diff --git "a/competition/11a_Llama-3_8b_p2_analysis.ipynb" "b/competition/11a_Llama-3_8b_p2_analysis.ipynb"
--- "a/competition/11a_Llama-3_8b_p2_analysis.ipynb"
+++ "b/competition/11a_Llama-3_8b_p2_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":15,"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��</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��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":15,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/llama3-8b_lora_sft_bf16-p2.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_27195/961288552.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":"iVBORw0KGgoAAAANSUhEUgAABE0AAAHACAYAAABXiZaAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAABM7klEQVR4nO3de1wWZf7/8fcNCogIeChAFyEPKW4KKsKimaYUVuum23c9JkgetpLSqM0oBc0SO3lKV9M0bdNEyza/X1vSZWU3lUJRPCTiIQ0rDpqrKBYY9/z+6OeddwzKrejt4fV8PObxcK65rpnP3APm/W7mGothGIYAAAAAAABgx8XZBQAAAAAAAFyLCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADABKEJAAAAAACACUITAAAAAAAAE3WcXUBNWK1Wfffdd2rQoIEsFouzywEAAAAA3OAMw9CpU6fUtGlTubhwv8HN6roITb777jsFBgY6uwwAAAAAwE3myJEj+s1vfuPsMuAk10Vo0qBBA0k//7B6e3s7uRoAAAAAwI2utLRUgYGBtu+juDldF6HJuUdyvL29CU0AAAAAAFcNU0Tc3HgwCwAAAAAAwAShCQAAAAAAgAlCEwAA4HRz585VcHCwPDw8FBkZqezs7Gr79uzZUxaLpcrywAMP2PoUFxdr+PDhatq0qTw9PdWnTx/t37//ovt59NFHr9g5AgCA6w+hCQAAcKq0tDQlJiYqJSVF27ZtU2hoqGJiYlRSUmLaf/Xq1SosLLQtu3fvlqurq/70pz9J+vkVkf369dNXX32ljz/+WNu3b1dQUJCio6NVVlZmt69Ro0bZ7evVV1+94ucLAACuH4QmAADAqaZPn65Ro0YpPj5e7dq10/z58+Xp6anFixeb9m/UqJH8/f1ty/r16+Xp6WkLTfbv36/PP/9c8+bNU5cuXdSmTRvNmzdPP/zwg95//327fXl6etrtiwnnAQDA+QhNAACA01RUVCgnJ0fR0dG2NhcXF0VHRysrK6tG+1i0aJEGDRqk+vXrS5LKy8slSR4eHnb7dHd318aNG+3GLlu2TE2aNNEdd9yhpKQknTlz5nJPCQAA3ECui1cOAwCAG9OxY8dUWVkpPz8/u3Y/Pz/t3bv3ouOzs7O1e/duLVq0yNbWtm1bNW/eXElJSXrrrbdUv359zZgxQ998840KCwtt/YYMGaKgoCA1bdpUO3fu1Pjx45Wfn6/Vq1fX3gkCAIDrGneaALgp1PYkk6dPn1ZCQoJ+85vfqF69erZHCi62HyaZBGrXokWL1L59e0VERNja6tatq9WrV2vfvn1q1KiRPD09tWHDBt13331ycfnlnz6jR49WTEyM2rdvr6FDh+rdd9/VRx99pIMHDzrjVAAAwDXokkITR758SNLMmTPVpk0b1atXT4GBgXrqqaf0448/XlLBAOCo2p5kUpISExOVnp6u9957T3l5eRo3bpwSEhK0Zs0au30xySRwYU2aNJGrq6uKi4vt2ouLi+Xv73/BsWVlZVqxYoVGjBhRZVvnzp2Vm5urEydOqLCwUOnp6fr+++/VokWLavcXGRkpSTpw4MAlnAkAALgRORyaOPrlY/ny5XruueeUkpKivLw8LVq0SGlpaXr++ecvu3gAqInanmRSkjZv3qy4uDj17NlTwcHBGj16tEJDQ6uEyEwyCVyYm5ubOnfurIyMDFub1WpVRkaGoqKiLjh21apVKi8v18MPP1xtHx8fH91yyy3av3+/tm7dqgcffLDavrm5uZKkgIAAx04CAADcsBwOTRz98rF582Z169ZNQ4YMUXBwsO69914NHjz4onenAEBtuBKTTEpS165dtWbNGn377bcyDEMbNmzQvn37dO+999qNZZJJ4OISExO1cOFCLV26VHl5eXrsscdUVlam+Ph4SVJsbKySkpKqjFu0aJH69eunxo0bV9m2atUqZWZm2l47fM8996hfv36239GDBw9qypQpysnJ0eHDh7VmzRrFxsbqrrvuUocOHa7sCQMAgOuGQxPBnvvycf4/XC725aNr16567733lJ2drYiICH311Vf65JNPNGzYsMurHABq4EpMMilJb775pkaPHq3f/OY3qlOnjlxcXLRw4ULdddddtj5MMgnUzMCBA3X06FElJyerqKhIYWFhSk9Pt/3eFhQU2M1FIkn5+fnauHGj1q1bZ7rPwsJCJSYmqri4WAEBAYqNjdXEiRNt293c3PTPf/5TM2fOVFlZmQIDA/XQQw9pwoQJV+5EAQDAdceh0ORSvnwMGTJEx44d05133inDMPTTTz/p0UcfveDjOeXl5bbXBUpSaWmpI2UCQK0xm2RS+jk0+fzzz7VmzRoFBQXpP//5j8aMGaOmTZva7moZPXq0rX/79u0VEBCg3r176+DBg2rZsuVVPQ/gWpeQkKCEhATTbZmZmVXa2rRpI8Mwqt3fk08+qSeffLLa7YGBgfr3v//tcJ0AAODmcsXfnpOZmampU6fqr3/9q7Zt26bVq1dr7dq1mjJlSrVjUlNT5ePjY1sCAwOvdJkAblBXYpLJH374Qc8//7ymT5+uvn37qkOHDkpISNDAgQP1+uuvV7s/JpkEAAAAri8OhSaX8uVj4sSJGjZsmEaOHKn27durf//+mjp1qlJTU2W1Wk3HJCUl6eTJk7blyJEjjpQJADZXYpLJs2fP6uzZs1UeF3B1da327zWJSSZrW22/Rtpsu8Vi0WuvvWbrc/z4cQ0dOlTe3t7y9fXViBEjdPr06St6nsD1iN9PAMCNwqHHc87/8tGvXz9Jv3z5qO6W2jNnzph+sZBU7W217u7ucnd3d6Q0AKhWYmKi4uLiFB4eroiICNscBudPMtmsWTOlpqbajatukklvb2/16NFDf/nLX1SvXj0FBQXp3//+t959911Nnz5d0s+TTC5fvlz333+/GjdurJ07d+qpp55ikslacu5NbvPnz1dkZKRmzpypmJgY5efn69Zbb63Sf/Xq1aqoqLCtf//99woNDbV7I1JhYaHdmH/84x8aMWKEHnroIVvb0KFDVVhYqPXr1+vs2bOKj4/X6NGjtXz58itwlrWn/dL2zi4BtWhX3C5nl3BB/H4CAG4kFuNCDwSbSEtLU1xcnN566y3bl4+VK1dq79698vPzq/LlY9KkSZo+fboWLFigyMhIHThwQI899pg6d+6stLS0Gh2ztLRUPj4+OnnyJK/rBHBJ5syZo9dee802yeTs2bNtj8uce23wkiVLbP3z8/PVtm1brVu3Tvfcc0+V/RUVFSkpKUnr1q3T8ePHFRQUpNGjR+upp56SxWLRkSNH9PDDD2v37t22SSb79++vCRMm8PdYLYiMjFSXLl00Z84cST8H+IGBgXriiSf03HPPXXT8zJkzlZycrMLCQru3Ip2vX79+OnXqlO0upby8PLVr105btmxReHi4JCk9PV3333+/vvnmGzVt2rSWzq72EZrcWK710ITfTwA3Cr6HQnLwThPJ8RnuJ0yYIIvFogkTJujbb7/VLbfcor59++rll1+uvbMAgIuo7Ukm/f399c4771S7nUkmr5xLeZPbr5m9Rvp8xcXFWrt2rZYuXWpry8rKkq+vr+0LmSRFR0fLxcVFX3zxhfr373+JZwTcOPj9BADcaBwOTSTHvnzUqVNHKSkpSklJuZRDAQBg50q9Rvp8S5cuVYMGDfTHP/7R1lZUVFTl0YI6deqoUaNGKioqcvAsgBsTv58AgBvNJYUmAHC+4OfWOrsE1KLD0x64eKfrWHWvkT7f4sWLNXToUHl4eFzFygDw+wkAuNZc8VcOAwBQm67Ea6TP99lnnyk/P18jR460a/f391dJSYld208//aTjx49f9LjAzYLfTwDAjYbQBABwXbkSr5E+36JFi9S5c2eFhobatUdFRenEiRPKycmxtf3rX/+S1Wq1TSoM3Oz4/QQA3GgITQAA153ExEQtXLhQS5cuVV5enh577LEqr5E+fyLKc6p7jfQ5paWlWrVqVZX/iy1JISEh6tOnj0aNGqXs7Gxt2rRJCQkJGjRoEG/mAM7D7ycA4EbCnCYAgOuOo29yk35+jfTGjRu1bt26ave7YsUKGYahwYMHm25ftmyZEhIS1Lt3b7m4uOihhx7S7Nmza+/EgBsAv58AgBuJxbjQOzWvEbwfG7i2MRHsjeVGnwj2ZtR+aXtnl4BatCtul7NLAICbAt9DIfF4DgAAAAAAgCkezwEA2Jvk4+wKUNtua+7sCgAAAK5LhCYAAADXkby2Ic4uAbUoZG+es0sAAFwAj+cAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADABKEJAAAAAACACUITAAAAAAAAE4QmAAAAAAAAJghNAAAAAAAATBCaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwcUmhydy5cxUcHCwPDw9FRkYqOzu72r49e/aUxWKpsjzwwAOXXDQAAAAAAMCV5nBokpaWpsTERKWkpGjbtm0KDQ1VTEyMSkpKTPuvXr1ahYWFtmX37t1ydXXVn/70p8suHgAAAAAA4EpxODSZPn26Ro0apfj4eLVr107z58+Xp6enFi9ebNq/UaNG8vf3ty3r16+Xp6cnoQkAAAAAALimORSaVFRUKCcnR9HR0b/swMVF0dHRysrKqtE+Fi1apEGDBql+/fqOVQoAAAAAAHAV1XGk87Fjx1RZWSk/Pz+7dj8/P+3du/ei47Ozs7V7924tWrTogv3Ky8tVXl5uWy8tLXWkTAAAAAAAgMt2Vd+es2jRIrVv314REREX7JeamiofHx/bEhgYeJUqBAAAAAAA+JlDoUmTJk3k6uqq4uJiu/bi4mL5+/tfcGxZWZlWrFihESNGXPQ4SUlJOnnypG05cuSII2UCAAAAAABcNodCEzc3N3Xu3FkZGRm2NqvVqoyMDEVFRV1w7KpVq1ReXq6HH374osdxd3eXt7e33QIAAAAAAHA1OTSniSQlJiYqLi5O4eHhioiI0MyZM1VWVqb4+HhJUmxsrJo1a6bU1FS7cYsWLVK/fv3UuHHj2qkcAAAAAADgCnI4NBk4cKCOHj2q5ORkFRUVKSwsTOnp6bbJYQsKCuTiYn8DS35+vjZu3Kh169bVTtUAAAAAAABXmMOhiSQlJCQoISHBdFtmZmaVtjZt2sgwjEs5FAAAAAAAgFNc1bfnAAAAAAAAXC8ITQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADABKEJAAAAAACACUITAAAAAAAAE4QmAAAAAAAAJghNAAAAAAAATBCaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwcUmhydy5cxUcHCwPDw9FRkYqOzv7gv1PnDihMWPGKCAgQO7u7rr99tv1ySefXFLBAAAAAAAAV0MdRwekpaUpMTFR8+fPV2RkpGbOnKmYmBjl5+fr1ltvrdK/oqJC99xzj2699VZ98MEHatasmb7++mv5+vrWRv0AAAAAAABXhMOhyfTp0zVq1CjFx8dLkubPn6+1a9dq8eLFeu6556r0X7x4sY4fP67Nmzerbt26kqTg4ODLqxoAAAAAAOAKc+jxnIqKCuXk5Cg6OvqXHbi4KDo6WllZWaZj1qxZo6ioKI0ZM0Z+fn664447NHXqVFVWVlZ7nPLycpWWltotAAAAAAAAV5NDocmxY8dUWVkpPz8/u3Y/Pz8VFRWZjvnqq6/0wQcfqLKyUp988okmTpyoN954Qy+99FK1x0lNTZWPj49tCQwMdKRMAAAAAACAy3bF355jtVp16623asGCBercubMGDhyoF154QfPnz692TFJSkk6ePGlbjhw5cqXLBAAAAAAAsOPQnCZNmjSRq6uriouL7dqLi4vl7+9vOiYgIEB169aVq6urrS0kJERFRUWqqKiQm5tblTHu7u5yd3d3pDQAAAAAAIBa5dCdJm5uburcubMyMjJsbVarVRkZGYqKijId061bNx04cEBWq9XWtm/fPgUEBJgGJgAAAAAAANcChx/PSUxM1MKFC7V06VLl5eXpscceU1lZme1tOrGxsUpKSrL1f+yxx3T8+HGNHTtW+/bt09q1azV16lSNGTOm9s4CAAAAAACgljn8yuGBAwfq6NGjSk5OVlFRkcLCwpSenm6bHLagoEAuLr9kMYGBgfr000/11FNPqUOHDmrWrJnGjh2r8ePH195ZAAAAAAAA1DKLYRiGs4u4mNLSUvn4+OjkyZPy9vZ2djkAfiX4ubXOLgG16LDHEGeXgFrW/rbmzi4BtWhl6k/OLgG1KGRvnrNLAFANvodCugpvzwEAAAAAALgeEZoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADABKEJAAAAAACACUITAAAAAAAAE4QmAAAAAAAAJghNAAAAAAAATBCaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADABKEJAAAAAACACUITAAAAAAAAE4QmAAAAAAAAJuo4uwAAAAAAAK5HVqtVFRUVzi4DDqpbt65cXV1r1JfQBAAAAAAAB1VUVOjQoUOyWq3OLgWXwNfXV/7+/rJYLBfsR2gCAAAAAIADDMNQYWGhXF1dFRgYKBcXZr64XhiGoTNnzqikpESSFBAQcMH+lxSazJ07V6+99pqKiooUGhqqN998UxEREaZ9lyxZovj4eLs2d3d3/fjjj5dyaAAAAAAAnOqnn37SmTNn1LRpU3l6ejq7HDioXr16kqSSkhLdeuutF3xUx+E4LC0tTYmJiUpJSdG2bdsUGhqqmJgYW0pjxtvbW4WFhbbl66+/dvSwAAAAAABcEyorKyVJbm5uTq4El+pc2HX27NkL9nM4NJk+fbpGjRql+Ph4tWvXTvPnz5enp6cWL15c7RiLxSJ/f3/b4ufn5+hhAQAAAAC4plxsPgxcu2p67RwKTSoqKpSTk6Po6OhfduDioujoaGVlZVU77vTp0woKClJgYKAefPBBffnllxc8Tnl5uUpLS+0WAAAAAACAq8mh0OTYsWOqrKyscqeIn5+fioqKTMe0adNGixcv1scff6z33ntPVqtVXbt21TfffFPtcVJTU+Xj42NbAgMDHSkTAAAAAADgsl3xt+dERUUpKirKtt61a1eFhITorbfe0pQpU0zHJCUlKTEx0bZeWlpKcAIAAAAAuKYFP7f2qh7v8LQHrurxbkYOhSZNmjSRq6uriouL7dqLi4vl7+9fo33UrVtXHTt21IEDB6rt4+7uLnd3d0dKAwAAAAAA15mzZ8+qbt26zi6jWg49nuPm5qbOnTsrIyPD1ma1WpWRkWF3N8mFVFZWateuXRd9FzIAAAAAAKhd6enpuvPOO+Xr66vGjRvr97//vQ4ePGjb/s0332jw4MFq1KiR6tevr/DwcH3xxRe27f/7v/+rLl26yMPDQ02aNFH//v1t2ywWi/7+97/bHc/X11dLliyRJB0+fFgWi0VpaWnq0aOHPDw8tGzZMn3//fcaPHiwmjVrJk9PT7Vv317vv/++3X6sVqteffVVtWrVSu7u7mrevLlefvllSVKvXr2UkJBg1//o0aNyc3Ozyy8uhcNvz0lMTNTChQu1dOlS5eXl6bHHHlNZWZni4+MlSbGxsUpKSrL1f/HFF7Vu3Tp99dVX2rZtmx5++GF9/fXXGjly5GUVDgAAAAAAHFNWVqbExERt3bpVGRkZcnFxUf/+/WW1WnX69Gn16NFD3377rdasWaMdO3bo2WefldVqlSStXbtW/fv31/3336/t27crIyNDERERDtfw3HPPaezYscrLy1NMTIx+/PFHde7cWWvXrtXu3bs1evRoDRs2TNnZ2bYxSUlJmjZtmiZOnKg9e/Zo+fLltvlWR44cqeXLl6u8vNzW/7333lOzZs3Uq1evy/q8HJ7TZODAgTp69KiSk5NVVFSksLAwpaen24otKCiQi8svWcx///tfjRo1SkVFRWrYsKE6d+6szZs3q127dpdVOAAAAAAAcMxDDz1kt7548WLdcsst2rNnjzZv3qyjR49qy5YtatSokSSpVatWtr4vv/yyBg0apMmTJ9vaQkNDHa5h3Lhx+uMf/2jX9swzz9j+/MQTT+jTTz/VypUrFRERoVOnTmnWrFmaM2eO4uLiJEktW7bUnXfeKUn64x//qISEBH388ccaMGCAJGnJkiUaPnz4Zb8W+pImgk1ISKhy68s5mZmZduszZszQjBkzLuUwAAAAAACgFu3fv1/Jycn64osvdOzYMdtdJAUFBcrNzVXHjh1tgcmv5ebmatSoUZddQ3h4uN16ZWWlpk6dqpUrV+rbb79VRUWFysvL5enpKUnKy8tTeXm5evfubbo/Dw8PDRs2TIsXL9aAAQO0bds27d69W2vWrLnsWq/423MAAAAAAMC1oW/fvgoKCtLChQvVtGlTWa1W3XHHHaqoqFC9evUuOPZi2y0WiwzDsGs7e/ZslX7169e3W3/ttdc0a9YszZw5U+3bt1f9+vU1btw4VVRU1Oi40s+P6ISFhembb77RO++8o169eikoKOii4y7G4TlNAAAAAADA9ef7779Xfn6+JkyYoN69eyskJET//e9/bds7dOig3NxcHT9+3HR8hw4dLjix6i233KLCwkLb+v79+3XmzJmL1rVp0yY9+OCDevjhhxUaGqoWLVpo3759tu2tW7dWvXr1Lnjs9u3bKzw8XAsXLtTy5cv1yCOPXPS4NUFoAgAAAADATaBhw4Zq3LixFixYoAMHDuhf//qXEhMTbdsHDx4sf39/9evXT5s2bdJXX32lDz/8UFlZWZKklJQUvf/++0pJSVFeXp527dqlV155xTa+V69emjNnjrZv366tW7fq0UcfrdHrhFu3bq3169dr8+bNysvL05///GcVFxfbtnt4eGj8+PF69tln9e677+rgwYP6/PPPtWjRIrv9jBw5UtOmTZNhGHZv9bkchCYAAAAAANwEXFxctGLFCuXk5OiOO+7QU089pddee8223c3NTevWrdOtt96q+++/X+3bt9e0adPk6uoqSerZs6dWrVqlNWvWKCwsTL169bJ7w80bb7yhwMBAde/eXUOGDNEzzzxjm5fkQiZMmKBOnTopJiZGPXv2tAU355s4caKefvppJScnKyQkRAMHDlRJSYldn8GDB6tOnToaPHiwPDw8LuOT+oXF+PUDR9eg0tJS+fj46OTJk/L29nZ2OQB+Jfi5tc4uAbXosMcQZ5eAWtb+tubOLgG1aGXqT84uAbUoZG+es0sAUI0LfQ/98ccfdejQId1222219uUcl+/w4cNq2bKltmzZok6dOl2wb02vIRPBAgAAAACA69bZs2f1/fffa8KECfrd73530cDEETyeAwAAAAAArlubNm1SQECAtmzZovnz59fqvrnTBAAAAAAAXLd69uxZ5VXHtYU7TQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAHBFZGZmymKx6MSJE7Xa92qp4+wCAAAAAAC4IUzyucrHO3l1j3cJunbtqsLCQvn4XPyzcaTv1cKdJgAAAAAAoIqKiorL3oebm5v8/f1lsVhqte/VQmgCAAAAAMBNoGfPnkpISFBCQoJ8fHzUpEkTTZw4UYZhSJKCg4M1ZcoUxcbGytvbW6NHj5Ykbdy4Ud27d1e9evUUGBioJ598UmVlZbb9lpeXa/z48QoMDJS7u7tatWqlRYsWSar6yM3XX3+tvn37qmHDhqpfv75++9vf6pNPPjHtK0kffvihfvvb38rd3V3BwcF644037M4pODhYU6dO1SOPPKIGDRqoefPmWrBgQa19ZoQmAAAAAADcJJYuXao6deooOztbs2bN0vTp0/X222/btr/++usKDQ3V9u3bNXHiRB08eFB9+vTRQw89pJ07dyotLU0bN25UQkKCbUxsbKzef/99zZ49W3l5eXrrrbfk5eVlevwxY8aovLxc//nPf7Rr1y698sor1fbNycnRgAEDNGjQIO3atUuTJk3SxIkTtWTJErt+b7zxhsLDw7V9+3Y9/vjjeuyxx5Sfn3/5H5aY0wQAAAAAgJtGYGCgZsyYIYvFojZt2mjXrl2aMWOGRo0aJUnq1auXnn76aVv/kSNHaujQoRo3bpwkqXXr1po9e7Z69OihefPmqaCgQCtXrtT69esVHR0tSWrRokW1xy8oKNBDDz2k9u3bX7Tv9OnT1bt3b02cOFGSdPvtt2vPnj167bXXNHz4cFu/+++/X48//rgkafz48ZoxY4Y2bNigNm3aOP4B/Qp3mgAAAAAAcJP43e9+ZzdnSFRUlPbv36/KykpJUnh4uF3/HTt2aMmSJfLy8rItMTExslqtOnTokHJzc+Xq6qoePXrU6PhPPvmkXnrpJXXr1k0pKSnauXNntX3z8vLUrVs3u7Zu3brZ1StJHTp0sP3ZYrHI399fJSUlNarnYghNAAAAAACAJKl+/fp266dPn9af//xn5ebm2pYdO3Zo//79atmyperVq+fQ/keOHKmvvvpKw4YN065duxQeHq4333zzsmquW7eu3brFYpHVar2sfZ5DaAIAAAAAwE3iiy++sFv//PPP1bp1a7m6upr279Spk/bs2aNWrVpVWdzc3NS+fXtZrVb9+9//rnENgYGBevTRR7V69Wo9/fTTWrhwoWm/kJAQbdq0ya5t06ZNuv3226utt7YRmgAAAAAAcJMoKChQYmKi8vPz9f777+vNN9/U2LFjq+0/fvx4bd68WQkJCcrNzdX+/fv18ccf2yaCDQ4OVlxcnB555BH9/e9/16FDh5SZmamVK1ea7m/cuHH69NNPdejQIW3btk0bNmxQSEiIad+nn35aGRkZmjJlivbt26elS5dqzpw5euaZZy7/g6ghJoIFAAAAAOAmERsbqx9++EERERFydXXV2LFjba8WNtOhQwf9+9//1gsvvKDu3bvLMAy1bNlSAwcOtPWZN2+enn/+eT3++OP6/vvv1bx5cz3//POm+6usrNSYMWP0zTffyNvbW3369NGMGTNM+3bq1EkrV65UcnKypkyZooCAAL344ot2k8BeaRbj3AuZr2GlpaXy8fHRyZMn5e3t7exyAPxK8HNrnV0CatFhjyHOLgG1rP1tzZ1dAmrRytSfnF0CalHI3jxnlwCgGhf6Hvrjjz/q0KFDuu222+Th4eGkCh3Xs2dPhYWFaebMmc4uxelqeg15PAcAAAAAAMAEoQkAAAAAAIAJ5jQBAAAAAOAmkJmZ6ewSrjvcaQIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMXFJoMnfuXAUHB8vDw0ORkZHKzs6u0bgVK1bIYrGoX79+l3JYAAAAAABwHZk0aZLCwsJs68OHD7+uMoE6jg5IS0tTYmKi5s+fr8jISM2cOVMxMTHKz8/XrbfeWu24w4cP65lnnlH37t0vq2AAAAAAAK5F7Ze2v6rH2xW366oe72bk8J0m06dP16hRoxQfH6927dpp/vz58vT01OLFi6sdU1lZqaFDh2ry5Mlq0aLFZRUMAAAAAAAuX0VFhbNLuOY5FJpUVFQoJydH0dHRv+zAxUXR0dHKysqqdtyLL76oW2+9VSNGjKjRccrLy1VaWmq3AAAAAACAS9ezZ08lJCRo3LhxatKkiWJiYrR7927dd9998vLykp+fn4YNG6Zjx47ZxlitVr366qtq1aqV3N3d1bx5c7388su27ePHj9ftt98uT09PtWjRQhMnTtTZs2edcXpXhEOhybFjx1RZWSk/Pz+7dj8/PxUVFZmO2bhxoxYtWqSFCxfW+Dipqany8fGxLYGBgY6UCQAAAAAATCxdulRubm7atGmTpk2bpl69eqljx47aunWr0tPTVVxcrAEDBtj6JyUladq0aZo4caL27Nmj5cuX22UCDRo00JIlS7Rnzx7NmjVLCxcu1IwZM5xxaleEw3OaOOLUqVMaNmyYFi5cqCZNmtR4XFJSkhITE23rpaWlBCcAAAAAAFym1q1b69VXX5UkvfTSS+rYsaOmTp1q27548WIFBgZq3759CggI0KxZszRnzhzFxcVJklq2bKk777zT1n/ChAm2PwcHB+uZZ57RihUr9Oyzz16lM7qyHApNmjRpIldXVxUXF9u1FxcXy9/fv0r/gwcP6vDhw+rbt6+tzWq1/nzgOnWUn5+vli1bVhnn7u4ud3d3R0oDAAAAAAAX0blzZ9ufd+zYoQ0bNsjLy6tKv4MHD+rEiRMqLy9X7969q91fWlqaZs+erYMHD+r06dP66aef5O3tfUVqdwaHHs9xc3NT586dlZGRYWuzWq3KyMhQVFRUlf5t27bVrl27lJuba1v+8Ic/6O6771Zubi53jwAAAAAAcBXVr1/f9ufTp0+rb9++dt/Zc3NztX//ft11112qV6/eBfeVlZWloUOH6v7779f//d//afv27XrhhRduqAlmHX48JzExUXFxcQoPD1dERIRmzpypsrIyxcfHS5JiY2PVrFkzpaamysPDQ3fccYfdeF9fX0mq0g4AAAAAAK6eTp066cMPP1RwcLDq1KkaD7Ru3Vr16tVTRkaGRo4cWWX75s2bFRQUpBdeeMHW9vXXX1/Rmq82h0OTgQMH6ujRo0pOTlZRUZHCwsKUnp5umwimoKBALi4Ov8kYAAAAAABcRWPGjNHChQs1ePBgPfvss2rUqJEOHDigFStW6O2335aHh4fGjx+vZ599Vm5uburWrZuOHj2qL7/8UiNGjFDr1q1VUFCgFStWqEuXLlq7dq0++ugjZ59WrbqkiWATEhKUkJBgui0zM/OCY5csWXIphwQAAAAAALWoadOm2rRpk8aPH697771X5eXlCgoKUp8+fWw3Q0ycOFF16tRRcnKyvvvuOwUEBOjRRx+VJP3hD3/QU089pYSEBJWXl+uBBx7QxIkTNWnSJCeeVe2yGIZhOLuIiyktLZWPj49Onjx5Q00oA9wogp9b6+wSUIsOewxxdgmoZe1va+7sElCLVqb+5OwSUItC9uY5uwQA1bjQ99Aff/xRhw4d0m233SYPDw8nVYjLUdNryHM0AAAAAAAAJghNAAAAAAAATBCaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAuAkYhqHRo0erUaNGslgsys3NdXZJ17w6zi4AAAAAAIAbQV7bkKt6vJC9eQ71T09P15IlS5SZmakWLVpo37596tu3r3JyclRYWKiPPvpI/fr1uzLFXqe40wQAAAAAgJvAwYMHFRAQoK5du8rf319lZWUKDQ3V3LlznV3aNYs7TQAAAAAAuMENHz5cS5culSRZLBYFBQXp8OHDuu+++5xc2bWN0AQAAAAAgBvcrFmz1LJlSy1YsEBbtmyRq6urs0u6LhCaAAAAAABwg/Px8VGDBg3k6uoqf39/Z5dz3WBOEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAEwwpwkAAAAAADeh06dP68CBA7b1Q4cOKTc3V40aNVLz5s2dWNm1g9AEAAAAAICb0NatW3X33Xfb1hMTEyVJcXFxWrJkiZOqurYQmgAAAAAAUAtC9uY5u4QLGjdunMaNG2db79mzpwzDcF5B1wHmNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAC4Bk6hev2p67QhNAAAAAABwgKurqySpoqLCyZXgUp05c0aSVLdu3Qv245XDAAAAAAA4oE6dOvL09NTRo0dVt25dubhwP8L1wjAMnTlzRiUlJfL19bUFYNUhNAEAAAAAwAEWi0UBAQE6dOiQvv76a2eXg0vg6+srf3//i/YjNAEAAAAAwEFubm5q3bo1j+hch+rWrXvRO0zOITQBAAAAAOASuLi4yMPDw9ll4AriwSsAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMXFJoMnfuXAUHB8vDw0ORkZHKzs6utu/q1asVHh4uX19f1a9fX2FhYfrb3/52yQUDAAAAAABcDQ6HJmlpaUpMTFRKSoq2bdum0NBQxcTEqKSkxLR/o0aN9MILLygrK0s7d+5UfHy84uPj9emnn1528QAAAAAAAFeKw6HJ9OnTNWrUKMXHx6tdu3aaP3++PD09tXjxYtP+PXv2VP/+/RUSEqKWLVtq7Nix6tChgzZu3HjZxQMAAAAAAFwpDoUmFRUVysnJUXR09C87cHFRdHS0srKyLjreMAxlZGQoPz9fd911V7X9ysvLVVpaarcAAAAAAABcTQ6FJseOHVNlZaX8/Pzs2v38/FRUVFTtuJMnT8rLy0tubm564IEH9Oabb+qee+6ptn9qaqp8fHxsS2BgoCNlAgAAAAAAXLar8vacBg0aKDc3V1u2bNHLL7+sxMREZWZmVts/KSlJJ0+etC1Hjhy5GmUCAAAAAADY1HGkc5MmTeTq6qri4mK79uLiYvn7+1c7zsXFRa1atZIkhYWFKS8vT6mpqerZs6dpf3d3d7m7uztSGgAAAAAAQK1y6E4TNzc3de7cWRkZGbY2q9WqjIwMRUVF1Xg/VqtV5eXljhwaAAAAAADgqnLoThNJSkxMVFxcnMLDwxUREaGZM2eqrKxM8fHxkqTY2Fg1a9ZMqampkn6enyQ8PFwtW7ZUeXm5PvnkE/3tb3/TvHnzavdMAAAAAAAAapHDocnAgQN19OhRJScnq6ioSGFhYUpPT7dNDltQUCAXl19uYCkrK9Pjjz+ub775RvXq1VPbtm313nvvaeDAgbV3FgAAAAAAALXMYhiG4ewiLqa0tFQ+Pj46efKkvL29nV0OgF8Jfm6ts0tALTrsMcTZJaCWtb+tubNLQC1amfqTs0tALQrZm+fsEgBUg++hkK7S23MAAAAAAACuN4QmAAAAAAAAJghNAAAAAAAATBCaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADABKEJAAAAAACACUITAAAAAAAAE4QmAAAAAAAAJghNAAAAAAAATBCaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAExcUmgyd+5cBQcHy8PDQ5GRkcrOzq6278KFC9W9e3c1bNhQDRs2VHR09AX7AwAAAAAAXAscDk3S0tKUmJiolJQUbdu2TaGhoYqJiVFJSYlp/8zMTA0ePFgbNmxQVlaWAgMDde+99+rbb7+97OIBAAAAAACuFIdDk+nTp2vUqFGKj49Xu3btNH/+fHl6emrx4sWm/ZctW6bHH39cYWFhatu2rd5++21ZrVZlZGRcdvEAAAAAAABXikOhSUVFhXJychQdHf3LDlxcFB0draysrBrt48yZMzp79qwaNWpUbZ/y8nKVlpbaLQAAAAAAAFeTQ6HJsWPHVFlZKT8/P7t2Pz8/FRUV1Wgf48ePV9OmTe2Cl19LTU2Vj4+PbQkMDHSkTAAAAAAAgMt2Vd+eM23aNK1YsUIfffSRPDw8qu2XlJSkkydP2pYjR45cxSoBAAAAAACkOo50btKkiVxdXVVcXGzXXlxcLH9//wuOff311zVt2jT985//VIcOHS7Y193dXe7u7o6UBgAAAAAAUKscutPEzc1NnTt3tpvE9dykrlFRUdWOe/XVVzVlyhSlp6crPDz80qsFAAAAAAC4Shy600SSEhMTFRcXp/DwcEVERGjmzJkqKytTfHy8JCk2NlbNmjVTamqqJOmVV15RcnKyli9fruDgYNvcJ15eXvLy8qrFUwEAAAAAAKg9DocmAwcO1NGjR5WcnKyioiKFhYUpPT3dNjlsQUGBXFx+uYFl3rx5qqio0P/8z//Y7SclJUWTJk26vOoBAAAAAACuEIdDE0lKSEhQQkKC6bbMzEy79cOHD1/KIQAAAAAAAJzqqr49BwAAAAAA4HpBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADABKEJAAAAAACACUITAAAAAAAAE4QmAAAAAAAAJghNAAAAAAAATBCaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADAxCWFJnPnzlVwcLA8PDwUGRmp7Ozsavt++eWXeuihhxQcHCyLxaKZM2deaq0AAAAAAABXjcOhSVpamhITE5WSkqJt27YpNDRUMTExKikpMe1/5swZtWjRQtOmTZO/v/9lFwwAAAAAAHA1OByaTJ8+XaNGjVJ8fLzatWun+fPny9PTU4sXLzbt36VLF7322msaNGiQ3N3dL7tgAAAAAACAq8Gh0KSiokI5OTmKjo7+ZQcuLoqOjlZWVlatFwcAAAAAAOAsdRzpfOzYMVVWVsrPz8+u3c/PT3v37q21osrLy1VeXm5bLy0trbV9AwAAAAAA1MQ1+fac1NRU+fj42JbAwEBnlwQAAAAAAG4yDoUmTZo0kaurq4qLi+3ai4uLa3WS16SkJJ08edK2HDlypNb2DQAAAAAAUBMOhSZubm7q3LmzMjIybG1Wq1UZGRmKioqqtaLc3d3l7e1ttwAAAAAAAFxNDs1pIkmJiYmKi4tTeHi4IiIiNHPmTJWVlSk+Pl6SFBsbq2bNmik1NVXSz5PH7tmzx/bnb7/9Vrm5ufLy8lKrVq1q8VQAAAAAAABqj8OhycCBA3X06FElJyerqKhIYWFhSk9Pt00OW1BQIBeXX25g+e6779SxY0fb+uuvv67XX39dPXr0UGZm5uWfAQAAAAAAwBXgcGgiSQkJCUpISDDd9usgJDg4WIZhXMphAAAAAAAAnOaafHsOAAAAAACAsxGaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAAAAAADABKEJAAAAAACACUITAAAAAAAAE4QmAAAAAAAAJghNAAAAAAAATBCaAAAAAAAAmCA0AQAAAAAAMEFoAgAAAAAAYILQBAAAAAAAwAShCQAAAAAAgAlCEwAAAAAAABOEJgAAAAAAACYITQAAAAAAAEwQmgAAAAAAAJggNAEAAAAAADBxSaHJ3LlzFRwcLA8PD0VGRio7O/uC/VetWqW2bdvKw8ND7du31yeffHJJxQIAAAAAAFwtDocmaWlpSkxMVEpKirZt26bQ0FDFxMSopKTEtP/mzZs1ePBgjRgxQtu3b1e/fv3Ur18/7d69+7KLBwAAAAAAuFIcDk2mT5+uUaNGKT4+Xu3atdP8+fPl6empxYsXm/afNWuW+vTpo7/85S8KCQnRlClT1KlTJ82ZM+eyiwcAAAAAALhSHApNKioqlJOTo+jo6F924OKi6OhoZWVlmY7Jysqy6y9JMTEx1fYHAAAAAAC4FtRxpPOxY8dUWVkpPz8/u3Y/Pz/t3bvXdExRUZFp/6KiomqPU15ervLyctv6yZMnJUmlpaWOlAvgKrGWn3F2CahFpRbD2SWgllX+UOnsElCLTldyPW8k/PsWuHad+/00DP5tdDNzKDS5WlJTUzV58uQq7YGBgU6oBgBuLj7OLgBXQJ6zC0AtinB2AahdPvytC1zrTp06JR9+V29aDoUmTZo0kaurq4qLi+3ai4uL5e/vbzrG39/fof6SlJSUpMTERNu61WrV8ePH1bhxY1ksFkdKBgDgplZaWqrAwEAdOXJE3t7ezi4HAIDrhmEYOnXqlJo2bersUuBEDoUmbm5u6ty5szIyMtSvXz9JPwcaGRkZSkhIMB0TFRWljIwMjRs3zta2fv16RUVFVXscd3d3ubu727X5+vo6UioAADiPt7c3oQkAAA7iDhM4/HhOYmKi4uLiFB4eroiICM2cOVNlZWWKj4+XJMXGxqpZs2ZKTU2VJI0dO1Y9evTQG2+8oQceeEArVqzQ1q1btWDBgto9EwAAAAAAgFrkcGgycOBAHT16VMnJySoqKlJYWJjS09Ntk70WFBTIxeWXl/J07dpVy5cv14QJE/T888+rdevW+vvf/6477rij9s4CAAAAAACgllkMpgIGAOCGVV5ertTUVCUlJVV59BUAAAAXRmgCAAAAAABgwuXiXQAAAAAAAG4+hCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAOAGNXfuXAUHB8vDw0ORkZHKzs52dkkAAADXFUITAABuQGlpaUpMTFRKSoq2bdum0NBQxcTEqKSkxNmlAQAAXDd45TAAADegyMhIdenSRXPmzJEkWa1WBQYG6oknntBzzz3n5OoAAACuD9xpAgDADaaiokI5OTmKjo62tbm4uCg6OlpZWVlOrAwAAOD6QmgCAMAN5tixY6qsrJSfn59du5+fn4qKipxUFQAAwPWH0AQAAAAAAMAEoQkAADeYJk2ayNXVVcXFxXbtxcXF8vf3d1JVAAAA1x9CEwAAbjBubm7q3LmzMjIybG1Wq1UZGRmKiopyYmUAAADXlzrOLgAAANS+xMRExcXFKTw8XBEREZo5c6bKysoUHx/v7NIAAACuG4QmAADcgAYOHKijR48qOTlZRUVFCgsLU3p6epXJYQEAAFA9i2EYhrOLAAAAAAAAuNYwpwkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAwQWgCAAAAAABggtAEAG4SFotFf//73x0el5+fL39/f506dapW6xk+fLj69etXq/u8nhw+fFgWi0W5ubk1HtOzZ0+NGzfuitV0JUyaNEl+fn62n7+b9bpfyvW+koKDgzVz5swa9580aZLCwsJq1Hf+/Pnq27fvpRUGAMA1htAEAK6w4cOHy2KxVFn69Onj7NJqJCkpSU888YQaNGhga9u5c6e6d+8uDw8PBQYG6tVXX3VihbiQl19+WV27dpWnp6d8fX1rNCY/P1933323/Pz85OHhoRYtWmjChAk6e/asQ8fOy8vT5MmT9dZbb6mwsFD33XefZs2apSVLljh+Ig66WcOZa8Ejjzyibdu26bPPPnN2KQAAXLY6zi4AAG4Gffr00TvvvGPX5u7u7qRqaq6goED/93//pzfffNPWVlpaqnvvvVfR0dGaP3++du3apUceeUS+vr4aPXq0E6uFmYqKCv3pT39SVFSUFi1aVKMxdevWVWxsrDp16iRfX1/t2LFDo0aNktVq1dSpU2t87IMHD0qSHnzwQVksFknXx889Lo+bm5uGDBmi2bNnq3v37s4uBwCAy8KdJgBwFbi7u8vf399uadiwoW27xWLRvHnzdN9996levXpq0aKFPvjgA7t97Nq1S7169VK9evXUuHFjjR49WqdPn7brs3jxYv32t7+Vu7u7AgIClJCQYLf92LFj6t+/vzw9PdW6dWutWbPmgnWvXLlSoaGhatasma1t2bJlqqiosB1r0KBBevLJJzV9+vRL+mwmT56sW265Rd7e3nr00UdVUVFh25aenq4777xTvr6+aty4sX7/+9/bvohLPwcCCQkJCggIkIeHh4KCgpSammrbfuLECY0cOdK2/169emnHjh3V1nLuEYqVK1eqe/fuqlevnrp06aJ9+/Zpy5YtCg8Pl5eXl+677z4dPXrUNs5qterFF1/Ub37zG7m7uyssLEzp6el2+87OzlbHjh3l4eGh8PBwbd++vcrxd+/erfvuu09eXl7y8/PTsGHDdOzYsUv6XM+ZPHmynnrqKbVv377GY1q0aKH4+HiFhoYqKChIf/jDHzR06FCH7hyYNGmS7RENFxcXW2jy6ztAevbsqSeffFLPPvusGjVqJH9/f02aNMluX45ex0mTJmnp0qX6+OOPbXd2ZWZmKjMzUxaLRSdOnLD1zc3NlcVi0eHDhyVJS5Yska+vrz799FOFhITIy8tLffr0UWFhod0x3n77bYWEhMjDw0Nt27bVX//6V7vtNbnevxYcHKyXXnpJsbGx8vLyUlBQkNasWaOjR4/qwQcflJeXlzp06KCtW7fajfvwww9tv/fBwcF644037LaXlJSob9++qlevnm677TYtW7asyrEd/YwzMzMVERGh+vXry9fXV926ddPXX39t2963b1+tWbNGP/zww0XPGwCAaxmhCQBcIyZOnKiHHnpIO3bs0NChQzVo0CDl5eVJksrKyhQTE6OGDRtqy5YtWrVqlf75z3/ahSLz5s3TmDFjNHr0aO3atUtr1qxRq1at7I4xefJkDRgwQDt37tT999+voUOH6vjx49XW9Nlnnyk8PNyuLSsrS3fddZfc3NxsbTExMcrPz9d///tfSbJ9OT33RbQ6GRkZysvLU2Zmpt5//32tXr1akydPtm0vKytTYmKitm7dqoyMDLm4uKh///6yWq2SpNmzZ2vNmjVauXKl8vPztWzZMgUHB9vG/+lPf1JJSYn+8Y9/KCcnR506dVLv3r0veM6SlJKSogkTJmjbtm2qU6eOhgwZomeffVazZs3SZ599pgMHDig5OdnWf9asWXrjjTf0+uuva+fOnYqJidEf/vAH7d+/X5J0+vRp/f73v1e7du2Uk5OjSZMm6ZlnnrE75okTJ9SrVy917NhRW7duVXp6uoqLizVgwIAL1no1HDhwQOnp6erRo4et7WLX+JlnnrHdXVVYWFgldDjf0qVLVb9+fX3xxRd69dVX9eKLL2r9+vW27Y5ex2eeeUYDBgywhR2FhYXq2rVrjc/3zJkzev311/W3v/1N//nPf1RQUGB3vZYtW6bk5GS9/PLLysvL09SpUzVx4kQtXbpUUs2ud3VmzJihbt26afv27XrggQc0bNgwxcbG6uGHH9a2bdvUsmVLxcbGyjAMSVJOTo4GDBigQYMGadeuXZo0aZImTpxo9wjU8OHDdeTIEW3YsEEffPCB/vrXv6qkpMTuuI58xj/99JP69eunHj16aOfOncrKytLo0aNtwZgkhYeH66efftIXX3xR488dAIBrkgEAuKLi4uIMV1dXo379+nbLyy+/bOsjyXj00UftxkVGRhqPPfaYYRiGsWDBAqNhw4bG6dOnbdvXrl1ruLi4GEVFRYZhGEbTpk2NF154odo6JBkTJkywrZ8+fdqQZPzjH/+odkxoaKjx4osv2rXdc889xujRo+3avvzyS0OSsWfPHsMwDOOLL74w2rRpY3zzzTfV7jsuLs5o1KiRUVZWZmubN2+e4eXlZVRWVpqOOXr0qCHJ2LVrl2EYhvHEE08YvXr1MqxWa5W+n332meHt7W38+OOPdu0tW7Y03nrrLdP9Hzp0yJBkvP3227a2999/35BkZGRk2NpSU1ONNm3a2NabNm1qdz0NwzC6dOliPP7444ZhGMZbb71lNG7c2Pjhhx/szlWSsX37dsMwDGPKlCnGvffea7ePI0eOGJKM/Px8wzAMo0ePHsbYsWNNa7+Yd955x/Dx8XFoTFRUlOHu7m5IMkaPHm13XWpyjT/66CPj1//UiIuLMx588EHbeo8ePYw777zTrk+XLl2M8ePHG4ZxadfR7DiGYRgbNmwwJBn//e9/bW3bt283JBmHDh0yDOPnz0mSceDAAVufuXPnGn5+fnbHXr58ud2+p0yZYkRFRRmGUbPrbSYoKMh4+OGHbeuFhYWGJGPixIm2tqysLEOSUVhYaBiGYQwZMsS455577Pbzl7/8xWjXrp1hGIaRn59vSDKys7Nt2/Py8gxJxowZMwzDqNlnnJKSYoSGhhqGYRjff/+9IcnIzMys9lwMwzAaNmxoLFmy5IJ9AAC41nGnCQBcBXfffbdyc3PtlkcffdSuT1RUVJX1c3ea5OXlKTQ0VPXr17dt79atm6xWq/Lz81VSUqLvvvtOvXv3vmAdHTp0sP25fv368vb2rvJ/nM/3ww8/yMPDo8bneU5ERIT27t1r91iPmdDQUHl6etrWo6KidPr0aR05ckSStH//fg0ePFgtWrSQt7e37S6SgoICST//H/Tc3Fy1adNGTz75pNatW2fb144dO3T69Gk1btxYXl5etuXQoUN2j/iYOf9z8vPzkyS7x1v8/Pxsn1tpaam+++47devWzW4f3bp1s7t+HTp0sPssf329d+zYoQ0bNtjV2rZtW0m6aL2X47e//a3tePfdd5/dtrS0NG3btk3Lly/X2rVr9frrr9u21fQa18T5n7ckBQQE2D7fi13HgoICu3ZH5lypjqenp1q2bGlaT1lZmQ4ePKgRI0bYHfell16yXaeaXO/q1ORnT5Ktnry8PNOfvf3796uyslJ5eXmqU6eOOnfubNvetm1bu0mBHf1dadSokYYPH66YmBj17dtXs2bNMr2TqF69ejpz5kyNzhsAgGsVE8ECwFVQv379Ko/K1KZ69erVqF/dunXt1i0Wi+1RFzNNmjSxPXJzjr+/v4qLi+3azq37+/vXqI6a6tu3r4KCgrRw4UI1bdpUVqtVd9xxh23ek06dOunQoUP6xz/+oX/+858aMGCAoqOj9cEHH+j06dMKCAhQZmZmlf1e7C0y539O5x45+HXbhT63S3H69Gn17dtXr7zySpVtAQEBtXqs833yySe2t+L8+ucoMDBQktSuXTtVVlZq9OjRevrpp+Xq6lqrNVzo5/Ji19HX19fuNb6NGjWq9jguLj//vyLj/z/aIsn0jUBm9Zwbc24eoYULFyoyMtKuX218LjX52ZNUqz9/l/K78s477+jJJ59Uenq60tLSNGHCBK1fv16/+93vbH2OHz+uW265pdbqBADAGQhNAOAa8fnnnys2NtZuvWPHjpKkkJAQLVmyRGVlZba7TTZt2iQXFxe1adNGDRo0UHBwsDIyMnT33XfXWk0dO3bUnj177NqioqL0wgsv6OzZs7Yvc+vXr1ebNm3sJretiR07duiHH36wfVn//PPP5eXlpcDAQH3//ffKz8/XwoULbW/g2LhxY5V9eHt7a+DAgRo4cKD+53/+R3369NHx48fVqVMnFRUVqU6dOnbznNQ2b29vNW3aVJs2bbKb82PTpk2KiIiQ9PP1+9vf/qYff/zRdvfB559/brefTp066cMPP1RwcLDq1Ll6/3kOCgqqUT+r1aqzZ8/KarXWemhyITW5jmaBpJubmyorK+3azn2BLywstP2snh+41ISfn5+aNm2qr776SkOHDjXtU5PrXVtCQkK0adMmu7ZNmzbp9ttvl6urq9q2bauffvpJOTk56tKli6SfXyl9/mS4l/q70rFjR3Xs2FFJSUmKiorS8uXLbaHJwYMH9eOPP9r+DgMA4HrF4zkAcBWUl5erqKjIbvn1W1FWrVqlxYsXa9++fUpJSVF2drZtotehQ4fKw8NDcXFx2r17tzZs2KAnnnhCw4YNs92uP2nSJL3xxhuaPXu29u/fr23bttm9KvhSxMTEKCsry+7L55AhQ+Tm5qYRI0boyy+/VFpammbNmqXExERbn+zsbLVt21bffvvtBfdfUVGhESNGaM+ePfrkk0+UkpKihIQEubi4qGHDhmrcuLEWLFigAwcO6F//+pfdMSRp+vTpev/997V3717t27dPq1atkr+/v3x9fRUdHa2oqCj169dP69at0+HDh7V582a98MILVd4+crn+8pe/6JVXXlFaWpry8/P13HPPKTc3V2PHjrV9ZhaLRaNGjbKd6/mPukjSmDFjdPz4cQ0ePFhbtmzRwYMH9emnnyo+Pr7Kl39HFBQUKDc3VwUFBaqsrLQ9HvbrNy+db9myZVq5cqXy8vL01VdfaeXKlUpKStLAgQNtQVlNr/HlutTrGBwcrJ07dyo/P1/Hjh3T2bNn1apVKwUGBmrSpEnav3+/1q5dW+VNMzUxefJkpaamavbs2dq3b5927dqld955x/YGqZpc79ry9NNPKyMjQ1OmTNG+ffu0dOlSzZkzxzbxbJs2bdSnTx/9+c9/1hdffKGcnByNHDnS7q4iRz/jQ4cOKSkpSVlZWfr666+1bt067d+/XyEhIbY+n332mVq0aGH3mBMAANclZ0+qAgA3uri4OENSleX8iUQlGXPnzjXuuecew93d3QgODjbS0tLs9rNz507j7rvvNjw8PIxGjRoZo0aNMk6dOmXXZ/78+UabNm2MunXrGgEBAcYTTzxhd4yPPvrIrr+Pj4/xzjvvVFv72bNnjaZNmxrp6el27Tt27DDuvPNOw93d3WjWrJkxbdo0u+3nJtw8N7lmdZ/Lgw8+aCQnJxuNGzc2vLy8jFGjRtlNRrl+/XojJCTEcHd3Nzp06GBkZmbanceCBQuMsLAwo379+oa3t7fRu3dvY9u2bbbxpaWlxhNPPGE0bdrUqFu3rhEYGGgMHTrUKCgoMK3p3ESw50/WaTZ56K8nVa2srDQmTZpkNGvWzKhbt64RGhpaZYLdrKwsIzQ01HBzczPCwsKMDz/8sMqx9u3bZ/Tv39/w9fU16tWrZ7Rt29YYN26cbaLbX08Em5KSYgQFBVX7GZ/7nM1+/jZs2FDtmBUrVhidOnUyvLy8jPr16xvt2rUzpk6dajexaU2ucU0ngv315LYPPvigERcXZ1t39DoahmGUlJQY99xzj+Hl5WV3vhs3bjTat29veHh4GN27dzdWrVpVZSLYX0+Ya3Yey5YtM8LCwgw3NzejYcOGxl133WWsXr3atr0m1/vXgoKCbJOznvPr31uzn9EPPvjAaNeunVG3bl2jefPmxmuvvWa3j8LCQuOBBx4w3N3djebNmxvvvvtulWNd7DM+fyLYoqIio1+/fkZAQIDh5uZmBAUFGcnJyXYTBd97771GampqtecKAMD1wmIY5z3YCwBwCovFoo8++kj9+vVzdilVzJ07V2vWrNGnn37q7FLwK3FxcbJYLHavlwWc7csvv1SvXr20b98++fj4OLscAAAuC3OaAAAu6M9//rNOnDihU6dOqUGDBs4uB/+fYRjKzMw0necFcKbCwkK9++67BCYAgBsCd5oAwDXgWr7TBAAAALhZcacJAFwDyK8BAACAaw9vzwEAAAAAADBBaAIAAAAAAGCC0AQAAAAAAMAEoQkAAAAAAIAJQhMAAAAAAAAThCYAAAAAAAAmCE0AAAAAAABMEJoAAAAAAACYIDQBAAAAAAAw8f8AhPjuKDiTlx4AAAAASUVORK5CYII=","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","      <th>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-525</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","      <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","      <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","      <td>是</td>\n","      <td>是</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","      <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>不是</td>\n","      <td>不是</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","      <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>不重要。</td>\n","      <td>是</td>\n","      <td>不重要</td>\n","      <td>不重要</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>不是</td>\n","      <td>不是</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","      <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","      <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>不是</td>\n","      <td>不是</td>\n","      <td>问法错误</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3000 rows × 9 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                                不重要。   \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                                                     是   \n","3                                                     是   \n","4                                                    不是   \n","...                                                 ...   \n","2995                                                  是   \n","2996                                                 不是   \n","2997                                                  是   \n","2998                                                  是   \n","2999                                                 不是   \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                                                不重要   \n","2996                                                 不是   \n","2997                                                  是   \n","2998                                                  是   \n","2999                                                 不是   \n","\n","     shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-525  \n","0                                                    不是  \n","1                                                     是  \n","2                                                     是  \n","3                                                     是  \n","4                                                    不是  \n","...                                                 ...  \n","2995                                                不重要  \n","2996                                                 不是  \n","2997                                                  是  \n","2998                                                  是  \n","2999                                               问法错误  \n","\n","[3000 rows x 9 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-p2.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',\n"," 'shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-525']"]},"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。          1295\n","是。            686\n","是             632\n","问法错误          154\n","不重要。          117\n","不重要            63\n","回答正确           36\n","问法错误。          15\n","他要带走的是物品。       1\n","回答正确。           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","不是      1848\n","是        993\n","不重要       72\n","问法错误      45\n","回答正确      42\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","不是      1226\n","是       1074\n","不重要      389\n","问法错误     277\n","回答正确      34\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA94AAAI2CAYAAACmDVBwAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAABiX0lEQVR4nO3dd3QU1f/G8Sc9m4Qk9BISei82qoBSBUEJQcQCShWQIkVFkaYiICBiAURQUBC/KKCAEVCkSBEEKYIiPZCAJECAFMhuks38/uCwP9aEIu5kCbxf5+yRvffO7Gc2szHPzp0ZD8MwDAEAAAAAAFN4ursAAAAAAABuZwRvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARN7uLsBVsrKy9Pfffytfvnzy8PBwdzkAAAAAgNucYRhKSUlRiRIl5Ol59ePat03w/vvvvxUeHu7uMgAAAAAAd5i4uDiVLFnyqv23TfDOly+fpEsbHBwc7OZqAAAAAAC3u+TkZIWHhzvy6NXcNsH78vTy4OBggjcAAAAAINdc73RnLq4GAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN7INdu2bdOKFSvcXQYAAAAA5CqCNxyaNGkiT09PvfPOO07tGzduVN26dRUcHKx69eppy5Ytjj673a633npLpUuXVuHChdW9e3clJSVlW3dWVpb69OmjlJQU07cDAAAAAG4lBG84rF27VqNGjXJqO3jwoDp27KixY8cqISFBQ4cOVbt27XT8+HFJ0tixY7Vx40Zt2rRJ+/fvl5eXl7p165Zt3TNmzFDhwoXVsWPHXNkWAAAAALhVeLu7ANzapk6dqiFDhqh58+aSpPbt2+vXX3/V119/rSFDhuj999/X3r17VbRoUUnSRx99pFKlSuns2bMqUKCAJOnMmTMaO3as1q9f77btAAAAAAB34Yg3rqlMmTKKjIx0agsPD1dCQoJSU1PVs2dPR+iWJG9vbxUvXlwJCQmOtldeeUXPP/+8ypUrl2t1AwAAAMCtguCNaxo0aJAqVKjg1BYdHa1atWopKChIEyZMcOqLjY3V8ePHVbZsWUmXLqg2Z84czZw5U4ULF9akSZNyrXYAAAAAuBUQvPGvfPbZZ4qPj1dUVFS2Prvdrm7duumll16Sn5+fJGn48OHq1auXdu/erZ9++kkzZ87Ud999l9tlAwAAAIDbcI43bti2bdv0yiuvaN26dfL2zr7rvPLKK/Lx8dGQIUMkSWfPntXevXv1/fffy8fHR6GhoZoyZYqmT5+uRx99NLfLBwAAAAC3IHjjhsTGxioqKkqffvqpqlSpkq1/1qxZio6O1ubNm+XpeWkixeHDh1WxYkX5+Pg4xtWsWVPHjh3LtboBAAAAwN0I3riulJQUPfLII3r55Zf1yCOPZOv/6aefNGrUKG3cuFH58+d3tJcsWVL79+9XRkaGI3zv2bNHZcqUybXaAQAAAMDdOMcb12S329WxY0c98MADGjhwYLb+vXv3qlOnTlq4cGG2q5YXL15cderU0YABA3T+/Hnt3r1bQ4YMyXE9AAAAAHC7InjjmgYMGKCVK1dqxowZ8vb2djyaNWumU6dOqU2bNjp16pQaN27s1D937lxJly7GduHCBZUtW1YdO3bU6NGj1aJFCzdvFQAAAADkHg/DMAx3F+EKycnJCgkJUVJSkoKDg91dzr9S+tXv3V3CHefo223cXQIAAACAPO5GcyhHvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAw0U0F7yZNmsjT01PvvPOOU/vGjRtVt25dBQcHq169etqyZYtT/5tvvqmiRYsqODhY3bt3V2pqqqMvOTlZnTp1UlBQkEqUKKEJEybcTGkAAAAAANxSbip4r127VqNGjXJqO3jwoDp27KixY8cqISFBQ4cOVbt27XT8+HFJ0owZM7RkyRJt2bJFx48fl4eHh5577jnH8r169ZKPj49OnDihzZs3a9GiRfr444//w6YBAAAAAOB+3q5a0dSpUzVkyBA1b95cktS+fXv9+uuv+vrrrzVkyBBNmTJFX375pcqUKSPpUhAvV66cDh8+LH9/f61du1bHjh2Tv7+/QkJCNHfuXD388MPq3bu3q0oEAAAAACDXuSx4lylTRm3aON+iKTw8XHFxcTp16pQuXLig++67z9Hn4+Ojtm3bas2aNQoJCVGLFi3k7+/v6K9SpYqCgoJ08OBBVahQwVVlAgAAAACQq1x2cbVBgwZlC8jR0dGqVauWYmNjVb58+WzLVKpUSUeOHLluPwAAAAAAeZVpVzX/7LPPFB8fr6ioKKWlpSkgICDbGIvForS0tOv258Rmsyk5OdnpAQAAAADArcaU4L1t2za98sor+t///idvb29ZLBZZrdZs4xITExUQEHDd/pyMHz9eISEhjkd4eLjLtwMAAAAAgP/K5cE7NjZWUVFR+vTTT1WlShVJUkREhGJiYrKNjYmJUdmyZa/bn5Nhw4YpKSnJ8YiLi3PthgAAAAAA4AIuDd4pKSl65JFH9PLLL+uRRx5xtBcpUkS+vr7av3+/oy0zM1NLly5Vs2bN1KBBA61evVqZmZmO/j/++EM2my3Hc78lyc/PT8HBwU4PAAAAAABuNS4L3na7XR07dtQDDzyggQMHZusfPHiwevbsqePHjyslJUUDBgxQ8+bNVaZMGYWFhen+++/X4MGDlZqaqri4OD333HMaMWKEq8oDAAAAAMAtXBa8BwwYoJUrV2rGjBny9vZ2PJo1ayZJ6tOnj1q0aKF7771XYWFhSk9P14wZMxzLf/zxxzp79qyKFSumOnXqqH379urRo4erygMAAAAAwC08DMMw3F2EKyQnJyskJERJSUl5btp56Ve/d3cJd5yjb7e5/iAAAAAAuIYbzaGm3U4MAAAAAAAQvAEAAAAAMBXBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbwB2lSZMm8vT01DvvvOPUvmnTJt19992yWCyqXbu2tm7d6ujr0aOHvL29nR4eHh6aMmVKjq+xaNEibd++3dTtAAAAQN5B8AZwR1m7dq1GjRrl1JaQkKCoqCiNGjVKycnJGj58uCIjIxUfHy9J+vTTT5WZmel4HDlyRGFhYerdu3e29Z88eVK9e/eWYRi5sj0AAAC49RG8AdzxZs+erSeeeELt27eXj4+P2rVrpy5dumj69Ok5jp8wYYIGDBiggICAbH3du3dXUlKS2SUDAAAgDyF4A7jjbdiwQZGRkU5tHTp00OrVq7ONPXnypJYsWaK+fftm65s2bZouXLig+++/37RaAQAAkPcQvAHc8WJjY1W+fHmntkqVKunIkSPZxk6aNEl9+vRRvnz5nNoPHDigt956S3PnzpWnJ79aAQAA8P+83V0AALhbWlpatmnjFotFaWlpTm2nT5/WV199pb179zq1Z2ZmqnPnzpowYYJKly5tdrkAAADIYzgsA+COZ7FYZLVandoSExOzhfF3331X3bt3V0hIiFP7W2+9pVKlSunZZ581vVYAAADkPRzxBnDHi4iIUExMjCIiIhxtMTExKlu2rOP5uXPnNHfuXO3evdtp2e3bt2vChAnKysqSv7+/JCk9PV0NGjTQ5MmT1b9//9zZCAAAANyyOOIN4I7XsGFDrVy50qlt0aJFat68ueP5Bx98oE6dOqlgwYJO4+677z6lpaXJZrPJarXKarXqgQce0KZNmwjdAAAAkMQRbwBQjx49dM899+iBBx5QixYttHLlSi1YsEA7duyQJKWkpGjWrFnavn27mysFAABAXkTwBnDHK1q0qBYuXKh+/fopKipK1atX15IlS1SkSBFJ0t69e9WzZ08VLVrUzZUCAAAgL/IwDMNwdxGukJycrJCQECUlJSk4ONjd5fwrpV/93t0l3HGOvt3G3SXccdjPcx/7OQAAgLluNIdyjjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYKKbCt5NmjSRp6en3nnnHaf2TZs26e6775bFYlHt2rW1detWp/6ZM2cqIiJCgYGBioqKUkJCgqMvIyNDL7zwgvLnz6+CBQvq5ZdfVmZm5s2UBwAAAADALeOmgvfatWs1atQop7aEhARFRUVp1KhRSk5O1vDhwxUZGan4+HhJ0sqVKzVu3DhFR0frzJkzql69uqKiohzLjxw5UgcOHNC+ffu0b98+7d27VyNHjvwPmwYAAAAAgPu5bKr57Nmz9cQTT6h9+/by8fFRu3bt1KVLF02fPl2SNGXKFE2ePFk1a9aUxWLRmDFjlJWVpTVr1ig9PV2zZs3SZ599pqJFi6pw4cKaO3euPvnkE124cMFVJQIAAAAAkOtcFrw3bNigyMhIp7YOHTpo9erVMgxDv/76q9q0aZNj/65du1SlShUVK1bM0VewYEHVrVtXv/zyi6tKBAAAAAAg17kseMfGxqp8+fJObZUqVdKRI0eUmJio0NBQ+fv759if07JX9ufEZrMpOTnZ6QEAAAAAwK3GZcE7LS1NAQEBTm0Wi0VpaWk59v2b/pyMHz9eISEhjkd4eLhrNgQAAAAAABdyWfC2WCyyWq1ObYmJiQoICMix79/052TYsGFKSkpyPOLi4lyzIQAAAAAAuJDLgndERIRiYmKc2mJiYlS2bFkVLFhQ58+fV0ZGRo79OS17ZX9O/Pz8FBwc7PQAAAAAAOBW47Lg3bBhQ61cudKpbdGiRWrevLk8PDxUq1YtrVmzJsf+u+++W3v37tW5c+ccfWfPntWvv/6q+++/31UlAgAAAACQ61wWvHv06KHPP/9cK1asUGZmpqKjo7VgwQL17dtXkjRkyBANGjRI+/btk9Vq1ZgxY2SxWNS4cWP5+vqqW7dueu6555SYmKgzZ86oe/fu6t+//1WnmgMAAAAAkBe4LHgXLVpUCxcu1LBhwxQUFKTXX39dS5YsUZEiRSRJrVq10qBBg9SiRQsVKFBAO3bs0OLFix3Lv/nmmypevLjKlSunihUrqkKFCnr99dddVR4AAAAAAG7hYRiG4e4iXCE5OVkhISFKSkrKc+d7l371e3eXcMc5+nab6w+CS7Gf5z72cwAAAHPdaA512RFvAAAAAACQHcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAE7k0eCcmJqpz584qUKCAIiIiNHnyZEffX3/9pYYNG8pisahatWpavny507JLlixRxYoVZbFY1LRpUx08eNCVpQEAAAAA4BYuDd5dunRR+fLlFRcXp23btmnDhg36/PPPZbPZ1Lp1az311FNKSkrSjBkz1LNnT+3Zs0eStGfPHvXu3VuzZs1SUlKSOnbsqFatWslqtbqyPAAAAAAAcp1Lg/f69ev12muvKTAwUEWLFtWAAQP07bff6ptvvlH16tXVr18/+fr6qlGjRho1apQmTZokSZo6daqGDh2qBx98UL6+vurTp49q166tL7/80pXlAQAAAACQ61wavNu0aaOhQ4cqOTlZcXFxGjdunIoWLaoNGzYoMjLSaWyHDh20evVqSbpuPwAAAAAAeZVLg/e0adO