models.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "47cae84d",
   "metadata": {},
   "source": [
    "# <center>Рекомендательная система на основе эмбеддингов для датасета MovieLens</center>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23d482ba",
   "metadata": {},
   "source": [
    "# Модели на основе обучаемых эмбеддингов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b2663b85",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "101930ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from keras import Input, Model, layers, Sequential\n",
    "from tensorflow.keras.optimizers.legacy import Adam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6dc90647",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics.pairwise import cosine_similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "28774b63",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>Animation</th>\n",
       "      <th>Children</th>\n",
       "      <th>Comedy</th>\n",
       "      <th>Crime</th>\n",
       "      <th>Documentary</th>\n",
       "      <th>Drama</th>\n",
       "      <th>...</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>(no genres listed)</th>\n",
       "      <th>IMAX</th>\n",
       "      <th>rating_mean</th>\n",
       "      <th>rating_std</th>\n",
       "      <th>rating_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>movieId</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Toy Story</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.891454</td>\n",
       "      <td>0.917794</td>\n",
       "      <td>2469.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jumanji</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.231282</td>\n",
       "      <td>0.959175</td>\n",
       "      <td>975.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Grumpier Old Men</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.190355</td>\n",
       "      <td>0.999860</td>\n",
       "      <td>591.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Waiting to Exhale</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.995902</td>\n",
       "      <td>1.031520</td>\n",
       "      <td>122.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Father of the Bride Part II</td>\n",
       "      <td>1995</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.032907</td>\n",
       "      <td>1.034132</td>\n",
       "      <td>547.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               title  year  Action  Adventure  Animation  \\\n",
       "movieId                                                                    \n",
       "1                          Toy Story  1995       0          1          1   \n",
       "2                            Jumanji  1995       0          1          0   \n",
       "3                   Grumpier Old Men  1995       0          0          0   \n",
       "4                  Waiting to Exhale  1995       0          0          0   \n",
       "5        Father of the Bride Part II  1995       0          0          0   \n",
       "\n",
       "         Children  Comedy  Crime  Documentary  Drama  ...  Romance  Sci-Fi  \\\n",
       "movieId                                               ...                    \n",
       "1               1       1      0            0      0  ...        0       0   \n",
       "2               1       0      0            0      0  ...        0       0   \n",
       "3               0       1      0            0      0  ...        1       0   \n",
       "4               0       1      0            0      1  ...        1       0   \n",
       "5               0       1      0            0      0  ...        0       0   \n",
       "\n",
       "         Thriller  War  Western  (no genres listed)  IMAX  rating_mean  \\\n",
       "movieId                                                                  \n",
       "1               0    0        0                   0     0     3.891454   \n",
       "2               0    0        0                   0     0     3.231282   \n",
       "3               0    0        0                   0     0     3.190355   \n",
       "4               0    0        0                   0     0     2.995902   \n",
       "5               0    0        0                   0     0     3.032907   \n",
       "\n",
       "         rating_std  rating_count  \n",
       "movieId                            \n",
       "1          0.917794        2469.0  \n",
       "2          0.959175         975.0  \n",
       "3          0.999860         591.0  \n",
       "4          1.031520         122.0  \n",
       "5          1.034132         547.0  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies_df = pd.read_csv(\"ml-latest\\movies_mod.csv\", index_col='movieId')\n",
    "movies_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1ddd2be7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>307</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1256677221</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>481</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1256677456</td>\n",
       "    </tr>\n",
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       "      <th>2</th>\n",
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       "      <td>1.5</td>\n",
       "      <td>1256677471</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>4.5</td>\n",
       "      <td>1256677460</td>\n",
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       "      <th>4</th>\n",
       "      <td>1</td>\n",
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      "text/plain": [
       "   userId  movieId  rating   timestamp\n",
       "0       1      307     3.5  1256677221\n",
       "1       1      481     3.5  1256677456\n",
       "2       1     1091     1.5  1256677471\n",
       "3       1     1257     4.5  1256677460\n",
       "4       1     1449     4.5  1256677264"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_df = pd.read_csv(r\"ml-latest\\ratings.csv\").iloc[:100_000]\n",
    "ratings_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c603dcd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>007</th>\n",
       "      <th>007 (series)</th>\n",
       "      <th>18th century</th>\n",
       "      <th>1920s</th>\n",
       "      <th>1930s</th>\n",
       "      <th>1950s</th>\n",
       "      <th>1960s</th>\n",
       "      <th>1970s</th>\n",
       "      <th>1980s</th>\n",
       "      <th>19th century</th>\n",
       "      <th>...</th>\n",
       "      <th>world politics</th>\n",
       "      <th>world war i</th>\n",
       "      <th>world war ii</th>\n",
       "      <th>writer's life</th>\n",
       "      <th>writers</th>\n",
       "      <th>writing</th>\n",
       "      <th>wuxia</th>\n",
       "      <th>wwii</th>\n",
       "      <th>zombie</th>\n",
       "      <th>zombies</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>movieId</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02900</td>\n",
       "      <td>0.02375</td>\n",
       "      <td>0.05425</td>\n",
       "      <td>0.06875</td>\n",
       "      <td>0.16000</td>\n",
       "      <td>0.19525</td>\n",
       "      <td>0.07600</td>\n",
       "      <td>0.25200</td>\n",
       "      <td>0.22750</td>\n",
       "      <td>0.02400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03775</td>\n",
       "      <td>0.02250</td>\n",
       "      <td>0.04075</td>\n",
       "      <td>0.03175</td>\n",
       "      <td>0.12950</td>\n",
       "      <td>0.04550</td>\n",
       "      <td>0.02000</td>\n",
       "      <td>0.03850</td>\n",
       "      <td>0.09125</td>\n",
       "      <td>0.02225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.03625</td>\n",
       "      <td>0.03625</td>\n",
       "      <td>0.08275</td>\n",
       "      <td>0.08175</td>\n",
       "      <td>0.10200</td>\n",
       "      <td>0.06900</td>\n",
       "      <td>0.05775</td>\n",
       "      <td>0.10100</td>\n",
       "      <td>0.08225</td>\n",
       "      <td>0.05250</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04775</td>\n",
       "      <td>0.02050</td>\n",
       "      <td>0.01650</td>\n",
       "      <td>0.02450</td>\n",
       "      <td>0.13050</td>\n",
       "      <td>0.02700</td>\n",
       "      <td>0.01825</td>\n",
       "      <td>0.01225</td>\n",
       "      <td>0.09925</td>\n",
       "      <td>0.01850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.04150</td>\n",
       "      <td>0.04950</td>\n",
       "      <td>0.03000</td>\n",
       "      <td>0.09525</td>\n",
       "      <td>0.04525</td>\n",
       "      <td>0.05925</td>\n",
       "      <td>0.04000</td>\n",
       "      <td>0.14150</td>\n",
       "      <td>0.04075</td>\n",
       "      <td>0.03200</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05800</td>\n",
       "      <td>0.02375</td>\n",
       "      <td>0.03550</td>\n",
       "      <td>0.02125</td>\n",
       "      <td>0.12775</td>\n",
       "      <td>0.03250</td>\n",
       "      <td>0.01625</td>\n",
       "      <td>0.02125</td>\n",
       "      <td>0.09525</td>\n",
       "      <td>0.01750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.03350</td>\n",
       "      <td>0.03675</td>\n",
       "      <td>0.04275</td>\n",
       "      <td>0.02625</td>\n",
       "      <td>0.05250</td>\n",
       "      <td>0.03025</td>\n",
       "      <td>0.02425</td>\n",
       "      <td>0.07475</td>\n",
       "      <td>0.03750</td>\n",
       "      <td>0.02400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04900</td>\n",
       "      <td>0.03275</td>\n",
       "      <td>0.02125</td>\n",
       "      <td>0.03675</td>\n",
       "      <td>0.15925</td>\n",
       "      <td>0.05225</td>\n",
       "      <td>0.01500</td>\n",
       "      <td>0.01600</td>\n",
       "      <td>0.09175</td>\n",
       "      <td>0.01500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.04050</td>\n",
       "      <td>0.05175</td>\n",
       "      <td>0.03600</td>\n",
       "      <td>0.04625</td>\n",
       "      <td>0.05500</td>\n",
       "      <td>0.08000</td>\n",
       "      <td>0.02150</td>\n",
       "      <td>0.07375</td>\n",
       "      <td>0.02825</td>\n",
       "      <td>0.02375</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05375</td>\n",
       "      <td>0.02625</td>\n",
       "      <td>0.02050</td>\n",
       "      <td>0.02125</td>\n",
       "      <td>0.17725</td>\n",
       "      <td>0.02050</td>\n",
       "      <td>0.01500</td>\n",
       "      <td>0.01550</td>\n",
       "      <td>0.08875</td>\n",
       "      <td>0.01575</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 1128 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             007  007 (series)  18th century    1920s    1930s    1950s  \\\n",
       "movieId                                                                   \n",
       "1        0.02900       0.02375       0.05425  0.06875  0.16000  0.19525   \n",
       "2        0.03625       0.03625       0.08275  0.08175  0.10200  0.06900   \n",
       "3        0.04150       0.04950       0.03000  0.09525  0.04525  0.05925   \n",
       "4        0.03350       0.03675       0.04275  0.02625  0.05250  0.03025   \n",
       "5        0.04050       0.05175       0.03600  0.04625  0.05500  0.08000   \n",
       "\n",
       "           1960s    1970s    1980s  19th century  ...  world politics  \\\n",
       "movieId                                           ...                   \n",
       "1        0.07600  0.25200  0.22750       0.02400  ...         0.03775   \n",
       "2        0.05775  0.10100  0.08225       0.05250  ...         0.04775   \n",
       "3        0.04000  0.14150  0.04075       0.03200  ...         0.05800   \n",
       "4        0.02425  0.07475  0.03750       0.02400  ...         0.04900   \n",
       "5        0.02150  0.07375  0.02825       0.02375  ...         0.05375   \n",
       "\n",
       "         world war i  world war ii  writer's life  writers  writing    wuxia  \\\n",
       "movieId                                                                        \n",
       "1            0.02250       0.04075        0.03175  0.12950  0.04550  0.02000   \n",
       "2            0.02050       0.01650        0.02450  0.13050  0.02700  0.01825   \n",
       "3            0.02375       0.03550        0.02125  0.12775  0.03250  0.01625   \n",
       "4            0.03275       0.02125        0.03675  0.15925  0.05225  0.01500   \n",
       "5            0.02625       0.02050        0.02125  0.17725  0.02050  0.01500   \n",
       "\n",
       "            wwii   zombie  zombies  \n",
       "movieId                             \n",
       "1        0.03850  0.09125  0.02225  \n",
       "2        0.01225  0.09925  0.01850  \n",
       "3        0.02125  0.09525  0.01750  \n",
       "4        0.01600  0.09175  0.01500  \n",
       "5        0.01550  0.08875  0.01575  \n",
       "\n",
       "[5 rows x 1128 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genome = pd.read_csv(r\"ml-latest\\genome-pivot.csv\", index_col='movieId')\n",
    "genome.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae1fe9d0",
   "metadata": {},
   "source": [
    "## Создание датасета для обучения"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ded75635",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>movieId</th>\n",
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       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId    rating  year  Action  Adventure  Animation  Children  \\\n",
       "0       1      307  0.666667  1993       0          0          0         0   \n",
       "1       1      481  0.666667  1993       0          0          0         0   \n",
       "2       1     1091  0.222222  1989       0          0          0         0   \n",
       "3       1     1257  0.888889  1985       0          0          0         0   \n",
       "4       1     1449  0.888889  1996       0          0          0         0   \n",
       "\n",
       "   Comedy  Crime  ...  Romance  Sci-Fi  Thriller  War  Western  \\\n",
       "0       0      0  ...        0       0         0    0        0   \n",
       "1       0      0  ...        0       0         1    0        0   \n",
       "2       1      0  ...        0       0         0    0        0   \n",
       "3       1      0  ...        1       0         0    0        0   \n",
       "4       1      0  ...        0       0         0    0        0   \n",
       "\n",
       "   (no genres listed)  IMAX  rating_mean  rating_std  rating_count  \n",
       "0                   0     0     4.036164    0.959485         318.0  \n",
       "1                   0     0     3.371542    0.886573         253.0  \n",
       "2                   0     0     2.815421    1.122663         214.0  \n",
       "3                   0     0     3.799550    0.921905         222.0  \n",
       "4                   0     0     3.916667    0.974243         246.0  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_df = ratings_df.drop('timestamp', axis=1)\n",
    "ratings_df = pd.merge(ratings_df, movies_df, how='left', left_on='movieId', right_on='movieId')\n",
    "ratings_df = ratings_df.drop('title', axis=1)\n",
    "ratings_df['rating'] = (ratings_df['rating'] - 0.5)/4.5\n",
    "ratings_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8fef0118",
   "metadata": {},
   "outputs": [
    {
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       "      <th>99997</th>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.367391</td>\n",
       "      <td>0.983944</td>\n",
       "      <td>230.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100000 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       userId  movieId  year  Action  Adventure  Animation  Children  Comedy  \\\n",
       "0           1      307  1993       0          0          0         0       0   \n",
       "1           1      481  1993       0          0          0         0       0   \n",
       "2           1     1091  1989       0          0          0         0       1   \n",
       "3           1     1257  1985       0          0          0         0       1   \n",
       "4           1     1449  1996       0          0          0         0       1   \n",
       "...       ...      ...   ...     ...        ...        ...       ...     ...   \n",
       "99995    1041     1393  1996       0          0          0         0       0   \n",
       "99996    1041     1411  1996       0          0          0         0       0   \n",
       "99997    1041     1419  1971       0          1          0         0       0   \n",
       "99998    1041     1446  1996       0          0          0         0       1   \n",
       "99999    1041     1476  1997       0          0          0         0       1   \n",
       "\n",
       "       Crime  Documentary  ...  Romance  Sci-Fi  Thriller  War  Western  \\\n",
       "0          0            0  ...        0       0         0    0        0   \n",
       "1          0            0  ...        0       0         1    0        0   \n",
       "2          0            0  ...        0       0         0    0        0   \n",
       "3          0            0  ...        1       0         0    0        0   \n",
       "4          0            0  ...        0       0         0    0        0   \n",
       "...      ...          ...  ...      ...     ...       ...  ...      ...   \n",
       "99995      0            0  ...        1       0         0    0        0   \n",
       "99996      1            0  ...        1       0         0    0        0   \n",
       "99997      0            0  ...        0       0         0    0        0   \n",
       "99998      0            0  ...        0       0         0    0        0   \n",
       "99999      0            0  ...        0       0         0    0        0   \n",
       "\n",
       "       (no genres listed)  IMAX  rating_mean  rating_std  rating_count  \n",
       "0                       0     0     4.036164    0.959485         318.0  \n",
       "1                       0     0     3.371542    0.886573         253.0  \n",
       "2                       0     0     2.815421    1.122663         214.0  \n",
       "3                       0     0     3.799550    0.921905         222.0  \n",
       "4                       0     0     3.916667    0.974243         246.0  \n",
       "...                   ...   ...          ...         ...           ...  \n",
       "99995                   0     0     3.609509    0.932208         936.0  \n",
       "99996                   0     0     3.678138    1.004385         247.0  \n",
       "99997                   0     0     3.833333    0.988264          51.0  \n",
       "99998                   0     0     4.058824    0.874274          85.0  \n",
       "99999                   0     0     3.367391    0.983944         230.0  \n",
       "\n",
       "[100000 rows x 26 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = ratings_df.drop('rating', axis=1)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "762be9c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        0.666667\n",
       "1        0.666667\n",
       "2        0.222222\n",
       "3        0.888889\n",
       "4        0.888889\n",
       "           ...   \n",
       "99995    0.777778\n",
       "99996    0.777778\n",
       "99997    0.555556\n",
       "99998    0.777778\n",
       "99999    0.777778\n",
       "Name: rating, Length: 100000, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = ratings_df['rating']\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "99338546",
   "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>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>007</th>\n",
       "      <th>007 (series)</th>\n",
       "      <th>18th century</th>\n",
       "      <th>1920s</th>\n",
       "      <th>1930s</th>\n",
       "      <th>1950s</th>\n",
       "      <th>1960s</th>\n",
       "      <th>...</th>\n",
       "      <th>world politics</th>\n",
       "      <th>world war i</th>\n",
       "      <th>world war ii</th>\n",
       "      <th>writer's life</th>\n",
       "      <th>writers</th>\n",
       "      <th>writing</th>\n",
       "      <th>wuxia</th>\n",
       "      <th>wwii</th>\n",
       "      <th>zombie</th>\n",
       "      <th>zombies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>307</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.02025</td>\n",
