diff --git a/presets/falcon/inference-benchmark.py b/presets/falcon/inference-benchmark.py
new file mode 100644
index 000000000..84619b032
--- /dev/null
+++ b/presets/falcon/inference-benchmark.py
@@ -0,0 +1,101 @@
+import csv
+import argparse
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+import torch
+from datetime import datetime
+import time
+import uuid
+from accelerate import Accelerator
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model", type=str, required=True)
+    parser.add_argument("--num_nodes", type=int, required=True)
+    parser.add_argument("--num_processes", type=int, required=True)
+    parser.add_argument("--num_gpus", type=int, required=True)
+    parser.add_argument("--num_prompts", type=int, required=True)
+    parser.add_argument("--model_parallelism", type=str, required=True)
+    parser.add_argument("--data_parallelism", type=str, required=True)
+    parser.add_argument("--quantization", type=str, required=True)
+    parser.add_argument("--machine", type=str, required=True)
+    parser.add_argument("--use_accelerator", action='store_true', help="Use the Accelerator for parallel processing.")
+    return parser.parse_args()
+
+def inference(requests):
+    for request in requests:
+        start_time = time.time()
+
+        sequences = pipeline(
+            request,
+            max_length=200,
+            do_sample=True,
+            top_k=10,
+            num_return_sequences=1,
+            eos_token_id=tokenizer.eos_token_id,
+        )
+
+        end_time = time.time()
+        inference_time = end_time - start_time
+        timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+    
+        result = {
+            "model": args.model,
+            "num_nodes": args.num_nodes,
+            "num_processes": args.num_processes,
+            "num_gpus": args.num_gpus,
+            "num_prompts": args.num_prompts,
+            "prompt_len": len(request),
+            "model_parallelism": args.model_parallelism,
+            "data_parallelism": args.data_parallelism,
+            "quantization": args.quantization,
+            "machine": args.machine,
+            "inference_time": inference_time,
+            "request_id": str(uuid.uuid4()), # Generate a unique UUID
+            "timestamp": timestamp
+        }
+        writer.writerow(result)
+
+        for seq in sequences:
+            print(f"Result: {seq['generated_text']}")
+
+args = get_args()
+
+model_id = "tiiuae/falcon-7b-instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="auto",
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+)
+
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+    device_map="auto",
+)
+
+
+
+with open("requests.csv", "r") as f:
+    requests = [line.strip() for line in f.readlines()]
+
+fieldnames = ["model", "num_nodes", "num_processes", "num_gpus", "num_prompts", "prompt_len", "model_parallelism", "data_parallelism", "quantization", "machine", "inference_time", "request_id", "timestamp"]
+
+with open("results.csv", "a", newline='') as f:
+    writer = csv.DictWriter(f, fieldnames=fieldnames)
+    writer.writeheader()
+
+    if args.use_accelerator:
+        accelerator = Accelerator()
+        # Split requests across processes
+        with accelerator.split_between_processes(requests) as split_requests:
+            inference(split_requests)
+    else:
+        inference(requests)
+
+        
\ No newline at end of file
diff --git a/presets/falcon/plot.ipynb b/presets/falcon/plot.ipynb
new file mode 100644
index 000000000..50e9b6958
--- /dev/null
+++ b/presets/falcon/plot.ipynb
@@ -0,0 +1,804 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(\"benchmark.csv\")\n",
+    "df['timestamp'] = pd.to_datetime(df['timestamp'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>model</th>\n",
+       "      <th>num_nodes</th>\n",
+       "      <th>num_processes</th>\n",
+       "      <th>num_gpus</th>\n",
+       "      <th>num_prompts</th>\n",
+       "      <th>data_parallelism</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>falcon-7b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>falcon-7b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>falcon-7b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>falcon-7b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>falcon-7b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>falcon-7b</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>132</td>\n",
