O56IiNzE2KX7uZCWQc1SAbS/q7jZcUSyyrgMu39yXOL++JYrgxaI6OhYoLp0A1PjiYjkNDWKRCRfsFgs9G5QhrvLF+P5aVFsP5rAoB+2sHRPKV6/vyp+unKOiIhTij17ge/XHwHg5fYRWCw6dVicRFoKbP0O1o6D846/o7h5OU4tu3sQBFY0N5+ISC5Ro0hE8pUKQYWYNbARHy/ex6fL9zNry1E2HD7DR90jqVu2qNnxRETkHz5atJf0DIMmlQJpVDHQ7DgikBzvWKB645dw6bxjzLso1H8C6j0BhYJMjSciktvUKBKRfMfdZmVYu3CaVg7i+WlRxJ69SPfP1jKoRUWea1UJd619ISLiFPacTGRO1DEAXmwXbnIaKfBO7XUsUL1tGmSkOsaKlIOGgyCyN3j4mJtPRCSPqFEkIvlW/XJFmTekCa//+Aeztx7jf0v3s3Lfacb0iKRcoK/Z8URECrzRC6IxDOhYPZQapQqbHUcKIsOAmLWOBar3zvtrvGRdxwLVEfdpgWoRKXDUKBKRfM3fy50Pe0TSIiKY/8zZwbbY89z78e+M6FSVnvXCtBaGiIhJNh0+y+Ld8disFl5oW9nsOFLQ2DNg98+OBaqPbfprPPzeKwtU3w16jyAiBZQaRSJSIHSqWYI6ZYrwwvRtrD14huGzd7B0TzzvdqlOsUKeZscTESlQDMPgvfl7AOheN4zyQYVMTpQH9i6EE1GO2SlWN8fNYsv6deZ929++//fvXWPbG27jBhZr1q+ttoLdAEm7AFHfw9qxcO6wY8zmCTV7QqNnIbCSqfFERJyBGkUiUmCUKOzN94834IvfDzJ6YTSLdsURFXue/3uoBs3Dg82OJyJSYCyLjmfj4XN4ulkZ3KoA/Md8zVhY+B+zU/zl782jazar/tnMukYT66pG1T///LMpdRuNrDtqpl1nm4w0iPrBsUD1xbOO4+BdBOo9DvWfhEJ6HyAi8ic1ikSkQLFaLfyrWQXuqRTI4KlR7I9Ppv9XG+nfqCyvdIjAy13rEIiI5Ca73eD9+dEA9G9cluIBXiYnymVbJv/VJIq4D7wLO057smeA/fKVWwYY//g6y/cvg2HP+vVN93H5+pkMu6NxkpGWJ4fA6RQuAw2fgVq9wUNrFoqI/JMaRSJSIFUrEcAvz97Du/P28PWaw3y95jCr959mTM9IqpUIMDueiEi+9dO24+w5mYSflxsDm1UwO07u2vUj/Pyc436jZ6HNm3l72pf9H80l4xoNqH82nK7aJiPrn0bGtcevuU02G1pX5bxZU+xa29zstWZAyTrQ6Bmocr8WqBYRuQE1ikSkwPJyt/H6/dVoFh7EizO2sy8+mc7jVvNiu3Aev6c8VmsBXsNBRCQXpF2288Eix2yip5pVoLCPh8mJctGBpTDrcUdDo1afvG8SAVitYPUA8vFxFhGRHGc1O4CIiNlahAezYEgT2lQNIT3D4J3f9tD7y/UcP3/R7GgiIvnK1I0xxJ69SLCfJ482Lmd2nNwTuwGm9nac2lX1Aej0ccFeQFpERFyKGkUiIkCxQp583qcOo7pUx9vdxtqDZ2g/ZiU/bztudjQRkXwhJfUynyzZB8BzrSrh7ZFPT/05uRO+fwjSL0CFltDlC53mJCIiLkWNIhGRKywWC73ql+a3wU2oWSqAxEuXeXbKVoZOiyLxUrrZ8UREXNqkVYc4nZxGmWI+9KgXZnac3HHmAHzXBS4lQKn60OM7cPM0O5WIiMgtUaNIROQfygX6MnNgI55rWRGrBWZvPUaHMb+z8fBZs6OJiLiksylpfL7yIAAvtA3H3ZYP34ImHofJnSE5DkLugt7TdUUtERFxSfmwSouI3Dl3m5WhbcOZ/q+GhBX15tj5i/T4bC2j5u0mJfUGlxwWEZGrjF++n6TUy1Qr4c991UPNjpPzLpyFyQ/C+RgoWh4emQ3eRcxOJSIiclvUKBIRuYG6ZYvy23NN6Fq7FHYDPltxkFYfrODHqGMYhmF2PBERp3f8/EW+WXsEgJfaR+S/K0qmJsF3XeHUHvArAX3mgl+I2alERERumxpFIiI34eflzgfda/J5nzqUKuLNycRLDJ4aRbcJa9l5LMHseCIiTm3M4r2kXbZzd/miNK0UaHacnJV+Cab0guNbwLso9J0LRcqYnUpEROSOqFFkgnHjxlG2bFm8vLxo0KABGzZsuO62s2fPpm7duhQuXBhfX18iIyOZPHlyHqYVkT+1rVacxUObMaxtZbzdbWw6co5OY1cxfPZ2ziSnmh1PRMTp7I9PYubmo4BjNpElP10iPuMyzHwUDv8OHoXgkVkQFG52KhERkTumRlEemzZtGkOHDmXkyJFs2bKFmjVr0q5dO+Lj46+5fdGiRfnPf/7D2rVr2b59OwMGDGDAgAEsWLAgj5OLCICXu41nWlZi6bBmPBBZAsOAKRtiaT56ORNXHSI9w252RBERpzF6wV7sBrStGkLt0vlozR67HX4cBNG/gs0Tek2FkrXNTiUiIpIjLIYW2chTDRo0oF69eowdOxYAu91OWFgYzz77LK+88kq29lG7dm06duzIm2++ma3tExMTCQgIICEhAX9//9vOLiJX23j4LK//9Ad/HE8EoGJwIUbcV5WmlYNMTibivFSXss+Vj1VU7Hk6j1uN1QILhjSlUoif2ZFyhmHAvJdhw2dgsUHP7yG8g9mpRETyhCvXJck+zSjKQ2lpaWzevJnWrVtnjlmtVlq3bs3atWtv+njDMFiyZAnR0dE0bdo0N6OKSDbVK1uUn565h1FdqlPU14P98cn0nbSBJ77dxJEzKWbHExExhWEYvDdvDwBda5fKP00igOXvOppEAJ3Hq0kkIiL5jpvZAQqS06dPk5GRQUhI1ithhISEsGfPnus+LiEhgZIlS5KamorNZuPTTz+lTZs2190+NTWV1NS/1ktJTEy88/Aicl02q4Ve9Utz712hjFmyl2/XHmHRrjhWRJ/i8SblGNSiIr6e+udWRAqO3/edZu3BM3jYrAxpU9nsODln3XhY8a7j/r2joWYPc/OIiIjkAs0ocgF+fn5ERUWxceNG3n77bYYOHcry5cuvu/2oUaMICAjIvIWFheVdWJECLMDHnZGdqjF/cBOaVAokLcPOp8sP0PKD5czdegyd6SsiBYHdbvD+AscHYH0alqFkYW+TE+WQrd/D/CvLBLR4Feo/YW4eERGRXKJGUR4KDAzEZrMRFxeXZTwuLo7ixYtf93FWq5WKFSsSGRnJCy+8wEMPPcSoUaOuu/3w4cNJSEjIvMXGxubYaxCRm6sU4se3j9bn8z51KF3Uh7jEVIZMi+KhCWvZcTTB7Hgich23clXS5s2bY7FYrrp17Ngxc5v+/ftf9f327dvnxUsx1W87T7DzWCKFPN14unkFs+PkjN0/w0/POO7fPQiaDjM3j4iISC5SoygPeXh4UKdOHZYsWZI5ZrfbWbJkCQ0bNsz2fux2e5ZTy/7J09MTf3//LDcRyVsWi4W21Yqz8PmmvNguHG93G5uPnOP+cat4eeZ2Tidf/3dYRPLerV6VdPbs2Zw4cSLztnPnTmw2G926dcuyXfv27bNsN2XKlLx4OaZJz7DzwcK9ADzRpDzFCnmanCgHHFgGMx8Fww6Rj0C7t8FiMTuViIhIrlGjKI8NHTqUL774gm+++Ybdu3czcOBAUlJSGDBgAAB9+/Zl+PDhmduPGjWKRYsWcfDgQXbv3s0HH3zA5MmTeeSRR8x6CSJyC7zcbQxqUZFlw5rTObIEhgHTNsXS4v+W8+XvB0nPsJsdUUSADz/8kCeeeIIBAwZQtWpVJkyYgI+PD5MmTbrm9kWLFqV48eKZt0WLFuHj43NVo8jT0zPLdkWK5KNLxF/DjE1HOXQ6hWK+HjzepJzZce7c0U0wtTdkpEGVTtDpYzWJREQk39PqqnmsR48enDp1ihEjRnDy5EkiIyOZP39+5gLXMTExWK1/9e9SUlJ4+umnOXr0KN7e3kRERPDdd9/Ro4cWTxRxJcUDvBjTsxaP3F2G13/+g53HEnnr191M2RDDiE7VaFY5yOyIIgXWn1cl/fsHNbdyVVKAiRMn0rNnT3x9fbOML1++nODgYIoUKULLli156623KFasWI7mdxYX0zIYs9gxm+jZlvlgEf+4XfBdV0hPgfLNoetEsLn4axIREckGi6HVVfO9xMREAgICSEhI0GloIk4gw24wY1Ms/7cgmjMpaQC0rhLMqx2rUjbQ9yaPFnF9zlaXjh8/TsmSJVmzZk2WU8FfeuklVqxYwfr162/4+A0bNtCgQQPWr19P/fr1M8enTp2Kj48P5cqV48CBA/z73/+mUKFCrF27FpvNds19XevKpWFhYU5zrG5k/PIDvDd/D6WKeLPkhWZ4ul37NbqEs4dgUntIPgml6kGfueBZyOxUIiKmc7YaLrlDH4uIiOQxm9VCz/ql6VA9lE+W7OObNYdZvDuelXtP81iTcgxqUZFCrv5JvEgBMnHiRKpXr56lSQTQs2fPzPvVq1enRo0aVKhQgeXLl9OqVatr7mvUqFG88cYbuZo3NyRcSGf88v0ADG1T2bWbRIkn4NsHHE2i4Krw8HQ1iUREpEDRGkUiIiYJ8HbntfuqMn9IE5pUCiQtw8745QdoOXo5s7ccxW7XhE+RvHC7VyUFxyniU6dO5bHHHrvp85QvX57AwED2799/3W1c9cqlE1YeIPHSZcJD/HggsqTZcW7fhbMw+UE4fwSKlIM+c8CnqNmpRERE8pQaRSIiJqsY7Me3j9bni751KV3Uh/ikVIZO30bXCWvYFnve7Hgi+d6dXJV0xowZpKamZusiE0ePHuXMmTOEhoZedxtXvHJpXOIlvlp9CICX2odjs7roYs+pyfB9Nzi1G/xCoe9c8Ltxo1BERCQ/UqNIRMQJWCwW2lQNYeHzTXmxXTg+Hja2xpyn86ereWnmNk4lpd58JyJy2271qqR/mjhxIp07d75qgerk5GRefPFF1q1bx+HDh1myZAkPPPAAFStWpF27dnnymvLKx0v2cSndTt0yRWgZEWx2nNuTfgmmPgzHNoF3EcdMoiJlzU4lIiJiCi2CISLiRLzcbQxqUZGutUvx3vw9zNl6jOmbjjJvx0mea1WJfo3K4uGmHr9ITrvVq5ICREdHs2rVKhYuXHjV/mw2G9u3b+ebb77h/PnzlChRgrZt2/Lmm2/i6emZJ68pLxw6ncK0jY7T417uEIHFFS8dn3EZZj0Gh1aARyHoPQuCq5idSkRExDS66lkBoJXpRVzX5iPneP2nP9hxLAGA8kG+jLivKs3DXfRTexFUl26Fsx+rZ37Ywi/bT9AyIphJ/euZHefW2e3w4yDY9gPYPKH3DCjfzOxUIiJOy9nrkuQMfSwtIuLE6pQpwo+DGvN+1xoEFvLg4KkU+n+1kce+3sih0ylmxxORAmznsQR+2X4CiwVebBdudpxbZxiw4N+OJpHFBt2+UpNIREQENYpERJye1Wqhe70wlg5rzuP3lMPNamHJnnjafrSCUfN2k5x62eyIIlIAvb8gGoDOkSWpEuqCnyqveB/Wj3fcf2AcRHQ0N4+IiIiTUKNIRMRF+Hu58+p9VZk/pClNKweRnmHw2YqDtBi9nFmbj2K360xiEckbaw6cZuXeU7jbLDzfurLZcW7dugmw/B3H/fbvQWQvc/OIiIg4ETWKRERcTMXgQnwzoB5f9q1LmWI+nEpK5YUZ2+gyfg3bYs+bHU9E8jnDMHhvvmM20cP1S1O6mI/JiW5R1BSY/7LjfvPhcPdT5uYRERFxMmoUiYi4IIvFQuuqISx8vikvt4/A18NGVOx5Hhi3mhdnbCM+6ZLZEUUkn1rwRxzbYs/j42HjmZaVzI5za/b86li8GqDBQGj2srl5REREnJAaRSIiLszTzcbA5hVYOqw5XWqXBGDG5qO0HL2Cz1ceIO2y3eSEIpKfXM6wM3qhYzbRY/eUI8jP0+REt+DgCpjRH4wMiOwN7d4Bi8XsVCIiIk5HjSIRkXwgxN+LD7tHMvvpRtQoFUBy6mXe+W0P7cesZNmeeLPjiUg+MXvrMfbHJ1PEx50nmpY3O072Hd0MUx+GjDSIuA86fQJWvQ0WERG5FlVIEZF8pHbpIsx9ujHvP1SDwEIeHDydwoCvN/Lo1xs5dDrF7Hgi4sIupWcwZtFeAAa1qIi/l7vJibIpfjd83xXSkqFcU+g6EWxuZqcSERFxWmoUiYjkM1arhe51w1g6rDlPNCmHm9XC0j3xtP1oBaN+203SpXSzI4qIC/pu3RGOJ1wiNMCLR+4uY3ac7Dl3GCY/CBfPQck60PMHcPcyO5WIiIhTU6NIRCSf8vdy5z8dq7Lg+aY0Dw8iPcPgs5UHafnBCmZuPordbpgdUURcROKldMYt2w/A860r4+VuMzlRNiSdhG8fgKQTEFQFes8ETz+zU4mIiDg9NYpERPK5CkGF+HpAfSb1r0u5QF9OJaUybMY2Hhy/hqjY82bHExEX8OXKg5y7kE6FIN/MhfOd2oWzMLmLY0ZRkbLQZw74FDU7lYiIiEtQo0hEpIBoGRHC/CFNeKVDBL4eNrbFnqfzuNW8MH0b8YmXzI4nIk7qVFIqX646BMCL7SJwszn528fUZPihO8T/AYWKQ5+54B9qdioRERGX4eSVXkREcpKnm42nmlVg2bDmdK1dCoBZW47SYvRyPltxgLTLdpMTioizGbt0HxfSMqgZVph21ULMjnNjl1Nh2iNwdCN4FXbMJCpazuxUIiIiLkWNIhGRAijY34sPutdkztONqBlWmJS0DEbN20O7MStZuifO7Hgi4iRizlzghw0xALzcPhyLxWJyohvIuAyzHoODy8DdFx6ZBSFVzU4lIiLictQoEhEpwGqVLsKcgY0Y3a0mgYU8OXQ6hUe/3kT/rzZw4FSy2fFExGQfLd5LeoZBk0qBNKoQaHac6zMM+Hkw7P4ZbB7Q6wcoVdfsVCIiIi5JjSIRkQLOarXwUJ1SLBvWjH81LY+7zcLy6FO0H7OSd37bTdKldLMjiogJdp9IZG7UMQBeahdhcpobMAxY+CpEfQcWKzw0Cco3NzuViIiIy1KjSEREAPDzcmf4vVVYMKQpLcKDSM8w+HzlQVqMXsH0TbHY7YbZEUUkD41eEI1hQMcaoVQvFWB2nOtbORrWjnXcv38sVOlkbh4REREXp0aRiIhkUT6oEF8NqM9X/etRLtCX08mpvDRzOw9+upotMefMjicieWDj4bMs2ROPzWphWNtws+Nc3/rPYdlbjvvtRkGt3ubmERERyQfUKBIRkWtqERHMgiFN+fe9ERTydGPb0QS6fLqGodOjiE+8ZHY8EcklhmHw3rw9APSoF0a5QF+TE13H9ukw70XH/WYvQ8Onzc0jIiKST6hRJCIi1+XhZuXJphVYOqwZ3eqUAmD2lmO0GL2c8csPkHo5w+SEIpLTlu6JZ9ORc3i6WRncqpLZca4teh7Mecpxv/6/oPlwc/OIiIjkI2oUiYjITQX7efF/3Woyd1BjIsMKk5KWwXvz99Duo5Us2R2HYWj9IpH8IMNu8P78aAAGNC5HiL+XyYmu4dDvML0fGBlQoye0fxcsFrNTiYiI5BtqFImISLZFhhVm9sBGfNCtJkF+nhw+c4HHvtlE/682cuBUstnxROQO/bTtGNFxSfh7uTGwWQWz41zt2BaY0hMyUiH8XnhgLFj1dlZERCQnqbKKiMgtsVotdK1TimXDmvOvZuVxt1lYsfcU7T5ayVu/7CLxUrrZEUXkNqRdtvPBwr0ADGxekQAfd5MT/UP8HviuK6QlQ9km8NBXYHOyjCIiIvmAGkUiInJbCnm6MbxDFRY+34xWEcFctht8ueoQLUcvZ/rGWOx2nY4m4kp+WH+Eo+cuEuznSf9GZc2Ok9W5IzD5Qbh4FkrUhl5TwN0JT4sTERHJB9QoEhGRO1Iu0JeJ/evx9YB6lA/y5XRyGi/N2k7nT1ez+cg5s+OJSDYkp17mf0v3AzC4dSW8PWwmJ/qbpDiY3BmSjkNQBDwyCzz9zE4lIiKSb6lRJCIiOaJ5eDDzBzflP/dWoZCnG9uPJtB1/BqGTosiLvGS2fFE5AYmrTrEmZQ0yhbzoXvdMLPj/OXiOfiuC5w9CIVLQ5854FPU7FQiIiL5mhpFIiKSYzzcrDzRtDzLhjWne91SAMzeeowWo5fz6fL9pF7OMDmhiPzT2ZQ0Pl95EIAX2objbnOSt4dpKfB9d4jbCb7B0Gcu+JcwO5WIiEi+5yTvBEREJD8J8vPk/Ydq8uOgxtQqXZgLaRm8Pz+ath+tZNGuOAxD6xeJOItPl+0nOfUyd5X0p2P1ULPjOFxOhWmPwNEN4BXgmElUzAmvwiYiIpIPqVEkIiK5pmZYYWY91YgPu9ck2M+TI2cu8MS3m+g7aQP745PMjidS4B07f5Fv1x4B4KV2EVitFpMTAfYMmP0EHFgK7j7QeyYUv8vsVCIiIgWGGkUiIpKrrFYLXWqXYumw5gxsXgEPm5Xf952m/ZjfefOXXSReSjc7okiBNWbRXtIy7DQsX4wmlQLNjgOGAT8Phl0/gtUden4PYfXNTiUiIlKgqFEkIiJ5opCnGy+3j2Dh801pXSWYy3aDiasO0eL/ljNtYwx2u05HE8lL++KSmLXlKAAvtQ/HYjF5NpFhwKLXYOtksFjhoYlQoaW5mURERAogNYpERCRPlQ305ct+9fjm0fqUD/LlTEoaL8/awQPjVrP5yFmz44kUGKMXRmM3oF21EGqVLmJ2HPj9A1jzP8f9Tp9A1QfMzSMiIlJAqVEkIiKmaFY5iPmDm/Jqxyr4ebqx41gCXcevZcjUrZxMuGR2PJF8bWvMORb8EYfVAi+2Czc7Dmz8Epa+6bjf9m2o3cfcPCIiIgWYGkUiImIaDzcrjzcpz9JhzelRNwyLBeZGHaflB8sZt2w/l9IzzI4oku8YhsF78/cA8FCdUlQM9jM30I6Z8Oswx/2mL0KjZ8zNIyIiUsCpUSQiIqYL8vPkvYdq8NOge6hdujAX0jL4vwXRtP1oJQv/OIlhaP0ikZyyct9p1h08i4eblcGtK5sbZu8CmPMvwIB6T0CL/5ibR0RERNQoEhER51G9VACzBjZiTI9IQvw9iTl7gScnb6bvpA3sj08yO56Iy7PbDd6/Mpuo791lKFnY27wwh1fB9L5gvwzVu0OH98HsBbVFREREjSIREXEuFouFzrVKsvSF5jzdvAIeNiu/7ztNuzG/8/LM7Ww/el4zjERu0687TvDH8UT8PN14ukVF84Ic3wo/9ITLl6ByB+j8KVj1tlRERMQZqCKLiIhT8vV046X2ESwa2pTWVULIsBtM2xTL/WNX0/GTVUxed4TES+lmxxRxGekZdj5YGA3Ak03LU9TXw5wgp/bCd10hLQnK3APdvgKbuzlZRERE5CpqFImIiFMrU8yXL/vVZfq/GvJAZAk8bFZ2nUjktbk7afD2El6auY0tMec0y0jkJqZtjOXwmQsEFvLg0XvKmRPifAxM7gwXzkBoJPSaAu4mnv4mIiIiV3EzO4CIiEh21C9XlPrlivJ6pzRmbTnK1I2x7I9PZvqmo0zfdJSI4n70ql+azrVKEuCt2Qkif3cxLYOPl+wD4NmWlfD1NOEtYHI8fNsZEo9BYGV4ZDZ4+ed9DhEREbkhNYpERMSlFPH14PEm5XnsnnJsOnKOKetj+HXHCfacTGLkT3/wzm+76VgjlIfrl6ZOmSJYtDiuCAkX06kS6o+nWzK96pfO+wAXz8PkLnD2AASUhj5zwbdY3ucQERGRm7IYmquf7yUmJhIQEEBCQgL+/vrkTkTyn4QL6czZepQpG2KJjvvr6miVggvRs35putYuSWEfk9ZjkauoLmVfTh+rsylpeb82UdoFmPwgxK4D32B4dD4Uq5C3GUREJEeohhcMahQVAPplFpGCwjAMtsaeZ8r6GH7efpxL6XYAPNys3HtXcXrWL02DckU1y8hkqkvZ5/LH6nIaTO0F+xeDVwD0/xWKVzc7lYiI3CaXr0uSLTr1TERE8g2LxULt0kWoXboIr3Wqyo9bj/HDhlh2n0hkbtRx5kYdp3yQL73qlaZrnVLmXfVJpCCwZ8CcJx1NIjdveHiGmkQiIiIuQDOKCgB1fUWkIDMMg+1HE5iyIYafth3nQloGAB42K22rhfBw/dLcXb4YVqtmGeUV1aXsc9ljZRjw82DY8g1Y3eHhqVCxtdmpRETkDrlsXZJbohlFIiKSr1ksFmqGFaZmWGFeva8qP0UdZ8qGGHYcS+CX7Sf4ZfsJyhbzoUe90jxUpxRBfp5mRxZxfYtHOppEFit0/UJNIhEREReiGUUFgLq+IiJX23nMMcvox6jjJKdeBsDNaqFttRB61S9N4wqBmmWUS1SXss8lj9Wqj2Dx6477nT6BOv1MjSMiIjnHJeuS3DI1igoA/TKLiFxfSuplftl+nCkbYomKPZ85HlbUm571StOtTimC/b3MC5gPqS5ln8sdq02T4JfnHffbvAmNnzM3j4iI5CiXq0tyW9QoKgD0yywikj27jicydWMMc7YcI+nKLCOb1UKriGB6NShN00pB2DTL6I6pLmWfSx2rHTNh1uOAAU1egFYjzE4kIiI5zKXqktw2NYoKAP0yi4jcmotpGfy64wRTNsSw+ci5zPGShb3pUS+M7nXDKB6gWUa3S3Up+1zmWO1dCFN7gf0y1H0MOn4AFjVVRUTyG5epS3JH1CgqAPTLLCJy+/bGJTFlQwyztxwj4WI6AFYLtIwIplf90jSrHISbzWpySteiupR9LnGsjqyByQ/C5Utw10PQ5Quw6ndCRCQ/com6JHdMjaICQL/MIiJ37lJ6BvN2nmDK+lg2HD6bOV7c34vu9cLoUS+MkoW9TUzoOlSXss/pj9WJbfD1fZCaCJXaQc/vweZudioREcklTl+XJEeoUVQA6JdZRCRn7Y9PYuqGWGZtOcq5C45ZRhYLNK8cRM/6pWkZEYy7Zhldl+pS9jn1sTq9Dya1hwunoUxjeGQWuKtZKiKSnzl1XZIco0ZRAaBfZhGR3JF6OYMFf8QxZX0Maw+eyRwP9vOke13HLKOwoj4mJnROqkvZ57TH6nyso0mUeBRCa0K/n8ErwOxUIiKSy5y2LkmOUqOoANAvs4hI7jt4KplpG2OZufkoZ1LSAMcso3sqBvJw/dK0rhqiWUZXqC5ln1Meq+RT8FV7OLMfilWCR+eDb6DZqUREJA84ZV2SHKdGUQGgX2YRkbyTdtnOol1xTNkQw6r9pzPHAwt58lCdUvSsF0bZQF8TE5pPdSn7nO5YXUpwrEl0cjsEhDmaRAGlzE4lIiJ5xOnqkuQKN7MDiIiI5CceblY61gilY41QjpxJYdrGWKZvOsrp5FQmrDjAhBUHaFyxGL3ql6ZN1RA83WxmRxbJnrQL8ENPR5PINwj6zFWTSEREJB9So0hERCSXlCnmy0vtI3i+TWWW7I5jyoZYVu47xer9Z1i9/wxFfT0yZxmVDypkdlyR67ucBjP6Qcwa8PSHR2ZDYEWzU4mIiEguUKNIREQkl7nbrLS/K5T2d4USe/YC0zfFMn1TLHGJqXy+8iCfrzxIg3JFebhBadpVK46Xu2YZiROxZ8Dcp2DfQnDzhoenQ2gNs1OJiIhILlGjSEREJA+FFfXhhbbhDG5ViWXRp5iyIYbl0fGsP3SW9YfOUtjHnS61StGrfhiVQvzMjisFnWHAry/AzllgdYMek6FMQ7NTiYiISC5So0hERMQEbjYrbaqG0KZqCMfPX2T6plimbYzlRMIlJq0+xKTVh6hXtgi96pfm3uqhmmUk5ljyX9j8FWCBLp9DpTZmJxIREZFcpqueFQBamV5ExDVk2A1W7I1nyoZYlu6JJ8PuKNH+Xm50qV2KnvXDiCju+v+Oqy5ln6nHavXHsGiE436nj6FO/7x9fhERcTqq4QWDZhSJiIg4CZvVQsuIEFpGhHAy4RIzNsUydWMsx85f5Os1h/l6zWFqlS5Mr/qlua9GKD4eKuOSSzZ//VeTqPUbahKJiIgUIJpRVACo6ysi4roy7Aar9p9myvoYFu+O4/KVWUZ+nm50rlWSnvXDqFYiwOSUt0Z1KftMOVY7Z8PMRwEDGg+BNm/kzfOKiIjTUw0vGPRRpIiIiBOzWS00qxxEs8pBxCddYubmo0zdEEvM2QtMXneEyeuOULNUAL3ql6ZTzRL4eqq0yx3YtxhmPwkYUGcAtH7d7EQiIiKSx6xmByiIxo0bR9myZfHy8qJBgwZs2LDhutt+8cUXNGnShCJFilCkSBFat259w+1FRCT/Cvbz4unmFVk+rDnfPdaAjjVCcbdZ2HY0gVdm76D+24sZPnsHO44mmB1VXFHMOpj2CNjToVoX6PgBWCxmpxIREZE8pkZRHps2bRpDhw5l5MiRbNmyhZo1a9KuXTvi4+Ovuf3y5cvp1asXy5YtY+3atYSFhdG2bVuOHTuWx8lFRMRZWK0W7qkUyLiHa7N2eCuGd4igbDEfUtIymLIhhk5jV3Hf/37nu3VHSLqUbnZccQUntsP33eHyRajYBh78DKy60p6IiEhBpEZRHvvwww954oknGDBgAFWrVmXChAn4+PgwadKka27//fff8/TTTxMZGUlERARffvkldrudJUuW5HFyERFxRoGFPPlXswosG9acKU/czf01S+Bhs7LzWCKvzt1J/beX8PLM7UTFnkfLEt7Yrcz4bd68ORaL5apbx44dM7cxDIMRI0YQGhqKt7c3rVu3Zt++fXnxUm7N6f3wXRdITYDSDaH7t+DmYXYqERERMYkaRXkoLS2NzZs307p168wxq9VK69atWbt2bbb2ceHCBdLT0ylatGhuxRQRERdksVhoWKEYn/Sqxbp/t+LVjlWoEOTLxfQMpm2KpfO41XT4+He+XXuYhIuaZfRPtzrjd/bs2Zw4cSLztnPnTmw2G926dcvc5v333+eTTz5hwoQJrF+/Hl9fX9q1a8elS5fy6mXdXMJRmNwZUk5B8erQayp4+JidSkREREykRlEeOn36NBkZGYSEhGQZDwkJ4eTJk9nax8svv0yJEiWyNJv+KTU1lcTExCw3EREpOIr6evB4k/IsHtqM6f9qyIO1SuLhZmXPySRG/PgHDd5ZzAvTt7H5yFnNMrriVmf8Fi1alOLFi2feFi1ahI+PT2ajyDAMxowZw6uvvsoDDzxAjRo1+Pbbbzl+/Dhz587Nw1d2AymnYfKDkBALxSrCI3PAu7DZqURERMRkahS5kHfffZepU6cyZ84cvLy8rrvdqFGjCAgIyLyFhYXlYUoREXEWFouF+uWK8lGPSDb8uxUjO1WlckghLqXbmbXlKF3Hr6XdmJV8tfoQ5y+kmR3XNDkx43fixIn07NkTX19fAA4dOsTJkyez7DMgIIAGDRrccJ959mHPpUT4riuc3gv+paDPXCgUlDvPJSIiIi5FjaI8FBgYiM1mIy4uLst4XFwcxYsXv+FjR48ezbvvvsvChQupUaPGDbcdPnw4CQkJmbfY2Ng7zi4iIq6tsI8HAxqXY8GQpswa2IiH6pTCy93K3rhk3vh5F/XfWcLz06LYcKjgzTK60xm/GzZsYOfOnTz++OOZY38+7lb3mScf9qRfhCk94UQU+BSDvnOhsD5UEhEREQc1ivKQh4cHderUybIQ9Z8LUzds2PC6j3v//fd58803mT9/PnXr1r3p83h6euLv75/lJiIiAo5ZRnXKFGF0t5qs/3dr/vtANSKK+5F22c6crcfo/tlaWn+4gi9/P8jZlII7y+hWTJw4kerVq1O/fv073leuf9iTkQ7T+8GR1eDpD4/MhsBKOfscIiIi4tLczA5Q0AwdOpR+/fpRt25d6tevz5gxY0hJSWHAgAEA9O3bl5IlSzJq1CgA3nvvPUaMGMEPP/xA2bJlMz+FLFSoEIUKFTLtdYiIiOsL8Hanb8Oy9Lm7DNuOJjBlfQw/bz/OgVMpvPXrbt6fH037u4rTs34YDcsXw2KxmB05V9zJjN+UlBSmTp3Kf//73yzjfz4uLi6O0NDQLPuMjIy87v48PT3x9PS8xVeQTXY7zB0I+xaAm5dj4eoS188iIiIiBZNmFOWxHj16MHr0aEaMGEFkZCRRUVHMnz8/c2p6TEwMJ06cyNx+/PjxpKWl8dBDDxEaGpp5Gz16tFkvQURE8hmLxUJkWGHee6gG6//dircfvIu7SvqTlmHnp23HefiL9bT8YAWfrzyQL09Lu90ZvwAzZswgNTWVRx55JMt4uXLlKF68eJZ9JiYmsn79+pvuM1cYBsx7EXbMAKsbdJ8MZRvnfQ4RERFxehYjP77jkywSExMJCAggISFBp6GJiEi27TiawJSNMfy49RgpaRk0LF+MKU/efcf7dca6NG3aNPr168dnn32WOeN3+vTp7Nmzh5CQkKtm/P6pSZMmlCxZkqlTp161z/fee493332Xb775hnLlyvHaa6+xfft2du3adcOLUvxdjh2r+N3wWVPHqWddv4TqD93+vkREpMByxhouOU+nnomIiMg1VS8VQPVS1fnPvVX4edtxShbxNjtSrunRowenTp1ixIgRnDx5ksjIyKtm/FqtWSdiR0dHs2rVKhYuXHjNfb700kukpKTw5JNPcv78ee655x7mz5+f7SZRjgquAg9Pg/MxahKJiIjIDWlGUQGgrq+IiDgT1aXs07ESERFnorpUMGiNIhERERERERERAdQoEhERERERERGRK9QoEhERERERERERQI0iERERERERERG5Qo0iEREREREREREB1CgSEREREREREZEr1CgSERERERERERFAjSIREREREREREblCjSIREREREREREQHUKBIRERERERERkSvUKBIREREREREREUCNIhERERERERERuUKNIhERERERERERAdQoEhERERERERGRK9QoEhERERERERERANzMDiC5zzAMABITE01OIiIi8lc9+rM+yfWphouIiDNRDS8Y1CgqAJKSkgAICwszOYmIiMhfkpKSCAgIMDuGU1MNFxERZ6Qanr9ZDLUC8z273c7x48fx8/PDYrHc0b4SExMJCwsjNjYWf3//HEqYd5TfXMpvLuU3l/L/xTAMkpKSKFGiBFarzoK/EdXwvyi/uZTfXMpvLuX/i2p4waAZRQWA1WqlVKlSObpPf39/l/xH8k/Kby7lN5fym0v5HfQpZPaohl9N+c2l/OZSfnMpv4NqeP6nFqCIiIiIiIiIiABqFImIiIiIiIiIyBVqFMkt8fT0ZOTIkXh6epod5bYov7mU31zKby7lF7O5+s9Q+c2l/OZSfnMpvxQ0WsxaREREREREREQAzSgSEREREREREZEr1CgSERERERERERFAjSIREREREREREblCjSLJYuXKlXTq1IkSJUpgsViYO3fuTR+zfPlyateujaenJxUrVuTrr7/O9ZzXc6v5ly9fjsViuep28uTJvAn8N6NGjaJevXr4+fkRHBxM586diY6OvunjZsyYQUREBF5eXlSvXp3ffvstD9Je7Xbyf/3111cdey8vrzxKnNX48eOpUaMG/v7++Pv707BhQ+bNm3fDxzjLsYdbz+9Mx/5a3n33XSwWC0OGDLnhds70M/hTdrI72/F//fXXr8oTERFxw8c447Ev6FTDVcNvl2q4anhOceX6DarhIn9So0iySElJoWbNmowbNy5b2x86dIiOHTvSokULoqKiGDJkCI8//jgLFizI5aTXdqv5/xQdHc2JEycyb8HBwbmU8PpWrFjBoEGDWLduHYsWLSI9PZ22bduSkpJy3cesWbOGXr168dhjj7F161Y6d+5M586d2blzZx4md7id/AD+/v5Zjv2RI0fyKHFWpUqV4t1332Xz5s1s2rSJli1b8sADD/DHH39cc3tnOvZw6/nBeY79P23cuJHPPvuMGjVq3HA7Z/sZQPazg/Md/2rVqmXJs2rVqutu64zHXlTDVcNvn2q4anhOcOX6DarhZh9/cTKGyHUAxpw5c264zUsvvWRUq1Yty1iPHj2Mdu3a5WKy7MlO/mXLlhmAce7cuTzJdCvi4+MNwFixYsV1t+nevbvRsWPHLGMNGjQw/vWvf+V2vJvKTv6vvvrKCAgIyLtQt6hIkSLGl19+ec3vOfOx/9ON8jvrsU9KSjIqVapkLFq0yGjWrJkxePDg627rbD+DW8nubMd/5MiRRs2aNbO9vbMde7maari5VMPNpxqet1y5fhuGarjZx1+cj2YUyR1Zu3YtrVu3zjLWrl071q5da1Ki2xMZGUloaCht2rRh9erVZscBICEhAYCiRYtedxtnPv7ZyQ+QnJxMmTJlCAsLu+mnZ3klIyODqVOnkpKSQsOGDa+5jTMf++zkB+c89oMGDaJjx45XHdtrcbafwa1kB+c7/vv27aNEiRKUL1+e3r17ExMTc91tne3Yy+3JLz9H1fCcpxpuHlet4a5cv0E13OzjL87HzewA4tpOnjxJSEhIlrGQkBASExO5ePEi3t7eJiXLntDQUCZMmEDdunVJTU3lyy+/pHnz5qxfv57atWublstutzNkyBAaN27MXXfddd3trnf8zVif4e+ymz88PJxJkyZRo0YNEhISGD16NI0aNeKPP/6gVKlSeZjYYceOHTRs2JBLly5RqFAh5syZQ9WqVa+5rTMe+1vJ72zHHmDq1Kls2bKFjRs3Zmt7Z/oZ3Gp2Zzv+DRo04OuvvyY8PJwTJ07wxhtv0KRJE3bu3Imfn99V2zvTsZfbpxqeO1TDVcNvhyvXcFeu36AaDub//Rfno0aRFGjh4eGEh4dnft2oUSMOHDjARx99xOTJk03LNWjQIHbu3HnD84udWXbzN2zYMMunZY0aNaJKlSp89tlnvPnmm7kd8yrh4eFERUWRkJDAzJkz6devHytWrLjuGzVncyv5ne3Yx8bGMnjwYBYtWuQ0C3Jm1+1kd7bj36FDh8z7NWrUoEGDBpQpU4bp06fz2GOP5XkekexQDc8dquHmcNUa7sr1G1TDRa5HjSK5I8WLFycuLi7LWFxcHP7+/k7/SeT11K9f39Q3d8888wy//PILK1euvOmnEtc7/sWLF8/NiDd0K/n/yd3dnVq1arF///5cSndjHh4eVKxYEYA6deqwceNGPv74Yz777LOrtnXGY38r+f/J7GO/efNm4uPjs8wCyMjIYOXKlYwdO5bU1FRsNluWxzjLz+B2sv+T2cf/nwoXLkzlypWvm8dZjr3cGdXwnKcarhp+u1y1hrty/QbV8D+Z/fdfnI/WKJI70rBhQ5YsWZJlbNGiRTc8p9rZRUVFERoamufPaxgGzzzzDHPmzGHp0qWUK1fupo9xpuN/O/n/KSMjgx07dphy/K/FbreTmpp6ze8507G/nhvl/yezj32rVq3YsWMHUVFRmbe6devSu3dvoqKirvkmzVl+BreT/Z/MPv7/lJyczIEDB66bx1mOvdyZ/PhzVA2/Parhzvd331VquCvXb1AN/5Oz/f0XJ2DuWtribJKSkoytW7caW7duNQDjww8/NLZu3WocOXLEMAzDeOWVV4w+ffpkbn/w4EHDx8fHePHFF43du3cb48aNM2w2mzF//nyXyP/RRx8Zc+fONfbt22fs2LHDGDx4sGG1Wo3FixfnefaBAwcaAQEBxvLly40TJ05k3i5cuJC5TZ8+fYxXXnkl8+vVq1cbbm5uxujRo43du3cbI0eONNzd3Y0dO3a4RP433njDWLBggXHgwAFj8+bNRs+ePQ0vLy/jjz/+yPP8r7zyirFixQrj0KFDxvbt241XXnnFsFgsxsKFC6+Z3ZmO/e3kd6Zjfz3/vOqIs/8M/u5m2Z3t+L/wwgvG8uXLjUOHDhmrV682WrdubQQGBhrx8fHXzO/Mx74gUw1XDc/L/M7075hquHPVcFeu34ahGi5iGIahRpFk8eelZv9569evn2EYhtGvXz+jWbNmVz0mMjLS8PDwMMqXL2989dVXeZ7771luJf97771nVKhQwfDy8jKKFi1qNG/e3Fi6dKkp2a+VG8hyPJs1a5b5Wv40ffp0o3LlyoaHh4dRrVo149dff83b4FfcTv4hQ4YYpUuXNjw8PIyQkBDj3nvvNbZs2ZL34Q3DePTRR40yZcoYHh4eRlBQkNGqVavMN2iG4dzH3jBuPb8zHfvr+ecbNWf/GfzdzbI72/Hv0aOHERoaanh4eBglS5Y0evToYezfvz/z+6507Asy1XDV8NulGq4anpNcuX4bhmq4iGEYhsUwDCPn5ymJiIiIiIiIiIir0RpFIiIiIiIiIiICqFEkIiIiIiIiIiJXqFEkIiIiIiIiIiKAGkUiIiIiIiIiInKFGkUiIiIiIiIiIgKoUSQiIiIiIiIiIleoUSQiIiIiIiIiIoAaRSIiIiIiIiIicoUaRSIiucBisTB37lyzY4iIiMgtUP0WEVGjSETyof79+2OxWK66tW/f3uxoIiIich2q3yIizsHN7AAiIrmhffv2fPXVV1nGPD09TUojIiIi2aH6LSJiPs0oEpF8ydPTk+LFi2e5FSlSBHBMKx8/fjwdOnTA29ub8uXLM3PmzCyP37FjBy1btsTb25tixYrx5JNPkpycnGWbSZMmUa1aNTw9PQkNDeWZZ57J8v3Tp0/z4IMP4uPjQ6VKlfjpp58yv3fu3Dl69+5NUFAQ3t7eVKpU6ao3xiIiIgWN6reIiPnUKBKRAum1116ja9eubNu2jd69e9OzZ092794NQEpKCu3ataNIkSJs3LiRGTNmsHjx4ixvJMePH8+gQYN48skn2bFjBz/99BMVK1bM8hxvvPEG3bt3Z/v27dx777307t2bs2fPZj7/rl27mDdvHrt372b8+PEEBgbm3QEQERFxQarfIiJ5wBARyWf69etn2Gw2w9fXN8vt7bffNgzDMADjqaeeyvKYBg0aGAMHDjQMwzA+//xzo0iRIkZycnLm93/99VfDarUaJ0+eNAzDMEqUKGH85z//uW4GwHj11Vczv05OTjYAY968eYZhGEanTp2MAQMG5MwLFhERyQdUv0VEnIPWKBKRfKlFixaMHz8+y1jRokUz7zds2DDL9xo2bEhUVBQAu3fvpmbNmvj6+mZ+v3HjxtjtdqKjo7FYLBw/fpxWrVrdMEONGjUy7/v6+uLv7098fDwAAwcOpGvXrmzZsoW2bdvSuXNnGjVqdFuvVUREJL9Q/RYRMZ8aRSKSL/n6+l41lTyneHt7Z2s7d3f3LF9bLBbsdjsAHTp04MiRI/z2228sWrSIVq1aMWjQIEaPHp3jeUVERFyF6reIiPm0RpGIFEjr1q276usqVaoAUKVKFbZt20ZKSkrm91evXo3VaiU8PBw/Pz/Kli3LkiVL7ihDUFAQ/fr147vvvmPMmDF8/vnnd7Q/ERGR/E71W0Qk92lGkYjkS6mpqZw8eTLLmJubW+aCkzNmzKBu3brcc889fP/992zYsIGJEycC0Lt3b0aOHEm/fv14/fXXOXXqFM8++yx9+vQhJCQEgNdff52nnnqK4OBgOnToQFJSEqtXr+bZZ5/NVr4RI0ZQp04dqlWrRmpqKr/88kvmG10REZGCSvVbRMR8ahSJSL40f/58QkNDs4yFh4ezZ88ewHFFk6lTp/L0008TGhrKlClTqFq1KgA+Pj4sWLCAwYMHU69ePXx8fOjatSsffvhh5r769evHpUuX+Oijjxg2bBiBgYE89NBD2c7n4eHB8OHDOXz4MN7e3jRp0oSpU6fmwCsXERFxXarfIiLmsxiGYZgdQkQkL1ksFubMmUPnzp3NjiIiIiLZpPotIpI3tEaRiIiIiIiIiIgAahSJiIiIiIiIiMgVOvVMREREREREREQAzSgSEREREREREZEr1CgSERERERERERFAjSIREREREREREblCjSIREREREREREQHUKBIRERERERERkSvUKBIREREREREREUCNIhERERERERERuUKNIhERERERERERAdQoEhERERERERGRK/4fiGXWbFTU4tIAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = Adam, lr = 0.005\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.582 | Train Acc: 69.63%\n",
            "\t Val. Loss: 0.532 |  Val. Acc: 72.73%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.360 | Train Acc: 84.12%\n",
            "\t Val. Loss: 0.505 |  Val. Acc: 76.09%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.241 | Train Acc: 89.77%\n",
            "\t Val. Loss: 0.523 |  Val. Acc: 78.00%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.157 | Train Acc: 93.79%\n",
            "\t Val. Loss: 0.578 |  Val. Acc: 79.09%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.111 | Train Acc: 95.15%\n",
            "\t Val. Loss: 0.645 |  Val. Acc: 79.27%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = SGD, lr = 0.005\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.683 | Train Acc: 56.73%\n",
            "\t Val. Loss: 0.672 |  Val. Acc: 58.64%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.662 | Train Acc: 61.94%\n",
            "\t Val. Loss: 0.659 |  Val. Acc: 61.91%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.651 | Train Acc: 63.02%\n",
