{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Transformer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\">\n",
    "\n",
    "This tutorial is available as an IPython notebook at [Malaya/example/transformer](https://github.com/huseinzol05/Malaya/tree/master/example/transformer).\n",
    "    \n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Malaya provided basic interface for Pretrained Transformer encoder models, specific to Malay, local social media slang and Manglish language, we called it Transformer-Bahasa. Below are the list of dataset we pretrained,\n",
    "\n",
    "Standard Bahasa dataset, \n",
    "\n",
    "1. [Malay-dataset/dumping](https://github.com/huseinzol05/Malay-Dataset/tree/master/dumping).\n",
    "2. [Malay-dataset/pure-text](https://github.com/huseinzol05/Malay-Dataset/tree/master/pure-text).\n",
    "\n",
    "Bahasa social media,\n",
    "\n",
    "1. [Malay-dataset/dumping/instagram](https://github.com/huseinzol05/Malay-Dataset/tree/master/dumping/instagram).\n",
    "2. [Malay-dataset/dumping/twitter](https://github.com/huseinzol05/Malay-Dataset/tree/master/dumping/twitter).\n",
    "\n",
    "Singlish / Manglish,\n",
    "\n",
    "1. [Malay-dataset/dumping/singlish](https://github.com/huseinzol05/Malay-Dataset/tree/master/dumping/singlish-text).\n",
    "2. [Malay-dataset/dumping/singapore-news](https://github.com/huseinzol05/Malay-Dataset/tree/master/dumping/singapore-news).\n",
    "\n",
    "**This interface not able us to use it to do custom training**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to download pretrained model for Transformer-Bahasa and use it for custom transfer-learning, you can download it here, https://github.com/huseinzol05/Malaya/tree/master/pretrained-model/, some notebooks to help you get started.\n",
    "\n",
    "Or you can simply use [hugging-face transformers](https://huggingface.co/models?filter=ms) to try transformer models from Malaya, simply check available models from here, https://huggingface.co/models?filter=ms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import Image, display\n",
    "\n",
    "display(Image('huggingface.png', width=500))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.88 s, sys: 641 ms, total: 5.52 s\n",
      "Wall time: 4.5 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "import malaya"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### list Transformer-Bahasa available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>Size (MB)</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bert</th>\n",
       "      <td>425.6</td>\n",
       "      <td>Google BERT BASE parameters</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tiny-bert</th>\n",
       "      <td>57.4</td>\n",
       "      <td>Google BERT TINY parameters</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>albert</th>\n",
       "      <td>48.6</td>\n",
       "      <td>Google ALBERT BASE parameters</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tiny-albert</th>\n",
       "      <td>22.4</td>\n",
       "      <td>Google ALBERT TINY parameters</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xlnet</th>\n",
       "      <td>446.6</td>\n",
       "      <td>Google XLNET BASE parameters</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alxlnet</th>\n",
       "      <td>46.8</td>\n",
       "      <td>Malaya ALXLNET BASE parameters</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>electra</th>\n",
       "      <td>443</td>\n",
       "      <td>Google ELECTRA BASE parameters</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>small-electra</th>\n",
       "      <td>55</td>\n",
       "      <td>Google ELECTRA SMALL parameters</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Size (MB)                      Description\n",
       "bert              425.6      Google BERT BASE parameters\n",
       "tiny-bert          57.4      Google BERT TINY parameters\n",
       "albert             48.6    Google ALBERT BASE parameters\n",
       "tiny-albert        22.4    Google ALBERT TINY parameters\n",
       "xlnet             446.6     Google XLNET BASE parameters\n",
       "alxlnet            46.8   Malaya ALXLNET BASE parameters\n",
       "electra             443   Google ELECTRA BASE parameters\n",
       "small-electra        55  Google ELECTRA SMALL parameters"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "malaya.transformer.available_transformer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "strings = ['Kerajaan galakkan rakyat naik public transport tapi parking kat lrt ada 15. Reserved utk staff rapid je dah berpuluh. Park kereta tepi jalan kang kene saman dgn majlis perbandaran. Kereta pulak senang kene curi. Cctv pun tak ada. Naik grab dah 5-10 ringgit tiap hari. Gampang juga',\n",
    "           'Alaa Tun lek ahhh npe muka masam cmni kn agong kata usaha kerajaan terdahulu sejak selepas merdeka',\n",
    "           \"Orang ramai cakap nurse kerajaan garang. So i tell u this. Most of our local ppl will treat us as hamba abdi and they don't respect us as a nurse\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load XLNET-Bahasa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/xlnet.py:70: The name tf.gfile.Open is deprecated. Please use tf.io.gfile.GFile instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/__init__.py:81: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/xlnet.py:253: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/xlnet.py:253: The name tf.AUTO_REUSE is deprecated. Please use tf.compat.v1.AUTO_REUSE instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/modeling.py:686: The name tf.logging.info is deprecated. Please use tf.compat.v1.logging.info instead.\n",
      "\n",
      "INFO:tensorflow:memory input None\n",
      "INFO:tensorflow:Use float type <dtype: 'float32'>\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/modeling.py:693: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/modeling.py:797: dropout (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use keras.layers.dropout instead.\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow_core/python/layers/core.py:271: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `layer.__call__` method instead.\n",
      "WARNING:tensorflow:\n",
      "The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
      "For more information, please see:\n",
      "  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
      "  * https://github.com/tensorflow/addons\n",
      "  * https://github.com/tensorflow/io (for I/O related ops)\n",
      "If you depend on functionality not listed there, please file an issue.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/modeling.py:99: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use keras.layers.Dense instead.\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/__init__.py:94: The name tf.InteractiveSession is deprecated. Please use tf.compat.v1.InteractiveSession instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/__init__.py:95: The name tf.global_variables_initializer is deprecated. Please use tf.compat.v1.global_variables_initializer instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/__init__.py:96: The name tf.trainable_variables is deprecated. Please use tf.compat.v1.trainable_variables instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/__init__.py:100: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.\n",
      "\n",
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/malaya/transformers/xlnet/__init__.py:103: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n",
      "\n",
      "INFO:tensorflow:Restoring parameters from /Users/huseinzolkepli/Malaya/xlnet-model/base/xlnet-base/model.ckpt\n"
     ]
    }
   ],
   "source": [
    "xlnet = malaya.transformer.load(model = 'xlnet')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I have random sentences copied from Twitter, searched using `kerajaan` keyword."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Vectorization\n",
    "\n",
    "Change a string or batch of strings to latent space / vectors representation.\n",
    "\n",
    "```python\n",
    "def vectorize(self, strings: List[str]):\n",
    "\n",
    "    \"\"\"\n",
    "    Vectorize string inputs.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    strings : List[str]\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    result: np.array\n",
    "    \"\"\"\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 768)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v = xlnet.vectorize(strings)\n",
    "v.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Attention"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "def attention(self, strings: List[str], method: str = 'last', **kwargs):\n",
    "    \"\"\"\n",
    "    Get attention string inputs from bert attention.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    strings : List[str]\n",
    "    method : str, optional (default='last')\n",
    "        Attention layer supported. Allowed values:\n",
    "\n",
    "        * ``'last'`` - attention from last layer.\n",
    "        * ``'first'`` - attention from first layer.\n",
    "        * ``'mean'`` - average attentions from all layers.\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    result : List[List[Tuple[str, float]]]\n",