0ePFihYSEKCIiQidPntTo0aMVGxur8uXLO40tVKiQrFarbDabTpw4obJlyzr1V6pUSUeOHLnqa9lsNiUnJzs9AAAAAAC41bgseGdmZurRRx/V008/rcTERB07dkytWrXSqVOnlJaWpoCAgGzLWCwWpaWlKSsrS56enjn2Xc348eMVEhLieISHh7tqUwAAAAAAcBmXBe/o6GhZLBZNmDDBcVXzMWPGqFu3bvL19c3xQmlnz55VQECAPD09ZRiGU19iYmKOYf2yYcOGKSkpyfGIi4tz1aYAAAAAAOAyLgve+/fvV6NGjZzaAgMDFRoaKkmKiYlx6ouPj1eBAgXk6+ursLAwxcbGOvXHxMRkm35+JT8/PwUHBzs9AAAAAAC41bgseJctW1b79u1zarNarfrrr7/UuXNnrVy50qlv0aJFat68uSSpYcOG1+wHAAAAACCvclnwfvTRR7Vjxw5NmzZNKSkpOnHihLp06aL69evrscce09atWzV37lxlZGRo8+bNmjhxol5++WVJ0oABA/TWW2/p119/VUZGhmbPnq3du3frqaeeclV5AAAAAAC4hcuCt7+/v6Kjo7Vs2TIVLVpUdevWVZEiRTR37lz5+/vru+++08yZM5UvXz716NFDM2fOVLVq1SRJNWrU0IcffqhnnnlGwcHB+uKLL7R8+XL5+fm5qjwAAAAAANzC25Urq1Chgn744Ycc+6pWraqNGzdeddl27dqpXbt2riwHAAAAAAC3c+l9vAEAAAAAgDOCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAiU4P3sWPH9Pnnn5v5EgAAAAAA3NJMDd4DBw5UQkKC4/mmTZt09913y2KxqHbt2tq6davT+JkzZyoiIkKBgYGKiopyWhYAAAAAgLzItOC9fPlyHT58WEOGDJEkJSQkKCoqSqNGjVJycrKGDx+uyMhIxcfHS5JWrlypcePGKTo6WmfOnFH16tUVFRVlVnkAAAAAAOQKU4K3zWbToEGDNGPGDHl7e0uSZs+erSeeeELt27eXj4+P2rVrpy5dumj69OmSpClTpmjy5MmqWbOmLBaLxowZo6ysLK1Zs8aMEgEAAAAAyBWmBO+JEyfqgQceUIMGDRxtGzZsUGRkpNO4Dh06aPXq1TIMQ7/++qvatGmTYz8AAAAAAHmVy4N3XFycxo8frx9++EH58+fXiy++qKysLMXGxqp8+fJOYytVqqQjR44oMTFRoaGh8vf3z7E/JzabTcnJyU4PAAAAAABuNS4P3mPGjFGLFi20fft27dixQxs3btS0adOUlpamgIAAp7EWi0VpaWk59l3Zn5Px48crJCTE8QgPD3f1pgAAAAAA8J95u3qFS5cu1b59+5Q/f35J0qeffqqOHTvKYrHIarU6jU1MTFRAQECOfVf252TYsGGOC7dJUnJyMuEbAAAAAHDLcekR79OnTyswMNARuiWpWrVqOn78uCIiIhQTE+M0PiYmRmXLllXBggV1/vx5ZWRk5NifEz8/PwUHBzs9AAAAAAC41bg0eBcsWFDnzp3TuXPnHG179+5VRESEGjZsqJUrVzqNX7RokZo3by4PDw/VqlUr2xXML/cDAAAAAJBXuTR4e3p6qmvXruratatOnTqlmJgY9ezZUwMHDlSPHj30+eefa8WKFcrMzFR0dLQWLFigvn37SpKGDBmiQYMGad++fbJarRozZowsFosaN27syhIBAAAAAMhVLj/H++2339Yrr7yi6tWrKzAwUC+88IKee+45SdLChQvVr18/RUVFqXr16lqyZImKFCkiSWrVqpWOHTumFi1aKDExUS1bttTixYtdXR4AAAAAALnKwzAMw91FuEJycrJCQkKUlJSU5873Lv3q9+4u4Y5z9O021x8El2I/z33s5wAAAOa60Rzq8tuJAQAAAACA/0fwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAOA2FhMTo1atWilfvnyqVKmSFixY4Ohbt26datWqpaCgINWvX1+//faboy8jI0MjRoxQRESEChcurF69eik1NdUdmwAAQJ5H8AYA4DZlGIbatm2rpk2b6syZM/r66681bNgwbdmyRbGxserSpYumTJmic+fOafLkyXr22WeVmJgoSRoxYoT++OMPbdmyRfv375dhGOrbt6+btwgAgLzJ1OA9adIknTlzRpL0119/qWHDhrJYLKpWrZqWL1/uNHbJkiWqWLGiLBaLmjZtqoMHD5pZGgAAt73z58+rf//+Gjp0qPz8/HTXXXcpMjJSGzdu1NatW/XAAw+oUaNG8vHx0f3336/77rtPGzZskCTNmzdPs2fPVokSJVSgQAF99NFH+uGHH2Sz2dy8VQAA5D2mBe/du3dr5MiRkiSbzabWrVvrqaeeUlJSkmbMmKGePXtqz549kqQ9e/aod+/emjVrlpKSktSxY0e1atVKVqvVrPIAALjt5c+fX71795Ykpaena9WqVVq8eLGaNm2qBg0aaMOGDVqxYoXS09P1448/atmyZSpatKgkyW63y8PDw2l9mZmZSklJyfXtAAAgrzMleKenp+uZZ55RZmamJOmbb75R9erV1a9fP/n6+qpRo0YaNWqUJk2aJEmaOnWqhg4dqgcffFC+vr7q06ePateurS+//NKM8gAAuOPUrVtXDz30kBo3bqx77rlHxYsX18SJE9W6dWv5+fmpZcuW6tatm+rXry9Jeuyxx9SjRw+dPHlSZ8+e1fPPP6+iRYuqUKFCbt4SAADyHlOC9/Dhw1WjRg2VLFlSkrRhwwZFRkY6jenQoYNWr159Q/0AAOC/2bx5szZv3qz9+/dr3Lhx2r59u1566SV9//33unjxon788Ud5e3s7ppJPmjRJhQsX1l133aUaNWrok08+0fDhw928FQAA5E0uD97r16/XokWLNG3aNEdbbGysypcv7zSuUKFCslqtstlsOnHihMqWLevUX6lSJR05csTV5QEAcEfy9/dXvXr19O233+rdd9/VmDFjNG7cOLVu3VoWi0UtWrRQnTp1HOE6MDBQH3/8sU6dOqXIyEg1b95cnTp1cvNWAACQN7k0eCcnJ6tr166aM2eOQkJCHO1paWkKCAjINt5isSgtLU1ZWVny9PTMse9qbDabkpOTnR4AAOD/HT16VCdPnnRqCwsLk5eXl37//Xc1atTIqa9u3br64YcfnNq2bdum+fPna9asWabXCwDA7cqlwfuFF17QY489psaNGzu1WyyWHC+UdvbsWQUEBMjT01OGYTj1JSYm5hjWLxs/frxCQkIcj/DwcJdsAwAAt4tNmzbppZdecmo7evSo8uXLp6pVq2rfvn1OfTt27FCxYsUcz+12u/r06aO33npLpUuXzo2SAQC4LbkseC9dulTz58/Xhx9+KH9/f/n7++vYsWMqWbKk/vzzT8XExDiNj4+PV4ECBeTr66uwsDDFxsY69cfExGSbfn6lYcOGKSkpyfGIi4tz1aYAAHBbaNeunbZu3arPP/9caWlp2rdvn5588kmNHDlSgwcP1oABA7RlyxbZbDatX79eAwcOVL9+/RzLT5s2TRaLxakNAAD8ey4L3pGRkcrIyJDVanU8SpUqpePHj2vs2LFauXKl0/hFixapefPmkqSGDRtesz8nfn5+Cg4OdnoAAID/FxgYqOjoaH3xxRcqXLiwHnroIT399NPq2rWrmjdvrhEjRuiZZ55RaGioBgwYoIkTJ6pdu3aO5fPly6dPP/002+lgAADg3/HOjRdp3769Ro4cqblz5+qpp57Sb7/9pokTJ2rFihWSpAEDBqh169a6++67de+992revHnavXu35s+fnxvlAQBw26pUqZJWrVqVY9+zzz6rZ5999qrLduvWzayyAAC4o+RK8Pb399d3332nXr16qVevXipbtqxmzpypatWqSZJq1KihDz/8UM8884zi4uJUv359LV++XH5+frlRHgAALlH61e/dXcId5+jbbdxdAgAA12Vq8D569Kjj31WrVtXGjRuvOrZdu3ZO09sAAAAAALgdcNIWAAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAACDPOnfunLp06aLChQurdOnSevvtt5WVlaW5c+fK29vb6eHp6anIyEhJUo8ePbL1e3h4aMqUKW7eIgC3I4I3AAAA8qwOHTooLCxMhw8f1qpVq7RkyRJNnTpVzz77rDIzMx2P9PR0ValSRSNGjJAkffrpp079R44cUVhYmHr37u3mLQJwOyJ4AwAAIE/auXOnTp06pbFjxyo4OFgVKlTQnDlz9Mknn2Qbu3jxYkVERKh27do5rmvChAkaMGCAAgICzC4bwB3I290FAAAAADfDbrdryJAh8vDwcLSFh4crISHBaZxhGBo7dqymT5+e43pOnjypJUuWaN++fabWC+DORfAGAABAnlSrVi3VqlXLqS06Ojpb23fffaeCBQvq/vvvz3E9kyZNUp8+fZQvXz7TagVwZyN4AwAA4LYQHx+vF198Ud98841T+1tvvaWJEyfmuMzp06f11Vdfae/evblRIoA7FOd4AwAAIM+z2Wx67LHH1LdvX9WtW9fR/sMPP8jPz0+NGzfOcbl3331X3bt3V0hISC5VCuBOxBFvAAAA5Hk9evRQeHi4XnvtNaf2sWPHauTIkTkuc+7cOc2dO1e7d+/OjRIB3MEI3gAAAMjTXn/9dR05ckRr1qxxutDazz//LJvNpoceeijH5T744AN16tRJBQsWzK1SAdyhCN4AAADIs+bPn6958+Zp8+bN8vf3d+obM2aM477d/5SSkqJZs2Zp+/btuVEmgDscwRsAAAB50oYNG9S9e3dlZGSoRIkSTn2HDx9WwYIF9eijj+a47N69e9WzZ08VLVo0N0oFcIcjeAMAAOCGlX71e3eX4KT44G9ybH/woz+kMs9ep97a+uwW256cHH27jbtLAPAfcVVzAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAEzk0uB97tw5denSRYULF1bp0qX19ttvKysrS5K0adMm3X333bJYLKpdu7a2bt3qtOzMmTMVERGhwMBARUVFKSEhwZWlAQAAAADgFi4N3h06dFBYWJgOHz6sVatWacmSJZo6daoSEhIUFRWlUaNGKTk5WcOHD1dkZKTi4+MlSStXrtS4ceMUHR2tM2fOqHr16oqKinJlaQAAAAAAuIXLgvfOnTt16tQpjR07VsHBwapQoYLmzJmjTz75RLNnz9YTTzyh9u3by8fHR+3atVOXLl00ffp0SdKUKVM0efJk1axZUxaLRWPGjFFWVpbWrFnjqvIAAAAAAHALlwVvu92uIUOGyMPDw9EWHh6uhIQEbdiwQZGRkU7jO3TooNWrV8swDP36669q06ZNjv0AAAAAAORl3q5aUa1atVSrVi2ntujoaNWqVUvHjh1T+fLlnfoqVaqkI0eOKDExUaGhofL398/W/+WXX1719Ww2m2w2m+N5cnKyC7YCAAAAAADXMu2q5vHx8XrxxRc1atQopaWlKSAgwKnfYrEoLS0tx74r+69m/PjxCgkJcTzCw8Ndvg0AAAAAAPxXpgRvm82mxx57TH379lXdunVlsVhktVqdxiQmJiogICDHviv7r2bYsGFKSkpyPOLi4ly+HQAAAAAA/Fcum2p+pR49eig8PFyvvfaaJCkiIkIxMTGKiIhwjImJiVHZsmVVsGBBnT9/XhkZGfLx8cnWfzV+fn7y8/Mzo3wAAAAAAFzG5Ue8X3/9dR05ckSfffaZ40JrDRs21MqVK53GLVq0SM2bN5eHh4dq1aqV7Qrml/sBAAAAAMjLXHrEe/78+Zo3b542b97sdLG0Hj166J577tEDDzygFi1aaOXKlVqwYIF27NghSRoyZIgGDRqkb7/9VqVLl9akSZNksVjUuHFjV5YHAAAAAECuc1nw3rBhg7p3766MjAyVKFHCqe/w4cNauHCh+vXrp6ioKFWvXl1LlixRkSJFJEmtWrXSsWPH1KJFCyUmJqply5ZavHixq0oDAAAAAMBtXBa8GzVq5HR7r38qVaqUdu3addX+3r17q3fv3q4qBwAAAACAW4JptxMDAAAAAAAEbwAAAAAATEXwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAACAPCQmJkatWrVSvnz5VKlSJS1YsCDHcRkZGRo5cmQuV4ecELwBAAAAII8wDENt27ZV06ZNdebMGX399dcaNmyYtmzZkm3sqFGjtHPnTjdUiX8ieAMAAABAHnH+/Hn1799fQ4cOlZ+fn+666y5FRkZq48aNTuM2bdqkd999101V4p8I3gAAAACQR+TPn1+9e/eWJKWnp2vVqlVavHixmjZt6hiTmpqqLl266KWXXnJXmfgHgjcAAAAA5EF169bVQw89pMaNG+uee+5xtA8cOFBt2rRRixYt3FgdrkTwBgAAAIA8aPPmzdq8ebP279+vcePGSZKWLl2qLVu2aMKECW6uDlfydncBAAAAAIB/z9/fX/Xq1dO3336rmjVr6rnnnlO/fv303Xffyd/f393l4QoEbwAAAADII44ePSo/Pz8VL17c0RYWFiYvLy89//zzSkhIUP369SVJWVlZstvtKlasmOLj491VMsRUcwAAAADIMzZt2pTtomlHjx5Vvnz5tHjxYmVkZMhqtcpqterHH3/Uww8/TOi+BRC8AQAAACCPaNeunbZu3arPP/9caWlp2rdvn5588kmNHDnS3aXhGgjeAAAAAJBHBAYGKjo6Wl988YUKFy6shx56SE8//bS6du3q7tJwDZzjDQAAAABXKP3q9+4u4fruG6RC9w2SJL37t/Tu1Wqu/nye2J6jb7dxdwmm4og3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgolsqeCcnJ6tTp04KCgpSiRIlNGHCBHeXBAAAAADAf3JL3ce7V69e8vf314kTJ3T+/Hl16NBBoaGh6t27t7tLAwAAAADgptwywfvEiRNau3atjh07Jn9/f4WEhGju3Ll6+OGHCd4AAAAAgDzrlplqvmnTJrVo0UL+/v6OtipVqigoKEgHDx50Y2UAAAAAANy8W+aId2xsrMqXL5+tvVKlSjpy5IgqVKjg1G6z2WSz2RzPk5KSJF06TzyvybJddHcJd5y8uJ/kdeznuY/9PPexn+c+9vPcx36e+9jPcx/7ee7Lq/v55boNw7jmuFsmeKelpSkgICBbu8ViUVpaWrb28ePH64033sjWHh4ebkp9uL2EvOfuCgDzsZ/jTsB+jjsB+znuBHl9P09JSVFISMhV+2+Z4G2xWHTxYvZvlhITE3MM5MOGDdOQIUMcz7OysnT27FkVLFhQHh4eptaKS5KTkxUeHq64uDgFBwe7uxzAFOznuBOwn+NOwH6OOwH7ee4zDEMpKSkqUaLENcfdMsE7IiJCK1asyNYeExOjsmXLZmv38/OTn5+fU1toaKhZ5eEagoOD+WDjtsd+jjsB+znuBOznuBOwn+euax3pvuyWubhagwYNtHr1amVmZjra/vjjD9lsthzP/QYAAAAAIC+4ZYJ3WFiY7r//fg0ePFipqamKi4vTc889pxEjRri7NAAAAAAAbtotE7wl6eOPP9bZs2dVrFgx1alTR+3bt1ePHj3cXRauws/PT6NHj8425R+4nbCf407Afo47Afs57gTs57cuD+N61z0HAAAAAAA37ZY64g0AAAAAwO2G4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN64aRcuXFDNmjWVmZnpaFu3bp2GDx/u1AbkZampqQoODnbap5cvX65OnTopPT3djZUB/05SUpIGDhx41f7AwECdPn3a8fzChQu5URYAAHcE7uONm5aZmSl/f3+lpaXpyy+/VJcuXbRu3To1a9ZMSUlJCgoKcneJwH9mt9vl5+enCxcuaOLEiRo5cqQ2bNigxo0bs58jT0lOTla1atUUFxenWbNm6eLFi/Lw8JDFYtFzzz2nQoUKKTY2VgEBAUpISNC9996rX375RaVKlXJ36YBLZGZmqlevXnr//feVL18+7dmzR56enqpWrZq7SwP+s+XLlysgIECentmPq3p4eKhYsWKqUKGCGyrDZQRvXNeFCxf00EMPyc/PT5JkGIZCQkK0ZMkSBQUF6ezZsypWrJjOnj2rXbt26b777lNycrICAwPdXDlw41JTU1WpUiWn/bxgwYL67bfflC9fPsd+npiYqN9//1333nsv+znyFJvNpurVq+vgwYOqXLmyGjVqJElau3atDh06pFKlSunYsWOSpGnTpunTTz/Vjh073Fky8K/ZbDZ99NFHslgs8vLy0sWLFxUVFaVmzZppx44dCg0N1fnz5xUUFKSnn35av/zyiw4ePCgfHx93lw7clNjYWEVERKh48eKqXbu2DMPQzz//rAcffFDbt29X9erV5evrqw0bNmjPnj2KiIhwd8l3LKaa47r8/PwUFxenHj166NChQ+rZs6cOHDggSfL395evr6+8vb0dzyXJ19fXbfUCN8Niscjf31/z5s2Th4eHvvjiC128eFHSpc+Aj4+PYz+/vH9fDulAXuDt7e20D8+aNUuzZs2Sl5eXo61t27ZKSEjQ4sWL9dJLL7mzXOCmGIahIUOGaP78+fr88881ZMgQ2Ww2HTlyRP7+/vLz85Ofn5++++47LV68WJ988gmhG3la/fr19cUXXyggIEDLli3Td999p5IlS+q7775T3bp19dlnnyk6OlrdunVz/F0D9/B2dwG49Xl7eys0NFSdOnXShAkT1KlTJ40fP97RJ8nxP62MjAz5+PjwPzHkOV5eXgoMDFSDBg0c/708XeufgTs9PV3+/v6OdiAv8PLyUkJCgvr27av4+Hj17dtXkpz286ZNm6pRo0Y6d+6cHnvsMXeWC9wUPz8/eXl5af369ZKkgIAApy9PPT09NWfOHI0YMUJffvmlmjdv7uaKgf/GYrFo6dKlOnbsmN58801J0pkzZ/Tmm29q//79evfddxUcHKyAgABVrlzZzdXe2firETfl8h9qNptNb775plJTU/Xmm2/qxIkTKlasmJurA1zj8n6elpam7t2769y5c+revbtOnz6t4sWLu7k64N+zWCxq0KCBli9frgYNGsgwDK1du1bSpXMABw0apJSUFC1fvpwZHciTPDw85OHh4dTm5eUlT09PjRgxQhkZGdq0aZO2bt2q0qVLu6dIwAV+++03fffdd/Lz89PChQtVqlQpxwwmDw8PeXl5Of7r6ekpm83m5orBVHPclMuXBsjKytLBgwfVtm1bHTx4ULt27dJdd93l5uoA17i8n3t6eiosLEyDBw9WWFiY0tPTVatWLTdXB/x7ISEh6tSpk/Lnz69OnTqpc+fOkqRBgwYpOTlZkvT3339r9+7d2rlzpztLBW7aPy9flJWVJcMwdPjwYdntdi1dulRffPFFtnFAXpKRkaEff/xRx44d0/Hjx+Xh4aHu3bura9euCgkJUbdu3VSqVCn1799fI0aM0OTJk91d8h2PI964KZf/Z2WxWDRv3jxHe+vWrR1/yAF53eX93NfXV2PGjHG0NWjQQEOGDHFnacBNOXr0qOrUqaODBw+qTp06jvYiRYro3LlzWrFihX7++Wc999xzWrRoke655x43Vgv8e1lZWdmOeGdmZsput+t///ufli1bpnXr1unZZ5/VwYMH9fnnn7upUuC/qV+/vjZv3qwpU6aoVatW8vb2Vr169Ryz9erXr6+zZ8+qUqVKatasmd58801+p7sZR7xxXXa7Xenp6Tpw4IDjv5fvaZyZmak9e/bor7/+0ttvvy2r1arHH3/czRUD/57dbldqaqp+/PFHx38v7+d2u12//PKLfvjhB/Xr109lypRRy5Yt3Vwx8O8VK1ZM8+bNU0REhL744gvNnTtXhmHotddeU4kSJTRixAj5+/srMjJSmzZtcne5wL9mtVqVmZnpNL02JSVFGRkZSk9PV0ZGhipXrqx169Zp7dq1mjlzprtLBm7a6dOntW/fPk2fPl2HDh3SsWPHFBMTo5iYGB07dkwpKSn666+/VKdOHTVt2lTbtm1zd8l3NI5447qsVqsOHDigKlWqyDAMVa5cWSVLlpR06RzvnTt3qnfv3goKCtKWLVvcXC1wc9LS0mS1WtW7d29JUu/evVWgQAFJlz4Dly9GZbfbtXLlSneWCtyUrKwseXt7q1KlSo5z/zw8PJSVlSXp0hepGzZs0KpVq1SiRAn9/vvvbq4Y+Pf8/Py0Z88exz5ut9tVsmRJffjhh0pPT1dmZqYuXLggi8WiadOmqVu3burUqRO3hkSe5OnpqWXLlunjjz+WJNWtW1cJCQlO9/K22Wxq1aqVFi1axHUN3Iz7eOOGXL5a+WXp6eny9vaWv7+/0tPTlZiYqClTpuijjz7SiBEjNHjwYDdWC7iO3W6Xv7+/MjIyZLfbNWfOHL366qvq1KmTJk6cyAWokGdYrVZVqVJFMTExeuCBB5SQkKCMjAwVLVpUmzdvVsmSJXX06FF5e3vrzJkzKlKkiBITE5U/f353lw78a1999ZWioqKy3d40ISFBGzdu1MCBA7VixQr9+eefevLJJ91UJfDfpKamKiIiQp999pmaNGmihx56SA8++KAGDBgg6dLpcXXq1NHevXsVGhrq3mJB8MbNu3jxooKCgpSRkeG4iuLmzZvVvXt3bdy4UQULFnRzhcB/l5qaquDgYMeXTZJ0+PBh9ejRQ99//z1HSZBnnD17VuXKldO5c+dy7A8JCVFcXJyCg4OVkpKiuXPnqlevXtweEnlKbGysHnvsMe3atUuLFi3SxYsXNX78ePn7+zvGGIahAwcOyNvbW19//bWaNWvmxoqBm5ecnKwSJUqoYcOG+v3335WSkqKaNWs6XQB2zpw56tatmyTpgw8+cFepEFPNcYPsdrtOnDih8PBwx0VL/P39tWfPHqfpLPXr19f27dsVEBDgrlIBlwoKClJKSorTPbvLlSuntWvXZruAD3ArK1CgwFVDtyQtWLBAFotFkpQvXz7169cvt0oDXKZYsWKqVauWFixYoHLlyunLL7/UxYsX9eKLLzqNs9vt+vXXXx2nWgB50YULF+Tn56eVK1fKbrdrzZo1mjp1qqZOnao2bdqoXbt2eu+995SamqrExER3l3vH44g3bkhcXJxKly6t+Ph4FS5c2KmvZ8+eqlGjhgYOHOim6gAAALL74YcfFB0drQ8//NDdpQAuZ7VatWPHDt1///1O7WvXrtUXX3yhDz/8kINhtxCCN27I2bNnVahQIaWkpDhNre3Tp4/mzJmjjz76SN27d3djhQCAG3H69Gndd999+v333696/nZcXJx69OihH3/8MZerAwDg9sTtxHBD/Pz85OHh4XSRkhdeeEGLFi3STz/9ROgGgDwgJSVFFotFx48fl8ViUVxcnM6cOaPTp08rNjZWp0+f1rhx4+Tl5aXffvvN3eUCNy0tLU3ffPONJCkiIkJxcXFurghwj1OnTunee+/V/v373V3KHY/gjRty+eI6l89z/eabbzRnzhwtX75cjRo1