+       "      <td>embarrassingly-parallel</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>falcon-40b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>falcon-40b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>falcon-40b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>falcon-40b</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>132</td>\n",
+       "      <td>embarrassingly-parallel</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>falcon-40b</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>132</td>\n",
+       "      <td>embarrassingly-parallel</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         model  num_nodes  num_processes  num_gpus  num_prompts  \\\n",
+       "0    falcon-7b          1              1         1            1   \n",
+       "1    falcon-7b          1              1         2            1   \n",
+       "2    falcon-7b          1              2         2            1   \n",
+       "3    falcon-7b          1              1         3            1   \n",
+       "4    falcon-7b          1              1         4            1   \n",
+       "5    falcon-7b          2              2         2          132   \n",
+       "6   falcon-40b          1              1         2            1   \n",
+       "7   falcon-40b          1              1         3            1   \n",
+       "8   falcon-40b          1              1         4            1   \n",
+       "9   falcon-40b          2              2         4          132   \n",
+       "10  falcon-40b          2              2         8          132   \n",
+       "\n",
+       "           data_parallelism  \n",
+       "0                      none  \n",
+       "1                      none  \n",
+       "2                      none  \n",
+       "3                      none  \n",
+       "4                      none  \n",
+       "5   embarrassingly-parallel  \n",
+       "6                      none  \n",
+       "7                      none  \n",
+       "8                      none  \n",
+       "9   embarrassingly-parallel  \n",
+       "10  embarrassingly-parallel  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "unique_experiments = df[['model', 'num_nodes', 'num_processes', 'num_gpus', 'num_prompts', 'data_parallelism']].drop_duplicates().reset_index(drop=True)\n",
+    "unique_experiments_sorted = unique_experiments.sort_values(by=['model'], ascending=False).reset_index(drop=True)\n",
+    "unique_experiments_sorted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "         model  num_nodes  num_processes  num_gpus  num_prompts  \\\n",
+      "0   falcon-40b          1              1         2            1   \n",
+      "1   falcon-40b          1              1         3            1   \n",
+      "2   falcon-40b          1              1         4            1   \n",
+      "3   falcon-40b          1              1         4            1   \n",
+      "4   falcon-40b          2              2         4          132   \n",
+      "5   falcon-40b          2              2         8          132   \n",
+      "6    falcon-7b          1              1         1            1   \n",
+      "7    falcon-7b          1              1         2            1   \n",
+      "8    falcon-7b          1              1         3            1   \n",
+      "9    falcon-7b          1              1         4            1   \n",
+      "10   falcon-7b          1              2         2            1   \n",
+      "11   falcon-7b          2              2         2          132   \n",
+      "\n",
+      "      model_parallelism         data_parallelism experiment_length  \n",
+      "0   accelerate-naive-mp                     none   0 days 00:22:48  \n",
+      "1   accelerate-naive-mp                     none   0 days 00:24:25  \n",
+      "2   accelerate-naive-mp                     none   0 days 00:26:25  \n",
+      "3      deepspeed+dynamo                     none   0 days 00:23:35  \n",
+      "4   accelerate-naive-mp  embarrassingly-parallel   0 days 00:14:31  \n",
+      "5   accelerate-naive-mp  embarrassingly-parallel   0 days 00:15:23  \n",
+      "6   accelerate-naive-mp                     none   0 days 00:07:05  \n",
+      "7   accelerate-naive-mp                     none   0 days 00:07:56  \n",
+      "8   accelerate-naive-mp                     none   0 days 00:07:42  \n",
+      "9   accelerate-naive-mp                     none   0 days 00:08:20  \n",