    "    \"\"\"\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can give list of strings or a string to get the attention, in this documentation, I just want to use a string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[('Alaa', 0.062061824),\n",
       "  ('Tun', 0.051056776),\n",
       "  ('lek', 0.13115405),\n",
       "  ('ahhh', 0.08195943),\n",
       "  ('npe', 0.06210695),\n",
       "  ('muka', 0.04706182),\n",
       "  ('masam', 0.058289353),\n",
       "  ('cmni', 0.026094284),\n",
       "  ('kn', 0.056146827),\n",
       "  ('agong', 0.033949938),\n",
       "  ('kata', 0.052644122),\n",
       "  ('usaha', 0.07063393),\n",
       "  ('kerajaan', 0.046773836),\n",
       "  ('terdahulu', 0.057166394),\n",
       "  ('sejak', 0.045712817),\n",
       "  ('selepas', 0.047048207),\n",
       "  ('merdeka', 0.07013944)]]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xlnet.attention([strings[1]], method = 'last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[('Alaa', 0.045956098),\n",
       "  ('Tun', 0.040094823),\n",
       "  ('lek', 0.0611072),\n",
       "  ('ahhh', 0.07029096),\n",
       "  ('npe', 0.048513662),\n",
       "  ('muka', 0.056670234),\n",
       "  ('masam', 0.04088071),\n",
       "  ('cmni', 0.08728454),\n",
       "  ('kn', 0.047778472),\n",
       "  ('agong', 0.081243224),\n",
       "  ('kata', 0.03866041),\n",
       "  ('usaha', 0.058326427),\n",
       "  ('kerajaan', 0.055446573),\n",
       "  ('terdahulu', 0.077162124),\n",
       "  ('sejak', 0.05951431),\n",
       "  ('selepas', 0.05385498),\n",
       "  ('merdeka', 0.07721528)]]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xlnet.attention([strings[1]], method = 'first')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[('Alaa', 0.06978634),\n",
       "  ('Tun', 0.0517442),\n",
       "  ('lek', 0.059642658),\n",
       "  ('ahhh', 0.055883657),\n",
       "  ('npe', 0.05339206),\n",
       "  ('muka', 0.06806306),\n",
       "  ('masam', 0.0489921),\n",
       "  ('cmni', 0.0698193),\n",
       "  ('kn', 0.057752036),\n",
       "  ('agong', 0.065566674),\n",
       "  ('kata', 0.059152905),\n",
       "  ('usaha', 0.063305095),\n",
       "  ('kerajaan', 0.050608452),\n",
       "  ('terdahulu', 0.05888331),\n",
       "  ('sejak', 0.057429556),\n",
       "  ('selepas', 0.042058233),\n",
       "  ('merdeka', 0.067920305)]]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xlnet.attention([strings[1]], method = 'mean')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualize Attention"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before using attention visualization, we need to load D3 into our jupyter notebook first. This visualization borrow from https://github.com/jessevig/bertviz .\n",
    "\n",
    "```python\n",
    "def visualize_attention(self, string: str):\n",
    "\n",
    "    \"\"\"\n",
    "    Visualize attention.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    string : str\n",
    "    \"\"\"\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "require.config({\n",
       "  paths: {\n",
       "      d3: '//cdnjs.cloudflare.com/ajax/libs/d3/3.4.8/d3.min',\n",
       "      jquery: '//ajax.googleapis.com/ajax/libs/jquery/2.0.0/jquery.min',\n",
       "  }\n",
       "});\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "require.config({\n",
    "  paths: {\n",
    "      d3: '//cdnjs.cloudflare.com/ajax/libs/d3/3.4.8/d3.min',\n",
    "      jquery: '//ajax.googleapis.com/ajax/libs/jquery/2.0.0/jquery.min',\n",
    "  }\n",
    "});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "          <span style=\"user-select:none\">\n",
       "            Layer: <select id=\"layer\"></select>\n",
       "          </span>\n",
       "          <div id='vis'></div>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "window.params = {\"attention\": {\"all\": {\"attn\": [[[[0.1508517563343048, 0.18098671734333038, 0.23584957420825958, 0.15355485677719116, 0.145206019282341, 0.05799558758735657, 0.026901736855506897, 0.032964687794446945, 0.015689149498939514], [0.8990172147750854, 0.09100620448589325, 0.00408910820260644, 0.0001899389608297497, 6.359920371323824e-05, 6.2013634305913e-05, 0.0002482223208062351, 0.003288511885330081, 0.002035270445048809], [0.20051594078540802, 0.46846988797187805, 0.2764476537704468, 0.026639852672815323, 0.0044734179973602295, 0.001753539894707501, 0.002262086607515812, 0.010953827761113644, 0.008483807556331158], [0.018590092658996582, 0.030009571462869644, 0.0739763155579567, 0.09789494425058365, 0.21980617940425873, 0.13438430428504944, 0.11604717373847961, 0.2459673136472702, 0.06332405656576157], [0.3478426933288574, 0.1260591745376587, 0.06657165288925171, 0.039296552538871765, 0.08041822910308838, 0.08056806772947311, 0.05723264068365097, 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0.025597158819437027, 0.9677168726921082]]]], \"left_text\": [\"\\u2581nak\", \"\\u2581makan\", \"\\u2581ayam\", \"\\u2581dgn\", \"\\u2581hu\", \"se\", \"in\", \"<sep>\", \"<cls>\"], \"right_text\": [\"\\u2581nak\", \"\\u2581makan\", \"\\u2581ayam\", \"\\u2581dgn\", \"\\u2581hu\", \"se\", \"in\", \"<sep>\", \"<cls>\"]}}, \"default_filter\": \"all\"}"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/**\n",
       " * @fileoverview Transformer Visualization D3 javascript code.\n",
       " *\n",
       " *\n",
       "\n",
       " *  Based on: https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/visualization/attention.js\n",
       " *\n",
       " * Change log:\n",
       " *\n",
       " * 12/19/18  Jesse Vig   Assorted cleanup. Changed orientation of attention matrices.\n",
       " */\n",
       "\n",
       "requirejs(['jquery', 'd3'], function($, d3) {\n",
       "\n",
       "const TEXT_SIZE = 15;\n",
       "const BOXWIDTH = TEXT_SIZE * 8;\n",
       "const BOXHEIGHT = TEXT_SIZE * 1.5;\n",
       "const WIDTH = 2000;\n",
       "const HEIGHT_PADDING = 100;\n",
       "const MATRIX_WIDTH = 150;\n",
       "const HEAD_COLORS = d3.scale.category10();\n",
       "const CHECKBOX_SIZE = 20;\n",
       "\n",
       "var params = window.params;\n",
       "var config = {};\n",
       "initialize();\n",
       "\n",
       "function lighten(color) {\n",
       "  var c = d3.hsl(color);\n",
       "  var increment = (1 - c.l) * 0.6;\n",
       "  c.l += increment;\n",
       "  c.s -= increment;\n",
       "  return c;\n",
       "}\n",
       "\n",
       "function transpose(mat) {\n",
       "  return mat[0].map(function(col, i) {\n",
       "    return mat.map(function(row) {\n",
       "      return row[i];\n",
       "    });\n",
       "  });\n",
       "}\n",
       "\n",
       "function zip(a, b) {\n",
       "  return a.map(function (e, i) {\n",
       "    return [e, b[i]];\n",
       "  });\n",
       "}\n",
       "\n",
       "function render() {\n",
       "\n",
       "  var attnData = config.attention[config.filter];\n",
       "  var leftText = attnData.left_text;\n",
       "  var rightText = attnData.right_text;\n",
       "  var attentionHeads = attnData.attn[config.layer];\n",
       "\n",
       "  $(\"#vis svg\").empty();\n",
       "  $(\"#vis\").empty();\n",
       "\n",
       "  var height = config.initialTextLength * BOXHEIGHT * 2 + HEIGHT_PADDING;\n",
       "  var svg = d3.select(\"#vis\")\n",
       "            .append('svg')\n",
       "            .attr(\"width\", WIDTH)\n",
       "            .attr(\"height\", height);\n",
       "\n",
       "  var attData = [];\n",
       "  for (var i=0; i < config.nHeads; i++) {\n",
       "    var att = attentionHeads[i];\n",
       "    var att_trans = transpose(att);\n",
       "    attData.push(zip(att_trans, att));\n",
       "  }\n",
       "\n",
       "  renderText(svg, leftText, true, attData, 0);\n",
       "  renderText(svg, rightText, false, attData, MATRIX_WIDTH + BOXWIDTH);\n",
       "\n",
       "  renderAttentionHighlights(svg, attData);\n",
       "\n",
       "  svg.append(\"g\").classed(\"attentionHeads\", true);\n",
       "\n",
       "  renderAttention(svg, attentionHeads);\n",
       "\n",
       "  drawCheckboxes(0, svg, attentionHeads);\n",
       "\n",
       "}\n",
       "\n",
       "function renderText(svg, text, isLeft, attData, leftPos) {\n",
       "  // attData: list of tuples (att, att_trans), one for each layer. att and att_trans are attention matrics for each layer.\n",
       "  //           att is of shape [nHeads, source_len, target_len)\n",
       "  var id = isLeft ? \"left\" : \"right\";\n",
       "  var textContainer = svg.append(\"svg:g\")\n",
       "                         .attr(\"id\", id);\n",
       "\n",
       "  textContainer.append(\"g\").classed(\"attentionBoxes\", true)\n",
       "               .selectAll(\"g\")\n",
       "               .data(attData)\n",
       "               .enter()\n",
       "               .append(\"g\")\n",
       "               .selectAll(\"rect\")\n",
       "               .data(function(d) {return d;})\n",
       "               .enter()\n",
       "               .append(\"rect\")\n",
       "               .attr(\"x\", function(d, i, j) {\n",
       "                 return leftPos + boxOffsets(j);\n",
       "               })\n",
       "               .attr(\"y\", function(d, i) {\n",
       "                 return (+1) * BOXHEIGHT;\n",
       "               })\n",