       "      <td>0.01975</td>\n",
       "      <td>0.07075</td>\n",
       "      <td>0.06975</td>\n",
       "      <td>0.04925</td>\n",
       "      <td>0.05175</td>\n",
       "      <td>0.0435</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05975</td>\n",
       "      <td>0.02825</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.07925</td>\n",
       "      <td>0.17325</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.03925</td>\n",
       "      <td>0.00725</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.0185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>307</td>\n",
       "      <td>0.777778</td>\n",
       "      <td>0.02025</td>\n",
       "      <td>0.01975</td>\n",
       "      <td>0.07075</td>\n",
       "      <td>0.06975</td>\n",
       "      <td>0.04925</td>\n",
       "      <td>0.05175</td>\n",
       "      <td>0.0435</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05975</td>\n",
       "      <td>0.02825</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.07925</td>\n",
       "      <td>0.17325</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.03925</td>\n",
       "      <td>0.00725</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.0185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56</td>\n",
       "      <td>307</td>\n",
       "      <td>0.777778</td>\n",
       "      <td>0.02025</td>\n",
       "      <td>0.01975</td>\n",
       "      <td>0.07075</td>\n",
       "      <td>0.06975</td>\n",
       "      <td>0.04925</td>\n",
       "      <td>0.05175</td>\n",
       "      <td>0.0435</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05975</td>\n",
       "      <td>0.02825</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.07925</td>\n",
       "      <td>0.17325</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.03925</td>\n",
       "      <td>0.00725</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.0185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>71</td>\n",
       "      <td>307</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.02025</td>\n",
       "      <td>0.01975</td>\n",
       "      <td>0.07075</td>\n",
       "      <td>0.06975</td>\n",
       "      <td>0.04925</td>\n",
       "      <td>0.05175</td>\n",
       "      <td>0.0435</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05975</td>\n",
       "      <td>0.02825</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.07925</td>\n",
       "      <td>0.17325</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.03925</td>\n",
       "      <td>0.00725</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.0185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>84</td>\n",
       "      <td>307</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>0.02025</td>\n",
       "      <td>0.01975</td>\n",
       "      <td>0.07075</td>\n",
       "      <td>0.06975</td>\n",
       "      <td>0.04925</td>\n",
       "      <td>0.05175</td>\n",
       "      <td>0.0435</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05975</td>\n",
       "      <td>0.02825</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.07925</td>\n",
       "      <td>0.17325</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.03925</td>\n",
       "      <td>0.00725</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.0185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 1131 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   userId  movieId    rating      007  007 (series)  18th century    1920s  \\\n",
       "0       1      307  0.666667  0.02025       0.01975       0.07075  0.06975   \n",
       "1       6      307  0.777778  0.02025       0.01975       0.07075  0.06975   \n",
       "2      56      307  0.777778  0.02025       0.01975       0.07075  0.06975   \n",
       "3      71      307  1.000000  0.02025       0.01975       0.07075  0.06975   \n",
       "4      84      307  0.555556  0.02025       0.01975       0.07075  0.06975   \n",
       "\n",
       "     1930s    1950s   1960s  ...  world politics  world war i  world war ii  \\\n",
       "0  0.04925  0.05175  0.0435  ...         0.05975      0.02825         0.017   \n",
       "1  0.04925  0.05175  0.0435  ...         0.05975      0.02825         0.017   \n",
       "2  0.04925  0.05175  0.0435  ...         0.05975      0.02825         0.017   \n",
       "3  0.04925  0.05175  0.0435  ...         0.05975      0.02825         0.017   \n",
       "4  0.04925  0.05175  0.0435  ...         0.05975      0.02825         0.017   \n",
       "\n",
       "   writer's life  writers  writing    wuxia     wwii  zombie  zombies  \n",
       "0        0.07925  0.17325    0.068  0.03925  0.00725   0.073   0.0185  \n",
       "1        0.07925  0.17325    0.068  0.03925  0.00725   0.073   0.0185  \n",
       "2        0.07925  0.17325    0.068  0.03925  0.00725   0.073   0.0185  \n",
       "3        0.07925  0.17325    0.068  0.03925  0.00725   0.073   0.0185  \n",
       "4        0.07925  0.17325    0.068  0.03925  0.00725   0.073   0.0185  \n",
       "\n",
       "[5 rows x 1131 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_df = ratings_df[['userId', 'movieId', 'rating']]\n",
    "ratings_df = pd.merge(ratings_df, genome, how='inner', left_on='movieId', right_on='movieId')\n",
    "ratings_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "482a5321",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_genome = ratings_df.drop('rating', axis=1)\n",
    "y_genome = ratings_df.rating"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41a86177",
   "metadata": {},
   "source": [
    "Для валидации оставляем 10 процентов датасета (т.к. данных достаточно много)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "187c7b1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_valid, y_train, y_valid = train_test_split(X, y, test_size=0.10, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a32c5b5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_autoenc, X_valid_autoenc, _, _ = train_test_split(genome.values, genome.values, test_size=0.1, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "36af8f54",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_genome, X_valid_genome, y_train_genome, y_valid_genome = train_test_split(X_genome, y_genome, test_size=0.10, shuffle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e25a5b3c",
   "metadata": {},
   "source": [
    "## Модель с эмбеддингами на основе id "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "a9f28d6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def id_embedding_model(num_users, num_movies, rows_count, emb_size):\n",
    "    movie_input = Input(shape=(1,), name='movie_id')\n",
    "    movie_emb = layers.Embedding(output_dim=emb_size, input_dim=num_movies+1, input_length=rows_count+1, name='movie_emb')(movie_input)\n",
    "    movie_vec = layers.Flatten(name='movie_emb_flatten')(movie_emb)\n",
    "\n",
    "    movie_model = keras.Model(inputs=movie_input, outputs=movie_vec)\n",
    "\n",
    "    user_input = Input(shape=(1,), name='user_id')\n",
    "    user_emb = layers.Embedding(output_dim=emb_size, input_dim=num_users+1, input_length=rows_count+1, name='user_emb')(user_input)\n",
    "    user_vec = layers.Flatten(name='user_emb_flatten')(user_emb)\n",
    "\n",
    "    user_model = keras.Model(inputs=user_input, outputs=user_vec)\n",
    "\n",
    "    merged = layers.Dot(name = 'dot_product', normalize = True, axes=1)([movie_vec, user_vec])\n",
    "    merged_dropout = layers.Dropout(0.2)(merged)\n",
    "\n",
    "\n",
    "    dense_1 = layers.Dense(128,name='FullyConnected-1')(merged)\n",
    "    dropout_1 = layers.Dropout(0.2,name='Dropout-1')(dense_1)\n",
    "\n",
    "    dense_2 = layers.Dense(64,name='FullyConnected-2')(dropout_1)\n",
    "    dropout_2 = layers.Dropout(0.2,name='Dropout-2')(dense_2)\n",
    "\n",
    "    dense_3 = layers.Dense(16,name='FullyConnected-3')(dropout_2)\n",
    "    dropout_3 = layers.Dropout(0.2,name='Dropout-3')(dense_3)\n",
    "\n",
    "    dense_4 = layers.Dense(4,name='FullyConnected-4', activation='relu')(dropout_3)\n",
    "\n",
    "    result = layers.Dense(1, name='result', activation=\"sigmoid\")(dense_4)\n",
    "\n",
    "    adam = Adam(learning_rate=0.001)\n",
    "    model = keras.Model([movie_input, user_input], result)\n",
    "    model.compile(optimizer=adam, loss= 'mean_absolute_error', metrics='mean_squared_error')\n",
    "    return movie_model, user_model, model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "f886bd4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "id_movie_model, id_user_model, id_model = id_embedding_model(X.userId.nunique(), movies_df.index.max(), ratings_df.shape[0], 32)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee357c70",
   "metadata": {},
   "source": [
    "**Схема модели**"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "710c1372",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src=\"attachment:image.png\" width=\"500\"/>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8217f07e",
   "metadata": {},
   "source": [
    "Модель состоит из трёх частей:\n",
    "* Модель фильма\n",
    "* Модель пользователя\n",
    "* Полносвязные слои\n",
    "\n",
    "Модели фильма и пользователя получают на вход id, а затем строят эмбеддинги длины 32. Полученные эмбединги перемножаются скалярно, и затем используются полносвязные слои. Было использовано 4 слоя, т.к. зависимость между скалярным произведением эмбеддингов и рейтигом фильма довольно сложная. К слоям применяется dropout для того, чтобы переизбежать переобучения и модель выучила сложную зависимость\n",
    "\n",
    "В этой модели и далее в качестве loss-функции и метрики используется $MAE$. Её преимущетсво в том, что она хорошо интерпретируется, по нему можно легко оценить качество предсказаний модели. Также для оценки работы моделей будут использованы $MSE$ и $RMSE$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "81171296",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "900/900 [==============================] - 87s 94ms/step - loss: 0.1960 - mean_squared_error: 0.0633 - val_loss: 0.1992 - val_mean_squared_error: 0.0686\n",
      "Epoch 2/50\n",
      "900/900 [==============================] - 85s 94ms/step - loss: 0.1888 - mean_squared_error: 0.0600 - val_loss: 0.1789 - val_mean_squared_error: 0.0555\n",
      "Epoch 3/50\n",
      "900/900 [==============================] - 85s 94ms/step - loss: 0.1432 - mean_squared_error: 0.0395 - val_loss: 0.1751 - val_mean_squared_error: 0.0545\n",
      "Epoch 4/50\n",
      "900/900 [==============================] - 85s 94ms/step - loss: 0.1244 - mean_squared_error: 0.0310 - val_loss: 0.1763 - val_mean_squared_error: 0.0539\n",
      "Epoch 5/50\n",
      "900/900 [==============================] - 87s 97ms/step - loss: 0.1129 - mean_squared_error: 0.0263 - val_loss: 0.1766 - val_mean_squared_error: 0.0543\n",
      "Epoch 6/50\n",
      "900/900 [==============================] - 84s 94ms/step - loss: 0.1042 - mean_squared_error: 0.0233 - val_loss: 0.1772 - val_mean_squared_error: 0.0550\n",
      "Epoch 7/50\n",
      "900/900 [==============================] - 84s 93ms/step - loss: 0.0985 - mean_squared_error: 0.0214 - val_loss: 0.1783 - val_mean_squared_error: 0.0553\n",
      "Epoch 8/50\n",
      "900/900 [==============================] - 85s 94ms/step - loss: 0.0942 - mean_squared_error: 0.0205 - val_loss: 0.1817 - val_mean_squared_error: 0.0587\n",
      "Epoch 9/50\n",
      "900/900 [==============================] - 85s 94ms/step - loss: 0.0902 - mean_squared_error: 0.0201 - val_loss: 0.1801 - val_mean_squared_error: 0.0584\n",
      "Epoch 10/50\n",
      "900/900 [==============================] - 85s 94ms/step - loss: 0.0865 - mean_squared_error: 0.0195 - val_loss: 0.1804 - val_mean_squared_error: 0.0586\n",
      "Epoch 11/50\n",
      "900/900 [==============================] - 85s 95ms/step - loss: 0.0839 - mean_squared_error: 0.0191 - val_loss: 0.1805 - val_mean_squared_error: 0.0587\n",
      "Epoch 12/50\n",
      "900/900 [==============================] - 85s 94ms/step - loss: 0.0824 - mean_squared_error: 0.0187 - val_loss: 0.1797 - val_mean_squared_error: 0.0587\n",
      "Epoch 13/50\n",
      "900/900 [==============================] - 83s 92ms/step - loss: 0.0812 - mean_squared_error: 0.0183 - val_loss: 0.1802 - val_mean_squared_error: 0.0591\n"
     ]
    }
   ],
   "source": [
    "callbacks = [keras.callbacks.EarlyStopping('val_loss', patience=10),\n",
    "             keras.callbacks.ModelCheckpoint('models/id/model/besttest.h5', save_best_only=True)]\n",
    "\n",
    "history = id_model.fit([X_train['movieId'], X_train['userId']], y_train, batch_size=100,\n",
    "                              epochs=50, validation_data=([X_valid['movieId'], X_valid['userId']], y_valid),\n",
    "                              verbose=1, \n",
    "                              callbacks = callbacks)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "7c4e8cbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(history.history['loss'] , 'g')\n",
    "plt.plot(history.history['val_loss'] , 'r')\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epochs')\n",
    "plt.legend(['train', 'valid'], loc='upper right')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0184a2e0",
   "metadata": {},
   "source": [
    "Можно сделать вывод, что модель обучается довольно быстро, однако ошибка на отложенной выборке высока - в среднем $ MAE = 0.18$. Т.к. оценки нормируются и респределены от 0 до 1, то ошибка составляет в среднем 18%. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e20dc72",
   "metadata": {},
   "source": [
    "**Плюсы модели**:\n",
    "* Простота\n",
    "* Быстрота обучения\n",
    "\n",
    "**Минусы**:\n",
    "* Низкая точность\n",
    "* Склонность к перообучению"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ff7df96",
   "metadata": {},
   "source": [
    "## Модель с эмбеддингами на основе жанров"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "86e39b41",
   "metadata": {},
   "outputs": [],
   "source": [
    "def features_embedding_model(num_users, num_movies, rows_count, text_emb_size, emb_size):\n",
    "    n_genres = 20\n",
    "    n_features = 4\n",
    "\n",
    "    movie_features_input = keras.Input(shape=(n_genres+n_features,), name='movie_features')    \n",
    "    movie_vec = layers.Dense(emb_size, activation='relu', name='movie_vec')(movie_features_input)\n",
    "    movie_model = keras.Model(inputs= movie_features_input, outputs=movie_vec)\n",
    "\n",
    "    user_input = keras.Input(shape=(1,), name='user_id')\n",
    "    user_emb = layers.Embedding(output_dim=emb_size, input_dim=num_users+1, input_length=rows_count+1, name='user_emb')(user_input)\n",
    "    user_vec = layers.Flatten(name='user_emb_flatten')(user_emb)\n",
    "    user_model = keras.Model(inputs=user_input, outputs=user_vec)\n",
    "\n",
    "    merged = layers.Dot(name = 'dot_product', normalize = True, axes=1)([movie_vec, user_vec])\n",
    "    merged_dropout = layers.Dropout(0.2)(merged)\n",
    "\n",
    "    dense_1 = layers.Dense(256,name='FullyConnected-1')(merged)\n",
    "    dropout_1 = layers.Dropout(0.2,name='Dropout_1')(dense_1)\n",
    "\n",
    "    dense_2 = layers.Dense(128,name='FullyConnected-2')(dropout_1)\n",
    "    dropout_2 = layers.Dropout(0.2,name='Dropout_2')(dense_2)\n",
    "\n",
    "    dense_3 = keras.layers.Dense(32,name='FullyConnected-3')(dropout_2)\n",
    "    dropout_3 = keras.layers.Dropout(0.2,name='Dropout_3')(dense_3)\n",
    "\n",
    "    dense_4 = keras.layers.Dense(8,name='FullyConnected-4', activation='relu')(dropout_3)\n",
    "\n",
    "    result = layers.Dense(1, name='result', activation=\"sigmoid\")(dense_4)\n",
    "\n",
    "    adam = Adam(learning_rate=0.001)\n",
    "    model = keras.Model([movie_features_input, user_input], result)\n",
    "    model.compile(optimizer=adam, loss= 'mean_absolute_error', metrics='mean_squared_error')\n",
    "    return movie_model, user_model, model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1f24eeb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "feat_movie_model, feat_user_model, feat_model = features_embedding_model(X.userId.nunique(), movies_df.index.max(), ratings_df.shape[0], 16, 32)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7bed503",
   "metadata": {},
   "source": [
    "**Схема модели фильма**"
   ]
  },
  {
   "attachments": {
    "image-3.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "c2d73d23",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src=\"attachment:image-3.png\" width=\"500\"/>\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56b20fc4",
   "metadata": {},
   "source": [
    "Модель получает на вход параметры фильма: жанры фильма, год выпуска, средняя оценка, отклонение оценок, количество оценок. Вектор из параметров проходит через полносвязный слой, на выходе получается векторное представление фильма"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1875c33",
   "metadata": {},
   "source": [
    "**Полная схема модели**"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "669e6387",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src=\"attachment:image-2.png\" width=\"500\"/>\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2407ad08",
   "metadata": {},
   "source": [
    "При помощи модели для фильмов создаётся векторное представление для фильма. Для пользователя обучается эмбеддинг. Векторы перемножаются скалярно, а затем применяется 4 полносвязных слоя с дропаутом. Количество нейронов слоях было увеличено по сравнению с предыдущей моделью т.к. теперь векторное представление фильма устроено сложнее"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "bf6b99bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "900/900 [==============================] - 7s 5ms/step - loss: 0.1777 - mean_squared_error: 0.0545 - val_loss: 0.1695 - val_mean_squared_error: 0.0498\n",
      "Epoch 2/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1696 - mean_squared_error: 0.0512 - val_loss: 0.1671 - val_mean_squared_error: 0.0494\n",
      "Epoch 3/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1679 - mean_squared_error: 0.0506 - val_loss: 0.1656 - val_mean_squared_error: 0.0501\n",
      "Epoch 4/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1671 - mean_squared_error: 0.0503 - val_loss: 0.1654 - val_mean_squared_error: 0.0492\n",
      "Epoch 5/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1664 - mean_squared_error: 0.0501 - val_loss: 0.1657 - val_mean_squared_error: 0.0501\n",
      "Epoch 6/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1658 - mean_squared_error: 0.0500 - val_loss: 0.1652 - val_mean_squared_error: 0.0493\n",
      "Epoch 7/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1655 - mean_squared_error: 0.0499 - val_loss: 0.1649 - val_mean_squared_error: 0.0496\n",
      "Epoch 8/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1651 - mean_squared_error: 0.0498 - val_loss: 0.1649 - val_mean_squared_error: 0.0499\n",
      "Epoch 9/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1648 - mean_squared_error: 0.0498 - val_loss: 0.1647 - val_mean_squared_error: 0.0491\n",
      "Epoch 10/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1644 - mean_squared_error: 0.0496 - val_loss: 0.1645 - val_mean_squared_error: 0.0490\n",
      "Epoch 11/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1640 - mean_squared_error: 0.0494 - val_loss: 0.1666 - val_mean_squared_error: 0.0495\n",
      "Epoch 12/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1638 - mean_squared_error: 0.0496 - val_loss: 0.1642 - val_mean_squared_error: 0.0494\n",
      "Epoch 13/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1633 - mean_squared_error: 0.0494 - val_loss: 0.1644 - val_mean_squared_error: 0.0490\n",
      "Epoch 14/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1631 - mean_squared_error: 0.0493 - val_loss: 0.1642 - val_mean_squared_error: 0.0490\n",
      "Epoch 15/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1628 - mean_squared_error: 0.0491 - val_loss: 0.1635 - val_mean_squared_error: 0.0490\n",
      "Epoch 16/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1622 - mean_squared_error: 0.0490 - val_loss: 0.1633 - val_mean_squared_error: 0.0491\n",
      "Epoch 17/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1617 - mean_squared_error: 0.0488 - val_loss: 0.1635 - val_mean_squared_error: 0.0489\n",
