{ "cells": [ { "cell_type": "markdown", "id": "5fa29457", "metadata": {}, "source": [ "# Fine-tuning CamemBERT" ] }, { "cell_type": "code", "execution_count": 1, "id": "e523e792", "metadata": {}, "outputs": [], "source": [ "#Import des bibliothèques" ] }, { "cell_type": "code", "execution_count": 2, "id": "287c4002", "metadata": {}, "outputs": [], "source": [ "!pip install -q transformers datasets" ] }, { "cell_type": "code", "execution_count": 3, "id": "ef1b0d46", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: accelerate in /home/asma/miniconda3/lib/python3.9/site-packages (0.21.0)\n", "Requirement already satisfied: numpy>=1.17 in /home/asma/miniconda3/lib/python3.9/site-packages (from accelerate) (1.22.4)\n", "Requirement already satisfied: packaging>=20.0 in /home/asma/miniconda3/lib/python3.9/site-packages (from accelerate) (23.0)\n", "Requirement already satisfied: pyyaml in /home/asma/miniconda3/lib/python3.9/site-packages (from accelerate) (6.0)\n", "Requirement already satisfied: torch>=1.10.0 in /home/asma/miniconda3/lib/python3.9/site-packages (from accelerate) (2.0.1)\n", "Requirement already satisfied: psutil in /home/asma/miniconda3/lib/python3.9/site-packages (from accelerate) (5.9.3)\n", "Requirement already satisfied: jinja2 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (3.1.2)\n", "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.7.4.91)\n", "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.7.101)\n", "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.10.3.66)\n", "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.4.0.1)\n", "Requirement already satisfied: sympy in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (1.12)\n", "Requirement already satisfied: filelock in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (3.8.0)\n", "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.7.99)\n", "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.7.99)\n", "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (8.5.0.96)\n", "Requirement already satisfied: typing-extensions in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (4.4.0)\n", "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (10.2.10.91)\n", "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.7.91)\n", "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (10.9.0.58)\n", "Requirement already satisfied: triton==2.0.0 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (2.0.0)\n", "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (2.14.3)\n", "Requirement already satisfied: networkx in /home/asma/miniconda3/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (3.1)\n", "Requirement already satisfied: setuptools in /home/asma/miniconda3/lib/python3.9/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10.0->accelerate) (63.4.1)\n", "Requirement already satisfied: wheel in /home/asma/miniconda3/lib/python3.9/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10.0->accelerate) (0.37.1)\n", "Requirement already satisfied: lit in /home/asma/miniconda3/lib/python3.9/site-packages (from triton==2.0.0->torch>=1.10.0->accelerate) (16.0.6)\n", "Requirement already satisfied: cmake in /home/asma/miniconda3/lib/python3.9/site-packages (from triton==2.0.0->torch>=1.10.0->accelerate) (3.27.0)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /home/asma/miniconda3/lib/python3.9/site-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.1)\n", "Requirement already satisfied: mpmath>=0.19 in /home/asma/miniconda3/lib/python3.9/site-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n" ] } ], "source": [ "!pip install accelerate" ] }, { "cell_type": "code", "execution_count": 4, "id": "b8edf45a", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "import re\n", "import string" ] }, { "cell_type": "code", "execution_count": 5, "id": "248270e2", "metadata": {}, "outputs": [], "source": [ "from datasets import DatasetDict, Dataset\n", "from sklearn.model_selection import train_test_split\n", "from transformers import AutoTokenizer, AutoModel, AutoModelForSequenceClassification, TrainingArguments, Trainer\n", "from sklearn.metrics import f1_score, accuracy_score\n", "from sklearn.metrics import confusion_matrix\n", "from sklearn.metrics import classification_report" ] }, { "cell_type": "code", "execution_count": 6, "id": "5c1cda5d", "metadata": {}, "outputs": [], "source": [ "import torch\n", "\n", "from transformers import AutoTokenizer\n", "from torch.utils.data import TensorDataset, DataLoader, WeightedRandomSampler \n", "from transformers import BertTokenizer, BertForSequenceClassification, get_linear_schedule_with_warmup\n", "\n", "from transformers import CamembertForSequenceClassification\n", "\n", "# Définir le device\n", "#device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")" ] }, { "cell_type": "code", "execution_count": 7, "id": "23fcabb7", "metadata": {}, "outputs": [], "source": [ "import nltk\n", "from nltk.corpus import stopwords\n", "from nltk.tokenize import word_tokenize" ] }, { "cell_type": "code", "execution_count": 8, "id": "529a67f7", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[nltk_data] Downloading package stopwords to /home/asma/nltk_data...\n", "[nltk_data] Package stopwords is already up-to-date!\n", "[nltk_data] Downloading package punkt to /home/asma/nltk_data...\n", "[nltk_data] Package punkt is already up-to-date!\n" ] }, { "data": { "text/plain": [ "True" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "nltk.download('stopwords')\n", "# Télécharger le package punkt\n", "nltk.download('punkt')" ] }, { "cell_type": "code", "execution_count": 9, "id": "e5bad71a", "metadata": {}, "outputs": [], "source": [ "import shutil\n", "import zipfile" ] }, { "cell_type": "code", "execution_count": 10, "id": "68dd70cc", "metadata": {}, "outputs": [], "source": [ "# Option pour afficher toutes les lignes d'un dataframe\n", "#pd.set_option('display.max_rows', None)" ] }, { "cell_type": "code", "execution_count": 11, "id": "b191a27e", "metadata": {}, "outputs": [], "source": [ "data = pd.read_csv('discussions-annotations-public-.csv', delimiter=',')" ] }, { "cell_type": "code", "execution_count": 12, "id": "5ef16929", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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2601ba51cb94ff759925437d6Simulateur de COUT DU CERTIFICAT D’IMMATRICUL...Mise à jour fichiers simulateurs 2021Bonjour, suite à la mise à jour de mon simulat...Incohérence des donnéesFiabilité2021-02-04 08:41
3601c336736c1b45b238d2598Lieux de vaccination contre la Covid-19Coordonnées des centres de vaccinationsBonjour, j'ai contacté le centre de vaccinatio...Questions ou remarques d'usagersAutre2021-02-04 18:48
4601971b73363cef6fbdb08b3Vaccination et dépistage COVID-19IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE...Annonce faite dans les médias qui veulent souv...Commentaire sans valeurAutre2021-02-02 16:37
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" ], "text/plain": [ " id dgf \\\n", "0 NaN \n", "1 NaN \n", "2 601ba51cb94ff759925437d6 \n", "3 601c336736c1b45b238d2598 \n", "4 601971b73363cef6fbdb08b3 \n", "\n", " subject \\\n", "0 NaN \n", "1 NaN \n", "2 Simulateur de COUT DU CERTIFICAT D’IMMATRICUL... \n", "3 Lieux de vaccination contre la Covid-19 \n", "4 Vaccination et dépistage COVID-19 \n", "\n", " title \\\n", "0 NaN \n", "1 NaN \n", "2 Mise à jour fichiers simulateurs 2021 \n", "3 Coordonnées des centres de vaccinations \n", "4 IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE... \n", "\n", " messages \\\n", "0 NaN \n", "1 NaN \n", "2 Bonjour, suite à la mise à jour de mon simulat... \n", "3 Bonjour, j'ai contacté le centre de vaccinatio... \n", "4 Annonce faite dans les médias qui veulent souv... \n", "\n", " Annotation categorie created \n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 Incohérence des données Fiabilité 2021-02-04 08:41 \n", "3 Questions ou remarques d'usagers Autre 2021-02-04 18:48 \n", "4 Commentaire sans valeur Autre 2021-02-02 16:37 " ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "code", "execution_count": 15, "id": "e078fd0e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(7961, 7)" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.shape" ] }, { "cell_type": "code", "execution_count": 16, "id": "7aa49b03", "metadata": {}, "outputs": [], "source": [ "# Suppression des NaNs ('messages', 'Annotation', 'categorie')" ] }, { "cell_type": "code", "execution_count": 17, "id": "6aeda762", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Nombre de valeurs manquantes dans df['messages'] : 2\n", "Nombre de valeurs manquantes dans df['Annotation'] : 11\n", "Nombre de valeurs manquantes dans df['categorie'] : 11\n" ] } ], "source": [ "print(\"Nombre de valeurs manquantes dans df['messages'] :\", df.messages.isna().sum())\n", "print(\"Nombre de valeurs manquantes dans df['Annotation'] :\", df['Annotation'].isna().sum())\n", "print(\"Nombre de valeurs manquantes dans df['categorie'] :\", df['categorie'].isna().sum())" ] }, { "cell_type": "code", "execution_count": 18, "id": "a1ff0dc7", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Nombre total de lignes avec des NaNs dans les trois colonnes : 11\n" ] } ], "source": [ "total_nan_rows = sum(df['messages'].isna() | df['Annotation'].isna() | df['categorie'].isna())\n", "print(\"Nombre total de lignes avec des NaNs dans les trois colonnes :\", total_nan_rows)" ] }, { "cell_type": "code", "execution_count": 19, "id": "6f78c0a0", "metadata": {}, "outputs": [], "source": [ "# Suppression des lignes où les colonnes contiennent des NaNs\n", "df.dropna(subset=[\"messages\", \"Annotation\", \"categorie\"], inplace=True)\n", "\n", "# Réinitialisation de l'index\n", "df = df.reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": 20, "id": "00e1da7a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Nombre de valeurs manquantes dans df['messages'] : 0\n", "Nombre de valeurs manquantes dans df['Annotation'] : 0\n", "Nombre de valeurs manquantes dans df['categorie'] : 0\n" ] } ], "source": [ "# Vérification de la suppression des NaNs\n", "print(\"Nombre de valeurs manquantes dans df['messages'] :\", df.messages.isna().sum())\n", "print(\"Nombre de valeurs manquantes dans df['Annotation'] :\", df['Annotation'].isna().sum())\n", "print(\"Nombre de valeurs manquantes dans df['categorie'] :\", df['categorie'].isna().sum())" ] }, { "cell_type": "code", "execution_count": 21, "id": "9e45490f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(7950, 7)" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.shape" ] }, { "cell_type": "code", "execution_count": 22, "id": "2a0d9f46", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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0601ba51cb94ff759925437d6Simulateur de COUT DU CERTIFICAT D’IMMATRICUL...Mise à jour fichiers simulateurs 2021Bonjour, suite à la mise à jour de mon simulat...Incohérence des donnéesFiabilité2021-02-04 08:41
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2601971b73363cef6fbdb08b3Vaccination et dépistage COVID-19IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE...Annonce faite dans les médias qui veulent souv...Commentaire sans valeurAutre2021-02-02 16:37
3601cf95e3f8affb8232057a8Base Sirene des entreprises et de leurs établi...Manque d'effectifsBonjour,\\nje constate une disparition d'un gra...Incohérence des donnéesFiabilité2021-02-05 08:53
4601a99d34d7375a1d7b5f753Hydrométrie - situation hydrologique en Bretag...Temporalité des donnéesNous souhaiterions utilisé ces données. nous r...Erreur d'actualisationActualisation2021-02-03 13:40
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" ], "text/plain": [ " id dgf \\\n", "count 7950 \n", "unique 7950 \n", "top 601ba51cb94ff759925437d6 \n", "freq 1 \n", "\n", " subject \\\n", "count 7946 \n", "unique 2631 \n", "top Base Sirene des entreprises et de leurs établi... \n", "freq 327 \n", "\n", " title messages \\\n", "count 7950 7950 \n", "unique 6544 7663 \n", "top Suggestion d'un nouveau mot-clé pour améliorer... DELETED \n", "freq 130 62 \n", "\n", " Annotation categorie created \n", "count 7950 7950 7947 \n", "unique 28 8 7722 \n", "top Questions ou remarques d'usagers Accessibilité 2019-03-27 15:28 \n", "freq 1419 2579 55 " ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.describe()" ] }, { "cell_type": "code", "execution_count": 25, "id": "e95dceb6", "metadata": {}, "outputs": [], "source": [ "# Ajout d'une colonne qui concatène la colonne 'messages' et la colonne 'title'\n", "df['combined_text'] = df['title'] + ' ' + df['messages']" ] }, { "cell_type": "code", "execution_count": 26, "id": "1627e5e4", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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id dgfsubjecttitlemessagesAnnotationcategoriecreatedcombined_text
0601ba51cb94ff759925437d6Simulateur de COUT DU CERTIFICAT D’IMMATRICUL...Mise à jour fichiers simulateurs 2021Bonjour, suite à la mise à jour de mon simulat...Incohérence des donnéesFiabilité2021-02-04 08:41Mise à jour fichiers simulateurs 2021 Bonjour,...
1601c336736c1b45b238d2598Lieux de vaccination contre la Covid-19Coordonnées des centres de vaccinationsBonjour, j'ai contacté le centre de vaccinatio...Questions ou remarques d'usagersAutre2021-02-04 18:48Coordonnées des centres de vaccinations Bonjou...
2601971b73363cef6fbdb08b3Vaccination et dépistage COVID-19IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE...Annonce faite dans les médias qui veulent souv...Commentaire sans valeurAutre2021-02-02 16:37IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE...
3601cf95e3f8affb8232057a8Base Sirene des entreprises et de leurs établi...Manque d'effectifsBonjour,\\nje constate une disparition d'un gra...Incohérence des donnéesFiabilité2021-02-05 08:53Manque d'effectifs Bonjour,\\nje constate une d...
4601a99d34d7375a1d7b5f753Hydrométrie - situation hydrologique en Bretag...Temporalité des donnéesNous souhaiterions utilisé ces données. nous r...Erreur d'actualisationActualisation2021-02-03 13:40Temporalité des données Nous souhaiterions ut...
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" ], "text/plain": [ " id dgf \\\n", "0 601ba51cb94ff759925437d6 \n", "1 601c336736c1b45b238d2598 \n", "2 601971b73363cef6fbdb08b3 \n", "3 601cf95e3f8affb8232057a8 \n", "4 601a99d34d7375a1d7b5f753 \n", "\n", " subject \\\n", "0 Simulateur de COUT DU CERTIFICAT D’IMMATRICUL... \n", "1 Lieux de vaccination contre la Covid-19 \n", "2 Vaccination et dépistage COVID-19 \n", "3 Base Sirene des entreprises et de leurs établi... \n", "4 Hydrométrie - situation hydrologique en Bretag... \n", "\n", " title \\\n", "0 Mise à jour fichiers simulateurs 2021 \n", "1 Coordonnées des centres de vaccinations \n", "2 IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE... \n", "3 Manque d'effectifs \n", "4 Temporalité des données \n", "\n", " messages \\\n", "0 Bonjour, suite à la mise à jour de mon simulat... \n", "1 Bonjour, j'ai contacté le centre de vaccinatio... \n", "2 Annonce faite dans les médias qui veulent souv... \n", "3 Bonjour,\\nje constate une disparition d'un gra... \n", "4 Nous souhaiterions utilisé ces données. nous r... \n", "\n", " Annotation categorie created \\\n", "0 Incohérence des données Fiabilité 2021-02-04 08:41 \n", "1 Questions ou remarques d'usagers Autre 2021-02-04 18:48 \n", "2 Commentaire sans valeur Autre 2021-02-02 16:37 \n", "3 Incohérence des données Fiabilité 2021-02-05 08:53 \n", "4 Erreur d'actualisation Actualisation 2021-02-03 13:40 \n", "\n", " combined_text \n", "0 Mise à jour fichiers simulateurs 2021 Bonjour,... \n", "1 Coordonnées des centres de vaccinations Bonjou... \n", "2 IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE... \n", "3 Manque d'effectifs Bonjour,\\nje constate une d... \n", "4 Temporalité des données Nous souhaiterions ut... " ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "id": "39e9802d", "metadata": {}, "source": [ "# Les catégories" ] }, { "cell_type": "code", "execution_count": 27, "id": "73654171", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Accessibilité 2579\n", "Autre 2211\n", "Actualisation 1213\n", "Fiabilité 897\n", "Exploitabilité 577\n", "Compréhension 471\n", "Autre, Actualisation 1\n", "Accessibilité , Accessibilité 1\n", "Name: categorie, dtype: int64" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['categorie'].value_counts()" ] }, { "cell_type": "code", "execution_count": 28, "id": "dc5434da", "metadata": {}, "outputs": [], "source": [ "# On enlève les espaces en trop des noms de catégories\n", "def preprocess_categories(text):\n", " # Supprimer les espaces en trop\n", " text_nspaces = re.sub(r'\\s+', '', text)\n", " return text_nspaces" ] }, { "cell_type": "code", "execution_count": 29, "id": "9c083563", "metadata": {}, "outputs": [], "source": [ "# Appliquer la fonction de prétraitement sur la colonne\n", "df['categorie'] = df['categorie'].apply(preprocess_categories)" ] }, { "cell_type": "code", "execution_count": 30, "id": "adb5ec5c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Accessibilité 2579\n", "Autre 2211\n", "Actualisation 1213\n", "Fiabilité 897\n", "Exploitabilité 577\n", "Compréhension 471\n", "Autre,Actualisation 1\n", "Accessibilité,Accessibilité 1\n", "Name: categorie, dtype: int64" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['categorie'].value_counts()" ] }, { "cell_type": "code", "execution_count": 31, "id": "44319301", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['Fiabilité', 'Autre', 'Actualisation', 'Accessibilité',\n", " 'Compréhension', 'Exploitabilité', 'Autre,Actualisation',\n", " 'Accessibilité,Accessibilité'], dtype=object)" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['categorie'].unique()" ] }, { "cell_type": "code", "execution_count": 32, "id": "14224294", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "8" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['categorie'].nunique()" ] }, { "cell_type": "code", "execution_count": 33, "id": "c9a97ac8", "metadata": {}, "outputs": [], "source": [ "# On retire les catégories d'annotations multiples\n", "mask = df['categorie'].isin([\"Autre,Actualisation\", \"Accessibilité,Accessibilité\"])\n", "#df[mask].index\n", "df = df.drop(df[mask].index)\n", "\n", "# Réinitialiser l'index\n", "df = df.reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": 34, "id": "dfde408e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Accessibilité 2579\n", "Autre 2211\n", "Actualisation 1213\n", "Fiabilité 897\n", "Exploitabilité 577\n", "Compréhension 471\n", "Name: categorie, dtype: int64" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['categorie'].value_counts()" ] }, { "cell_type": "code", "execution_count": 35, "id": "6adf9161", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "6" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['categorie'].nunique()" ] }, { "cell_type": "code", "execution_count": 36, "id": "bda30b2d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(7948, 8)" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.shape" ] }, { "cell_type": "code", "execution_count": 37, "id": "be3ed7dc", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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id dgfsubjecttitlemessagesAnnotationcategoriecreatedcombined_text
0601ba51cb94ff759925437d6Simulateur de COUT DU CERTIFICAT D’IMMATRICUL...Mise à jour fichiers simulateurs 2021Bonjour, suite à la mise à jour de mon simulat...Incohérence des donnéesFiabilité2021-02-04 08:41Mise à jour fichiers simulateurs 2021 Bonjour,...
1601c336736c1b45b238d2598Lieux de vaccination contre la Covid-19Coordonnées des centres de vaccinationsBonjour, j'ai contacté le centre de vaccinatio...Questions ou remarques d'usagersAutre2021-02-04 18:48Coordonnées des centres de vaccinations Bonjou...
2601971b73363cef6fbdb08b3Vaccination et dépistage COVID-19IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE...Annonce faite dans les médias qui veulent souv...Commentaire sans valeurAutre2021-02-02 16:37IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE...
3601cf95e3f8affb8232057a8Base Sirene des entreprises et de leurs établi...Manque d'effectifsBonjour,\\nje constate une disparition d'un gra...Incohérence des donnéesFiabilité2021-02-05 08:53Manque d'effectifs Bonjour,\\nje constate une d...
4601a99d34d7375a1d7b5f753Hydrométrie - situation hydrologique en Bretag...Temporalité des donnéesNous souhaiterions utilisé ces données. nous r...Erreur d'actualisationActualisation2021-02-03 13:40Temporalité des données Nous souhaiterions ut...
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" ], "text/plain": [ " id dgf \\\n", "0 601ba51cb94ff759925437d6 \n", "1 601c336736c1b45b238d2598 \n", "2 601971b73363cef6fbdb08b3 \n", "3 601cf95e3f8affb8232057a8 \n", "4 601a99d34d7375a1d7b5f753 \n", "\n", " subject \\\n", "0 Simulateur de COUT DU CERTIFICAT D’IMMATRICUL... \n", "1 Lieux de vaccination contre la Covid-19 \n", "2 Vaccination et dépistage COVID-19 \n", "3 Base Sirene des entreprises et de leurs établi... \n", "4 Hydrométrie - situation hydrologique en Bretag... \n", "\n", " title \\\n", "0 Mise à jour fichiers simulateurs 2021 \n", "1 Coordonnées des centres de vaccinations \n", "2 IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE... \n", "3 Manque d'effectifs \n", "4 Temporalité des données \n", "\n", " messages \\\n", "0 Bonjour, suite à la mise à jour de mon simulat... \n", "1 Bonjour, j'ai contacté le centre de vaccinatio... \n", "2 Annonce faite dans les médias qui veulent souv... \n", "3 Bonjour,\\nje constate une disparition d'un gra... \n", "4 Nous souhaiterions utilisé ces données. nous r... \n", "\n", " Annotation categorie created \\\n", "0 Incohérence des données Fiabilité 2021-02-04 08:41 \n", "1 Questions ou remarques d'usagers Autre 2021-02-04 18:48 \n", "2 Commentaire sans valeur Autre 2021-02-02 16:37 \n", "3 Incohérence des données Fiabilité 2021-02-05 08:53 \n", "4 Erreur d'actualisation Actualisation 2021-02-03 13:40 \n", "\n", " combined_text \n", "0 Mise à jour fichiers simulateurs 2021 Bonjour,... \n", "1 Coordonnées des centres de vaccinations Bonjou... \n", "2 IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE... \n", "3 Manque d'effectifs Bonjour,\\nje constate une d... \n", "4 Temporalité des données Nous souhaiterions ut... " ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "code", "execution_count": 38, "id": "0c6efda7", "metadata": {}, "outputs": [], "source": [ "# Création des tables de correspondances id2label et label2id pour numériser nos catégories" ] }, { "cell_type": "code", "execution_count": 39, "id": "c0a4bbe2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['Fiabilité', 'Autre', 'Actualisation', 'Accessibilité', 'Compréhension', 'Exploitabilité']\n" ] } ], "source": [ "# Définir les labels\n", "#labels = ['cat1', 'cat2', 'cat3', 'cat4', 'cat5', 'cat6']\n", "labels = df['categorie'].unique().tolist()\n", "print(labels)" ] }, { "cell_type": "code", "execution_count": 40, "id": "ac5f6a41", "metadata": {}, "outputs": [], "source": [ "# Créer des dictionnaires pour convertir les identifiants de label et les labels\n", "id2label = {idx:label for idx, label in enumerate(labels)}\n", "label2id = {label:idx for idx, label in enumerate(labels)}" ] }, { "cell_type": "code", "execution_count": 41, "id": "88f4e063", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{0: 'Fiabilité', 1: 'Autre', 2: 'Actualisation', 3: 'Accessibilité', 4: 'Compréhension', 5: 'Exploitabilité'}\n" ] } ], "source": [ "print(id2label)" ] }, { "cell_type": "code", "execution_count": 42, "id": "95cc8877", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'Fiabilité': 0, 'Autre': 1, 'Actualisation': 2, 'Accessibilité': 3, 'Compréhension': 4, 'Exploitabilité': 5}\n" ] } ], "source": [ "print(label2id)" ] }, { "cell_type": "code", "execution_count": 43, "id": "b347e7c4", "metadata": {}, "outputs": [], "source": [ "# Division du jeu de données (Train/Validation/Test set)" ] }, { "cell_type": "code", "execution_count": 44, "id": "38cc3be1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DatasetDict({\n", " train: Dataset({\n", " features: ['id dgf', 'subject', 'title', 'messages', 'combined_text', 'Annotation', 'categorie', '__index_level_0__'],\n", " num_rows: 5086\n", " })\n", " validation: Dataset({\n", " features: ['id dgf', 'subject', 'title', 'messages', 'combined_text', 'Annotation', 'categorie', '__index_level_0__'],\n", " num_rows: 1272\n", " })\n", " test: Dataset({\n", " features: ['id dgf', 'subject', 'title', 'messages', 'combined_text', 'Annotation', 'categorie', '__index_level_0__'],\n", " num_rows: 1590\n", " })\n", "})\n" ] } ], "source": [ "# Diviser le jeu de données en ensembles d'entraînement et de test\n", "train_df, test_df = train_test_split(df, test_size=0.2, random_state=42, stratify=df['categorie'])\n", "\n", "# Diviser l'ensemble d'entraînement en ensembles d'entraînement et de validation\n", "train_df, val_df = train_test_split(train_df, test_size=0.2, random_state=42, stratify=train_df['categorie'])\n", "\n", "# Créer des Datasets pour les ensembles train, validation et test\n", "train_dataset = Dataset.from_pandas(train_df[['id dgf', 'subject', 'title', 'messages', 'combined_text', 'Annotation', 'categorie']])\n", "val_dataset = Dataset.from_pandas(val_df[['id dgf', 'subject', 'title', 'messages', 'combined_text', 'Annotation', 'categorie']])\n", "test_dataset = Dataset.from_pandas(test_df[['id dgf', 'subject', 'title', 'messages', 'combined_text', 'Annotation', 'categorie']])\n", "\n", "# Créer un DatasetDict\n", "dataset = DatasetDict({\n", " 'train': train_dataset,\n", " 'validation': val_dataset,\n", " 'test': test_dataset\n", "})\n", "\n", "print(dataset)" ] }, { "cell_type": "code", "execution_count": 45, "id": "979c6adb", "metadata": {}, "outputs": [], "source": [ "# Affichage des différents datasets après division" ] }, { "cell_type": "code", "execution_count": 46, "id": "a62b6c57", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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v68qVKwoNDdXx48fTjHberVs3i4HJevbsKRcXF/3+++/mNg8PD/P/U5+3Tp06un79uo4cOWLxfO7u7urcubMtNj+NCxcuaM+ePXrttdfk5+dnbn/iiSf0zDPPWGxDqruvy61Tp46uXLmi+Pj4DNezc+dOxcTEqEePHhbXab722mvy8fGx6PvTTz8pODhYZcuWNb/+ly9fVsOGDSXJfGpp6tGnX3/91eKU1/+yaNEipaSkKDw8XE5Oln/S/j2VkjU/s/RkdjuWL18u6c5R6X/r06ePxf3k5GStXLlSrVu3VokSJcztBQsW1Msvv6xNmzal+Rl07dr1P6/fXrVqleLi4vTSSy9Z5HR2dlaNGjXMOT08POTm5qb169enuXziv1y5csXibJK7devWTatWrUpzK1eunEW/cuXKmS8JkaQCBQqoTJkyOnnypLnN19dXBw8e1PHjx9Nd1/38jnfp0sVi36hRo4YMw1CXLl3Mbc7OzqpWrZpFllStW7fWY489Zr5fvXp11ahRI93fr1QLFixQSkqK2rdvb/FzCQwMVOnSpdM9xTpVcnKyVqxYodatW6tIkSLm9uDgYIWGhmb4uFQ//fST6tSpo7x581qsu3HjxkpOTtbGjRst+r/44osWP9/Un1F6r0VG2rVrl2aGCGdnZ/P7RUpKimJjY3X79m1Vq1ZNu3btytTz/tf7lbWvs5eXlzp06GC+X6ZMGfn6+io4ONjiTJPU/6e+BoZh6JdfflGLFi1kGIbFukJDQ3X16tU029S5c2eL98v7eV1Tfy7pnUkC4OHG6eUAHNbkyZP1+OOP6+rVq/rmm2+0ceNGi1Gc//zzTxmGocGDB2vw4MHpPkdMTIzFB+jSpUtbLPfy8lLBggUtrnM9ePCgPvzwQ61duzZNYXT16lWL+4899limBhDKDmfOnJF054Pj3YKDg7VixQrzAFyp/v0hXvq/D3V///13hqcvpq7n7tfK1dXVooCUpOPHj+vw4cMZTtEWExMj6c4H/enTp+uNN97Q+++/r0aNGqlt27Z6/vnn0xTT/3bixAk5OTmlKejuZs3PLD2Z3Y4zZ87IyclJxYsXt1h+94j5ly5d0vXr1zP8WaWkpOjs2bPm06wlpXnOjHJKMn8ZcLfUn6m7u7vGjBmjgQMHKiAgQDVr1tRzzz2nV199VYGBgf+5HiODa52lO/tFZq73vnvfk+7sf//+EmD48OFq1aqVHn/8cVWoUEHPPvusOnXqpCeeeELS/f2O373e1C+K/n1ZRGp7el9I3L3fS9Ljjz+uH3/8MaNN1fHjx2UYRrqPlXTPGQguXbqkGzdupPvYMmXK3LPYT133vn37/nPfTXWv94TMymhfnTVrlj777DMdOXJESUlJ/9n/bv/1fmXt61yoUKE085z7+Pikuy+krke68zOJi4vTtGnTNG3atHTXZYvXNfX3LqfNzQ48Cii6ATis6tWrm0cvb926tWrXrq2XX35ZR48elZeXl/mI6dtvv53hESFrpw+Li4tTvXr15O3treHDh6tkyZLKlSuXdu3apffeey/NUdp/H2F9GGV05PReRZU1UlJSVLFiRY0bNy7d5akfbj08PLRx40atW7dOv/32m5YvX6758+erYcOGWrlyZZZG6Lb2Z5aV7bClzOxLqdvy3XffpVs8//ua6n79+qlFixZatGiRVqxYocGDB2v06NFau3btPaf3ypcvn9VHx9OTmX2vbt26OnHihH799VetXLlS06dP1/jx4zV16lS98cYb9/U7ntF602vPzt8Dk8mkZcuWpbuee43TkB3rfuaZZ/Tuu++mu/zxxx+3uJ8d7wnp7avff/+9XnvtNbVu3VrvvPOO/P395ezsrNGjR6cZ/DIj/5XN2tfZmn3h7vVI0iuvvKKwsLB0+6Z+MZTZ58yM1N+7/PnzZ/oxAB4OFN0AcoTUD28NGjTQF198offff9981NXV1TXTIy0fP37cYu7ha9eu6cKFC+Z5h9evX68rV65owYIFqlu3rrnfqVOnrMprzZGKzPYtWrSoJOno0aNplh05ckT58+e3OMp9v1LXc/z4cYsjqklJSTp16pQqVapkbitZsqT27t2rRo0a/ed2ODk5qVGjRmrUqJHGjRunUaNG6YMPPtC6desy/PmVLFlSKSkpOnToUIYDMVnzM8soY2a3o2jRokpJSdGpU6csjrb9e5Ri6c6p1Llz587wZ+Xk5HRfhXzq/L3+/v6Z2udLliypgQMHauDAgTp+/LgqV66szz77TN9//32GjylbtqzmzJmjq1evprmcwBb8/PzUuXNnde7cWdeuXVPdunU1dOhQvfHGG/f1O55V6Z3qfuzYsXsOPleyZEkZhqHixYunKXL/S4ECBeTh4ZHuetPbf9Jb97Vr17L19bmfI60///yzSpQooQULFlg8fsiQIdmWKyuvszUKFCigPHnyKDk5+YG+rqdOnZKTk5NNtw2AbXBNN4Aco379+qpevbomTJigmzdvyt/fX/Xr19dXX32lCxcupOmf3hyw06ZNszjtccqUKbp9+7aaNm0q6f+OVvz76ERiYqK+/PJLq7J6enoqLi4u030zcwp0wYIFVblyZc2aNcviuQ8cOKCVK1eavzjIqmrVqqlAgQKaOnWqEhMTze0zZ85Ms03t27fXuXPn9PXXX6d5nhs3bphH4Y6NjU2zPLWIvntKrn9r3bq1nJycNHz48DRHrFN/Rtb8zDJ6rTO7HalHW+9+7kmTJlncd3Z2VpMmTfTrr79aXLpw8eJFzZ07V7Vr176v0YlDQ0Pl7e2tUaNGWezHqVL3+evXr+vmzZsWy0qWLKk8efLc8/WWpJCQEBmGocjISKvzWevKlSsW9728vFSqVClzxvv5Hc+qRYsWWVwnvn37dm3bts38HpGetm3bytnZWcOGDUtzZNMwjDTb+W/Ozs4KDQ3VokWLFBUVZW4/fPiwVqxY8Z9527dvr4iIiHT7xsXF6fbt2//5HHdL/fIus+9hUvq/h9u2bVNERITV689IVl5nazg7O6tdu3b65Zdf0p0u7n73u/96r4+MjFT58uUfyJddALIXR7oB5CjvvPOOXnjhBc2cOVM9evTQ5MmTVbt2bVWsWFFdu3ZViRIldPHiRUVEROivv/7S3r17LR6fmJioRo0aqX379jp69Ki+/PJL1a5dWy1btpQkPf3008qbN6/CwsLUt29fmUwmfffdd1afhlq1alVNmTJFH330kUqVKiV/f/8Mr8OtWrWq5s+frwEDBuipp56Sl5eXWrRokW7fTz75RE2bNlVISIi6dOlinjLMx8cnzRzR98vV1VUfffSRunfvroYNG+rFF1/UqVOn9O2336a5prtTp0768ccf1aNHD61bt061atVScnKyjhw5oh9//FErVqxQtWrVNHz4cG3cuFHNmzdX0aJFFRMToy+//FKFChVS7dq1M8xSqlQpffDBBxoxYoTq1Kmjtm3byt3dXTt27FBQUJBGjx5t1c8so9c6s9tRtWpVtWvXThMmTNCVK1fMU4YdO3ZMkuWRrI8++sg8N/mbb74pFxcXffXVV7p165bGjh17Xz8bb29vTZkyRZ06ddKTTz6pDh06qECBAoqKitJvv/2mWrVq6YsvvtCxY8fM+3m5cuXk4uKihQsX6uLFixYDS6Wndu3aypcvn1avXp3uPrtr1650j5SXLFlSISEhVm1PuXLlVL9+fVWtWlV+fn7auXOnfv75Z/Xu3dvcx9rf8awqVaqUateurZ49e+rWrVuaMGGC8uXLl+Hp29Kdbf/oo480aNAgnT59Wq1bt1aePHl06tQpLVy4UN26ddPbb7+d4eOHDRum5cuXq06dOnrzzTd1+/ZtTZo0SeXLl9e+ffvumfedd97R4sWL9dxzz5mnZEtISND+/fv1888/6/Tp01afrly1alVJUt++fRUaGipnZ+f/3G+ee+45LViwQG3atFHz5s116tQpTZ06VeXKldO1a9esWn9Gsvo6W+Pjjz/WunXrVKNGDXXt2lXlypVTbGysdu3apdWrV6f7ReJ/udd7fVJSkjZs2JBmkEYADuKBjJEOANkodeqfHTt2pFmWnJxslCxZ0ihZsqR5eqUTJ04Yr776qhEYGGi4uroajz32mPHcc88ZP//8c5rn3LBhg9GtWzcjb968hpeXl9GxY0eL6bcMwzA2b95s1KxZ0/Dw8DCCgoKMd9991zylzL+n+qpXr55Rvnz5dLchOjraaN68uZEnTx6LabbSmzLs2rVrxssvv2z4+voaksxTyqQ3ZZhhGMbq1auNWrVqGR4eHoa3t7fRokUL49ChQxZ9UqfguXuKrrunoLqXL7/80ihevLjh7u5uVKtWzdi4caNRr169NFOhJSYmGmPGjDHKly9vuLu7G3nz5jWqVq1qDBs2zLh69aphGIaxZs0ao1WrVkZQUJDh5uZmBAUFGS+99FKaaY4y8s033xhVqlQxP3+9evWMVatWmZdn9meW0Wud2e0wDMNISEgwevXqZfj5+RleXl5G69atjaNHjxqSjI8//tgi965du4zQ0FDDy8vLyJ07t9GgQQNjy5YtFn3utb9n9PNat26dERoaavj4+Bi5cuUySpYsabz22mvGzp07DcMwjMuXLxu9evUyypYta3h6eho+Pj5GjRo1jB9//DFTr3ffvn2NUqVKWbT915RhYWFh5r5FixZNdyqwu/efjz76yKhevbrh6+treHh4GGXLljVGjhxpMa2fYVj3O37365jR70JYWJjh6emZZvs++eQT47PPPjMKFy5suLu7G3Xq1DH27t2b7nPe7ZdffjFq165teHp6Gp6enkbZsmWNXr16GUePHk3T924bNmwwqlatari5uRklSpQwpk6dmuF67vbPP/8YgwYNMkqVKmW4ubkZ+fPnN55++mnj008/Nb+W/96+u+muKbxu375t9OnTxyhQoIBhMpnMGe71HCkpKcaoUaOMokWLGu7u7kaVKlWMpUuXGmFhYWmmybp7fda+X2Xmdc7o/TmjfVOS0atXL4u2ixcvGr169TIKFy5suLq6GoGBgUajRo2MadOmmfukvqf/9NNPFo9N7/37Xu8/y5YtMyQZx48fT5MNwMPPZBjZNEoIADiwmTNnqnPnztqxY4d5cDYgu+zZs0dVqlTR999/r44dO9o7TpadPHlSZcuW1bJly9SoUSN7xwFyvNatW8tkMmnhwoX2jgLgPnB6OQAA2ejGjRtpRm+eMGGCnJycLAZyc2QlSpRQly5d9PHHH1N0AzZ2+PBhLV26VHv27LF3FAD3iaIbAIBsNHbsWEVGRqpBgwZycXHRsmXLtGzZMnXr1u2BTC32oEyZMsXeEYBHQnBw8H0NeAfg4UHRDQBANnr66ae1atUqjRgxQteuXVORIkU0dOhQffDBB/aOBgAA7IBrugEAAAAAsBHm6QYAAAAAwEYougEAAAAAsBGu6c6klJQUnT9/Xnny5JHJZLJ3HAAAAACAHRmGoX/++UdBQUFycsr4eDZFdyadP38+R406CwAAAADIurNnz6pQoUIZLqfozqQ8efJIuvOCent72zkNAAAAAMCe4uPjVbhwYXOtmBGK7kxKPaXc29ubohsAAAAAIEn/efkxA6kBAAAAAGAjFN0AAAAAANgIRTcAAAAAADZC0Q0AAAAAgI1QdAMAAAAAYCMU3QAAAAAA2AhFNwAAAAAANkLRDQAAAACAjVB0AwAAAABgIxTdAAAAAADYCEU3AAAAAAA2QtENAAAAAICNUHQDAAAAAGAjFN0AAAAAANiIi70DIGtatLB3AseyZIm9EwAAAAB4lHCkGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAbsWvRvXHjRrVo0UJBQUEymUxatGhRmj6HDx9Wy5Yt5ePjI09PTz311FOKiooyL79586Z69eqlfPnyycvLS+3atdPFixctniMqKkrNmzdX7ty55e/vr3feeUe3b9+29eYBAAAAAB5xdi26ExISVKlSJU2ePDnd5SdOnFDt2rVVtmxZrV+/Xvv27dPgwYOVK1cuc5/+/ftryZIl+umnn7RhwwadP39ebdu2NS9PTk5W8+bNlZiYqC1btmjWrFmaOXOmwsPDbb59AAAAAIBHm8kwDMPeISTJZDJp4cKFat26tbmtQ4cOcnV11XfffZfuY65evaoCBQpo7ty5ev755yVJR44cUXBwsCIiIlSzZk0tW7ZMzz33nM6fP6+AgABJ0tSpU/Xee+/p0qVLcnNzy1S++Ph4+fj46OrVq/L29s7axmYj5um2DvN0AwAAAMgOma0RH9prulNSUvTbb7/p8ccfV2hoqPz9/VWjRg2LU9AjIyOVlJSkxo0bm9vKli2rIkWKKCIiQpIUERGhihUrmgtuSQoNDVV8fLwOHjyY4fpv3bql+Ph4ixsAAAAAANZ4aIvumJgYXbt2TR9//LGeffZZrVy5Um3atFHbtm21YcMGSVJ0dLTc3Nzk6+tr8diAgABFR0eb+/y74E5dnrosI6NHj5aPj4/5Vrhw4WzcOgAAAADAo+ChLbpTUlIkSa1atVL//v1VuXJlvf/++3ruuec0depUm69/0KBBunr1qvl29uxZm68TAAAAAJCzPLRFd/78+eXi4qJy5cpZtAcHB5tHLw8MDFRiYqLi4uIs+ly8eFGBgYHmPnePZp56P7VPetzd3eXt7W1xAwAAAADAGg9t0e3m5qannnpKR48etWg/duyYihYtKkmqWrWqXF1dtWbNGvPyo0ePKioqSiEhIZKkkJAQ7d+/XzExMeY+q1atkre3d5qCHgAAAACA7ORiz5Vfu3ZNf/75p/n+qVOntGfPHvn5+alIkSJ655139OKLL6pu3bpq0KCBli9friVLlmj9+vWSJB8fH3Xp0kUDBgyQn5+fvL291adPH4WEhKhmzZqSpCZNmqhcuXLq1KmTxo4dq+joaH344Yfq1auX3N3d7bHZAAAAAIBHhF2L7p07d6pBgwbm+wMGDJAkhYWFaebMmWrTpo2mTp2q0aNHq2/fvipTpox++eUX1a5d2/yY8ePHy8nJSe3atdOtW7cUGhqqL7/80rzc2dlZS5cuVc+ePRUSEiJPT0+FhYVp+PDhD25DAQAAAACPpIdmnu6HHfN05wzM0w0AAAAgOzj8PN0AAAAAADg6im4AAAAAAGyEohsAAAAAABuh6AYAAAAAwEYougEAAAAAsBGKbgAAAAAAbISiGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALARim4AAAAAAGyEohsAAAAAABuh6AYAAAAAwEYougEAAAAAsBGKbgAAAAAAbISiGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALARim4AAAAAAGyEohsAAAAAABuh6AYAAAAAwEYougEAAAAAsBGKbgAAAAAAbMTFnivfuHGjPvnkE0VGRurChQtauHChWrdunW7fHj166KuvvtL48ePVr18/c3tsbKz69OmjJUuWyMnJSe3atdPnn38uLy8vc599+/apV69e2rFjhwoUKKA+ffro3XfftfHWAY6tRQt7J3AsS5bYOwEAAAAeRnY90p2QkKBKlSpp8uTJ9+y3cOFCbd26VUFBQWmWdezYUQcPHtSqVau0dOlSbdy4Ud26dTMvj4+PV5MmTVS0aFFFRkbqk08+0dChQzVt2rRs3x4AAAAAAP7Nrke6mzZtqqZNm96zz7lz59SnTx+tWLFCzZs3t1h2+PBhLV++XDt27FC1atUkSZMmTVKzZs306aefKigoSHPmzFFiYqK++eYbubm5qXz58tqzZ4/GjRtnUZzf7datW7p165b5fnx8fBa2FAAAAADwKHqor+lOSUlRp06d9M4776h8+fJplkdERMjX19dccEtS48aN5eTkpG3btpn71K1bV25ubuY+oaGhOnr0qP7+++8M1z169Gj5+PiYb4ULF87GLQMAAAAAPAoe6qJ7zJgxcnFxUd++fdNdHh0dLX9/f4s2FxcX+fn5KTo62twnICDAok/q/dQ+6Rk0aJCuXr1qvp09ezYrmwIAAAAAeATZ9fTye4mMjNTnn3+uXbt2yWQyPfD1u7u7y93d/YGvFwAAAACQczy0R7r/+OMPxcTEqEiRInJxcZGLi4vOnDmjgQMHqlixYpKkwMBAxcTEWDzu9u3bio2NVWBgoLnPxYsXLfqk3k/tAwAAAACALTy0RXenTp20b98+7dmzx3wLCgrSO++8oxUrVkiSQkJCFBcXp8jISPPj1q5dq5SUFNWoUcPcZ+PGjUpKSjL3WbVqlcqUKaO8efM+2I0CAAAAADxS7Hp6+bVr1/Tnn3+a7586dUp79uyRn5+fihQponz58ln0d3V1VWBgoMqUKSNJCg4O1rPPPquuXbtq6tSpSkpKUu/evdWhQwfz9GIvv/yyhg0bpi5duui9997TgQMH9Pnnn2v8+PEPbkMBAAAAAI8kuxbdO3fuVIMGDcz3BwwYIEkKCwvTzJkzM/Ucc+bMUe/evdWoUSM5OTmpXbt2mjhxonm5j4+PVq5cqV69eqlq1arKnz+/wsPD7zldGAAAAAAA2cGuRXf9+vVlGEam+58+fTpNm5+fn+bOnXvPxz3xxBP6448/rI0HAAAAAECWPLTXdAMAAAAA4OgougEAAAAAsBGKbgAAAAAAbISiGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALARim4AAAAAAGyEohsAAAAAABuh6AYAAAAAwEYougEAAAAAsBGKbgAAAAAAbISiGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALARim4AAAAAAGyEohsAAAAAABuh6AYAAAAAwEasLrpv3Lih69evm++fOXNGEyZM0MqVK7M1GAAAAAAAjs7qortVq1aaPXu2JCkuLk41atTQZ599platWmnKlCnZHhAAAAAAAEdlddG9a9cu1alTR5L0888/KyAgQGfOnNHs2bM1ceLEbA8IAAAAAICjsrrovn79uvLkySNJWrlypdq2bSsnJyfVrFlTZ86cyfaAAAAAAAA4KquL7lKlSmnRokU6e/asVqxYoSZNmkiSYmJi5O3tbdVzbdy4US1atFBQUJBMJpMWLVpkXpaUlKT33ntPFStWlKenp4KCgvTqq6/q/PnzFs8RGxurjh07ytvbW76+vurSpYuuXbtm0Wffvn2qU6eOcuXKpcKFC2vs2LHWbjYAAAAAAFazuugODw/X22+/rWLFiqlGjRoKCQmRdOeod5UqVax6roSEBFWqVEmTJ09Os+z69evatWuXBg8erF27dmnBggU6evSoWrZsadGvY8eOOnjwoFatWqWlS5dq48aN6tatm3l5fHy8mjRpoqJFiyoyMlKffPKJhg4dqmnTplm76QAAAAAAWMVkGIZh7YOio6N14cIFVapUSU5Od+r27du3y9vbW2XLlr2/ICaTFi5cqNatW2fYZ8eOHapevbrOnDmjIkWK6PDhwypXrpx27NihatWqSZKWL1+uZs2a6a+//lJQUJCmTJmiDz74QNHR0XJzc5Mkvf/++1q0aJGOHDmS6Xzx8fHy8fHR1atXrT6ib0stWtg7gWNZssTeCRwH+5Z12LcAAAAeLZmtEe9rnu7AwEBVqVLFXHBLUvXq1e+74M6sq1evymQyydfXV5IUEREhX19fc8EtSY0bN5aTk5O2bdtm7lO3bl1zwS1JoaGhOnr0qP7+++8M13Xr1i3Fx8db3AAAAAAAsIaLtQ9ISEjQxx9/rDVr1igmJkYpKSkWy0+ePJlt4f7t5s2beu+99/TSSy+Zv0WIjo6Wv7+/RT8XFxf5+fkpOjra3Kd48eIWfQICAszL8ubNm+76Ro8erWHDhmX3ZgAAAAAAHiFWF91vvPGGNmzYoE6dOqlgwYIymUy2yGUhKSlJ7du3l2EYD2wu8EGDBmnAgAHm+/Hx8SpcuPADWTcAAAAAIGewuuhetmyZfvvtN9WqVcsWedJILbjPnDmjtWvXWpwrHxgYqJiYGIv+t2/fVmxsrAIDA819Ll68aNEn9X5qn/S4u7vL3d09uzYDAAAAAPAIsvqa7rx588rPz88WWdJILbiPHz+u1atXK1++fBbLQ0JCFBcXp8jISHPb2rVrlZKSoho1apj7bNy4UUlJSeY+q1atUpkyZTI8tRwAAAAAgOxgddE9YsQIhYeH6/r161le+bVr17Rnzx7t2bNHknTq1Cnt2bNHUVFRSkpK0vPPP6+dO3dqzpw5Sk5OVnR0tKKjo5WYmChJCg4O1rPPPquuXbtq+/bt2rx5s3r37q0OHTooKChIkvTyyy/Lzc1NXbp00cGDBzV//nx9/vnnFqeOAwAAAABgC1ZPGValShWdOHFChmGoWLFicnV1tVi+a9euTD/X+vXr1aBBgzTtYWFhGjp0aJoB0FKtW7dO9evXlyTFxsaqd+/eWrJkiZycnNSuXTtNnDhRXl5e5v779u1Tr169tGPHDuXPn199+vTRe++9l+mcElOG5RRM65R57FvWYd8CAAB4tGS2RrT6mu57zaNtrfr16+teNX9mvg/w8/PT3Llz79nniSee0B9//GF1PgAAAAAAssLqonvIkCG2yAEAAAAAQI5jddGdKjIyUocPH5YklS9fXlWqVMm2UAAAAAAA5ARWF90xMTHq0KGD1q9fL19fX0lSXFycGjRooHnz5qlAgQLZnREAAAAAAIdk9ejlffr00T///KODBw8qNjZWsbGxOnDggOLj49W3b19bZAQAAAAAwCFZfaR7+fLlWr16tYKDg81t5cqV0+TJk9WkSZNsDQcAAAAAgCOz+kh3SkpKmmnCJMnV1VUpKSnZEgoAAAAAgJzA6qK7YcOGeuutt3T+/Hlz27lz59S/f381atQoW8MBAAAAAODIrC66v/jiC8XHx6tYsWIqWbKkSpYsqeLFiys+Pl6TJk2yRUYAAAAAAByS1dd0Fy5cWLt27dLq1at15MgRSVJwcLAaN26c7eEAAAAAAHBk9zVPt8lk0jPPPKNnnnkmu/MAAAAAAJBjZKronjhxYqafkGnDAAAAAAC4I1NF9/jx4zP1ZCaTiaIbAAAAAID/L1NF96lTp2ydAwAAAACAHMfq0csBAAAAAEDmZOpI94ABAzL9hOPGjbvvMAAAAAAA5CSZKrp3796dqSczmUxZCgMAAAAAQE6SqaJ73bp1ts4BAAAAAECOwzXdAAAAAADYSKaOdLdt21YzZ86Ut7e32rZte8++CxYsyJZgAAAAAAA4ukwV3T4+Pubrtb29vbl2GwAAAACATMhU0f3tt9+a/z9z5kxbZQEAAAAAIEex+pruhg0bKi4uLk17fHy8GjZsmB2ZAAAAAADIEawuutevX6/ExMQ07Tdv3tQff/yRLaEAAAAAAMgJMnV6uSTt27fP/P9Dhw4pOjrafD85OVnLly/XY489lr3pAAAAAABwYJkuuitXriyTySSTyZTuaeQeHh6aNGlStoYDAAAAAMCRZbroPnXqlAzDUIkSJbR9+3YVKFDAvMzNzU3+/v5ydna2SUgAAAAAABxRpovuokWLSpJSUlJsFgYAAAAAgJwk00X3vx0/flzr1q1TTExMmiI8PDw8W4IBAAAAAODorC66v/76a/Xs2VP58+dXYGCgTCaTeZnJZKLoBgAAAADg/7O66P7oo480cuRIvffee7bIAwAAAABAjmH1PN1///23XnjhhWxZ+caNG9WiRQsFBQXJZDJp0aJFFssNw1B4eLgKFiwoDw8PNW7cWMePH7foExsbq44dO8rb21u+vr7q0qWLrl27ZtFn3759qlOnjnLlyqXChQtr7Nix2ZIfAAAAAIB7sbrofuGFF7Ry5cpsWXlCQoIqVaqkyZMnp7t87NixmjhxoqZOnapt27bJ09NToaGhunnzprlPx44ddfDgQa1atUpLly7Vxo0b1a1bN/Py+Ph4NWnSREWLFlVkZKQ++eQTDR06VNOmTcuWbQAAAAAAICNWn15eqlQpDR48WFu3blXFihXl6upqsbxv376Zfq6mTZuqadOm6S4zDEMTJkzQhx9+qFatWkmSZs+erYCAAC1atEgdOnTQ4cOHtXz5cu3YsUPVqlWTJE2aNEnNmjXTp59+qqCgIM2ZM0eJiYn65ptv5ObmpvLly2vPnj0aN26cRXEOAAAAAEB2s7ronjZtmry8vLRhwwZt2LDBYpnJZLKq6L6XU6dOKTo6Wo0bNza3+fj4qEaNGoqIiFCHDh0UEREhX19fc8EtSY0bN5aTk5O2bdumNm3aKCIiQnXr1pWbm5u5T2hoqMaMGaO///5befPmTXf9t27d0q1bt8z34+Pjs2W7AAAAAACPDquL7lOnTtkiRxrR0dGSpICAAIv2gIAA87Lo6Gj5+/tbLHdxcZGfn59Fn+LFi6d5jtRlGRXdo0eP1rBhw7K+IQAAAACAR5bV13Q/KgYNGqSrV6+ab2fPnrV3JAAAAACAg7H6SLck/fXXX1q8eLGioqKUmJhosWzcuHHZEiwwMFCSdPHiRRUsWNDcfvHiRVWuXNncJyYmxuJxt2/fVmxsrPnxgYGBunjxokWf1PupfdLj7u4ud3f3LG8HAAAAAODRZXXRvWbNGrVs2VIlSpTQkSNHVKFCBZ0+fVqGYejJJ5/MtmDFixdXYGCg1qxZYy6y4+PjtW3bNvXs2VOSFBISori4OEVGRqpq1aqSpLVr1yolJUU1atQw9/nggw+UlJRkHvRt1apVKlOmTIanlgMAAAAAkB2sPr180KBBevvtt7V//37lypVLv/zyi86ePat69epZPX/3tWvXtGfPHu3Zs0fSnevF9+zZo6ioKJlMJvXr108fffSRFi9erP379+vVV19VUFCQWrduLUkKDg7Ws88+q65du2r79u3avHmzevfurQ4dOigoKEiS9PLLL8vNzU1dunTRwYMHNX/+fH3++ecaMGCAtZsOAAAAAIBVrD7SffjwYf3www93Huziohs3bsjLy0vDhw9Xq1atzEehM2Pnzp1q0KCB+X5qIRwWFqaZM2fq3XffVUJCgrp166a4uDjVrl1by5cvV65cucyPmTNnjnr37q1GjRrJyclJ7dq108SJE83LfXx8tHLlSvXq1UtVq1ZV/vz5FR4eznRhAAAAAACbs7ro9vT0NF/HXbBgQZ04cULly5eXJF2+fNmq56pfv74Mw8hwuclk0vDhwzV8+PAM+/j5+Wnu3Ln3XM8TTzyhP/74w6psAAAAAABkldVFd82aNbVp0yYFBwerWbNmGjhwoPbv368FCxaoZs2atsgIAAAAAIBDsrroHjdunK5duyZJGjZsmK5du6b58+erdOnS2TZyOQAAAAAAOYHVRXeJEiXM//f09NTUqVOzNRAAAAAAADnFfc3TLUmJiYmKiYlRSkqKRXuRIkWyHAoAAAAAgJzA6qL72LFj6tKli7Zs2WLRbhiGTCaTkpOTsy0cAAAAAACOzOqiu3PnznJxcdHSpUtVsGBBmUwmW+QCAAAAAMDhWV1079mzR5GRkSpbtqwt8gAAAAAAkGM4WfuAcuXKWT0fNwAAAAAAj6JMFd3x8fHm25gxY/Tuu+9q/fr1unLlisWy+Ph4W+cFAAAAAMBhZOr0cl9fX4trtw3DUKNGjSz6MJAaAAAAAACWMlV0r1u3ztY5AAAAAADIcTJVdNerV8/WOQAAAAAAyHGsHkjt22+/1U8//ZSm/aefftKsWbOyJRQAAAAAADmB1UX36NGjlT9//jTt/v7+GjVqVLaEAgAAAAAgJ7C66I6KilLx4sXTtBctWlRRUVHZEgoAAAAAgJzA6qLb399f+/btS9O+d+9e5cuXL1tCAQAAAACQE1hddL/00kvq27ev1q1bp+TkZCUnJ2vt2rV666231KFDB1tkBAAAAADAIWVq9PJ/GzFihE6fPq1GjRrJxeXOw1NSUvTqq69yTTcAAAAAAP9iddHt5uam+fPna8SIEdq7d688PDxUsWJFFS1a1Bb5AAAAAABwWFYX3amKFSsmwzBUsmRJ8xFvAAAAAADwf6y+pvv69evq0qWLcufOrfLly5tHLO/Tp48+/vjjbA8IAAAAAICj+s+i+6uvvtKuXbvM9wcNGqS9e/dq/fr1ypUrl7m9cePGmj9/vm1SAgAAAADggP6z6C5btqxatWqllStXSpIWLlyoL774QrVr15bJZDL3K1++vE6cOGG7pAAAAAAAOJj/LLrr1aunDRs2KDw8XJJ0+fJl+fv7p+mXkJBgUYQDAAAAAPCoy9Q13SVKlNDGjRslSdWqVdNvv/1mXpZaaE+fPl0hISE2iAgAAAAAgGPK9LDjbm5ukqRRo0apadOmOnTokG7fvq3PP/9chw4d0pYtW7RhwwabBQUAAAAAwNFYPXp57dq1tWfPHt2+fVsVK1bUypUr5e/vr4iICFWtWtUWGQEAAAAAcEj3NcF2yZIl9fXXX2d3FgAAAAAAchSrj3QDAAAAAIDMyfSRbicnJ5lMJhmGIZPJpOTkZFvmAgAAAADA4WX6SPepU6d08uRJ878PQnJysgYPHqzixYvLw8NDJUuW1IgRI2QYhrmPYRgKDw9XwYIF5eHhocaNG+v48eMWzxMbG6uOHTvK29tbvr6+6tKli65du/ZAtgEAAAAA8OjK9JHuokWL2jJHusaMGaMpU6Zo1qxZKl++vHbu3KnOnTvLx8dHffv2lSSNHTtWEydO1KxZs1S8eHENHjxYoaGhOnTokHLlyiVJ6tixoy5cuKBVq1YpKSlJnTt3Vrdu3TR37twHvk0AAAAAgEdHporuffv2ZfoJn3jiifsOc7ctW7aoVatWat68uSSpWLFi+uGHH7R9+3ZJd45yT5gwQR9++KFatWolSZo9e7YCAgK0aNEidejQQYcPH9by5cu1Y8cOVatWTZI0adIkNWvWTJ9++qmCgoLSXfetW7d069Yt8/34+Phs2y4AAAAAwKMhU0V35cqVLa7nvpfsvNb76aef1rRp03Ts2DE9/vjj2rt3rzZt2qRx48ZJunPKe3R0tBo3bmx+jI+Pj2rUqKGIiAh16NBBERER8vX1NRfcktS4cWM5OTlp27ZtatOmTbrrHj16tIYNG5Zt2wIAAAAAePRkqug+deqU+f+7d+/W22+/rXfeeUchISGSpIiICH322WcaO3ZstoZ7//33FR8fr7Jly8rZ2VnJyckaOXKkOnbsKEmKjo6WJAUEBFg8LiAgwLwsOjpa/v7+FstdXFzk5+dn7pOeQYMGacCAAeb78fHxKly4cLZsFwAAAADg0ZCpovvf13O/8MILmjhxopo1a2Zue+KJJ1S4cGENHjxYrVu3zrZwP/74o+bMmaO5c+eqfPny2rNnj/r166egoCCFhYVl23rS4+7uLnd3d5uuAwAAAACQs2V6ILVU+/fvV/HixdO0Fy9eXIcOHcqWUKneeecdvf/+++rQoYMkqWLFijpz5oxGjx6tsLAwBQYGSpIuXryoggULmh938eJFVa5cWZIUGBiomJgYi+e9ffu2YmNjzY8HAAAAAMAWMj1lWKrg4GCNHj1aiYmJ5rbExESNHj1awcHB2Rru+vXrcnKyjOjs7KyUlBRJdwr9wMBArVmzxrw8Pj5e27ZtM5/6HhISori4OEVGRpr7rF27VikpKapRo0a25gUAAAAA4N+sPtI9depUtWjRQoUKFTKPVL5v3z6ZTCYtWbIkW8O1aNFCI0eOVJEiRVS+fHnt3r1b48aN0+uvvy5JMplM6tevnz766COVLl3aPGVYUFCQ+TT34OBgPfvss+rataumTp2qpKQk9e7dWx06dMhw5HIAgO20aGHvBI4lm/+0AgCAB8zqort69eo6efKk5syZoyNHjkiSXnzxRb388svy9PTM1nCTJk3S4MGD9eabbyomJkZBQUHq3r27wsPDzX3effddJSQkqFu3boqLi1Pt2rW1fPly8xzdkjRnzhz17t1bjRo1kpOTk9q1a6eJEydma1YAAAAAAO5mMgzDsHcIRxAfHy8fHx9dvXpV3t7e9o5jxhEj63DEKPPYt6zDvpV57FvWYd8CAODhlNka0eprugEAAAAAQOZQdAMAAAAAYCMU3QAAAAAA2AhFNwAAAAAANnJfRXdcXJymT5+uQYMGKTY2VpK0a9cunTt3LlvDAQAAAADgyKyeMmzfvn1q3LixfHx8dPr0aXXt2lV+fn5asGCBoqKiNHv2bFvkBAAAAADA4Vh9pHvAgAF67bXXdPz4cYu5sJs1a6aNGzdmazgAAAAAAByZ1UX3jh071L179zTtjz32mKKjo7MlFAAAAAAAOYHVRbe7u7vi4+PTtB87dkwFChTIllAAAAAAAOQEVhfdLVu21PDhw5WUlCRJMplMioqK0nvvvad27dple0AAAAAAAByV1UX3Z599pmvXrsnf3183btxQvXr1VKpUKeXJk0cjR460RUYAAAAAAByS1aOX+/j4aNWqVdq8ebP27t2ra9eu6cknn1Tjxo1tkQ8AAAAAAIdlVdGdlJQkDw8P7dmzR7Vq1VKtWrVslQsAAAAAAIdn1enlrq6uKlKkiJKTk22VBwAAAACAHMPqa7o/+OAD/e9//1NsbKwt8gAAAAAAkGNYfU33F198oT///FNBQUEqWrSoPD09LZbv2rUr28IBAAAAAODIrC66W7dubYMYAAAAAADkPFYX3UOGDLFFDgAAAAAAchyri+5UO3fu1OHDhyVJ5cqVU9WqVbMtFAAAAAAAOYHVRfdff/2ll156SZs3b5avr68kKS4uTk8//bTmzZunQoUKZXdGAAAAAAAcktWjl7/xxhtKSkrS4cOHFRsbq9jYWB0+fFgpKSl64403bJERAAAAAACHZPWR7g0bNmjLli0qU6aMua1MmTKaNGmS6tSpk63hAAAAAABwZFYf6S5cuLCSkpLStCcnJysoKChbQgEAAAAAkBNYXXR/8skn6tOnj3bu3Glu27lzp9566y19+umn2RoOAAAAAABHlqnTy/PmzSuTyWS+n5CQoBo1asjF5c7Db9++LRcXF73++uvM4w0AAAAAwP+XqaJ7woQJNo4BAAAAAEDOk6miOywszNY5AAAAAADIcawevTxVTEyMYmJilJKSYtH+xBNPZDkUAAAAAAA5gdVFd2RkpMLCwnT48GEZhmGxzGQyKTk5OdvCAQAAAADgyKwevfz111/X448/ri1btujkyZM6deqU+Xby5MlsD3ju3Dm98sorypcvnzw8PFSxYkWLkdMNw1B4eLgKFiwoDw8PNW7cWMePH7d4jtjYWHXs2FHe3t7y9fVVly5ddO3atWzPCgAAAADAv1l9pPvkyZP65ZdfVKpUKVvksfD333+rVq1aatCggZYtW6YCBQro+PHjyps3r7nP2LFjNXHiRM2aNUvFixfX4MGDFRoaqkOHDilXrlySpI4dO+rChQtatWqVkpKS1LlzZ3Xr1k1z5861+TYAAAAAAB5dVhfdjRo10t69ex9I0T1mzBgVLlxY3377rbmtePHi5v8bhqEJEyboww8/VKtWrSRJs2fPVkBAgBYtWqQOHTro8OHDWr58uXbs2KFq1apJkiZNmqRmzZrp008/VVBQkM23AwAAAADwaLK66J4+fbrCwsJ04MABVahQQa6urhbLW7ZsmW3hFi9erNDQUL3wwgvasGGDHnvsMb355pvq2rWrJOnUqVOKjo5W48aNzY/x8fFRjRo1FBERoQ4dOigiIkK+vr7mgluSGjduLCcnJ23btk1t2rRJd923bt3SrVu3zPfj4+OzbbsAAAAAAI8Gq4vuiIgIbd68WcuWLUuzLLsHUjt58qSmTJmiAQMG6H//+5927Nihvn37ys3NTWFhYYqOjpYkBQQEWDwuICDAvCw6Olr+/v4Wy11cXOTn52fuk57Ro0dr2LBh2bYtAAAAAIBHj9UDqfXp00evvPKKLly4oJSUFItbdo9cnpKSoieffFKjRo1SlSpV1K1bN3Xt2lVTp07N1vWkZ9CgQbp69ar5dvbsWZuvEwAAAACQs1hddF+5ckX9+/dPc3TZFgoWLKhy5cpZtAUHBysqKkqSFBgYKEm6ePGiRZ+LFy+alwUGBiomJsZi+e3btxUbG2vukx53d3d5e3tb3AAAAAAAsIbVRXfbtm21bt06W2RJo1atWjp69KhF27Fjx1S0aFFJdwZVCwwM1Jo1a8zL4+PjtW3bNoWEhEiSQkJCFBcXp8jISHOftWvXKiUlRTVq1HgAWwEAAAAAeFRZfU33448/rkGDBmnTpk2qWLFimoHU+vbtm23h+vfvr6efflqjRo1S+/bttX37dk2bNk3Tpk2TdOca8n79+umjjz5S6dKlzVOGBQUFqXXr1pLuHBl/9tlnzaelJyUlqXfv3urQoQMjlwMAAAAAbOq+Ri/38vLShg0btGHDBotlJpMpW4vup556SgsXLtSgQYM0fPhwFS9eXBMmTFDHjh3Nfd59910lJCSoW7duiouLU+3atbV8+XLzHN2SNGfOHPXu3VuNGjWSk5OT2rVrp4kTJ2ZbTgAAYH8tWtg7geNYssTeCQDg0WEyDMOwdwhHEB8fLx8fH129evWhur6bDxjW4UNG5rFvWYd9K/PYt6zDvpV57FuZx34FAFmX2RrR6mu6/80wDFGzAwAAAACQvvsqumfPnq2KFSvKw8NDHh4eeuKJJ/Tdd99ldzYAAAAAABya1dd0jxs3ToMHD1bv3r1Vq1YtSdKmTZvUo0cPXb58Wf3798/2kAAAAAAAOCKri+5JkyZpypQpevXVV81tLVu2VPny5TV06FCKbgAAAAAA/j+rTy+/cOGCnn766TTtTz/9tC5cuJAtoQAAAAAAyAmsLrpLlSqlH3/8MU37/PnzVbp06WwJBQAAAABATmD16eXDhg3Tiy++qI0bN5qv6d68ebPWrFmTbjEOAAAAAMCjyuoj3e3atdO2bduUP39+LVq0SIsWLVL+/Pm1fft2tWnTxhYZAQAAAABwSFYf6ZakqlWr6vvvv8/uLAAAAAAA5Cj3NU83AAAAAAD4b5k+0u3k5CSTyXTPPiaTSbdv385yKAAAAAAAcoJMF90LFy7McFlERIQmTpyolJSUbAkFAAAAAEBOkOmiu1WrVmnajh49qvfff19LlixRx44dNXz48GwNBwAAAACAI7uva7rPnz+vrl27qmLFirp9+7b27NmjWbNmqWjRotmdDwAAAAAAh2VV0X316lW99957KlWqlA4ePKg1a9ZoyZIlqlChgq3yAQAAAADgsDJ9evnYsWM1ZswYBQYG6ocffkj3dHMAAAAAAPB/Ml10v//++/Lw8FCpUqU0a9YszZo1K91+CxYsyLZwAAAAAAA4skwX3a+++up/ThkGAAAAAAD+T6aL7pkzZ9owBgAAAAAAOc99jV4OAAAAAAD+G0U3AAAAAAA2QtENAAAAAICNUHQDAAAAAGAjFN0AAAAAANgIRTcAAAAAADZC0Q0AAAAAgI1QdAMAAAAAYCMU3QAAAAAA2AhFNwAAAAAANkLRDQAAAACAjThU0f3xxx/LZDKpX79+5rabN2+qV69eypcvn7y8vNSuXTtdvHjR4nFRUVFq3ry5cufOLX9/f73zzju6ffv2A04PAAAAAHjUOEzRvWPHDn311Vd64oknLNr79++vJUuW6KefftKGDRt0/vx5tW3b1rw8OTlZzZs3V2JiorZs2aJZs2Zp5syZCg8Pf9CbAAAAAAB4xDhE0X3t2jV17NhRX3/9tfLmzWtuv3r1qmbMmKFx48apYcOGqlq1qr799ltt2bJFW7dulSStXLlShw4d0vfff6/KlSuradOmGjFihCZPnqzExMQM13nr1i3Fx8db3AAAAAAAsIZDFN29evVS8+bN1bhxY4v2yMhIJSUlWbSXLVtWRYoUUUREhCQpIiJCFStWVEBAgLlPaGio4uPjdfDgwQzXOXr0aPn4+JhvhQsXzuatAgAAAADkdA990T1v3jzt2rVLo0ePTrMsOjpabm5u8vX1tWgPCAhQdHS0uc+/C+7U5anLMjJo0CBdvXrVfDt79mwWtwQAAAAA8KhxsXeAezl79qzeeustrVq1Srly5Xqg63Z3d5e7u/sDXScAAAAAIGd5qI90R0ZGKiYmRk8++aRcXFzk4uKiDRs2aOLEiXJxcVFAQIASExMVFxdn8biLFy8qMDBQkhQYGJhmNPPU+6l9AAAAAACwhYe66G7UqJH279+vPXv2mG/VqlVTx44dzf93dXXVmjVrzI85evSooqKiFBISIkkKCQnR/v37FRMTY+6zatUqeXt7q1y5cg98mwAAAAAAj46H+vTyPHnyqEKFChZtnp6eypcvn7m9S5cuGjBggPz8/OTt7a0+ffooJCRENWvWlCQ1adJE5cqVU6dOnTR27FhFR0frww8/VK9evTh9HAAAAABgUw910Z0Z48ePl5OTk9q1a6dbt24pNDRUX375pXm5s7Ozli5dqp49eyokJESenp4KCwvT8OHD7ZgaAAAAAPAocLiie/369Rb3c+XKpcmTJ2vy5MkZPqZo0aL6/fffbZwMAAAAOVGLFvZO4DiWLLF3AuDh81Bf0w0AAAAAgCOj6AYAAAAAwEYougEAAAAAsBGKbgAAAAAAbISiGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALARim4AAAAAAGzExd4BAAAAAOBR1KKFvRM4jiVL7J3g/nGkGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALARim4AAAAAAGyEohsAAAAAABuh6AYAAAAAwEYougEAAAAAsBGKbgAAAAAAbISiGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAbeeiL7tGjR+upp55Snjx55O/vr9atW+vo0aMWfW7evKlevXopX7588vLyUrt27XTx4kWLPlFRUWrevLly584tf39/vfPOO7p9+/aD3BQAAAAAwCPmoS+6N2zYoF69emnr1q1atWqVkpKS1KRJEyUkJJj79O/fX0uWLNFPP/2kDRs26Pz582rbtq15eXJyspo3b67ExERt2bJFs2bN0syZMxUeHm6PTQIAAAAAPCJc7B3gvyxfvtzi/syZM+Xv76/IyEjVrVtXV69e1YwZMzR37lw1bNhQkvTtt98qODhYW7duVc2aNbVy5UodOnRIq1evVkBAgCpXrqwRI0bovffe09ChQ+Xm5pZmvbdu3dKtW7fM9+Pj4227oQAAAACAHOehP9J9t6tXr0qS/Pz8JEmRkZFKSkpS48aNzX3Kli2rIkWKKCIiQpIUERGhihUrKiAgwNwnNDRU8fHxOnjwYLrrGT16tHx8fMy3woUL22qTAAAAAAA5lEMV3SkpKerXr59q1aqlChUqSJKio6Pl5uYmX19fi74BAQGKjo429/l3wZ26PHVZegYNGqSrV6+ab2fPns3mrQEAAAAA5HQP/enl/9arVy8dOHBAmzZtsvm63N3d5e7ubvP1AAAAAAByLoc50t27d28tXbpU69atU6FChcztgYGBSkxMVFxcnEX/ixcvKjAw0Nzn7tHMU++n9gEAAAAAILs99EW3YRjq3bu3Fi5cqLVr16p48eIWy6tWrSpXV1etWbPG3Hb06FFFRUUpJCREkhQSEqL9+/crJibG3GfVqlXy9vZWuXLlHsyGAAAAAAAeOQ/96eW9evXS3Llz9euvvypPnjzma7B9fHzk4eEhHx8fdenSRQMGDJCfn5+8vb3Vp08fhYSEqGbNmpKkJk2aqFy5curUqZPGjh2r6Ohoffjhh+rVqxenkAMAAAAAbOahL7qnTJkiSapfv75F+7fffqvXXntNkjR+/Hg5OTmpXbt2unXrlkJDQ/Xll1+a+zo7O2vp0qXq2bOnQkJC5OnpqbCwMA0fPvxBbQYAAAAA4BH00BfdhmH8Z59cuXJp8uTJmjx5coZ9ihYtqt9//z07owEAAAAAcE8P/TXdAAAAAAA4KopuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALARim4AAAAAAGyEohsAAAAAABuh6AYAAAAAwEYougEAAAAAsBGKbgAAAAAAbISiGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALARim4AAAAAAGyEohsAAAAAABuh6AYAAAAAwEYougEAAAAAsBGKbgAAAAAAbISiGwAAAAAAG6HoBgAAAADARii6AQAAAACwEYpuAAAAAABshKIbAAAAAAAboegGAAAAAMBGKLoBAAAAALCRR6ronjx5sooVK6ZcuXKpRo0a2r59u70jAQAAAABysEem6J4/f74GDBigIUOGaNeuXapUqZJCQ0MVExNj72gAAAAAgBzqkSm6x40bp65du6pz584qV66cpk6dqty5c+ubb76xdzQAAAAAQA7lYu8AD0JiYqIiIyM1aNAgc5uTk5MaN26siIiIdB9z69Yt3bp1y3z/6tWrkqT4+HjbhrVSUpK9EziWh+zH91Bj37IO+1bmsW9Zh30r89i3Mo/9yjrsW5nHvmUd9q3Mexj3rdTa0DCMe/Z7JIruy5cvKzk5WQEBARbtAQEBOnLkSLqPGT16tIYNG5amvXDhwjbJiAfDx8feCZBTsW/BVti3YAvsV7AV9i3YysO8b/3zzz/yuUfAR6Lovh+DBg3SgAEDzPdTUlIUGxurfPnyyWQy2THZwy8+Pl6FCxfW2bNn5e3tbe84yEHYt2Ar7FuwFfYt2Ar7FmyFfSvzDMPQP//8o6CgoHv2eySK7vz588vZ2VkXL160aL948aICAwPTfYy7u7vc3d0t2nx9fW0VMUfy9vbmFxU2wb4FW2Hfgq2wb8FW2LdgK+xbmXOvI9ypHomB1Nzc3FS1alWtWbPG3JaSkqI1a9YoJCTEjskAAAAAADnZI3GkW5IGDBigsLAwVatWTdWrV9eECROUkJCgzp072zsaAAAAACCHemSK7hdffFGXLl1SeHi4oqOjVblyZS1fvjzN4GrIOnd3dw0ZMiTN6flAVrFvwVbYt2Ar7FuwFfYt2Ar7VvYzGf81vjkAAAAAALgvj8Q13QAAAAAA2ANFNwAAAAAANkLRDQAAAACAjVB0AwAAAABgIxTdAAAAAADYCEU3AIdw8+ZNe0cAAAAArPbIzNMN2/ruu+80depUnTp1ShERESpatKgmTJig4sWLq1WrVvaOBweVkpKikSNHaurUqbp48aKOHTumEiVKaPDgwSpWrJi6dOli74hwUMnJyZo5c6bWrFmjmJgYpaSkWCxfu3atnZIhJ/nzzz914sQJ1a1bVx4eHjIMQyaTyd6xkEPcvHlTuXLlsncM5BD8XbQtjnTDaitWrNDVq1fN96dMmaIBAwaoWbNmiouLU3JysiTJ19dXEyZMsFNK5AQfffSRZs6cqbFjx8rNzc3cXqFCBU2fPt2OyeDo3nrrLb311ltKTk5WhQoVVKlSJYsbYI27P5xeuXJFjRs31uOPP65mzZrpwoULkqQuXbpo4MCB9oiIHCIlJUUjRozQY489Ji8vL508eVKSNHjwYM2YMcPO6eDI+LtoYwZgpZkzZxrly5c3zp49axiGYQQHBxsLFy40DMMwvLy8jBMnThiGYRj79+838uXLZ6+YyAFKlixprF692jAMy33r8OHDhq+vrz2jwcHly5fP+O233+wdAznEJ598YrE/derUyQgNDTXOnj1r8d61fPlyo1y5cvaKCQc0b94848yZM+b7w4YNM0qUKGF8//33hoeHh3nfmjdvnlGzZk17xUQOwN9F2+JIN6wWFhamYcOGKTQ0VJJ06tQpValSJU0/d3d3JSQkPOh4yEHOnTunUqVKpWlPSUlRUlKSHRIhp3Bzc0t33wLuxzPPPKO+ffuajzSuXLlSY8aMUaFChSz6lS5dWmfOnLFHRDioXLlyqW7dutq7d68kadasWZo2bZo6duwoZ2dnc79KlSrpyJEj9oqJHIC/i7ZF0Y370q5dOy1evFiSVLx4ce3ZsydNn+XLlys4OPgBJ0NOUq5cOf3xxx9p2n/++ed0v+gBMmvgwIH6/PPPZRiGvaMgB6hUqZK2b9+uRYsWSZISEhKUO3fuNP1iY2Pl7u7+gNPBkbVq1Urz5s3TK6+8Ikk6f/48X0bDJvi7aFsMpIb7VrJkSUnSgAED1KtXL928eVOGYWj79u364YcfNHr0aK67RZaEh4crLCxM586dU0pKihYsWKCjR49q9uzZWrp0qb3jwYFt2rRJ69at07Jly1S+fHm5urpaLF+wYIGdksFR+fn5acmSJZKkOnXqaPbs2RoxYoQkyWQyKSUlRWPHjlWDBg3sGRMOqGbNmtqwYYOk//syumjRohZ9+DIaWcXfRdui6EaWvfHGG/Lw8NCHH36o69ev6+WXX1ZQUJA+//xzdejQwd7x4MBatWqlJUuWaPjw4fL09FR4eLiefPJJLVmyRM8884y948GB+fr6qk2bNvaOgRxq7NixatSokXbu3KnExES9++67OnjwoGJjY7V582Z7x4MD8vPzk8SX0bAd/i7alsngHAJko+vXr+vatWvy9/e3dxQ4uNu3b2vUqFF6/fXX01wXCQAPu6tXr+qLL77Q3r17de3aNT355JPq1auXChYsaO9ocHB//PGHhg8fbrFvhYeHq0mTJvaOBiADFN3IsoYNG2rBggXy9fW1aI+Pj1fr1q2Z1w/3zcvLSwcOHFCxYsXsHQU51KVLl3T06FFJUpkyZVSgQAE7J0JOEBUVpcKFC6c7J3dUVJSKFClih1QA8N/4u2gbDKSGLFu/fr0SExPTtN+8eTPdQbCAzGrUqJH5OjYgOyUkJOj1119XwYIFVbduXdWtW1dBQUHq0qWLrl+/bu94cHDFixfXpUuX0rRfuXJFxYsXt0Mi5BQlSpTQlStX0rTHxcWpRIkSdkiEnIK/i7bFNd24b/v27TP//9ChQ4qOjjbfT05O1vLly/XYY4/ZIxpyiKZNm+r999/X/v37VbVqVXl6elosb9mypZ2SwdENGDBAGzZs0JIlS1SrVi1JdwaR6du3rwYOHKgpU6bYOSEcmWEY6R7lvnbtmnLlymWHRMgpTp8+reTk5DTtt27d0rlz5+yQCDkFfxdti9PLcd+cnJzMHyrS2408PDw0adIkvf766w86GnIIJ6eMT8YxmUzpfvAAMiN//vz6+eefVb9+fYv2devWqX379ukepQT+y4ABAyRJn3/+ubp27WoxbVhycrK2bdsmZ2dnBlOD1VKnaW3durVmzZolHx8f87Lk5GStWbNGq1atMp8WDFiLv4u2xZFu3LdTp07JMAyVKFFC27dvt7jmw83NTf7+/nJ2drZjQji6lJQUe0dADnX9+nUFBASkaff39+c0Oty33bt3S7rzRfT+/fvl5uZmXubm5qZKlSrp7bfftlc8OLDWrVtLuvOFc1hYmMUyV1dXFStWTJ999pkdkiGn4O+ibXGkG8BDa/bs2XrxxRfl7u5u0Z6YmKh58+bp1VdftVMyOLpGjRopX758mj17tvl03xs3bigsLEyxsbFavXq1nRPCkXXu3Fmff/65vL297R0FOUzx4sW1Y8cO5c+f395RkMPwd9G2KLpxXxYvXqymTZvK1dXVfMpTRrjuFvfL2dlZFy5cSDMF3ZUrV+Tv78/p5bhvBw4cUGhoqG7duqVKlSpJkvbu3atcuXJpxYoVKl++vJ0TAgDw4PB30bYounFfnJycFB0dLX9/f667hc04OTnp4sWLaaar2Lt3rxo0aKDY2Fg7JUNOcP36dc2ZM0dHjhyRJAUHB6tjx47y8PCwczI4orZt22rmzJny9vZW27Zt79l3wYIFDygVcoKJEyeqW7duypUrlyZOnHjPvn379n1AqZAT8XfRdrimG/fl39fact0tsluVKlVkMplkMpnUqFEjubj831tVcnKyTp06pWeffdaOCZET5M6dW127drV3DOQQPj4+5sFF/z3IFZBV48ePV8eOHZUrVy6NHz8+w34mk4miG1nC30Xb4Ug3gIfOsGHDzP8OHDhQXl5e5mVubm4qVqyY2rVrZzFIEfBfuCwGAID/w9/FB4eiG/flv05v+je+dcX9mjVrll588UXmtUW24LIYAAD+D38XHxyKbtyX4sWLZ6qfyWTSyZMnbZwGAAD7Sr0sJjN27dpl4zTISVLnf8+McePG2TAJgPvFNd24L6dOnbJ3BDwCnJyc7vkhlm9dcb+Yjg7ZLXUeZSC7pc7//l8y+6UPkFlxcXHy9fW1d4wcgSPdAB5aixYtsvgQkZSUpN27d2vWrFkaNmyYunTpYsd0cGRMRwcAwP8ZM2aMihUrphdffFGS9MILL+iXX35RwYIF9fvvv5unEcP9oejGfRkwYIBGjBghT0/P/zztiVOdkN3mzp2r+fPn69dff7V3FDgopqMDAOD/FC9eXHPmzNHTTz+tVatWqX379po/f75+/PFHRUVFaeXKlfaO6NA4vRz3Zffu3UpKSjL/PyOc6gRbqFmzprp162bvGHBATEcHW/Hz89OxY8eUP39+5c2b955///hSB9ZgDng8CNHR0SpcuLAkaenSpWrfvr2aNGmiYsWKqUaNGnZO5/gounFf1q1bl+7/AVu7ceOGJk6cqMcee8zeUeCAUq+73bNnj0JDQzOcjg6w1vjx45UnTx5J0oQJE+wbBjkKc8DjQcibN6/Onj2rwoULa/ny5froo48kSYZhcMlVNuD0cmSrs2fPSpL5mzIgK+4+WmQYhv755x95eHhozpw5zBmJ+8Z0dAAA/J/evXtr6dKlKl26tHbv3q3Tp0/Ly8tL8+bN09ixY5l1IYs40o0su337toYNG6aJEyfq2rVrkiQvLy/16dNHQ4YMkaurq50TwlHdfbTIyclJBQoUUI0aNXTu3Dn7hEKOEBYWZu8IyOGSk5O1cOFCHT58WJJUrlw5tWrVyuKSBuB+xcTE6OjRo5KkMmXKpBkUErDW+PHjVaxYMZ09e1Zjx441nwl24cIFvfnmm3ZO5/g40o0s69mzpxYsWKDhw4crJCREkhQREaGhQ4eqdevWmjJlip0TIqf4559/9MMPP2jGjBnauXMnpzvhviUnJ2v8+PHmAWISExMtlnPNLbLi4MGDatmypaKjo1WmTBlJ0rFjx1SgQAEtWbJEFSpUsHNCOKr4+Hj16tVL8+bNM/8NdHZ21osvvqjJkydz+jnwkKLoRpb5+Pho3rx5atq0qUX777//rpdeeklXr161UzLkFBs3btSMGTP0yy+/KCgoSG3btlW7du301FNP2TsaHFR4eLimT5+ugQMH6sMPP9QHH3yg06dPa9GiRQoPD1ffvn3tHREOLCQkRAUKFNCsWbOUN29eSdLff/+t1157TZcuXdKWLVvsnBCO6sUXX9Tu3bs1adIkiwMdb731lipXrqx58+bZOSEc2fHjx7Vu3TrFxMQoJSXFYll4eLidUuUMFN3IMn9/f23YsEHBwcEW7YcPH1bdunV16dIlOyWDI4uOjtbMmTM1Y8YMxcfHq3379po6dar27t2rcuXK2TseHFzJkiU1ceJENW/eXHny5NGePXvMbVu3btXcuXPtHREOzMPDQzt37lT58uUt2g8cOKCnnnpKN27csFMyODpPT0+tWLFCtWvXtmj/448/9OyzzyohIcFOyeDovv76a/Xs2VP58+dXYGCgxZg6JpOJa7qzyMneAeD4evfurREjRujWrVvmtlu3bmnkyJHq3bu3HZPBUbVo0UJlypTRvn37NGHCBJ0/f16TJk2ydyzkINHR0apYsaKkO2NQpJ6R89xzz+m3336zZzTkAI8//rguXryYpj0mJkalSpWyQyLkFPny5Uv3FHIfHx/zWRXA/fjoo480cuRIRUdHa8+ePdq9e7f5RsGddYzmgfty9zyRq1evVqFChVSpUiVJ0t69e5WYmKhGjRrZIx4c3LJly9S3b1/17NlTpUuXtncc5ECFChXShQsXVKRIEZUsWVIrV67Uk08+qR07dsjd3d3e8eCA4uPjzf8fPXq0+vbtq6FDh6pmzZqSpK1bt2r48OEaM2aMvSIiB/jwww81YMAAfffddwoMDJR050vEd955R4MHD7ZzOjiyv//+Wy+88IK9Y+RYFN24L3d/y3r3vLZMGYas2LRpk2bMmKGqVasqODhYnTp1UocOHewdCzlImzZttGbNGtWoUUN9+vTRK6+8ohkzZigqKkr9+/e3dzw4IF9f3zRTHLZv397clno1X4sWLRgEElapUqWKxb51/PhxFSlSREWKFJEkRUVFyd3dXZcuXVL37t3tFRMO7oUXXtDKlSvVo0cPe0fJkbimG8BDKyEhQfPnz9c333yj7du3Kzk5WePGjdPrr7+uPHny2DsecpCIiAhFRESodOnSatGihb3jwAFt2LAh033r1atnwyTIaYYNG5bpvkOGDLFhEuRko0eP1rhx49S8eXNVrFgxzZS/DDCaNRTdABzC0aNHNWPGDH333XeKi4vTM888o8WLF9s7FgAAgMMrXrx4hstMJpNOnjz5ANPkPBTduC9PPvmk1qxZo7x586Y57eluDL6A7JScnKwlS5bom2++oejGfZs1a5by58+v5s2bS5LeffddTZs2TeXKldMPP/ygokWL2jkhcoLr16+nOw/8E088YadEAAB74Jpu3JdWrVqZBxtq3bq1fcPgkeLs7KzWrVuz3yFLRo0apSlTpki6c2r5F198oQkTJmjp0qXq37+/FixYYOeEcGSXLl1S586dtWzZsnSXc0037ldycrLGjx+vH3/8Md0vdGJjY+2UDDlFYmKiTp06pZIlS8rFhVIxu3CkGwDwyMmdO7eOHDmiIkWK6L333tOFCxc0e/ZsHTx4UPXr19elS5fsHREOrGPHjjpz5owmTJig+vXra+HChbp48aI++ugjffbZZ+YzLABrhYeHa/r06Ro4cKA+/PBDffDBBzp9+rQWLVqk8PBwrrvFfbt+/br69OmjWbNmSZKOHTumEiVKqE+fPnrsscf0/vvv2zmhY2OebmTZ2bNn9ddff5nvb9++Xf369dO0adPsmAoAMubl5aUrV65IklauXKlnnnlGkpQrVy7duHHDntGQA6xdu1bjxo1TtWrV5OTkpKJFi+qVV17R2LFjNXr0aHvHgwObM2eOvv76aw0cOFAuLi566aWXNH36dIWHh2vr1q32jgcHNmjQIO3du1fr169Xrly5zO2NGzfW/Pnz7ZgsZ6DoRpa9/PLLWrdunaQ7c0U2btxY27dv1wcffKDhw4fbOR0ApPXMM8/ojTfe0BtvvKFjx46pWbNmkqSDBw+qWLFi9g0Hh5eQkCB/f39JUt68ec1nTlSsWJFxTpAl0dHRqlixoqQ7Xx5evXpVkvTcc8/pt99+s2c0OLhFixbpiy++UO3atS3GaipfvrxOnDhhx2Q5A0U3suzAgQOqXr26JOnHH39UxYoVtWXLFs2ZM0czZ860bzgASMfkyZMVEhKiS5cu6ZdfflG+fPkkSZGRkXrppZfsnA6OrkyZMjp69KgkqVKlSvrqq6907tw5TZ06VQULFrRzOjiyQoUK6cKFC5KkkiVLauXKlZKkHTt2mMfaAe7HpUuXzF8W/ltCQsI9B0xG5nB1PLIsKSnJ/Ea/evVqtWzZUpJUtmxZ8x8GAHiY+Pr66osvvkjTbs18uEBG3nrrLfPfvyFDhujZZ5/VnDlz5ObmxpfRyJI2bdpozZo1qlGjhvr06aNXXnlFM2bMUFRUlPr372/veHBg1apV02+//aY+ffpIkrnQnj59ukJCQuwZLUdgIDVkWY0aNdSgQQM1b95cTZo00datW1WpUiVt3bpVzz//vMX13gBgL/v27VOFChXk5OSkffv23bMvUzohO12/ft08cF/+/PntHQc5yNatW7VlyxaVLl1aLVq0sHccOLBNmzapadOmeuWVVzRz5kx1795dhw4d0pYtW7RhwwZVrVrV3hEdGkU3smz9+vVq06aN4uPjFRYWpm+++UaS9L///U9Hjhxh6h0ADwUnJydFR0fL399fTk5OMplM+vefwNT7JpOJKZ0APJQ2btyop59+Os1UTrdv39aWLVtUt25dOyVDTnDixAl9/PHH2rt3r65du6Ynn3xS7733nnkcAdw/im5ki+TkZMXHxytv3rzmttOnTyt37tzpXh8CAA/amTNnVKRIEZlMJp05c+aefYsWLfqAUiGnGDBggEaMGCFPT08NGDDgnn3HjRv3gFIhp3F2dtaFCxfSfLa6cuWK/P39+cIQeEhxTTey7MaNGzIMw1xwnzlzRgsXLlRwcLBCQ0PtnA4A7vh3IU1Rjey2e/duHTlyRFWqVNHu3bsz7MeARMiK1LNx7nblyhV5enraIRFykpSUFP3555+KiYlRSkqKxTLOosgajnQjy5o0aaK2bduqR48eiouLU9myZeXq6qrLly9r3Lhx6tmzp70jAoAWL16c6b6pA0IC1rj7KOSLL76oiRMnKiAgwM7J4Ojatm0rSfr111/17LPPWoxUnpycrH379qlMmTJavny5vSLCwW3dulUvv/yyzpw5o7vLQy67yjqOdCPLdu3apfHjx0uSfv75ZwUEBGj37t365ZdfFB4eTtEN4KHQunXrTPXjwwXu190fVJctW6aEhAQ7pUFO4uPjI+nOPpYnTx55eHiYl7m5ualmzZrq2rWrveIhB+jRo4d5BPOCBQtyVk42o+hGll2/fl158uSRJK1cuVJt27aVk5OTatas+Z/XTQLAg3L3qXKArXEyIbLLt99+K0kqVqyY3n77bU4lR7Y7fvy4fv75Z5UqVcreUXIkJ3sHgOMrVaqUFi1apLNnz2rFihVq0qSJJCkmJkbe3t52TgcAwINhMpnSHB3iaBGy05AhQyi4YRM1atTQn3/+ae8YORZHupFl4eHhevnll9W/f381bNhQISEhku4c9a5SpYqd0wFA+hISErRhwwZFRUUpMTHRYlnfvn3tlAqOzDAMvfbaa+brbW/evKkePXqkKZKYShPWePLJJ7VmzRrlzZtXVapUuecXObt27XqAyeDo9u3bZ/5/nz59NHDgQEVHR6tixYpydXW16PvEE0886Hg5CgOpIVtER0frwoULqlSpkpyc7pxAsX37dnl7e6ts2bJ2TgcAlnbv3q1mzZrp+vXrSkhIkJ+fny5fvmye5vDkyZP2jggH1Llz50z1Sz1VGMiMYcOG6Z133lHu3Lk1bNiwe/YdMmTIA0qFnMDJyUkmkynDS2FSlzHWSdZRdCPb/Pnnnzpx4oTq1q0rDw+PDKe1AAB7q1+/vh5//HFNnTpVPj4+2rt3r1xdXfXKK6/orbfeMo8UDABATmXN2EtMtZk1FN3IsitXrqh9+/Zat26dTCaTjh8/rhIlSuj1119X3rx59dlnn9k7IgBY8PX11bZt21SmTBn5+voqIiJCwcHB2rZtm8LCwnTkyBF7RwSADEVGRurw4cOSpPLly3M5H/CQYyA1ZFn//v3l6uqqqKgo5c6d29z+4osvMl8kgIeSq6ur+VIYf39/RUVFSbozLc/Zs2ftGQ0AMhQTE6OGDRvqqaeeUt++fdW3b19VrVpVjRo10qVLl+wdDw7uu+++U61atRQUFGQ+Cj5hwgT9+uuvdk7m+Ci6kWUrV67UmDFjVKhQIYv20qVLM2UYgIdSlSpVtGPHDklSvXr1FB4erjlz5qhfv36qUKGCndMBQPr69Omjf/75RwcPHlRsbKxiY2N14MABxcfHMwAkrLJixQpdvXrVfH/KlCkaMGCAmjVrpri4OPM13L6+vpowYYKdUuYcFN3IsoSEBIsj3KliY2PNI7gCwMNk1KhRKliwoCRp5MiRyps3r3r27KlLly5p2rRpdk4HAOlbvny5vvzySwUHB5vbypUrp8mTJ2vZsmV2TAZHEx0drVq1aumvv/6SJE2aNElff/21PvjgAzk7O5v7VatWTfv377dXzByDKcOQZXXq1NHs2bM1YsQISXdGOkxJSdHYsWPVoEEDO6cDgLSqVatm/r+/vz+XwgBwCCkpKWmmcpLuXDKTkpJih0RwVGFhYfLy8lJoaKgOHjyoU6dOpTs2gLu7uxISEuyQMGeh6EaWjR07Vo0aNdLOnTuVmJiod99913za0+bNm+0dDwAAIEdo2LCh3nrrLf3www8KCgqSJJ07d079+/dXo0aN7JwOjqZdu3aqXLmyJKl48eLas2dPmlHKly9fbnFmBe4PRTeyrEKFCjp27Ji++OIL5cmTR9euXVPbtm3Vq1cv8+mbAPAwKV68+D2nNGSebgAPoy+++EItW7ZUsWLFVLhwYUnS2bNnVaFCBX3//fd2TgdHVLJkSUnSgAED1KtXL928eVOGYWj79u364YcfNHr0aE2fPt3OKR0fU4YBAB45n3/+ucX9pKQk7d69W8uXL9c777yj999/307JAODeDMPQ6tWrzVMbBgcHq3HjxnZOhZxgzpw5Gjp0qE6cOCFJCgoK0rBhw9SlSxc7J3N8FN3Ism+//VZeXl564YUXLNp/+uknXb9+XWFhYXZKBgDWmTx5snbu3Klvv/3W3lEAAHggbt++rblz5yo0NFQBAQG6fv26rl27Jn9/f3tHyzEoupFljz/+uL766qs0g6Zt2LBB3bp109GjR+2UDACsc/LkSVWuXFnx8fH2jgIAkqSJEydmui/ThuF+5c6dW4cPH05zTTeyB9d0I8uioqJUvHjxNO1FixZVVFSUHRIBwP35+eef5efnZ+8YAGA2fvz4TPUzmUwU3bhv1atX1+7duym6bYSiG1nm7++vffv2qVixYhbte/fuVb58+ewTCgDuoUqVKhYDqRmGoejoaF26dElffvmlHZMBgKVTp07ZOwIeAW+++aYGDhyov/76S1WrVpWnp6fF8ieeeMJOyXIGim5k2UsvvaS+ffsqT548qlu3rqQ7p5a/9dZb6tChg53TAUBarVq1sii6nZycVKBAAdWvX19ly5a1YzIAyJzUK0TvNRMDkFmpn9n/fbaEyWSSYRgymUxKTk62V7QcgWu6kWWJiYnq1KmTfvrpJ7m43PkeJyUlRa+++qqmTp0qNzc3OycEAADIGWbMmKHx48fr+PHjkqTSpUurX79+euONN+ycDI7szJkz91zOaedZQ9GNbHP8+HHt2bNHHh4eqlixIr+cAB5azs7OunDhQpqRWa9cuSJ/f3++0QfwUAoPD9e4cePUp08fhYSESJIiIiL0xRdfqH///ho+fLidEwJID0U3AOCR4+TkpOjo6DRF9/nz51WyZEnduHHDTskAIGMFChTQxIkT9dJLL1m0//DDD+rTp48uX75sp2TICY4ePapJkybp8OHDku7MAd+nTx+VKVPGzskcH9d0I8vatWun6tWr67333rNoHzt2rHbs2KGffvrJTskAwFLq1Dsmk0nTp0+Xl5eXeVlycrI2btzINd0AHlpJSUmqVq1amvaqVavq9u3bdkiEnOKXX35Rhw4dVK1aNfNZFFu3blWFChU0b948tWvXzs4JHRtHupFlBQoU0Nq1a1WxYkWL9v3796tx48a6ePGinZIBgKXU6Q3PnDmjQoUKydnZ2bzMzc1NxYoV0/Dhw1WjRg17RQSADPXp00eurq4aN26cRfvbb7+tGzduaPLkyXZKBkdXsmRJdezYMc0lCkOGDNH333+vEydO2ClZzkDRjSzz8PDQnj170px6cuTIEVWpUoXTNAE8dBo0aKAFCxYob9689o4CAJnWp08fzZ49W4ULF1bNmjUlSdu2bVNUVJReffVVubq6mvveXZgD95I7d27t27dPpUqVsmg/fvy4KlWqpOvXr9spWc7A6eXIsooVK2r+/PkKDw+3aJ83b57KlStnp1QAkLF169bZOwIAWO3AgQN68sknJcl85DF//vzKnz+/Dhw4YO7HNGKwVv369fXHH3+kKbo3bdqkOnXq2ClVzkHRjSwbPHiw2rZtqxMnTqhhw4aSpDVr1mju3Ln6+eef7ZwOANJiLAoAjogvDGErLVu21HvvvafIyEjzWRRbt27VTz/9pGHDhmnx4sUWfWEdTi9Htvjtt980atQo85RhlSpV0pAhQ+Tn56cKFSrYOx4AWGAsCgCO6NKlSypQoEC6y/bv35/mPQ3ILCcnp0z1M5lMTKt5HzL36gL/oXnz5tq8ebMSEhJ08uRJtW/fXm+//bYqVapk72gAkMa1a9fk5uaWpt3V1VXx8fF2SAQA/61ixYr67bff0rR/+umnql69uh0SIadISUnJ1I2C+/5QdCPbbNy4UWFhYQoKCtJnn32mhg0bauvWrfaOBQBppI5FcTfGogDwMBswYIDatWunnj176saNGzp37pwaNWqksWPHau7cufaOByADXNONLImOjtbMmTM1Y8YMxcfHq3379rp165YWLVrEB1cADy3GogDgiN59910988wz6tSpk5544gnFxsaqRo0a2rdvnwIDA+0dDw5ux44dWrdunWJiYpSSkmKxjNHws4aiG/etRYsW2rhxo5o3b64JEybo2WeflbOzs6ZOnWrvaABwTy1atNCiRYs0atQo/fzzz+axKNauXSs/Pz97xwOADJUqVUoVKlTQL7/8Ikl68cUXKbiRZaNGjdKHH36oMmXKKCAgwGIEfEbDzzoGUsN9c3FxUd++fdWzZ0+VLl3a3O7q6qq9e/dypBuAw4iPj9cPP/ygGTNmKDIykmvWADyUNm/erFdeeUV+fn76/vvvtXnzZg0YMEBNmzbV1KlTlTdvXntHhIMKCAjQmDFj9Nprr9k7So7ENd24b5s2bdI///yjqlWrqkaNGvriiy90+fJle8cCgExjLAoAjqRhw4Z68cUXtXXrVgUHB+uNN97Q7t27FRUVxcjlyBInJyfVqlXL3jFyLI50I8sSEhI0f/58ffPNN9q+fbuSk5M1btw4vf7668qTJ4+94wGAhfTGopg6dSpn6AB46G3YsEH16tVL056SkqKRI0dq8ODBdkiFnGDs2LE6f/68JkyYYO8oORJFN7LV0aNHNWPGDH333XeKi4vTM888o8WLF9s7FgBIshyLomPHjuaxKLgsBsDDrFmzZvrhhx/k4+MjSfr444/Vo0cP+fr6SpKuXLmiOnXq6NChQ3ZMCUeWkpKi5s2b69ixYypXrpxcXV0tli9YsMBOyXIGim7YRHJyspYsWaJvvvmGohvAQ4OxKAA4ImdnZ124cEH+/v6SJG9vb+3Zs0clSpSQJF28eFFBQUGMR4H71rt3b02fPl0NGjRIM5CaJH377bd2SpYzMHo5bMLZ2VmtW7dW69at7R0FAMw2bdqkGTNmqGrVqgoODlanTp3UoUMHe8cCgHu6+xgZx8yQ3WbNmqVffvlFzZs3t3eUHImB1AAAj4yaNWvq66+/1oULF9S9e3fNmzdPQUFBSklJ0apVq/TPP//YOyIAAA+cn5+fSpYsae8YORZFNwDgkePp6anXX39dmzZt0v79+zVw4EB9/PHH8vf3V8uWLe0dDwAsmEymNKf7MncystPQoUM1ZMgQXb9+3d5RciSu6QYAQIxFAeDh5eTkpKZNm8rd3V2StGTJEjVs2FCenp6SpFu3bmn58uVc0437VqVKFZ04cUKGYahYsWJpBlLbtWuXnZLlDBTdAAAAwEOsc+fOmerHYFe4X8OGDbvn8iFDhjygJDkTRTcAAAAAADbC6OUAAAAAAEVGRurw4cOSpPLly6tKlSp2TpQzUHQDAAAAwCMsJiZGHTp00Pr16+Xr6ytJiouLU4MGDTRv3jwVKFDAvgEdHKOXAwAAAMAjrE+fPvrnn3908OBBxcbGKjY2VgcOHFB8fLz69u1r73gOj2u6AQAAAOAR5uPjo9WrV+upp56yaN++fbuaNGmiuLg4+wTLITjSDQAAAACPsJSUlDTThEmSq6urUlJS7JAoZ6HoBgAAAIBHWMOGDfXWW2/p/Pnz5rZz586pf//+atSokR2T5QycXg4AAAAAj7CzZ8+qZcuWOnjwoAoXLmxuq1ChghYvXqxChQrZOaFjo+gGAAAAgEecYRhavXq1jhw5IkkKDg5W48aN7ZwqZ6DoBgAAAIBH0Nq1a9W7d29t3bpV3t7eFsuuXr2qp59+WlOnTlWdOnXslDBn4JpuAAAAAHgETZgwQV27dk1TcEt3RjTv3r27xo0bZ4dkOQtFNwAAAAA8gvbu3atnn302w+VNmjRRZGTkA0yUM1F0AwAAAMAj6OLFi+lOFZbKxcVFly5deoCJciaKbgAAAAB4BD322GM6cOBAhsv37dunggULPsBEORNFNwAAAAA8gpo1a6bBgwfr5s2baZbduHFDQ4YM0XPPPWeHZDkLo5cDAAAAwCPo4sWLevLJJ+Xs7KzevXurTJkykqQjR45o8uTJSk5O1q5duxQQEGDnpI6NohsAAAAAHlFnzpxRz549tWLFCqWWhiaTSaGhoZo8ebKKFy9u54SOj6IbAAAAAB5xf//9t/78808ZhqHSpUsrb9689o6UY1B0AwAAAABgIwykBgAAAACAjVB0AwAAAABgIxTdAAAAAADYCEU3AABIV2JiokaNGqXDhw/bOwoAAA6LohsAAKRr4MCB2r9/v8qWLftA1rd+/XqZTCbFxcU9kPUBAPAgUHQDAOCAoqOj1adPH5UoUULu7u4qXLiwWrRooTVr1mTq8TNnzpSvr2+Gy3/88UcdPHhQs2bNkslkyqbU9/b000/rwoUL8vHxeSDrAwDgQXCxdwAAAGCd06dPq1atWvL19dUnn3yiihUrKikpSStWrFCvXr105MiRLK+jffv2at++fTakzZykpCS5ubkpMDDwga0TAIAHgSPdAAA4mDfffFMmk0nbt29Xu3bt9Pjjj6t8+fIaMGCAtm7dKkkaN26cKlasKE9PTxUuXFhvvvmmrl27JunOadydO3fW1atXZTKZZDKZNHToUEnSrVu39Pbbb+uxxx6Tp6enatSoofXr11us/+uvv1bhwoWVO3dutWnTRuPGjUtz1HzKlCkqWbKk3NzcVKZMGX333XcWy00mk6ZMmaKWLVvK09NTI0eOTPf08k2bNqlOnTry8PBQ4cKF1bdvXyUkJGTr6wkAgC1RdAMA4EBiY2O1fPly9erVS56enmmWpxa/Tk5OmjhxovkU8bVr1+rdd9+VdOc07gkTJsjb21sXLlzQhQsX9Pbbb0uSevfurYiICM2bN0/79u3TCy+8oGeffVbHjx+XJG3evFk9evTQW2+9pT179uiZZ57RyJEjLTIsXLhQb731lgYOHKgDBw6oe/fu6ty5s9atW2fRb+jQoWrTpo3279+v119/Pc22nDhxQs8++6zatWunffv2af78+dq0aZN69+6d5dcRAIAHxWQYhmHvEAAAIHO2b9+uGjVqaMGCBWrTpk2mH/fzzz+rR48eunz5sqQ713T369fP4qhyVFSUSpQooaioKAUFBZnbGzdurOrVq2vUqFHq0KGDrl27pqVLl5qXv/LKK1q6dKn5uWrVqqXy5ctr2rRp5j7t27dXQkKCfvvtN0l3jnT369dP48ePN/dZv369GjRooL///lu+vr5644035OzsrK+++srcZ9OmTapXr54SEhKUK1euTG8/AAD2wpFuAAAcSGa/K1+9erUaNWqkxx57THny5FGnTp105coVXb9+PcPH7N+/X8nJyXr88cfl5eVlvm3YsEEnTpyQJB09elTVq1e3eNzd9w8fPqxatWpZtNWqVSvN1GPVqlW75zbs3btXM2fOtMgSGhqqlJQUnTp16j9fAwAAHgYMpAYAgAMpXbq0TCbTPQdLO336tJ577jn17NlTI0eOlJ+fnzZt2qQuXbooMTFRuXPnTvdx165dk7OzsyIjI+Xs7GyxzMvLK1u3Q1K6p8ffnad79+7q27dvmmVFihTJ9jwAANgCRTcAAA7Ez89PoaGhmjx5svr27ZumcI2Li1NkZKRSUlL02WefycnpzkltP/74o0U/Nzc3JScnW7RVqVJFycnJiomJUZ06ddJdf5kyZbRjxw6LtrvvBwcHa/PmzQoLCzO3bd68WeXKlbNqW5988kkdOnRIpUqVsupxAPD/2Lvz8JjO94/jn0kkEYkkQhYqtlD7VorYiliK2lu0aqtSSrSirfq2VXQJ2qLU0kVtpSiqpbUvUVupnaIoYotYmgQhSM7vD1fm15HQSHJMlvfruuaSec4z57nPzBkz95xnATITupcDAJDFTJo0SQkJCapRo4YWLVqko0eP6tChQ5owYYKCgoJUsmRJ3b59WxMnTtTff/+t2bNna+rUqTb7KFasmK5du6a1a9fq0qVLiouL0+OPP64uXbqoW7duWrx4sU6cOKHt27crLCzMOhY7JCREv/76q8aOHaujR4/qyy+/1PLly23W8n7zzTc1Y8YMTZkyRUePHtXYsWO1ePFi62RtqTVkyBBt2bJFAwYM0J49e3T06FH99NNPTKQGAMhSSLoBAMhiSpQooV27dqlhw4YaPHiwKlSooCZNmmjt2rWaMmWKKleurLFjx2r06NGqUKGC5syZo7CwMJt91K5dW3379lWnTp3k4+OjMWPGSJKmT5+ubt26afDgwSpdurTatm2rHTt2WLtz16lTR1OnTtXYsWNVuXJlrVixQoMGDbKZ1Kxt27b6/PPP9emnn6p8+fL68ssvNX36dDVo0OChjrNSpUoKDw/XX3/9pXr16qlq1aoaNmyYzSRvAABkdsxeDgAA0qV37946fPiwfvvtN3uHAgBApsOYbgAA8FA+/fRTNWnSRG5ublq+fLlmzpypyZMn2zssAAAyJa50AwCAh9KxY0dt2LBBV69eVYkSJRQSEqK+ffvaOywAADIlkm4AAAAAAEzCRGoAAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAAAAATELSDQAAAACASUi6AQAAAAAwCUk3AAAAAAAmIekGAAAAAMAkJN0AAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAAAAATELSDQAAAACASUi6AQAAAAAwCUk3ANzH7du3NWrUKC1dutTeoSCL+/nnnzV69Gjdvn3b3qEAAIBHjKQbAO7j7bff1jfffKNatWrZO5QUbdiwQRaLRRs2bPjPuidPnpTFYtGMGTNMjyu1GjRooAYNGtg7DNP98ccf6ty5s0qWLCknJye7xTFjxgxZLBadPHnykbf96quvqkmTJo+8XXtJer99+umn/1l3+PDhslgspsf0qNpJq5TOz9T+H/Ew/xc+DIvFouHDh2foPu9Vq1YtvfXWW6a2AcD+SLoBZGtJX+SSbrly5dJjjz2mHj166OzZs/d93E8//aTvvvtOK1askI+PzyOMOLnJkyenOlmeO3euxo8fb2o8uCs1z3V0dLQ6duyoUaNGqUOHDo8msEzmxIkT+uabb/S///3PWpaUlN7vNmrUKDtGjJzk119/NT2xfpAhQ4Zo0qRJioyMtFsMAMyXy94BAMCjMHLkSBUvXlw3b97Utm3bNGPGDG3atEkHDhxQ7ty5k9U/efKkli9frpIlS9ohWluTJ09WgQIF1KNHD5vy+vXr68aNG3J2draWzZ07VwcOHNDrr79uU7do0aK6ceOGXa+0Zjf3e67/bc+ePXr33Xf10ksvPbrA7qNr167q3LmzXFxcHmm7n3/+uYoXL66GDRsm2/b888+rRYsWycqrVq36KEJDJrdq1SrT2/j11181adKkFBPvGzduKFcuc78qt2nTRh4eHpo8ebJGjhxpalsA7IekG0CO0Lx5c1WvXl2S9PLLL6tAgQIaPXq0fv75Z3Xs2DFZ/ddee+1Rh5hMXFyc8uTJc9/tDg4OKf5gkBKLxZLqusg4maEL/fXr1+Xm5iZHR0c5Ojo+0rZv376tOXPmqG/fviluf+KJJ/Tiiy8+0piQdfz7B0V7eBT/Zzo4OOjZZ5/VrFmzNGLEiEw9BABA2tG9HECOVK9ePUnS8ePHbcoPHz6sZ599Vt7e3sqdO7eqV6+un3/+2aZOUpf1jRs36pVXXlH+/Pnl4eGhbt266Z9//rGp+9NPP6lly5YqVKiQXFxcFBgYqA8++EAJCQk29Ro0aKAKFSpo586dql+/vvLkyaP//e9/KlasmA4ePKjw8HBr19ukJO7ecYwNGjTQL7/8olOnTlnrFitWTNL9x3SvW7dO9erVk5ubm7y8vNSmTRsdOnTIpk7SWNBjx46pR48e8vLykqenp3r27Km4uLhUPd9fffWVAgMD5erqqho1aui3335LsV58fLzef/99lSxZUi4uLgoICNBbb72l+Ph4m3qrV69W3bp15eXlJXd3d5UuXdqm+/KDfPfdd6pRo4by5MmjfPnyqX79+jZX1FLzmj3ouX6Y47hx44YGDhyoAgUKKG/evGrdurXOnj2b4ljS3bt3q3nz5vLw8JC7u7uCg4O1bds2mzpJ52Z4eLheffVV+fr6qnDhwjbb7h3TvXz5cus5kDdvXrVs2VIHDx60qRMZGamePXuqcOHCcnFxUcGCBdWmTZv/HB++adMmXbp0SY0bN35gvQcpVqyYnnnmGW3atEk1atRQ7ty5VaJECc2aNcum3u3btzVixAiVKlVKuXPnVv78+VW3bl2tXr3apt7DvMc3bdqkgQMHysfHR15eXnrllVd069YtRUdHq1u3bsqXL5/y5cunt956S4ZhpBj/uHHjVLRoUbm6uuqpp57SgQMHUnXc3333napVqyZXV1d5e3urc+fOOn36dKoeu2nTJj355JPKnTu3AgMD9eWXX2ZoOwsXLrSeZ/f68ssvZbFYrMe5b98+9ejRQyVKlFDu3Lnl7++vl156SZcvX/7P40jpR6szZ86obdu2cnNzk6+vrwYNGpTsfSVJv/32m5577jkVKVLE+h4cNGiQbty4Ya3To0cPTZo0SZJshjckSe/7cPPmzQoNDZWPj4/c3NzUrl07Xbx4MVmsTZo00alTp7Rnz57/fE4AZE1c6QaQIyUlC/ny5bOWHTx4UHXq1NFjjz2mt99+W25ublqwYIHatm2rRYsWqV27djb7GDBggLy8vDR8+HAdOXJEU6ZM0alTp6zJsHT3y5e7u7tCQ0Pl7u6udevWadiwYYqNjdUnn3xis7/Lly+refPm6ty5s1588UX5+fmpQYMGCgkJkbu7u9555x1Jkp+fX4rH9M477ygmJkZnzpzRuHHjJEnu7u73fQ7WrFmj5s2bq0SJEho+fLhu3LihiRMnqk6dOtq1a5dNEilJHTt2VPHixRUWFqZdu3bpm2++ka+vr0aPHv3A53ratGl65ZVXVLt2bb3++uv6+++/1bp1a3l7eysgIMBaLzExUa1bt9amTZvUp08flS1bVvv379e4ceP0119/acmSJdbX6ZlnnlGlSpU0cuRIubi46NixY9q8efMD45CkESNGaPjw4apdu7ZGjhwpZ2dn/f7771q3bp2aNm0qKXWv2YOe69Qeh3T3S/+CBQvUtWtX1apVS+Hh4WrZsmWyuA8ePKh69erJw8NDb731lpycnPTll1+qQYMGCg8PV82aNW3qv/rqq/Lx8dGwYcN0/fr1+z4fs2fPVvfu3dWsWTONHj1acXFxmjJliurWravdu3dbz4EOHTro4MGDCgkJUbFixRQVFaXVq1crIiIi2Xnyb1u2bJHFYrlvd/G4uDhdunQpWbmXl5dNt95jx47p2WefVa9evdS9e3d9++236tGjh6pVq6by5ctLuvvjUFhYmF5++WXVqFFDsbGx+uOPP7Rr1y7rJG4P+x4PCQmRv7+/RowYoW3btumrr76Sl5eXtmzZoiJFiujjjz/Wr7/+qk8++UQVKlRQt27dbB4/a9YsXb16Vf3799fNmzf1+eefq1GjRtq/f/9938eS9NFHH+m9995Tx44d9fLLL+vixYuaOHGi6tevr927d8vLy+u+j92/f7+aNm0qHx8fDR8+XHfu3NH777+fYntpbadly5Zyd3fXggUL9NRTT9lsmz9/vsqXL68KFSpIuvsD2d9//62ePXvK399fBw8e1FdffaWDBw9q27ZtD3Vl98aNGwoODlZERIQGDhyoQoUKafbs2Vq3bl2yuj/88IPi4uLUr18/5c+fX9u3b9fEiRN15swZ/fDDD5KkV155RefOndPq1as1e/bs/2z/Yd+HISEhypcvn95//32dPHlS48eP14ABAzR//nybetWqVZMkbd68maEVQHZlAEA2Nn36dEOSsWbNGuPixYvG6dOnjYULFxo+Pj6Gi4uLcfr0aWvd4OBgo2LFisbNmzetZYmJiUbt2rWNUqVKJdtntWrVjFu3blnLx4wZY0gyfvrpJ2tZXFxcspheeeUVI0+ePDbtPPXUU4YkY+rUqcnqly9f3njqqaeSla9fv96QZKxfv95a1rJlS6No0aLJ6p44ccKQZEyfPt1aVqVKFcPX19e4fPmytWzv3r2Gg4OD0a1bN2vZ+++/b0gyXnrpJZt9tmvXzsifP3+ytv7t1q1bhq+vr1GlShUjPj7eWv7VV18ZkmyOa/bs2YaDg4Px22+/2exj6tSphiRj8+bNhmEYxrhx4wxJxsWLFx/Y9r2OHj1qODg4GO3atTMSEhJstiUmJlr/Tu1rdr/nOrXHsXPnTkOS8frrr9vU69GjhyHJeP/9961lbdu2NZydnY3jx49by86dO2fkzZvXqF+/vrUs6dysW7eucefOHZv9Jm07ceKEYRiGcfXqVcPLy8vo3bu3Tb3IyEjD09PTWv7PP/8YkoxPPvkk2bH+lxdffDHFcyTpfLzfbevWrda6RYsWNSQZGzdutJZFRUUZLi4uxuDBg61llStXNlq2bPnAeB72Pd6sWTObcyMoKMiwWCxG3759rWV37twxChcubHMuJx2fq6urcebMGWv577//bkgyBg0aZC1Len8lOXnypOHo6Gh89NFHNrHv37/fyJUrV7Lye7Vt29bInTu3cerUKWvZn3/+aTg6OmZoO88//7zh6+trc56dP3/ecHBwMEaOHGktS+n99P333yd7Te89Pw3j7v+L/35ex48fb0gyFixYYC27fv26UbJkyWT/F6bUblhYmGGxWGyem/79+9s8L/+W3vdh48aNbc6fQYMGGY6OjkZ0dHSytpydnY1+/fqlGAeArI/u5QByhMaNG8vHx0cBAQF69tln5ebmpp9//tna9fbKlStat26dOnbsqKtXr+rSpUu6dOmSLl++rGbNmuno0aPJZjvv06ePzcRk/fr1U65cufTrr79ay1xdXa1/J+23Xr16iouL0+HDh2325+Liop49e5px+MmcP39ee/bsUY8ePeTt7W0tr1Spkpo0aWJzDEnuHZdbr149Xb58WbGxsfdt548//lBUVJT69u1rMz6zR48e8vT0tKn7ww8/qGzZsipTpoz1+b906ZIaNWokSVq/fr0kWa++/fTTT0pMTEz1MS9ZskSJiYkaNmyYHBxsP/7+fbXtYV6zlKT2OFasWCHp7lXpfwsJCbG5n5CQoFWrVqlt27YqUaKEtbxgwYJ64YUXtGnTpmSvQe/evf9z/Pbq1asVHR2t559/3iZOR0dH1axZ0xqnq6urnJ2dtWHDhmTDJ/7L5cuXbXqT3KtPnz5avXp1slu5cuVs6pUrV846JESSfHx8VLp0af3999/WMi8vLx08eFBHjx5Nsa20vMd79eplc27UrFlThmGoV69e1jJHR0dVr17dJpYkbdu21WOPPWa9X6NGDdWsWTPF91eSxYsXKzExUR07drR5Xfz9/VWqVCnr65KShIQErVy5Um3btlWRIkWs5WXLllWzZs0yrB1J6tSpk6KiomyW6Vq4cKESExPVqVMna9m/3083b97UpUuXrMsw7tq164Ft3OvXX39VwYIF9eyzz1rL8uTJoz59+iSr++92r1+/rkuXLql27doyDEO7d+9+qHaltL0P+/TpY3P+1KtXTwkJCTp16lSy/efLly/FXh8Asge6lwPIESZNmqTHH39cMTEx+vbbb7Vx40abWZyPHTsmwzD03nvv6b333ktxH1FRUTZfoEuVKmWz3d3dXQULFrQZ53rw4EG9++67WrduXbIvZDExMTb3H3vssUc2cVDSl77SpUsn21a2bFmtXLnSOgFXkn9/iZf+v2v+P//8Iw8Pjwe2c+9z5eTkZPPFVZKOHj2qQ4cO3XeJtqioKEl3v+x/8803evnll/X2228rODhY7du317PPPpssmf6348ePy8HBIVlCd6+Hec1SktrjOHXqlBwcHFS8eHGb7ffOmH/x4kXFxcXd97VKTEzU6dOnrd2sJSXb5/3ilGT9MeBeSa+pi4uLRo8ercGDB8vPz0+1atXSM888o27dusnf3/8/2zHuM9ZZuntepGa8973nnnT3/Pv3jwAjR45UmzZt9Pjjj6tChQp6+umn1bVrV1WqVElS2t7j97ab9EPRv4dFJJWn9IPEvee9JD3++ONasGDB/Q5VR48elWEYKT5W0gNXILh48aJu3LiR4mNLly5tk+ynpx1Jevrpp+Xp6an58+crODhY0t2u5VWqVNHjjz9urXflyhWNGDFC8+bNs577SVLzfvq3U6dOqWTJksm6pKf03oiIiNCwYcP0888/J3ttHrZdKW3vwwf9n3kvwzCYRA3Ixki6AeQINWrUsM5e3rZtW9WtW1cvvPCCjhw5Ind3d+sV0zfeeCPZFaEkD7t8WHR0tJ566il5eHho5MiRCgwMVO7cubVr1y4NGTIk2VXaf1+ZyYzud+X0QUnVw0hMTFTFihU1duzYFLcnJTqurq7auHGj1q9fr19++UUrVqzQ/Pnz1ahRI61atSpdM3Q/7GuWnuMwU2rOpaRjmT17dorJ87/HVL/++utq1aqVlixZopUrV+q9995TWFiY1q1b98AxqPnz53/oq+MpSc25V79+fR0/flw//fSTVq1apW+++Ubjxo3T1KlT9fLLL6fpPX6/dlMqz8j3gcVi0fLly1Ns50HzNDzKdlxcXNS2bVv9+OOPmjx5si5cuKDNmzfr448/tqnXsWNHbdmyRW+++aaqVKli/f/26aeffqieKg8jISFBTZo00ZUrVzRkyBCVKVNGbm5uOnv2rHr06GFau/d6mP8zo6OjVaBAAbNDAmAnJN0AchxHR0eFhYWpYcOG+uKLL/T2229br7o6OTmleqblo0eP2qw9fO3aNZ0/f9667vCGDRt0+fJlLV68WPXr17fWO3HixEPF+zBXP1Jbt2jRopKkI0eOJNt2+PBhFShQwOYqd1oltXP06FGbK6q3b9/WiRMnVLlyZWtZYGCg9u7dq+Dg4P88DgcHBwUHBys4OFhjx47Vxx9/rHfeeUfr16+/7+sXGBioxMRE/fnnn6pSpUqKdR7mNbtfjKk9jqJFiyoxMVEnTpywudp47Ngxm3o+Pj7KkyfPfV8rBweHNCXygYGBkiRfX99UnfOBgYEaPHiwBg8erKNHj6pKlSr67LPP9N133933MWXKlNGcOXMUExOTbDiBGby9vdWzZ0/17NlT165dU/369TV8+HC9/PLLaXqPp1dKXd3/+uuvB04+FxgYKMMwVLx4cZsrxqnh4+MjV1fXFNu99/xJTztJOnXqpJkzZ2rt2rU6dOiQDMOw6Vr+zz//aO3atRoxYoSGDRtmLb/fEID/UrRoUR04cCDZVeF7j23//v3666+/NHPmTJvJ7e6dyV5K/f+ZZr0PJens2bO6deuWypYtm6bHA8j8GNMNIEdq0KCBatSoofHjx+vmzZvy9fVVgwYN9OWXX+r8+fPJ6qe0zMtXX32l27dvW+9PmTJFd+7cUfPmzSX9/1WOf1/VuHXrliZPnvxQsbq5uSk6OjrVdVPTdbJgwYKqUqWKZs6cabPvAwcOaNWqVdYfDtKrevXq8vHx0dSpU3Xr1i1r+YwZM5IdU8eOHXX27Fl9/fXXyfZz48YN6yzcV65cSbY9KYlOaemgJG3btpWDg4NGjhyZ7EpX0mv0MK/Z/Z7r1B5H0tXWe/c9ceJEm/uOjo5q2rSpfvrpJ5uhCxcuXNDcuXNVt27d+3bvf5BmzZrJw8NDH3/8sc15nCTpnI+Li9PNmzdttgUGBipv3rwPfL4lKSgoSIZhaOfOnQ8d38O6dwkqd3d3lSxZ0hpjWt7j6bVkyRKbceLbt2/X77//bv0/IiXt27eXo6OjRowYkeyKqGEYD1xqy9HRUc2aNdOSJUsUERFhLT906JBWrlyZYe0kady4sby9vTV//nzNnz9fNWrUsBnakNL7SZLGjx//n/tOSYsWLXTu3DktXLjQWhYXF6evvvrKpl5K7RqGoc8//zzZPpN+XPyv/2PNeh9Ksr4/ateunabHA8j8uNINIMd688039dxzz2nGjBnq27evJk2apLp166pixYrq3bu3SpQooQsXLmjr1q06c+aM9u7da/P4W7duKTg4WB07dtSRI0c0efJk1a1bV61bt5Z09wtUvnz51L17dw0cOFAWi0WzZ89+6G6o1apV05QpU/Thhx+qZMmS8vX1ve843GrVqmn+/PkKDQ3Vk08+KXd3d7Vq1SrFup988omaN2+uoKAg9erVy7pkmKenZ7K1adPKyclJH374oV555RU1atRInTp10okTJzR9+vRkY7q7du2qBQsWqG/fvlq/fr3q1KmjhIQEHT58WAsWLNDKlStVvXp1jRw5Uhs3blTLli1VtGhRRUVFafLkySpcuLDq1q1731hKliypd955Rx988IHq1aun9u3by8XFRTt27FChQoUUFhb2UK/Z/Z7r1B5HtWrV1KFDB40fP16XL1+2Lhn2119/SbK9Avfhhx9a1yZ/9dVXlStXLn355ZeKj4/XmDFj0vTaeHh4aMqUKerataueeOIJde7cWT4+PoqIiNAvv/yiOnXq6IsvvtBff/1lPc/LlSunXLly6ccff9SFCxfUuXPnB7ZRt25d5c+fX2vWrEnxnN21a1eKV8oDAwMVFBT0UMdTrlw5NWjQQNWqVZO3t7f++OMPLVy4UAMGDLDWedj3eHqVLFlSdevWVb9+/RQfH6/x48crf/78euutt+77mMDAQH344YcaOnSoTp48qbZt2ypv3rw6ceKEfvzxR/Xp00dvvPHGfR8/YsQIrVixQvXq1dOrr76qO3fuaOLEiSpfvrz27duXYe1Id9/f7du317x583T9+nV9+umnNts9PDxUv359jRkzRrdv39Zjjz2mVatWPXRvnyS9e/fWF198oW7dumnnzp0qWLCgZs+erTx58tjUK1OmjAIDA/XGG2/o7Nmz8vDw0KJFi1Ic6pC0XNfAgQPVrFkzOTo63ve8NuN9KN29Al+kSBGWCwOys0cyRzoA2EnS0i07duxIti0hIcEIDAw0AgMDrcveHD9+3OjWrZvh7+9vODk5GY899pjxzDPPGAsXLky2z/DwcKNPnz5Gvnz5DHd3d6NLly42y28ZhmFs3rzZqFWrluHq6moUKlTIeOutt4yVK1cmW97mqaeeMsqXL5/iMURGRhotW7Y08ubNa7PMVkpLhl27ds144YUXDC8vL0OSdUmrlJYMMwzDWLNmjVGnTh3D1dXV8PDwMFq1amX8+eefNnWSljS6d4mulJb4uZ/JkycbxYsXN1xcXIzq1asbGzduTLYckGHcXWJs9OjRRvny5Q0XFxcjX758RrVq1YwRI0YYMTExhmEYxtq1a402bdoYhQoVMpydnY1ChQoZzz//vPHXX3/9ZxyGYRjffvutUbVqVev+n3rqKWP16tXW7al9ze73XKf2OAzj7nJH/fv3N7y9vQ13d3ejbdu2xpEjRwxJxqhRo2zi3rVrl9GsWTPD3d3dyJMnj9GwYUNjy5YtNnUedL7f7/Vav3690axZM8PT09PInTu3ERgYaPTo0cP4448/DMMwjEuXLhn9+/c3ypQpY7i5uRmenp5GzZo1bZZtepCBAwcaJUuWtCn7ryXDunfvbq1btGjRFJcCu/f8+fDDD40aNWoYXl5ehqurq1GmTBnjo48+slnWzzAe7j1+7/N4v/dC9+7dDTc3t2TH98knnxifffaZERAQYLi4uBj16tUz9u7dm+I+77Vo0SKjbt26hpubm+Hm5maUKVPG6N+/v3HkyJFkde8VHh5uVKtWzXB2djZKlChhTJ061ZR2DMMwVq9ebUgyLBaLzRKMSc6cOWO0a9fO8PLyMjw9PY3nnnvOOHfuXLLluFKzZJhhGMapU6eM1q1bG3ny5DEKFChgvPbaa8aKFSuSvT///PNPo3Hjxoa7u7tRoEABo3fv3sbevXuT/T94584dIyQkxPDx8TEsFovNc3RvjIaRvvdhSv9nJyQkGAULFjTefffdlJ9gANmCxTAyaOYPAMghZsyYoZ49e2rHjh3WydmAjLJnzx5VrVpV3333nbp06WLvcNLt77//VpkyZbR8+XLrLNcA7lqyZIleeOEFHT9+XAULFrR3OABMwphuAADs5MaNG8nKxo8fLwcHB5uJ3LKyEiVKqFevXho1apS9QwEyndGjR2vAgAEk3EA2x5huAADsZMyYMdq5c6caNmyoXLlyafny5Vq+fLn69OnzSJYWe1SmTJli7xCATGnr1q32DgHAI0DSDQCAndSuXVurV6/WBx98oGvXrqlIkSIaPny43nnnHXuHBgAAMghjugEAAAAAMAljugEAAAAAMAndy1MpMTFR586dU968eW3WTgUAAAAA5DyGYejq1asqVKiQHBzufz2bpDuVzp07l60mtQEAAAAApN/p06dVuHDh+24n6U6lvHnzSrr7hHp4eNg5GgAAAACAPcXGxiogIMCaK94PSXcqJXUp9/DwIOkGAAAAAEjSfw4/ZiI1AAAAAABMQtINAAAAAIBJSLoBAAAAADAJSTcAAAAAACYh6QYAAAAAwCQk3QAAAAAAmISkGwAAAAAAk5B0AwAAAABgEpJuAAAAAABMQtINAAAAAIBJSLoBAAAAADAJSTcAAAAAACYh6QYAAAAAwCQk3QAAAAAAmCSXvQNAOrVqZe8IspalS+0dAQAAAIAchCvdAAAAAACYhKQbAAAAAACTkHQDAAAAAGASkm4AAAAAAExC0g0AAAAAgElIugEAAAAAMEmWSrpHjRoli8Wi119/3Vp28+ZN9e/fX/nz55e7u7s6dOigCxcu2DwuIiJCLVu2VJ48eeTr66s333xTd+7cecTRAwAAAABymiyTdO/YsUNffvmlKlWqZFM+aNAgLV26VD/88IPCw8N17tw5tW/f3ro9ISFBLVu21K1bt7RlyxbNnDlTM2bM0LBhwx71IQAAAAAAcpgskXRfu3ZNXbp00ddff618+fJZy2NiYjRt2jSNHTtWjRo1UrVq1TR9+nRt2bJF27ZtkyStWrVKf/75p7777jtVqVJFzZs31wcffKBJkybp1q1b920zPj5esbGxNjcAAAAAAB5Glki6+/fvr5YtW6px48Y25Tt37tTt27dtysuUKaMiRYpo69atkqStW7eqYsWK8vPzs9Zp1qyZYmNjdfDgwfu2GRYWJk9PT+stICAgg48KAAAAAJDdZfqke968edq1a5fCwsKSbYuMjJSzs7O8vLxsyv38/BQZGWmt8++EO2l70rb7GTp0qGJiYqy306dPp/NIAAAAAAA5TS57B/Agp0+f1muvvabVq1crd+7cj7RtFxcXubi4PNI2AQAAAADZS6a+0r1z505FRUXpiSeeUK5cuZQrVy6Fh4drwoQJypUrl/z8/HTr1i1FR0fbPO7ChQvy9/eXJPn7+yebzTzpflIdAAAAAADMkKmT7uDgYO3fv1979uyx3qpXr64uXbpY/3ZyctLatWutjzly5IgiIiIUFBQkSQoKCtL+/fsVFRVlrbN69Wp5eHioXLlyj/yYAAAAAAA5R6buXp43b15VqFDBpszNzU358+e3lvfq1UuhoaHy9vaWh4eHQkJCFBQUpFq1akmSmjZtqnLlyqlr164aM2aMIiMj9e6776p///50HwcAAAAAmCpTJ92pMW7cODk4OKhDhw6Kj49Xs2bNNHnyZOt2R0dHLVu2TP369VNQUJDc3NzUvXt3jRw50o5RAwAAAAByAothGIa9g8gKYmNj5enpqZiYGHl4eNg7nP/XqpW9I8hali61dwQAAAAAsoHU5oiZekw3AAAAAABZGUk3AAAAAAAmIekGAAAAAMAkJN0AAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAAAAATELSDQAAAACASUi6AQAAAAAwCUk3AAAAAAAmIekGAAAAAMAkJN0AAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAAAAATELSDQAAAACASUi6AQAAAAAwCUk3AAAAAAAmIekGAAAAAMAkJN0AAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAAAAATELSDQAAAACASUi6AQAAAAAwCUk3AAAAAAAmIekGAAAAAMAkJN0AAAAAAJiEpBsAAAAAAJOQdAMAAAAAYJJc9g7gv0yZMkVTpkzRyZMnJUnly5fXsGHD1Lx5c0lSgwYNFB4ebvOYV155RVOnTrXej4iIUL9+/bR+/Xq5u7ure/fuCgsLU65cmf7wAftp1creEWQtS5faOwIAAABkQpk+6yxcuLBGjRqlUqVKyTAMzZw5U23atNHu3btVvnx5SVLv3r01cuRI62Py5Mlj/TshIUEtW7aUv7+/tmzZovPnz6tbt25ycnLSxx9//MiPBwAAAACQc2T6pLvVPVfbPvroI02ZMkXbtm2zJt158uSRv79/io9ftWqV/vzzT61Zs0Z+fn6qUqWKPvjgAw0ZMkTDhw+Xs7Nzio+Lj49XfHy89X5sbGwGHREAAAAAIKfIUmO6ExISNG/ePF2/fl1BQUHW8jlz5qhAgQKqUKGChg4dqri4OOu2rVu3qmLFivLz87OWNWvWTLGxsTp48OB92woLC5Onp6f1FhAQYM5BAQAAAACyrUx/pVuS9u/fr6CgIN28eVPu7u768ccfVa5cOUnSCy+8oKJFi6pQoULat2+fhgwZoiNHjmjx4sWSpMjISJuEW5L1fmRk5H3bHDp0qEJDQ633Y2NjSbwBAAAAAA8lSyTdpUuX1p49exQTE6OFCxeqe/fuCg8PV7ly5dSnTx9rvYoVK6pgwYIKDg7W8ePHFRgYmOY2XVxc5OLikhHhAwAAAAByqCzRvdzZ2VklS5ZUtWrVFBYWpsqVK+vzzz9PsW7NmjUlSceOHZMk+fv768KFCzZ1ku7fbxw4AAAAAAAZIUsk3fdKTEy0meTs3/bs2SNJKliwoCQpKChI+/fvV1RUlLXO6tWr5eHhYe2iDgAAAACAGTJ99/KhQ4eqefPmKlKkiK5evaq5c+dqw4YNWrlypY4fP665c+eqRYsWyp8/v/bt26dBgwapfv36qlSpkiSpadOmKleunLp27aoxY8YoMjJS7777rvr370/3cQAAAACAqTJ90h0VFaVu3brp/Pnz8vT0VKVKlbRy5Uo1adJEp0+f1po1azR+/Hhdv35dAQEB6tChg959913r4x0dHbVs2TL169dPQUFBcnNzU/fu3W3W9QYAAAAAwAyZPumeNm3afbcFBAQoPDz8P/dRtGhR/frrrxkZFgAAAAAA/ylLjukGAAAAACArIOkGAAAAAMAkJN0AAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAAAAATELSDQAAAACASUi6AQAAAAAwCUk3AAAAAAAmIekGAAAAAMAkJN0AAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAAAAATELSDQAAAACASUi6AQAAAAAwCUk3AAAAAAAmIekGAAAAAMAkJN0AAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAAAAATELSDQAAAACASUi6AQAAAAAwiSlJ940bNxQXF2e9f+rUKY0fP16rVq0yozkAAAAAADIlU5LuNm3aaNasWZKk6Oho1axZU5999pnatGmjKVOmmNEkAAAAAACZjilJ965du1SvXj1J0sKFC+Xn56dTp05p1qxZmjBhghlNAgAAAACQ6ZiSdMfFxSlv3rySpFWrVql9+/ZycHBQrVq1dOrUKTOaBAAAAAAg0zEl6S5ZsqSWLFmi06dPa+XKlWratKkkKSoqSh4eHmY0CQAAAABApmNK0j1s2DC98cYbKlasmGrWrKmgoCBJd696V61a9aH2NWXKFFWqVEkeHh7y8PBQUFCQli9fbt1+8+ZN9e/fX/nz55e7u7s6dOigCxcu2OwjIiJCLVu2VJ48eeTr66s333xTd+7cSf+BAgAAAADwALnM2Omzzz6runXr6vz586pcubK1PDg4WO3atXuofRUuXFijRo1SqVKlZBiGZs6cqTZt2mj37t0qX768Bg0apF9++UU//PCDPD09NWDAALVv316bN2+WJCUkJKhly5by9/fXli1bdP78eXXr1k1OTk76+OOPM/S4AQAAAAD4N4thGIa9g3hY3t7e+uSTT/Tss8/Kx8dHc+fO1bPPPitJOnz4sMqWLautW7eqVq1aWr58uZ555hmdO3dOfn5+kqSpU6dqyJAhunjxopydnVPVZmxsrDw9PRUTE5O5usi3amXvCLKWpUvtHUHWwbn1cDi3AAAAcpTU5oimdC+/fv263nvvPdWuXVslS5ZUiRIlbG5plZCQoHnz5un69esKCgrSzp07dfv2bTVu3Nhap0yZMipSpIi2bt0qSdq6dasqVqxoTbglqVmzZoqNjdXBgwfv21Z8fLxiY2NtbgAAAAAAPAxTupe//PLLCg8PV9euXVWwYEFZLJZ07W///v0KCgrSzZs35e7urh9//FHlypXTnj175OzsLC8vL5v6fn5+ioyMlCRFRkbaJNxJ25O23U9YWJhGjBiRrrgBAAAAADmbKUn38uXL9csvv6hOnToZsr/SpUtrz549iomJ0cKFC9W9e3eFh4dnyL7vZ+jQoQoNDbXej42NVUBAgKltAgAAAACyF1OS7nz58snb2zvD9ufs7KySJUtKkqpVq6YdO3bo888/V6dOnXTr1i1FR0fbXO2+cOGC/P39JUn+/v7avn27zf6SZjdPqpMSFxcXubi4ZNgxAAAAAAByHlPGdH/wwQcaNmyY4uLizNi9EhMTFR8fr2rVqsnJyUlr1661bjty5IgiIiKsy5QFBQVp//79ioqKstZZvXq1PDw8VK5cOVPiAwAAAABAMulK92effabjx4/Lz89PxYoVk5OTk832Xbt2pXpfQ4cOVfPmzVWkSBFdvXpVc+fO1YYNG7Ry5Up5enqqV69eCg0Nlbe3tzw8PBQSEqKgoCDVqlVLktS0aVOVK1dOXbt21ZgxYxQZGal3331X/fv350o2AAAAAMBUpiTdbdu2zbB9RUVFqVu3bjp//rw8PT1VqVIlrVy5Uk2aNJEkjRs3Tg4ODurQoYPi4+PVrFkzTZ482fp4R0dHLVu2TP369VNQUJDc3NzUvXt3jRw5MsNiBAAAAAAgJVlynW57YJ3ubIK1lFOPc+vhcG4BAADkKKnNEU250p1k586dOnTokCSpfPnyqlq1qpnNAQAAAACQqZiSdEdFRalz587asGGDdVbx6OhoNWzYUPPmzZOPj48ZzQIAAAAAkKmYMnt5SEiIrl69qoMHD+rKlSu6cuWKDhw4oNjYWA0cONCMJgEAAAAAyHRMudK9YsUKrVmzRmXLlrWWlStXTpMmTVLTpk3NaBIAAAAAgEzHlCvdiYmJyZYJkyQnJyclJiaa0SQAAAAAAJmOKUl3o0aN9Nprr+ncuXPWsrNnz2rQoEEKDg42o0kAAAAAADIdU5LuL774QrGxsSpWrJgCAwMVGBio4sWLKzY2VhMnTjSjSQAAAAAAMh1TxnQHBARo165dWrNmjQ4fPixJKlu2rBo3bmxGcwAAAAAAZEqmrdNtsVjUpEkTNWnSxKwmAAAAAADI1DIs6Z4wYUKq67JsGAAAAAAgJ8iwpHvcuHGpqmexWEi6AQAAAAA5QoYl3SdOnMioXQEAAAAAkC2YMns5AAAAAADIwCvdoaGhqa47duzYjGoWAAAAAIBMK8OS7t27d6eqnsViyagmAQAAAADI1DIs6V6/fn1G7QoAAAAAgGyBMd0AAAAAAJgkw650t2/fXjNmzJCHh4fat2//wLqLFy/OqGYBAAAAAMi0Mizp9vT0tI7X9vDwYOw2AAAAACDHy7Cke/r06da/Z8yYkVG7BQAAAAAgyzJlTHejRo0UHR2drDw2NlaNGjUyo0kAAAAAADIdU5LuDRs26NatW8nKb968qd9++82MJgEAAAAAyHQyrHu5JO3bt8/6959//qnIyEjr/YSEBK1YsUKPPfZYRjYJAAAAAECmlaFJd5UqVWSxWGSxWFLsRu7q6qqJEydmZJMAAAAAAGRaGZp0nzhxQoZhqESJEtq+fbt8fHys25ydneXr6ytHR8eMbBIAAAAAgEwrQ5PuokWLSpISExMzcrcAAAAAAGRJGZp0/9vRo0e1fv16RUVFJUvChw0bZlazAAAAAABkGqYk3V9//bX69eunAgUKyN/fXxaLxbrNYrGQdAMAAAAAcgRTku4PP/xQH330kYYMGWLG7gEAAAAAyBJMWaf7n3/+0XPPPWfGrgEAAAAAyDJMSbqfe+45rVq1KkP2FRYWpieffFJ58+aVr6+v2rZtqyNHjtjUadCggXWpsqRb3759bepERESoZcuWypMnj3x9ffXmm2/qzp07GRIjAAAAAAApMaV7ecmSJfXee+9p27ZtqlixopycnGy2Dxw4MNX7Cg8PV//+/fXkk0/qzp07+t///qemTZvqzz//lJubm7Ve7969NXLkSOv9PHnyWP9OSEhQy5Yt5e/vry1btuj8+fPq1q2bnJyc9PHHH6fjSAEAAAAAuD+LYRhGRu+0ePHi92/QYtHff/+d5n1fvHhRvr6+Cg8PV/369SXdvdJdpUoVjR8/PsXHLF++XM8884zOnTsnPz8/SdLUqVM1ZMgQXbx4Uc7OzskeEx8fr/j4eOv92NhYBQQEKCYmRh4eHmmOP8O1amXvCLKWpUvtHUHWwbn1cDi3AAAAcpTY2Fh5enr+Z45oSvfyEydO3PeWnoRbkmJiYiRJ3t7eNuVz5sxRgQIFVKFCBQ0dOlRxcXHWbVu3blXFihWtCbckNWvWTLGxsTp48GCK7YSFhcnT09N6CwgISFfcAAAAAICcx7R1us2QmJio119/XXXq1FGFChWs5S+88IKKFi2qQoUKad++fRoyZIiOHDmixYsXS5IiIyNtEm5J1vuRkZEptjV06FCFhoZa7ydd6QYAAAAAILVMS7rPnDmjn3/+WREREbp165bNtrFjx6Zpn/3799eBAwe0adMmm/I+ffpY/65YsaIKFiyo4OBgHT9+XIGBgWlqy8XFRS4uLml6LAAAAAAAkklJ99q1a9W6dWuVKFFChw8fVoUKFXTy5EkZhqEnnngiTfscMGCAli1bpo0bN6pw4cIPrFuzZk1J0rFjxxQYGCh/f39t377dps6FCxckSf7+/mmKBwAAAACA/2LKmO6hQ4fqjTfe0P79+5U7d24tWrRIp0+f1lNPPfXQ63cbhqEBAwboxx9/1Lp16x44SVuSPXv2SJIKFiwoSQoKCtL+/fsVFRVlrbN69Wp5eHioXLlyDxUPAAAAAACpZUrSfejQIXXr1k2SlCtXLt24cUPu7u4aOXKkRo8e/VD76t+/v7777jvNnTtXefPmVWRkpCIjI3Xjxg1J0vHjx/XBBx9o586dOnnypH7++Wd169ZN9evXV6VKlSRJTZs2Vbly5dS1a1ft3btXK1eu1Lvvvqv+/fvThRwAAAAAYBpTkm43NzfrOO6CBQvq+PHj1m2XLl16qH1NmTJFMTExatCggQoWLGi9zZ8/X5Lk7OysNWvWqGnTpipTpowGDx6sDh06aOm/lu9xdHTUsmXL5OjoqKCgIL344ovq1q2bzbreAAAAAABkNFPGdNeqVUubNm1S2bJl1aJFCw0ePFj79+/X4sWLVatWrYfa138tIx4QEKDw8PD/3E/RokX166+/PlTbAAAAAACkhylJ99ixY3Xt2jVJ0ogRI3Tt2jXNnz9fpUqVSvPM5QAAAAAAZDWmJN0lSpSw/u3m5qapU6ea0QwAAAAAAJmaaet0S9KtW7cUFRWlxMREm/IiRYqY2SwAAAAAAJmCKUn3X3/9pV69emnLli025YZhyGKxKCEhwYxmAQAAAADIVExJunv27KlcuXJp2bJlKliwoCwWixnNAAAAAACQqZmSdO/Zs0c7d+5UmTJlzNg9AAAAAABZginrdJcrV+6h1+MGAAAAACC7ybCkOzY21nobPXq03nrrLW3YsEGXL1+22RYbG5tRTQIAAAAAkKllWPdyLy8vm7HbhmEoODjYpg4TqQEAAAAAcpIMS7rXr1+fUbsCAAAAACBbyLCk+6mnnsqoXQEAAAAAkC2YMpHa9OnT9cMPPyQr/+GHHzRz5kwzmgQAAAAAINMxJekOCwtTgQIFkpX7+vrq448/NqNJAAAAAAAyHVOS7oiICBUvXjxZedGiRRUREWFGkwAAAAAAZDqmJN2+vr7at29fsvK9e/cqf/78ZjQJAAAAAECmY0rS/fzzz2vgwIFav369EhISlJCQoHXr1um1115T586dzWgSAAAAAIBMJ8NmL/+3Dz74QCdPnlRwcLBy5brbRGJiorp168aYbgAAAABAjmFK0u3s7Kz58+frgw8+0N69e+Xq6qqKFSuqaNGiZjQHAAAAAECmZErSnaRYsWIyDEOBgYHWK94AAAAAAOQUpozpjouLU69evZQnTx6VL1/eOmN5SEiIRo0aZUaTAAAAAABkOhmSdH/55ZfatWuX9f7QoUO1d+9ebdiwQblz57aWN27cWPPnz8+IJgEAAAAAyPQyJOkuU6aM2rRpo1WrVkmSfvzxR33xxReqW7euLBaLtV758uV1/PjxjGgSAAAAAIBML0OS7qeeekrh4eEaNmyYJOnSpUvy9fVNVu/69es2STgAAAAAANlZho3pLlGihDZu3ChJql69un755RfrtqRE+5tvvlFQUFBGNQkAAAAAQKaWoVOKOzs7S5I+/vhjNW/eXH/++afu3Lmjzz//XH/++ae2bNmi8PDwjGwSAAAAAIBMy5TZy+vWras9e/bozp07qlixolatWiVfX19t3bpV1apVM6NJAAAAAAAyHdMWzw4MDNTXX39t1u4BAAAAAMj0TLnSDQAAAAAAMvhKt4ODgywWiwzDkMViUUJCQkbuHgAAAACALCVDr3SfOHFCf//9t/XfjBAWFqYnn3xSefPmla+vr9q2basjR47Y1Ll586b69++v/Pnzy93dXR06dNCFCxds6kRERKhly5bKkyePfH199eabb+rOnTsZEiMAAAAAACnJ0KS7aNGiNreMEB4erv79+2vbtm1avXq1bt++raZNm+r69evWOoMGDdLSpUv1ww8/KDw8XOfOnVP79u2t2xMSEtSyZUvdunVLW7Zs0cyZMzVjxgzruuIAAAAAAJjBYhiGkRE72rdvX6rrVqpUKc3tXLx4Ub6+vgoPD1f9+vUVExMjHx8fzZ07V88++6wk6fDhwypbtqy2bt2qWrVqafny5XrmmWd07tw5+fn5SZKmTp2qIUOG6OLFi9alzh4kNjZWnp6eiomJkYeHR5rjz3CtWtk7gqxl6VJ7R5B1cG49HM4tAACAHCW1OWKGjemuUqWKzXjuB0nPWO+YmBhJkre3tyRp586dun37tho3bmytU6ZMGRUpUsSadG/dulUVK1a0JtyS1KxZM/Xr108HDx5U1apVk7UTHx+v+Ph46/3Y2Ng0xwwAAAAAyJkyrHv5v8dzL1q0SMWLF9fkyZO1e/du7d69W5MnT1ZgYKAWLVqU5jYSExP1+uuvq06dOqpQoYIkKTIyUs7OzvLy8rKp6+fnp8jISGudfyfcSduTtqUkLCxMnp6e1ltAQECa4wYAAAAA5EwZdqX732O4n3vuOU2YMEEtWrSwllWqVEkBAQF677331LZt2zS10b9/fx04cECbNm1Kb7j/aejQoQoNDbXej42NJfEGAAAAADyUDF0yLMn+/ftVvHjxZOXFixfXn3/+maZ9DhgwQMuWLdPGjRtVuHBha7m/v79u3bql6Ohom6vdFy5ckL+/v7XO9u3bbfaXNLt5Up17ubi4yMXFJU2xAgAAAAAgZfDs5UnKli2rsLAw3bp1y1p269YthYWFqWzZsg+1L8MwNGDAAP34449at25dsmS+WrVqcnJy0tq1a61lR44cUUREhIKCgiRJQUFB2r9/v6Kioqx1Vq9eLQ8PD5UrVy4thwgAAAAAwH8y5Ur31KlT1apVKxUuXNg6U/m+fftksVi09CFn+O3fv7/mzp2rn376SXnz5rWOwfb09JSrq6s8PT3Vq1cvhYaGytvbWx4eHgoJCVFQUJBq1aolSWratKnKlSunrl27asyYMYqMjNS7776r/v37czUbAAAAAGAaU5LuGjVq6O+//9acOXN0+PBhSVKnTp30wgsvyM3N7aH2NWXKFElSgwYNbMqnT5+uHj16SJLGjRsnBwcHdejQQfHx8WrWrJkmT55srevo6Khly5apX79+CgoKkpubm7p3766RI0em/SABAGnDcnQPh+XoAADI0jJsne7sjnW6swm+vKYe59bD4dxKPc6th8O5BQBAppTaHNGUMd0AAAAAAICkGwAAAAAA05B0AwAAAABgEpJuAAAAAABMYlrSHR0drW+++UZDhw7VlStXJEm7du3S2bNnzWoSAAAAAIBMxZQlw/bt26fGjRvL09NTJ0+eVO/eveXt7a3FixcrIiJCs2bNMqNZAAAAAAAyFVOudIeGhqpHjx46evSocufObS1v0aKFNm7caEaTAAAAAABkOqYk3Tt27NArr7ySrPyxxx5TZGSkGU0CAAAAAJDpmJJ0u7i4KDY2Nln5X3/9JR8fHzOaBAAAAAAg0zEl6W7durVGjhyp27dvS5IsFosiIiI0ZMgQdejQwYwmAQAAAADIdExJuj/77DNdu3ZNvr6+unHjhp566imVLFlSefPm1UcffWRGkwAAAAAAZDqmzF7u6emp1atXa/Pmzdq7d6+uXbumJ554Qo0bNzajOQAAAAAAMqUMT7pv374tV1dX7dmzR3Xq1FGdOnUyugkAAAAAALKEDO9e7uTkpCJFiighISGjdw0AAAAAQJZiypjud955R//73/905coVM3YPAAAAAECWYMqY7i+++ELHjh1ToUKFVLRoUbm5udls37VrlxnNAgAAAACQqZiSdLdt29aM3QIAAAAAkKWYknS///77ZuwWAAAAAIAsxZSkO8kff/yhQ4cOSZLKlSunatWqmdkcAAAAAACZiilJ95kzZ/T8889r8+bN8vLykiRFR0erdu3amjdvngoXLmxGswAAAAAAZCqmzF7+8ssv6/bt2zp06JCuXLmiK1eu6NChQ0pMTNTLL79sRpMAAAAAAGQ6plzpDg8P15YtW1S6dGlrWenSpTVx4kTVq1fPjCYBAAAAAMh0TLnSHRAQoNu3bycrT0hIUKFChcxoEgAAAACATMeUpPuTTz5RSEiI/vjjD2vZH3/8oddee02ffvqpGU0CAAAAAJDpZFj38nz58slisVjvX79+XTVr1lSuXHebuHPnjnLlyqWXXnqJdbwBAAAAADlChiXd48ePz6hdAQAAAACQLWRY0t29e/eM2hUAAAAAANmCKbOXJ4mKilJUVJQSExNtyitVqmRmswAAAAAAZAqmJN07d+5U9+7ddejQIRmGYbPNYrEoISHBjGYBAAAAAMhUTEm6X3rpJT3++OOaNm2a/Pz8bCZYAwAAAAAgpzBlybC///5bY8aMUc2aNVWsWDEVLVrU5vYwNm7cqFatWqlQoUKyWCxasmSJzfYePXrIYrHY3J5++mmbOleuXFGXLl3k4eEhLy8v9erVS9euXUvvYQIAAAAA8ECmJN3BwcHau3dvhuzr+vXrqly5siZNmnTfOk8//bTOnz9vvX3//fc227t06aKDBw9q9erVWrZsmTZu3Kg+ffpkSHwAAAAAANyPKd3Lv/nmG3Xv3l0HDhxQhQoV5OTkZLO9devWqd5X8+bN1bx58wfWcXFxkb+/f4rbDh06pBUrVmjHjh2qXr26JGnixIlq0aKFPv30UxUqVCjFx8XHxys+Pt56PzY2NtUxAwAAAAAgmZR0b926VZs3b9by5cuTbTNjIrUNGzbI19dX+fLlU6NGjfThhx8qf/781li8vLysCbckNW7cWA4ODvr999/Vrl27FPcZFhamESNGZGicAAAAAICcxZTu5SEhIXrxxRd1/vx5JSYm2twyOuF++umnNWvWLK1du1ajR49WeHi4mjdvbm0nMjJSvr6+No/JlSuXvL29FRkZed/9Dh06VDExMdbb6dOnMzRuAAAAAED2Z8qV7suXL2vQoEHy8/MzY/c2OnfubP27YsWKqlSpkgIDA7VhwwYFBweneb8uLi5ycXHJiBABAAAAADmUKVe627dvr/Xr15ux6/9UokQJFShQQMeOHZMk+fv7KyoqyqbOnTt3dOXKlfuOAwcAAAAAICOYcqX78ccf19ChQ7Vp0yZVrFgx2URqAwcONKNZSdKZM2d0+fJlFSxYUJIUFBSk6Oho7dy5U9WqVZMkrVu3TomJiapZs6ZpcQAAAAAAYNrs5e7u7goPD1d4eLjNNovF8lBJ97Vr16xXrSXpxIkT2rNnj7y9veXt7a0RI0aoQ4cO8vf31/Hjx/XWW2+pZMmSatasmSSpbNmyevrpp9W7d29NnTpVt2/f1oABA9S5c+f7zlwOAACyoFat7B1B1rF0qb0jAIAcw5Sk+8SJExm2rz/++EMNGza03g8NDZUkde/eXVOmTNG+ffs0c+ZMRUdHq1ChQmratKk++OADm/HYc+bM0YABAxQcHCwHBwd16NBBEyZMyLAYAQAAAABIiSlJ978ZhiHp7hXutGjQoIF1HylZuXLlf+7D29tbc+fOTVP7AAAAAACklSkTqUnSrFmzVLFiRbm6usrV1VWVKlXS7NmzzWoOAAAAAIBMx5Qr3WPHjtV7772nAQMGqE6dOpKkTZs2qW/fvrp06ZIGDRpkRrMAAAAAAGQqpiTdEydO1JQpU9StWzdrWevWrVW+fHkNHz6cpBsAAAAAkCOY0r38/Pnzql27drLy2rVr6/z582Y0CQAAAABApmNK0l2yZEktWLAgWfn8+fNVqlQpM5oEAAAAACDTMaV7+YgRI9SpUydt3LjROqZ78+bNWrt2bYrJOAAAAAAA2ZEpV7o7dOig33//XQUKFNCSJUu0ZMkSFShQQNu3b1e7du3MaBIAAAAAgEzHtHW6q1Wrpu+++86s3QMAAAAAkOmZtk43AAAAAAA5XYZe6XZwcJDFYnlgHYvFojt37mRkswAAAAAAZEoZmnT/+OOP9922detWTZgwQYmJiRnZJAAAAAAAmVaGJt1t2rRJVnbkyBG9/fbbWrp0qbp06aKRI0dmZJMAAAAAAGRapo3pPnfunHr37q2KFSvqzp072rNnj2bOnKmiRYua1SQAAAAAAJlKhifdMTExGjJkiEqWLKmDBw9q7dq1Wrp0qSpUqJDRTQEAAAAAkKllaPfyMWPGaPTo0fL399f333+fYndzAAAAAAByigxNut9++225urqqZMmSmjlzpmbOnJlivcWLF2dkswAAAAAAZEoZmnR369btP5cMAwAAAAAgp8jQpHvGjBkZuTsAAAAAALI002YvBwAAAAAgpyPpBgAAAADAJCTdAAAAAACYhKQbAAAAAACTkHQDAAAAAGASkm4AAAAAAExC0g0AAAAAgElIugEAAAAAMAlJNwAAAAAAJiHpBgAAAADAJCTdAAAAAACYJNMn3Rs3blSrVq1UqFAhWSwWLVmyxGa7YRgaNmyYChYsKFdXVzVu3FhHjx61qXPlyhV16dJFHh4e8vLyUq9evXTt2rVHeBQAAAAAgJwo0yfd169fV+XKlTVp0qQUt48ZM0YTJkzQ1KlT9fvvv8vNzU3NmjXTzZs3rXW6dOmigwcPavXq1Vq2bJk2btyoPn36PKpDAAAAAADkULnsHcB/ad68uZo3b57iNsMwNH78eL377rtq06aNJGnWrFny8/PTkiVL1LlzZx06dEgrVqzQjh07VL16dUnSxIkT1aJFC3366acqVKjQIzsWAAAAAEDOkumvdD/IiRMnFBkZqcaNG1vLPD09VbNmTW3dulWStHXrVnl5eVkTbklq3LixHBwc9Pvvv9933/Hx8YqNjbW5AQAAAADwMLJ00h0ZGSlJ8vPzsyn38/OzbouMjJSvr6/N9ly5csnb29taJyVhYWHy9PS03gICAjI4egAAAABAdpelk24zDR06VDExMdbb6dOn7R0SAAAAACCLydJJt7+/vyTpwoULNuUXLlywbvP391dUVJTN9jt37ujKlSvWOilxcXGRh4eHzQ0AAAAAgIeRpZPu4sWLy9/fX2vXrrWWxcbG6vfff1dQUJAkKSgoSNHR0dq5c6e1zrp165SYmKiaNWs+8pgBAAAAADlHpp+9/Nq1azp27Jj1/okTJ7Rnzx55e3urSJEiev311/Xhhx+qVKlSKl68uN577z0VKlRIbdu2lSSVLVtWTz/9tHr37q2pU6fq9u3bGjBggDp37szM5QAAAAAAU2X6pPuPP/5Qw4YNrfdDQ0MlSd27d9eMGTP01ltv6fr16+rTp4+io6NVt25drVixQrlz57Y+Zs6cORowYICCg4Pl4OCgDh06aMKECY/8WAAAAAAAOUumT7obNGggwzDuu91isWjkyJEaOXLkfet4e3tr7ty5ZoQHAACA7K5VK3tHkHUsXWrvCIBMJ0uP6QYAAAAAIDMj6QYAAAAAwCQk3QAAAAAAmISkGwAAAAAAk5B0AwAAAABgEpJuAAAAAABMQtINAAAAAIBJSLoBAAAAADAJSTcAAAAAACYh6QYAAAAAwCQk3QAAAAAAmISkGwAAAAAAk5B0AwAAAABgklz2DgAAAAAAcqRWrewdQdaxdKm9I0gzrnQDAAAAAGASkm4AAAAAAExC0g0AAAAAgElIugEAAAAAMAlJNwAAAAAAJiHpBgAAAADAJCTdAAAAAACYhKQbAAAAAACTkHQDAAAAAGASkm4AAAAAAExC0g0AAAAAgElIugEAAAAAMAlJNwAAAAAAJiHpBgAAAADAJCTdAAAAAACYhKQbAAAAAACTZPmke/jw4bJYLDa3MmXKWLffvHlT/fv3V/78+eXu7q4OHTrowoULdowYAAAAAJBTZPmkW5LKly+v8+fPW2+bNm2ybhs0aJCWLl2qH374QeHh4Tp37pzat29vx2gBAAAAADlFLnsHkBFy5colf3//ZOUxMTGaNm2a5s6dq0aNGkmSpk+frrJly2rbtm2qVavWffcZHx+v+Ph46/3Y2NiMDxwAAAAAkK1liyvdR48eVaFChVSiRAl16dJFERERkqSdO3fq9u3baty4sbVumTJlVKRIEW3duvWB+wwLC5Onp6f1FhAQYOoxAAAAAACynyyfdNesWVMzZszQihUrNGXKFJ04cUL16tXT1atXFRkZKWdnZ3l5edk8xs/PT5GRkQ/c79ChQxUTE2O9nT592sSjAAAAAABkR1m+e3nz5s2tf1eqVEk1a9ZU0aJFtWDBArm6uqZ5vy4uLnJxccmIEAEAAAAAOVSWv9J9Ly8vLz3++OM6duyY/P39devWLUVHR9vUuXDhQopjwAEAAAAAyEjZLum+du2ajh8/roIFC6patWpycnLS2rVrrduPHDmiiIgIBQUF2TFKAAAAAEBOkOW7l7/xxhtq1aqVihYtqnPnzun999+Xo6Ojnn/+eXl6eqpXr14KDQ2Vt7e3PDw8FBISoqCgoAfOXA4AAAAAQEbI8kn3mTNn9Pzzz+vy5cvy8fFR3bp1tW3bNvn4+EiSxo0bJwcHB3Xo0EHx8fFq1qyZJk+ebOeoAQAAAAA5QZZPuufNm/fA7blz59akSZM0adKkRxQRAAAAAAB3Zbsx3QAAAAAAZBYk3QAAAAAAmISkGwAAAAAAk5B0AwAAAABgEpJuAAAAAABMQtINAAAAAIBJSLoBAAAAADAJSTcAAAAAACYh6QYAAAAAwCQk3QAAAAAAmISkGwAAAAAAk5B0AwAAAABgEpJuAAAAAABMQtINAAAAAIBJSLoBAAAAADAJSTcAAAAAACYh6QYAAAAAwCQk3QAAAAAAmISkGwAAAAAAk5B0AwAAAABgEpJuAAAAAABMQtINAAAAAIBJSLoBAAAAADAJSTcAAAAAACYh6QYAAAAAwCQk3QAAAAAAmISkGwAAAAAAk5B0AwAAAABgEpJuAAAAAABMQtINAAAAAIBJclTSPWnSJBUrVky5c+dWzZo1tX37dnuHBAAAAADIxnJM0j1//nyFhobq/fff165du1S5cmU1a9ZMUVFR9g4NAAAAAJBN5bJ3AI/K2LFj1bt3b/Xs2VOSNHXqVP3yyy/69ttv9fbbbyerHx8fr/j4eOv9mJgYSVJsbOyjCTi1bt+2dwRZS2Z7/TIzzq2Hw7mVepxbD4dzK/U4t1KP8+rhcG6lHufWw+HcSr1MeG4l5YaGYTywXo5Ium/duqWdO3dq6NCh1jIHBwc1btxYW7duTfExYWFhGjFiRLLygIAA0+LEI+Dpae8IkF1xbsEsnFswA+cVzMK5BbNk4nPr6tWr8nxAfDki6b506ZISEhLk5+dnU+7n56fDhw+n+JihQ4cqNDTUej8xMVFXrlxR/vz5ZbFYTI03q4uNjVVAQIBOnz4tDw8Pe4eDbIRzC2bh3IJZOLdgFs4tmIVzK/UMw9DVq1dVqFChB9bLEUl3Wri4uMjFxcWmzMvLyz7BZFEeHh68UWEKzi2YhXMLZuHcglk4t2AWzq3UedAV7iQ5YiK1AgUKyNHRURcuXLApv3Dhgvz9/e0UFQAAAAAgu8sRSbezs7OqVaumtWvXWssSExO1du1aBQUF2TEyAAAAAEB2lmO6l4eGhqp79+6qXr26atSoofHjx+v69evW2cyRcVxcXPT+++8n654PpBfnFszCuQWzcG7BLJxbMAvnVsazGP81v3k28sUXX+iTTz5RZGSkqlSpogkTJqhmzZr2DgsAAAAAkE3lqKQbAAAAAIBHKUeM6QYAAAAAwB5IugEAAAAAMAlJNwAAAAAAJiHpBgAAAADAJCTdALKEmzdv2jsEAAAA4KGRdCNDzJ49W3Xq1FGhQoV06tQpSdL48eP1008/2TkyZGWJiYn64IMP9Nhjj8nd3V1///23JOm9997TtGnT7BwdAAD2w4/RQNZB0o2HtnLlSsXExFjvT5kyRaGhoWrRooWio6OVkJAgSfLy8tL48ePtFCWygw8//FAzZszQmDFj5OzsbC2vUKGCvvnmGztGhqwuISFB06ZN0wsvvKDGjRurUaNGNjcgIxw7dkwrV67UjRs3JEms0or04sdomIXPRXORdOOhRUZGqk6dOjpz5owkaeLEifr666/1zjvvyNHR0VqvevXq2r9/v73CRDYwa9YsffXVV+rSpYvNuVW5cmUdPnzYjpEhq3vttdf02muvKSEhQRUqVFDlypVtbsDDSExMtLl/+fJlNW7cWI8//rhatGih8+fPS5J69eqlwYMH2yNEZFHz589XRESE9T4/RsMsfC6aK5e9A0DW0717d7m7u6tZs2Y6ePCgTpw4oapVqyar5+LiouvXr9shQmQXZ8+eVcmSJZOVJyYm6vbt23aICNnFvHnztGDBArVo0cLeoSAbGDt2rMqVK2c9nwYNGqRcuXIpIiJCZcuWtdbr1KmTQkND9dlnn9krVGQxuXPnVv369fXTTz+pcuXKmjlzpr766isFBwerb9++1nr8GI304nPRXCTdSJMOHTqoSpUqkqTixYtrz549Klq0qE2dFStW2HzZAB5WuXLl9NtvvyU7txYuXJjiDz1Aajk7O6f4gw6QFk2aNFGHDh10/vx59erVS6tWrdLKlStVuHBhm3qlSpWyznsCpEabNm3k5+enF198Ufv379e5c+f4MRqm4HPRXCTdSLPAwEBJUmhoqPr376+bN2/KMAxt375d33//vcLCwujqhHQZNmyYunfvrrNnzyoxMVGLFy/WkSNHNGvWLC1btsze4SELGzx4sD7//HN98cUXslgs9g4HWVzlypW1fft2de/eXb169dL169eVJ0+eZPWuXLkiFxcXO0SIrKxWrVoKDw+XxI/RMA+fi+ayGMzqgQwwZ84cDR8+XMePH5ckFSpUSCNGjFCvXr3sHBmyut9++00jR47U3r17de3aNT3xxBMaNmyYmjZtau/QkIW1a9dO69evl7e3t8qXLy8nJyeb7YsXL7ZTZMgOWrRooWrVqumDDz5Q3rx5tW/fPhUtWlSdO3dWYmKiFi5caO8QkUX99NNP6t69u4YOHaqRI0dqxIgRNj9GN2nSxN4hIovic9FcJN3IUHFxcbp27Zp8fX3tHQqyuDt37ujjjz/WSy+9lKyLJpBePXv2fOD26dOnP6JIkB0dOHBAwcHBeuKJJ7Ru3Tq1bt1aBw8e1JUrV7R582ZrTzEgLfgxGmbgc9FcJN1It0aNGmnx4sXy8vKyKY+NjVXbtm21bt06+wSGLM/d3V0HDhxQsWLF7B0KADyUmJgYffHFFzaJUf/+/VWwYEF7hwYAeMRIupFuDg4OioyMTHZ1OyoqSo899hgTeyDN2rRpo/bt26t79+72DgXZ1MWLF3XkyBFJUunSpeXj42PniJAdREREKCAgIMVxkRERESpSpIgdokJ2UKJECe3YsUP58+e3KY+OjtYTTzxhXbcbSCs+F83BRGpIs3379ln//vPPPxUZGWm9n5CQoBUrVuixxx6zR2jIJpo3b663335b+/fvV7Vq1eTm5mazvXXr1naKDFnd9evXFRISolmzZlnXWHZ0dFS3bt00ceLEFCfBAlKrePHiOn/+fLIfoy9fvqzixYsrISHBTpEhqzt58mSK5098fLzOnj1rh4iQXfC5aC6SbqRZlSpVZLFYZLFY1KhRo2TbXV1dNXHiRDtEhuzi1VdflXR3Ddx7WSwWvrgizUJDQxUeHq6lS5eqTp06kqRNmzZp4MCBGjx4sKZMmWLnCJGVGYaR4lXua9euKXfu3HaICFndzz//bP175cqV8vT0tN5PSEjQ2rVrGYqFdOFz0Vx0L0eanTp1SoZhqESJEtq+fbtN9xNnZ2f5+vrK0dHRjhECQMoKFCighQsXqkGDBjbl69evV8eOHXXx4kX7BIYsLTQ0VJL0+eefq3fv3jZXhhISEvT777/L0dFRmzdvtleIyKIcHBwk3f3B+d6v7k5OTipWrJg+++wzPfPMM/YID9kAn4vm4ko30ixpjcikLihARps1a5Y6deqUbF3bW7duad68eerWrZudIkNWFxcXJz8/v2Tlvr6+iouLs0NEyA52794t6e6V7v3798vZ2dm6zdnZWZUrV9Ybb7xhr/CQhSV91ypevLh27NihAgUK2DkiZDd8LpqLK91Ik59//lnNmzeXk5OTTZenlDDuFmnl6Oh433GRvr6+dC9HmgUHByt//vyaNWuWtbvvjRs31L17d125ckVr1qyxc4TIynr27KnPP/9cHh4e9g4FAFKFz0VzkXQjTf49Y3lSl6eUMO4W6eHg4KALFy4kmzlz7969atiwoa5cuWKnyJDVHThwQM2aNVN8fLwqV64s6e55lTt3bq1cuVLly5e3c4QAcNeECRPUp08f5c6dWxMmTHhg3YEDBz6iqJDd8LloLpJuAJlO1apVZbFYtHfvXpUvX165cv3/SJiEhASdOHFCTz/9tBYsWGDHKJHVxcXFac6cOTp8+LAkqWzZsurSpYtcXV3tHBmyovbt22vGjBny8PBQ+/btH1h38eLFjygqZAfFixfXH3/8ofz586t48eL3rWexWFgyDOnC56J5GNMNINNp27atJGnPnj1q1qyZ3N3drducnZ1VrFgxdejQwU7RIbvIkyePevfube8wkE14enpaZyz/98zSQHqdOHEixb+BjMbnonm40o00+a/uTf9GVyek1cyZM9WpUyeW2EGGYC4KAAD+H5+Ljw5JN9LkQd2b/o2uTgAyC+aiAJAVJS1Flxpjx441MRJkN3wuPjp0L0ea0L0Jj4KDg4O1u2ZK+ADAw/j38oYsdYiMljQXRWrs2rXL5GiQnSQtRfdfUnv+AUn4XHx0SLoBZFqLFy+2+RJx+/Zt7d69WzNnztSIESPsGBmyOtaAR0ZLmosCyGjr16+3dwjIoaKjo+Xl5WXvMLIFupcjTUJDQ/XBBx/Izc3tP7s90dUJGW3u3LmaP3++fvrpJ3uHgiyKNeABAPh/o0ePVrFixdSpUydJ0nPPPadFixapYMGC+vXXX63LiCFtuNKNNNm9e7du375t/ft+6OoEM9SqVUt9+vSxdxjIwgzDSPH/pzNnzjDzNIBMheXo8ChMnTpVc+bMkSStXr1aa9as0YoVK7RgwQK9+eabWrVqlZ0jzNpIupEm/+7qRLcnPEo3btzQhAkT9Nhjj9k7FGRBSeNuLRaLgoOD77sGPPCwvL299ddff6lAgQLKly/fA390vnLlyiOMDFkdy9HhUYiMjFRAQIAkadmyZerYsaOaNm2qYsWKqWbNmnaOLusj6UaGOn36tCRZ37RAetz7xdUwDF29elWurq7WX2OBh8Ea8DDLuHHjlDdvXknS+PHj7RsMspXp06en+DeQkfLly6fTp08rICBAK1as0Icffijp7ncvhlylH2O6kW537tzRiBEjNGHCBF27dk2S5O7urpCQEL3//vtycnKyc4TIqmbOnGlz38HBQT4+PqpZs6bOnj2rChUq2CkyZHWsAQ8gK4uKitKRI0ckSaVLl042PwXwsAYMGKBly5apVKlS2r17t06ePCl3d3fNmzdPY8aMYdWFdCLpRrr169dPixcv1siRIxUUFCRJ2rp1q4YPH662bdtqypQpdo4Q2cXVq1f1/fffa9q0afrjjz/45RVAppWQkKAff/xRhw4dkiSVK1dObdq0sRnSADys2NhY9e/fX/PmzbN+Bjo6OqpTp06aNGkS3c+RZrdv39bnn3+u06dPq0ePHqpataqk/+/F8/LLL9s5wqyNpBvp5unpqXnz5ql58+Y25b/++quef/55xcTE2CkyZBcbN27UtGnTtGjRIhUqVEjt27dXhw4d9OSTT9o7NGRRCQkJGjdunBYsWKCIiAjdunXLZjtjbpEeBw8eVOvWrRUZGanSpUtLkv766y/5+Pho6dKl9NJBmnXq1Em7d+/WxIkTbS50vPbaa6pSpYrmzZtn5wgBpISfW5FuLi4uKlasWLLy4sWLy9nZ+dEHhGwhMjJSM2bM0LRp0xQbG6uOHTsqPj5eS5YsUbly5ewdHrK4ESNG6JtvvtHgwYP17rvv6p133tHJkye1ZMkSDRs2zN7hIYt7+eWXVb58ef3xxx/Kly+fJOmff/5Rjx491KdPH23ZssXOESKrWrZsmVauXKm6detay5o1a6avv/6aSSCRbkePHtX69esVFRWlxMREm218NqYPV7qRbiNHjtThw4c1ffp0ubi4SJLi4+PVq1cvlSpVSu+//76dI0RW06pVK23cuFEtW7ZUly5d9PTTT8vR0VFOTk7au3cvSTfSLTAwUBMmTFDLli2VN29e7dmzx1q2bds2zZ07194hIgtzdXXVH3/8ofLly9uUHzhwQE8++aRu3Lhhp8iQ1RUpUkS//PKLKlasaFO+b98+tWjRQmfOnLFTZMjqvv76a/Xr108FChSQv7+/zUS2FouFMd3pxJVupMm960SuWbNGhQsXVuXKlSVJe/fu1a1btxQcHGyP8JDFLV++XAMHDlS/fv1UqlQpe4eDbCgyMtL6pdXd3d06DOaZZ57Re++9Z8/QkA08/vjjunDhQrKkOyoqSiVLlrRTVMgO3n33XYWGhmr27Nny9/eXdPf/szfffJP/u5AuH374oT766CMNGTLE3qFkSyTdSJN7J+q4d4kdlgxDemzatEnTpk1TtWrVVLZsWXXt2lWdO3e2d1jIRgoXLqzz58+rSJEiCgwM1KpVq/TEE09ox44d1h47wMOIjY21/h0WFqaBAwdq+PDhqlWrliRp27ZtGjlypEaPHm2vEJFFVa1a1eaq49GjR1WkSBEVKVJEkhQRESEXFxddvHhRr7zyir3CRBb3zz//6LnnnrN3GNkW3csBZFrXr1/X/Pnz9e2332r79u1KSEjQ2LFj9dJLL1nXwwXS4u2335aHh4f+97//af78+XrxxRdVrFgxRUREaNCgQRo1apS9Q0QW4+DgYJMYJX29Sir7931WXsDDGDFiRKrrMqQPadWrVy89+eST6tu3r71DyZZIugFkCUeOHNG0adM0e/ZsRUdHq0mTJvr555/tHRayia1bt2rr1q0qVaqUWrVqZe9wkAWFh4enuu5TTz1lYiQA8PDCwsI0duxYtWzZUhUrVpSTk5PN9oEDB9opsuyBpBtp8sQTT2jt2rXKly9fsm5P92LiBWSkhIQELV26VN9++y1JNwAAQAYoXrz4fbdZLBb9/fffjzCa7Icx3UiTNm3aWMc9tm3b1r7BIEdxdHRU27ZtOe+QLjNnzlSBAgXUsmVLSdJbb72lr776SuXKldP333+vokWL2jlCZAdxcXEprgNfqVIlO0WErC4hIUHjxo3TggULUjy3rly5YqfIkNWdOHHC3iFka1zpBgDkOKVLl9aUKVPUqFEjbd26VcHBwRo/fryWLVumXLlyafHixfYOEVnYxYsX1bNnTy1fvjzF7YzpRloNGzZM33zzjQYPHqx3331X77zzjk6ePKklS5Zo2LBhdAFGut26dUsnTpxQYGCgcuXi+mxGcbB3AMj6Tp8+bbMu5Pbt2/X666/rq6++smNUAHB/p0+fti7dtGTJEj377LPq06ePwsLC9Ntvv9k5OmR1r7/+uqKjo/X777/L1dVVK1as0MyZM1WqVCmGxSBd5syZo6+//lqDBw9Wrly59Pzzz+ubb77RsGHDtG3bNnuHhywsLi5OvXr1Up48eVS+fHlFRERIkkJCQphcNAOQdCPdXnjhBa1fv17S3bUiGzdurO3bt+udd97RyJEj7RwdACTn7u6uy5cvS5JWrVqlJk2aSJJy586tGzdu2DM0ZAPr1q3T2LFjVb16dTk4OKho0aJ68cUXNWbMGIWFhdk7PGRhkZGRqlixoqS7/4/FxMRIkp555hn98ssv9gwNWdzQoUO1d+9ebdiwQblz57aWN27cWPPnz7djZNkDSTfS7cCBA6pRo4YkacGCBapYsaK2bNmiOXPmaMaMGfYNDgBS0KRJE7388st6+eWX9ddff6lFixaSpIMHD6pYsWL2DQ5Z3vXr1+Xr6ytJypcvny5evChJqlixIpOLIl0KFy6s8+fPS5ICAwO1atUqSdKOHTusc+0AabFkyRJ98cUXqlu3rs0EyeXLl9fx48ftGFn2QNKNdLt9+7b1P/o1a9aodevWkqQyZcpYPxgAIDOZNGmSgoKCdPHiRS1atEj58+eXJO3cuVPPP/+8naNDVle6dGkdOXJEklS5cmV9+eWXOnv2rKZOnaqCBQvaOTpkZe3atdPatWsl3e32+95776lUqVLq1q2bXnrpJTtHh6zs4sWL1h8L/+369esPXKUIqcNEaki3mjVrqmHDhmrZsqWaNm2qbdu2qXLlytq2bZueffZZm/HeAABkd999953u3LmjHj16aOfOnXr66ad15coVOTs7a8aMGerUqZO9Q0Q2sW3bNm3ZskWlSpVSq1at7B0OsrD69evrueeeU0hIiPLmzat9+/apePHiCgkJ0dGjR7VixQp7h5ilkXQj3TZs2KB27dopNjZW3bt317fffitJ+t///qfDhw8zCzCATGHfvn2qUKGCHBwctG/fvgfWZUknZKS4uDgdPnxYRYoUUYECBewdDrKwjRs3qnbt2slmlb5z5462bNmi+vXr2ykyZHWbNm1S8+bN9eKLL2rGjBl65ZVX9Oeff2rLli0KDw9XtWrV7B1ilkbSjQyRkJCg2NhY5cuXz1p28uRJ5cmTJ8WuKgDwqDk4OCgyMlK+vr5ycHCQxWLRvz8Ck+5bLBaWdAKQKTk6Our8+fPJvltdvnxZvr6+/N+FdDl+/LhGjRqlvXv36tq1a3riiSc0ZMgQ6+R9SDsWX0O63bhxQ4ZhWBPuU6dO6ccff1TZsmXVrFkzO0cHAHedOHFCPj4+1r+BjBQaGqoPPvhAbm5uCg0NfWDdsWPHPqKokN0k/TB4r8uXL8vNzc0OESE7CQwM1Ndff23vMLIlkm6kW5s2bdS+fXv17dtX0dHRqlmzppycnHTp0iWNHTtW/fr1s3eIAKCiRYum+DeQEXbv3q3Dhw+ratWq2r17933rMSER0qJ9+/aS7p4/PXr0sJmpPCEhQfv27VPt2rXtFR6yicTERB07dkxRUVFKTEy02cbQhfQh6Ua67dq1S+PGjZMkLVy4UH5+ftq9e7cWLVqkYcOGkXQDyBR+/vnnVNdNWoUBSK3169dbu/6uX79ektSpUydNmDBBfn5+do4OWZ2np6eku1e68+bNK1dXV+s2Z2dn1apVS71797ZXeMgGtm3bphdeeEGnTp3SvaOPGXaVfiTdSLe4uDjlzZtXkrRq1Sq1b99eDg4OqlWrlk6dOmXn6ADgrrZt26aqHl8ukFb3flFdvny5rl+/bqdokJ1Mnz5dklSsWDG98cYbdCVHhuvbt6+qV6+uX375RQULFqRXTgYj6Ua6lSxZUkuWLFG7du20cuVKDRo0SJIUFRUlDw8PO0cHAHfd21UOMBtz1SKjvf/++/YOAdnU0aNHtXDhQpUsWdLeoWRLJN1It2HDhumFF17QoEGD1KhRIwUFBUm6e9W7atWqdo4OAIBHw2KxJLs6xNUipNcTTzyhtWvXKl++fKpateoDz6ldu3Y9wsiQndSsWVPHjh0j6TYJSTfS7dlnn1XdunV1/vx5Va5c2VoeHBysdu3a2TEyALi/69evKzw8XBEREbp165bNtoEDB9opKmRlhmHYTHJ18+ZN9e3bN1lX4MWLF9sjPGRRbdq0sZ5TqR0mA6TGvn37rH+HhIRo8ODBioyMVMWKFeXk5GRTt1KlSo86vGyFdbqRYY4dO6bjx4+rfv36cnV1ve+yFgBgb7t371aLFi0UFxen69evy9vbW5cuXVKePHnk6+urv//+294hIgvq2bNnquoljc8FAHtycHCQxWK571CYpG3MdZJ+JN1It8uXL6tjx45av369LBaLjh49qhIlSuill15Svnz59Nlnn9k7RACw0aBBAz3++OOaOnWqPD09tXfvXjk5OenFF1/Ua6+9Zl2eBwAyo507d+rQoUOSpPLlyzOcD2nyMBMes9Rm+pB0I926deumqKgoffPNNypbtqz27t2rEiVKaOXKlQoNDdXBgwftHSIA2PDy8tLvv/+u0qVLy8vLS1u3blXZsmX1+++/q3v37jp8+LC9QwSAZKKiotS5c2dt2LBBXl5ekqTo6Gg1bNhQ8+bNk4+Pj30DBJAiB3sHgKxv1apVGj16tAoXLmxTXqpUKZYMA5ApOTk5ycHh7kegr6+vIiIiJN1dC/f06dP2DA0A7iskJERXr17VwYMHdeXKFV25ckUHDhxQbGwsc1Eg3WbPnq06deqoUKFC1u/w48eP108//WTnyLI+km6k2/Xr15UnT55k5VeuXLFO/AEAmUnVqlW1Y8cOSdJTTz2lYcOGac6cOXr99ddVoUIFO0cHAClbsWKFJk+erLJly1rLypUrp0mTJmn58uV2jAxZzcqVKxUTE2O9P2XKFIWGhqpFixaKjo62juH28vLS+PHj7RRl9kHSjXSrV6+eZs2aZb1vsViUmJioMWPGqGHDhnaMDABS9vHHH6tgwYKSpI8++kj58uVTv379dPHiRX311Vd2jg4AUpaYmJhsVmnpbu+dxMREO0SErCoyMlJ16tTRmTNnJEkTJ07U119/rXfeeUeOjo7WetWrV9f+/fvtFWa2wZhupNuBAwcUHBysJ554QuvWrVPr1q2t3Z42b96swMBAe4cIAACQ5bVp00bR0dH6/vvvVahQIUnS2bNn1aVLF+XLl08//vijnSNEVrJo0SINGzZMBw8elKurqw4fPqyiRYsqb9681jmajh49qkqVKunGjRv2DjdL40o30q1ChQr666+/VLduXbVp00bXr19X+/bttXv3bhJuAACADPLFF18oNjZWxYoVU2BgoAIDA1W8eHHFxsZq4sSJ9g4PWUyHDh30888/S5KKFy+uPXv2JKuzYsUKm+EMSJtc9g4A2YOnp6feeecde4cBAKlSvHhxWSyW+25nnW4AmVFAQIB27dqlNWvWWFdZKFu2rBo3bmznyJBVJV0gCw0NVf/+/XXz5k0ZhqHt27fr+++/V1hYmL755hs7R5n10b0c6TZ9+nS5u7vrueeesyn/4YcfFBcXp+7du9spMgBI2eeff25z//bt29q9e7dWrFihN998U2+//badIgMAwD7mzJmj4cOH6/jx45KkQoUKacSIEerVq5edI8v6SLqRbo8//ri+/PLLZJOmhYeHq0+fPjpy5IidIgOAhzNp0iT98ccfmj59ur1DAQBJ0oQJE1Jdl2XDkBZ37tzR3Llz1axZM/n5+SkuLk7Xrl2Tr6+vvUPLNki6kW65c+fW4cOHVaxYMZvykydPqmzZsky8ACDL+Pvvv1WlShXFxsbaOxQAkHR3OExqWCwWhsYgzfLkyaNDhw6paNGi9g4lW2JMN9LN19dX+/btS5Z07927V/nz57dPUACQBgsXLpS3t7e9wwAAqxMnTtg7BOQANWrU0O7du0m6TULSjXR7/vnnNXDgQOXNm1f169eXdLdr+WuvvabOnTvbOToASK5q1ao2E6kZhqHIyEhdvHhRkydPtmNkAJA6SZ1VHzQpJJBar776qgYPHqwzZ86oWrVqcnNzs9leqVIlO0WWPdC9HOl269Ytde3aVT/88INy5br7O05iYqK6deumqVOnytnZ2c4RAoCt4cOH23xRdXBwkI+Pjxo0aKAyZcrYMTIAeLBp06Zp3LhxOnr0qCSpVKlSev311/Xyyy/bOTJkZQ4OyVeStlgsMgxDFotFCQkJdogq+yDpRoY5evSo9uzZI1dXV1WsWJHuKQAAABlo2LBhGjt2rEJCQhQUFCRJ2rp1q7744gsNGjRII0eOtHOEyKpOnTr1wO18r08fkm4AQI7j6Oio8+fPJ5uZ9fLly/L19eUXfQCZko+PjyZMmKDnn3/epvz7779XSEiILl26ZKfIADxI8n4EwEPq0KGDRo8enax8zJgxydbuBoDM4H6/N8fHxzMkBkCmdfv2bVWvXj1ZebVq1XTnzh07RITs5MiRIxowYICCg4MVHBysAQMGsPRvBmEiNaTbxo0bNXz48GTlzZs312efffboAwKA+0ha79Ziseibb76Ru7u7dVtCQoI2btzImG4AmVbXrl01ZcoUjR071qb8q6++UpcuXewUFbKDRYsWqXPnzqpevbp16MK2bdtUoUIFzZs3Tx06dLBzhFkb3cuRbq6urtqzZ49Kly5tU3748GFVrVqVdboBZBpJ692eOnVKhQsXlqOjo3Wbs7OzihUrppEjR6pmzZr2ChEA7iskJESzZs1SQECAatWqJUn6/fffFRERoW7dusnJycla997EHHiQwMBAdenSJdm8AO+//76+++47HT9+3E6RZQ8k3Ui3GjVq6JlnntGwYcNsyocPH66lS5dq586ddooMAFLWsGFDLV68WPny5bN3KACQag0bNkxVPYvFonXr1pkcDbKTPHnyaN++fSpZsqRN+dGjR1W5cmXFxcXZKbLsge7lSLf33ntP7du31/Hjx9WoUSNJ0tq1azV37lwtXLjQztEBQHLr16+3dwgA8ND4vwtmadCggX777bdkSfemTZtUr149O0WVfZB0I91atWqlJUuW6OOPP9bChQvl6uqqypUra926dfL29rZ3eACQTIcOHVSjRg0NGTLEpnzMmDHasWOHfvjhBztFBgD3d/HiRfn4+KS4bf/+/apYseIjjgjZRevWrTVkyBDt3LnTOnRh27Zt+uGHHzRixAj9/PPPNnXxcOhejgwXGxur77//XtOmTdPOnTtZegdApuPj46N169Yl+4K6f/9+NW7cWBcuXLBTZABwf/7+/po2bZpatmxpU/7pp5/qvffeYx4dpJmDQ+oWtbJYLHy3TwOWDEOG2bhxo7p3765ChQrps88+U6NGjbRt2zZ7hwUAyVy7di3FpcGcnJwUGxtrh4gA4L+FhoaqQ4cO6tevn27cuKGzZ88qODhYY8aM0dy5c+0dHrKwxMTEVN1IuNOGpBvpEhkZqVGjRqlUqVJ67rnn5OHhofj4eC1ZskSjRo3Sk08+ae8QASCZihUrav78+cnK582bp3LlytkhIgD4b2+99Za2bt2q3377TZUqVVKlSpXk4uKiffv2qV27dvYOD8B9MKYbadaqVStt3LhRLVu21Pjx4/X000/L0dFRU6dOtXdoAPBATAAJIKsqWbKkKlSooEWLFkmSOnXqJH9/fztHhexgx44dWr9+vaKiopSYmGizjSXo0oekG2m2fPlyDRw4UP369VOpUqXsHQ4ApBoTQALIijZv3qwXX3xR3t7e2rdvnzZv3qyQkBD9+uuvmjp1KssgIs0+/vhjvfvuuypdurT8/PxksVis2/79N9KGidSQZtu2bdO0adM0f/58lS1bVl27dlXnzp1VsGBB7d27ly6aALIMJoAEkBW4uLho0KBB+uCDD+Tk5CRJOn78uF588UWdPn1aZ86csXOEyKr8/Pw0evRo9ejRw96hZEuM6Uaa1apVS19//bXOnz+vV155RfPmzVOhQoWUmJio1atX6+rVq/YOEQAeiAkgAWQlq1at0qhRo6wJtyQFBgZq8+bNeuWVV+wYGbI6BwcH1alTx95hZFsk3Ug3Nzc3vfTSS9q0aZP279+vwYMHa9SoUfL19WUdPwCZDhNAAshqWrRooZiYGD311FOSpFGjRik6Otq6/Z9//tH3339vp+iQHQwaNEiTJk2ydxjZFt3LYYqEhAQtXbpU3377rX7++Wd7hwMAkmwngOzSpYt1AkgnJyeGxQDItBwdHXX+/Hn5+vpKkjw8PLRnzx6VKFFCknThwgUVKlSIoTFIs8TERLVs2VJ//fWXypUrZ9ObQpIWL15sp8iyByZSgykcHR3Vtm1btW3b1t6hAIAVE0ACyIruvUbGNTNktIEDB2r9+vVq2LCh8ufPz+RpGYykGwCQY2zatEnTpk1TtWrVbCaABAAgJ5s5c6YWLVqkli1b2juUbIkx3QCAHIMJIAFkRRaLJdmVR65EIiN5e3srMDDQ3mFkW4zpBgDkaEeOHNG0adM0e/ZsRUdHq0mTJsxFASBTcXBwUPPmzeXi4iJJWrp0qRo1aiQ3NzdJUnx8vFasWMGYbqTZ9OnTtWLFCk2fPl158uSxdzjZDkk3AABiAkgAmVfPnj1TVW/69OkmR4LsqmrVqjp+/LgMw1CxYsWSTaS2a9cuO0WWPZB0AwAAAEAONmLEiAduf//99x9RJNkTSTcAAAAAACZh9nIAAAAAgHbu3KlDhw5JksqXL6+qVavaOaLsgaQbAAAAAHKwqKgode7cWRs2bJCXl5ckKTo6Wg0bNtS8efPk4+Nj3wCzOJYMAwAAAIAcLCQkRFevXtXBgwd15coVXblyRQcOHFBsbKwGDhxo7/CyPMZ0AwAAAEAO5unpqTVr1ujJJ5+0Kd++fbuaNm2q6Oho+wSWTXClGwAAAABysMTExGTLhEmSk5OTEhMT7RBR9kLSDQAAAAA5WKNGjfTaa6/p3Llz1rKzZ89q0KBBCg4OtmNk2QPdywEAAAAgBzt9+rRat26tgwcPKiAgwFpWoUIF/fzzzypcuLCdI8zaSLoBAAAAIIczDENr1qzR4cOHJUlly5ZV48aN7RxV9kDSDQAAAAA50Lp16zRgwABt27ZNHh4eNttiYmJUu3ZtTZ06VfXq1bNThNkDY7oBAAAAIAcaP368evfunSzhlu7OaP7KK69o7NixdogseyHpBgAAAIAcaO/evXr66afvu71p06bauXPnI4woeyLpBgAAAIAc6MKFCykuFZYkV65cunjx4iOMKHsi6QYAAACAHOixxx7TgQMH7rt93759Kliw4COMKHsi6QYAAACAHKhFixZ67733dPPmzWTbbty4offff1/PPPOMHSLLXpi9HAAAAAByoAsXLuiJJ56Qo6OjBgwYoNKlS0uSDh8+rEmTJikhIUG7du2Sn5+fnSPN2ki6AQAAACCHOnXqlPr166eVK1cqKTW0WCxq1qyZJk2apOLFi9s5wqyPpBsAAAAAcrh//vlHx44dk2EYKlWqlPLly2fvkLINkm4AAAAAAEzCRGoAAAAAAJiEpBsAAAAAAJOQdAMAAAAAYBKSbgAAkKJbt27p448/1qFDh+wdCgAAWRZJNwAASNHgwYO1f/9+lSlT5pG0t2HDBlksFkVHRz+S9gAAeBRIugEAyIIiIyMVEhKiEiVKyMXFRQEBAWrVqpXWrl2bqsfPmDFDXl5e992+YMECHTx4UDNnzpTFYsmgqB+sdu3aOn/+vDw9PR9JewAAPAq57B0AAAB4OCdPnlSdOnXk5eWlTz75RBUrVtTt27e1cuVK9e/fX4cPH053Gx07dlTHjh0zINrUuX37tpydneXv7//I2gQA4FHgSjcAAFnMq6++KovFou3bt6tDhw56/PHHVb58eYWGhmrbtm2SpLFjx6pixYpyc3NTQECAXn31VV27dk3S3W7cPXv2VExMjCwWiywWi4YPHy5Jio+P1xtvvKHHHntMbm5uqlmzpjZs2GDT/tdff62AgADlyZNH7dq109ixY5NdNZ8yZYoCAwPl7Oys0qVLa/bs2TbbLRaLpkyZotatW8vNzU0fffRRit3LN23apHr16snV1VUBAQEaOHCgrl+/nqHPJwAAZiLpBgAgC7ly5YpWrFih/v37y83NLdn2pOTXwcFBEyZMsHYRX7dund566y1Jd7txjx8/Xh4eHjp//rzOnz+vN954Q5I0YMAAbd26VfPmzdO+ffv03HPP6emnn9bRo0clSZs3b1bfvn312muvac+ePWrSpIk++ugjmxh+/PFHvfbaaxo8eLAOHDigV155RT179tT69ett6g0fPlzt2rXT/v379dJLLyU7luPHj+vpp59Whw4dtG/fPs2fP1+bNm3SgAED0v08AgDwqFgMwzDsHQQAAEid7du3q2bNmlq8eLHatWuX6sctXLhQffv21aVLlyTdHdP9+uuv21xVjoiIUIkSJRQREaFChQpZyxs3bqwaNWro448/VufOnXXt2jUtW7bMuv3FF1/UsmXLrPuqU6eOypcvr6+++spap2PHjrp+/bp++eUXSXevdL/++usaN26ctc6GDRvUsGFD/fPPP/Ly8tLLL78sR0dHffnll9Y6mzZt0lNPPaXr168rd+7cqT5+AADshSvdAABkIan9rXzNmjUKDg7WY489prx586pr1666fPmy4uLi7vuY/fv3KyEhQY8//rjc3d2tt/DwcB0/flySdOTIEdWoUcPmcffeP3TokOrUqWNTVqdOnWRLj1WvXv2Bx7B3717NmDHDJpZmzZopMTFRJ06c+M/nAACAzICJ1AAAyEJKlSoli8XywMnSTp48qWeeeUb9+vXTRx99JG9vb23atEm9evXSrVu3lCdPnhQfd+3aNTk6Omrnzp1ydHS02ebu7p6hxyEpxe7x98bzyiuvaODAgcm2FSlSJMPjAQDADCTdAABkId7e3mrWrJkmTZqkgQMHJktco6OjtXPnTiUmJuqzzz6Tg8PdTm0LFiywqefs7KyEhASbsqpVqyohIUFRUVGqV69eiu2XLl1aO3bssCm7937ZsmW1efNmde/e3Vq2efNmlStX7qGO9YknntCff/6pkiVLPtTjAADITOheDgBAFjNp0iQlJCSoRo0aWrRokY4ePapDhw5pwoQJCgoKUsmSJXX79m1NnDhRf//9t2bPnq2pU6fa7KNYsWK6du2a1q5dq0uXLikuLk6PP/64unTpom7dumnx4sU6ceKEtm/frrCwMOtY7JCQEP36668aO3asjh49qi+//FLLly+3Wcv7zTff1IwZMzRlyhQdPXpUY8eO1eLFi62TtaXWkCFDtGXLFg0YMEB79uzR0aNH9dNPPzGRGgAgSyHpBgAgiylRooR27dqlhg0bavDgwapQoYKaNGmitWvXasqUKapcubLGjh2r0aNHq0KFCpozZ47CwsJs9lG7dm317dtXnTp1ko+Pj8aMGSNJmj59urp166bBgwerdOnSatu2rXbs2GHtzl2nTh1NnTpVY8eOVeXKlbVixQoNGjTIZlKztm3b6vPPP9enn36q8uXL68svv9T06dPVoEGDhzrOSpUqKTw8XH/99Zfq1aunqlWratiwYTaTvAEAkNkxezkAAEiX3r176/Dhw/rtt9/sHQoAAJkOY7oBAMBD+fTTT9WkSRO5ublp+fLlmjlzpiZPnmzvsAAAyJS40g0AAB5Kx44dtWHDBl29elUlSpRQSEiI+vbta++wAADIlEi6AQAAAAAwCROpAQAAAABgEpJuAAAAAABMQtINAAAAAIBJSLoBAAAAADAJSTcAAAAAACYh6QYAAAAAwCQk3QAAAAAAmISkGwAAAAAAk5B0AwAAAABgEpJuAAAAAABMQtINAMD/tXfncVVU/x/H3xcERBAQFXAXcVfcvyq575mppOWSW6WZpmhi6zd3U9O+qWmmleaWpmVmmbkvmFvu+5qiWIq4hCioKMzvjx7cX1fUUBgvF1/Px4NH3jOHOZ+BIXjfmXMGAADAJIRuAAAAAABMQugGAAAAAMAkhG4AsKPbt2/rww8/1NKlS+1dChzcTz/9pLFjx+r27dv2LgUAAPwDoRsA7Ojdd9/V9OnTVbNmTXuXck8bNmyQxWLRhg0b/rXv6dOnZbFYNGvWLNPrSqv69eurfv369i7DdDt37lSHDh1UvHhxubi42K2OWbNmyWKx6PTp04997Ndff11NmjR57OPaS8rP2//+979/7Tts2DBZLBbTa3pc4zwu06ZNU+HChXXr1i17lwLAwRG6ASCdUoJGyke2bNlUoEABvfTSS/rzzz/v+3k//vijvv76a61YsUJ58+Z9jBWn9tlnn6U5LM+fP18TJ040tR78LS1f69jYWLVr104ffvih2rZt+3gKy2QiIyM1ffp0/fe//7W2pYTS+318+OGHdqwYabFlyxYNGzZMsbGxpo4zevRoLVmyJFX7Sy+9pMTERH3++eemjg8g68tm7wIAIKsYMWKEAgMDdfPmTW3btk2zZs3Spk2bdPDgQWXPnj1V/9OnT2v58uUqXry4Haq19dlnnylPnjx66aWXbNrr1q2rGzduyNXV1do2f/58HTx4UG+88YZN3yJFiujGjRt2vdKa1dzva/1Pe/fu1aBBg/TKK688vsLuo0uXLurQoYPc3Nwe67iffPKJAgMD1aBBg1TbOnbsqGeeeSZVe+XKlR9HaUiHLVu2aPjw4XrppZfk4+Nj2jijR4/W888/r9DQUJv27Nmzq1u3bho/frzCwsKy1FV8AI8XoRsAMkjz5s1VrVo1SVKPHj2UJ08ejR07Vj/99JPatWuXqn///v0fd4mpJCQkKEeOHPfd7uTkdM83DO7FYrGkuS8yTma4hT4+Pl4eHh5ydnaWs7PzYx379u3bmjdvnnr16nXP7VWqVFHnzp0fa03IOtq1a6dx48Zp/fr1atiwob3LAeCguL0cAExSp04dSdLJkydt2o8eParnn39evr6+yp49u6pVq6affvrJpk/KLesbN27Ua6+9pty5c8vLy0tdu3bVX3/9ZdP3xx9/VIsWLZQ/f365ubkpKChII0eOVFJSkk2/+vXrq3z58tq1a5fq1q2rHDly6L///a+KFi2qQ4cOKSIiwnrrbUqIu3tOd/369bVs2TKdOXPG2rdo0aKS7j+ne926dapTp448PDzk4+Oj1q1b68iRIzZ9UuaC/v7779arWt7e3nr55ZeVkJCQpq/3F198oaCgILm7u6t69er69ddf79nv1q1bGjp0qIoXLy43NzcVKlRIb7/9dqp5m6tXr1bt2rXl4+MjT09PlSpVyub25Qf5+uuvVb16deXIkUO5cuVS3bp1tWrVKuv2tHzPHvS1fpjjuHHjhvr166c8efIoZ86catWqlf78809ZLBYNGzbMpu+ePXvUvHlzeXl5ydPTU40aNdK2bdts+qScmxEREXr99dfl5+enggUL2my7e0738uXLredAzpw51aJFCx06dMimT3R0tF5++WUVLFhQbm5uypcvn1q3bv2v88M3bdqkr3qjagAAbJtJREFUS5cuqXHjxg/s9yBFixbVs88+q02bNql69erKnj27ihUrpjlz5tj0u337toYPH64SJUooe/bsyp07t2rXrq3Vq1fb9HuYn/FNmzapX79+yps3r3x8fPTaa68pMTFRsbGx6tq1q3LlyqVcuXLp7bfflmEY96x/woQJKlKkiNzd3VWvXj0dPHgwTcf99ddfq2rVqnJ3d5evr686dOigs2fPpulzN23apP/85z/Knj27goKCHngL9qOMM2zYML311luSpMDAQOvPwD/Ph7Ts98SJE2rbtq0CAgKUPXt2FSxYUB06dNDVq1cl/f1mYXx8vGbPnm0d4593/FStWlW+vr768ccf0/R1AYB74Uo3AJgk5Y/DXLlyWdsOHTqkWrVqqUCBAnr33Xfl4eGhb7/9VqGhofr+++/13HPP2eyjb9++8vHx0bBhw3Ts2DFNnTpVZ86csYZh6e8/3j09PRUeHi5PT0+tW7dOQ4YMUVxcnD766COb/V2+fFnNmzdXhw4d1LlzZ/n7+6t+/foKCwuTp6en3n//fUmSv7//PY/p/fff19WrV/XHH39owoQJkiRPT8/7fg3WrFmj5s2bq1ixYho2bJhu3LihyZMnq1atWtq9e7dNiJT+vqoUGBioMWPGaPfu3Zo+fbr8/Pw0duzYB36tZ8yYoddee01PPfWU3njjDZ06dUqtWrWSr6+vChUqZO2XnJysVq1aadOmTerZs6fKlCmjAwcOaMKECTp+/Lh1XuehQ4f07LPPqkKFChoxYoTc3Nz0+++/a/PmzQ+sQ5KGDx+uYcOG6amnntKIESPk6uqq3377TevWrVPTpk0lpe179qCvdVqPQ/p7Xuq3336rLl26qGbNmoqIiFCLFi1S1X3o0CHVqVNHXl5eevvtt+Xi4qLPP/9c9evXV0REhGrUqGHT//XXX1fevHk1ZMgQxcfH3/frMXfuXHXr1k3NmjXT2LFjlZCQoKlTp6p27dras2eP9Rxo27atDh06pLCwMBUtWlQxMTFavXq1oqKiUp0n/7RlyxZZLJb73i6ekJCgS5cupWr38fFRtmz//2fQ77//rueff17du3dXt27d9NVXX+mll15S1apVVa5cOUl/B8ExY8aoR48eql69uuLi4rRz507t3r3buojbw/6Mh4WFKSAgQMOHD9e2bdv0xRdfyMfHR1u2bFHhwoU1evRo/fLLL/roo49Uvnx5de3a1ebz58yZo2vXrqlPnz66efOmPvnkEzVs2FAHDhy478+xJI0aNUqDBw9Wu3bt1KNHD128eFGTJ09W3bp1tWfPngfezn3gwAE1bdpUefPm1bBhw3Tnzh0NHTr0nuM96jht2rTR8ePH9c0332jChAnKkyePJFnXv0jLfhMTE9WsWTPdunXL+nX+888/9fPPPys2Nlbe3t6aO3eu9fvZs2dPSVJQUJBNLVWqVEnTzz4A3JcBAEiXmTNnGpKMNWvWGBcvXjTOnj1rLFq0yMibN6/h5uZmnD171tq3UaNGRnBwsHHz5k1rW3JysvHUU08ZJUqUSLXPqlWrGomJidb2cePGGZKMH3/80dqWkJCQqqbXXnvNyJEjh8049erVMyQZ06ZNS9W/XLlyRr169VK1r1+/3pBkrF+/3trWokULo0iRIqn6RkZGGpKMmTNnWtsqVapk+Pn5GZcvX7a27du3z3BycjK6du1qbRs6dKghyXjllVds9vncc88ZuXPnTjXWPyUmJhp+fn5GpUqVjFu3blnbv/jiC0OSzXHNnTvXcHJyMn799VebfUybNs2QZGzevNkwDMOYMGGCIcm4ePHiA8e+24kTJwwnJyfjueeeM5KSkmy2JScnW/+d1u/Z/b7WaT2OXbt2GZKMN954w6bfSy+9ZEgyhg4dam0LDQ01XF1djZMnT1rbzp07Z+TMmdOoW7eutS3l3Kxdu7Zx584dm/2mbIuMjDQMwzCuXbtm+Pj4GK+++qpNv+joaMPb29va/tdffxmSjI8++ijVsf6bzp073/McSTkf7/exdetWa98iRYoYkoyNGzda22JiYgw3Nzdj4MCB1raKFSsaLVq0eGA9D/sz3qxZM5tzIyQkxLBYLEavXr2sbXfu3DEKFixocy6nHJ+7u7vxxx9/WNt/++03Q5IxYMAAa1vKz1eK06dPG87OzsaoUaNsaj9w4ICRLVu2VO13Cw0NNbJnz26cOXPG2nb48GHD2dk5Q8f56KOPbM6nh93vnj17DEnGd99998BxPDw8jG7dut13e8+ePQ13d/cH7gMAHoTbywEggzRu3Fh58+ZVoUKF9Pzzz8vDw0M//fST9dbbK1euaN26dWrXrp2uXbumS5cu6dKlS7p8+bKaNWumEydOpFrtvGfPnjYLk/Xu3VvZsmXTL7/8Ym1zd3e3/jtlv3Xq1FFCQoKOHj1qsz83Nze9/PLLZhx+KufPn9fevXv10ksvydfX19peoUIFNWnSxOYYUtw9L7dOnTq6fPmy4uLi7jvOzp07FRMTo169etks+PbSSy/J29vbpu93332nMmXKqHTp0tav/6VLl6xzNdevXy9J1qtvP/74o5KTk9N8zEuWLFFycrKGDBkiJyfbX7H/XITpYb5n95LW41ixYoWkv69K/1NYWJjN66SkJK1atUqhoaEqVqyYtT1fvnx68cUXtWnTplTfg1dfffVf52+vXr1asbGx6tixo02dzs7OqlGjhrVOd3d3ubq6asOGDammT/yby5cv29xNcreePXtq9erVqT7Kli1r069s2bLWKSHS31dUS5UqpVOnTlnbfHx8dOjQIZ04ceKeYz3Kz3j37t1tzo0aNWrIMAx1797d2ubs7Kxq1arZ1JIiNDRUBQoUsL6uXr26atSocc+frxSLFy9WcnKy2rVrZ/N9CQgIUIkSJazfl3tJSkrSypUrFRoaqsKFC1vby5Qpo2bNmmXYOA+S1v2m/PyvXLkyzdNU7iVXrly6ceNGuvYB4MnG7eUAkEGmTJmikiVL6urVq/rqq6+0ceNGm1Wcf//9dxmGocGDB2vw4MH33EdMTIzNH9AlSpSw2e7p6al8+fLZzGs8dOiQBg0apHXr1qUKRinzFlMUKFDAJpia6cyZM5KkUqVKpdpWpkwZrVy50roAV4p//hEv/f+t+X/99Ze8vLweOM7dXysXFxebACn9Pb/zyJEj931EW0xMjCSpffv2mj59unr06KF3331XjRo1Ups2bfT888+nCtP/dPLkSTk5OaUKdHd7mO/ZvaT1OM6cOSMnJycFBgbabL97xfyLFy8qISHhvt+r5ORknT171nqbtaRU+7xfnZLuuwBVyvfUzc1NY8eO1cCBA+Xv76+aNWvq2WefVdeuXRUQEPCv4xj3mess/X1epGW+993nnvT3+ffPNwFGjBih1q1bq2TJkipfvryefvppdenSRRUqVJD0aD/jd4+bEhT/OS0ipf1eb0jcfd5LUsmSJfXtt9/e71B14sQJGYZxz8+V9MAnEFy8eFE3bty45+eWKlXKJuynZ5wHSet+AwMDFR4ervHjx2vevHmqU6eOWrVqpc6dO6d6Q+5BUs4vVi8H8KgI3QCQQapXr25dvTw0NFS1a9fWiy++qGPHjsnT09N6xfTNN99MdUUoxcM+Piw2Nlb16tWTl5eXRowYoaCgIGXPnl27d+/WO++8k+oq7T+vsGZG97ty+qBQ9TCSk5MVHBys8ePH33N7StBxd3fXxo0btX79ei1btkwrVqzQwoUL1bBhQ61atSpdK3Q/7PcsPcdhprScSynHMnfu3HuG53/OqX7jjTfUsmVLLVmyRCtXrtTgwYM1ZswYrVu37oGP98qdO/dDXx2/l7Sce3Xr1tXJkyf1448/atWqVZo+fbomTJigadOmqUePHo/0M36/ce/VnpE/BxaLRcuXL7/nOA9apyEzjPMw+/3444/10ksvWb9n/fr105gxY7Rt2zbrXUj/5q+//lKOHDky/f8/AWRehG4AMIGzs7PGjBmjBg0a6NNPP9W7775rverq4uKS5pWWT5w4YfPs4evXr+v8+fPW5w5v2LBBly9f1uLFi1W3bl1rv8jIyIeq92Gu4KS1b5EiRSRJx44dS7Xt6NGjypMnj81V7keVMs6JEydsrqjevn1bkZGRqlixorUtKChI+/btU6NGjf71OJycnNSoUSM1atRI48eP1+jRo/X+++9r/fr19/3+BQUFKTk5WYcPH1alSpXu2edhvmf3qzGtx1GkSBElJycrMjLS5qrg77//btMvb968ypEjx32/V05OTo8U5FMWpPLz80vTOR