+      "10  accelerate-naive-mp                     none   0 days 00:08:38  \n",
+      "11  accelerate-naive-mp  embarrassingly-parallel   0 days 00:04:43  \n"
+     ]
+    }
+   ],
+   "source": [
+    "def experiment_length(group):\n",
+    "    duration = group['timestamp'].max() - group['timestamp'].min()\n",
+    "    return duration\n",
+    "\n",
+    "columns_to_group_by = ['model', 'num_nodes', 'num_processes', 'num_gpus', 'num_prompts', 'model_parallelism', 'data_parallelism']\n",
+    "\n",
+    "experiment_lengths = df.groupby(columns_to_group_by).apply(experiment_length).reset_index(name='experiment_length')\n",
+    "\n",
+    "print(experiment_lengths)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "experiment_lengths['experiment_length'] = pd.to_timedelta(experiment_lengths['experiment_length'])\n",
+    "\n",
+    "experiment_lengths['experiment_length'] = experiment_lengths['experiment_length'].dt.total_seconds() / 60\n",
+    "\n",
+    "def plot_for_model(model_name):\n",
+    "    plt.figure(figsize=(10, 6))\n",
+    "\n",
+    "    # Filter by model\n",
+    "    filtered_df = experiment_lengths[experiment_lengths['model'] == model_name]\n",
+    "    \n",
+    "    # Plot for num_nodes=1 and num_processes=1\n",
+    "    subset_1 = filtered_df[(filtered_df['num_nodes'] == 1) & (filtered_df['num_processes'] == 1) & (filtered_df['model_parallelism'] == 'accelerate-naive-mp')]\n",
+    "    if not subset_1.empty:\n",
+    "        plt.plot(subset_1['num_gpus'], subset_1['experiment_length'], marker='o', label='1 Node, 1 Process', color='blue')\n",
+    "        for i, row in subset_1.iterrows():\n",
+    "            plt.annotate(f\"{row['experiment_length']:.2f}\", \n",
+    "                         (row['num_gpus'], row['experiment_length']),\n",
+    "                         textcoords=\"offset points\",\n",
+    "                         xytext=(0, 5),\n",
+    "                         ha='center')\n",
+    "\n",
+    "    # Plot for num_nodes=2 and num_processes=2\n",
+    "    subset_2 = filtered_df[(filtered_df['num_nodes'] == 2) & (filtered_df['num_processes'] == 2)  & (filtered_df['model_parallelism'] == 'accelerate-naive-mp')]\n",
+    "    if not subset_2.empty:\n",
+    "        plt.plot(subset_2['num_gpus'], subset_2['experiment_length'], marker='o', label='2 Nodes, 2 Processes', color='green')\n",
+    "        for i, row in subset_2.iterrows():\n",
+    "            plt.annotate(f\"{row['experiment_length']:.2f}\", \n",
+    "                         (row['num_gpus'], row['experiment_length']),\n",
+    "                         textcoords=\"offset points\",\n",
+    "                         xytext=(0, 5),\n",
+    "                         ha='center')\n",
+    "    plt.title(f'Experiment Time vs. Number of GPUs ({model_name})')\n",
+    "    plt.xlabel('Number of GPUs')\n",
+    "    plt.ylabel('Experiment Time (minutes)')\n",
+    "    plt.legend()\n",
+    "    plt.grid(True, which='both', linestyle='--', linewidth=0.5)\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()\n",
+    "\n",
+    "# Plot for each model\n",
+    "plot_for_model('falcon-40b')\n",
+    "plot_for_model('falcon-7b')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_filtered = df[df['num_processes'] == 1]\n",
+    "# GPU memory requirements (in GB)\n",
+    "gpu_memory = {\n",
+    "    'falcon-7b': {1: 15, 2: 7.5, 3: 5, 4: 3.75},\n",
+    "    'falcon-40b': {2: 45, 3: 30, 4: 22.5}\n",
+    "}\n",
+    "\n",
+    "df_grouped = df_filtered.groupby(['model', 'num_gpus']).inference_time.mean().reset_index()\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(12, 7))\n",
+    "\n",
+    "for model in df_grouped['model'].unique():\n",
+    "    subset = df_grouped[df_grouped['model'] == model]\n",
+    "    plt.plot(subset['num_gpus'], subset['inference_time'], marker='o', label=model)\n",
+    "\n",
+    "    # Annotate with mean inference time\n",
+    "    for i, row in subset.iterrows():\n",
+    "        # Displaying inference time\n",
+    "        plt.annotate(f\"{row['inference_time']:.2f}s\", \n",
+    "                     (row['num_gpus'], row['inference_time']),\n",
+    "                     textcoords=\"offset points\",\n",
+    "                     xytext=(0, 10),\n",
+    "                     ha='center')\n",
+    "        # Displaying GPU memory requirement\n",