       "               .attr(\"width\", BOXWIDTH / activeHeads())\n",
       "               .attr(\"height\", function() { return BOXHEIGHT; })\n",
       "               .attr(\"fill\", function(d, i, j) {\n",
       "                  return HEAD_COLORS(j);\n",
       "                })\n",
       "               .style(\"opacity\", 0.0);\n",
       "\n",
       "  var tokenContainer = textContainer.append(\"g\").selectAll(\"g\")\n",
       "                                    .data(text)\n",
       "                                    .enter()\n",
       "                                    .append(\"g\");\n",
       "\n",
       "  tokenContainer.append(\"rect\")\n",
       "                .classed(\"background\", true)\n",
       "                .style(\"opacity\", 0.0)\n",
       "                .attr(\"fill\", \"lightgray\")\n",
       "                .attr(\"x\", leftPos)\n",
       "                .attr(\"y\", function(d, i) {\n",
       "                  return (i+1) * BOXHEIGHT;\n",
       "                })\n",
       "                .attr(\"width\", BOXWIDTH)\n",
       "                .attr(\"height\", BOXHEIGHT);\n",
       "\n",
       "  var textEl = tokenContainer.append(\"text\")\n",
       "                              .text(function(d) { return d; })\n",
       "                              .attr(\"font-size\", TEXT_SIZE + \"px\")\n",
       "                              .style(\"cursor\", \"default\")\n",
       "                              .style(\"-webkit-user-select\", \"none\")\n",
       "                              .attr(\"x\", leftPos)\n",
       "                              .attr(\"y\", function(d, i) {\n",
       "                                return (i+1) * BOXHEIGHT;\n",
       "                              });\n",
       "\n",
       "  if (isLeft) {\n",
       "    textEl.style(\"text-anchor\", \"end\")\n",
       "           .attr(\"dx\", BOXWIDTH - TEXT_SIZE)\n",
       "           .attr(\"dy\", TEXT_SIZE);\n",
       "  } else {\n",
       "    textEl.style(\"text-anchor\", \"start\")\n",
       "           .attr(\"dx\", + TEXT_SIZE)\n",
       "           .attr(\"dy\", TEXT_SIZE);\n",
       "  }\n",
       "\n",
       "  tokenContainer.on(\"mouseover\", function(d, index) {\n",
       "    textContainer.selectAll(\".background\")\n",
       "                 .style(\"opacity\", function(d, i) {\n",
       "                   return i == index ? 1.0 : 0.0;\n",
       "                 });\n",
       "\n",
       "    svg.selectAll(\".attentionHeads\").style(\"display\", \"none\");\n",
       "\n",
       "    svg.selectAll(\".lineHeads\")  // To get the nesting to work.\n",
       "       .selectAll(\".attLines\")\n",
       "       .attr(\"stroke-opacity\", function(d) {\n",
       "          return 1.0;\n",
       "        })\n",
       "       .attr(\"y1\", function(d, i) {\n",
       "        if (isLeft) {\n",
       "          return (index+1) * BOXHEIGHT + (BOXHEIGHT/2);\n",
       "        } else {\n",
       "          return (i+1) * BOXHEIGHT + (BOXHEIGHT/2);\n",
       "        }\n",
       "     })\n",
       "     .attr(\"x1\", BOXWIDTH)\n",
       "     .attr(\"y2\", function(d, i) {\n",
       "       if (isLeft) {\n",
       "          return (i+1) * BOXHEIGHT + (BOXHEIGHT/2);\n",
       "        } else {\n",
       "          return (index+1) * BOXHEIGHT + (BOXHEIGHT/2);\n",
       "        }\n",
       "     })\n",
       "     .attr(\"x2\", BOXWIDTH + MATRIX_WIDTH)\n",
       "     .attr(\"stroke-width\", 2)\n",
       "     .attr(\"stroke\", function(d, i, j) {\n",
       "        return HEAD_COLORS(j);\n",
       "      })\n",
       "     .attr(\"stroke-opacity\", function(d, i, j) {\n",
       "      if (isLeft) {d = d[0];} else {d = d[1];}\n",
       "      if (config.headVis[j]) {\n",
       "        if (d) {\n",
       "          return d[index];\n",
       "        } else {\n",
       "          return 0.0;\n",
       "        }\n",
       "      } else {\n",
       "        return 0.0;\n",
       "      }\n",
       "     });\n",
       "\n",
       "    function updateAttentionBoxes() {\n",
       "      var id = isLeft ? \"right\" : \"left\";\n",
       "      var leftPos = isLeft ? MATRIX_WIDTH + BOXWIDTH : 0;\n",
       "      svg.select(\"#\" + id)\n",
       "         .selectAll(\".attentionBoxes\")\n",
       "         .selectAll(\"g\")\n",
       "         .selectAll(\"rect\")\n",
       "         .attr(\"x\", function(d, i, j) { return leftPos + boxOffsets(j); })\n",
       "         .attr(\"y\", function(d, i) { return (i+1) * BOXHEIGHT; })\n",
       "         .attr(\"width\", BOXWIDTH/activeHeads())\n",
       "         .attr(\"height\", function() { return BOXHEIGHT; })\n",
       "         .style(\"opacity\", function(d, i, j) {\n",
       "            if (isLeft) {d = d[0];} else {d = d[1];}\n",
       "            if (config.headVis[j])\n",
       "              if (d) {\n",
       "                return d[index];\n",
       "              } else {\n",
       "                return 0.0;\n",
       "              }\n",
       "            else\n",
       "              return 0.0;\n",
       "         });\n",
       "    }\n",
       "\n",
       "    updateAttentionBoxes();\n",
       "  });\n",
       "\n",
       "  textContainer.on(\"mouseleave\", function() {\n",
       "    d3.select(this).selectAll(\".background\")\n",
       "                   .style(\"opacity\", 0.0);\n",
       "    svg.selectAll(\".attLines\").attr(\"stroke-opacity\", 0.0);\n",
       "    svg.selectAll(\".attentionHeads\").style(\"display\", \"inline\");\n",
       "    svg.selectAll(\".attentionBoxes\")\n",
       "       .selectAll(\"g\")\n",
       "       .selectAll(\"rect\")\n",
       "       .style(\"opacity\", 0.0);\n",
       "  });\n",
       "}\n",
       "\n",
       "function renderAttentionHighlights(svg, attention) {\n",
       "  var line_container = svg.append(\"g\");\n",
       "  line_container.selectAll(\"g\")\n",
       "                .data(attention)\n",
       "                .enter()\n",
       "                .append(\"g\")\n",
       "                .classed(\"lineHeads\", true)\n",
       "                .selectAll(\"line\")\n",
       "                .data(function(d){return d;})\n",
       "                .enter()\n",
       "                .append(\"line\").classed(\"attLines\", true);\n",
       "}\n",
       "\n",
       "function renderAttention(svg, attentionHeads) {\n",
       "  var line_container = svg.selectAll(\".attentionHeads\");\n",
       "  line_container.html(null);\n",
       "  for(var h=0; h<attentionHeads.length; h++) {\n",
       "    for(var s=0; s<attentionHeads[h].length; s++) {\n",
       "      for(var a=0; a<attentionHeads[h][s].length; a++) {\n",
       "        line_container.append(\"line\")\n",
       "        .attr(\"y1\", (s+1) * BOXHEIGHT + (BOXHEIGHT/2))\n",
       "        .attr(\"x1\", BOXWIDTH)\n",
       "        .attr(\"y2\", (a+1) * BOXHEIGHT + (BOXHEIGHT/2))\n",
       "        .attr(\"x2\", BOXWIDTH + MATRIX_WIDTH)\n",
       "        .attr(\"stroke-width\", 2)\n",
       "        .attr(\"stroke\", HEAD_COLORS(h))\n",
       "        .attr(\"stroke-opacity\", function() {\n",
       "          if (config.headVis[h]) {\n",
       "            return attentionHeads[h][s][a]/activeHeads();\n",
       "          } else {\n",
       "            return 0.0;\n",
       "          }\n",
       "        }());\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "}\n",
       "\n",
       "// Checkboxes\n",
       "function boxOffsets(i) {\n",
       "  var numHeadsAbove = config.headVis.reduce(\n",
       "      function(acc, val, cur) {return val && cur < i ? acc + 1: acc;}, 0);\n",
       "  return numHeadsAbove * (BOXWIDTH / activeHeads());\n",
       "}\n",
       "\n",
       "function activeHeads() {\n",
       "  return config.headVis.reduce(function(acc, val) {\n",
       "    return val ? acc + 1: acc;\n",
       "  }, 0);\n",
       "}\n",
       "\n",
       "function drawCheckboxes(top, svg, attentionHeads) {\n",
       "  var checkboxContainer = svg.append(\"g\");\n",
       "  var checkbox = checkboxContainer.selectAll(\"rect\")\n",
       "                                  .data(config.headVis)\n",
       "                                  .enter()\n",
       "                                  .append(\"rect\")\n",
       "                                  .attr(\"fill\", function(d, i) {\n",
       "                                    return HEAD_COLORS(i);\n",
       "                                  })\n",
       "                                  .attr(\"x\", function(d, i) {\n",
       "                                    return (i+1) * CHECKBOX_SIZE;\n",
       "                                  })\n",
       "                                  .attr(\"y\", top)\n",
       "                                  .attr(\"width\", CHECKBOX_SIZE)\n",
       "                                  .attr(\"height\", CHECKBOX_SIZE);\n",
       "\n",
       "  function updateCheckboxes() {\n",
       "    checkboxContainer.selectAll(\"rect\")\n",
       "                              .data(config.headVis)\n",
       "                              .attr(\"fill\", function(d, i) {\n",
       "      var headColor = HEAD_COLORS(i);\n",