8UFKSBAwdq4MCBOnHihCpVqqSPP/5YX3/99X0/p3Tp0po3b56uXr36UFcvH5Wvr69efvllvfzyy7p+/brq1q2rYcOGqUePHo/0M55e97rV/fjx4w9cfC4oKEiGYSgwMFAlS5Z8qPHy5s0rd3f3e4579/mTnnGkB5//D7Pf4OBgBQcHa9CgQdqyZYtq1aqladOm6YMPPnjgOCkiIyNVpkyZh64fAFIwpxsATFK/fn1Vr15dEydO1M2bN+Xn56f69evr888/1/nz51P1v3jxYqq2L774Qrdv37a+njp1qu7cuaPmzZtL+v+rYf+8ApaYmKjPPvvsoWr18PBQbGxsmvum5RbofPnyqVKlSpo9e7bNvg8ePKhVq1ZZ3zhIr2rVqilv3ryaNm2aEhMTre2zZs1KdUzt2rXTn3/+qS+//DLVfm7cuGFdhfvKlSuptqeE6LsfyfVPoaGhcnJy0ogRI1JdsU75Hj3M9+x+X+u0HkfK1da79z158mSb187OzmratKl+/PFHm6kLFy5c0Pz581W7du373t7/IM2aNZOXl5dGjx5tcx6nSDnnExISdPPmTZttQUFBypkz5wO/3pIUEhIiwzC0a9euh67vYV2+fNnmtaenp4oXL26t8VF+xtNryZIlNvPEt2/frt9++836/4h7adOmjZydnTV8+PBUV88Nw0h1nP/k7OysZs2aacmSJYqKirK2HzlyRCtXrsywcSRZ35S7++c4rfuNi4vTnTt3bLYHBwfLycnJ5rz6t///7d69W0899dQDawWAB+FKNwCY6K233tILL7ygWbNmqVevXpoyZYpq166t4OBgvfrqqypWrJguXLigrVu36o8//tC+fftsPj8xMVGNGjVSu3btdOzYMX322WeqXbu2WrVqJUl66qmnlCtXLnXr1k39+vWTxWLR3LlzH/o21KpVq2rq1Kn64IMPVLx4cfn5+d13Hm7VqlW1cOFChYeH6z//+Y88PT3VsmXLe/b96KOP1Lx5c4WEhKh79+7WR4Z5e3unekb0o3JxcdEHH3yg1157TQ0bNlT79u0VGRmpmTNnpprT3aVLF3377bfq1auX1q9fr1q1aikpKUlHjx7Vt99+q5UrV6patWoaMWKENm7cqBYtWqhIkSKKiYnRZ599poIFC6p27dr3raV48eJ6//33NXLkSNWpU0dt2rSRm5ubduzYofz582vMmDEP9T2739c6rcdRtWpVtW3bVhMnTtTly5etjww7fvy4JNsrfB988IH12eSvv/66smXLps8//1y3bt3SuHHjHul74+XlpalTp6pLly6qUqWKOnTooLx58yoqKkrLli1TrVq19Omnn+r48ePW87xs2bLKli2bfvjhB124cEEdOnR44Bi1a9dW7ty5tWbNmnues7t3777nlfKgoCCFhIQ81PGULVtW9evXtz67eefOnVq0aJH69u1r7fOwP+PpVbx4cdWuXVu9e/fWrVu3NHHiROXOnVtvv/32fT8nKChIH3zwgd577z2dPn1aoaGhypkzpyIjI/XDDz+oZ8+eevPNN+/7+cOHD9eKFStUp04dvf7667pz544mT56scuXKaf/+/Rk2TtWqVSX9/fi8Dh06yMXFRS1btkzzftetW6e+ffvqhRdeUMmSJXXnzh3NnTtXzs7Oatu2rc04a9as0fjx45U/f34FBgZaH5G3a9cuXblyRa1bt07z9wQAUnlcy6QDQFaV8uifHTt2pNqWlJRkBAUFGUFBQdbHK508edLo2rWrERAQYLi4uBgFChQwnn32WWPRokWp9hkREWH07NnTyJUrl+Hp6Wl06tTJ5vFbhmEYmzdvNmrWrGm4u7sb+fPnN95++21j5cqVqR71Va9ePaNcuXL3PIbo6GijRYsWRs6cOW0es3WvR4Zdv37dePHFFw0fHx9DkvWRVvd6ZJhhGMaaNWuMWrVqGe7u7oaXl5fRsmVL4/DhwzZ9Uh5pdPcjuu5+BNWDfPbZZ0ZgYKDh5uZmVKtWzdi4caNRr169VI9CS0xMNMaOHWuUK1fOcHNzM3LlymVUrVrVGD58uHH16lXDMAxj7dq1RuvWrY38+fMbrq6uRv78+Y2OHTsax48f/9c6DMMwvvrqK6Ny5crW/derV89YvXq1dXtav2f3+1qn9TgMwzDi4+ONPn36GL6+voanp6cRGhpqHDt2zJBkfPjhhzZ1796922jWrJnh6elp5MiRw2jQoIGxZcsWmz4POt/v9/1av3690axZM8Pb29vInj27ERQUZLz00kvGzp07DcMwjEuXLhl9+vQxSpcubXh4eBje3t5GjRo1jG+//TZNX+9+/foZxYsXt2n7t0eG/fMRUUWKFLnno8DuPn8++OADo3r16oaPj4/h7u5ulC5d2hg1apTNY/0M4+F+xu/+Ot7vZ6Fbt26Gh4dHquP76KOPjI8//tgoVKiQ4ebmZtSpU8fYt2/fPfd5t++//96oXbu24eHhYXh4eBilS5c2+vTpYxw7dixV37tFREQYVatWNVxdXY1ixYoZ06ZNM2WckSNHGgUKFDCcnJxSnVv/tt9Tp04Zr7zyihEUFGRkz57d8PX1NRo0aGCsWbPGZoyjR48adevWNdzd3VOdG++8845RuHBhm8e6AcDDshhGBq3KAQDIMLNmzdLLL7+sHTt2WBdnAzLK3r17VblyZX399dfq1KmTvctJt1OnTql06dJavny5GjVqZO9ykEXcunVLRYsW1bvvvqv+/fvbuxwADow53QAAZGE3btxI1TZx4kQ5OTnZLOTmyIoVK6bu3bvrww8/tHcpyEJmzpwpFxcX9erVy96lAHBwzOkGACALGzdunHbt2qUGDRooW7ZsWr58uZYvX66ePXs+lkeLPS5Tp061dwnIYnr16kXgBpAhCN0AAGRhTz31lFavXq2RI0fq+vXrKly4sIYNG6b333/f3qUBAPBEYE43AAAAAAAmYU43AAAAAAAmIXQDAAAAAGAS5nSnUXJyss6dO6ecOXPKYrHYuxwAAAAAgB0ZhqFr164pf/78cnK6//VsQncanTt3Lkut8goAAAAASL+zZ8+qYMGC991O6E6jnDlzSvr7C+rl5WXnagAAAAAA9hQXF6dChQpZs+L9ELrTKOWWci8vL0I3AAAAAECS/nX6MQupAQAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgkmz2LgDp0/KblvYuwaEs7bjU3iUAAAAAeIJwpRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADBJpg/dw4YNk8VisfkoXbq0dfvNmzfVp08f5c6dW56enmrbtq0uXLhgs4+oqCi1aNFCOXLkkJ+fn9566y3duXPncR8KAAAAAOAJ4xDP6S5XrpzWrFljfZ0t2/+XPWDAAC1btkzfffedvL291bdvX7Vp00abN2+WJCUlJalFixYKCAjQli1bdP78eXXt2lUuLi4aPXr0Yz8WAAAAAMCTwyFCd7Zs2RQQEJCq/erVq5oxY4bmz5+vhg0bSpJmzpypMmXKaNu2bapZs6ZWrVqlw4cPa82aNfL391elSpU0cuRIvfPOOxo2bJhcXV0f9+EAAAAAAJ4Qmf72ckk6ceKE8ufPr2LFiqlTp06KioqSJO3atUu3b99W48aNrX1Lly6twoULa+vWrZKkrVu3Kjg4WP7+/tY+zZo1U1xcnA4dOnTfMW/duqW4uDibDwAAAAAAHkamD901atTQrFmztGLFCk2dOlWRkZGqU6eOrl27pujoaLm6usrHx8fmc/z9/RUdHS1Jio6OtgncKdtTtt3PmDFj5O3tbf0oVKhQxh4YAAAAACDLy/S3lzdv3tz67woVKqhGjRoqUqSIvv32W7m7u5s27nvvvafw8HDr67i4OII3AAAAAOChZPor3Xfz8fFRyZIl9fvvvysgIECJiYmKjY216XPhwgXrHPCAgIBUq5mnvL7XPPEUbm5u8vLysvkAAAAAAOBhOFzovn79uk6ePKl8+fKpatWqcnFx0dq1a63bjx07pqioKIWEhEiSQkJCdODAAcXExFj7rF69Wl5eXipbtuxjrx8AAAAA8OTI9LeXv/nmm2rZsqWKFCmic+fOaejQoXJ2dlbHjh3l7e2t7t27Kzw8XL6+vvLy8lJYWJhCQkJUs2ZNSVLTpk1VtmxZdenSRePGjVN0dLQGDRqkPn36yM3Nzc5HBwAAAADIyjJ96P7jjz/UsWNHXb58WXnz5lXt2rW1bds25c2bV5I0YcIEOTk5qW3btrp165aaNWumzz77zPr5zs7O+vnnn9W7d2+FhITIw8ND3bp104gRI+x1SAAAAACAJ4TFMAzD3kU4gri4OHl7e+vq1auZan53y29a2rsEh7K041J7lwAAAAAgC0hrRnS4Od0AAAAAADgKQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmyWbvAgBkTi2/aWnvEhzK0o5L7V0CAAAAMiGudAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0AwAAAABgEkI3AAAAAAAmIXQDAAAAAGAShwrdH374oSwWi9544w1r282bN9WnTx/lzp1bnp6eatu2rS5cuGDzeVFRUWrRooVy5MghPz8/vfXWW7pz585jrh4AAAAA8KRxmNC9Y8cOff7556pQoYJN+4ABA7R06VJ99913ioiI0Llz59SmTRvr9qSkJLVo0UKJiYnasmWLZs+erVmzZmnIkCGP+xAAAAAAAE8Yhwjd169fV6dOnfTll18qV65c1varV69qxowZGj9+vBo2bKiqVatq5syZ2rJli7Zt2yZJWrVqlQ4fPqyvv/5alSpVUvPmzTVy5EhNmTJFiYmJ9jokAAAAAMATwCFCd58+fdSiRQs1btzYpn3Xrl26ffu2TXvp0qVVuHBhbd26VZK0detWBQcHy9/f39qnWbNmiouL06FDh+475q1btxQXF2fzAQAAAADAw8hm7wL+zYIFC7R7927t2LEj1bbo6Gi5urrKx8fHpt3f31/R0dHWPv8M3CnbU7bdz5gxYzR8+PB0Vg8AAAAAeJJl6ivdZ8+eVf/+/TVv3jxlz579sY793nvv6erVq9aPs2fPPtbxAQAAAACOL1OH7l27dikmJkZVqlRRtmzZlC1bNkVERGjSpEnKli2b/P39lZiYqNjYWJvPu3DhggICAiRJAQEBqVYzT3md0ude3Nzc5OXlZfMBAAAAAMDDyNShu1GjRjpw4ID27t1r/ahWrZo6depk/beLi4vWrl1r/Zxjx44pKipKISEhkqSQkBAdOHBAMTEx1j6rV6+Wl5eXypYt+9iPCQAAAADw5MjUc7pz5syp8uXL27R5eHgod+7c1vbu3bsrPDxcvr6+8vLyUlhYmEJCQlSzZk1JUtOmTVW2bFl16dJF48aNU3R0tAYNGqQ+ffrIzc3tsR8TAAAAAODJkalDd1pMmDBBTk5Oatu2rW7duqVmzZrps88+s253dnbWzz//rN69eyskJEQeHh7q1q2bRowYYceqAQAAAABPAocL3Rs2bLB5nT17dk2ZMkVTpky57+cUKVJEv/zyi8mVAQAAAABgy5Q53Tdu3FBCQoL19ZkzZzRx4kStWrXKjOEAAAAAAMiUTAndrVu31pw5cyRJsbGxqlGjhj7++GO1bt1aU6dONWNIAAAAAAAyHVNC9+7du1WnTh1J0qJFi+Tv768zZ85ozpw5mjRpkhlDAgAAAACQ6ZgSuhMSEpQzZ05J0qpVq9SmTRs5OTmpZs2aOnPmjBlDAgAAAACQ6ZgSuosXL64lS5bo7NmzWrlypZo2bSpJiomJkZeXlxlDAgAAAACQ6ZgSuocMGaI333xTRYsWVY0aNRQSEiLp76velStXNmNIAAAAAAAyHVMeGfb888+rdu3aOn/+vCpWrGhtb9SokZ577jkzhgQAAAAAINMx7TndAQEBCggIsGmrXr26WcMBAAAAAJDpmBK64+Pj9eGHH2rt2rWKiYlRcnKyzfZTp06ZMSwAAAAAAJmKKaG7R48eioiIUJcuXZQvXz5ZLBYzhgEAAAAAIFMzJXQvX75cy5YtU61atczYPQAAAAAADsGU1ctz5colX19fM3YNAAAAAIDDMCV0jxw5UkOGDFFCQoIZuwcAAAAAwCGYcnv5xx9/rJMnT8rf319FixaVi4uLzfbdu3ebMSwAAAAAAJmKKaE7NDTUjN0CAAAAAOBQTAndQ4cONWO3AAAAAAA4FFNCd4pdu3bpyJEjkqRy5cqpcuXKZg4HAAAAAECmYkrojomJUYcOHbRhwwb5+PhIkmJjY9WgQQMtWLBAefPmNWNYAAAAAAAyFVNWLw8LC9O1a9d06NAhXblyRVeuXNHBgwcVFxenfv36mTEkAAAAAACZjilXulesWKE1a9aoTJky1rayZctqypQpatq0qRlDAgAAAACQ6ZhypTs5OTnVY8IkycXFRcnJyWYMCQAAAABApmNK6G7YsKH69++vc+fOWdv+/PNPDRgwQI0aNTJjSAAAAAAAMh1TQvenn36quLg4FS1aVEFBQQoKClJgYKDi4uI0efJkM4YEAAAAACDTMWVOd6FChbR7926tWbNGR48elSSVKVNGjRs3NmM4AAAAAAAyJdOe022xWNSkSRM1adLErCEAAAAAAMjUMix0T5o0Kc19eWwYAAAAAOBJkGGhe8KECWnqZ7FYCN0AAAAAgCdChoXuyMjIjNoVAAAAAABZgimrlwMAAAAAgAy80h0eHp7mvuPHj8+oYQEAAAAAyLQyLHTv2bMnTf0sFktGDQkAAAAAQKaWYaF7/fr1GbUrAAAAAACyBOZ0AwAAAABgkgy70t2mTRvNmjVLXl5eatOmzQP7Ll68OKOGBQAAAAAg08qw0O3t7W2dr+3l5cXcbQAAAADAEy/DQvfMmTOt/541a1ZG7RYAAAAAAIdlypzuhg0bKjY2NlV7XFycGjZsaMaQAAAAAABkOqaE7g0bNigxMTFV+82bN/Xrr7+aMSQAAAAAAJlOht1eLkn79++3/vvw4cOKjo62vk5KStKKFStUoECBjBwSAAAAAIBMK0NDd6VKlWSxWGSxWO55G7m7u7smT56ckUMCAAAAAJBpZWjojoyMlGEYKlasmLZv3668efNat7m6usrPz0/Ozs4ZOSQAAAAAAJlWhobuIkWKSJKSk5MzcrcAAAAAADikDA3d/3TixAmtX79eMTExqUL4kCFDzBoWAAAAAIBMw5TQ/eWXX6p3797KkyePAgICZLFYrNssFguhGwAAAADwRDAldH/wwQcaNWqU3nnnHTN2DwAAAACAQzDlOd1//fWXXnjhBTN2DQAAAACAwzAldL/wwgtatWqVGbsGAAAAAMBhmHJ7efHixTV48GBt27ZNwcHBcnFxsdner18/M4YFAAAAACBTMSV0f/HFF/L09FRERIQiIiJstlksFkI3AAAAAOCJYErojoyMNGO3AAAAAAA4FFPmdAMAAAAAAJOudEvSH3/8oZ9++klRUVFKTEy02TZ+/HizhgUAAAAAINMwJXSvXbtWrVq1UrFixXT06FGVL19ep0+flmEYqlKlihlDAgAAAACQ6Zhye/l7772nN998UwcOHFD27Nn1/fff6+zZs6pXrx7P7wYAAAAAPDFMCd1HjhxR165dJUnZsmXTjRs35OnpqREjRmjs2LEPta+pU6eqQoUK8vLykpeXl0JCQrR8+XLr9ps3b6pPnz7KnTu3PD091bZtW124cMFmH1FRUWrRooVy5MghPz8/vfXWW7pz5076DxQAAAAAgAcwJXR7eHhY53Hny5dPJ0+etG67dOnSQ+2rYMGC+vDDD7Vr1y7t3LlTDRs2VOvWrXXo0CFJ0oABA7R06VJ99913ioiI0Llz59SmTRvr5yclJalFixZKTEzUli1bNHv2bM2aNUtDhgzJgCMFAAAAAOD+TJnTXbNmTW3atEllypTRM888o4EDB+rAgQNavHixatas+VD7atmypc3rUaNGaerUqdq2bZsKFiyoGTNmaP78+WrYsKEkaebMmSpTpoy2bdummjVratWqVTp8+LDWrFkjf39/VapUSSNHjtQ777yjYcOGydXVNcOOGwAAAACAfzLlSvf48eNVo0YNSdLw4cPVqFEjLVy4UEWLFtWMGTMeeb9JSUlasGCB4uPjFRISol27dun27dtq3LixtU/p0qVVuHBhbd26VZK0detWBQcHy9/f39qnWbNmiouLs14tv5dbt24pLi7O5gMAAAAAgIdhypXuYsWKWf/t4eGhadOmpWt/Bw4cUEhIiG7evClPT0/98MMPKlu2rPbu3StXV1f5+PjY9Pf391d0dLQkKTo62iZwp2xP2XY/Y8aM0fDhw9NVNwAAAADgyWbac7olKTExUTExMUpOTrZpL1y48EPtp1SpUtq7d6+uXr2qRYsWqVu3boqIiMjIUlN57733FB4ebn0dFxenQoUKmTomAAAAACBrMSV0Hz9+XN27d9eWLVts2g3DkMViUVJS0kPtz9XVVcWLF5ckVa1aVTt27NAnn3yi9u3bKzExUbGxsTZXuy9cuKCAgABJUkBAgLZv326zv5TVzVP63Iubm5vc3Nweqk4AAAAAAP7JlND98ssvK1u2bPr555+VL18+WSyWDN1/cnKybt26papVq8rFxUVr165V27ZtJUnHjh1TVFSUQkJCJEkhISEaNWqUYmJi5OfnJ0lavXq1vLy8VLZs2QytCwAAAACAfzIldO/du1e7du1S6dKl072v9957T82bN1fhwoV17do1zZ8/Xxs2bNDKlSvl7e2t7t27Kzw8XL6+vvLy8lJYWJhCQkKsq6Q3bdpUZcuWVZcuXTRu3DhFR0dr0KBB6tOnD1eyAQAAAACmMiV0ly1b9qGfx30/MTEx6tq1q86fPy9vb29VqFBBK1euVJMmTSRJEyZMkJOTk9q2batbt26pWbNm+uyzz6yf7+zsrJ9//lm9e/dWSEiIPDw81K1bN40YMSJD6gMAAAAA4H4shmEYGbGjfz5Sa+fOnRo0aJBGjx6t4OBgubi42PT18vLKiCEfq7i4OHl7e+vq1auZqv6W37T8906wWtpxqb1LcBicWw+HcwsAAODJktaMmGFXun18fGzmbhuGoUaNGtn0edSF1AAAAAAAcEQZFrrXr1+fUbsCAAAAACBLyLDQXa9evYzaFQAAAAAAWYKTGTudOXOmvvvuu1Tt3333nWbPnm3GkAAAAAAAZDqmhO4xY8YoT548qdr9/Pw0evRoM4YEAAAAACDTMSV0R0VFKTAwMFV7kSJFFBUVZcaQAAAAAABkOqaEbj8/P+3fvz9V+759+5Q7d24zhgQAAAAAINMxJXR37NhR/fr10/r165WUlKSkpCStW7dO/fv3V4cOHcwYEgAAAACATCfDVi//p5EjR+r06dNq1KiRsmX7e4jk5GR17dqVOd0AAAAAgCeGKaHb1dVVCxcu1MiRI7Vv3z65u7srODhYRYoUMWM4AAAAAAAyJVNCd4qiRYvKMAwFBQVZr3gDAAAAAPCkMGVOd0JCgrp3764cOXKoXLly1hXLw8LC9OGHH5oxJAAAAAAAmU6GhO7PP/9cu3fvtr5+7733tG/fPm3YsEHZs2e3tjdu3FgLFy7MiCEBAAAAAMj0MiR0ly5dWq1bt9aqVaskST/88IM+/fRT1a5dWxaLxdqvXLlyOnnyZEYMCQAAAABAppchobtevXqKiIjQkCFDJEmXLl2Sn59fqn7x8fE2IRwAAAAAgKwsw+Z0FytWTBs3bpQkVatWTcuWLbNuSwna06dPV0hISEYNCQAAAABAppahS4q7urpKkkaPHq3mzZvr8OHDunPnjj755BMdPnxYW7ZsUUREREYOCQAAAABApmXK6uW1a9fW3r17defOHQUHB2vVqlXy8/PT1q1bVbVqVTOGBAAAAAAg0zHt4dlBQUH68ssvzdo9AAAAAACZnilXugEAAAAAQAZf6XZycpLFYpFhGLJYLEpKSsrI3QMAAAAA4FAyNHRHRkZm5O4AAAAAAHBoGRq6ixQpkpG7AwAAAADAoWVY6N6/f3+a+1aoUCGjhgUAAAAAINPKsNBdqVIlm/ncD8JcbwAAAADAkyDDVi+PjIzUqVOnFBkZqe+//16BgYH67LPPtGfPHu3Zs0efffaZgoKC9P3332fUkAAAAAAAZGoZdqX7n/O5X3jhBU2aNEnPPPOMta1ChQoqVKiQBg8erNDQ0IwaFgAAAACATMuU53QfOHBAgYGBqdoDAwN1+PBhM4YEAAAAACDTMSV0lylTRmPGjFFiYqK1LTExUWPGjFGZMmXMGBIAAAAAgEwnQx8ZlmLatGlq2bKlChYsaF2pfP/+/bJYLFq6dKkZQwIAAAAAkOmYErqrV6+uU6dOad68eTp69KgkqX379nrxxRfl4eFhxpAAAAfR8puW9i7BoSztyJvVAAA4MlNCtyR5eHioZ8+eZu0eAAAAAIBMz5Q53QAAAAAAgNANAAAAAIBpCN0AAAAAAJiE0A0AAAAAgElMC92xsbGaPn263nvvPV25ckWStHv3bv35559mDQkAAAAAQKZiyurl+/fvV+PGjeXt7a3Tp0/r1Vdfla+vrxYvXqyoqCjNmTPHjGEBAAAAAMhUTLnSHR4erpdeekknTpxQ9uzZre3PPPOMNm7caMaQAAAAAABkOqaE7h07dui1115L1V6gQAFFR0ebMSQAAAAAAJmOKaHbzc1NcXFxqdqPHz+uvHnzmjEkAAAAAACZjimhu1WrVhoxYoRu374tSbJYLIqKitI777yjtm3bmjEkAAAAAACZjimh++OPP9b169fl5+enGzduqF69eipevLhy5sypUaNGmTEkAAAAAACZjimrl3t7e2v16tXavHmz9u3bp+vXr6tKlSpq3LixGcMBAAAAAJApZXjovn37ttzd3bV3717VqlVLtWrVyughAAAAAABwCBl+e7mLi4sKFy6spKSkjN41AAAAAAAOxZQ53e+//77++9//6sqVK2bsHgAAAAAAh2DKnO5PP/1Uv//+u/Lnz68iRYrIw8PDZvvu3bvNGBYAAAAAgEzFlNAdGhpqxm4BAAAAAHAopoTuoUOHmrFbAAAAAAAciimhO8XOnTt15MgRSVLZsmVVtWpVM4cDAAAAACBTMSV0//HHH+rYsaM2b94sHx8fSVJsbKyeeuopLViwQAULFjRjWAAAAAAAMhVTVi/v0aOHbt++rSNHjujKlSu6cuWKjhw5ouTkZPXo0cOMIQEAAAAAyHRMudIdERGhLVu2qFSpUta2UqVKafLkyapTp44ZQwIAAAAAkOmYcqW7UKFCun37dqr2pKQk5c+f/6H2NWbMGP3nP/9Rzpw55efnp9DQUB07dsymz82bN9WnTx/lzp1bnp6eatu2rS5cuGDTJyoqSi1atFCOHDnk5+ent956S3fu3Hn4gwMAAAAAII1MCd0fffSRwsLCtHPnTmvbzp071b9/f/3vf/97qH1FRESoT58+2rZtm1avXq3bt2+radOmio+Pt/YZMGCAli5dqu+++04RERE6d+6c2rRpY92elJSkFi1aKDExUVu2bNHs2bM1a9YsDRkyJP0HCwAAAADAfVgMwzAyYke5cuWSxWKxvo6Pj9edO3eULdvfd7Cn/NvDw0NXrlx55HEuXrwoPz8/RUREqG7durp69ary5s2r+fPn6/nnn5ckHT16VGXKlNHWrVtVs2ZNLV++XM8++6zOnTsnf39/SdK0adP0zjvv6OLFi3J1dU01zq1bt3Tr1i3r67i4OBUqVEhXr16Vl5fXI9ef0Vp+09LeJTiUpR2X2rsEh8G59XA4t9KOc+vhcG4BAJA5xcXFydvb+18zYobN6Z44cWJG7eqBrl69Kkny9fWVJO3atUu3b99W48aNrX1Kly6twoULW0P31q1bFRwcbA3cktSsWTP17t1bhw4dUuXKlVONM2bMGA0fPtzkowEAAAAAZGUZFrq7deuWUbu6r+TkZL3xxhuqVauWypcvL0mKjo6Wq6ur9dFkKfz9/RUdHW3t88/AnbI9Zdu9vPfeewoPD7e+TrnSDQAAAABAWpmyenmKmJgYxcTEKDk52aa9QoUKj7S/Pn366ODBg9q0aVNGlPdAbm5ucnNzM30cAAAAAEDWZUro3rVrl7p166YjR47o7injFotFSUlJD73Pvn376ueff9bGjRtVsGBBa3tAQIASExMVGxtrc7X7woULCggIsPbZvn27zf5SVjdP6QMAAAAAQEYzZfXyV155RSVLltSWLVt06tQpRUZGWj9OnTr1UPsyDEN9+/bVDz/8oHXr1ikwMNBme9WqVeXi4qK1a9da244dO6aoqCiFhIRIkkJCQnTgwAHFxMRY+6xevVpeXl4qW7ZsOo4UAAAAAID7M+VK96lTp/T999+rePHi6d5Xnz59NH/+fP3444/KmTOndQ62t7e33N3d5e3tre7duys8PFy+vr7y8vJSWFiYQkJCVLNmTUlS06ZNVbZsWXXp0kXjxo1TdHS0Bg0apD59+nALOQAAAADANKZc6W7UqJH27duXIfuaOnWqrl69qvr16ytfvnzWj4ULF1r7TJgwQc8++6zatm2runXrKiAgQIsXL7Zud3Z21s8//yxnZ2eFhISoc+fO6tq1q0aMGJEhNQIAAAAAcC+mXOmePn26unXrpoMHD6p8+fJycXGx2d6qVas07ystjxHPnj27pkyZoilTpty3T5EiRfTLL7+keVwAAAAAANLLlNC9detWbd68WcuXL0+17VEXUgMAAAAAwNGYcnt5WFiYOnfurPPnzys5Odnmg8ANAAAAAHhSmBK6L1++rAEDBsjf39+M3QMAAAAA4BBMCd1t2rTR+vXrzdg1AAAAAAAOw5Q53SVLltR7772nTZs2KTg4ONVCav369TNjWAAAAAAAMhXTVi/39PRURESEIiIibLZZLBZCNwAAyHAtv2lp7xIcxtKOS+1dAgA8MUwJ3ZGRkWbsFgAAAAAAh2LKnO5/MgwjTc/aBgAAAAAgqzEtdM+ZM0fBwcFyd3eXu7u7KlSooLlz55o1HAAAAAAAmY4pt5ePHz9egwcPVt++fVWrVi1J0qZNm9SrVy9dunRJAwYMMGNYAAAAAAAyFVNC9+TJkzV16lR17drV2taqVSuVK1dOw4YNI3QDAAAAAJ4Iptxefv78eT311FOp2p966imdP3/ejCEBAAAAAMh0TAndxYsX17fffpuqfeHChSpRooQZQwIAAAAAkOmYcnv58OHD1b59e23cuNE6p3vz5s1au3btPcM4AAAAAABZkSlXutu2bavffvtNefLk0ZIlS7RkyRLlyZNH27dv13PPPWfGkAAAAAAAZDqmXOmWpKpVq+rrr782a/cAAAAAAGR6pj2nGwAAAACAJ12GXul2cnKSxWJ5YB+LxaI7d+5k5LAAAAAAAGRKGRq6f/jhh/tu27p1qyZNmqTk5OSMHBIAAAAAgEwrQ0N369atU7UdO3ZM7777rpYuXapOnTppxIgRGTkkAAAAAACZlmlzus+dO6dXX31VwcHBunPnjvbu3avZs2erSJEiZg0JAAAAAECmkuGh++rVq3rnnXdUvHhxHTp0SGvXrtXSpUtVvnz5jB4KAAAAAIBMLUNvLx83bpzGjh2rgIAAffPNN/e83RwAAAAAgCdFhobud999V+7u7ipevLhmz56t2bNn37Pf4sWLM3JYAAAAAAAypQwN3V27dv3XR4YBAAAAAPCkyNDQPWvWrIzcHQAAAAAADs201csBAAAAAHjSEboBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMEk2excAAAAAZGYtv2lp7xIcxtKOS+1dApDpcKUbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAk2T60L1x40a1bNlS+fPnl8Vi0ZIlS2y2G4ahIUOGKF++fHJ3d1fjxo114sQJmz5XrlxRp06d5OXlJR8fH3Xv3l3Xr19/jEcBAAAAAHgSZfrQHR8fr4oVK2rKlCn33D5u3DhNmjRJ06ZN02+//SYPDw81a9ZMN2/etPbp1KmTDh06pNWrV+vnn3/Wxo0b1bNnz8d1CAAAAACAJ1Smf0538+bN1bx583tuMwxDEydO1KBBg9S6dWtJ0pw5c+Tv768lS5aoQ4cOOnLkiFasWKEdO3aoWrVqkqTJkyfrmWee0f/+9z/lz5//nvu+deuWbt26ZX0dFxeXwUcGAAAAAMjqMv2V7geJjIxUdHS0GjdubG3z9vZWjRo1tHXrVknS1q1b5ePjYw3cktS4cWM5OTnpt99+u+++x4wZI29vb+tHoUKFzDsQAAAAAECW5NChOzo6WpLk7+9v0+7v72/dFh0dLT8/P5vt2bJlk6+vr7XPvbz33nu6evWq9ePs2bMZXD0AAAAAIKvL9LeX24ubm5vc3NzsXQYAAAAAwIE59JXugIAASdKFCxds2i9cuGDdFhAQoJiYGJvtd+7c0ZUrV6x9AAAAAAAwg0Nf6Q4MDFRAQIDWrl2rSpUqSfp7wbPffvtNvXv3liSFhIQoNjZWu3btUtWqVSVJ69atU3JysmrUqGGv0gEAAAA84Vp+09LeJTiMpR2X2ruER5bpQ/f169f1+++/W19HRkZq79698vX1VeHChfXGG2/ogw8+UIkSJRQYGKjBgwcrf/78Cg0NlSSVKVNGTz/9tF599VVNmzZNt2/fVt++fdWhQ4f7rlwOAAAAAEBGyPShe+fOnWrQoIH1dXh4uCSpW7dumjVrlt5++23Fx8erZ8+eio2NVe3atbVixQplz57d+jnz5s1T37591ahRIzk5Oalt27aaNGnSYz8WAAAAAMCTJdOH7vr168swjPtut1gsGjFihEaMGHHfPr6+vpo/f74Z5QEAAAAAcF8OvZAaAAAAAACZGaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkxC6AQAAAAAwCaEbAAAAAACTELoBAAAAADAJoRsAAAAAAJMQugEAAAAAMAmhGwAAAAAAkzxRoXvKlCkqWrSosmfPrho1amj79u32LgkAAAAAkIU9MaF74cKFCg8P19ChQ7V7925VrFhRzZo1U0xMjL1LAwAAAABkUdnsXcDjMn78eL366qt6+eWXJUnTpk3TsmXL9NVXX+ndd99N1f/WrVu6deuW9fXVq1clSXFxcY+n4DS6nXDb3iU4lMz2/cvMOLceDudW2nFuPRzOrbTj3Eo7zquHw7mVdpxbD4dzK+0y47mVUpNhGA/sZzH+rUcWkJiYqBw5cmjRokUKDQ21tnfr1k2xsbH68ccfU33OsGHDNHz48MdYJQAAAADA0Zw9e1YFCxa87/Yn4kr3pUuXlJSUJH9/f5t2f39/HT169J6f89577yk8PNz6Ojk5WVeuXFHu3LllsVhMrdfRxcXFqVChQjp79qy8vLzsXQ6yEM4tmIVzC2bh3IJZOLdgFs6ttDMMQ9euXVP+/Pkf2O+JCN2Pws3NTW5ubjZtPj4+9inGQXl5efGDClNwbsEsnFswC+cWzMK5BbNwbqWNt7f3v/Z5IhZSy5Mnj5ydnXXhwgWb9gsXLiggIMBOVQEAAAAAsronInS7urqqatWqWrt2rbUtOTlZa9euVUhIiB0rAwAAAABkZU/M7eXh4eHq1q2bqlWrpurVq2vixImKj4+3rmaOjOPm5qahQ4emuj0fSC/OLZiFcwtm4dyCWTi3YBbOrYz3RKxenuLTTz/VRx99pOjoaFWqVEmTJk1SjRo17F0WAAAAACCLeqJCNwAAAAAAj9MTMacbAAAAAAB7IHQDAAAAAGASQjcAAAAAACYhdAMAAAAAYBJCNwAAAAAAJiF0A3AIN2/etHcJAAAAwEPLZu8CkDXMnTtX06ZNU2RkpLZu3aoiRYpo4sSJCgwMVOvWre1dHhxUcnKyRo0apWnTpunChQs6fvy4ihUrpsGDB6to0aLq3r27vUuEg0pKStKsWbO0du1axcTEKDk52Wb7unXr7FQZspLff/9dJ0+eVN26deXu7i7DMGSxWOxdFrKImzdvKnv27PYuA1kEvxfNxZVuPLSVK1fq6tWr1tdTp05VeHi4nnnmGcXGxiopKUmS5OPjo4kTJ9qpSmQFH3zwgWbNmqVx48bJ1dXV2l6+fHlNnz7djpXB0fXv31/9+/dXUlKSypcvr4oVK9p8AA/j7j9OL1++rMaNG6tkyZJ65plndP78eUlS9+7dNXDgQHuUiCwiOTlZI0eOVIECBeTp6alTp05JkgYPHqwZM2bYuTo4Mn4vmswAHtKsWbOMcuXKGWfPnjUMwzDKlClj/PDDD4ZhGIanp6dx8uRJwzAM48CBA0bu3LntVSaygKCgIGPNmjWGYdieW0eOHDF8fHzsWRocXO7cuY1ly5bZuwxkER999JHN+dSlSxejWbNmxtmzZ23+37VixQqjbNmy9ioTDmjBggXGmTNnrK+HDx9uFCtWzPj6668Nd3d367m1YMECo2bNmvYqE1kAvxfNxZVuPLRu3bpp+PDhatasmSQpMjJSlStXTtXPzc1N8fHxj7s8ZCF//vmnihcvnqo9OTlZt2/ftkNFyCpcXV3veW4Bj6JJkybq16+f9UrjqlWrNHbsWBUsWNCmX4kSJXTmzBl7lAgHlT17dtWtW1f79u2TJM2ePVtffPGFOnXqJGdnZ2u/ihUr6ujRo/YqE1kAvxfNRejGI2nbtq1++uknSVJgYKD27t2bqs+KFStUpkyZx1wZspKyZcvq119/TdW+aNGie77RA6TVwIED9cknn8gwDHuXgiygYsWK2r59u5YsWSJJio+PV44cOVL1u3Llitzc3B5zdXBkrVu31oIFC9S5c2dJ0rlz53gzGqbg96K5WEgNjywoKEiSFB4erj59+ujmzZsyDEPbt2/XN998ozFjxjDvFukyZMgQdevWTX/++aeSk5O1ePFiHTt2THPmzNHPP/9s7/LgwDZt2qT169dr+fLlKleunFxcXGy2L1682E6VwVH5+vpq6dKlkqQ6depozpw5GjlypCTJYrEoOTlZ48aNU4MGDexZJhxQzZo1FRERIen/34wuUqSITR/ejEZ68XvRXIRupFuPHj3k7u6uQYMGKSEhQS+++KLy58+vTz75RB06dLB3eXBgrVu31tKlSzVixAh5eHhoyJAhqlKlipYuXaomTZrYuzw4MB8fHz333HP2LgNZ1Lhx49SoUSPt3LlTiYmJevvtt3Xo0CFduXJFmzdvtnd5cEC+vr6SeDMa5uH3orksBvcQIAMlJCTo+vXr8vPzs3cpcHB37tzR6NGj9corr6SaFwkAmd3Vq1f16aefat++fbp+/bqqVKmiPn36KF++fPYuDQ7u119/1YgRI2zOrSFDhqhp06b2Lg3AfRC6kW4NGzbU4sWL5ePjY9MeFxen0NBQnuuHR+bp6amDBw+qaNGi9i4FWdTFixd17NgxSVKpUqWUN29eO1eErCAqKkqFChW65zO5o6KiVLhwYTtUBQD/jt+L5mAhNaTbhg0blJiYmKr95s2b91wEC0irRo0aWeexARkpPj5er7zyivLly6e6deuqbt26yp8/v7p3766EhAR7lwcHFxgYqIsXL6Zqv3z5sgIDA+1QEbKKYsWK6fLly6naY2NjVaxYMTtUhKyC34vmYk43Htn+/fut/z58+LCio6Otr5OSkrRixQoVKFDAHqUhi2jevLneffddHThwQFWrVpWHh4fN9latWtmpMji68PBwRUREaOnSpapVq5akvxeR6devnwYOHKipU6fauUI4MsMw7nmV+/r168qePbsdKkJWcfr0aSUlJaVqv3Xrlv788087VISsgt+L5uL2cjwyJycn6x8V9zqN3N3dNXnyZL3yyiuPuzRkEU5O978Zx2Kx3PMPDyAt8uTJo0WLFql+/fo27evXr1e7du3ueZUS+Dfh4eGSpE8++USvvvqqzWPDkpKS9Ntvv8nZ2ZnF1PDQUh7TGhoaqtmzZ8vb29u6LSkpSWvXrtXq1auttwUDD4vfi+biSjceWWRkpAzDULFixbR9+3abOR+urq7y8/OTs7OzHSuEo0tOTrZ3CciiEhIS5O/vn6rdz8+P2+jwyPbs2SPp7zeiDxw4IFdXV+s2V1dXVaxYUW+++aa9yoMDCw0NlfT3G87dunWz2ebi4qKiRYvq448/tkNlyCr4vWgurnQDyLTmzJmj9u3by83NzaY9MTFRCxYsUNeuXe1UGRxdo0aNlDt3bs2ZM8d6u++NGzfUrVs3XblyRWvWrLFzhXBkL7/8sj755BN5eXnZuxRkMYGBgdqxY4fy5Mlj71KQxfB70VyEbjySn376Sc2bN5eLi4v1lqf7Yd4tHpWzs7POnz+f6hF0ly9flp+fH7eX45EdPHhQzZo1061bt1SxYkVJ0r59+5Q9e3atXLlS5cqVs3OFAAA8PvxeNBehG4/EyclJ0dHR8vPzY94tTOPk5KQLFy6kelzFvn371KBBA125csVOlSErSEhI0Lx583T06FFJUpkyZdSpUye5u7vbuTI4ojZt2mjWrFny8vJSmzZtHth38eLFj6kqZAWTJk1Sz549lT17dk2aNOmBffv16/eYqkJWxO9F8zCnG4/kn3NtmXeLjFa5cmVZLBZZLBY1atRI2bL9//+qkpKSFBkZqaefftqOFSIryJEjh1599VV7l4Eswtvb27q46D8XuQLSa8KECerUqZOyZ8+uCRMm3LefxWIhdCNd+L1oHq50A8h0hg8fbv3vwIED5enpad3m6uqqokWLqm3btjaLFAH/hmkxAAD8P34vPj6EbjySf7u96Z941xWPavbs2Wrfvj3PtUWGYFoMAAD/j9+Ljw+hG48kMDAwTf0sFotOnTplcjUAANhXyrSYtNi9e7fJ1SArSXn+e1qMHz/exEoAPCrmdOORREZG2rsEPAGcnJwe+Ecs77riUfE4OmS0lOcoAxkt5fnv/yatb/oAaRUbGysfHx97l5ElcKUbQKa1ZMkSmz8ibt++rT179mj27NkaPny4unfvbsfq4Mh4HB0AAP9v7NixKlq0qNq3by9JeuGFF/T9998rX758+uWXX6yPEcOjIXTjkYSHh2vkyJHy8PD419ueuNUJGW3+/PlauHChfvzxR3uXAgfF4+gAAPh/gYGBmjdvnp566imtXr1a7dq108KFC/Xtt98qKipKq1atsneJDo3by/FI9uzZo9u3b1v/fT/c6gQz1KxZUz179rR3GXBAPI4OZvH19dXx48eVJ08e5cqV64G//3hTBw+DZ8DjcYiOjlahQoUkST///LPatWunpk2bqmjRoqpRo4adq3N8hG48kvXr19/z34DZbty4oUmTJqlAgQL2LgUOKGXe7d69e9WsWbP7Po4OeFgTJkxQzpw5JUkTJ060bzHIUngGPB6HXLly6ezZsypUqJBWrFihDz74QJJkGAZTrjIAt5cjQ509e1aSrO+UAelx99UiwzB07do1ubu7a968eTwzEo+Mx9EBAPD/+vbtq59//lklSpTQnj17dPr0aXl6emrBggUaN24cT11IJ650I93u3Lmj4cOHa9KkSbp+/bokydPTU2FhYRo6dKhcXFzsXCEc1d1Xi5ycnJQ3b17VqFFDf/75p32KQpbQrVs3e5eALC4pKUk//PCDjhw5IkkqW7asWrdubTOlAXhUMTExOnbsmCSpVKlSqRaFBB7WhAkTVLRoUZ09e1bjxo2z3gl2/vx5vf7663auzvFxpRvp1rt3by1evFgjRoxQSEiIJGnr1q0aNmyYQkNDNXXqVDtXiKzi2rVr+uabbzRjxgzt3LmT253wyJKSkjRhwgTrAjGJiYk225lzi/Q4dOiQWrVqpejoaJUqVUqSdPz4ceXNm1dLly5V+fLl7VwhHFVcXJz69OmjBQsWWH8HOjs7q3379poyZQq3nwOZFKEb6ebt7a0FCxaoefPmNu2//PKLOnbsqKtXr9qpMmQVGzdu1IwZM/T9998rf/78atOmjdq2bav//Oc/9i4NDmrIkCGaPn26Bg4cqEGDBun999/X6dOntWTJEg0ZMkT9+vWzd4lwYCEhIcqbN69mz56tXLlySZL++usvvfTSS7p48aK2bNli5wrhqNq3b689e/Zo8uTJNhc6+vfvr0qVKmnBggV2rhCO7MSJE1q/fr1iYmKUnJxss23IkCF2qiprIHQj3fz8/BQREaEyZcrYtB85ckR169bVxYsX7VQZHFl0dLRmzZqlGTNmKC4uTu3atdO0adO0b98+lS1b1t7lwcEFBQVp0qRJatGihXLmzKm9e/da27Zt26b58+fbu0Q4MHd3d+3cuVPlypWzaT948KD+85//6MaNG3aqDI7Ow8NDK1euVO3atW3af/31Vz399NOKj4+3U2VwdF9++aV69+6tPHnyKCAgwGZNHYvFwpzudHKydwFwfH379tXIkSN169Yta9utW7c0atQo9e3b146VwVG1bNlSpUqV0v79+zVx4kSdO3dOkydPtndZyEKio6MVHBws6e81KFLuyHn22We1bNkye5aGLKBkyZK6cOFCqvaYmBgVL17cDhUhq8idO/c9byH39va23lUBPIoPPvhAo0aNUnR0tPbu3as9e/ZYPwjc6cdqHngkdz8ncs2aNSpYsKAqVqwoSdq3b58SExPVqFEje5QHB7d8+XL169dPvXv3VokSJexdDrKgggUL6vz58ypcuLCCgoK0atUqValSRTt27JCbm5u9y4MDiouLs/57zJgx6tevn4YNG6aaNWtKkrZt26YRI0Zo7Nix9ioRWcCgQYMUHh6uuXPnKiAgQNLfbyK+9dZbGjx4sJ2rgyP766+/9MILL9i7jCyL0I1Hcve7rHc/15ZHhiE9Nm3apBkzZqhq1aoqU6aMunTpog4dOti7LGQhzz33nNauXasaNWooLCxMnTt31owZMxQVFaUBAwbYuzw4IB8fn1SPOGzXrp21LWU2X8uWLVkEEg+lcuXKNufWiRMnVLhwYRUuXFiSFBUVJTc3N128eFGvvfaavcqEg3vhhRe0atUq9erVy96lZEnM6QaQacXHx2vhwoX66quvtH37diUlJWn8+PF65ZVXlDNnTnuXhyxk69at2rp1q0qUKKGWLVvauxw4oIiIiDT3rVevnomVIKsZPnx4mvsOHTrUxEqQlY0ZM0bjx49XixYtFBwcnOqRvywwmj6EbgAO4dixY5oxY4bmzp2r2NhYNWnSRD/99JO9ywIAAHB4gYGB991msVh06tSpx1hN1kPoxiOpUqWK1q5dq1y5cqW67eluLL6AjJSUlKSlS5fqq6++InTjkc2ePVt58uRRixYtJElvv/22vvjiC5UtW1bffPONihQpYucKkRUkJCTc8znwFSpUsFNFAAB7YE43Hknr1q2tiw2Fhobatxg8UZydnRUaGsp5h3QZPXq0pk6dKunvW8s//fRTTZw4UT///LMGDBigxYsX27lCOLKLFy/q5Zdf1vLly++5nTndeFRJSUmaMGGCvv3223u+oXPlyhU7VYasIjExUZGRkQoKClK2bETFjMKVbgDAEydHjhw6evSoChcurHfeeUfnz5/XnDlzdOjQIdWvX18XL160d4lwYJ06ddKZM2c0ceJE1a9fXz/88IMuXLigDz74QB9//LH1DgvgYQ0ZMkTTp0/XwIEDNWjQIL3//vs6ffq0lixZoiFDhjDvFo8sISFBYWFhmj17tiTp+PHjKlasmMLCwlSgQAG9++67dq7QsfGcbqTb2bNn9ccff1hfb9++XW+88Ya++OILO1YFAPfn6empy5cvS5JWrVqlJk2aSJKyZ8+uGzdu2LM0ZAHr1q3T+PHjVa1aNTk5OalIkSLq3Lmzxo0bpzFjxti7PDiwefPm6csvv9TAgQOVLVs2dezYUdOnT9eQIUO0bds2e5cHB/bee+9p37592rBhg7Jnz25tb9y4sRYuXGjHyrIGQjfS7cUXX9T69esl/f2syMaNG2v79u16//33NWLECDtXBwCpNWnSRD169FCPHj10/PhxPfPMM5KkQ4cOqWjRovYtDg4vPj5efn5+kqRcuXJZ75wIDg5mnROkS3R0tIKDgyX9/ebh1atXJUnPPvusli1bZs/S4OCWLFmiTz/9VLVr17ZZq6lcuXI6efKkHSvLGgjdSLeDBw+qevXqkqRvv/1WwcHB2rJli+bNm6dZs2bZtzgAuIcpU6YoJCREFy9e1Pfff6/cuXNLknbt2qWOHTvauTo4ulKlSunYsWOSpIoVK+rzzz/Xn3/+qWnTpilfvnx2rg6OrGDBgjp//rwkKSgoSKtWrZIk7dixw7rWDvAoLl68aH2z8J/i4+MfuGAy0obZ8Ui327dvW/9Hv2bNGrVq1UqSVLp0aesvBgDITHx8fPTpp5+man+Y5+EC99O/f3/r77+hQ4fq6aef1rx58+Tq6sqb0UiX5557TmvXrlWNGjUUFhamzp07a8aMGYqKitKAAQPsXR4cWLVq1bRs2TKFhYVJkjVoT58+XSEhIfYsLUtgITWkW40aNdSgQQO1aNFCTZs21bZt21SxYkVt27ZNzz//vM18bwCwl/3796t8+fJycnLS/v37H9iXRzohIyUkJFgX7suTJ4+9y0EWsm3bNm3ZskUlSpRQy5Yt7V0OHNimTZvUvHlzde7cWbNmzdJrr72mw4cPa8uWLYqIiFDVqlXtXaJDI3Qj3TZs2KDnnntOcXFx6tatm7766itJ0n//+18dPXqUR+8AyBScnJwUHR0tPz8/OTk5yWKx6J+/AlNeWywWHukEIFPauHGjnnrqqVSPcrpz5462bNmiunXr2qkyZAUnT57Uhx9+qH379un69euqUqWK3nnnHes6Anh0hG5kiKSkJMXFxSlXrlzWttOnTytHjhz3nB8CAI/bmTNnVLhwYVksFp05c+aBfYsUKfKYqkJWER4erpEjR8rDw0Ph4eEP7Dt+/PjHVBWyGmdnZ50/fz7V31aXL1+Wn58fbxgCmRRzupFuN27ckGEY1sB95swZ/fDDDypTpoyaNWtm5+oA4G//DNKEamS0PXv26OjRo6pcubL27Nlz334sSIT0SLkb526XL1+Wh4eHHSpCVpKcnKzff/9dMTExSk5OttnGXRTpw5VupFvTpk3Vpk0b9erVS7GxsSpdurRcXFx06dIljR8/Xr1797Z3iQCgn376Kc19UxaEBB7G3Vch27dvr0mTJsnf39/OlcHRtWnTRpL0448/6umnn7ZZqTwpKUn79+9XqVKltGLFCnuVCAe3bds2vfjiizpz5ozujodMu0o/rnQj3Xbv3q0JEyZIkhYtWiR/f3/t2bNH33//vYYMGULoBpAphIaGpqkff1zgUd39h+ry5csVHx9vp2qQlXh7e0v6+xzLmTOn3N3drdtcXV1Vs2ZNvfrqq/YqD1lAr169rCuY58uXj7tyMhihG+mWkJCgnDlzSpJWrVqlNm3ayMnJSTVr1vzXeZMA8LjcfascYDZuJkRGmTlzpiSpaNGievPNN7mVHBnuxIkTWrRokYoXL27vUrIkJ3sXAMdXvHhxLVmyRGfPntXKlSvVtGlTSVJMTIy8vLzsXB0AAI+HxWJJdXWIq0XISEOHDiVwwxQ1atTQ77//bu8ysiyudCPdhgwZohdffFEDBgxQw4YNFRISIunvq96VK1e2c3UAcG/x8fGKiIhQVFSUEhMTbbb169fPTlXBkRmGoZdeesk63/bmzZvq1atXqpDEozTxMKpUqaK1a9cqV65cqly58gPfyNm9e/djrAyObv/+/dZ/h4WFaeDAgYqOjlZwcLBcXFxs+laoUOFxl5elsJAaMkR0dLTOnz+vihUrysnp7xsotm/fLi8vL5UuXdrO1QGArT179uiZZ55RQkKC4uPj5evrq0uXLlkfc3jq1Cl7lwgH9PLLL6epX8qtwkBaDB8+XG+99ZZy5Mih4cOHP7Dv0KFDH1NVyAqcnJxksVjuOxUmZRtrnaQfoRsZ5vfff9fJkydVt25dubu73/exFgBgb/Xr11fJkiU1bdo0eXt7a9++fXJxcVHnzp3Vv39/60rBAABkVQ+z9hKP2kwfQjfS7fLly2rXrp3Wr18vi8WiEydOqFixYnrllVeUK1cuffzxx/YuEQBs+Pj46LffflOpUqXk4+OjrVu3qkyZMvrtt9/UrVs3HT161N4lAsB97dq1S0eOHJEklStXjul8QCbHQmpItwEDBsjFxUVRUVHKkSOHtb19+/Y8LxJApuTi4mKdCuPn56eoqChJfz+W5+zZs/YsDQDuKyYmRg0bNtR//vMf9evXT/369VPVqlXVqFEjXbx40d7lwcHNnTtXtWrVUv78+a1XwSdOnKgff/zRzpU5PkI30m3VqlUaO3asChYsaNNeokQJHhkGIFOqXLmyduzYIUmqV6+ehgwZonnz5umNN95Q+fLl7VwdANxbWFiYrl27pkOHDunKlSu6cuWKDh48qLi4OBaAxENZuXKlrl69an09depUhYeH65lnnlFsbKx1DrePj48mTpxopyqzDkI30i0+Pt7mCneKK1euWFdwBYDMZPTo0cqXL58kadSoUcqVK5d69+6tixcv6osvvrBzdQBwbytWrNBnn32mMmXKWNvKli2rKVOmaPny5XasDI4mOjpatWrV0h9//CFJmjx5sr788ku9//77cnZ2tvarVq2aDhw4YK8yswweGYZ0q1OnjubMmaORI0dK+nulw+TkZI0bN04NGjSwc3UAkFq1atWs//bz82MqDACHkJycnOpRTtLfU2aSk5PtUBEcVbdu3eTp6almzZrp0KFDioyMvOfaAG5uboqPj7dDhVkLoRvpNm7cODVq1Eg7d+5UYmKi3n77bettT5s3b7Z3eQAAAFlCw4YN1b9/f33zzTfKnz+/JOnPP//UgAED1KhRIztXB0fTtm1bVapUSZIUGBiovXv3plqlfMWKFTZ3VuDRELqRbuXLl9fx48f16aefKmfOnLp+/bratGmjPn36WG/fBIDMJDAw8IGPNOQ53QAyo08//VStWrVS0aJFVahQIUnS2bNnVb58eX399dd2rg6OKCgoSJIUHh6uPn366ObNmzIMQ9u3b9c333yjMWPGaPr06Xau0vHxyDAAwBPnk08+sXl9+/Zt7dmzRytWrNBbb72ld999106VAcCDGYahNWvWWB9tWKZMGTVu3NjOVSErmDdvnoYNG6aTJ09KkvLnz6/hw4ere/fudq7M8RG6kW4zZ86Up6enXnjhBZv27777TgkJCerWrZudKgOAhzNlyhTt3LlTM2fOtHcpAAA8Fnfu3NH8+fPVrFkz+fv7KyEhQdevX5efn5+9S8syCN1It5IlS+rzzz9PtWhaRESEevbsqWPHjtmpMgB4OKdOnVKlSpUUFxdn71IAQJI0adKkNPflsWF4VDly5NCRI0dSzelGxmBON9ItKipKgYGBqdqLFCmiqKgoO1QEAI9m0aJF8vX1tXcZAGA1YcKENPWzWCyEbjyy6tWra8+ePYRukxC6kW5+fn7av3+/ihYtatO+b98+5c6d2z5FAcADVK5c2WYhNcMwFB0drYsXL+qzzz6zY2UAYCsyMtLeJeAJ8Prrr2vgwIH6448/VLVqVXl4eNhsr1Chgp0qyxoI3Ui3jh07ql+/fsqZM6fq1q0r6e9by/v3768OHTrYuToASK1169Y2odvJyUl58+ZV/fr1Vbp0aTtWBgBpkzJD9EFPYgDSKuVv9n/eLWGxWGQYhiwWi5KSkuxVWpbAnG6kW2Jiorp06aLvvvtO2bL9/T5OcnKyunbtqmnTpsnV1dXOFQIAAGQNM2bM0IQJE3TixAlJUokSJfTGG2+oR48edq4MjuzMmTMP3M5t5+lD6EaGOXHihPbu3St3d3cFBwfzwwkg03J2dtb58+dTrcx6+fJl+fn58Y4+gExpyJAhGj9+vMLCwhQSEiJJ2rp1qz799FMNGDBAI0aMsHOFAO6F0A0AeOI4OTkpOjo6Veg+d+6cgoKCdOPGDTtVBgD3lzdvXk2aNEkdO3a0af/mm28UFhamS5cu2akyZAXHjh3T5MmTdeTIEUl/PwM+LCxMpUqVsnNljo853Ui3tm3bqnr16nrnnXds2seNG6cdO3bou+++s1NlAGAr5dE7FotF06dPl6enp3VbUlKSNm7cyJxuAJnW7du3Va1atVTtVatW1Z07d+xQEbKK77//Xh06dFC1atWsd1Fs27ZN5cuX14IFC9S2bVs7V+jYuNKNdMubN6/WrVun4OBgm/YDBw6ocePGunDhgp0qAwBbKY83PHPmjAoWLChnZ2frNldXVxUtWlQjRoxQjRo17FUiANxXWFiYXFxcNH78eJv2N998Uzdu3NCUKVPsVBkcXVBQkDp16pRqisLQoUP19ddf6+TJk3aqLGsgdCPd3N3dtXfv3lS3nhw9elSVK1fmNk0AmU6DBg20ePFi5cqVy96lAECahYWFac6cOSpUqJBq1qwpSfrtt98UFRWlrl27ysXFxdr37mAOPEiOHDm0f/9+FS9e3Kb9xIkTqlixohISEuxUWdbA7eVIt+DgYC1cuFBDhgyxaV+wYIHKli1rp6oA4P7Wr19v7xIA4KEdPHhQVapUkSTrlcc8efIoT548OnjwoLUfjxHDw6pfv75+/fXXVKF706ZNqlOnjp2qyjoI3Ui3wYMHq02bNjp58qQaNmwoSVq7dq3mz5+vRYsW2bk6AEiNtSgAOCLeMIRZWrVqpXfeeUe7du2y3kWxbds2fffddxo+fLh++uknm754ONxejgyxbNkyjR492vrIsIoVK2ro0KHy9fVV+fLl7V0eANhgLQoAjujixYvKmzfvPbcdOHAg1f/TgLRycnJKUz+LxcJjNR9B2r66wL9o0aKFNm/erPj4eJ06dUrt2rXTm2++qYoVK9q7NABI5fr163J1dU3V7uLiori4ODtUBAD/Ljg4WMuWLUvV/r///U/Vq1e3Q0XIKpKTk9P0QeB+NIRuZJiNGzeqW7duyp8/vz7++GM1bNhQ27Zts3dZAJBKyloUd2MtCgCZWXh4uNq2bavevXvrxo0b+vPPP9WoUSONGzdO8+fPt3d5AO6DOd1Il+joaM2aNUszZsxQXFyc2rVrp1u3bmnJkiX84Qog02ItCgCO6O2331aTJk3UpUsXVahQQVeuXFGNGjW0f/9+BQQE2Ls8OLgdO3Zo/fr1iomJUXJyss02VsNPH0I3HlnLli21ceNGtWjRQhMnTtTTTz8tZ2dnTZs2zd6lAcADtWzZUkuWLNHo0aO1aNEi61oU69atk6+vr73LA4D7Kl68uMqXL6/vv/9ektS+fXsCN9Jt9OjRGjRokEqVKiV/f3+bFfBZDT/9WEgNjyxbtmzq16+fevfurRIlSljbXVxctG/fPq50A3AYcXFx+uabbzRjxgzt2rWLOWsAMqXNmzerc+fO8vX11ddff63NmzcrPDxczZs317Rp05QrVy57lwgH5e/vr7Fjx+qll16ydylZEnO68cg2bdqka9euqWrVqqpRo4Y+/fRTXbp0yd5lAUCasRYFAEfSsGFDtW/fXtu2bVOZMmXUo0cP7dmzR1FRUaxcjnRxcnJSrVq17F1GlsWVbqRbfHy8Fi5cqK+++krbt29XUlKSxo8fr1deeUU5c+a0d3kAYONea1FMmzaNO3QAZHoRERGqV69eqvbk5GSNGjVKgwcPtkNVyArGjRunc+fOaeLEifYuJUsidCNDHTt2TDNmzNDcuXMVGxurJk2a6KeffrJ3WQAgyXYtik6dOlnXomBaDIDM7JlnntE333wjb29vSdKHH36oXr16ycfHR5J0+fJl1alTR4cPH7ZjlXBkycnJatGihY4fP66yZcvKxcXFZvvixYvtVFnWQOiGKZKSkrR06VJ99dVXhG4AmQZrUQBwRM7Ozjp//rz8/PwkSV5eXtq7d6+KFSsmSbpw4YLy58/PehR4ZH379tX06dPVoEGDVAupSdLMmTPtVFnWwOrlMIWzs7NCQ0MVGhpq71IAwGrTpk2aMWOGqlatqjJlyqhLly7q0KGDvcsCgAe6+xoZ18yQ0WbPnq3vv/9eLVq0sHcpWRILqQEAnhg1a9bUl19+qfPnz+u1117TggULlD9/fiUnJ2v16tW6du2avUsEAOCx8/X1VVBQkL3LyLII3QCAJ46Hh4deeeUVbdq0SQcOHNDAgQP14Ycfys/PT61atbJ3eQBgw2KxpLrdl2cnIyMNGzZMQ4cOVUJCgr1LyZKY0w0AgFiLAkDm5eTkpObNm8vNzU2StHTpUjVs2FAeHh6SpFu3bmnFihXM6cYjq1y5sk6ePCnDMFS0aNFUC6nt3r3bTpVlDYRuAAAAIBN7+eWX09SPxa7wqIYPH/7A7UOHDn1MlWRNhG4AAAAAAEzC6uUAAAAAAO3atUtHjhyRJJUrV06VK1e2c0VZA6EbAAAAAJ5gMTEx6tChgzZs2CAfHx9JUmxsrBo0aKAFCxYob9689i3QwbF6OQAAAAA8wcLCwnTt2jUdOnRIV65c0ZUrV3Tw4EHFxcWpX79+9i7P4TGnGwAAAACeYN7e3lqzZo3+85//2LRv375dTZs2VWxsrH0KyyK40g0AAAAAT7Dk5ORUjwmTJBcXFyUnJ9uhoqyF0A0AAAAAT7CGDRuqf//+OnfunLXtzz//1IABA9SoUSM7VpY1cHs5AAAAADzBzp49q1atWunQoUMqVKiQta18+fL66aefVLBgQTtX6NgI3QAAAADwhDMMQ2vWrNHRo0clSWXKlFHjxo3tXFXWQOgGAAAAgCfQunXr1LdvX23btk1eXl42265evaqnnnpK06ZNU506dexUYdbAnG4AAAAAeAJNnDhRr776aqrALf29ovlrr72m8ePH26GyrIXQDQAAAABPoH379unpp5++7/amTZtq165dj7GirInQDQAAAABPoAsXLtzzUWEpsmXLposXLz7GirImQjcAAAAAPIEKFCiggwcP3nf7/v37lS9fvsdYUdZE6AYAAACAJ9AzzzyjwYMH6+bNm6m23bhxQ0OHDtWzzz5rh8qyFlYvBwAAAIAn0IULF1SlShU5Ozurb9++KlWqlCTp6NGjmjJlipKSkrR79275+/vbuVLHRugGAAAAgCfUmTNn1Lt3b61cuVIp0dBisahZs2aaMmWKAgMD7Vyh4yN0AwAAAMAT7q+//tLvv/8uwzBUokQJ5cqVy94lZRmEbgAAAAAATMJCagAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAADuKTExUaNHj9aRI0fsXQoAAA6L0A0AAO5p4MCBOnDggEqXLv1YxtuwYYMsFotiY2Mfy3gAADwOhG4AABxQdHS0wsLCVKxYMbm5ualQoUJq2bKl1q5dm6bPnzVrlnx8fO67/dtvv9WhQ4c0e/ZsWSyWDKr6wZ566imdP39e3t7ej2U8AAAeh2z2LgAAADyc06dPq1atWvLx8dFHH32k4OBg3b59WytXrlSfPn109OjRdI/Rrl07tWvXLgOqTZvbt2/L1dVVAQEBj21MAAAeB650AwDgYF5//XVZLBZt375dbdu2VcmSJVWuXDmFh4dr27ZtkqTx48crODhYHh4eKlSokF5//XVdv35d0t+3cb/88su6evWqLBaLLBaLhg0bJkm6deuW3nzzTRUoUEAeHh6qUaOGNmzYYDP+l19+qUKFCilHjhx67rnnNH78+FRXzadOnaqgoCC5urqqVKlSmjt3rs12i8WiqVOnqlWrVvLw8NCoUaPueXv5pk2bVKdOHbm7u6tQoULq16+f4uPjM/TrCQCAmQjdAAA4kCtXrmjFihXq06ePPDw8Um1PCb9OTk6aNGmS9RbxdevW6e2335b0923cEydOlJeXl86fP6/z58/rzTfflCT17dtXW7du1YIFC7R//3698MILevrpp3XixAlJ0ubNm9WrVy/1799fe/fuVZMmTTRq1CibGn744Qf1799fAwcO1MGDB/Xaa6/p5Zdf1vr16236DRs2TM8995wOHDigV155JdWxnDx5Uk8//bTatm2r/fv3a+HChdq0aZP69u2b7q8jAACPi8UwDMPeRQAAgLTZvn27atSoocWLF+u5555L8+ctWrRIvXr10qVLlyT9Paf7jTfesLmqHBUVpWLFiikqKkr58+e3tjdu3FjVq1fX6NGj1aFDB12/fl0///yzdXvnzp31888/W/dVq1YtlStXTl988YW1T7t27RQfH69ly5ZJ+vtK9xtvvKEJEyZY+2zYsEENGjTQX3/9JR8fH/Xo0UPOzs76/PPPrX02bdqkevXqKT4+XtmzZ0/z8QMAYC9c6QYAwIGk9b3yNWvWqFGjRipQoIBy5sypLl266PLly0pISLjv5xw4cEBJSUkqWbKkPD09rR8RERE6efKkJOnYsWOqXr26zefd/frIkSOqVauWTVutWrVSPXqsWrVqDzyGffv2adasWTa1NGvWTMnJyYqMjPzXrwEAAJkBC6kBAOBASpQoIYvF8sDF0k6fPq1nn31WvXv31qhRo+Tr66tNmzape/fuSkxMVI4cOe75edevX5ezs7N27dolZ2dnm22enp4ZehyS7nl7/N31vPbaa+rXr1+qbYULF87wegAAMAOhGwAAB+Lr66tmzZppypQp6tevX6rgGhsbq127dik5OVkff/yxnJz+vqnt22+/tenn6uqqpKQkm7bKlSsrKSlJMTExqlOnzj3HL1WqlHbs2GHTdvfrMmXKaPPmzerWrZu1bfPmzSpbtuxDHWuVKlV0+PBhFS9e/KE+DwCAzITbywEAcDBTpkxRUlKSqlevru+//14nTpzQkSNHNGnSJIWEhKh48eK6ffu2Jk+erFOnTmnu3LmaNm2azT6KFi2q69eva+3atbp06ZISEhJUsmRJderUSV27dtXixYsVGRmp7du3a8yYMda52GFhYfrll180fvx4nThxQp9//rmWL19u8yzvt956S7NmzdLUqVN14sQJjR8/XosXL7Yu1pZW77zzjrZs2aK+fftq7969OnHihH788UcWUgMAOBRCNwAADqZYsWLavXu3GjRooIEDB6p8+fJq0qSJ1q5dq6lTp6pixYoaP368xo4dq/Lly2vevHkaM2aMzT6eeuop9erVS+3bt1fevHk1btw4SdLMmTPVtWtXDRw4UKVKlVJoaKh27NhhvZ27Vq1amjZtmsaPH6+KFStqxYoVGjBggM2iZqGhofrkk0/0v//9T+XKldPnn3+umTNnqn79+g91nBUqVFBERISOHz+uOnXqqHLlyhoyZIjNIm8AAGR2rF4OAADS5dVXX9XRo0f166+/2rsUAAAyHeZ0AwCAh/K///1PTZo0kYeHh5YvX67Zs2frs88+s3dZAABkSlzpBgAAD6Vdu3basGGDrl27pmLFiiksLEy9evWyd1kAAGRKhG4AAAAAAEzCQmoAAAAAAJiE0A0AAAAAgEkI3QAAAAAAmITQDQAAAACASQjdAAAAAACYhNANAAAAAIBJCN0AAAAAAJiE0A0AAAAAgEn+D0bO6ltcIhetAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Train : \n", " Accessibilité 1650\n", "Autre 1415\n", "Actualisation 776\n", "Fiabilité 573\n", "Exploitabilité 370\n", "Compréhension 302\n", "Name: categorie, dtype: int64\n", "\n", "\n", "Validation : \n", " Accessibilité 413\n", "Autre 354\n", "Actualisation 194\n", "Fiabilité 144\n", "Exploitabilité 92\n", "Compréhension 75\n", "Name: categorie, dtype: int64\n", "\n", "\n", "Test : \n", " Accessibilité 516\n", "Autre 442\n", "Actualisation 243\n", "Fiabilité 180\n", "Exploitabilité 115\n", "Compréhension 94\n", "Name: categorie, dtype: int64\n" ] } ], "source": [ "# Avant la division\n", "plt.figure(figsize=(10, 8))\n", "plt.subplot(2, 1, 1)\n", "plt.title(\"Répartition des catégories (Avant la division)\")\n", "df['categorie'].value_counts().plot(kind='bar')\n", "plt.xlabel(\"Catégorie\")\n", "plt.ylabel(\"Nombre d'échantillons\")\n", "\n", "# Après la division\n", "train_counts = train_df['categorie'].value_counts()\n", "val_counts = val_df['categorie'].value_counts()\n", "test_counts = test_df['categorie'].value_counts()\n", "\n", "# Répartition des catégories dans train_df\n", "plt.figure(figsize=(10, 16))\n", "plt.subplot(3, 1, 1)\n", "plt.title(\"Répartition des catégories (Ensemble d'entraînement)\")\n", "train_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.xlabel(\"Catégorie\")\n", "plt.ylabel(\"Nombre d'échantillons\")\n", "\n", "# Répartition des catégories dans val_df\n", "plt.subplot(3, 1, 2)\n", "plt.title(\"Répartition des catégories (Ensemble de validation)\")\n", "val_counts.plot(kind='bar', color='red', alpha=0.7)\n", "plt.xlabel(\"Catégorie\")\n", "plt.ylabel(\"Nombre d'échantillons\")\n", "\n", "# Répartition des catégories dans test_df\n", "plt.subplot(3, 1, 3)\n", "plt.title(\"Répartition des catégories (Ensemble de test)\")\n", "test_counts.plot(kind='bar', color='green', alpha=0.7)\n", "plt.xlabel(\"Catégorie\")\n", "plt.ylabel(\"Nombre d'échantillons\")\n", "\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "print('Train : \\n', train_counts)\n", "print('\\n')\n", "print('Validation : \\n', val_counts)\n", "print('\\n')\n", "print('Test : \\n', test_counts)" ] }, { "cell_type": "code", "execution_count": 47, "id": "9a0c52b3", "metadata": {}, "outputs": [], "source": [ "# On vérifie le premier exemple de l'ensemble de train" ] }, { "cell_type": "code", "execution_count": 48, "id": "0dd11758", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'id dgf': '56981b6288ee3813e8b7e1f8',\n", " 'subject': 'Gares ferroviaires de tous types,exploitées ou non',\n", " 'title': 'Certificat expiré',\n", " 'messages': \"Le certificat associé à static.data.gouv.fr est périmé. Message du navigateur quand on essaie de télécharger la ressource : Le certificat a expiré le mercredi 16 décembre 2015 07:41. De plus, si on essaie de passer en http simple, on est redirigé sur https. Du coup, cette source n'est plus accessible, tout comme de nombreuses autres.\",\n", " 'combined_text': \"Certificat expiré Le certificat associé à static.data.gouv.fr est périmé. Message du navigateur quand on essaie de télécharger la ressource : Le certificat a expiré le mercredi 16 décembre 2015 07:41. De plus, si on essaie de passer en http simple, on est redirigé sur https. Du coup, cette source n'est plus accessible, tout comme de nombreuses autres.\",\n", " 'Annotation': 'Lien mort',\n", " 'categorie': 'Accessibilité',\n", " '__index_level_0__': 2973}" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "example = dataset['train'][0]\n", "example" ] }, { "cell_type": "markdown", "id": "54c9303f", "metadata": {}, "source": [ "# Preprocessing des données" ] }, { "cell_type": "code", "execution_count": 49, "id": "10a80388", "metadata": {}, "outputs": [], "source": [ "# Prétraitement et tokenisation à l'aide du tokenizer" ] }, { "cell_type": "code", "execution_count": 50, "id": "c218a34b", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "00dd6017f09e45e1b0f72680fb761767", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Map: 0%| | 0/5086 [00:00 certificat expiré le certificat associé à static.data.gouv.fr est périmé. message du navigateur quand on essaie de télécharger la ressource le certificat a expiré le mercredi. de plus, si on essaie de passer en http simple, on est redirigé sur https. du coup, cette source n'est plus accessible, tout comme de nombreuses autres.\"" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Décodage de l'exemple pour 'dénumériser' l'exemple\n", "\n", "tokenizer.decode(example['input_ids'])" ] }, { "cell_type": "code", "execution_count": 55, "id": "833dabdf", "metadata": {}, "outputs": [], "source": [ "# Affichage du label de l'exemple ci-dessus après l'étape de preprocessing" ] }, { "cell_type": "code", "execution_count": 56, "id": "59a0a849", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3\n", "Accessibilité\n" ] } ], "source": [ "label = example['labels']\n", "print(label)\n", "print(id2label[label])" ] }, { "cell_type": "markdown", "id": "0a9c98a3", "metadata": {}, "source": [ "# Définition du modèle CamemBERT" ] }, { "cell_type": "code", "execution_count": 57, "id": "0750f47d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'# Calculez les poids de classe\\n#batch_size=16\\nclass_labels = train_df[\\'categorie\\'].unique().tolist()\\nclass_counts = train_df[\\'categorie\\'].value_counts()\\nclass_weights = 1.0 / torch.tensor(class_counts, dtype=torch.float)\\nsample_weights = class_weights[train_df[\\'categorie\\'].map(label2id).values]\\n\\n\\n# Afficher les poids attribués à chaque classe\\nprint(\"Poids assignés à chaque classe :\")\\nfor label_id, weight in enumerate(sample_weights.tolist()):\\n label_name = id2label[label_id]\\n print(f\"{label_name}: {weight}\")\\n print(\\'\\n\\')\\n\\n# Créez un WeightedRandomSampler pour l\\'ensemble d\\'entraînement\\nsampler = WeightedRandomSampler(sample_weights, len(sample_weights))\\n\\n# Créez un DataLoader avec le WeightedRandomSampler\\ntrain_loader = DataLoader(encoded_dataset[\\'train\\'], batch_size=batch_size, sampler=sampler)\\n'" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"# Calculez les poids de classe\n", "#batch_size=16\n", "class_labels = train_df['categorie'].unique().tolist()\n", "class_counts = train_df['categorie'].value_counts()\n", "class_weights = 1.0 / torch.tensor(class_counts, dtype=torch.float)\n", "sample_weights = class_weights[train_df['categorie'].map(label2id).values]\n", "\n", "\n", "# Afficher les poids attribués à chaque classe\n", "print(\"Poids assignés à chaque classe :\")\n", "for label_id, weight in enumerate(sample_weights.tolist()):\n", " label_name = id2label[label_id]\n", " print(f\"{label_name}: {weight}\")\n", " print('\\n')\n", "\n", "# Créez un WeightedRandomSampler pour l'ensemble d'entraînement\n", "sampler = WeightedRandomSampler(sample_weights, len(sample_weights))\n", "\n", "# Créez un DataLoader avec le WeightedRandomSampler\n", "train_loader = DataLoader(encoded_dataset['train'], batch_size=batch_size, sampler=sampler)\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 58, "id": "f109318b", "metadata": {}, "outputs": [], "source": [ "# Définir la taille du lot et la métrique d'évaluation\n", "#batch_size = 8\n", "batch_size = 16\n", "#batch_size = 32\n", "#batch_size = len(encoded_dataset['train'])\n", "#metric_name = \"f1\"\n", "metric_name = \"accuracy\"\n", "\n", "# Définir les arguments pour l'entraînement\n", "args = TrainingArguments(\n", " \"bert-finetuned-my-data\",\n", " #f\"bert-finetuned-sem_eval-english\",\n", " evaluation_strategy = \"epoch\",\n", " save_strategy = \"epoch\",\n", " #learning_rate=2e-6,\n", " #learning_rate=1e-5,\n", " #learning_rate=2e-5,\n", " learning_rate=3e-5,\n", " #learning_rate=4e-5,\n", " per_device_train_batch_size=batch_size,\n", " per_device_eval_batch_size=batch_size,\n", " num_train_epochs=5,\n", " weight_decay=0.01,\n", " load_best_model_at_end=True,\n", " metric_for_best_model=metric_name,\n", " #push_to_hub=True,\n", ")" ] }, { "cell_type": "code", "execution_count": 59, "id": "4f35a344", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Some weights of CamembertForSequenceClassification were not initialized from the model checkpoint at camembert-base and are newly initialized: ['classifier.dense.weight', 'classifier.out_proj.bias', 'classifier.out_proj.weight', 'classifier.dense.bias']\n", "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n" ] } ], "source": [ "from transformers import AdamW, AutoModelForSequenceClassification, TrainingArguments, Trainer\n", "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n", "\n", "model = AutoModelForSequenceClassification.from_pretrained(\"camembert-base\",\n", " problem_type=\"single_label_classification\",\n", " num_labels=len(labels),\n", " id2label=id2label,\n", " label2id=label2id)\n", "\n", "# Variables globales pour stocker y_true et y_pred\n", "y_true_global = None\n", "y_pred_global = None\n", "\n", "#Définition de la fonction compute_metrics\n", "def compute_metrics(eval_pred):\n", " global y_true_global, y_pred_global\n", "\n", " predictions, y_true = eval_pred\n", " y_pred = predictions.argmax(axis=1)\n", " accuracy = accuracy_score(y_true, y_pred)\n", " precision = precision_score(y_true, y_pred, average=\"weighted\")\n", " recall = recall_score(y_true, y_pred, average=\"weighted\")\n", " f1 = f1_score(y_true, y_pred, average='weighted')\n", "\n", " # Assigner les valeurs à y_true_global et y_pred_global\n", " y_true_global = y_true.tolist()\n", " y_pred_global = y_pred.tolist()\n", "\n", " metrics = {\n", " 'accuracy': accuracy,\n", " 'f1': f1,\n", " 'precision': precision,\n", " 'recall': recall\n", " }\n", "\n", " return metrics\n" ] }, { "cell_type": "code", "execution_count": 60, "id": "de254ead", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/asma/miniconda3/lib/python3.9/site-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n", " warnings.warn(\n", "You're using a CamembertTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n" ] }, { "data": { "text/html": [ "\n", "