      "Epoch 18/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1613 - mean_squared_error: 0.0485 - val_loss: 0.1635 - val_mean_squared_error: 0.0485\n",
      "Epoch 19/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1606 - mean_squared_error: 0.0482 - val_loss: 0.1638 - val_mean_squared_error: 0.0488\n",
      "Epoch 20/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1602 - mean_squared_error: 0.0480 - val_loss: 0.1623 - val_mean_squared_error: 0.0487\n",
      "Epoch 21/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1597 - mean_squared_error: 0.0477 - val_loss: 0.1623 - val_mean_squared_error: 0.0478\n",
      "Epoch 22/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1591 - mean_squared_error: 0.0474 - val_loss: 0.1624 - val_mean_squared_error: 0.0474\n",
      "Epoch 23/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1587 - mean_squared_error: 0.0472 - val_loss: 0.1620 - val_mean_squared_error: 0.0484\n",
      "Epoch 24/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1584 - mean_squared_error: 0.0470 - val_loss: 0.1608 - val_mean_squared_error: 0.0477\n",
      "Epoch 25/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1577 - mean_squared_error: 0.0468 - val_loss: 0.1623 - val_mean_squared_error: 0.0469\n",
      "Epoch 26/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1575 - mean_squared_error: 0.0467 - val_loss: 0.1610 - val_mean_squared_error: 0.0469\n",
      "Epoch 27/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1573 - mean_squared_error: 0.0466 - val_loss: 0.1613 - val_mean_squared_error: 0.0479\n",
      "Epoch 28/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1567 - mean_squared_error: 0.0464 - val_loss: 0.1612 - val_mean_squared_error: 0.0466\n",
      "Epoch 29/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1564 - mean_squared_error: 0.0461 - val_loss: 0.1607 - val_mean_squared_error: 0.0467\n",
      "Epoch 30/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1561 - mean_squared_error: 0.0461 - val_loss: 0.1609 - val_mean_squared_error: 0.0481\n",
      "Epoch 31/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1559 - mean_squared_error: 0.0461 - val_loss: 0.1596 - val_mean_squared_error: 0.0465\n",
      "Epoch 32/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1557 - mean_squared_error: 0.0460 - val_loss: 0.1597 - val_mean_squared_error: 0.0465\n",
      "Epoch 33/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1555 - mean_squared_error: 0.0459 - val_loss: 0.1601 - val_mean_squared_error: 0.0466\n",
      "Epoch 34/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1551 - mean_squared_error: 0.0457 - val_loss: 0.1594 - val_mean_squared_error: 0.0469\n",
      "Epoch 35/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1548 - mean_squared_error: 0.0456 - val_loss: 0.1598 - val_mean_squared_error: 0.0461\n",
      "Epoch 36/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1544 - mean_squared_error: 0.0454 - val_loss: 0.1598 - val_mean_squared_error: 0.0471\n",
      "Epoch 37/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1542 - mean_squared_error: 0.0454 - val_loss: 0.1590 - val_mean_squared_error: 0.0464\n",
      "Epoch 38/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1539 - mean_squared_error: 0.0453 - val_loss: 0.1586 - val_mean_squared_error: 0.0458\n",
      "Epoch 39/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1537 - mean_squared_error: 0.0450 - val_loss: 0.1583 - val_mean_squared_error: 0.0461\n",
      "Epoch 40/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1534 - mean_squared_error: 0.0451 - val_loss: 0.1587 - val_mean_squared_error: 0.0457\n",
      "Epoch 41/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1530 - mean_squared_error: 0.0449 - val_loss: 0.1582 - val_mean_squared_error: 0.0459\n",
      "Epoch 42/100\n",
      "900/900 [==============================] - 34s 38ms/step - loss: 0.1529 - mean_squared_error: 0.0448 - val_loss: 0.1580 - val_mean_squared_error: 0.0458\n",
      "Epoch 43/100\n",
      "900/900 [==============================] - 5s 6ms/step - loss: 0.1525 - mean_squared_error: 0.0447 - val_loss: 0.1612 - val_mean_squared_error: 0.0460\n",
      "Epoch 44/100\n",
      "900/900 [==============================] - 5s 6ms/step - loss: 0.1522 - mean_squared_error: 0.0445 - val_loss: 0.1596 - val_mean_squared_error: 0.0459\n",
      "Epoch 45/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1522 - mean_squared_error: 0.0445 - val_loss: 0.1619 - val_mean_squared_error: 0.0463\n",
      "Epoch 46/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1518 - mean_squared_error: 0.0443 - val_loss: 0.1571 - val_mean_squared_error: 0.0453\n",
      "Epoch 47/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1513 - mean_squared_error: 0.0442 - val_loss: 0.1590 - val_mean_squared_error: 0.0455\n",
      "Epoch 48/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1512 - mean_squared_error: 0.0441 - val_loss: 0.1581 - val_mean_squared_error: 0.0450\n",
      "Epoch 49/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1508 - mean_squared_error: 0.0438 - val_loss: 0.1569 - val_mean_squared_error: 0.0453\n",
      "Epoch 50/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1506 - mean_squared_error: 0.0438 - val_loss: 0.1598 - val_mean_squared_error: 0.0453\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 51/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1508 - mean_squared_error: 0.0439 - val_loss: 0.1579 - val_mean_squared_error: 0.0452\n",
      "Epoch 52/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1500 - mean_squared_error: 0.0436 - val_loss: 0.1566 - val_mean_squared_error: 0.0449\n",
      "Epoch 53/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1495 - mean_squared_error: 0.0433 - val_loss: 0.1579 - val_mean_squared_error: 0.0452\n",
      "Epoch 54/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1497 - mean_squared_error: 0.0434 - val_loss: 0.1561 - val_mean_squared_error: 0.0448\n",
      "Epoch 55/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1494 - mean_squared_error: 0.0432 - val_loss: 0.1576 - val_mean_squared_error: 0.0454\n",
      "Epoch 56/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1495 - mean_squared_error: 0.0432 - val_loss: 0.1581 - val_mean_squared_error: 0.0454\n",
      "Epoch 57/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1490 - mean_squared_error: 0.0430 - val_loss: 0.1569 - val_mean_squared_error: 0.0446\n",
      "Epoch 58/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1489 - mean_squared_error: 0.0429 - val_loss: 0.1568 - val_mean_squared_error: 0.0444\n",
      "Epoch 59/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1487 - mean_squared_error: 0.0427 - val_loss: 0.1563 - val_mean_squared_error: 0.0444\n",
      "Epoch 60/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1485 - mean_squared_error: 0.0427 - val_loss: 0.1563 - val_mean_squared_error: 0.0449\n",
      "Epoch 61/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1481 - mean_squared_error: 0.0423 - val_loss: 0.1563 - val_mean_squared_error: 0.0448\n",
      "Epoch 62/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1480 - mean_squared_error: 0.0421 - val_loss: 0.1576 - val_mean_squared_error: 0.0437\n",
      "Epoch 63/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1477 - mean_squared_error: 0.0414 - val_loss: 0.1560 - val_mean_squared_error: 0.0432\n",
      "Epoch 64/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1471 - mean_squared_error: 0.0404 - val_loss: 0.1547 - val_mean_squared_error: 0.0428\n",
      "Epoch 65/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1468 - mean_squared_error: 0.0403 - val_loss: 0.1569 - val_mean_squared_error: 0.0428\n",
      "Epoch 66/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1459 - mean_squared_error: 0.0399 - val_loss: 0.1601 - val_mean_squared_error: 0.0436\n",
      "Epoch 67/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1458 - mean_squared_error: 0.0398 - val_loss: 0.1572 - val_mean_squared_error: 0.0435\n",
      "Epoch 68/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1453 - mean_squared_error: 0.0395 - val_loss: 0.1540 - val_mean_squared_error: 0.0430\n",
      "Epoch 69/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1453 - mean_squared_error: 0.0395 - val_loss: 0.1551 - val_mean_squared_error: 0.0434\n",
      "Epoch 70/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1448 - mean_squared_error: 0.0391 - val_loss: 0.1551 - val_mean_squared_error: 0.0430\n",
      "Epoch 71/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1446 - mean_squared_error: 0.0390 - val_loss: 0.1615 - val_mean_squared_error: 0.0447\n",
      "Epoch 72/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1442 - mean_squared_error: 0.0389 - val_loss: 0.1577 - val_mean_squared_error: 0.0430\n",
      "Epoch 73/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1442 - mean_squared_error: 0.0389 - val_loss: 0.1594 - val_mean_squared_error: 0.0435\n",
      "Epoch 74/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1434 - mean_squared_error: 0.0385 - val_loss: 0.1600 - val_mean_squared_error: 0.0440\n",
      "Epoch 75/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1434 - mean_squared_error: 0.0385 - val_loss: 0.1532 - val_mean_squared_error: 0.0421\n",
      "Epoch 76/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1435 - mean_squared_error: 0.0385 - val_loss: 0.1566 - val_mean_squared_error: 0.0422\n",
      "Epoch 77/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1436 - mean_squared_error: 0.0385 - val_loss: 0.1549 - val_mean_squared_error: 0.0431\n",
      "Epoch 78/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1431 - mean_squared_error: 0.0384 - val_loss: 0.1549 - val_mean_squared_error: 0.0422\n",
      "Epoch 79/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1426 - mean_squared_error: 0.0381 - val_loss: 0.1601 - val_mean_squared_error: 0.0432\n",
      "Epoch 80/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1423 - mean_squared_error: 0.0380 - val_loss: 0.1588 - val_mean_squared_error: 0.0437\n",
      "Epoch 81/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1427 - mean_squared_error: 0.0382 - val_loss: 0.1583 - val_mean_squared_error: 0.0428\n",
      "Epoch 82/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1423 - mean_squared_error: 0.0380 - val_loss: 0.1563 - val_mean_squared_error: 0.0425\n",
      "Epoch 83/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1419 - mean_squared_error: 0.0378 - val_loss: 0.1528 - val_mean_squared_error: 0.0422\n",
      "Epoch 84/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1417 - mean_squared_error: 0.0378 - val_loss: 0.1558 - val_mean_squared_error: 0.0426\n",
      "Epoch 85/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1416 - mean_squared_error: 0.0377 - val_loss: 0.1589 - val_mean_squared_error: 0.0432\n",
      "Epoch 86/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1417 - mean_squared_error: 0.0378 - val_loss: 0.1564 - val_mean_squared_error: 0.0423\n",
      "Epoch 87/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1416 - mean_squared_error: 0.0377 - val_loss: 0.1591 - val_mean_squared_error: 0.0435\n",
      "Epoch 88/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1411 - mean_squared_error: 0.0374 - val_loss: 0.1552 - val_mean_squared_error: 0.0426\n",
      "Epoch 89/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1410 - mean_squared_error: 0.0375 - val_loss: 0.1552 - val_mean_squared_error: 0.0426\n",
      "Epoch 90/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1410 - mean_squared_error: 0.0374 - val_loss: 0.1593 - val_mean_squared_error: 0.0436\n",
      "Epoch 91/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1410 - mean_squared_error: 0.0374 - val_loss: 0.1564 - val_mean_squared_error: 0.0428\n",
      "Epoch 92/100\n",
      "900/900 [==============================] - 4s 4ms/step - loss: 0.1409 - mean_squared_error: 0.0373 - val_loss: 0.1587 - val_mean_squared_error: 0.0431\n",
      "Epoch 93/100\n",
      "900/900 [==============================] - 4s 5ms/step - loss: 0.1403 - mean_squared_error: 0.0371 - val_loss: 0.1558 - val_mean_squared_error: 0.0423\n"
     ]
    }
   ],
   "source": [
    "callbacks = [keras.callbacks.EarlyStopping('val_loss', patience=10),\n",
    "             keras.callbacks.ModelCheckpoint('models/features/model/besttest.h5', save_best_only=True)]\n",
    "\n",
    "f_history = feat_model.fit([X_train.drop(['userId', 'movieId'], axis=1), X_train['userId']], y_train, batch_size=100,\n",
    "                              epochs=100, validation_data=([X_valid.drop(['userId', 'movieId'], axis=1), X_valid['userId']], y_valid),\n",
    "                              verbose=1,\n",
    "                              callbacks = callbacks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "ec093116",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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empqKadOm4a+//kJ0dDQyMzPx8OHDfNfC/a86derkfGxnZwcHBwfExcXppcanYbgycjP3z8TysOV4s/ybGIGCrwdGRERERKRSqQq9NM9Y/bfr3/jx47Fjxw589dVXqFq1KsqUKYO33noLGRkZTz2OpaVlns9VKhV0Op3e6/0vLgs0cg28ZHq/+vCqwpUQEREREemHlZUVsrKynrnfgQMHMGDAAHTt2hW1a9eGh4cHIiMjDV9gETFcGblgr2AAwNW0q8/VhYWIiIiIyFj5+vri33//RWRkJO7evfvEWaWqVati48aNCA8Px6lTp9CrV68SmYEqKoYrI1e7fG1Yqi2RnJWMGw9uKF0OEREREVGxffjhh9BoNKhRowbc3NyeeA7VvHnzULZsWTRr1gydO3fGK6+8gvr165dwtYXHc66MnLWFNWqVr4Ww2DCExoTC381f6ZKIiIiIiIqlWrVqOHLkSJ5tAwYMyLefr68vdu/enWfbyJEj83z+32WCBa32SkxMLFKdz4szVyYg2EMuDQyNDVW4EiIiIiIiehKGKxMQ7CnDVVhMmMKVEBERERHRkzBcmYD6nnJd6cnYk2xqQURERERkpBiuTEBNt5qwUFng/qP7uJ54XelyiIiIiIioAAxXJsBKYwVfG18AwInoE8oWQ0REREREBWK4MhFVbasCYLgiIiIiIjJWDFcmooptFQBAaAw7BhIRERERGSOGKxNRpcz/h6voUDa1ICIiIiIyQgxXJqJSmUqw1ljjQfoDXL1/VelyiIiIiIjoPxiuTISFygJ13OsA4HlXRERERGTefH19MX/+/JzPVSoVNm3a9MT9IyMjoVKpEB4ebtC6GK5MSLCHvJgwwxURERERUa6YmBi0b99e6TJgoXQBVHjBnjJcsakFEREREVEuDw8PpUsAwJkrkxLkGQRANrXQCZ3C1RARERGRURECSE1V5u05Gq4tXboUFSpUgE6X9/nsa6+9hv79++Pq1at4/fXX4e7uDnt7ezRs2BC7du166jH/uyzw2LFjCAoKgo2NDRo0aICwsLDn+lYWFWeuTEgN1xqwsbBBckYyrty7gmrlqildEhEREREZi7Q0wN5emftOSQHs7Aq169tvv433338fe/bswcsvvwwAuH//Pnbs2IE///wTKSkp6NChA2bOnAkbGxusWbMGnTt3xqVLl1CpUqVnHj81NRWdOnXCSy+9hJ9++gnXr1/H6NGji/XwCoszVybEQm2Beh71APC8KyIiIiIyTS4uLnj11Vexbt26nG2//vorXFxc8PLLL6Nu3boYNmwYateuDX9/f8ycOROVK1fGli1bCnX8tWvXIisrCytXrkTNmjXRqVMnjB8/3lAPJw+GKxPTwLMBAIYrIiIiIvoPW1s5g6TEm63tc5Xau3dv/P7770hPTwcgA1GPHj2g0WiQmpqKjz76CDVq1ICzszPs7e1x8eJFREVFFerYFy5cQN26dWH7WE1NmzZ9rvqKissCTUwDLxmu2NSCiIiIiPJQqQq9NE9pnTt3hk6nw9atW9GwYUMcOHAAc+fOBQCMHz8eO3bswFdffYWqVauiTJkyeOutt5CRkVGoY4vnOP9L3xiuTEywl+wYeDLmJHRCB7WKk49EREREZFrKlCmDN954A2vXrsWVK1dQrVo1BAfL57kHDhzAgAED0LVrVwBASkoKIiMjC33sGjVq4Mcff8TDhw9RpkwZAMDRo0f1/hgKwmfmJqa6a3XYWtoiJSMFlxMuK10OEREREVGR9O7dG1u3bsXKlSvRp0+fnO1Vq1bFxo0bER4ejlOnTqFXr175Ogs+Ta9evaBWqzFo0CCcP38e27Ztw1dffWWIh5APw5WJYVMLIiIiIioNXnrpJbi4uODSpUvo1atXzvZ58+ahbNmyaNasGTp37oxXXnkF9evXL/Rx7e3t8eeff+L8+fMICgrC5MmT8cUXXxjiIeTDZYEmqIFnAxy+eRgnok+gT50+z74BEREREZGR0Wg0iI6Ozrfd19cXu3fvzrNt5MiReT7/7zLB/55n1aRJE4SHhz91H0PgzJUJYlMLIiIiIiLjw3Blgh5vapGly1K4GiIiIiIiAhiuTFJAuQDYWdohTZuGi3cvKl0OERERERGB4cokadQaBHkGAeDSQCIiIiIiY8FwZaIaeMrzrtgxkIiIiMi8KXnR3NJCX99DhisTxaYWRERERObN0tISAJCWlqZwJaYvIyMDgOxgWBxsxW6isptahMWEIVOXCQs1h5KIiIjInGg0Gjg7OyMuLg4AYGtrC5VKpXBVpken0yE+Ph62trawsCjec2o+IzdR1cpVg72VPVIyUnAh/gJqu9dWuiQiIiIiKmEeHh4AkBOwqGjUajUqVapU7HDKcGWi1Co16nvWx/4b+xEaE8pwRURERGSGVCoVPD09Ub58eWi1WqXLMVlWVlZQq4t/xhTDlQlr4NkA+2/sx4noExhQb4DS5RARERGRQjQaTbHPF6LiY0MLE8amFkRERERExoPhyoRlN7UIjw2HNovTwERERERESmK4MmFVXarC0doRjzIf4Xz8eaXLISIiIiIyawxXJiy7qQXApYFEREREREpjuDJxDTzleVcnok8oXAkRERERkXljuDJxbGpBRERERGQcGK5MXHZTi1Oxp5CRlaFwNURERERE5ovhysRVKVsFTtZOSM9Kx7m4c0qXQ0RERERkthiuTJxKpeLSQCIiIiIiI8BwVQoEe8qlgWxqQURERESkHIarUoAzV0REREREymO4KgUeb2qRnpmucDVEREREROaJ4aoU8HP2Q1mbstDqtDgbd1bpcoiIiIiIzBLDVSnAphZERERERMpjuCol2NSCiIiIiEhZDFelRPbMFcMVEREREZEyGK5KieymFmfjzuJR5iOFqyEiIiIiMj8MV6WEj5MPypUpB61OizN3zihdDhERERGR2WG4KiXY1IKIiIiISFkMV6UIm1oQERERESmH4aoUYVMLIiIiIiLlMFyVItlNLc7Fn8ND7UOFqyEiIiIiMi8MV6WIt6M33GzdkKnLxOk7p5Uuh4iIiIjIrDBclSJsakFEREREpByGq1KGTS2IiIiIiJTBcFXKsKkFEREREZEyGK5KmeymFufjzyNNm6ZwNURERERE5oPhqpSp4FAB7nbuyBJZOBV7SulyiIiIiIjMBsNVKcOmFkREREREymC4KoXY1IKIiIiIqOQxXJVCbGpBRERERFTyFA9XS5YsgZ+fH2xsbBAcHIwDBw48cd+YmBj06tULAQEBUKvVGDNmTIH7zZ8/HwEBAShTpgy8vb0xduxYPHr0yECPwPhkN7W4cPcCUjNSFa6GiIiIiMg8KBquNmzYgDFjxmDy5MkICwtDy5Yt0b59e0RFRRW4f3p6Otzc3DB58mTUrVu3wH3Wrl2LiRMnYsqUKbhw4QJWrFiBDRs2YNKkSYZ8KEbFy8ELnvae0AkdwmPDlS6HiIiIiMgsKBqu5s6di0GDBmHw4MEIDAzE/Pnz4e3tjW+//bbA/X19fbFgwQL069cPTk5OBe5z5MgRNG/eHL169YKvry/atWuHnj174sQJ81oix6YWREREREQly0KpO87IyEBoaCgmTpyYZ3u7du1w+PDhIh+3RYsW+Omnn3Ds2DE0atQI165dw7Zt29C/f/8n3iY9PR3p6ek5nyclJQEAtFottFptkWvRl+wanqeWeu718OflP3Hs1jFo6yv/GOj5FGXMyfRx3M0Tx908cdzNE8fdND3PeCkWru7evYusrCy4u7vn2e7u7o7Y2NgiH7dHjx6Ij49HixYtIIRAZmYm3n333Xwh7nGzZ8/GtGnT8m3fuXMnbG1ti1yLvoWEhBR6X/FAAAD2RezDtm3bDFUSGdjzjDmVHhx388RxN08cd/PEcTctaWlphd5XsXCVTaVS5flcCJFv2/PYu3cvZs2ahSVLlqBx48a4cuUKRo8eDU9PT3z66acF3mbSpEkYN25czudJSUnw9vZGu3bt4OjoWORa9EWr1SIkJARt27aFpaVloW5TP6U+Zi6cidvpt/FCmxdgb2Vv4CpJn4oy5mT6OO7mieNunjju5onjbpqyV7UVhmLhytXVFRqNJt8sVVxcXL7ZrOfx6aefom/fvhg8eDAAoHbt2khNTcXQoUMxefJkqNX5TzOztraGtbV1vu2WlpZG9YP/PPV4l/VGBYcKuJ18G2fvnkVLn5YGro4Mwdh+BqlkcNzNE8fdPHHczRPH3bQ8z1gp1tDCysoKwcHB+aZFQ0JC0KxZsyIfNy0tLV+A0mg0EEJACFHk45oiXu+KiIiIiKjkKLoscNy4cejbty8aNGiApk2b4vvvv0dUVBSGDx8OQC7Xu337Nn744Yec24SHhwMAUlJSEB8fj/DwcFhZWaFGjRoAgM6dO2Pu3LkICgrKWRb46aef4rXXXoNGoynxx6ikYM9gbL60mR0DiYiIiIhKgKLhqnv37khISMD06dMRExODWrVqYdu2bfDx8QEgLxr832teBQUF5XwcGhqKdevWwcfHB5GRkQCATz75BCqVCp988glu374NNzc3dO7cGbNmzSqxx2UsOHNFRERERFRyFG9oMWLECIwYMaLAr61evTrftmct7bOwsMCUKVMwZcoUfZRn0oK9ggEAlxMuIyk9CY7WyjfnICIiIiIqrRS9iDAZVnm78vB29IaAQFhMmNLlEBERERGVagxXpRyXBhIRERERlQyGq1Iu2FMuDWRTCyIiIiIiw2K4KuU4c0VEREREVDIYrkq57KYWEfci8ODRA4WrISIiIiIqvRiuSjlXW1f4OMnW9idjTipcDRERERFR6cVwZQa4NJCIiIiIyPAYrswAm1oQERERERkew5UZ4MwVEREREZHhMVyZgfqe9QEAV+9fxf2H9xWuhoiIiIiodGK4MgPlbMvBz9kPAJtaEBEREREZCsOVmeDSQCIiIiIiw2K4MhNsakFEREREZFgMV2aCM1dERERERIbFcGUmsptaXE+8jnsP7ylcDRERERFR6cNwZSbKlimLKmWrAABCo7k0kIiIiIhI3xiuzAiXBhIRERERGQ7DlRlhUwsiIiIiIsNhuDIjnLkiIiIiIjIchiszkt3U4saDG7ibdlfhaoiIiIiISheGKzPiZOMEfxd/AGxqQURERESkbwxXZoZLA4mIiIiIDIPhysywqQURERERkWEwXJkZzlwRERERERkGw5WZCfIMggoq3Ey6ibjUOKXLISIiIiIqNRiuzIyjtSOqlasGgE0tiIiIiIj0ieHKDHFpIBERERGR/jFcmSE2tSAiIiIi0j+GKzPEmSsiIiIiIv1juDJD2U0tbiffRmxKrNLlEBERERGVCgxXZsjeyh7VXasDYFMLIiIiIiJ9YbgyU1waSERERESkXwxXZopNLYiIiIiI9Ivhykxx5oqIiIiISL8YrsxUPY96UKvUiEmJQXRytNLlEBERERGZPIYrM2VnZYdA10AAbGpBRERERKQPDFdmjEsDiYiIiIj0h+HKjLGpBRERERGR/jBcmbHHZ66EEApXQ0RERERk2hiuzFhdj7rQqDS4k3oHt5NvK10OEREREZFJY7gyY7aWtqjhVgMAm1oQERERERUXw5WZY1MLIiIiIiL9YLgyc9lNLU7EMFwRERERERUHw5WZy565Co0OZVMLIiIiIqJiYLgyc3Xc68BCbYH4tHjcTLqpdDlERERERCaL4crMlbEsg5puNQGwqQURERERUXEwXFHO0sB/b/+rcCVERERERKaL4YrQpGITAMCXh7/Eu3+9i4S0BIUrIiIiIiIyPQxXhH51+6FnrZ7QCR2+C/0O/t/4Y8nxJcjUZSpdGhERERGRyWC4IlhprLDuzXXY238vapevjfuP7mPktpEI/j4Y+yL3KV0eEREREZFJYLiiHK18W+HksJNY1H4RytqUxek7p/HimhfR8/eeuPmAnQSJiIiIiJ6G4YrysFBbYGSjkbg86jKGBw+HCiqsP7se1RdXx6z9s/Ao85HSJRIRERERGSWGK2OXmgokJpb43brauuLbTt8idGgoWlRqgTRtGj7Z8wlqLK6BzRc384LDRERERET/wXBl7NauhUXFimj4v/9B9ccfQHp6id59kGcQ9g/Yj3VvrIOXgxeuJ15Hlw1d0H5te1y8e7FEayEiIiIiMmYMV8buyBGoMjLgdfQoLLp3Bzw8gCFDgH37AJ2uREpQqVToWbsnLr13CZNaTIKVxgo7ru5A7W9r48OdHyIpPalE6iAiIiIiMmYMV8Zu5Upojx9HRJcuEBUqyCWCy5cDL74I+PoCEycCZ86USCn2Vvb4/OXPcW7EOXSu1hmZukx8feRrVPumGlaHr4ZOlEzYIyIiIiIyRgxXxk6lAurWxfkBA5B55QqwezcwaBDg6AjcvAl88QVQp458mzNHbjOwqi5VsaXnFmzrtQ3VylXDndQ7eGfzO2i2ohmO3z5u8PsnIiIiIjJGDFemRKMBWreWM1d37gC//QZ06QJYWsrZqwkTAB+f3H0M3AijvX97nHn3DOa0mQN7K3v8e/tfNFreCIM2D8KdlDsGvW8iIiIiImPDcGWqbGyAN98E/vgDiI0Fli4FXngBEALYu1eel+XuLvfZuNFgjTCsNFYY33w8Lr93Gf3q9gMArAxfiWqLqmHekXnQZmkNcr9ERERERMaG4ao0cHEBhg6VTS4iI4HZs4GaNYGMDBms3nwztxHG3r0GaYTh6eCJNV3W4PDAwwj2DEZSehLG7RyHut/Vxa5ru/R+f0RERERExobhqrTx8cltchEeDowfDzzeCKN1a9kIY8IEgzTCaOrdFP8O/hfLOi+Dq60rLty9gLY/tsUbG97A9fvX9X5/RERERETGwkLpAshA/r8RBurWlTNZ+/cDP/0kz9O6eVM2v5gzB6hdG+jTB+jZU4aw9HTg0aMnv3/a1/7/vSY9HYMfPULf1E4Iv/EvrsdehHXmH7j42WbcerEdWsz9DSo7O6W/Q0REREREesVwZQ6yG2G0bg0sXgxs3SqD1tatuY0wJkzQ+91aA2j8/2+SDri8Hff/8ITzgqVQ9eghQyARERERUSnAcGVushthvPkmcO+enMlau1bObD1OpZL7WlsX/P5pXytgH2Flhb0Xt6Py6s3wiU8GevWCWLwYqgULgOBgZb4XRERERER6xHBlzrIbYQwdKs/J0mpzA5GlpV5nlVQAWmM4VnVbgmufjMTEg4DdoUMQDRtCNWAA8PnnsukGEREREZGJYkMLkpydATc3wMEBsLIy2HK9d5qNQI0F61BjlBo/1gFUQgCrVgHVqslzwAzUMp6IiIiIyNAYrqjE9azdEwuHbMTgt63QZBBwsYoTkJwsz/uqWRPYvFler4uIiIiIyIQwXJEiXq/+Ov7q+RfOVLZFjd4P8PngAOg8PYCrV4EuXYC2bYGzZ5Uuk4iIiIio0BiuSDFtq7TFjj474FDGEZMrXsJLH1fAw/Fj5Tlf//wj28iPHAkkJChdKhERERHRMzFckaJaVGqB3f12o1yZctiXEIrGfrsQf2K/7Gao0wFLlgD+/sDChbLhBhERERGRkWK4IsUFewVj34B98LD3wJm4M2ixty9urpgH7NkD1KkD3L8PjB4tZ7J27FC6XCIiIiKiAjFckVGoWb4mDrxzAJWcKuFywmW0XNUSV+t4AydPAt99B7i6AhcuAK++CnTuDFy+rHTJRERERER5MFyR0ajqUhUH3jkAfxd/3HhwAy1XtcT5e5eAYcOAiAhg7FjAwgL46y+gVi3gww+BBw+ULpuIiIiICADDFRmZSk6VsP+d/ahVvhZiUmLwwqoXcDLmpLwO19y5soNghw7y/Kuvv5bnYy1fDmRlKV06EREREZk5hisyOh72Htjbfy8aeDVAwsMEtF7TGoeiDskvBgQAW7cC27bJj+PjgSFDgAYNgP37lS2ciIiIiMya4uFqyZIl8PPzg42NDYKDg3HgwIEn7hsTE4NevXohICAAarUaY8aMybfPiy++CJVKle+tY8eOBnwUpG/lbMvhn37/oGWllkhKT0K7n9ph17VduTu0bw+cOQPMmwc4OQHh4UCrVkC3bsCNG4rVTURERETmS9FwtWHDBowZMwaTJ09GWFgYWrZsifbt2yMqKqrA/dPT0+Hm5obJkyejbt26Be6zceNGxMTE5LydPXsWGo0Gb7/9tiEfChmAo7UjtvfZjnZV2iFNm4aO6zriz0t/5u5gaQmMGSPPxxo+HFCrgV9/BRo1Au7dU6xuIiIiIjJPioaruXPnYtCgQRg8eDACAwMxf/58eHt749tvvy1wf19fXyxYsAD9+vWDk5NTgfu4uLjAw8Mj5y0kJAS2trYMVybK1tIWW3psQdfqXZGRlYE3fnkD68+uz7uTmxvw7bdAWBhQrRoQFwd8/rkyBRMRERGR2bJQ6o4zMjIQGhqKiRMn5tnerl07HD58WG/3s2LFCvTo0QN2dnZP3Cc9PR3p6ek5nyclJQEAtFottEZw4drsGoyhFiWoocbaLmsx6M9B+Pncz+j1ey8kPUzCO/XeybtjYCBUX38Ni86dIb75BpnDhgG+vorUXFzmPubmiuNunjju5onjbp447qbpecZLsXB19+5dZGVlwd3dPc92d3d3xMbG6uU+jh07hrNnz2LFihVP3W/27NmYNm1avu07d+6Era2tXmrRh5CQEKVLUNTbFm/jXrl72JGwA8O2DcOxU8fQ2a1z3p2EQLM6deB2+jRihwzBybFjlSlWT8x9zM0Vx908cdzNE8fdPHHcTUtaWlqh91UsXGVTqVR5PhdC5NtWVCtWrECtWrXQqFGjp+43adIkjBs3LufzpKQkeHt7o127dnB0dNRLLcWh1WoREhKCtm3bwtLSUulyFNVRdMTE3RMx7995WHF7BSpVrYSJzSbm/Znx8gIaN4b3vn3wmDMHCApSruAi4pibJ467eeK4myeOu3niuJum7FVthaFYuHJ1dYVGo8k3SxUXF5dvNqso0tLSsH79ekyfPv2Z+1pbW8Pa2jrfdktLS6P6wTe2epTy9Stfw8nGCVP3TcWUfVOQlpmG2S/Pzg1YjRoBvXoB69bB8uOPgZAQQE+BvaRxzM0Tx908cdzNE8fdPHHcTcvzjJViDS2srKwQHBycb1o0JCQEzZo1K/bxf/nlF6Snp6NPnz7FPhYZF5VKhSkvTsFXbb8CAHxx6AuM+nsUdEKXu9PMmYCVFfDPP8DOnQpVSkRERETmRNFugePGjcPy5cuxcuVKXLhwAWPHjkVUVBSGDx8OQC7X69evX57bhIeHIzw8HCkpKYiPj0d4eDjOnz+f79grVqxAly5dUK5cuRJ5LFTyPmj2Ab7r+B1UUGHx8cUYuHkgMnWZ8ot+fsB778mPJ0wAsrKUK5SIiIiIzIKi51x1794dCQkJmD59OmJiYlCrVi1s27YNPj4+AORFg/97zaugx86fCQ0Nxbp16+Dj44PIyMic7ZcvX8bBgwexkzMWpd6wBsNgZ2WHAZsGYM2pNUjVpmLtG2thpbECPv4YWLECOHUKWLsW+E9QJyIiIiLSJ8UbWowYMQIjRowo8GurV6/Ot00I8cxjVqtWrVD7UenQp04f2Fnaoftv3fHb+d+QqcvExm4boSpXTgasCROATz4BunUDbGyULpeIiIiISilFlwUS6UvXwK74s+efsNJYYdPFTTh666j8wqhRgLc3cPMm8M03yhZJRERERKUawxWVGq9UfQU9a/UEACwNXSo3likDzJghP541C0hIUKg6IiIiIirtGK6oVBkWPAwAsOHcBtx/eF9u7NMHqFMHePAA+PxzBasjIiIiotKM4YpKlSYVm6B2+dp4lPkIP57+UW7UaIA5c+THixYBjzU/ISIiIiLSF4YrKlVUKlXO7NXS0KW5jU3atQPatAEyMmRzCyIiIiIiPWO4olKnT50+sLW0xfn48zh085DcqFIBX3whP167Fjh5UrkCiYiIiKhUYriiUsfJxgk9avYA8FhjCwCoXx/o3Vt+PH48wHb9RERERKRHDFdUKg1vMBwA8Ou5X5GQ9liHwJkzASsrYPduYMcOhaojIiIiotKI4YpKpQZeDRDkEYT0rHT8cOqH3C/4+gLvvSc/njAByMpSpD4iIiIiKn0YrqhUemJjCwCYPBlwdgZOnwZ++kmZAomIiIio1GG4olKrV+1esLeyx6WES9h/Y3/uF1xcgI8/lh9/8gnw8KEyBRIRERFRqcJwRaWWg7UDetXqBeA/jS0AYNQowNsbuHUL+OYbBaojIiIiotKG4YpKtWEN5NLA387/hvjU+Nwv2NjI5hYA8PnnQEJCAbcmIiIiIio8hisq1ep71kcDrwbQ6rRYHb467xd79wbq1gUePABmzVKkPiIiIiIqPRiuqNTLbmzx/cnvoRO63C9oNMCcOfLjRYuA69cVqI6IiIjMRnKy0hWQgTFcUanXo1YPOFg54Mq9K9hzfU/eL7ZrB7RpA2i1srkFERERkSGsWAHLcuVQfe1apSshA2K4olLP3soefer0AVBAYwsgd/Zq3TogNLQEKyMiIiKzcOUK8P77AICAX3+FKiRE4YLIUBiuyCxkLw384+IfuJNyJ+8Xg4KAPjJ8Yfx44PFrYhEREREVR1YW0L8/kJYGYW8PANAMHAjcufOMG5IpYrgis1DXoy4aV2iMTF0mVoWvyr/DjBmAlRWwZw+wfXvJF0hERESl01dfAYcPAw4OyDxyBA98fKC6cwcYMADQ6Z55czItDFdkNrJnr5adXJa3sQUA+PrKa18BwIQJ8lUmIiIiouI4cwb47DP58YIFQEAAQj/8EMLGRr6YO3++ouWR/jFckdnoXqs7nKydcO3+Ney6tiv/Dh9/DDg7yz+EP/5Y4vURERFRKZKRAfTtK9937ixnqgAke3tD9/XXcp+JE3m+dynDcEVmw9bSFn3r9AXwhMYWLi4yYAHAp58CDx+WYHVERERUqkyfDpw6BZQrB3z/PaBS5XxJN3gw8MYbsltxjx5s0V6KMFyRWRnWQC4N3HxxM2KSY/LvMGoUUKkScOsWsHBhCVdHREREpcLRo8Ds2fLj774DPDzyfl2lApYtA7y9ZSfB7FMTyOQxXJFZqVW+Fpp5N0OWyMLKsJX5d7CxAWbOlB9//jlw927JFkhERESmLS1NdgfU6YBevYC33ip4PxcXYO1aQK0G1qyRH5PJY7gis/N4Y4ssXQGNK3r3BurWBZKSgFmzSrg6IiIiMmkTJwKXLwNeXsCiRU/ft2XL3IYX774LXL1q+PrIoBiuyOy8XeNtlLUpixsPbmDn1Z35d1Crcy8svHgxcO1ayRZIREREpumff4BvvpEfr1wJlC377NtMnixDVnKynOnSag1bIxkUwxWZnTKWZdCvbj8AT2hsAQDt2gFt28o/cJ98UoLVERERkUl68AB45x358fDhwCuvFO52FhbATz/JIHbsWO5MFpkkhisyS9lLA/+6/BduJ90ueKcvvpAnnP78M3DiRAlWR0RERCZnzBjg5k2gcmXgyy+f77aVKgHLl8uPv/gC2FXAJWPIJDBckVkKdAtEy0otkSWysCJsRcE7BQXJ868AYPx4QIiSK5CIiIhMx5YtwOrV8kXZNWsAe/vnP8Ybb8gZLyHk9bHi4/VeJhkewxWZrezZq+Unlxfc2AKQnQOtrIC9e4G//y654oiIiMg0xMcDQ4bIjz/8EGjRoujHmjsXqFkTiI2VFx3mC7smh+GKzNabNd5EuTLlcDPpJv6+8oTg5OMDvP++/HjCBCDrCSGMiIiIzI8QsstfXJwMRdOnF+94ZcoA69fLS8Ns28ZrbpoghisyWzYWNhhQbwCApzS2AICPP5YnmZ49C/zwQ8kUR0RERMZv3Trg999lU4off5ShqLhq1ZIzWADw0UdAWFjxj0klhuGKzNrQ4KEAgG0R23Dzwc2CdypbVgYsAPj0U3lxQCIiIjJvt24B770nP/7sM3mutr4MHw506QJkZAA9egApKfo7NhkUwxWZtWrlqqG1b2vohA7LTy5/8o7vvSc7+dy+zSl6IiKikpSVJa8BZUyEAAYNAhITgYYNgUmT9Ht8lUp2D6xQQV6QePRo/R6fDIbhisxeTmOLsOXI1GUWvJONDTBrlvx49mzg7t0Sqo6IiMiM6XTAa6/JVSRTpwKZT/g/XdK++w7YuVM+P/jhB7ksUN/KlQPWrpVBa+VKeS4WGT2GKzJ7XQO7ws3WDdHJ0fjr8l9P3rFXL6BePSApSXYRJCKiXEIAqalKV0GlzapVsrFDVhYwbRrQsiVw9aqyNV25IrsCAsD//gdUr264+2rVCvjkE/nxsGHA9euGuy/SC4YrMntWGiu8U09eUf2pjS3UamDOHPnxggUyaI0dK69tkZho8DqJiIzWxYtAgwaAuztw5IjS1VBpERubG2K6dwecnICjR+X/39WrlWlTnpUlW6SnpQGtWwOjRhn+Pj/7DGjWTL6426sXoNUa/j6pyBiuiAAMCZbXp9hxZQciEyOfvGPbtsBQ2QQDp04B8+cDr78OuLgAwcHyn8DWrcCDBwavmf5faqpc6755s9KVEJkfIYClS4H69YGTJ+Xv43vvyaVcRMU1Zox88TI4GPjpJ/l/94UXZHOHd94BunUD7t0r2Zq+/ho4dAhwcJCzauoSeCptYSG7EmaHy6lTDX+fVGRF+olYs2YNtm7dmvP5Rx99BGdnZzRr1gw3btzQW3FEJaWqS1W0qdwGAgLLQpc9feelS+WraevXy24+AQHyCcbJk/KPbqdOMmw1aiSvjbV9u/GdiFtaZJ9Q/L//AW++Cfz7r9IVEZmPhATgjTfk38GHD4GXXwYcHeXfwjVrlK6OTN3WrcCGDYBGAyxbJgOGjw+we7c899nCAvjtN6BOHbmtJJw5I7sGA/LFVR+fkrlfQN7Xsv9/fjJ7NrBnT8ndNz2XIoWrzz//HGXKlAEAHDlyBIsWLcKcOXPg6uqKsWPH6rVAopKS3dhiZfhKaLOeMeXu7i6XKHz7rVwOc/u2POl0yBCgalX5qu3x43IZYfv28kTcpk1lS/edO3legr589ZX85wvIpRq9ejHIEpWEf/6RT2o3bQIsLeULSzt35j7x/Phj/i5S0aWkACNGyI/Hjs3b4lyjASZOlMtPq1WT/3/btAHGjwfS0w1XU0YG0K+ffN+pk5w5K2lvvy2fZwgB9OnD5lpGqkjh6ubNm6hatSoAYNOmTXjrrbcwdOhQzJ49GwcOHNBrgUQl5fWA1+Fu547YlFhsubTl+W7s5SWf2H//PRARAURFye5BAwcCfn7yif/Ro/LVpldekWGrRQv5ROSff+SrvvR8QkLkP1gA+Pxz2Sr/2rWSWf9OZK4yMuRFTdu2BaKj5Yn8//4LjBsnl0e9/758gSk2Vv5eEhXFp5/K/6N+fk9eAteggZwlHTpUho2vvgKaNAEuXDBMTTNmAOHhsoPfsmWyg58S5s8HAgPl79/Agcqcd0ZPVaRwZW9vj4SEBADAzp070aZNGwCAjY0NHvJJIpkoS40lBgYNBPCMxhaF4e0N9O0LrFghn/BHRsq12f36ya9ptXLN9syZ8hU3Z2fZEWjqVGDvXuDRo2I+mlLu2jU5c6jTyX8uEyfK9fhqtVyOlD2bRUT6c+mSPKn+yy/lE7phw4DQ0LyzClZWchYLAObOlb+rRM/j+PHc60l++y1gZ/fkfe3s5FL9TZsAV1cZfurXB5Ys0W/oOHZMvjiaXZOHh/6O/bxsbYGffwasrYE//wQWL1auFipQkcJV27ZtMXjwYAwePBiXL19Gx44dAQDnzp2Dr6+vPusjKlFD6g+BCiqEXAvB1Xt6bPXq4yO7C61ZA9y4IdvILl8O9O4tZ70yMoD9+2Wb2datYeHmhqZTp8r13ZRXaqq8av39+/K8tsWL5SuILVvKpUiAfNLH8z+J9EMI+feqfn0ZplxcgD/+kNf5sbXNv3/nzvJFo4wMuVSLqLC0WrnsTaeT/x9feaVwt3v9deD0abn/o0fAyJHy5/DOneLXlJYmXxjNygJ69pRL85RWt66cqQNkI61Tp5Sth/IoUrhavHgxmjZtivj4ePz+++8oV64cACA0NBQ9e/bUa4FEJcmvrB/aVWkHAFh28hmNLYpKpQIqV5aNGH76Cbh1S159felSoEcPwMMDqvR0lA8Ph0Xz5vJVMk77S0LImaozZ+R5bxs3ygs4ZvvsM6BxY9mtsW9f+c+QiIru3j3grbfkE960NNm04swZ+QLHk6hUwLx5ciZ540Y5G09UGHPnyqDg4iJ/hp6Hp6e8HtaCBXJWZ+tWoHZt+b44Jk2Ss7ZeXsCiRcU7lj5lB8j0dPncgedyG40ihStnZ2csWrQImzdvxquvvpqzfdq0aZg8ebLeiiNSQnZji1Xhq5CRlWH4O1SpAH9/uW7855+B6GhoT51CbHAwVI8eyZN633yz5NvNGqM5c4BffpEn0P/+O1ChQt6vW1rKxiL29sCBA7KLIBEVzZ49smnFxo3yd2vOHNm0wsvr2betVUt2EQRkO22+0EHPcvVq7vlVc+cCbm7Pf4zs8/5OnJDBKj5eNp8YOVK+OPC8du/OXaK4YoUMfcZCpQJWrpS/jxcvysYfZBSKFK62b9+OgwcP5ny+ePFi1KtXD7169cL9+/f1VhyREjpV6wRPe0/EpcZh08VNJV+ASgUEBuLfyZOR9eWX8knNH3/IZQDm3DBmxw75CiIg/9k1b17wflWq5K5BnzKF7dmJnldGhjyP8eWXZSe2atVkQ57x45/vmj7TpsnzSU+dkk9MiZ5ECBnGHz2SP3f9+hXveLVqyfOksgPHkiXyWllhYYU/xoMHuR0Bhw0DHptMMBqurnIFjEolm2z8+qvSFRGKGK7Gjx+PpKQkAMCZM2fwwQcfoEOHDrh27RrGjRun1wKJSpqlxhKDggYB0ENji+JQq6EbPVo+qfH3l8sHX3xRPmHJzFSuLiVcvSqXPQgBDB4s/9E9Td++cn+2Zyd6PhER8oWLL76Qv29DhsiObPXrP/+xXF1zZyI++YQXV6cn+/FHYNcuucz7u+/004nPxkbOgO3cKZcMXrwol43PmVO4i1yPHSs7FlaunHt+kzFq3Tr3hcchQ3i+sREoUri6fv06atSoAQD4/fff0alTJ3z++edYsmQJ/v77b70WSKSEwfUHQwUVdl/fjYiECGWLyT6JvH9/+Q9h6lTgpZeAmzeVraukpKTI8zsSE2Wb3UWLnv2PV6WS56qxPTtR4QghlxgFBcklVWXLyqW333//9G5tzzJihGzXHh8vW1kT/Vd8vGzlD8j/b/9/qR+9adtWNrvo2lU2zJgwQTZcedr/0D//lB1+VSpg9Wq51NyYTZ0q/z8+eCBfUDS3F2CNTJHClZWVFdL+f+3qrl270K6dbADg4uKSM6NFZMp8nH3Q3r89AOD70O8VrgaAg4P8A//TT7nnE9WtK9vPlmZCyGUZZ8/K1re//y5PVC4MZ2e2ZycqjPv3gW7dZJOd1FT5Svjp08AbbxT/2JaWcvYAkMt5IxR+sYqMz7hxQEKCPL/PUKufXF3l/4/ly2WHy+zzCX/5Jf++d+/KGSAA+OAD2YnW2FlaAuvWAY6OwOHDwPTpSldk1ooUrlq0aIFx48ZhxowZOHbsWE4r9suXL6NixYp6LZBIKdmNLVafWo30TANe9f159O4t14w3aCCfEHXtKk/ULa3Xl/viC+C333IbWBTmRPrHsT070dPt2yefZP72G2BhIZvAhIQA+vxf3r69fNNq5ZNVAqKjoZ4xA35btwJxcUpXo5ydO/OeM2Rpabj7UqnkCwjh4UDDhnI1RPfu8jIp2RMDQgDvvitbuNesaVqzrX5+cqYZkNfQnDoV+OYbuW31atkwa+NG2T1x1y75Iu2xY/KcyIsXgevX5YWJExLkihGtlp2Ki0oUwY0bN0THjh1FnTp1xPLly3O2jxkzRowaNaoohzQqDx48EADEgwcPlC5FCCFERkaG2LRpk8jIyFC6FLOizdKKCl9XEJgKse70uhK972eOeXq6EOPHCyH/9AlRu7YQ586VaI0G9/ffQqhU8vF9913Rj5ORIUTjxvI4LVsKkZmpvxr1jL/r5kmRcc/IEOLjj3N/x/z9hTh+3HD3d+GCEBYW8r527jTc/Rg7rVaI+fOFcHDI+fut02iEaN9eiJ9+EiIlRekKS05KihB+fvL7MHp0yd53RoYQkycLoVbL+/fzE+LQISHWrpWfW1gIERpqoLs28O/7wIG5zw2K+6ZSCWFjI4SjoxBubkJUrChElSpC1KghRP36QowaJcTdu4Z5HEbmebJBkcJVacdwRdmm7JkiMBWi1apWJXq/hR7z7duFKF9e/hEsU0aIpUuF0OlKpkhDiogQwtlZPq4hQ4p/vCtXhLC3l8ebObP4xzMQ/q6bpxIf94gIIRo1yn0CNXCgEMnJhr/f0aPl/dWsKUOGuTlyRIh69XK+71nBweKev3/eJ7O2tkL07i3Etm2l/3uU/QKht7cQSUnK1HDggBA+PrIOtVoIOzv58bRpBrtLg/++p6YKMWOGEH37CtGtmxCvvy7Eq68K0bq1EM2aCREcLEStWvIFlUqVhHB3F6JsWfmzp9E8fwBzcRHi22+N+oVLfSiRcJWZmSl+++03MWPGDDFz5kzx+++/i8xS8o1luKJsNx/cFOppaoGpEBfiL5TY/T7XmMfGCtGuXe4furffFuL+fYPXaDDJyfLJFyBE06ZCPHqkn+OuWSOPqdEIcfSofo6pZ/xdN08lNu46nRCrVuW+0ODsLMSvvxr2Ph937558IgYIsWhRyd2v0hIShBg6NHeW0NlZiO++ExkPH8pxP3tWiM8+kzMCjz9pdXMT4r335N+r0vCi2eNOnsx9Iv/XX8rWkpgoRJ8+ud/3hg3lzJaBGP3f+cxMGdDu3RMiJkaIyEghLl0S4vRpObt98KAQ//wjxIYNQtSpk/t9CwqSs3+llMHDVUREhPD39xe2trYiKChI1KtXT9ja2oqAgABx5cqVohzSqDBc0eM6r+ssMBVi7PaxJXafzz3mWVlCzJmTu+zGx8c0/8jpdEK8+aZ8DJ6eQty+rd9j9+ghj125snKvlD4Ff9fNU4mM+717QnTvnvtEqFUrIaKiDHd/T7JoUe6r3QkJJX//JSkrS4iVK4Vwdc39vvfvL8SdO0KIAsZdp5NBatQoGaweD1pVqsgAdumSco9HX7RaOXsCyJkVY7F+vZw1vHrVoHdTqv7Oa7VCfPNN7koTQIh+/WQoK2WeJxsUqaHF+++/jypVquDmzZs4efIkwsLCEBUVBT8/P7z//vv6Oh2MyChkN7ZYc2oNHmU+UriaJ1Cr5QU+Dx+WF9G9cQN44QVg1ix5rSdTMXu2bFxR1AYWT8P27GRuIiPlBbU7dJC/Sxs2yKYVn38O/PMP4O1d8jUNGyYbBdy7J6/ZV1qdOQO0agUMHCi7z9WsKZuHrF4NlC9f8G1UKnkdpoUL5cWbt22TTYxsbeW1/qZPBwICZDOG+fOB2NiSfET688038vIizs7AggVKV5Ore3fZXKNyZaUrMR0WFsB77wGXLslmISoV8MMP8sLj8+bJphhmqEjhat++fZgzZw5cXFxytpUrVw7/+9//sG/fPr0VR2QMXq36Kio5VcK9h/fw2/nflC7n6Ro2lBf87N1bhqpPPpHX+Lh9W+nKnm3bNlkvIJ8QNm2q//tge3YqzbRaYO9e+UJLzZqye9h77wF//w08egQEBgKHDskLjmo0ytRoYSGfdAHy9/zCBWXqMJSUFPn9DwoCDh6UwWjOHNnl9YUXCn8cS0vZYfGnn2Q3wbVr5ecajbwO2dixQIUKwCuvyCezpnKh9MjI3L/zX34pL7FBpq98ednm/uhR+TwkOVm21a9XT76QY2aKFK6sra2RXMAvckpKCqysrIpdFJEx0ag1GFJfXvNiaehShaspBEdHebX71avlxT/37JHXxPrrL6Ure7KICHnhQyHkK9vZ1xgxhP+2Z4+KMtx9ERlaXJx8oaBbN8DNTV6j6quvgPPn5RPxF16Q7dXPnAHOnQMaNVK6YvmCT+fO8gWg0tKaXQg52x4YKL//WVnyUhkXLsiwVZwW43Z28u/jtm2yVfY338gLxup0spV5//6AuzvQo4f8O2+sswXZbc7T0uTP5cCBSldE+taokQxYy5fLa4udPy8v2Nytm1n9ry1SuOrUqROGDh2Kf//9F0Ket4WjR49i+PDheO211/RdI5HiBgYNhEalwcGogzgXd07pcp5NpZL/cE+elK+gJiTIJzOjRwPpRnLNrmzJyUCXLvLK8s2aySUxhvbZZ3L5zYMHQJ8+prV0ksybTidnLqZNk09kPDzkdXp+/VX+PLu6An37AuvXA/HxcinahAlArVry74Kx+PprGTj+/lu+mbJr14COHYG33gJu3QJ8fWXI2bhRLkPWp/Ll5WzkkSPyRalp0+QSrIcP5Ux8586ApycwYoScpTSm6xStXw9s3w5YWclrL6mL9BSUjJ1aLZcIXr4sf1bVavn3KTBQnqrwyEhPr9CjIv1kL1y4EFWqVEHTpk1hY2MDGxsbNGvWDFWrVsX8+fP1XCKR8rwcvPBagHzhwCRmr7JVqyb/CY8dKz9fuFC+4nnpkrJ1ZRNCPjE8f16eE/Lbb/Ifr6FZWsplNvb28kKK//uf4e+T9CsxUS6H+v13+SLC/ftKV2Q4SUnyd2PgQPl70rChvEDo8ePyd6h+feDTT+UrxrGx8vvSvTtQtqzSlT+Zvz+QfY72uHHGO9vyNOnp8iKzNWvKgGhpCUyeLGcIO3Y0/P1XrSpfKLp4Uf4sjBkjZ7ASEuT5pS1ayPOHvvhC+RfV7t2TL+4BcllgQICy9ZDhlS0rZ1lPnpQrRtLS5NjXqiUvZFyaFadzRkREhNiyZYvYvHmziIiIKM6hjAq7BVJBtkdsF5gK4TTbSaRmpBr0vgwy5lu35natsrWVXayUbu87c6asx8pKXgOmpBlZe3b+rhdCQoIQn34qL2r53+utODkJUbeuEF26CDF2rBALFwrx559CnD1r1BdnLbBr3IULQnz1lbw2TXYX0Ow3e3shunYVYvly/XbULGmJibld8ebPV7qa5xMSIq8TlD0mL70kxMWLz3UIg/y+a7VC7NghO7Zlt9zPvkj09u36u5/n9c47so4aNYRIT1euDiNgln/ndTp5gWYvr9yfyU6d5DUoTcTzZAOVEIWbMx43blyhA9vcuXOLGPWMQ1JSEpycnPDgwQM4OjoqXQ60Wi22bduGDh06wLI467apWHRCh6oLq+J64nWsen0VBtQbYLD7MtiYx8TIJUPZJ5j26CE7UPn76+8+CmvrVrmERQhg2TJg8OCSr0EIeS7D+vXyFd7wcMDBQZk6Nm+GbtYspF+/DquuXaHp2VN2G1Oq8YCxuXtXNkL45pvck/erV5dNSq5fB+7cefYxypeXS7b8/PK/VapUMrOmBdBqtdi+aRPalykDix075Lk1167l3alaNTkb0rGjnJGwtlakVr37/nt57qOzs1zm5uqqdEVPFx0tZ9qym+F4eABz58q/pc+57NLg/9vT0oBffpHnmMbEyG1vvinr1fdyxafZvRt4+WX5/Tl4UC7/NmNm/ZwuORmYOVP+DGZmyr+548fLJjt2dkpX91TPkw0KHa5at25dqDtXqVTYvXt3ofY1VgxX9CSzD8zGx7s/RpOKTXBk0BGD3Y9Bx1ynk92rPvkk91yj2rXlP9033iiZczMuX5bnizx4AAwfLpewKCUxUTb8iIqS56mtXl1y963TAZs2yYB76lT+r5cvL8/j6N4daN7cPINWfLw8P2fRIiA1VW6rU0cuh+raNfe8jbQ02Yns+vXct8c/T0x8+v2o1bL7WnbYejyE2dgAGRlFe9Nqn7mP7uFD6MLDYfH40i0rK+DFF2Ub9Y4d5RKw0igrCwgOlj//I0bIDoLGKDNT1vbpp/IJoloNjBwplwU6ORXpkCX2vz0pSS4jXbhQfr9tbeXjGDfO8C8oPHwof1+vXDHu8S1BfE4HuZT1/feBkBD5ube3DFxvvmlc54Y+5rmygYFn0UwSlwXSk8QkxwiL6RYCUyEORx022P2UyJgfOSJEu3b5lxz5+wsxcaK8Ershlg0+eCBEYKC8r+bNjWOJyP79QqjVsqb16w1/f1lZQvz2W96r2zs4iMyJE8XhTz4RWQMHyousPj4unp5CvP++EAcPytuXdrGxQnz4oVzCmv09CAoS4o8/ivb4798X4uRJIX7/XS63GzlSiI4d5TKlMmXyLzFU4E1XoYIQQ4YIsWmTEMnJ+v6OGq89e+T3QK0W4swZpavJ78gRIerVyx2rRo2ECA0t9mFL/H/76dNCtGyZ+zgCAuTyRkP6+GN5X15echko8TldNp1OiI0bhfDxyf2ZfPllIc6dU7qyAhlkWaA54cwVPc2gzYOwMnwlGldojMODDkOt0n/HoxId83v3gD//lJ2tduzIe+JzpUpyNuvNN+V1p4o7c6LTyWNt2iRPzA8NNZ7rnHz6qVyu4OQEnD5tmGUzOp38Pk+fLltjA3IZ4ujRwNix0Do45I47IJdvbtgA/PGHnOXLVrGibG3brZucATTSV/qKJCZGzqwuXSpf9QaABg3kTFWnToZ5rELIluYFzXpFRuYuX7G0lO8L+1bI/TNVKhyIjkaLESNgaa6XM3nzTfm70aaNbC9uDD/T9+7J5UrLlsmfEWdn2fxm8GC9zCIr8r9dCNnM58MPc5fSdusmZ4crVtTvfZ05I5utZGbKse3aVb/HN1F8TvcfaWnyb/7//ieff1hYyFmtKVPkpWWMBGeuiokzV/Q00UnRwv5ze4GpED+e+tEg96HYmCclyZmbt98Wws4u7yvrHh5CDB8uX+ksal3Tp+c2sDCCBhJ5ZGQI0bixrK9lSyEyM/V37KwsIX75RYhatXK/n46OsjFDQsJjJTxh3B89ko0Z+vQRwsEh77j4+AgxfrwQJ04o36CkOG7dEmLUKCGsrXMfW+PGQmzbZtqPqxD4N14IcfWq/LsACLF5s7K1ZGUJsWpVbgMgQIj+/YW4c0evd6PouN+/L2fCs2fs7eyEmDNHfysJMjNz/5527aqfY5YS/H1/gqtXhXj99dzfOXd3IX74wWj+/j9PNmC4KgDDFT3L5/s/F5gKUeHrCiIlXf9dyIxizNPS5PKkvn1lF7bHn9C7uAgxYIB8wv/oUeGO9+efQqhU8vYrVhi09CK7ciW3w9bMmcU/XlaWEBs2CFGzZt5Q9dlnQty7l2/3Qo37w4dyaVyPHvkDcJUqQkyaJER4uNH8Q3qmqCghRozIfWINCNGsmex4ZiqPoZiM4vfdGEycKMe/atXC/13Rt5Mn5c9f9s9izZpC7NtnkLsyinEPD8/7eAMDhdi9u/jH/eab3L93t24V/3iliFGMuzHbti1vJ85mzYS4dEnpqhiuiovhip7lofah8J3vKzAVYsqeKXo/vtGNeXq6bOM7ZEhu6+THzhUSPXsK8euvT253ffFibuvsESNKtvbnpY/27JmZcgbw8VDl5CTElCkFhqpszz3uqany+/722/nPG6pWTc6MGeM5LEIIcf26EMOGCWFpmVtzy5ZC7NplNqEqm9H9vislKUm+Wg0I8eWXJXvfCQlCvPtu3pmcL74o+ix9IRjNuGdlCbF6dd6/7T17Fr3Nf1RU7otUS5bot9ZSwGjG3Zg9eiTE//4nfw9tbYW4eVPpihiuiovhigrj13O/CkyFKDOzjIhKjNLrsY16zDMz5Qnoo0YJUaFC3if0ZcrIJSA//ZR78vKDB0JUry6/3qKFcTSweBqdToju3WW9lSvLJ3yFlZkpxM8/yyYJj4eqqVPlMpxnKNa4JyfLQNe1a96ldYCsZ9o0ee0kpV29KsTgwXkbqbRuLX+mzJRR/76XtBUrcmc89LwMr0CZmUIsXSpEuXK5P489epTIkzmjG/d792Sjl+yAaW8vxNdfP1/A1OmE6Nw5d8bBHJrvPCejG3djdvOmXEFjBBiuionhigpDp9OJlitbCkyF6PV7L70e22TGPCtLdtL68EMh/PzyPqG3tBSifXshXnxRfl6hguwAZwru3xeiUqXccy2eJTNTiHXrcrsgAkI4O8tAU4hQlU1v4/7ggQy4nTvnXW4HyA6Fn34qLyL9999CnDolRFyc4Z8ERUTIC4lqNLm1tGkjOzWaOZP5fS8JWVlC1K8vfz6GDDHsfR09KkSDBnmXAJZgyDfacQ8NFaJJk9zvS61ahV8a+dtvuX//z541bJ0mymjHnZ7qebKB/tucEZkJlUqF+a/OhwoqrDuzDkduGu66V0ZLrQaaNAG+/BK4ehUIC5PXzwoMlNf3+ftvYO9eecHTjRsBd3elKy4cZ2fgp5/k41uzJveCof+VlQWsWyevDdarF3Dhgrzt9Omyy9xnn8nPS5qjI9C7N7Bli+wItnq1vF6ShYXshDhjBjBwINC+vbzGV/ny8lpOlSoBjRsDXbrIa9LMmAEsXy4v+BwWBsTG5l4brbAuXwb69QMCAoBVq+TtX3kFOHRIXuOkZUtDfAfIVKnVwPz58uPly+WFvfUtLg4YNEj+7TpxQv6+zJ8vf8ZffFH/92dq6teXv58rVsiLOp89Ky9o3rev/BvwJImJwHvvyY8nTgRq1iyRcomMjYXSBRCZsvqe9fFOvXewMnwlxuwYgyODjhikNbtJUKmAevXk24wZMmhs3CjD1bvvypbhpqRlS+Djj2V79mHDZCv67PbsWVnA+vXycV66JLeVLSsvyjlqVJEvKmoQzs7y4sj9+8vW0n/8ARw8KFuex8QA0dHA3bsyDN+8Kd+eRqORIdnTU755eeV+/PjniYnA55/L75NOJ2/boYMMnI0bG/pRkylr2VK2B//lF2DMGGDPHv20Zs/MlBcs//TT3EsbDBggW0Cbygs/JUWtli/AdOkCTJ4sL43w00/yBZvp0+UFlC3+8xRy4kQZvgIC5N9OIjPFcEVUTLNenoVfzv+CY7ePYe3ptehbt6/SJRmHwED5T3nyZKUrKbrPPpOzK//+C/TpA+zaJZ/wzZghZ2QAwMUlN1QZ0TU5CuTiIl+xHzQo7/aMDDnDlR22Hg9e2R/HxMh9srLk9ujowt9v587ye9mggX4fD5Vec+bIJ/L79skXad58s3jH279fzqpkX1+ufn1g0SL5ogk9mYuLDKQDB8rZ7BMnZOBduRJYsgRo3lzud+CADGCAfG9jo1jJREpjuCIqJg97D0xuORmT/pmEif9MxBuBb8DOyk7pskgfLC3lBTfr1ZNPHry8gIQE+TUXF+CDD+QTNmMPVc9iZQV4e8u3p8nMlEuqCgpfj3+cvXywSxcZqoKCSuRhUCni4yMvdDtzpnzfsWPRnrBHRwPjx8vlu4CcYf78c2DIEL1cCNhsNGwIHD0qlwpOmiSXF7doIWfEZ8wAhg6V+w0eLJcQEpkxhisiPRjTZAy+D/0e1xOv44tDX2B66+lKl0T6UqUKsHixfBKRkACUK5cbqhwclK6uZFlYyIDp5fX0/bKy5GxYmTIlUxeVThMmyBmSyEh5TtTEiYW/bUYGsHAhMG0akJIilxUOHSrDmquroSou3TQa+T184w257G/ZMnlO6k8/yd95d3c540hk5hQ/OWTJkiXw8/ODjY0NgoODceDAgSfuGxMTg169eiEgIABqtRpjxowpcL/ExESMHDkSnp6esLGxQWBgILZt22agR0AE2FjY4Mu2XwIAvjz8JaIeRClcEelV377Ad9/JJ3jXr8tXbs0tWD0PjYbBiorP3l6eDwUAs2bJWdHCCAmRjVrGj5fBqnFj4Phx+TvMYFV8rq7A99/Lmaz69XOb3CxcKGcGicycouFqw4YNGDNmDCZPnoywsDC0bNkS7du3R1RUwU9M09PT4ebmhsmTJ6Nu3boF7pORkYG2bdsiMjISv/32Gy5duoRly5ahQoUKhnwoRHgj8A208mmFR5mPMHHXc7zCSsZPpZJNLUaPZqgiKkm9e8tmOCkpzz5/88YN4K23gHbtgIsXATc32aHy8GEgOLhk6jUnjRsDx44BP/wglwu+/bbSFREZBUXD1dy5czFo0CAMHjwYgYGBmD9/Pry9vfHtt98WuL+vry8WLFiAfv36wekJ3bhWrlyJe/fuYdOmTWjevDl8fHzQokWLJ4YxIn1RqVSY98o8qKDCz2d/xuGbh5UuiYjItKnVwIIF8uPVq4HQ0Pz7PHokl/sFBgK//y5nTkePlk1nBgyQxyDD0GjkzP7Agfrp6EhUCih2zlVGRgZCQ0Mx8T9rqNu1a4fDh4v+pHTLli1o2rQpRo4cic2bN8PNzQ29evXChAkToHnCyavp6elIT0/P+TwpKQkAoNVqodVqi1yLvmTXYAy10NPVcq2FAXUHYNWpVRj992gcHHCwSK3ZOebmieNunjjuzxAcDE3PnlD//DN077+PrMdas6u2boXmgw+gunYNAKBr2RJZ8+YBderI2xrx95Tjbp447qbpecZLsXB19+5dZGVlwf0/15Zwd3dH7NMuUvcM165dw+7du9G7d29s27YNERERGDlyJDIzM/HZZ58VeJvZs2dj2rRp+bbv3LkTtra2Ra5F30JCQpQugQqhVWYrrFevx4mYE5iwdgJau7Qu8rE45uaJ426eOO5PZvPyy3h540ZYHD6M0MmT8aBKFdRasQIeJ04AAB66uODcgAG43bIlcOuWfDMRHHfzxHE3LWlpaYXeV/Fugar/TCMLIfJtex46nQ7ly5fH999/D41Gg+DgYERHR+PLL798YriaNGkSxo0bl/N5UlISvL290a5dOzgaQYtlrVaLkJAQtG3bFpaWlkqXQ4Vwu/xtTN4zGb/e+xVTuk2BvZX9c92eY26eOO7mieNeOKqoKGD6dDRYuRJISYEqIwPC0hK699+Hxccfo66DA0zpBACOu3niuJum7FVthaFYuHJ1dYVGo8k3SxUXF5dvNut5eHp6wtLSMs8SwMDAQMTGxiIjIwNWVlb5bmNtbQ1ra+t82y0tLY3qB9/Y6qEn+6DZB1gRvgLX7l/D3H/nYsZLM4p0HI65eeK4myeO+zNMmACsWgXVzZvy87ZtoVq4EJrq1WHKV6ziuJsnjrtpeZ6xUuwsTysrKwQHB+ebFg0JCUGzZs2KfNzmzZvjypUr0Ol0OdsuX74MT0/PAoMVkSFYW1jntGb/6shXuJF4Q+GKiIhMnK2tvBhw586yccWOHUD16kpXRUSUh6ItdMaNG4fly5dj5cqVuHDhAsaOHYuoqCgMHz4cgFyu169fvzy3CQ8PR3h4OFJSUhAfH4/w8HCcP38+5+vvvvsuEhISMHr0aFy+fBlbt27F559/jpEjR5boYyPqWr0rXvR9EY8yH2HCrglKl0NEZPpatAC2bJEXsmV3OiIyQoqec9W9e3ckJCRg+vTpiImJQa1atbBt2zb4+PgAkBcN/u81r4KCgnI+Dg0Nxbp16+Dj44PIyEgAgLe3N3bu3ImxY8eiTp06qFChAkaPHo0JE/jklkpWdmv2+kvrY8O5DRjVaBSaV2qudFlEREREZCCKN7QYMWIERowYUeDXVq9enW+bEOKZx2zatCmOHj1a3NKIiq2eRz0Mrj8Yy04uw5gdY/Dv4H+L1JqdiIiIiIwfn+URGdiM1jPgYOWAE9En8OOpH5Uuh4iIiIgMhOGKyMDc7d3xyQufAAAm/TMJKRkpCldERERERIbAcEVUAkY3Ho3KZSsjJiUG/zv4P6XLISIiIiIDYLgiKgHWFtb4qu1XAICvDrM1OxEREVFpxHBFVEK6VO+C1r6tkZ6Vjo92faR0OURERESkZwxXRCUkuzW7WqXGL+d+wcGog0qXRERERER6xHBFVILqetTF4KDBAIAx28dAJ3QKV0RERERE+sJwRVTCZrw0A47WjgiNCcUPp35QuhwiIiIi0hOGK6ISVt6uPD594VMAsjV7cnqywhURERERkT4wXBEpYFSjUahStgpiU2LZmp2IiIiolGC4IlKAtYU1vm73NQDg6yNfIzIxUtmCiIiIiKjYGK6IFPJawGt4ye8l2Zo9hK3ZiYiIiEwdwxWRQh5vzf7r+V9x4MYBpUsiIiIiomJguCJSUB33OhhSfwgAYMwOtmYnIiIiMmUMV0QKm956OhytHXEy5iTWhK9RuhwiIiIiKiKGKyKFlbcrj89e+AwA8PHuj9manYiIiMhEMVwRGYFRjUehqktVxKbEYvbB2UqXQ0RERERFwHBFZASsNFY5rdnnHpmL64nXFa6IiIiIiJ4XwxWRkehcrTNe9nsZ6VnpmLR7ktLlEBEREdFzYrgiMhKPt2bfeHEjzqWcU7okIiIiInoODFdERqS2e20MrT8UALDi9gpk6bIUroiIiIiICovhisjITG89HU7WTrj28Bp6bOyBxEeJSpdERERERIXAcEVkZNzs3LDo1UWwUFlg8+XNCP4+GGExYUqXRURERETPwHBFZIS61+yO2f6z4ePkg2v3r6HpiqZYemIphBBKl0ZERERET8BwRWSk/G398e/Af9GpWiekZ6Vj+Nbh6PtHX6RkpChdGhEREREVgOGKyIi5lHHB5h6bMafNHGhUGqw9sxaNljXC+fjzSpdGRERERP/BcEVk5NQqNcY3H489/ffAy8ELF+5eQMNlDfHjqR+VLo2IiIiIHsNwRWQiWvq0RNiwMLSp3AZp2jT029QPQ/8ciofah0qXRkRERERguCIyKeXtymN77+2Y2moqVFBh2cllaLayGa7cu6J0aURERERmj+GKyMRo1BpMeXEKdvTZATdbN4THhqP+0vr4/fzvSpdGREREZNYYrohMVNsqbRE2LAwtKrVAckYy3vr1LYzZPgYZWRlKl0ZERERklhiuiExYBccK2N1vNz5q9hEAYMG/C/DCqhcQ9SBK4cqIiIiIzA/DFZGJs9RY4ou2X2Bzj81wtnHGv7f/RdDSIGy9vFXp0oiIiIjMCsMVUSnxWsBrCBsWhgZeDXDv4T10+rkTPv7nY2TqMpUujYiIiMgsMFwRlSK+zr44+M5BvNfwPQDA7IOz0eaHNohJjlG4MiIiIqLSj+GKqJSxtrDGNx2+wfo318Peyh77buxDvaX1sPv6bqVLIyIiIirVGK6ISqnutbojdGgoapevjbjUOLT9sS1m7JsBndApXRoRERFRqcRwRVSKVStXDUcHH8XAegOhEzp8tvczdFjbAfGp8UqXRkRERFTqMFwRlXK2lrZY8foKrHp9FcpYlMGOqzsQtDQIh28eVro0IiIiolKF4YrITAyoNwD/Dv4XAeUCcDv5NlqtboWvD38NIYTSpRERERGVCgxXRGaktnttHB9yHD1q9UCmLhMfhnyIVqtb4fSd00qXRkRERGTyGK6IzIyDtQPWvbEOSzosga2lLQ5EHUD9pfUx+u/RSHyUqHR5RERERCaL4YrIDKlUKrzb8F1cGHkBb9V4C1kiCwuPLUTAogCsDl/NjoJERERERcBwRWTGKjlVwq9v/4qQviGo7lodcalxeGfzO2ixsgXCYsKULo+IiIjIpDBcERHaVG6DU8NPYU6bObCztMORW0fQYFkDjNw6Evce3lO6PCIiIiKTwHBFRAAAK40Vxjcfj0vvXULPWj2hEzosObEEAYsCsPzkci4VJCIiInoGhisiyqOCYwWse3Md9vTfg5puNXE37S6G/DkETVc0xYnoE0qXR0RERGS0GK6IqEAv+r6IsGFhmPfKPDhaO+LY7WNotKwRhv45FHfT7ipdHhEREZHRYbgioiey1FhiTJMxuPTeJfSt0xcCAstOLkPAogB8d+I7ZOmylC6RiIiIyGgwXBHRM3nYe+CHrj/gwDsHUNe9Lu49vId3t76LRssb4eito0qXR0RERGQUGK6IqNBaVGqBE0NP4Jv238DJ2gknY06i6YqmGLh5IOJS45Quj4iIiEhRDFdE9Fws1BZ4r9F7uDzqMgbWGwgAWBW+CgGLArDo2CJk6jIVrpCIiIhIGQxXRFQk5e3KY8XrK3Bk0BHU96yPxEeJGPX3KAR/H4yDUQeVLo+IiIioxDFcEVGxNKnYBMcGH8O3Hb9FWZuyOH3nNFquaom+f/RFTHKM0uURERERlRiGKyIqNo1ag+ENhuPyqMsYWn8oVFDhp9M/IWBRAOYdmQdtllbpEomIiIgMjuGKiPTG1dYVSzsvxbEhx9CoQiMkZyRj3M5xqLywMr44+AXuPbyndIlEREREBsNwRUR618CrAY4MOoLlnZfD3c4dt5JuYeI/E1FxbkW8+9e7uBB/QekSiYiIiPSO4YqIDEKtUmNQ/UG4MeYGVr++GvU86uFh5kN8F/odaiypgfZr22PHlR0QQihdKhEREZFeMFwRkUFZW1ijf73+ODn0JPb234su1btABRW2X9mOV9e+ippLauL70O+Rpk1TulQiIiKiYmG4IqISoVKp0Mq3Ff7o/gciRkVgTOMxcLBywIW7FzDsr2HwnueNj//5GLeTbitdKhEREVGRMFwRUYmr4lIF816dh1vjbmHeK/Pg5+yHew/vYfbB2fBd4Itev/fCsdvHlC6TiIiI6LkwXBGRYhytHTGmyRhEjIrAH93/QCufVsjUZeLnsz+j8fLGaL6yOX499ysydZlKl0pERET0TAxXRKQ4jVqDLtW7YO+AvTg59CT61+0PS7UlDt88jG6/dUPlBZXx5aEvcf/hfaVLJSIiInoihisiMipBnkFY3WU1osZG4bMXPoObrRtuJt3ER7s+QsV5FTFy60hcuntJ6TKJiIiI8mG4IiKj5GHvgWmtpyFqbBRWvrYSddzrIE2bhiUnlqD64urouK4jQq6GsJU7ERERGQ2GKyIyajYWNngn6B2EDwvH7n678VrAa1BBhW0R29Dup3ao/W1tLD+5HA+1D5UulYiIiMwcwxURmQSVSoXWfq2xucdmXB51GaMajYKdpR3OxZ/DkD+HoOo3VbEsdBmbXxAREZFiGK6IyORUdamKhe0X4ta4W/i63deo5FQJ0cnRGPrXUNRaUgsbL2zkckEiIiIqcQxXRGSynG2cMa7pOFx+7zLmvzIf5cqUw6WES3jzlzfRdEVT7I3cq3SJREREZEYYrojI5FlbWGN0k9G4NvoaPn3hU9ha2uLf2/+i9ZrW6LC2A07FnlK6RCIiIjIDDFdEVGo4WjtieuvpuPr+VYxoMAIWagv8feVvBC0NQt8/+uL6/etKl0hERESlGMMVEZU6HvYeWNxxMS6MvIDuNbtDQOCn0z8hYFEARv89GvGp8UqXSERERKUQwxURlVpVXapi/VvrcWLICbSp3AZanRYLjy1ElYVVMH3fdKRkpChdIhEREZUiDFdEVOoFewUjpG8IQvqGINgzGMkZyZiydwqqLKyCxccWIyMrQ+kSiYiIqBRguCIis9GmchscG3IM699cjyplqyAuNQ7v/f0eAhcHYv3Z9dAJndIlEhERkQlTPFwtWbIEfn5+sLGxQXBwMA4cOPDEfWNiYtCrVy8EBARArVZjzJgx+fZZvXo1VCpVvrdHjx4Z8FEQkalQq9ToXqs7Loy8gMUdFsPdzh3X7l9Dz997osH3DRByNUTpEomIiMhEKRquNmzYgDFjxmDy5MkICwtDy5Yt0b59e0RFRRW4f3p6Otzc3DB58mTUrVv3icd1dHRETExMnjcbGxtDPQwiMkGWGkuMaDgCV96/ghmtZ8DBygFhsWFo91M7tPmhDU5En1C6RCIiIjIxFkre+dy5czFo0CAMHjwYADB//nzs2LED3377LWbPnp1vf19fXyxYsAAAsHLlyiceV6VSwcPDo9B1pKenIz09PefzpKQkAIBWq4VWqy30cQwluwZjqIVKBse85FirrDGh6QQMrDMQXxz+At+d/A7/XP8HDZc1xFuBb2Faq2nwd/EvkVo47uaJ426eOO7mieNump5nvBQLVxkZGQgNDcXEiRPzbG/Xrh0OHz5crGOnpKTAx8cHWVlZqFevHmbMmIGgoKAn7j979mxMmzYt3/adO3fC1ta2WLXoU0gIlyuZG455yXoJL6FmtZr4OfZn7Lu/D79d+A1/XPgDbcu1RTePbnCxdCmROjju5onjbp447uaJ425a0tLSCr2vYuHq7t27yMrKgru7e57t7u7uiI2NLfJxq1evjtWrV6N27dpISkrCggUL0Lx5c5w6dQr+/gW/+jxp0iSMGzcu5/OkpCR4e3ujXbt2cHR0LHIt+qLVahESEoK2bdvC0tJS6XKoBHDMlfUO3sHpuNP4dM+n+Pvq39iesB37k/ajZ82eqO9RH7XL10ZNt5pwsHbQ6/1y3M0Tx908cdzNE8fdNGWvaisMRZcFAnIJ3+OEEPm2PY8mTZqgSZMmOZ83b94c9evXxzfffIOFCxcWeBtra2tYW1vn225paWlUP/jGVg8ZHsdcOcEVgrGtzzbsv7EfE3ZNwNFbR7EifAVWYEXOPpXLVkbt8rVRx71OzluVslWgUWuKdd8cd/PEcTdPHHfzxHE3Lc8zVoqFK1dXV2g0mnyzVHFxcflms4pDrVajYcOGiIiI0Nsxich8vODzAg4PPIy/r/yNvZF7cSbuDE7fOY3o5Ghcu38N1+5fw+ZLm3P2L2NRBjXL10Sd8rmBq7Z7bbjauir4KIiIiKgkKBaurKysEBwcjJCQEHTt2jVne0hICF5//XW93Y8QAuHh4ahdu7bejklE5kWlUqGDfwd08O+Qs+1u2l2cuSODVnbgOht3Fg8zH+JE9Il83Qa9HLxk0Hpspqu6a3VYaaxK+uEQERGRgSi6LHDcuHHo27cvGjRogKZNm+L7779HVFQUhg8fDkCeC3X79m388MMPObcJDw8HIJtWxMfHIzw8HFZWVqhRowYAYNq0aWjSpAn8/f2RlJSEhQsXIjw8HIsXLy7xx0dEpZerrSta+7VGa7/WOduydFm4ev+qDFx3zuB03GmcvnMa1+5fQ3RyNKKTo7H9yvac/S3UFgh0DcwJXTVca+BB5gMlHg4RERHpgaLhqnv37khISMD06dMRExODWrVqYdu2bfDx8QEgLxr832tePd71LzQ0FOvWrYOPjw8iIyMBAImJiRg6dChiY2Ph5OSEoKAg7N+/H40aNSqxx0VE5kmj1qBauWqoVq4a3qrxVs725PRknI07mzPDlf32IP0BzsSdwZm4Mzn7qqHGr+m/YliDYWhftX2xz98iIiKikqN4Q4sRI0ZgxIgRBX5t9erV+bYJIZ56vHnz5mHevHn6KI2ISC8crB3Q1Lspmno3zdkmhMDNpJs5SwtPx51GeEw4LiZcxF8Rf+GviL9Q0bEiBtYbiIFBA+Hj7KPgIyAiIqLCUDxcERGZI5VKhUpOlVDJqRI6VusIQLboXbpxKa46XsWPZ37EraRbmL5/Ombsn4FXqr6CIfWHoHO1zrDUsMMUERGRMVIrXQAREeXytvHGnDZzcHvcbax/cz1e9nsZAgLbr2zHm7+8Ce953pi4ayKu3LuidKlERET0HwxXRERGyNrCGt1rdceufrtwZdQVTGw+Ee527riTegdfHPoC/t/446U1L+HnMz8jPTNd6XKJiIgIDFdEREaviksVzG4zGzfH3sTGbhvRvmp7qKDCnsg96LWxFyrMrYBxO8bhQvwFpUslIiIyawxXREQmwlJjia6BXbGt9zZcH30dn73wGSo6VkTCwwTMOzoPNZbUQIuVLbAmfA3StGlKl0tERGR2GK6IiEyQj7MPprWehsjRkfir5194PeB1aFQaHLp5CAM2D4DX114YuXUkwmPDlS6ViIjIbDBcERGZMI1ag47VOmJTj02IGhuFWS/Ngp+zHx6kP8CSE0sQtDQIjZY1wrLQZUhOT1a6XCIiolKN4YqIqJTwcvDCxy0/xpX3r2Bnn514u8bbsFRb4nj0cQz9ayg8v/bEkC1DcOTmEWTqMpUul4iIqNThda6IiEoZtUqNtlXaom2VtohLjcMPp37AspPLcDnhMpaHLcfysOWwt7JH04pN0aJSC7So1AKNKzSGnZWd0qUTERGZNIYrIqJSrLxdeXzY7EN80PQD7L+xH8tOLsOfl/9EUnoSQq6FIORaCABAo9Kgvmf9nLDV3Ls53O3dFa6eiIjItDBcERGZAZVKhVa+rdDKtxWydFk4F38OB6MO4mDUQRyIOoBbSbdwPPo4jkcfx7yj8wAA/i7+OWGrRaUW8Hfxh0qlUviREBERGS+GKyIiM6NRa1DHvQ7quNfBiIYjAABRD6JywtbBqIM4G3cWEfciEHEvAqvCVwEA3Gzd8oStII8gWGoslXwoRERERoXhioiIUMmpEnrV7oVetXsBAO4/vI8jt47khK1jt48hPi0ef1z8A39c/AMAUMaiDJpUbILm3s3RolILNPVuCkdrRyUfBhERkaIYroiIKJ+yZcqig38HdPDvAABIz0zHyZiTMmzdlIHr3sN72BO5B3si9wCQjTTquNdBC+8WaObdDAGuAfBz9kPZMmWVfChEREQlhuGKiIieydrCGk29m6Kpd1OMx3johA6X7l7KE7au3b+G8NhwhMeGY9HxRTm3dbJ2QuWyleFX1g9+zn7yY2c/+JX1g6+zL2wsbBR8ZERERPrDcEVERM9NrVIj0C0QgW6BGBI8BAAQnRyNQ1GHcDDqII5HH8e1+9dwJ/UOHqQ/QFhsGMJiwwo8lpeDV57Q9XgQ83LwgkatKcmHRkREVGQMV0REpBdeDl54u+bbeLvm2znbUjNSEZkYieuJ13Ht/jVcv3899+PE60jJSEF0crQMZjcP5TumlcYKPk4+8Cvrh8rOeWe/KpetzCWHRERkVBiuiIjIYOys7FCzfE3ULF8z39eEEEh4mFBg6Lp2/xqiHkQhIysjp2thQfxd/PGS30t4ye8ltPZtDTc7N0M/JCIioidiuCIiIkWoVCq42rrC1dYVjSo0yvf1TF0mbifdzglc1+9fx7XE3CAWmxKbE7yWhi4FANRxr4OXfGXYesHnBTjZOJX0wyIiIjPGcEVEREbJQm0BH2cf+Dj7oDVa5/t64qNEHLhxALuv78Y/1//BmbgzOH3nNE7fOY35/86HWqVGA68GeNnvZbzk9xKaeTeDraWtAo+EiIjMBcMVERGZJGcbZ3QO6IzOAZ0BAHGpcdgbuRe7r+/G7uu7EXEvAsduH8Ox28cw++BsWGms0LRi05xlhI0qNIKVxkrhR0FERKUJwxUREZUK5e3Ko1vNbuhWsxsA4OaDmzJoRe7GP9f+we3k29h3Yx/23diHKXunwM7SDi19WuYsI6znUY+dCYmIqFgYroiIqFTydvJG/3r90b9efwghcOXelZywtfv6btxNu4vtV7Zj+5XtAICyNmXxou+LOTNbga6BUKlUCj8KIiIyJQxXRERU6qlUKviX84d/OX8MazAMOqHD2bizOUsI993Yh/uP7uOPi3/gj4t/AADc7dzxkt9LaFqxKeq410Ed9zps/U5ERE/FcEVERGZHrVLnBKYxTcYgU5eJkzEnc5pjHIw6iDupd/Dz2Z/x89mfc25XyakS6rjXQV33uqjrXhd13OugqktVLickIiIADFdERESwUFugUYVGaFShESa2mIj0zHQcvXUUeyL3ICw2DKdiT+HGgxuIehCFqAdR+OvyXzm3tbW0Ra3ytXLCVvZ7toEnIjI/DFdERET/YW1hjVa+rdDKt1XOtsRHiThz5wxO3TmFU7GncDruNM7cOYM0bVpOV8LH+Tj5oK5H3Tyhq4pLFahV6pJ+OEREVEIYroiIiArB2cYZLX1aoqVPy5xtWbosXLl3BafvnJah684pnL5zGlEPonDjwQ3ceHADWy5tydnfztIOtd1ro075OjnBq7pLdSUeDhERGQDDFRERURFp1BoEuAYgwDUAb9d8O2f7/Yf3cwJX9vuzcWeRqk3F0VtHcfTW0TzHKWdZDgF3A1DZpTJ8nXzh65z75u3kzetxERGZCIYrIiIiPStbpmy+ZYWZukxcuXcFp2JP5Qldt5JuIUGbgMO3DuPwrcP5jqWCChUcK8DP2S9P6MoJX47esNRYluTDIyKiJ2C4IiIiKgEWagtUd62O6q7V0b1W95ztd5Lu4Ie/fkCFmhVwK+UWIhMjEZkYieuJ1xGZGIlHmY9wK+kWbiXdwoGoA/mOq1apUdGxYm7g+s/MV0XHis8MXzqhQ3pmOh5lPkJ61v+/z0x/4sfZ+/33Y41ag8plK8PfRba9d7Zx1ve3kYjIqDFcERERKciljAuq2VVDhxodYGmZNwQJIRCXGpcTuP4bvCITI5GelZ7TxXD/jf35jq9RaVDRsSLKlin7xMCUqcs0yGNztXXNCVr+Lv45H1d1qQpHa0eD3CcRkZIYroiIiIyUSqWCu7073O3d0bhi43xf1wldnvB1/f7/h64H8vMbiTeQnpWe01yjUPcJFawtrGGtsYaNhQ2sLf7/vcb6iR9nv0/PSseVe1cQcS8CsSmxuJt2F3fT7uLIrSP57qe8XfknBi97K/tif++IiJTAcEVERGSi1Co1POw94GHvgSYVm+T7uk7ocCflDq4nXkdSelKewPSk8GSptoRKpSp2bcnpyTlBKyIhAlfuX0FEQgQi7kUgLjUu5+3QzUP5butp71lg6KrqUhW2lrbFro2IyFAYroiIiEoptUoNTwdPeDp4lvh9O1g7IMgzCEGeQfm+9uDRgzzBK+JeRM7HCQ8TEJMSg5iUmAKXOVZyqoSX/V5GR/+OaFulLZcXEpFRYbgiIiKiEuVk44Rgr2AEewXn+9r9h/dzZ7uyA9j/f37/0X1EPYjCqvBVWBW+CpZqS7T0aYmO/h3R0b8jqpWrppdZNyKiomK4IiIiIqNRtkxZNKrQCI0qNMr3tYS0BITFhmFbxDZsjdiKywmXsfv6buy+vhsf7PwAVcpWkUGrWke08mkFawtrBR4BEZkzhisiIiIyCeVsy6FN5TZoU7kN5r4yFxEJEdgasRVbI7ZiX+Q+XL1/FQuPLcTCYwthZ2mHtlXaoqN/R3Tw7wAvBy+lyyciM8BwRURERCbJv5w/xpQbgzFNxiA5PRm7ru3C1oit2BaxDTEpMdh0cRM2XdwEAAjyCMqZ1Wro1RAatUbZ4omoVGK4IiIiIpPnYO2AroFd0TWwK3RCh/DYcGy9LGe1jt0+hrDYMITFhmHmgZlwtXVF+6rt0dG/I16p+govdkxEesNwRURERKWKWqVGfc/6qO9ZH5+2+hRxqXHYfmU7tkZsxfYr23E37S5+PP0jfjz9IzQqDZpXap7TFKOGWw02xSCiImO4IiIiolKtvF159KvbD/3q9oM2S4tDNw/lzGpduHsB+2/sx/4b+zFh1wT4OvuiQ9UOaFyxMWqXr41At0DYWNgo/RCIyEQwXBEREZHZsNRY4kXfF/Gi74v4st2XuH7/ek5TjD3X9yAyMRJLTizBkhNLAAAalQb+5fxRu3xt+eYu3/uV9YNapVb40RCRsWG4IiIiIrPlV9YP7zV6D+81eg+pGanYfX03Qq6F4NSdUzhz5wzuP7qPi3cv4uLdi/j1/K85t7OztEPN8jXzhS43OzcFHw0RKY3hioiIiAiAnZUdOgd0RueAzgAAIQSik6NxJu4Mztw5I9/HncH5+PNI1abi2O1jOHb7WJ5juNu55wSt7NBVw60GbC1tlXhIRFTCGK6IiIiICqBSqVDBsQIqOFbAq1VfzdmeqctEREJEvtB17f413Em9gzvX7mDXtV05+6tValQpWyVP6KruUh13M+7i6v2r0Kl0yMjKQHpmOtKz0ov+Pis933E8HTzRwrsFWlRqgTruddiCnsjAGK6IiIiInoOF2gKBboEIdAtEt5rdcranZKTgXNy5fKHrbtpdRNyLQMS9CGy8sDHvwc4bvt5fzv0CAHCwckBT76Y5YatRhUaws7IzfAFEZoThioiIiEgP7K3s0bhiYzSu2DhnmxACd1Lv5AlbZ+7IpYUZmRmwsbSBtYU1rDXWOe+tNFb5tuV7X4j9LdWWiLgXgYNRB3H45mEkZyRj59Wd2Hl1JwAZEoM8gtCikgxbzb2bw93eXalvH1GpwHBFREREZCAqlQoe9h7wsPdA2yptc7ZrtVps27YNHTp0gKWlpcHryNJl4UzcGRyMOpjzdjv5No5HH8fx6OOYd3QeAMDfxT8nbLWo1AL+Lv687hfRc2C4IiIiIirlNGoN6nnUQz2Peniv0XsQQiDqQVRu2Lp5EGfjzuYsX1wVvgoA4GbrhuaVmucsJQzyDIKVxkrhR0NkvBiuiIiIiMyMSqWCj7MPfJx90LtObwDA/Yf3cfjmYRyMOohDNw/h2O1jiE+Lx6aLm7Dp4iYAQBmLMmhcsXFO2GpSsQmcbJwUfCRExoXhioiIiIhQtkxZdKzWER2rdQQApGemIzQmNGd269DNQ7j38B72Ru7F3si9AAAVZEizt7KHraUt7CztYGdll/ux5f9/bPV8H9tY2HA5IpkkhisiIiIiysfawhrNvJuhmXczfNT8I+iEDhfvXswTtq7dv4bIxEi937dapYatpW1OSPN08ETPWj3Rq3YvuJRx0fv9EekLwxURERERPZNapUYNtxqo4VYDQ4OHAgCik6NxI/EG0rRpSNWmIjUj9ckfZ6YhNSMVqdr/317AvulZ6QAAndAhJSMFKRkpAIDriddx+OZhfLDzA3Sp3gUD6w1Em8pteN0uMjoMV0RERERUJF4OXvBy8NLb8TJ1mUjTpuWEr+wgdvz2cawKX4Ww2DD8cu4X/HLuF1R0rIj+dfvjnXrvoIpLFb3VQFQcDFdEREREZBQs1BZwtHaEo7Vjnu1NKjbBqMajEBYThlXhq7D2zFrcSrqFWQdmYdaBWWjl0woDgwbizcA3eWFkUpRa6QKIiIiIiAojyDMIC9svRPS4aPzy1i94teqrUEGFfTf2of+m/vD82hNDtgzBkZtHIIRQulwyQwxXRERERGRSrC2s8XbNt/F3779xY8wNzGw9E1XKVkFyRjKWhy1Hs5XNUGNJDXx56EvEpsQqXS6ZEYYrIiIiIjJZ3k7emPzCZESMisC+AfvQv25/2Fra4uLdi/ho10eoOLciXvv5NWy6uAnaLK3S5VIpx3BFRERERCZPpVLhBZ8XsLrLasR8EINlnZehacWmyBJZ+PPyn+i6oSsqzquID3d+iHNx55Qul0ophisiIiIiKlUcrR0xuP5gHB50GBdGXsBHzT6Cu5074lLj8PWRr1Hr21povLwxlp5YigePHihdLpUiDFdEREREVGpVd62OL9p+gZtjb2JLjy3oUr0LLNQWOHb7GIZvHQ6Prz3QZ2Mf7Ly6E/ce3lO6XDJxbMVORERERKWepcYSnQM6o3NAZ8SlxuGn0z9hRdgKnI8/j7Vn1mLtmbUAgHJlyqFauWo5bwHlAlCtXDVUdamKMpZlFH4UZOwYroiIiIjIrJS3K49xTcdhbJOxOB59HCvDVmJrxFbcSrqFhIcJOHLrCI7cOpLvdpWcKsnQ5VItTwDzcfaBhZpPq4nhioiIiIjMlEqlQqMKjdCoQiMAQGpGKq7cu4LLCZdxKeESLidczvk48VEioh5EIepBFHZd25XnOJZqS1RxqVJg8PKw94BKpVLi4ZECGK6IiIiIiADYWdmhrkdd1PWom2e7EAIJDxNywtbjbxH3IvAo8xEu3r2Ii3cv5jumvZV9zvLCKs5VkJGYAf97/qhevjrUKrY/KG0YroiIiIiInkKlUsHV1hWutq5o5t0sz9d0QodbSbcKDF7XE68jJSMFJ2NO4mTMyZzbzPluDuws7VDbvTbqlK8jA517XdRxrwMHa4eSfnikRwxXRERERERFpFapUcmpEio5VUKbym3yfC09Mx3XE6/nhK1zcedw8PJB3NLeQqo2FUdvHcXRW0fz3KZy2co5Qauuu5xF83X25SyXiWC4IiIiIiIyAGsLa1R3rY7qrtUBAFqtFttU29Du1XaITIrE6TuncerOKfkWewq3k2/j2v1ruHb/Gv64+EfOcRysHPKErTrudVC7fG3YWdkp9dDoCRiuiIiIiIhKkIXaAoFugQh0C0T3Wt1ztt9NuysDV+wpnI6T78/Fn0NyRjIO3TyEQzcP5eyrggpVXarmLCnMnu2q5FSJDTQUxHBFRERERGQEXG1d8ZLfS3jJ76WcbdosLS4lXMKp2FN5ZrnupN5BxL0IRNyLwG/nf8vZ39nGGTXcaiDQNRCBroGo7lodgW6B8HHygUatUeJhmRWGKyIiIiIiI2WpsUSt8rVQq3wt9EbvnO13Uu7kW1Z44e4FJD5KxOGbh3H45uE8x7GxsEG1ctVk2MoOXa6BqFauGi+OrEcMV0REREREJsbd3h1t7duibZW2OdvSM9Nx8e5FXLh7ARfiL+BiwkVciL+AywmX8SjzEU7fOY3Td07nOY4KKvg6++YNXW7yvauta0k/LJPHcEVEREREVApYW1gXeJ2uLF0WIhMjc4LX4wHs/qP7uJ54HdcTr+PvK3/nuZ2rrWu+ma7qrtXh4+zD7oVPoHi4WrJkCb788kvExMSgZs2amD9/Plq2bFngvjExMfjggw8QGhqKiIgIvP/++5g/f/4Tj71+/Xr07NkTr7/+OjZt2mSYB0BEREREZMQ0ag2quFRBFZcq6FitY852IQTi0+Jl2Iq/kCd4RT2Iwt20uzgYdRAHow7mOV4ZizJ4wecFjGg4Ah39O/JcrscoGq42bNiAMWPGYMmSJWjevDmWLl2K9u3b4/z586hUqVK+/dPT0+Hm5obJkydj3rx5Tz32jRs38OGHHz4xqBERERERmTOVSoXyduVR3q48XvB5Ic/XUjNScSnhUk7wyl5iGHEvAg8zH2LH1R3YcXUHfJx88G6DdzGo/iAuI4TC4Wru3LkYNGgQBg8eDACYP38+duzYgW+//RazZ8/Ot7+vry8WLFgAAFi5cuUTj5uVlYXevXtj2rRpOHDgABITEw1SPxERERFRaWRnZYf6nvVR37N+nu2ZukxcTriMNeFrsDxsOW48uIGJ/0zElL1T0KNWD7zX6D008GqgUNXKUyxcZWRkIDQ0FBMnTsyzvV27djh8+PATblU406dPh5ubGwYNGoQDBw48c//09HSkp6fnfJ6UlARAXuhNq9UWqxZ9yK7BGGqhksExN08cd/PEcTdPHHfzVFrG3d/ZHzNfnInJzSfjl/O/YEnoEoTFhmHNqTVYc2oNGno1xLvB7+KtwLdgY2GjdLnF9jzjpVi4unv3LrKysuDu7p5nu7u7O2JjY4t83EOHDmHFihUIDw8v9G1mz56NadOm5du+c+dO2NraFrkWfQsJCVG6BCphHHPzxHE3Txx388RxN0+ladzd4IbP3D/DZYfL2HZ3Gw4lHsLx6OM4Hn0cY7aNQdtybfGq66tws3JTutQiS0tLK/S+ije0+O8VpIUQRb6qdHJyMvr06YNly5bB1bXwaz4nTZqEcePG5XyelJQEb29vtGvXDo6OjkWqRZ+0Wi1CQkLQtm1bWFpaKl0OlQCOuXniuJsnjrt54ribp9I87h3REWMxFnGpcVgZvhLfn/wet5Jv4fe43/FH/B/o5N8JI4JHoLVv6yI/11dK9qq2wlAsXLm6ukKj0eSbpYqLi8s3m1VYV69eRWRkJDp37pyzTafTAQAsLCxw6dIlVKlSJd/trK2tYW1tnW+7paWlUf3gG1s9ZHgcc/PEcTdPHHfzxHE3T6V53Cs4V8CnL36KSS9MwpZLW7D4+GLsvr4bWy5vwZbLW1DdtTpGNhyJfnX7wdFa+UmMwniesVKsQb2VlRWCg4PzTYuGhISgWbNmRTpm9erVcebMGYSHh+e8vfbaa2jdujXCw8Ph7e2tj9KJiIiIiOgpLNQWeCPwDfzT7x+cG3EOIxuOhL2VPS7evYhRf49ChbkVMHLrSJyPP690qXql6LLAcePGoW/fvmjQoAGaNm2K77//HlFRURg+fDgAuVzv9u3b+OGHH3Juk30uVUpKCuLj4xEeHg4rKyvUqFEDNjY2qFWrVp77cHZ2BoB824mIiIiIyPBquNXAog6L8PnLn+PHUz9i0fFFuHj3IpacWIIlJ5agtW9rjGw4Eq9Xfx0WasXPWioWRavv3r07EhISMH36dMTExKBWrVrYtm0bfHx8AMiLBkdFReW5TVBQUM7HoaGhWLduHXx8fBAZGVmSpRMRERER0XNwtHbEyEYjMaLhCOy+vhuLjy/G5kubsSdyD/ZE7kFFx4oYHjwcg+sPhrt90U4TUpri0XDEiBEYMWJEgV9bvXp1vm1CiOc6fkHHICIiIiIiZahUKrxc+WW8XPllRD2IwtITS7Hs5DLcSrqFT/Z8gmn7pqFbzW4Y2XAkmlRsYlINMBQ754qIiIiIiMxbJadKmPXyLNwcexM/dv0RjSs0hlanxdoza9FsZTMcunlI6RKfi+IzV0REREREZN6sLazRp04f9KnTByeiT2Dx8cUIiwlDM++iNbpTCsMVEREREREZjQZeDbDq9VXI0mVBrTKthXamVS0REREREZkFjVqjdAnPjeGKiIiIiIhIDxiuiIiIiIiI9IDhioiIiIiISA8YroiIiIiIiPSA4YqIiIiIiEgPGK6IiIiIiIj0gOGKiIiIiIhIDxiuiIiIiIiI9IDhioiIiIiISA8YroiIiIiIiPSA4YqIiIiIiEgPGK6IiIiIiIj0gOGKiIiIiIhIDxiuiIiIiIiI9IDhioiIiIiISA8YroiIiIiIiPSA4YqIiIiIiEgPLJQuwBgJIQAASUlJClciabVapKWlISkpCZaWlkqXQyWAY26eOO7mieNunjju5onjbpqyM0F2RngahqsCJCcnAwC8vb0VroSIiIiIiIxBcnIynJycnrqPShQmgpkZnU6H6OhoODg4QKVSKV0OkpKS4O3tjZs3b8LR0VHpcqgEcMzNE8fdPHHczRPH3Txx3E2TEALJycnw8vKCWv30s6o4c1UAtVqNihUrKl1GPo6OjvxFNDMcc/PEcTdPHHfzxHE3Txx30/OsGatsbGhBRERERESkBwxXREREREREesBwZQKsra0xZcoUWFtbK10KlRCOuXniuJsnjrt54ribJ4576ceGFkRERERERHrAmSsiIiIiIiI9YLgiIiIiIiLSA4YrIiIiIiIiPWC4IiIiIiIi0gOGKyO3ZMkS+Pn5wcbGBsHBwThw4IDSJZEBTZ06FSqVKs+bh4eH0mWRnu3fvx+dO3eGl5cXVCoVNm3alOfrQghMnToVXl5eKFOmDF588UWcO3dOmWJJb5417gMGDMj3+9+kSRNliiW9mD17Nho2bAgHBweUL18eXbp0waVLl/Lsw9/30qcw487f99KL4cqIbdiwAWPGjMHkyf/X3v3HVFX/cRx/3d3giok5vPy4TEEqMH/QXUhjoOkoZTFXI2zcpuZtzsqpLSW17dKKpKm50VZRbLVmutlaKy033JKG3KboRsxrDFlQktgWXSXNRMMlpz8a99sNU/flwIHL87Gd7dxzDmevnc/ef7zP+ZxDmY4fP64HHnhAhYWF6uzstDoahtCsWbP0888/h5bm5marI8FkPT09crvdqqqquu7+HTt26I033lBVVZUaGxuVlJSkRYsW6ffffx/mpDDTzcZdkh5++OGw+j9w4MAwJoTZ/H6/1q5dq2PHjqm2tlZ//vmnCgoK1NPTEzqGeo88tzLuEvUeqfgU+wiWk5OjrKwsVVdXh7bNmDFDRUVF2rZtm4XJMFTKy8v1+eefKxAIWB0Fw8Rms2nfvn0qKiqS9Pdd7OTkZK1fv14vvviiJKm3t1eJiYl6/fXX9eyzz1qYFmb597hLf9/JvnDhwoAnWogcZ8+eVUJCgvx+v+bPn0+9jxH/HneJeo9kPLkaoa5evaqmpiYVFBSEbS8oKFBDQ4NFqTAc2tvblZycrLS0ND3xxBM6deqU1ZEwjDo6OtTV1RVW+w6HQwsWLKD2x4D6+nolJCQoIyNDTz/9tILBoNWRYKLffvtNkhQXFyeJeh8r/j3u/aj3yERzNUKdO3dO165dU2JiYtj2xMREdXV1WZQKQy0nJ0e7d+/Wl19+qffff19dXV3Ky8tTd3e31dEwTPrrm9ofewoLC7Vnzx7V1dWpsrJSjY2NevDBB9Xb22t1NJjAMAyVlpZq3rx5mj17tiTqfSy43rhL1Hsku83qALgxm80W9tswjAHbEDkKCwtD65mZmcrNzdVdd92lXbt2qbS01MJkGG7U/tjj8XhC67Nnz1Z2drZSU1NVU1Oj4uJiC5PBDOvWrdO3336rw4cPD9hHvUeu/xp36j1y8eRqhHI6nbLb7QPuXAWDwQF3uBC5br/9dmVmZqq9vd3qKBgm/V+HpPbhcrmUmppK/UeA5557Tvv379ehQ4c0ZcqU0HbqPbL917hfD/UeOWiuRqjo6GjNmTNHtbW1Ydtra2uVl5dnUSoMt97eXrW2tsrlclkdBcMkLS1NSUlJYbV/9epV+f1+an+M6e7u1pkzZ6j/UcwwDK1bt0579+5VXV2d0tLSwvZT75HpZuN+PdR75GBa4AhWWlqqJ598UtnZ2crNzdV7772nzs5OrV692upoGCIbN27UI488opSUFAWDQb322mu6ePGivF6v1dFgokuXLun7778P/e7o6FAgEFBcXJxSUlK0fv16bd26Venp6UpPT9fWrVs1fvx4LV261MLUGKwbjXtcXJzKy8u1ZMkSuVwu/fjjj/L5fHI6nXrssccsTI3BWLt2rT766CN98cUXio2NDT2huuOOOxQTEyObzUa9R6CbjfulS5eo90hmYER75513jNTUVCM6OtrIysoy/H6/1ZEwhDwej+FyuYyoqCgjOTnZKC4uNlpaWqyOBZMdOnTIkDRg8Xq9hmEYRl9fn/HKK68YSUlJhsPhMObPn280NzdbGxqDdqNxv3z5slFQUGDEx8cbUVFRRkpKiuH1eo3Ozk6rY2MQrjfekoydO3eGjqHeI8/Nxp16j2z8nysAAAAAMAHvXAEAAACACWiuAAAAAMAENFcAAAAAYAKaKwAAAAAwAc0VAAAAAJiA5goAAAAATEBzBQAAAAAmoLkCAAAAABPQXAEAMEj19fWy2Wy6cOGC1VEAABaiuQIAAAAAE9BcAQAAAIAJaK4AAKOeYRjasWOH7rzzTsXExMjtduvTTz+V9L8pezU1NXK73Ro3bpxycnLU3Nwcdo7PPvtMs2bNksPh0LRp01RZWRm2v7e3V5s3b9bUqVPlcDiUnp6uDz74IOyYpqYmZWdna/z48crLy9N3330X2nfixAnl5+crNjZWEydO1Jw5c/TNN98M0RUBAFjhNqsDAAAwWC+99JL27t2r6upqpaen6+uvv9by5csVHx8fOmbTpk168803lZSUJJ/Pp0cffVRtbW2KiopSU1OTSkpKVF5eLo/Ho4aGBq1Zs0aTJ0/WU089JUlasWKFjh49qrfeektut1sdHR06d+5cWI6ysjJVVlYqPj5eq1ev1sqVK3XkyBFJ0rJly3TfffepurpadrtdgUBAUVFRw3aNAABDz2YYhmF1CAAA/l89PT1yOp2qq6tTbm5uaPuqVat0+fJlPfPMM8rPz9fHH38sj8cjSfr11181ZcoUffjhhyopKdGyZct09uxZHTx4MPT3mzdvVk1NjVpaWtTW1qbp06ertrZWCxcuHJChvr5e+fn5+uqrr/TQQw9Jkg4cOKDFixfrypUrGjdunCZOnKi3335bXq93iK8IAMAqTAsEAIxqJ0+e1B9//KFFixZpwoQJoWX37t364YcfQsf9s/GKi4vT9OnT1draKklqbW3V3Llzw847d+5ctbe369q1awoEArLb7VqwYMENs9x7772hdZfLJUkKBoOSpNLSUq1atUoLFy7U9u3bw7IBACIDzRUAYFTr6+uTJNXU1CgQCISWkydPht67+i82m03S3+9s9a/3++fEjpiYmFvK8s9pfv3n689XXl6ulpYWLV68WHV1dZo5c6b27dt3S+cFAIwONFcAgFFt5syZcjgc6uzs1N133x22TJ06NXTcsWPHQuvnz59XW1ub7rnnntA5Dh8+HHbehoYGZWRkyG63KzMzU319ffL7/YPKmpGRoQ0bNujgwYMqLi7Wzp07B3U+AMDIwgctAACjWmxsrDZu3KgNGzaor69P8+bN08WLF9XQ0KAJEyYoNTVVkrRlyxZNnjxZiYmJKisrk9PpVFFRkSTphRde0P3336+Kigp5PB4dPXpUVVVVevfddyVJ06ZNk9fr1cqVK0MftDh9+rSCwaBKSkpumvHKlSvatGmTHn/8caWlpemnn35SY2OjlixZMmTXBQAw/GiuAACjXkVFhRISErRt2zadOnVKkyZNUlZWlnw+X2ha3vbt2/X888+rvb1dbrdb+/fvV3R0tCQpKytLn3zyiV5++WVVVFTI5XJpy5YtoS8FSlJ1dbV8Pp/WrFmj7u5upaSkyOfz3VI+u92u7u5urVixQr/88oucTqeKi4v16quvmn4tAADW4WuBAICI1v8lv/Pnz2vSpElWxwEARDDeuQIAAAAAE9BcAQAAAIAJmBYIAAAAACbgyRUAAAAAmIDmCgAAAABMQHMFAAAAACaguQIAAAAAE9BcAQAAAIAJaK4AAAAAwAQ0VwAAAABgAporAAAAADDBX6oYKtkoRaUCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(f_history.history['loss'] , 'g')\n",
    "plt.plot(f_history.history['val_loss'] , 'r')\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epochs')\n",
    "plt.legend(['train', 'valid'], loc='upper right')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "269a9000",
   "metadata": {},
   "source": [
    "Можно заметить, что на валидацонной выборке ошибка уменьшилась (теперь она порядка 0.15-0.16). По сравнению с предыдущей моделью, удалось уменьшить ошибку на отложенной выборке. Такой подход кажется более естественным, т.к. используется не просто порядковый номер фильма, а его параметры"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a271b9c",
   "metadata": {},
   "source": [
    "**Плюсы модели**:\n",
    "* Использует признаки фильмов\n",
    "* Работает точнее\n",
    "* Обучается быстрее\n",
    "\n",
    "**Минусы**:\n",
    "* Усложнилась архитектура модели фильма\n",
    "* Требуется больше эпох"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c56efae",
   "metadata": {},
   "source": [
    "## Encoder для тегов фильма"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "998c22a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def encoder_model(num_users, n_genome, rows_count, emb_size):\n",
    "    autoencoder_input = Input(shape=(n_genome,), name='autoencoder_input')\n",
    "    encoder_dense_1 = layers.Dense(512, name='EncoderDense-1')(autoencoder_input)\n",
    "    encoder_dense_2 = layers.Dense(256, name='EncoderDense-2')(encoder_dense_1)\n",
    "    encoder_dense_3 = layers.Dense(128, name='EncoderDense-3')(encoder_dense_2)\n",
    "    encoder_dense_4 = layers.Dense(emb_size, name='EncoderDense-4')(encoder_dense_3)\n",
    "    \n",
    "    decoder_dense_1 = layers.Dense(128,name='DecoderDense-1')(encoder_dense_4)\n",
    "    decoder_dense_2 = layers.Dense(256,name='DecoderDense-2')(decoder_dense_1)\n",
    "    decoder_dense_3 = layers.Dense(512,name='DecoderDense-3')(decoder_dense_2)\n",
    "    decoder_dense_4 = layers.Dense(n_genome,name='DecoderDense-4')(decoder_dense_3)\n",
    "    \n",
    "    encoder = Model(inputs=autoencoder_input, outputs=encoder_dense_4)\n",
    "    decoder = Model(inputs=encoder_dense_4, outputs=decoder_dense_4)\n",
    "    autoencoder = Model(inputs=autoencoder_input, outputs=decoder_dense_4)\n",
    "    \n",
    "    adam = keras.optimizers.Adam(learning_rate=0.001)\n",
    "    autoencoder.compile(optimizer=adam, loss= 'mean_absolute_error', metrics='mean_squared_error')\n",
    "\n",
    "    user_input = keras.Input(shape=(1,), name='user_id')\n",
    "    user_emb = layers.Embedding(output_dim=emb_size, input_dim=num_users+1, input_length=rows_count+1, name='user_emb')(user_input)\n",
    "    user_vec = layers.Flatten(name='user_emb_flatten')(user_emb)\n",
    "\n",
    "    user_model = keras.Model(inputs=user_input, outputs=user_vec)\n",
    "\n",
    "    merged = layers.Dot(name = 'dot_product', normalize = True, axes=1)([encoder_dense_4, user_vec])\n",
    "    merged_dropout = layers.Dropout(0.2)(merged)\n",
    "\n",
    "\n",
    "    dense_1 = layers.Dense(256,name='FullyConnected-1')(merged)\n",
    "    dropout_1 = layers.Dropout(0.2,name='Dropout-1')(dense_1)\n",
    "\n",
    "    dense_2 = layers.Dense(128,name='FullyConnected-2')(dropout_1)\n",
    "    dropout_2 = layers.Dropout(0.2,name='Dropout-2')(dense_2)\n",
    "\n",
    "    dense_3 = keras.layers.Dense(32,name='FullyConnected-3')(dropout_2)\n",
    "    dropout_3 = keras.layers.Dropout(0.2,name='Dropout-3')(dense_3)\n",
    "\n",
    "    dense_4 = keras.layers.Dense(8,name='FullyConnected-4', activation='relu')(dropout_3)\n",
    "\n",
    "    result = layers.Dense(1, name='result', activation=\"sigmoid\")(dense_4)\n",
    "\n",
    "    model = keras.Model([autoencoder_input, user_input], result)\n",
    "    model.compile(optimizer=adam, loss= 'mean_absolute_error', metrics='mean_squared_error')\n",
    "    return encoder, decoder, autoencoder, user_model, model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "fdec8090",
   "metadata": {},
   "outputs": [],
   "source": [