       "      var color = d ? headColor : lighten(headColor);\n",
       "      return color;\n",
       "    });\n",
       "  }\n",
       "\n",
       "  updateCheckboxes();\n",
       "\n",
       "  checkbox.on(\"click\", function(d, i) {\n",
       "    if (config.headVis[i] && activeHeads() == 1) return;\n",
       "    config.headVis[i] = !config.headVis[i];\n",
       "    updateCheckboxes();\n",
       "    renderAttention(svg, attentionHeads);\n",
       "  });\n",
       "\n",
       "  checkbox.on(\"dblclick\", function(d, i) {\n",
       "    // If we double click on the only active head then reset\n",
       "    if (config.headVis[i] && activeHeads() == 1) {\n",
       "      config.headVis = new Array(config.nHeads).fill(true);\n",
       "    } else {\n",
       "      config.headVis = new Array(config.nHeads).fill(false);\n",
       "      config.headVis[i] = true;\n",
       "    }\n",
       "    updateCheckboxes();\n",
       "    renderAttention(svg, attentionHeads);\n",
       "  });\n",
       "}\n",
       "\n",
       "function initialize() {\n",
       "  config.attention = params['attention'];\n",
       "  config.filter = params['default_filter'];\n",
       "  config.nLayers = config.attention[config.filter]['attn'].length;\n",
       "  console.log('num layers')\n",
       "  console.log(config.nLayers)\n",
       "  config.nHeads = config.attention[config.filter]['attn'][0].length;\n",
       "  config.headVis  = new Array(config.nHeads).fill(true);\n",
       "  config.layer = 0;\n",
       "  config.initialTextLength = config.attention[config.filter].right_text.length\n",
       "}\n",
       "\n",
       "$(\"#layer\").empty();\n",
       "for(var i=0; i<config.nLayers; i++) {\n",
       "  $(\"#layer\").append($(\"<option />\").val(i).text(i));\n",
       "}\n",
       "\n",
       "$(\"#layer\").on('change', function(e) {\n",
       "  config.layer = +e.currentTarget.value;\n",
       "  render();\n",
       "});\n",
       "\n",
       "$(\"#filter\").on('change', function(e) {\n",
       "  config.filter = e.currentTarget.value;\n",
       "  render();\n",
       "});\n",
       "\n",
       "render();\n",
       "\n",
       "});\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xlnet.visualize_attention('nak makan ayam dgn husein')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_I attached a printscreen, readthedocs cannot visualize the javascript._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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N2uU6ubrxej76FgYKhpxGCKP3xs9Mrpjmm0WbO1moWLJZrli9sb5nU2ubb5dkH+jg6KjvJO8s4EJyxbouu310H/Ho9rzjVb/zrPexXYd8kn2pfhSyr79HgFOgfZBNsCXFMsQsVDNMNlwggmU3TSQicjXqB/Vn9FosOo4YL5SgsccpMTqpMLll71QKzX6+VJk07QM26X4H4zMOH6rMbMsazv6ey3xY4Yh9XsTRw/l1BY+OvTu+XshZpFxsdzK05GDpmVPNp3vLZs78OsdcLnFeu8LuArkytupQdTG8z3XXzV0iXlasd7wSdTXvWl1D5/WRG1+aMM0cNyVvady2aHG7E9ga05ZyN7X9QMfBexmdh+5nPsh+mPvocNfhx4efHO7OfZrzLKvnUG96X2r/3udxf0UN7B6MfBEzlPTy4PCxV+UjDa8fjL5882kcvCVOCL6Tn9SZMp/2mzn7/tNH5dmkT62ff81rLsR9ufz13SL7kuX3lB8NP6dXuFcd1rJ/dW6PvzFCH7kD+RnVjj6EccSKYxdwN/EZBAcabppR2vN04fTqDAiGdsZ0JgsiA7GXdJTZloWB5SlrNpsJO8TezBHBKcQ5xJXDrcP9iaeU14z3G18Zvxn/Z4HjghqCI0J7hfmFW0W8RVZFi8WUxLrFA8RXJY5JSkm2STlKTUmnyojIDMnm7jDY8U2uSt5TgU6hTTFSSUCpXzlNRUFlXDVPTVvtk3qphrnGouZ5LXutX9p1Ou66WN0bemR9ov5dg0hDfsNeozRjJeNpkxJTW/jecds8ykLK4p1lmZWHNav1c5sCWwc7kt2g/UkHb0dhxw9OV50TXYxdGVyH3Srdoz0MPGk9B73O7Az2VvBe2XXfJ9/Xy0/Cb4nc6X8swDdQMQgVNBhcS0kJcQqVDkOHvQm/FVG8Oz7SNUqDyhuNip6NGYhtj6uPL0vI25OaGJ8Umuy/d+c+txSn/Q6p9mn2BxzSnQ66Z+w8FJAZmhWdnZKTmVtwuOxITV7j0Xv5fQWjxz6fQBVKFHkVHz15v2TllOxpv7ITZx6fXS1XOB9QUXKhpwpVrVUTX1tf9/GS5OWQ+torc9dUGvZf727kaApr7rzFdzul5W2rVVtLu3zHxU6p+1cfGjwafpzQzfe0t+dwn9Nz0QEw+HHo3fCH1+CNyPiuidop9EziR/CpYp78VXdJ7afzavHG+G/93rdRMCoAnDgEwMbvOQ41AOReBEBsDwBscO5pRweAkzpACJgCaLEDQBbaf84PCE48CYAEeIAkUANmcH4ZBueURaAedIEJsAaxQ8qQIxQNnYCaoddwzieNcEGkIuoRo0gGpAEyHnkJOQVnaV6oUtQrOBPzQV9Af8KoYFIxz7A82HBsG46Eo+Da8Zz4WHw/QZFQRFilIdM8pVWnraZjp8ulR9An0X9niGVYYkxkgpiyiazECpIaqZc5hAXLcoHVmHWKLZNdir2XI4aTg7OVy5+bhvsajwcvkvcSnyecEfQJ5AnaCjEJPRcuEvEUFRCdErsoHi2hIQlJdknlS3vCs3Netn9Hi1ylfIHCPkWKkqOyhgqfKqQ6ptaiflwjRFNbi15rRLtGJ0ZXVw+n16ffYHDdsMnolnGryT3TLrMe80GLUctpqwXrFVucHau9qIOao5UT2TnZpdi11W3Gg+Sp7xW5s9x7wIfgq++XRG72/x6oFpQU3B5CCHUOqwhf3G0WWRY1F60VkxM7Gq+UcHTPQpJr8oN92imtqZZpE+lZGdqZIKsv58rhU3kF+WbHkMfvF+YXB5QYnpIuEzwrUq5UYVMZVV1a++QSqFe9atPgfiO4KfnmidvX7vS3LXXwdpo9iHl09vGz7rUemb6dz48M3B0iDZNHLo3OjnNPqE3qTcu/p//wYvbI5x1z7QtmXzq/KSyWLC3/sP95YXlhVWMt5dfdzf1ja/yJ8PhLAFVgAlxBCNgHjoM60AlGwQ+IBMlBNlAEdBRqgF4iAEICzvLTEFcRb+E83gqZjmxDrqC0UQdQ3Wh2dCC6EYPHeGMasYzYMOwTnDQuD7eI98I/IMgSimiQNFE047TOtI/pDOla6bXo78BZ7CNGe8ZROE9dJx4nyZKeMkfAmWczqy8bDVszeyAHK8dDzj1c0lzj3EU8trw43g6+/fwGAhiBp4KFQr7CssKrIt2iZWJR4sYSXBJfJB9LnZdOkfGU1dwhIccuj5dfVZhTnFB6ofxY5bbqRbUS9UMaVE1PLUNtSR1GnUXdYb1W/XqDq4YNRk3Gt03aTDvNHpv3WrywfGM1bb1gs2KHs2d1EHNUd7J29nfZ61ridtN92GPNS3CnhXfMrrM+PX4QWcU/IqAmcCpYlBIScjV0Odw0onD3TJQWdW90Wywqziq+KGEqUT3pSPL0PuOU6lT6tD0HpuH9pDfTIuthjllu9xGHvLH8lGO8x+8WBhbTn2wu9T9NKntwdm+5yvkvF65WxdZo1WEuDly+cCX5mtd1lUb6pomb128fuGPTxn53vKOmk/pA6xG2a/BJzdP9PV59Os9FBpgGHw05v5x8lfiaefTamNP46kT1pPs0w0zXh8xZy8+Mcy8Wzn4NWVT5jvjRs1y6GvRLcXv8kQADaDd3AHGgAs8ANxAODoIz4DYYhte/IGQBxUIV0CCCBmEEr/wOJA5pjzyD/IKyQFWh8Wgq+g3GCV7tNtgBHBn3E19IUCdM0pyk1aMdoUui56fvYohnlGScYDpD9CNJkL4zP2QpY01i82TX45DiZOei4UZwr/Is867yAwEsfAPlEZYV0RZ1EAsS3y9xUvIGnHfPyzLuUJBzld+nUKHYo7SiIqHqrlag3q/JrOWuXaEzp6etf9jgjZGicY7JuJmWeaHFFys760u2tHZh9o8dJZ1ynD+4WrjVeuA9KV4PvUV3HfSZ9DMkVwYgA/2D7lFEQzJCZ8KtIuojWaISqGMxRrGX49kT9u35mOQGr1OVlKpUjrQj6aiDyRlfMj2yrmav5zodrjqyfNQx//IxwnHKiQdFUsW5J+dKXU/dKRM9kw/v/f7nuy9oVlZVM9Uk1k5ddLzUUi96Je/qUoP39QeNMk1Hm+dv2d++fIfQGtjW2k7sCLjXeB/1wO5h6aOJxxJPKN2VT8d7OHvt+w72X3/+doAwKPfCYYj68shwzat7IwOvp0YX3qyOQ2+xE5h3mEkwuTz1aXp05un75g/lHzNnIz5Zf5aaw869mW9eyPri8VXi65dvLYtpS0bfMd87f6T81Py5sHxhxWOVsNq4Rv5F9+vauvvG+EcHKipsHh8QrQEA6NH19a+iAGALAFjLX19fKV9fXzsPJxsjANwN2/oPafOsYQTgLNcG6rsy+frf/+X8D78U1VXQOwEbAAABnWlUWHRYTUw6Y29tLmFkb2JlLnhtcAAAAAAAPHg6eG1wbWV0YSB4bWxuczp4PSJhZG9iZTpuczptZXRhLyIgeDp4bXB0az0iWE1QIENvcmUgNS40LjAiPgogICA8cmRmOlJERiB4bWxuczpyZGY9Imh0dHA6Ly93d3cudzMub3JnLzE5OTkvMDIvMjItcmRmLXN5bnRheC1ucyMiPgogICAgICA8cmRmOkRlc2NyaXB0aW9uIHJkZjphYm91dD0iIgogICAgICAgICAgICB4bWxuczpleGlmPSJodHRwOi8vbnMuYWRvYmUuY29tL2V4aWYvMS4wLyI+CiAgICAgICAgIDxleGlmOlBpeGVsWERpbWVuc2lvbj40MjI8L2V4aWY6UGl4ZWxYRGltZW5zaW9uPgogICAgICAgICA8ZXhpZjpQaXhlbFlEaW1lbnNpb24+Mjg3PC9leGlmOlBpeGVsWURpbWVuc2lvbj4KICAgICAgPC9yZGY6RGVzY3JpcHRpb24+CiAgIDwvcmRmOlJERj4KPC94OnhtcG1ldGE+Cmowy9wAAEAASURBVHgB7F0FnFRV+362u4BlWRZYurtbQEBCULERsLHAzwDr0z8qqNjxKdiBhSAg0iAh3d3dLL3d8X/fM8zs9M6dnVlmd9/Db5h7T9/nzt33nue84VVACZIEAUFAEBAEBAEPQcDbQ+Yh0xAEBAFBQBAQBBQCIpjkhyAICAKCgCDgUQj4etRsSngyJ06cwKFDh3D58mXk5+eX8OiFw3l7e6NixYqoV68e4uPjCwvkSBAQBASBcoiAV3ndY9q2bRvOnz+Phg0bonLlyvDx8blutz8vLw8XLlzA/v37ERMTg1atWl23ucjAgoAgIAhcbwTKpWDildK+ffvQvXv36yqQzG8+C6iVK1eiUaNGsnIyB0fOBQFBoNwgUC73mJi+45XS9VwlWfuF8Xx4Xjw/SYKAICAIlFcEXCqYzp49i3Pnznk8lrynxPSdI4m16VNTUx2p6nCdyZMn4/Tp01br87x4fpIEAUFAECivCLhUMD3yyCN48MEHPR5LVnQoarXEdSZMmKAEWKVKlVC9enVMmzat2NfGwvvVV19VH2ud8byupyKGtTlJniAgCAgCJYmASwVTSU7c3WNNmjRJCaYvvvgCW7duxahRozBixAisX7++WEOzUEpLS8PUqVMxa9asYvUljQUBQUAQKIsIlKhgWrt2Lbp27Yrw8HD1ueOOO3D16lVFXbVp08biD/Xdd9+Nt956S+G+Z88e9OvXT7XjPqZPn264H506dcK///6LJ554Qmm1MU3G/bFwcTZ99913GDlyJO666y40btwYL774Ipo1a4Zff/3V2S4xe/Zs/Pbbb4b2r732mqyODGjIgSAgCAgCOgRKTDDxPg0LFrbZ+eqrr/Dee+9hxowZ4P0WtuEJCQnBDz/8YLgvp06dUtRZhw4d1L5V06ZNERwcjO+//16pU7PA+Oeff1R9XsWwEJk7dy7uu+8+tSLhVQ6rYDubWGuP7YqMU4MGDXDy5EnjLE3HLIiM0+HDh21Sesb15FgQEAQEgfKEQIkZ2PIf9I4dO+Kzzz5TmmcM8i+//IKjR48qvB966CG1P8UrqKioKMyZM0ft7/To0QPjxo1D/fr1laDy9fUFr7RYyYL76t27t2qfm5sLXlXxaowTq16zECxOCgoKMmnOwtNZYbd9+3Z8/fXXJv3pT3hPqbhz1fcl34KAICAIlHYESkwwMR3GK6SFCxfip59+wpo1a9SH1aM5DRkyRAmmefPmYdiwYYqqY0UKFkRbtmxBYmIihg4dasB7165dJhqADz/8sEEocSVX/KFn4WaccnJynO63ZcuWxl3JsSAgCAgCgoANBEpMMB0/fhzNmzdHdHQ0br/9dvAKyVj7jFc6DzzwgFIK6Nu3L1asWIFPP/1UTTs9PR2hoaGoVq2a4TL42Fj41KhRw1DmigOe58WLF026Yk8RTDs6k3jFlJmZabVp+/btTa7FaiXJFAQEAUGgnCBQYoKJlRVSUlLUKocpMU68X2ScWDAxdccrKhZi/OHUpEkTJcQ++ugjQ3VeWRnbAvHKypWJx1y9erWhSxaOGzduxOjRow15Wg54xcTXc/DgQZNmzz33nKI4TTLlRBAQBASBcoxA8TZhrADHez/Lli2z+Ohpsb1794JteT788EOsWrVK7dlkZWWpnrp166ZWRS+88IJaUem7Z0qPqT/W0GOlCO7/3nvvVTSfvo7xN/fPihY//vijcbamY1au4FXb559/rnzYsVYeC9ZBgwZp6se48vjx441PUbduXaWSbpIpJ4KAICAIlHcE2Imrq9LAgQM56KDVz5EjRwpon8lQ1qtXr4Jnn31WnZMShGEKb7zxhsoj4WLI4wNaRRWEhYWpMv5+/PHHC2jPR9XhMX///XdDfXKGquqR0oQhz/iAVLYLiFaz+yEtwoLHHntM9aO/JlK2sNumqD65nPbJDH3ynK214flJEgQEAUGgvCJQok5ceU/p0qVLYG03Ei7qnSAhIUHZHnl5ealztkViJ6vz589X5+b/8YqsuN7ASSAoZQvzvq2d82qONQV5z6kobxHW2pvn8WqO7aF45WVrRTdz5ky1IjRvK+eCgCAgCJQHBFy7MVMEYqysYO6jrkqVKqrV5s2bwZ8vv/xS2SPZ6io2NtZWkcP5PA+mFh0RNAEBAdDP0eEB7FSsWrWqou9sUYKuUHO3M7wUCQKCgCDg8QiUqGCyhwbHR3r//ffBRqhECdqrWuwy1qxjeyRXCDlnJsOrQluJ5+Ws5p+tPiVfEBAEBIHShECJUnmeAozEY/KUOyHzEAQEAUHAEoFyKZgYBolga/ljkBxBQBAQBDwBgXIrmBh8XjlxUD6Of2Rs7FvSN4b3vJi+Y9988fHxJT28jCcICAKCgEch4LGCyfeFf5CXz5rVrkkFgTeTA71s13RGvQS1qYbMPJ39lSs6TXg4HQUUDsNV6Z8H1yAn09SlUnH6zvX7BFlprguY+EC1N4B0181vct21SEt3HX49+n+F7JyE4kBm0rZ7+9MI9I8zyZMTQUAQsI6Ayw1srQ8juYKAICAICAKCgGMIiGByDCepJQgIAoKAIFBCCIhgKiGgZRhBQBAQBAQBxxAQweQYTlJLEBAEBAFBoIQQEMFUQkDLMIKAICAICAKOISCCyTGcpJYgIAgIAoJACSEggqmEgJZhBAFBQBAQBBxDQASTYzhJLUFAEBAEBIESQkAEUwkBLcMIAoKAICAIOIaACCbHcJJagoAgIAgIAiWEgAimEgJahhEEBAFBQBBwDAERTI7hJLUEAUFAEBAESggBEUwlBLQMIwgIAoKAIOAYAiKYHMNJagkCgoAgIAiUEAIimEoIaBlGEBAEBAFBwDEERDA5hpPUEgQEAUFAECghBEQwlRDQMowgIAgIAoKAYwiIYHIMJ6klCAgCgoAgUEIIiGAqIaBlGEFAEBAEBAHHEPAqoORY1ZKtlZfv2mn5IN+lF5Dn5dLu4OPa6aHAy9XvHK69H15wLYD5cPH8vFzdn49rfzDSmyBQhhHwWMFUhjGXSxMEBAFBQBCwg4CvnTL3FxVoXyak5KYiKz9X89zC952gd3Rtb+lpOYHwia+paaz8vDyEVvLX1IYr+/hovxU5OTmAt7ZrKiDM/fy0v717eXEbbWNpBkEaCAKCgCBACGj/a2gDNmcIQS+mXzQ3LMDFrEs2ZmE7O3jrNiBfmyDMbdwF6eczbHdqpSQgxBt5JC+0Jh/1h19bK2Zhc3O0CWkfH0LdiRcCnWDSNj+pLQgIAoKAMwi4eiPCmTlIG0FAEBAEBAFBwICACCYDFHIgCAgCgoAg4AkIiGDyhLsgcxAEBAFBQBAwICCCyQBF2Ti499578eqrr5aNi5GrEAQ8GIEPPvgAnTp18uAZlt6puUz5ofRCULZmnpCQgMjIyLJ1UXI1goAHIpCUlISjR4964MxK/5RkxeTB9/DKlSukQWfd0DMrKwsXLlwAf0sSBASB4iGQnp4OFjTWUh6ZgPCzlpqaaq1Y8tyAgAgmN4DqbJez/voL4RUi8ce0aYiJi0XFmGhEVIzCr7/9Zujy7NmzGDBoIAJDg1E9vgYqVKiAZ599Frm51tXGv/32W8TExODdd9819CEHgoAgALRp0wZvvvkmbr75ZoSEhCimoW/fvuAXQk5sJzh69Gj4+vqqZygsLAw9e/ZUQsoafhs2bFD1Bg8ejOzsbGtVJM9BBEQwOQhUSVTj1U9KSgrGvDgWn338KebPmYeGDRpi2P3DVT7PYeQTj2HBwoX45aefsXbNGjz99NP4+uuvsWnTJospfvbZZ/jPf/6jBNeLL75oUS4ZgkB5RiAxMRHjxo1D9erVsXLlSkycOBFLlizBF198oWD53//+h88//xwTJkzA+vXr8cMPP2DFihX47rvvLGDj9h07dkSHDh0wdepU+PtrN7K36LQcZ8gekwfe/C+/mIyBAwaomTGNMOjWwTh+4jiaNW2GWjVr4afvf8R9Q4ciOzcHvn5+YAF0+vRpkyvhh2z8+PH49NNP8cgjj5iUOXOSfOYMwuOqOdNU2ggCHotA69atMWnSJHh5eaFbt274jdiJXbt2qfkGBgaCX+j++9//qnOuy+cnT540uZ7FixfjpptuwvDhw5XQ8qNnUlLxEBDBVDz83NK6LVEM+hQbW0Ud6qmBD9//APPmz8cLL72I7Tt3qDc8fV3995QpU/SHaN68ueG4OAf7p/1FHom8EV4jFhUa1EflJk2K0520FQQ8AoGuXbsqoaSfTHx8PDIzM9Xpk08+idWrVyu6b+fOnVi1apUFjcd7TyyUOPGzJkJJQVHs/4TKKzaEru/AFg3AwqnrDd0x5M7b1Z7SXXfehblz51qdAL/5xcXFYeTIkcjI0OZWybzDZFqN5WVmITs5FZd2H8LBGfOwbuJH2P3zrzi1bgOyZFPYHDI5LyUI8KrIVhozZoxaRR04cAC9e/dWFF39+vUtqjM7cdttt2Hs2LHYv3+/RblkaEdAVkzaMbtuLXbt3oVNmzdh2u9/4M477lBU3u69eyzmM2LECNxyyy0IDQ0Fb8S+/fbbitazqOhgRni1auj08nO4sGsPrhw6hOQTZ5GdkobEY2fU58SSfxEcUwkRtWogumlDhFcVys9BaKWahyLAFPqHH34IXjXp95xYwYj3pYxT5cqVFb137tw5/PPPP+Bnb+3atUphwrieHGtDQASTNryua239SmrZ8mVo2bIFjpANxdgXX1BzOnz4sNIiMp7gjTfeqB6Ujz76CIMGDUL79u2NizUfV27WFPzhlHz6FC7u2Y+kYyeRfuEyObu9pD7n1m+Ff3ioUH6a0ZUGnoSAt7c3WAtv69atYBqPFZPYoJapuxMnTliolsfGxioBxoLp448/VqsnT7qe0jYXofJcfMfyyYO5Mx+2V+INWE76b+OpcV7TJk0x6smn8OXXX6F+o4boP3AA7rvvPhJSLZXm0PHjx1UT4/bvvPMOoqOjFaWn36cy7tfZ4/Bq1VHnpj5o/fjDaPfs46jRuxsia1aFD4XUsKT8flOUX7ZQfs7CLe2sIMDPjDPPGrfRJ+NnhfNYIPGH81kjj7XxWrRooV7qgoOD8cQTT2DBggX4888/VR39yyK3HTZsGPr3748XXngBh4hZkOQ8Ai4LFGjDDtTuzLyQpznsRUpeGk5nnLfbr7XC+D9Xaw57kU5hL7LDdMoH1vo0z1vy70I8MHqoebZD540bNcaenTptoKIasCFgcnIyomMqU1zeArVSunr1KphWKCpx2AtnlIa8vZmLdywe04Vdu00oP+M5FVJ+jYjyizMukmNBQBMCLDB4NeNMmjlzptoXKqotK0KcP38eVapUQUBAgKrOtoR8zgJMknsQECrPhbja8tLgyBC2DGSttY2IiAB/WF08Pz9PaQI5IpSs9eWOPC2UX8Q1Lb9o0fJzx62QPm0g4OizysoRrKlnnKpWrWp8KsduQEBWTHZA1bpiysnJRkZuMkIra5f3wcFhyouDnelYFLFgyiXBpCWVxIrJ1nyyUpJxnlZTyYePIuXMeQqoWDh3H39fhMVVQUTdOqjSrAn8SHFDkiBgDwFmCZylp9mfpH4FZG8MKbs+CIhgsoO7VsHEXXEE27Aq2gWTv3+QnZlYLyptgsn8Ki7svEb5ndRp+RmXB1epRHtWrOXXCGFC+RlDI8eCQJlHQPtf0DIPiVxgSSFQuTlp+dGHk07Lbx9p+Z3SafklkJYffc5e0/ITyq+k7oqMIwhcfwREMF3/eyAzIARYy48/nMwpP9byu0iGvfw5PGeREeXXlCi/ENVG/hMEBIGyg4BQeXbupVB5heBo0corbOWaI3uUXwhRfhFC+bkGaOlFEPAQBFwmmK6k52i+pDCfHPh5FdoUONJBFilIp7KaucYUmZhNys6OqTvru84qCESejzYvwQUFOaTAna7vwuHvkIJwq/ZL9jpIQQayaDwtyccnF0EhOl9gWtoFBdSk+V1/9Vhzys/4GtiwVyg/Y0TkWBAonQi4TDBddkIwhTshmLLpz34KrMcesncLopK1C7NsryDkFWhjO8mqiFS4tQcUC0GEZsGZ4pWBzHxtcV98ffNIMGn3nRcUUMsjBJPxPTan/Kxp+UWSll8M7WP5UbwdSYKAIFA6EBDBZOc+iWAqBMcTBVPh7HRHQvmZIyLngkDpREAEk537JoKpEJzSIJgKZ2up5WdcJpSfMRpyLAh4HgIimOzck5IWTKvXr8WwJ+7H6nkrUN0BD93lncqzc+tMiuxTfn4IqxaDyDpC+ZmAJieaEeDwMhwWg4NzDhkyRHN7aVCIgLYNlMJ2cuQGBDIzM3D67BkLL+FuGKpcdRkQFo4anTsD/KFkTvklHj0N/hyn8B2i5VeufhouvVh2DsuRpNPS0lzab3nsTASTi+56UlIiucknzbprimv8I00kZ6tR5PrE3IMx++niMtYSjIyM0DwDbn+VxkvzykRgeLDN9hw7hn3qmY9vs0E5KbBn2JtGRr38MTHsbVgf0Y0lYm9Z/nmkp6fDx8fHxE3RlStXEB4ebjW2Uip5yucVUlRUlNVye1ip55fcKfFzye1tJR6fy8vj83v99X9t3RUPzz+XcA5VakXj2x+/QcuOzRBXtwqq1onBnHlz8OkXk1C9XgPUatgY9Zo2x+q16wxX8+PPv6Ba3fqo2aAR4hs0RIv2HbGZYr5YSxcuXUTHm7qiUefmOHH6pKryzc/fIapuDKIbVEXN+rXRoUMHFTOGC+dTyPW6deti9uzZaNq0KRo2bIh69ephxowZ1rqXPEJAF76jr1H4jq668B2+uvAdbNR74M9rEXt/+Q2nKWJvjrwRl4nfTps2bfB///d/GDBgAEJIa5Mdtr788ssq4F/16tVRsWJF5SCZw1/oE4dab0IOhzlWEztOrlChAr799lt9sck3O2Z+8MEHlXBbvHixKvv666/VyyL3zW3rEIW8YcMGVTZr1ixV948//kBMTIwan18sf/31V5N+y8OJ7DHZucv29pjOEOXWoEUd1fqjiZ+gRfOW+O/rL2P9xnWoSd6In3/maVQjH28jnxqF6hQBdvmiBdi6fTt63tQfdxL//MDwYcoBJZc3pR/6kmkL8M+Kpeh39yAc2rgXAf4B6H17PxVCfdH0eagdXwubtm9RgureIXfj0eEPIzEnBSOffEw9KPxj/uuvv/D444+Dg5a9/vrr6uF57733sJ3G5UCCHNG2LKmL27l1Likyp/yMOxXKzxiN0nnMQuEoBdt85plncAdFhGYBMHnyZHUxb731lgqrPn78eCxZskRFrmXBxbHN+GXvjTfeQKVKlZRg43IOj8GCiJ+xKVOm4O6771bxmaZPn67iN/Xr1w+bNm1ScZ2GDh2q4qNx8MHhw4ereE8suKZOnYp7770X1ejvBQcl5NXauHHjVDsOc8PCsLwkofKKeadfe3kcRj78uOrlqcdGKcH0f6+8hNtvvVXlDRt6L775/gd1nJKSgvvuuRtv049aT+F17dIZ27bvMJnFsRPH8PiYUQgNCcWCv+agSuWYa+2Tcf89w/HhG+8pipCVHzrTvsmOHabt33//ffTu3Vu14RDR/OM/deoUGjVqZDKOnNhHwJjySyL8Lu0t9OVnSflVRYWG9YTysw+px5X26NFDRZzlidWqVUsJJn65e+WVV9Rcn332WSWYOAYTC4bbb79dvfwxU8HptttuU+Uc2ZZXQJx4j4mVH1auXIl169ahY8eOKp+FywMPPACOKK2n8Hj8zZs3q3L9f19++SUGDhyoTvn55ejTHAS0WbNm+ipl/lsEUzFvcYtmLQ09BAXp9ns6tGtnyAs1Muy8oVs3VIuLwy/0ZrRr925F4R0+clStsAwN6KDvnbof5YA+/Q1Cict7deuJ6nHV8ePUKdi+ewfWb92Aw0eOWMSL4QBq+sSUAKecHG0eIvTt9d87ls5BUGgY7WlVQGhkBYRVioYzHtH1/ZW27wiidvjDyUTL7/R5FbH34u6D5MvvIA77LxYtv1J0c9u3b2+YLUeo5dS9e3dDHq+A9IlXMh9++KFiJn766ScVpHDNmjX6YsM3R7nlxFRfgwYNDPk33ngjatSogR9++EGxGEzhHTx4ELVr1zbU4YO2bdsazpn94ORseA9DR6XsQASTG26Yrc3K+YsW4d4RD6Bzxw4YQEv7224ZjHnzF2Kl2Y/71gGD0bFNB7w0/r/4edqvGH7XfWqWcxbNxa0j7kS3jl0wuN8g3HzLIPw9fw7MHw7jcM+uuryUqwlIvnzWpDsfohsDAkMQEBxO3iToQ3x4WFQ0wivphKFJ5TJ0Ilp+ZehmWrkUa88vKywcO3ZM0W5M540YMQKjR49W1NuoUaNMemGV8bffflvRg88995wSRFzh77//xi233KIoQv6+6667lJBbvny5SXt3PL8mA5SCExFMJXiTptDmed06tTFv1kxDWOZpf860mMH7r09EfLUaYEE0+uVn1UopLrYqvv3lR9SvUw/LZi1W7ZnKm/rnHxbtXZ2RkZqBGo3bISMlERmkjZSdnoLsrDTkZWchnT/JV3DVbFC/wFAEBLHQCkNwWASCaaUVThu+QeG2tZDMuig1p6aU30mi/PYbwndYpfwaEeXXSLT8Ss0NvjZRVipiOn7//v3QR7FlZQbz9OqrryrKj+lAvYBiao6VJFhorVixwvD8l0fFBnO8rJ2LYLKGipvyAgIDkHD+Atau30B8dBTmL1yEGaSwwHQB2y8ZJ1Zd/ebjL9G4Sws8PnYU/v55BmkNBeDc+QSsWr8GFYnPnr5wlnrj4vbnzp0zbu7S46DQIFSo2JjUVr1N+k1LvIxUUmllwZSekoTMDBJYGWnIyeRPqvqkXj2Py0atvH184cerLBJcQTTvskYNRlSvQZRfDXXFDlF+7MuvmfjyM/qJeOyhPuIta792I1qelRnGjBmj5rtnzx6VZzx5FlB//vknHnroISXMWHmCn9NVq1YpjTsWdKzwwHtXbP8kqRCBci2Y2NbIXsonz+f5BdbrWFvue3vr/nAbezEnUwVDev7pp7GRNjoH3qazCu/Yvh0mTngTL736f/jvW/+H++8epurq+25AauXv/t/bePHNV/DbjKl46ekXsH7zBvS6ra+q17F9B7DW0GuvvQbWIurTp49hLPMDfZ/m+cU5D4msCP6YpwIK955Mqu6pVy8qgZWRloQsXmVlpFM49Sxk8Tl9ko0lFnVS1qhB25TfGWSnpCujXmXYu1gMe81/Q46cM73GH2eS4Vk1ekCtPSP6PP5mjTle4Tz66KNqSN5DYi2+YcOGKVouISFB5evbBAUFgfeiOnXqhLFjxypVdFaGYIUHTl26dMEnn3yitAJZTf3mm29W+fr26uTaf9byjMvL2nG5VRe/QgZu0bSsdjYd23cK0aQAYJ6K8i7OKqXnSYMnnN6S9OqfFy9dQtWI6gjwCzDvzuKc25+7kIAINuYN91PexS9Re7Z38PPzs6hvnnG91cWzaEWVcuUy0q/SKiv1igk1yALNVipr1GDSKT3ld5Ii9l4xuWydL7+qqEiUXyWh/EywMT5hJZ+dO3caZzl8PHPmTKVR53ADo4rnz59XArFKlSoql7XtOLF6d1FJPb+0auLnVV+fNfoiyRBf9pYK0Su3KyZn37T00Dnb3tfXF3FVq+q7Ud/RZA/hT/8cSdxe70eP4zFxYnuK0pLUvlNcCBCno7uM55129Ro1mGJEDaYTLUj7WWWNGnSU8vPRa/kpyq8Zhe+w7enDGEs5to+As88v96rXdNWPoBcw+nN73+r5vabdqa/HKy9JpgiU2xUT/zAv0ErDXsrxokCBNuIx8WrJ2vK6qBWTrfEkHpMtZAAdNXiBqMFLhdRgGlGDmTpq0FbL0koNFhr26ig/4+sTw95CNK4S6+GsGjWvUPR7RoU9ypGnIFBuBZMjN8Ce5wdb7UUw2ULGPflZtKJKoZVWGlGDGWWQGhTKzz2/G+nVsxEQwWTn/ohgKgSntMVj4pnbowYLr8z0yKrWYBQZFFesTHsAgaaVS/jMXMsvL7dwT84ngMJ3xFH4DhWxlyi/a8aiJTxFGU4QcAkCIpjswCiCqRCc0iiYCmdvelRAbl6SL5d+alAoP9P7KmdlBwERTHbupQimQnDKkmAqvCrLo6y0VKQkkvJFcbQGw8mgOKxkDYqF8rO8l5JTehFwmWA6n5qtGYWQjHMIDdCmGHg1JxmZIZa2M0UNXjm5QMU/KqqecXl6uhe8HVABNW6TRZvyvkHWbZ+M65kfBxeEwdvMgNW8jvn5pRQyBAotWkXcuF1efhKpphatlm7cho8D/GNJ2UPbvTLvo7Sfu4QajLjma9CN1KCjlF+V5s3ge50pP1ZgYEelksomAqxkwpqIWpPLBNPJxEytYyMmNwEBuSma2qWRrc75gCBNbbhyfIofvDTa4uUEhCPfxzE1bv2ECgpy6UFL1Z86/B3iTXZJ9E9LSivIRGaBNuesvn4FCArK1TKMqhvgz/7vTD0/aO6kjDbwdGrQkyk/dmLqrGZdGf05lanL4tAibGisNWkXZVpHkPqCQBlHwIvcR0VUjlUf80vVUYNsUHzVwqDYYV+DxaQGrfvy0xn2WvPlV7FRfTLsbWx+KXIuCJQYArJisgO1rJgKwZEVUyEWrjpyHTVYkbQGOQyJNq1Be5SfL2n5hV7T8qvSojnR09rfeh3BSVZMjqBUeus4u2ISwWTnnotgKgRHBFMhFu4+KiC3U8lX2NdgyRoUF035xSO6aUOEUWRmVyURTK5C0jP7cVYwCZXnmfdTZlWOEfCizWK3U4MchqSCaRgSU8rvBC7tOYCk4+aU3xYoX37x5MuvoVB+5fhn6tZLF8HkVnilc0HAtQgEhFCcK/ogLt6i4zRyjptKXjDSU65S7KwkZHAYEmu+Bs8UNrUwKFZag0QNUuTjOtV1YxRSfkeQcvqCLmLvLorYSx/fgEUlQvkVzliOygMCIphK4C6zX77ExCRSt4byIqx1yCwKxpeYRGre5JE4gKLGWksZGRngGE7GHopZFZc9mDujrmltDMnzbARCaAXEH/NUFDXoaBiSqE6tUIMiFGeevYgrhw4h+aSt8B1M+TUiys/UWbH5vDzlnLUCOQAgPyvGz48j8+Nnm72Ls99Me85cuY5xeVZWFnJyclQsNkfGKW91RP/XzXf8hyk/I652XcTXb4Aa9Rqgedv22LxlK65cuYqqtepg4gcfmszgmynfIyI+GhwK42zCOQy8+xYExUYgtmEN9T3qhf+AXedz6tbrBkycOBH33HMPatSogbi4OEyYMAH//vuvCgHN0TJjY2NV5EyTQeSkXCGgpwbjGjRDvbZd0fyGgWg34B50GfIQOtw8HI27DkB8k06oHN+AlCjiKPIwmS54++giFHN04oTjOHtkJ45sXYXtS2di/75VuOqbCt8mVRHUuhb8alaAV5gf8ihsCWv5nV2/BTu+/QUbP5mEA7P+wqV9ez0Sbw438cQTT6BNmzYqRhJ/c1wztqv6/PPP0bFjRyV09JPn/P79++PTTz9VWRwEkGMtde3aVcVW4jJ9GI6lS5eq9nPnzsUNN9ygynv37o1DJNA5sm3btm1VWw6vzvOQZIqAKD+Y4mFyVlzlh63btqNH35tw5+1D8OCI4RSOPBuPPvkUmjZtgtnTp+G+Bx7E+g0bcWjPLoT5Rio7pm4DelKspnDM+2M2Bt17G+YtXoCfv/wBDerVx9QZ0/DRpE+xav5ydOnQCbVbN8TxE8fx2GOPYfDgwSpa5g8//KCu4b///a96MD788EMVyvnIkSPqjU3smExusZzYQcAeNWitGa/McmhlkJeWg4KULHjnk2Welx98vf0oYnEAwqvFKV9+xlp+11P54amnnsLKlSvVy13NmjXBkWmnTJmiPhxtloUGv+jdcsst6nLXr1+vggRysEAONMiBAwcMGIA777xT2WJxsL8GDRqAw60vWLAAL7zwggqRwYKIV2Ic7TYtLQ0dOnTAfffdp1Zp/Jw+/PDDKligNUxLe54oP3jgHUwmeuA+Ws28M/4NA4XXjaJWbt2+Xc32geHDMGfefKzfuBF9OvfFCQoet2bDOvz501RVXqtGTfw46Tvcd+e96pxpPBZMp86covNOKo+jYPLDw4lXTSyYHnjgAcMP/fHHH1eCiaNrGlMJqoGG/y6fOU7hJwo0tJCqZQEBH38fWkVVUh/99RRQVOeUpMvIpN93ZloycohG5phZWRzoMTgAPvRBdChyqCw3OQP52YkoyMjDhYOn4H1wE7znToM/7ZN5hwQgtH4ThFaro++6RL+ZYeAV0sCBA9W4LDxYMPGzwqufpk2bYs6cOQbBtGjRIsTHx6N58+bYsGGDymfho3+u2rVrBw6xbpzeffddtSLjvEGDBqlQ6vy86