            "\t Val. Loss: 0.656 |  Val. Acc: 62.64%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.643 | Train Acc: 65.00%\n",
            "\t Val. Loss: 0.653 |  Val. Acc: 62.27%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.636 | Train Acc: 64.94%\n",
            "\t Val. Loss: 0.646 |  Val. Acc: 63.00%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = RMSprop, lr = 0.005\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.987 | Train Acc: 70.50%\n",
            "\t Val. Loss: 0.520 |  Val. Acc: 75.00%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.338 | Train Acc: 85.21%\n",
            "\t Val. Loss: 0.571 |  Val. Acc: 76.00%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.236 | Train Acc: 89.83%\n",
            "\t Val. Loss: 0.819 |  Val. Acc: 70.18%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.165 | Train Acc: 93.13%\n",
            "\t Val. Loss: 0.527 |  Val. Acc: 80.00%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.117 | Train Acc: 95.12%\n",
            "\t Val. Loss: 0.767 |  Val. Acc: 73.64%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = Adam, lr = 0.01\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.540 | Train Acc: 72.92%\n",
            "\t Val. Loss: 0.483 |  Val. Acc: 77.27%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.314 | Train Acc: 86.17%\n",
            "\t Val. Loss: 0.577 |  Val. Acc: 77.91%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.198 | Train Acc: 91.33%\n",
            "\t Val. Loss: 0.588 |  Val. Acc: 80.18%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.146 | Train Acc: 93.75%\n",
            "\t Val. Loss: 0.668 |  Val. Acc: 80.18%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.131 | Train Acc: 94.37%\n",
            "\t Val. Loss: 0.831 |  Val. Acc: 80.36%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = SGD, lr = 0.01\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.672 | Train Acc: 59.02%\n",
            "\t Val. Loss: 0.660 |  Val. Acc: 64.36%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.647 | Train Acc: 63.71%\n",
            "\t Val. Loss: 0.669 |  Val. Acc: 58.64%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.634 | Train Acc: 64.50%\n",
            "\t Val. Loss: 0.651 |  Val. Acc: 61.64%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.623 | Train Acc: 66.06%\n",
            "\t Val. Loss: 0.633 |  Val. Acc: 65.55%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.612 | Train Acc: 67.63%\n",
            "\t Val. Loss: 0.625 |  Val. Acc: 65.91%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCEWithLogitsLoss(), optimizer = RMSprop, lr = 0.01\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 3.715 | Train Acc: 68.19%\n",
            "\t Val. Loss: 0.597 |  Val. Acc: 76.45%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.301 | Train Acc: 87.02%\n",
            "\t Val. Loss: 0.548 |  Val. Acc: 76.91%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.189 | Train Acc: 92.13%\n",
            "\t Val. Loss: 0.581 |  Val. Acc: 76.27%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.138 | Train Acc: 94.06%\n",
            "\t Val. Loss: 0.592 |  Val. Acc: 79.27%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.117 | Train Acc: 94.79%\n",
            "\t Val. Loss: 0.683 |  Val. Acc: 79.36%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with criteria = BCELoss(), optimizer = Adam, lr = 0.001\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "RuntimeError",
          "evalue": "Found dtype Double but expected Float",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-279-585817b0837e>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mTuning_model_CNN\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlearning_rate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcriterias\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moptimizers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrain_dataloader\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalid_dataloader\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_epochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-278-9df8871ae665>\u001b[0m in \u001b[0;36mTuning_model_CNN\u001b[0;34m(learning_rate, criterias, optimizers, train_dataloader, valid_dataloader, device, num_epochs)\u001b[0m\n\u001b[1;32m     50\u001b[0m           \u001b[0mstart_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     51\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 52\u001b[0;31m           \u001b[0mtrain_loss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrain_acc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrain_dataloader\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moptimizer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcriterion\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     53\u001b[0m           \u001b[0mvalid_loss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalid_acc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mevaluate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalid_dataloader\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcriterion\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     54\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-271-231a5523df3e>\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(model, dataloader, optimizer, criterion, device)\u001b[0m\n\u001b[1;32m     21\u001b[0m         \u001b[0mpredictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreviews\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreviews_lengths\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     22\u001b[0m         \u001b[0msentiments\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbatch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"sentiments\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 23\u001b[0;31m         \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcriterion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpredictions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msentiments\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     24\u001b[0m         \u001b[0macc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbinary_accuracy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpredictions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msentiments\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1509\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compiled_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[misc]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1510\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1511\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1512\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1513\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_call_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1518\u001b[0m                 \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_pre_hooks\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0m_global_backward_hooks\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1519\u001b[0m                 or _global_forward_hooks or _global_forward_pre_hooks):\n\u001b[0;32m-> 1520\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mforward_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1521\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1522\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/modules/loss.py\u001b[0m in \u001b[0;36mforward\u001b[0;34m(self, input, target)\u001b[0m\n\u001b[1;32m    616\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    617\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mforward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTensor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTensor\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mTensor\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 618\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mF\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbinary_cross_entropy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreduction\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreduction\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    619\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    620\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/nn/functional.py\u001b[0m in \u001b[0;36mbinary_cross_entropy\u001b[0;34m(input, target, weight, size_average, reduce, reduction)\u001b[0m\n\u001b[1;32m   3125\u001b[0m         \u001b[0mweight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexpand\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3126\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3127\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_C\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_nn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbinary_cross_entropy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreduction_enum\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3129\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mRuntimeError\u001b[0m: Found dtype Double but expected Float"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "0NYbJWQNl1qD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "zI5ybh-l5uAO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "def train_model(HIDDEN_DIMs, N_LAYERSs, DROPOUTs, train_dataloader, valid_dataloader, num_epochs=10):\n",
        "    best_valid_loss = float(\"inf\")\n",
        "\n",
        "    for HIDDEN_DIM in HIDDEN_DIMs:\n",
        "        for N_LAYERS in N_LAYERSs:\n",
        "            for DROPOUT in DROPOUTs:\n",
        "                print(f\"Training with HIDDEN_DIM={HIDDEN_DIM}, N_LAYERS={N_LAYERS}, DROPOUT={DROPOUT}\")\n",
        "\n",
        "                INPUT_DIM = len(vocab)  # Assuming vocab is defined elsewhere\n",
        "                EMBEDDING_DIM = 100  # Adjust as needed\n",
        "                PAD_IDX = vocab[\"<pad>\"]\n",
        "\n",
        "                model = CNN(INPUT_DIM,\n",
        "                            EMBEDDING_DIM,\n",
        "                            HIDDEN_DIM,\n",
        "                            N_LAYERS,\n",
        "                            BIDIRECTIONAL,\n",
        "                            DROPOUT,\n",
        "                            PAD_IDX)\n",
        "\n",
        "                optimizer = optim.Adam(model.parameters())\n",
        "                criterion = nn.BCEWithLogitsLoss()\n",
        "\n",
        "                train_losses = []\n",
        "                train_accs = []\n",