    "encoder, decoder, autoencoder, enc_user_model, enc_model = encoder_model(X.userId.nunique(), genome.shape[1], X.shape[0], 64)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d19c4b7e",
   "metadata": {},
   "source": [
    "**Cхема автоэнкодера**"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "1ee06ff0",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src=\"attachment:image.png\" width=\"500\"/>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd758bd0",
   "metadata": {},
   "source": [
    "Идея состоит в том, чтобы использовать датасет *genome*. В нём даны темы фильмов и релеватность каждого фильма каждой теме. Такие векторы можно использовать для определения схожести фильмов: похожие фильмы имеют похожие темы. Проблема заключается в том, что многие темы похожи, а самих тем довольно много. Можно обучить автоэнкодер для уменьшения размерности вектора с темами, а затем использовать энкодер для создания векторных представлений фильмов"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66eca9a3",
   "metadata": {},
   "source": [
    "**Полная схема модели**"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "5419020c",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src=\"attachment:image.png\" width=\"500\"/>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6801b7c",
   "metadata": {},
   "source": [
    "Фильмы кодируются с помощью энкодера тематик, а для пользователя создаётся эмбеддинг. Также был увеличен размер эмбеддингов."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5922f9a0",
   "metadata": {},
   "source": [
    "Обучение энкодера"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "a088d7cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "119/119 [==============================] - 5s 33ms/step - loss: 0.0673 - mean_squared_error: 0.0176 - val_loss: 0.0461 - val_mean_squared_error: 0.0099\n",
      "Epoch 2/100\n",
      "119/119 [==============================] - 3s 25ms/step - loss: 0.0432 - mean_squared_error: 0.0087 - val_loss: 0.0411 - val_mean_squared_error: 0.0079\n",
      "Epoch 3/100\n",
      "119/119 [==============================] - 3s 25ms/step - loss: 0.0399 - mean_squared_error: 0.0074 - val_loss: 0.0391 - val_mean_squared_error: 0.0072\n",
      "Epoch 4/100\n",
      "119/119 [==============================] - 3s 26ms/step - loss: 0.0383 - mean_squared_error: 0.0068 - val_loss: 0.0379 - val_mean_squared_error: 0.0066\n",
      "Epoch 5/100\n",
      "119/119 [==============================] - 4s 30ms/step - loss: 0.0373 - mean_squared_error: 0.0064 - val_loss: 0.0369 - val_mean_squared_error: 0.0064\n",
      "Epoch 6/100\n",
      "119/119 [==============================] - 4s 31ms/step - loss: 0.0367 - mean_squared_error: 0.0062 - val_loss: 0.0369 - val_mean_squared_error: 0.0063\n",
      "Epoch 7/100\n",
      "119/119 [==============================] - 4s 29ms/step - loss: 0.0361 - mean_squared_error: 0.0060 - val_loss: 0.0360 - val_mean_squared_error: 0.0059\n",
      "Epoch 8/100\n",
      "119/119 [==============================] - 3s 29ms/step - loss: 0.0357 - mean_squared_error: 0.0059 - val_loss: 0.0359 - val_mean_squared_error: 0.0058\n",
      "Epoch 9/100\n",
      "119/119 [==============================] - 4s 32ms/step - loss: 0.0353 - mean_squared_error: 0.0058 - val_loss: 0.0353 - val_mean_squared_error: 0.0058\n",
      "Epoch 10/100\n",
      "119/119 [==============================] - 4s 31ms/step - loss: 0.0353 - mean_squared_error: 0.0057 - val_loss: 0.0351 - val_mean_squared_error: 0.0058\n",
      "Epoch 11/100\n",
      "119/119 [==============================] - 4s 30ms/step - loss: 0.0350 - mean_squared_error: 0.0057 - val_loss: 0.0352 - val_mean_squared_error: 0.0057\n",
      "Epoch 12/100\n",
      "119/119 [==============================] - 4s 31ms/step - loss: 0.0348 - mean_squared_error: 0.0056 - val_loss: 0.0348 - val_mean_squared_error: 0.0056\n",
      "Epoch 13/100\n",
      "119/119 [==============================] - 4s 33ms/step - loss: 0.0347 - mean_squared_error: 0.0056 - val_loss: 0.0349 - val_mean_squared_error: 0.0057\n",
      "Epoch 14/100\n",
      "119/119 [==============================] - 4s 31ms/step - loss: 0.0347 - mean_squared_error: 0.0056 - val_loss: 0.0349 - val_mean_squared_error: 0.0056\n",
      "Epoch 15/100\n",
      "119/119 [==============================] - 3s 27ms/step - loss: 0.0346 - mean_squared_error: 0.0056 - val_loss: 0.0348 - val_mean_squared_error: 0.0056\n",
      "Epoch 16/100\n",
      "119/119 [==============================] - 3s 27ms/step - loss: 0.0346 - mean_squared_error: 0.0056 - val_loss: 0.0349 - val_mean_squared_error: 0.0056\n",
      "Epoch 17/100\n",
      "119/119 [==============================] - 3s 28ms/step - loss: 0.0346 - mean_squared_error: 0.0056 - val_loss: 0.0347 - val_mean_squared_error: 0.0056\n",
      "Epoch 18/100\n",
      "119/119 [==============================] - 4s 32ms/step - loss: 0.0345 - mean_squared_error: 0.0056 - val_loss: 0.0346 - val_mean_squared_error: 0.0056\n",
      "Epoch 19/100\n",
      "119/119 [==============================] - 3s 29ms/step - loss: 0.0345 - mean_squared_error: 0.0055 - val_loss: 0.0347 - val_mean_squared_error: 0.0056\n",
      "Epoch 20/100\n",
      "119/119 [==============================] - 3s 28ms/step - loss: 0.0345 - mean_squared_error: 0.0055 - val_loss: 0.0349 - val_mean_squared_error: 0.0056\n",
      "Epoch 21/100\n",
      "119/119 [==============================] - 4s 32ms/step - loss: 0.0345 - mean_squared_error: 0.0055 - val_loss: 0.0346 - val_mean_squared_error: 0.0056\n",
      "Epoch 22/100\n",
      "119/119 [==============================] - 3s 28ms/step - loss: 0.0345 - mean_squared_error: 0.0055 - val_loss: 0.0349 - val_mean_squared_error: 0.0056\n",
      "Epoch 23/100\n",
      "119/119 [==============================] - 3s 29ms/step - loss: 0.0345 - mean_squared_error: 0.0055 - val_loss: 0.0347 - val_mean_squared_error: 0.0056\n",
      "Epoch 24/100\n",
      "119/119 [==============================] - 3s 29ms/step - loss: 0.0345 - mean_squared_error: 0.0055 - val_loss: 0.0347 - val_mean_squared_error: 0.0056\n",
      "Epoch 25/100\n",
      "119/119 [==============================] - 4s 30ms/step - loss: 0.0345 - mean_squared_error: 0.0055 - val_loss: 0.0349 - val_mean_squared_error: 0.0056\n",
      "Epoch 26/100\n",
      "119/119 [==============================] - 4s 32ms/step - loss: 0.0345 - mean_squared_error: 0.0055 - val_loss: 0.0346 - val_mean_squared_error: 0.0056\n",
      "Epoch 27/100\n",
      "119/119 [==============================] - 4s 33ms/step - loss: 0.0344 - mean_squared_error: 0.0055 - val_loss: 0.0346 - val_mean_squared_error: 0.0056\n",
      "Epoch 28/100\n",
      "119/119 [==============================] - 4s 31ms/step - loss: 0.0344 - mean_squared_error: 0.0055 - val_loss: 0.0347 - val_mean_squared_error: 0.0057\n",
      "Epoch 29/100\n",
      "119/119 [==============================] - 4s 32ms/step - loss: 0.0344 - mean_squared_error: 0.0055 - val_loss: 0.0347 - val_mean_squared_error: 0.0056\n",
      "Epoch 30/100\n",
      "119/119 [==============================] - 4s 32ms/step - loss: 0.0344 - mean_squared_error: 0.0055 - val_loss: 0.0347 - val_mean_squared_error: 0.0056\n",
      "Epoch 31/100\n",
      "119/119 [==============================] - 4s 36ms/step - loss: 0.0344 - mean_squared_error: 0.0055 - val_loss: 0.0347 - val_mean_squared_error: 0.0056\n"
     ]
    }
   ],
   "source": [
    "callbacks = [keras.callbacks.EarlyStopping('val_loss', patience=10),\n",
    "             keras.callbacks.ModelCheckpoint('models/features/model/besttesttt.h5', save_best_only=True)]\n",
    "\n",
    "encoder_history = autoencoder.fit(X_train_autoenc, X_train_autoenc, batch_size=100,\n",
    "                              epochs=100, validation_data=(X_valid_autoenc, X_valid_autoenc),\n",
    "                              verbose=1,\n",
    "                              callbacks = callbacks)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b233b0b6",
   "metadata": {},
   "source": [
    "Обучение модели"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cfdb1b4c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "447/447 [==============================] - 13s 23ms/step - loss: 0.1638 - mean_squared_error: 0.0472 - val_loss: 0.1512 - val_mean_squared_error: 0.0400\n",
      "Epoch 2/50\n",
      "447/447 [==============================] - 9s 21ms/step - loss: 0.1483 - mean_squared_error: 0.0395 - val_loss: 0.1467 - val_mean_squared_error: 0.0384\n",
      "Epoch 3/50\n",
      "447/447 [==============================] - 10s 22ms/step - loss: 0.1430 - mean_squared_error: 0.0373 - val_loss: 0.1447 - val_mean_squared_error: 0.0380\n",
      "Epoch 4/50\n",
      "447/447 [==============================] - 10s 21ms/step - loss: 0.1405 - mean_squared_error: 0.0362 - val_loss: 0.1436 - val_mean_squared_error: 0.0373\n",
      "Epoch 5/50\n",
      "447/447 [==============================] - 10s 22ms/step - loss: 0.1384 - mean_squared_error: 0.0355 - val_loss: 0.1432 - val_mean_squared_error: 0.0371\n",
      "Epoch 6/50\n",
      "447/447 [==============================] - 10s 22ms/step - loss: 0.1366 - mean_squared_error: 0.0348 - val_loss: 0.1421 - val_mean_squared_error: 0.0368\n",
      "Epoch 7/50\n",
      "447/447 [==============================] - 10s 22ms/step - loss: 0.1350 - mean_squared_error: 0.0341 - val_loss: 0.1429 - val_mean_squared_error: 0.0367\n",
      "Epoch 8/50\n",
      "447/447 [==============================] - 12s 26ms/step - loss: 0.1338 - mean_squared_error: 0.0337 - val_loss: 0.1427 - val_mean_squared_error: 0.0373\n",
      "Epoch 9/50\n",
      "447/447 [==============================] - 12s 27ms/step - loss: 0.1324 - mean_squared_error: 0.0331 - val_loss: 0.1427 - val_mean_squared_error: 0.0368\n",
      "Epoch 10/50\n",
      "447/447 [==============================] - 12s 28ms/step - loss: 0.1316 - mean_squared_error: 0.0328 - val_loss: 0.1442 - val_mean_squared_error: 0.0384\n",
      "Epoch 11/50\n",
      "447/447 [==============================] - 12s 28ms/step - loss: 0.1304 - mean_squared_error: 0.0323 - val_loss: 0.1412 - val_mean_squared_error: 0.0368\n",
      "Epoch 12/50\n",
      "447/447 [==============================] - 12s 28ms/step - loss: 0.1294 - mean_squared_error: 0.0319 - val_loss: 0.1426 - val_mean_squared_error: 0.0378\n",
      "Epoch 13/50\n",
      "447/447 [==============================] - 13s 28ms/step - loss: 0.1283 - mean_squared_error: 0.0315 - val_loss: 0.1446 - val_mean_squared_error: 0.0377\n",
      "Epoch 14/50\n",
      "447/447 [==============================] - 12s 27ms/step - loss: 0.1275 - mean_squared_error: 0.0312 - val_loss: 0.1409 - val_mean_squared_error: 0.0371\n",
      "Epoch 15/50\n",
      "447/447 [==============================] - 12s 27ms/step - loss: 0.1266 - mean_squared_error: 0.0310 - val_loss: 0.1404 - val_mean_squared_error: 0.0365\n",
      "Epoch 16/50\n",
      "447/447 [==============================] - 12s 27ms/step - loss: 0.1259 - mean_squared_error: 0.0308 - val_loss: 0.1414 - val_mean_squared_error: 0.0371\n",
      "Epoch 17/50\n",
      "447/447 [==============================] - 12s 28ms/step - loss: 0.1250 - mean_squared_error: 0.0304 - val_loss: 0.1408 - val_mean_squared_error: 0.0364\n",
      "Epoch 18/50\n",
      "447/447 [==============================] - 15s 35ms/step - loss: 0.1244 - mean_squared_error: 0.0302 - val_loss: 0.1427 - val_mean_squared_error: 0.0378\n",
      "Epoch 19/50\n",
      "447/447 [==============================] - 15s 34ms/step - loss: 0.1241 - mean_squared_error: 0.0301 - val_loss: 0.1410 - val_mean_squared_error: 0.0370\n",
      "Epoch 20/50\n",
      "447/447 [==============================] - 15s 34ms/step - loss: 0.1237 - mean_squared_error: 0.0299 - val_loss: 0.1423 - val_mean_squared_error: 0.0378\n",
      "Epoch 21/50\n",
      "447/447 [==============================] - 16s 36ms/step - loss: 0.1228 - mean_squared_error: 0.0297 - val_loss: 0.1419 - val_mean_squared_error: 0.0372\n",
      "Epoch 22/50\n",
      "447/447 [==============================] - 17s 39ms/step - loss: 0.1225 - mean_squared_error: 0.0296 - val_loss: 0.1401 - val_mean_squared_error: 0.0364\n",
      "Epoch 23/50\n",
      "447/447 [==============================] - 19s 42ms/step - loss: 0.1217 - mean_squared_error: 0.0292 - val_loss: 0.1407 - val_mean_squared_error: 0.0368\n",
      "Epoch 24/50\n",
      "447/447 [==============================] - 19s 42ms/step - loss: 0.1213 - mean_squared_error: 0.0291 - val_loss: 0.1399 - val_mean_squared_error: 0.0361\n",
      "Epoch 25/50\n",
      "447/447 [==============================] - 18s 39ms/step - loss: 0.1207 - mean_squared_error: 0.0289 - val_loss: 0.1421 - val_mean_squared_error: 0.0375\n",
      "Epoch 26/50\n",
      "447/447 [==============================] - 18s 39ms/step - loss: 0.1204 - mean_squared_error: 0.0288 - val_loss: 0.1404 - val_mean_squared_error: 0.0368\n",
      "Epoch 27/50\n",
      "447/447 [==============================] - 19s 43ms/step - loss: 0.1197 - mean_squared_error: 0.0287 - val_loss: 0.1427 - val_mean_squared_error: 0.0377\n",
      "Epoch 28/50\n",
      "447/447 [==============================] - 17s 39ms/step - loss: 0.1193 - mean_squared_error: 0.0285 - val_loss: 0.1415 - val_mean_squared_error: 0.0377\n",
      "Epoch 29/50\n",
      "447/447 [==============================] - 15s 34ms/step - loss: 0.1191 - mean_squared_error: 0.0285 - val_loss: 0.1415 - val_mean_squared_error: 0.0372\n",
      "Epoch 30/50\n",
      "447/447 [==============================] - 15s 33ms/step - loss: 0.1185 - mean_squared_error: 0.0282 - val_loss: 0.1417 - val_mean_squared_error: 0.0377\n",
      "Epoch 31/50\n",
      "447/447 [==============================] - 15s 33ms/step - loss: 0.1182 - mean_squared_error: 0.0281 - val_loss: 0.1422 - val_mean_squared_error: 0.0375\n",
      "Epoch 32/50\n",
      "447/447 [==============================] - 15s 33ms/step - loss: 0.1180 - mean_squared_error: 0.0280 - val_loss: 0.1421 - val_mean_squared_error: 0.0377\n",
      "Epoch 33/50\n",
      "447/447 [==============================] - 15s 33ms/step - loss: 0.1176 - mean_squared_error: 0.0279 - val_loss: 0.1411 - val_mean_squared_error: 0.0371\n",
      "Epoch 34/50\n",
      "447/447 [==============================] - 15s 33ms/step - loss: 0.1169 - mean_squared_error: 0.0277 - val_loss: 0.1415 - val_mean_squared_error: 0.0376\n"
     ]
    }
   ],
   "source": [
    "callbacks = [keras.callbacks.EarlyStopping('val_loss', patience=10),\n",
    "             keras.callbacks.ModelCheckpoint('models/features/model/besttesttt.h5', save_best_only=True)]\n",
    "\n",
    "encoder_f_history = enc_model.fit([X_train_genome.drop(['userId', 'movieId'], axis=1), X_train_genome['userId']], y_train_genome, batch_size=200,\n",
    "                              epochs=50, validation_data=([X_valid_genome.drop(['userId', 'movieId'], axis=1), X_valid_genome['userId']], y_valid_genome),\n",
    "                              verbose=1,\n",
    "                              callbacks = callbacks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d8c54552",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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A+/fvz9v26NEjBAUFYcCAAUhJSUHXrl2xd+9enDt3Dp06dUKPHj0QFRVVouOnpqaie/fu8PHxQUhICGbOnInJkyeX+tdZFkyudIiPrQ8AFrUgIiIiIt1lY2ODzp07Y8OGDXnbfv/9d9jY2KBDhw7w9fXFiBEj0KBBA3h5eeHLL79ErVq1sH379hIdf/369cjJycHq1atRr149dO/eHVOmTCmv0ymAc650iLetNwAWtSAiIiKiIpiZASkp8j13KQwYMADvv/8+li9fDmNjY6xfvx5vv/02VCoVUlNTMWvWLOzYsQPR0dHIzs7G48ePS9xzdfXqVfj6+sLsiZj8/PxKFV9ZMbnSIbnJ1b/xHBZIRERERE9RKIAqVeSOokR69OgBtVqNnTt3onnz5jh8+DAWLlwIAJgyZQqCgoKwYMECeHp6wtTUFH369EFmZmaJji2VYv6XpjG50iG1bWsDYM8VEREREek2U1NTvP7661i/fj2uX78Ob29vNG3aFABw+PBhDBkyBL179wYApKSkIDIyssTHrlu3Ln755Rc8fvwYpqamAIATJ05o/ByKwjlXOsTLxgsAcC/1HhLSE+QNhoiIiIjoBQwYMAA7d+7E6tWr8c477+Rt9/T0xJ9//onQ0FCcP38e/fv3L1RZ8Fn69+8PpVKJYcOG4cqVKwgMDMSCBQvK4xQKYXKlQyyNLVHdojoA9l4RERERkW575ZVXYGNjg2vXrqF///552xctWoSqVavC398fPXr0QKdOndCkSZMSH9fc3Bx///03rly5gsaNG2P69On45ptvyuMUCuGwQB3jY+uD6ORoXIu/hpY1WsodDhERERFRmahUKkRHRxfa7u7ujn379hXYNmbMmAK3nx4m+PQ8q1atWiE0NPSZ+5QH9lzpmNxy7FzrioiIiIhIuzC50jG17f4rasG1roiIiIiItAqTKx3jY/ffQsKcc0VEREREpFWYXOmY3GGB4Q/DkaPOkTkaIiIiIiLKxeRKx7haucLEwASZOZmITIiUOxwiIiIikpmci+bqC039DmVPrpYvX46aNWvCxMQETZs2xeHDh4vdNyYmBv3794ePjw+USiXGjx9f5H4JCQkYM2YMnJycYGJigjp16iAwMLCczqBiqZSqvPWuOO+KiIiIqPIyNDQEAKSlpckcie7LzMwEICoYvghZS7Fv3rwZ48ePx/Lly9G6dWusXLkSXbp0wZUrV+Dq6lpo/4yMDNjb22P69OlYtGhRkcfMzMxEx44d4eDggD/++AM1atTA7du3YWFhUd6nU2Fq29XGxbiL+PfBv+jq1VXucIiIiIhIBiqVCtbW1oiLiwMAmJmZQaFQyByV7lGr1bh//z7MzMxgYPBi6ZGsydXChQsxbNgwvPfeewCAxYsXIygoCCtWrMDcuXML7e/u7o4lS5YAAFavXl3kMVevXo2HDx/i2LFjedm8m5tbOZ2BPHLnXbGoBREREVHlVq1aNQDIS7CobJRKJVxdXV84OZUtucrMzERISAimTp1aYHtAQACOHTtW5uNu374dfn5+GDNmDLZt2wZ7e3v0798fH3/8cbHdfBkZGcjIyMi7nZSUBADIyspCVlZWmWPRlNwYcn96VPUAINa60ob4SHi6nUh7sa10B9tKd7CtdAPbSXeUpq3s7OxQtWpVZGdnc/5VGSgUChgaGkKhUBT5+y7N+0W25OrBgwfIycmBo6Njge2Ojo6IjY0t83Fv3LiBffv2YcCAAQgMDER4eDjGjBmD7OxsfP7550U+Zu7cuZg1a1ah7Xv27IGZmVmZY9G04OBgAEB8WjwA4EL0Bb2ZS6ZPctuJtB/bSnewrXQH20o3sJ10B9tKfqWZ0ybrsEAAhbreJEl6oe44tVoNBwcH/Pjjj1CpVGjatCmio6Mxf/78YpOradOmYeLEiXm3k5KS4OLigoCAAFhaWpY5Fk3JyspCcHAwOnbsCENDQyRlJGHyt5ORkJ0A/1f8YW1iLXeIhMLtRNqLbaU72Fa6g22lG9hOuoNtpT1yR7WVhGzJlZ2dHVQqVaFeqri4uEK9WaXh5OQEQ0PDAkMA69Spg9jYWGRmZsLIyKjQY4yNjWFsbFxou6GhoVa9mHPjsTW0hZO5E2JSYnAj8QZaWrSUOzR6gra9bqh4bCvdwbbSHWwr3cB20h1sK/mV5vcvWyl2IyMjNG3atFBXZ3BwMPz9/ct83NatW+P69etQq9V528LCwuDk5FRkYqWratvVBsBy7ERERERE2kLWda4mTpyIVatWYfXq1bh69SomTJiAqKgojBw5EoAYrjdo0KACjwkNDUVoaChSUlJw//59hIaG4sqVK3n3jxo1CvHx8fjwww8RFhaGnTt3Ys6cORgzZkyFnlt5Y8VAIiIiIiLtIuucq759+yI+Ph6zZ89GTEwM6tevj8DAwLzS6TExMYiKiirwmMaNG+ddDwkJwYYNG+Dm5obIyEgAgIuLC/bs2YMJEyagYcOGcHZ2xocffoiPP/64ws6rIvjYieTq3/h/ZY6EiIiIiIgALShoMXr0aIwePbrI+9asWVNoW0nKS/r5+eHEiRMvGppWyxsWyJ4rIiIiIiKtIOuwQCq73GGB4Q/DkaPOkTkaIiIiIiJicqWjXK1cYWJggsycTEQmRModDhERERFRpcfkSkeplCp42XgBYMVAIiIiIiJtwORKh+UVtXjAohZERERERHJjcqXDatuyqAURERERkbZgcqXDcnuuOCyQiIiIiEh+TK50WG7FQA4LJCIiIiKSH5MrHZbbc3Uv9R4S0xNljoaIiIiIqHJjcqXDLI0t4WTuBIBDA4mIiIiI5MbkSsfVthNFLTg0kIiIiIhIXkyudFzuvCtWDCQiIiIikheTKx2Xt9ZVPHuuiIiIiIjkxORKx+UOC2TPFRERERGRvJhc6bjcYYHhD8ORo86RORoiIiIiosqLyZWOc7VyhbHKGJk5mYhMiJQ7HCIiIiKiSovJlY5TKVXwtvUGwHLsRERERERyYnKlB3KLWnDeFRERERGRfJhc6YHceVdc64qIiIiISD5MrvRAXsVADgskIiIiIpINkys9wJ4rIiIiIiL5MbnSA7lzru6l3kNieqLM0RARERERVU5MrvSApbElnMydAHBoIBERERGRXJhc6Ync3isODSQiIiIikgeTKz1R2/a/ohYsx05EREREJAsmV3oib60rDgskIiIiIpIFkys9wYqBRERERETyYnKlJ3LXugp/GI4cdY7M0RARERERVT5MrvSEq5UrjFXGyMzJRGRCpNzhEBERERFVOkyu9IRKqYK3rTcAzrsiIiIiIpIDkys9klfUghUDiYiIiIgqHJMrPcKiFkRERERE8mFypUdyi1pwWCARERERUcVjcqVHcnuumFwREREREVU8Jld6JHfOVWxKLBLTE2WOhoiIiIiocmFypUcsjS3hZO4EgL1XREREREQVjcmVnsntvWJRCyIiIiKiisXkSs/Utv2vqAXLsRMRERERVSgmV3omb60rDgskIiIiIqpQTK70DNe6IiIiIiKSB5MrPZO71tX1h9eRo86RORoiIiIiosqDyZWecbVyhbHKGBk5GbiVeEvucIiIiIiIKg0mV3pGpVTBy9YLAIcGEhERERFVJCZXeih3aCArBhIRERERVRwmV3qIRS2IiIiIiCoekys9lJtcsRw7EREREVHFYXKlh/KGBTK5IiIiIiKqMEyu9FDuQsKxKbFITE+UORoiIiIiosqByZUesjS2hJO5EwD2XhERERERVRQmV3oqt/eKFQOJiIiIiCoGkys9xYqBREREREQVi8mVnmJRCyIiIiKiisXkSk+xHDsRERERUcVicqWncudchceHI0edI3M0RERERET6j8mVnnKzcoOxyhgZORm4lXhL7nCIiIiIiPQekys9pVKq4GXrBYBFLYiIiIiIKgKTKz2WV9SC5diJiIiIiModkys9xqIWREREREQVh8mVHuNaV0REREREFYfJlR7jWldERERERBWHyZUeyy3HHpsSi8T0RJmjISIiIiLSb0yu9JilsSWqmVcDwN4rIiIiIqLyxuRKz7FiIBERERFRxWBypedY1IKIiIiIqGIwudJzLMdORERERFQxmFzpOVYMJCIiIiKqGEyu9FxuxcDw+HDkqHNkjoaIiIiISH8xudJzblZuMFYZIyMnA7cSb8kdDhERERGR3mJypedUShW8bL0AsGIgEREREVF5YnJVCbBiIBERERFR+WNyVQmwqAURERERUfljcqXt7tyB8oMPYBYTU+ZDsOeKiIiIiKj8MbnSdh98ANWPP6L2pk1lPkRuxUD2XBERERERlR8mV9ru888BADUOHQIuXSrTIXJ7rmJTYpGYnqix0IiIiIiIKB+TK23XpAnUvXtDIUlQzZpVpkNYmVihmnk1AOy9IiIiIiIqL0yudEDOjBmQlEoot20DTp8u0zHyilqwHDsRERERUblgcqUL6tbF7bZtxfVPPy3TIXKHBrLnioiIiIiofDC50hHX+vaFZGAA7NkDHDpU6sezYiARERERUflicqUj0qpVg3rYMHFj+nRAkkr1eK51RURERERUvphc6RD1tGmAiQlw5Aiwe3epHptbjj08Phw56pzyCI+IiIiIqFKTPblavnw5atasCRMTEzRt2hSHDx8udt+YmBj0798fPj4+UCqVGD9+fKF91qxZA4VCUeiSnp5ejmdRQapXB8aMEdenTwfU6hI/1M3KDcYqY2TkZOBW4q1yCpCIiIiIqPKSNbnavHkzxo8fj+nTp+PcuXN46aWX0KVLF0RFRRW5f0ZGBuzt7TF9+nT4+voWe1xLS0vExMQUuJiYmJTXaVSsqVMBc3Pg3Dngzz9L/DCVUgUvWy8ArBhIRERERFQeZE2uFi5ciGHDhuG9995DnTp1sHjxYri4uGDFihVF7u/u7o4lS5Zg0KBBsLKyKva4CoUC1apVK3DRG3Z2wMSJ4vrnnwM5JR/ix6IWRERERETlx0CuJ87MzERISAimTp1aYHtAQACOHTv2QsdOSUmBm5sbcnJy0KhRI3zxxRdo3LhxsftnZGQgIyMj73ZSUhIAICsrC1lZWS8UiybkxpAXy9ixMFi6FIqrV5G9di2kgQNLdBzPqp4AgKv3r2rFeembQu1EWottpTvYVrqDbaUb2E66g22lPUrTBrIlVw8ePEBOTg4cHR0LbHd0dERsbGyZj1u7dm