oMM/v777yrcunEbOQZkj8mNv4Ie3buhOr0l/vL7VOzcvVtReIdp5VKTftycetISn4METp8xUwmmmXP/QlhoGAb27a/KPxj/LuYtWYAXX38FO2lVtWjZEpVv/F/r1q0Np3oLa6YX9CkkhILyuSDtXD4b+cSJSxIE7CJAQis3J4voMFo15ZMXlMA8FPjTdz55huE8r1wU+GUhPTgDXkFJyD1K9lLXSTBxuHNeMX300UfglduaNWtMLu3uu+/Ga6+9pgRVhQoV1Cpo1KhRqg6veli4/PXXX9i/f7+i8E6cOIFq1aqZ9FGvXj3DeTC5f+Igg3qhxAWuej4Ng5SRAxFMbryR8xcuwj3DR6AzcdUD+/fDEKIE5hJdsHK17gFgpYTHRz6Kjz/7Hz57+xP8Ou13PDriIaXgwBuy3Qb0wqZtm/HsE0/j7iF34flRz6LvkAFFzthqAEPapC1O8vUjA0s/iZ5aHAzLctu8nEzkEVVNYgmglbU3CugoHz7eXuDoHN753sjzykOebzYKAjLhE5BK4cl9kHhhB6pB9yJWkviw4sGIESOwm14Y+ZtXSMw0PProo4Zp9OnTRwmmxYsXg6k+puG4Hqfly5fj6aefBr8Y9urVCzfddBOWLVuGjcR+2Et+5FLNPBUnmq55X2XlXASTG+/kT7/8grrkK2r+7FmKk+ahptGGqXEaevddGP/2O/h08ufYunMbvv/8a1W8a99uJZT++P5X3HnL7Spv74F9xk1L9Ljb3SNpPNGVKVHQPWywjKREpJHn9QzaR8pIS0RWegrReGkqkrCfL/3BpXcXTnm0YkolA+GCTBJWdJxLK6W8PBJTpJXq7ecD79xgFFxip8VhaD107HXxlcdKCCyUeA+2b9++at68D2uceDXDikWzZ89We0csqCpW1Gk9zpw5U9F6TJ3zfhOnefPmGTeX42IgIIKpGOAV1TQwIBAJ589jLW2aVqBgc/MWLsSfpKUUGhqKM2fPIo7UafnDq6lXxr+G1s1boXmTZqpbfz+d89jlq1agZbMWav9pzGsvqrKDRw4pVdOixpdyQUArAllZmUi7cgWZpI3HAigzPUnZQmVnpqkQ97b6y+V2ZNKQQ2FDcjKzSenBhwRWtk4oFWSRYg8pQ/iS1/08kk5eQYiu1Q697h+tKDRbfbozX79y4b0iVlg4d+4c3n//fTUkU3Ks+cqMxpAhQ9S+EFN9kydPNkyJ96Mukebs1q1b1f4xr5ZY4YGF2Xl65iUVDwERTHbw4yV2fr62EBa8McxtmE577pmnsXHzZgy45TY1Ssf27fHuWxPw4n9fxesT3sI3k75Q+fcPG4Z5CxZi5AOPGGbTtFETjHrkCXz+7WR8+cM3Kp/3nH6bPhWvTxyPu2+7U+UZ03bGx/qO9Hn6b32+fJdnBAqQQn9U05JYAOlWP9kkULKz00hF3Hb4Gh+iofwCdAa+gcERuHruNJJJ1Tn9aiJyMzMUoKz/wHZ3BXm0UvImweSVTOvsHAR4B9DKghQj/CNQo1UvUlfXsQDFuQv8fDpLg9WtW1dp1bHywbRp09Q0eM+J1bu/+OIL9OvXT9F3jRo1AptdsBAy3rt95JFHsGPHDjz44IOqbatWrfDiiy+ClR0++eQTpSLOBY48d47UUYOUo/9EXdzOzX7+LfqRTfrMTg3bRU8+NhITJ4xXb14J5y8gIjxMGfBxC7ZRiiCP0f7+Or75p19+xehnn8PlI+cQFRll0mlSchJYuy8utqqiDJgbv5J4FTHRlSFhL0ygkhMzBDKSiXqjgId66i2bqLfsa9SbWVXDqRfRUv4kfPyDQxAYEo7AsAgEhUcihFb8uSRwjm7eiEvHjyLt0kXkG8VRys/LJvFDn7xMeAf4IDP7PAmnqwjMDyLKLghePsEICKuC+t37o1G7bobxiqMufvvttzu94mLhceONNyI1NVV9KleurJ4vXikl0cpPT9mx7RLvIbFKuF7xQT95Lrt48aJiQJgF4XSFVptsqKtfkenrltdvURd3w52n9zGne82/plrNdEC1OFMLeNbE43Ts+HGcOn0GE9//AI89+KiFUOI6LMD4o0/8g2ehJEkQYAScpd78KaaZXzCtfoLDlAAKZuETWQFBEZEmwJ47egBHN63H1VOnSMAlmpT5BQaRxh3NIScNObm6lVYeuUHKyb+EQMr3ziSVcN8IePmSoAuPRsMe/VCveXuTPq7XiX6lxQJFL1R4Lvy86oXSli1bsHr1aiVsmNIzT+xpxVjDjstZe09S8RGQFZMdDK/m+iA1U5uKNOsi5eWlIYRUQ4tSBf3q228x9uX/KgWJf+cuRWzlKnZmY1kkKyZLTMpmjhXqLZ2oN7Idcpx6C9etfCKiEBbNL0a2FVmObl6PcwcPIJk8j+Rco+j0uPLqKap6DWTRb/zKxZMkrK6qolyKLA3/RPgFUZDMVD94Z0XSSolWET5BCIypiiZd+6IGeZ4wT8VZMbGbH2YQnEmOuB9q1kw3X7ZVGj58uDPDlPs2zq6YRDDZ+ekU1/ODna5VEVMBSUnJiIqKRKgPvVlKBNuiICvT5a6m3gKCHFPvT0+6ShTdJlw8fsSCovOmVUFopcqoVKs2qjVrin2b/8W5w3sMe0o+pGUH3yRSAT+ljCJzSdvOvyAGeaQK7k0rqrC4WmjSpRdiqls3oi2OYHL3j4FpPl5BsRcISc4h4KxgEuUH5/B2SSumAipUMN1TcknH0onHIpCdnYnUy9q13hyl3hy98ASi6E7v2k0UHa96LCm68CqxiCX/jrXbdsTFsyewd91i7J/yDyn2kHYDpYCQMASEswr4YWTnpCI3yRdemXEICaiMrIxk+IZFIaJqPJrd0BdR0bGOTsuj6hlTfB41sXIwGRFM5eAmyyWWNAIlS705enWOUHTVmjVHldr1VJdH927B4l8+QeK5U4YhQitEIyquIrIy95DH/MMq3zs5BiF50bRyCiCNvHQExMQhvHIcWt84GEEu8jximIAclAsERDCVi9ssF+kOBK4X9ebotaTT/o+i6I6xFt0FEy06puhCiKKLJoquTtt2tP9UuHLfvX4pTu7eRLGdLhqGioqtgVot2uHqxTU4c3K2yvenPSSf1NrkpDUcWQUptLuagxCKExUWXRUd+1kqCxg6kwNBoAgEXLbHlJKpW+IXMZ5JcYB3Dvy9tGm+ZRfkIYts9LSmEPJ4rHUPJyuXXPl7aZPdefmknVSQrnV6CM4jS/hrFuSONk7KT0c2Yagl+fhkIySU/JZpTIEBtcgmQxsWGofwyOrFot6Crtn8hETAltabqy9aC0VnPvbmf2bgzMFdyEpLUUUsvCrVbIAmnXrj0vl1OLbnL0XbcWFEYCt4JUWSZ4ccZGalIp8MwgNJpTySBFO7XoPMu7Z5zjZ/eg05m5WkoNQiwH/TnLHTctlfGrIn1Zy8KeYLNAomb9Im8irQxSPSMqCXl20tJFv9ePlQG232tSRcvOjNVJuw5fHVzdPoz86LxtL6UDMOWtvo8HHiBtsC1uPyXUi9kdZaKJkDcDyjkkqOUXTNiKKrbzGlpCsJ2LlmIS4cOajcB3EF38BgxNZtjDa9bsHl8/uwZ8PHBtouMqo+gvLqI/Us70vlkGp4LrxJxdyfvJxUjq+PFt37WoxhL0Pry5i9vqSs7CDgMsFUdiCRKymrCCjqjX29kSYk+3rTbHAaTAanZFMWRJ+QqIoUUM8xrTdX4+koRVebKLpgI4rOeB5njuzD/k0rcPmUbp+Iy4IorHr1Rq3QstsAUkVPxY61X+DMiX9VswC/MFSrMxDpJ3KQelHncifX1xs+ITq7p2oNW5gYzhqPJceCgFYERDBpRUzqezQC5tRbFvl6y0pnR6P2fb0prbfrQL05CmbC0YOkRbfLqhadL6llRxhp0dnrc/+21Ti+Yz2SL54zVAuvHEv7R53RoGVnlbdv+1QT2i6uZg9UjuqO4xvXIJdCgjPFh2Dy6HCNhKjZor3HGM4aLkoOSjUCIpg8+PbtIW/iA+4djDm/zELzxk09eKYlPbXSTb05ilZxKDrzMbavmodTe7eTavgVQ1HFGnXRsF0PxNVupPLOndyCA1t/NqHtGrUdjkt7z+DwqmWqTgC5zCoI8ENmZjrRz96oT+6FrBnOGgYpZQcc6I/95LGncA4IKOn6ICCC6frg7tCo2TnZOH3uDG0ua1dWcGgAD69kTL1lXguz4JivtxDy9RaKQA+h3hyFmb0oHCFD10ukRZdqVYsumrTo6pBtkW2KznisTFolblv+t6lBLEVBjqnTEM0790N4BZ1rqxyi7bavnWxC29VqOgQ169yEHfNmGKi78KrVke1ToOyefPwCyHC2JxnO1jUestQfcxy006dPk+Atn8+cp9xAEUyecieuzYO1lC6T482KpOFkK7EbFhZaCLG/wZ6YmIiICPIo4Yxmiq3BXZzP1FsaGZzymzw7Gy0r1JujMLmKojMe7+I5Mohdu5g8ORwyMYit1qA52txoqsa9b/sfRNvNMmjbVSXarlWX0Ug4uA8bfv/OQN1VImWIK4nnkZ1GdkpBYWQ424cMZ6saD1tqj9Uzd/mywUeetQtRzxwJraLcjLET16ioKI9+5qxdn6fliWDykDuSQT7JXhr/X0yZ9itSUlNQuVI0Hrz3fpPZJVw4j8fGPoW5i+er/N69eiM6JlpF1vzqq69UPBiOqvnBBx/g1VdfVa762XqdXfFbc0Jp0rmbT1LIG3UarQgyyXNzRhrH+CFP1874emOtt4qk9cb7HKU0OUbRNSUtugaarvDovi04vGWVhUFsjabt0bRDL5O+bNF2MXGtsGfJXCQc2K3qB5Jj1+gmzXHqwA7k0wtRcERFMpwdRIazOm/aJp2WspOMjAywH7yffvoJKeTBnz2MP/TQQyZXkZCQgJEjR2LOnDkqnyPYxsbGKo/kf/zxB2bNmoX7778f33zzjYpoe4HCgLAfPo7ddN9995n0JSeOIyCCyXGs3FrzudfG4ptfvsfbr7yJrh27YPX6NXjl7f8zjMl+9frcOQCXrlzC719OQTT9cX5n0gfgeDLslp9TFm1Ms3+vN954AxMmTFAPCAc/e+qpp1SUTne7WMlIuRZmgbTeik290R/EAAq9UBaSqyk6c0x2byCD2F2WBrF123RDrUatTarbou0atrgTmanJ2PDHDwbqrmKt+oiiCMwHN61SfYSRa6GO/YofR8lkQtfx5JlnnsHXX3+Nd955B926dcOqVavw8ssvG2bEzxyHxuBYTFOnTkV0dDTee+89fP/994YQ6/zMsVAbM2YMPvvsM4SHh2PcuHEYRjHWBg8ebAh1Y+hUDhxCQASTQzC5t9JVotxYKD372NN4cfQYNViXdp2QTm90Ez5+R50vW70ce4leWTj1b/S5obfKa9i6GRq20G1cG8+QH57evXV1+OEaMWIETlHYAg56VtxU3qk3R/FLOHqItOh2FluLzt54m5eSQewBI4NYsp2KrtUAjckgNjo23qIp03bHibbLIt92nPS0nR/tF53asx1H1y43UHc123VGjo+fQShpNZy1GNzDMphyY6H03HPP4aWXXlKz69KlC9LT0zF+/Hh1vnTpUuzduxeLFi0yhF9vT8E+q1LUafP05ZdfYuDAgSqbn7lBgwbhOIW10XsoN68v5/YREMFkH58SKT167Jga56aeOmGiH7T/jTcZBNOufXtUdtcOXfTFiu9u27at4Vx/0KJFC/0hYmJi1LGz4QG4cQ7tZx1cNRs5WenawyyUAerNAGYRB+6i6IyHTb5yngxiF+C8NYPYnoPhH2i5ykwgbbv920jb7qrOZomNZBu1GY6Yaq1U1+bUXZM+N+M07U+d27dNlVeOr0eGszcZT6PUHx8+rMPipptMr2vAgAEGwbSL1PM58WpKn5h16NxZp1avz+Nv4+eQqT5OrEghyTkERDA5h1uJtDK2iucNWk7mXhuYJzffkPX3pyhtLkx+5G4mhzS82P2MLsKpFa23MkS9OQqdQxRdzWtadBQHqThJGcRuJoPYk0YGseFkENtYZxBrrW97tB3XZ+rOWOuOqbuWA4dgx7/kCeLaOHFkONvYKOKstXHKUp4jzxyvqsxpcVc/c2UJU2euRQSTM6i5uE3tWrVUj0tXrTDQdJyxbNVyw0iN6jVUxyvWrMSA3v3UMW+0btiwwbDHZKjshoOazTshNKqSRYRTNwzl0V2WBEVnDIAyiN1JBrEXzhmylUFsczKIbWX55q6vZJ22G0Uhv3WxhaxRd7XadsHmJX/jasJJ1U1ZNpytW7euukam6/r2LXSjxOf6pKe+ly9fbqDpWBmC96JYCUKS+xAQweQ+bB3uOSoyEo8Oewjvf/ERqsbEomfXHtiwdSP++844Qx839eyD+hSO4OFnH8PHb76PoKAgvPHR24Zydx9UimcnrqVXE644+JQERWc+P0cMYs3b8HlRtB3XsUbdhVeOwfr505Fy+XyZNJzl6zZOHAKdte14P5b3jFiBaP369XjllVcM1djQtn79+kpT75NPPlHPnH7/yVBJDtyCgAgmF8HKFJv6kNdXPe3maNdMH3z45nvII7ru2f8ba2j22IhH8NWUb5VNBEfS/GfGAjw+dhTue/IBVWf40GGoVqOaYTy9vZL+29ARHVjLMy6X40IE2LD3yOaNZOh6hAxdL5FT3lxDoS5cRDR53dZRdCHFpOgMHdOBbYPYBmQQ299gEGvcRn9cFG3H9bKIuttuZDCrp+7SKX/d31PBPvjYcLYxGc5WKQWGs/pnTo+Blm9+5j7++GOwogJr5+nT448/DlZk4OeFn7lly5bhsccew9ChQ1WVhx9+GLWI4dA/4/rnSv+t74e/reUZl8uxbQRcFvYiNUt72ItAn3z4avQunosCZDrhXTwkrfCPi204TEuy8/2Rm+9tmmnjrOMN7bB7j26z1EYVm9m//PA97ul3D4XloA1TUjS4QDY/vHIy5ruTyPh03eb1aN+6HcJDw1RfKd5ZaNa2udIAYhVxR5KfXx6CgtMcqWpSJyiwDj1oZXfFVNIUnTG4OoPYJWQQe9DEIDaODGLbmhnEGrfTH1un7Z4k2q7Qyawt6u7yhTPYvXIRsjNKn+EsK/ns3LlTD4Om75kzZ+K2225TbVhJgWlxXjmZPHNkc7d27Vp06NBBqYFzZRY2NWvWxJ133omPPvpI05hS2XEEZMXkOFbuq2kU7sKfFA2qxcZZjEXPAwbedyvuGDQEE156XT1A73/zKc6dO4ebb77Zor5kFI2AfYouAlHVayCuWTPEajR0LXpkXY1j+7bi0JaVVgxi25FB7I1FduMIbcedWKPuImOq4ixp3u1bv6zMGc4WCRxVMFYiYsWFatWqWTRjIcRaeiyE3nrrLfXMMaXHLovuuOMOi/qS4ToERDC5CMuFsxfTaieH1nM5RP1oW5Gw26CiUnhYOOb9+hdGv/IsGnbROZdkzSB+a2vXrl1RzaWcEMhIScKRTRuKoOhqK190IRQCwl3JmkFsZGx11GvT3cIg1tocHKHtuJ0t6o7LTuzfYbBRKq2GsytWrHBaJTuS9nWLSmwsO3/+fIwaNUrtNXF99urw3XffWVUZL6o/KXccAaHy7GClhcrTd6MTTDoDRn2eI98h+eTTzoGK/KZ3JfGqjgOPCiJaM8uBVoVVyhuVZ6DoTp+kOEwc3K4wFYaLqE/CqFNhgZuOLA1ifRFdsx4ad+5j1SDW2jQcoe24nS3qjssObtuIE7s38qHmiLOqUTn7Tz1zZJDLKyhWmpDkfgRkxeR+jF06Aj8cegev5PjHpX2Xlc6Obt6Acwf3IznhHNlfZZhcFgf5czdFZzygziB2IRnEHjCKEBtEEWKboDUZxAZYMYg1bq8/dpS24/qm1F0UmvQZBKbuOO3e8C9ho9sLLYuGs+oiXfyfeuYqVnRxr9KdPQREMNlDR8pKBQIZpFV2ZOP6a+EiLtrQonM/RWcM1pmj+3CAIsRe0mAQa9xef+wobcf17VF3XF6eDWf5+iWVHgREMJWeeyUzNULAkyg6o2nhwLY1OLZznRWD2E5kEFvoTsq4ja1jHW33F/m2S1FVdL7tTLXt9G05CODRNaa+7thgVp82/0OGs+fKvuGs/nrlu3Qj4DLBlJ6jXV08P+UKwoO0TSE5h0JlB+rUpbVAH5icSXs4juziFPaadqUA3uTFW0tKT7qKwHDtWBT4hJK7H23q2JnJafCO0OZ+KDs7GcGh2trorp9dImmbnxbcHKnrSRSd+XytGcRWogixDYwixJq3sXVuSdvVI992Iwy+7czb2aPu8gvysXHBjGuGs14UcbZ7mYo4a46FnJcNBLRJBTvXnJSp3U4otCAbSLtqp1fLIl8fb5zNKgwPbVnDek7FSxQKusB6mc3cwFjaMKc5akje5JE5k8I/aE0RkdGsw6qpWXB4CO0y5WhqExgYAW8v7YLzetgwmVB0l4miyy38jRUaupYsRWcMdhb5D9xqHiGWDFRj6pBBbBeOEKtzoGvcxt5xTjZFkl1jGUmWQ1JYS0VRd2w4u23pnFJnOGvtWiWvfCHgMsFUvmCTq3UXAvYpukBEVKmKWHITUxJadLau0bZBbDMyiL3dVjO7+ftVJNlC2i6uZg+07Ey0nX+hkaxxB6bUnTdqtusCY+quNBvOGl+nHJdPBEQwlc/77lFXXUjRJZAWXbrJ3ILC9Fp0TRFbR+fI1qRCCZ5YNYiNikaNZo4ZxFqbqlbajvvY8w9FmN2/W3UXGGmqdceZbDi7nwxn2Rt8cDhFnO1dNiLOqguW/8oFAiKYysVt9qyL9HSKzhwtZRC7myLEXrloKNJiEGtoZHSglbbjphbUXU0KU3HzEKNey4bhrMkFyUm5REAEUym67T1u64t+vfripWtRbkvR1FFI0Z2ifTvTfUXfQD1FV48ous4ec1mbl86kCLE7kZWm04rz5gixJAy0GMRauxgL2i6eaLsutmk77sOYuvOifdZaZtQd1xHDWUbB8dS9e3cVvsI4nLrjraWmOxEQweROdF3c95mEs0g0817g4iFc2t3RLRuQcGA/kiiGjTWKLpJ80VVrdv0pOuOLTr5yATvXcoRYMojN1nnVYA8RbBDbigxiAx00iDXuU39slbZrTdp21XWRZPX1zL+Lou64vhjOmqNW9PmZM2eQmKhdUanonqVGcREQwVRcBK9T+8TkJKR7Z8M/Iug6zcByWI6Ielhv6GpNi64ihYuodf206CxnXJhj2yC2JVp2G1hY0YmjnOw00rabhDMn/lWtA/zCUKvpENjSttMPoaPuZiL1YoLKqmiFuuMCU8PZ5hRxtru+C/l2EAEWUOzhwRG/lQ52KdWKgYAIpmKAdz2aHjt1At1v6Y01m9ap4W+44QZ8/fXXYKeU7HBy9OjR2L59u3I2yRX27NmDwYMHY86cOWjcuLHLp5xw7DBO79yBq6