        "                val_losses = []\n",
        "                val_accs = []\n",
        "\n",
        "                model = model.to(device)\n",
        "                criterion = criterion.to(device)\n",
        "\n",
        "                for epoch in range(num_epochs):\n",
        "                    start_time = time.time()\n",
        "\n",
        "                    train_loss, train_acc = train(model, train_dataloader, optimizer, criterion, device)\n",
        "                    valid_loss, valid_acc = evaluate(model, valid_dataloader, criterion, device)\n",
        "\n",
        "                    train_losses.append(train_loss)\n",
        "                    train_accs.append(train_acc)\n",
        "                    val_losses.append(valid_loss)\n",
        "                    val_accs.append(valid_acc)\n",
        "\n",
        "                    end_time = time.time()\n",
        "                    epoch_mins, epoch_secs = epoch_time(start_time, end_time)\n",
        "\n",
        "                    if valid_loss < best_valid_loss:\n",
        "                        best_valid_loss = valid_loss\n",
        "                        torch.save(model.state_dict(), \"best_model_cnn.pt\")\n",
        "\n",
        "                    print(f\"Epoch: {epoch+1:02} | Epoch Time: {epoch_mins}m {epoch_secs}s\")\n",
        "                    print(f\"\\tTrain Loss: {train_loss:.3f} | Train Acc: {train_acc*100:.2f}%\")\n",
        "                    print(f\"\\tVal. Loss: {valid_loss:.3f} | Val. Acc: {valid_acc*100:.2f}%\")\n",
        "\n",
        "                # Plot\n",
        "                plt.figure(figsize=(10, 5))\n",
        "                plt.subplot(1, 2, 1)\n",
        "                plt.plot(range(1, num_epochs + 1), train_losses, label='Train Loss')\n",
        "                plt.plot(range(1, num_epochs + 1), val_losses, label='Val Loss')\n",
        "                plt.xlabel('Epochs')\n",
        "                plt.ylabel('Loss')\n",
        "                plt.title(f\"Loss with HIDDEN_DIM={HIDDEN_DIM}, N_LAYERS={N_LAYERS}, DROPOUT={DROPOUT}\")\n",
        "                plt.legend()\n",
        "\n",
        "                plt.subplot(1, 2, 2)\n",
        "                plt.plot(range(1, num_epochs + 1), train_accs, label='Train Acc')\n",
        "                plt.plot(range(1, num_epochs + 1), val_accs, label='Val Acc')\n",
        "                plt.xlabel('Epochs')\n",
        "                plt.ylabel('Accuracy')\n",
        "                plt.title(f\"Accuracy with HIDDEN_DIM={HIDDEN_DIM}, N_LAYERS={N_LAYERS}, DROPOUT={DROPOUT}\")\n",
        "                plt.legend()\n",
        "\n",
        "                plt.tight_layout()\n",
        "                plt.show()\n",
        "\n",
        "# Sử dụng hàm train_model với các giá trị hyperparameters\n",
        "HIDDEN_DIMs = [128, 256]\n",
        "N_LAYERSs = [2, 3]\n",
        "DROPOUTs = [0.3, 0.5]\n",
        "\n",
        "train_model(HIDDEN_DIMs, N_LAYERSs, DROPOUTs, train_dataloader, valid_dataloader, num_epochs=10)"
      ],
      "metadata": {
        "id": "CVcKBryi5uC-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "704bd833-851f-4b1d-f5a2-1c31ef927121"
      },
      "execution_count": 280,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with HIDDEN_DIM=128, N_LAYERS=2, DROPOUT=0.3\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.605 | Train Acc: 67.90%\n",
            "\tVal. Loss: 0.554 | Val. Acc: 71.27%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.482 | Train Acc: 78.37%\n",
            "\tVal. Loss: 0.498 | Val. Acc: 75.18%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.391 | Train Acc: 83.73%\n",
            "\tVal. Loss: 0.470 | Val. Acc: 75.91%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.324 | Train Acc: 87.50%\n",
            "\tVal. Loss: 0.444 | Val. Acc: 79.00%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.265 | Train Acc: 90.96%\n",
            "\tVal. Loss: 0.432 | Val. Acc: 80.00%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.221 | Train Acc: 92.83%\n",
            "\tVal. Loss: 0.436 | Val. Acc: 79.82%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.184 | Train Acc: 94.25%\n",
            "\tVal. Loss: 0.427 | Val. Acc: 81.27%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.161 | Train Acc: 95.06%\n",
            "\tVal. Loss: 0.445 | Val. Acc: 81.00%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.140 | Train Acc: 95.58%\n",
            "\tVal. Loss: 0.455 | Val. Acc: 80.64%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.121 | Train Acc: 95.90%\n",
            "\tVal. Loss: 0.484 | Val. Acc: 79.82%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with HIDDEN_DIM=128, N_LAYERS=2, DROPOUT=0.5\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.600 | Train Acc: 67.58%\n",
            "\tVal. Loss: 0.552 | Val. Acc: 72.64%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.477 | Train Acc: 78.63%\n",
            "\tVal. Loss: 0.487 | Val. Acc: 76.18%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.393 | Train Acc: 83.29%\n",
            "\tVal. Loss: 0.451 | Val. Acc: 76.91%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.327 | Train Acc: 87.04%\n",
            "\tVal. Loss: 0.438 | Val. Acc: 78.64%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.268 | Train Acc: 90.15%\n",
            "\tVal. Loss: 0.426 | Val. Acc: 79.64%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.227 | Train Acc: 92.23%\n",
            "\tVal. Loss: 0.430 | Val. Acc: 79.91%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.191 | Train Acc: 93.77%\n",
            "\tVal. Loss: 0.430 | Val. Acc: 80.00%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.162 | Train Acc: 94.79%\n",
            "\tVal. Loss: 0.444 | Val. Acc: 79.55%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.137 | Train Acc: 95.79%\n",
            "\tVal. Loss: 0.443 | Val. Acc: 80.36%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.122 | Train Acc: 95.79%\n",
            "\tVal. Loss: 0.450 | Val. Acc: 80.27%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with HIDDEN_DIM=128, N_LAYERS=3, DROPOUT=0.3\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.600 | Train Acc: 67.69%\n",
            "\tVal. Loss: 0.545 | Val. Acc: 72.64%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.475 | Train Acc: 78.50%\n",
            "\tVal. Loss: 0.493 | Val. Acc: 75.00%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.395 | Train Acc: 83.85%\n",
            "\tVal. Loss: 0.466 | Val. Acc: 76.09%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.324 | Train Acc: 87.21%\n",
            "\tVal. Loss: 0.448 | Val. Acc: 78.09%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.273 | Train Acc: 89.87%\n",
            "\tVal. Loss: 0.447 | Val. Acc: 77.27%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.227 | Train Acc: 92.54%\n",
            "\tVal. Loss: 0.437 | Val. Acc: 79.09%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.189 | Train Acc: 94.17%\n",
            "\tVal. Loss: 0.437 | Val. Acc: 79.55%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.162 | Train Acc: 94.90%\n",
            "\tVal. Loss: 0.441 | Val. Acc: 80.64%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.140 | Train Acc: 95.65%\n",
            "\tVal. Loss: 0.452 | Val. Acc: 80.00%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.125 | Train Acc: 95.81%\n",
            "\tVal. Loss: 0.461 | Val. Acc: 79.45%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with HIDDEN_DIM=128, N_LAYERS=3, DROPOUT=0.5\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.593 | Train Acc: 68.38%\n",
            "\tVal. Loss: 0.544 | Val. Acc: 72.36%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.472 | Train Acc: 78.44%\n",
            "\tVal. Loss: 0.506 | Val. Acc: 74.36%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.391 | Train Acc: 83.50%\n",
            "\tVal. Loss: 0.462 | Val. Acc: 76.64%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.327 | Train Acc: 87.19%\n",
            "\tVal. Loss: 0.450 | Val. Acc: 78.18%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.272 | Train Acc: 90.12%\n",
            "\tVal. Loss: 0.443 | Val. Acc: 78.00%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.229 | Train Acc: 92.12%\n",
            "\tVal. Loss: 0.440 | Val. Acc: 79.36%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.187 | Train Acc: 94.00%\n",
            "\tVal. Loss: 0.425 | Val. Acc: 80.73%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.159 | Train Acc: 94.98%\n",
            "\tVal. Loss: 0.434 | Val. Acc: 80.18%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.138 | Train Acc: 95.54%\n",
            "\tVal. Loss: 0.433 | Val. Acc: 80.64%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.125 | Train Acc: 95.69%\n",
            "\tVal. Loss: 0.457 | Val. Acc: 80.55%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with HIDDEN_DIM=256, N_LAYERS=2, DROPOUT=0.3\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.584 | Train Acc: 69.60%\n",
            "\tVal. Loss: 0.530 | Val. Acc: 73.18%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.448 | Train Acc: 79.90%\n",
            "\tVal. Loss: 0.511 | Val. Acc: 74.64%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.365 | Train Acc: 84.92%\n",
            "\tVal. Loss: 0.463 | Val. Acc: 77.09%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.296 | Train Acc: 88.37%\n",
            "\tVal. Loss: 0.457 | Val. Acc: 77.18%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.236 | Train Acc: 91.94%\n",
            "\tVal. Loss: 0.441 | Val. Acc: 78.55%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.191 | Train Acc: 93.46%\n",
            "\tVal. Loss: 0.470 | Val. Acc: 79.36%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.159 | Train Acc: 94.52%\n",
            "\tVal. Loss: 0.485 | Val. Acc: 80.55%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.136 | Train Acc: 95.56%\n",
            "\tVal. Loss: 0.490 | Val. Acc: 80.27%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.117 | Train Acc: 96.15%\n",
            "\tVal. Loss: 0.498 | Val. Acc: 79.82%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.114 | Train Acc: 95.81%\n",
            "\tVal. Loss: 0.491 | Val. Acc: 80.45%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with HIDDEN_DIM=256, N_LAYERS=2, DROPOUT=0.5\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.597 | Train Acc: 68.04%\n",