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EpochTraining LossValidation LossAccuracyF1PrecisionRecall
1No log0.9614510.6839620.6529440.6564650.683962
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n" ] }, { "data": { "text/plain": [ "TrainOutput(global_step=1590, training_loss=0.7260929323592276, metrics={'train_runtime': 5182.2295, 'train_samples_per_second': 4.907, 'train_steps_per_second': 0.307, 'total_flos': 1672788609469440.0, 'train_loss': 0.7260929323592276, 'epoch': 5.0})" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Création de l'optimiseur AdamW avec le taux d'apprentissage spécifié\n", "optimizer = AdamW(model.parameters(), lr=args.learning_rate)\n", "\n", "# Création d'une instance de la classe Trainer en spécifiant l'optimiseur\n", "trainer = Trainer(\n", " model=model,\n", " args=args,\n", " train_dataset=encoded_dataset[\"train\"],\n", " #train_dataset=train_loader.dataset,\n", " eval_dataset=encoded_dataset[\"validation\"],\n", " optimizers=(optimizer, None), # spécifier l'optimiseur pour l'entraînement\n", " tokenizer=tokenizer,\n", " compute_metrics=compute_metrics,\n", ")\n", "\n", "# Lancement de l'entraînement du modele\n", "trainer.train()\n" ] }, { "cell_type": "code", "execution_count": 61, "id": "7eec9c20", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "

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\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "{'eval_loss': 0.9926791787147522, 'eval_accuracy': 0.7182389937106918, 'eval_f1': 0.7154476658487445, 'eval_precision': 0.7168117201187565, 'eval_recall': 0.7182389937106918, 'eval_runtime': 87.9158, 'eval_samples_per_second': 18.085, 'eval_steps_per_second': 1.137, 'epoch': 5.0}\n" ] } ], "source": [ "# Evaluation\n", "# Évaluer le modèle sur l'ensemble de test\n", "eval_results = trainer.evaluate(encoded_dataset['test'])\n", "print(eval_results)" ] }, { "cell_type": "code", "execution_count": 62, "id": "b548d094", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y_true_global: [3, 1, 3, 4, 2, 1, 0, 2, 0, 4, 1, 3, 3, 4, 3, 1, 3, 5, 3, 1, 1, 4, 3, 3, 1, 0, 2, 5, 2, 2, 3, 4, 3, 3, 3, 1, 3, 2, 3, 3, 2, 3, 1, 2, 0, 3, 2, 1, 3, 4, 0, 1, 0, 3, 2, 1, 0, 2, 5, 1, 3, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 5, 1, 1, 2, 2, 3, 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1, 3, 1, 3, 1, 1, 1, 3, 0, 2, 1, 0, 2, 2, 2, 5, 0, 3, 3, 0, 2, 2, 2, 3, 3, 1, 3, 1, 5, 3, 5, 1, 2, 3, 1, 1, 3, 3, 0, 3, 3, 4, 5, 3, 1, 3, 3, 3, 2, 2, 2, 1, 1, 2, 1, 2, 1, 3, 0, 3, 2, 1, 2, 3, 3, 2, 3, 4, 3, 3, 3, 0, 3, 3, 5, 1, 3, 3, 3, 0, 3, 3, 2, 2, 1, 5, 2, 3, 1, 3, 1, 3, 5, 3, 1, 1, 0, 3, 1, 4, 0, 3, 5, 3, 5, 1, 1, 3, 2, 2, 3, 3, 0, 4, 0, 1, 1, 2, 1, 0, 1, 3, 3, 2, 5, 1, 1, 1, 4, 3, 4, 1, 1, 4, 3, 1, 3, 3, 2, 1, 3, 2, 5, 3, 1, 1, 5, 3, 0, 2, 5, 0, 1, 2, 3, 3, 3, 5, 2, 3, 1, 3, 2, 1, 0, 0, 3, 1, 0, 2, 1, 1, 5, 0, 3, 1, 3, 3, 3, 5, 4, 0, 3, 3, 3, 3, 3, 2, 1, 5, 2, 1, 2, 3, 3, 4, 1, 0, 0, 5, 1, 5, 1, 2, 3, 0, 1, 3, 0, 3, 3, 4, 0, 1, 0, 3, 2, 4, 3, 1, 1, 1, 3, 3, 2, 2, 3, 0, 5, 3, 3, 0, 5, 3, 2, 2, 2, 1, 3, 0, 3, 3, 2, 5, 4, 1, 1, 3, 3, 3, 3, 1, 5, 1, 5, 4, 3, 1, 1, 3, 0, 1, 1, 2, 0, 3, 2, 1, 3, 2, 0, 0, 0, 1, 1, 1, 3, 2, 3, 3, 2, 2, 0, 2, 3, 1, 3, 0, 1, 2, 3, 1, 1, 3, 3, 3, 2, 1, 4, 3, 1, 5, 3, 4, 3, 1, 3, 3, 1, 3, 3, 3, 4, 3, 3, 3, 1, 2, 2, 1, 1, 3, 5, 2, 3, 2, 4, 3, 1, 3, 1, 2, 0, 3, 5, 1, 4, 3, 3, 1, 3, 3, 4, 5, 5, 0, 3, 1, 5, 0, 3, 1, 3, 1, 5, 2, 1, 1, 1, 1, 2, 3, 3, 2, 0, 3, 3, 3, 1, 1, 2, 1, 1, 3, 0, 1, 1, 2, 3, 3, 3, 1, 4, 1, 1, 5, 1, 1, 4, 1, 1, 3, 4, 3, 1, 2, 1, 1, 2, 0, 2, 1, 1, 5, 2, 1, 3, 3, 2, 0, 1, 5, 1, 2, 3, 3, 1, 1, 4, 5, 3, 5, 1, 5, 3, 5, 0, 5, 3, 4, 0, 2, 3, 3, 2, 5, 1, 3, 3, 0, 1, 2, 0, 1, 0, 3, 2, 5, 1, 0, 2, 1, 2, 1, 4, 1, 3, 3, 1, 0, 1, 1, 2, 3, 0, 1, 3, 3, 1, 3, 1, 2, 2, 3, 5, 3, 1, 3, 0, 5, 3, 1, 3, 5, 5, 0, 3, 3, 1, 1, 0, 0, 3, 3, 0, 2, 3, 0, 2, 3, 2, 3, 1, 0, 2, 5, 4, 2, 3, 1, 3, 1, 1, 1, 3, 1, 1, 1, 0, 2, 3, 0, 2, 3, 3, 1, 4, 3, 2, 1, 3, 3, 2, 3, 4, 1, 3, 2, 2, 3, 2, 0, 1, 3, 3, 1, 3, 4, 2, 1, 2, 0, 4, 1, 1, 1, 1, 5, 3, 4, 1, 3, 1, 3, 0, 0, 1, 4, 1, 3, 3, 2, 3, 5, 1, 3, 1, 0, 0, 1, 1, 1, 1, 3, 1, 0, 2, 0, 5, 1, 3, 4, 1, 0, 1, 3, 4, 4, 0, 3, 1, 1, 0, 2, 1, 2, 3, 3, 4, 0, 5, 0, 3, 3, 1, 3, 1, 2, 1, 2, 3, 1, 3, 2, 0, 3, 3, 0, 3, 1, 3, 1, 4, 1, 3, 2, 3, 0, 3, 5, 5, 2, 3, 2, 3, 2, 1, 3, 1, 3, 3, 3, 3, 0, 3, 1, 1, 3, 5, 1, 5, 5, 1, 3, 5, 3, 3, 0, 2, 0, 5, 2, 1, 1, 2, 2, 1, 4, 2, 3, 1, 1, 1, 3, 1, 3, 2, 1, 1, 1, 5, 1, 4, 5, 3, 3, 1, 2, 1, 3, 3, 1, 1, 1, 5, 3, 4, 3, 1, 4, 2, 1, 1, 3, 5, 0, 1, 1, 0, 1, 3, 3, 0, 2, 1, 0, 3, 2, 0, 5, 4, 4, 1, 2, 5, 3, 3, 1, 2, 1, 1, 1, 2, 1, 3, 1, 3, 0, 2, 0, 1, 3, 3, 3, 3, 1, 2, 3, 3, 1, 1, 4, 0, 2, 3, 3, 3, 1, 3, 1, 1, 1, 3, 2, 4, 1, 0, 1, 0, 4, 3, 3, 2, 4, 1, 2, 3, 0, 3, 2, 2, 4, 0, 1, 1, 3, 1, 1, 3, 2, 3, 2, 1, 3, 1, 2, 3, 2, 1, 1, 0, 5, 2, 3, 3, 0, 1, 3, 1, 3, 5, 3, 1, 3, 1, 3, 1, 1, 1, 1, 0, 3, 0, 1, 1, 5, 1, 1, 4, 3, 1, 3, 3, 3, 3]\n", "y_pred_global: [3, 0, 3, 4, 2, 1, 0, 2, 0, 4, 3, 3, 1, 4, 3, 1, 3, 3, 3, 1, 0, 4, 3, 3, 2, 0, 3, 5, 2, 2, 3, 4, 3, 3, 3, 1, 3, 2, 3, 3, 2, 3, 1, 2, 0, 3, 2, 1, 3, 1, 0, 0, 0, 3, 2, 1, 1, 2, 1, 1, 2, 2, 2, 3, 3, 2, 3, 3, 2, 3, 1, 1, 3, 5, 3, 4, 2, 2, 3, 3, 0, 3, 5, 3, 3, 2, 5, 0, 3, 4, 1, 4, 3, 0, 1, 1, 1, 2, 3, 3, 3, 2, 4, 2, 1, 3, 1, 1, 0, 3, 3, 0, 3, 1, 1, 2, 3, 3, 2, 3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 2, 1, 3, 4, 5, 1, 4, 3, 0, 1, 1, 2, 5, 2, 0, 0, 3, 1, 3, 3, 2, 3, 0, 0, 2, 1, 0, 2, 0, 1, 1, 2, 0, 1, 4, 1, 0, 3, 0, 1, 4, 1, 5, 1, 3, 1, 1, 3, 2, 3, 3, 3, 1, 3, 3, 0, 3, 3, 2, 3, 2, 2, 0, 3, 5, 3, 1, 4, 3, 1, 3, 3, 3, 3, 1, 5, 3, 5, 0, 0, 0, 3, 3, 2, 3, 3, 1, 3, 0, 1, 3, 2, 0, 2, 3, 3, 1, 3, 3, 1, 3, 1, 3, 3, 2, 3, 2, 5, 1, 2, 3, 1, 1, 3, 3, 2, 0, 3, 0, 0, 2, 0, 1, 5, 1, 0, 1, 3, 5, 0, 2, 2, 2, 1, 1, 3, 1, 0, 1, 3, 3, 1, 1, 3, 3, 1, 2, 3, 1, 1, 1, 1, 2, 3, 3, 2, 3, 1, 3, 3, 0, 2, 3, 3, 1, 1, 3, 4, 3, 1, 1, 2, 1, 3, 2, 1, 3, 3, 3, 1, 1, 3, 1, 3, 2, 1, 1, 1, 2, 3, 3, 2, 1, 3, 1, 2, 0, 1, 0, 1, 0, 1, 3, 2, 3, 3, 1, 3, 0, 3, 0, 2, 1, 3, 2, 1, 3, 3, 0, 4, 1, 3, 2, 1, 5, 0, 3, 1, 1, 1, 1, 3, 2, 3, 3, 3, 3, 3, 1, 3, 1, 2, 3, 5, 2, 2, 1, 3, 5, 0, 3, 0, 1, 5, 3, 3, 3, 2, 3, 3, 5, 3, 1, 1, 3, 2, 2, 3, 0, 2, 3, 0, 1, 3, 3, 3, 2, 3, 1, 1, 1, 3, 5, 4, 3, 0, 0, 3, 4, 3, 5, 1, 1, 2, 5, 2, 3, 0, 4, 2, 3, 4, 3, 3, 2, 1, 3, 3, 1, 1, 2, 5, 3, 3, 3, 1, 3, 0, 3, 1, 4, 0, 5, 0, 3, 4, 0, 0, 2, 3, 2, 0, 0, 1, 3, 0, 3, 1, 1, 5, 2, 3, 1, 3, 3, 0, 1, 2, 2, 0, 1, 1, 0, 3, 4, 3, 0, 1, 3, 1, 1, 0, 3, 3, 5, 2, 5, 2, 2, 3, 1, 5, 3, 1, 4, 3, 3, 1, 1, 3, 2, 3, 3, 2, 3, 4, 3, 0, 1, 1, 1, 3, 3, 1, 1, 5, 2, 3, 0, 3, 0, 0, 3, 1, 3, 1, 1, 2, 1, 3, 5, 3, 3, 3, 4, 2, 1, 3, 3, 2, 1, 0, 1, 4, 2, 0, 1, 4, 1, 1, 2, 0, 5, 1, 3, 1, 2, 3, 5, 3, 3, 3, 2, 3, 3, 0, 3, 2, 2, 1, 3, 5, 0, 3, 1, 1, 2, 3, 2, 3, 2, 1, 3, 1, 1, 0, 4, 1, 2, 2, 1, 3, 1, 5, 0, 3, 1, 3, 3, 1, 3, 1, 2, 2, 1, 1, 1, 1, 3, 1, 3, 1, 3, 0, 3, 3, 3, 1, 3, 2, 5, 1, 1, 0, 1, 3, 0, 1, 3, 1, 0, 3, 3, 2, 5, 3, 3, 1, 2, 1, 1, 1, 4, 3, 3, 3, 4, 0, 3, 1, 4, 1, 3, 3, 5, 1, 2, 3, 1, 1, 1, 0, 1, 1, 2, 2, 0, 1, 4, 1, 3, 3, 1, 3, 3, 2, 3, 3, 2, 3, 3, 1, 0, 0, 1, 1, 2, 2, 0, 3, 3, 2, 1, 1, 3, 1, 0, 1, 1, 3, 1, 1, 2, 1, 2, 1, 3, 2, 0, 5, 3, 3, 3, 3, 5, 3, 3, 1, 2, 4, 2, 2, 4, 5, 1, 0, 3, 3, 2, 3, 5, 3, 1, 3, 2, 1, 3, 1, 3, 1, 1, 3, 3, 1, 2, 3, 0, 2, 2, 3, 3, 1, 3, 3, 5, 0, 2, 2, 3, 3, 3, 3, 1, 3, 3, 0, 1, 2, 3, 1, 1, 3, 3, 0, 3, 3, 5, 0, 3, 1, 3, 3, 3, 3, 2, 2, 4, 1, 1, 1, 2, 4, 3, 2, 0, 2, 3, 2, 3, 1, 2, 2, 3, 3, 3, 3, 0, 3, 3, 3, 1, 3, 3, 3, 0, 3, 3, 2, 2, 1, 5, 2, 3, 1, 3, 1, 1, 5, 1, 2, 1, 0, 0, 1, 5, 2, 3, 5, 3, 3, 1, 1, 3, 2, 2, 3, 3, 0, 4, 3, 1, 0, 2, 1, 0, 3, 3, 3, 2, 5, 1, 1, 1, 4, 3, 4, 1, 1, 4, 3, 1, 3, 3, 0, 1, 3, 2, 5, 3, 3, 1, 3, 3, 0, 2, 5, 0, 3, 1, 3, 2, 3, 0, 2, 3, 1, 3, 2, 1, 1, 0, 3, 1, 0, 2, 1, 1, 5, 1, 3, 1, 3, 2, 3, 0, 0, 0, 2, 3, 3, 3, 3, 1, 3, 3, 2, 1, 0, 0, 3, 4, 3, 0, 1, 5, 1, 5, 1, 2, 3, 3, 1, 3, 1, 3, 3, 4, 0, 1, 3, 3, 3, 1, 3, 1, 3, 4, 3, 3, 3, 2, 3, 0, 3, 3, 3, 0, 5, 3, 2, 2, 1, 1, 4, 0, 3, 3, 2, 3, 4, 0, 1, 3, 1, 3, 3, 1, 3, 1, 0, 4, 3, 1, 1, 3, 3, 1, 1, 2, 3, 3, 2, 1, 0, 2, 1, 0, 0, 1, 1, 1, 3, 2, 3, 0, 2, 5, 5, 2, 2, 1, 3, 0, 2, 2, 3, 1, 1, 3, 1, 3, 2, 1, 4, 1, 1, 5, 0, 1, 3, 1, 3, 3, 5, 3, 3, 3, 3, 1, 3, 3, 4, 2, 2, 1, 1, 3, 0, 2, 3, 2, 4, 3, 1, 3, 0, 2, 0, 1, 5, 5, 3, 1, 3, 1, 3, 3, 1, 5, 5, 0, 1, 1, 5, 0, 3, 1, 3, 1, 5, 2, 3, 1, 1, 1, 3, 1, 3, 2, 0, 3, 3, 3, 1, 1, 2, 1, 1, 3, 2, 1, 1, 3, 1, 3, 3, 1, 1, 1, 1, 3, 1, 3, 5, 3, 1, 3, 4, 3, 1, 1, 1, 1, 2, 0, 2, 1, 1, 3, 2, 1, 3, 3, 2, 0, 1, 5, 5, 2, 3, 3, 1, 3, 3, 5, 3, 5, 1, 0, 3, 0, 0, 0, 3, 3, 3, 2, 3, 3, 2, 5, 1, 2, 3, 0, 1, 2, 0, 2, 3, 3, 2, 0, 1, 3, 2, 1, 3, 2, 0, 1, 3, 1, 3, 0, 1, 0, 2, 3, 3, 1, 3, 3, 1, 2, 1, 2, 1, 3, 5, 3, 1, 3, 1, 3, 3, 5, 3, 4, 3, 5, 3, 1, 3, 1, 0, 0, 3, 1, 0, 2, 3, 3, 2, 3, 2, 1, 1, 0, 2, 3, 4, 2, 3, 1, 1, 4, 0, 1, 3, 1, 5, 3, 0, 2, 3, 1, 2, 3, 3, 1, 4, 3, 2, 1, 3, 1, 2, 3, 4, 3, 3, 2, 2, 3, 0, 0, 1, 3, 3, 1, 4, 3, 2, 1, 1, 0, 4, 1, 1, 1, 1, 0, 3, 1, 1, 3, 4, 0, 0, 0, 1, 4, 5, 3, 3, 2, 3, 0, 1, 3, 1, 0, 0, 5, 1, 1, 3, 3, 0, 0, 2, 0, 3, 1, 2, 1, 1, 0, 1, 3, 4, 3, 0, 3, 1, 1, 0, 2, 1, 1, 3, 3, 1, 0, 0, 0, 1, 3, 0, 3, 1, 2, 1, 2, 2, 3, 3, 0, 0, 3, 2, 0, 3, 1, 0, 1, 4, 1, 3, 2, 2, 5, 3, 5, 3, 2, 3, 1, 3, 2, 1, 3, 1, 3, 0, 3, 0, 0, 3, 1, 1, 1, 5, 1, 5, 5, 3, 3, 0, 3, 3, 3, 2, 0, 1, 3, 4, 1, 2, 3, 1, 2, 2, 3, 1, 2, 0, 3, 1, 3, 2, 1, 1, 1, 3, 2, 4, 3, 3, 3, 1, 2, 1, 3, 3, 1, 1, 1, 0, 0, 1, 3, 1, 3, 2, 1, 1, 5, 0, 0, 2, 1, 0, 1, 3, 2, 3, 2, 1, 2, 3, 5, 0, 5, 1, 4, 1, 2, 5, 3, 3, 3, 2, 0, 1, 1, 3, 1, 3, 1, 3, 3, 2, 0, 1, 3, 3, 3, 2, 1, 2, 4, 3, 1, 1, 4, 0, 5, 3, 5, 3, 3, 4, 1, 1, 3, 3, 2, 1, 1, 0, 3, 1, 4, 3, 3, 2, 4, 3, 2, 3, 0, 3, 2, 2, 0, 0, 3, 1, 3, 3, 1, 2, 2, 3, 2, 1, 3, 1, 2, 3, 2, 3, 3, 0, 3, 2, 3, 3, 0, 1, 3, 1, 3, 5, 0, 1, 3, 1, 3, 1, 2, 1, 1, 0, 3, 0, 1, 1, 5, 1, 1, 1, 3, 3, 3, 3, 3, 3]\n" ] } ], "source": [ "# Afficher les valeurs de y_true_global et y_pred_global\n", "print(\"y_true_global:\", y_true_global)\n", "print(\"y_pred_global:\", y_pred_global)" ] }, { "cell_type": "code", "execution_count": 63, "id": "9d6b8e3f", "metadata": {}, "outputs": [], "source": [ "y_true = y_true_global\n", "y_pred = y_pred_global" ] }, { "cell_type": "markdown", "id": "bb778db7", "metadata": {}, "source": [ "# Evaluation du modèle : Rapport de classification" ] }, { "cell_type": "code", "execution_count": 64, "id": "e0574ce6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Fiabilité',\n", " 'Autre',\n", " 'Actualisation',\n", " 'Accessibilité',\n", " 'Compréhension',\n", " 'Exploitabilité']" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "target_names = [label for _, label in sorted(id2label.items())]\n", "target_names" ] }, { "cell_type": "code", "execution_count": 65, "id": "923bdb36", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Fiabilité',\n", " 'Autre',\n", " 'Actualisation',\n", " 'Accessibilité',\n", " 'Compréhension',\n", " 'Exploitabilité']" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "labels" ] }, { "cell_type": "code", "execution_count": 66, "id": "25fce216", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{0: 'Fiabilité',\n", " 1: 'Autre',\n", " 2: 'Actualisation',\n", " 3: 'Accessibilité',\n", " 4: 'Compréhension',\n", " 5: 'Exploitabilité'}" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "id2label" ] }, { "cell_type": "code", "execution_count": 67, "id": "5a136aa8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " Fiabilité 0.59 0.66 0.62 180\n", " Autre 0.76 0.73 0.75 442\n", " Actualisation 0.76 0.77 0.76 243\n", " Accessibilité 0.74 0.80 0.77 516\n", " Compréhension 0.69 0.52 0.59 94\n", "Exploitabilité 0.58 0.44 0.50 115\n", "\n", " accuracy 0.72 1590\n", " macro avg 0.69 0.65 0.67 1590\n", " weighted avg 0.72 0.72 0.72 1590\n", "\n" ] } ], "source": [ "# Générer le rapport de classification\n", "report = classification_report(y_true, y_pred, target_names=labels)\n", "#report = classification_report(y_true, y_pred)\n", "\n", "# Afficher le rapport de classification\n", "print(report)" ] }, { "cell_type": "code", "execution_count": 68, "id": "28a724f9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Accessibilité 2579\n", "Autre 2211\n", "Actualisation 1213\n", "Fiabilité 897\n", "Exploitabilité 577\n", "Compréhension 471\n", "Name: categorie, dtype: int64" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['categorie'].value_counts()" ] }, { "cell_type": "markdown", "id": "d9a9828f", "metadata": {}, "source": [ "# Evaluation du modèle : Matrice de confusion" ] }, { "cell_type": "code", "execution_count": 69, "id": "d577ff38", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Calculer la matrice de confusion\n", "confusion_mat = confusion_matrix(y_true, y_pred)\n", "\n", "# Obtenir les noms des classes à partir des identifiants de label\n", "class_names = [id2label[i] for i in range(len(labels))]\n", "\n", "# Normaliser la matrice de confusion pour afficher les pourcentages\n", "confusion_mat_norm = confusion_mat.astype('float') / confusion_mat.sum(axis=1)[:, np.newaxis]\n", "\n", "# Créer une figure\n", "plt.figure(figsize=(8, 6))\n", "\n", "# Tracer la matrice de confusion\n", "sns.heatmap(confusion_mat_norm, annot=True, fmt=\".2f\", cmap=\"Blues\", xticklabels=class_names, yticklabels=class_names)\n", "\n", "# Ajouter des étiquettes aux axes\n", "plt.xlabel(\"Prédictions\")\n", "plt.ylabel(\"Vraies étiquettes\")\n", "\n", "# Ajouter un titre\n", "plt.title(\"Matrice de confusion\")\n", "\n", "# Afficher la figure\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "dc957de9", "metadata": {}, "source": [ "# Recharger le modèle pré-entrainé (non zippé)" ] }, { "cell_type": "code", "execution_count": 70, "id": "42cb23b4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'# Sauvegarde du modèle pré-entraîné\\n\\n# Chemin de destination pour enregistrer le modèle et le tokenizer\\noutput_dir = \"modeleBertSaved\"\\n\\n# Enregistrer le modèle\\nmodel.save_pretrained(output_dir)\\n\\n# Enregistrer le tokenizer\\ntokenizer.save_pretrained(output_dir)\\n'" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"# Sauvegarde du modèle pré-entraîné\n", "\n", "# Chemin de destination pour enregistrer le modèle et le tokenizer\n", "output_dir = \"modeleBertSaved\"\n", "\n", "# Enregistrer le modèle\n", "model.save_pretrained(output_dir)\n", "\n", "# Enregistrer le tokenizer\n", "tokenizer.save_pretrained(output_dir)\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 71, "id": "462067d6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'# Rechargement du modèle pré-entraîné\\n\\n# Charger le modèle à partir du dossier sauvegardé\\nmodel_saved = AutoModelForSequenceClassification.from_pretrained(output_dir)\\n\\n# Charger le tokenizer à partir du dossier sauvegardé\\ntokenizer_saved = AutoTokenizer.from_pretrained(output_dir)\\n'" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"# Rechargement du modèle pré-entraîné\n", "\n", "# Charger le modèle à partir du dossier sauvegardé\n", "model_saved = AutoModelForSequenceClassification.from_pretrained(output_dir)\n", "\n", "# Charger le tokenizer à partir du dossier sauvegardé\n", "tokenizer_saved = AutoTokenizer.from_pretrained(output_dir)\n", "\"\"\"" ] }, { "cell_type": "markdown", "id": "a22ea361", "metadata": {}, "source": [ "# Recharger le modèle pré-entrainé (zippé)" ] }, { "cell_type": "code", "execution_count": 72, "id": "8c122953", "metadata": {}, "outputs": [], "source": [ "# Enregistrement les fichiers de poids et d'entrainement du modele\n", "\n", "#import shutil\n", "#import zipfile\n", "\n", "# Chemin de destination pour enregistrer le modèle\n", "model_directory = \"bert-finetuned-my-data-final\"\n", "\n", "# Sauvegarder le modèle avec les fichiers de poids\n", "trainer.save_model(model_directory)\n", "# Sauvegarder le tokenizer\n", "tokenizer.save_pretrained(model_directory)\n", "\n", "# Compresser le dossier au format .zip\n", "shutil.make_archive(model_directory + \"_archive\", 'zip', model_directory)\n", "\n", "# Chemin de destination pour le fichier .zip\n", "zip_file_path = model_directory + \"_archive.zip\"\n" ] }, { "cell_type": "code", "execution_count": 73, "id": "15aff158", "metadata": {}, "outputs": [], "source": [ "# Charger le model pré-entrainé (zippé)\n", "\n", "# Extraire le contenu du fichier .zip dans un répertoire temporaire\n", "zip_file_path = \"bert-finetuned-my-data-final_archive.zip\"\n", "extract_dir = \"extracted_model\"\n", "with zipfile.ZipFile(zip_file_path, 'r') as zip_ref:\n", " zip_ref.extractall(extract_dir)\n", "\n", "# Charger le modèle à partir du répertoire extrait\n", "model_saved = AutoModelForSequenceClassification.from_pretrained(extract_dir)\n", "\n", "# Charger le tokenizer à partir du même répertoire extrait\n", "tokenizer_saved = AutoTokenizer.from_pretrained(extract_dir)" ] }, { "cell_type": "code", "execution_count": 74, "id": "a6e7e313", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Texte : Problème avec le lien, je n'arrive pas à accéder à la page\n", "Label prédit : 3\n", "Nom du label prédit : Accessibilité\n" ] } ], "source": [ "# Test\n", "\n", "# Prétraitement des nouvelles données\n", "new_data = [\"Problème avec le lien, je n'arrive pas à accéder à la page\"]\n", "\n", "encoded_inputs = tokenizer_saved(new_data, truncation=True, padding=True, return_tensors=\"pt\")\n", "\n", "# Passage des données dans le modèle pour l'inférence\n", "with torch.no_grad():\n", " outputs = model_saved(**encoded_inputs)\n", "\n", "# Récupération des prédictions\n", "predictions = outputs.logits\n", "predicted_labels = torch.argmax(predictions, dim=1)\n", "\n", "# Affichage des résultats\n", "for text, label in zip(new_data, predicted_labels):\n", " print(f\"Texte : {text}\")\n", " print(f\"Label prédit : {label}\")\n", " #print(type(label))\n", " label = label.item()\n", " #print(type(label))\n", " print(f\"Nom du label prédit : {id2label[label]}\")" ] }, { "cell_type": "markdown", "id": "168368da", "metadata": {}, "source": [ "# Inférence avec les données du MEFSIN" ] }, { "cell_type": "code", "execution_count": 75, "id": "3b22a960", "metadata": {}, "outputs": [], "source": [ "# Chargement des données du MEFSIN\n", "\n", "df_MEFSIN = pd.read_csv(\"DISCUSSIONS_MEFSIN_DATAGOUV_27032023.csv\")\n", "\n", "#df_MEFSIN = pd.read_csv(\"Jeu_MEFSIN_Asma.csv\")" ] }, { "cell_type": "code", "execution_count": 76, "id": "0ae9c71b", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idusersubjecttitlesizemessagescreatedclosedclosed_byMEFSIN
06418839138db635b9a8ec61aChristophe BADOLParcellaire Express (PCI)Disparition de la table arrondissement de la l...2Bonjour,\\n\\nla table arrondissement a disparu ...2023-03-20T17:02:25.636000NaNNaN1
1641861cca4f1971589503cb9Estelle CrĆFichiers des locaux et des parcelles des perso...Siren cessĆ1Bonjour, Pourquoi y a-t-il des Siren dont l'Ć2023-03-20T14:38:20.353000NaNNaN1
26413358dcce10824f53a9bc9Camille BaconDemandes de valeurs fonciĆ1 idloc = 1 local1Bonjour,\\n\\nTout d'abord, merci pour ces donnĆ2023-03-16T16:28:13.300000NaNNaN1
364088027de783a9eadb04349JĆPrix des carburants en France - Flux instantanĆDate d'obsolescence de ce jeu de donnĆ1Bonjour, la description du jeu de donnĆ2023-03-08T13:31:35.125000NaNNaN1
4640869f8abc8970cefa9c3d4Anne SolazL'impĆliens non focntionnels1Bonjour, Je n'arrive pas Ć2023-03-08T11:56:56.125000NaNNaN1
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" ], "text/plain": [ " id user \\\n", "0 6418839138db635b9a8ec61a Christophe BADOL \n", "1 641861cca4f1971589503cb9 Estelle CrĆ \n", "2 6413358dcce10824f53a9bc9 Camille Bacon \n", "3 64088027de783a9eadb04349 JĆ \n", "4 640869f8abc8970cefa9c3d4 Anne Solaz \n", "\n", " subject \\\n", "0 Parcellaire Express (PCI) \n", "1 Fichiers des locaux et des parcelles des perso... \n", "2 Demandes de valeurs fonciĆ \n", "3 Prix des carburants en France - Flux instantanĆ \n", "4 L'impĆ \n", "\n", " title size \\\n", "0 Disparition de la table arrondissement de la l... 2 \n", "1 Siren cessĆ 1 \n", "2 1 idloc = 1 local 1 \n", "3 Date d'obsolescence de ce jeu de donnĆ 1 \n", "4 liens non focntionnels 1 \n", "\n", " messages \\\n", "0 Bonjour,\\n\\nla table arrondissement a disparu ... \n", "1 Bonjour, Pourquoi y a-t-il des Siren dont l'Ć \n", "2 Bonjour,\\n\\nTout d'abord, merci pour ces donnĆ \n", "3 Bonjour, la description du jeu de donnĆ \n", "4 Bonjour, Je n'arrive pas Ć \n", "\n", " created closed closed_by MEFSIN \n", "0 2023-03-20T17:02:25.636000 NaN NaN 1 \n", "1 2023-03-20T14:38:20.353000 NaN NaN 1 \n", "2 2023-03-16T16:28:13.300000 NaN NaN 1 \n", "3 2023-03-08T13:31:35.125000 NaN NaN 1 \n", "4 2023-03-08T11:56:56.125000 NaN NaN 1 " ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_MEFSIN.head()" ] }, { "cell_type": "code", "execution_count": 77, "id": "577f490d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"# Remplacement des encodages incorrectes\\ndef corriger_encodage(df, colonnes):\\n for colonne in colonnes:\\n df[colonne] = df[colonne].str.replace('é', 'é')\\n df[colonne] = df[colonne].str.replace('é', 'é')\\n df[colonne] = df[colonne].str.replace('à¨', 'è')\\n df[colonne] = df[colonne].str.replace('ê', 'ê')\\n df[colonne] = df[colonne].str.replace('à‰', 'É')\\n df[colonne] = df[colonne].str.replace('Ã', 'à')\\n df[colonne] = df[colonne].str.replace('à¢', 'â')\\n df[colonne] = df[colonne].str.replace('à´', 'ô')\\n df[colonne] = df[colonne].str.replace('à®', 'î')\\n df[colonne] = df[colonne].str.replace('à§', 'ç')\\n df[colonne] = df[colonne].str.replace('’', ''')\\n df[colonne] = df[colonne].str.replace('à€', 'À')\\n df[colonne] = df[colonne].str.replace('Â', '')\\n return df\\n\\ndf_MEFSIN = corriger_encodage(df_MEFSIN, ['user', 'subject', 'title', 'messages'])\\n\"" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"# Remplacement des encodages incorrectes\n", "def corriger_encodage(df, colonnes):\n", " for colonne in colonnes:\n", " df[colonne] = df[colonne].str.replace('é', 'é')\n", " df[colonne] = df[colonne].str.replace('é', 'é')\n", " df[colonne] = df[colonne].str.replace('à¨', 'è')\n", " df[colonne] = df[colonne].str.replace('ê', 'ê')\n", " df[colonne] = df[colonne].str.replace('à‰', 'É')\n", " df[colonne] = df[colonne].str.replace('Ã', 'à')\n", " df[colonne] = df[colonne].str.replace('à¢', 'â')\n", " df[colonne] = df[colonne].str.replace('à´', 'ô')\n", " df[colonne] = df[colonne].str.replace('à®', 'î')\n", " df[colonne] = df[colonne].str.replace('à§', 'ç')\n", " df[colonne] = df[colonne].str.replace('’', '\\'')\n", " df[colonne] = df[colonne].str.replace('à€', 'À')\n", " df[colonne] = df[colonne].str.replace('Â', '')\n", " return df\n", "\n", "df_MEFSIN = corriger_encodage(df_MEFSIN, ['user', 'subject', 'title', 'messages'])\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 78, "id": "a9cceba7", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idusersubjecttitlesizemessagescreatedclosedclosed_byMEFSIN
06418839138db635b9a8ec61aChristophe BADOLParcellaire Express (PCI)Disparition de la table arrondissement de la l...2Bonjour,\\n\\nla table arrondissement a disparu ...2023-03-20T17:02:25.636000NaNNaN1
1641861cca4f1971589503cb9Estelle CrĆFichiers des locaux et des parcelles des perso...Siren cessĆ1Bonjour, Pourquoi y a-t-il des Siren dont l'Ć2023-03-20T14:38:20.353000NaNNaN1
26413358dcce10824f53a9bc9Camille BaconDemandes de valeurs fonciĆ1 idloc = 1 local1Bonjour,\\n\\nTout d'abord, merci pour ces donnĆ2023-03-16T16:28:13.300000NaNNaN1
364088027de783a9eadb04349JĆPrix des carburants en France - Flux instantanĆDate d'obsolescence de ce jeu de donnĆ1Bonjour, la description du jeu de donnĆ2023-03-08T13:31:35.125000NaNNaN1
4640869f8abc8970cefa9c3d4Anne SolazL'impĆliens non focntionnels1Bonjour, Je n'arrive pas Ć2023-03-08T11:56:56.125000NaNNaN1
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" ], "text/plain": [ " id user \\\n", "0 6418839138db635b9a8ec61a Christophe BADOL \n", "1 641861cca4f1971589503cb9 Estelle CrĆ \n", "2 6413358dcce10824f53a9bc9 Camille Bacon \n", "3 64088027de783a9eadb04349 JĆ \n", "4 640869f8abc8970cefa9c3d4 Anne Solaz \n", "\n", " subject \\\n", "0 Parcellaire Express (PCI) \n", "1 Fichiers des locaux et des parcelles des perso... \n", "2 Demandes de valeurs fonciĆ \n", "3 Prix des carburants en France - Flux instantanĆ \n", "4 L'impĆ \n", "\n", " title size \\\n", "0 Disparition de la table arrondissement de la l... 2 \n", "1 Siren cessĆ 1 \n", "2 1 idloc = 1 local 1 \n", "3 Date d'obsolescence de ce jeu de donnĆ 1 \n", "4 liens non focntionnels 1 \n", "\n", " messages \\\n", "0 Bonjour,\\n\\nla table arrondissement a disparu ... \n", "1 Bonjour, Pourquoi y a-t-il des Siren dont l'Ć \n", "2 Bonjour,\\n\\nTout d'abord, merci pour ces donnĆ \n", "3 Bonjour, la description du jeu de donnĆ \n", "4 Bonjour, Je n'arrive pas Ć \n", "\n", " created closed closed_by MEFSIN \n", "0 2023-03-20T17:02:25.636000 NaN NaN 1 \n", "1 2023-03-20T14:38:20.353000 NaN NaN 1 \n", "2 2023-03-16T16:28:13.300000 NaN NaN 1 \n", "3 2023-03-08T13:31:35.125000 NaN NaN 1 \n", "4 2023-03-08T11:56:56.125000 NaN NaN 1 " ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_MEFSIN.head()" ] }, { "cell_type": "code", "execution_count": 79, "id": "e8454c6d", "metadata": {}, "outputs": [], "source": [ "df_MEFSIN['combined_text'] = df_MEFSIN['title'] + ' ' + df_MEFSIN['messages']\n", "\n", "#df_MEFSIN['combined_text'] = df_MEFSIN['title_discussion'] + ' ' + df_MEFSIN['messages_discussion']" ] }, { "cell_type": "code", "execution_count": 80, "id": "e44a24f9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "id 6418839138db635b9a8ec61a\n", "user Christophe BADOL\n", "subject Parcellaire Express (PCI)\n", "title Disparition de la table arrondissement de la l...\n", "size 2\n", "messages Bonjour,\\n\\nla table arrondissement a disparu ...\n", "created 2023-03-20T17:02:25.636000\n", "closed NaN\n", "closed_by NaN\n", "MEFSIN 1\n", "combined_text Disparition de la table arrondissement de la l...\n", "Name: 0, dtype: object" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_MEFSIN.iloc[0]" ] }, { "cell_type": "code", "execution_count": 81, "id": "781c75df", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Disparition de la table arrondissement de la livraison 2023 Bonjour,\\n\\nla table arrondissement a disparu de la livraison au 1er janvier 2023. Sait-on pourquoi ?\\nLa classe ARRONDISSEMENT nÄ\\x86ÂḃÄ\\x81â\\x80\\x9aÂỲÄ\\x81â\\x80\\x9eÂḃest prÄ\\x86'" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_MEFSIN.loc[0, \"combined_text\"]" ] }, { "cell_type": "code", "execution_count": 82, "id": "e1779f4f", "metadata": {}, "outputs": [], "source": [ "#Sélection des features (X) à utiliser pour l'inférence\n", "\n", "#features = df_MEFSIN[\"messages\"]\n", "###features = df_MEFSIN[\"combined_text\"]" ] }, { "cell_type": "code", "execution_count": 83, "id": "5ca02d27", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['disparition de la table arrondissement de la livraison bonjour, la table arrondissement a disparu de la livraison au er . sait-on pourquoi la classe arrondissement näâḃäââỳäââḃest prä',\n", " \"siren cessä bonjour, pourquoi y a-t-il des siren dont l'ä\",\n", " \"idloc local bonjour, tout d'abord, pour ces donnä\",\n", " \"date d'obsolescence de ce jeu de donnä bonjour, la description du jeu de donnä\",\n", " \"liens non focntionnels bonjour, je n'arrive pas ä\",\n", " 'plateforme non indiquä bonjour, pourriez-vous me dire si les donnä',\n", " 'donnä ma collectivitä',\n", " 'parcelle bt - commune de carriä bonjour, je vous contacte car je souhaiterais connaitre les ventes dans la rä',\n", " \"lien vers le flux bonjour, j'ai quelques questions de base sur vos donnä\",\n", " 'impossible de trouver nos donnä bonjour, nos donnä',\n", " 'vue satellite depuis quelque temps, impossible de faire des recherches sur dvf avec une vue satellite, seul lä',\n", " \"frä bonjour, je me demandais s'il y avait une raison de faire une mise ä\",\n", " \"telechargement automatisä bonjour, j'utilisais curl sous windows cmd, pour tä\",\n", " 'documentation jeu de donnä nous avons dä',\n", " \"une erreur sur la surface d'un bien. comment faire la correction bonjour, je constate une erreur sur la surface indiquä\",\n", " 'accä je me permets de vous contacter car depuis dä',\n", " \"donnä bonjour, serait-il possible d'obtenir les donnä\",\n", " \"data bonjour, serait-il possible d'avoir en flux json la donnä\",\n", " 'problä veuillez conträ',\n", " 'problä bonjour, je vous contacte urgement pour vous signaler un trou dans les donnä',\n", " \"travail salut. avez-vous une liste de site internet pour la recherche d'emplois pour l' immigration en france plusieurs sites oä\",\n", " 'apparemment, rien non plus sur ma commune sainte genevieve des bois - en espä',\n", " \"erreur sur le prix de vente de ma parcelle (le prix n'est pas sensä bonjour, il y a une erreur sur le prix de vente de ma parcelle annoncä\",\n", " \"manque une paecelle dans la vente il manque la parcelle principale dans l'achat que j'ai effectuä\",\n", " 'absences de donnä il semblerait que sur la commune de marseille et sur ses arrondissements le nombre de transactions rä',\n", " 'mise ä bonjour, avez-vous un dä',\n", " \"recherche historique construction sur parcelles ä bonjour, je recherche l'historique sur plusieurs parcelles mitoyennes propriä\",\n", " 'donnä bonjour, je travaille sur un project de recherche et voulais savoir si il ä',\n", " \"dä je vous contacte car depuis le mercredi votre site dvf dysfonctionne... j'ai essayä\",\n", " 'historiques de plusieurs parcelles bonjour. je suis ä',\n", " \"erreur d'adresse vente maison rue de la piscine (saint-genis-laval) bonjour, la maison vendue le au prix de äâḃäâ\",\n", " 'produits de fonctionnement caf bonjour, beaucoup pour ces fichiers qui sont trä',\n", " \"declarations avant non disponibles bonjour, pourquoi est-il impossible de telecharger l'ensemble des declarations prealables a (toutes indiquees comme indisponibles) bien cordialement, al\",\n", " 'gestion des doublons bonjour, le ficher dvf peut comporter certains doublons. le problä',\n", " \"mise ä bonjour, je voulais savoir s'il y allait avoir une mise ä\",\n", " 'avenue alexandre - nanterre bonjour, il manque apparemment une vente de maison avenue alexandre ä',\n", " 'station fermä sa garages nation rue de picpus paris id et elle ne rouvrira pas. les rä',\n", " 'publication des donnä bonjour, les donnä',\n", " 'mise ä bonjour, auriez-vous de la visibilitä',\n", " 'coordonnä les stations suivantes ont des coordonnä',\n", " 'rupture carburant bonjour, la donnä',\n", " \"historique des flux quotidien bonjour, auriez vous l'historique des flux quotidien au format xml pour ce mois d'octobre ( du er au ). d'avance bonjour, vous pouvez rä\",\n", " 'quelle fiabilitä ä',\n", " 'donnä bonjour, je constate que dans le fichier instantanä',\n", " \"changement des id bonjour, dans la nuit du au l'ensemble des id des produits a ä\",\n", " 'date prochaine publication bonjour, connaissez-vous la date de publication des prochaines donnä',\n", " \"incohä bonjour, j'observe pour certaines communes certains chiffres que je n'arrive pas ä\",\n", " 'publication donnä bonjour, pourriez-vous nous donner la date prä',\n", " \"donnä bonjour, je souhaitais savoir s'il existait des donnä\",\n", " \"dvf en alsace moselle, est-ce pour bientä bonjour, j'aimerais savoir si les donnä\",\n", " 'prix de vente affichä la maison au rue casabianca toulon cadastre bd, ne s est pas vendu au prix de äâḃäâ',\n", " 'code rä bonjour, a quoi correspondent les codes rä',\n", " \"type de locaux bonjour, je travaille sur le dataset fichier des locaux et nous avons des doutes . si j'ai bien compris, une parcelle peut comprendre plus d'un local, non . afin d'identifier chaque local, nous avons utilisä\",\n", " \"diffä bonjour, j'avais pris l'habitude de traiter les donnä\",\n", " 'une api qui fournit les impä bonjour, je serais intä',\n", " 'donnä a quelle date le rei pourra t il ä',\n", " \"nature mutation ä bonjour, pourriez-vous m'indiquer ä\",\n", " \"donnä bonjour, je vous contacte car j'aimerais savoir quand les donnä\",\n", " \"erreur prix de vente bonjour, j'ai achetä\",\n", " 'millä pour information, la gä',\n", " 'balances comptables bonjour, connaissez-vous la date de la publication des balances comptables par avance,',\n", " 'le lien de la description du fichier fantoir ne fonctionne plus pouvez-vous le reparer bonjour, le dernier fichier fantoir, en situation , est disponible et tä',\n", " 'effondrement du nombre de ventes en commune de marseille bonjour, le nombre de transactions dans sa totalitä',\n", " 'disponibilitä serait il possible dans le dä',\n", " 'rei bonjour. le fichier du rei me semble erronä',\n", " \"erreur sur m de mon appartement bonjour, j'ai achetä\",\n", " \"personnes morales non associä bonjour, j'ai remarquä\",\n", " \"erreur plan maison d'une parcelle cadastrale bonjour, j'ai remarquä\",\n", " \"question sur la mä bonjour, j'aimerais connaitre la mä\",\n", " 'lien cassä bonjour, le lien vers la notice officielle est cassä',\n", " 'plus de maj depuis le bonjour, je ne vois plus de maj depuis le pour votre aide pour votre signalement, nous venons de rä',\n", " 'transactions immobiliä bonjour, comment et ou sont enregisträ',\n", " 'ontology, classes manquantes bonjour, concernant les spä',\n", " 'modifications donnä bonjour, comment modifier une donnä',\n", " 'limites et prä chä',\n", " \"donnä bonjour, sur dvf il est impossible d'accä\",\n", " 'document descriptif des fichiers des parcelles de personnes morales - erreur sur la forme juridique abrä madame, monsieur bonjour, nous constatons une erreur dans le fichier fichier des parcelles des personnes morales_descriptif - .pdf. en effet il existe un dä',\n", " 'erreur