2sWbMGDRo0QFJSEpYsWYLWrVvj/Pnz8PLyKvIxc+fOxaxZswpt37NnD8zMzMoci6YFBwfnXffs0QP11q1DxrRp+MfSEpKh4XMfn/5QzDs7Hn4cgVJgucVZ2T3ZTqTd2Fa6g22lO9hWuoHtpDvYVvJLS0sr8b6yJVe5FApFgduSJBXaVhqtWrVCq1at8m63bt0aTZo0wdKlS/Hdd98V+Zhp06ZhYu5QO4ieKxcXFwQEBMDS0rLMsWhKVlYWgoOD0bFjRxjmJlFt20LaswdVYmPRLTYW6hEjnnsc+2h7LFmzBA+kB+jatWs5R135FNlOpJXYVrqDbaU72Fa6ge2kO9hW2iN3VFtJyJZc2dnZQaVSFeqliouLK9Sb9SKUSiWaN2+O8PDwYvcxNjaGsbFxoe2GhoZa9WIuEI+1tagYOHYsVHPmQDVsGGBq+szH13OsBwCITY1FWk4arEyKn7dGZadtrxsqHttKd7CtdAfbSjewnXQH20p+pfn9y1bQwsjICE2bNi3U1RkcHAx/f3+NPY8kSQgNDYWTk5PGjqk1hg8HXF2BmBhg2bLn7m5lYoVq5qK4BxcTJiIiIiLSLFmrBU6cOBGrVq3C6tWrcfXqVUyYMAFRUVEYOXIkADFcb9CgQQUeExoaitDQUKSkpOD+/fsIDQ3FlStX8u6fNWsWgoKCcOPGDYSGhmLYsGEIDQ3NO6ZeMTYGZs4U17/+GihBl2VuxUCWYyciIiIi0ixZ51z17dsX8fHxmD17NmJiYlC/fn0EBgbCzc0NgFg0+Ok1r56s+hcSEoINGzbAzc0NkZGRAICEhAS8//77iI2NhZWVFRo3boxDhw6hRYsWFXZeFWrgQOCbb4Br14DFi0V59meobVcbB28dZM8VEREREZGGyV7QYvTo0Rg9enSR961Zs6bQNkmSnnm8RYsWYdGiRZoITTcYGACzZgFvvw0sWACMGQPY2ha7O9e6IiIiIiIqH7IOCyQNefNNwNcXSE4G5s175q4+dv8NC2TPFRERERGRRjG50gdKJfDll+L60qWiwEUxatvVBgCEx4cjR51TEdEREREREVUKTK70RbduQKtWwOPHwFdfFbubm5UbjFXGyMjJwK3EWxUYIBERERGRfmNypS8UCmDOHHH9xx+B/wp8PE2lVMHL1gsAKwYSEREREWkSkyt90r490KEDkJUFzJ5d7G4sakFEREREpHlMrvRN7pDAtWuBf4tOnvLWumJRCyIiIiIijWFypW9atgR69gTUamDGjCJ3yS1qweSKiIiIiEhzmFzpoy++EHOwfvsNCA0tdHcd+zoAgLMxZ5GSmVLBwRERERER6ScmV/qoYUOgb19x/dNPC93duFpjeNp4IikjCf87978KDo6IiIiISD8xudJXs2YBKhWwcydw/HiBu1RKFSa2mggAWHRiEde7IiIiIiLSACZX+srbGxgyRFz/5BNAkgrcPbjRYNia2uJmwk389e9fFR8fEREREZGeYXKlzz7/HDAyAg4cAP75p8BdZoZmGN18NABgwbEFkJ5KvoiIiIiIqHSYXOkzV1dg5Ehxffr0Qr1XY5qPgbHKGCfvnsSx28dkCJCIiIiISH8wudJ3n3wCmJkBp04Bf/9d4C5Hc0e80/AdAMC3x7+VIzoiIiIiIr3B5ErfOToC48aJ659+Kta/esJEP1HYYuu/WxEeH17R0RERERER6Q0mV5XBlCmApSVw8SKweXOBu+ra10VXr66QIGHxicXyxEdEREREpAeYXFUGNjYiwQJEkYusrAJ3T/abDAD4X+j/EJ8WX9HRERERERHpBSZXlcWHHwJ2dsD168DatQXuaufeDo2rNcbj7MdYcWaFTAESEREREek2JleVhYUFMG2auD57NpCenneXQqHAZH/Re7X01FKkZ6cXdQQiIiIiInoGJleVyahRgLMzcPs2sHJlgbverPsmaljWQFxqHNZfWC9TgEREREREuovJVWViagp89pm4PmcOkJqad5ehyhAftvwQgCjLrpbURR2BiIiIiIiKweSqshk6FKhVC4iLAxYvLnDX8CbDYWFkgasPrmL39d3yxEdEREREpKOYXFU2hobArFni+uefAwsXApIEALAyscLwJsMBcFFhIiIiIqLSYnJVGfXvL3qw1Gpg0iRg4EDg8WMAwIetPoRKocK+m/twLuaczIESEREREekOJleVkVIJrFoFfPcdoFIB69cDbdoAUVFwtXLFW/XeAsDeKyIiIiKi0mByVVkpFMDYsUBwMGBrC5w9CzRrBhw8iEl+kwAAmy5twu3E2zIHSkRERESkG5hcVXbt2wNnzgCNGgH37wOvvoqmfx5HO7e2yJFy8N3J7+SOkIiIiIhIJzC5IsDdHTh6FOjXD8jOBsaOxbodRjDKBn48+yOSMpLkjpCIiIiISOsxuSLBzEzMvZo/H1Aq4bIlGKd+NUGV+0lYdXaV3NEREREREWk9JleUT6EAJk8Gdu0CqlaFb2Q6Qn4EDm36Blk5WXJHR0RERESk1ZhcUWEBAcDp01DXqwenFOC37+Nw9osxckdFRERERKTVmFxR0Tw8oDxxAldfrgMjNdBy1k+QRo0CMjPljoyIiIiISCsxuaLimZvDPvAgZrxqADUAxQ8/AB06APfuyR0ZEREREZHWYXJFz2RXxR5xH76Hnv2AVFMD4MgRoGlT4PRpuUMjIiIiItIqTK7ouSb4TUCgjwJNhmUjw7MmcPcu8NJLwLp1codGRERERKQ1mFzRc3nbeqOnT0+E2QEfffEy0KMHkJEBDB4MjB8PZLGSIBERERERkysqkcn+kwEAK69vwr1fVwKffSbuWLIE6NQJePBAxuiIiIiIiOTH5IpKpLVLa7RwboGMnAwsD/kBmD0b2LIFqFIF2L8faNYMCA2VO0wiIiIiItkwuaISUSgUmOQ3CQCw7PQypGWlAa+/Dpw4AXh4ALduAf7+wIYNgCTJHC0RERERUcVjckUl9nqd1+Fu7Y74x/FYd/6/Yhb164vKgZ06AY8fAwMGiGIXQUFMsog0ISoKyM6WOwoiIiIqASZXVGIGSgOMbzkeALDw+EKoJbW4o2pVYOdO4NNPAWNj4OhRoHNnoFUrYMcOJllEZZGTA0ycCLi5iSIyfB8RERFpPSZXVCpDGw+FtYk1wh+G4+9rf+ffoVIBX3wB3LwJTJgAmJoCp06JD4VNmwJ//QWo1fIFTqRLkpKAnj2BRYvE7d27gZ9/ljcmIiIiei4mV1QqFsYWGNF0BADg2+PfFt7ByQlYuBCIjAQ++kgUvDh3TszP8vUFNm8W38gTUdFu3AD8/IDAQMDEBHjzTbF98mQgOlre2IiIiOiZmFxRqY1tMRaGSkMcjjqMU3dPFb2TgwPwzTciyZo+HbC0BC5dAt5+W8zTWr+e80jo+VJSgF9+AWJi5I6kYhw+DLRsCVy5AlSvLm5v2CCqcSYmAh98IHeERERE9AxMrqjUnC2d0a9BPwDF9F49yc4O+PJLkWTNnAlYWwP//gu88w5Qpw6wZg0XIaai7dwJ1KsHDBoEvPwy8OiR3BGVr9WrgQ4dxJpxTZuKYbXNmgEGBmJIoIGBGF67ZYvckRIREVExmFxRmeSWZf/jyh+4+ejm8x9QtSowY4Yo2T5nDmBrC1y/Drz7LuDtDfz4I5CZWc5Rk06IjQX69gW6dxeV8gDxWhkwQD+HlObkAFOmAMOGiS8a3nwTOHQIcHbO36dhQ2DqVHF9zBj9TzSJiIh0FJMrKpOGjg3RsVZHqCU1lpxcUvIHWloC06aJnqz588XwwchIYMQIwNMTWLYMSE8vr7BJm6nVIsmuUwf47TdRJGXyZFF90tQU2LUL+PxzuaPUrKQk4LXXgAULxO0ZM4BNmwAzs8L7fvopULs2cO8eMGlShYZJREREJcPkisost/dq1dlVePS4lN+km5uLD843bwKLF4tCGLdvizkltWqJbWlpGo+ZtNTVq0DbtiLJTkgQw+JOnxYJuL9/fqW8OXP0Z1hcZCTQurVYrsDEBNi4UQydVRbzZ9nYGFi1ClAogP/9D9i7tyKjJSIiohJgckVlFuARgPoO9ZGalYofQ34s20HMzIAPPxQV0pYtA1xcRPGCCROAmjXFh+uUFM0GTtojI0MkFL6+wJEjorrk4sXAyZNA48b5+/Xrl99bM3iwKI6iy44cAVq0EOfh5AQcPCiKvTxP69bA6NHi+vvvA6mp5RsnERERlQqTKyozhUKR13v13anvkJnzAnOmTEzEh8br18XQsJo1gbg4Uc7dzQ3o1UvMS1m1SlRQi4vjoqq67uBBkVTNmiXmGnXrJqrkffihGBL4tK+/FgUfUlPFUDpdnXe0dq04j/v3RQJ56pRItEpq7lzxJcTNm/o3TJKIiEjHMbmiF9Kvfj84mTshOjkamy5tevEDGhkBw4cD166JoU9eXsDDh8D27WJeyvDhonKcoyNgYyPKVg8aBHz1FfD778CFC8Djxy8eB5WfR49EO7ZrJ9q5WjUxx+rvvwFX1+IfZ2Ag1klzdwciIkRvli4VuMjJAT7+GBgyRBRveeMN8UVBjRqlO46FBbBypbi+eLEYPklERERagckVvRBjA2OMbTEWALDg2AJImupNMjQUH0KvXAH27QO+/x4YNw7o1El8uFYoxNycU6fEOkiffgq89ZboCalSRewTEACMHSseGxwsKhWq1ZqJj0pPkkSxhtq1RQ8kIOZYXb0qKuQpFM8/hq0tsHWrKHARFCTaXRckJ4uFtOfNE7c//VQklFWqlO14XbqI6olqtagyyEqbREREWsFA7gBI941oNgJfHf4KF+MuYu+Nvejo0VFzBzcwANq3F5cnpaeLIYTXrolLWFj+9UePRCJ165ZIqp5kaip6w3x8xDGHDBHbqHxFRophn7t2idt16ojhn23alP5Yvr5iTah+/cRQwSZNRHKmrW7dAnr0AC5eFEUpVq8G+vd/8eMuXiwSzIsXxYLdn3324sckIiKiF8KeK3phNqY2GNp4KIASLCqsKSYmQP36YmjVJ5+IxYiPHwfi48V8rCNHRIW5jz4S87Xq1BG9YY8fi6GDv/8uPuy7u4sPpklJFRN3ZZOdDXz7rVgMeNcuMexz9mzg3LmyJVa53n5bVJsERIJ88aJGwtW4Y8fEfKqLF8VQ1oMHNZNYAWKB7iX/LYPw5ZeiB5CIiIhkxeSKNGJ8q/FQKpQIighCYHigfIEoFIC9vaiqNnSoSJy2bhXDC9PSgPBwYOdOURTA3V0kYlOnirk+n30migyQZoSEiMRi8mTxu2/bViS2n30menBe1Ny5wKuvimO/9pqYm6dNfvlF9I7GxYnettOnxRxBTerXD+jaVQwLfO89DnslIiKSGZMr0ohaVWvhvcbvAQD6/NYHx24fkzmiIhgYiIWKu3YVCVVYGLBunejVSkwU3/67uQHjxwN37sgdrRAdDfz6q+hp27dPJCfR0aKEubZKSQEmThSJ1blzQNWqohdx/34xHFNTDAzEHK6aNUUpf20pcKFWi4WyBw0SSc9rr4meVBcXzT+XQgH88INYN+7YMWD5cs0/BxEREZUY51yRxiztuhRRSVHYfX03um3ohsPvHkZ9h/pyh1U8Q0Ng4EBRGGDbNrFA7ZkzYqjV8uXiw/HHH4s5WhUpKkoslPvHH+IDc3EsLESBBzu7wpeittvainMuTzt3iuGWUVHidr9+wKJFYkhcebC1Bf76C/DzA/bsAaZPF/Ow5JKSIl5TW7eK2598AnzxRfELA2uCi4vooR0zRiR1PXs+u+oiERERlRsmV6QxRioj/PHmH+j4S0ccv3McAb8E4OjQo6hZtabcoT2bUgn07i16GPbuFUnWgQOit+V//xPFEqZNE0O7yktERH5C9XRp7RYtxByzBw/EJT5e9NAkJ4tLZGTJn8fSMj/ZMjERx8nJEb0tudefvl2a+3J71NzdgRUrgM6dNfUbKp6vr2int98WSUaTJqJyZEW7eVO8js6fF3PLfv4ZeOedinnukSOBjRtFD9nIkSLJLUn1RdKcQ4fEGmbvv6/54Z9E2i4wUAwBb9NGfCnp4SF3RESyYXJFGlXFqAp29N+Bl//3Mi7fv4yAXwNw5N0jcDQvp54LTVIogI4dxeXYMTGnZ8cOsbbS5s1ikdtPPgH8/TXzfNeuiWRqyxYxfO7JOF5+GejTR3xYd3Yu+Di1WhTgyE22chOuJ28/vT0+Pv9xSUliGF15UKmACROAmTPLXma8LPr2Bc6eFaXO331XlHtv2LBinvvxY2D+fPF6SU8HHBxEz5WfX8U8PyC+IPjpJ5Fo7toFrF9fcYldZSdJwMKF4gNlTo4orvPxx8CMGZqZW0ik7TZtEj322dmisM7PP4tRC9OmiWJGRJUMkyvSOBtTGwS9E4Q2/2uD6w+vo/P6zjgw+ACsTKzkDq3k/P3Forbnz4thZr/9JnoDdu4UhRk++UQkYaXpHZAk4PLl/ITq0qX8+1QqUfygTx/Rg/asYXRKJWBtLS6eniV7brVarAuWm2jdvy/mAymV4rlzL0/eLst91taid0wOc+YAoaFieOBrr4khnjY25fd8kiSGk06YkN97+PLLYh6fm1v5PW9xatcGPv9crKE1frxYE87evuLjqEySk0XhnD/+ELcbNBCVIXO/mFm3DmjUSNYQicrVjz+K3nJJEmv5paUBu3eLL3jWrxdfEE6fDjRtKnekRBVHokISExMlAFJiYqLcoUiSJEmZmZnS1q1bpczMTLlDKZWwB2GSw3wHCTMhvfy/l6W0zDS5Qyq7sDBJeu89STI0lCTxb0SSmjaVpC1bJCknR5KkYtpJrZaks2clafp0SfLxyX8sII7VpYskrVolSffvy3RieiY+XpJq1RK/344dJSkrq8jdXvg99e+/khQQkN+Wzs6StHGjaG85ZWZKUsOGIqZ+/eSNRUO09u/flSuSVLt2/nt5+XLR/lu2SJK9vdhuYCBJX3xR7OtQNmq1JGVkaPywWttWVIDG2mnevPy/gaNG5f0vlM6ckaTXXy/4/65zZ0k6dOjFg69k+J7SHqXJDdhzReXGy9YLuwfsRru17XDo1iG8veVtbHlrCwyUOviy8/ISw65mzBDrNv34oyg1/sYbotrg1Kmi1wkQ/0pOncqfQ/XkEDxjYyAgQOzbo4eopEeaY2MjhuS1aiUWkP7kEzFUUFOSk0WBisWLgawsMbdq0iTxPObmmnuesjI0FENyWrYUc7AGDBDDWUmzfv9d9FilpIhhu3/8IV5zgPj2vk0bYNQo4M8/xdID27eL+Vh16sgbd06OeF3Mni2WpXB2Fn/bnr54eIg5mURFkSTRQz5njrg9bRrw1Vf5IzmaNhX//y5fFr24GzeK3qzdu0Xv/vTppR/5UZmo1cD160BICJRnzqDRhQtQ7t4NmJmJzxAmJuLnk9eL+1ncfUZG/P2XpwpI9nQOe64068DNA5LxF8YSZkIasnWIpJb7231NiIuTpE8/lSQrq7xv5tRubtLNgABJ7epa8Bs7U1PxLd6GDZKkJa8pvbd5c/7vf+PGQneX+j2lVkvSL79IkpNT/nG7dZOk8HANB64hkyeLGGvU0PnXnFb9/cvKkqRJk/JfA+3bS9K9e0Xvq1ZL0q+/SpK1tdjX2FiSFiyQpOzsio1ZkkSPwsaN+T1tz7soFJLk6ipJHTpI0siRIu5t20RvXXp6sU+jVW2lD7KyRO/Q6tX5vUIa8ELtlJMjSaNH579Wvv76+Y+5fl2Shg8vOPKjWTNJ+usvjZ6XTsrOlqTLl8X/l/HjJenllyXJwqJk79MXuVSpInobw8Lk/g3ojNLkBgpJkiS5Ezxtk5SUBCsrKyQmJsJSrvkjT8jKykJgYCC6du0Kw/IupV1Otv27Da//9jrUkhqT/SZjfsB8uUPSjKQkURVv4UKxWGyuKlWA7t1FD1WXLhVb3IGEqVNF9UBTU+D48QLVHkv1njp3Dhg7Fjh6VNz28BDl+rW5RygtTRT0iIgQpfGXLZM7ojLTmr9/sbGiIuXBg+L2xx+LtfEMntMTf/cuMHy4KDQCiF6tNWsqppqaWi2WKpgxQ/QiAKK3fMoUUfDk7l3Rg/X0JSmp+GMqlaLUfxE9XlnOzgjcu1f+ttIHjx+LQj1//y1ud+ggqqJqYL28Mr+nsrJEj+2vv4pejxUrgBEjSv74O3eABQvEyI/Hj8W2+vVFz9dbbz3/vaTrcgt+hISIAkwhIWKecFpa4X1NTQFfX+Q0boxrSUnwcXeHKitLVORNT3/2z+Luy8ws/DwKhVi+Y9Ik8beJvVnFKlVuUO6png5iz1X5WH12tYSZkDAT0jdHvpE7HM1KS5Oyly6VIrp2lbL++EOS0nR4fpm+yM6WpE6dxLd07u6S9OBB3l0lek89eCC+2VMqxTHMzCTpq68k6fHjCgheA/75J/9bSh2e66AVf/+OHMnvtbSwEPOqSkOtlqSffpIkc/P819KyZeX3rb1aLXqaGjXKfw1YWUnS7NnP78lUq0Vv3JEjkvS//0nSJ59I0ltvSVLjxvnxF3NRGxtLV/r1kzKf0btFJfDokSS99JL4vZqYiNdLbhv+8ssLz+0s03vq8WNJ6tkzfy7hhg1lD+DePUmaNq1gD42Hh3iPlMNcQFlkZEjSuXNiTvXo0ZLUsqVoy+J6kdq0kaRx4yRp7VpJungxb56mRv/+5eSIdkxIkKR9+ySpe/eCcTRrJnq4tW2OqJYoTW7A5KoITK7Kz/yj8/MSrFUhq+QOR6P0qZ30xpMFLl59tWT/sLKzJWnFCkmyscn/p9O3ryRFRVVw8BowbJiI39tbd5LCp8j6vlKrJem778SHSUCS6tYVxUzK6uZNSWrXLv919eqrknTrlsbCldRqSQoMFB+Scp/DwkKSPvtMkh4+1MzxY2JEsv7zz5I0daokvfGGKKKSmwAAUk6XLpp5vsooJkaSfH3zk6lDh8TQrZYt89v0jTdeqAhSqd9TSUmS9Mor+cNb//67zM9dwKNHouCLrW3+udWoIUlLlkhSaqpmnqM8ZWSI/wunTknS9u2iqM2IEeL9Z2RUdCJlYSFJbdtK0oQJYtjw1avPHCpc7n//rl6VpPffL5j4ubpK0rff6vyQck1jcvWCmFyVr4+DP5YwE5JyllL688qfcoejMfrWTnrjwgXxzSAg5iJJz2irI0fEN/S5/2Tq15ek/fsrPmZNefhQkqpVE+fyySdyR1Mmsr2vUlIkqX//ggl2cvKLHzcnR3x4NDUVx7W0FD1EL9IboVZL0p49ktSqVcFvw6dOLdBjW67Uailr1SopO/dDZc2aolIqldz16/lfBlWrJknnz+ffl5UlSV9+mZ/oOzpK0o4dZXqaUr2n4uPzEztz8/L5e5icLD7M5/6tAiTJwUHM56roz2E5OWJO9YUL4j21bp2Y9zZxovh78Mor4kuWJ798K+5ibS32nzJF9AiFhZW6t7rC/v7FxUnSrFn5lU5zE8GJEzX7BZAO45yrF8Q5V+VLkiQM/3s4fj73M4xURtg9YDfa12wvd1gvTN/aSa/8/rsY0w8AGzYgq0+fgm0VEwN89JGYSwCI9bpmzxYV33R9HsBff4kKdgYGYu2vJ+ae6QJZ3lfh4eJ3dumSWL9twQLgww81Ox8hLAwYPBg4cULc7tFDzEWpVq10xzlwQKxvdviwuG1qCowZI+ZVOThoLt4SyMrKwtHvv0fbpUuhuHlTVCX74QdxnvRsoaFA587AvXtiPt6ePUCtWoX3O3tWLNh75Yq4PXy4mPNbimqlJX5PxcaK6rYXL4pKrLt3A82bl+68SiM9Xcwr++Yb4NYtsc3aWqzZZ2hYcG3Fkl4MDIrenp0tftexseLvf2ysuNy7J6pqlpShoXjP5l7q1RPVEps0AWrWfOG/GRX+9y89XfwfXLhQzA8DxO/rzTfFvKxmzco/hiclJIi/x+X5uishzrl6Qey5Kn9ZOVlS7029JcyEZD7HXDpz94zcIb0wfWwnvTJ1al71xsxTp0RbpaRI0vz5+XNJFAqxnllcnNzRatYbb4jza9pUt8bTx8RI2d99J52eNEnKvH27Yp5z61bRm5Tbe1Ce89WysyXpm2/yhxDZ2EjSpk0le+zhw6JaYe63zMbGkvThh2JYmUzy/gbGxkpS1675sY0c+cwqg5XewYP5rzlf3+e34ePHokdBoRCPqVVLvB5KqET/q27eFPOgADHf8NKlEh//hWVmStKaNYXXhqzIi729JDVoINZLHDhQ9D59+60krV8v5rNevix69cq5+rFsnytyciRp58784aC5l5deEn8jNT1f9PFjMUdt3TpJ+ugjsQaoi0v+86akaPb5yoA9Vy+IPVcVIz07HV3Xd8X+yP2wM7PDkXePwMfOR+6wykxf20lv5OSICo67d0Nyd8fpt95C861boQgLE/e3bAksXaoV35BpXGysWGMpIQGYPx+YPFnuiIonScCxY6LC4R9/iApluerWBdq3B155BWjbFrC11dzz5uSINanmzhW327QBfvsNcHLS3HMU59IlYNAgUZkSEL2sy5YBdnaF9z15UvRU7dkjbhsaAu+/LyquOTuXf6zPUOBvoEolqinOnCnatEUL0Z4aqHanV7ZtE1UBMzLEGlDbtwNWViV77IEDolcwKkr0kHz0ETBrlljL6Bme+7/q6lWxDtXdu6L3Ze/eonvRyltODhAYKNZ8ysnR7EWlAhwdC/Y65V4cHMT7SgtoxeeK0FDRk7Vxo+jxA0SF0AkTxOvPzKzkx8rJEVVsL10Sl4sXxc/w8OJ7DF1cxGvQ2/uFT+VFlHvP1Zo1a6QdT4z1nTJlimRlZSX5+flJkZGRZTmkVmHPVcVJTE+UmqxsImEmJNdFrtLtxAr6droc6HM76Y2HD/O/jX1ybL+G15HRSj//nF99TBvX50pNFdXCnqxwB0g5zZtLj2rWlNS539LnXhQKse/EiWLuyYv8vY6LE8Ulco89frz49rwiZWZK0owZkqRS5b8ut23Lv//MGbG2Wm6MBgZiIroWzYco8m9gYKAkVa0qYrazk6S9e+ULUNusXp1fjbRXr7IVnUlIkKQhQ/JfFw0bFpyrVYRn/q8KCRHtlFvA5e7d0sdEGqNVnyvu3JGkjz/OX7svt7d9+vTCva1qtdh/924xOmTwYElq0qT4iomA+Dvx8suSNGaMKCp15IgoeqIlyr2ghbe3t/TPP/9IkiRJx44dk0xNTaWVK1dKPXr0kHr37l2WQ2oVJlcV617KPcl7qbeEmZDqLqsrPUitoAnYGqbv7aQ3Ll2S1BYWUo5SKWWPGyc+nFQGarVYFBYQw8m0ZTHv8HCRID35D9vERJKGDpWkkJD891VMjCiBPmaM+ND39D9mlUpMvJ82TUxEL2m1sZMn84efmJkVueh0hTpzpuD5vfOO+OD95HkOHSpJN27IG2cRiv0beONGfqEYpVKS5s7VntefXObNy2/ToUNffLjun3/mJ0VGRmK4aTFV6Iptp0OH8ocnNmtWccVQqFha+bkiOVlUUa1ZM/81bGQkEqjRo8XQwdwvVIq6mJiIIepDhogFyoOCRBKv5X8Tyj25MjU1lW79923ZRx99JA0cOFCSJEm6dOmSZGdnV5ZDahUmVxUv8lGk5Pyts4SZkFr+1FJKztBAVa4KVhnaSV9kRkZKu1etqnxtFRGRX6Xuxx/liyM7W/Q2de5c8J9urVriW874+Lxdi31fxcSItXaGDy/cGwlIkqGh+Cc/Y4aY0/L0nB+1WpJWrsyf7+TtXbHzSp7l8WMx7+DJ3jqlUsz9CAuTO7piPfNvYFqaJL37bv75vPZa5fli40lqtahamvt7+OgjzX2ojI2VpB498o/dpo14zz+l2B7G3F6Ftm1ZhltLaPXniuxsSfrjD0ny8ys6iVIqJal2bUl6801RifDPP8Xfr2eUntdm5Z5c2dvbS2f/K7HaqFEjae3atZIkSdL169elKlWqlOWQWoXJlTwux12WbL6xkTATUsAvAVJGtm4tJlhZ2kkfVOq2+vbb/H9+Hh6SNGCA+Bby5MnyLzrw4IH4xv7JbzwVCjF5eefOIodmlritbt0Sk+AHDRJr5Tz9j97UVAz9mzNHko4eLfhBv3dv7fwweeSI+ODSv78kXbkidzTP9dy2UqtFUp+b0Hp5iQVTK4usrIJD+ObP1/xzqNViCHBukR5zczHc9okErlA7bd6cX+K9e3eRCJNW0Jn/VceOiV6rjz4SRSnOndPZtRWLU5rcoEw1hjt27Ij33nsPjRs3RlhYGLp16wYAuHz5Mtzd3ctySCLUta+LwP6B6LCuA/ZE7MGgvwZh/evroVKq5A6NSH98+CFw/LgoLhARIS7r14v7jIyAxo1FcY/cS61aL16CPCREFGjYuFGU+gWAqlWBoUNFuXsPjxc7PgC4uorJ1YMHi4+uERHAvn35l/v3xaTovXvzH6NUigIWU6Zotsy6prRuLYp76AuFQpQOb9QIeOMNMYm9ZUtg1SqgX7+KiSE2Fti1C3j4EOjZU0zMrwiPH4vCFX//LYop/Pxz+ZSoVyjE+6p9e2DIEODQIfE737YN+OmnwqX+V60SBVEkCXj7bWDdOq0p5kA6xM9PXAgAUKbkatmyZfj0009x+/ZtbNmyBbb/VWwKCQlBv4r6A0l6qWWNlviz75/ovqE7Nl/eDFtTW3zf9XsotPGDD5EuUqnEul+PHgGnTonqc7mX+Pj867ns7ESlt5YtgVatxHVr6+c/T0aGeJ5ly/LXcgLEB+sPPhAfpktTZao0FArA01Nccj84XrmSn2gdPCgqsv38s6g8SBWreXOxXlP//kBwsPh54oSoZGlkpNnnyskR67vt3Ckqz4WE5N83ebJYt6d/f5H4VK+u2efOlZAgErnDh8XaX7/9JtY1K081a4rX+qJFwPTpwI4dQP36Yi21/55buWgR8PHHYv8RI8R7VcUvM4leWAX0pOkcDguU3+ZLmyXFTIWEmZA+3/e53OGUSGVsJ13FtiqCWi1J16+LdVzGjRPFIXKHbz198fERw++WLRMFGJ78Pd66JUmffCLWiXly/lP//mI4Xinnl5RLW2n5xGldVeq2ys4WlcZyXyetW2umOl18vChMMnBgfpGHJy/NmklSQEB+Zcbc4ant24shdA8fvngMuaKjRQU/QJKsrMp33bTiXLwo1s/KrcA5YIB0LXftO03P+yKN4v8q7VHuwwJ3794Nc3NztGnTBoDoyfrpp59Qt25dLFu2DFWrVtVg+keV0Vv13kJ8WjxGB47G7EOzYWxgjGltprEHi6i8KBRieJ6Hh/gmHxC9T6GhBXu3IiKAa9fEZd06sZ+JCdCkiegNCgoC1Gqx3dkZGDlSDEtydJTltIrEvyPaIXctrBYtgIEDgaNHxevot9/Emk8lJUlivZzAQNFDdexY/msQACwtgU6dgG7dgM6d81+L9++L3tUNG8Rz798vLqNHA127it7VHj3K3sMaEQEEBAA3bojheLt3A76+ZTvWi6hfX/RSz5wJfPMNlOvXI2/FoLlzgalTKz4mIj2mLMuDpkyZgqSkJADAxYsXMWnSJHTt2hU3btzAxIkTS3Ws5cuXo2bNmjAxMUHTpk1x+PDhYveNiYlB//794ePjA6VSifHjxz/z2Js2bYJCocBrr71WqphIO4xqPgpftP8CADB933SM2jkK2epsmaMiqkSMjcVwwHHjxLys69fFB9KdO8VCtp06iblT6eniA+2uXeJDbfv2wJYtQGQk8Omn2pVYkfbp2VMM3WvQALh3TwzVXLhQJE3FSUkRC+6OGCHm2/n6ioWUjxwRr8F69cSiugcOAA8eiIRt8OCCr0V7e5FIHTkiXqtffw00bCgWrt62TcxBcnQUid+uXQUXtH6e0FAxZ+7GDfGFxdGj8iRWuYyMgDlzgMOHIXl4QFIqkfPdd0ysiMpBmXqubt68ibp16wIAtmzZgu7du2POnDk4e/YsunbtWuLjbN68GePHj8fy5cvRunVrrFy5El26dMGVK1fg6upaaP+MjAzY29tj+vTpWLRo0TOPfevWLUyePBkvvfRS6U6OtMqnL38KS2NLjN89HitDVuJ20m1s7rMZ5kbmcodGVDnZ2Ylv9XP/1kuSKExw8iRw5w7Qqxfw3/8HohLz8hKFVkaMEIn8pEliHtbPPwMWFmKf8HDROxUYKJKmzMz8x5uaAh065L823dxK9/xubmL+0ccfA5cuieIrGzaIpOvXX8XFzg54803Rs+vvLwqiFOXQIdHjlZQkEqrduwsXkpCLvz+yL1zAP7/9hg4DBoAzrIg0r0w9V0ZGRkhLSwMA7N27FwEBAQAAGxubvB6tkli4cCGGDRuG9957D3Xq1MHixYvh4uKCFStWFLm/u7s7lixZgkGDBsHKyqrY4+bk5GDAgAGYNWsWatWqVYozI200ruU4bHlrC0wMTBAYHoi2a9oiNiVW7rCICBBD7Ly9xbf706YxsaKyq1IF+OUX4PvvAQMDMWSvZUtg/HjxGvP2Ftf37BGJVc2aojjKrl2iGMvff4vqk6VNrJ5Wvz7w1Vei1+n4cWDsWMDBQfSArVgBvPSSeO6pU4Hz5wv2sG3bJoYCJiWJoY0HD2pPYpXL0BAZnL5BVG7K1HPVpk0bTJw4Ea1bt8apU6ewefNmAEBYWBhq1KhRomNkZmYiJCQEU5/qkg4ICMCxFyw9O3v2bNjb22PYsGHPHGaYKyMjAxkZGXm3cxPErKwsZJVmGEA5yY1BG2KRS3fP7ggeEIzev/XG2ZizaLWqFba9tQ117bXngxzbSXewrXQH20p3aKyt3n8figYNoOrXD4qrV4GrVwEAkoEBpJdegtSlC9SdOwM+PgXnz5XHa6RpU3H55hso9u+HctMmKLZuhSIqCvjmG+CbbyDVqQP1228D5uZQTpkChVoNdY8eyPn1V9GjpmWvXb6ndAfbSnuUpg0UkvSsQc1Fi4qKwujRo3H79m2MGzcOw4YNAwBMmDABOTk5+O677557jOjoaDg7O+Po0aPw9/fP2z5nzhysXbsW165de+bj27Vrh0aNGmHx4sUFth89ehR9+/ZFaGgo7OzsMGTIECQkJGDr1q3FHmvmzJmYNWtWoe0bNmyAWXmVCqYyicmIwRc3vkB0RjSqqKpgWs1pqG9eX+6wiIhIw4wTElBvzRqoDQxwr2lT3Pf1RbYW/E9WZmTAMSQENQ4dgmNICFRPfei61aEDzo8eDYllzYn0RlpaGvr374/ExERYWlo+c98y9Vy5urpix44dhbY/bx5UUZ6u/iZJUpkrwiUnJ+Odd97BTz/9BDs7uxI/btq0aQUKcSQlJcHFxQUBAQHP/QVWhKysLAQHB6Njx44w5OJ+6JXWC2/88QaO3zmOWTdmYVWPVehXT/711dhOuoNtpTvYVrqjXNrqv8qV5bQCVdn17g0AUCcmQtq2TfRoHToE9fjxqP7FF6iuxRUp+Z7SHWwr7VGaaU9lSq4AMa9p69atuHr1KhQKBerUqYNevXpBVcJvauzs7KBSqRAbW3DuTFxcHBzLWFkqIiICkZGR6PHE4nzq/8qxGhgY4Nq1a/Dw8Cj0OGNjYxgbGxfabmhoqFUvZm2LRy5OVk74Z9A/GLR1EP648gcGbxuMu8l3MbXNVK0o1c520h1sK93BttIdlaqt7OyAYcPERZKgUih0pkhEpWonHce2kl9pfv9lSq6uX7+Orl274u7du/Dx8YEkSQgLC4OLiwt27txZZALzNCMjIzRt2hTBwcHo/d83QAAQHByMXr16lSUs1K5dGxcvXiyw7dNPP0VycjKWLFkCFxeXMh2XtI+poSk299mMj4M/xoLjC/DJvk9wM+EmlndbDgNlmb8zICIiKhst+HKPiORXpk+h48aNg4eHB06cOAEbGxsAQHx8PN555x2MGzcOO3fuLNFxJk6ciIEDB6JZs2bw8/PDjz/+iKioKIwcORKAGK539+5drMtdqBJAaGgoACAlJQX3799HaGgojIyMULduXZiYmKB+/YLzb6ytrQGg0HbSfUqFEvMD5sPN2g3jdo3DT2d/wp2kO9jcZzMsjC3kDo+IiIiIKpkyJVcHDx4skFgBgK2tLb7++mu0bt26xMfp27cv4uPjMXv2bMTExKB+/foIDAyE239lVGNiYhAVFVXgMY0bN867HhISgg0bNsDNzQ2RkZFlORXSAx+0+AAuli7ot6Ufdl3fhbZr2mJH/x2obqF1o/SJiIiISI+VKbkyNjZGcnJyoe0pKSkwMjIq1bFGjx6N0aNHF3nfmjVrCm0rbXHDoo5B+qdX7V44MOQAum/ojnOx59BqVSvsGrAL9RzqyR0aEREREVUSZVpEuHv37nj//fdx8uRJSJIESZJw4sQJjBw5Ej179tR0jEQl0sK5BU68dwLett64nXQbrVe3xv6b++UOi4iIiIgqiTIlV9999x08PDzg5+cHExMTmJiYwN/fH56enoXWnSKqSLWq1sKxocfQxrUNEjMS0enXTvj1wq9yh0VERERElUCZhgVaW1tj27ZtuH79Oq5evQpJklC3bl14enpqOj6iUrM1s0XwwGAM3joYv13+DQP/GohbCbfwyUufaEWpdiIiIiLSTyVOrp5cZLcoBw4cyLu+cOHCMgdEpAkmBibY+MZGuFm5Yf6x+fh0/6eITIjE8m7LYajiWhFEREREpHklTq7OnTtXov3YM0DaQqlQYl7HeXC3dsfYXWOx6twq3E66jd/f/J2l2omIiIhI40qcXO3fz8IApJtGNx8NF0sXvL3lbQRFBOHlNS9jZ/+dLNVORERERBpVpoIWRLqmh08PHBxyEA5VHBAaG4pWq1rhUtwlucMiIiIiIj3C5IoqjWbVm+HEsBOobVcbt5Nuo9WqVlgTuqbUa6cRERERERWFyRVVKjWr1sTRoUfRoWYHpGal4t1t7+Kdv95BUkaS3KERERERkY5jckWVjo2pDYLeCcJXr3wFlUKFDRc3oMnKJjh997TcoRERERGRDmNyRZWSSqnCJy99gkPvHoKblRsiHkXAf7U/FhxbALWkljs8IiIiItJBTK6oUvN38UfoyFD0qdsH2epsTAmegq7ru+Jeyj25QyMiIiIiHcPkiio9axNr/NbnN6zsvhImBiYIigiC7w++CI4Iljs0IiIiItIhTK6IIBa/fr/p+zgz/AzqO9THvdR7CPg1AB8Hf4ysnCy5wyMiIiIiHcDkiugJ9Rzq4dR7pzCy6UgAwLxj89Dmf21w49ENmSMjIiIiIm3H5IroKaaGpljRfQX+ePMPWJtY49TdU2i8sjE2Xdokd2hEREREpMWYXBEV4426b+D8yPNo7dIaSRlJ6LelH4ZtG4bUzFS5QyMiIiIiLcTkiugZXK1ccWDIAXz28mdQQIHVoavR7KdmOB97Xu7QiIiIiEjLMLkieg4DpQFmt5+NfYP3obpFdfz74F+0XNUS35/6HpIkyR0eEREREWkJJldEJdTOvR3OjzyPHt49kJGTgbG7xqL35t6IT4uXOzQiIiIi0gJMrohKwc7MDtve3oYlnZfASGWEbde2odHKRjh065DcoRERERGRzJhcEZWSQqHAuJbjcGLYCXjbeuNO0h20X9sesw/NRo6UI3d4RERERCQTJldEZdTYqTFC3g/Bu43ehVpS48sjX+Kz65/hZsJNuUMjIiIiIhkwuSJ6AeZG5ljdazU2vL4BFkYWuJJ6BU1XNcWPIT+y2AURERFRJcPkikgD+jXoh9PDTqNelXpIyUzBiB0j0Hl9Z9xOvC13aERERERUQZhcEWlIraq18IXnF1jw6gKYGJhgT8Qe1F9RH2tC17AXi4iIiKgSYHJFpEFKhRLjWoxD6IhQtKrRCkkZSXh327vouaknYpJj5A6PiIiIiMoRkyuicuBj54Mj7x7B1x2+hpHKCDvCdqDe8nrYeHEje7GIiIiI9BSTK6JyolKq8HGbjxHyfgiaODXBo/RH6P9nf7z5+5uIS42TOzwiIiIi0jAmV0TlrL5DfZwYdgKz2s2CgdIAW65uQf3l9bHlyha5QyMiIiIiDWJyRVQBDFWG+Lzt5zj13ik0cGiA+2n30ef3Pui/pT8ePn4od3hEREREpAFMrogqUGOnxjg9/DQ+afMJlAolNl7aiHrL62FH2A65QyMiIiKiF8TkiqiCGRsY46sOX+H4sOOobVcbsSmx6LGxB97d9i4S0xPlDo+IiIiIyojJFZFMWji3wNn3z2KS3yQooMCa0DWov6I+9kTskTs0IiIiIioDJldEMjI1NMWCgAU49O4heFT1wJ2kO+j0ayeM3DESyRnJcodHRERERKXA5IpIC7RxbYPzI8/jg+YfAABWhqxEwx8a4kDkAXkDIyIiIqISY3JFpCWqGFXB0q5LsW/QPrhZuSEyIRLt17bHuF3jkJKZInd4RERERPQcTK6ItEz7mu1xcdRFvN/kfQDA0lNLUXNJTXxz5BsmWURERERajMkVkRayMLbAyh4rsXvAbnhU9cCDtAeY+s9UuC92x9zDc5GUkSR3iERERET0FCZXRFqsk2cn/PvBv1j72lp42Xgh/nE8Ptn3CdwXu+PLQ1+ydDsRERGRFmFyRaTlDJQGGOQ7CFfGXMEvvX+Bj60PHqU/wmf7P4P7EnfMOjALCekJcodJREREVOkxuSLSEQZKA7zT8B1cHn0ZG17fgDp2dZCQnoCZB2fCfbE7ZuyfgUePH8kdJhEREVGlxeSKSMeolCr0a9APF0ddxKY3NqGefT0kZiRi9qHZcFvshk/3fYr4tHi5wyQiIiKqdJhcEekolVKFvvX74sKoC/j9zd/RwKEBkjOT8dXhr+C+xB2f/PMJHqQ9kDtMIiIiokqDyRWRjlMqlOhTtw9CR4Ziy1tb4Ovoi5TMFMw9Mhfui93xcfDHuJ96X+4wiYiIiPQekysiPaFUKPF6nddxbsQ5bO27FU2cmiA1KxXzjs2D+xJ3TN4zGfdS7skdJhEREZHeYnJFpGcUCgV61e6FM8PP4O9+f6NZ9WZIy0rDt8e/Rc0lNTExaCJiU2LlDpOIiIhI7zC5ItJTCoUC3b2749R7p7Cz/060cG6Bx9mPsejEItRcUhOTgiZxnSwiIiIiDWJyRaTnFAoFunp1xYlhJ7B7wG741fBDenY6Fp5YCO/vvbE2dC3UklruMImIiIh0HpMrokpCoVCgk2cnHB16FIH9A+Fj64O41DgM2TYErVe3Rkh0iNwhEhEREek0JldElYxCoUAXry64MOoC5r06D+ZG5jhx5wSa/9QcI3eM5BpZRERERGXE5IqokjJSGWFK6yn4d8y/6N+gPyRIWBmyEt7fe+OHMz8gR50jd4hEREREOoXJFVEl52zpjPWvr8fBIQfR0LEhHj5+iFE7R6H5T81x7PYxucMjIiIi0hlMrogIAPCy28sIeT8ES7sshbWJNc7FnkPr1a0xeOtglm4nIiIiKgEmV0SUx0BpgA9afIBrH1zDsMbDAADrzq+D91JvLDq+CFk5WTJHSERERKS9mFwRUSEOVRywqucqnHzvJJpXb47kzGRM3DMRjVY2wj83/pE7PCIiIiKtxOSKiIrVwrkFTrx3Aqt6rIKdmR2u3L+CV395FW/9/haiEqPkDo+IiIhIqzC5IqJnUiqUGNZkGMI+CMMHzT+AUqHE71d+R51ldfDVoa+Qnp0ud4hEREREWoHJFRGVSFXTqljadSnOvn8WL7m+hLSsNHy6/1PUX14fO8N2yh0eERERkeyYXBFRqfhW88XBIQex/vX1cDJ3QsSjCHTf2B09NvZAxMMIucMjIiIikg2TKyIqNYVCgf4N+uPaB9cwxX8KDJQG2BG2A7WX1UbPjT3x2+Xf8DjrsdxhEhEREVUoJldEVGYWxhaY13EeLo66iACPAGSrs/F32N/o+0dfOC5wxJCtQxAcEYwcdY7coRIRERGVOyZXRPTCatvVRtA7Qbg06hKmtZkGNys3JGcmY+35tQj4NQA1FtXAhN0TcCb6DCRJkjtcIiIionLB5IqINKaeQz3M6TAHNz68gcPvHsbIpiNhY2qD2JRYLD65GM1/ao7ay2pj9sHZnJ9FREREeofJFRFpnFKhRBvXNljRfQViJsVg+9vb0bdeX5gYmCAsPgwzDsyA51JPtFrVCktPLkVcapzcIRMRERG9MCZXRFSujFRG6OHTA5v6bELc5DisfW0tAjwCoFQocfLuSYzbPQ7Vv62OLuu74NcLvyIlM0XukImIiIjKxEDuAIio8rAwtsAg30EY5DsIsSmx2HRpE9ZfXI8z0Wew+/pu7L6+G2aGZujl0wsDGgxAgEcADFWGcodNREREVCLsuSIiWVQzr4bxrcbj9PDTuPbBNXz+8ufwqOqBtKw0bLy0Ed03dkf1hdUxZucYXIq7JHe4RERERM/F5IqIZOdt641Z7WchfGw4Tgw7gbEtxsKhigMepD3A8jPL0WBFA7y++XWcjTkrd6hERERExWJyRURaQ6FQoGWNlviuy3e4O/Eudg3YhTfqvAEFFPjr37/Q9Mem6LahG47fPi53qERERESFMLkiIq1koDRAZ8/O+OOtP3Bp9CUMaDAASoUSgeGB8F/tj1fXvYoDkQe4bhYRERFpDSZXRKT16trXxa+v/4prH1zD0EZDYaA0wD83/0H7te3x8pqXEXQ9iEkWERERyY7JFRHpDE8bT/zc62dcH3