cmdpAIAb8Pnnn+ull16Sv7+/PDw85O/vr4oVK6po0aIqVqyYypQpo6VLl2r8+PEKDg52uhgVkNdkZGSof//+kiRfX18VKlRImzZtUsuWLdW6dWu1bt1aLVq00COPPOLmSoGbt2vXLgUHB+vvv/+WJCUlJWno0KE6c+aMY4zFYtGuXbu4Ls0tgOCNG+Ll5SXDMDR//nxJUmRkpH766SfVqVPHzZUBAG7EgQMHHPfyvnxRzNKlS8tut6tOnTqaPXu2AgMDVbBgQfn5+TldUBDIK+x2u6pVq6a2bdvq3Llzatq0qU6ePCk/Pz9ZLBadO3dOlStXVtOmTbVz50699tpr7i4ZuGkBAQFKTU11nAbq6+uryZMn6+LFi44xl79E/eet9ZD7+L8q/pWBAwfq3XffVfXq1SVJ06ZNc+rPzMzU+fPntXz5cneUBwC4ipo1a+r777+X9P9/gF15H/rLpxPly5dP3t7eBG/kSRkZGRoxYoQCAwPVt29fvfLKK+rRo4c8PT1lsVhUsGBBVa5cWeXKlZOvr2+2i1IBecnlGUyX70hhsVhkGIbT7+/L/75861+4D0e8ccM8PDy0f/9+1alTR/Pnz9eWLVuUkZHh9EhPT1d6erq7SwUA/EPZsmUVExOj9evXS5LWr1+vixcvav369UpOTta+fft08OBBWa1WbdiwwelWkUBe4e/vr6ZNm6pNmzYKCAhQy5YtHVd1ZqotbjeXTwW9/F/p0n5+5b5++d/8Tnc/vs7GDbl88ftChQppxowZatiwofr166eePXuqWbNmbq4OAHA9RYsW1c6dO/Xiiy8qPT1dL774ok6cOKEXX3xRsbGxWrBggby9vXXy5Em9+OKL/JGGPCkjI0PFixeXt7e37Ha7fHx8lJWVpYyMDFmtVqWlpSkxMVFBQUGy2+2Ki4tTeHi4u8sGboqnp6cMw3D6W9wwDHXo0CHbjCa4H8EbNyQzM1PSpXOnvLy81LlzZwUHBysqKkqrVq1S3bp13VwhAOBaChQooIiICG3btk1BQUHatm2b7r77bm3btk3169fX888/r/z582v48OHatm2bypUr5+6SgX/N09NTcXFxjmsXHD58WBUqVFBqaqoSExN14sQJzZ07V5KUP39+NWjQQLGxsW6uGvhvrvw7/J9/kxuGoZ9//pnwfQsgeOOGZGRkSLoUwC+fI9K2bVv1799fjz/++DXvBwsAcD+LxaLz589LuvQl6pX/vSwrK0sXL16UYRjKysrK7RKB/8zLy0thYWFKS0vTzJkzFRgYqJ49ezqC+DvvvKNWrVpp06ZNatq0qbvLBf4TwzDk4eGh8ePHX3PcxIkTHbNX4T7MI8MNsVqtkiSbzebUPmbMGFksFnXp0sUdZQEAbpCXl5fS0tJkGIbjy9SzZ89q1KhROn78uL755hulpaXp3LlzstlsjplOQF5kGIa6deumEydO6MKFCypUqJDsdrsGDRokPz8/jRs3TgsXLnR3mcB/cuWMVEnavHmzYmNjsz08PDwI3rcAjnjjhqSnp6tq1aqOP9Yu8/Ly0qhRo7RixQplZWVxTiAA3KIyMjKUlZUlq9UqwzBkt9vVtWtXeXh4qHv37rJarY5zY1NTU7N90QrkBVlZWWratKmGDh3qaNu4caPmzp0ru90uq9WquXPn6r777lOPHj1UtWpVVatWzY0VAzfv8u9pm80mm82mBg0aOIXsy//28PDINsMJuY/gjRsSFhamPXv25Nj39NNPq2PHjoRuALiFGYahRYsW6cKFCzIMQxcuXNDYsWOzjUtISNCxY8d04cIFN1QJ/Depqam655571LFjR3l5eenChQuKi4vTt99+K8MwlJqaqm+//VaSVLx4cX388cf64IMP3Fw1cHNSU1Md+3WBAgV06NAhp4uqSZe+dC1XrhyzmG4BHgbzDgAAuCPY7Xbt379fGzduVJcuXbL9gXbZhQsXtGnTJj300EO5XCHgGsePH1ePHj2UlJSk3r17q1u3bjp58qRq166t48ePS7o0m+/yPe2BvOjChQv6448/dO+99zrdUuxKiYmJKly4sHbv3q3q1avncoW4EsEbAIA7RFxcnEqXLq34+HgVLlzYqa9nz56qUaOGBg4c6KbqANd7//331aNHDwUFBclqtWr//v2666673F0WkGsyMjJ04MABlS9f/qpftiJ3MDcYAIA7RGBgoAzDUEBAgFN7nz59NG/ePOXLl89NlQHmGDhwoIKCgiRJ/v7+hG7ccXx8fFStWjVC9y2A4A0AwB3Cz89PHh4eTtNrX3jhBS1atEg//fSTunfv7sbqANex2+06cuSIJCk5OVnBwcGKj493GnP8+HHFxcW5ozzAZQoUKJCtrUOHDlq/fr0bqsG1ELwBALhDXD4H0Nv70rVVv/nmG82ZM0fLly9Xo0aN3Fka4FLJycmqUKGCMjMzFRAQoNTUVKcZHZ988omqV6+u119/3X1FAi4QGhoqwzAUGxsrSUpLS9Py5cuz3YkI7sc53gAA3CHsdrt8fHw0d+5cde7cWXa7Xb/99pvq1q3r7tIAl8rIyFBQUJDjdkve3t6yWq1KTU1V9+7dtXz5cpUvX17bt29nCi7yrJSUFFWoUEG+vr6qVq2aVqxYoTlz5mjcuHHaunWrunbtKi8vLxmGodDQUM2ZM8fdJd/RuJ0YAAB3mIEDB+rdd991XOF22rRpTv2ZmZk6f/68li9f7o7ygP/k4sWLCggIcDqlwtPTU97e3oqLi1NmZqY2b96sRx55hNCNPCshIUENGjSQJK1cuVJVq1bVuXPnNGrUKPXr108eHh7auHGj3n33XQ0bNkzTp093c8VgqjkAAHcQDw8P7d+/X3Xq1NH8+fO1ZcsWZWRkOD3S09OVnp7u7lKBf80wDJUpU0Z16tSR1WpVnTp1VKdOHdntdq1du1b+/v5atmyZ7rnnHiUmJiotLc3dJQM3JTAwUC+++KJ8fX21YMECpaSkqEOHDuratau+/vprJSYmKjAwUF26dFFISIjatWvn7pLveBzxBgDgDnH57LJChQppxowZatiwofr166eePXuqWbNmbq4O+O8yMjL06quvKl++fOrXr5/69esnwzDUo0cPvffee/rll1/02WefqU2bNipWrJgOHTqkGjVquLts4F8LCgrS888/rxo1amjatGkqU6aMhg8frsGDBys6OprZHLcggjcAAHeIzMxMSZfO9fby8lLnzp0VHBysqKgorVq1inO9kef5+vpq8ODByszMVL9+/dSlSxdH8P7666+1aNEiDRgwQCtXrlSBAgW0f/9+gjfytG7duik6Olr79+/Xli1bZBiGPDw85OHh4e7S8A9MNQcA4A5x+Sq3lwO4JLVt21b9+/fX448/rnPnzrmrNMClkpKSlJGRIZvN5tjvMzIy1KlTJ+3du1fe3t7atWuXtmzZ4uZKgf/G399f8fHxmjRpkpKTkzVs2DBJ4nShWxDBGwCAO4TVapUkx5WeLxszZowsFou6dOnijrIAl7NYLDp27Jj8/PyUlpamEiVK6OLFi5IuBZUpU6Zo/vz5ev75591cKXDzfvzxR0nS888/r3379mnhwoVatGiRateurcDAQKWlpWnZsmVKTU3Vd9995+Zqwe3EAAC4Q5w4cUKtWrXSunXrVLBgQae++fPna8WKFZo7d648PfleHnnbs88+q8TERH3//ffasGGDKlWqpMDAQL333nt6/PHHVbFiRXeXCPwnFy9eVNGiRWW1WnX69GmFhoZKkr7//nv16dNHv/zyi5566in5+PjIbrfr4sWL+u2339xb9B2O4A0AAGQYhjIzM+Xj4+PuUoD/ZOnSpXruuef066+/qkyZMrrrrrvUs2dP1a1bV6NGjdK6detUtmxZPfLII2rWrJlatmzp7pKBm3Ly5Em9+OKL2rJli5YuXeq4XkGLFi1Uq1YtjR8/3s0V4koEbwAAANw2MjMztW/fPlWvXl27d+/Wo48+qiNHjsjLy0uSlJiYqNmzZ2vq1Knq3r27Ro8e7eaKgf/mo48+0rx58/TLL79IunRf72effVYnT5507PdwP4I3AAAAbluHDh1S+fLls7VnZGTIy8uLUytwWzh79qwKFCjgeL59+3bdd999bqwI/0TwBgAAwG3Bbrfrvffeu6FTJjw9PVWzZk098MADuVAZ4Hqpqalau3at8uXLd80vkDIyMpSRkaFWrVrlYnX4J4I3AAAAbhve3t6qU6eO/Pz8rjkuPj5eJ06c0Llz55iOizwpPj5eJUqUyHaxzH86e/asKlasqL/++iuXKkNOCN4AAAC4bQQEBOjQoUMqUaLENcft379fVapU0b59+7jKOfKkpKQk5c+fX6mpqQoICMhxjNVqVUBAgLKysnK5OvyTt7sLAAAAAFzlyqPXNptNH330kTw8POTh4aHLx5v69eunAgUKaPPmzYRu5Fne3t7y8PCQdGna+f/+9z/HTA+r1apnn33Wse/D/TjiDQAAgNtGYGCgDh48qBIlSshms8lisahz587y8vKSYRiaN2+ebDabvL05/oS87fLR7NTUVNntdoWGhqp3794yDEOzZ89WUlKSPDw8FBAQILvd7u5y73gEbwAAANw2fH19tWfPHlWqVEmGYcjLy8sxFTczM1O+vr5Mu8Vt4fIXS6mpqfL395efn58yMjIkSfny5VNKSopsNhvB+xbB/RMAAABwW8jMzFTRokWVlpYmSY5ptpen2jLtFrcrT09Pp337ylMrcGtgjg0AAABuC97e3oqLi3Mc0U5PT5dhGBo6dKh8fHwc7ZmZmUw1R553ZbC2Wq2y2+16+umnZRiGbDab0tLSuGL/LYTfOAAAALgtpKam6o033tDq1au1bds22e12jRw5Un5+fvL09FRWVpZGjBjBVHPcFux2u+Mot2EYmjp1quPq5k2aNLnmvb2R+zjHGwAAALeF3r176+eff9bLL7+sTp06yd/f390lAaZJSkpSgQIFtHfvXlkslhzH2Gw2Va5cWUePHlV4eHguV4grEbwBAABwWzh37pzy5csnb29vbd26VQ8//LACAwOvuUxsbGwuVQe41t9//62SJUve0PncHh4eXGDNzZhqDgAAgNtC/vz5Hf8uXbq05s6de9VzuW02m86dO5dbpQEuV6RIEZ05c0ZBQUHXPJc7PT1dZ8+ezcXKkBOOeAMAAAAAYCLOuAcAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGgH/h9ddf1zvvvOO21y9durTOnDlz1f4OHTropZdeysWKzFGnTh2tXbtW0tW3+XrvRW7auXOnGjRooKCgIN1zzz1avXr1NcenpaVpwIABKlKkiIoVK6ZXXnlFmZmZjv7SpUvL29tb+fPnV7NmzfT777/fUB2nTp3Syy+/rPLly8tisahkyZLq0qWL/vzzT8eYdevW6ZFHHrnqOv7++28VLlxY27dvv6HXdBdXbOu/4erPfteuXbVo0SKXre9qPvvsM/Xv39/U17DZbIqIiNDSpUtveJkb2f7rfa6sVqu8vb2dHl9//bWj/80331TRokUVHBys7t27KzU19d9tGAC4EMEbAG4jpUuXVlhYmLvL+E+OHj2q2NhYPfDAA+4u5YZcuHBBbdq0Ud++fXX27Fm999576ty5s44dO3bVZV5++WXZbDbt379f+/btU1JSksaOHes0Jj4+XgkJCerXr5+ioqJks9muWcfvv/+ue++9V1arVcuXL1dqaqq2bdume++9V02aNNFXX311Q9vj7++vihUrKl++fDc03h1cta1wDW9vb1WsWFEFChRw2Tpv5HO1b98+NWrUSJmZmY5Hx44dJUkzZszQkiVLtGXLFh0/flweHh567rnnXFYfAPxbBG8AuI288847Gjx4sLvL+E8WLVqkqKioa96T9FZy5swZvfvuu+rUqZN8fX314IMPqm7dutq2bdtVl1m3bp1eeeUV5c+fX6GhoXr55Zf17bffZhvn6+ur9u3bKywsTPv377/q+tLS0tShQweNHj1aH374oSpWrCgvLy8VL15cAwcO1OrVq3Xw4MEb2p4CBQpo06ZNqlix4g2Nz22u3Fa4hpeXl3766Sc1atTIZeu8kc/Vn3/+qcqVK+e4/JQpUzRr1iyVKVNGwcHBmjFjhjZt2qTDhw+7rEYA+DcI3gBwDa+//rry58+vSpUqad26dY72mTNnqmzZso4pjFar1Wm5KVOmqGzZsvLz81O1atU0b948R9/Ro0dVvXp17d27V40bN1ZAQIBq1aqlHTt2SJKWL1/uNHXS09NTd999t+x2uyTp/Pnz6tKli4KDg1WqVCnNnz/fse7+/fvrs88+y3FbmjZtqg0bNji1vfnmmzp//rxTW+vWrbVy5UpJ0unTp/Xss88qNDRUoaGheuaZZ3T06FGVLl3aMT4oKEgnTpxQ27ZtFRQUpCpVqmjVqlVO6zxx4oSeeuophYaGqmDBghowYIC2b9+u6tWrZ6tz4cKFevzxx3Pchmv56quvVL16dfn7+6tatWr66quv9NJLLznej9dff10TJ07UqFGjVKhQIRUvXlyzZ8+WYRgaM2aMihYtquLFi2d7/44cOaJ27dopKChIhQsX1gsvvKCtW7eqcePGkqRSpUrpySeflHQpFH799dfaunWr6tevf9VaH330Ub322ms6deqUzpw5o5EjR6po0aJXHZ+UlHTNLyK++uorlStX7qpH9GrUqKERI0Y4tW3cuFG1atVSQECAmjRpopiYGEdfUFCQ07+v9/M9ePCgHn30UQUFBSl//vzq1KmTTp486ejfvHmzKleurJCQEI0YMUJZWVmOvmt9VnJjWyVp9erVqlOnjvz9/VWuXDlNnTpVU6dO1euvvy5Jqlevnt5880298sorCg0NvWZ9V5o/f77uuece+fv7q3jx4urTp4/T6RFZWVkaO3asSpQoofz58+uVV15xem8yMjI0fPhwhYWFyd/fX7Vr19aKFSuyvc6BAwf02GOPKX/+/MqXL5+aNm3q9PvqSkOHDlXdunV19uxZx1T8DRs2qF69erJYLCpTpowmTpwowzCclvv55591//33y9/fXyVKlNCrr76q9PR0R3/16tV19OhRSZdm3hw6dOiqv6eKFSumuXPn6oknntDdd9+dY5038rnau3evKlWqlG3ZU6dO6cKFC7rvvvscbT4+Pmrbtq3WrFmT4+sBgOkMAECO/vrrL+Ouu+4yzp07Z6xbt86YM2eOMXr0aKNGjRrGU089ZZw6dcqIj4832rZtawwdOtSx3LBhw4x27doZBw8eNGw2m7FlyxajVq1axtSpUw3DMIyYmBijWLFiRq1atYwtW7YYFy9eNGbNmmWULFnSSE9Pd6ohMzPTuOeee4wNGzYYhmEYpUqVMmrXrm189tlnhtVqNTZs2GAUKVLE+OOPPwzDMIx+/foZc+bMyXF7vvzyS6Nr166O5+np6UaRIkWMDz74wNEWGxtrlC1b1rDb7UZKSopRpUoVY+DAgUZcXJxx7tw546OPPjLuvfdeo1SpUo5l/Pz8jHr16hnLly83rFarsXTpUiN//vzG6dOnDcMwjFOnThllypQxRowYYZw8edI4c+aMMWHCBKN69epGtWrVnGo8duyYUaRIESMzM9PRVqpUKce6rnRl+yeffGKUKVPG+PHHH42LFy8au3fvNpo0aWJUrlzZ8X6MHj3aKFWqlDFs2DAjNTXV2LFjh1G4cGGjT58+xmuvvWakpqYau3fvNooXL24cPnzYMAzDOH78uBEWFmaMHTvWOHXqlJGQkGCMGTPGqFatmvHggw9mqyk0NNSQZLz22ms5/gwus1qtxt13321IMiQZYWFhjp/hldt2+vRp44033jDuu+++a66vc+fOV/25/9PatWuN8uXLG/Xq1TP+/PNPIzk52RgzZoxRp04dx5jAwEDHv6/3842LizPKlCljLFiwwLhw4YJx5swZ4+233zYqVqxoJCUlGYZhGHXr1jXWrVtnxMfHG6NHjzbS0tIMw7j+ZyU3tnXlypVG0aJFjYULFxopKSnGoUOHjA4dOhhVqlQxRo8e7Rg3evRoY9KkSTf0uoZhOPbxNWvWGBcvXjTi4+ONN954w6hWrZqRkZFhdOnSxahRo4YxZMgQIykpyYiJiTHq1q1rTJ8+3bGOp556yujVq5dx/Phxw2q1GqtWrTIqVKhgLFu2zDFm//79RokSJYwpU6YY8fHxhtVqNaKjo40yZcoY69evN+bMmWP069fPsNvtRu/evY2mTZsaKSkpjvenTJkyxn333Wds2LDBuHjxorFjxw7j/vvvN/r16+d4jdWrVxtFixY1vvrqKyMlJcXYt2+f8cgjjxiRkZGOMdWqVTNiYmIMw7i0/9apU8eYO3eu4/dUoUKFnPbxLl26GAsXLryh9/Jqn6vIyEgjLCzMCA0NNerXr29s27bNMAzD2LZtW46fzw8++MB49dVXb+g1AcDVCN4AcBUHDhwwatWq5RSGR48ebVStWtXIyspytO3bt8+oWrWqYRiGceLECaNMmTKGzWZzWtepU6eM4sWLG5mZmUZMTIwhydiyZYvTmNq1axtbt251aps6darRuXNnx/NSpUoZb7/9ttOYV1991Zg4caJhGNcO3lar1YiIiHD80b1gwQKjcePGRo0aNRxjXn/9deOtt94yDMMwJk6caDz55JPZ1vP+++87BW9JxoIFC5zGPP7448bXX39tGIZhDBo0yHjhhReyrWfo0KHZgvfkyZONXr16ObVdL3hbrVajSJEixp49e5z6U1JSjPDwcKfgXbduXacxvXr1MurVq+fU1rdvX2Pu3LmOf+f0h/rgwYNz/MM+NTXV+PHHH40KFSoYX3zxRbb+yx5//HHjmWeeMU6ePGkkJCQYI0aMMFatWuW0bT4+Po5gPnr0aKcvI/6pRYsWxo8//njV/iutXbvW8PHxMWJjYx1tWVlZRokSJYxTp04ZhuEcvK/38+3bt69TWLxs8ODBxrvvvmsYhmHcf//9xo4dO5z6b+SzkhvbWrVqVWPlypVOy2VmZhq1atW66eCdkJBgFC9e3Dh58mS2vsttXbp0MVq1auXUt3LlSqN169aGYRjG1q1bs+2vhmEYv//+u1GzZk3H83bt2hkff/xxtnGnTp0yMjMzjTlz5hi9e/c2OnXqZLRt29awWq2OMWvXrjUCAwOd3h/DMIykpCSjZMmSxt69ew3DMIwaNWoY0dHRTmPS09ONmjVrGj/88INhGNmD9z9/T7388suO31OXt/9Gg/fVPlfLli0zjh8/bqSlpRmLFi0yihcvbpw6dcpYv3698fDDD2dbz6xZs4yBAwfe0GsCgKsx1RwArqJChQpq2bKl6tatq19++cXR3q5dO3l4eDiely1bVvHx8ZKkX375RceOHVNwcLD8/f0dj/DwcJ0+fdoxxbVEiRKqW7eu0+uVL1/esR7p0jmOkyZN0qRJk5zGtW/f3un5la9/LX5+foqKinJceOrjjz/W+PHjVaxYMW3atElZWVmaN2+eunfvLunS1NLOnTtnW88TTzzh9NzDw0NRUVFX3ZbVq1c71nmlnKaT38w08z179igiIiLbtPWgoCC1adPGqe3y9PDLChcunO281IIFCyoxMVHSjb8HlwUGBqpFixb67LPPrnoF7F27dmn37t2aPXu2ihUrpiJFiuiNN97QiBEjlJCQ4Bj3999/KzMzU3v27NHmzZvVp0+fnN8ASYUKFdKpU6eu2v9PtWvXVnh4uOO5h4eHSpcuneN+dL2f788//6xBgwY57e/+/v6aNm2adu7cKUmaPHmyOnTooMmTJzuu3n6jnxUzt/XMmTM6deqUWrZs6bSMl5eXOnTocMOv8U8bN25Uw4YNVaxYsWx9V7Zd67P8888/67fffsv2vtapU0d79+51TPNeu3atnn766WyvU7hwYcfpCXPmzNHFixe1ePFi+fn5OY27//77nd4fSQoODlabNm20fv16JSYm6sSJE9k+Sz4+PnryySevOqX9n9v2z99v/8bVPlePPvqoYxr+Y489pieffFILFiyQxWLJdvqPJCUmJiogIOCmagCA/4rgDQDX8NZbb2n69Ol6/vnnNXfuXElSSEiI0xgfHx+nK04//vjjslqt2R4ZGRkqX758juuQLl1I68r1vPrqq3rhhRey/fF+vdeXLl106MrzxF955RVJUs+ePTVnzhwdOHBA58+fV7169dS7d299/PHHWrVqlWrWrKnixYtLuhRQjH+c55kTf39/+fr6XnVb7Ha7LBZLtuW8vb2dnsfFxenw4cPZwvH13GidkpQ/f/5sNfzzSsyenp6OcHgj6963b5/Onj3r1HbXXXfp5MmTunDhgtPP4YknntD+/ftVv359p+339PRUlSpVtHHjRqf1eHl5qXr16vrmm280b948paam6oknnnBa54ULF9SkSRN98803N/QeSDnvfzntR9L1f77SpauM/3N/t9lsjs9MvXr1tG3bNh04cECtW7d2vKfX+6yYva1XfoHmSna73en2cFdzvc/ySy+9dNX35/LPJDMz03H9h6spV66cdu3a5TgH+0rX27+zsrKyfVYv8/Lycjon/Ur/3LZ/7jNX+ud1LaZPn37Nz9XVlC1bVsePH1dERESOX9zExMSobNmyV10eAMxE8AaA66hXr56++uorx5EWT8+r/+qsX7++Nm7cqJSUFKf2EydOaOjQoY7n11qHJG3btk2//vqrXnjhhWx911tWkqpVq+Z0i50JEyZIunQBpKysLL344ovq1auXJCkyMlIbN27UO++842iTLh0d/uKLL7Kt+5+3arpePQ0bNswxKP3znr+LFi1Su3btrvpH/tXUqFFDx48f1x9//OHUnpqaquXLlzu15XSBsmu93o28B4sXL9bkyZOd+rdt26aqVasqMDDQ6efw1VdfqWzZstq3b5/TeMMwtGvXrhyPkEqXApnFYpGHh4e++uorp3UGBgaqc+fO+u233656X+SDBw9q+vTpjuc3sg/d6NiGDRvqu+++y9Y+ceJEp/uPFyhQQB9//LGSk5O1c+fOG/qsmL2tBQsWVLFixRwXE7zMbrf/p3ts33///fr5558VFxeXre/K4Hit2ho2bKjly5dnC9U7d+50mgXTqFGjHC+oeOrUKceyTZs21TvvvKPmzZtn2/c2b96s2NhYp7akpCR9//33euCBB1S4cGEVLFgw24UZ7Xa7Fi5cqAcffDDH+v/NPta6dWunn3Pfvn2v+bmSpH79+mnr1q1O/Rs3blTFihVVpEgR+fr6Ot0JIDMzU0uXLlWzZs1uuC4AcCWCNwBcxbp16zRt2jRdvHhRy5cvV6lSpa67TFhYmDp16qSoqCjHdNBNmzapZcuWN3x7JsMw1L9/f73//vv/OoTeiB49emjdunXq1KmTpEvB8+mnn9ahQ4f00EMPOcb16dNHf/zxhwYNGqQTJ07o/Pnz+uijj/Tll1/+q9cbPny4PvzwQ02dOlVnz55VYmKiPvjgA/3vf/9z2r6FCxfe1PReX19fvf3222rbtq1WrVqltLQ07dmzR5GRkf/5XtSvvfaa5s+fr3HjxunMmTM6ffq03nrrLa1du9YxpmvXrvr888+1fPly2Ww2/fbbb+rdu7dGjhyZ4zpr1aolHx8fjRgxQmfPntWZM2c0ePBgeXt7Zzv9QLoU1J