            "\tVal. Loss: 0.533 | Val. Acc: 72.64%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.463 | Train Acc: 78.90%\n",
            "\tVal. Loss: 0.481 | Val. Acc: 75.09%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.371 | Train Acc: 84.85%\n",
            "\tVal. Loss: 0.449 | Val. Acc: 76.73%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.299 | Train Acc: 89.13%\n",
            "\tVal. Loss: 0.439 | Val. Acc: 78.91%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.240 | Train Acc: 91.94%\n",
            "\tVal. Loss: 0.439 | Val. Acc: 78.64%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.201 | Train Acc: 93.40%\n",
            "\tVal. Loss: 0.429 | Val. Acc: 80.09%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.164 | Train Acc: 94.62%\n",
            "\tVal. Loss: 0.436 | Val. Acc: 80.27%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.137 | Train Acc: 95.56%\n",
            "\tVal. Loss: 0.443 | Val. Acc: 80.45%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.123 | Train Acc: 95.77%\n",
            "\tVal. Loss: 0.454 | Val. Acc: 81.00%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.105 | Train Acc: 96.29%\n",
            "\tVal. Loss: 0.481 | Val. Acc: 80.45%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with HIDDEN_DIM=256, N_LAYERS=3, DROPOUT=0.3\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.582 | Train Acc: 69.71%\n",
            "\tVal. Loss: 0.530 | Val. Acc: 73.36%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.451 | Train Acc: 80.35%\n",
            "\tVal. Loss: 0.500 | Val. Acc: 74.91%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.358 | Train Acc: 85.62%\n",
            "\tVal. Loss: 0.468 | Val. Acc: 78.00%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.290 | Train Acc: 89.21%\n",
            "\tVal. Loss: 0.451 | Val. Acc: 77.73%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.236 | Train Acc: 91.62%\n",
            "\tVal. Loss: 0.447 | Val. Acc: 79.55%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.189 | Train Acc: 93.77%\n",
            "\tVal. Loss: 0.459 | Val. Acc: 79.82%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.156 | Train Acc: 94.73%\n",
            "\tVal. Loss: 0.472 | Val. Acc: 80.18%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.130 | Train Acc: 95.71%\n",
            "\tVal. Loss: 0.505 | Val. Acc: 79.82%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.116 | Train Acc: 95.85%\n",
            "\tVal. Loss: 0.519 | Val. Acc: 78.45%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.106 | Train Acc: 96.12%\n",
            "\tVal. Loss: 0.521 | Val. Acc: 80.00%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training with HIDDEN_DIM=256, N_LAYERS=3, DROPOUT=0.5\n",
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.591 | Train Acc: 68.52%\n",
            "\tVal. Loss: 0.551 | Val. Acc: 71.18%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.452 | Train Acc: 79.83%\n",
            "\tVal. Loss: 0.494 | Val. Acc: 76.27%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.362 | Train Acc: 85.48%\n",
            "\tVal. Loss: 0.494 | Val. Acc: 75.73%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.291 | Train Acc: 89.19%\n",
            "\tVal. Loss: 0.469 | Val. Acc: 77.64%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.231 | Train Acc: 92.35%\n",
            "\tVal. Loss: 0.456 | Val. Acc: 79.36%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.182 | Train Acc: 94.33%\n",
            "\tVal. Loss: 0.460 | Val. Acc: 79.45%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.153 | Train Acc: 94.88%\n",
            "\tVal. Loss: 0.480 | Val. Acc: 79.64%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.134 | Train Acc: 95.25%\n",
            "\tVal. Loss: 0.488 | Val. Acc: 79.73%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.115 | Train Acc: 96.13%\n",
            "\tVal. Loss: 0.525 | Val. Acc: 79.36%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.109 | Train Acc: 95.96%\n",
            "\tVal. Loss: 0.568 | Val. Acc: 80.00%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "k6SEJ1ro5uGA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "1WHJ0IsU5uJi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Final CNN model\n",
        "\n",
        "- hidden-dim = 128\n",
        "- n-layers = 2\n",
        "- dropout = 0.5\n",
        "- optim = Adam\n",
        "- loss Function = BCELogistsloss()\n",
        "- learning-rate = 0.001"
      ],
      "metadata": {
        "id": "6QFajEGCvtwG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "INPUT_DIM = len(vocab)\n",
        "EMBEDDING_DIM = 100\n",
        "HIDDEN_DIM = 128\n",
        "N_LAYERS = 2\n",
        "BIDIRECTIONAL = True\n",
        "DROPOUT = 0.5\n",
        "PAD_IDX = vocab[\"<pad>\"]\n",
        "\n",
        "\n",
        "model = CNN(INPUT_DIM,\n",
        "            EMBEDDING_DIM,\n",
        "            HIDDEN_DIM,\n",
        "            N_LAYERS,\n",
        "            BIDIRECTIONAL,\n",
        "            DROPOUT,\n",
        "            PAD_IDX)\n",
        "# model.embedding.weight.data.copy_(word_embedding.vectors)\n",
        "# model.embedding.weight.data[UNK_IDX] = torch.zeros(EMBEDDING_DIM)\n",
        "# model.embedding.weight.data[PAD_IDX] = torch.zeros(EMBEDDING_DIM)"
      ],
      "metadata": {
        "id": "eblwEyA85tCS"
      },
      "execution_count": 281,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.to(device)"
      ],
      "metadata": {
        "id": "K5wOi00jlvug",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9fa026b1-5479-4087-b72d-2cf233b53aac"
      },
      "execution_count": 282,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "CNN(\n",
              "  (embedding): Embedding(6252, 100, padding_idx=0)\n",
              "  (conv): Conv1d(100, 128, kernel_size=(3,), stride=(1,))\n",
              "  (fc): Linear(in_features=128, out_features=1, bias=True)\n",
              "  (dropout): Dropout(p=0.5, inplace=False)\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 282
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Khởi tạo optimizer và hàm loss\n",
        "optimizer = optim.Adam(model.parameters(), lr = 0.001)\n",
        "criterion = nn.BCEWithLogitsLoss().to(device)"
      ],
      "metadata": {
        "id": "8mAD8RPplvxA"
      },
      "execution_count": 283,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_losses = []\n",
        "train_accs = []\n",
        "val_losses = []\n",
        "val_accs = []\n",
        "best_valid_loss = float(\"inf\")\n",
        "\n",
        "for epoch in range(15):\n",
        "  start_time = time.time()\n",
        "\n",
        "  train_loss, train_acc = train(model, train_dataloader, optimizer, criterion, device)\n",
        "  valid_loss, valid_acc = evaluate(model, valid_dataloader, criterion, device)\n",
        "\n",
        "  train_losses.append(train_loss)\n",
        "  train_accs.append(train_acc)\n",
        "  val_losses.append(valid_loss)\n",
        "  val_accs.append(valid_acc)\n",
        "\n",
        "  end_time = time.time()\n",
        "\n",
        "  epoch_mins, epoch_secs = epoch_time(start_time, end_time)\n",
        "\n",
        "  if valid_loss < best_valid_loss:\n",
        "      best_valid_loss = valid_loss\n",
        "      torch.save(model.state_dict(), \"Best_model_CNN.pt\")\n",
        "\n",
        "  print(f\"Epoch: {epoch+1:02} | Epoch Time: {epoch_mins}m {epoch_secs}s\")\n",
        "  print(f\"\\tTrain Loss: {train_loss:.3f} | Train Acc: {train_acc*100:.2f}%\")\n",
        "  print(f\"\\t Val. Loss: {valid_loss:.3f} |  Val. Acc: {valid_acc*100:.2f}%\")"
      ],
      "metadata": {
        "id": "ZD_hWbrjlvz_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "08c6bc29-b449-4c53-bc69-8f502a4b9fb6"
      },
      "execution_count": 284,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 01 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.596 | Train Acc: 67.85%\n",
            "\t Val. Loss: 0.545 |  Val. Acc: 71.91%\n",
            "Epoch: 02 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.475 | Train Acc: 77.90%\n",
            "\t Val. Loss: 0.507 |  Val. Acc: 74.36%\n",
            "Epoch: 03 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.394 | Train Acc: 83.50%\n",
            "\t Val. Loss: 0.480 |  Val. Acc: 75.82%\n",
            "Epoch: 04 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.331 | Train Acc: 86.67%\n",
            "\t Val. Loss: 0.459 |  Val. Acc: 77.45%\n",
            "Epoch: 05 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.274 | Train Acc: 90.12%\n",
            "\t Val. Loss: 0.453 |  Val. Acc: 78.91%\n",
            "Epoch: 06 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.229 | Train Acc: 92.35%\n",
            "\t Val. Loss: 0.440 |  Val. Acc: 79.73%\n",
            "Epoch: 07 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.191 | Train Acc: 93.96%\n",
            "\t Val. Loss: 0.471 |  Val. Acc: 79.00%\n",
            "Epoch: 08 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.166 | Train Acc: 94.85%\n",
            "\t Val. Loss: 0.457 |  Val. Acc: 79.09%\n",
            "Epoch: 09 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.143 | Train Acc: 95.10%\n",
            "\t Val. Loss: 0.459 |  Val. Acc: 79.64%\n",
            "Epoch: 10 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.127 | Train Acc: 95.75%\n",
            "\t Val. Loss: 0.476 |  Val. Acc: 79.45%\n",
            "Epoch: 11 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.119 | Train Acc: 95.92%\n",
            "\t Val. Loss: 0.491 |  Val. Acc: 79.36%\n",
            "Epoch: 12 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.105 | Train Acc: 96.08%\n",
            "\t Val. Loss: 0.489 |  Val. Acc: 80.09%\n",
            "Epoch: 13 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.103 | Train Acc: 96.10%\n",
            "\t Val. Loss: 0.542 |  Val. Acc: 79.73%\n",
            "Epoch: 14 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.093 | Train Acc: 96.33%\n",
            "\t Val. Loss: 0.519 |  Val. Acc: 80.18%\n",
            "Epoch: 15 | Epoch Time: 0m 0s\n",
            "\tTrain Loss: 0.087 | Train Acc: 96.48%\n",
            "\t Val. Loss: 0.530 |  Val. Acc: 80.00%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "ZuEOQGozlv25"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(model)"
      ],
      "metadata": {
        "id": "pM3pbSn55tWY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e50ef30d-400d-4b8e-bd5f-9bb6b3663a83"