sur m et nombre de piä bonjour, nous avons constatä',\n", " 'et ensuite aprä',\n", " \"mise ä bonjour, dans le cadre de l'ä\",\n", " 'rei bonjour, savez vous quand le rei millä',\n", " 'parcelle privä madame, monsieur, je suis ä',\n", " \"fichier fantoir bonjour, savez-vous quand le fichier fantoir d'avril sera disponible bonjour, la publication des fichiers fantoir a lieu tous les trimestres, en fä\",\n", " 'changement dä bonjour, un de nos contact vient de nous signaler, sur les plans mis ä',\n", " 'erreur prix de vente bonjour, je suis allä',\n", " 'prix de vente sur data gouv et prä bonjour, nous constatons que le prix de vente effectif du bien que nous occupons est bien infä',\n", " \"accä bonjour, dans le cadre de l'ä\",\n", " \"transaction avec plusieurs disposition bonjour, j'essaie de comprendre les mutations avec plusieurs dispositions. il y a beaucoup de mutations avec un numä\",\n", " \"erreur sur m de mon appartement bonjour, j'ai achetä\",\n", " 'dvf gä bonjour, les dvf du ä',\n", " 'fichiers historiques bonjour, en voulant accä',\n", " \"idem m. bottari la recherche d'adresse, ne fonctionne toujours pas , seule figure ä\",\n", " 'envoyer un tableau de ean dans la requete avec le parametre q bonjour, ma question est sur le fait que je dä',\n", " 'forte baisse du nombre de transactions dans le dä bonjour, dans le cadre däâḃäââỳäââḃune ä',\n", " 'baisse du nombre de transactions dans le finistä bonjour, dans le cadre däâḃäââỳäââḃune ä',\n", " 'informations sur le donnä bonjour, je travaille pour une spin-off italienne du politecnico di torino, nous dä',\n", " 'site inaccessible bonjour, nous ne pouvons plus accä',\n", " \"prix d'une acquisition bonjour, je cherche ä\",\n", " 'reprä bonjour, ä',\n", " 'accä bonjour, je vois que le fichier proposä',\n", " 'donnä bonjour, serait-il possible de mettre ä',\n", " 'ajout de champs ä nous exploitons votre export csv pour publier les donnä',\n", " \"mise ä bonjour, quand peut-on s'attendre ä\",\n", " \"identifiant unique pour chaque propriä bonjour, j'ai tä\",\n", " 'absence donnä bonjour, les donnä',\n", " 'beaucoup de communes manquantes bonjour, je suis confrontä',\n", " 'anterioritä nous sommes ä',\n", " 'localisation des projets laurä bonjour, pourriez-vous localiser les projets laurä',\n", " 'tableau de la fiscalitä je ne peux plus accä',\n", " \"incohä bonjour, une transaction apparait sur la parcelle bm pour l'annä\",\n", " 'mise ä je suis ä',\n", " \"prix incomprä bonjour, je ne comprends pas certains prix dvf. pour prendre seulement exemples, lorsque l'on cherche dans la carte etalab dvf, avec dä\",\n", " 'contenu des donnä bonjour, est-ce que le jeu de donnä',\n", " \"bureaux distributeurs de la poste bonjour, pouvez-vous m'indiquer si les bureaux distributeurs de la poste, prä\",\n", " 'fichier tracä le fichier tracä',\n", " 'numä bonjour, les donnä',\n", " 'identifiant du marchä bonjour, les donnä',\n", " \"prix et viager bonjour, lors d'une vente en viager quel montant apparait publiquement sur dvf. florent\",\n", " 'fichiers indisponibles bonjour, les fichiers de cette page ne sont actuellement pas disponibles au tä',\n", " 'difference entre fma du mä quelle est la diffä',\n", " 'url stable du fichier fma du jour je viens bä',\n", " 'erreur surface donnä il existe une erreur de surface sur les donnä',\n", " \"fixing unknown distribution formats hello there, thanks for this great dataset. i'm from data.europa.eu and came across this dataset. i would like to ask if it may be possible to change the formats of the distributions for this dataset. the mime-type seems to be correct, but the format shows something like tour..csv. this is not very helpful when searching for datasets that provides distributions with a specific format. i would expect a format like csv in this case. thanks a lot ben hi, thank you for your comment. we have expertised the issue and came to the conclusion that it's the data.gouv.fr platform that infers file types from file extensions. beginning today ( jan ), we have modified the file names to correct this issue. we hope that this will help the data.europa.eu platform index this dataset. thank you the datatourisme team dear datatourisme team, thanks a lot for the fast response. this truly helps to make it easier finding your data. best ben sujet clos\",\n", " 'retrouver des fichiers transmis via pes bonjour, etant une esh, je travaille avec marcoweb et afin de faire le recensement je dois transmettre les donnä',\n", " \"au sujet d'etalab bonjour, je suis un particulier qui a achetä\",\n", " \"absence näâäâḟsiren bonjour, je m'associe ä\",\n", " \"numä bonjour, pouvez-vous m'indiquer dans quel(s) cas un numä\",\n", " \"frä bonjour, serait-il possible d'augmenter la frä\",\n", " 'fimoca et fimoct de a quelle date allons-nous avoir les fichiers fimoca et fimoct de svp bonjour, je vous informe que les fichiers fimoct et fimoca du mois de seront disponibles trä',\n", " \"impossible d'ouvrir le fichier sous excel bonjour, souhaitant rä\",\n", " 'donä bonjour, est-ce normal que certains agents immobilier comme meilleursagents.com ou mobe.fr affiche publiquement et plus de ans aprä',\n", " \"fiabilitä bonjour, j'essaie actuellement d'analyser les donnä\",\n", " 'comment distinguer les poi dans le fichier par rä bonjour, dans le fichier par rä',\n", " 'source sgpr bonjour, pouvez vous prä',\n", " \"droits d'accä bonjour, faisant parti de l'ä\",\n", " 'fichier des parcelles bonjour, je ne trouve pas de donnä',\n", " \"ressources dä bonjour, j'ai plusieurs demandes - d'abord une vä\",\n", " \"question sur les donnä bonjour, j'ai remarquä\",\n", " \"donnä bonjour, pour les besoins du calcul de l'empreinte biodiversitä\",\n", " \"ifer et rä bonjour, les chiffres de l'ifer ne correspondent pas ä\",\n", " \"heure de mis ä bonjour, de m'indiquer les heures de mise ä\",\n", " 'erreur däâḃäââỳäââḃanalyse xml aucun ä bonjour, mä',\n", " 'surface du propriä il semblerait que la donnä',\n", " \"renseignement - indicateurs madame, monsieur, j'aimerais savoir la signification des colonnes engagement_manifeste et engagement_data et leur diffä\",\n", " 'erreur adresse bonjour, sur la parcelle cadastrale d, je me suis aperä',\n", " \"erreur concernant la vente d'une cave le bonjour, pour les ventes concernant aubervilliers () et plus particuliä\",\n", " 'donnä bonjour, je remarque que de nombreuses parcelles appartenant pourtant ä',\n", " \"annä lorsque l'on cherche ä\",\n", " \"montants des financements erronä en ce qui concerne l'anct (et peut-ä\",\n", " 'absences de surfaces de logements bonjour, jäâḃäââỳäââḃai constatä',\n", " 'fichier dgfip-pes-decp.xml indisponible bonjour, le fichier dgfip-pes-decp.xml est indisponible depuis plusieurs jours taille octets quand on le tä',\n", " 'empty file bonjour, je reä',\n", " \"dvf gä bonjour, les dvf du er trimestre viennent d'ä\",\n", " \"manque nature_mutation dans documentation hello, juste pour info, il manque la colonne näâäâḟ nature_mutation dans la doc. alors qu'elle est bien prä\",\n", " \"comment ouvrir le fichier fantoir bonjour, a l'aide de quel logiciel peut-on ouvrir et lire ce fichier. rien d'indiquä\",\n", " 'mise a disposition des donnä bonjour, existe-t-il une api pour rä',\n", " 'erreur bien annoncä bonjour, ma rä',\n", " \"identification des produits par leur code-barre tout d'abord bravo pour la mise ä\",\n", " \"ce fichier balances-comptables-des-syndicats-depuis-.csv dont le nom porte depuis n'a plus les donnä bonjour, en tä\",\n", " 'demande de donnä bonjour, je souhaite demander une nouvelle donnä',\n", " \"donnä bonjour, je suis open data manager pour la dgfip (dont provient l'original du jeu de donnä\",\n", " 'ajout donnä bonjour, pour le fichier sur les locaux, serait-il possible de rajouter le type de local (logementbureauusineautre) cette donnä',\n", " 'dä est-il possible de faire la jointure entre ancien et nouveau libellä',\n", " \"baisse du nombre de biens dvf en bonjour, j'ai remarquä\",\n", " 'donnä les donnä',\n", " 'prochaine mise ä bonjour, savez-vous lorsque ce fichier sera mis ä',\n", " 'demande de renseignements sur les donnä madame, monsieur, ou puis-je trouver les indicateurs renseignä',\n", " 'documentation manquante bonjour, pour information le lien vers la notice officielle (httpscadastre.data.gouv.frdatahackathon-dgfip-dvfnotice-descriptive-du-fichier-dvf.pdf) est mort.',\n", " 'caractä bonjour, il semblerait que les caractä',\n", " \"fraicheur des donnä j'ai trouvä\",\n", " 'erreur surface je viens de regarder votre site recensant les ventes immobiliä',\n", " \"simulation taxe gemapi bonjour, dans le cadre de simulations de la taxe gemapi, j'ai besoin de recenser la taxe fonciä\",\n", " 'fichier txt bonjour, est-il possible de tä',\n", " 'le fichier principal au format ocds decp.ocds.json est tronquä chez moi le fichier decp.ocds.json est tronquä',\n", " 'dvf gä deleted',\n", " \"demande de donnä bonjour, je travaille dans l'agence de notation financiä\",\n", " \"erreur ä bonjour, c'est un peu long ä\",\n", " 'zonage plu bonjour, serait-ce possible de rä',\n", " 'dvf moselle alsace indisponibles bonjour, pour quelle raison lä',\n", " \"problä bonjour, j'ä\",\n", " 'erreur ä bonjour, cette voie publique a ä',\n", " \"id identifiant du ministä bonjour, pourriez-vous m'indiquer comment faire correspondre l'identifiant du ministä\",\n", " \"demande de document bonjour, est-il possible d'avoir la dvf , et en format .cvs je suis dans le dä\",\n", " 'valeur fonciä sur la base dvf, les valeurs fonciä',\n", " 'crä bonjour, je me permets de vous contacter afin de connaä',\n", " \"suggestion d'un nouveau mot-clä bonjour, je propose ce nouveau mot-clä\",\n", " \"prä bonjour, j'utilise la base donnä\",\n", " 'rä bonjour, je recherche les rä',\n", " \"changement url bonjour, l'url permettant d'accä\",\n", " 'utilisation fantoir bonjour, avec quel logiciel puis-je lire le fichier fantoir bonjour, le fichier fantoir tä',\n", " 'valeur total dvf bonjour, dans un premier temps pour le travail que vous avez effectuä',\n", " 'prä bonjour, je voulais savoir si les entreprises mentionnä',\n", " 'mise ä bonjour, utilisateur rä',\n", " 'carte dä bonjour, madame monsieur je vous ä',\n", " \"histoire numä bonjour, je cherche l'historique de la numä\",\n", " \"donnä je ne trouve pas dans vos fichiers les stations d'avitaillement situä\",\n", " \"niveau local bonjour, pourriez-vous m'indiquer s'il y a une table de correspondance pour le niveau des locaux je vois beaucoup de valeur entre et ... cordialement, bonjour, je me joins ä\",\n", " 'droit ä bonjour, nous avons achetä',\n", " 'actualisation bonjour, les donnä',\n", " 'mise ä monsieur, la mise ä',\n", " 'ancien näâäâḟ de parcelle des voisins me fait des difficultä',\n", " 'lecture des donnä bonjour, pouvez-vous nous indiquer sur la page comment lire les donnä',\n", " 'dvf gä deleted',\n", " \"etalab l 'application httpsapp.dvf.etalab.gouv.fr ne fonctionne plus comment y remä\",\n", " 'type de transaction bonjour, avez vous le type de transaction dans le csv car je ne le trouve pas dans les points txt il y a le type de transaction.',\n", " 'automatisation bonjour, est il possible de rä',\n", " \"demande d'information sur les donnä je suis bloquä\",\n", " 'il n y a pas les näâäâḟdes parcelles sur les plans comment les trouver alors ., il n y a pas les näâäâḟdes parcelles sur les plans demande de valeurs fonciä',\n", " 'actualisation des donnä bonjour, les donnä',\n", " 'ajout nouvelles voies bonjour, la commune de claret () souhaite pouvoir mettre ä',\n", " \"ordre de parution de la publication du fichier fantoir bonjour, pourriez-vous inverser l'affichage de l'ordre de parution des diffä\",\n", " 'import geojson par commune du finistä bonjour, la page commune du dä',\n", " 'donnä bonjour, nous utilisons le pes marchä',\n", " 'flux non rä bonjour, nous utilisons le pes marchä',\n", " 'mise ä bonjour, les donnä',\n", " \"historique parcelle cadastrale bonsoir, est-il possible de trouver l'historique de parcelles cadastrales en remontant jusqu'en\",\n", " 'demande de coordonnä puis-je avoir les coordonnä',\n", " \"comment est alimenter le fichier fantoir comment est alimenter le fichier fantoir en effet, dans ma commune (bobigny,) existe une rue marcello mastroianni. mais celle-ci n'est pas rä\",\n", " \"disparition d'une section cadastrale sur rueil-malmaison bonjour, depuis läâḃäââỳäââḃannä\",\n", " 'rä ä',\n", " 'filiation des parcelles cadastrales je cherche ä',\n", " \"disparition d'une parcelle asnieres sur seine ( ) depuis l'annä\",\n", " 'absence de la colonne section_prefixe bonjour, ces fichiers de donnä',\n", " \"donnä bonjour, j'ai tä\",\n", " 'codes insee de commune inconnues du code officiel gä bonjour, ä',\n", " 'donnä y-a-t-il des modifications sur les fichiers - ä',\n", " 'mise ä la nouvelle version du fichier source dvf a ä',\n", " 'page trop lourde ä bonjour, la prä',\n", " \"l'adresse courriel ne fonctionne plus rencontrant des difficultä\",\n", " 'donnä pour cette mise ä',\n", " \"eme semetre bonjour, quand le fichier du eme semetre sera t'il disponible bonjour, avez-vous prä\",\n", " \"inventaire immobilier de l'ä bonjour, les donnä\",\n", " \"rei quand ou ou est il possible d'avoir les taux d'imposition en fiscalitä\",\n", " \"prä bonjour, je voudrai calculer le montant total des importations en . exemple en sommant l'ensemble des donnä\",\n", " 'url stable pour fichier journalier bonjour, mis ä',\n", " 'donnä bonjour, serait-il possible de rä',\n", " \"certains valeurs fonciä bonjour, j'ai un traitement qui prä\",\n", " 'demande info christophe guyon le sorineau commequiers pouvez-vous me communiquer par retour de mail läâḃäââỳäââḃä',\n", " 'mise ä bonjour, je recherche les donnä',\n", " 'problem adresse cadastre bjr nouvellement habitant ä',\n", " 'adresse postale et parcelle cadastrale bonjour, je cherche ä',\n", " 'disponibilitä bonjour, juste pour vous signaler une difficultä',\n", " 'suppression de parcelles bleu bonjour, en isä',\n", " 'prix bien inferieur au prix du marche bonjour, les prix affichä',\n", " 'taxe gemapi je recherche les derniä',\n", " 'mise ä bonsoir, sauf erreur le jeu de donnä',\n", " 'balance comptable de la rä bonjour, je ne trouve pas la balance comptable de la rä',\n", " 'balance comptable de la rä bonjour, je ne trouve pas la balance comptable de la rä',\n", " \"data only showing in code i can't see this data except in code, either live or once downloaded. any ideas\",\n", " 'existe-t-il ce genre de document de filitation pour les sections cadastrales je cherche un document de filiation des sections cadastrales cela existe-t-il',\n", " \"rectification concernant la vente de l'appartement sur paris parcelle ak - rue de quatrefages - du au prix de äâḃäâ\",\n", " 'email des administrations et pour la mise ä',\n", " 'cadre juridique bonjour, je souhaitais une prä',\n", " 'fichier fimoct bonjour, il semble que le fichier fimoct de proposä',\n", " 'dgfip remboursement je viens de recevoir un mail des impots gouv un remboursement par le dgfip pour un remboursement mais comme il faut donner mon numä',\n", " \"l'aide aux entreprises fragilisä j'ai faire dä\",\n", " 'coordonnä comment peut on avoir les coordonnä',\n", " \"erreur probable j'ai vu sur la commune de mon indivision, des prix de terre agricole ä\",\n", " 'contrat de service bonjour, pourriez vous me fournir le contrat de service (wsdl) correspondant au xml gä',\n", " 'exhaustivitä bonjour, dans le fichier csv il ne semble y avoir que communes. est-ce une erreur et comment avoir les autres beaucoup pour ce jeu de donnä',\n", " \"dvf bonjour, je m'interroge concernant la commune de sillingy () haute-savoie car plus aucunes donnä\",\n", " \"erreur faute de frappe, zero en trop il y a une erreur sur id mutation - (nice parcelle cadastrale lo). a mon avis, faute de frappe et zero en trop car il est impossible qu'un appartement de mäâäâġ dans cet immeuble (le mien) se soit vendu pour , million d'euros. impossible. de corriger. bonjour, cela a t il ä\",\n", " 'millä bonjour, pouvez-vous mäâḃäââỳäââḃindiquer quand la date de la prochaine livraison däâḃäââỳäââḃavance.',\n", " 'volet performance bonjour, serait-il possible de mettre en ligne le mä',\n", " 'manque un caractä bonjour, comment corriger un caractä',\n", " 'balances comptables des groupements ä dans le cadre de nos travaux de notation des epci, nous utilisons les fichiers des balances comptables que vous mettez ä',\n", " 'problä aprä',\n", " 'tä aprä',\n", " 'site dvf hs bonsoir, le site dvf ne semble plus fonctionner, ni sur edge, ni sur chrome, par contre il fonctionne sur mon mobile. auriez-vous une explication cordialement. en vidant le cache, ä',\n", " \"valeurs fonciä bonjour, je n'arrive pas ä\",\n", " 'millä bonjour, peut-on envisager que les millä',\n", " \"donnä bonjour, pourriez-vous publier le fichier contenant les comptes des communes pour l'annä\",\n", " 'uilisation de fantoir quel est le logiciel qui peut lire le fichier fantoir excel bonjour, le fichier fantoir tä',\n", " 'rei les donnä',\n", " \"visualisation agglomä bonjour, existe-t-il une page web qui permettrait de visualiser l'intä\",\n", " 'gä bonjour, je voudrais savoir en quelle gä',\n", " 'que signifie echange dans votre site est ce seulement un ä puis je savoir ce que regroupe le terme ä',\n", " 'diffä bonjour, jäâḃäââỳäââḃaurais besoin de vos lumiä',\n", " \"absences de donnä bonjour, il n'y a aucunes donnä\",\n", " 'reclamatio covid madame je peut ä',\n", " \"comptes individuels des communes je suis en charge de l'agence technique dä\",\n", " 'le dessin de fichier comptes-individuels des communes ne correspond pas entiä bonjour, le fichier comptes-individuels des communes ne correspond pas entiä',\n", " 'orthotypographie de fantoir bonjour, fantoir ä',\n", " 'problä bonsoir, cette donnä',\n", " \"inventaire immobilier des operateurs de l'etat l'inventaire mis ä\",\n", " \"donnä bonjour, un grand pour ce travail qui est d'une grande pour l'analyse comparative des finances des collectivitä\",\n", " \"donnä bonjour, en cherchant l'historique des ventes au sein d'une co-propriä\",\n", " \"demande d'informations madame paclot, actuellement en recherche d'appartement, j'aurais aimä\",\n", " \"cohä bonjour, je vous remercie tout d'abord pour ces jeux de donnä\",\n", " \"cadastre comment faire pour l'avoir mon livre foncier a ma terrain\",\n", " 'actualisation des donnä bonjour, quand seront disponibles les donnä',\n", " 'informations actualisä la date exacte des publications des donnä',\n", " \"nom des stations essence bonjour, une info qui me semble importante n'est pas prä\",\n", " \"comptes consolidä bonjour, j'ai besoin des comptes consolidä\",\n", " 'question extraction donnä bonjour, pour un ä',\n", " 'demander fichiers dvf antä bonjour, nous aurions souhaitä',\n", " 'comptes des eple bonjour, je ne retrouve pas les comptes des ä',\n", " \"recherche d'un propriä a l'attention de la cdif de saint-nazaire propriä\",\n", " \"id_mutation bonjour, l'id_mutation est il une donnä\",\n", " \"latitude longitude bonjour, les colonnes lat et long sont vides, säâḃäââỳäââḃagit-il däâḃäââỳäââḃune erreur ou elles ne sont plus disponibles dans le nouveau format je confirme, en effet il y avait des erreurs dans le traitement. nous venons de relancer l'opä\",\n", " 'version agrä bonjour, il serait intä',\n", " 'actualisation fin bonjour, envisagez vous de diffuser les derniä',\n", " 'demandes de valeurs fonciä bonjour, a quelle date prä',\n", " \"question bonjour, a quelle date votre fichier dvf enrichi d'octobre sera-t-il disponible en effet, le dernier jeu de donnä\",\n", " 'mise ä bonjour, la publication des donnä',\n", " \"archive invalide bonjour, j'ai souhaitä\",\n", " \"demande j'aimerai vous envoyer un message via la plateforme des impä\",\n", " \"demande de valeurs fonä bonjour, dans la rubrique dvf, sur l'image reprä\",\n", " \"erreur de visualisation de fichiers bonjour, les fichiers concernant le vapotatge sont corrompus. de bien vouloir m'avertir quand ce sera bon. cdlt laurent bonjour, les fichiers peuvent ä\",\n", " \"numä bonjour, j'ai essayä\",\n", " \"libellä bonjour, selon la dgcl, les nomenclatures m et m n'ä\",\n", " \"recherche vente bd de metz rennes prix acheteur j'ai appris la vente du bd de metz ä\",\n", " 'mä bonjour, ouvrir les zip qui sont dä',\n", " \"doublons bonjour, j'ai relevä\",\n", " 'cellfood est ce que cellfood vendu par cellfood france est autorisä',\n", " 'date prochaine actualisation bonjour, pouvez vous svp me dire ä',\n", " 'coordonnees geometres je dä',\n", " 'comptes des communautä bonjour, pouvez-vous me dire comment calculer les buget des regroupement de communes (cc, ca, cu) peut-on simplement pour chaque annä',\n", " 'comptes des communes - bonjour, je cherche ä',\n", " \"plan cadastral erronä bonjour, j'ai du mal ä\",\n", " 'bati bonjour, je constate un dä',\n", " \"cadastre bonjour, le syndicat d'irrigation drä\",\n", " \"donnä serait-il possible d'avoir accä\",\n", " \"besoin d'aide j'aimerai rä\",\n", " 'erreurs de donnä comment faire corriger des sources erronä',\n", " \"problä bonjour, j'ai tä\",\n", " \"sondage l'utilisation et la contribution ä bonjour, je souhaiterais vous contacter ä\",\n", " 'fichier invalide pour cette mise ä',\n", " 'polynä bonjour, je ne parviens pas ä',\n", " \"valeurs financiä bonjour, j'ai tä\",\n", " 'disponibilitä bonjour, serait-il possible de connaä',\n", " 'historique cadastrale jouy le potier bonjour, il nous est nä',\n", " \"demande d'informations bonjour, est-ce possible de tä\",\n", " \"site aides entreprises et api sont inaccessible bonjour, je vous signale que le site httpsaides-entreprises.fr et ses api sont inaccessibles. depuis quelques temps, le site est inaccessible mais l'api marchait encore avec l'adresse ip suivante http... aujourd'hui, elle ne marche plus. puis-je vous demander de vä\",\n", " \"aide aux entreprises fragilises le j'avais fait la dä\",\n", " \"donnä vous indiquez dans l'historique nouvelles donnä\",\n", " \"mise ä bonjour, il n'y a plus de mise ä\",\n", " \"erreur ä bonjour, cette voie rend hommage au consul nordling sans w, je n'ai pas trouvä\",\n", " 'comment sä bonjour. je souhaite savoir si il y a un moyen de sä',\n", " \"liste vide ( aussi) bonjour, il n'y a qu'une liste de chiffres dans le csv, aucune liste d'associations comme les prä\",\n", " \"actualisation des donnä pouvez vous nous indiquer la date d'actualisation des donnä\",\n", " \"demande de renseignement cadastre gouv.com bonjour, je ne sais pas ou m' adresser , je vous explique j ai fait diviser une parcelle par deux par un gä\",\n", " \"fichier invalide le fichier httpscadastre.data.gouv.frdataetalab-cadastre--shpdepartementscadastre--subdivisions_fiscales-shp.zip est incorrect j'ai regardä\",\n", " \"erreur nom de rue bonjour, comment faire modifier une erreur de saisie d'un nom de rue la rue robert schuman ä\",\n", " \"fichier bonjour, quand est ce que le fichier semestriel d'avril sera disponible bonjour, il manque les donnä\",\n", " 'information sur ma demande autoentrepreneur bonjours jäâḃäââỳäââḃai effectuer une demande en date du sur mon espace impä',\n", " 'offre de pret entre particuliere en ligne sans frais le prä',\n", " \"risque de disparition des donnä bonjour, afin de nous organiser au mieux, je me permets de vous contacter pour savoir s'il y aurait un risque que ces donnä\",\n", " 'code ministä bonjour, oä',\n", " 'suppression donnee mon tä',\n", " 'synchronisation impots.gouv.fr et api data.gouv.fr bonjour, je souhaiterais savoir combien de temps il y a entre la publication des donnä',\n", " \"code fantoir sur nouveau lotissement et nouvelle voies privatives bonjour, un lotissement est sur le point d'ä\",\n", " \"le souhait d'obtenir les dvf (demande de valeurs fonciä le bonjour, je rencontre des difficultä\",\n", " \"coordonnä bonjour, je me permet de vous contacter afin d'obtenir l'historique de vente du bien situä\",\n", " \"rei bonjour, pouvez-vous me dire quand sera disponible le rei merci. meme question je suis a la recherche du rei ou . j'ai l'impression que le site data.gouv ne reä\",\n", " \"fonciä bonjour, il n'y a pas de donnä\",\n", " 'manuel z bonjour, je cherche une liste publique et mise a jour des agences de voyages franä',\n", " 'carte geolocalise dvf bonjour, je me suis identifiä',\n", " \"demande d'information cadastrales bonjour, je souhaite connaä\",\n", " \"vente d'une maison sur montauriol madame paclot, je me permets de revenir vers vous, j'essaye de prouver officiellement que le domicile conjugal a ä\",\n", " 'coquille dans schä bonjour, il y a une petite coquille sur le schä',\n", " 'trafic de stupä bonjour, je suis ä',\n", " \"automatisation de l'accä bonjour, les donnä\",\n", " \"consultation donnä bonjour, le juin, j'ai saisi marchä\",\n", " \"erreur ä concernant cette voie xcrsde la ferme st lazarerlazare il s'agit d'une cour (cour) et non d'un cours (crs) voir arrä\",\n", " \"date de mise ä bonjour, tout d'abord, grand aux ä\",\n", " \"prä mme, je vous remercie tout d'abord sur ce site qui est trä\",\n", " 'les donnä bonjour, plus de lignes en , ä',\n", " \"demande d'effacement de fiche personnelle monsieur, je ne vous le demanderai qu'une fois, je vous prie de m'effacer de votre fichier, je ne vous ai pas donnä\",\n", " 'rei bonjour, je recherche les donnä',\n", " 'erreur ä concernant cette voie gruejacquartr qjacquart son libellä',\n", " \"base de donnä bonjour, est-il possible d'accä\",\n", " 'mise ä bonjour, bientä',\n", " 'cibler sur un dä bonjour, pour la mise ä',\n", " 'dvf je fais de la publicitä',\n", " 'salut salut',\n", " \"actualisation du fichier bonjour, nous observons que le fichier n'est pas actualisä\",\n", " 'impossibilitä bonjour, pas de rä',\n", " 'type de bien hello, i would like to ask whether you have a more granular breakdown relative to the category local industriel. commercial ou assimilä',\n", " 'mise ä bonjour, certainement du au confinement, la mise ä',\n", " 'fichier compactä avez vous produit un fichier des prix moyens ä',\n", " \"telechargement bonjour, j'essaie de tä\",\n", " 'mise ä bonjour, nous vous informons quäâḃäââỳäââḃune mise ä',\n", " 'possibilitä madame, monsieur, dans le cadre de mon mä',\n", " \"demande d'information bonjour, je m'appelle sandrine gharbi, je viens d'arriver dans la rä\",\n", " 'nombre de lot egal a zero bonjour, un grand pour le travail fourni pour maintenir cette base de donnä',\n", " 'soucis dans le zip bonjour, depuis hier le zip des instantanä',\n", " 'mise ä bonjour, je souhaiterai savoir si la mise ä',\n", " 'utilisation du fichier fantoir pour un notaire et excusez-moi de vous dä',\n", " \"millesime - retour des erreurs renconträ bonjour, j'ai importä\",\n", " 'fonds de solidaritä bonjour, je suis auto entrepreneur depuis dä',\n", " \"donnä je suis un peu surprise qu'en , les derniä\",\n", " \"questions natures_culture et doublons de ligne bonjour, j'ai parcouru assez longuement cette base de donnä\",\n", " 'erreur nom de rue bonjour, la ligne ci-dessous prä',\n", " 'zones gä bonjour, nos services rectoraux souhaiteraient obtenir les lieu-dit, type de voie, libellä',\n", " 'dä bonjour, le code des dä',\n", " \"donnä bonjour, j'effectue une analyse de donnä\",\n", " 'droits de succession bonjour, je suis professeur de droit fiscal et je suis ä',\n", " \"quelques erreurs dans les fichiers bonjour, pour la publication des fichiers projet de loi de finances initiale pour (lfi ) . j'ai deux remarques ) dans le fichier projet de loi de finances initiale pour (lfi ), il y a deux colonnes ae lfi . je suppose que l'une des deux contient en rä\",\n", " \"dep bonjour, et pour cette lecture des balances en , la liste des communes de la sein-maritime () s'arrä\",\n", " 'erreur sur rue du docteur rafin ä bonjour, la rue du docteur rafin est ä',\n", " \"demande d'informations complä bonjour, le code source relatif ä\",\n", " 'rei pourriez vous me prä',\n", " 'nouvelle version bonjour, pour cette nouvelle version bien plus facile ä',\n", " 'identifiant mutation bonjour, pourriez vous me renseigner sur la faä',\n", " 'comment obtenir une dvf antä comment obtenir une dvf antä',\n", " 'erreur de chargement des donnä bonjour, je note que pour le fichier projet de loi de finances pour (plf ), donnä',\n", " \"diffä bonsoir, depuis , parmi les indicateurs d'endettement est apparu dans la base une nouvelle mesure intitulä\",\n", " 'moissonnage des de bonjour, les decp moissonnä',\n", " 'dvf - appartement bonjour, je souhaitais vä',\n", " \"rä a qui s'adresser pour dä\",\n", " \"millä bonjour, pouvez-vous m'indiquer la date de publication du prochain millä\",\n", " 'demande par rapport au fichier de valeur fonciere de bonjour, je souhaiterais savoir si il existe un fichier permettant de connaitre les proprietaires des differents etablissement proposä',\n", " 'budget dä pourrais-je avoir un fichier excel avec les intitulä',\n", " 'marchä bonjour, pouvez-vous nous indiquer quand les donnä',\n", " \"lien vers comptes individuels par commune bonjour, je n'arrive pas a charger les comptes individuels par commune. il semble que le lien ne fonctionne plus.\",\n", " 'disponibilitä bonjour, serait-il possible de disposer sur les donnä',\n", " \"j'ai tä mais il est impossible de d'ouvrir le fichier pdf. pouvez-vous m'indiquer avec quel logiciel je peux ouvrir ce fichier. je suis prä\",\n", " 'construction table shp tab rä bonjour, je souhaiterais construire la table dä',\n", " \"lien casse bonjour, le lien vers les comptes individuels des communes ne fonctionne plus. on peut choisir le departement et ensuite on obtient un message d'erreur. pouvez vous reparer le lien svp. depuis plus d'une semaine, il m'est impossible de revenir sur la base de donnä\",\n", " 'problä bonjour. ce sont de trä',\n", " 'recherche de propriä bonjour, je cherche les coordonnä',\n", " 'edmond rostand ecrivant un livre sur edmond rostand, je cherche ä',\n", " \"demande d'informations sur l'impä dans le cadre de läâḃäââỳäââḃä\",\n", " 'ifi et isf bonjour, est-il possible de recevoir le nombre de contribuables total concernä',\n", " 'mise ä christian, un jeu de donnä',\n", " 'fichier du budget total allouä bonjour, existe-t-il un fichier dä',\n", " \"fichier du budget global allouä bonjour, j'ai consultä\",\n", " 'donnä christian, en ä',\n", " 'diffä en explorant le jeu de donnä',\n", " 'mise ä bonjour, la derniä',\n", " \"sä bonjour, j'essaie d'implä\",\n", " 'demande däâḃäââỳäââḃinformation bonjour, serait-il possible de me donner la date du prochain millä',\n", " 'millä bonjour, je souhaiterai avoir confirmation du millä',\n", " 'dvf et bonne annä',\n", " \"accä oubliez mon message, j'ai trouvä\",\n", " 'accä bonjour, je pensais trouver les donnä',\n", " 'divorce dans le cadre de läâḃäââỳäââḃexamen du projet de loi de finances pour , le gouvernement propose däâḃäââỳäââḃabaisser le taux de , ä',\n", " \"dä bonjour, il semble qu'il manque les donnä\",\n", " \"grand lyon - liste des stations bonjour, je travaille au grand lyon, vous est il possible de m'envoyer un fichier excel avec la localisation des stations et les marques david et pour votre commentaire. en revanche, je ne suis pas sä\",\n", " \"taxe sur la valeur ajoutä bonjour, j'aurais voulu savoir si vous disposiez des donnä\",\n", " 'convertir donnä bonjour, pourriez-vous indiquer comment convertir des donnä',\n", " \"donnä christian, pour l'excellent travail rä\",\n", " 'cadastre ou es ce que je peux demander une matrice cadastal bonjour, cette demande doit ä',\n", " 'bati bdotpo ign vs bati etalab bonjour, laquelle de ces bases de donnä',\n", " 'valeur d une maison bonjour. j ai besoin de savoir le prix du marchä',\n", " 'mä bonjour, les libellä',\n", " 'code fantoir je souhaite choisir un opä',\n", " \"valeurs fonciä bonjour, je m'aperä\",\n", " \"accä j'aurais besoin des dvf - sur mon dä\",\n", " \"tä bonjour, je n'arrive pas ä\",\n", " 'somme de encours_bancaire_net_solde_fonds_toxiques bonjour, ce champ apparait en pour ma commune, pourriez-vous me donner sa dä',\n", " 'types de batiments bonjour, une idä',\n", " \"impossibilitä bonjour, tout d'abord beaucoup pour le travail de toute votre ä\",\n", " 'utiliser la plateforme - donnä bonjour, je viens de dä',\n", " 'cadastre corneabarrieu bonjour, comment est il possible de connaitre la date de crä',\n", " 'pointer sur couche bonjour, pour le travail rä',\n", " \"historique des transactions d'une propriä bonjour, je voudrais dä\",\n", " 'champ dä bonjour, je viens de tä',\n", " \"absence des donnä bonjour, tout d'abord ä\",\n", " 'livraison oct bonjour, la disponibilitä',\n", " 'fichier json comment lire un fichier en .json et .ods bonjour, un fichier json est un fichier texte structurä',\n", " 'balances comptables des ä bonjour, le site data.gouv.fr fournit les donnä',\n", " \"disparition de donnä jäâḃäââỳäââḃai pu consulter des transactions en elles ne sont plus apparentes aujourdäâḃäââỳäââḃhui est-ce normal bonjour. non ce n'est pas normal. est ce que cela concerne toutes les transactions ou des transactions spä\",\n", " \"question vefa proposition d'amä bonjour, tout d'abord fä\",\n", " 'mise ä bonjour, savez vous quand les donnä',\n", " 'mise ä bonjour. pour cette super application cependant je ne trouve pas les derniä',\n", " \"actualisation des donnä bonjour, pourriez-vous svp nous indiquer la date d'actualisation de ces fichiers pour sachant que les donnä\",\n", " \"actualisation des donnä bonjour, pourriez-vous svp nous indiquer la date d'actualisation de ces fichiers pour sachant que les donnä\",\n", " 'comptes individuels des communes bonjour, sur le site httpswww.impots.gouv.frcllzfaccueilflux.ex_flowidaccueilcclloc-flow, il est ä',\n", " 'dä bonjour, je voulais savoir si certains dä',\n", " 'mise ä bonjour, serait il possible de mettre ä',\n", " 'taxe focier exoneration bjr je voudrais un renseignement sur l exoneration de la tf pour une personne de ans ..cette personne est mon beau pä',\n", " 'titre de propriä je souhaiterais savoir oä',\n", " 'code commune bonjour, oä',\n", " 'fimoca et fimoct bonjour, pourquoi la mise ä',\n", " 'dvf - type de local commercial... bonjour, suite ä',\n", " 'information surface bonjour. pour ces infos, trä',\n", " 'signalement de donnä bonjour, dans les donnä',\n", " 'millä bonjour, connaissez-vous la date de mise ä',\n", " 'taxe fonciä bonjour, pourriez-vous me communiquer la version du fichier dä',\n", " \"fantoir, comment l'ouvrir bonjour, tout est dans le titre. comment ouvre-t-on fantoir une fois le zip tä\",\n", " \"prochaine livraison bonjour, vous m'avez indiquä\",\n", " \"taxe fonciere bonjour, j'ai ans et j'ai reä\",\n", " 'dvf donnä bonjour, a quelle date pourrons-nous consulter les transactions rä',\n", " \"actualisation des donnä bonjour, pouvez vous nous indiquer la date d'actualisation de la base de donnä\",\n", " 'structure de donnä bonjour, dans ce lot de donnä',\n", " 'quand aurais-je mon avis de taxes fonciä quand saurais-je le montant de mes taxes fonciä',\n", " \"fichier dvf -absence d'information sur nice - parcelle kt, rue maccarani, bonjour, jäâḃäââỳäââḃai consultä\",\n", " \"donnä bonjour, tout d'abord, de votre travail, indiscutablement intä\",\n", " \"demande d'info sur dvf bonjour, en vue de rä\",\n", " 'quelques adaptations dans le schä par rapport au schä',\n", " \"demande d'explication sur le rä - je trouve votre application trä\",\n", " \"fusion de communes bonjour, dans le cas d'une fusion de communes, la filiation des parcelles figure-t-elle dans le fichier dfi en cas de fusion de parcelles qui auraient des prä\",\n", " 'dä , j ai dä',\n", " 'publication du code calcul de taxe fonciä bonjour, dans le cadre de la publication du code calcul de taxe fonciä',\n", " 'communes manquantes dans les fichiers communes du dä',\n", " 'conformitä les fichiers decp en format xml qui sont proposä',\n", " \"impossibilitä bonjour, j'ai crä\",\n", " \"import sous postgis j'essaye d'importer les fichier shapefile dä\",\n", " 'question sur le type de voie bonjour, pour la ville du touquet-paris-plage, pas-de-calais, il y a une diffä',\n", " \"donnä monsieur , pourrions-nous rentrer en contact dans le cadre de l'intä\",\n", " \"cquest bonjour, je n'arrive plus depuis cette semaine ä\",\n", " 'dominique miguel puis-je connaitre le prix moyen du terrain a batir a igny comblizy.viabillisä',\n", " \"mise ä bonjour, tout est dans le titre, j'avais compris une mise ä\",\n", " \"dvf, format document bonjour, serait-il possible d'avoir le document dvf sous format excel svp bonjour, il n'est pas prä\",\n", " 'historique des communes dans le cadre de mon travail jäâḃäââỳäââḃai besoin de läâḃäââỳäââḃhistorique des communes. or il semble quäâḃäââỳäââḃil y a peut-ä',\n", " 'problä bonjour, aprä',\n", " 'dä bonjour, nous utilisons les services de dematis via un partenariat avec le journal de montreuil. nous souhaitons dä',\n", " \"manque de donnees bonjour, j'ai vendu, le , une maison sur la commune de migennes dans l'yonne (rue du professeur ramon, ) mais cette vente n'est pas recensä\",\n", " 'cadastre bonjour, je vous contacte suite ä',\n", " 'prix annoncä bonjour, a quoi correspondent les prix annoncä',\n", " 'rei madame, monsieur, comment trouver la dä',\n", " 'csv incomplet deleted',\n", " \"etude du marche bonjour, nous sommes une agence immobiliere mondialement connue et nous effectuons une etude du marche parisien. nous avons du mal a nous retrouver avec les donnees. est ce que quelqu'un pourait m'aider avec le suivant äâḃäââỳäâḃ comment trouver la propriä\",\n", " 'mise ä bonjour, nous observons la diffusion du tracä',\n", " 'mise ä bonjour, nous observons la diffusion du tracä',\n", " 'mise ä bonjour, nous observons la diffusion du tracä',\n", " 'mise ä bonjour, quand seront disponibles les donnä',\n", " 'mise ä bonjour, quand seront disponibles les donnä',\n", " 'information aux utilisateurs information aux utilisateurs la direction adopte un nouveau mode de diffusion de ses donnä',\n", " 'information aux utilisateurs information aux utilisateurs la direction adopte un nouveau mode de diffusion de ses donnä',\n", " 'surface loi carrez bonjour, si je comprends bien, la surface rä',\n", " 'information aux utilisateurs la direction du budget adopte un nouveau mode de diffusion de ses donnä',\n", " 'information aux utilisateurs la direction adopte un nouveau mode de diffusion de ses donnä',\n", " 'a regrouper avec les autres millä bonjour, ne serait-l pas pertinent de publier ce jeu de donnä',\n", " 'code siren bonjour, a dä',\n", " 'code siren manquant bonjour, je tenais dä',\n", " 'dvf et patrim en open data bonjour, selon le cerema httpsdatafoncier.cerema.frdonneesdonnee-dvf, dvf a ä',\n", " 'signification date de validation du dfi bonjour, je ne suis pas sä',\n", " \"suggestion d'un nouveau mot-clä bonjour, je propose ce nouveau mot-clä\",\n", " 'csv inexploitable deleted deleted bonjour, nous vous remercions de läâḃäââỳäââḃintä',\n", " 'csv deleted',\n", " \"vie privä bonjour, je m'ä\",\n", " 'mise ä bonjour, le groupe national dvf vient de mettre ä',\n", " 'incident en cours suite ä',\n", " \"suggestion d'un nouveau mot-clä bonjour, je propose ce nouveau mot-clä\",\n", " 'tä bonjour, les fichiers au format shapefile par commune des derniers millä',\n", " \"numä bonjour, pensez-vous qu'il soit envisageable d'exporter le numä\",\n", " 'informations manquantes bonjour, sur le tä',\n", " \"detection habitation et local professionnel bonjour, ne trouvant pas d'informations sur les attributs section et contenance des parcelles et type pour les batiments, je voudrais savoir comment filtrer les parcelles dont la destination est habitation ou local professionnel. d'avance deleted\",\n", " 'dä bonjour, pour ce partage de base de donnä',\n", " 'suppression informations dvf bonjour, je souhaite faire supprimer les informations dvf pour mon bien immobilier. a qui dois-je faire la demande bien cordialement, vincent g. je vous laisse lire la faq du site app.dvf httpsapp.dvf.etalab.gouv.frfaq.html, vous y trouverez toutes les informations nä',\n", " \"feuille de route de l'open data - ville de bron de ce premier jeu de donnä\",\n", " 'donnä bonjour, bien que les donnä',\n", " 'valeur taxe fonciä je chercher ä',\n", " 'local tertiaire bonjour, les catä',\n", " \"demande de valeur fonciä bonjour, j'aimerais savoir comment obtenir une dvf de cordialement. la valeur fonciä\",\n", " 'informations sur les titres bonjour, ä',\n", " \"variables fichier rei bonjour, pourriez vous s'il vous plait rajouter la feuille avec les variables .