+    "        memory = gpu_memory[model][row['num_gpus']]\n",
+    "        plt.annotate(f\"{memory}GB/GPU\", \n",
+    "                     (row['num_gpus'], row['inference_time']),\n",
+    "                     textcoords=\"offset points\",\n",
+    "                     xytext=(0, -15),\n",
+    "                     ha='center', \n",
+    "                     color='blue', fontsize=9, style='italic')\n",
+    "\n",
+    "plt.title('Inference Time by Number of GPUs (1 Process, 1 Node)')\n",
+    "plt.xlabel('Number of GPUs')\n",
+    "plt.ylabel('Average Inference Time')\n",
+    "plt.xticks(df_grouped['num_gpus'].unique())\n",
+    "plt.legend()\n",
+    "plt.grid(True, which='both', linestyle='--', linewidth=0.5)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/isehgal2/.local/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
+      "  if pd.api.types.is_categorical_dtype(vector):\n",
+      "/home/isehgal2/.local/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
+      "  if pd.api.types.is_categorical_dtype(vector):\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Filter the data for falcon-7b, 1 process, 1 node, 1 gpu\n",
+    "subset = df[(df['model'] == 'falcon-7b') & (df['num_processes'] == 1) & (df['num_nodes'] == 1) & (df['num_gpus'] == 1)]\n",
+    "\n",
+    "# Scatter plot\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.scatterplot(data=subset, x='prompt_len', y='inference_time', alpha=0.7)\n",
+    "plt.title('Relationship between Prompt Length and Inference Time for falcon-7b (1 GPU, 1 Process, 1 Node)')\n",
+    "plt.xlabel('Prompt Length')\n",
+    "plt.ylabel('Inference Time')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/isehgal2/.local/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
+      "  if pd.api.types.is_categorical_dtype(vector):\n",
+      "/home/isehgal2/.local/lib/python3.10/site-packages/seaborn/_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
+      "  if pd.api.types.is_categorical_dtype(vector):\n"
+     ]
+    },
+    {
+     "data": {
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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Filter the data for falcon-4b, 2 gpus, 1 process, 1 node\n",
+    "subset = df[(df['model'] == 'falcon-40b') & (df['num_processes'] == 1) & (df['num_nodes'] == 1) & (df['num_gpus'] == 2)]\n",
+    "\n",
+    "# Scatter plot\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.scatterplot(data=subset, x='prompt_len', y='inference_time', alpha=0.7)\n",
+    "plt.title('Relationship between Prompt Length and Inference Time for falcon-40b (2 GPUs, 1 Process, 1 Node)')\n",
+    "plt.xlabel('Prompt Length')\n",
+    "plt.ylabel('Inference Time')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "deepspeed_df = pd.read_csv(\"benchmark-deepspeed.csv\")\n",
+    "deepspeed_df['timestamp'] = pd.to_datetime(deepspeed_df['timestamp'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>model</th>\n",
+       "      <th>num_nodes</th>\n",
+       "      <th>num_processes</th>\n",
+       "      <th>num_gpus</th>\n",
+       "      <th>num_prompts</th>\n",
+       "      <th>data_parallelism</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>falcon-7b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>falcon-7b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>falcon-40b</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>none</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        model  num_nodes  num_processes  num_gpus  num_prompts  \\\n",
+       "0   falcon-7b          1              1         1            1   \n",
+       "1   falcon-7b          1              2         2            1   \n",
+       "2  falcon-40b          1              1         4            1   \n",
+       "\n",
+       "  data_parallelism  \n",
+       "0             none  \n",
+       "1             none  \n",
+       "2             none  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "unique_experiments = deepspeed_df[['model', 'num_nodes', 'num_processes', 'num_gpus', 'num_prompts', 'data_parallelism']].drop_duplicates().reset_index(drop=True)\n",
+    "unique_experiments_sorted = unique_experiments.sort_values(by=['model'], ascending=False).reset_index(drop=True)\n",
+    "unique_experiments_sorted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "combined_df = pd.concat([df, deepspeed_df], ignore_index=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Filter for falcon-7b, 1 process, 1 node, and 1 GPU\n",