      },
      "execution_count": 285,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CNN(\n",
            "  (embedding): Embedding(6252, 100, padding_idx=0)\n",
            "  (conv): Conv1d(100, 128, kernel_size=(3,), stride=(1,))\n",
            "  (fc): Linear(in_features=128, out_features=1, bias=True)\n",
            "  (dropout): Dropout(p=0.5, inplace=False)\n",
            ")\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "7JxqnEM6Rt9x"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LUyVw6Yw7eru"
      },
      "source": [
        "# 9. Test the model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 293,
      "metadata": {
        "id": "bQTUTTo28sGD"
      },
      "outputs": [],
      "source": [
        "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
        "\n",
        "from underthesea import word_tokenize\n",
        "\n",
        "def predict_sentiment(model, sentence, vocab, device):\n",
        "    model.eval()\n",
        "    # Tokenize câu văn bản\n",
        "    tokenized_sentence = [word.replace(\" \", \"_\") for word in word_tokenize(sentence)]\n",
        "\n",
        "    # Chuyển đổi câu văn bản thành tensor theo từ điển vocab\n",
        "    indexed = [vocab[word] for word in tokenized_sentence]\n",
        "    # indexed_padded = indexed[:3] + [0] * (3 - len(indexed))\n",
        "    length = [len(indexed)]\n",
        "    tensor = torch.LongTensor(indexed).unsqueeze(1).to(device)\n",
        "\n",
        "    # Truyền qua mạng CNN\n",
        "    with torch.no_grad():\n",
        "        prediction = torch.sigmoid(model(tensor, torch.LongTensor(length).to(device)))\n",
        "\n",
        "    return prediction.item()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 294,
      "metadata": {
        "id": "lKxSmMbO929G",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "51f42151-d4e1-4091-fd89-affd6bb43bb4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'negative': 0, 'positive': 1}"
            ]
          },
          "metadata": {},
          "execution_count": 294
        }
      ],
      "source": [
        "dataset.sentiment2id"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "uploaded = files.upload()"
      ],
      "metadata": {
        "id": "hSR30dMtNtCT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "outputId": "d455e93a-2a9c-4516-f1cc-4786bbade936"
      },
      "execution_count": 255,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-22cac328-8ceb-4fe7-9ca1-c7316a99a548\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-22cac328-8ceb-4fe7-9ca1-c7316a99a548\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving testDataSentiment.xlsx to testDataSentiment (4).xlsx\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_excel(\"testDataSentiment.xlsx\")\n",
        "df = df[df['vi_review'].apply(lambda x: len(x.split()) >= 4)]"
      ],
      "metadata": {
        "id": "AhBpNYPcNtFQ"
      },
      "execution_count": 302,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def pred(text):\n",
        "    # Thực hiện dự đoán sentiment cho câu text\n",
        "    prediction = predict_sentiment(model, text, vocab, device)\n",
        "    # Trả về nhãn \"positive\" nếu dự đoán lớn hơn hoặc bằng 0.5, ngược lại trả về \"negative\"\n",
        "    return \"positive\" if prediction >= 0.5 else \"negative\""
      ],
      "metadata": {
        "id": "LSj3X9Y9NtIe"
      },
      "execution_count": 299,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "ugDCns4P41Hh",
        "outputId": "ded81f73-0096-454a-ef3e-eb1e3cfd8d11"
      },
      "execution_count": 303,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    sentiment                                          vi_review\n",
              "0    negative                              xin vd chua cap đc kh\n",
              "1    positive  Bảo Ngọc chắc có mỗi mình Nhật Minh là tán ngư...\n",
              "2    negative                                     xem và im lặng\n",
              "3    positive  màn hình điện thoại bên dưói sáng cũng k kém g...\n",
              "4    negative      Khong cần sự giàu có . Chỉ muốn kh mắc nợ aii\n",
              "..        ...                                                ...\n",
              "253  negative                         kiểu kh hi vọng gì nhiều..\n",
              "254  negative  Tôi mệt khi tất cả tôi chịu đựng không một ai ...\n",
              "255  negative                                      Rồi là vui zữ\n",
              "256  positive                              @Gió nhưng ko bằng em\n",
              "257  positive               @Dieudiudang đu trend với mỡ nè haha\n",
              "\n",
              "[208 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a6dbc240-1c8d-48c8-a5c6-62d87f8e7233\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sentiment</th>\n",
              "      <th>vi_review</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>negative</td>\n",
              "      <td>xin vd chua cap đc kh</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>positive</td>\n",
              "      <td>Bảo Ngọc chắc có mỗi mình Nhật Minh là tán ngư...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>negative</td>\n",
              "      <td>xem và im lặng</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>positive</td>\n",
              "      <td>màn hình điện thoại bên dưói sáng cũng k kém g...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>negative</td>\n",
              "      <td>Khong cần sự giàu có . Chỉ muốn kh mắc nợ aii</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>253</th>\n",
              "      <td>negative</td>\n",
              "      <td>kiểu kh hi vọng gì nhiều..</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>254</th>\n",
              "      <td>negative</td>\n",
              "      <td>Tôi mệt khi tất cả tôi chịu đựng không một ai ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>255</th>\n",
              "      <td>negative</td>\n",
              "      <td>Rồi là vui zữ</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>256</th>\n",
              "      <td>positive</td>\n",
              "      <td>@Gió nhưng ko bằng em</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>257</th>\n",
              "      <td>positive</td>\n",
              "      <td>@Dieudiudang đu trend với mỡ nè haha</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>208 rows × 2 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a6dbc240-1c8d-48c8-a5c6-62d87f8e7233')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "    </button>\n",
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              "      display:flex;\n",
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              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
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              "        document.querySelector('#df-a6dbc240-1c8d-48c8-a5c6-62d87f8e7233 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
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              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
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              "\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
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              "    display: none;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d89792f2-35d3-4cc0-bd45-81f0b1047437 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_0fe8efb2-136d-48da-a8e9-ef328b88a91b\">\n",
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              "      .colab-df-generate {\n",
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              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
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              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
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              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
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              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
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              "        document.querySelector('#id_0fe8efb2-136d-48da-a8e9-ef328b88a91b button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 208,\n  \"fields\": [\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"positive\",\n          \"negative\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"vi_review\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 207,\n        \"samples\": [\n          \"b\\u1ed9 \\u0111\\u1ed3 mua \\u1edf \\u0111\\u00e2u v\\u1eady\",\n          \"happy birthday color mini  partying-face \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 303
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"pred\"] = df[\"vi_review\"].apply(pred)"
      ],
      "metadata": {
        "id": "2nPpsDb6NtL3"
      },
      "execution_count": 304,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "WirTaZdZOwb_",
        "outputId": "bc96f391-e938-4590-b1df-aab93a39469b"
      },
      "execution_count": 305,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    sentiment                                          vi_review      pred\n",
              "0    negative                              xin vd chua cap đc kh  positive\n",
              "1    positive  Bảo Ngọc chắc có mỗi mình Nhật Minh là tán ngư...  negative\n",
              "2    negative                                     xem và im lặng  positive\n",
              "3    positive  màn hình điện thoại bên dưói sáng cũng k kém g...  negative\n",
              "4    negative      Khong cần sự giàu có . Chỉ muốn kh mắc nợ aii  negative\n",
              "..        ...                                                ...       ...\n",
              "253  negative                         kiểu kh hi vọng gì nhiều..  negative\n",
              "254  negative  Tôi mệt khi tất cả tôi chịu đựng không một ai ...  negative\n",
              "255  negative                                      Rồi là vui zữ  positive\n",
              "256  positive                              @Gió nhưng ko bằng em  positive\n",
              "257  positive               @Dieudiudang đu trend với mỡ nè haha  positive\n",
              "\n",
              "[208 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-75fcb7f3-c6af-4186-8eb6-774e3f957bea\" class=\"colab-df-container\">\n",
              "    <div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sentiment</th>\n",