\",\n", " 'calculer la surface du terrain au niveau mutation bonjour, peut-on calculer la surface du terrain avec les donnä',\n", " 'question sur la nature de mutation bonjour, en regroupant les donnä',\n", " 'commune de saint-pierre-en-auge manquante dans la ca lisieux normandie, les communes devenues dä bonjour, dans la communautä',\n", " 'communes dans le non rä bonjour, je ne trouve pas les communes ayant un code postal au-delä',\n", " \"point de contact pour signalement erreur bonjour, pourriez-vous m'indiquer comment obtenir un contact pour remonter une erreur sur une voie (erreur sur une nature de voie) merci. cordialement. bonjour, pour toute modification des libellä\",\n", " 'complä est ce que les donnä',\n", " \"donnä aujourd'hui, la base actuelle ne contient que ventes sur des f ä\",\n", " 'problä bonjour, dans les transactions fonciä',\n", " 'problä bonjour, je viens de tä',\n", " 'sä ce type de donnä',\n", " 'ä bonjour, les informations relatives au diagnostic de performance ä',\n", " 'donnä bonjour, pouquoi ne partagez vous pas les donnä',\n", " \"chiffres transmis ne correspondent pas aux prix d'achat bonjour, dans l'application de visualisation de vos donnä\",\n", " 'questions base de donnä bonjour, aprä',\n", " 'donnä bonjour, nous avons recherchä',\n", " \"tä bonjour, je n'arrive pas ä\",\n", " 'format du fichier dvf bonjour, pouvez vous transmettre les donnä',\n", " 'occupation du bien bonjour, pour ces prä',\n", " \"suggestion d'un nouveau mot-clä bonjour, je propose ce nouveau mot-clä\",\n", " \"diffä mon but est d'avoir tous les ä\",\n", " 'changement le nom de rue jäâḃäââỳäââḃaimerais bien savoir ä',\n", " \"disponibilitä bonjour, il semblerait que les taux de l'annä\",\n", " 'dä bonjour, nous venons de constater un dä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä bonjour, vous recevez ce message car vous avez ajoutä',\n", " 'dä message',\n", " 'fichier csv trop gros je recherche le numä',\n", " \"revenus par commune avant (revenus de ) bonjour, est-il possible d'accä\",\n", " 'donnä dans le fichier des donnä',\n", " \"code nomenclatures fonctionnelles par nomenclature bonjour, afin d'exploiter aisä\",\n", " \"harmonisation des termes utilisä bonjour, et tout d'abord, pour la mise ä\",\n", " \"codes siren bonjour, pour le partage de ces fichiers. cependant j'ai remarquä\",\n", " \"element des agrä bonjour, est-il possible d'avoir le fichier des agrä\",\n", " 'table nc multilingue bonjour, existe-t-il une version multilingue ä',\n", " 'pci - statistiques bonjour, existe t-il des statistiques, millä',\n", " \"suggestion d'un nouveau mot-clä bonjour, je propose ce nouveau mot-clä\",\n", " \"cadastres introuvables bonjour, j'ai un problä\",\n", " 'fimoca et fimoct bonjour, vous avez mis ä',\n", " \"balance comptables des communes message d'erreur fichier endommagä bonjour, je me lance dans les importations et je viens de travailler sur les balances des communes de . les millions de lignes ne peuvent pas ä\",\n", " 'recodification ou codification divergente possible bonjour, le fantoir est connu pour ä',\n", " \"code fantoir sous excel bonjour, comment faire pour avoir la liste des fantoirs sous excel, car en format txt ce n'est pas lisible. j'en ai trouvä\",\n", " 'bä bonjour, dä',\n", " 'base minimale de cfe une information importante pour nous est absente de ce fichier. il säâḃäââỳäââḃagit du barä',\n", " 'fichiers manquants bonjour, nous avons remarquä',\n", " \"information complä bonjour, j'ai rä\",\n", " 'millä bonjour, quand est-ce que le millä',\n", " \"le et... plus rien bonjour, j'ai deux questions ) pourquoi n'y a t-il plus de donnä\",\n", " \"impossible d'ouvrir les fichiers .txt.zip impossible d'ouvrir les fichiers dä\",\n", " \"ä bonjour, j'aimerai faire un graphique qui montre l'ä\",\n", " 'comment lire ce fichier... bonjour, question de dä',\n", " 'donnä bonjour, je ne trouve pas les donnä',\n", " \"parcellaire et adresses postales ou cadastrales bonjour, existe-t'il une base de donnä\",\n", " \"differences avec visudgfip nous utilisions visudgfip pour retrouver les parcelles primitives. a partir d'un näâäâḟ de parcelle, visudgfip nous donnait ä\",\n", " \"erreurs topologiques cadatres batiment du - dä bonjour, l'import sur une base postgis de la couche citä\",\n", " 'numä bonjour, les numä',\n", " 'normalisation des noms des communes bonjour, quelles sont les rä',\n", " 'millesime deleted les donnä',\n", " \"donnä bonjour, bravo pour ce travail serait-il possible d'avoir accä\",\n", " 'fichiers au format json-ld bonjour, les fichiers au format json-ld ne semblent pas ä',\n", " 'heure de mise a jour quotidienne bonjour, a quelle heure sont mis a jour les fichiers fermeture du post a ä',\n", " 'mise a jour des fichiers bonjour, est-ce que ce projet a ä',\n", " \"impots taxe d'habitation bonjour, j'ai ä\",\n", " 'renseignement dä bonjour, je vous remercie de bien vouloir me prä',\n", " \"accä bonjour, pourquoi n'avons nous pas accä\",\n", " \"mise ä bonjour, j'utilise vos donnä\",\n", " \"utilisation de la base bonjour, je n'arrive pas ä\",\n", " \"faute de typographie dans le nom d'une ressource plf comptes d'aff**r**ectation spä\",\n", " 'absence de parcelles filles bonjour, dans le cadre de läâḃäââỳäââḃanalyse des acquisitions de läâḃäââỳäââḃagence de läâḃäââỳäââḃeau seine normandie je me suis procurer les documents de filiation du service des cadastre, je näâḃäââỳäââḃai eu jusquäâḃäââỳäââḃä',\n", " 'sections cadastrales manquantes bonjour, certaines communes ont des sections cadastrales vides de donnä',\n", " 'un grand christian, beaucoup pour cette compilation de donnä',\n", " \"batiment näâäâḟ de parcelle bonjour, serait-il possible d'ajouter le näâäâḟ de parcelle sur laquelle se trouve un bä\",\n", " 'incohä bonjour, je suis partagä',\n", " \"fichier simplifie des evenements n'a que champs bonjour, je pensais que d'apres la description il aurait tous les champs specifies dans la description du fichier il n'y a que id et comment. merci.\",\n", " 'poudre de lait infantile bonjour, je souhaiterai obtenir les donnä',\n", " 'renseignement dä bonjour, le profil pour antin rä',\n", " \"dä bonjour, j'ai tä\",\n", " 'assemblage feuilles dxf-pci zones problä',\n", " 'cadeau pour naissance particulier, je dä',\n", " \"manque ain bonjour, tout d'abord, pour la mise ä\",\n", " \"type de bä bonjour, est ce qu'il existe une information parmi les donnä\",\n", " \"commune manquante bussurel bonjour, je pense qu'il en est de mä\",\n", " \"gip laboratoires et tout d'abord pour ces open data, trä\",\n", " 'mä bonjour, je suis ä',\n", " 'noms des stations est-il possible de lier ce jeu de donnä',\n", " 'comment faire bonjour, sorbonne universitä',\n", " \"commune inexistante si j'ai compris correctement la fiche de lecture bonjour, j'aimerais savoir pourquoi la commune d'herblay - ne figure pas je cherchais un remembrement effectuä\",\n", " \"indication des correspondances pour les code communes bonjour, en recherchant la filiation cadastrale d'une parcelle dans un fichier dä\",\n", " \"cotisation fonciä bonjour, nous aimerions recalculer le montant de la cfe pour les auto-entrepreneurs selon leur localisation. le calcul s'effectue en multipliant un taux de cotisation (prä\",\n", " 'marchä bonjour, pouvez-vous nous indiquer quand les donnä',\n", " 'valeur cadastre de mon apartment , je voudrais savoir le valeur cadastre de mon apartment in , boulevard carabacel - nice premiereetage (belle etage) apartment a droit bonjour, cette information ne peut ä',\n", " \"balance - exhaustivitä bonjour, tout d'abord pour votre travail et ces fichiers d'une grande qualitä\",\n", " \"liste des complä bonjour, dans le cadre d'un projet de start-up, j'aurais besoin de la liste des complä\",\n", " \"ce n'est pas le format officiel bonjour, beaucoup d'avoir publiä\",\n", " \"mise ä bonjour, tout d'abord un grand pour ce travail de compilation qui rend (enfin) utilisable ces donnä\",\n", " 'comment exploiter le fichier bonjour, je trouve votre initiative gä',\n", " 'script python et coquilles de description bonjour, je suis tombä',\n", " \"version de postgresql bonjour, pensez-vous qu'il soit possible de mettre ä\",\n", " 'rei ou trouver la description des variables',\n", " 'fantoir code inconnu bonjour, des codes sont utilisä',\n", " \"publication donnä deleted madame, de contacter l'administrateur du site pour toute information de ce type. mon expä\",\n", " 'couches absentes bonjour, la livraison des donnä',\n", " 'libellä bonjour, le libellä',\n", " \"batiment manquant bonjour, j'ai constatä\",\n", " \"anomalie sur une voie de villeneuve st georges ( ) bonjour, administrateur chez orange, pour les permissions de voiries ,je constate qu' il apparait que la voie av pierre mendes france est privä\",\n", " 'pci vecteur et pci image bonjour, peut-on se procurer ces logiciels en tant que particulier cdlt, franä',\n", " 'erreurs de coordonnä bonjour, dans le millä',\n", " \"taux d'imposition impot locaux bonjour, j'aimerai savoir si les taux pour les impä\",\n", " \"variables manquantes dans le rei ,il n'y a pas de variable correspondant au taux de majoration (votä\",\n", " 'donnä dans la base de donnä',\n", " 'comptes de commerce et compte de concours financiers dans la description du dataset, on parle de comptes de commerce mais dans les intitulä',\n", " 'oä en voulant crä',\n", " \"pci vecteur pci vecteur peut-on s'acheter ce logiciel en l'occurrence, pour prä\",\n", " 'pci vecteur bonjour, est-il ossible de se procurer cette aplication cdlt, fld',\n", " 'des doublons () bonjour, je fais suite ä',\n", " \"information balances comptables bonjour, je travaille dans un bureau d'ä\",\n", " 'ajout adresse + label deleted en fait les couches brutes existent et sont publiä',\n", " 'complet le fichier est-il vraiment complet aprä',\n", " \"montmagny bonjour, sur le fichier fantoir, il manque une rue de notre commune (ville de montmagny - val d'oise). il s'agit de la rue de sprimont, situä\",\n", " \"qualitä bonjour, et pour ce travail de mise en ligne des balances comptables j'ai nä\",\n", " \"problä bonjour, lorsque j'execute votre programme en python j'ai bien un csv en sortie mais il y a ä\",\n", " 'comptabilitä pouvez-vous dire quand seront publiä',\n", " 'diffä bonjour, afin de fiabiliser le traitement de la base de donnä',\n", " 'doublons dans fantoir bonjour, nous sommes tombä',\n", " \"pas d'en tä christian, il manque l'en-tä\",\n", " 'gä les coordonnä',\n", " 'mise ä le fichier actuel est dä',\n", " \"classer les donnä a l'ouverture du fichier j'ai dä\",\n", " 'donnä bonjour, beaucoup pour ces donnä',\n", " 'date de la derniä le lien de la ressource dit que la date de modification date du fä',\n", " \"plusieurs codes rivoli pour un mä bonjour, j'ai remarquä\",\n", " 'crä bonjour, je travaille ä',\n", " 'qualitä bonjour, je comprends que ce fichier est le rä',\n", " \"suggestion d'un nouveau mot-clä bonjour, je propose ce nouveau mot-clä\",\n", " 'nom de rue non rä la rue des vergers ä',\n", " 'montant tascom communes et gfp bonjour. en comparant le montant des produits au niveau national de la tascom sur le guide statistique de la fiscalitä',\n", " 'url de tä bonjour, il est explicitä',\n", " 'informations destination par fonction bonjour, est-il possible de savoir si vous avez ä',\n", " 'date de disponibilitä a quelle date la prochaine mise ä',\n", " 'trou dans le cadatsre travaillant ä',\n", " \"revenus par communes en de m'indiquer comment me procurer les revenus par communes en marie-odile dechezlepretrej\",\n", " 'mises ä bonjour, plus de mises ä',\n", " \"fichier global des comptes individuels des collectivitä bonjour, j'appuie les deux commentaires prä\",\n", " 'problä bonjour, aprä',\n", " 'champ licence faudrait prä',\n", " 'lieu dit manquant bonjour, le lieu dit correspondant ä',\n", " \"donnä bonjour, est-il possible d'obtenir ces donnä\",\n", " 'document csv - impossible de le lire bonjour, les donnä',\n", " \"nomenclature par fonction bonjour, tout d'abord un grand pour la publication de ces donnä\",\n", " \"identification de la parcelle bonjour, avec cette structure, sauf erreur de ma part, on perd l'identifiant de la parcelle auxquelles font rä\",\n", " 'erreur du dump bonjour, suis-je le seul ä',\n", " 'a quand un fichier global des comptes individuels des collectivitä bonjour, les donnä',\n", " \"prochaine mise ä bonjour, pouvez-vous m'indiquer quand aura lieu la prochaine mise ä\",\n", " 'gä bonjour, sur le site httpdgcisth.armadillo.frappphotopro.skhandicapsessionhistory-ready nous pouvons avoir la gä',\n", " 'dates de filiations bonjour, dans le fichier de filiations sur le dä',\n", " 'comptes individuels des collectivitä peut-on trouver une extraction complä',\n", " 'numä bonjour, est-il prä',\n", " \"problä j'ai tä\",\n", " \"doublons dans le fichier bonjour, j'ai remarquä\",\n", " \"nc des marchandises exclues des statistiques d'exportation bonjour, serait-il possible de connaä\",\n", " \"donnä bonjour, j'arrive ä\",\n", " 'dä bonjour, nous avons observä',\n", " 'balances comptables des dä bonjour, est-il possible de disposer de la prä',\n", " 'dä bonjour, le dä',\n", " \"format du fichier ascii au risque d'ä\",\n", " \"url de tä serait-il possible de disposer d'une url de tä\",\n", " \"diffä bonjour, je n'arrive pas ä\",\n", " 'nomenclature code douanier bonjour, je vous contacte, car nous rencontrons un problä',\n", " 'tä je souhaiterais pouvoir tä',\n", " 'lecture rei problä',\n", " \"aide tä bonjour, je viens d'essayer la dä\",\n", " 'systä existe t il une date pour la mise ä',\n", " 'projections des dom tom je voulais savoir avant de les importer si les dom tom avaient aussi la projection lambert ces fichiers geojson sont en wgs et non projetä',\n", " 'disponibilitä bonjour, des donnä',\n", " \"mä deleted type est une reprise d'un champ prä\",\n", " \"rue manquante bonjour, pour des raisons professionnelles j'ai besoin du code rivoli d'une nouvelle rue. celle-ci n'est pas ä\",\n", " 'systä bonjour, je viens de tä',\n", " 'not found bonjour, je souhaitais rä',\n", " \"suppression de mes coordonnä bonjour, j'ai demandä\",\n", " 'commune de marseille manquante.. le pci vecteur de la commune de marseille () est manquant dans la base de donnä',\n", " 'webservice pour le tä bonjour, existe il des webservices en place pour rä',\n", " \"calendrier d'avancement bonjour, existe-il un calendrier d'avancement pour la vectorisation des zones encore en format image si oui est-il possible d'en connaitre les dates clä\",\n", " 'emprunts des communes dans les ä',\n", " 'tä bonjour, sauriez-vous comment gä',\n", " \"changer properties id en cadastre_id bonjour, j'ai pas mal galä\",\n", " 'exploitation donnä bonjour, pour information aprä',\n", " \"rei l'url httpswww.impots.gouv.frportailwwwfichiersstatistiquesbase_de_donneesreirei_.zip renvoie bien un zip mais n'est pas listä\",\n", " 'incohä attention läâḃäââỳäââḃordre des colonnes dans le fichier ne correspond pas ä',\n", " 'demande dxf bonjour, je souhaiterai avoir le format dxf de la rue saint jaume sur la commune de digne les bains () section ae. merci. cordialement. les dxf seront diffusä',\n", " 'mä bonjour, trä',\n", " 'dasol ahn hello i would like to know something about pci. do you have an example in the sketch map if so, who will create it and who will manage it does the owner manage the country pci does the surveyor manage it what is the offical cadastral map that is managed by the country deleted',\n", " \"lien rpg pci bonjour, j'aimerais savoir si il existe un lien, ou les moyen d'en crä\",\n", " 'disponibilitä bonjour, avez vous une date de programmer pour la mise en place du tä',\n", " 'disponibilitä le cadastre est disponible via visudgfip ä',\n", " 'publication des localisants sur zones cadastre non vectoriel deleted bonjour, le pci image sera bientä',\n", " 'lieu dit manquant bonjour, le lieu dit correspondant ä',\n", " \"liens numä j'ai chargä\",\n", " \"liens numä j'ai chargä\",\n", " \"nature de la voie incluse dans la voie tout d'abord, d'avoir mis fantoir en ligne mes questions je remarque que certaines voies ont une nature de voie (par exemple rue) qui est incluse dans le libellä\",\n", " 'hauteur de bä bonjour, ces donnä',\n", " 'pä bonjour, selon quelle pä',\n", " 'format json et qgis bonjour, les donnä',\n", " 'problä bonjour, la page indique comme producteur la rä',\n", " 'disponibilitä deleted mä',\n", " 'tä bonjour, comment tä',\n", " 'abscence code activitä les fichiers ne contiennent pas le code activitä',\n", " \"construction des fichiers balances comptables j'ai besoin de connaä\",\n", " 'donnä bonjour, pourriez vous me dire ä',\n", " 'url invalides bonjour, le jeu de donnä',\n", " 'date de disponibilitä bonjour, peut-on avoir une date ä',\n", " 'lien cassä bonjour, les liens de cette ressources sont cassä',\n", " \"communes regroupä j'ai constatä\",\n", " \"surperfice des terrains cadastres bonjour, est ce que l'on pourrait rä\",\n", " \"date de disponibilitä pouvez-vous communiquer une date indicative de mise en ligne des balances comptables d'avance. bonjour, il est prä\",\n", " \"deamande d'information sur la disponiblitä je souhaiterais savoir si une date est prä\",\n", " 'caractä bonjour, je voudrais savoir quelle est la diffä',\n", " 'liens morts bonjour, pour information, tous les liens vers les xls des donnä',\n", " 'villes ou sous communes manquantes bonjour, nous utilisons le fichier fantoir pour alimenter une liste dä',\n", " 'tous les liens sont morts tous les liens sont morts deleted',\n", " 'nomenclature des dä bonjour, la nomenclature m est proposä',\n", " 'accä bonjour, comment peut on tä',\n", " 'extraire des donnä bonjour, je rä',\n", " 'historique je cherche un jeu de donnä',\n", " 'projet de loi de finances vs loi de finances seuls les documents annexes au plf sont disponibles sur data.gouv.fr. les documents annexes ä',\n", " 'metadata and explanations in order to understand these data, can you explain the difference between the two files consommations de crä',\n", " 'ecart avec les comptes publiä bonjour, je ne retrouve pas les chiffres publiä',\n", " 'lien httpwww.nosdonnees.frdatasetmarches-publics-en-france lien mort lien actuel () httpwww.nosdonnees.frdatasetmarches-publics-en-france',\n", " \"api d'accä bonjour, a titre expä\",\n", " \"suggestion d'un nouveau mot-clä bonjour, afin que les donnä\",\n", " \"suggestion d'un nouveau mot-clä bonjour, afin que les donnä\",\n", " \"suggestion d'un nouveau mot-clä bonjour, afin que les donnä\",\n", " 'fichier fantoir par departement bonjour, votre fichier fait mo, aprä',\n", " \"problä bonjour. lorsqu'on utilise l'encodage utf- pour lire le fichier, les accents et la plupart des autres caractä\",\n", " 'pdv en double avec des informations diffä bonjour, le point de vente est en double dans le fichier quotidien. le premier possä',\n", " 'balances comptables les balances des epci sans fiscalitä',\n", " \"disponibilitä quand les balances comptables des communes seront-elles disponibles y a-t-il quelqu'un avoir connaissance de la date approximative de mise ä\",\n", " 'donnä bonjour, pourquoi certaines informations relatives aux stations-service, qui sont affichä',\n", " 'la ä la ä',\n", " \"on trouve valeurs dans le fichier , n'est-ce pas une valeur non renseignä on trouve valeurs dans le fichier , n'est-ce pas une valeur non renseignä\",\n", " \"je remonte l'anomalie prä je remonte l'anomalie prä\",\n", " \"le fichier ascii contenu dans l'archive zip est probablement corrompu et est reconnu comme un fichier binaire ce qui pose problä le fichier ascii contenu dans l'archive zip est probablement corrompu et est reconnu comme un fichier binaire ce qui pose problä\",\n", " 'tous les liens sont morts, erreur tous les liens sont morts, erreur',\n", " \"format des horaires et jours d'ouvertures peu prä format des horaires et jours d'ouvertures peu prä\",\n", " 'position gä position gä',\n", " 'erreur de tä erreur de tä',\n", " 'tous les fichiers csv retournent une erreur (page introuvable) lorsque je tente des les tä tous les fichiers csv retournent une erreur (page introuvable) lorsque je tente des les tä',\n", " 'lien mort lien mort',\n", " 'la premiä bonjour, la premiä',\n", " 'trä bonjour, trä',\n", " 'tous les documents sont des pdf, donc un format non-rä tous les documents sont des pdf, donc un format non-rä',\n", " 'la derniä bonjour, la derniä',\n", " 'ces fichiers retraä ces fichiers retraä',\n", " \"erreur d'url sur le document principaux indicateurs ä erreur d'url sur le document principaux indicateurs ä\"]" ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" } ], "source": [ "preprocessed_data = preprocess_data(df_MEFSIN)\n", "preprocessed_data" ] }, { "cell_type": "code", "execution_count": 84, "id": "5375213c", "metadata": {}, "outputs": [], "source": [ "#Sélection des features (X) à utiliser pour l'inférence\n", "\n", "#features = df_MEFSIN[\"messages\"]\n", "#features = df_MEFSIN[\"combined_text\"]\n", "\n", "# Prétraitement des données d'inférence\n", "preprocessed_data = preprocess_data(df_MEFSIN)\n", "\n", "# Préparation des données pour l'inférence\n", "#messages = preprocessed_data[\"combined_text\"]\n", "\n", "# Préparation des données pour l'inférence\n", "messages = preprocessed_data\n", "#messages = preprocessed_data.tolist()\n", "\n", "# Créer une liste pour stocker les prédictions\n", "predictions = []\n", "\n", "# Définir la taille du batch d'inférence\n", "batch_size = 16\n", "\n", "# Diviser les données en lots plus petits\n", "num_batches = len(messages) // batch_size\n", "if len(messages) % batch_size != 0:\n", " num_batches += 1\n", "\n", "# Mettre le modèle en mode évaluation\n", "model_saved.eval()\n", "\n", "# Parcourir les lots et effectuer l'inférence\n", "for i in range(num_batches):\n", " # Sélectionner les textes du lot actuel\n", " batch_texts = messages[i * batch_size: (i + 1) * batch_size]\n", "\n", " # Appliquer le tokenizer et le modèle pour l'inférence\n", " with torch.no_grad():\n", " # Encoder les textes avec le tokenizer\n", " encoded_inputs = tokenizer_saved(\n", " batch_texts, padding=True, truncation=True, max_length=128, return_tensors=\"pt\"\n", " )\n", "\n", " # Passage des données dans le modèle pour l'inférence\n", " outputs = model_saved(input_ids=encoded_inputs['input_ids'], attention_mask=encoded_inputs['attention_mask'])\n", "\n", " # Récupération des prédictions\n", " predicted_labels = torch.argmax(outputs.logits, dim=1)\n", "\n", " # Ajouter les prédictions à la liste des résultats\n", " predictions.extend(predicted_labels.tolist())\n", "\n", "# Ajouter la liste des prédictions comme une nouvelle colonne \"predictions_motifs\" au DataFrame\n", "df_MEFSIN['predictions_motifs'] = predictions\n", "df_MEFSIN['predictions_motifs_label'] = [id2label[prediction] for prediction in predictions]\n" ] }, { "cell_type": "code", "execution_count": 86, "id": "52d8c242", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idusersubjecttitlesizemessagescreatedclosedclosed_byMEFSINcombined_textpredictions_motifspredictions_motifs_label
06418839138db635b9a8ec61aChristophe BADOLParcellaire Express (PCI)Disparition de la table arrondissement de la l...2Bonjour,\\n\\nla table arrondissement a disparu ...2023-03-20T17:02:25.636000NaNNaN1Disparition de la table arrondissement de la l...2Actualisation
1641861cca4f1971589503cb9Estelle CrĆFichiers des locaux et des parcelles des perso...Siren cessĆ1Bonjour, Pourquoi y a-t-il des Siren dont l'Ć2023-03-20T14:38:20.353000NaNNaN1Siren cessĆ Bonjour, Pourquoi y a-t-il des Si...1Autre
26413358dcce10824f53a9bc9Camille BaconDemandes de valeurs fonciĆ1 idloc = 1 local1Bonjour,\\n\\nTout d'abord, merci pour ces donnĆ2023-03-16T16:28:13.300000NaNNaN11 idloc = 1 local Bonjour,\\n\\nTout d'abord, me...1Autre
364088027de783a9eadb04349JĆPrix des carburants en France - Flux instantanĆDate d'obsolescence de ce jeu de donnĆ1Bonjour, la description du jeu de donnĆ2023-03-08T13:31:35.125000NaNNaN1Date d'obsolescence de ce jeu de donnĆ Bonjou...2Actualisation
4640869f8abc8970cefa9c3d4Anne SolazL'impĆliens non focntionnels1Bonjour, Je n'arrive pas Ć2023-03-08T11:56:56.125000NaNNaN1liens non focntionnels Bonjour, Je n'arrive pa...3Accessibilité
56408538a96433266c124be61Pierre L'HostisDonnĆPlateforme non indiquĆ1Bonjour,\\n\\nPourriez-vous me dire si les donnĆ2023-03-08T10:21:14.949000NaNNaN1Plateforme non indiquĆ Bonjour,\\n\\nPourriez-v...3Accessibilité
663fe2b9c047052abef06bfc1Corinne BCDRĆDonnĆ1Bonjour\\nMa collectivitĆ2023-02-28T17:28:12.244000NaNNaN1DonnĆ Bonjour\\nMa collectivitĆ1Autre
763f62c2468b60c13e99ab53cClaude LerouxDemandes de valeurs fonciĆparcelle BT2 - commune de CarriĆ1Bonjour,\\nje vous contacte car je souhaiterais...2023-02-22T15:52:20.774000NaNNaN1parcelle BT2 - commune de CarriĆ Bonjour,\\nje...1Autre
863e5e3174f42fe618e57ad7bIliyan PetrovRĆLien vers le flux1Bonjour,\\nJ'ai quelques questions de base sur ...2023-02-10T07:24:23.623000NaNNaN1Lien vers le flux Bonjour,\\nJ'ai quelques ques...1Autre
963e354bd89059f1ad24d03f4BĆDonnĆImpossible de trouver nos donnĆ2Bonjour,\\nNos donnĆ2023-02-08T08:52:29.253000NaNNaN1Impossible de trouver nos donnĆ Bonjour,\\nNos...3Accessibilité
\n", "
" ], "text/plain": [ " id user \\\n", "0 6418839138db635b9a8ec61a Christophe BADOL \n", "1 641861cca4f1971589503cb9 Estelle CrĆ \n", "2 6413358dcce10824f53a9bc9 Camille Bacon \n", "3 64088027de783a9eadb04349 JĆ \n", "4 640869f8abc8970cefa9c3d4 Anne Solaz \n", "5 6408538a96433266c124be61 Pierre L'Hostis \n", "6 63fe2b9c047052abef06bfc1 Corinne BCD \n", "7 63f62c2468b60c13e99ab53c Claude Leroux \n", "8 63e5e3174f42fe618e57ad7b Iliyan Petrov \n", "9 63e354bd89059f1ad24d03f4 BĆ \n", "\n", " subject \\\n", "0 Parcellaire Express (PCI) \n", "1 Fichiers des locaux et des parcelles des perso... \n", "2 Demandes de valeurs fonciĆ \n", "3 Prix des carburants en France - Flux instantanĆ \n", "4 L'impĆ \n", "5 DonnĆ \n", "6 RĆ \n", "7 Demandes de valeurs fonciĆ \n", "8 RĆ \n", "9 DonnĆ \n", "\n", " title size \\\n", "0 Disparition de la table arrondissement de la l... 2 \n", "1 Siren cessĆ 1 \n", "2 1 idloc = 1 local 1 \n", "3 Date d'obsolescence de ce jeu de donnĆ 1 \n", "4 liens non focntionnels 1 \n", "5 Plateforme non indiquĆ 1 \n", "6 DonnĆ 1 \n", "7 parcelle BT2 - commune de CarriĆ 1 \n", "8 Lien vers le flux 1 \n", "9 Impossible de trouver nos donnĆ 2 \n", "\n", " messages \\\n", "0 Bonjour,\\n\\nla table arrondissement a disparu ... \n", "1 Bonjour, Pourquoi y a-t-il des Siren dont l'Ć \n", "2 Bonjour,\\n\\nTout d'abord, merci pour ces donnĆ \n", "3 Bonjour, la description du jeu de donnĆ \n", "4 Bonjour, Je n'arrive pas Ć \n", "5 Bonjour,\\n\\nPourriez-vous me dire si les donnĆ \n", "6 Bonjour\\nMa collectivitĆ \n", "7 Bonjour,\\nje vous contacte car je souhaiterais... \n", "8 Bonjour,\\nJ'ai quelques questions de base sur ... \n", "9 Bonjour,\\nNos donnĆ \n", "\n", " created closed closed_by MEFSIN \\\n", "0 2023-03-20T17:02:25.636000 NaN NaN 1 \n", "1 2023-03-20T14:38:20.353000 NaN NaN 1 \n", "2 2023-03-16T16:28:13.300000 NaN NaN 1 \n", "3 2023-03-08T13:31:35.125000 NaN NaN 1 \n", "4 2023-03-08T11:56:56.125000 NaN NaN 1 \n", "5 2023-03-08T10:21:14.949000 NaN NaN 1 \n", "6 2023-02-28T17:28:12.244000 NaN NaN 1 \n", "7 2023-02-22T15:52:20.774000 NaN NaN 1 \n", "8 2023-02-10T07:24:23.623000 NaN NaN 1 \n", "9 2023-02-08T08:52:29.253000 NaN NaN 1 \n", "\n", " combined_text predictions_motifs \\\n", "0 Disparition de la table arrondissement de la l... 2 \n", "1 Siren cessĆ Bonjour, Pourquoi y a-t-il des Si... 1 \n", "2 1 idloc = 1 local Bonjour,\\n\\nTout d'abord, me... 1 \n", "3 Date d'obsolescence de ce jeu de donnĆ Bonjou... 2 \n", "4 liens non focntionnels Bonjour, Je n'arrive pa... 3 \n", "5 Plateforme non indiquĆ Bonjour,\\n\\nPourriez-v... 3 \n", "6 DonnĆ Bonjour\\nMa collectivitĆ 1 \n", "7 parcelle BT2 - commune de CarriĆ Bonjour,\\nje... 1 \n", "8 Lien vers le flux Bonjour,\\nJ'ai quelques ques... 1 \n", "9 Impossible de trouver nos donnĆ Bonjour,\\nNos... 3 \n", "\n", " predictions_motifs_label \n", "0 Actualisation \n", "1 Autre \n", "2 Autre \n", "3 Actualisation \n", "4 Accessibilité \n", "5 Accessibilité \n", "6 Autre \n", "7 Autre \n", "8 Autre \n", "9 Accessibilité " ] }, "execution_count": 86, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_MEFSIN.head(10)" ] }, { "cell_type": "code", "execution_count": 87, "id": "2b179377", "metadata": {}, "outputs": [], "source": [ "# Sauvegarde des résultats d'annotations sur les grandes catégories du jeu du MEFSIN\n", "df_MEFSIN.to_csv('Résultat_Annotations_GDMotifs.csv', index=False)" ] }, { "cell_type": "markdown", "id": "4a580443", "metadata": {}, "source": [ "##################################################################################################################\n", "##################################################################################################################\n", "##################################################################################################################" ] }, { "cell_type": "markdown", "id": "2ebafd31", "metadata": {}, "source": [ "# Modèle de prédictions sur les sous-motifs d'annotations (Jeu de Datactivist)" ] }, { "cell_type": "code", "execution_count": 143, "id": "fc9299d6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Questions ou remarques d'usagers 1419\n", "Demande de jeu de données (set) 1067\n", "Absence de mise à jour 740\n", "Lien mort 596\n", "Erreur dans les données fournies 426\n", "Absence d'information sur les mises à jour 419\n", "Incapacité à traiter les données 384\n", "Absence de données 323\n", "Absence de description des variables 270\n", "Commentaire sans valeur 254\n", "Formatage non respecté 247\n", "Incertitude des données 241\n", "Format incompatible 209\n", "Information des réutilisateurs 204\n", "Descriptions imprécises 201\n", "Message automatique 178\n", "Proposition de mots-clefs 156\n", "Problème de granularité 116\n", "Incohérence des données 107\n", "Demande de correction 84\n", "Problème d'uniformité dans la saisie 72\n", "Répétition des données 54\n", "Erreur d'actualisation 54\n", "Données non-ouvertes 49\n", "Source des données incorrecte ou imprécise 39\n", "Harmonisation des données 39\n", "Name: Annotation, dtype: int64" ] }, "execution_count": 143, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Annotation'].value_counts()" ] }, { "cell_type": "code", "execution_count": 144, "id": "227f2837", "metadata": {}, "outputs": [], "source": [ "#df2 = df.copy()" ] }, { "cell_type": "code", "execution_count": 145, "id": "52f4bf4e", "metadata": {}, "outputs": [], "source": [ "# On enlève les espaces en trop des noms de catégories\n", "def preprocess_sscategories(df, column_name):\n", " # Suppression des points\n", " df[column_name] = df[column_name].str.replace('.', '')\n", "\n", " # Suppression de plus d'un espace en les remplaçant par un seul espace\n", " df[column_name] = df[column_name].apply(lambda x: re.sub(r'\\s+', ' ', x))\n", "\n", " # Suppression des espaces en début et fin de texte\n", " df[column_name] = df[column_name].str.strip()" ] }, { "cell_type": "code", "execution_count": 146, "id": "5615876c", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_69560/243326824.py:4: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n", " df[column_name] = df[column_name].str.replace('.', '')\n" ] } ], "source": [ "# Appliquer la fonction de prétraitement sur la colonne\n", "preprocess_sscategories(df, 'Annotation')" ] }, { "cell_type": "code", "execution_count": 147, "id": "49d9ed63", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Questions ou remarques d'usagers 1419\n", "Demande de jeu de données (set) 1067\n", "Absence de mise à jour 740\n", "Lien mort 596\n", "Erreur dans les données fournies 426\n", "Absence d'information sur les mises à jour 419\n", "Incapacité à traiter les données 384\n", "Absence de données 323\n", "Absence de description des variables 270\n", "Commentaire sans valeur 254\n", "Formatage non respecté 247\n", "Incertitude des données 241\n", "Format incompatible 209\n", "Information des réutilisateurs 204\n", "Descriptions imprécises 201\n", "Message automatique 178\n", "Proposition de mots-clefs 156\n", "Problème de granularité 116\n", "Incohérence des données 107\n", "Demande de correction 84\n", "Problème d'uniformité dans la saisie 72\n", "Répétition des données 54\n", "Erreur d'actualisation 54\n", "Données non-ouvertes 49\n", "Source des données incorrecte ou imprécise 39\n", "Harmonisation des données 39\n", "Name: Annotation, dtype: int64" ] }, "execution_count": 147, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Annotation'].value_counts()" ] }, { "cell_type": "code", "execution_count": 150, "id": "50d558cf", "metadata": {}, "outputs": [], "source": [ "df['combined_text_2'] = df['categorie'] + ' ' + df['categorie'] + ' ' + df['categorie'] + ' ' + df['title'] + ' ' + df['messages']" ] }, { "cell_type": "code", "execution_count": 151, "id": "843ca227", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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id dgfsubjecttitlemessagesAnnotationcategoriecreatedcombined_textcombined_text_2
0601ba51cb94ff759925437d6Simulateur de COUT DU CERTIFICAT D’IMMATRICUL...Mise à jour fichiers simulateurs 2021Bonjour, suite à la mise à jour de mon simulat...Incohérence des donnéesFiabilité2021-02-04 08:41Mise à jour fichiers simulateurs 2021 Bonjour,...Fiabilité Fiabilité Fiabilité Mise à jour fich...
1601c336736c1b45b238d2598Lieux de vaccination contre la Covid-19Coordonnées des centres de vaccinationsBonjour, j'ai contacté le centre de vaccinatio...Questions ou remarques d'usagersAutre2021-02-04 18:48Coordonnées des centres de vaccinations Bonjou...Autre Autre Autre Coordonnées des centres de v...
2601971b73363cef6fbdb08b3Vaccination et dépistage COVID-19IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE...Annonce faite dans les médias qui veulent souv...Commentaire sans valeurAutre2021-02-02 16:37IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE...Autre Autre Autre IL EST ANNONCE QU'IL EST POS...
3601cf95e3f8affb8232057a8Base Sirene des entreprises et de leurs établi...Manque d'effectifsBonjour,\\nje constate une disparition d'un gra...Incohérence des donnéesFiabilité2021-02-05 08:53Manque d'effectifs Bonjour,\\nje constate une d...Fiabilité Fiabilité Fiabilité Manque d'effecti...
4601a99d34d7375a1d7b5f753Hydrométrie - situation hydrologique en Bretag...Temporalité des donnéesNous souhaiterions utilisé ces données. nous r...Erreur d'actualisationActualisation2021-02-03 13:40Temporalité des données Nous souhaiterions ut...Actualisation Actualisation Actualisation Temp...