599lk1adJEgYGBOa7TYrHom2++Uf/+/fXqq6/q0KFDysrK0qlTp/TRRx+pQYMGNzwr4N8aPny4pk6dqk8++UTJyck6c+aMRo8erTlz5qh8+fK6ePGiBg8erL///lt//fWXjh07phIlStz0Z8XV2zplyhR169ZNCxcu1IULF3T48GE9+eSTTlfsli4FyYyMjBtaZ1hYmJ5//nk99NBDWrNmjdLS0hQfH6+RI0eqVatWN3Q0vF69eqpSpYo6d+6so0ePymazaeXKlYqKilLNmjUd495++229+eabeuedd5SQkCCbzaZly5apbt262rJli2Nc+/btNW3aNLVs2dLpS6pixYrp8ccf18aNG2W1WrVz5061adNGjz76qKpUqeJ4jzp37qzo6GhdvHhRhw4d0pNPPqnChQurVatWN/Se/NP13s/rfa6qVq2qfv366dChQ0pJSdGkSZO0ZcsWPfXUU5KkwYMHq2fPnjp+/LhSUlI0YMAANW/eXGXKlLmpegHgvyJ4A8BV1KxZUz/88IMKFSqkhQsX6r333ruh5d5++221atVKjzzyiIKDg9WnTx+99tpr6tmz5w0t/+mnn2rr1q166KGHHFMv/f39/8OWOHvyySf1/PPPO4XSXr16qXfv3k5HqQIDA7Vu3TqdO3dO1atXV+nSpbV9+3YtXrz4X71eRESEVq1apejoaJUsWVKVK1fWvn37NG3aNMd01BMnTujgwYNq2rRpjusoVqyY473I6ahw165dNWHCBA0ZMsRxO6tBgwbddCi4rHjx4lq/fr22bdumMmXKqGrVqkpOTtYnn3ziGBMWFqZFixZpzJgxjtd+44031KRJkxzX6eHhoYULF2r//v0qVaqUqlWrpjNnzig6Otrpi4hixYrJy8tL9957r0JDQzV79uxr1nrffffpt99+U0pKipo1ayaLxaIaNWpo1apVWrJkifr16/ef3ourCQ8P1w8//KAlS5aoRIkSqlixog4fPqx169YpMDBQAQEBKlmypO666y41bdrUcV0B6eY/K67c1ubNm+vLL7/U5MmTVbBgQbVs2VIPP/xwttuV1a9fX+PGjdPAgQNvaL1vvfWWBg0apP79+ys0NFS1atXS+fPntW7duhv+Qm3evHkqXbq0GjRooNDQUI0aNUozZ850Oif9rrvu0po1a7RmzRqVK1dOhQsX1tSpU/XFF1+oQYMGTutr06aNZs2apTZt2mjXrl2SpMqVK2v69OkaPny48ufPr8jISLVu3VpTp051LNeyZUvNnj1bb731lvLnz69GjRopIiJC33zzzU1P12/UqJF69Ohx1WshXO9z1bdvX0VGRqpx48YqWrSofvzxR61YscJxDnefPn3UokUL3XvvvQoLC1N6erpmzJhxU7UCgCt4GGZ9BQ4AgKTo6GiFh4frrrvucmr/+OOP9eeff+qDDz7Q+++/rz179jgFWgDmWrdund555x1FR0e7uxQAuO1xxBsAYKp8+fKpXbt2Wr16tQzDUFZWlpYtW6Zx48Y5jkwWK1Ysx/PZgVtRjx49nC4GduVj2bJl7i4PAHAL4og3AMB069at0xtvvKG9e/cqIyNDdevW1ZQpU1S5cmV3lwbcsTjiDQC5h+ANAAAAAICJmGoOAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJjo/wBUfmNShWlrZQAAAABJRU5ErkJggg==","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-525 **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-525\n","不是      1193\n","是       1043\n","不重要      433\n","问法错误     286\n","回答正确      44\n","問法錯誤       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","是           1318\n","不是          1295\n","不重要          180\n","问法错误         169\n","回答正确          37\n","他要带走的是物品       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","不是      1848\n","是        993\n","不重要       72\n","问法错误      45\n","回答正确      42\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA94AAAI2CAYAAACmDVBwAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAAA9hAAAPYQGoP6dpAABiXklEQVR4nO3dd3gUVf/+8TuFJJuEJBCQUEIJvYoYCFUFRPiCShHbA4oUKYICIiASiqCCCGLBAiggiA30UUREeCjSFZQmGGogoQUSQgrJbrLJ/P7gyv5YE4qwk6W8X9c1l+w5Z2Y/k0xi7p0zMx6GYRgCAAAAAACm8HR3AQAAAAAA3MoI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIm83V2Aq+Tm5urEiRMqWrSoPDw83F0OAAAAAOAWZxiG0tLSVKZMGXl6Xvq89i0TvE+cOKHw8HB3lwEAAAAAuM3Ex8erXLlyl+y/ZYJ30aJFJV3Y4aCgIDdXAwAAAAC41aWmpio8PNyRRy/llgneedPLg4KCCN4AAAAAgEJzpcudubkaAAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjccWrZsKU9PT02dOtWpfe3atYqMjFRgYKCaNGmibdu2XXIbsbGxmjVrluN1Zmamnn/+ed1xxx0KCwvTyJEjZbfbTdsHAAAAALjRELzhsGbNGo0dO9apLS4uTj169ND06dOVnJysadOm6emnn1ZSUlK+9XNzc/XUU08pNTXV0TZ8+HDZbDbt27dPMTExSklJ0euvv276vgAAAADAjYLgjcv6/fffdc8996hFixYqUqSImjZtqrvvvlvr16/PN/bNN9/Uli1bnNrWrl2rkSNHqlixYgoJCdHw4cP13//+t7DKBwAAAAC3I3jjspo1a6b169fr559/VlZWllasWKElS5aoVKlSTuN27NihGTNmqE+fPk7tDz30kF555RWdPn1aiYmJGjNmTL51AQAAAOBW5u3uAnBjK126tKZMmaL27ds72gYPHqwmTZo4XlutVnXv3l0zZszQzp07ndYfP368Gjdu7AjbZcuW1S+//FI4xQMAAADADYAz3risP/74Qy+99JJ++uknZWRkaMWKFfL29pbNZnOMGTVqlBo1aqTOnTvnW/+pp55S3bp1dfLkSSUkJKhnz546efJkYe4CAAAAALgVZ7xxWRMnTtQbb7zhOOPdpk0bJScna/To0Zo6dapWr16tH3/8Udu3b8+37o4dO7Rr1y799ddf8va+cKi9+uqratq0qerWrcuUcwAAAAC3Bc5447L27dunFi1aOLVFRUXpl19+UWpqqvr06aO4uDiVLFlSfn5+eu211zRq1Cg99thj2rdvn5o0aeII3ZLk6empmjVrasOGDYW9KwAAAADgFgRvXFZERIRiYmKc2v7880+FhYUpKChIhw8fVlZWlqxWq6xWq6KjozVp0iR98803Ba5rGIZ27NihsLCwwtwNAAAAAHAbgjcua+jQoXr++ee1ZcsW2Ww2rVu3ToMHD9bAgQOvuG5kZKSKFCmi6OhonT17VomJiRo6dKi8vb0VFRVVCNUDAAAAgPsRvHFZ999/v6Kjo/XUU08pJCREzz//vKZMmaJOnTpdcV0PDw8tWrRI+/btU4UKFVS7dm0lJiZq6dKlTtPPAQAAAOBW5mEYhuHuIlwhNTVVwcHBSklJUVBQkLvL+VcqvvyTu0u47RyZ3MHdJQAAAAC4yV1tDuWMNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACa6puDdsmVLeXp6aurUqY62+fPny9vb22nx9PRUx44dHWMOHDggT09PpzG//fabJCk7O1svvPCCihUrptDQUA0fPlx2u/06dw8AAAAAAPe6puC9Zs0ajR071qnt6aeflt1udyxZWVmqWbOmoqOjHWP27NmjHj16OI2LioqSJI0ZM0b79+9XTEyMYmJitHfvXo0ZM+Y6dg0AAAAAAPfzNmvD3377rcqXL6+GDRs62vbs2aMaNWrkG5uVlaXZs2drz549KlWqlKQLZ9Br1Kih6OhoBQQEmFUmAAAAAACmMuUab8Mw9Prrr+c7Y713715Vr1493/gdO3aoZs2aCgsLc7SFhoYqKipKmzZtMqNEAAAAAAAKhSnB+8cff1RoaKiaNm3q1L5nzx4NHjxYxYoV0wMPPKCDBw9KkuLi4lSlSpV826levboOHz5sRokAAAAAABQKU6aav/baa5oyZUq+9ujoaN17773y9/fXggUL1K5dO+3Zs0eZmZny9/fPN95isSgzM7PA97DZbLLZbI7XqamprtsBAAAAAABcxOVnvH/55Rf5+vrqvvvuy9fXtWtXlSxZUgEBAerfv7/q1aunFStWyGKxyGq15huflJRUYCCXpEmTJik4ONixhIeHu3pXAAAAAAC4bi4P3gVd230pEREROnbsmMqXL6/Y2Nh8/bGxsYqIiChw3VGjRiklJcWxxMfHX1fdAAAAAACYwaXB+9dff5XNZtMDDzyQr69Lly75wvHGjRtVrVo11a9fX3v37lVycrKj7+zZs/rtt9/yXSeex9fXV0FBQU4LAAAAAAA3GpcG74kTJzo9t/tilStXVr9+/XTixAklJSVp6NChysnJUcuWLeXj46OePXvq2WefVVJSkhITE9WrVy8NGjToklPNAQAAAAC4GbgseKelpSk0NFQPPfRQgf2vv/664+x2xYoVFRcXp++//16enhdKmDBhgkqXLq3KlSurWrVqqlq1qsaPH++q8gAAAAAAcAsPwzAMdxfhCqmpqQoODlZKSspNN+284ss/ubuE286RyR3cXQIAAACAm9zV5lBTnuMNAAAAAAAuIHgDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgomsK3i1btpSnp6emTp2ar69s2bLy9vZ2LFOmTHH0zZo1S+XLl1dAQIA6d+6shIQER192drZeeOEFFStWTKGhoRo+fLjsdvu1lAcAAAAAwA3jmoL3mjVrNHbs2Hzt586dk6+vr+x2u2MZMWKEJGn58uV64403tHTpUiUmJqpOnTrq3LmzY90xY8Zo//79iomJUUxMjPbu3asxY8Zc424BAAAAAHBjcOlU8z179qh69eoF9k2fPl3Tpk1TvXr1ZLFYNHHiROXm5mr16tXKysrS7NmzNW/ePJUqVUolS5bU/Pnz9cknn+j8+fOuLBEAAAAAgELl0uC9d+/eAoO3YRj67bff1KFDB6f2rl27atWqVdqxY4dq1qypsLAwR19oaKiioqK0adMmV5YIAAAAAEChcvkZ76+++krFixdX/fr19csvv0iSkpKSFBISIj8/P6fx1atX1+HDhxUXF6cqVark215ef0FsNptSU1OdFgAAAAAAbjQuDd4dOnTQpk2bdOrUKU2bNk29evXS3r17lZmZKX9//3zjLRaLMjMzr9hfkEmTJik4ONixhIeHu3JXAAAAAABwCZcG7zZt2igiIkI+Pj5q3bq1Ro4cqU8//VQWi0VWqzXf+KSkJPn7+1+xvyCjRo1SSkqKY4mPj3flrgAAAAAA4BKmPsc7IiJCx44dU2hoqM6dO6fs7Gyn/tjYWEVERKh8+fKKjY3Nt35ef0F8fX0VFBTktAAAAAAAcKNxWfCeOHGilixZ4tS2YcMGVatWTR4eHoqMjNTq1aud+hcvXqz7779f9evX1969e5WcnOzoO3v2rH777Tc1bdrUVSUCAAAAAFDoXBa8GzRooCFDhmjHjh3KyMjQvHnz9Omnn2rAgAGSpBdffFFDhgxRTEyMrFarJk6cKIvFovvuu08+Pj7q2bOnnn32WSUlJSkxMVG9evXSoEGDLjnVHAAAAACAm4G3qzbUoUMHnThxQo888oiOHz+uu+66Sz/88IPKlCkjSWrXrp2OHj2qNm3aKCkpSW3bttW3337rWH/ChAkaNmyYKleuLE9PT/Xu3Vvjx493VXkAAAAAALiFh2EYhruLcIXU1FQFBwcrJSXlprveu+LLP7m7hNvOkckdrjwIAAAAAC7janOoqTdXAwAAAADgdkfwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAEx0TcG7ZcuW8vT01NSpU53aN2zYoKioKAUFBalx48basmWLU//KlSvl6ekpb29vx5KQkCBJSk1NVbdu3RQYGKgyZcrozTffvMZdAgAAAADgxnFNwXvNmjUaO3asU9uBAwf02GOP6fXXX1dCQoJGjBihTp066dixY44xe/bs0bhx42S32x1LqVKlJEl9+/ZVkSJFdPz4cW3evFmLFy/WzJkzr2PXAAAAAABwP5dNNZ8xY4ZefPFF3X///bJYLOrSpYt69Oihb775xjFmz549qlGjRr51jx8/rjVr1ujjjz9WcHCwKlSooPnz52vSpEmuKg8AAAAAALdwWfCuVKmSOnbs6NQWHh7umEouSXv37lX16tXzrbtx40a1adNGfn5+jraaNWsqMDBQBw4ccFWJAAAAAAAUOpcF7yFDhqhq1apObUuXLlVkZKTj9Z49e9SlSxeFhoaqa9euOn36tCQpLi5OVapUybfN6tWr6/Dhw64qEQAAAACAQmfaXc3nzZunU6dOqXPnzpIkq9WquXPn6s8//9Thw4dVq1YtdenSRZKUmZkpf3//fNuwWCzKzMwscPs2m02pqalOCwAAAAAANxpTgvfWrVs1cuRIffnll/L29pYk+fn5qXPnzgoJCVFwcLAmTJigjIwM7d69WxaLRVarNd92kpKSCgzkkjRp0iQFBwc7lvDwcDN2BQAAAACA6+Ly4B0XF6fOnTvr008/Vc2aNS87NiIiQseOHVP58uUVGxubrz82NlYREREFrjtq1CilpKQ4lvj4eJfUDwAAAACAK7k0eKelpenBBx/U8OHD9eCDDzras7Ky1KZNG6dp4zabTVu3blW1atXUrFkzrVq1Sna73dH/119/yWazFXjttyT5+voqKCjIaQEAAAAA4EbjsuCdk5Ojxx57TPfcc48GDx7s1Ofj46OQkBANHDhQycnJOnHihHr06KGGDRuqcuXKKlu2rJo2baqhQ4cqPT1d8fHxevbZZxUdHe2q8gAAAAAAcAuXBe/nn39ey5cv18cffyxvb2/H0rp1a0nS7NmzlZOTo8qVK6t27dry9/fXnDlzHOvPnDlTZ8+eVVhYmBo1aqQuXbqod+/erioPAAAAAAC38DAMw3B3Ea6Qmpqq4OBgpaSk3HTTziu+/JO7S7jtHJncwd0lAAAAALjJXW0ONe1xYgAAAAAAgOANAAAAAICpCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0AAAAAgIkI3gAAAAAAmIjgDQAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AblsHDx5U+/btFRwcrOrVq2vhwoWOvi+++EK1atVSUFCQHnjgAR06dMjRZ7Va1a9fP4WGhqp06dIaPXq0cnNz3bELAAAAuAkQvAHcls6fP6927dqpS5cuOnXqlL766iu9+uqrWrVqlX7++WdNmDBBCxcu1KlTp9S1a1d16NBBVqtVkjRs2DAlJyfrwIED2r59u7Zt26Zp06a5eY8AAABwoyJ4A7gtbdiwQXXq1FGfPn1ksVh011136c0339S8efM0f/58TZ48WXfddZf8/f3Vt29fVa9eXRs3bpQk1a1bV7NmzVLx4sUVFhamAQMG6Ndff3XzHgEAAOBGRfAGcFvKyckpsD05OfmyfZLUv39/hYSEKDc3V3/99ZfeeusttW3b1rRaAQAAcHO7puDdsmVLeXp6aurUqU7tGzduVP369WWxWNSwYUP9/vvvTv2zZs1S+fLlFRAQoM6dOyshIcHRl52drRdeeEHFihVTaGiohg8fLrvdfi3lAcAVNW/eXFu3btXcuXOVmZmp7du3a+TIkbrnnnvUtWtXjRo1Sjt37lRmZqZmzZqln3/+WU2bNnXaxrBhw1S3bl0lJyerR48ebtoTAAAA3OiuKXivWbNGY8eOdWpLSEhQ586dNXbsWKWmpmr06NHq2LGjTp06JUlavny53njjDS1dulSJiYmqU6eOOnfu7Fh/zJgx2r9/v2JiYhQTE6O9e/dqzJgx17FrAHBpQUFB+vHHHzV79myVKVNGrVu31rlz59S3b1899thj6tu3rzp27KjKlStrwIAB6tGjh8qUKeO0jalTp2r//v2KjIzUI4884qY9AQAAwI3OZVPN58yZo8cff1xdunRRkSJF1KlTJ/Xo0UMffvihJGn69OmaNm2a6tWrJ4vFookTJyo3N1erV69WVlaWZs+erXnz5qlUqVIqWbKk5s+fr08++UTnz593VYkA4KRBgwbatGmTjh49Kj8/P02fPl0hISGSpKFDh+rIkSN65513VLJkSb355pv51vfy8lLVqlU1b948HTt2TDt37izkPQAAAMDNwGXBe/369erYsaNTW9euXbVq1SoZhqHffvtNHTp0KLB/x44dqlmzpsLCwhx9oaGhioqK0qZNm1xVIgAUaPTo0WrQoIG6devm1J6WlqahQ4dqxowZKl68uKQL13nHxMQ4jfP09FSdOnV08uTJQqsZAAAANw9vV20oLi5OVapUcWqrXr26Dh8+rKSkJIWEhMjPzy9f/xdffFHguhevXxCbzSabzeZ4nZqa6oK9AHC7+eOPP7Rw4ULt2rUrX190dLQaN26srl27OtrOnz+vtm3b6vDhw/Ly8pIk2e12xweIAAAAwD+57Ix3Zmam/P39ndosFosyMzML7Ps3/QWZNGmSgoODHUt4eLhrdgTAbSM3N1f9+/fX5MmTVa5cOae+7du368svv9QHH3zg1F6uXDlFRUVpyJAhSk5O1pkzZzRgwAA1a9ZMFSpUKMzyAQAAcJNwWfC2WCyyWq1ObUlJSfL39y+w79/0F2TUqFFKSUlxLPHx8a7ZEQC3jczMTHXs2FF9+/bN15eVlaWZM2c6XQKTZ/bs2crIyFDVqlVVvXp1eXt766OPPiqMkgEAAHATctlU8/Llyys2Nlbly5d3tMXGxioiIkKhoaE6d+6csrOzVaRIkXz9eev+U2xs7CXvFOzr6ytfX19XlQ/AZBVf/sndJVzCXfrkkrX5aOhvl+gr2UWBfbpIkn6W9POrq02p7nocmdzhyoMAAABgOped8W7evLmWL1/u1LZ48WLdf//98vDwUGRkpFavXl1gf/369bV3714lJyc7+s6ePavffvst33NzAQAAAAC4mbgsePfu3VufffaZfv75Z9ntdi1dulRfffWVnnvuOUnSiy++qCFDhigmJkZWq1UTJ06UxWLRfffdJx8fH/Xs2VPPPvuskpKSlJiYqF69emnQoEGXnGoOAAAAAMDNwGXBu1SpUlq0aJFGjRqlwMBAjR8/Xt9//73uuOMOSVK7du00ZMgQtWnTRsWLF9eff/6pb7/91rH+hAkTVLp0aVWuXFnVqlVT1apVNX78eFeVBwAAAACAW3gYhmG4uwhXSE1NVXBwsFJSUhQUFOTucv6VG/fa11sX174WPo7zwsdxDgAAYK6rzaEuO+MNAAAAAADyI3gDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJiJ4AwAAAABgIoI3AAAAAAAmIngDAAAAAGAigjcAAAAAACYieAMAAAAAYCKCNwAAAAAAJnJp8Pb29s63WCwWnTx50jGmWbNmTv0DBw509H3//feqVq2aLBaLWrVqpQMHDriyPAAAAAAACp23Kzdmt9udXk+ePFnHjh1T6dKlHW0HDhyQ1WqVt7fzW+/evVv9+vXTN998oyZNmmjOnDlq166d9uzZIz8/P1eWCQAAAABAoTFtqnlGRoZmzJihkSNHOtqOHz+u0NDQfKFbkmbMmKERI0bo3nvvlY+Pj/r376+GDRvqiy++MKtEAAAAAABMZ1rwnjlzptq3b6/w8HBH2969e1W9evUCx69fv14dO3Z0auvatatWrVplVokAAAAAAJjOlOBts9n0zjvvaNSoUU7te/bs0YYNG1SiRAnVqFFDCxYscPQdP35cERERTuOrV6+uw4cPm1EiAAAAAACFwqXXeOf59NNP1bJlS1WqVMmpPTIyUuvWrVOVKlW0a9cuPfnkkwoLC1ObNm2Um5srT0/nzwEsFosyMzMLfA+bzSabzeZ4nZqa6vodAQAAAADgOrn8jHd2dramTp2qV155JV9f8+bNVatWLfn4+CgyMlLTpk3Txx9/fKEQT08ZhuE0PikpSf7+/gW+z6RJkxQcHOxYLp7SDgAAAADAjcLlwXv+/Plq3LixqlWrdsWxEREROnbsmCSpbNmyiouLc+qPjY3NN/08z6hRo5SSkuJY4uPjr794AAAAAABczKXBOycnR2+++aZGjx6dr++TTz7RzJkzndo2bNjgCOjNmzfX8uXLnfoXL16s+++/v8D38vX1VVBQkNMCAAAAAMCNxqXXeH/55ZeqW7euateuna8vMjJSbdu2VY0aNRQVFaUVK1ZozJgxWrlypSTp+eefV/v27VW/fn01aNBACxYs0K5du7Rw4UJXlggAAAAAQKFyafDeu3evoqOjC+yrX7++Zs2apeeee06HDh1StWrVNGfOHNWvX1+SVLduXb3//vt66qmnFB8fryZNmmjZsmXy9fV1ZYkAAAAAABQqD+OfdzS7SaWmpio4OFgpKSk33bTzii//5O4SbjtHJndwdwm3HY7zwsdxDgAAYK6rzaGmPMcbAAAAAABcQPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvAAAAAABMRPAGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARC4P3qNHj5aXl5e8vb3l7e2tOnXqSJL+/vtvNW/eXBaLRbVr19ayZcuc1vv+++9VrVo1WSwWtWrVSgcOHHB1aQAAAAAAFDqXB+89e/Zo9erVstvtstvt+uuvv2Sz2dS+fXs9+eSTSklJ0ccff6w+ffpo9+7dkqTdu3erX79+mj17tlJSUvTYY4+pXbt2slqtri4PAAAAAIBCZUrwrlGjhlPbd999pzp16mjgwIHy8fFRixYtNHbsWL311luSpBkzZmjEiBG699575ePjo/79+6thw4b64osvXF0eAAAAAACFyqXB22q1Kjk5WaVKlXJqX79+vTp27OjU1rVrV61ateqq+gEAAAAAuFm5NHjHxMTo/PnzCg8PV7ly5TRy5EhlZ2crLi5OVapUcRpbokQJWa1W2Ww2HT9+XBEREU791atX1+HDhy/5XjabTampqU4LAAAAAAA3GpcG74CAAP3vf//T/v37tXnzZu3Zs0fjx49XZmam/P398423WCzKzMxUbm6uPD09C+y7lEmTJik4ONixhIeHu3JXAAAAAABwCZcG76pVq6pZs2ayWCwKDw/XggULNHv2bFkslgJvlHb27Fn5+/vL09NThmE49SUlJRUY1vOMGjVKKSkpjiU+Pt6VuwIAAAAAgEuY+hzvYsWKyTAMlSxZUrGxsU59p06dUvHixeXj46OyZcsqLi7OqT82Njbf9POL+fr6KigoyGkBAAAAAOBG47Lg/ccff6h///5ObTExMfLz81ObNm20fPlyp77Fixfr/vvvlyQ1b978sv0AAAAAANysXBa8a9WqpeXLl+vDDz+U1WrVzp079fjjj2vkyJHq0qWLfv/9d82fP1/Z2dnavHmzpkyZouHDh0uSnn/+eb322mv67bfflJ2drTlz5mjXrl168sknXVUeAAAAAABu4bLgbbFY9NNPP2nRokUKDQ3Vgw8+qCeffFIDBw6Un5+ffvzxR82aNUtFixZV7969NWvWLNWuXVuSVLduXb3//vt66qmnFBQUpM8//1zLli2Tr6+vq8oDAAAAAMAtvF25sdq1a2vNmjUF9tWqVUsbNmy45LqdOnVSp06dXFkOAAAAAABuZ+rN1QAAAAAAuN0RvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATuTR4Jycnq0ePHipZsqQqVqyoyZMnKzc319FftmxZeXt7O5YpU6Y4+mbNmqXy5csrICBAnTt3VkJCgitLAwAAAADALVwavLt27aqyZcvq0KFDWrlypb7//nvNmDFDknTu3Dn5+vrKbrc7lhEjRkiSli9frjfeeENLly5VYmKi6tSpo86dO7uyNAAAAAAA3MJlwXv79u06ffq0Xn/9dQUFBalq1aqaO3euPvnkE0nSnj17VL169QLXnT59uqZNm6Z69erJYrFo4sSJys3N1erVq11VHgAAAAAAbuGy4J2Tk6MXX3xRHh4ejrbw8HDHlPG9e/cWGLwNw9Bvv/2mDh06OLV37dpVq1atclV5AAAAAAC4hcuCd2RkpHr27OnUtnTpUkVGRkq6cMb7q6++UvHixVW/fn398ssvkqSkpCSFhITIz8/Pad3q1avr8OHDrioPAAAAAAC38DZrw6dOndKwYcP03XffSZI6dOigF154QeXKldP69ev19NNPa+XKlSpatKj8/f3zrW+xWJSZmXnJ7dtsNtlsNsfr1NRU1+8EAAAAAADXyZTHidlsNj3yyCN67rnnFBUVJUlq06aNIiIi5OPjo9atW2vkyJH69NNPZbFYZLVa820jKSmpwECeZ9KkSQoODnYs4eHhZuwKAAAAAADXxZTg3bt3b4WHh+uVV1655JiIiAgdO3ZMoaGhOnfunLKzs536Y2NjFRERccn1R40apZSUFMcSHx/vsvoBAAAAAHAVlwfv8ePH6/Dhw5o3b57jRmsTJ07UkiVLnMZt2LBB1apVk4eHhyIjI/PdwXzx4sW6//77L/k+vr6+CgoKcloAAAAAALjRuPQa74ULF2rBggXavHmz083SGjRooOeff17ly5dXtWrV9M033+jTTz/Vzp07JUkvvviihgwZov/+97+qWLGi3nrrLVksFt13332uLA8AAAAAgELnsuC9fv169erVS9nZ2SpTpoxT36FDhzRq1Cg98sgjOn78uO666y798MMPjnHt2rXT0aNH1aZNGyUlJalt27b69ttvXVUaAAAAAABu42EYhuHuIlwhNTVVwcHBSklJuemmnVd8+Sd3l3DbOTK5w5UHwaU4zgsfxzkAAIC5rjaHmnJzNQAAAAAAcAHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMBHBGwCA24S3t3e+xWKx6OTJk5KkvXv3qlWrVgoKClK9evX0008/ubliAABuDd7uLgAAABQOu93u9Hry5Mk6duyYSpcurbNnz+qBBx7Q9OnT9eCDD2rLli3q1q2bfvrpJ911111uqhgAgFsDwRsAgNtQRkaGZsyYoc2bN0uSPvvsM3Xq1EmPPvqoJKlly5YaM2aM5s6dS/AGAOA6MdUcAIDb0MyZM9W+fXuFh4dLkkqWLKlu3bo5jQkPD1dCQoI7ygMA4JbCGW8AAG4zNptN77zzjtauXeto6969e75xS5cuVWRkZCFWBgDArYngDQDAbebTTz9Vy5YtValSpUuOWb16tZYtW6bdu3cXYmUAANyamGoOAMBtJDs7W1OnTtUrr7xyyTFHjhxR9+7dNX/+fAUHBxdidYDrvfXWW0pMTHS8btasmdOd/QcOHOjG6gDcLgjeAADcRubPn6/GjRurWrVqBfanpKSoQ4cOGjNmjO67777CLQ5wsV27dmnMmDFObQcOHJDVapXdbpfdbtcHH3zgpuoA17n4AyYeDXljIngDAHCbyMnJ0ZtvvqnRo0cX2G+329W1a1c98MADGjBgQCFXB7hWVlaWnnrqKafH6B0/flyhoaHy9uZqS9w6Lv6AKe/RkAMGDFBCQoLeffddPfvss9q+fbubqwTBGwCA28SXX36punXrqnbt2gX2DxgwQP7+/po2bVohVwa43ujRo1W3bl2VK1fO0bZ3715Vr17djVUBrvXPD5gufjSkxWJxejQk3IvgDQDAbWLv3r2Kjo4usG/KlCn65JNPtHTpUvn4+Diuf61SpUohVwlcv3Xr1mnx4sX5ppHv2bNHGzZsUIkSJVSjRg0tWLDATRUCrvHPD5h4NOSNi3k2AAC4SMWXb/Tr6Jrpi69PSF+fKKCvtiqMXJqv1a4be7+OTO7g7hJwg0lNTdUzzzyjuXPn5rs5YGRkpNatW6cqVapo165devLJJxUWFqY2bdq4qVrg2uV9wLRjxw7deeedkng05I2M4A0AAIBbxgsvvKBHHnmkwJsDNm/e3PHvyMhITZs2TR9//DHBGzedy33AdDEeDXnjYKo5AAAAbgk//PCDFi5cqPfff19+fn7y8/PT0aNHVa5cOf3444/5xkdEROjYsWNuqBS4Ppf7gCkPj4a8sRC8AQAAcEvo2LGjsrOzZbVaHUuFChV07NgxJSQkaObMmU7jN2zYcMlH6wE3qqv5gIlHQ954mGoOAACAW15kZKTatm2rGjVqKCoqSitWrNCYMWO0cuVKd5cG/Ct5HzBdrGLFitq2bZtKlCjBoyFvUARvAAAA3PLq16+vWbNm6bnnntOhQ4dUrVo1zZkzR/Xr13d3aYBL8WjIGxPBGwAAALesI0eOOP7dsWNHdezY0X3FACbLezSkp6enfHx8HO0VK1bUwYMH3VgZCN4AAAC4ajfy4+VuVTw2r/DddMf5Ex8ocupvulkfDSnd+sc5N1cDAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATHRDBe/U1FR169ZNgYGBKlOmjN588013lwQAAAAAwHW5oe5q3rdvX/n5+en48eM6d+6cunbtqpCQEPXr18/dpQEAAAAAcE1umOB9/PhxrVmzRkePHpWfn5+Cg4M1f/58/d///R/BGwAAAABw07phpppv3LhRbdq0kZ+fn6OtZs2aCgwM1IEDB9xYGQAAAAAA1+6GOeMdFxenKlWq5GuvXr26Dh8+rKpVqzq122w22Ww2x+uUlBRJF64Tv9nk2jLcXcJt52Y8Tm52HOeFj+O88HGcFz6O88LHcV74OM4LH8d54btZj/O8ug3DuOy4GyZ4Z2Zmyt/fP1+7xWJRZmZmvvZJkybp1VdfzdceHh5uSn24tQS/4+4KAPNxnON2wHGO2wHHOW4HN/txnpaWpuDg4Ev23zDB22KxKCMj/ydLSUlJBQbyUaNG6cUXX3S8zs3N1dmzZxUaGioPDw9Ta8UFqampCg8PV3x8vIKCgtxdDmAKjnPcDjjOcTvgOMftgOO88BmGobS0NJUpU+ay426Y4F2+fHn9/PPP+dpjY2MVERGRr93X11e+vr5ObSEhIWaVh8sICgriBxu3PI5z3A44znE74DjH7YDjvHBd7kx3nhvm5mrNmjXTqlWrZLfbHW1//fWXbDZbgdd+AwAAAABwM7hhgnfZsmXVtGlTDR06VOnp6YqPj9ezzz6r6Ohod5cGAAAAAMA1u2GCtyTNnDlTZ8+eVVhYmBo1aqQuXbqod+/e7i4Ll+Dr66tx48blm/IP3Eo4znE74DjH7YDjHLcDjvMbl4dxpfueAwAAAACAa3ZDnfEGAAAAAOBWQ/AGAAAAAMBEBG8AAAAAAExE8AYAAAAAwEQEbwAAAAAATETwBgAAAADARARvXLPz58+rXr16stvtjra1a9dq9OjRTm3AzSw9PV1BQUFOx/SyZcvUrVs3ZWVlubEy4N9JSUnR4MGDL9kfEBCgM2fOOF6fP3++MMoCAOC2wHO8cc3sdrv8/PyUmZmpL774Qj169NDatWvVunVrpaSkKDAw0N0lAtctJydHvr6+On/+vKZMmaIxY8Zo/fr1uu+++zjOcVNJTU1V7dq1FR8fr9mzZysjI0MeHh6yWCx69tlnVaJECcXFxcnf318JCQlq0KCBNm3apAoVKri7dMAl7Ha7+vbtq3fffVdFixbV7t275enpqdq1a7u7NOC6LVu2TP7+/vL0zH9e1cPDQ2FhYapataobKkMegjeu6Pz583rggQfk6+srSTIMQ8HBwfr+++8VGBios2fPKiwsTGfPntWOHTt09913KzU1VQEBAW6uHLh66enpql69utNxHhoaqm3btqlo0aKO4zwpKUk7d+5UgwYNOM5xU7HZbKpTp44OHDigGjVqqEWLFpKkNWvW6ODBg6pQoYKOHj0qSfrggw/06aef6s8//3RnycC/ZrPZ9NFHH8liscjLy0sZGRnq3LmzWrdurT///FMhISE6d+6cAgMD9Z///EebNm3SgQMHVKRIEXeXDlyTuLg4lS9fXqVLl1bDhg1lGIZ+/fVX3Xvvvfrjjz9Up04d+fj4aP369dq9e7fKly/v7pJvW0w1xxX5+voqPj5evXv31sGDB9WnTx/t379fkuTn5ycfHx95e3s7XkuSj4+P2+oFroXFYpGfn58WLFggDw8Pff7558rIyJB04WegSJEijuM87/jOC+nAzcDb29vpGJ49e7Zmz54tLy8vR9vDDz+shIQEffvtt3rppZfcWS5wTQzD0IsvvqiFCxfqs88+04svviibzabDhw/Lz89Pvr6+8vX11Y8//qhvv/1Wn3zyCaEbN7UmTZro888/l7+/v5YsWaIff/xR5cqV048//qioqCjNmzdPS5cuVc+ePR1/18A9vN1dAG583t7eCgkJUbdu3fTmm2+qW7dumjRpkqNPkuN/WtnZ2SpSpAj/E8NNx8vLSwEBAWrWrJnjv3nTtf4ZuLOysuTn5+doB24GXl5eSkhI0HPPPadTp07pueeekySn47xVq1Zq0aKFkpOT9cgjj7izXOCa+Pr6ysvLS+vWrZMk+fv7O3146unpqblz5yo6OlpffPGF7r//fjdXDFwfi8WiH374QUePHtWECRMkSYmJiZowYYL27dunt99+W0FBQfL391eNGjXcXO3tjb8acU3y/lCz2WyaMGGC0tPTNWHCBB0/flxhYWFurg5wjbzjPDMzU7169VJycrJ69eqlM2fOqHTp0m6uDvj3LBaLmjVrpmXLlqlZs2YyDENr1qyRdOEawCFDhigtLU3Lli1jRgduSh4eHvLw8HBq8/Lykqenp6Kjo5Wdna2NGzfq999/V8WKFd1TJOAC27Zt048//ihfX18tWrRIFSpUcMxg8vDwkJeXl+O/np6estlsbq4YTDXHNcm7NUBubq4OHDighx9+WAcOHNCOHTt05513urk6wDXyjnNPT0+VLVtWQ4cOVdmyZZWVlaXIyEg3Vwf8e8HBwerWrZuKFSumbt26qXv37pKkIUOGKDU1VZJ04sQJ7dq1S9u3b3dnqcA1++fti3Jzc2UYhg4dOqScnBz98MMP+vzzz/ONA24m2dnZWrFihY4ePapjx47Jw8NDvXr10jPPPKPg4GD17NlTFSpU0KBBgxQdHa1p06a5u+TbHme8cU3y/mdlsVi0YMECR3v79u0df8gBN7u849zHx0cTJ050tDVr1kwvvviiO0sDrsmRI0fUqFEjHThwQI0aNXK033HHHUpOTtbPP/+sX3/9Vc8++6wWL16su+66y43VAv9ebm5uvjPedrtdOTk5+vLLL7VkyRKtXbtWTz/9tA4cOKDPPvvMTZUC16dJkybavHmzpk+frnbt2snb21uNGzd2zNZr0qSJzp49q+rVq6t169aaMGECv9PdjDPeuKKcnBxlZWVp//79jv/mPdPYbrdr9+7d+vvvvzV58mRZrVY9+uijbq4Y+PdycnKUnp6uFStWOP6bd5zn5ORo06ZN+uWXXzRw4EBVqlRJbdu2dXPFwL8XFhamBQsWqHz58vr88881f/58GYahV155RWXKlFF0dLT8/PzUsWNHbdy40d3lAv+a1WqV3W53ml6blpam7OxsZWVlKTs7WzVq1NDatWu1Zs0azZo1y90lA9fszJkziomJ0YcffqiDBw/q6NGjio2NVWxsrI4ePaq0tDT9/fffatSokVq1aqWtW7e6u+TbGme8cUVWq1X79+9XzZo1ZRiGatSooXLlykm6cI339u3b1a9fPwUGBmrLli1urha4NpmZmbJarerXr58kqV+/fipevLikCz8DeTejysnJ0fLly91ZKnBNcnNz5e3trerVqzuu/fPw8FBubq6kCx+krl+/XitXrlSZMmW0c+dON1cM/Hu+vr7avXu34xjPyclRuXLl9P777ysrK0t2u13nz5+XxWLRBx98oJ49e6pbt248GhI3JU9PTy1ZskQzZ86UJEVFRSkhIcHpWd42m03t2rXT4sWLua+Bm/Ecb1yVvLuV58nKypK3t7f8/PyUlZWlpKQkTZ8+XR999JGio6M1dOhQN1YLuE5OTo78/PyUnZ2tnJwczZ07Vy+//LK6deumKVOmcAMq3DSsVqtq1qyp2NhY3XPPPUpISFB2drZKlSqlzZs3q1y5cjpy5Ii8vb2VmJioO+64Q0lJSSpWrJi7Swf+ta+//lqdO3fO93jThIQEbdiwQYMHD9bPP/+sPXv26IknnnBTlcD1SU9PV/ny5TVv3jy1bNlSDzzwgO699149//zzki5cHteoUSPt3btXISEh7i0WBG9cu4yMDAUGBio7O9txF8XNmzerV69e2rBhg0JDQ91cIXD90tPTFRQU5PiwSZIOHTqk3r1766effuIsCW4aZ8+eVeXKlZWcnFxgf3BwsOLj4xUUFKS0tDTNnz9fffv25fGQuKnExcXpkUce0Y4dO7R48WJlZGRo0qRJ8vPzc4wxDEP79++Xt7e3vvnmG7Vu3dqNFQPXLjU1VWXKlFHz5s21c+dOpaWlqV69ek43gJ07d6569uwpSXrvvffcVSrEVHNcpZycHB0/flzh4eGOm5b4+flp9+7dTtNZmjRpoj/++EP+/v7uKhVwqcDAQKWlpTk9s7ty5cpas2ZNvhv4ADey4sWLXzJ0S9JXX30li8UiSSpatKgGDhxYWKUBLhMWFqbIyEh99dVXqly5sr744gtlZGRo2LBhTuNycnL022+/OS61AG5G58+fl6+vr5YvX66cnBytXr1aM2bM0IwZM9ShQwd16tRJ77zzjtLT05WUlOTucm97nPHGVYmPj1fFihV16tQplSxZ0qmvT58+qlu3rgYPHuym6gAAAPL75ZdftHTpUr3//vvuLgVwOavVqj///FNNmzZ1al+zZo0+//xzvf/++5wMu4EQvHFVzp49qxIlSigtLc1pam3//v01d+5cffTRR+rVq5cbKwQAXI0zZ87o7rvv1s6dOy95/XZ8fLx69+6tFStWFHJ1AADcmnicGK6Kr6+vPDw8nG5S8sILL2jx4sX63//+R+gGgJtAWlqaLBaLjh07JovFovj4eCUmJurMmTOKi4vTmTNn9MYbb8jLy0vbtm1zd7nANcvMzNR3330nSSpfvrzi4+PdXBHgHqdPn1aDBg20b98+d5dy2yN446rk3Vwn7zrX7777TnPnztWyZcvUokULd5YGALgKn332mV566SX5+fnJw8NDfn5+qlatmkqVKqWwsDBVqlRJP/zwgyZNmqSgoCCnm1EBN5vs7GwNGjRIkuTj46MSJUpo48aNatu2rdq3b6/27durTZs2evDBB91cKXDtduzYoaCgIJ04cUKSlJKSohEjRigxMdExxmKxaMeOHdyX5gZA8MZV8fLykmEYWrhwoSSpY8eO+t///qdGjRq5uTIAwNXYv3+/41neeTfFrFixonJyctSoUSPNmTNHAQEBCg0Nla+vr9MNBYGbRU5OjmrXrq2HH35YycnJatWqlU6ePClfX19ZLBYlJyerRo0aatWqlbZv365XXnnF3SUD18zf31/p6emOy0B9fHw0bdo0ZWRkOMbkfYj6z0frofDxf1X8K4MHD9bbb7+tOnXqSJI++OADp3673a5z585p2bJl7igPAHAJ9erV008//STp//8BdvFz6PMuJypatKi8vb0J3rgpZWdnKzo6WgEBAXruuec0cuRI9e7dW56enrJYLAoNDVWNGjVUuXJl+fj45LspFXAzyZvBlPdECovFIsMwnH5/5/0779G/cB/OeOOqeXh4aN++fWrUqJEWLlyoLVu2KDs722nJyspSVlaWu0sFAPxDRESEYmNjtW7dOknSunXrlJGRoXXr1ik1NVUxMTE6cOCArFar1q9f7/SoSOBm4efnp1atWqlDhw7y9/dX27ZtHXd1ZqotbjV5l4Lm/Ve6cJxffKzn/Zvf6e7Hx9m4Knk3vy9RooQ+/vhjNW/eXAMHDlSfPn3UunVrN1cHALiSUqVKafv27Ro2bJiysrI0bNgwHT9+XMOGDVNcXJy++uoreXt76+TJkxo2bBh/pOGmlJ2drdKlS8vb21s5OTkqUqSIcnNzlZ2dLavVqszMTCUlJSkwMFA5OTmKj49XeHi4u8sGromnp6cMw3D6W9wwDHXt2jXfjCa4H8EbV8Vut0u6cO2Ul5eXunfvrqCgIHXu3FkrV65UVFSUmysEAFxO8eLFVb58eW3dulWBgYHaunWr6tevr61bt6pJkyYaMGCAihUrptGjR2vr1q2qXLmyu0sG/jVPT0/Fx8c77l1w6NAhVa1aVenp6UpKStLx48c1f/58SVKxYsXUrFkzxcXFublq4Ppc/Hf4P/8mNwxDv/76K+H7BkDwxlXJzs6WdCGA510j8vDDD2vQoEF69NFHL/s8WACA+1ksFp07d07ShQ9RL/5vntzcXGVkZMgwDOXm5hZ2icB18/LyUtmyZZWZmalZs2YpICBAffr0cQTxqVOnql27dtq4caNatWrl7nKB62IYhjw8PDRp0qTLjpsyZYpj9irch3lkuCpWq1WSZLPZnNonTpwoi8WiHj16uKMsAMBV8vLyUmZmpgzDcHyYevbsWY0dO1bHjh3Td999p8zMTCUnJ8tmszlmOgE3I8Mw1LNnTx0/flznz59XiRIllJOToyFDhsjX11dvvPGGFi1a5O4ygety8YxUSdq8ebPi4uLyLR4eHgTvGwBnvHFVsrKyVKtWLccfa3m8vLw0duxY/fzzz8rNzeWaQAC4QWVnZys3N1dWq1WGYSgnJ0fPPPOMPDw81KtXL1mtVse1senp6fk+aAVuBrm5uWrVqpVGjBjhaNuwYYPmz5+vnJwcWa1WzZ8/X3fffbd69+6tWrVqqXbt2m6sGLh2eb+nbTabbDabmjVr5hSy8/7t4eGRb4YTCh/BG1elbNmy2r17d4F9//nPf/TYY48RugHgBmYYhhYvXqzz58/LMAydP39er7/+er5xCQkJOnr0qM6fP++GKoHrk56errvuukuPPfaYvLy8dP78ecXHx+u///2vDMNQenq6/vvf/0qSSpcurZkzZ+q9995zc9XAtUlPT3cc18WLF9fBgwedbqomXfjQtXLlysxiugF4GMw7AADgtpCTk6N9+/Zpw4YN6tGjR74/0PKcP39eGzdu1AMPPFDIFQKucezYMfXu3VspKSnq16+fevbsqZMnT6phw4Y6duyYpAuz+fKeaQ/cjM6fP6+//vpLDRo0cHqk2MWSkpJUsmRJ7dq1S3Xq1CnkCnExgjcAALeJ+Ph4VaxYUadOnVLJkiWd+vr06aO6detq8ODBbqoOcL13331XvXv3VmBgoKxWq/bt26c777zT3WUBhSY7O1v79+9XlSpVLvlhKwoHc4MBALhNBAQEyDAM+fv7O7X3799fCxYsUNGiRd1UGWCOwYMHKzAwUJLk5+dH6MZtp0iRIqpduzah+wZA8AYA4Dbh6+srDw8Pp+m1L7zwghYvXqz//e9/6tWrlxurA1wnJydHhw8fliSlpqYqKChIp06dchpz7NgxxcfHu6M8wGWKFy+er61r165at26dG6rB5RC8AQC4TeRdA+jtfeHeqt99953mzp2rZcuWqUWLFu4sDXCp1NRUVa1aVXa7Xf7+/kpPT3ea0fHJJ5+oTp06Gj9+vPuKBFwgJCREhmEoLi5OkpSZmally5blexIR3I9rvAEAuE3k5OSoSJEimj9/vrp3766cnBxt27ZNUVFR7i4NcKns7GwFBgY6Hrfk7e0tq9Wq9PR09erVS8uWLVOVKlX0xx9/MAUXN620tDRVrVpVPj4+ql27tn7++WfNnTtXb7zxhn7//Xc988wz8vLykmEYCgkJ0dy5c91d8m2Nx4kBAHCbGTx4sN5++23HHW4/+OADp3673a5z585p2bJl7igPuC4ZGRny9/d3uqTC09NT3t7eio+Pl91u1+bNm/Xggw8SunHTSkhIULNmzSRJy5cvV61atZScnKyxY8dq4MCB8vDw0IYNG/T2229r1KhR+vDDD91cMZhqDgDAbcTDw0P79u1To0aNtHDhQm3ZskXZ2dlOS1ZWlrKystxdKvCvGYahSpUqqVGjRrJarWrUqJEaNWqknJwcrVmzRn5+flqyZInuuusuJSUlKTMz090lA9ckICBAw4YNk4+Pj7766iulpaWpa9eueuaZZ/TNN98oKSlJAQEB6tGjh4KDg9WpUyd3l3zb44w3AAC3ibyry0qUKKGPP/5YzZs318CBA9WnTx+1bt3azdUB1y87O1svv/yyihYtqoEDB2rgwIEyDEO9e/fWO++8o02bNmnevHnq0KGDwsLCdPDgQdWtW9fdZQP/WmBgoAYMGKC6devqgw8+UKVKlTR69GgNHTpUS5cuZTbHDYjgDQDAbcJut0u6cK23l5eXunfvrqCgIHXu3FkrV67kWm/c9Hx8fDR06FDZ7XYNHDhQPXr0cATvb775RosXL9bzzz+v5cuXq3jx4tq3bx/BGze1nj17aunSpdq3b5+2bNkiwzDk4eEhDw8Pd5eGf2CqOQAAt4m8u9zmBXBJevjhhzVo0CA9+uijSk5OdldpgEulpKQoOztbNpvNcdxnZ2erW7du2rt3r7y9vbVjxw5t2bLFzZUC18fPz0+nTp3SW2+9pdTUVI0aNUqSuFzoBkTwBgDgNmG1WiXJcafnPBMnTpTFYlGPHj3cURbgchaLRUePHpWvr68yMzNVpkwZZWRkSLoQVKZPn66FCxdqwIABbq4UuHYrVqyQJA0YMEAxMTFatGiRFi9erIYNGyogIECZmZlasmSJ0tPT9eOPP7q5WvA4MQAAbhPHjx9Xu3bttHbtWoWGhjr1LVy4UD///LPmz58vT08+l8fN7emnn1ZSUpJ++uknrV+/XtWrV1dAQIDeeecdPfroo6pWrZq7SwSuS0ZGhkqVKiWr1aozZ84oJCREkvTTTz+pf//+2rRpk5588kkVKVJEOTk5ysjI0LZt29xb9G2O4A0AAGQYhux2u4oUKeLuUoDr8sMPP+jZZ5/Vb7/9pkqVKunOO+9Unz59FBUVpbFjx2rt2rWKiIjQgw8+qNatW6tt27buLhm4JidPntSwYcO0ZcsW/fDDD477FbRp00aRkZGaNGmSmyvExQjeAAAAuGXY7XbFxMSoTp062rVrlx566CEdPnxYXl5ekqSkpCTNmTNHM2bMUK9evTRu3Dg3Vwxcn48++kgLFizQpk2bJF14rvfTTz+tkydPOo57uB/BGwAAALesgwcPqkqVKvnas7Oz5eXlxaUVuCWcPXtWxYsXd7z+448/dPfdd7uxIvwTwRsAAAC3hJycHL3zzjtXdcmEp6en6tWrp3vuuacQKgNcLz09XWvWrFHRokUv+wFSdna2srOz1a5du0KsDv9E8AYAAMAtw9vbW40aNZKvr+9lx506dUrHjx9XcnIy03FxUzp16pTKlCmT72aZ/3T27FlVq1ZNf//9dyFVhoIQvAEAAHDL8Pf318GDB1WmTJnLjtu3b59q1qypmJgY7nKOm1JKSoqKFSum9PR0+fv7FzjGarXK399fubm5hVwd/snb3QUAAAAArnLx2WubzaaPPvpIHh4e8vDwUN75poEDB6p48eLavHkzoRs3LW9vb3l4eEi6MO38yy+/dMz0sFqtevrppx3HPtyPM94AAAC4ZQQEBOjAgQMqU6aMbDabLBaLunfvLi8vLxmGoQULFshms8nbm/NPuLnlnc1OT09XTk6OQkJC1K9fPxmGoTlz5iglJUUeHh7y9/dXTk6Ou8u97RG8AQAAcMvw8fHR7t27Vb16dRmGIS8vL8dUXLvdLh8fH6bd4paQ98FSenq6/Pz85Ovrq+zsbElS0aJFlZaWJpvNRvC+QfD8BAAAANwS7Ha7SpUqpczMTElyTLPNm2rLtFvcqjw9PZ2O7YsvrcCNgTk2AAAAuCV4e3srPj7ecUY7KytLhmFoxIgRKlKkiKPdbrcz1Rw3vYuDtdVqVU5Ojv7zn//IMAzZbDZlZmZyx/4bCL9xAAAAcEtIT0/Xq6++qlWrVmnr1q3KycnRmDFj5OvrK09PT+Xm5io6Opqp5rgl5OTkOM5yG4ahGTNmOO5u3rJly8s+2xuFj2u8AQAAcEvo16+ffv31Vw0fPlzdunWTn5+fu0sCTJOSkqLixYtr7969slgsBY6x2WyqUaOGjhw5ovDw8EKuEBcjeAMAAOCWkJycrKJFi8rb21u///67/u///k8BAQGXXScuLq6QqgNc68SJEypXrtxVXc/t4eHBDdbcjKnmAAAAuCUUK1bM8e+KFStq/vz5l7yW22azKTk5ubBKA1zujjvuUGJiogIDAy97LXdWVpbOnj1biJWhIJzxBgAAAADARFxxDwAAAACAiQjeAAAAAACYiOANAAAAAICJCN4AAAAAAJiI4A0A/8L48eM1depUt71/xYoVlZiYeMn+rl276qWXXirEiszRqFEjrVmzRtKl9/lKX4vCtH37djVr1kyBgYG66667tGrVqsuOz8zM1PPPP6877rhDYWFhGjlypOx2u6O/YsWK8vb2VrFixdS6dWvt3Lnzquo4ffq0hg8fripVqshisahcuXLq0aOH9uzZ4xizdu1aPfjgg5fcxokTJ1SyZEn98ccfV/We7uKKff03XP2z/8wzz2jx4sUu296lzJs3T4MGDTL1PWw2m8qXL68ffvjhqte5mv3Pe/6wp6dnvrETJkyQt7e30+Lp6anBgwc7xqxcuVKenp5OYxISEv7dzgGAixC8AeAWUrFiRZUtW9bdZVyXI0eOKC4uTvfcc4+7S7kq58+fV4cOHfTcc8/p7Nmzeuedd9S9e3cdPXr0kusMHz5cNptN+/btU0xMjFJSUvT66687jTl16pQSEhI0cOBAde7cWTab7bJ17Ny5Uw0aNJDVatWyZcuUnp6urVu3qkGDBmrZsqW+/vrrq9ofPz8/VatWTUWLFr2q8e7gqn2Fa3h7e6tatWoqXry4S7fr6+urmJgYPf300/n6xo4dK7vd7ljOnTun0qVLa8SIEY4xe/bs0bhx45zGlSpVyqU1AsDVIngDwC1k6tSpGjp0qLvLuC6LFy9W586dL/tM0htJYmKi3n77bXXr1k0+Pj669957FRUVpa1bt15ynbVr12rkyJEqVqyYQkJCNHz4cP33v//NN87Hx0ddunRR2bJltW/fvktuLzMzU127dtW4ceP0/vvvq1q1avLy8lLp0qU1ePBgrVq1SgcOHLiq/SlevLg2btyoatWqXdX4wubKfYVreHl56X//+59atGjhtho++ugjPfzww04fPO7Zs0c1atRwW00AcDGCNwBcxvjx41WsWDFVr15da9eudbTPmjVLERERCgoKUq9evWS1Wp3Wmz59uiIiIuTr66vatWtrwYIFjr4jR46oTp062rt3r+677z75+/srMjJSf/75pyRp2bJl+aZP1q9fXzk5OZKkc+fOqUePHgoKClKFChW0cOFCx7YHDRqkefPmFbgvrVq10vr1653aJkyYoHPnzjm1tW/fXsuXL5cknTlzRk8//bRCQkIUEhKip556SkeOHFHFihUd4wMDA3X8+HE9/PDDCgwMVM2aNbVy5UqnbR4/flxPPvmkQkJCFBoaqueff15//PGH6tSpk6/ORYsW6dFHHy1wHy7n66+/Vp06deTn56fatWvr66+/1ksvveT4eowfP15TpkzR2LFjVaJECZUuXVpz5syRYRiaOHGiSpUqpdKlS+f7+h0+fFidOnVSYGCgSpYsqRdeeEG///677rvvPklShQoV9MQTT0i6EAq/+eYb/f7772rSpMkla33ooYf0yiuv6PTp00pMTNSYMWMueyYuJSXlsh9EfP3116pcubKeffbZAvvr1q2r6Ohop7YNGzYoMjJS/v7+atmypWJjYx19gYGBTv++0vf3wIEDeuihhxQYGKhixYqpW7duOnnypKN/8+bNqlGjhoKDgxUdHa3c3FxH3+V+VgpjXyVp1apVatSokfz8/FS5cmXNmDFDM2bM0Pjx4yVJjRs31oQJEzRy5EiFhIRctr6LLVy4UHfddZf8/PxUunRp9e/f3+nyiNzcXL3++usqU6aMihUrppEjRzp9bbKzszV69GiVLVtWfn5+atiwoX7++ed877N//3498sgjKlasmIoWLapWrVo5/b662IgRIxQVFaWzZ886puKvX79ejRs3lsViUaVKlTRlyhQZhuG03q+//qqmTZvKz89PZcqU0csvv6ysrCxHf506dXTkyBFJF2beHDx48JK/p8LCwjR//nw9/vjjql+//lV/PS8lMzNT7733nl5++WWn9r1796p69erXvX0AcAkDAFCgv//+27jzzjuN5ORkY+3atcbcuXONcePGGXXr1jWefPJJ4/Tp08apU6eMhx9+2BgxYoRjvVGjRhmdOnUyDhw4YNhsNmPLli1GZGSkMWPGDMMwDCM2NtYICwszIiMjjS1bthgZGRnG7NmzjXLlyhlZWVlONdjtduOuu+4y1q9fbxiGYVSoUMFo2LChMW/ePMNqtRrr16837rjjDuOvv/4yDMMwBg4caMydO7fA/fniiy+MZ555xvE6KyvLuOOOO4z33nvP0RYXF2dEREQYOTk5RlpamlGzZk1j8ODBRnx8vJGcnGx89NFHRoMGDYwKFSo41vH19TUaN25sLFu2zLBarcYPP/xgFCtWzDhz5oxhGIZx+vRpo1KlSkZ0dLRx8uRJIzEx0XjzzTeNOnXqGLVr13aq8ejRo8Ydd9xh2O12R1uFChUc27rYxe2ffPKJUalSJWPFihVGRkaGsWvXLqNly5ZGjRo1HF+PcePGGRUqVDBGjRplpKenG3/++adRsmRJo3///sYrr7xipKenG7t27TJKly5tHDp0yDAMwzh27JhRtmxZ4/XXXzdOnz5tJCQkGBMnTjRq165t3HvvvflqCgkJMSQZr7zySoHfgzxWq9WoX7++IcmQZJQtW9bxPbx4386cOWO8+uqrxt13333Z7XXv3v2S3/d/WrNmjVGlShWjcePGxp49e4zU1FRj4sSJRqNGjRxjAgICHP++0vc3Pj7eqFSpkvHVV18Z58+fNxITE43Jkycb1apVM1JSUgzDMIyoqChj7dq1xqlTp4xx48YZmZmZhmFc+WelMPZ1+fLlRqlSpYxFixYZaWlpxsGDB42uXbsaNWvWNMaNG+cYN27cOOOtt966qvc1DMNxjK9evdrIyMgwTp06Zbz66qtG7dq1jezsbKNHjx5G3bp1jRdffNFISUkxYmNjjaioKOPDDz90bOPJJ580+vbtaxw7dsywWq3GypUrjapVqxpLlixxjNm3b59RpkwZY/r06capU6cMq9VqLF261KhUqZKxbt06Y+7cucbAgQONnJwco1+/fkarVq2MtLQ0x9enUqVKxt13322sX7/eyMjIMP7880+jadOmxsCBAx3vsWrVKqNUqVLG119/baSlpRkxMTHGgw8+aHTs2NExpnbt2kZsbKxhGBeO30aNGhnz5893/J4qUaKE0zHeo0cPY9GiRVf1tbzS2Hfffdfo1atXvvbg4GCjUqVKRvHixY1HHnnESEhIuKr3AwAzELwB4BL2799vREZGOoXhcePGGbVq1TJyc3MdbTExMUatWrUMwzCM48ePG5UqVTJsNpvTtk6fPm2ULl3asNvtRmxsrCHJ2LJli9OYhg0bGr///rtT24wZM4zu3bs7XleoUMGYPHmy05iXX37ZmDJlimEYlw/eVqvVKF++vOOP7q+++sq47777jLp16zrGjB8/3njttdcMwzCMKVOmGE888US+7bz77rtOwVuS8dVXXzmNefTRR41vvvnGMAzDGDJkiPHCCy/k286IESPyBe9p06YZffv2dWq7UvC2Wq3GHXfcYezevdupPy0tzQgPD3cK3lFRUU5j+vbtazRu3Nip7bnnnjPmz5/v+PfLL7+c772HDh1aYPBOT083VqxYYVStWtX4/PPP8/XnefTRR42nnnrKOHnypJGQkGBER0cbK1eudNq3IkWKOIL5uHHjnD6M+Kc2bdoYK1asuGT/xdasWWMUKVLEiIuLc7Tl5uYaZcqUMU6fPm0YhnPwvtL397nnnnMKi3mGDh1qvP3224ZhGEbTpk2NP//806n/an5WCmNfa9WqZSxfvtxpPbvdbkRGRl5z8E5ISDBKly5tnDx5Ml9fXluPHj2Mdu3aOfUtX77caN++vWEYhvH777/nO14NwzB27txp1KtXz/G6U6dOxsyZM/ONO336tGG32425c+ca/fr1M7p162Y8/PDDhtVqdYxZs2aNERAQ4PT1MQzDSElJMcqVK2fs3bvXMAzDqFu3rrF06VKnMVlZWUa9evWMX375xTCM/MH7n7+nhg8f7vg9lbf/rgjeNpvNqFChgnHgwAGn9szMTOO7774zkpOTjXPnzhljxowxmjVrdlXvBwBmYKo5AFxC1apV1bZtW0VFRWnTpk2O9k6dOsnDw8PxOiIiQqdOnZIkbdq0SUePHlVQUJD8/PwcS3h4uM6cOeOY4lqmTBlFRUU5vV+VKlUc25EuXDv81ltv6a233nIa16VLF6fXF7//5fj6+qpz586OG0/NnDlTkyZNUlhYmDZu3Kjc3FwtWLBAvXr1knRhamn37t3zbefxxx93eu3h4aHOnTtfcl9WrVrl2ObFCppOfi3TzHfv3q3y5cvnm7YeGBioDh06OLXlTQ/PU7JkyXzXpYaGhiopKUnS1X8N8gQEBKhNmzaaN2/eJe+AvWPHDu3atUtz5sxRWFiY7rjjDr366quKjo52uuPyiRMnZLfbtXv3bm3evFn9+/cv+AsgqUSJEjp9+vQl+/+pYcOGCg8Pd7z28PBQxYoVCzyOrvT9/fXXXzVkyBCn493Pz08ffPCBtm/fLkmaNm2aunbtqmnTpjnu3n61Pytm7mtiYqJOnz6ttm3bOq3j5eWlrl27XvV7/NOGDRvUvHlzhYWF5eu7uO1yP8u//vqrtm3blu/r2qhRI+3du9cxzXvNmjX6z3/+k+99SpYs6bg8Ye7cucrIyNC3334rX19fp3FNmzZ1+vpIUlBQkDp06KB169YpKSlJx48fz/ezVKRIET3xxBOXnNL+z3375+83V5k7d65atGihKlWqOLX7+fmpc+fOCgkJUXBwsCZMmKCMjAzt3r3b5TUAwNUgeAPAZbz22mv68MMPNWDAAM2fP1+SFBwc7DSmSJEiTnecfvTRR2W1WvMt2dnZjj8O/7kN6cKNtC7ezssvv6wXXngh3x/vV3p/6cJNhS6+TnzkyJGSpD59+mju3Lnav3+/zp07p8aNG6tfv36aOXOmVq5cqXr16ql06dKSLgQU4x/XeRbEz89PPj4+l9yXnJwcWSyWfOt5e3s7vY6Pj9ehQ4fyheMrudo6JalYsWL5avjnnZg9PT0d4fBqth0TE6OzZ886td155506efKkzp8/7/R9ePzxx7Vv3z41adLEaf89PT1Vs2ZNbdiwwWk7Xl5eqlOnjr777jstWLBA6enpevzxx522ef78ebVs2VLffffdVX0NpIKPv4KOI+nK31/pwl3G/3m822w2x89M48aNtXXrVu3fv1/t27d3fE2v9LNi9r5e/AGaK+Xk5Dg9Hu5SrvSz/NJLL13y65P3PbHb7Y77P1xK5cqVtWPHDsc12Be70vGdm5ub72c1j5eXl9M16Rf7577985i52D/va/Hhhx9etqY8drtdb731lkaPHn1V4yMiInTs2LGrGgsArkbwBoAraNy4sb7++mvHGUxPz0v/6mzSpIk2bNigtLQ0p/bjx487PebmctuQpK1bt+q3337TCy+8kK/vSutKUu3atZ0eofPmm29KunADpNzcXA0bNkx9+/aVJHXs2FEbNmzQ1KlTHW3ShbPDn3/+eb5t//NRTVeqp3nz5gUGpX8+83fx4sXq1KnTJf/Iv5S6devq2LFj+uuvv5za09PTtWzZMqe2gm5Qdrn3u5qvwbfffqtp06Y59W/dulW1atVSQECA0/fh66+/VkREhGJiYpzGG4ahHTt2FHiGVLoQyCwWizw8PPT11187bTMgIEDdu3fXtm3bLvlc5AMHDjiFmas5hq52bPPmzfXjjz/ma58yZYrT88eLFy+umTNnKjU1Vdu3b7+qnxWz9zU0NFRhYWGOmwnmycnJua5nbDdt2lS//vqr4uPj8/VdfNO5y9XWvHlzLVu2LF+o3r59u9MsmBYtWhR4Q8XTp0871m3VqpWmTp2q+++/P9+xt3nzZsXFxTm1paSk6KefftI999yjkiVLKjQ0NN+NGXNycrRo0SLde++9Bdb/b46x9u3bO32fn3vuuatab+HChWrQoEG+O5dnZWWpTZs2yszMdLTZbDZt3br1hr1bP4BbH8EbAC5h7dq1+uCDD5SRkaFly5apQoUKV1ynbNmy6tatmzp37uyYDrpx40a1bdv2qv/gMwxDgwYN0rvvvvuvQ+jV6N27t9auXatu3bpJuhA8//Of/+jgwYN64IEHHOP69++vv/76S0OGDNHx48d17tw5ffTRR/riiy/+1fuNHj1a77//vmbMmKGzZ88qKSlJ7733nr788kun/Vu0aNE1Te/18fHR5MmT9fDDD2vlypXKzMzU7t271bFjx+t+FvUrr7yihQsX6o033lBiYqLOnDmj1157TWvWrHGMeeaZZ/TZZ59p2bJlstls2rZtm/r166cxY8YUuM3IyEgVKVJE0dHROnv2rBITEzV06FB5e3vnu/xAuhDUnn76abVs2VIBAQEFbtNisei7777ToEGD9PLLL+vgwYPKzc3V6dOn9dFHH6lZs2ZXPSvg3xo9erRmzJihTz75RKmpqUpMTNS4ceM0d+5cValSRRkZGRo6dKhOnDihv//+W0ePHlWZMmWu+WfF1fs6ffp09ezZU4sWLdL58+d16NAhPfHEE0537JYuBMns7Oyr2mbZsmU1YMAAPfDAA1q9erUyMzN16tQpjRkzRu3atbuqs+GNGzdWzZo11b17dx05ckQ2m03Lly9X586dVa9ePce4yZMna8KECZo6daoSEhJks9m0ZMkSRUVFacuWLY5xXbp00QcffKC2bds6fUgVFhamRx99VBs2bJDVatX27dvVoUMHPfTQQ6pZs6bja9S9e3ctXbpUGRkZOnjwoJ544gmVLFlS7dq1u6qvyT/9m69nQXJzczVp0qR8d7CXLvxOCAkJ0cCBA5WcnKwTJ06oR48eatiwoSpXrnzN7wkA14PgDQCXUK9ePf3yyy8qUaKEFi1apHfeeeeq1ps8ebLatWunBx98UEFBQerfv79eeeUV9enT56rW//TTT/X777/rgQcecEy99PPzu449cfbEE09owIABTqG0b9++6tevn9NZqoCAAK1du1bJycmqU6eOKlasqD/++EPffvvtv3q/8uXLa+XKlVq6dKnKlSunGjVqKCYmRh988IFjOurx48d14MABtWrVqsBthIWFOb4WBZ0VfuaZZ/Tmm2/qxRdfdDzOasiQIdccCvKULl1a69at09atW1WpUiXVqlVLqamp+uSTTxxjypYtq8WLF2vixImO93711VfVsmXLArfp4eGhRYsWad++fapQoYJq166txMRELV261OmDiLCwMHl5ealBgwYKCQnRnDlzLlvr3XffrW3btiktLU2tW7eWxWJR3bp1tXLlSn3//fcaOHDgdX0tLiU8PFy//PKLvv/+e5UpU0bVqlXToUOHtHbtWgUEBMjf31/lypXTnXfeqVatWjnuKyBd+8+KK/f1/vvv1xdffKFp06YpNDRUbdu21f/93//le1xZkyZN9MYbb2jw4MFXtd3XXntNQ4YM0aBBgxQSEqLIyEidO3dOa9euveoP1BYsWKCKFSuqWbNmCgkJ0dixYzVr1iyna9LvvPNOrV69WqtXr1blypVVsmRJzZgxQ59//rmaNWvmtL0OHTpo9uzZ6tChg3bs2CFJqlGjhj788EONHj1axYoVU8eOHdW+fXvNmDHDsV7btm01Z84cvfbaaypWrJhatGih8uXL67vvvrvm6fotWrRQ7969L3kvhCs5evSoWrVq5fQhxMVmz56tnJwcVa5cWbVr15a/v/8Vf4YAwEwehlkfgQMAIGnp0qUKDw/XnXfe6dQ+c+ZM7dmzR++9957effdd7d692ynQAjDX2rVrNXXqVC1dutTdpQDALY8z3gAAUxUtWlSdOnXSqlWrZBiGcnNztWTJEr3xxhuOM5NhYWEFXs8O3Ih69+7tdDOwi5clS5a4uzwAwA2IM94AANOtXbtWr776qvbu3avs7GxFRUVp+vTp+W6KBKDwcMYbAAoPwRsAAAAAABMx1RwAAAAAABMRvAEAAAAAMBHBGwAAAAAAExG8AQAAAAAwEcEbAAAAAAATEbwBAAAAADARwRsAAAAAABMRvAEAAAAAMNH/A82EUglpLQlRAAAAAElFTkSuQmCC","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","不是      1226\n","是       1074\n","不重要      389\n","问法错误     277\n","回答正确      34\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-525 **********\n","shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint-525\n","不是      1193\n","是       1043\n","不重要      433\n","问法错误     286\n","回答正确      44\n","問法錯誤       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_64708/961288552.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","/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"]},{"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>0.730000</td>\n","      <td>0.770974</td>\n","      <td>0.730000</td>\n","      <td>0.746291</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>0.773000</td>\n","      <td>0.773916</td>\n","      <td>0.773000</td>\n","      <td>0.764280</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>0.704667</td>\n","      <td>0.814516</td>\n","      <td>0.704667</td>\n","      <td>0.745365</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...</td>\n","      <td>0.679333</td>\n","      <td>0.803070</td>\n","      <td>0.679333</td>\n","      <td>0.724637</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  epoch                                              model  accuracy  \\\n","0     0                shenzhi-wang/Llama3-8B-Chinese-Chat  0.730000   \n","1     1  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.773000   \n","2     2  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.704667   \n","3     3  shenzhi-wang/Llama3-8B-Chinese-Chat_checkpoint...  0.679333   \n","\n","   precision    recall        f1  \n","0   0.770974  0.730000  0.746291  \n","1   0.773916  0.773000  0.764280  \n","2   0.814516  0.704667  0.745365  \n","3   0.803070  0.679333  0.724637  "]},"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_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}