              "      <th>vi_review</th>\n",
              "      <th>pred</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>negative</td>\n",
              "      <td>xin vd chua cap đc kh</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>positive</td>\n",
              "      <td>Bảo Ngọc chắc có mỗi mình Nhật Minh là tán ngư...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>negative</td>\n",
              "      <td>xem và im lặng</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>positive</td>\n",
              "      <td>màn hình điện thoại bên dưói sáng cũng k kém g...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>negative</td>\n",
              "      <td>Khong cần sự giàu có . Chỉ muốn kh mắc nợ aii</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>253</th>\n",
              "      <td>negative</td>\n",
              "      <td>kiểu kh hi vọng gì nhiều..</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>254</th>\n",
              "      <td>negative</td>\n",
              "      <td>Tôi mệt khi tất cả tôi chịu đựng không một ai ...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>255</th>\n",
              "      <td>negative</td>\n",
              "      <td>Rồi là vui zữ</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>256</th>\n",
              "      <td>positive</td>\n",
              "      <td>@Gió nhưng ko bằng em</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>257</th>\n",
              "      <td>positive</td>\n",
              "      <td>@Dieudiudang đu trend với mỡ nè haha</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>208 rows × 3 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-75fcb7f3-c6af-4186-8eb6-774e3f957bea')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-75fcb7f3-c6af-4186-8eb6-774e3f957bea button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-75fcb7f3-c6af-4186-8eb6-774e3f957bea');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 208,\n  \"fields\": [\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"positive\",\n          \"negative\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"vi_review\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 207,\n        \"samples\": [\n          \"b\\u1ed9 \\u0111\\u1ed3 mua \\u1edf \\u0111\\u00e2u v\\u1eady\",\n          \"happy birthday color mini  partying-face \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"pred\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"negative\",\n          \"positive\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 305
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "mIqPMUa2OwfV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pre = df[df[\"sentiment\"] != df[\"pred\"]]"
      ],
      "metadata": {
        "id": "7HhvXCgAPmcY"
      },
      "execution_count": 306,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pre"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "cixjxE9LQKBl",
        "outputId": "ca49cb3b-8cb9-43b7-b3d7-c3c2b40022b8"
      },
      "execution_count": 307,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    sentiment                                          vi_review      pred\n",
              "0    negative                              xin vd chua cap đc kh  positive\n",
              "1    positive  Bảo Ngọc chắc có mỗi mình Nhật Minh là tán ngư...  negative\n",
              "2    negative                                     xem và im lặng  positive\n",
              "3    positive  màn hình điện thoại bên dưói sáng cũng k kém g...  negative\n",
              "16   positive  Alhamdulillah..selamat hari jadi yg bln dan ha...  negative\n",
              "19   positive  Cố lên ta ơi cuộc đời cho ta ngàn lý do để khó...  negative\n",
              "30   positive    tuyệt quá à, nghe mà có thêm động lực vững bước  negative\n",
              "47   negative                             xin cap nhé thumbs-up   positive\n",
              "53   negative       T nhận chửi lộn dùm nha, nghe ghét cđ này qá  positive\n",
              "65   positive  Võ Lê Đông Thạnh xin tên cty bạn ơi  rolling-o...  negative\n",
              "67   negative                            Em đã hi vọng rất nhiều  positive\n",
              "69   negative  Phải gom góp bao nhiêu nỗi thất vọng mới có th...  positive\n",
              "84   positive  buôn bỏ những thứ không tốt.thu nhặt, kiến thứ...  negative\n",
              "85   negative                                     T Nghe mà nhột  positive\n",
              "97   negative  Ngta thường bảo con trai yêu bằng con mắt con ...  positive\n",
              "98   negative                              Tên bài hát là gì vậy  positive\n",
              "99   negative  @hồngngọc_2011 tulip  vd này nè lưu giùm r gửi...  positive\n",
              "107  negative     Ngoc Phuong giúp bạn này đi sinh viên nhân văn  positive\n",
              "109  negative              @Hiếu Phạm dạo này suy nghĩ nhiều quá  positive\n",
              "117  negative          cr mình thấy đổi thật rồi  pleading-face   positive\n",
              "128  negative  cho đi gõ lịch thấy bà hết pleading-face  plea...  positive\n",
              "134  positive                    Đọc thực sự tâm hồn sáng hơn ấy  negative\n",
              "141  negative  ui cái thằng chồng  grinning-face-with-sweat  ...  positive\n",
              "144  negative  hiện tượng này gây nên rối loạn lo âu, dẫn đến...  positive\n",
              "145  negative  nhìn mà sót , cố gắng lên bn sad-but-relieved-...  positive\n",
              "148  positive  Mẹ Salim và Pam xinh quá  smiling-face-with-he...  negative\n",
              "151  positive  Nhìn pam mà chỉ bt ước đc gặp để véo má thuuu ...  negative\n",
              "162  positive  Nhưng mà tóm lại là cái app nó để làm cái gì? ...  negative\n",
              "163  negative                                  béo là người hưak  positive\n",
              "182  negative                              @Mỹ ngân 🥀 cho tao ik  positive\n",
              "185  negative                       @Ánh Huyền💐 ciểu như này nek  positive\n",
              "195  negative         Anh Thuong em mà smiling-face-with-hearts   positive\n",
              "199  negative                    thật chạnh lòng  relieved-face   positive\n",
              "210  positive                 Mỹ Huyền chuyên gia cho lời khuyên  negative\n",
              "219  positive  tôi trúng số độc đắc 20 tỷ\\ntôi đã trả hết nợ....  negative\n",
              "221  negative  ai biết cách chữa sán giun lươn không ạ mn giú...  positive\n",
              "225  positive                             cho mình xin video nha  negative\n",
              "228  negative   loudly-crying-face  loudly-crying-face  loudl...  positive\n",
              "238  positive  Cho em một cốc trà đào.\\nTiện cho em hỏi lối v...  negative\n",
              "241  negative                cười nhạt một cái rồi mai tính tiếp  positive\n",
              "250  negative                                     Inter nay gà v  positive\n",
              "255  negative                                      Rồi là vui zữ  positive"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sentiment</th>\n",
              "      <th>vi_review</th>\n",
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              "      <td>positive</td>\n",
              "      <td>Bảo Ngọc chắc có mỗi mình Nhật Minh là tán ngư...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>negative</td>\n",
              "      <td>xem và im lặng</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>positive</td>\n",
              "      <td>màn hình điện thoại bên dưói sáng cũng k kém g...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>positive</td>\n",
              "      <td>Alhamdulillah..selamat hari jadi yg bln dan ha...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>positive</td>\n",
              "      <td>Cố lên ta ơi cuộc đời cho ta ngàn lý do để khó...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>positive</td>\n",
              "      <td>tuyệt quá à, nghe mà có thêm động lực vững bước</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>negative</td>\n",
              "      <td>xin cap nhé thumbs-up</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>negative</td>\n",
              "      <td>T nhận chửi lộn dùm nha, nghe ghét cđ này qá</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>65</th>\n",
              "      <td>positive</td>\n",
              "      <td>Võ Lê Đông Thạnh xin tên cty bạn ơi  rolling-o...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67</th>\n",
              "      <td>negative</td>\n",
              "      <td>Em đã hi vọng rất nhiều</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>69</th>\n",
              "      <td>negative</td>\n",
              "      <td>Phải gom góp bao nhiêu nỗi thất vọng mới có th...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>84</th>\n",
              "      <td>positive</td>\n",
              "      <td>buôn bỏ những thứ không tốt.thu nhặt, kiến thứ...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>85</th>\n",
              "      <td>negative</td>\n",
              "      <td>T Nghe mà nhột</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>negative</td>\n",
              "      <td>Ngta thường bảo con trai yêu bằng con mắt con ...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>negative</td>\n",
              "      <td>Tên bài hát là gì vậy</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>negative</td>\n",
              "      <td>@hồngngọc_2011 tulip  vd này nè lưu giùm r gửi...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>negative</td>\n",
              "      <td>Ngoc Phuong giúp bạn này đi sinh viên nhân văn</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>negative</td>\n",
              "      <td>@Hiếu Phạm dạo này suy nghĩ nhiều quá</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>negative</td>\n",
              "      <td>cr mình thấy đổi thật rồi  pleading-face</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>negative</td>\n",
              "      <td>cho đi gõ lịch thấy bà hết pleading-face  plea...</td>\n",
              "      <td>positive</td>\n",
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              "      <th>134</th>\n",
              "      <td>positive</td>\n",
              "      <td>Đọc thực sự tâm hồn sáng hơn ấy</td>\n",
              "      <td>negative</td>\n",