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" ], "text/plain": [ " id dgf \\\n", "0 601ba51cb94ff759925437d6 \n", "1 601c336736c1b45b238d2598 \n", "2 601971b73363cef6fbdb08b3 \n", "3 601cf95e3f8affb8232057a8 \n", "4 601a99d34d7375a1d7b5f753 \n", "\n", " subject \\\n", "0 Simulateur de COUT DU CERTIFICAT D’IMMATRICUL... \n", "1 Lieux de vaccination contre la Covid-19 \n", "2 Vaccination et dépistage COVID-19 \n", "3 Base Sirene des entreprises et de leurs établi... \n", "4 Hydrométrie - situation hydrologique en Bretag... \n", "\n", " title \\\n", "0 Mise à jour fichiers simulateurs 2021 \n", "1 Coordonnées des centres de vaccinations \n", "2 IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE... \n", "3 Manque d'effectifs \n", "4 Temporalité des données \n", "\n", " messages \\\n", "0 Bonjour, suite à la mise à jour de mon simulat... \n", "1 Bonjour, j'ai contacté le centre de vaccinatio... \n", "2 Annonce faite dans les médias qui veulent souv... \n", "3 Bonjour,\\nje constate une disparition d'un gra... \n", "4 Nous souhaiterions utilisé ces données. nous r... \n", "\n", " Annotation categorie created \\\n", "0 Incohérence des données Fiabilité 2021-02-04 08:41 \n", "1 Questions ou remarques d'usagers Autre 2021-02-04 18:48 \n", "2 Commentaire sans valeur Autre 2021-02-02 16:37 \n", "3 Incohérence des données Fiabilité 2021-02-05 08:53 \n", "4 Erreur d'actualisation Actualisation 2021-02-03 13:40 \n", "\n", " combined_text \\\n", "0 Mise à jour fichiers simulateurs 2021 Bonjour,... \n", "1 Coordonnées des centres de vaccinations Bonjou... \n", "2 IL EST ANNONCE QU'IL EST POSSIBLE DE REPRENDRE... \n", "3 Manque d'effectifs Bonjour,\\nje constate une d... \n", "4 Temporalité des données Nous souhaiterions ut... \n", "\n", " combined_text_2 \n", "0 Fiabilité Fiabilité Fiabilité Mise à jour fich... \n", "1 Autre Autre Autre Coordonnées des centres de v... \n", "2 Autre Autre Autre IL EST ANNONCE QU'IL EST POS... \n", "3 Fiabilité Fiabilité Fiabilité Manque d'effecti... \n", "4 Actualisation Actualisation Actualisation Temp... " ] }, "execution_count": 151, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "id": "169a8ccd", "metadata": {}, "source": [ "# Création des tables de correspondances id2sslabel et sslabel2id pour numériser nos sous-catégories" ] }, { "cell_type": "code", "execution_count": 152, "id": "2dfe19b2", "metadata": {}, "outputs": [], "source": [ "# Numérisation des sous-motifs d'annotations" ] }, { "cell_type": "code", "execution_count": 153, "id": "94263a7d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "26" ] }, "execution_count": 153, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Annotation'].nunique()" ] }, { "cell_type": "code", "execution_count": 154, "id": "36563198", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Incohérence des données',\n", " \"Questions ou remarques d'usagers\",\n", " 'Commentaire sans valeur',\n", " \"Erreur d'actualisation\",\n", " 'Absence de mise à jour',\n", " 'Erreur dans les données fournies',\n", " 'Lien mort',\n", " 'Format incompatible',\n", " 'Information des réutilisateurs',\n", " 'Absence de description des variables',\n", " 'Absence de données',\n", " 'Demande de jeu de données (set)',\n", " \"Absence d'information sur les mises à jour\",\n", " \"Problème d'uniformité dans la saisie\",\n", " 'Incertitude des données',\n", " 'Problème de granularité',\n", " 'Proposition de mots-clefs',\n", " 'Incapacité à traiter les données',\n", " 'Formatage non respecté',\n", " 'Source des données incorrecte ou imprécise',\n", " 'Descriptions imprécises',\n", " 'Données non-ouvertes',\n", " 'Répétition des données',\n", " 'Demande de correction',\n", " 'Message automatique',\n", " 'Harmonisation des données']" ] }, "execution_count": 154, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sslabels = df['Annotation'].unique().tolist()\n", "sslabels" ] }, { "cell_type": "code", "execution_count": 155, "id": "ce19c489", "metadata": {}, "outputs": [], "source": [ "# Créer des dictionnaires pour convertir les identifiants de label et les labels\n", "id2sslabel = {id:sslabel for id, sslabel in enumerate(sslabels)}\n", "sslabel2id = {sslabel:id for id, sslabel in enumerate(sslabels)}" ] }, { "cell_type": "code", "execution_count": 156, "id": "98575fd5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{0: 'Incohérence des données',\n", " 1: \"Questions ou remarques d'usagers\",\n", " 2: 'Commentaire sans valeur',\n", " 3: \"Erreur d'actualisation\",\n", " 4: 'Absence de mise à jour',\n", " 5: 'Erreur dans les données fournies',\n", " 6: 'Lien mort',\n", " 7: 'Format incompatible',\n", " 8: 'Information des réutilisateurs',\n", " 9: 'Absence de description des variables',\n", " 10: 'Absence de données',\n", " 11: 'Demande de jeu de données (set)',\n", " 12: \"Absence d'information sur les mises à jour\",\n", " 13: \"Problème d'uniformité dans la saisie\",\n", " 14: 'Incertitude des données',\n", " 15: 'Problème de granularité',\n", " 16: 'Proposition de mots-clefs',\n", " 17: 'Incapacité à traiter les données',\n", " 18: 'Formatage non respecté',\n", " 19: 'Source des données incorrecte ou imprécise',\n", " 20: 'Descriptions imprécises',\n", " 21: 'Données non-ouvertes',\n", " 22: 'Répétition des données',\n", " 23: 'Demande de correction',\n", " 24: 'Message automatique',\n", " 25: 'Harmonisation des données'}" ] }, "execution_count": 156, "metadata": {}, "output_type": "execute_result" } ], "source": [ "id2sslabel" ] }, { "cell_type": "code", "execution_count": 157, "id": "63a17b30", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'Incohérence des données': 0,\n", " \"Questions ou remarques d'usagers\": 1,\n", " 'Commentaire sans valeur': 2,\n", " \"Erreur d'actualisation\": 3,\n", " 'Absence de mise à jour': 4,\n", " 'Erreur dans les données fournies': 5,\n", " 'Lien mort': 6,\n", " 'Format incompatible': 7,\n", " 'Information des réutilisateurs': 8,\n", " 'Absence de description des variables': 9,\n", " 'Absence de données': 10,\n", " 'Demande de jeu de données (set)': 11,\n", " \"Absence d'information sur les mises à jour\": 12,\n", " \"Problème d'uniformité dans la saisie\": 13,\n", " 'Incertitude des données': 14,\n", " 'Problème de granularité': 15,\n", " 'Proposition de mots-clefs': 16,\n", " 'Incapacité à traiter les données': 17,\n", " 'Formatage non respecté': 18,\n", " 'Source des données incorrecte ou imprécise': 19,\n", " 'Descriptions imprécises': 20,\n", " 'Données non-ouvertes': 21,\n", " 'Répétition des données': 22,\n", " 'Demande de correction': 23,\n", " 'Message automatique': 24,\n", " 'Harmonisation des données': 25}" ] }, "execution_count": 157, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sslabel2id" ] }, { "cell_type": "markdown", "id": "f1f6ee6b", "metadata": {}, "source": [ "# Division du jeu de données (Train/Validation/Test set)" ] }, { "cell_type": "code", "execution_count": 158, "id": "d0955732", "metadata": {}, "outputs": [], "source": [ "# Diviser le jeu de données en ensembles d'entraînement et de test\n", "train2_df, test2_df = train_test_split(df, test_size=0.2, random_state=42, stratify=df['Annotation'])\n", "\n", "# Diviser l'ensemble d'entraînement en ensembles d'entraînement et de validation\n", "train2_df, val2_df = train_test_split(train2_df, test_size=0.2, random_state=42, stratify=train2_df['Annotation'])\n", "\n", "# Créer des Datasets pour les ensembles train, validation et test\n", "train2_dataset = Dataset.from_pandas(train2_df[['id dgf', 'subject', 'messages', 'Annotation', 'categorie', 'combined_text_2']])\n", "val2_dataset = Dataset.from_pandas(val2_df[['id dgf', 'subject', 'messages', 'Annotation', 'categorie', 'combined_text_2']])\n", "test2_dataset = Dataset.from_pandas(test2_df[['id dgf', 'subject', 'messages', 'Annotation', 'categorie', 'combined_text_2']])\n", "\n", "# Créer un DatasetDict\n", "dataset2 = DatasetDict({\n", " 'train2': train2_dataset,\n", " 'validation2': val2_dataset,\n", " 'test2': test2_dataset\n", "})" ] }, { "cell_type": "code", "execution_count": 159, "id": "99465bf4", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Train2 : \n", " Questions ou remarques d'usagers 908\n", "Demande de jeu de données (set) 683\n", "Absence de mise à jour 474\n", "Lien mort 382\n", "Erreur dans les données fournies 273\n", "Absence d'information sur les mises à jour 268\n", "Incapacité à traiter les données 246\n", "Absence de données 206\n", "Absence de description des variables 173\n", "Commentaire sans valeur 162\n", "Formatage non respecté 158\n", "Incertitude des données 154\n", "Format incompatible 134\n", "Information des réutilisateurs 130\n", "Descriptions imprécises 129\n", "Message automatique 114\n", "Proposition de mots-clefs 100\n", "Problème de granularité 74\n", "Incohérence des données 69\n", "Demande de correction 54\n", "Problème d'uniformité dans la saisie 46\n", "Répétition des données 34\n", "Erreur d'actualisation 34\n", "Données non-ouvertes 31\n", "Source des données incorrecte ou imprécise 25\n", "Harmonisation des données 25\n", "Name: Annotation, dtype: int64\n", "\n", "\n", "Validation2 : \n", " Questions ou remarques d'usagers 227\n", "Demande de jeu de données (set) 171\n", "Absence de mise à jour 118\n", "Lien mort 95\n", "Erreur dans les données fournies 68\n", "Absence d'information sur les mises à jour 67\n", "Incapacité à traiter les données 61\n", "Absence de données 52\n", "Absence de description des variables 43\n", "Commentaire sans valeur 41\n", "Formatage non respecté 40\n", "Incertitude des données 39\n", "Information des réutilisateurs 33\n", "Format incompatible 33\n", "Descriptions imprécises 32\n", "Message automatique 28\n", "Proposition de mots-clefs 25\n", "Problème de granularité 19\n", "Incohérence des données 17\n", "Demande de correction 13\n", "Problème d'uniformité dans la saisie 12\n", "Erreur d'actualisation 9\n", "Répétition des données 9\n", "Données non-ouvertes 8\n", "Harmonisation des données 6\n", "Source des données incorrecte ou imprécise 6\n", "Name: Annotation, dtype: int64\n", "\n", "\n", "Test2 : \n", " Questions ou remarques d'usagers 284\n", "Demande de jeu de données (set) 213\n", "Absence de mise à jour 148\n", "Lien mort 119\n", "Erreur dans les données fournies 85\n", "Absence d'information sur les mises à jour 84\n", "Incapacité à traiter les données 77\n", "Absence de données 65\n", "Absence de description des variables 54\n", "Commentaire sans valeur 51\n", "Formatage non respecté 49\n", "Incertitude des données 48\n", "Format incompatible 42\n", "Information des réutilisateurs 41\n", "Descriptions imprécises 40\n", "Message automatique 36\n", "Proposition de mots-clefs 31\n", "Problème de granularité 23\n", "Incohérence des données 21\n", "Demande de correction 17\n", "Problème d'uniformité dans la saisie 14\n", "Répétition des données 11\n", "Erreur d'actualisation 11\n", "Données non-ouvertes 10\n", "Harmonisation des données 8\n", "Source des données incorrecte ou imprécise 8\n", "Name: Annotation, dtype: int64\n" ] } ], "source": [ "# Avant la division\n", "plt.figure(figsize=(10, 8))\n", "plt.subplot(2, 1, 1)\n", "plt.title(\"Répartition des sous-catégories (Avant la division)\")\n", "df['Annotation'].value_counts().plot(kind='bar')\n", "plt.xlabel(\"Sous-catégorie\")\n", "plt.ylabel(\"Nombre d'échantillons\")\n", "\n", "# Après la division\n", "train2_counts = train2_df['Annotation'].value_counts()\n", "val2_counts = val2_df['Annotation'].value_counts()\n", "test2_counts = test2_df['Annotation'].value_counts()\n", "\n", "# Répartition des sous-catégories dans train2_df\n", "plt.figure(figsize=(10, 16))\n", "plt.subplot(3, 1, 1)\n", "plt.title(\"Répartition des sous-catégories (Ensemble d'entraînement)\")\n", "train2_counts.plot(kind='bar', color='blue', alpha=0.7)\n", "plt.xlabel(\"Sous-catégorie\")\n", "plt.ylabel(\"Nombre d'échantillons\")\n", "\n", "# Répartition des sous-catégories dans val2_df\n", "plt.subplot(3, 1, 2)\n", "plt.title(\"Répartition des sous-catégories (Ensemble de validation)\")\n", "val2_counts.plot(kind='bar', color='red', alpha=0.7)\n", "plt.xlabel(\"Sous-catégorie\")\n", "plt.ylabel(\"Nombre d'échantillons\")\n", "\n", "# Répartition des sous-catégories dans test2_df\n", "plt.subplot(3, 1, 3)\n", "plt.title(\"Répartition des sous-catégories (Ensemble de test)\")\n", "test2_counts.plot(kind='bar', color='green', alpha=0.7)\n", "plt.xlabel(\"Sous-catégorie\")\n", "plt.ylabel(\"Nombre d'échantillons\")\n", "\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "print('Train2 : \\n', train2_counts)\n", "print('\\n')\n", "print('Validation2 : \\n', val2_counts)\n", "print('\\n')\n", "print('Test2 : \\n', test2_counts)" ] }, { "cell_type": "code", "execution_count": 160, "id": "9c97edd1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'id dgf': '5885ec9588ee3837db9b81a5',\n", " 'subject': 'Points de recharge de véhicules électriques,administrés par MOPeasy',\n", " 'messages': \"Bonjour, je vous suggère de créer un nouveau jeu de données réactualisé avec ce modèle https://www.data.gouv.fr/s/resources/fichiers-pour-les-infrastructures-de-recharge-de-vehicules-electriques/20170115-225606/IRVE_modele_pour_fichier_CSV.xls conformément à l'arrêté du 12 janvier 2017 \\nSi le lien cité plus haut ne fonctionne pas retrouvez le modèle avec sa dernière mise à jour ici: \\nhttps://www.data.gouv.fr/fr/datasets/fichiers-pour-les-infrastructures-de-\\nrecharge-de-vehicules-electriques/\\nBonjour,\\nJe n'ai réussi à accéder à aucun des deux liens, si ce n'est la page sans doute périmé https://www.data.gouv.fr/fr/datasets/fichier-consolide-des-bornes-de-recharge-pour-vehicules-electriques-irve/\\n\\npouvez vous nous donner le bon lien et surtout vous assurer qu'il est bien indexé par le moteur de recherche du site?\\nBonjour effectivement le lien que vous avez comportait une césure accidentelle voici le bon lien :\\nhttps://www.data.gouv.fr/fr/datasets/fichiers-pour-les-infrastructures-de-recharge-de-vehicules-electriques/\\nMerci pour votre retour! \\nF.A\\n2 Avril 2017 Bonjour, j'attire votre attention sur le fait que le fichier IRVE publié ici doit être remanié pour qu'il soit conforme au modèle commun à tous les aménageurs. Voilà plus de 2 mois que le décret 2017-26 a donné ses directives. Pour vous permettre de renseigner au plus tôt votre mise à jour à publier sur le site national data.gouv , l'association AUBE vous a proposé des fichiers d'aide cités dans les messages précédents.\\n\\nMerci de veiller à faire une mise à jour dans les meilleurs délais par vos services compétents. En cas de difficultés particulières n'hésitez pas à poser vos questions en retour de ce mail ou sur les discussions communautaires en bas de la page suivante: > https://www.data.gouv.fr/fr/datasets/fichiers-pour-les-infrastructures-de-recharge-de-vehicules-electriques/ < Bien cordialement Frédéric ALLARI\\n\",\n", " 'Annotation': 'Formatage non respecté',\n", " 'categorie': 'Exploitabilité',\n", " 'combined_text_2': \"Exploitabilité Exploitabilité Exploitabilité Mise à jour du fichier avec nouvelles colonnes (décret N°2017-26) Bonjour, je vous suggère de créer un nouveau jeu de données réactualisé avec ce modèle https://www.data.gouv.fr/s/resources/fichiers-pour-les-infrastructures-de-recharge-de-vehicules-electriques/20170115-225606/IRVE_modele_pour_fichier_CSV.xls conformément à l'arrêté du 12 janvier 2017 \\nSi le lien cité plus haut ne fonctionne pas retrouvez le modèle avec sa dernière mise à jour ici: \\nhttps://www.data.gouv.fr/fr/datasets/fichiers-pour-les-infrastructures-de-\\nrecharge-de-vehicules-electriques/\\nBonjour,\\nJe n'ai réussi à accéder à aucun des deux liens, si ce n'est la page sans doute périmé https://www.data.gouv.fr/fr/datasets/fichier-consolide-des-bornes-de-recharge-pour-vehicules-electriques-irve/\\n\\npouvez vous nous donner le bon lien et surtout vous assurer qu'il est bien indexé par le moteur de recherche du site?\\nBonjour effectivement le lien que vous avez comportait une césure accidentelle voici le bon lien :\\nhttps://www.data.gouv.fr/fr/datasets/fichiers-pour-les-infrastructures-de-recharge-de-vehicules-electriques/\\nMerci pour votre retour! \\nF.A\\n2 Avril 2017 Bonjour, j'attire votre attention sur le fait que le fichier IRVE publié ici doit être remanié pour qu'il soit conforme au modèle commun à tous les aménageurs. Voilà plus de 2 mois que le décret 2017-26 a donné ses directives. Pour vous permettre de renseigner au plus tôt votre mise à jour à publier sur le site national data.gouv , l'association AUBE vous a proposé des fichiers d'aide cités dans les messages précédents.\\n\\nMerci de veiller à faire une mise à jour dans les meilleurs délais par vos services compétents. En cas de difficultés particulières n'hésitez pas à poser vos questions en retour de ce mail ou sur les discussions communautaires en bas de la page suivante: > https://www.data.gouv.fr/fr/datasets/fichiers-pour-les-infrastructures-de-recharge-de-vehicules-electriques/ < Bien cordialement Frédéric ALLARI\\n\",\n", " '__index_level_0__': 7439}" ] }, "execution_count": 160, "metadata": {}, "output_type": "execute_result" } ], "source": [ "example2 = dataset2['train2'][0]\n", "example2" ] }, { "cell_type": "markdown", "id": "da5b9f50", "metadata": {}, "source": [ "# Préprocessing des données" ] }, { "cell_type": "code", "execution_count": 161, "id": "9261f517", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "66299c5b45824a5a9b8c281e32dc2f37", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Map: 0%| | 0/5086 [00:00 exploitabilité exploitabilité mise à jour du fichier avec nouvelles colonnes (décret n-) bonjour, je vous suggère de créer un nouveau jeu de données réactualisé avec ce modèle httpswww.data.gouv.frsresourcesfichiers-pour-les-infrastructures-de-recharge-de-vehicules-electriques-irve_modele_pour_fichier_csv.xls conformément à l'arrêté du si le lien cité plus haut ne fonctionne pas retrouvez le modèle avec sa dernière mise à jour ici httpswww.data.gouv.frfrdatas\"" ] }, "execution_count": 138, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tokenizer2.decode(example2['input_ids'])" ] }, { "cell_type": "code", "execution_count": 139, "id": "8b38cd41", "metadata": {}, "outputs": [], "source": [ "# Changer le format des jeux de données pour torch\n", "#encoded_dataset2.set_format(\"torch\")" ] }, { "cell_type": "code", "execution_count": 140, "id": "360a7f3f", "metadata": {}, "outputs": [], "source": [ "# Définir la taille du lot et la métrique d'évaluation\n", "#batch_size = 8\n", "batch_size = 16\n", "#metric_name = \"f1\"\n", "metric_name = \"accuracy\"" ] }, { "cell_type": "code", "execution_count": 165, "id": "241a59ee", "metadata": {}, "outputs": [], "source": [ "# Définir les arguments pour l'entraînement\n", "args2 = TrainingArguments(\n", " \"bert-finetuned-my-data2\",\n", " #f\"bert-finetuned-sem_eval-english\",\n", " evaluation_strategy = \"epoch\",\n", " save_strategy = \"epoch\",\n", " #learning_rate=2e-6,\n", " ###learning_rate=2e-5,\n", " #learning_rate=1e-5,\n", " learning_rate=3e-5,\n", " #learning_rate=4e-5,\n", " per_device_train_batch_size=batch_size,\n", " per_device_eval_batch_size=batch_size,\n", " num_train_epochs=10,\n", " weight_decay=0.01,\n", " load_best_model_at_end=True,\n", " metric_for_best_model=metric_name,\n", " #push_to_hub=True,\n", ")" ] }, { "cell_type": "code", "execution_count": 166, "id": "a674b211", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Some weights of CamembertForSequenceClassification were not initialized from the model checkpoint at camembert-base and are newly initialized: ['classifier.dense.weight', 'classifier.out_proj.bias', 'classifier.out_proj.weight', 'classifier.dense.bias']\n", "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", "/home/asma/miniconda3/lib/python3.9/site-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n", " warnings.warn(\n" ] }, { "data": { "text/html": [ "\n", "
\n", " \n", " \n", " [3180/3180 2:55:24, Epoch 10/10]\n", "
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EpochTraining LossValidation LossAccuracyF1PrecisionRecall
1No log1.4012680.6336480.5109610.4625340.633648
21.8315001.0349070.6973270.6179250.5751810.697327
31.8315000.9022100.7075470.6349010.5979460.707547
40.9607000.8314720.7224840.6749100.6585370.722484
50.6715000.8271390.7342770.6912500.6652320.734277
60.6715000.7906970.7484280.7127300.6952160.748428
70.5004000.8455770.7437110.7114140.6961660.743711
80.3909000.8443190.7515720.7222010.7174370.751572
90.3909000.8774470.7515720.7262460.7264050.751572
100.3174000.8799350.7515720.7227050.7092840.751572

" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n" ] }, { "data": { "text/plain": [ "TrainOutput(global_step=3180, training_loss=0.7516984807620258, metrics={'train_runtime': 10527.3183, 'train_samples_per_second': 4.831, 'train_steps_per_second': 0.302, 'total_flos': 3346177969121280.0, 'train_loss': 0.7516984807620258, 'epoch': 10.0})" ] }, "execution_count": 166, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model2 = AutoModelForSequenceClassification.from_pretrained(\"camembert-base\",\n", " problem_type=\"single_label_classification\",\n", " num_labels=len(sslabels),\n", " id2label=id2sslabel,\n", " label2id=sslabel2id)\n", "\n", "# Variables globales pour stocker y_true et y_pred\n", "y_true_global2 = None\n", "y_pred_global2 = None\n", "\n", "def compute_metrics2(eval_pred2):\n", " global y_true_global2, y_pred_global2\n", "\n", " predictions2, y_true2 = eval_pred2\n", " y_pred2 = predictions2.argmax(axis=1)\n", "\n", " accuracy2 = accuracy_score(y_true2, y_pred2)\n", " precision2 = precision_score(y_true2, y_pred2, average=\"weighted\")\n", " recall2 = recall_score(y_true2, y_pred2, average=\"weighted\")\n", " f12 = f1_score(y_true2, y_pred2, average='weighted')\n", "\n", " # Assigner les valeurs à y_true_global et y_pred_global\n", " y_true_global2 = y_true2.tolist()\n", " y_pred_global2 = y_pred2.tolist()\n", "\n", " metrics2 = {\n", " 'accuracy': accuracy2,\n", " 'f1': f12,\n", " 'precision': precision2,\n", " 'recall': recall2\n", " }\n", "\n", " return metrics2\n", "\n", "# Créer l'optimiseur AdamW avec le taux d'apprentissage spécifié\n", "optimizer2 = AdamW(model2.parameters(), lr=args2.learning_rate)\n", "\n", "# Créer une instance de la classe Trainer en spécifiant l'optimiseur\n", "trainer2 = Trainer(\n", " model=model2,\n", " args=args2,\n", " train_dataset=encoded_dataset2[\"train2\"],\n", " eval_dataset=encoded_dataset2[\"validation2\"],\n", " optimizers=(optimizer2, None), # spécifier l'optimiseur pour l'entraînement\n", " tokenizer=tokenizer2,\n", " compute_metrics=compute_metrics2\n", ")\n", "\n", "# Lancer l'entraînement du modele\n", "trainer2.train()\n" ] }, { "cell_type": "markdown", "id": "ba27500a", "metadata": {}, "source": [ "# Evaluation du modèle 2 sur les données de test" ] }, { "cell_type": "code", "execution_count": 167, "id": "97cdadf2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "

\n", " \n", " \n", " [100/100 01:30]\n", "
\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n" ] }, { "data": { "text/plain": [ "{'eval_loss': 0.8758730888366699,\n", " 'eval_accuracy': 0.7377358490566037,\n", " 'eval_f1': 0.7094824730140812,\n", " 'eval_precision': 0.6972482540788782,\n", " 'eval_recall': 0.7377358490566037,\n", " 'eval_runtime': 91.8899,\n", " 'eval_samples_per_second': 17.303,\n", " 'eval_steps_per_second': 1.088,\n", " 'epoch': 10.0}" ] }, "execution_count": 167, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Évaluer le modèle sur l'ensemble de test\n", "eval_results2 = trainer2.evaluate(encoded_dataset2['test2'])\n", "eval_results2" ] }, { "cell_type": "code", "execution_count": 168, "id": "00810776", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y_true_global2: [19, 10, 16, 11, 6, 11, 6, 5, 10, 12, 17, 16, 5, 1, 9, 11, 19, 24, 1, 11, 9, 3, 24, 18, 4, 4, 18, 5, 11, 6, 4, 9, 15, 13, 1, 11, 11, 4, 9, 11, 8, 11, 4, 11, 11, 1, 15, 10, 4, 2, 17, 14, 18, 1, 1, 1, 1, 5, 7, 12, 23, 11, 14, 11, 9, 12, 1, 6, 8, 2, 1, 1, 11, 8, 4, 6, 10, 1, 1, 21, 5, 5, 7, 1, 11, 11, 12, 11, 17, 15, 2, 6, 1, 5, 2, 24, 4, 11, 19, 21, 12, 6, 5, 2, 8, 1, 9, 10, 23, 9, 11, 0, 17, 4, 9, 9, 5, 9, 5, 18, 8, 5, 0, 1, 15, 4, 14, 20, 12, 11, 1, 15, 17, 20, 10, 10, 2, 12, 11, 4, 11, 20, 14, 20, 17, 7, 10, 10, 1, 20, 1, 1, 16, 6, 1, 20, 4, 2, 1, 12, 14, 5, 9, 24, 6, 12, 2, 1, 14, 16, 8, 1, 20, 14, 4, 14, 0, 16, 24, 17, 6, 5, 1, 1, 8, 6, 1, 11, 4, 10, 14, 24, 1, 9, 20, 1, 1, 4, 11, 13, 1, 14, 2, 12, 2, 12, 1, 1, 4, 11, 14, 23, 17, 4, 4, 4, 1, 11, 24, 10, 4, 11, 12, 11, 11, 14, 1, 6, 2, 25, 13, 3, 4, 5, 1, 12, 5, 17, 11, 1, 4, 12, 1, 8, 1, 12, 11, 12, 14, 4, 5, 13, 1, 11, 3, 2, 5, 23, 12, 4, 1, 11, 12, 10, 1, 1, 6, 1, 11, 20, 1, 19, 1, 11, 4, 4, 2, 4, 6, 17, 13, 1, 5, 6, 12, 5, 4, 2, 1, 9, 9, 11, 11, 1, 5, 6, 18, 1, 11, 1, 18, 12, 1, 1, 11, 4, 1, 1, 4, 1, 5, 10, 1, 5, 10, 1, 1, 18, 7, 15, 4, 18, 6, 11, 23, 18, 1, 7, 1, 15, 10, 6, 22, 1, 1, 22, 11, 11, 5, 6, 12, 24, 11, 8, 4, 1, 6, 1, 6, 1, 0, 5, 1, 11, 9, 17, 9, 20, 11, 1, 11, 14, 1, 11, 1, 5, 1, 5, 20, 4, 10, 1, 6, 22, 25, 15, 4, 6, 11, 4, 10, 4, 7, 2, 9, 1, 14, 11, 11, 9, 9, 1, 0, 11, 23, 9, 14, 4, 10, 10, 10, 6, 4, 2, 11, 4, 7, 9, 12, 7, 4, 20, 14, 11, 5, 2, 6, 12, 11, 6, 1, 4, 16, 15, 11, 14, 5, 6, 11, 1, 1, 17, 12, 6, 17, 9, 6, 5, 1, 17, 11, 6, 18, 6, 14, 13, 7, 12, 17, 24, 12, 14, 17, 20, 12, 0, 8, 1, 6, 11, 2, 8, 1, 12, 24, 17, 1, 16, 1, 2, 2, 1, 17, 1, 11, 1, 1, 20, 14, 1, 10, 11, 1, 20, 8, 2, 2, 24, 1, 2, 24, 20, 17, 11, 6, 12, 1, 5, 7, 1, 18, 1, 9, 1, 1, 1, 2, 4, 1, 12, 10, 10, 20, 20, 20, 17, 11, 5, 4, 14, 1, 16, 4, 1, 2, 1, 8, 4, 16, 8, 16, 8, 23, 16, 4, 11, 11, 25, 4, 4, 20, 11, 0, 11, 11, 24, 6, 5, 1, 9, 1, 11, 1, 10, 12, 18, 1, 2, 11, 7, 11, 1, 11, 20, 6, 1, 11, 4, 24, 1, 5, 13, 17, 8, 10, 10, 5, 6, 7, 6, 18, 1, 6, 16, 4, 11, 11, 1, 24, 19, 12, 11, 6, 9, 12, 4, 4, 6, 6, 4, 6, 10, 1, 8, 14, 2, 11, 1, 4, 17, 11, 8, 4, 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24, 14, 1, 14, 6, 24, 12, 17, 12, 4, 4, 12, 1, 6, 1, 12, 11, 18, 24, 11, 4, 11, 4, 1, 22, 1, 11, 11, 6, 8, 12, 7, 11, 9, 18, 4, 23, 20, 17, 18, 11, 6, 5, 1, 1, 1, 10, 4, 2, 1, 6, 1, 4, 11, 11, 12, 11, 18, 22, 12, 16, 16, 6, 1, 11, 11, 1, 12, 11, 11, 11, 4, 1, 1, 4, 1, 4, 18, 1, 1, 14, 1, 7, 4, 23, 4, 12, 1, 8, 16, 11, 11, 0, 1, 1, 20, 1, 4, 11, 4, 5, 20, 8, 5, 18, 1, 4, 6, 1, 12, 1]\n", "y_pred_global2: [14, 10, 16, 11, 6, 11, 6, 5, 6, 12, 17, 16, 5, 1, 9, 17, 14, 24, 1, 11, 9, 4, 24, 15, 12, 4, 18, 5, 11, 6, 4, 9, 15, 18, 1, 11, 11, 4, 9, 11, 8, 11, 4, 11, 11, 1, 15, 11, 4, 2, 6, 5, 18, 1, 1, 1, 1, 5, 7, 12, 5, 11, 14, 10, 9, 12, 1, 6, 8, 1, 1, 1, 11, 8, 4, 6, 17, 1, 1, 15, 5, 5, 6, 1, 11, 11, 12, 17, 7, 15, 8, 6, 1, 14, 2, 24, 4, 11, 14, 18, 4, 6, 5, 2, 1, 1, 9, 11, 23, 9, 11, 5, 17, 12, 9, 9, 5, 9, 5, 18, 8, 5, 5, 2, 15, 4, 14, 9, 12, 11, 1, 15, 11, 9, 10, 11, 2, 12, 11, 4, 11, 9, 14, 9, 11, 17, 10, 10, 1, 9, 1, 8, 16, 6, 1, 9, 4, 2, 1, 12, 14, 5, 9, 24, 6, 4, 16, 1, 5, 16, 8, 1, 9, 14, 4, 14, 14, 16, 24, 17, 10, 5, 1, 1, 2, 6, 1, 11, 4, 7, 14, 24, 1, 9, 9, 8, 8, 4, 11, 18, 1, 14, 1, 12, 1, 12, 1, 1, 12, 11, 5, 5, 17, 4, 4, 4, 1, 11, 24, 10, 4, 11, 4, 11, 11, 14, 1, 17, 2, 15, 15, 12, 4, 5, 1, 4, 5, 7, 11, 1, 12, 4, 8, 8, 1, 4, 17, 12, 5, 12, 5, 18, 1, 11, 12, 2, 5, 5, 12, 4, 1, 11, 12, 10, 1, 1, 6, 1, 11, 9, 1, 14, 1, 11, 12, 4, 2, 4, 6, 11, 15, 1, 5, 11, 12, 14, 4, 2, 1, 9, 9, 11, 11, 1, 14, 6, 18, 1, 11, 1, 18, 12, 1, 1, 11, 12, 1, 1, 4, 1, 5, 10, 1, 5, 10, 1, 1, 18, 17, 18, 4, 18, 6, 11, 5, 18, 1, 7, 1, 15, 10, 17, 18, 1, 1, 15, 11, 11, 5, 7, 12, 24, 11, 8, 12, 1, 6, 1, 6, 1, 5, 14, 1, 11, 9, 11, 9, 9, 11, 1, 10, 5, 1, 10, 1, 5, 1, 5, 9, 4, 10, 1, 7, 15, 15, 15, 4, 6, 11, 4, 10, 4, 7, 2, 9, 1, 14, 11, 11, 9, 9, 2, 5, 11, 5, 9, 14, 4, 10, 10, 10, 6, 4, 1, 11, 4, 6, 9, 12, 10, 4, 9, 5, 11, 5, 2, 6, 12, 11, 6, 2, 4, 16, 15, 6, 14, 5, 6, 11, 1, 1, 6, 4, 6, 7, 9, 6, 5, 8, 17, 11, 6, 18, 6, 14, 18, 7, 12, 17, 24, 12, 14, 6, 9, 12, 14, 8, 1, 6, 7, 1, 8, 2, 4, 24, 7, 1, 16, 1, 2, 2, 1, 10, 1, 17, 1, 1, 9, 14, 1, 11, 11, 1, 9, 8, 2, 2, 24, 1, 1, 24, 9, 17, 11, 6, 12, 1, 5, 7, 1, 18, 1, 9, 1, 1, 1, 1, 4, 1, 12, 10, 10, 9, 9, 9, 7, 11, 5, 4, 14, 1, 16, 12, 1, 1, 1, 1, 4, 16, 8, 16, 8, 5, 16, 4, 11, 11, 15, 4, 4, 9, 11, 14, 11, 11, 24, 6, 5, 1, 9, 1, 11, 1, 10, 12, 15, 1, 1, 11, 6, 11, 1, 11, 9, 6, 1, 17, 12, 24, 1, 5, 18, 17, 8, 10, 10, 5, 6, 6, 6, 18, 1, 6, 16, 4, 11, 11, 1, 24, 14, 4, 11, 11, 9, 4, 4, 12, 6, 6, 4, 7, 10, 1, 8, 14, 1, 11, 1, 4, 11, 11, 8, 4, 18, 6, 1, 6, 11, 1, 11, 5, 4, 1, 14, 11, 12, 17, 5, 4, 1, 17, 11, 24, 15, 4, 6, 1, 17, 1, 5, 16, 6, 5, 12, 7, 4, 9, 12, 8, 4, 7, 11, 1, 11, 14, 1, 7, 4, 11, 1, 11, 10, 9, 1, 4, 18, 7, 14, 17, 12, 1, 1, 11, 1, 6, 4, 10, 2, 5, 4, 16, 14, 12, 1, 5, 11, 12, 14, 18, 5, 15, 18, 10, 15, 4, 1, 14, 11, 6, 1, 4, 11, 9, 1, 9, 4, 11, 24, 10, 4, 18, 6, 9, 2, 4, 1, 9, 6, 11, 11, 8, 1, 9, 4, 12, 6, 12, 14, 11, 1, 1, 1, 7, 1, 1, 8, 9, 1, 17, 6, 10, 9, 1, 4, 17, 6, 18, 18, 11, 18, 1, 11, 4, 11, 15, 5, 11, 10, 4, 1, 6, 4, 6, 1, 2, 5, 4, 1, 24, 10, 1, 17, 16, 10, 1, 5, 8, 5, 11, 10, 11, 11, 24, 11, 4, 7, 11, 9, 10, 1, 1, 12, 17, 6, 14, 16, 4, 7, 12, 12, 12, 18, 1, 24, 2, 11, 4, 8, 11, 5, 1, 5, 11, 8, 15, 12, 4, 24, 6, 16, 10, 2, 5, 4, 1, 11, 2, 1, 1, 14, 6, 1, 17, 1, 2, 5, 6, 9, 7, 6, 4, 4, 14, 11, 4, 1, 9, 2, 6, 11, 11, 5, 18, 18, 4, 6, 12, 1, 11, 10, 1, 11, 1, 14, 9, 7, 1, 10, 16, 17, 12, 6, 14, 11, 1, 15, 14, 11, 1, 17, 1, 4, 11, 6, 1, 10, 14, 9, 5, 4, 11, 17, 17, 11, 15, 18, 17, 12, 10, 9, 4, 1, 18, 1, 1, 1, 12, 11, 24, 18, 4, 15, 11, 9, 11, 14, 10, 12, 1, 11, 5, 24, 4, 6, 11, 4, 9, 18, 9, 15, 9, 10, 15, 6, 6, 11, 1, 18, 10, 17, 17, 12, 12, 1, 12, 12, 11, 7, 17, 14, 5, 10, 17, 9, 5, 12, 1, 9, 16, 11, 8, 1, 11, 4, 10, 10, 7, 23, 4, 4, 11, 1, 10, 7, 17, 2, 6, 6, 5, 11, 9, 10, 18, 2, 11, 6, 4, 1, 6, 17, 12, 17, 10, 9, 15, 10, 4, 18, 1, 12, 11, 1, 1, 5, 10, 11, 16, 10, 6, 11, 11, 9, 7, 5, 10, 12, 24, 6, 1, 10, 1, 1, 2, 10, 6, 22, 1, 4, 18, 4, 14, 1, 11, 17, 10, 11, 18, 11, 4, 8, 11, 1, 11, 4, 12, 8, 11, 5, 15, 12, 1, 10, 1, 11, 10, 2, 4, 18, 6, 14, 11, 15, 18, 1, 12, 24, 11, 17, 5, 6, 18, 5, 6, 11, 14, 1, 1, 11, 5, 12, 4, 5, 1, 6, 1, 14, 9, 12, 4, 1, 6, 6, 6, 5, 24, 4, 1, 1, 16, 9, 24, 1, 15, 4, 4, 11, 8, 1, 12, 4, 2, 7, 4, 5, 1, 4, 5, 5, 1, 9, 18, 11, 6, 6, 1, 10, 4, 7, 1, 6, 5, 9, 1, 1, 9, 11, 5, 11, 5, 11, 11, 1, 4, 6, 10, 1, 4, 1, 2, 16, 18, 1, 9, 12, 8, 10, 1, 1, 4, 12, 1, 14, 11, 1, 11, 1, 5, 17, 8, 14, 1, 17, 4, 14, 1, 18, 7, 17, 4, 6, 6, 7, 1, 11, 12, 1, 11, 12, 10, 6, 4, 11, 6, 11, 9, 1, 4, 6, 11, 11, 5, 12, 5, 1, 7, 12, 11, 5, 14, 24, 5, 11, 12, 1, 18, 7, 7, 11, 16, 11, 17, 2, 18, 4, 1, 1, 14, 5, 1, 2, 5, 10, 15, 24, 11, 17, 1, 1, 6, 8, 6, 11, 10, 7, 11, 1, 15, 14, 4, 24, 6, 1, 8, 9, 15, 15, 1, 4, 7, 8, 1, 12, 17, 5, 4, 1, 15, 1, 1, 8, 10, 12, 15, 10, 6, 5, 14, 5, 4, 6, 1, 5, 1, 9, 11, 1, 12, 6, 12, 15, 16, 8, 2, 5, 2, 1, 12, 1, 9, 12, 11, 4, 18, 7, 10, 15, 4, 11, 11, 10, 1, 7, 17, 17, 10, 6, 7, 11, 6, 12, 1, 17, 1, 1, 11, 18, 18, 15, 5, 6, 16, 1, 10, 24, 18, 6, 10, 17, 10, 9, 14, 17, 18, 14, 8, 9, 9, 1, 11, 5, 11, 11, 17, 14, 6, 1, 2, 16, 9, 7, 15, 9, 7, 6, 11, 18, 24, 7, 2, 6, 1, 9, 1, 11, 15, 1, 11, 5, 1, 1, 15, 15, 17, 11, 1, 2, 9, 17, 14, 1, 7, 7, 11, 1, 12, 18, 4, 1, 11, 5, 10, 12, 12, 11, 6, 11, 4, 1, 18, 7, 16, 1, 5, 12, 17, 4, 14, 10, 5, 1, 5, 10, 11, 15, 14, 6, 1, 18, 4, 12, 5, 15, 15, 9, 2, 12, 4, 5, 15, 1, 2, 14, 2, 6, 6, 11, 10, 9, 17, 11, 1, 17, 18, 12, 11, 6, 6, 1, 1, 11, 1, 11, 1, 1, 4, 24, 11, 1, 9, 7, 8, 5, 11, 7, 7, 6, 14, 11, 14, 8, 14, 1, 14, 6, 24, 12, 17, 12, 4, 4, 4, 1, 6, 1, 3, 6, 18, 24, 11, 12, 11, 4, 1, 18, 1, 11, 11, 6, 8, 4, 7, 11, 9, 18, 4, 5, 9, 17, 18, 11, 6, 5, 1, 1, 1, 10, 12, 2, 1, 6, 1, 4, 11, 11, 12, 17, 18, 15, 12, 16, 16, 10, 1, 10, 11, 1, 4, 11, 11, 11, 4, 1, 1, 4, 1, 4, 18, 1, 1, 5, 1, 6, 4, 23, 4, 12, 1, 24, 16, 10, 11, 5, 1, 8, 9, 1, 4, 11, 4, 5, 9, 8, 5, 18, 1, 12, 6, 1, 12, 1]\n" ] } ], "source": [ "# Afficher les valeurs de y_true_global et y_pred_global\n", "print(\"y_true_global2:\", y_true_global2)\n", "print(\"y_pred_global2:\", y_pred_global2)" ] }, { "cell_type": "code", "execution_count": 169, "id": "fcd1d9ad", "metadata": {}, "outputs": [], "source": [ "y_true2 = y_true_global2\n", "y_pred2 = y_pred_global2" ] }, { "cell_type": "markdown", "id": "99131664", "metadata": {}, "source": [ "# Evaluation du modèle 2 : Classification report" ] }, { "cell_type": "code", "execution_count": 170, "id": "6c55a4dc", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " Incohérence des données 0.00 0.00 0.00 21\n", " Questions ou remarques d'usagers 0.91 0.92 0.91 284\n", " Commentaire sans valeur 0.73 0.65 0.69 51\n", " Erreur d'actualisation 0.00 0.00 0.00 11\n", " Absence de mise à jour 0.79 0.77 0.78 148\n", " Erreur dans les données fournies 0.70 0.89 0.78 85\n", " Lien mort 0.82 0.82 0.82 119\n", " Format incompatible 0.42 0.50 0.46 42\n", " Information des réutilisateurs 0.64 0.68 0.66 41\n", " Absence de description des variables 0.57 1.00 0.73 54\n", " Absence de données 0.64 0.80 0.71 65\n", " Demande de jeu de données (set) 0.88 0.85 0.87 213\n", "Absence d'information sur les mises à jour 0.59 0.69 0.64 84\n", " Problème d'uniformité dans la saisie 0.00 0.00 0.00 14\n", " Incertitude des données 0.48 0.67 0.56 48\n", " Problème de granularité 0.42 0.91 0.58 23\n", " Proposition de mots-clefs 0.97 0.97 0.97 31\n", " Incapacité à traiter les données 0.54 0.43 0.48 77\n", " Formatage non respecté 0.69 0.90 0.78 49\n", "Source des données incorrecte ou imprécise 0.00 0.00 0.00 8\n", " Descriptions imprécises 0.00 0.00 0.00 40\n", " Données non-ouvertes 0.00 0.00 0.00 10\n", " Répétition des données 0.00 0.00 0.00 11\n", " Demande de correction 0.67 0.12 0.20 17\n", " Message automatique 0.97 0.97 0.97 36\n", " Harmonisation des données 0.00 0.00 0.00 8\n", "\n", " accuracy 0.74 1590\n", " macro avg 0.48 0.52 0.48 1590\n", " weighted avg 0.70 0.74 0.71 1590\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "/home/asma/miniconda3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n" ] } ], "source": [ "# Générer le rapport de classification\n", "report2 = classification_report(y_true2, y_pred2, target_names=sslabels)\n", "#report2 = classification_report(y_true2, y_pred2)\n", "\n", "# Afficher le rapport de classification\n", "print(report2)" ] }, { "cell_type": "markdown", "id": "fd9e0d48", "metadata": {}, "source": [ "# Evaluation du modèle 2 : Matrice de confusion" ] }, { "cell_type": "code", "execution_count": 171, "id": "e5a83aa7", "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Calculer la matrice de confusion\n", "confusion_mat = confusion_matrix(y_true2, y_pred2)\n", "\n", "# Obtenir les noms des classes à partir des identifiants de label\n", "class_names = [id2sslabel[i] for i in range(len(sslabels))]\n", "\n", "# Normaliser la matrice de confusion pour afficher les pourcentages\n", "confusion_mat_norm = confusion_mat.astype('float') / confusion_mat.sum(axis=1)[:, np.newaxis]\n", "\n", "# Créer une figure\n", "plt.figure(figsize=(15, 10))\n", "\n", "# Tracer la matrice de confusion\n", "sns.heatmap(confusion_mat_norm, annot=True, fmt=\".2f\", cmap=\"Blues\", xticklabels=class_names, yticklabels=class_names)\n", "\n", "# Ajouter des étiquettes aux axes\n", "plt.xlabel(\"Prédictions\")\n", "plt.ylabel(\"Vraies étiquettes\")\n", "\n", "# Ajouter un titre\n", "plt.title(\"Matrice de confusion\")\n", "\n", "plt.savefig('Matrice de confusion2.png')\n", "#files.download('Matrice de confusion2.png')\n", "\n", "# Afficher la figure\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "633e62f7", "metadata": {}, "source": [ "# Enregistrement des fichiers de poids et d'entrainement du modele 2 (zippé)" ] }, { "cell_type": "code", "execution_count": 172, "id": "5f7faf5f", "metadata": {}, "outputs": [], "source": [ "# Enregistrement des fichiers de poids (zippé)\n", "\n", "#import shutil\n", "#import zipfile\n", "\n", "# Chemin de destination pour enregistrer le modèle\n", "model_directory2 = \"bert-finetuned-my-data-final2\"\n", "\n", "# Sauvegarder le modèle avec les fichiers de poids\n", "trainer2.save_model(model_directory2)\n", "# Sauvegarder le tokenizer\n", "tokenizer2.save_pretrained(model_directory2)\n", "\n", "# Compresser le dossier au format .zip\n", "shutil.make_archive(model_directory2 + \"_archive2\", 'zip', model_directory2)\n", "\n", "# Chemin de destination pour le fichier .zip\n", "zip_file_path2 = model_directory2 + \"_archive2.zip\"\n", "\n", "# Télécharger le fichier .zip\n", "#files.download(zip_file_path2)" ] }, { "cell_type": "markdown", "id": "e063198b", "metadata": {}, "source": [ "# Charger le modele 2 pré-entrainé (zippé)" ] }, { "cell_type": "code", "execution_count": 173, "id": "a6a90625", "metadata": {}, "outputs": [], "source": [ "# Chargement du modèle 2 (zippé)\n", "\n", "# Extraire le contenu du fichier .zip dans un répertoire temporaire\n", "zip_file_path2 = \"bert-finetuned-my-data-final2_archive2.zip\"\n", "extract_dir2 = \"extracted_model2\"\n", "with zipfile.ZipFile(zip_file_path2, 'r') as zip_ref:\n", " zip_ref.extractall(extract_dir2)\n", "\n", "# Charger le modèle à partir du répertoire extrait\n", "model_saved2 = AutoModelForSequenceClassification.from_pretrained(extract_dir2)\n", "\n", "# Charger le tokenizer à partir du même répertoire extrait\n", "tokenizer_saved2 = AutoTokenizer.from_pretrained(extract_dir2)\n" ] }, { "cell_type": "code", "execution_count": 174, "id": "0913e5b0", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'# Enregistrer le modèle pré-entrainé (non zippé)\\n\\n# Chemin de destination pour enregistrer le modèle et le tokenizer\\noutput_dir2 = \"modeleBertSaved2\"\\n\\n# Enregistrer le modèle\\nmodel2.save_pretrained(output_dir2)\\n\\n# Enregistrer le tokenizer\\ntokenizer2.save_pretrained(output_dir2)\\n'" ] }, "execution_count": 174, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"# Enregistrer le modèle pré-entrainé (non zippé)\n", "\n", "# Chemin de destination pour enregistrer le modèle et le tokenizer\n", "output_dir2 = \"modeleBertSaved2\"\n", "\n", "# Enregistrer le modèle\n", "model2.save_pretrained(output_dir2)\n", "\n", "# Enregistrer le tokenizer\n", "tokenizer2.save_pretrained(output_dir2)\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 175, "id": "69a57c7d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'# Charger le modèle à partir du dossier sauvegardé (non zippé)\\nmodel_saved2 = AutoModelForSequenceClassification.from_pretrained(output_dir2)\\n\\n# Charger le tokenizer à partir du dossier sauvegardé\\ntokenizer_saved2 = AutoTokenizer.from_pretrained(output_dir2)\\n'" ] }, "execution_count": 175, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\"\"\"# Charger le modèle à partir du dossier sauvegardé (non zippé)\n", "model_saved2 = AutoModelForSequenceClassification.from_pretrained(output_dir2)\n", "\n", "# Charger le tokenizer à partir du dossier sauvegardé\n", "tokenizer_saved2 = AutoTokenizer.from_pretrained(output_dir2)\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 176, "id": "f6e052c5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Texte : Problème avec le lien, je n'arrive pas à accéder à la page\n", "Sous-label prédit : 6\n", "\n", "\n", "Nom du label prédit : Lien mort\n" ] } ], "source": [ "# Prétraitement des nouvelles données\n", "new_data = [\"Problème avec le lien, je n'arrive pas à accéder à la page\"]\n", "\n", "encoded_inputs2 = tokenizer_saved2(new_data, truncation=True, padding=True, return_tensors=\"pt\")\n", "\n", "# Passage des données dans le modèle pour l'inférence\n", "with torch.no_grad():\n", " outputs2 = model_saved2(**encoded_inputs2)\n", "\n", "# Récupération des prédictions\n", "predictions2 = outputs2.logits\n", "predicted_labels2 = torch.argmax(predictions2, dim=1)\n", "\n", "# Affichage des résultats\n", "for text2, sslabel2 in zip(new_data, predicted_labels2):\n", " print(f\"Texte : {text2}\")\n", " print(f\"Sous-label prédit : {sslabel2}\")\n", " print(type(sslabel2))\n", " sslabel2 = sslabel2.item()\n", " print(type(sslabel2))\n", " print(f\"Nom du label prédit : {id2sslabel[sslabel2]}\")" ] }, { "cell_type": "markdown", "id": "4a78ec8c", "metadata": {}, "source": [ "# Inférence du modèle 2 avec les données du MEFSIN" ] }, { "cell_type": "code", "execution_count": 178, "id": "3ce511f9", "metadata": {}, "outputs": [], "source": [ "# On récupère la prédiction précédente (modèle 1 grands motifs)\n", "\n", "df_MEFSIN['combined_text2'] = df_MEFSIN['predictions_motifs_label'] + ' ' + df_MEFSIN['predictions_motifs_label'] + ' ' + df_MEFSIN['predictions_motifs_label'] + ' ' + df_MEFSIN['title'] + ' ' + df_MEFSIN['messages']\n" ] }, { "cell_type": "code", "execution_count": 179, "id": "8a29463a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "id 6418839138db635b9a8ec61a\n", "user Christophe BADOL\n", "subject Parcellaire Express (PCI)\n", "title Disparition de la table arrondissement de la l...\n", "size 2\n", "messages Bonjour,\\n\\nla table arrondissement a disparu ...\n", "created 2023-03-20T17:02:25.636000\n", "closed NaN\n", "closed_by NaN\n", "MEFSIN 1\n", "combined_text Disparition de la table arrondissement de la l...\n", "predictions_motifs 2\n", "predictions_motifs_label Actualisation\n", "combined_text2 Actualisation Actualisation Actualisation Disp...\n", "Name: 0, dtype: object" ] }, "execution_count": 179, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_MEFSIN.iloc[0]" ] }, { "cell_type": "code", "execution_count": 180, "id": "34427825", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Actualisation Actualisation Actualisation Disparition de la table arrondissement de la livraison 2023 Bonjour,\\n\\nla table arrondissement a disparu de la livraison au 1er janvier 2023. Sait-on pourquoi ?\\nLa classe ARRONDISSEMENT nÄ\\x86ÂḃÄ\\x81â\\x80\\x9aÂỲÄ\\x81â\\x80\\x9eÂḃest prÄ\\x86'" ] }, "execution_count": 180, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_MEFSIN.loc[0, \"combined_text2\"]" ] }, { "cell_type": "code", "execution_count": 181, "id": "a9781bf7", "metadata": {}, "outputs": [], "source": [ "#Sélection des features (X) à utiliser pour l'inférence\n", "#features = df_MEFSIN[\"messages\"]\n", "features = df_MEFSIN[\"combined_text2\"]" ] }, { "cell_type": "code", "execution_count": 182, "id": "0fe2def6", "metadata": {}, "outputs": [], "source": [ "# Prétraitement des données de la colonne \"messages\"\n", "messages = features.tolist()\n", "\n", "# Créer une liste pour stocker les prédictions\n", "predictions2 = []\n", "\n", "# Définir la taille du batch d'inférence\n", "batch_size = 8\n", "\n", "# Diviser les données en lots plus petits\n", "num_batches = len(messages) // batch_size\n", "if len(messages) % batch_size != 0:\n", " num_batches += 1\n", "\n", "# Mettre le modèle en mode évaluation\n", "model_saved2.eval()\n", "\n", "# Parcourir les lots et effectuer l'inférence\n", "for i in range(num_batches):\n", " # Sélectionner les textes du lot actuel\n", " batch_texts = messages[i*batch_size:(i+1)*batch_size]\n", "\n", " # Convertir les textes en tenseurs PyTorch\n", " encoded_inputs2 = tokenizer_saved2.batch_encode_plus(batch_texts, truncation=True, padding=True, max_length=128, return_tensors=\"pt\")\n", "\n", " # Passage des données dans le modèle pour l'inférence\n", " with torch.no_grad():\n", " outputs2 = model_saved2(**encoded_inputs2)\n", "\n", " # Récupération des prédictions\n", " predicted_sslabels = torch.argmax(outputs2.logits, dim=1)\n", "\n", " # Ajouter les prédictions à la liste des résultats\n", " predictions2.extend(predicted_sslabels.tolist())\n", "\n", "# Ajouter la liste des prédictions comme une nouvelle colonne \"res_motifs\" au DataFrame\n", "#df_MEFSIN['res_motifs'] = id2label[predictions]\n", "df_MEFSIN['predictions_ssmotifs'] = predictions2\n", "df_MEFSIN['predictions_ssmotifs_label'] = [id2sslabel[prediction] for prediction in predictions2]\n" ] }, { "cell_type": "code", "execution_count": 183, "id": "0b50e9e6", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idusersubjecttitlesizemessagescreatedclosedclosed_byMEFSINcombined_textpredictions_motifspredictions_motifs_labelcombined_text2predictions_ssmotifspredictions_ssmotifs_label
06418839138db635b9a8ec61aChristophe BADOLParcellaire Express (PCI)Disparition de la table arrondissement de la l...2Bonjour,\\n\\nla table arrondissement a disparu ...2023-03-20T17:02:25.636000NaNNaN1Disparition de la table arrondissement de la l...2ActualisationActualisation Actualisation Actualisation Disp...4Absence de mise à jour
1641861cca4f1971589503cb9Estelle CrĆFichiers des locaux et des parcelles des perso...Siren cessĆ1Bonjour, Pourquoi y a-t-il des Siren dont l'Ć2023-03-20T14:38:20.353000NaNNaN1Siren cessĆ Bonjour, Pourquoi y a-t-il des Si...1AutreAutre Autre Autre Siren cessĆ Bonjour, Pourqu...2Commentaire sans valeur
26413358dcce10824f53a9bc9Camille BaconDemandes de valeurs fonciĆ1 idloc = 1 local1Bonjour,\\n\\nTout d'abord, merci pour ces donnĆ2023-03-16T16:28:13.300000NaNNaN11 idloc = 1 local Bonjour,\\n\\nTout d'abord, me...1AutreAutre Autre Autre 1 idloc = 1 local Bonjour,\\n...2Commentaire sans valeur
364088027de783a9eadb04349JĆPrix des carburants en France - Flux instantanĆDate d'obsolescence de ce jeu de donnĆ1Bonjour, la description du jeu de donnĆ2023-03-08T13:31:35.125000NaNNaN1Date d'obsolescence de ce jeu de donnĆ Bonjou...2ActualisationActualisation Actualisation Actualisation Date...12Absence d'information sur les mises à jour
4640869f8abc8970cefa9c3d4Anne SolazL'impĆliens non focntionnels1Bonjour, Je n'arrive pas Ć2023-03-08T11:56:56.125000NaNNaN1liens non focntionnels Bonjour, Je n'arrive pa...3AccessibilitéAccessibilité Accessibilité Accessibilité lien...6Lien mort
56408538a96433266c124be61Pierre L'HostisDonnĆPlateforme non indiquĆ1Bonjour,\\n\\nPourriez-vous me dire si les donnĆ2023-03-08T10:21:14.949000NaNNaN1Plateforme non indiquĆ Bonjour,\\n\\nPourriez-v...3AccessibilitéAccessibilité Accessibilité Accessibilité Plat...17Incapacité à traiter les données
663fe2b9c047052abef06bfc1Corinne BCDRĆDonnĆ1Bonjour\\nMa collectivitĆ2023-02-28T17:28:12.244000NaNNaN1DonnĆ Bonjour\\nMa collectivitĆ1AutreAutre Autre Autre DonnĆ Bonjour\\nMa collectiv...2Commentaire sans valeur
763f62c2468b60c13e99ab53cClaude LerouxDemandes de valeurs fonciĆparcelle BT2 - commune de CarriĆ1Bonjour,\\nje vous contacte car je souhaiterais...2023-02-22T15:52:20.774000NaNNaN1parcelle BT2 - commune de CarriĆ Bonjour,\\nje...1AutreAutre Autre Autre parcelle BT2 - commune de Ca...1Questions ou remarques d'usagers
863e5e3174f42fe618e57ad7bIliyan PetrovRĆLien vers le flux1Bonjour,\\nJ'ai quelques questions de base sur ...2023-02-10T07:24:23.623000NaNNaN1Lien vers le flux Bonjour,\\nJ'ai quelques ques...1AutreAutre Autre Autre Lien vers le flux Bonjour,\\n...2Commentaire sans valeur
963e354bd89059f1ad24d03f4BĆDonnĆImpossible de trouver nos donnĆ2Bonjour,\\nNos donnĆ2023-02-08T08:52:29.253000NaNNaN1Impossible de trouver nos donnĆ Bonjour,\\nNos...3AccessibilitéAccessibilité Accessibilité Accessibilité Impo...6Lien mort
\n", "
" ], "text/plain": [ " id user \\\n", "0 6418839138db635b9a8ec61a Christophe BADOL \n", "1 641861cca4f1971589503cb9 Estelle CrĆ \n", "2 6413358dcce10824f53a9bc9 Camille Bacon \n", "3 64088027de783a9eadb04349 JĆ \n", "4 640869f8abc8970cefa9c3d4 Anne Solaz \n", "5 6408538a96433266c124be61 Pierre L'Hostis \n", "6 63fe2b9c047052abef06bfc1 Corinne BCD \n", "7 63f62c2468b60c13e99ab53c Claude Leroux \n", "8 63e5e3174f42fe618e57ad7b Iliyan Petrov \n", "9 63e354bd89059f1ad24d03f4 BĆ \n", "\n", " subject \\\n", "0 Parcellaire Express (PCI) \n", "1 Fichiers des locaux et des parcelles des perso... \n", "2 Demandes de valeurs fonciĆ \n", "3 Prix des carburants en France - Flux instantanĆ \n", "4 L'impĆ \n", "5 DonnĆ \n", "6 RĆ \n", "7 Demandes de valeurs fonciĆ \n", "8 RĆ \n", "9 DonnĆ \n", "\n", " title size \\\n", "0 Disparition de la table arrondissement de la l... 2 \n", "1 Siren cessĆ 1 \n", "2 1 idloc = 1 local 1 \n", "3 Date d'obsolescence de ce jeu de donnĆ 1 \n", "4 liens non focntionnels 1 \n", "5 Plateforme non indiquĆ 1 \n", "6 DonnĆ 1 \n", "7 parcelle BT2 - commune de CarriĆ 1 \n", "8 Lien vers le flux 1 \n", "9 Impossible de trouver nos donnĆ 2 \n", "\n", " messages \\\n", "0 Bonjour,\\n\\nla table arrondissement a disparu ... \n", "1 Bonjour, Pourquoi y a-t-il des Siren dont l'Ć \n", "2 Bonjour,\\n\\nTout d'abord, merci pour ces donnĆ \n", "3 Bonjour, la description du jeu de donnĆ \n", "4 Bonjour, Je n'arrive pas Ć \n", "5 Bonjour,\\n\\nPourriez-vous me dire si les donnĆ \n", "6 Bonjour\\nMa collectivitĆ \n", "7 Bonjour,\\nje vous contacte car je souhaiterais... \n", "8 Bonjour,\\nJ'ai quelques questions de base sur ... \n", "9 Bonjour,\\nNos donnĆ \n", "\n", " created closed closed_by MEFSIN \\\n", "0 2023-03-20T17:02:25.636000 NaN NaN 1 \n", "1 2023-03-20T14:38:20.353000 NaN NaN 1 \n", "2 2023-03-16T16:28:13.300000 NaN NaN 1 \n", "3 2023-03-08T13:31:35.125000 NaN NaN 1 \n", "4 2023-03-08T11:56:56.125000 NaN NaN 1 \n", "5 2023-03-08T10:21:14.949000 NaN NaN 1 \n", "6 2023-02-28T17:28:12.244000 NaN NaN 1 \n", "7 2023-02-22T15:52:20.774000 NaN NaN 1 \n", "8 2023-02-10T07:24:23.623000 NaN NaN 1 \n", "9 2023-02-08T08:52:29.253000 NaN NaN 1 \n", "\n", " combined_text predictions_motifs \\\n", "0 Disparition de la table arrondissement de la l... 2 \n", "1 Siren cessĆ Bonjour, Pourquoi y a-t-il des Si... 1 \n", "2 1 idloc = 1 local Bonjour,\\n\\nTout d'abord, me... 1 \n", "3 Date d'obsolescence de ce jeu de donnĆ Bonjou... 2 \n", "4 liens non focntionnels Bonjour, Je n'arrive pa... 3 \n", "5 Plateforme non indiquĆ Bonjour,\\n\\nPourriez-v... 3 \n", "6 DonnĆ Bonjour\\nMa collectivitĆ 1 \n", "7 parcelle BT2 - commune de CarriĆ Bonjour,\\nje... 1 \n", "8 Lien vers le flux Bonjour,\\nJ'ai quelques ques... 1 \n", "9 Impossible de trouver nos donnĆ Bonjour,\\nNos... 3 \n", "\n", " predictions_motifs_label combined_text2 \\\n", "0 Actualisation Actualisation Actualisation Actualisation Disp... \n", "1 Autre Autre Autre Autre Siren cessĆ Bonjour, Pourqu... \n", "2 Autre Autre Autre Autre 1 idloc = 1 local Bonjour,\\n... \n", "3 Actualisation Actualisation Actualisation Actualisation Date... \n", "4 Accessibilité Accessibilité Accessibilité Accessibilité lien... \n", "5 Accessibilité Accessibilité Accessibilité Accessibilité Plat... \n", "6 Autre Autre Autre Autre DonnĆ Bonjour\\nMa collectiv... \n", "7 Autre Autre Autre Autre parcelle BT2 - commune de Ca... \n", "8 Autre Autre Autre Autre Lien vers le flux Bonjour,\\n... \n", "9 Accessibilité Accessibilité Accessibilité Accessibilité Impo... \n", "\n", " predictions_ssmotifs predictions_ssmotifs_label \n", "0 4 Absence de mise à jour \n", "1 2 Commentaire sans valeur \n", "2 2 Commentaire sans valeur \n", "3 12 Absence d'information sur les mises à jour \n", "4 6 Lien mort \n", "5 17 Incapacité à traiter les données \n", "6 2 Commentaire sans valeur \n", "7 1 Questions ou remarques d'usagers \n", "8 2 Commentaire sans valeur \n", "9 6 Lien mort " ] }, "execution_count": 183, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_MEFSIN.head(10)" ] }, { "cell_type": "markdown", "id": "7debb1d8", "metadata": {}, "source": [ "# Sauvegarde des résultats d'annotations sur les grandes catégories du jeu du MEFSIN" ] }, { "cell_type": "code", "execution_count": 184, "id": "e8fdf38f", "metadata": {}, "outputs": [], "source": [ "# Sauvegarde des résultats d'annotations sur les sous-catégories du jeu du MEFSIN\n", "df_MEFSIN.to_csv('Résultat_Annotations_sous-Motifs.csv', index=False)" ] }, { "cell_type": "code", "execution_count": null, "id": "1715318e", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 5 }