sdo5uNhrHKGEeijqDz+s5ouaoltl/bziSLiIiIZMPkioh0jpu1G5Z1W4YbH97AhFYTYGpgitPRp9FrUy80WtkIv13+DTnqHLnDJCIiokqGyRUR6azqFtWxsNNC3Bp/C9PaTIOFkQUu3LuAvn/0Rf0V9fHL+V+Qrc6WO0wiIiKqJJhcEZHOs69ijzkd5iByfCRmtp0JaxNr/PvgXwzaOgg+3/tg1dlVyMzJlDtMIiIi0nNMrohIb9iY2mBGuxm4Nf4W5naYCzszO9x4dAPD/x4Oz+888f2p7/E467HcYRIREZGeYnJFRHrH0tgSU9tMReSHkVjUaRGczJ1wO+k2xu4ai1rf1cKik4uQnpMud5hERESkZ5hcEZHeqmJUBeNbjceND29gedflcLVyRWxKLD7+52O8d+U9TNs3DVGJUXKHSURERHpC9uRq+fLlqFmzJkxMTNC0aVMcPny42H1jYmLQv39/+Pj4QKlUYvz48YX2+fPPP9GsWTNYW1ujSpUqaNSoEX755ZdyPAMi0nYmBiYY1XwUwseG4+eeP8OzqidSclLw7YlvUXNJTfT5rQ8O3zrMMu5ERET0QmRNrjZv3ozx48dj+vTpOHfuHF566SV06dIFUVFFf5OckZEBe3t7TJ8+Hb6+vkXuY2Njg+nTp+P48eO4cOEC3n33Xbz77rsICgoqz1MhIh1gpDLC0MZDcXHERXxS8xO84v4K1JIaW65uwctrXkbTH5tiTegapGdzyCARERGVnqzJ1cKFCzFs2DC89957qFOnDhYvXgwXFxesWLGiyP3d3d2xZMkSDBo0CFZWVkXu065dO/Tu3Rt16tSBh4cHPvzwQzRs2BBHjhwpz1MhIh2iUqrQwqoFdvffjYujLmJ4k+EwMTDBudhzeHfbu3Bd5IrP9n2G6ORouUMlIiIiHWIg1xNnZmYiJCQEU6dOLbA9ICAAx44d08hzSJKEffv24dq1a/jmm2+K3S8jIwMZGRl5t5OSkgAAWVlZyMrK0kgsLyI3Bm2IhYrHdtIdT7aVT1UfLOu8DLNfno3V51fjh5AfcDvpNr48/CW+Pvo1+tTpgw+afYAWzi1kjrpy4vtKd7CtdAPbSXewrbRHadpAIck0ySA6OhrOzs44evQo/P3987bPmTMHa9euxbVr1575+Hbt2qFRo0ZYvHhxofsSExPh7OyMjIwMqFQqLF++HEOHDi32WDNnzsSsWbMKbd+wYQPMzMxKflJEpPNypBycTDyJv+//jaupV/O2e5t5o7t9d/hZ+cFQaShjhERERFSR0tLS0L9/fyQmJsLS0vKZ+8rWc5VLoVAUuC1JUqFtpWVhYYHQ0FCkpKTgn3/+wcSJE1GrVi20a9euyP2nTZuGiRMn5t1OSkqCi4sLAgICnvsLrAhZWVkIDg5Gx44dYWjID3Xaiu2kO57XVj3QA1/iS5yLPYfvT3+PzVc2IywtDAtvLYSTuRNGNBmB9xq/B4cqDjJEX7nwfaU72Fa6ge2kO9hW2iN3VFtJyJZc2dnZQaVSITY2tsD2uLg4ODo6vtCxlUolPD09AQCNGjXC1atXMXfu3GKTK2NjYxgbGxfabmhoqFUvZm2Lh4rGdtIdz2urFi4tsM5lHeYHzMfKkJVYcWYFYlJiMPPQTMw9Ohf9GvTDhy0/RKNqjSos5sqK7yvdwbbSDWwn3cG2kl9pfv+yFbQwMjJC06ZNERwcXGB7cHBwgWGCmiBJUoE5VUREpeFo7ojP236OW+Nv4dfev6J59ebIyMnAmtA1aLyyMV7+38vYcmULstXZcodKREREMpJ1WODEiRMxcOBANGvWDH5+fvjxxx8RFRWFkSNHAhDD9e7evYt169blPSY0NBQAkJKSgvv37yM0NBRGRkaoW7cuAGDu3Llo1qwZPDw8kJmZicDAQKxbt67YCoRERCVlpDLCgIYDMKDhAJy4cwJLTi7BH1f+wOGowzgcdRiuVq4Y22Is3mvyHqxNrOUOl4iIiCqYrMlV3759ER8fj9mzZyMmJgb169dHYGAg3NzcAIhFg59e86px48Z510NCQrBhwwa4ubkhMjISAJCamorRo0fjzp07MDU1Re3atfHrr7+ib9++FXZeRKT/WtVohVY1WmFBxwVYcWYFVoasRFRiFKYET8HMAzMxtPFQfNjyQ3jYeMgdKhEREVUQ2QtajB49GqNHjy7yvjVr1hTa9rzihl9++SW+/PJLTYRGRPRczpbO+PKVL/Hpy59i/YX1WHRiES7fv4ylp5bi+1Pfo6dPT0z0m4iXXF964WI9REREpN1kXUSYiEhfmBiYYFiTYbg46iL2vLMHXTy7QIKEbde2oe2atmj2UzP8euFXZOZkyh0qERERlRMmV0REGqRQKNDRoyMCBwTiyugrGNF0BEwMTHA25iwG/jUQNZfUxJzDcxCfFi93qERERKRhTK6IiMpJHfs6+KH7D7g94Ta+bP8lnMydEJ0cjen7psNlkQtG7hiJfx/8K3eYREREpCFMroiIypmdmR2mvzwdkeMjse61dWhcrTEeZz/GypCVqLOsDrpt6Ia9N/Y+d04pERERaTcmV0REFcRIZYSBvgMR8n4IDgw+gF4+vaCAAoHhgej4S0f4/uCL1edWIz07Xe5QiYiIqAyYXBERVTCFQoG27m2x9e2tCBsbhg+af4AqhlVwMe4ihm0fBrfFbph5YCbupdyTO1QiIiIqBSZXREQy8rTxxNKuS3F7wm3Me3UeXCxdEJcah1kHZ8F1sSuGbhuKU3dPccggERGRDmByRUSkBaqaVsWU1lMQMS4Cm97YhJbOLZGZk4n/hf4PLVe1hM/3Pph5YCbC4sPkDpWIiIiKweSKiEiLGKoM0bd+X5x47wSODT2G/g36w9TAFOEPwzHr4Cz4fO+D5j81x6LjixCTHCN3uERERPQEA7kDICKiovm5+MHPxQ8pmSnY9u82rL+4Hnsi9uBM9BmciT6DycGT0d69PQY0GIDX67wOKxMruUMmIiKq1NhzRUSk5cyNzDGg4QAEDghEzKQYfN/le/i7+EMtqfHPzX8wdPtQOC5wRJ/f+uDPq3+y2iAREZFMmFwREekQ+yr2GNNiDI4OPYob427gq1e+Ql37usjIycCWq1vwxm9voNqCahi2bRj23dyHHHWO3CETERFVGkyuiIh0VM2qNfHJS5/g0qhLCB0Riin+U1DDsgYSMxKxOnQ1OqzrANfFrpgUNAkh0SGsOEhERFTOmFwREek4hUIB32q+mNdxHm6Nv4UDgw9geJPhsDaxRnRyNBaeWIhmPzVDnWV1MPvgbFx/eF3ukImIiPQSkysiIj2iVCjR1r0tfuzxI2InxWJr3614q95bMDEwwbX4a5hxYAa8lnqh5aqWWHpyKeJS4+QOmYiISG8wuSIi0lPGBsboVbsXNvfZjHuT72FNrzUI8AiAUqHEqbunMG73OFT/tjq6ru+KDRc3IDUzVe6QiYiIdBpLsRMRVQKWxpYY3GgwBjcajNiUWGy+tBnrL67H6ejT2HV9F3Zd34UqhlXQu05vDGgwAK/WehUGSv6LICIiKg32XBERVTLVzKvhw1Yf4tTwU/h3zL/47OXPUKtqLaRmpeLXC7+iy/oucF7ojPG7x+P03dMshEFERFRCTK6IiCoxHzsfzG4/G9fHXsexoccwpvkY2JraIi41DktOLkGLVS1Qe1ltzD44GxEPI+QOl4iISKsxuSIiIigUCvi5+OH7rt8jZlIMdvTbgbfrvw1TA1OExYdhxoEZ8FzqCb+f/bDs1DLcT70vd8hERERah8kVEREVYKgyRDfvbtj4xkbcm3wPa19bm1cI48SdE/hg1weovrA6um/ojk2XNiEtK03ukImIiLQCZysTEVGxLIwtMMh3EAb5DkJMcgw2X96MXy/8ipCYEOwM34md4TthbmSO1+u8jgENBqC9e3sYqgzlDpuIiEgW7LkiIqIScbJwwvhW43Hm/TO4OuYqPn3pU9S0romUzBSsO78OnX7tBPv59ui3pR82XtyIhPQEuUMmIiKqUEyuiIio1Grb1cYXr3yBiHERODr0KEY3Gw17M3skZiRi06VN6P9nf9jPt0eHdR2w+MRi3Hh0Q+6QiYiIyh2HBRIRUZkpFAr4u/jD38Uf33X5DqfunsL2a9vxd9jfuHz/Mvbd3Id9N/dhQtAE1LOvh54+PdHDuwda1mgJpYLf7xERkX5hckVERBqhUqrg5+IHPxc/zH11LiIeRuDvsL+x/dp2HLp1CJfvX8bl+5cx98hcOFRxQHev7ujp0xOv1noVVYyqyB0+ERHRC2NyRURE5cLDxgPjW43H+Fbj8ejxI+y6vgt/h/2NwPBAxKXGYXXoaqwOXQ0TAxO8WutV9PDuge7e3VHdorrcoRMREZUJkysiIip3VU2ron+D/ujfoD8yczJx+NZhbL+2HdvDtiMyIRI7wnZgR9gOAEDz6s3R06cnevr0RO2qtWWOnIiIqOSYXBERUYUyUhmhQ60O6FCrAxZ3XoxLcZfyEq1Td0/hdPRpnI4+jc/2fwZXS1c0MWkCz3hP1KtWT+7QiYiInonJFRERyUahUKCBYwM0cGyA6S9PR0xyDHaG78T2a9sRfCMYUUlRiEqKwtaVW/Gy28sY3mQ43qjzBkwNTeUOnYiIqBCWaiIiIq3hZOGE95q8h+39tiP+o3hsfn0zmlk2g1KhxKFbhzDwr4Fw+tYJHwR+gPOx5+UOl4iIqAAmV0REpJXMDM3Qu3ZvfFrrU4SPCcfsdrPhZuWGxIxELDu9DI1WNkLzn5rjx5AfkZSRJHe4RERETK6IiEj7uVi64LO2n+HGhzcQ9E4Q3qz7JgyVhjgTfQYjdoyA07dOGLZtGI7fPg5JkuQOl4iIKikmV0REpDOUCiUCPALw25u/4c7EO1jQcQFq29VGWlYaVoeuhv9qfzRY0QCLTyzGg7QHcodLRESVDJMrIiLSSQ5VHDDJfxKujL6Cw+8exmDfwTA1MMXl+5cxIWgCnBc64+0/3sY/N/6BWlLLHS4REVUCTK6IiEinKRQKtHFtgzWvrUHMpBgs77ocTZyaIDMnE5svb8arv7wKr6VemHN4DqKTo+UOl4iI9BiTKyIi0htWJlYY1XwUQt4PQcj7IRjVbBQsjS1x49ENTN83Ha6LXNFzY0/8fvl3xCTHyB0uERHpGa5zRUREeqmJUxMs77YcCwIW4PfLv2PVuVU4EnUEf4f9jb/D/gYAuFm5wc/FD341xKVRtUYwVBnKHDkREekqJldERKTXzAzNMLjRYAxuNBj/PvgXP5/9GUERQbgUdwm3Em/hVuItbLq0CQBgYmCCZtWb5SVbfi5+qGZeTeYzICIiXcHkioiIKo3adrUxP2A+5mM+kjKScOruKZy4cwLH7xzHiTsn8PDxQxyJOoIjUUfyHuNu7Q6/Gn5oVaMVe7eIiOiZmFwREVGlZGlsiVdrvYpXa70KAJAkCWHxYTh+5ziO3z6O43eO41LcJUQmRCIyIRIbL20EwN4tIiIqHpMrIiIiiKqDPnY+8LHzwZBGQwAgr3crN9k6cecEHqU/KrJ3q1WNVqhvXx917euijn0deFT1YA8XEVElw+SKiIioGKXt3XqSodIQXrZeqGNXR1zs66CufV342PrA1NBUhrMhIqLyxuSKiIiohJ7Vu3X67mlcfXBVXO5fRWpWKq7cv4Ir968UPAYUcLd2Fz1c/yVduT+tTawr/qSIiEhjmFwRERG9gKd7twBALalxJ+kOrt6/iiv3r+QlXVfuX8HDxw9xM+EmbibcxM7wnQWO5WTuJHq47OrmJV0+dj5wMneCQqGo6FMjIqJSYnJFRESkYUqFEq5WrnC1ckUnz0552yVJwv20+7h6Pz/Zyu3pupt8FzEpMYhJicG+m/sKHK+KYRV42XrB29YbXjZe8LL577qtF2xNbZl4ERFpCSZXREREFUShUMChigMcqjigrXvbAvclpifi3wf/5iVbVx5cwdX7V3Ez4SZSs1IRGhuK0NjQQsesalIVXrZPJFxPJF6WxpYVdGZERAQwuSIiItIKViZWaFmjJVrWaFlge2ZOJm4+uomw+DCEPwxHeHw4wh6GITw+HLeTbuNR+iOcunsKp+6eKnRMhyoORfZ2edl4sagGEVE5YHJFRESkxYxURnlFNJ6WlpWGiIcR+UnXfwlYWHwY7qXeQ1xqHOJS4wqUjQcAUwNTvF7ndQz2HYxXar4ClVJVUadDRKTXmFwRERHpKDNDMzRwbIAGjg0K3ZeUkYTrD6+LhCs+PC/pCosPw6P0R1h/cT3WX1wPZwtnDGw4EIMbDUZtu9oynAURkf5gckVERKSHLI0t0cSpCZo4NSmwXZIknI4+jbWha7Hx0kbcTb6Lr49+ja+Pfo0Wzi0w2Hcw3q7/NmxMbWSKnIhIdynlDoCIiIgqjkKhQAvnFljWbRliJsXgjzf/QA/vHlApVDh19xTGBI6B07dO6PNbH/x97W9k5WTJHTIRkc5gckVERFRJGRsY4426b2B7v+2InhSNRZ0WoVG1RsjMycSWq1vQc1NP1FhUAxN2TyiyUiERERXE5IqIiIjgUMUB41uNx7kR5xA6IhQTWk2AQxUHxKXGYfHJxWi8sjF8f/DFwuMLcS/lntzhEhFpJSZXREREVIBvNV8s7LQQdybcwd/9/kafun1gpDLChXsXMGnPJDgvdEb3Dd3x++XfkZ6dLne4RERagwUtiIiIqEiGKkN09+6O7t7d8fDxQ2y+tBlrz6/FybsnsTN8J3aG74S1iTXervc2+tXrh0x1ptwhExHJiskVERERPZeNqQ1GNR+FUc1H4d8H/2Ld+XX45cIvuJN0Bz+E/IAfQn4AADjfdEatqrVQq2oteFT1yLteq2otOFRxgEKhkPlMiIjKD5MrIiIiKpXadrUxp8McfNH+C+yP3I+159di+7XtSMpIwt3ku7ibfBeHow4XepyZoVmxiZe7tTtMDExkOBsiIs1hckVERERlolKq8GqtV/FqrVeRmZmJzX9vRq2mtRCVHIUbj26IS4L4eTvxNtKy0nAp7hIuxV0q8njOFqLXy8PGA7WsRdLVqkYreNh4VPCZERGVDZMrIiIiemEKhQKWBpZo4dwCrQ1bF7o/IzsDUYlRiHgUkZ94/XeJeBSBlMyUYnu9mjg1wVt138Kb9d5Eraq1KuqUiIhKjckVERERlTtjA2N42XrBy9ar0H2SJCH+cXzBhOthBMIehuH47eM4G3MWZ2POYuo/U9G8enO8Ve8tvFn3TbhZu8lwJkRExWNyRURERLJSKBSwM7ODnZkdWji3KHDfg7QH+OvqX9h8eTP2R+7H6ejTOB19GlOCp6Clc8u8RMvFykWm6ImI8nGdKyIiItJadmZ2GN50OPYO2ouYSTFY0W0F2ru3hwIKnLx7EpP2TILrYle0Xt0aS04swd2ku3KHTESVGJMrIiIi0gkOVRwwstlI7Bu8D9GTovF9l+/xstvLUECBY7ePYXzQeNRYVAMv/e8lfH/qe8Qkx8gdMhFVMkyuiIiISOdUM6+GMS3G4OCQg7gz8Q6+6/wdWruIQhpHoo5g7K6xcF7ojHZr2mH56eW4l3JP5oiJqDJgckVEREQ6rbpFdYxtORZHhh7B7Qm3sajTIvjV8IMECQdvHcSYwDGovrA6Xln7ClaeWclEi4jKDQtaEBERkd6oYVkD41uNx/hW43Er4Rb+uPIHfrvyG07dPYX9kfuxP3I/Ru4cCSdzJ9R3qI8GDg3QwLEBGjg0QF37ujA1NJX7FIhIhzG5IiIiIr3kZu2GSf6TMMl/Em4+uok/rvyBzZc3IyQmBDEpMYhJiUHwjeC8/ZUKJTyqeuQlWw0cGqC+Q3142nhCpVTJeCZEpCuYXBEREZHeq1m1Jqa0noIpracgOSMZl+9fxsV7F3Ex7iIuxV3CxbiLeJD2AOEPwxH+MBx/Xv0z77EmBiaoa1+3QMLVwLEBnMydoFAoZDwrItI2TK6IiIioUrEwtkCrGq3QqkarvG2SJOFe6j1cvJefbF2Mu4jLcZfxOPtx3kLGT7IxtclLtho6NoS/iz/q2teFUsEp7USVFZMrIiIiqvQUCgWqmVdDNfNq6OjRMW97jjoHNxNu5vVy5fZ0hcWH4eHjhzh46yAO3jqYt7+dmR3aurVFO/d2aOfejskWUSXD5IqIiIioGCqlCp42nvC08UTvOr3ztqdnp+Pq/at5ydbZmLM4fuc4HqQ9wJarW7Dl6hYATLaIKhsmV0RERESlZGJggsZOjdHYqXHetsycTJyJPoMDkQdwIPIAjt4+ymSLqJJhckVERESkAUYqI/i7+MPfxR+fvPRJgWTr4K2DOBJ1pFCyZWtqi7bubdHOTSRb9RzqMdki0mFMroiIiIjKQVHJVkh0iOjZunUAR6KOIP5xPP68+mdedUImW0S6jckVERERUQUwUhnBz8UPfi5+mPbSNGTlZOUPIywm2TJSGcHF0gXu1u5ws3KDm7Ub3KzcxG1rN9SwrAEDJT/OEWkLvhuJiIiIZGCoMiyUbIXEhOTN2ToSdQSpWamIeBSBiEcRRR5DqVCihmWNwonXf7ddrVxhYmBSwWdGVHkxuSIiIiLSAoYqw7z1t6a2mYpsdTbuJt3FrcRbuJVwC5EJkeJ6orgelRiFzJxMRCVGISoxCoejDhd53Grm1fKSLRcLF6THp6NuQl142XtV8BkS6T/Zk6vly5dj/vz5iImJQb169bB48WK89NJLRe4bExODSZMmISQkBOHh4Rg3bhwWL15cYJ+ffvoJ69atw6VLlwAATZs2xZw5c9CiRYvyPhUiIiIijTFQGojeKGs3wK3w/WpJjXsp9/KSrVsJ+YlXbkKWmpWK2JRYxKbE4uTdk3mPXbZ8GXxsfdDZszM6e3ZGW7e2MDU0rcCzI9JPsiZXmzdvxvjx47F8+XK0bt0aK1euRJcuXXDlyhW4uroW2j8jIwP29vaYPn06Fi1aVOQxDxw4gH79+sHf3x8mJiaYN28eAgICcPnyZTg7O5f3KRERERFVCKVCCScLJzhZOKFVjVaF7pckCfGP4/OSrlsJt3Dj4Q38c/UfhKWF4Vr8NVyLv4YlJ5fAxMAEbd3a5iVbPrY+UCgUMpwVkW6TNblauHAhhg0bhvfeew8AsHjxYgQFBWHFihWYO3duof3d3d2xZMkSAMDq1auLPOb69esL3P7pp5/wxx9/4J9//sGgQYM0fAZERERE2kmhUMDOzA52ZnZoWr0pACArKwuB2YFo/UprHLpzCLuv78au67twJ+kOgiKCEBQRhAlBE+Bm5ZaXaL1S8xVYGlvKfDZEukG25CozMxMhISGYOnVqge0BAQE4duyYxp4nLS0NWVlZsLGxKXafjIwMZGRk5N1OSkoCIP4AZWVlaSyWssqNQRtioeKxnXQH20p3sK10B9tKN+S2j5nKDD08e6CHZw9IkoSrD65iz4092HNjDw5FHcKtxFtYGbISK0NWwkBpAP8a/gioFYAAjwD4OviyV6sC8D2lPUrTBgpJkqRyjKVY0dHRcHZ2xtGjR+Hv75+3fc6cOVi7di2uXbv2zMe3a9cOjRo1KjTn6mljxoxBUFAQLl26BBOToqvlzJw5E7NmzSq0fcOGDTAzM3v+yRARERHpifScdFxKvYRzSedwLvkcojOiC9xf1aAqGlk0QhPLJvC18IWlAXu1SL+lpaWhf//+SExMhKXls1/vshe0ePqbD0mSNPZtyLx587Bx40YcOHCg2MQKAKZNm4aJEyfm3U5KSoKLiwsCAgKe+wusCFlZWQgODkbHjh1haGgodzhUDLaT7mBb6Q62le5gW+mGkrbT63g973rEowgE3whG0I0g7I/cj0dZj7D/0X7sf7QfCijQvHpzdKzVEa2cW6GhY0NUq1KNPVsawPeU9sgd1VYSsiVXdnZ2UKlUiI2NLbA9Li4Ojo6OL3z8BQsWYM6cOdi7dy8aNmz4zH2NjY1hbGxcaLuhoaFWvZi1LR4qGttJd7CtdAfbSnewrXRDadqptkNt1HaojbGtxiIjOwNHbx/F7uu7sfv6blyMu4hT0adwKvpU3v4OVRzg6+gLX0dfNKrWCL7VfOFj6wNDFV8XZcH3lPxK8/uXLbkyMjJC06ZNERwcjN69e+dtDw4ORq9evV7o2PPnz8eXX36JoKAgNGvW7EVDJSIiIiIAxgbGeKXmK3il5iuY13Ee7iTdwZ6IPdh7Yy/OxZ5DWHwY4lLjEHwjGME3gvMfpzJGPYd6aOQokq1G1RqhoWNDWJtYy3cyROVA1mGBEydOxMCBA9GsWTP4+fnhxx9/RFRUFEaOHAlADNe7e/cu1q1bl/eY0NBQAEBKSgru37+P0NBQGBkZoW7dugDEUMDPPvsMGzZsgLu7e17PmLm5OczNzSv2BImIiIj0WA3LGhjaeCiGNh4KAEjLSsOluEs4H3seobGhOH/vPM7fO4+UzBScjTmLszFnCzze3do9v4fL0Re+1XxR07omhxWSzpI1uerbty/i4+Mxe/ZsxMTEoH79+ggMDISbm1gpLyYmBlFRUQUe07hx47zrISEh2LBhA9zc3BAZGQlALEqcmZmJPn36FHjcjBkzMHPmzHI9HyIiIqLKzMzQDC2cW6CFc4u8bWpJjZuPbuL8vfyEKzQ2FFGJUYhMiERkQiS2XduWt7+lsSUaOjZEI8dGqFW1FqxNrFHVtCqsTazFdRNx3cLYAkqFUo7TJCqW7AUtRo8ejdGjRxd535o1awpte15xw9wki4iIiIjkp1Qo4WHjAQ8bD7xeJ79QxsPHD3Hh3gXRy3UvFOdjz+Py/ctIykjCkagjOBJ15JnHVUABKxOrvGTr6eQr77ZpwdvVzKvBzsyuvE+bKinZkysiIiIiqnxsTG3Qzr0d2rm3y9uWlZOFfx/8m9fDdTf5LhLSE/Iujx4/wqP0R8jMyYQEKW97adWzr4dOHp3QybMTXnJ9CaaGppo7MarUmFwRERERkVYwVBmigWMDNHBsgIEYWOx+6dnpecnWk8lXQnoCHqU/eubt+LR4XL5/GZfvX8bCEwthYmCCtm5t0cmjEwI8AlDXvi7nfFGZMbkiIiIiIp1iYmCCaubVUM28WqkfG58Wj7039iIoIghBEUGITo7Ouw6IIh0BtQLQybMTOtTsAFszW02HT3qMyRURERERVRq2ZrboW78v+tbvC0mScPn+ZeyJ2IOgiCAcunUId5LuYHXoaqwOXS0WSXZuLoYQenRCyxotYaDkx2cqHl8dRERERFQpKRQK1Heoj/oO9THRbyIeZz3GoVuH8pKty/cv49TdUzh19xS+OPQFrIyt0KFWh7yeLXdrd7lPgbQMkysiIiIiIgCmhqbo5CkKXXyLb/MWSQ6KCMLeG3vx8PFD/Hn1T/x59U8AgLetd95crcbVGsPJwonl4Ss5JldEREREREV4cpHkHHUOQmJCEHRdzM86cecEwuLDEBYfhqWnlgIATA1MUatqLXjaeMKjqof4aSN+ulq5ckhhJcAWJiIiIiJ6DpVSlbdA8mdtP0NieiL23dyHoIgg7Lu5Dzce3cDj7Md5lQifZqA0gLu1e4HEK/d6zao1YWJgIsNZkaYxuSIiIiIiKiUrEyv0rtMbvev0BiDW6LqVeAsRDyNw/eF1RDwSP68/vI4bj24gIycj7/bTFFCghmWNAomXu5U7olKj4P3QG46WjrAytoJKqaro06RSYnJFRERERPSCDFWGeb1RndCpwH1qSY27SXcLJFy51yMeRiA5Mxm3k27jdtJt7I/cX+CxH4V/BEAkYNYm1rAxtYGtmS1sTG3ExcQm73qB7f9drE2sORyxAvE3TURERERUjpQKJVysXOBi5YJ27u0K3CdJEu6n3c9LtHITr/D4cNy8fxOPFY+RkpkCCRIepT/Co/RHiHgUUarnz03KbExtYG9mD4+qHvCy9YKXjRe8bL3gbu3OBExD+FskIiIiIpKJQqGAQxUHOFRxgL+Lf972rKwsBAYGomvXrpCUEh49foSHjx8i/nE8Hj5+WOhS1PakjCQAQEJ6AhLSE3Dj0Y0iYzBQGqBW1Voi2fov4cr96WLpwuGIpcDkioiIiIhIixmpjOBo7ghHc8dSPS4rJwuP0h8VSLhikmNw/eF1hD8MR/jDcFx/eB3p2el5lQ+fZqwyhoeNR6HEy9vWG9UtqkOhUGjqNPUCkysiIiIiIj1kqDLM6xUrjlpS407SHYTHi2Qr7+fDcEQ8jEBGTgau3L+CK/evFHqsmaEZPG084WXjhTaubdDNqxu8bL3K85S0HpMrIiIiIqJKSqlQwtXKFa5WruhQq0OB+3LUOYhKjEJYfFihxOvmo5tIy0rDhXsXcOHeBWy5ugUTgibA29Yb3b26o5t3N7RxbQMjlZFMZyYPJldERERERFSISqlCzao1UbNqzUIVELNysnAz4SbC48Nx5f4VBEUE4eCtgwiLD8PC+IVYeGIhLI0t0cmjE7p5dUMXry7P7EHTF0yuiIiIiIioVAxVhvC29Ya3rTe6eXfDlNZTkJieiOAbwdgZvhM7w3biftp9/H7ld/x+5XcooEDLGi3Rzasbunt3h6+jr17O12JyRUREREREL8zKxAp96vZBn7p9oJbUOBN9BjvCdmBH2A6ciz2HE3dO4MSdE/hs/2dwtnDOS7Q61OoAM0MzucPXCCZXRERERESkUUqFEi2cW6CFcwvMbj8bd5PuIjA8EDvCd2Dvjb24m3wXP579ET+e/REmBiZo794e3b27o5tXN7hZu8kdfpkxuSIiIiIionLlbOmM4U2HY3jT4UjPTseByAPYGbYTO8J3IDIhEruu78Ku67swBmNQ36E+unt1R3fv7mhVo5VOrbOllDsAIiIiIiKqPEwMTNDZszOWdl2KG+Nu4NKoS/jm1W/wkutLUCqUuBR3CV8f/Rpt/tcG52LPyR1uqbDnioiIiIiIZKFQKFDPoR7qOdTDR60/wsPHDxF0PQg7wnfgfOx5NHFqIneIpcLkioiIiIiItIKNqQ36NeiHfg36QZIknasoyGGBRERERESkdXQtsQKYXBEREREREWkEkysiIiIiIiINYHJFRERERESkAUyuiIiIiIiINIDJFRERERERkQYwuSIiIiIiItIAJldEREREREQawOSKiIiIiIhIA5hcERERERERaQCTKyIiIiIiIg1gckVERERERKQBTK6IiIiIiIg0gMkVERERERGRBjC5IiIiIiIi0gAmV0RERERERBrA5IqIiIiIiEgDmFwRERERERFpgIHcAWgjSZIAAElJSTJHImRlZSEtLQ1JSUkwNDSUOxwqBttJd7CtdAfbSnewrXQD20l3sK20R25OkJsjPAuTqyIkJycDAFxcXGSOhIiIiIiItEFycjKsrKyeuY9CKkkKVsmo1WpER0fDwsICCoVC7nCQlJQEFxcX3L59G5aWlnKHQ8VgO+kOtpXuYFvpDraVbmA76Q62lfaQJAnJycmoXr06lMpnz6piz1URlEolatSoIXcYhVhaWvLNpQPYTrqDbaU72Fa6g22lG9hOuoNtpR2e12OViwUtiIiIiIiINIDJFRERERERkQYwudIBxsbGmDFjBoyNjeUOhZ6B7aQ72Fa6g22lO9hWuoHtpDvYVrqJBS2IiIiIiIg0gD1XREREREREGsDkioiIiIiISAOYXBEREREREWkAkysiIiIiIiINYHKl5ZYvX46aNWvCxMQETZs2xeHDh+UOiZ4yc+ZMKBSKApdq1arJHRYBOHToEHr06IHq1atDoVBg69atBe6XJAkzZ85E9erVYWpqinbt2uHy5cvyBFuJPa+dhgwZUug91qpVK3mCreTmzp2L5s2bw8LCAg4ODnjttddw7dq1AvvwfSW/krQT31faYcWKFWjYsGHeQsF+fn7YtWtX3v18P+keJldabPPmzRg/fjymT5+Oc+fO4aWXXkKXLl0QFRUld2j0lHr16iEmJibvcvHiRblDIgCpqanw9fXF999/X+T98+bNw8KFC/H999/j9OnTqFatGjp27Ijk5OQKjrRye147AUDnzp0LvMcCAwMrMELKdfDgQYwZMwYnTpxAcHAwsrOzERAQgNTU1Lx9+L6SX0naCeD7ShvUqFEDX3/9Nc6cOYMzZ87glVdeQa9evfISKL6fdJBEWqtFixbSyJEjC2yrXbu2NHXqVJkioqLMmDFD8vX1lTsMeg4A0l9//ZV3W61WS9WqVZO+/vrrvG3p6emSlZWV9MMPP8gQIUlS4XaSJEkaPHiw1KtXL1nioWeLi4uTAEgHDx6UJInvK231dDtJEt9X2qxq1arSqlWr+H7SUey50lKZmZkICQlBQEBAge0BAQE4duyYTFFRccLDw1G9enXUrFkTb7/9Nm7cuCF3SPQcN2/eRGxsbIH3mLGxMdq2bcv3mBY6cOAAHBwc4O3tjeHDhyMuLk7ukAhAYmIiAMDGxgYA31fa6ul2ysX3lXbJycnBpk2bkJqaCj8/P76fdBSTKy314MED5OTkwNHRscB2R0dHxMbGyhQVFaVly5ZYt24dgoKC8NNPPyE2Nhb+/v6Ij4+XOzR6htz3Ed9j2q9Lly5Yv3499u3bh2+//RanT5/GK6+8goyMDLlDq9QkScLEiRPRpk0b1K9fHwDfV9qoqHYC+L7SJhcvXoS5uTmMjY0xcuRI/PXXX6hbty7fTzrKQO4A6NkUCkWB25IkFdpG8urSpUve9QYNGsDPzw8eHh5Yu3YtJk6cKGNkVBJ8j2m/vn375l2vX78+mjVrBjc3N+zcuROvv/66jJFVbh988AEuXLiAI0eOFLqP7yvtUVw78X2lPXx8fBAaGoqEhARs2bIFgwcPxsGDB/Pu5/tJt7DnSkvZ2dlBpVIV+mYiLi6u0DcYpF2qVKmCBg0aIDw8XO5Q6BlyKzryPaZ7nJyc4ObmxveYjMaOHYvt27dj//79qFGjRt52vq+0S3Ht9P927i4kqrUN4/gls8ePSBMby4m03GiGUUNqhBmFaEFIURoOZDkhElFBWerBFGUaKoEH9iUEUXQQEmUUGKFhFqVBCROiklaWdZJlRZllkOs92DRvw+6teJsarf8PFixnLR9u1sMNXuOzni+hr3zH399fMTExSkpKUkVFhWw2m6qrq+mnMYpwNUr5+/srMTFRjY2NHp83NjZqwYIFPqoK32N4eFhdXV2yWq2+LgVfER0drYiICI8e+/Dhg65evUqPjXIDAwN6/PgxPeYDhmFoy5YtqqurU1NTk6Kjoz2u01ejw7fm6Uvoq9HDMAwNDw/TT2MUywJHse3bt2vdunVKSkpScnKyjh49qr6+Pm3cuNHXpeEzhYWFWr58uaKiotTf3699+/bp9evXcjgcvi7tjzc4OKh79+65f+7t7ZXL5VJYWJiioqK0bds2lZeXKzY2VrGxsSovL9e4ceO0Zs0aH1b95/naPIWFhamkpERZWVmyWq16+PChnE6nLBaLVq1a5cOq/0ybN2/WqVOndP78eQUHB7u/UZ8wYYKCgoLk5+dHX40C35qnwcFB+mqUcDqdWrZsmSIjI/XmzRvV1taqublZly5dop/GKp/tU4jvcvjwYWPatGmGv7+/kZCQ4LGNKkYHu91uWK1Ww2w2G1OmTDEyMzONjo4OX5cFwzCuXLliSPrX4XA4DMP4Z9voPXv2GBEREUZAQICxaNEio7293bdF/4G+Nk9DQ0PG0qVLjfDwcMNsNhtRUVGGw+Ew+vr6fF32H+lL8yTJOH78uPse+sr3vjVP9NXokZeX5/47Lzw83EhLSzMaGhrc1+mnscfPMAzjV4Y5AAAAAPgd8c4VAAAAAHgB4QoAAAAAvIBwBQAAAABeQLgCAAAAAC8gXAEAAACAFxCuAAAAAMALCFcAAAAA4AWEKwAAAADwAsIVAAA/qLm5WX5+fnr16pWvSwEA+BDhCgAAAAC8gHAFAAAAAF5AuAIAjHmGYWj//v36+++/FRQUJJvNpjNnzkj675K9+vp62Ww2BQYGav78+Wpvb/cY4+zZs5o1a5YCAgI0ffp0VVVVeVwfHh5WcXGxIiMjFRAQoNjYWB07dszjnra2NiUlJWncuHFasGCB7t696752584dpaamKjg4WCEhIUpMTNTt27d/0hMBAPjCX74uAACAH7Vr1y7V1dWppqZGsbGxunbtmtauXavw8HD3PUVFRaqurlZERIScTqdWrFih7u5umc1mtbW1KTs7WyUlJbLb7WppadGmTZs0ceJErV+/XpKUm5ur1tZWHThwQDabTb29vXr+/LlHHTt37lRVVZXCw8O1ceNG5eXl6caNG5KknJwczZ07VzU1NTKZTHK5XDKbzb/sGQEAfj4/wzAMXxcBAMD/6+3bt7JYLGpqalJycrL78/z8fA0NDWnDhg1KTU1VbW2t7Ha7JOnFixeaOnWqTpw4oezsbOXk5OjZs2dqaGhw/35xcbHq6+vV0dGh7u5uxcXFqbGxUenp6f+qobm5Wampqbp8+bLS0tIkSRcvXlRGRobevXunwMBAhYSE6ODBg3I4HD/5iQAAfIVlgQCAMa2zs1Pv37/XkiVLNH78ePdx8uRJ3b9/333f58ErLCxMcXFx6urqkiR1dXUpJSXFY9yUlBT19PTo48ePcrlcMplMWrx48VdrmTNnjvvcarVKkvr7+yVJ27dvV35+vtLT01VZWelRGwDg90C4AgCMaSMjI5Kk+vp6uVwu99HZ2el+7+p/8fPzk/TPO1ufzj/5fGFHUFDQd9Xy+TK/T+N9qq+kpEQdHR3KyMhQU1OT4uPjde7cue8aFwAwNhCuAABjWnx8vAICAtTX16eYmBiPIzIy0n3fzZs33ecvX75Ud3e3Zs6c6R7j+vXrHuO2tLRoxowZMplMmj17tkZGRnT16tUfqnXGjBkqKChQQ0ODMjMzdfz48R8aDwAwurChBQBgTAsODlZhYaEKCgo0MjKihQsX6vXr12ppadH48eM1bdo0SVJpaakmTpyoyZMna+fOnbJYLFq5cqUkaceOHZo3b57Kyspkt9vV2tqqQ4cO6ciRI5Kk6dOny+FwKC8vz72hxaNHj9Tf36/s7Oxv1vju3TsVFRVp9erVio6O1pMnT3Tr1i1lZWX9tOcCAPj1CFcAgDGvrKxMkyZNUkVFhR48eKDQ0FAlJCTI6XS6l+VVVlZq69at6unpkc1m04ULF+Tv7y9JSkhI0OnTp7V7926VlZXJarWqtLTUvVOgJNXU1MjpdGrTpk0aGBhQVFSUnE7nd9VnMpk0MDCg3NxcPX36VBaLRZmZmdq7d6/XnwUAwHfYLRAA8Fv7tJPfy5cvFRoa6utyAAC/Md65AgAAAAAvIFwBAAAAgBewLBAAAAAAvID/XAEAAACAFxCuAAAAAMALCFcAAAAA4AWEKwAAAADwAsIVAAAAAHgB4QoAAAAAvIBwBQAAAABeQLgCAAAAAC/4D9L+4glxmzckAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(encoder_f_history.history['loss'] , 'g')\n",
    "plt.plot(encoder_f_history.history['val_loss'] , 'r')\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epochs')\n",
    "plt.legend(['train', 'valid'], loc='upper right')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c895ba3c",
   "metadata": {},
   "source": [
    "Можно заметить, что удалось достигнуть ещё более низкой ошибки. Однако, в датасете *genome* представлены не вске фильмы, из-за чего размер выборок уменьшается и не все фильмы можно будет закодировать при помощи этой модели "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a65ae6c",
   "metadata": {},
   "source": [
    "**Плюсы модели**:\n",
    "* Использует признаки фильмов\n",
    "* Работает точнее\n",
    "\n",
    "**Минусы**:\n",
    "* Много слоёв и параметров\n",
    "* Ограничения из-за количества фильмов в датасете\n",
    "\n",
    "Можно сделать вывод, что из представленных моделей целесообразнее использовать модель с эмбеддингом на основе признаков фильма"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "719ddc71",
   "metadata": {},
   "source": [
    "## Сохранение моделей"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "1eecfb64",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _update_step_xla while saving (showing 1 of 1). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/id/model\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/id/model\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/id/movie_model\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/id/movie_model\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/id/user_model\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/id/user_model\\assets\n"
     ]
    }
   ],
   "source": [
    "id_model.save('models/id/model')\n",
    "id_movie_model.save('models/id/movie_model')\n",
    "id_user_model.save('models/id/user_model')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "70d298df",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Found untraced functions such as _update_step_xla while saving (showing 1 of 1). These functions will not be directly callable after loading.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/features/model\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/features/model\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/features/movie_model\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/features/movie_model\\assets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/features/user_model\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: models/features/user_model\\assets\n"
     ]
    }
   ],
   "source": [
    "feat_model.save('models/features/model')\n",
    "feat_movie_model.save('models/features/movie_model')\n",
    "feat_user_model.save('models/features/user_model')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb57e5c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "feat_model.save('models/features/model')\n",
    "feat_movie_model.save('models/features/movie_model')\n",
    "feat_user_model.save('models/features/user_model')"
   ]
  }
 ],
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