+    "df_filtered = combined_df[(combined_df['model'] == 'falcon-7b') & \n",
+    "                          (combined_df['num_processes'] == 1) & \n",
+    "                          (combined_df['num_nodes'] == 1) & \n",
+    "                          (combined_df['num_gpus'] == 1)]\n",
+    "\n",
+    "# Group by model and parallelism type\n",
+    "df_grouped = df_filtered.groupby(['model', 'model_parallelism']).inference_time.mean().reset_index()\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "\n",
+    "# Plotting each group\n",
+    "for parallelism in df_grouped['model_parallelism'].unique():\n",
+    "    subset = df_grouped[df_grouped['model_parallelism'] == parallelism]\n",
+    "    plt.bar(subset['model_parallelism'], subset['inference_time'], label=f\"falcon-7b ({parallelism})\")\n",
+    "    \n",
+    "    # Annotate with mean inference time\n",
+    "    for i, row in subset.iterrows():\n",
+    "        plt.annotate(f\"{row['inference_time']:.2f}s\", \n",
+    "                     (i, row['inference_time']),\n",
+    "                     textcoords=\"offset points\",\n",
+    "                     xytext=(0, 10),\n",
+    "                     ha='center')\n",
+    "\n",
+    "plt.title('Inference Time for falcon-7b (1 Process, 1 Node, 1 GPU)')\n",
+    "plt.xlabel('Optimization Type')\n",
+    "plt.ylabel('Average Inference Time')\n",
+    "plt.legend(loc='lower right')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Filter for falcon-7b, 1 process, 1 node, and 1 GPU\n",
+    "df_filtered = combined_df[(combined_df['model'] == 'falcon-7b') & \n",
+    "                          (combined_df['num_processes'] == 2) & \n",
+    "                          (combined_df['num_nodes'] == 1) & \n",
+    "                          (combined_df['num_gpus'] == 2)]\n",
+    "\n",
+    "# Group by model and parallelism type\n",
+    "df_grouped = df_filtered.groupby(['model', 'model_parallelism']).inference_time.mean().reset_index()\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "\n",
+    "# Plotting each group\n",
+    "for parallelism in df_grouped['model_parallelism'].unique():\n",
+    "    subset = df_grouped[df_grouped['model_parallelism'] == parallelism]\n",
+    "    plt.bar(subset['model_parallelism'], subset['inference_time'], label=f\"falcon-7b ({parallelism})\")\n",
+    "    \n",
+    "    # Annotate with mean inference time\n",
+    "    for i, row in subset.iterrows():\n",
+    "        plt.annotate(f\"{row['inference_time']:.2f}s\", \n",
+    "                     (i, row['inference_time']),\n",
+    "                     textcoords=\"offset points\",\n",
+    "                     xytext=(0, 10),\n",
+    "                     ha='center')\n",
+    "\n",
+    "plt.title('Inference Time for falcon-7b (2 Process, 1 Node, 2 GPU)')\n",
+    "plt.xlabel('Optimization Type')\n",
+    "plt.ylabel('Average Inference Time')\n",
+    "plt.legend(loc='lower right')\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Filter for falcon-40b, 1 process, 1 node, and 1 GPU\n",
+    "df_filtered = combined_df[(combined_df['model'] == 'falcon-40b') & \n",
+    "                          (combined_df['num_processes'] == 1) & \n",
+    "                          (combined_df['num_nodes'] == 1) & \n",
+    "                          (combined_df['num_gpus'] == 4)]\n",
+    "\n",
+    "# Group by model and parallelism type\n",
+    "df_grouped = df_filtered.groupby(['model', 'model_parallelism']).inference_time.mean().reset_index()\n",
+    "\n",
+    "# Plot\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "\n",
+    "# Plotting each group\n",
+    "for parallelism in df_grouped['model_parallelism'].unique():\n",
+    "    subset = df_grouped[df_grouped['model_parallelism'] == parallelism]\n",
+    "    plt.bar(subset['model_parallelism'], subset['inference_time'], label=f\"falcon-7b ({parallelism})\")\n",
+    "    \n",
+    "    # Annotate with mean inference time\n",
+    "    for i, row in subset.iterrows():\n",
+    "        plt.annotate(f\"{row['inference_time']:.2f}s\", \n",
+    "                     (i, row['inference_time']),\n",
+    "                     textcoords=\"offset points\",\n",
+    "                     xytext=(0, 10),\n",
+    "                     ha='center')\n",
+    "\n",
+    "plt.title('Inference Time for falcon-40b (1 Process, 1 Node, 4 GPU)')\n",
