diff --git "a/competition/11_Llama-3_8b_analysis.ipynb" "b/competition/11_Llama-3_8b_analysis.ipynb"
--- "a/competition/11_Llama-3_8b_analysis.ipynb"
+++ "b/competition/11_Llama-3_8b_analysis.ipynb"
@@ -1 +1 @@
-{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"0ea8b46b-839b-445b-8043-ccdf4e920ace","showTitle":false,"title":""},"id":"YLH80COBzi_F"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":2,"metadata":{"id":"63B5exAuzq4M"},"outputs":[],"source":["from pathlib import Path\n","\n","try:\n","    from google.colab import drive\n","    drive.mount('/content/drive')\n","    workding_dir = \"/content/drive/MyDrive/logical-reasoning/\"\n","except ModuleNotFoundError:\n","    workding_dir = str(Path.cwd().parent)"]},{"cell_type":"code","execution_count":3,"metadata":{"executionInfo":{"elapsed":368,"status":"ok","timestamp":1719461634865,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"zFulf0bg0H-9","outputId":"debdd535-c828-40b9-efc0-8a180e5830dd"},"outputs":[{"name":"stdout","output_type":"stream","text":["workding dir: /Users/inflaton/code/engd/projects/logical-reasoning\n"]}],"source":["import os\n","import sys\n","\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"workding dir:\", workding_dir)"]},{"cell_type":"code","execution_count":4,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"9f67ec60-2f24-411c-84eb-0dd664b44775","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":589,"status":"ok","timestamp":1719462011879,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"DIUiweYYzi_I","outputId":"e16e9247-9077-4b0c-f8ea-17059f05a1c4"},"outputs":[{"name":"stdout","output_type":"stream","text":["loading env vars from: /Users/inflaton/code/engd/projects/logical-reasoning/.env.example\n"]},{"data":{"text/plain":["True"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["from dotenv import find_dotenv, load_dotenv\n","\n","found_dotenv = find_dotenv(\".env\")\n","\n","if len(found_dotenv) == 0:\n","    found_dotenv = find_dotenv(\".env.example\")\n","print(f\"loading env vars from: {found_dotenv}\")\n","load_dotenv(found_dotenv, override=True)"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"W2QyVreqhOGM","outputId":"68b9590e-1ac6-4c6f-e0c4-e273ec816419"},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>label</th>\n","      <th>title</th>\n","      <th>puzzle</th>\n","      <th>truth</th>\n","      <th>shenzhi-wang/Llama3-8B-Chinese-Chat</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>甄加索是自杀吗</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是。</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>甄加索有身体上的疾病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是。</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>画作是甄的</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>甄有心脏病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是。</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>车轮是凶手留下的</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是。</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2995</th>\n","      <td>哭泣者必须在晚上祭奠吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是。</td>\n","    </tr>\n","    <tr>\n","      <th>2996</th>\n","      <td>尸体在湖里吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是。</td>\n","    </tr>\n","    <tr>\n","      <th>2997</th>\n","      <td>哭泣者和死者有特殊关系吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是。</td>\n","    </tr>\n","    <tr>\n","      <th>2998</th>\n","      <td>是帽子的主人去世了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2999</th>\n","      <td>死者受伤了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是。</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 6 columns</p>\n","</div>"],"text/plain":["              text label title  \\\n","0          甄加索是自杀吗    不是  海岸之谜   \n","1      甄加索有身体上的疾病吗     是  海岸之谜   \n","2            画作是甄的     是  海岸之谜   \n","3           甄有心脏病吗     是  海岸之谜   \n","4         车轮是凶手留下的    不是  海岸之谜   \n","...            ...   ...   ...   \n","2995   哭泣者必须在晚上祭奠吗     是  甄庄哭声   \n","2996        尸体在湖里吗    不是  甄庄哭声   \n","2997  哭泣者和死者有特殊关系吗     是  甄庄哭声   \n","2998    是帽子的主人去世了吗    不是  甄庄哭声   \n","2999        死者受伤了吗    不是  甄庄哭声   \n","\n","                                                 puzzle  \\\n","0     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","1     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","2     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","3     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","4     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","...                                                 ...   \n","2995  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2996  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2997  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2998  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2999  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","\n","                                                  truth  \\\n","0     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","1     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","2     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","3     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","4     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","...                                                 ...   \n","2995  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2996  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2997  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2998  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2999  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","\n","     shenzhi-wang/Llama3-8B-Chinese-Chat  \n","0                                    不是。  \n","1                                     是。  \n","2                                      是  \n","3                                     是。  \n","4                                    不是。  \n","...                                  ...  \n","2995                                 不是。  \n","2996                                 不是。  \n","2997                                  是。  \n","2998                                   是  \n","2999                                 不是。  \n","\n","[3000 rows x 6 columns]"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/llama3-8b_lora_sft_bf16-p1.csv\")\n","df"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","def plot_value_counts(df, column):\n","    font_family = rcParams[\"font.family\"]\n","    # Set the font to SimHei to support Chinese characters\n","    rcParams[\"font.family\"] = \"STHeiti\"\n","    rcParams[\"axes.unicode_minus\"] = False  # This is to support the minus sign in Chinese.\n","\n","    plt.figure(figsize=(12, 6))\n","    df[column].value_counts().plot(kind=\"bar\")\n","    # add values on top of bars\n","    for i, v in enumerate(df[column].value_counts()):\n","        plt.text(i, v + 0.1, str(v), ha=\"center\")\n","    plt.show()\n","    \n","    rcParams[\"font.family\"] = font_family\n"]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[{"data":{"text/plain":["['text',\n"," 'label',\n"," 'title',\n"," 'puzzle',\n"," 'truth',\n"," 'shenzhi-wang/Llama3-8B-Chinese-Chat']"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["df.columns.to_list()"]},{"cell_type":"code","execution_count":8,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat\n","不是。                            1624\n","是。                              876\n","是                               473\n","不重要。                             11\n","小男孩。                              2\n","小男孩放的。                            2\n","问法错误。                             2\n","不是                                1\n","他要带走的是物品。                         1\n","小男孩的哭声。                           1\n","小男孩和他的爷爷。                         1\n","小男孩是湖边的孩子。                        1\n","是男。                               1\n","小男孩把帽子放在湖边是希望能让爷爷的在天之灵得到安慰。       1\n","破旧。                               1\n","是小男孩。                             1\n","破旧帽子是小男孩的。                        1\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["for col in df.columns[5:]:\n","    print(\"*\" * 10, col, \"*\" * 10)\n","    print(df[col].value_counts())\n","    plot_value_counts(df, col)"]},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[],"source":["import re\n","\n","\n","def clean_up(df, model_name):\n","    df[model_name] = df[model_name].apply(\n","        lambda x: re.sub(r\"回答.*是\", \"是\", x)\n","        .replace(\"是男孩\", \"是\")\n","        .replace(\"。\", \"\")\n","        .strip()\n","    )\n","    return df"]},{"cell_type":"code","execution_count":10,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat\n","不是                            1625\n","是                             1349\n","不重要                             11\n","问法错误                             2\n","小男孩                              2\n","小男孩放的                            2\n","他要带走的是物品                         1\n","小男孩的哭声                           1\n","小男孩和他的爷爷                         1\n","小男孩是湖边的孩子                        1\n","是男                               1\n","小男孩把帽子放在湖边是希望能让爷爷的在天之灵得到安慰       1\n","破旧                               1\n","是小男孩                             1\n","破旧帽子是小男孩的                        1\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["for col in df.columns[5:]:\n","    df = clean_up(df, col)\n","    print(\"*\" * 10, col, \"*\" * 10)\n","    print(df[col].value_counts())\n","    plot_value_counts(df, col)"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n","\n","\n","def calc_metrics_for_col(df, col):\n","    y_true = df[\"label\"]\n","    y_pred = df[col]\n","\n","    accuracy = accuracy_score(y_true, y_pred)\n","    precision = precision_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    recall = recall_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    f1 = f1_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","\n","    return accuracy, float(precision), float(recall), float(f1)"]},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/Users/inflaton/anaconda3/envs/llm-finetuning/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1517: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n","/var/folders/7x/56svhln929zdh2xhr3mwqg4r0000gn/T/ipykernel_26910/961288552.py:9: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n","  perf_df = pd.concat([perf_df, pd.DataFrame([new_model_metrics])], ignore_index=True)\n"]},{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>epoch</th>\n","      <th>model</th>\n","      <th>accuracy</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","      <th>f1</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat</td>\n","      <td>0.785333</td>\n","      <td>0.770106</td>\n","      <td>0.794604</td>\n","      <td>0.769681</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  epoch                                model  accuracy  precision    recall  \\\n","0     0  shenzhi-wang/Llama3-8B-Chinese-Chat  