dtUHTkCie2PlF07TyHojMG4cC2tWQQu9YlBrHG/eqPnaHtuK0j1B3XE8NZRsH5dOzYMXTt2hVr1qxRnfTp0wdTp05VPvHGjBmDbdu2wTiqLcdqGjduHM6fP+/7+HLdAAAswklEQVT8oNKySAREMBUJkWdV+HPOTHAAwbdeeQP/blmDcRPewPfff4/nnntOeVpOTU1Vwc/0s84l2x/OyyENLVel0kjRmV/79lXz6Y//NmQkF9rEVSSD2IZOGMSa983nztJ23HYvad2ds6N1x3UoHCU2zhfDWcaiOGn69Ong4IDvvPOOir300ksv4YsvvsBrr72GtLQ0C6ovMzNTxW4qzpjStmgERDAVjZFH1WjdrCW+eOcTRTu06tQWf8ycjn379rl1jpmpaTi0fQn5ojuGVFsUXc1rFF2k53pfziaD2M1kEJtweA9yrzl35YitzhrEWgPdOm13G9F2d1mrbpLnKHVnYTjbmSLOklCVpB2B1q1bY9KkSep56tatG3777Tfs2rVLe0fSwqUIiGByKZzu76xL+87qIdKPxAHO+C3OnYldOR1dv5qG0EXzVVp0Hk7RGeOhDGLXUYTYY4coQqzOe0RASBjiGjhvEGvcv/7YWdqO25/au4N83S1DblYWlNYd+bljzTvzpDOcpdhfGWkICApDsxv6ICq6qnk1OXcQAabxeG9Jn+Lj493+POnHkm/bCIhgso2NR5YEBgRomhdTecVNAaHBCKLAeZFx1UmLrgkZujYqbpcl0t4dBrHWJq6j7X5B4tVDqjgyinzbOaBtp+/LhLqLIIPZvoVhKvR1+FsMZ43RcM1xIJkqaEkchl2S+xEQweR+jEtsBD8/PzXW1atXlTIEn+zcudMl4/d56j/Uj27F5JIO3djJ7g3LcJIC4ZkbxNalCLG1G7V22cjFoe14Eo5Sd1z3xP6dOLRpJUVIpiiq0bHo2M8510fclyTHEOCQ6xxGnQMF6ldVmzdvdqyx1CoWAiKYigWfZzWuXbu2mtB7772HJ554AqxxNGHCBM+apBtnY90gliPE9nU4Qqyj07NO2z1Bvu1CHOrCUeqOOxPDWYcgdXmlhg0bKkWHiRMnYuDAgViwYAFYWUKS+xEQweR+jA0j8JsXf6yl/Px8w1uZtXJvb91qRf/mpq+jz+fzRo0aKXXx//3vf5g5cyZCQ0OVdtGLL75ot299X6Xx250GsdbwOH9yC/Ztc5624z4dpe64rhjOMgrWk73nyXqLwlz9c2PveRo2bBhmzZqFV155RX3Y3OKNN95Q6uKFPcmROxDwoptr/S+lxtEOUVgJrSmu4BKCC9I0NUsmdywnfbVPuf5R7WEvUijsRVaBNgNWL59M2mAv9KlmfHG9b7sD+w4eNM5y+HjGd7/j1v6DTeqnemch08tSDTwjIwNM58XGxloIJD+/AgSHaA97EeBfhcb2HCqPDWL3U4TYyxYRYotvEGsC8rWT4tJ23I0W6o7ri+Eso2A7tWjRwmmqml/cbrvtNtudG5WwzRILsuhoCk0jqUQQkBVTicBc/EG0vD8EBQWBP2UxHdhOBrE7zAxiac+lZouOaNiqq1suubi0HU/qNGndHXFA605/AWI4q0fCPd9anqeYGG1xtdwz4/LVqwimErzfM376Htk2DF2jw+MtVjfGU4uMiDA+LXfHVg1iq18ziHWTluD5k1uJtvvZTNtuOPm206ZAoYW6Mzecrde2O+IbNit399uRC16xYoUyKnekrnkd9pQiyXMREMFUgvcmIjzc5mgxkZXtCiabDctwQXZWOrYsm41zh/eSQayOKmaD2Mp16qsIsREVmF50fXIFbcezsqTu6lGYCtvadGI4q+1eRkVFaWsgtUsNAiKYSs2tKj8T1RnE/kMGsQcNBrH+ZBBbrT4ZxPa2/YfdFQhZ0nY3XAtJ4Zi2nX4OWqm7yxfOYvfKRcpw1j8oFM1v6CuGs3ow5bvcISCCqdzdcs+9YDaIPbxlFa6eO2mYZGgxI8QaOiri4Pwpou22Fp+242G0UHdc39Jw9mYEkSCWJAiUVwREMJXXO+9B123TILZ1N9Ru3MatM3UVbceT1ErdcRsxnGUUJAkCpgi4TDBdSrNUWzYdyvIsOu8ygn0yLAvs5GR45yIlONhODRtFOawiXegTy0Ytk2w/5MAn0va+kEnlayes7RMQVt1akd08b38/8pHmY7eOeWFBKvlVy9N2TQUFbC/lb96VA+faVfSL6nTLspk4TR4NTCPEuscg1tpcXEXbcd9aqTtuI4azjIIkQcASAZcJprx87X+4vH3JhU5+quWs7OT4egcgn/64ak/0B1yjyZZ3gD/yjRw8OjKmD7kx8fLRPj8llDSO5c2CLE+bLzxvb2dvuWtsmHQGsQspQux+l0eIdeT+cB1X0nbcnwV11+dmRFaJ4yKbac+Gf3H24C5VXjm+Llp072ezrhQIAuUNAWf/SpU3nOR6i4mAVYNYclhavVGrYkeIdXRq1mm7Wykkxd2OdmFSzxnqjjsQw1kTGOVEELBAQASTBSSS4UoErodBrLX5u5K24/6doe643aZ//kbiNeWOmi3ao17z9pwtSRAQBIwQEMFkBIYcug6B7asW4BRp2WUkGUWIdbNBrLXZu5q24zEsqLu+RN3F2KfulOHsAoo4e+m8slcTw1lrd0vyBAEdAiKY5JfgMgSsG8T6k0FsA7caxFq7AKu0XROi7Vo6R9vxGFmpKdg+bwZSLyaoISvWtG8wq5+XueFso049EUv7SpIEAUHAOgIimKzj4vG5KSkpSExJoiimgVY9RnCAQI5syx7G3Z0uJpzAnrX/UOj1A2QQq3MQ6x+sixDbzs0Gsdaubf+OP3Bs91/IyklRxXHxzhnJGvftLHV3hQxnd4nhrDGULj9mTdgrV66A4yeFhVm3/0pLSwPHK+M6kjwfAdeoWnn+dZaZGe7ZuwftO3dEeMVI1KgZjyZNmqgQF/oLZK/iHIupatWq4PhMN910E7Zu3aovdun38f3bsOSXT7H8589w4cheJZTYILZxtwG49anXUdJCiWm7FbOfxX7yb8dCiSPJdrrxTbTrOdbhOEnWAGLq7sCyBSrseSApbLS+7T6rYc/N2549cQjbl81R3hyCwyuiff8h4s3BHKRinrOX8CpVqqBSpUoIJ5df7HF827Zthl537dqFTp06qRe0AIr+PHjwYFy8aN37v6GRHFx3BFwW9mL1sUTNF9Pc5zTC869qanfZzx/7A7TZ7vAA7Y6SFZNGdfHsSvHIDdJmx+RNYSX8grSriwf6k22WA+rinbp1UW+Hkz+fpKJQvPfB+1i0aBH279+votbyg8du+sePH68exo8//lg9qKtWrUJcXBy9NXpR2AtNkKvK/n4V6VuH+/U0iLU2cx1tNxlnTqxQxQF+YahVTNqOO3KWuuO2YjjLKLg3JScnI4KcG99yyy14+eWXkZSUpOKRcbj0HTt2qOegXr166Ny5syq/fPky/vOf/6By5crYtGmTCmXh3hlK784iIFSes8hdp3YXLlxQAqgprZSCQoPxwQcfqDdCpu3WrFmDjRs3YuHChWjdWucBu2XLlmjevDmmTp2K559/vliztmkQ24kixFaNL1bfzjbev2Ma0XazXErb8VzMqbuabbqgdvsuDk3z0LaNOE6h3TlFxsWjXa9BDrWTStoQSE3V2UByWAr+nfOK6Oeffwa/hDG9N3nyZNXhjBkzEBKiexvj1VWXLl1UnRtuuEHbgFK7xBAQwVRiULtmoNf/bxxGPHg/YqrFomPHjujWrZsKeMbU3Zw5c9Qg/Paoj9DJGfwAF4fO273+XxzbupkMYrNV/76BQYit2wStbhiEwGD372GpQc3+c4e2nX4IC607Bwxm9W33bCTD2QO71KkYzupRcc83/+ZHjhyJr7/+Wn0GDRqEG2+8EQ888IDad+XfPO/F9u7d2zCBvDzdHuiWLVsggskAi8cdCJVn55Z4IpXH0z1z9gwWLV6MJcv+USshzvvrr78UfTFu3DgVBtqHvUIYJY5me8cddzhN5c376jP40sZxSRrEGk3fcOgu2o4HKA51x+3FcJZRKPm0c+dOLFmyBEuXLsWCBQsUVcd7Sw899JB6JkaNGmUxKd536t69u0W+ZHgGArJi8oz74NAs0tPTMebFsRg29D489MCDuPOuO/HSSy8pGoMfSH5b5NSzZ0+1CczHrJ335ptvKkUIPnc2NenaD/Vbdna2uUvauYu248kVh7rj9puWzkHi2RN8iJpkNFuPjGcluRcBFj5M173++uuKpmaqevr06bjrrrsUrc2KECtXrlT7TsHX/GueOnUKEyZMwMCBA907Oem9WAiIYCoWfCXbmB8uXin9Sw/b5M+/QFTFCurB41nUqVMHXbt2RYMGDfDII49g4sSJiI6Oxh9//IFvvvkGjz76aLEmW79lp2K1L05jS9quLhq1okiyNdoUp1tDWwvqrjcZzMbaN5jVN85HATYu+FMMZ/WAlOA3R6FlwcRKDa+88gpY6WHt2rVqBnXr1lX7rG+//bYSVK+++qqKdstC6cyZM/jiiy9KcKYylFYERDBpRew61//zj2kYdv8I3HBjT8NMhg8fjqFDh8LX1xe///670jy69957VTkrPkyaNAnVq2v3eG4Y4DoduJO240syp+4qkMFsKzsRZs1hEMNZc0RK9px/07/99hueeeYZTJs2TQ3Odkz/+9//0KyZLhz9Cgq/zpQeU3ec+vfvjx9++EE9KypD/vNIBGSPyc5t8dQ9Jp7ypUuXcP7SBYRFhCMoKMjiKjIyMsBGhWzfYZxcoS5u3J+7jt1J2/Gci0vdmRvONqOIsxWiq7oLDunXDgJMV7O2an5+vrJp4hc088QGuGxga8sA17y+nF9fBCzv4PWdj4zuIAIscAKCA5GZnWW1BQsrawLLamUPyjx/ahtFkp2CxKuH1Kwio+qiIdF2VVxE23GnFtSdBq07bs+Gs/vXLUNeTg7YcLZ174EUcVabvRv3I8k1CLAgYg09e6lChQr2iqXMwxAQweRhN6S8TsfdtB3jakHdxRN1N+h2TZDrDGfJTob+hVWqgo7979DUXioLAoJA0QiIYCoaI6nhZgTcTdvx9ItL3XEfYjjLKEgSBNyPgAgm92MsI9hAoCRoOx66uNQd97Fn40oynN3JhxDDWQWD/CcIuA0BEUxug1Y6toWAJW0XSr7tbitWSAprY2WRx4vt8/40hKmo4AR1x/2K4aw1dCVPEHAfAiKY3Iet9GwFgZKg7XhYV1B33I8YzjIKkgSBkkXAZYIpwFd7BI28U9uB0ABNV3whKwEFtZywqo+MgDf905TycuEfrA2ifGrjQ2qpmpM3ee52wLu4cb/sqJIdV2pJBQVZNIwzMWkKaBidd3Et4+nrlhRtx+NZUHekNRcZW00/FYe+2T/8xgXTxXDWIbSkkiDgWgS0/dW1M7a/j/Y/WmHe5BT0xCY7vVoWVahcG8dzdF6FLUtt5/jENoK3lzbBFEKW5GSJZ7tTqyXO/NGnjvjvvsbENkwsnLQl9rJMuGtO2u8vD5GTnY7tayYZhaRwD23HY2WlEXU3t/jUXXpaMrb9MwfpyVfpJSMAEnGW0ZUkCJQcAlr/6pbczGSkUo9ASdF2DJSrqDsLw9nuZDhb2b6NTKm/UXIBgoCHISCCycNuSFmYTknSdoyXK6g77kdnOLucDGezleFsK6IAg8VwlqGRJAiUKAIimEoU7rI9mKLt1hJtd3yFutAAv1DUJG27Ri3vdsuFu4q648mJ4axbbpF0Kgg4hYAIJqdg85xGH374IWbOnKnc/F/PWe3fMZ0iyc40iyT7BPz83RNI0FXUHWMmhrPX85dTvLGHDBkCDp/+7rvvFq8jae1RCIhg8qjboX0y7A8vPPz6+WkradqOEdr7zzyc26+LEhsYEYUmTmjd6ZEWw1k9EqXzOzQ0tFT6hCydaJfcrF3mXXzH2RTNs25ycjp8L+7Q1O48aeVtrdFUUxuu3De0nWatPC+ntPI0T03XQKtyHbVif232tPLYo3JUVJQKM104Kx5Iu1aetzdpKBqpi5c0bcfzdyV1x/0ZG85WbdAcTdpLRFPGpSwk9jiemJho4V2/LFxbebgGbfrT5QGRUnaN77zzDlq1aqVmzeHVOXgax6bhUOocKJAFE8escWVi2u6f6Q8b9pLi4m9A7zu/ddteEs+dqbv1v32jvDh4+XijZvuumh2wGmPAhrMXTh5WWTWbtRehZAxOKTru16+fij/GUx4zZgzuuOMOFdWZvYnz758DaG7btq0UXZFMlREQKq+U/w447lJCQoK6iqysLKSkpGDs2LH49NNPFcX3+uuvgwMJDho0qNixaM6fppAUW36mkBQH1XjuCElh7Xa4krrj9eIGFXE2gdZ/XqjXrhviGza3NqzklQIEkpKSkEqupzhx/LEZM2agS5cuat/14sWLeOyxx/Dcc89h+fLlpeBqZIp6BEQw6ZEoQ98cbnrAgAHqivLy8jB48GAcP37cENVT66Xm5GRgx7rPcfb4v6qpP2nbsW87d2nb6efnaupOZzg7lwxnr4jhrB7kMvg9a9YstVriS+PV0pdfflkGr7JsX5IIpjJ4f9u0aWO4qipVqqjj7Gzt+0r6Tq5cOGQQSkzbtexM2nYB7tG2049prnUX36Yz6hB952wSw1lnkStd7erXr28QSjxzDiDILIKk0oWACKbSdb8cmq2/v5NukWz0HhPXHHE1e6B67Z4ujSRrYziXat3xGGdPHL4WcVYMZ21hXlbyWUtPUulHQART6b+HJXIF7Xo8T+M45y/P0Qm6mrrjcc0NZztQxFn3XoWjVyv1BAFBwBYCIphsISP5JYqAq6k7nvyh7RtxfNdGdR2RcfFo12tQiV6TDCYICALOISCCyTncPKaVF4XK0FN3fMxJ/208SWt5xuXX83jvUjKY3bdLTaG4BrP66zAxnK1RFy1u6Kcvku8yhoD+t63/Nr48a3nG5XLsmQiIga2d+1LaDWytX5prDGyt960t1x3UHc9ADGe13QepLQh4GgKyYvK0O1JO5uMO6o6hM4k4S4az9Vo6EVSynNwDuUxBwFMREMHkqXemDM/Lgrq7kSLMVtUWYdYcHjGcNUdEzgWB0ouACKbSe+9K3czdRd2ZGs76U8TZXoiNr1vq8JEJCwKCgA4BEUzySygRBM6Qr7vDa5Yhl9wmsa+74hrM6ietM5xdjOyMVPgHhaKZRJzVQyPfgkCpRUAEU6m9daVn4hbUXTHCVBhf9TkynN23btm1iLMV0Kr3zRJx1hggORYESikCIphK6Y0rDdPOSk/F9jkzyCP4OTXdCvH1iuUR3PiaxXDWGA05FgTKFgIuUxc/mZihGZmKaccQ4pOvqd2l/HRcCo3S1IYr1z6VBW+NNv/ZQZWQF6ItCF9+fja8vNM1zy/EJ9Kq/ZG9jjK8cpCrET8v7xwEBubZ69Zqmb9fJcr3sVpmLdOCumtNvu46OO/rzngME8PZqmQ4e6MYzhrjI8eCQGlHwGUrJu9rxp1aAPEJqUDR7jK1NEGgVyh8vLQJMx7Ai7xsU1w9bcnbC/l5GhuRjWs+j6U1KdtYjWPR3cvP14aFD11TQYG2NrpLcdyRjwV15wKtOz2cYjirR0K+BYGyi4DLBFPZhUiuzFEE3End8RzEcNbROyH1BIHSjYAIptJ9/zxm9u6k7vgixXDWY261TEQQcDsCIpjcDnHZH8CSuhtABrPVXXbh6yXirMuwlI4EgdKAgAim0nCXPHSOWelp2D73T6RecL3WHV+yueFsQzKcrSqGsx76a5BpCQKuQ0AEk+uwdKin1NRU5JJyRER4uFUtvNzcXGRkZiAsNMxmf1xeUFAArzDXBgS0OaCVAkvqrhNp3XWzUtO5LDGcdQ43aWUdAX5erly5ojzxh4VZf7bS0tLg5+dn8NZvrSfuo0IFUtqS5FYEvN3aeznuPI+Ez8IlS/DoqNEKhf0HDuLGgTejeoNGqNW4KRq0bI0Zf802IHQl8SqGPfEgAuLCEVknBh1v6oaN2zYbym+8rR/uGTkcvW8fgND4igirWQm9broRBw8eVHUWLlyIN998E2fPnjW0cdcBU3f7ly1QXhw4TEXrW+51qVBiw9nty+Yqbw7B4RXQrv8QVKhc1V2XI/2WMQRYwEyePBnjx49XVzZz5kxUqVIFlSpVQji9ELZo0QLbtm0zXPWuXbvQqVMncPTbgIAADB48GBcvXlTlixcvVm3ef/999V2xYkX1zc8aP+Ochg8fjr///ttwrjLlv2IhIIKpWPBZNs7IyMCU335H227d8fSYF9C+TRtVafSYsUhOTsHsaVOxZM5stGnVCo88NQqX6Q2MVb5vHX4HNmzZiFk/TcPSmQvoIQlD3zsG4tTZ06r9lcQrmD57Bj04/lg8fS7+/P53nCEh1Lt3b+o3GfXr18fhw4fRtGlTjBo1Cnv27LGcXDFzmLrbMO0nQ+wkNpjtMvwxl+4nseHsnpWLlDeHsEpV0PmWoeLNoZj3rbw0P3fuHF5//XXExsbi22+/VcKGn43bb79dHa9fvx6LFi1CZmYmHnjgAQXL+fPn0aVLF0RERGDFihWYMWOGElr9+vVTz2V2djZSUlLwwgsv4N1338XKlSvxyCOPYNy4cWBhxaljx4549NFH1TP4zTffID1dux2j6kj+MyAgVJ4BiuIdXLx0ET/88h0+m/wx4qrG4uXnn8ctg25GgL+Obrt0+RLRdxFo1KABounN7ZP3JmLazA7IIt9xq9auxdqN67Bu4Uq0b9VWTaRNi9ao3qIufpr6M1597mWVV7lSNGb++Af1GaDOq9WNR8funTFt2jT1sEyZMkUJp6+++grdunVDr1698NRTT6FHjx5WaUMtV6yj7lYU+rpr7VrqjucihrNa7ojU1SOwd+9efPrpp/j6668xcOBAzJ492/Cb1zMIMTExaNmypVoR/fzzz1i1apWiw3llxYkFUkhIiDrm1RULK66jT5MmTcITTzyhTvnZOn36NN5++22MHTtWPWMsmPg5fOedd/A8PftjxozB448/jsqVK+u7kG8NCMiKSQNYtqqOe+tV1GtRE+s2rMGUb6Zg3bKluOv2IQahxO1eeu457CDKoH6LVuh36xD88PMv6NenN6rS293efftV10+/9Cy6DOihPv3uGoSU1BRs2LrJMOzNfQcahBJnNm3SFNHR0di3b5+hTt26ddWb3IEDB9ChQwfcf//96Ny5M3bu3Gmoo/Vg/4qVRN0tdBt1x/Nhw1l9GPTKFHFWvDlovUvlr35SUhJuvvlmNGnSRNFoTMnNnTsXPXv2NLyIVa1aFSNHjlRCKzAwUNF069atUysmjm67detWtSJi5oHpPP4888wzCswtW7YYQOUVlHEaMGCAanfmzBmVzVGkhw0bht27d4Opw9WrV4OFIQsoSdoRkBWTdswsWmy5thfUsX1nNGvSzPBQGFe8+47b0b1rFyxd8S9W04Px7kcfq8/cP6cjnzZmOd0yYBB8vAvd/tzSfxDiYu3vrfBmLdMN5on59Pbt26Nhw4bYvHkzLl++bF7F4fOGPbpjU8IlhERVcZmvO+PBxXDWGA05dhQBpuQ2bdqkViW8wqlTp47VpswgMHOwhPZ8ly5dqgQPr3ZYkDGNXq1aNdx6660mbZn+a9u2raLJucA8RLuvr+5PJysrGSeu17x5c8VY8HgbN240LpZjBxGQFZODQNmrNmf6Avw1dS42bl6Pes3r4fmXX8GhI0cMTXjfifNO0fJ/2D1348tPP8Gezbof7DzivJne49S3Rx+8MPp59Xnuif/g/MULCA4KNvSzeMUS5OTkGM6PHjuqlB14f0mfWEhNnz4d3bt3V5uyffr0Aa+e+C2yOKlhj35uEUqbls3BhZOH1dRqUsTZJu27F2ea0rYcIcArkhMnTqi9n4kTJ6oVClNpxi9hLHyefPJJpfzAFNv8+fMV5XbhwgWsWbNGKULwymv06NF48cUX1Wfo0KE4evSoifbdsmXLTJBlAcepRo0ahnx+zlgA8ry4bxZM//77r6FcDhxHQAST41jZrMlvST269cSMX2dj7dK1agXTvnsPDH/kURJWmxEUFIRl9AN9euwLWLt+A46fOIkVq1ar/urWro3uXTqjcf1GuOfRYVi4dDG27tyOMa+/hE+++h9aNW9pGPf02TMY9uSDSltv5brVGPHQ/arsnnvuUbQC8+DNmjXDe++9p+gLflCYA2e6r7ipUo1axe3Coj0bziaeOUGudb1Qv113CYNugZBkFIUA03OsyMB0Nu/xLF++XGnfPfvsszh27BgiIyOVhh4Lnh07dqiXtLW0p8uJaW+m+Vi54a677gIrR7Byw8MPP6yoOGYb9InzfvnlF7XKYqWHH3/8UQkxXjlxf0OGDFHsBCs+8DisJcv0oPlKS9+ffNtHwGXexU8naXPGytOqVJCIQI1OXFPJl+g5jR61eayax1LgpdFHanZELHL8Q7m544k8fhcUpCCBtH2+n/Iz/qY3tPXLl2Encc8jRz+NAwcPGfq6/76heHfCeLUXdSUhDY/853EsX71ClbcmgfTMY6Nx3x33qvNWPdujcnQMkpISsWm7jvuuVbMmJn/5paLs+KH86aef8PTTT4NXSd7e1t85fHzzaQPYkvozTMrGQYB/DJVY79NGE5vZGWnJ2PrPPKQnX4aPnz8adupJhrP1bNaXAkFACwKsCs7KECw0WDvv999/V/Qdr5I4sR0TU3msvcqJVzUPPfSQWiXxef/+/fH666+r54r3rAYNGqTaf/LJJ1ysErdlAcWCkfe4WDCxcgTvaUkqPgIimOxgWBzBpO82hzhoP3pA9InVw9PS0kkzr6JaSenzw3wr0rqBvB1kpCOV7DBYA884sWDq0qEzPp/4CRIunFcPXUjlCGR76Thu5rr1vLdxO/Pj6y2YxHDW/I7IubsQYNqb92A58fPBgon3lFjrztqzwsazXN/YAFcvmFjJgQ1rExIS1J6UcXtHnz13XWdZ7LfwL2ZZvDoPuCZjocTTqUg/bv7YSrynZLyvZK1elcq8egEyULjxavygWGvjCXm6iLPLyUYpC2w4KxFnPeGulN056IUSXyE/H0WtZory6MCro5rEUpin0vDsmc/Z089FMHn6Hbo2P3ZRFBgQWEpmaznNE/t34dDmlcp2hA1n2/e/w0XEoOVYkiMIuAoBHx+dlqzsFbkKUcf6EcHkGE7XvdbKOTotoOs+EScmcGjHRhzfqdNCjJSIs04gKE2uFwK838R+9iSVLAIimEoW73I32t5NK3GG3AxxYsPZFjeYGiqWO0DkggUBQaBIBEQwFQmRVHAWgR0rF+ICOWTlVLVBc7FRchZIaScIlDMERDCVsxteUpfLhrNso8SpZtP2qNeqfUkNLeMIAoJAKUfAZYIpN187D5uenoLAEJ2TU0dxTM++Cu/gSEerF9YLZMen2uxwctMyaazwwj4cOMpKzYJ/cKFbIQea6KqQkZWXDdsjW33kZGTBK0TbLczJySTbC50Kra1+rec7fn8l4qx1BCVXEBAEHENA2181O31m5OTbKbVeVCk4jAqyrBfayA0JrIBUOP5HUt+Nd0SkZgPbwIBQ5F/TytH3U9S3Dxnk5uWkFlXNotzLj4UZWzI5nvxDA5FdUKgy7khLf79gskbXfq8cEepiOOvIHZA6goAgUBQCLhNMRQ0k5WUbgasXz2Lnv4tVcD//oBA0636TBPcr27dcrk4QcBsCIpjcBm356djCcPbGmxEcqo0CLT9oyZUKAoJAUQiIYCoKISm3i4Cp4WwMGc7eTjt52vby7A4ghYKAIPD/7d1/TJXXGQfwB5EKbJXSISoFFcGiA5V1BbXID7FTqvzRpuBcAEUjrbURicYFMbRaQpWqWEFEKHZTS9YMNVrnMuzSAs5iZkLTGphDY+toYlRQa7X+QKTnOfbeXC73AC9cem53v29CuPc97/uel8+9h+c95/3xOJ0A/oM4+Ef+ctoCyt6Q45B7yTfONp+ulTcg8o2z019IRlByyE8KO9WTAD+AlVNeYHIcAfSYHOezsLknl8RDI72f8LZZpnMmbpzVqY+67Slw6dIl8vZ2vDZmz7/x57Yt9Jgc5BPjx560trXKFNG97RKnXL9+47q2R6XwjbOmpzn4hUzG0xx6+8BQ7hACso219rGNiRxN16/ra2MOAaZxJxCYfmJ8TiRWIZKMFWwrlDXfv99Ob7yVR95jfMk3+Cly8/GkrOzVXTLVmnax8WwTTZsdRV4BPvSrwFEU+HQQHTx4UBZzYrKNGzfKjLam5Qfjt8w4++PTHPjG2dDI2MGoBtuEQL8Fbou0MaWlpZSXlye3wVmdeajOy8tLJs3kp4GvWrXKdhtrbJR5mIYPHy7TXHCKDM7nxNPRo0dp3bp19I3IRI1pcAUQmAbX17x1Thy4SSQWCw6bTHs/qKTIiGdl2ZsiUeC7O3fSH7PW0Kd/+5hy1+ZQUVkJbdr+jnld04uMlcvp25vf0j+PVNNnH9dRxG+fpWXLlslU0pxe/fz58zJpGad3bhQNzN7TqX8c7JpxFk9zsDcxtjcAAR6S27BhA40ePVomCJwxY4bcWnZ2tszqzMGppqaGcnNzqaioiDgNu/XE7YlTrXPq9Pr6epo2bRpxqvVW0dOaNGmSzIAbEBBAS5YsoS+/fPQMSOtt4P3ABXCOaeCGPW7h7H+bqfS9cvqTyGY7V2SW/XDfPooWqdT5MfrcAEp2l9Hry1+lnDXZ4vZaF4qNipHJAjlTrfV0pfUKPSFuFA6bFCqy2Y6g4neLaPpf/0L37t2j8SJF+/79++ncuXNUVlZGM2fOpNmzZ9OKFSto1qxZA0rxfEccgf67plpknL2GjLPWHwreaxdoamqSGWvLy8tp/vz5dOTIEYqLi5Pf+Rs3btD27duJU62vX79e7mtsbCzxyAWXWU+cTJDTsYeFhZGvr69sSzExMXT37l2Ziv3QoUMyOHFgmzp1Ks2dO5dWr14ts0YjNYa1Zv/fo8fUf7se17x58yYlp6RSZHS0PG90qq6Wqio/oJiZUeYg8fXFR8+S+118fJdtbckroG35W7rM4zdvZudSwxef06in/Sk6YRbt+fP7lJCQ0CUB2oQJE2jr1q3U3Nwsj/YWL15MfOQ4kKO7y//7WgYlvnE2PD4RadC7fTKYoUOAD+wSExPlKEFHRwedOXOGOOOs5YHYhQsX5K5xO7GcuI0UFj4aTreczz2uhoYGGjlypDy444M8Tq3u7+9vXiwkJIRKSkroshgFiYqKoqSkJBnIOKU7JvsIIDDZx7HbVu6KXkyD+KKO8PGh6ZGRFDhunM1leKara9eOK5+k5RTQ1lPa71Oopekrqiguo/HjAuntzZvkePjJkyetFyUfUW9ERARNnDhRHuHxUER/p3GihzYm9DcUkfAynubQX0SsZ3cB7sWcPn1a9mw4QAQFBXWrg5fhyTrLrLKNpaXJc0h79uyRoxB83pbbUG1tbbdtjxCjFnzQFxoaStxru3r1ardlMKN/AghM/XPrdS0eamv8vIHeeiOXCouKKejXobRtxw66Jq70MU2mYPXZqVOmWfJ33Pzn6YWkxC7zvr/zPb2+JpMutlykpanptHf3+9TcdFYuc+zYMfOyfKK3qqqKokVPLU00sjlz5sjeU7xVr8y8Qh9fhDzzHJ7m0EcrLPbTCHCv5qIYdSgoKKDNmzfLXg6fN2prazPvgClYnThxwjyPX/BwnnUviof3eOibt7l06VLaJ4bdW1pa5HqHDx82r89trLKyksLDw4nvgZo3b57sPXFbw2Qfga6H6vbZJrbyo4D7sGGUsnAh/WHBAvpEnHQtLt1NG/PfphWvvkKvZWTQ2DFjKOmlF+VFEeMDgih88lT66O9H6UT9v+QFDpaQnh6eVP3Jcao9WUe7CovJ38+fPq2vkYsEBwfTd+LyVm5IO0Tw46uPVq5cScnJyeTh4WG5GbyGwP+VgLu7O6Wnp9OiRYvo+PHjcnguJyeHsrKyKDMzkwIDA2mhaIM8RMfDcRxM+BwUByq+wMFy8vQUbay6WvaO+Ko+Xr6urk4uwhcX8fB8RUWFDIR8Hmrt2rXywgheD5N9BRCY7Otpc2tDRDqL50WPhX++EOPgpeXv0RZxQnan+CkUR3s8lJeRuVyuOyV0MvE5pviYOPO2TCdVq/Z+SGmvpBP3qEwTn0NKSUmRjY17TsXFxfJELNeJCQLOIsDfd+4B8Q+f6+EDtPz8fBlIdu3aJYfy+Io7nqZMmSLPw1qOIpja2IEDByg1NVX2qEx2GeIgkntQPBLBPSce5uNeEtqYScj+v13EWKvxHBI29uM/V27bmNvzrAC37+iXLsbSXtwe4kKXhxjf5bG3hxlOe/FApr3gPE59nx4+bO9T2ov29nZyc3Mzb9it04Parl0jv1GjzfNUL/hG3FviSrnHfb1oqPujfFYPHjzoNo5ua31X105y9+h+/srWspbz3IY+Kd66WM7Cawg4tIB1G+MhOD7X6ufn1+t+83K3bt2S569MPaK+trFeN44FehVAYOqBaDADk3W1v3DzEv/2jf3jv+Ny33A+JgQma3m8hwAEHE0A4z2O9olgfyAAAQg4uQACk5N/AfDnQwACEHA0AQQmR/tEsD8QgAAEnFwAgcnJvwD48yEAAQg4mgACk6N9ItgfCEAAAk4uYLer8u53GL8EmcSl1Y8ZvN+mXawjniRq+GMbKnbP6FVvnQ/FZelDjd3q9VA8s8tFXNJudOJ9M7p/HfzYIoOHFp2dHeK+KVejuyee78cVGf+7DFeEFSAAAacXsFtgcnpJAEAAAhCAgF0EDB5v26VObAQCEIAABCCgFEBgUtKgAAIQgAAEdAggMOlQR50QgAAEIKAUQGBS0qAAAhCAAAR0CCAw6VBHnRCAAAQgoBRAYFLSoAACEIAABHQIIDDpUEedEIAABCCgFEBgUtKgAAIQgAAEdAggMOlQR50QgAAEIKAUQGBS0qAAAhCAAAR0CCAw6VBHnRCAAAQgoBRAYFLSoAACEIAABHQIIDDpUEedEIAABCCgFEBgUtKgAAIQgAAEdAggMOlQR50QgAAEIKAUQGBS0qAAAhCAAAR0CCAw6VBHnRCAAAQgoBRAYFLSoAACEIAABHQIIDDpUEedEIAABCCgFEBgUtKgAAIQgAAEdAggMOlQR50QgAAEIKAUQGBS0qAAAhCAAAR0CCAw6VBHnRCAAAQgoBRAYFLSoAACEIAABHQIIDDpUEedEIAABCCgFEBgUtKgAAIQgAAEdAggMOlQR50QgAAEIKAUQGBS0qAAAhCAAAR0CCAw6VBHnRCAAAQgoBRAYFLSoAACEIAABHQIIDDpUEedEIAABCCgFEBgUtKgAAIQgAAEdAggMOlQR50QgAAEIKAUQGBS0qAAAhCAAAR0CCAw6VBHnRCAAAQgoBRAYFLSoAACEIAABHQI/ADNkukNJP7dHgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 300
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import Image, display\n",
    "\n",
    "display(Image('xlnet-attention.png', width=300))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**All attention models able to use these interfaces.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load ELECTRA-Bahasa\n",
    "\n",
    "Feel free to use another models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:56: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n",
      "\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/modeling.py:240: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use keras.layers.Dense instead.\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/tensorflow_core/python/layers/core.py:187: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `layer.__call__` method instead.\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:79: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.\n",
      "\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:93: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.\n",
      "\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/sampling.py:26: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:114: multinomial (from tensorflow.python.ops.random_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.random.categorical` instead.\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:117: The name tf.InteractiveSession is deprecated. Please use tf.compat.v1.InteractiveSession instead.\n",
      "\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:118: The name tf.global_variables_initializer is deprecated. Please use tf.compat.v1.global_variables_initializer instead.\n",
      "\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:120: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.\n",
      "\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:121: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.\n",
      "\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:127: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.\n",
      "\n",
      "WARNING:tensorflow:From /Users/huseinzolkepli/Documents/Malaya/malaya/transformers/electra/__init__.py:129: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n",
      "\n",
      "INFO:tensorflow:Restoring parameters from /Users/huseinzolkepli/Malaya/electra-model/base/electra-base/model.ckpt\n"
     ]
    }
   ],
   "source": [
    "electra = malaya.transformer.load(model = 'electra')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[('Alaa', 0.059817147),\n",
       "  ('Tun', 0.075028375),\n",
       "  ('lek', 0.057848394),\n",
       "  ('ahhh', 0.046973262),\n",
       "  ('npe', 0.05160833),\n",
       "  ('muka', 0.06221234),\n",
       "  ('masam', 0.058585588),\n",
       "  ('cmni', 0.054711323),\n",
       "  ('kn', 0.06741887),\n",
       "  ('agong', 0.056326747),\n",
       "  ('kata', 0.054182768),\n",
       "  ('usaha', 0.07986903),\n",
       "  ('kerajaan', 0.05559596),\n",
       "  ('terdahulu', 0.052879248),\n",
       "  ('sejak', 0.049992196),\n",
       "  ('selepas', 0.053916205),\n",
       "  ('merdeka', 0.06303418)]]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "electra.attention([strings[1]], method = 'last')"
   ]
  }
 ],
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