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              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>negative</td>\n",
              "      <td>ui cái thằng chồng  grinning-face-with-sweat  ...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144</th>\n",
              "      <td>negative</td>\n",
              "      <td>hiện tượng này gây nên rối loạn lo âu, dẫn đến...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>negative</td>\n",
              "      <td>nhìn mà sót , cố gắng lên bn sad-but-relieved-...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>positive</td>\n",
              "      <td>Mẹ Salim và Pam xinh quá  smiling-face-with-he...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>151</th>\n",
              "      <td>positive</td>\n",
              "      <td>Nhìn pam mà chỉ bt ước đc gặp để véo má thuuu ...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>positive</td>\n",
              "      <td>Nhưng mà tóm lại là cái app nó để làm cái gì? ...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>163</th>\n",
              "      <td>negative</td>\n",
              "      <td>béo là người hưak</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>182</th>\n",
              "      <td>negative</td>\n",
              "      <td>@Mỹ ngân 🥀 cho tao ik</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>185</th>\n",
              "      <td>negative</td>\n",
              "      <td>@Ánh Huyền💐 ciểu như này nek</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>negative</td>\n",
              "      <td>Anh Thuong em mà smiling-face-with-hearts</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>negative</td>\n",
              "      <td>thật chạnh lòng  relieved-face</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>positive</td>\n",
              "      <td>Mỹ Huyền chuyên gia cho lời khuyên</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>219</th>\n",
              "      <td>positive</td>\n",
              "      <td>tôi trúng số độc đắc 20 tỷ\\ntôi đã trả hết nợ....</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>221</th>\n",
              "      <td>negative</td>\n",
              "      <td>ai biết cách chữa sán giun lươn không ạ mn giú...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>225</th>\n",
              "      <td>positive</td>\n",
              "      <td>cho mình xin video nha</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>228</th>\n",
              "      <td>negative</td>\n",
              "      <td>loudly-crying-face  loudly-crying-face  loudl...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>238</th>\n",
              "      <td>positive</td>\n",
              "      <td>Cho em một cốc trà đào.\\nTiện cho em hỏi lối v...</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>negative</td>\n",
              "      <td>cười nhạt một cái rồi mai tính tiếp</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250</th>\n",
              "      <td>negative</td>\n",
              "      <td>Inter nay gà v</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>255</th>\n",
              "      <td>negative</td>\n",
              "      <td>Rồi là vui zữ</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "        document.querySelector('#df-61f6ff47-14d9-4c88-9077-103473f1ec25 button.colab-df-convert');\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-63b82f90-0b0c-4952-9d19-82f2a8192b24 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_4a4954db-72ca-40cb-934e-6ceb9dbb29dc\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('pre')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_4a4954db-72ca-40cb-934e-6ceb9dbb29dc button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('pre');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "pre",
              "summary": "{\n  \"name\": \"pre\",\n  \"rows\": 42,\n  \"fields\": [\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"positive\",\n          \"negative\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"vi_review\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 42,\n        \"samples\": [\n          \"M\\u1eb9 Salim v\\u00e0 Pam xinh qu\\u00e1  smiling-face-with-hearts \",\n          \"T Nghe m\\u00e0 nh\\u1ed9t\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"pred\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"negative\",\n          \"positive\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 307
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"Acc of test dataset is {round(100 -(len(pre) / len(df))*100,2)}%\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t3M_aPLJPmfO",
        "outputId": "ea6a6397-8cf6-4360-c62d-ac38ff558816"
      },
      "execution_count": 308,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Acc of test dataset is 79.81%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "2ABrqMNlPmiM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "_t1RsNxrPmlf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install gradio"
      ],
      "metadata": {
        "id": "I44686ez1s-z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a3e4a7dd-604e-4d32-ca3d-b07d8c43fb35"
      },
      "execution_count": 263,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting gradio\n",
            "  Downloading gradio-4.24.0-py3-none-any.whl (17.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m17.1/17.1 MB\u001b[0m \u001b[31m47.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting aiofiles<24.0,>=22.0 (from gradio)\n",
            "  Downloading aiofiles-23.2.1-py3-none-any.whl (15 kB)\n",
            "Requirement already satisfied: altair<6.0,>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (4.2.2)\n",
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            "  Downloading fastapi-0.110.0-py3-none-any.whl (92 kB)\n",
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            "\u001b[?25hCollecting ffmpy (from gradio)\n",
            "  Downloading ffmpy-0.3.2.tar.gz (5.5 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "Building wheels for collected packages: ffmpy\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.2-py3-none-any.whl size=5584 sha256=4c46d6e44edbeed78d41f6bfc4835caaaca560c5933ca5980a1705e66c706350\n",
            "  Stored in directory: /root/.cache/pip/wheels/bd/65/9a/671fc6dcde07d4418df0c592f8df512b26d7a0029c2a23dd81\n",
            "Successfully built ffmpy\n",
            "Installing collected packages: pydub, ffmpy, websockets, tomlkit, shellingham, semantic-version, ruff, python-multipart, orjson, h11, colorama, aiofiles, uvicorn, starlette, httpcore, httpx, fastapi, gradio-client, gradio\n",
            "Successfully installed aiofiles-23.2.1 colorama-0.4.6 fastapi-0.110.0 ffmpy-0.3.2 gradio-4.24.0 gradio-client-0.14.0 h11-0.14.0 httpcore-1.0.5 httpx-0.27.0 orjson-3.10.0 pydub-0.25.1 python-multipart-0.0.9 ruff-0.3.4 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.36.3 tomlkit-0.12.0 uvicorn-0.29.0 websockets-11.0.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import gradio as gr"
      ],
      "metadata": {
        "id": "jhQZB3pr1Opc"
      },
      "execution_count": 264,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def predict(text):\n",
        "  pre = predict_sentiment(model, text, vocab, device)\n",
        "  return {'Positive':(pre),\n",
        "          \"Negative\": (1- (pre))}\n"
      ],
      "metadata": {
        "id": "EcdPLHzY3ZHA"
      },
      "execution_count": 265,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "demo = gr.Interface(\n",
        "    fn=predict,\n",
        "    inputs=gr.components.Textbox(label='Input query'),\n",
        "    outputs=gr.components.Label(label='Predictions'),\n",
        "    allow_flagging='never'\n",
        ")\n",
        "\n",
        "demo.launch(share=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        },
        "id": "Ce5qrrQN1OsG",
        "outputId": "032ddcdd-dfba-493c-d49f-83405dace1cb"
      },
      "execution_count": 266,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://36601b2587fce5aaf7.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div><iframe src=\"https://36601b2587fce5aaf7.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 266
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "J2ZLFakY3-9K"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "filtered_df = df[df['sentiment']!=df['prediction']]"
      ],
      "metadata": {
        "id": "Ovy9pPeGBBzS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 477
        },
        "outputId": "ca9ff281-6ed7-4826-8607-f7fd554ba5f1"
      },
      "execution_count": 267,
      "outputs": [
        {
          "output_type": "error",
          "ename": "KeyError",
          "evalue": "'prediction'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   3801\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3802\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3803\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 'prediction'",
            "\nThe above exception was the direct cause of the following exception:\n",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-267-07fd23b60475>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfiltered_df\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'sentiment'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m!=\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'prediction'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3805\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3806\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3807\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3808\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3809\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   3802\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3803\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3804\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3805\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3806\u001b[0m                 \u001b[0;31m# If we have a listlike key, _check_indexing_error will raise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 'prediction'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "filtered_df.to_excel(\"WrongPred.xlsx\")"
      ],
      "metadata": {
        "id": "S6HE-Ri_BB1g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(filtered_df)"
      ],
      "metadata": {
        "id": "X-MTq8XFBB5C"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "uHzp93EDCgqc"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}