0.785333   0.770106  0.794604   \n","\n","         f1  \n","0  0.769681  "]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","perf_df = pd.DataFrame(columns=[\"epoch\", \"model\", \"accuracy\", \"precision\", \"recall\", \"f1\"])\n","for i, col in enumerate(df.columns[5:]):\n","    accuracy, precision, recall, f1 = calc_metrics_for_col(df, col)\n","    new_model_metrics = {\"epoch\": i, \"model\": col, \"accuracy\": accuracy, \"precision\": precision, \"recall\": recall, \"f1\": f1}\n","\n","    # Convert the dictionary to a DataFrame and concatenate it with the existing DataFrame\n","    perf_df = pd.concat([perf_df, pd.DataFrame([new_model_metrics])], ignore_index=True)\n","\n","perf_df"]},{"cell_type":"code","execution_count":14,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1200x500 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# plot metrics for each model\n","import matplotlib.pyplot as plt\n","\n","fig, ax = plt.subplots(1, 1, figsize=(12, 5))\n","\n","perf_df.plot(x=\"epoch\", y=[\"accuracy\", \"precision\", \"recall\", \"f1\"], kind=\"bar\", ax=ax)\n","\n","# add values on top of bars\n","for p in ax.patches:\n","    ax.annotate(\n","        f\"{p.get_height():.3f}\",\n","        (p.get_x() + p.get_width() / 2, p.get_height()),\n","        ha=\"center\",\n","        va=\"bottom\",\n","        fontsize=10,\n","    )\n","\n","# add title and labels\n","# ax.set_title(\"Metrics for different settings\")\n","# ax.set_ylabel(\"Value\")\n","ax.set_xlabel(\"Epoch (0: base model, 1-3: fine-tuned models)\")\n","# rotate x labels\n","plt.xticks(rotation=0)\n","\n","# set legend at the right to avoid overlapping with bars\n","plt.legend(loc=\"center left\", bbox_to_anchor=(1.0, 0.5))\n","# plt.tight_layout()\n","\n","plt.show()"]},{"cell_type":"code","execution_count":14,"metadata":{},"outputs":[],"source":["perf_df.to_csv(\"results/mgtv-results_p2_full_metrics.csv\", index=False)"]}],"metadata":{"accelerator":"GPU","application/vnd.databricks.v1+notebook":{"dashboards":[],"environmentMetadata":null,"language":"python","notebookMetadata":{"pythonIndentUnit":4},"notebookName":"07_MAC_+_Qwen2-7B-Instructi_Unsloth_train","widgets":{}},"colab":{"gpuType":"T4","provenance":[]},"kernelspec":{"display_name":"Python 3","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":"3.11.9"}},"nbformat":4,"nbformat_minor":0}
+{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"0ea8b46b-839b-445b-8043-ccdf4e920ace","showTitle":false,"title":""},"id":"YLH80COBzi_F"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":2,"metadata":{"id":"63B5exAuzq4M"},"outputs":[],"source":["from pathlib import Path\n","\n","try:\n","    from google.colab import drive\n","    drive.mount('/content/drive')\n","    workding_dir = \"/content/drive/MyDrive/logical-reasoning/\"\n","except ModuleNotFoundError:\n","    workding_dir = str(Path.cwd().parent)"]},{"cell_type":"code","execution_count":3,"metadata":{"executionInfo":{"elapsed":368,"status":"ok","timestamp":1719461634865,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"zFulf0bg0H-9","outputId":"debdd535-c828-40b9-efc0-8a180e5830dd"},"outputs":[{"name":"stdout","output_type":"stream","text":["workding dir: /Users/inflaton/code/engd/projects/logical-reasoning\n"]}],"source":["import os\n","import sys\n","\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"workding dir:\", workding_dir)"]},{"cell_type":"code","execution_count":4,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{},"inputWidgets":{},"nuid":"9f67ec60-2f24-411c-84eb-0dd664b44775","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":589,"status":"ok","timestamp":1719462011879,"user":{"displayName":"Donghao Huang","userId":"00463591218503521679"},"user_tz":-480},"id":"DIUiweYYzi_I","outputId":"e16e9247-9077-4b0c-f8ea-17059f05a1c4"},"outputs":[{"name":"stdout","output_type":"stream","text":["loading env vars from: /Users/inflaton/code/engd/projects/logical-reasoning/.env.example\n"]},{"data":{"text/plain":["True"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["from dotenv import find_dotenv, load_dotenv\n","\n","found_dotenv = find_dotenv(\".env\")\n","\n","if len(found_dotenv) == 0:\n","    found_dotenv = find_dotenv(\".env.example\")\n","print(f\"loading env vars from: {found_dotenv}\")\n","load_dotenv(found_dotenv, override=True)"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"W2QyVreqhOGM","outputId":"68b9590e-1ac6-4c6f-e0c4-e273ec816419"},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>label</th>\n","      <th>title</th>\n","      <th>puzzle</th>\n","      <th>truth</th>\n","      <th>shenzhi-wang/Llama3-8B-Chinese-Chat</th>\n","      <th>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-175</th>\n","      <th>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-350</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>甄加索是自杀吗</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是。</td>\n","      <td>不是</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>甄加索有身体上的疾病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是。</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>画作是甄的</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>��远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是</td>\n","      <td>问法错误</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>甄有心脏病吗</td>\n","      <td>是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>是。</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>车轮是凶手留下的</td>\n","      <td>不是</td>\n","      <td>海岸之谜</td>\n","      <td>在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...</td>\n","      <td>甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...</td>\n","      <td>不是。</td>\n","      <td>问法错误</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2995</th>\n","      <td>哭泣者必须在晚上祭奠吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是。</td>\n","      <td>不重要</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2996</th>\n","      <td>尸体在湖里吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是。</td>\n","      <td>不重要</td>\n","      <td>不是</td>\n","    </tr>\n","    <tr>\n","      <th>2997</th>\n","      <td>哭泣者和死者有特殊关系吗</td>\n","      <td>是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是。</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2998</th>\n","      <td>是帽子的主人去世了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>是。</td>\n","      <td>是</td>\n","      <td>是</td>\n","    </tr>\n","    <tr>\n","      <th>2999</th>\n","      <td>死者受伤了吗</td>\n","      <td>不是</td>\n","      <td>甄庄哭声</td>\n","      <td>在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...</td>\n","      <td>原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...</td>\n","      <td>不是。</td>\n","      <td>不重要</td>\n","      <td>不重要</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 8 columns</p>\n","</div>"],"text/plain":["              text label title  \\\n","0          甄加索是自杀吗    不是  海岸之谜   \n","1      甄加索有身体上的疾病吗     是  海岸之谜   \n","2            画作是甄的     是  海岸之谜   \n","3           甄有心脏病吗     是  海岸之谜   \n","4         车轮是凶手留下的    不是  海岸之谜   \n","...            ...   ...   ...   \n","2995   哭泣者必须在晚上祭奠吗     是  甄庄哭声   \n","2996        尸体在湖里吗    不是  甄庄哭声   \n","2997  哭泣者和死者有特殊关系吗     是  甄庄哭声   \n","2998    是帽子的主人去世了吗    不是  甄庄哭声   \n","2999        死者受伤了吗    不是  甄庄哭声   \n","\n","                                                 puzzle  \\\n","0     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","1     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","2     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","3     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","4     在远离城市喧嚣的海边小屋，一天清晨，邻居发现甄加索僵卧在沙滩上，已无生命迹象。现场没有发现任...   \n","...                                                 ...   \n","2995  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2996  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2997  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2998  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","2999  在一个安静的夜晚，小村庄的湖边突然传来了阵阵哭泣声。第二天早晨，村长甄锐发现湖边的石头上放着...   \n","\n","                                                  truth  \\\n","0     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","1     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","2     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","3     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","4     甄加索是一位热爱自然的画家，他每年都会来到这个海边小屋寻找灵感。在他生命的最后几天，他一直在...   \n","...                                                 ...   \n","2995  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2996  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2997  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2998  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","2999  原来，这顶破旧的帽子属于一个小男孩，他小时候与爷爷在湖边生活。爷爷教他钓鱼、游泳，还告诉他湖...   \n","\n","     shenzhi-wang/Llama3-8B-Chinese-Chat  \\\n","0                                    不是。   \n","1                                     是。   \n","2                                      是   \n","3                                     是。   \n","4                                    不是。   \n","...                                  ...   \n","2995                                 不是。   \n","2996                                 不是。   \n","2997                                  是。   \n","2998                                  是。   \n","2999                                 不是。   \n","\n","     shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-175  \\\n","0                                                    不是   \n","1                                                     是   \n","2                                                  问法错误   \n","3                                                     是   \n","4                                                  问法错误   \n","...                                                 ...   \n","2995                                                不重要   \n","2996                                                不重要   \n","2997                                                  是   \n","2998                                                  是   \n","2999                                                不重要   \n","\n","     shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-350  \n","0                                                    不是  \n","1                                                     是  \n","2                                                     是  \n","3                                                     是  \n","4                                                    不是  \n","...                                                 ...  \n","2995                                                  是  \n","2996                                                 不是  \n","2997                                                  是  \n","2998                                                  是  \n","2999                                                不重要  \n","\n","[3000 rows x 8 columns]"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/llama3-8b_lora_sft_bf16-p1.csv\")\n","df"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","def plot_value_counts(df, column):\n","    font_family = rcParams[\"font.family\"]\n","    # Set the font to SimHei to support Chinese characters\n","    rcParams[\"font.family\"] = \"STHeiti\"\n","    rcParams[\"axes.unicode_minus\"] = False  # This is to support the minus sign in Chinese.\n","\n","    plt.figure(figsize=(12, 6))\n","    df[column].value_counts().plot(kind=\"bar\")\n","    # add values on top of bars\n","    for i, v in enumerate(df[column].value_counts()):\n","        plt.text(i, v + 0.1, str(v), ha=\"center\")\n","    plt.show()\n","    \n","    rcParams[\"font.family\"] = font_family\n"]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[{"data":{"text/plain":["['text',\n"," 'label',\n"," 'title',\n"," 'puzzle',\n"," 'truth',\n"," 'shenzhi-wang/Llama3-8B-Chinese-Chat',\n"," 'shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-175',\n"," 'shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-350']"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["df.columns.to_list()"]},{"cell_type":"code","execution_count":8,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat\n","不是。           1610\n","是。             989\n","是              375\n","不重要。            12\n","问法错误。            2\n","小男孩。             2\n","小男孩放的。           2\n","他要带走的是物品。        1\n","不是               1\n","小男孩的哭声。          1\n","小男孩和他的爷爷。        1\n","是男。              1\n","破旧。              1\n","是小男孩。            1\n","破旧帽子是小男孩的。       1\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA94AAAKKCAYAAADLBYN+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAACvfklEQVR4nOzdd3hU1f7+/Ts9k0rvQQhNqooUpSlSFZHOUVGQjiJSrAhykCKIvaAIKgiCHqWDNKX8QAQsqIBIEQIkUVoC6ZlMZtbzB0/m6xzisTA7E5L367rmSmatPeSzyGRm37P3XsvPGGMEAAAAAAAs4e/rAgAAAAAAKMoI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWCjQ1wV4i8vl0q+//qrIyEj5+fn5uhwAAAAAQBFnjFFaWpoqVaokf/8/Pq5dZIL3r7/+qpiYGF+XAQAAAAAoZuLj41WlSpU/7C8ywTsyMlLSpQFHRUX5uBoAAAAAQFGXmpqqmJgYdx79I0UmeOedXh4VFUXwBgAAAAAUmD+73JnJ1QAAAAAAsBDBGwAAAAAACxG8AQAAAACwEMEbAAAAAAALEbwBAAAAALAQwRsAAAAAAAsRvP+hJUuW6OjRo74uAwAAAABQyBG889G2bVv5+/vrxRdfzLc/MTFRY8eOVVBQkEf7v//9bwUEBOjOO++87DG//vqrunTporCwMMXGxmrBggVWlA4AAAAAKGQI3vnYunWrJk2a9If9Y8eO1dixY1WtWjWP9meffVabN2/O9zG9evXSddddp6SkJK1atUpTp07Vhg0bvFk2AAAAAKAQInj/TZs3b9bBgwf16KOP/uXH7Nq1SxkZGZo+fbpsNpsaNmyo2bNn67nnnrOwUgAAAABAYUDw/hscDoceeeQRvf3225edZv6/7NixQ3fddZf8/PzcbR06dNCBAweUnZ1tRakAAAAAgEKC4P03vPbaazp27Jj69OmjWrVqadOmTX/pcadOnVLNmjU92gICAlS9enWdPHnSilIBAAAAAIUEwfsvysjI0MyZMzV79mwdO3ZML7zwgvr166fffvvtTx+blZWlsLCwy9ptNpuysrKsKBcAAAAAUEgQvP+iTZs26bbbbtPgwYMVHh6u7t27a8CAAVq0aNGfPtZms+V7SnlSUlK+gRwAAAAAUHQQvP+iX375RQ0aNPBoa9So0V86Vbxq1aqKi4vzaHM4HDp9+rSuueYar9YJAAAAAChcLAveS5Ys0dGjR6365wtclSpVdODAAY+2/fv3q3r16n/62FatWl22dNjGjRt13XXXKSQkxKt1AgAAAAAKl38UvNu2bSt/f3+9+OKL+fYnJiZq7Nixl838PWXKFJUvX15RUVEaNGiQ0tPT3X2pqanq16+fIiIiVKlSJT3//PP/pDTL3HXXXdqzZ4/ee+89ZWZmavXq1VqyZIkGDBjwp49t0aKFJGnGjBnKzs52L0c2YcIEq8sGAAAAAPjYPwreW7du1aRJk/6wf+zYsRo7dqyqVavmbpszZ45Wrlyp3bt3KyEhQX5+fho6dKi7f9iwYQoKClJiYqJ27dqlpUuX6p133vkn5VkiPDxcGzdu1MKFC1WhQgXNnDlTa9euVdmyZf/S45cuXaovv/xSpUqVUpcuXTRhwgR16NDB4qoBAAAAAL7mZ4wx/+SBkydPVkREhB577DGP9s2bN2v06NH6/vvvPY5416lTR0uWLNGNN94o6dI1zjVq1NDWrVsVGhqqxo0b6+TJkwoNDZUk/fzzz7r99tt14sSJv1RPamqqoqOjlZKSoqioqH8yJAAAAAAA/rK/mkMDvflDHQ6HHnnkEc2ZM8cjdJ89e1YZGRnu0C1JQUFBuuuuu7RlyxZFR0erQ4cO7tAtSXXr1lVERISOHj2qWrVqebPMfFV76jPLf8YfOTGzi89+NgAAAADAWl6dXO21117TsWPH1KdPH9WqVUubNm2SJJ06dUo1a9a8bPs6dero+PHjf9oPAAAAAMDVymtHvDMyMjRz5kzNnj1bd999tz7//HP169dP+/btU1ZWVr7rVdtsNmVlZf1pf37sdrvsdrv7fmpqqreGAgAAAACA13jtiPemTZt02223afDgwQoPD1f37t01YMAALVq0SDabTdnZ2Zc9JikpSWFhYX/an58ZM2YoOjrafYuJifHWUAAAAAAA8BqvBe9ffvlFDRo08Ghr1KiRTp48qapVqyouLu6yx8TFxSk2NvZP+/Mzfvx4paSkuG/x8fHeGQgAAAAAAF7kteBdpUoVHThwwKNt//79ql69usqVK6fg4GAdPnzY3Zebm6tVq1apXbt2atmypTZv3qzc3Fx3/4EDB2S32/O99luSQkJCFBUV5XEDAAAAAKCw8Vrwvuuuu7Rnzx699957yszM1OrVq7VkyRINGDBA0qW1vYcMGaKEhASlpaVp1KhRat++vapXr67KlSurRYsWGjt2rNLT0xUfH6+hQ4dq4sSJ3ioPAAAAAACf8FrwDg8P18aNG7Vw4UJVqFBBM2fO1Nq1a1W2bFlJ0ogRI9ShQwc1btxYlStXVk5OjubMmeN+/DvvvKPk5GRVqFBBzZo1U8+ePTV48GBvlQcAAAAAgE/4GWOMr4vwhr+6cPkfYR1vAAAAAMDf8VdzqFfX8QYAAAAAAJ4I3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFjoHwXvtm3byt/fXy+++OIfbuNwOPTMM894tM2dO1dVq1ZVeHi4evTooTNnznhs/8gjj6hkyZIqXbq0Hn/8ceXm5v6T8gAAAAAAKDT+UfDeunWrJk2a9D+3mTRpkr7//nv3/Q0bNui5557T2rVrdf78eTVo0EA9evRw9z/zzDM6cuSIDh06pEOHDungwYOXBXcAAAAAAK42lpxqvnPnTr388sseba+88opeeuklNWrUSDabTVOnTpXL5dKWLVuUk5OjefPmacGCBSpfvrzKli2rhQsX6t1331VGRoYVJQIAAAAAUCC8HrzT09M1YMAAPfbYY+42Y4z27NmjLl26eGzbu3dvbd68WT/88IPq1q2rChUquPtKly6t5s2b66uvvvJ2iQAAAAAAFBivB+/Ro0erS5cu6tChg7stKSlJJUqUUGhoqMe2derU0fHjx3Xq1CnVrFnzsn8rrx8AAAAAgKtVoDf/sVWrVmn37t367rvvtHv3bnd7VlaWwsLCLtveZrMpKyvrT/vzY7fbZbfb3fdTU1O9MAIAAAAAALzLa0e8z549q5EjR+rDDz+87Mi2zWZTdnb2ZY9JSkpSWFjYn/bnZ8aMGYqOjnbfYmJivDMQAAAAAAC8yGtHvB988EGdOXNGN998syTJ5XLJ6XSqQoUK+u2333Tx4kU5HA4FBQW5HxMXF6fY2FhVrVpVcXFxl/2bcXFx6tWrV74/b/z48Ro3bpz7fmpqKuEbAAAAAFDoeO2I97Jly+RwOJSdna3s7Gxt2rRJt99+u06fPi0/Pz81adJEW7Zs8XjM0qVL1b59e11//fU6ePCgLly44O5LTk7Wnj171KJFi3x/XkhIiKKiojxuAAAAAAAUNpYsJ5afcePGacyYMTp06JCys7M1depU2Ww23XrrrQoODtbAgQM1dOhQJSUl6fz58xo0aJAefvjhPzzVHAAAAACAq0GBBe/OnTtrzJgx6tChg0qVKqW9e/dq2bJl7v4pU6aoYsWKqlGjhmrXrq1atWpp8uTJBVUeAAAAAACW8DPGGF8X4Q2pqamKjo5WSkrKPzrtvNpTn1lQ1V9zYmaXP98IAAAAAFCo/NUcWmBHvAEAAAAAKI4I3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIX+UfBu27at/P399eKLL3q0f/nll2revLmioqJ00003affu3R79U6ZMUfny5RUVFaVBgwYpPT3d3Zeamqp+/fopIiJClSpV0vPPP/9PSgMAAAAAoFD5R8F769atmjRpkkfb0aNH1bdvX02fPl1nzpzRE088oe7duyshIUGSNGfOHK1cuVK7d+9WQkKC/Pz8NHToUPfjhw0bpqCgICUmJmrXrl1aunSp3nnnnSsYGgAAAAAAvhforX/ozTff1Lhx49S+fXtJUs+ePbVnzx598sknGjdunF555RUtWbJE1atXl3QpiNeoUUPHjh1TaGiotm7dqpMnTyo0NFTR0dFauHChbr/9dg0fPtxbJQIAAAAAUOC8FryrV6+uLl26eLTFxMQoPj5eZ8+eVUZGhm688UZ3X1BQkO666y5t2bJF0dHR6tChg0JDQ939devWVUREhI4ePapatWp5q0wAAAAAAAqU1yZXGzNmzGUBee3atWrSpIlOnTqlmjVrXvaYOnXq6Pjx43/aDwAAAADA1cqyWc0XLFig06dPq0ePHsrKylJYWNhl29hsNmVlZf1pf37sdrtSU1M9bgAAAAAAFDaWBO9vvvlGTz75pD766CMFBgbKZrMpOzv7su2SkpIUFhb2p/35mTFjhqKjo923mJgYr48DAAAAAIAr5fXgferUKfXo0UPvvfee6tatK0mqWrWq4uLiLts2Li5OsbGxf9qfn/HjxyslJcV9i4+P9+5AAAAAAADwAq8G77S0NN155516/PHHdeedd7rby5Urp+DgYB0+fNjdlpubq1WrVqldu3Zq2bKlNm/erNzcXHf/gQMHZLfb8732W5JCQkIUFRXlcQMAAAAAoLDxWvB2Op3q27ev2rRpo9GjR1/WP3bsWA0ZMkQJCQlKS0vTqFGj1L59e1WvXl2VK1dWixYtNHbsWKWnpys+Pl5Dhw7VxIkTvVUeAAAAAAA+4bXgPWrUKG3YsEFz5sxRYGCg+9auXTtJ0ogRI9ShQwc1btxYlStXVk5OjubMmeN+/DvvvKPk5GRVqFBBzZo1U8+ePTV48GBvlQcAAAAAgE/4GWOMr4vwhtTUVEVHRyslJeUfnXZe7anPLKjqrzkxs8ufbwQAAAAAKFT+ag61bDkxAAAAAABA8AYAAAAAwFIEbwAAAAAALETwBgAAAADAQgRvAAAAAAAsRPAGAAAAAMBCBG8AAAAAACxE8AYAAAAAwEIEbwAAAAAALETwBgAAAADAQgRvAAAAAAAsRPAGAAAAAMBCBG8AAAAAACxE8AYAAAAAwEIEbwAAAAAALETwBgAAAADAQgRvAAAAAAAsRPAGAAAAAMBCBG8AAAAAACxE8AYAAAAAwEIEbwAAAAAALETwBgAAAADAQgRvAAAAAAAsRPAGAAAAAMBCBG8AAAAAACxE8AYAAAAAwEIEbwAAAAAALETwBgAAAADAQgRvAAAAAAAsRPAGAAAAAMBCBG8AAAAAACxE8AYAAAAAwEIEbwAAAAAALETwBgAAAADAQgRvAAAAAAAsRPAGAAAAAMBCBG8AAAAAACxE8AYAAAAAwEIEbwAAAAAALETwBgAAAADAQgRv5OuXX37RHXfcoejoaNWpU0eLFy92923btk1NmjRRRESEbr75Zn377bfuPofDoYkTJ6pq1aoqW7ashg0bpvT0dF8MAQAAAAAKBYI3LpORkaHOnTurZ8+eOn36tD7++GM9++yz2rx5s06dOqUBAwbolVde0YULF/TSSy+pf//+SkpKkiRNnDhRBw4c0O7du3X48GEZY/TQQw/5eEQAAAAA4DuBvi4Ahc+XX36pBg0aaMiQIZKkG264Qc8//7wWLFigbt26qU2bNmrdurUkqUWLFrrxxhu1Y8cOde/eXYsWLdKBAwdUqlQpSdLbb7+typUry263KyQkxGdjAgAAAABf+UdHvNu2bSt/f3+9+OKLHu07d+7U9ddfL5vNpqZNm+rrr7/26J87d66qVq2q8PBw9ejRQ2fOnHH3ORwOPfLIIypZsqRKly6txx9/XLm5uf+kPFwhp9OZb/uFCxfUsmVL7dixQ+vXr1dOTo42bdqk1atXq3z58u7H+vn5eTwuNzdXaWlpltcNAAAAAIXRPwreW7du1aRJkzzazpw5ox49emjSpElKTU3VhAkT1K1bN50+fVqStGHDBj333HNau3atzp8/rwYNGqhHjx7uxz/zzDM6cuSIDh06pEOHDungwYN65plnrmBo+KdatWqlb775RvPnz1dWVpa+//57Pfnkk2rTpo0qVqyoWbNm6Y477lBISIg6deqkgQMH6uabb5Yk9erVS4MHD9Zvv/2m5ORkPfjggypfvrzKlCnj41EBAAAAgG947Rrv999/X//617/Us2dPBQUFqXv37howYIDeeustSdIrr7yil156SY0aNZLNZtPUqVPlcrm0ZcsW5eTkaN68eVqwYIHKly+vsmXLauHChXr33XeVkZHhrRLxF0VFRWnNmjWaN2+eKlWqpHbt2unixYsaNmyYvvvuOz322GP67LPPlJmZqU2bNikwMFB2u12S9MILL6hs2bK67rrr1LBhQ7377ruaMGGCj0cEAAAAAL7jteC9Y8cOdevWzaOtd+/e2rx5s4wx2rNnj7p06ZJv/w8//KC6deuqQoUK7r7SpUurefPm+uqrr7xVIv6Gxo0b66uvvtLJkycVGhqqV155RSVKlNDUqVP13HPP6Y477pDNZlOHDh3UrFkzd7gODw/XO++8o7Nnz6pbt25q3769+vXr5+PRAAAAAIDveC14nzp1SjVr1vRoq1Onjo4fP66kpCSVKFFCoaGh+fbn99jf98N3JkyYoMaNG7vD8+HDh90Tq+Vp3ry5Nm7c6NH2zTffaPHixZo3b16B1QoAAAAAhZHXZjXPyspSWFiYR5vNZlNWVla+fX+nPz92u919erMkpaamXuEI8N++++47LV68WPv27XO3xcbG6tChQ7rmmmvcbXv37vU4W8HpdGrEiBGaNm2aqlWrVpAlAwAAAECh47Uj3jabTdnZ2R5tSUlJCgsLy7fv7/TnZ8aMGYqOjnbfYmJivDMQSJJcLpdGjBihmTNnqkqVKu72sWPHatSoUdq9e7fsdru2b9+u0aNHa+TIke5tZs+eLZvN5tEGAAAAAMWV14J31apVFRcX59EWFxen2NhYlS5dWhcvXpTD4ci3P7/H/r4/P+PHj1dKSor7Fh8f762hQJfOYOjWrZuGDRvm0d6+fXtNnDhR999/v0qUKKFRo0Zp1qxZ6t69u3ubyMhIvffee/L399rTCwAAAACuWl5LRq1atdKGDRs82pYuXar27dvLz89PTZo00ZYtW/Ltv/7663Xw4EFduHDB3ZecnKw9e/aoRYsW+f68kJAQRUVFedzgPeHh4Zo4cWK+ff3799fRo0eVlZWlH3/8UXfffbdH/8CBA1WnTp2CKBMAAAAACj2vXeM9ePBg3XDDDWrTpo06dOigDRs26OOPP9bevXslSePGjdOYMWO0YsUKVatWTS+88IJsNptuvfVWSZfC2tChQ/XOO+/IGKMhQ4bo4Ycf/sNTzeEd1Z76zGc/+8TMLn++EQAAAABc5bx2xLt8+fL69NNPNX78eEVERGjy5MlauXKlypUrJ0nq3LmzxowZow4dOqhUqVLau3evli1b5n78lClTVLFiRdWoUUO1a9dWrVq1NHnyZG+VBwAAAACAT/gZY4yvi/CG1NRURUdHKyUl5R+ddl5cj/wW13EDAAAAwJX6qzmU2a8AAAAAALAQwRsAAAAAAAsRvAEAAAAAsBDBGwAAAAAACxG8AQAAAACwEMEbAAAAAAALEbwBAAAAALAQwRsAAAAAAAsRvAEAAAAAsBDBGwAAAAAACxG8AQAAAACwEMEbAAAAAAALEbwBAAAAALAQwRsAAAAAAAsRvAEAAAAAsBDBGwAAAAAACxG8AQAAAACwEMEbAAAAAAALEbwBAAAAALAQwRsAAAAAAAsRvAEAAAAAsBDBGwAAAAAACxG8AQAAAACwEMEbAAAAAAALEbwBAAAAALAQwRsAAAAAAAsRvAEAAAAAsBDBGwAAAAAACxG8AQAAAACwEMEbAAAAAAALEbwBAAAAALAQwRsAAAAAAAsRvAEAAAAAsBDBGwAAAAAACxG8AQAAAACwEMEbAAAAAAALEbwBAAAAALAQwRsAAAAAAAsRvAEAAAAAsBDBGwAAAAAACxG8AQAAAACwEMEbAAAAAAALeTV4JyUl6b777lOpUqVUtWpVvfTSS+6+n3/+Wa1atZLNZlP9+vW1bt06j8euXLlStWvXls1m02233aajR496szQAAAAAAHzCq8F7wIABqlmzpuLj4/XNN99ox44d+uCDD2S323XHHXfonnvuUUpKiubMmaMhQ4Zo//79kqT9+/dr+PDhmjdvnlJSUtS3b1917txZ2dnZ3iwPAAAAAIAC59XgvX37dj399NMKDw9X+fLlNWrUKK1YsULLly9XgwYNNHLkSAUHB6t169aaNGmSXnjhBUnSm2++qSeeeEK33HKLgoODNWLECDVt2lRLlizxZnkAAAAAABQ4rwbvLl266IknnlBqaqri4+P13HPPqXz58tqxY4e6devmsW3v3r21efNmSfrTfgAAAAAArlZeDd6zZ8/WsmXLFB0drapVq+q3337Tv//9b506dUo1a9b02LZMmTLKzs6W3W5XYmKiYmNjPfrr1Kmj48ePe7M8AAAAAAAKnNeCd25urrp27ap7771XSUlJOnnypDp37qyzZ88qKytLYWFhlz3GZrMpKytLLpdL/v7++fb9EbvdrtTUVI8bAAAAAACFjdeC99q1a2Wz2fT888+7ZzWfOnWqBg4cqODg4HwnSktOTlZYWJj8/f1ljPHoS0pKyjes55kxY4aio6Pdt5iYGG8NBQAAAAAAr/Fa8D58+LBat27t0RYeHq4SJUpIkuLi4jz6Tp8+rVKlSik4OFiVK1fWqVOnPPrj4uIuO/3898aPH6+UlBT3LT4+3jsDAQAAAADAi7wWvGNjY3Xo0CGPtuzsbP3888+67777tGHDBo++pUuXqn379pKkVq1a/c/+/ISEhCgqKsrjBgAAAABAYeO14N21a1ft3btXs2fPVlpamhITEzVgwADdfPPN6tWrl77++mstXLhQDodDu3bt0qxZs/T4449LkkaNGqVp06Zpz549cjgcev/997Vv3z7dc8893ioPAAAAAACf8FrwDg0N1dq1a7V69WqVL19ezZs3V7ly5bRw4UKFhoZqzZo1mjt3riIjIzV48GDNnTtX9evXlyQ1bNhQb7zxhu6//35FRUXpww8/1Lp16xQSEuKt8gAAAAAA8IlAb/5jtWrV0saNG/Ptq1evnr788ss/fGz37t3VvXt3b5YDAAAAAIDPeXUdbwAAAAAA4IngDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUI3gAAAAAAWIjgDQAAAACAhQjeAAAAAABYiOANAAAAAICFCN4AAAAAAFiI4A0AAAAAgIUsDd4nT57UBx98YOWPAAAAAACgULM0eI8ePVpnzpxx39+5c6euv/562Ww2NW3aVF9//bXH9nPnzlXVqlUVHh6uHj16eDwWAAAAAICrkWXBe926dTp27JjGjRsnSTpz5ox69OihSZMmKTU1VRMmTFC3bt10+vRpSdKGDRv03HPPae3atTp//rwaNGigHj16WFUeAAAAAAAFwpLgbbfbNWbMGM2ZM0eBgYGSpPfff1//+te/1LNnTwUFBal79+4aMGCA3nrrLUnSK6+8opdeekmNGjWSzWbT1KlT5XK5tGXLFitKBAAAAACgQFgSvGfNmqU2bdqoZcuW7rYdO3aoW7duHtv17t1bmzdvljFGe/bsUZcuXfLtBwAAAADgauX14B0fH68ZM2Zo48aNKlmypB599FG5XC6dOnVKNWvW9Ni2Tp06On78uJKSklSiRAmFhobm2w8AAAAAwNXK68F76tSp6tChg7777jvt3btXX375pWbPnq2srCyFhYV5bGuz2ZSVlZVv3+/782O325WamupxAwAAAACgsAn09j+4atUqHTp0SCVLlpQkvffee+rbt69sNpuys7M9tk1KSlJYWFi+fb/vz8+MGTP07LPPert8AAAAAAC8yqtHvM+dO6fw8HB36Jak+vXrKyEhQVWrVlVcXJzH9nFxcYqNjVXp0qV18eJFORyOfPvzM378eKWkpLhv8fHx3hwKAAAAAABe4dXgXbp0aV24cEEXLlxwtx08eFBVq1ZVq1attGHDBo/tly5dqvbt28vPz09NmjS5bAbzvP78hISEKCoqyuMGAAAAAEBh49Xg7e/vrwceeEAPPPCAzp49q7i4OA0ZMkSjR4/W4MGD9cEHH2j9+vXKzc3V2rVr9fHHH+uhhx6SJI0bN05jxozRoUOHlJ2dralTp8pms+nWW2/1ZokAAAAAABQor1/jPXPmTD355JNq0KCBwsPD9cgjj2jo0KGSpE8//VQjR45Ujx491KBBA61cuVLlypWTJHXu3FknT55Uhw4dlJSUpE6dOmnZsmXeLg8AAAAAgALlZ4wxvi7CG1JTUxUdHa2UlJR/dNp5tac+s6Cqv+bEzC5/vpFFiuu4AQAAAOBK/dUc6vXlxAAAAAAAwP8heAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABayNHi/8MILOn/+vCTp559/VqtWrWSz2VS/fn2tW7fOY9uVK1eqdu3astlsuu2223T06FErSwMuExcXp86dOysyMlJ16tTRxx9/LElauHChAgMDPW7+/v7q1q2b+7FHjx6Vv7+/xzZ79uzx1VAAAAAAFCKWBe99+/bpmWeekSTZ7Xbdcccduueee5SSkqI5c+ZoyJAh2r9/vyRp//79Gj58uObNm6eUlBT17dtXnTt3VnZ2tlXlAR6MMbrrrrt022236fz58/rkk080fvx47d69W/3791dubq77lpOTo7p162rixInux//0008aMGCAx3bNmzf34YgAAAAAFBaWBO+cnBzdf//9ys3NlSQtX75cDRo00MiRIxUcHKzWrVtr0qRJeuGFFyRJb775pp544gndcsstCg4O1ogRI9S0aVMtWbLEivKAy1y8eFEPP/ywnnjiCYWEhOi6665Tt27d9OWXX1627bJly1S1alU1bdrU3fbTTz/p2muvLciSAQAAAFwlLAneEyZMUMOGDVWlShVJ0o4dOzxOy5Wk3r17a/PmzX+pH7BayZIlNXz4cEmXPjj6/PPPtWzZMt12220e2xljNH36dPfZHHkOHjyoOnXqFFi9AAAAAK4eXg/e27dv19KlSzV79mx326lTp1SzZk2P7cqUKaPs7GzZ7XYlJiYqNjbWo79OnTo6fvy4t8sD/lTz5s3VsWNH3Xrrrbrhhhs8+tasWaPSpUurRYsWHu0//fSTRo8erZIlS6pjx4765ZdfCrJkAAAAAIWYV4N3amqqHnjgAc2fP1/R0dHu9qysLIWFhV22vc1mU1ZWllwul/z9/fPt+yN2u12pqakeN8Abdu3apV27dunw4cN67rnnPPqmTZt22dFuSZo4caK+/fZbJSQkqGfPnurcubPsdntBlQwAAACgEPNq8H7kkUfUq1cv3XrrrR7tNpst34nSkpOTFRYWJn9/fxljPPqSkpLyDet5ZsyYoejoaPctJibGK2MAQkNDddNNN2nFihV6+eWX3e0bN25USEjIZc9v6dKlEWXLllV4eLhGjBihRo0aadOmTQVYNQAAAIDCymvBe9WqVVq8eLHeeOMNhYaGKjQ0VCdPnlSVKlX0008/KS4uzmP706dPq1SpUgoODlblypV16tQpj/64uLjLTj//vfHjxyslJcV9i4+P99ZQUAydOHFCv/32m0db5cqVFRAQ4D7zIr9ru/9IbGysEhISvF4nAAAAgKuP14J3t27d5HA4lJ2d7b5dc801SkhI0PTp07VhwwaP7ZcuXar27dtLklq1avU/+/MTEhKiqKgojxvwT+3cuVOPPfaYR9uJEycUGRkpm82m//f//p/sdrs6dux42WN79ux52Qc/O3fuVO3atS2tGQAAAMDVwbJ1vH+vZ8+e+vrrr7Vw4UI5HA7t2rVLs2bN0uOPPy5JGjVqlKZNm6Y9e/bI4XDo/fff1759+3TPPfcURHmAunfvrq+//loffPCBsrKydOjQId19993uI9xTp071WLf792rUqKHhw4fr119/VVJSksaOHSun06m2bdsW5BAAAAAAFFIFErxDQ0O1Zs0azZ07V5GRkRo8eLDmzp2r+vXrS5IaNmyoN954Q/fff7+ioqL04Ycfat26dQoJCSmI8gCFh4dr7dq1+vDDD1W2bFl17NhR9957rx544AGlpaWpdOnS6tq1a76PnT59umrXrq3rr79e1apV06lTp7Ry5crLJgwEAAAAUDz5mf+e1ewqlZqaqujoaKWkpPyj086rPfWZBVX9NSdmdvHZzy6u4wYAAACAK/VXc2hgAdYEFBp84AAAAACgoHAuLAAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABbyavC+cOGCBgwYoLJly6patWqaOXOmXC6XJGnnzp26/vrrZbPZ1LRpU3399dcej507d66qVq2q8PBw9ejRQ2fOnPFmaQAAAAAA+IRXg3fv3r1VuXJlHTt2TJ9//rlWrlypN998U2fOnFGPHj00adIkpaamasKECerWrZtOnz4tSdqwYYOee+45rV27VufPn1eDBg3Uo0cPb5YGAAAAAIBPeC14f//99zp79qymT5+uqKgo1apVS/Pnz9e7776r999/X//617/Us2dPBQUFqXv37howYIDeeustSdIrr7yil156SY0aNZLNZtPUqVPlcrm0ZcsWb5UHAAAAAIBPeC14O51OjRs3Tn5+fu62mJgYnTlzRjt27FC3bt08tu/du7c2b94sY4z27NmjLl265NsPAAAAAMDVzGvBu0mTJho4cKBH29q1a9WkSROdOnVKNWvW9OirU6eOjh8/rqSkJJUoUUKhoaH59gMAAAAAcDWzbFbz06dP69FHH9WkSZOUlZWlsLAwj36bzaasrKx8+37f/0fsdrtSU1M9bgAAAAAAFDaWBG+73a5evXrpoYceUvPmzWWz2ZSdne2xTVJSksLCwvLt+33/H5kxY4aio6Pdt5iYGK+PAwAAAACAK2VJ8B48eLBiYmL09NNPS5KqVq2quLg4j23i4uIUGxur0qVL6+LFi3I4HPn2/5Hx48crJSXFfYuPj/f+QAAAAAAAuEJeD96TJ0/W8ePHtWDBAvdEa61atdKGDRs8tlu6dKnat28vPz8/NWnS5LIZzPP6/0hISIiioqI8bgAAAAAAFDaB3vzHFi9erEWLFmnXrl0ek6UNHjxYN9xwg9q0aaMOHTpow4YN+vjjj7V3715J0rhx4zRmzBitWLFC1apV0wsvvCCbzaZbb73Vm+UBAAAAAFDgvBa8d+zYoUGDBsnhcKhSpUoefceOHdOnn36qkSNHqkePHmrQoIFWrlypcuXKSZI6d+6skydPqkOHDkpKSlKnTp20bNkyb5UGAAAAAIDPeC14t27dWna7/Q/7r7nmGv3www9/2D98+HANHz7cW+UAAAAAAFAoWLacGAAAAAAAIHgDAAAAAGApgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjcAAAAAABYieAMAAAAAYCGCN4B8tW3bVv7+/nrxxRc92r/88ks1b95cUVFRuummm7R7924fVQgAAABcHQjeAPK1detWTZo0yaPt6NGj6tu3r6ZPn64zZ87oiSeeUPfu3ZWQkOCjKgEAAIDCj+AN4C978803NW7cOLVv3142m009e/bUgAED9Mknn/i6NK+7cOGCBgwYoLJly6patWqaOXOmXC6Xr8uyHOMuXuMGAAAFg+AN4C+rXr26unXr5tEWExOjM2fO+Kgi6/Tu3VuVK1fWsWPH9Pnnn2vlypV68803fV2W5Rh38Rp3nj+6tKSoY9yMuzhg3Iy7OLgaxk3wBvCXjRkzRrVq1fJoW7t2rZo0aeKjiqzx/fff6+zZs5o+fbqioqJUq1YtzZ8/X++++66vS7MU4y5e4/69/C4tKQ4Yd/HCuIsXxl28XA3jJngD+McWLFig06dPq0ePHr4uxaucTqfGjRsnPz8/d1tRPbL/e4y7eI0bAAAUnEBfFwDg6vTNN9/oySef1LZt2xQYWLReSpo0aXLZUfyieGT/vzHu/1Mcxg0AAApO0dpbBlAgTp06pR49eui9995T3bp1fV2O5U6fPq1HH31Uy5cv93UpBYpxF69xAwAA63CqOYC/JS0tTXfeeacef/xx3Xnnnb4ux3J2u129evXSQw89pObNm/u6nALDuIvXuAEAgLUKVfBOTU1Vv379FBERoUqVKun555/3dUkAfsfpdKpv375q06aNRo8e7etyCsTgwYMVExOjp59+2telFCjGXbzGDQAArFWoTjUfNmyYQkNDlZiYqIsXL6p3794qUaKEhg8f7uvSAEgaNWqUNmzYoICAAM2ZM8fdfsstt2jz5s0+rMwakydP1vHjx7VlyxaPibeKOsZdvMYNAACsV2iCd2JiorZu3aqTJ08qNDRU0dHRWrhwoW6//XaCN+AjkydP9rj/1ltv6a233vJNMQVs8eLFWrRokXbt2qXQ0FBfl1NgGHfxGjcAACgYhSZ479y5Ux06dPDY4albt64iIiJ09OjRy9YOBvD3VXvqM5/97BMzu/jsZ/9dO3bs0KBBg+RwOFSpUiWPvmPHjumaa67xUWXWYtzFa9wAAKDgFJrgferUKdWsWfOy9jp16uj48eMEbwAFpnXr1rLb7b4uo8AxbgAAAGsUmuCdlZWlsLCwy9ptNpuysrIua7fb7R47SikpKZIuTdD2T7jsmf/ocd7wT2v2BsZd8Bh3wWvw740++9kHnu3ks5/NuAueL8d9pcaNGyfJt3+rvsC4GXdxwLgZd3Hgq3Hn/TxjzP/crtAEb5vNpszMy0NBUlJSvoF8xowZevbZZy9rj4mJsaQ+K0W/6usKfINxFy+Mu3hh3AAAoDhJS0tTdHT0H/YXmuBdtWpVrV+//rL2uLg4xcbGXtY+fvx496cakuRyuZScnKzSpUsX+Gy0qampiomJUXx8vKKiogr0Z/sS42bcxQHjZtzFAeNm3MUB42bcxQHjLvhxG2OUlpZ22Twx/63QBO+WLVvqscceU25urgIDL5V14MAB2e32fK/9DgkJUUhIiEdbiRIlCqLUPxQVFVWsnuB5GHfxwriLF8ZdvDDu4oVxFy+Mu3hh3AXrfx3pzuNfAHX8JZUrV1aLFi00duxYpaenKz4+XkOHDtXEiRN9XRoAAAAAAP9YoQnekvTOO+8oOTlZFSpUULNmzdSzZ08NHjzY12UBAAAAAPCPFZpTzaVLh+gXL17s6zL+tpCQEP373/++7NT3oo5xM+7igHEz7uKAcTPu4oBxM+7igHEX3nH7mT+b9xwAAAAAAPxjhepUcwAAAAAAihqCNwAAAAAAFiJ4AwAAAABgIYI3AAAAAAAWIngDAAAAAGAhgjfwN6WnpysqKkq5ubnutnXr1qlfv37KycnxYWUAgL8jIyNDjRo18ng937ZtmyZMmODRBgDAlSJ4A3+TzWZTZmamnE6npk6dKkmKjIzUxx9/TPAGgKtISEiIDh48KGOMPvjgA3f7zJkzlZ2d7cPKAABFDet4A38gPT1dderUUUhIiCTJGKPSpUvr22+/VWRkpJKTk1WhQgUlJSXpxx9/VOPGjZWamqrw8HAfVw4A+L2MjAx17NjR4/U8OjpaK1euVEREhPv1PDk5WT/88INuvPFGXs8BAF7FEW/gD9hsNoWGhmrRokXy8/PThx9+qMzMTEmXjpIEBQUpMDBQkhQcHOxuBwAULiEhIYqPj9fgwYP1yy+/aMiQITpy5IgkKTQ0VMHBwe7X89DQUEn/97oOAIA3ELyBPxAQEKDw8HC1bNnS/dXf/9KfzH8H7pycHIWGhrrbAQCFR2BgoEqUKKF+/fq5v/7363lQUJAkyeFwKCgoyH0fAABvICUAf0PejlpWVpYGDRqkCxcuaNCgQTp37pwqVqzo4+oAAH9V3uu53W7XlClTlJ6erilTpigxMVEVKlTwcXUAgKKG4A38DXlTIvj7+6ty5coaO3asJCkxMVFNmjTxZWkAgL8h7/Xc5XLp6NGjuuuuu3T06FEdOXJE1113nY+rAwAUNQRveIXdbpfT6VRYWJivS7FU3o5acHCwe0ZzY4xatmypcePG+bI0AMDfkPd6brPZtGjRInf7HXfcofvuu89XZQEArlBhzSUEby/asWOH3n33XTmdTj3wwANq3769r0sqEMuWLdP69eslSbfddpvuvfdeH1fkHU6nU+np6dq0aZP7a966rk6nU1999ZXS0tK0atUqVa9eXZ06dfJxxdY7ePCgXn31VTmdTo0aNUrXX3+9r0uCxYrj7zwtLU2vvvqqHA6Hxo4dq5IlS/q6pAJ14sQJORwO1apVy9eleI3T6VROTo6OHDni/pr3ep6bm6v9+/crMDBQq1atUnZ2tvr06ePjiguG0+nUhx9+qJycHD3wwAPF5rr2ovgc/yuK635qcR33r7/+qhdffFG5ubl69NFHdc011/i6pAJRqHOJgdd07NjROBwOk5OTYzp06ODrcgpM+/bt8/3+apeWlmYqVqxoqlWr5r41btzYGGNMeHi4WbZsmSlfvrwpU6aM+fbbb31cbcHo0qWLSU9PN2lpaeaOO+7wdTkFJjEx0YwdO9aMGjXKnDhxwtflFKji+Dvv37+/+fnnn82hQ4fMvffe6+tyCtRbb71lnn76aTNx4kTz8ssv+7ocr0lPTzd+fn7G39/f+Pn5GT8/PxMTE2OMMSYiIsJ88MEHJjQ01JQpU8b88ssvPq624Dz88MNmw4YN5vPPPzfDhw/3dTkFoqg+x/+K4rqfWlzH3atXL3P69Glz+vRp06NHD1+XU2AKcy7hiLcXxcbGauvWrTLGqHbt2r4up8A0bdpU8+bNkzFGLVq08HU5XhMREaFff/31snan0ym73a6ePXuqW7dumj9/vjp16qR+/fpp1qxZRXpJsRIlSig+Pt69pnlx8cgjj2j27NmSpAcffFDLly/3cUUFpzj+zs+dO6eqVavK5XLp4sWLvi6nQC1fvlyff/65JKldu3bueSyuduHh4bLb7R5HdHNycuRyuWS329W/f3916dJFr7zyipo1a6aJEycWmbH/L4cPH9Yrr7wiY4xmzZrl63IKRFF9jv8VxXU/tbiO2+Vyyc/Pz/21uCjMucTPmP//IidcsZycHC1cuFCBgYG67777itXSUl988YUCAgLUtm1bX5diufT0dEVFRSknJ8f9Oz527JgGDx6szz77TOHh4T6u0DoXLlzQq6++qsDAQI0ePVpRUVG+LqlA9OzZU3PmzJHL5dLIkSO1bNkyX5dUYIrj7/zHH3/Ua6+95h5z/fr1fV1SgXnttdd09uxZ+fn5qVKlSnrooYd8XZKlMjMzFRERIYfDoYCAAEnSrl27NGjQIH355ZdF/sOmLVu26L333lNgYKAGDx6sNm3a+LokyxW35/jvFdf91OI67lOnTumFF15QYGCgHnvsMVWuXNnXJRWYwppLCN7AP5CRkXFZwDbGFKtPFIuT4vzmheLnl19+kb+/v2JjY31dilc5nU4lJiYqJibG/Vrtcrn0888/q169eh6v35mZmYVuUh54T1F9jgMo3Aje+MfS09NVqVIlJScnuz89XLdunRYvXqz58+crODjYxxUCAHBJfHy8qlWrptOnT6ts2bIefUOGDFHDhg01evRoH1UHACjq/H1dQFGQkZGhRo0auWdIlaRt27ZpwoQJHm1Fjc1mU2ZmppxOp3tprcjISH388cfKycnxcXX4J1JSUv7njmd4eLjOnTvnvp+RkVEQZaEAnD9/XtHR0R5tBw4c8Li/dOlSvfXWWwVZlqXS09P13Xff6ciRI0pMTNTFixflcDh8XRYsEh4eLmPMZUeyR4wYoUWLFikyMtJHlVnL6XRq+fLlysrK8nUpPvXdd98V+/8DFE3Jyclq1KiRR9t/z1G0fft2rVy5sgCrst7x48fVtWtX3XvvvRo6dKjGjBmjCRMmaPr06Xr11Vc1b948rVu3Ti6Xy9elunHE2wtyc3MVGhqqrKwsLVmyRAMGDNC2bdvUrl07paSkKCIiwtclXpH09HTVqVPHPWlY3iRL3377rSIjI5WcnKwKFSooKSlJP/74oxo3bqzU1NQifa1zUZWamqr69esrPj5e8+bNU2Zmpvz8/GSz2TR06FCVKVNGp06dUlhYmM6cOaPGjRvrq6++KtJLVOTm5mrYsGF67bXXFBkZqf3798vf37/IXfebnZ2tmJgYnTt3Ttu2bVODBg0UGxurGTNmaOTIkdq3b59atGihxx57TJMnT/Z1uV5x5MgRXXvttfLz8/O4VCQgIEBhYWEKDw9X5cqV9eqrrxa6CVq8LTU1VYMHD/YIn8YYRURE6I033vBhZd6TkZGhqKgoZWdnuydZe+SRR7RkyRKtWLFCrVu39nGF1nA4HAoNDVVCQoJ27Nihu+66S3FxcbLZbPLz81NOTo5KlSpV5K5n37Jli5KTk9W7d29Jcp/RMGTIEB9XZp309HRNmzZNkZGR7tczY4wyMjI0depUpaSkqGfPnqpcubJiY2PVqlWrIrMU6sGDB9W1a1eFhYX9z8v+srKylJKSorNnzxZgddbKyspSTEyMzp8/r4MHD6p8+fK6/vrrNXv2bN111106deqUmjRp4p6vpqg4efKkatasqXHjxikzM9N9y8jIUGZmptLT0/Xjjz9q+PDhevXVV31driSC99+SkZGhjh07egTQ6OhorVy5UhEREe4AmpycrB9++EE33nhjkQigTqdTtWvX1sKFC9W/f38tXLhQQ4cO1cGDB1WmTBmdP39e5cuX15kzZ/Tzzz+rQYMGstvtxWbyiqLEbrerQYMGOnr0qK699lr3jujWrVv1yy+/6JprrtHJkyclSbNnz9Z7772nvXv3+rJkr7Db7Xr77bdls9kUEBCgzMxM9ejRQ+3atdPevXtVokQJXbx4UREREbr33nv11Vdf6ejRo0VqzVuXy6UqVapozZo1at26tT755BPZ7XYNHTpUgwYN0vLlyzV8+HA9+eSTvi7VaxITE1WzZk0lJyfn+6adlpamGTNmKDs7W19//bWvy7WU3W5XRESEJk6c6G6bMWOGXnzxRT388MM+rMx7cnJyZLPZlJubKz8/Py1fvlwDBgzQ5s2b1axZM1+XZ6nQ0FCdPXtWtWrV0qFDhxQTE6OsrCz3B04vvPCCxo0b5+syveq2225TjRo1NG/ePElS+fLl9f7772v79u2KiIhQdHS0brnlFl133XU+rtR70tPTVblyZQ0YMEDGGC1atEj333+/5s6dK7vd7p4cdsqUKTp06JCWLVumDz74QH379vV16Vfs9OnTqlSpkubPny/p0j76oEGDNGfOHPd+e05OjoYPH6733ntPAwcO9GW5XuV0OhUTE6O1a9eqU6dOWrdunbZv365Jkybp+eef1/vvv6+bb77ZvTpLUZGYmKhatWopMzPzD7eZOHGi3nnnHY+zNX2qYFYtKxocDoeJiYkxH374oftr3bp1jTHGlC5d2hhjTNmyZY0xxvz888/G39/f5OTk+Kxeb2rYsKHH1/r16xtjjClfvrwxxpgqVaoYY4z54YcfTFhYmA8qhDfk5uaaa6+91hjzf79rY4ypXbu2McaYmjVrmq5du5rTp0+btm3bmsWLF/ukTm/Lysoyfn5+pnXr1qZVq1YmICDAHD161AQEBBiHw2HCwsJMTk6OWb16tQkODjaff/65r0v2mtzcXLNgwQLzn//8x/13nLem8YIFC8zRo0dNxYoVTbt27XxcqXcdPXrUJCQkGJvN5tGenZ1t/vOf/7jvv/DCC6ZMmTIFXZ5lzp8/b+677z4zcOBA9+1f//qXSU5ONqGhoR7bRkRE+KhKa+Tm5ho/Pz+zaNEi9/3du3f7uKqCERUVZex2u7nmmmtMVlaWKV26tMnIyDBpaWkmMDDQ5Obm+rpEr9q7d6+Jjo42Z86cMcYYc+bMGWOz2cyBAweMv7+/6datm2ncuLF7362oyMnJMdWqVXPfr169ujHGmJIlSxpjLj3n/f393f09evQwDz/8cMEWaZGUlBSPsRljjJ+fn8nIyHDfz87ONv7+/sbpdBZ0eZbZtm2b+fzzz93v35MnTzZRUVFm06ZNZufOnSYyMtLccsstvi3Sy1wulxk8eLD59ttvPd7DXS6XmT17tmnQoIGx2+3GGGPeeecdM2vWLF+Vehmu8f4bAgMDVaJECfXr18/91d/f390nyX0EzOFwKCgoqEgdEfu9vHFnZWVp0KBBunDhggYNGqSJEyeqYsWKPq4O/1RAQIDOnDmjhx56SKdPn9ZDDz2khx56yON5ftttt6l169bav3+/evXq5eOKvSMkJEQBAQHavn27duzYoeDgYIWEhCgoKEiBgYHy9/fX/PnzNXjwYC1ZskTt27f3dcle43Q6NWXKFGVlZcnlcmnatGm6++67Vbp0aT3yyCM6ePCgNmzYoO+//17r16/3dblekZqaqkaNGmn8+PEe7bt371bt2rU1ZswYpaSkSJI6dep02bVyV7OQkBAtXrxYDofDffv0008VHBx82emZRXWVhtGjR6tx48YaOHCgZs+erf79+3vc7r33Xt1xxx2+LtOrAgMDFRAQ4PG6FhYWpoiICPn5+bmXUisqXnzxRQ0fPlyPP/64jhw5oi1btqhjx44qUaKE/P39tXLlSn399dfKzs7Wb7/95utyvSYoKCjfv9u8fdT//j03a9ZMffr0KZDarFbUnsN/RUZGhrp166b9+/fL5XJp/vz5mjRpksLDw9W7d2/3c/3777/XN9984+tyvSYpKUm7d+9WixYt5HA4tHjxYqWlpWnFihWaPHmyBg8eLPP/n9A9bNgwPf744z6u+P9wLvAVygskdrtdU6ZMUXp6uqZMmaLExERVqFDBx9VZJ+8J7e/vr8qVK2vs2LGSLp320aRJE1+Whitks9nUsmVLrVu3Ti1btpQxRlu3bpV0aUd8zJgxSktL07p169ynb13t/Pz8LttZCQgIkL+/vyZOnCiHw6GdO3fq66+/VrVq1XxTpEWCg4N15MgRGWP05JNP6tSpU+rTp49CQkI0Y8YM9e/fX/v27dO8efN0//336+eff75sRuirTUhIiD744APt2rVLlStXVs2aNdWvXz916tRJgwYN0vjx492rMjRs2NDH1XpX3sRiixYtcrctWbLEfa3v7wNnVlaW7rjjDq1bt67A67SKn5+fDh8+rIkTJ2revHmqUaOGbrzxRo9tHA5HkZogNG+HOyEhQS6XSwEBAfLz89Nvv/1WqCYd8qbOnTurXbt2euKJJ9SnTx9VqFBBDz/8sAIDAz3mctizZ0+RO1hw8eJFzZo1S8YYpaSkuL93Op3Kyspy77dK0lNPPeXDSr3LFMMrZ8PDw3XixAlFRkZq1qxZWr58ufbs2aPIyEiNHTtWPXv21P79+/X888+rT58+OnDgwFU/75QklSlTRgcOHNDFixf12Wefae7cuXrwwQf1zjvv6Oeffy7U81UQvK9Q3h+6y+XS0aNHddddd+no0aM6cuRIkbpu6L/ljTs4ONg9o7kxRi1btixy14kVN9HR0erXr59efPFF9evXT5I0ffp0jRkzRqmpqZIuzZa5b98+ff/997rhhht8Wa7X/PebtsvlkjFGx44dk9Pp1KpVq1SrVi1NmDChyB0JDAgIUHp6uux2u+bOnasPPvhAa9asUceOHfXAAw9o2LBh2rBhg9577z299tprmjZtmq9LviIhISHq06eP+vTpo5dffllbt27VxIkTdcstt+jf//63r8uzlL+/f77PX39/f73yyiuKiopyt/3rX/8qUisX5P2NlylTRnPmzFGrVq00cuRIDRkyRO3atfNxddZIT09X8+bN5efnp+rVq3v87qtUqeIxqWBRcv/990u69AFT165dtWfPHnXp0kXJyckyxmj//v3uMLpt2zbdeuutvi3Yi3Jzc3XixAkZY5Sbm6u4uDhJ0q5du9SpUye5XC69++676t+/f5Fa9jW/FSny+1A9r72oKFGihDIzM+VwOLRmzRpNmTJFx44d06BBg7R371498sgjWrx4sRYuXKi33367UB39vVJ5k4GOGzdOGzZsUEBAgHbu3OmxTd5cFnfffbcvSrwMwfsK5b2R22w2jyMId9xxh+677z5fleVVTqdT6enp2rRpk/tr3jJpTqdTX331ldLS0rRq1SpVr169yMyQWVydOHFCzZo109GjRz0mHCpXrpwuXLig9evX6//9v/+noUOHaunSpUUieLtcrsveiHNzc+V0OvXRRx9p9erV2rZtm/r376+jR4/qgw8+8FGl1jl37pzuvPNOSdKAAQNUsmRJlShRQs8++6xq1KihjRs36vHHH1efPn00ZcoUj6MmVyuHw6F69eopMjJSxhg99thjl22TlZWlyMjIIj+5WnBwsPvo5+9nQy5Kfv++FRAQoPvuu09RUVHq0aOHPv/8czVv3tzHFXpfeHi4Tp8+rXr16unEiRMeZ6Q5HA65XK7LllcrCnJzc92nV6ekpCg1NVXffPONatasKafT6XFgxM/PT06n01elel3p0qXdyz5u3LhRb7/9tpYvX65q1appy5YtatmypebMmaN3331X69evV8mSJX1csXekpqbKGKOqVau624wxql27tsf7uzFG11xzjU6dOuWLMi2Rk5PjPnNn0qRJKlmypEJCQvTqq6+qZs2a2r17t8aPH68RI0bo0UcfLRLv39KlgwYDBgxQ1apVZYzRhg0bFB8fr5iYGElyf1+pUiWC99XI6XQqJydHR44ccX/NeyPPzc3V/v37FRgYqFWrVik7O7vIXDeTlZWl7OxsDR8+XJI0fPhwlSpVStKlJYjyrgV2Op3asGGDL0uFF1SoUEGLFi1Sjx499OGHH8rlcql79+56+umnNX/+fE2cOFGhoaHq1q2bnn32WV+X6xXZ2dnKzc1VQECA+whQWlqa+5RTh8Oha6+9Vtu2bdP111+vuXPnatiwYb4u26sGDBigypUru+/v2bNHpUuXVsuWLfXaa6+padOmKlmypN5///0i8aadkpKi6OhoxcfH65133pF0aYds5MiReuutt2SM0YMPPqg5c+Zc9StT/N4fnVpsjNHEiRPVqlUrd9vWrVvVuXNnPfTQQwVVnqXyjojl/a1L0l133aWHH35Yffr00Y8//lhkQkgePz8/lStXTi6XSzabTS6XS7m5uXK5XPL39y8Sf8v5mT59uho1aqRvv/1WgYGBmjhxoqZNm+Z+/crbd3O5XO75HIoCp9OZ79Hc3NxcValSRVWqVJF06eh3v379NHLkSC1ZsqSgy7REeHi4li5d+j+XEzPGuFeuKEp69erlcVmUy+VSXFycGjZsqMmTJ6t8+fJq2rSpJkyYUCT+5l0ul5577jk9+OCDCgkJ0fHjx919JUuWdJ/lERkZ6f6+sGA5sb8hIyPDvTZi3n9blSpVdOrUKUVGRmr27NkaPny4IiIitHv3btWoUcPHFVvL6XQqNDRUDodDTqdT8+fP11NPPaV+/fpp1qxZReb63+LE5XLp2muv1ZEjR9SwYUMtX75cLpdLXbt21ZEjR1S9enX99NNP+vzzz3Xttdfqpptu0oULF3xd9hVzOp06dOiQ+9pHp9OpKlWqaNGiRRowYICioqJ07tw52Ww2bd68WQMHDtTJkyeLVCDr0KGDkpOTVbduXfXt21effPKJEhISPC4dCQgIUPPmzVWmTBkfVnrlUlNTVaNGDd17772aO3eusrKy3H0lS5Z0P6ejoqLcl1cUFXnLCT3wwAPutg8++EApKSmqUaOGfvvtN/eOWdmyZQvPEixecO7cOVWoUEEXLlzwOKXe6XSqXr16qlOnjlavXu3DCq0THR2ts2fPqk6dOjp48KBiYmK0atUq+fn5qW3btkpJSZHNZvN1mV4zf/58jR8/Xv/5z390/fXXKycnR9WrV9fnn3+uVq1aKScnp0hOxpWZmamYmBj9+9//ljFGU6dO1aRJk/Tkk0+6J9AMCgpSTk6O0tLSVK1aNX3xxRdFYm6ejIyMv/yeXNQusWjfvr2OHj2qfv366e6779abb76pc+fOeRwcCQgIUO3atYvEpM8JCQmqXbu2ey6OvA/SJKlUqVJKTk6WVDjfwzni/TeEh4fLbrd7PGlzcnLkcrlkt9vVv39/denSRa+88oqaNWumiRMnuicdK4qysrLkdDrdp3QNGTJEbdu21eDBg5Wbm0vwvgrlHd2VLgWQO++8Uw6HQ+XLl5d06YhRcHCwunXrpvPnzyslJUUXLly46o8SBQQEqH79+vrPf/6jHj16uK97GzlypCTpt99+07Zt2zR69GitX79eb775ZpEK3dKlI2NvvfWWvvnmG/e6t99//70mT57sPhIeFxenUqVKafv27b4s9Yq5XC499thjiouLk8PhUHx8vPvDVGOM+/7vv//96YtXs5ycHA0ZMsTj+Tto0CD3qba/3xktSjum0qWx16tX77JrQQMCAjRp0iStX7/efSS4qMnOznav45x3PWjv3r0VHBys4OBgRUdHq1evXnrllVeKxMSwAwcO1JEjR/TSSy+5P0zp3r273n77bUVFRSktLU0lSpTwbZEWyM3NVfv27fX9999Lkrp27arvvvtOnTt3ltPplN1ulzFG6enpKlGihO655x7NnTu3SATv7du3695773Vf95sfY4yys7N18eLFfK8Jv1r5+flp8eLFWrlypXtunqNHj2rv3r3uDxnPnz+vG2+8UWvXrvVlqV5RpUoVZWZm6tdff1XVqlU1aNAgd19GRob7fnZ2tvv7999/3ye1/jeOeHtBZmamIiIi5HA43J+g7tq1S4MGDdKXX35ZqGfXu1L5fcJY1D5JLE6Sk5NVo0aNPzyKnXdqbt6Oy8KFCzVs2LCr/hPUU6dOqVevXvrhhx+0dOlSZWZmasaMGQoNDXVvY4zRkSNHFBgYqE8++aTITcZ06623avr06WrZsqW7beDAgTp//rzWrFkjSVqxYoV7eZ6iEE4cDodCQkI8zmLKT1G7BvSPREREqGnTpu7X7y+//FKtWrXS+vXri/wHqXkTUV3tr2X5ycnJUWhoqBISEpSUlKR69ep5HO01xmjz5s3uFSsOHjxYJD5YtNvtuvbaazVz5kz961//0kcffaQZM2Zo3759vi7NZ3JycvTRRx/p7rvvVkhIiLZs2aKYmBjVqlXL16VdsZMnT2rv3r2y2Wx/uA/qcrmUnp6u9PR0DRw4sIArtE7btm01ffp0tWjRwt129913KygoyD3/1PLlyzVw4EBduHChSLx/S5few8eOHfs/z9bJyspSWlpaoZmbh+D9NzmdTiUmJiomJsb9h+1yufTzzz+rXr16Hn/smZmZRXLSEhRf69evV/v27YvczmlOTo5Gjx6txx57TDVq1NCSJUs0adIkPfPMMx7bOZ1O7dmzR71791aHDh18VK01PvvsM914440eR7u++eYb/fTTT+7TkrOysorU6ajSpaMAf+VNu3r16gVYVcEzxmjRokUegcsYowsXLmjQoEFF8rTc4sLlcmnHjh26+eab/+cs1mlpadq+fbu6dOlSgNVZa/PmzWrdurWCg4P1yy+/6KGHHtJnn31W5N7D8NcVxbNa3nvvPbVr185judMvvvhCX331lSZNmiTp0ntdZGRkkf8QtbAjeP9N8fHxqlatmk6fPn3ZWrZDhgxRw4YNNXr0aB9VB8AbNm7cqLVr1+qNN97wdSkAAFyR9PR0VapUScnJye7Z3tetW6fFixdr/vz5RWZZsYyMDMXExKh169Z68cUXFRQU5BFGpUsTh44bN04bN24sEmtaF2fZ2dlauXLl/5yxPCcnRzk5OYXmd120PvIpAOHh4TLGXHYke8SIEVq0aNH/vLYEuFqcO3dOVatW/Z8Tp8XHx6tjx44FWFXB6dSpE6G7GMjJyVHfvn2VmZn5h9tMmzatyE64derUqSIxOSL+PqfTqeXLl3vM7rxx48b/+bdwtVuzZo1Onz7t6zJ8wmazKTMzU06nU1OnTpV0acbnjz/+2D1BVVGQN84+ffrI4XAoNjZW5cuXV9++ffXpp5/K6XRq3bp1stlshSaI4Z+z2+3uFZfyTJ482eM5PWzYMI/JRH2NI95/U0ZGhqKiopSdne0+VemRRx7RkiVLtGLFCrVu3drHFQJXJi0tTX5+foqKilJmZqZ7Nm9jjPtU43nz5umBBx5QgwYN3LNHFgVZWVlav369evbsqapVq2rnzp3u9SCLqvT0dE2bNs29YoN06RTjjIwMTZ06VSkpKerZs6cqV66s2NhYtWrVSp06dfJx1d7j7++vZcuWqXLlyqpSpYoqVark0d+oUSNdd9117uvkipLGjRvr0KFDcjgcKlOmjMqUKaOyZcuqbNmyqlKlijp06KDOnTv7ukxcgfT0dD3yyCPuJZYyMzM1b94896okx48f1zXXXCNjjMqUKaM+ffpozpw5vi7bK5YtW6aEhAT3WYj169fXk08+qf79+/u4Muukp6erTp067tOJjTEqXbq0vv32W0VGRio5OVkVKlRQUlKSfvzxRzVu3FipqalF4pr+rVu3qkaNGqpTp46OHDkil8ulunXr6uuvv9bu3bu1cOFC96Sw27ZtKxLXtWdlZemDDz7I9/17yJAhSktL0+jRo93v3y1bttS1117r46q9x+FwKCYmRseOHdNjjz2mKVOmqEmTJqpatarWrFmj999/X7NmzdKGDRt0/fXX+7rcSwz+Frvdbvz9/Y3L5TLGGLNs2TITERFh9uzZ4+PKgCu3YMECM2zYMONwOIy/v78xxpjQ0FDj7+/vvs2bN89ERESYtLQ0U7FiRR9X7F0pKSnuMdWoUcNkZmaaL7/80nTs2NHcfvvt5vbbbzft27c3Xbp08XGl3pOWlmaioqLMqFGjzMMPP2yio6PNww8/bIKDg939fn5+ZurUqaZfv34mNDTU/Oc///Fx1d7j5+dn6tSpYypVqmQCAwNNVFSU6dGjh1m7dq1ZtWqVCQoKMj/99JOvy7RE69atzTfffGMyMzNNXFyc2b17t1m1apV5++23zcCBA01AQID59ttvfV0mrkBOTo4pWbKkeeqpp8xTTz1lSpUqZTZt2mQ+//xz4+/vb86ePWuMMWbFihXGz8+vSO3L3HjjjebJJ5903y9ZsqT57LPPTN++fc2gQYPM2LFjzbp163xYoffl5uaa2NhY8+WXX7q/1q1b1xhjTOnSpY0xxpQrV84YY8zBgweNv7+/cTgcPqvXWzIyMkxQUJApXbq08ff3NxUrVjQVKlQwYWFhxhhjEhISzNNPP23KlStnYmNjzalTp3xcsXekpqaasLAw07VrV3PnnXea8PBwc+edd5qgoCB3v5+fnxk8eLBp2bKlCQgIMBs2bPBx1d6TmZlpKlWqZA4fPmwqVapk7r77bnP69GnTrVs3U6tWLVOuXDmzb98+X5fpgeXE/qaAgAAZY7R48WLdd9996tatm7744gs1a9bM16UBVyzvU+LAwED35CPVqlXTzz//rJtvvlkjRoxQcHCwSpcurZCQEPe1Ylc7p9OpRo0aqWzZsrpw4YJuu+02/fbbbwoJCZHNZtOFCxfUqlUrVapUSTNnzixSpx6HhISoVKlSev311yVdmmTtjTfe0OLFiyXJPUPsxIkTJV2aNHLHjh3q27evz2q+UpmZmTp58qTq1q0rSdq7d6/CwsKUm5uro0eP6vPPP9fIkSN1+vRpjR8/XvXq1fNxxdYICAhQ+/btFRoaqvr16+vmm29W165dddddd2nEiBE6ePCgdu/erRtvvNHXpeIfCgoKUunSpTVjxgxJ0qeffqpNmzYpODhYISEhCg4OVlJSkp544gn179+/yOzLbNu2TQkJCXr00UclXVr31+l0qkaNGlq6dKlGjRql48ePq2/fvkpJSSkyk20FBAQoPDxcLVu2dH/NG1ve+3Xe9dx5s90XhffxsLAwZWdny9/fX2FhYfr1118lXVqp4dprr5XT6VS/fv20b98+rVixQnfeeae+/fbbq36SvZCQEJUrV869TxIbG6s1a9a4l3jNuyz23XfflXRpebmNGzde9WetZWZmqkuXLmrSpIn8/f1VtmxZfffdd6pVq5bS0tK0dOlS3XvvvYqPj3e/zxcWV/9fm4+MHj1aL7/8sho0aCBJmj17tkd/bm6uLl68qHXr1vmiPOAfadSokT777DNJ//fm/PsZMP38/BQcHKzIyEgFBgYWiTds6dLpShMnTlR4eLgeeughPfnkkxo8eLD8/f1ls9lUunRpXXvttapRo4aCg4M9luy42gUFBeW79Ere7/a/Z7Nu1qzZVT/+jRs3qm/fvuratavH2A8cOKC9e/dq9+7dSk1NVd26dfWf//xHI0eOVLly5XxYsXdlZ2e7l8pbunSpbrjhBu3du1dbtmzR3XffrXLlymnu3LmaP39+odtpwd/jcrnkcDi0f/9+GWOUk5OjSZMmKTIyUq+//roOHTqk4cOHq1atWpftx1zNXn75ZY0aNUr33XefpkyZop9++kldu3ZVRESE/P399eqrr0qSypcvr3Pnzql8+fK+LdhCecE7KytLgwYNcq9UcO7cOVWsWNHH1XmPv7+/cnNz5XA49Nhjj8nPz08Oh0PNmjXTTTfdpJiYGDkcDg0fPlxLlixRYmLiZROvXW3+6P077wOFgIAAj/7atWurVatWBVafVcLCwtSmTRvdf//9Wrx4sbp166Y33nhDZcuWVWJioh5++GF9/PHHat++vR599FG99tprvi7ZrWjsNRcwPz8/HT58WBMnTtS8efNUo0aNy44IOByOIjVhBYqH2NhYxcXFafv27ZKk7du3KzMzU9u3b1dqaqoOHTrknuNgx44dReYoQWhoqG677TaVKVNGYWFh6tSpk/uT4uKwJv3Fixc1a9YsGWOUkpLi/t7pdCorK8vj9/zUU0/5sFLvuPnmm/Wf//xHW7ZsUdmyZdW0aVM999xzevbZZ1W5cmXddtttevnllxUVFaXWrVtrxIgRWr58ua/L9gpjjJo1a6YnnnhCLpdL/fv3l8PhUMeOHXX//fdr+vTpev3119WmTRt98sknBO+rXFpamjIyMnTnnXfKGKPMzEz99ttvys3NVUBAgAYOHKjRo0dr2LBhReq1bsyYMbrhhhuUnp6uf/3rX6pQoYJmzpypwMBAj3Hu37+/SH2olh/z/0/l5O/vr8qVK2vs2LGSpMTERDVp0sSXpXmd0+nUpEmTFBQUJGOMJk6cqMzMTO3fv18bNmzQnj17VLduXU2ZMuWqD93Spf2T9PR0ffrpp3K5XMrIyNAnn3zi7v/vpdNeeuklX5RpiWeffVY5OTlyuVx69tlnNWTIEGVkZOizzz5TmzZtdPvtt+vDDz9U/fr1dc899+imm27ydcmSCN5/W94LWJkyZTRnzhy1atVKI0eO1JAhQ9SuXTsfVwdcmfLly+v777/Xo48+qpycHD366KNKTEzUo48+qlOnTunjjz9WYGCgfvvtNz366KNFJng7HA5VrFhRgYGBcjqdCgoKch8pys7OVlZWlpKSkhQRESGn06n4+PgiNelabm6uTpw4IWOMcnNzFRcXJ0natWuXOnXqJJfLpXfffVf9+/cvEsvOVKhQQT179lTPnj0lXTqro3///jpy5MhlR75mzZqlWbNmFZm1X/NO0Xv22Wd17Ngxvfbaa7r77rv12Wef6ZlnntHUqVO1aNEiVahQQX369NGuXbtUv359X5eNfyg6Olrnzp3zaBs7dqxee+01+fn5qVmzZmrevHmRCt2SdNttt0mSZsyYoYSEBG3cuFG33nqrkpKS5HK5tGbNGveHiykpKYVq1mNvy9tvDQ4Ods9oboxRy5YtNW7cOF+W5nUfffSRTpw4offee09xcXFauHChIiMjFRERoSpVqqhevXqKi4tTjx499NNPP102mebVKD09XfPnz5cxxv29y+XS3r171atXLxlj9MUXX6h9+/a+LtXrMjIylJGRobZt22r58uVq2rSpoqKi9M477+iRRx7R0aNHNWrUKM2YMUOrVq3ydbmX+OC68qtaVlaW8ff3N7m5ue62VatWmcjISLN7924fVgZcubS0NPdELOHh4cYYY6677jpjjDE33XST+eCDD8zq1atNw4YNjTHGxMbG+qROb8vNzTUJCQnm5MmTpnz58iY9Pd1UrFjRJCcnmy+++MLUrFnTXHvttebaa681derUMTExMb4u2auqVavm/r569erGmEsT8MTHx5vdu3ebgIAAc+ONN5rmzZub5ORkX5VpCZvNZhITE01iYqIpW7asqVGjhrn++utN69atTZcuXcyDDz5oDh8+7OsyLbFp0yZz6623msaNGxtjjDl8+LCZNm2a6dixozHGmMcff9z89ttvviwRV8jpdJry5cuba665xlSrVs1UrFjR7Nu3zxw6dMhERkaa+++/34SGhprZs2f7ulSvSktLM8Zcmnypfv36JjIy0qxfv96cP3/e+Pn5mWrVqplq1aqZmJgYEx0d7dtivSg3N9dUr17dbNy40f21Tp06xphLk6vt3LnTbNiwwTz44IPm3nvv9XG13rdo0SLTv39/Y4wxu3btMq1btzavvvqq+xYZGWm2b99uEhMTfVyp9/zR+/eBAwfMxx9/bAICAkyVKlVM9+7dTXZ2tq/KtMR7771nXn31Vff9zMxMdz5r1qyZWbFihTl16pRp0KCBcTqdvirTA8H7b0pNTTX+/v6XPXnHjx9vYmJiitxOKYqX3Nxc96zeoaGhxhhjGjRoYIz5v+C9cuVKU6NGDeNyuTxe8IuCzMxMs2rVKmOMMc8884w5d+6cSU1NNStXrjTZ2dlm8+bNPq7Q+/J21PLkfV+qVCl3W0BAgMnJyTF9+vQx99xzT4HX6G2ZmZnmww8/NDt37jTR0dHm/PnzxphLM5yvWrXKfPrpp+a9994zL7zwgqlSpYoZMmSIjyv2rrwdkMzMTNOjRw/zxRdfGGOMadq0qdm7d685c+aML8uDl1WpUsXs3r3b7Nq1y9SuXdv9fI+Ojjapqanmo48+MgEBAe7XvqLg4YcfNu+8844ZN26c6du3r3n99dfNLbfcYs6cOeNesaMoylttJO+DhWrVqrk/WAsPDzfLli0z5cuXN2XKlCmSKxZ89NFHJjQ01HTs2NFMmDDBjBo1yqO/bNmyPqrMGk6nM9/377wZ7I259P6dkpJibrnllsv+P652bdu2NbGxsebkyZPGGGPuuOMO8/rrrxtjjDlx4oR7u3PnzvmkvvxwqvnflJ2dLenSou2/n3Rq6tSpWrZsmQYMGFCkZjxG8RIQEKCsrCwZY+RwOCRJycnJmjRpkhISErR8+XLdfffdunDhgux2u3Jzc31csXcZYzRw4EDt27dPGRkZKlOmjC5evKgxY8YoLi5Ozz33nJKSktSnTx9fl+o1drtdKSkpev3112WMUWpqql5//XVlZmZKunSNmDFG/v7+mjt3rqpVq6Zvv/32qr42cPfu3erfv7/Gjh0rPz8/LViwQJUqVZKfn5/7dMS8ycfOnj2r8+fP+7hi78nNzVWDBg1UqVIlGWO0Y8cOXbx4UdOnT9fp06d17733qmLFinI4HMrMzFRGRoYOHTrk67JxBUJDQ9W8eXNJUnh4uPu0cofDodzcXN19993aunWrRowYoXbt2hWJNZ27du2qe+65RytXrlTz5s1lt9s1ceJE/fjjj5Iu/R0UlclBfy8iIsI9o/fvOZ1O2e129ezZU926ddP8+fPVqVMn9evXT7NmzfLYn72a5ebmqmPHjurbt68++eQTffbZZ3r77bfds3y7XC6Fhoaqb9++WrhwoY+rvXJ2u10ZGRlas2aNXC6XMjMztXr1amVlZUm6tE9jjFF4eLg++ugj1axZUyNHjlSdOnV8XLl3BAQEqF+/frr99ttVp04d/fbbb5o2bZq2bt3qsc29996rHj16+LDS/+NnzP9/8Qf+ksTERHXu3Fnbtm1T6dKlPfoWL16s9evXa+HChUXiWkAUPw6HQ2XKlNHp06cVERHhngE3bwclOztbd9xxh/r27auffvpJ9erV09mzZ31c9ZVzuVy67bbb9MQTT+j+++/Xvn371LNnT40cOVJOp1NPP/20nn/+ef300096++23i9R1r6mpqRo6dKh7Mjnp0v9Hamqqli5dKrvdroiICF24cEHR0dF68MEH5XQ6NXfuXB9WfeXOnDmj8uXLq0SJErrhhhvkcDiUlJSk06dPKzU1Vddee617wrHGjRv7ulyvcTgcWrt2rfz9/RUSEqLu3btr9erV7hmv77nnHn300UeS5A7egwYN8nHVuBLR0dHu5YO++OILHT16VKVLl1ZQUJASEhJUvnx5/frrr6pWrZrmzJlTZH7fr7zyipYuXaovv/xSfn5+GjZsmFJSUnTkyBFt27ZN0dHRvi6xwKSnpysqKko5OTnu9/Njx45p8ODB+uyzz4rEhy2StHDhQn355Zfu96ft27erR48eeu2113Tfffe5t3M6nZet2HE1unjxosdksNL/vX9/++23cjgcCgsL08WLFxUVFaUBAwaoRIkShWqW7yvRvn17Pffcc6pQoYK++eYbSdLEiRPVtGlTdevWTdKlpQVXrlyp+Ph4X5b6f3x1qL0ocrlcJicnx9dlAP+Y3W43mzZtMufOnTN+fn4mJSXlD7c9ceKECQsLK8DqrJOSkmLGjBljwsPDTVRUlDl8+LCpWLGi6d69u+nWrZuJiIgw3bt3N927dze1a9cucqdr/S92u90sWLDAfXnN5s2bzZEjR3xclfeEhoZedr3f2bNnzaeffmq6dOliAgMDzdNPP+2j6qyzfv16ExMTYwICAsyjjz5qVq9ebYwxpkWLFub999/3cXXwFqfTaWbMmGFef/1189prr5kZM2aY9PR0k5OTY/z8/Mzx48fd23bu3Nn07t3bh9V6l9PpNPXr1zeLFy82xhizfPlyU6NGDR9X5Tvp6emXtblcLh9UUrDyTkMujrKysszkyZNNRkaGMebS38COHTt8XJX3tGjRwmzdutWjbdKkSe65iowxZseOHWby5MmF5hpvjngD8OB0OnX48GF9+eWXGjBgwB+egpaRkaGdO3eqY8eOBVyhdRISEjR48GClpKRo+PDhGjhwoH777Tc1bdpUCQkJkqScnJwiMbP3X+VwOJSenu4+Va+oGTdunJ5++mmVKVMm3/4vvvhCOTk5uuOOOwq4MmslJibq0KFDSk1NVVxcnPz9/TVmzBjNnDlTGRkZ7tmPUTS5XC7t2LFDzZs3d19W8f3336tevXpF5rRjSfrxxx913XXXSZJOnjypqVOnas6cOUXyNHMAl5ZQDAoKcr+uFTYEbwAe4uPjVa1aNZ0+fVply5b16BsyZIgaNmyo0aNH+6i6gvHaa69p8ODBioiIUHZ2tg4fPuzeeSsunE6n5s+fr2nTpun222/X22+/7euSAADA31DcDhYUdlyIDMBDeHi4jDEe1wxJ0ogRI7Ro0SJFRkb6qLKCM3r0aEVEREi6NDFRcQvdW7dudX/A0rFjRz388MO+LskS58+fv+w6zwMHDnjcX7p0qd56662CLMsncnNztXz5cv3+s/jz588rJyfHh1XBWy5cuKBly5Zp06ZN2rlzp3744QcdPXpUiYmJunjxonsyzaIkb94GnsMojr744gu1aNFCzzzzjK9LKXC5ubk6ceJEofzbJ3gD8BASEiI/Pz+PT0gfeeQRLV26VF988UWRmXgnP06nU8ePH5d0adKxqKgonT592mObhISEwjNJhwXeeustderUSe3atdOpU6c0d+7cIjOR3H+LiIhwP8+3bdum8+fPq0WLFpo9e7Ykad++fXrggQeKxASCf8bhcFw2W/9XX30lm82mjIwMH1UFb8lbjeH+++9X586d1aRJE9WpU0cxMTEqXbq0QkNDVa5cOa1Zs8bXpXrNsWPHVK5cOdlsNgUFBalEiRKqXLmyatWqpeuvv14tW7ZU3759dfjwYV+XCnjNkSNH1LFjR3Xs2FERERHq0KGDr0vyuuTkZFWoUEG1atVS7dq1Vbt2bdWsWVOVK1dWbm6uUlJSFBsbK5vNppiYGN17771KSkryddmSJC5yAeAhKChIktzXwC1fvlzz58/X5s2b1axZM1+WZrnU1FTVqlVLdrtdYWFhSk9P9zjC/+677+qxxx5Tr1699N577/mwUut07txZP/zwg+rVq+frUiwXHBysoKAgfffdd7rjjjv0ySefaP78+Ro6dKji4uK0fPlyPfPMM3ryySd9XarXOBwObdu2zX0drzFGTqdTbdu2VWBgoLKystS4cWMdOnRI5cuXdy9Hg6ubzWZTSEiIzpw5427LW4ooMzNTaWlpevLJJ/XUU0+pa9euPqzUeyIiIhQUFKTvv/9emZmZ7lvemNPT0/X2229rxIgRHssPAVerRYsWaciQIerYsaP2799fZD80t9lsCggI0McffyxjjLp3765Vq1apTZs2CgwMdM/Sf/LkSf38888aMWKE3n//fT3++OM+rpzgDeC/BAQEyBijxYsX67777lO3bt30xRdfFPnQLV3aUQsMDHR/6JC35NLFixc1aNAgrVu3TjVr1ixypx7//hqw2NhYH1djPafTqQ8//ND95n3jjTdqzpw56tOnj+bMmaOvv/5abdq0Ub169YpU6JYujb1r166KiYlRQkKCqlSpooCAAB06dEg2m02hoaHudcvz1nwuCsvuFGc7duxQbGyse/3uPCkpKVqwYIGeeOIJSdItt9yiEydO+KBC70tOTpafn5/8/f1Vt25dj75du3bp5ptvlnTpw9bJkyf7oELA+xo1aqQ1a9YUqUlv8xMcHKyQkBDdeOON7vs33nijbDabpP87c7NKlSqqUqWKmjRpol9++cWXJbsRvAHka/To0Xr55ZfVoEEDSXKffpsnNzdXFy9e1Lp163xRntdlZmYqLCzM4xR7f39/BQYGKj4+Xrm5udq1a5fuvPPOIjXrryTVqFFDtWrV+tPtAgIC1KdPHw0bNqwAqrKO0+nUlClTNGnSJLlcLk2bNk1PPPGEnn76aT3yyCNatGiRNmzYoLZt22r9+vW6/fbbfV2y1wQHB6tWrVrav3+/GjZs6HFUJDg4WP7+/u6zXvz9L12Nlrczg6tPUlKSbr31VrVp08a9VntwcLA2b96snj17qkaNGho+fLiio6PVt29fPfroo74u+YplZmaqQYMGeuCBBzzaDxw4oMGDB+vgwYNKSEhQdHS0WrRoobi4ON8UCnhZcZmP5o8+DM5r/+8PGceOHaumTZtaXtdfQfAGcBk/Pz8dPnxYEydO1Lx581SjRg33J4t5HA5HoZy44p8wxqh69eq65pprlJ2d7T6673Q6tXXrVlWpUkWrV6+WdGlHNisrq0iFkd69e7uP9v8vX331lZ5++umrPngHBwfryJEjMsboySef1KlTp9SnTx+FhIRoxowZ6t+/v/bt26d58+bp/vvv188//3zZDP9XK39/f/dOSd7XvICdt9OS9zzIzs6+bPI5XF1KliypPXv26KuvvlJAQIDKlSunbt266b777tPrr7+uAQMGuLeNiYnxYaXeY4zR2LFjtWvXLgUGBqp9+/bq16+fGjZsqHr16mn16tXu53WrVq18XC1wZZo1a+Y+QPK/BAQEqGvXrrrrrrsKoCrrJSQkuC+JS0xMVL169ZSbm6sLFy5oxYoV7vc1Sbrpppt8VeZlWE4MgIfc3FyFhITI6XRKkj788EONHDlSy5cvV7t27XxcnTVycnI0e/ZsRUZGauTIkZo7d66MMRo8eLDuvPNOffXVV1qwYIG6dOmiatWqac2aNWrYsKGvyy5wGzdu1IgRI/Tjjz8qKirK1+VcsfT0dMXExOjChQv64IMP3Ou2z5gxQ4cOHdKGDRvUpUsX3XDDDZo2bZqvy/WaRo0aad++fZd9tdlsysnJkTHGHcqvv/56fffddz6uGN5y7NgxPfPMMxo/fny+r2FOp7NIXVpgt9u1ZMkSTZkyRbNmzbpsAkHgatejR4+/9MH5Dz/8oHPnzikhIaGAKrNWpUqVtGLFChlj1KtXLy1fvlxdu3bVu+++q6eeekqHDx/WTTfdpJdeeongDaDwys7OVnh4uHJyctw7YKtXr9Z9992nzz//XM2bN/dxhdbJzc1VeHi47Ha7jDEKDAxUZmamli5dqmeeeUZdunTRzp079fTTT6t3796+LtcS27dvV2pqqu68887L+jIyMhQWFnbZaVxXq7i4OE2aNEmLFi2SdOl53qlTJ2VnZ6tGjRpavHixQkJC1KdPH505c8bjE/Sr2X8H7rxTzsuVK6ddu3ZJunTU8NVXX1VERIRmzpzp44pxpfJe2/KWi8zvbzgrK0tly5bVqVOnfFCh9zkcDt1xxx2KjIyU3W7P9xKhvLOXli9f7oMKgYKzYcMG9erVS7/++muROJOpevXq7stEYmNjdfz4cZUrV869CklgYKBefPFFTZkyRatXry40Z7cUjb0IAF6Tt55rbm6uu+2uu+7Sww8/rD59+ujChQu+Ks1yKSkpcjgcstvt7v8Hh8Ohfv366eDBgwoMDNQPP/yg3bt3+7hS62zfvl133XWXYmNjNX36dJ07d87dlzfZVlExYMAAj+f5nj179O233yo6OlqvvfaamjZtqltuuUXvv/9+kQnd+X3W7nK53N9Xq1ZNNWrUUGhoqFavXq2HHnqoIMuDBY4fP67AwED5+/trxYoVWrlypZYvXy6Hw6EVK1Zo+fLlys7O1oYNG/TJJ5/4ulyvcLlcCgoK0vbt23XdddepWbNmuu6667RhwwZdd911uu6667Ru3TrddNNNat26ta/LBbzi+++/1/79+/Pta9Kkic6cOVMkQrfD4ch3X+T37+fGGI0aNUovvfSSBg4cWGgujeSINwAP586dU4UKFXThwgWP04mdTqfq1aunOnXquK93LmoyMzOVlJSkmJgYpaSkqEGDBvruu+9Urlw59zYfffSRmjVrpho1aviwUmudO3dOy5Yt0zvvvKPjx4/r6aefLnKze0tShw4dlJycrLp166pv37765JNPlJCQoHHjxrm3CQgIUPPmzVWmTBkfVuo9OTk5Kl++vG6//Xb3xHHffPONjh49qhIlSuj111/X+vXrdfjwYT3zzDPq0aOHr0vGFUhOTlbFihXVuXNnbdy4UdnZ2e6+UqVKKTk5WZIUFRWl1NRUX5XpVRkZGWrSpImGDRumCRMmKDMz091XsmRJ94fHkZGRSktL81WZgNdNmDBBM2bMUJs2bTR06FD16dPHY8LYoiItLU1lypRxTwz6008/qX79+tq/f78cDof7ksmMjAyFhoaqUaNGeuKJJ3Tffff5uHImVwPwX3JyclSvXj33Ed88AQEBmjRpktavXy+Xy1VkjgD+3ogRI5SUlKTPPvtM+/bt03fffafw8HBNnz5dffr0Ue3atXXPPff4ukzLlS1bViNGjNCIESP06aefFtnTMP38/PTWW2/pm2++0bx58yRdOmIwefJkVa5cWdKl09FLlSql7du3+7JUr3G5XHrooYcUHBysOnXqSJJ7Yh673a6bbrpJP/zwgzZv3qzt27erXbt2ReJ6/uIqJCRECxcu1PHjx7Vu3Trt2LHDfdZDbm6u+77T6XR/36ZNGx9XfWWysrJ06623auPGjZcd5fr9UbKidPYOIElTpkxRt27dtGLFCj322GPuIF7U9luCg4O1cuVKhYWFudtcLpdSU1NljFFmZqaMMUpPT1doaKj69OmjvXv3ForgzRFvAH+ZMUa5ubnu5YaKklWrVmno0KHas2ePqlevruuuu05DhgxR8+bNNWnSJG3btk2xsbG688471a5dO3Xq1MnXJeMK3XrrrZo+fbpatmzpbhs4cKDOnz+vNWvWSJJWrFihxx9/XEeOHCmSHzblcTgcCgkJcZ92npycrMGDB2vv3r369ttvi8ys7sWVw+FQiRIlPHZU/1tWVpaysrLcE2te7ZxOp4KCgjwC9u+vb8/b/fXz8ysyYwbyZGdn64033tC6deu0detWX5fjU7/++qsqVKhQKN7DCd4AoEtHfw4dOqQGDRpo37596tq1q44fP+6eYC4pKUnvv/++3nzzTQ0aNEj//ve/fVwxrtRnn32mG2+8URUqVHC3ffPNN/rpp5/cawAXtaXj/khWVpb69++vjz/+2P2cN8bo/fff1+DBg31cHQrKH028djVyuVzau3fv//z7zcrKUlpamtq2bVuAlQEFp6itVHC1I3gDQD5++eUX1axZ87J2h8OhgICAQvHJKQAAwO+lp6erUqVKSk5Odi8ztm7dOi1evFjz588vktd9/97GjRtls9kK5WUzBG8AxZ7T6dSrr776l06h9/f3V6NGjQrlCzrwV6Wnp+vw4cOKjIx0LzMVHh5eJC8jgXT+/HnVqFFDKSkp7rYDBw64r++XpKVLl+rs2bPFZib7rVu3avXq1XrqqadUvnx5X5cDeI3T6XRPLjZr1iw988wz2rFjh2699ValpKQoIiLC1yVaYufOnXryySe1a9cuDRs2TG+//bavS7oMk6sBKPYCAgL05JNPqlmzZvmu9fp7p0+fVmJioi5cuMDpW1ep9PR0TZs2TZGRkR7Xe2ZkZGjq1KlKSUlRz549VblyZcXGxqpVq1ZF7pr+X3/9VU2bNpWfn5/H6cUBAQEKCwtTeHi4KleurFdffVUtWrTwcbW4UhEREe6jXNu2bVODBg3UokULzZgxQyNHjtS+ffv0wAMP6LHHHvNxpd41efJkLV68WFFRUe5bhQoV9Oyzz+rIkSNavXq1tm/fru+++87XpQJ/W3p6uurUqePebzHGqHTp0vr2229ls9nk7++vV199Vc8884x7ksyicinJ7505c0ZPPPGEFi9erJ49e2rHjh2F9n2LI94AICksLEy//PKLKlWq9D+3O3z4sOrWratDhw6pdu3aBVQdvCk9PV2VK1fWgAEDZIzRokWLdP/992vu3Lmy2+1KT09XVFSUpkyZokOHDmnZsmX64IMP1LdvX1+X7jWJiYmqWbOmkpOTlZmZ6b5lZGQoMzNTaWlpmjFjhrKzs/X111/7ulxcIZfLpSpVqmjNmjVq3bq1PvnkE9ntdg0dOlSDBg3S8uXLNXz48CK3bODBgwd13XXXacGCBbLb7UpNTdWCBQvUs2dPTZo0Sfv27VOLFi2Unp7u61KBv83pdKp27dpauHCh+vfvr4ULF2ro0KE6ePCgypQpo/Pnz6t8+fI6c+aMfv75ZzVo0EB2u919+nlR8dprr+mTTz7Rq6++qqZNm/q6nP+paP3PA8A/9Puj13a7XW+//bb8/PzcRwQlaeTIkSpVqpR27dpF6L6KhYSEqFSpUnr99dclXZpk7Y033tDixYslSTabTX5+fvr/2rvzuCjL/f/jr2FfBhAQFxRF1I57njKXsNQ6SZqVdSQ94d5XUbFSyyU0XCsltdyX45J77ictc8lEWkzJPKkYooKgaAKKDNvs9+8Pf9ynCUlccBQ+z8ejR8x133PzvgcG53Nf131dEyZMAG6s7/7dd99VmML77Nmz6jm6u7vj7u6Ov78/BoOBL774Qj3PxMREZsyYYee04m5YLBbWrl2Lu7s7jo6OPP744yxevJjw8HAWL17MkSNHePrpp2nSpEmFKroLCgrw9PSkSZMmPPbYY/j4+NCtWzfgxvu7fv36AISEhNisbS7Ew8TR0RFPT09CQ0PV/xfPP1NcXBePdDEajbi5uVW4ohtufDZ7++237R2jTCreqy+EEHegeBmlYqNGjaJ37944OjqqvaJRUVEEBATI0koPuT8vMVSs+APJn28haN269QM7bO126XQ6WrRoQY8ePWzaf/rpJ3r27InJZCIsLAwfHx/CwsIemg8z4uYsFgtTpkwhJiYGq9XKtGnTGDNmDNHR0bz11lusWbOG3bt306lTJ77++mu6dOli78h3zWKxUKtWLfz8/IAbK1L069cPHx8f4MZwXJPJhLe3N7/88kuJv/1CPMyKC++ioiIGDhxITk4OAwcOJCsri5o1a9o53b3z5Zdf0qJFi1vu5+joSGBg4AMzxF4KbyGE4MZs5Xl5ecD/rhAvXrwYDw8PzGYzq1evrpBXiiur69evExsbi6Io5Obmql9bLBaKiopsZq0fN26cHZPeW66urqxatYpDhw5Rq1YtGjRoQEREBGFhYQwcOJD33ntP/f1v3ry5ndOKu+Xi4kJycjKKojB27FjS09MJDw/H1dWVjz76iL59+3L8+HH+/e9/06dPH3777beH/sKi1Wpl69at+Pj4oNFo0Ol0vPDCC+zcuVO9F9ZsNqPX6ykqKpK/66JCKR6h5+DgQK1atRg5ciRw4/aiVq1a2TPaPdW9e3f+eLf0zZZCLG57/vnn+eqrr+53xJuSvzZCiErPbDZTvXp1ioqKANQh5sV/xP/4tagYzGYz58+fR1EUzGYzqampABw6dIiwsDCsVivLli2jb9++FWrpFVdXV8LDwwkPD2f27NkcOHCACRMm0KFDB1mbvoJydHQkPz8fg8HA0qVLWbVqFTt37qRz587079+fwYMHs3v3bpYvX86cOXOYNm2avSPfFWdnZ5599lmSk5Px9vamXr16PProo1y4cIHnnnvOZt8DBw7g6elpp6RC3HvFxaiLiwtTp05V20JDQxk1apQ9o91TR48eRavV3vLC2caNG3n//fcxmUwPxKodMrmaEEL8f1arFQcHB/VeqKioKJydnbFarcybN69CTkpSWdWrV08ttkNCQkhJSaF69eocPXqUjIwMQkNDadmyJU5OTnz99df4+vraOfG9ZTKZaNKkCV5eXjftKYAbQxW9vLxkcrUKIDU1lZiYGNasWQPAjh07CAsLQ6/XU79+fdatW6delLly5YrNiI+H1eLFixk2bJjNzP1//sjr4ODAa6+9xvr16+2UUog7Z7FYaNiwIYsXL2bIkCEsXryYt956i6SkJKpWrcqOHTvIy8vjiy++IDc3V53HpKIxGo2lXiA/cuQIX375JdHR0bi5ud3nZCXJJ0ghRKWXn5/P5MmT2b9/PwkJCVgsFt5//31cXV1xcHDAarUyYcIEuRewgrBYLDctNM1mM7Vr16Z27drAjd7viIgIoqKiKtQH89zcXHx8fLhw4QJLliwBbvSIREVFsXDhQhRFYejQoSxevFh6AyuIfv36UatWLfXx4cOH8ff3JzQ0lDlz5vDEE0/g6+vLihUrKkTRvXPnTnr27Enfvn1xc3PjwoULNGvWjEuXLuHl5WXveELcE0VFRej1eiIjIwGIjIxU5zbQ6/X8/vvvDBs2DIvFwu7du+0ZtVytWrWKPXv28Oabb9KhQwebba1bt6Z169Z2SlaS9HgLISq9yMhIDh48yOjRo4mIiHggroqK8lNYWEhQUBATJ05EURSmTp1KTEwMY8eOpaioCKvVirOzM0ajkby8PIKDg/nmm28qxP1xOp2O+vXr8/rrr7N06VL19goAX19fcnJyAPD29kan09krprjHnnvuOa5du0bjxo157bXX2LRpExcvXrQZeuro6EibNm2oWrWqHZPevYKCAoKCgvD19SUmJoZnnnkGRVF47733iIyMJDg4uMRz6tSpc/+DClFOLBYLbm5umEwmLBYLK1euZNy4cURERBAbG6vOdVBRfPHFFyxdupRvv/2WoKAgRo0axeDBgx/Ii4hSeAshKr2cnBy8vLxwcnLiyJEjdOnS5ZY9fenp6fcpnbjXdDodgwYNwsPDQ22zWq3odDq2bNmCwWBAq9WSk5ODj48PQ4cOxWKxsHTpUjumvjeuX7/OkiVLSE1NZdmyZaSmpqrDb1u0aMGJEydQFIWmTZty6tQpFEWRoqQC6Ny5M1OnTiUhIYE9e/YAEB8fT/369dWe8NTUVPz8/IiPj7dn1LumKAr//e9/2blzJytWrODChQvAjYtJf2QymSgsLESj0WCxWOwRVYhykZ+fj7e3N0ajUb097ty5c7zxxht89dVXFXYkk06nY/ny5Xz88cfUq1ePH374wd6RSpDCWwgh/iAzM5OEhIRS7+U2GAzk5OTQr1+/+5xM3C9Go5ENGzbQq1cvXF1d1avoDRs2tHe0e8ZkMuHq6nrT+17/SIqSiqFjx4588MEHhIaGqm0DBgwgOzubnTt3ArB9+3ZGjx5NcnLyA9lTdCesViufffYZMTEx1K1bl0WLFtksQWSxWMjLy6NKlSr2CylEOShey/6PSpvPo6LJy8tjz549JZbNfBBI4S2EEEL8gclkIj8/v8JNqPZn2dnZuLu7l7q9qKiIvLw86tWrdx9TifLw1Vdf8fjjj1OjRg21LSEhgcTERPr37w/c+Hn/1e/Dw+z69etERUXRs2dPXnrpJXvHEUJUUlJ4CyGEEKDeCzdt2jS6dOnCokWL7B1JCCGEEGVgNBqZP38+I0aMUEftpKWlYTQaH5gRa1J4CyGEqPQOHDhAVFQUaWlpRERE8Pbbb9O0aVN7xyp3xR9U+vfvr86GWyw5ORmTyVQpXgdRsSiKwrlz50pdYshqtVJQUECdOnVklnMhKgiDwYCHhwcWi0UdVr9r1y5efPFFdDrdA3FvuxTeQgghKrWFCxcyYsQIIiMjmTRpEv7+/vaOVK6sVisnT56kSZMmWCwWPDw8OHv2LDVr1mTv3r2EhYXh6urKhg0b6NOnD2az2d6RxR3Kz89n2rRpeHl5qfd2KopCQUEBU6dOJTc3l1dffZVatWoREhJC+/btCQsLs3Pqu2c2m3FxcSl1DoPi1+Lrr7+mc+fO9zueEOIuGAwGVq9erc7OXlxkFy8fmJ2dTWBgIDqdjoSEBNq0aYNOp0Or1do5uRTeQgghKrmUlBT0ej1NmjSxd5T7Ij8/Hx8fH37//XcCAgJwcHDg0qVLuLu74+fnx7Vr1/Dx8SE+Pp5OnTrJ5GoPsfz8fGrVqkW/fv1QFIU1a9bQp08fli5disFgUGc/njJlCklJSWzdupVVq1bx2muv2Tv6XXNxcSE7O/umE0y5u7uj1+txdHS0UzohxJ0yGAxUrVqVtm3bcvjwYdq0acOFCxdISkqiSpUq5OTkEBAQQHZ2NomJibRo0YKCgoIHYqnYm0/bK4QQQlRgRqNRHYYaEhJi5zT3l5ubG4qiqAWJi4sLzs7OaLVam/aK3vNfGbi6uuLn58fcuXOBG5OszZs3j3Xr1gHg7u6ORqNhwoQJwI017r/77rsKU3g7OTndtLjWaDRSdAvxkHJxcaFevXrs27eP5s2bs2/fPvWWqOLVOor/fddoNGg0mgei6AYpvIUQQlRC9evXL9NkK46OjoSHhzN48OD7kOr+cHR0tPlg4ujoiLOzM46Ojjg4OKhL6Tk4OKhD+cTDydnZ+abLBxX/jP9cfLZu3Zonn3zyvmQrb3q9noMHD5b4HVYUBUVROHDgADVr1qRRo0Z2SiiEuBN//JtW/HXxZGoajYb09HQALly4QEpKSon5S+xJCm8hhBCVTo8ePdBqtaWu117sxx9/JDo6ukIV3tu3bwcgLi4OBwcHFEVhx44deHh4oNFo2L59O4qicPbsWapWrWrntOJuXb9+ndjYWBRFITc3V/3aYrFQVFRks2b3uHHj7Jj03jEajVSrVo1hw4YB2NzrrdFoqF27Nj179uTVV19l8eLF9owqhLgHigvw3Nxc6tWrh6Io1K1bF41GwxNPPGHndP8jhbcQQohK55NPPinTfnv27GHIkCHodDq8vb3LOVX5MxqNDB8+HIBBgwapbR999BEODg40atSImJgYADIzM3nsscfsllXcG2azmfPnz6MoCmazmdTUVAAOHTpEWFgYVquVZcuW0bdv31JnAX/YnDlzhkuXLgFQUFDA9OnTmTx5Mg4ODixbtox+/frh7Oxs55RCiHul+MKaj48PGRkZatt7772Hj4+PPaPZkMnVhBBCVGrx8fHodDq6detWYltBQYHaE1xRKIqCo6MjBoMBZ2dnvLy8uHjxos2HE6PRyGOPPcaoUaMYOHCgHdOKu1WvXj212A4JCSElJYXq1atz9OhRMjIyCA0NpWXLljg5OfH111/j6+tr58R3Z/v27YwcOZLz588DYDKZ8PT0xGg0EhERQUpKClu3biUwMNC+QYUQd0RRFB599FGOHz9OixYtOH78OI0bN+a3336jWrVqnDt3Di8vLxITE+nSpQu//PLLAzN6S3q8hRBCVGrx8fHExMQQHBzMG2+8weDBgwkICAB4INb9vNcsFgsajQaz2az2+imKwpkzZ9BqtWi1Wnr37k21atXo37+/fcOKu1L8s/4zs9lM7dq1qV27NnCj9zsiIoKoqCjWr19/v2PeU+3btycjI4PPPvtMHUbv6OjI6tWrsVqtDBo0iG+++Qa4UZTn5OTw7rvv2jOyEOI2GI1Gzp07x5NPPqn+32Qyqds2bNjAqlWruHr1Khs3bnxgim6QHm8hhBCCrKwstm7dypIlS0hJSSE6OpqxY8faO1a5KCwsRKvVkpWVhb+/P+7u7ly4cIEPPviAxYsX4+3tTfv27dmwYUOFGXpcWRUWFhIUFMTEiRNRFIWpU6cSExPD2LFjKSoqwmq14uzsjNFoJC8vj+DgYL755htatWpl7+h3pTh/8QW0ffv2YbVaqVu3Lo0bN1aHpZpMJvLy8jh8+LDdsgohbo/RaGTVqlU2/z4Vr+Pt7u5Oeno6GzZsYM6cObRo0YI5c+ZQp04dOyb+Hym8hRBCiD/YvHkz27ZtY8OGDfaOUi4KCwt54403mD9/Pv7+/jg6OpKeno6fnx/ffvsta9euZfv27YSFhTFz5swyzf4uHkw6nY5Bgwbh4eGhtlmtVnQ6HVu2bMFgMKDVasnJycHHx4ehQ4disVhYunSpHVPfvUGDBvH3v/9dnVzNz8+PvXv3EhUVRbVq1YiNjaVx48Z2TimEuJeMRiNubm5YrVbgxsieUaNGsXbtWk6fPq1eiLMnKbyFEEKISkqv1+Ph4UFycjINGjRQ2y9cuMCoUaP47rvvSE9Pl57vCqp4WGavXr1wdXXl22+/JSgo6KG/2PLBBx9gNBqZPHkyRqMRLy8vDAYDVquVd955hyVLlhAbG6tONCiEePjp9Xref/99pk+fbrNU4r59+3juuefsmOx/pPAWQgghKimLxUJcXBzt2rWz6RUtlpCQ8EAtxSLuLZPJRH5+/kM/odqf5eTkqOdkMBjYsmULERER6vZPP/2Upk2bPjAfxoUQlYMU3kIIIYQQlYjFYmHlypVMmzaNLl26sGjRIntHEkKIO2YymRg7dizvvPMOtWrVsnecUjnYO4AQQggh7q958+ah1+sB+PDDD5kyZYq67rGo2A4cOEDz5s15++236dy5c4Udbp2dnV1i/d6TJ0/aPN6yZQsLFy68n7GEEHfJarWyd+9eCgoK1DZnZ2fmzJlDXl6eHZPdmhTeQgghRCUzduxYdfmV2NhYzp49S1FREVevXkWn06HT6ZABcRXPwoULCQsL49lnnyU9PZ2lS5fStGlTe8cqF1qtVp2bIC4ujuzsbJ588kkWLFgAwPHjx+nfvz+ZmZn2jCmEuE0ajYYuXbqwZcsWm3YXFxfc3d3tlKpsZKi5EEIIUYkcO3aMDh06cOzYMWrWrElwcDCZmZnqjLAajQZFUQgODubcuXM3XQdaPJxSUlLQ6/U0adLE3lHKndVqpXbt2uzcuZOnnnqKTZs2YTAYGDRoEAMHDmTbtm1ERkZW2GUDhajI3N3d0Wq1HDt2jNq1awPg4+NDUlISNWvWtHO60kmPtxBCCFGJvPbaaxQWFtKpUycOHjyIs7MzcKO3wN/fn0uXLpGWlkZubi7nz5+3b1hx14xGo/p1SEhIhS+6LRYLq1atYsuWLTg6OvL444+zePFiwsPDyc/P58iRI6xfv56QkBApuoV4SDk5OdGpUyf++c9/Yjab1TYnJyc7J/tr0uMthBBCVDIBAQFkZWUBEBQUxIULFwCoU6cO6enpAGzdupWuXbs+8EP3xF8r6/Jgjo6OhIeHM3jw4PuQqvwYjUYaN25MTEwM0dHRDB06lDFjxhASEkJeXh5r1qwhODiYTp06sXbtWrp06WLvyEKI2+Tt7c2JEyeIiIigQYMGvPTSSwwYMIC5c+fi5eWl7ufq6krHjh3x9PS0Y9r/kcJbCCGEqESWL1/OO++8w8qVK2nZsiVPP/00S5Ys4eLFi8TExBAbGwvcmCU2NzeXUaNG2TmxuBsjR45Eq9Xesifoxx9/5OjRo2RnZ9+nZOXHYrGgKAq1a9fmpZde4sqVK5w8eZJJkybx5ptvcvz4cX7++WcGDx7Mb7/9RkBAgL0jCyFug5eXF6dPn+bKlSu8/PLLKIrC5cuXqV69Og4O/xvQnZ2dzQsvvFDifnB7kcJbCCGEqCQsFgsvv/wy33zzDV27dmXIkCG88cYbjBkzhs2bN3P06FFat24N3Ci8dTodx48ft3NqcT/s2bOHIUOG8Ouvv+Lt7W3vOHctPz+foKAgcnJyWLVqFQMGDODy5ct89NFHJCUlsXv3bl544QX+/ve/M23aNHvHFULcBq1WS3JyMoGBgWpbQEAASUlJ+Pv7q21z5sxhypQpXL161R4xS5DCWwghhKhk/jjU/I/Dyxs0aMDZs2ftGU2Uo/j4eHQ6Hd26dSuxraCgAA8PjwozmV5qaioxMTGsWbMGgB07dhAWFoZer6d+/fqsW7cOV1dXwsPDuXLlik0vmRDiwebm5kZKSopN4e3v709SUpLNCJZvv/2WM2fOEBkZaY+YJchfGSGEEKIS+fjjjzEYDCxatIiEhASbZcOsVqsdk4nyFh8fz0svvURISAgffPCBevEFwNPTs8IU3QD9+vVTJ10COHz4MD///DM+Pj7MmTOHJ554gg4dOrBixQopuoV4yJjN5hL/XpnNZnWZzGLPPPPMA1N0gxTeQgghRKVy9uxZTCYTJ06cIDMz06Y4ycrKYuDAgQwcOJDhw4fbMaUoDxMmTODKlSuMGTOGLVu20KBBA2bMmGHvWOXC1dWV5ORkevfuzY4dO0hLS2P8+PHs2LEDLy8vvv/+e3bt2kW7du3sHVUIcRsMBgNWqxWDwVCi/c9tDxoZai6EEEJUMj4+PmRlZeHi4kJAQADHjx/Hy8uL8ePH4+LiAoBGo1EnWhMV0+bNm9m2bRsbNmywd5R7rnPnzkydOpWEhAT27NkD3Ojxr1+/PrVq1QJuDEf38/MjPj7enlGFELfJYDDg6uqqPjaZTLi6uvLrr7/SvHlzOyb7a1J4CyGEEJWMl5cXaWlp+Pn54eHhgcFg4N///jcDBw60dzQh7omOHTvywQcfEBoaqrYNGDCA7Oxsdu7cCcD27dsZPXo0ycnJMtxciIeY2Wzmq6++omPHjvj4+Ng7Tqmk8BZCCCGEEBXKV199xeOPP06NGjXUtoSEBBITE+nfvz8ARUVFsk69EOK+kcJbCCGEEABcuHCB2rVrV6hJtoQQQlQsU6ZMwcnJCQBFUfDz8+Nf//oXubm5Nv9+WSwWLBYLDRo0sFdUGzKuRgghhKgkcnJyePXVV0vd3qRJE65du6Y+zsjIuB+xhBBCiDJbsGCBOou52WzG2dmZrVu38uijj9KgQQNatWpF48aNadSoEYMHD7Z3XJX0eAshhBCVRF5eHk2bNiU9PZ2JEyei0+nQaDR4eXkxefJkqlWrRlpaGu7u7pw/f56mTZuSmJhIcHCwvaMLUSb5+flMmzYNLy8vtedLURQKCgqYOnUqubm5vPrqq9SqVYuQkBDat29PWFiYnVMLIW5H8+bN+eabb3j77bf57LPPiImJoVmzZiiKwvTp01m7di0zZ84kMTGR48eP2zuuSnq8hRBCiErC1dUVNzc3ADZt2kTVqlXx9/dn3bp1wI21nItnit28eTOtWrWSols8dBYtWsSVK1e4fPkysbGx/P7778yaNQtHR0dcXFyIj4+ncePGpKam0r17dzZt2mTvyEKI26DRaHB2dmbbtm24ubmxfft2m20P6u1STvYOIIQQQoj7w8nJCUdHRwCcnZ0ZP348AGvWrFG3P/7446xfv55t27YRHR1tt6xC3AlXV1f8/PyYO3cucGOStXnz5qkXl9zd3dFoNEyYMAGAwsJCvvvuO1577TW7ZRZC3D6z2YzVasVisWC1Wu0dp0yk8BZCCCEqCQcHBy5evEjXrl1JT0+na9euKIqi9g44OTkxceJEunTpgtFo5IUXXrBzYiFuj7Oz8017u4onYiq+8FSsdevWPPnkk/clmxDi3jCZTGRlZTF79mxSU1OZMGECFouFAwcOkJOTw6ZNmzhz5gzXrl1j1apV9OvXz96RASm8hRBCiErF39+f8ePHM2DAAMaPH4+iKAwaNAiz2YxGo6F79+6cOXOG9evXy9rG4qF0/fp1YmNjURSF3Nxc9WuLxUJRUZHN7/W4cePsmFQIcScKCwt55ZVXAPj0009p1qwZ0dHRJCcnq8sFPvfccxiNRhITE+2Y1JYU3kIIIUQl4uHhQWhoKFqtltDQULW9T58+6ozmp06dIi0tjfj4eJ5++ml7RRXijpjNZs6fP4+iKJjNZlJTUwE4dOgQYWFhWK1Wli1bRt++fXFxcbFzWiHE7UpLS8NqtRIVFaW2rV69muI5wx0cHPjHP/6hFucPCpnVXAghhKhEnJ2d8fX15fr161SpUgVFUahatSrR0dFERUURGxvL7Nmz6dWrF/n5+cyePdvekYW4LfXq1VOL7ZCQEFJSUqhevTpHjx4lIyOD0NBQWrZsiZOTE19//TW+vr52TiyEuBPu7u5Mnz69xHv44sWLrFu37oHq7QYpvIUQQohKpVGjRvz666+0bt2ahIQErFYrLVu2JCkpiYYNG/LII49w7do1Pv74Y0aPHs2hQ4fsHVmIMrNYLDRs2JCUlBTgf4W3v78/V69eBW7c711UVERERAROTk6sX7/enpGFELfBbDbTrl07atasye7du+nYsaO6Gkcxq9WKg4MDer2e3Nxcjhw5Yqe0tmSouRBCCFFJFM/+6urqitVq5eDBgyiKos4IazKZ2LFjB0eOHKFq1aqcPHnSzomFuD0Gg4Hc3Fzmzp2LoijodDrmzp1LYWEhcOMDuaIoODg4sHTpUoKDg/n5559p1aqVnZMLIcpCURQmTpyIu7s7+/fvJzIykoCAgJvuq9frKSgouM8JSyc93kIIIUQlUVRURKNGjUhLS+Nf//oX165dw2Qy4efnx5YtWwgMDCQtLQ1nZ2euXr1KQEAAV65cKfVDjRAPGp1Ox6BBg/Dw8FDbrFYrOp2OLVu2YDAY0Gq15OTk4OPjw9ChQ7FYLCxdutSOqYUQd8LBwYGgoKASqxUUr9Zx7ty5B2pNb+nxFkIIISoJvV6Pj48PABs2bCixPT8/n8LCQnx8fHBzc2Pnzp1SdIuHire3Nxs3bix1u5OTEytXrsTNzQ2A8PBwgoKC7lc8IcQ9dPny5Zu2m0wmCgsLH6iiG6THWwghhBD/36lTp2jUqBEFBQXo9XopukWFYzKZyM/PlwnVhBD3nSzQKYQQQlRC33zzDevWrWPnzp0cPHiQY8eO4evri4ODA9HR0dSpU4eZM2faO6YQ94TFYmHZsmU0bNiQ6Ohoe8cRQlRCMtRcCCGEqISuXLlC//79+dvf/oZOp0On05GXl8e2bduYNWsWVatWJTY2lnfffdfeUYW4KwcOHCAqKoq0tDQiIiIYPny4vSMJIe7CqVOnePHFF/Hw8PjL4eRFRUXk5uaSmZl5H9OVToaaCyGEEJWQXq+nZs2aHD16lJCQEAAGDRqEj48PM2fOJCsri9q1a2MwGOycVIg7t3DhQkaMGEFkZCSTJk3C39/f3pGEEHfp999/JzAwkJUrVwI3JlMbOHAgixcvVpcWMxqNREZGsnz5cgYMGGDPuCopvIUQQohKZNq0adSpUweAefPm0axZMzp16gTAhQsXqFGjBhqNhtdffx1PT08sFos94wpxV1JSUtDr9TRp0sTeUYQQ94hOp8PX19fm3ycHBwfy8/PVFQ0MBgMeHh6YTCYcHB6Mu6tlqLkQQghRSRQVFbFnzx58fHzQaDR4e3uzYcMGsrOz1X3MZjPOzs707NnTjkmFuHNGoxEXFxcAdTSHEKLi+PPyYQ8L6fEWQgghKilFUQgMDOSHH34oUaCkpaXRuHFjCgsL7ZROiDsTFBREw4YNb7mfo6Mj4eHhDB48+D6kEkLcK/n5+fj4+Dx0Pd5SeAshhBCVzPr164mPj8fFxYVdu3ZRr149GjdubLNPYmIiqamppKSk2CmlEHdm5MiRaLVanJz+emDnjz/+yNGjR21GfAghHnw5OTlUrVrVpvB2dHQkPz8fd3d34H+Ft9lsfmDW85ah5kIIIUQlYrVaCQwMxNvbGzc3N/7xj3+wfv162rdvb7Nfp06dmDRpkn1CCnEXPvnkkzLtt2fPHoYMGYJOp8Pb27ucUwkh7hWdToeiKOp8JXBjBNcjjzxiU2QrikLdunVJT0+3R8wSpMdbCCGEqESef/55evTowcCBA3FwcMBkMuHv788PP/xA8+bN7R1PiHsqPj4enU5Ht27dSmwrKCi45XJEQogHT3Z2NvHx8X/5/lUUhcLCQgoKCujTp899TnhzUngLIYQQlUReXh69e/cmLi6OatWq8dRTTwFw9erVUpdZWrFixf2MKMQ9NW3aNGJiYggODuaNN95g8ODBBAQE2DuWEOIuFBQU4OnpWaZ9FUV5YC6uSeEthBBCVDKFhYWsX7+eGTNmcO7cOZ5//nmef/55ij8SmEwmcnNzycvL49NPP7VvWCHuUlZWFlu3bmXJkiWkpKQQHR3N2LFj7R1LCHGHvv76a15//XW8vLxK3UdRFPR6PdevX8dkMt3HdKWTwlsIIYSopMxmM59++ikTJkxgypQpjBkzxt6RhChXmzdvZtu2bWzYsMHeUYQQdygtLY1ffvkFd3f3UnuzrVYr+fn55OfnM2DAgPuc8Oak8BZCCCEqucTERBo2bKiufSyEEEI87KxW6wOzlBjAg5NECCGEEHbRtGlTKbqFEEI8NAoKCvDz8+Pll1/mzJkznD9/vsQ+CQkJhIaGkp+ff/8D3oQU3kIIIYQQQgghHhru7u4UFhYSHh6OyWQiJCSE6tWr89prr7F582YsFgu7du3C3d0drVZr77iADDUXQgghhBBCCPGQOHDgAPXr1+dvf/sbycnJWK1WGjduzJEjR/jpp59YvXo12dnZ5ObmEhcXR8OGDe0dGQAnewcQQgghhBBCCCFupbCwkLCwMLy9vTEajbRp00ZdMqxZs2b4+vqSmprKsmXL0Gq1uLm52TuySoaaCyGEEEIIIYR44Hl4eKDX68nOzsbV1ZVLly5x+fJlNBoNjRo1omPHjjg7O3P8+HFGjx5Nt27dHpjlxKTHWwghhBBCCCHEQ8HBwQGz2YzJZOLdd99Fo9FgMplo3bo1bdu2JSgoCJPJRGRkJOvXrycjI4Pg4GB7x5Z7vIUQQgghhBBCPDwMBgOxsbE4OzujKApms5nCwkKuX79ORkYGhw8fpnHjxkyaNImOHTvaOy4ghbcQQgghhBBCiIfIZ599xnfffcfy5ctJTU1l9erVahEOkJeXR2pqKnv37iUxMZHAwEA7J5Z7vIUQQgghhBBCPEScnJwwm80AXLlyhf379+Pp6YlWq0Wr1bJw4UKGDx/+wBTdID3eQgghhBBCCCEeIp9//jkDBgzg6aef5oknnkCn0zF37lx1e7Vq1cjMzLRjwpKkx1sIIYQQQgghxEPDbDbTuXNn+vbty4kTJ1i4cCHOzs5Uq1aNatWqYbVacXNzo2/fvvaOqpLCWwghhBBCCCHEQ8NqtVK9enUiIiL44osv+Pbbb/H29mb27NlkZmaSnZ2NXq9n5cqV9o6qkqHmQgghhBBCCCEeaunp6dSpU8feMUolhbcQQgghhBBCCFGOZKi5EEIIIYQQQghRjqTwFkIIIYQQQgghypEU3kIIIYQQQgghRDmSwlsIIYQQQgghhChHUngLIYRQTZo0iZkzZ9rt+wcHB5OdnV3q9h49evDuu+/ex0Tlo3Xr1hw4cAAo/Zxv9VrcT8eOHSM0NBStVsvf//539u/f/5f7FxUV8eabb1KtWjVq1KjB2LFjMZvN6vbg4GCcnJzw9fXl2Wef5ddffy1TjszMTEaPHk2DBg1wd3endu3a9OvXj8TERHWfuLg4unXrVuoxLl26REBAAEePHi3T97SXe3Gut8Pe730hhKjopPAWQgjx0AgODqZWrVr2jnFXzp8/T3p6Ok8//bS9o5RJQUEBL7zwAsOGDePatWt8+umn9O7dm7S0tFKfM3r0aAwGA6dPnyYpKYnc3Fw++OADm31+//13rly5QlRUFK+88goGg+Evc/z666889thj6PV6du3aRX5+PgkJCTz22GN06tSJjRs3lul83NzceOSRR/Dy8irT/vZwr85VCCHEg0MKbyGEEA+NmTNnMnLkSHvHuCtbtmzhlVdewdHR0d5RyiQ7O5vZs2cTERGBi4sLHTp0oE2bNiQkJJT6nLi4OMaOHYuvry9VqlRh9OjRbN++vcR+Li4uvPrqq9SqVYvTp0+XeryioiJ69OjBxIkTmTdvHo888giOjo7UrFmTt99+m/3793PmzJkynY+fnx8//PADjzzySJn2v9/u5bkKIYR4cEjhLYQQldikSZPw9fXlb3/7G3FxcWr70qVLCQkJwdvbm4EDB6LX622e98knnxASEoKrqytNmzZlzZo16rbz58/TrFkzTp06RceOHfHw8KBVq1b88ssvAOzatQsnJyf1PwcHB1q2bInFYgHg+vXr9OvXD29vb+rWrcu6devUYw8fPpzPPvvspufyzDPP8N1339m0TZkyhevXr9u0de3ald27dwOQlZVF3759qVKlClWqVKFPnz6cP3+e4OBgdX+tVktGRgYvvfQSWq2Wxo0bs2/fPptjZmRk8K9//YsqVarg7+/Pm2++ydGjR2nWrFmJnJs3byY8PPym5/BXNm7cSLNmzXBzc6Np06Zs3LiRd999V309Jk2aRGxsLDExMVStWpWaNWuyYsUKFEVh6tSpVK9enZo1a5Z4/VJSUujevTtarZaAgADeeustjhw5QseOHQGoW7cuvXr1Am4UhZs2beLIkSO0a9eu1Kwvvvgi0dHRZGZmkp2dzfvvv0/16tVL3T83N/cvL0Rs3LiR+vXrM2jQoJtub968ORMmTLBp+/7772nVqhUeHh506tSJ1NRUdZtWq7X5+lY/3zNnzvDiiy+i1Wrx9fUlIiKCy5cvq9sPHTpEo0aN8PHxYcKECVitVnXbX71X7se5Auzfv5/WrVvj5uZG/fr1mT9/PvPnz2fSpEkAtG3blilTpjB27FiqVKnyl/mEEELcGSm8hRCikkpKSuI///kPqampLF26lPPnzwOwevVq4uLiOHz4MGfOnOHq1atMnDhRfV50dDTx8fHs3buXvLw8VqxYwdy5c1mwYIG6z9WrV+nXrx8zZszg6tWrDBkyhJdffhmTyUTXrl0xm82YzWYMBgMtW7Zk/vz5auH1+uuv88wzz5CVlcW6desYNWqUzX2tpRk0aBArVqxQH5tMJhYsWGBT6Fy4cIHTp0/TuXNn8vPz6dChA35+fpw8eZLz588TGhrKP//5T5vjms1mevTowdChQ7l69SozZsygZ8+e6v3XWVlZPPXUUzRo0ICkpCSSk5MJCgqif//+JTKmp6dz/vx5OnTocOsf0B8sX76c9957j08++YScnBw+//xzlixZwldffWWz38KFCzGbzaSlpbFr1y7GjRvHsGHD0Ov1pKSksHfvXqKjo0lJSQFuXDB4+umnad26NampqSQmJlKtWjUGDhx40xyBgYH07NmTAQMG/OWQ/0mTJpGcnEz16tUJCAggPj6e2bNnl9gvOzubKVOm4OLiQtOmTUs93v79+9XivyxOnz7N6NGjWb16NVeuXOHZZ58t9fm3+vlevHiRsLAwevfuTWZmJmfPnqVFixZ07NgRnU4HwMiRI1myZAnJyck4OTlhNBqBsr1Xyvtc9+zZQ0REBGPGjCE7O5u9e/dy8OBBFi5cqO7z008/ERMTw4wZM0pcqBJCCHGPKEIIISql5ORkpVWrVorRaFTbJk6cqDRp0kSxWq1qW1JSktKkSRNFURQlIyNDqVevnmIwGGyOlZmZqdSsWVMxm81KamqqAig//fSTzT5PPPGEcuTIEZu2+fPnK71791Yf161bV5k+fbrNPuPGjVNiY2MVRVGUqKgoZeXKlTc9H71er9SpU0fJy8tTFEVRPv/8c6Vjx45K8+bN1X0mTZqkTJs2TVEURYmNjVV69epV4jhz5sxR6tatqz4GlM8//9xmn/DwcGXTpk2KoijKiBEjlLfeeqvEccaMGaM0bdrUpm3WrFnK4MGDbdrq1q2rZGVllXh+cbter1eqVaumnDhxwmZ7Xl6eEhQUpL4eEydOVNq0aWOzz+DBg5W2bdvatA0bNkxZvXq1+vW4ceNKfO+RI0cqHTp0KNGen5+v7N27V2nYsKGydu3aEtuLhYeHK3369FEuX76sXLlyRZkwYYKyb98+m3NzdnZWAAVQJk6cqJjN5lKP99xzzyl79+4tdfsfHThwQHF2dlbS09PVNqvVqgQGBiqZmZmKoiiKp6enuu1WP99hw4YpCxcuLPF9Ro4cqcyePVtRFEV58sknlV9++cVme1neK/fjXJs0aaLs3r3b5nlms1lp1aqVMnHiRLVt4sSJyscff1ym7yuEEOL2SY+3EEJUUg0bNiQsLIw2bdrw448/qu3du3dHo9Goj0NCQvj9998B+PHHH0lLS8Pb2xs3Nzf1v6CgILKystQhroGBgbRp08bm+zVo0EA9Dtzo7fz444/5+OOPbfZ79dVXbR7/8fv/FVdXV1555RV14qklS5bw0UcfUaNGDX744QesVitr1qxRe3MPHjxI7969SxynZ8+eNo81Gg2vvPJKqeeyf//+m/YQ32w4+Z0MMz9x4gR16tQpMWxdq9Xywgsv2LQVDw8vFhAQwFNPPWXT5u/vz9WrV4GyvwbFPD09ee655/jss89KnQH7v//9L8ePH2fFihXUqFGDatWqMXnyZCZMmMCVK1fU/S5duoTZbObEiRMcOnSIIUOG3PwFAKpWrUpmZmap2//siSeeICgoSH2s0WgIDg6+6e/RrX6+Bw8eZMSIETa/725ubixYsIBjx44BMGvWLHr06MGsWbPU2dvL+l4pz3PNzs4mMzOTsLAwm+c4OjrSo0ePMn8PIYQQd08KbyGEqMSmTZvGwoULGTp0KKtXrwbAx8fHZh9nZ2ebGafDw8PR6/Ul/jOZTDRo0OCmx4AbE2n98Tjjxo3jrbfeokaNGjb73er7AyQmJtrcJz527FgA/u///o+VK1eSnJzM9evXadu2LZGRkSxZsoR9+/bRokULatasCdwoUBRFueVr5ObmhouLS6nnYrFYcHd3L/E8Jycnm8cXLlzg3LlzJYrjWylrTgBfX98SGfz8/GzaHBwc1OKwLMdOSkri2rVrNm2PPvooly9fpqCgwObn0LNnT06fPk27du1szt/BwYHGjRvz/fff2xzH0dGRZs2asW3bNtasWUN+fj49e/a0OWZBQQGdOnVi27ZtZXoN4Oa/fzf7PYJb/3zhxizjf/59NxgM6numbdu2JCQkkJycTNeuXdXX9FbvlfI+1z9eQBNCCGFfUngLIUQl17ZtWzZu3Kj2YDo4lP5PQ7t27fj+++/Jy8uzac/IyGDMmDHq4786BkBCQgKHDx/mrbfeKrHtVs8FaNq0qXqfuNlsZsaMGQA0a9YMq9XKO++8w+DBgwF4+eWX+f7775k5c6baBjd6h9euXVvi2H9equlWedq3b3/TQumLL76webxlyxa6d+9eoiC/lebNm3Px4kVOnjxp056fn8+uXbts2m42Qdlffb+yvAZbt25l1qxZNtsTEhJo0qQJnp6eNj+HjRs3EhISQlJSks3+iqLw3//+t8RFlmLOzs64u7uj0WjYuHGjzTE9PT3p3bs3P//8M1u2bLnp88+cOWNzz3JZfofKum/79u3ZuXNnifbY2Fib9cf9/PxYsmQJOp2OY8eOlem9Ut7n6u/vT40aNdTJBItZLJZSjy+EEKJ8SOEthBCVVFxcHAsWLKCwsJBdu3ZRt27dWz6nVq1aRERE8Morr3Dq1CmMRiM//PADYWFhZV6eSVEUhg8fzpw5c267CC2LN954g7i4OCIiIoAbhefrr7/O2bNn6dy5s7rfkCFDOHnyJCNGjCAjI4Pr16+zaNEi1q9ff1vfb/z48cybN4/58+dz7do1rl69yty5c9mwYYPN+W3evPmOhve6uLgwffp0XnrpJfbt20dRUREnTpzg5Zdfvuu1qKOjo1m3bh0ffvgh2dnZZGVlMW3aNA4cOKDu079/f1atWsWuXbswGAz8/PPPREZG8v7779/0mK1atcLZ2ZkJEyZw7do1srOzGTlyJE5OTiVuPwC4fPkyffv2pVOnTnh6et70mO7u7mzbto3hw4czbtw4zp49i9VqJTMzk0WLFhEaGlrmUQG3a/z48cyfP59ly5ah0+nIzs5m4sSJrFy5kgYNGlBYWMjIkSO5dOkSv/32G2lpaQQGBt7xe+Ven+snn3zCgAED2Lx5MwUFBZw7d45evXqpE8AVc3BwwGQy3fHrJIQQ4q9J4S2EEJVUixYt2LNnD1WrVmXz5s18+umnZXre9OnTef755+nWrRve3t4MGTKE6Oho/u///q9Mz1++fDlHjhyhc+fO6hBbNze3uzgTW7169WLo0KE2RengwYOJjIy06R309PQkLi6OnJwcmjVrRnBwMEePHmXr1q239f3q1KnDvn37+PLLL6lduzaNGjUiKSmJBQsWqMOAMzIyOHPmDM8888xNj1GjRg31tbhZr3D//v2ZMWMGo0aNUpezGjFiBM8///xtZf2zmjVrEh8fT0JCAvXq1aNJkybodDqWLVum7lOrVi22bNnC1KlT1e89efJkOnXqdNNjajQaNm/ezOnTp6lbty5NmzYlOzubL7/80uZCRI0aNXB0dOSxxx6jSpUqNjPS38zjjz/Ozz//TF5eHs8++yzu7u40b96cffv28Z///IeoqKi7ei1KExQUxJ49e/jPf/5DYGAgjzzyCOfOnSMuLg5PT088PDyoXbs2jz76KM8884w6rwDc+XvlXp7rP/7xD9avX8+sWbPw9/cnLCyMLl26lFiurF27dnz44Ye8/fbbt/8iCSGEuCWNUl6XiIUQQohK4MsvvyQoKIhHH33Upn3JkiUkJiYyd+5c5syZw4kTJ2wKWiGEEEJUHtLjLYQQQtwFLy8vunfvzv79+1EUBavVyo4dO/jwww/VnskaNWrc9H52IYQQQlQO0uMthBBC3KW4uDgmT57MqVOnMJlMtGnThk8++YRGjRrZO5oQQgghHgBSeAshhBBCCCGEEOVIhpoLIYQQQgghhBDlSApvIYQQQgghhBCiHEnhLYQQQgghhBBClCMpvIUQQgghhBBCiHIkhbcQQgghhBBCCFGOpPAWQgghhBBCCCHKkRTeQgghhBBCCCFEOZLCWwghhBBCCCGEKEdSeAshhBBCCCGEEOXo/wEhtNWEOKuwUAAAAABJRU5ErkJggg==","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-175 **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-175\n","是       1149\n","不重要      833\n","不是       679\n","问法错误     292\n","回答正确      47\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-350 **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-350\n","是       1181\n","不是      1145\n","不重要      374\n","问法错误     268\n","回答正确      32\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["for col in df.columns[5:]:\n","    print(\"*\" * 10, col, \"*\" * 10)\n","    print(df[col].value_counts())\n","    plot_value_counts(df, col)"]},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[],"source":["import re\n","\n","\n","def clean_up(df, model_name):\n","    df[model_name] = df[model_name].apply(\n","        lambda x: re.sub(r\"回答.*是\", \"是\", x)\n","        .replace(\"是男孩\", \"是\")\n","        .replace(\"。\", \"\")\n","        .strip()\n","    )\n","    return df"]},{"cell_type":"code","execution_count":10,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat\n","不是           1611\n","是            1364\n","不重要            12\n","问法错误            2\n","小男孩             2\n","小男孩放的           2\n","他要带走的是物品        1\n","小男孩的哭声          1\n","小男孩和他的爷爷        1\n","是男              1\n","破旧              1\n","是小男孩            1\n","破旧帽子是小男孩的       1\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-175 **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-175\n","是       1149\n","不重要      833\n","不是       679\n","问法错误     292\n","回答正确      47\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-350 **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-350\n","是       1181\n","不是      1145\n","不重要      374\n","问法错误     268\n","回答正确      32\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["for col in df.columns[5:]:\n","    df = clean_up(df, col)\n","    print(\"*\" * 10, col, \"*\" * 10)\n","    print(df[col].value_counts())\n","    plot_value_counts(df, col)"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n","\n","\n","def calc_metrics_for_col(df, col):\n","    y_true = df[\"label\"]\n","    y_pred = df[col]\n","\n","    accuracy = accuracy_score(y_true, y_pred)\n","    precision = precision_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    recall = recall_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","    f1 = f1_score(y_true, y_pred, average=\"weighted\", labels=np.unique(y_pred))\n","\n","    return accuracy, float(precision), float(recall), float(f1)"]},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["/Users/inflaton/anaconda3/envs/llm-finetuning/lib/python3.11/site-packages/sklearn/metrics/_classification.py:1517: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n","/var/folders/7x/56svhln929zdh2xhr3mwqg4r0000gn/T/ipykernel_58653/961288552.py:9: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n","  perf_df = pd.concat([perf_df, pd.DataFrame([new_model_metrics])], ignore_index=True)\n"]},{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>epoch</th>\n","      <th>model</th>\n","      <th>accuracy</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","      <th>f1</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat</td>\n","      <td>0.783667</td>\n","      <td>0.766712</td>\n","      <td>0.792917</td>\n","      <td>0.767940</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.568667</td>\n","      <td>0.807123</td>\n","      <td>0.568667</td>\n","      <td>0.625399</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.704333</td>\n","      <td>0.810817</td>\n","      <td>0.704333</td>\n","      <td>0.742186</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  epoch                                              model  accuracy  \\\n","0     0                shenzhi-wang/Llama3-8B-Chinese-Chat  0.783667   \n","1     1  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.568667   \n","2     2  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.704333   \n","\n","   precision    recall        f1  \n","0   0.766712  0.792917  0.767940  \n","1   0.807123  0.568667  0.625399  \n","2   0.810817  0.704333  0.742186  "]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","perf_df = pd.DataFrame(columns=[\"epoch\", \"model\", \"accuracy\", \"precision\", \"recall\", \"f1\"])\n","for i, col in enumerate(df.columns[5:]):\n","    accuracy, precision, recall, f1 = calc_metrics_for_col(df, col)\n","    new_model_metrics = {\"epoch\": i, \"model\": col, \"accuracy\": accuracy, \"precision\": precision, \"recall\": recall, \"f1\": f1}\n","\n","    # Convert the dictionary to a DataFrame and concatenate it with the existing DataFrame\n","    perf_df = pd.concat([perf_df, pd.DataFrame([new_model_metrics])], ignore_index=True)\n","\n","perf_df"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1200x500 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# plot metrics for each model\n","import matplotlib.pyplot as plt\n","\n","fig, ax = plt.subplots(1, 1, figsize=(12, 5))\n","\n","perf_df.plot(x=\"epoch\", y=[\"accuracy\", \"precision\", \"recall\", \"f1\"], kind=\"bar\", ax=ax)\n","\n","# add values on top of bars\n","for p in ax.patches:\n","    ax.annotate(\n","        f\"{p.get_height():.3f}\",\n","        (p.get_x() + p.get_width() / 2, p.get_height()),\n","        ha=\"center\",\n","        va=\"bottom\",\n","        fontsize=10,\n","    )\n","\n","# add title and labels\n","# ax.set_title(\"Metrics for different settings\")\n","# ax.set_ylabel(\"Value\")\n","ax.set_xlabel(\"Epoch (0: base model, 1-3: fine-tuned models)\")\n","# rotate x labels\n","plt.xticks(rotation=0)\n","\n","# set legend at the right to avoid overlapping with bars\n","plt.legend(loc=\"center left\", bbox_to_anchor=(1.0, 0.5))\n","# plt.tight_layout()\n","\n","plt.show()"]},{"cell_type":"code","execution_count":14,"metadata":{},"outputs":[],"source":["perf_df.to_csv(\"results/mgtv-llama3_p1_full_metrics.csv\", index=False)"]}],"metadata":{"accelerator":"GPU","application/vnd.databricks.v1+notebook":{"dashboards":[],"environmentMetadata":null,"language":"python","notebookMetadata":{"pythonIndentUnit":4},"notebookName":"07_MAC_+_Qwen2-7B-Instructi_Unsloth_train","widgets":{}},"colab":{"gpuType":"T4","provenance":[]},"kernelspec":{"display_name":"Python 3","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":"3.11.9"}},"nbformat":4,"nbformat_minor":0}