+    "plt.xlabel('Optimization Type')\n",
+    "plt.ylabel('Average Inference Time')\n",
+    "plt.legend(loc='lower right')\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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t5edk48aNxoULF4wzZ84Yy5YtMwoWLGg4ODgYZ8+eNQzjf9+jQ4YMMVt/1apVhiTjo48+Mmtv06aNYWVlZfz111+GYRjG8ePHDWtra+Pll182kpKSzPqmfI3//fdfw9nZ2ejWrZvZ8qioKMPJycnUfuXKlft+TqxcudKQZOzduzfD5yKj9u7da0gy5s+fn+F17v6Z2bZtmyHJmDx5sml58eLFjcDAQNP7jJ7XlJ+Lnj17mvVr3759qu+Frl27GoULFzYuXrxo1rddu3aGk5NTmj+/GfHuu+8a3t7epp/x/x5LeqZNm2ZIMlatWmXWfvv2bePChQtmr7v/n1S8eHGjUaNGpmW//fab0a5dO0OS0bt3b7N+6dVxr69ho0aNjNKlS2fk0IGnGpeXA8iUGTNmKDQ01Oz13wcglStXTqNGjdIXX3yhgIAAXbx4UQsXLkzznupOnTopf/78pvdt2rRR4cKF9fPPP0u68+Cl48ePq3379rp06ZIuXryoixcv6tq1a2rYsKHCwsKUnJxsts3M3KPWsGFDs8tNU6ZACQoKMqsrpf3vv//Osrrq1KmjS5cupXrabFbKly+fpDujKw/C29tbAQEBqdrvHnFKufqhXr16+vvvvxUXF5fp/ezbt08xMTHq2bOn2b3egYGB8vX11U8//ZRqnbTOZ8rXJ7NSvt/69+9v1p7y8KH/7j+985IZd5/Df//9VxcvXlSdOnV0/fp1HT16NN31vvvuO1lZWZkuW79byiWnmT2eMmXKqE6dOqb3rq6uKlWqVIbO56VLlzRixAgNHz78nvdI37hxQ9KdS4//y97e3rT8bilXTaTo3bu3pP8d371qKlCgwH1rf1D+/v5ydXVV0aJF1a5dO+XLl08rV67UM888Y9bvv1dd/Pzzz8qVK5f69Olj1j5gwAAZhmH6LF21apWSk5M1YsQIWVub/6qW8jUODQ1VbGysXnvtNdPnz8WLF5UrVy5Vr15dW7ZskSTT8wu2bt2qK1eupHk8KVeRrFmzRomJiQ92Uiykbt26atCggSZMmJDm94iU8fOa8n3z337/HbU2DEPfffedmjdvLsMwzM5vQECA4uLidODAgUwfy59//qlp06Zp4sSJaf4c3EvK/ydSPtNTHDx4UK6urmavS5cumfXZsGGDaVmFChW0YsUKdezY0XSV1cMoUKDAQ0/tBzwNuLwcQKa88MILGXqQ2sCBA7Vs2TLt2bNHY8eOVZkyZdLs99xzz5m9t7KyUokSJUz3Gh4/flySFBwcnO6+4uLizH7BTuvp6ukpVqyY2XsnJydJUtGiRdNsT/ml9UHq+u++UpZduXLF7B7XrJQyFdPdf0DIjPTO5c6dO/XBBx8oPDw81ZQ+cXFxpvOVUadOnZKkNC/T9vX11Y4dO8zaUu5jvluBAgXSDRUZ2b+1tXWqJ117eHjI2dnZVF+KzHyPpefw4cMaNmyYNm/enOoPL/f6w8WJEyfk6ekpFxeXdPtk9nj++70pmZ/PpKQkXbhwwWy5i4uLbG1tNWzYMLm4uJgCcXpS/sjw33vKJaX7ILr/fj74+PjI2to6zecr/Jdxn1tLHsaMGTNUsmRJ2djYyN3dXaVKlUoVjm1sbFSkSBGztlOnTsnT0zPVz2Pp0qVNy6U7X2Nra+t0Pzel/30GpdxP/l8pnyl2dnYaP368BgwYIHd3d9WoUUPNmjVTp06dTJc316tXT0FBQRo1apSmTJmi+vXrq1WrVmrfvn2mw6EljBw5UvXq1dPs2bPTvIw5o+c15efiv7ft/Pdz58KFC4qNjdXcuXPTneIv5QGJmfHOO++oZs2aCgoKyvS6Kcf23+n1SpQoYbqFaNGiRVq8eHGqdatXr66PPvpIVlZWypMnj0qXLv1AD3ZM6z5ywzDSbAdgjtANwCL+/vtv0y+FKQ8mexApo8UTJ05UxYoV0+zz37/8Z+Ypt+ndG5dee8ov8g9S1/22aQmHDh2Sm5ub6Rfw9H45Su/hXWmdyxMnTqhhw4by9fXV5MmTVbRoUdna2urnn3/WlClTUo3wW8LD3tOYnoz+8viwT1KOjY1VvXr15OjoqNGjR8vHx0f29vY6cOCABg8enGXnMKPHc7/vzTNnzqT6Q8OWLVv0zDPPaO7cuZo6dar++ecf07KbN28qMTFRJ0+elKOjo1xcXFS4cGFJ0vnz51Pt5/z58/L09Myy4ylYsOAD/wEmIzLyx0c7O7tUQTwrpXyPLF68OM17g+++sqhv375q3ry5Vq1apfXr12v48OEaN26cNm/erEqVKsnKykrffvutdu3apdWrV2v9+vV644039Mknn2jXrl2pPssetbp166p+/fqaMGHCQz1tO6NSzu3rr7+e7h9WU57NkFGbN2/WunXr9P3335v90ej27du6ceOGTp48KRcXl3T/AOvr6yvpzmd6y5YtTe358uUzPdDsv3+cTFGoUKE0Hyp4t/SuNpFk+sNqWjNOXLlyRYUKFbrntgEQugFYQHJysjp37ixHR0f17dvXNPd069atU/VNCeYpDMPQX3/9ZfqFJmVEwtHR8b6/NDxKlqorK0cMwsPDdeLECbOpYlJG12NjY81GOv478nkvq1evVkJCgn788UezEdKUy1nvltHjSXng1bFjx1KN3B07dsziD8QqXry4kpOTdfz4cdPomHTnYUqxsbFZvv+tW7fq0qVL+v7771W3bl1Te0aeJuzj46P169fr8uXL6Y52Z/XxeHh4pHogX4UKFfTbb78pOTlZffr0SXXJrnTnioB33nlHU6dOVbly5WRjY6N9+/apbdu2pj63bt1SRESEWVuK48ePm4X9v/76S8nJyfd9Armvr6++++67TB3jo1C8eHFt3LhR//77r9mobMrtBClfFx8fHyUnJ+uPP/5I9496KZ9Bbm5uGfoM8vHx0YABAzRgwAAdP35cFStW1CeffKKvvvrK1KdGjRqqUaOGxowZo6VLl6pDhw5atmyZ3nzzzQc95CwzcuRI1a9fP82ZAjJ6XlN+Lk6cOGE2un3s2DGz7aU82TwpKSnLPt9Pnz4tSWn+f/DcuXPy9vbWlClT0n1AW506deTk5KRly5Zp6NChWf4HneLFi+uPP/5Ic1nK+UnrcyMyMjJLpqQEnnTc0w0gy02ePFm//PKL5s6dqw8//FA1a9ZUjx490rzva9GiRWb3G3/77bc6f/68mjRpIkmqUqWKfHx8NGnSpFSX1UlKdcnro2KpuvLmzavY2NiHrO5OiO7cubNsbW01cOBAU3vKL+phYWGmtpRpyjIqZVT07hH6uLg4zZ8/P1XfjB5P1apV5ebmptmzZ5tdfrx27VodOXIkzacLZ6WmTZtKUqrpriZPnixJWb7/tM7hrVu3NHPmzPuuGxQUJMMwNGrUqFTLUraX1cdjb28vf39/s1eBAgVUrlw5rVy5MtWrbNmyKlasmFauXKmuXbtKunOLhr+/v7766iuzn/nFixfr6tWreuWVV1Ltd8aMGWbvP/30U0kyfT6kx8/PT1euXHnge/wtpWnTpkpKStJnn31m1j5lyhRZWVmZjqtVq1aytrbW6NGjU131kPI1DggIkKOjo8aOHZvmfdgpn0HXr19PNc2aj4+P8ufPb/pZu3LlSqorblLCflq3A2SHevXqqX79+ho/fnyq48noeU357/Tp0836/ffnJFeuXAoKCtJ3332nQ4cOparlQT7fX3zxxTR/VlxdXVW1alWtXLlSzZs3T3f9PHnyaNCgQTp06JCGDBmS5hVSD3PVVNOmTXX27FmtWrXKrD0hIcE000blypXNlsXFxenEiROmGSAApI+RbgCZsnbt2jQf8lSzZk09++yzOnLkiIYPH67OnTubfoFYsGCBKlasqJ49e6aai9fFxUW1a9dWly5dFB0dralTp6pEiRLq1q2bJMna2lpffPGFmjRporJly6pLly565plndO7cOW3ZskWOjo5avXq15Q/8PyxVV5UqVbRx40ZNnjxZnp6e8vb2Nj3ELT0HDhzQV199peTkZMXGxmrv3r2mh20tXrzY7DLIRo0aqVixYuratasGDhyoXLlyad68eXJ1dTWNxNxPo0aNZGtrq+bNm+utt97S1atX9fnnn8vNzS3VpcNVqlTRrFmz9NFHH6lEiRJyc3NL8x7U3Llza/z48erSpYvq1aun1157zTRlmJeXl8Wno6lQoYKCg4M1d+5c06Xfe/bs0cKFC9WqVSs1aNAgS/dXs2ZNFShQQMHBwerTp4/pa5WRX5obNGigjh07avr06Tp+/LgaN26s5ORkbd++XQ0aNFCvXr0e2fEUKlRIrVq1StWeEmL+u2zMmDGqWbOm6tWrp+7du+vs2bP65JNP1KhRIzVu3DjVdiIjI9WiRQs1btxY4eHhpqme7jeyFhgYKBsbG23cuNE0/V6KxYsX69SpU6ZLZsPCwvTRRx9Jkjp27GjRqyqaN2+uBg0a6P3339fJkydVoUIFbdiwQT/88IP69u1r+qNYiRIl9P777+vDDz9UnTp11Lp1a9nZ2Wnv3r3y9PTUuHHj5OjoqFmzZqljx46qXLmy2rVrZ/o5/umnn1SrVi199tln+vPPP9WwYUO1bdtWZcqUkY2NjVauXKno6Gi1a9dOkrRw4ULNnDlTL7/8snx8fPTvv//q888/l6Ojo+kPONKd+ccXLlyoyMjI+15t8Nlnnyk2NtZ028Hq1atN82H37t070899kKQPPvggze/djJ7XihUr6rXXXtPMmTMVFxenmjVratOmTfrrr79SbfPjjz/Wli1bVL16dXXr1k1lypTR5cuXdeDAAW3cuFGXL1829a1fv762bdt2z5/fYsWKpfnshL59+8rd3T3Nn6P/GjJkiI4cOaKJEydqw4YNCgoKUpEiRXTlyhUdOHBAK1askJubW5qXgd9P9+7dNW/ePL3yyit64403VKlSJV26dEnLly/XoUOHtGjRItna2pqts3HjRhmGYXa5O4B0PNJnpQPIse41ZZj+fyqR27dvG9WqVTOKFClixMbGmq2fMt3J8uXLDcP435RRX3/9tTF06FDDzc3NcHBwMAIDA41Tp06l2v+vv/5qtG7d2ihYsKBhZ2dnFC9e3Gjbtq2xadMmU5/0pma6e9ndJBkhISFmbelNw5VS74oVK7KsrrSm6Tp69KhRt25dw8HBwZB0z+nDUmpNednY2BguLi5G9erVjaFDh6Z5Hg3DMPbv329Ur17dsLW1NYoVK2ZMnjw53SnD0ptC5scffzSef/55w97e3vDy8jLGjx9vzJs3L9U2oqKijMDAQCN//vyGJNP0Yf+dMizF8uXLjUqVKhl2dnaGi4uL0aFDB9M0TCnSmvLLMNKfDu2/0ls/MTHRGDVqlOHt7W3kzp3bKFq0qDF06FCz6bvud17Skt7Xf+fOnUaNGjUMBwcHw9PT0xg0aJCxfv36VOflv1OGGcadaYImTpxo+Pr6Gra2toarq6vRpEkTY//+/Vl2PPXq1UtzureMSGvKsBTbt283atasadjb2xuurq5GSEiI2fR8hvG/c/bHH38Ybdq0MfLnz28UKFDA6NWrl9mUcvfSokULo2HDhmnWlt7n2H+/H/8r5efkflNrpfc9Zhh3pvrq16+f4enpaeTOndt47rnnjIkTJ5pN85Ri3rx5pp+HAgUKGPXq1TNCQ0PN+mzZssUICAgwnJycDHt7e8PHx8fo3LmzsW/fPsMwDOPixYtGSEiI4evra+TNm9dwcnIyqlevbnzzzTembRw4cMB47bXXjGLFihl2dnaGm5ub0axZM9M2UgQFBRkODg7GlStX7nn8hvG/qejSet39GZGWe32Wp3z9/vs9m9HzeuPGDaNPnz5GwYIFjbx58xrNmzc3zpw5k+b0cdHR0UZISIhRtGhRI3fu3IaHh4fRsGFDY+7cuWb9qlSpYjblXWZk9vPEMO5M8da0aVPD1dXVsLGxMZydnY3atWsbEydOTPX/3sxs/8qVK0a/fv1MnxmOjo5GgwYNjLVr16bZ/9VXXzVq166dqdqBp5WVYVjwCT4AkI6tW7eqQYMGWrFihdq0aZPd5QB4wmzfvl3169fX0aNHUz0FHQ/G3d1dnTp10sSJE7O7lMfGv//+KxcXF02dOjXVFHdPsqioKHl7e2vZsmWMdAMZwD3dAADgiVOnTh01atRIEyZMyO5SngiHDx/WjRs3NHjw4Owu5bESFhamZ555xnRL1NNi6tSpKl++PIEbyCBGugFkC0a6AQAA8DRgpBsAAAAAAAthpBsAAAAAAAthpBsAAAAAAAshdAMAAAAAYCE22V1ATpGcnKx//vlH+fPnl5WVVXaXAwAAAADIRoZh6N9//5Wnp6esrdMfzyZ0Z9A///yjokWLZncZAAAAAIDHyJkzZ1SkSJF0lxO6Myh//vyS7pxQR0fHbK4G2SE0NFS7du1SxYoV9frrr2vJkiVq1qyZaXmPHj0UExOjmTNnmtpsbW1VoEAB0/vKlSvLx8dHH3zwgRwcHDRz5kwtXbpUERERcnd3lyQ5OTlp5syZ8vf3N63n5OQke3v7dGsLCgpSdHS0pk6dqsTERPXs2VOVK1fWl19+KUmKj49XlSpVVL9+ffXv31+HDx9Wr169NG7cOHXp0iXLzhEAAADwtIiPj1fRokVNWTE9PL08g+Lj4+Xk5KS4uDhCN2RlZaWVK1eqVatWprbOnTsrNjZWq1atSnOdixcvytXVVWFhYapTp44k6d9//5Wjo6NCQ0NNITutbd/LkSNHVKZMGe3du1dVq1aVJK1bt05NmzbV2bNn5enpqVmzZun9999XVFSUbG1tJUlDhgzRqlWrdPToUUl35s0eNGiQDh8+rNy5c6ts2bJaunSpihcv/gBnCAAAAHiyZTQj8iA1IAtt3bpVbm5uKlWqlHr06KFLly6ZlhUsWFClSpXSokWLdO3aNd2+fVtz5syRm5ubqlSpYradkJAQFSpUSC+88ILmzZune/1tLDw8XM7OzqbALUn+/v6ytrbW7t27TX3q1q1rCtySFBAQoGPHjunKlSu6ffu2WrVqpXr16un3339XeHi4unfvzvMLAAAAgIfE5eVAFmncuLFat24tb29vnThxQu+9956aNGmi8PBw5cqVS1ZWVtq4caNatWql/Pnzy9raWm5ublq3bp3ZJeijR4/Wiy++qDx58mjDhg3q2bOnrl69qj59+qS536ioKLm5uZm12djYyMXFRVFRUaY+3t7eZn1SLmePioqSYRiKi4tTs2bN5OPjI0kqXbp0lp0bAAAA4GlF6AaySLt27Uz/Ll++vJ5//nn5+Pho69atatiwoQzDUEhIiNzc3LR9+3Y5ODjoiy++UPPmzbV3714VLlxYkjR8+HDTdipVqqRr165p4sSJ6YburODi4qLOnTsrICBAL730kvz9/dW2bVtTTQAAAAAeDJeXAxby7LPPqlChQvrrr78kSZs3b9aaNWu0bNky1apVS5UrV9bMmTPl4OCghQsXprud6tWr6+zZs0pISEhzuYeHh2JiYszabt++rcuXL8vDw8PUJzo62qxPyvuUPvPnz1d4eLhq1qyp5cuXq2TJktq1a9eDHTwAAAAASYRuwGLOnj2rS5cumUaLr1+/Lkmp5vCztrZWcnJyutuJiIhQgQIFZGdnl+ZyPz8/xcbGav/+/aa2zZs3Kzk5WdWrVzf1CQsLU2JioqlPaGioSpUqZXZpe6VKlTR06FD98ssvKleunJYuXZrJowYAAABwN0I3kEFXr15VRESEIiIiJEmRkZGKiIjQ6dOndfXqVQ0cOFC7du3SyZMntWnTJrVs2VIlSpRQQECApDvBt0CBAgoODtZvv/2mP//8UwMHDlRkZKQCAwMlSatXr9YXX3yhQ4cO6a+//tKsWbM0duxY9e7d21THnj175Ovrq3Pnzkm6c+9148aN1a1bN+3Zs0c7d+5Ur1691K5dO3l6ekqS2rdvL1tbW3Xt2lWHDx/W8uXLNW3aNPXv3990LEOHDlV4eLhOnTqlDRs26Pjx49zXDQAAADwk7ukGMmjfvn1q0KCB6X1KYA0ODtasWbP0+++/a+HChYqNjZWnp6caNWqkDz/80DRCXahQIa1bt07vv/++XnzxRSUmJqps2bL64YcfVKFCBUlS7ty5NWPGDPXr10+GYahEiRKaPHmyunXrZtrv9evXdezYMbNR6yVLlqhXr15q2LChrK2tFRQUpOnTp5uWOzk5acOGDQoJCVGVKlVUqFAhjRgxQt27d5ck5cmTR0ePHtXChQtNo/MhISF66623LHdCAQAAgKcA83RnEPN0AwAAAABSME83AAAAAADZjNANAAAAAICFELoBAAAAALAQQjcAAAAAABaSraE7LCxMzZs3l6enp6ysrLRq1apUfY4cOaIWLVrIyclJefPmVbVq1XT69GnT8ps3byokJEQFCxZUvnz5FBQUpOjoaLNtnD59WoGBgcqTJ4/c3Nw0cOBA3b5929KHBwAAAAB4ymVr6L527ZoqVKigGTNmpLn8xIkTql27tnx9fbV161b9/vvvGj58uOzt7U19+vXrp9WrV2vFihXatm2b/vnnH7Vu3dq0PCkpSYGBgbp165Z++eUXLVy4UAsWLNCIESMsfnwAAAAAgKfbYzNlmJWVlVauXKlWrVqZ2tq1a6fcuXNr8eLFaa4TFxcnV1dXLV26VG3atJEkHT16VKVLl1Z4eLhq1KihtWvXqlmzZvrnn3/k7u4uSZo9e7YGDx6sCxcuyNbWNkP1MWUYAAAAACBFjp8yLDk5WT/99JNKliypgIAAubm5qXr16maXoO/fv1+JiYny9/c3tfn6+qpYsWIKDw+XJIWHh6t8+fKmwC1JAQEBio+P1+HDhx/Z8QAAAAAAnj6PbeiOiYnR1atX9fHHH6tx48basGGDXn75ZbVu3Vrbtm2TJEVFRcnW1lbOzs5m67q7uysqKsrU5+7AnbI8ZVl6EhISFB8fb/YCAAAAACAzbLK7gPQkJydLklq2bKl+/fpJkipWrKhffvlFs2fPVr169Sy6/3HjxmnUqFEW3QcAAAAA4Mn22I50FypUSDY2NipTpoxZe+nSpU1PL/fw8NCtW7cUGxtr1ic6OloeHh6mPv99mnnK+5Q+aRk6dKji4uJMrzNnzjzsIQEAAAAAnjKPbei2tbVVtWrVdOzYMbP2P//8U8WLF5ckValSRblz59amTZtMy48dO6bTp0/Lz89PkuTn56eDBw8qJibG1Cc0NFSOjo6pAv3d7Ozs5OjoaPYCAAAAACAzsvXy8qtXr+qvv/4yvY+MjFRERIRcXFxUrFgxDRw4UK+++qrq1q2rBg0aaN26dVq9erW2bt0qSXJyclLXrl3Vv39/ubi4yNHRUb1795afn59q1KghSWrUqJHKlCmjjh07asKECYqKitKwYcMUEhIiOzu77DhsAAAAAMBTIlunDNu6dasaNGiQqj04OFgLFiyQJM2bN0/jxo3T2bNnVapUKY0aNUotW7Y09b1586YGDBigr7/+WgkJCQoICNDMmTPNLh0/deqUevTooa1btypv3rwKDg7Wxx9/LBubjP/NIadMGeY15KfsLgFABpz8ODC7SwAAAMBDyGhGfGzm6X7cEboBZCVCNwAAQM6W4+fpBgAAAAAgpyN0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAFkiLCxMzZs3l6enp6ysrLRq1ap0+7799tuysrLS1KlTzdrHjBmjmjVrKk+ePHJ2dk5zXSsrq1SvZcuW3bO2y5cvq0OHDnJ0dJSzs7O6du2qq1evmvX5/fffVadOHdnb26to0aKaMGFCRg4buCdCNwAAAIAsce3aNVWoUEEzZsy4Z7+VK1dq165d8vT0TLXs1q1beuWVV9SjR497bmP+/Pk6f/686dWqVat79u/QoYMOHz6s0NBQrVmzRmFhYerevbtpeXx8vBo1aqTixYtr//79mjhxokaOHKm5c+fec7vA/dhkdwEAAAAAngxNmjRRkyZN7tnn3Llz6t27t9avX6/AwMBUy0eNGiVJWrBgwT234+zsLA8PjwzVdeTIEa1bt0579+5V1apVJUmffvqpmjZtqkmTJsnT01NLlizRrVu3NG/ePNna2qps2bKKiIjQ5MmTTeF869atGjRokA4fPqzcuXOrbNmyWrp0qYoXL56hOvB0YqQbAAAAwCORnJysjh07auDAgSpbtuxDbSskJESFChXSCy+8oHnz5skwjHT7hoeHy9nZ2RS4Jcnf31/W1tbavXu3qU/dunVla2tr6hMQEKBjx47pypUrun37tlq1aqV69erp999/V3h4uLp37y4rK6uHOg48+RjpBgAAAPBIjB8/XjY2NurTp89DbWf06NF68cUXlSdPHm3YsEE9e/bU1atX091uVFSU3NzczNpsbGzk4uKiqKgoUx9vb2+zPu7u7qZlhmEoLi5OzZo1k4+PjySpdOnSD3UceDoQugEAAABY3P79+zVt2jQdOHDgoUeHhw8fbvp3pUqVdO3aNU2cOPGhw/y9uLi4qHPnzgoICNBLL70kf39/tW3bVoULF7bYPvFk4PJyAAAAABa3fft2xcTEqFixYrKxsZGNjY1OnTqlAQMGyMvL66G2Xb16dZ09e1YJCQlpLvfw8FBMTIxZ2+3bt3X58mXTfeEeHh6Kjo4265PyPqXP/PnzFR4erpo1a2r58uUqWbKkdu3a9VC148lH6AYAAABgcR07dtTvv/+uiIgI08vT01MDBw7U+vXrH2rbERERKlCggOzs7NJc7ufnp9jYWO3fv9/UtnnzZiUnJ6t69eqmPmFhYUpMTDT1CQ0NValSpVSgQAFTW6VKlTR06FD98ssvKleunJYuXfpQtePJR+gGACCHut98uCNHjpSvr6/y5s2rAgUKyN/f3/TAoBR//vmnWrZsqUKFCsnR0VG1a9fWli1bzPps2rRJNWvWVP78+eXh4aHBgwfr9u3b96zt5s2bCgkJUcGCBZUvXz4FBQWlGkE6ffq0AgMDlSdPHrm5uWngwIH33S6Ax9vVq1dNgVqSIiMjFRERodOnT6tgwYIqV66c2St37tzy8PBQqVKlTNs4ffq0aZ2kpCTT9lLm1F69erW++OILHTp0SH/99ZdmzZqlsWPHqnfv3qZt7NmzR76+vjp37pykO/deN27cWN26ddOePXu0c+dO9erVS+3atTNNW9a+fXvZ2tqqa9euOnz4sJYvX65p06apf//+pmMZOnSowsPDderUKW3YsEHHjx/nvm7cF6EbAIAc6n7z4ZYsWVKfffaZDh48qB07dsjLy0uNGjXShQsXTH2aNWum27dva/Pmzdq/f78qVKigZs2amR4s9Ntvv6lp06Zq3Lixfv31Vy1fvlw//vijhgwZcs/a+vXrp9WrV2vFihXatm2b/vnnH7Vu3dq0PCkpSYGBgbp165Z++eUXLVy4UAsWLNCIESOy4MwAyC779u1TpUqVVKlSJUlS//79ValSpUz9bI8YMUKVKlXSBx98oKtXr5q2t2/fPklS7ty5NWPGDPn5+alixYqaM2eOJk+erA8++MC0jevXr+vYsWNmo9ZLliyRr6+vGjZsqKZNm6p27dpmc3A7OTlpw4YNioyMVJUqVTRgwACNGDHCNF1Ynjx5dPToUQUFBalkyZLq3r27QkJC9NZbbz3UOcOTz8q417P1YRIfHy8nJyfFxcXJ0dExu8tJl9eQn7K7BAAZcPLj1POSAg/DyspKK1euVKtWrdLtk/L/so0bN6phw4a6ePGiXF1dFRYWpjp16kiS/v33Xzk6Oio0NFT+/v567733FBoaqr1795q2s3r1arVt21YxMTHKnz9/qv3ExcXJ1dVVS5cuVZs2bSRJR48eVenSpRUeHq4aNWpo7dq1atasmf755x/T04Fnz56twYMH68KFC7K1tdVvv/2mvn37at++fbKystJzzz2nOXPmmE35AwBAdsloRmSkGwCAp8CtW7c0d+5cOTk5qUKFCpKkggULqlSpUlq0aJGuXbum27dva86cOXJzc1OVKlUkSQkJCbK3tzfbloODg27evGl2b+Td9u/fr8TERPn7+5vafH19VaxYMYWHh0u6Mx9u+fLlTYFbujMfbnx8vA4fPixJ6tChg4oUKaK9e/dq//79GjJkiHLnzp11JwUAgEeAKcMAAHiCrVmzRu3atdP169dVuHBhhYaGqlChQpLujI5v3LhRrVq1Uv78+WVtbS03NzetW7fO9NCggIAATZ06VV9//bXatm2rqKgojR49WpJ0/vz5NPcZFRUlW1tbOTs7m7W7u7ubzYd7d+BOWZ6yTLpzX+fAgQPl6+srSXruueey4IwAAPBoMdINAMATrEGDBoqIiNAvv/yixo0bmy4LlyTDMBQSEiI3Nzdt375de/bsUatWrdS8eXNToG7UqJEmTpyot99+W3Z2dipZsqSaNm0qSbK2tuyvEf3799ebb74pf39/ffzxxzpx4oRF9wcAgCUQugEAeILlzZtXJUqUUI0aNfTll1/KxsZGX375paQ70+WsWbNGy5YtU61atVS5cmXNnDlTDg4OWrhwoWkb/fv3V2xsrE6fPq2LFy+qZcuWkqRnn302zX16eHjo1q1bio2NNWuPjo7O1Hy4I0eO1OHDhxUYGKjNmzerTJkyWrly5cOfFAAAHiFCNwAAT5Hk5GQlJCRIuvN0Xyn1iLW1tbWSk5PN2qysrOTp6SkHBwd9/fXXKlq0qCpXrpzmPqpUqaLcuXNr06ZNprZjx47p9OnT8vPzk3RnPtyDBw+aRt2lO/PhOjo6qkyZMqa2kiVLql+/ftqwYYNat26t+fPnP8TRAwDw6HFPNwAAOdTVq1f1119/md6nzIfr4uKiggULasyYMWrRooUKFy6sixcvasaMGTp37pxeeeUVSXeCb4ECBRQcHKwRI0bIwcFBn3/+uSIjIxUY+L8n7E+cOFGNGzeWtbW1vv/+e3388cf65ptvlCtXLknSuXPn1LBhQy1atEgvvPCCnJyc1LVrV/Xv318uLi5ydHRU79695efnpxo1aki6c9l6mTJl1LFjR02YMEFRUVEaNmyYQkJCZGdnpxs3bmjgwIFq06aNvL29dfbsWe3du1dBQUGP8AwDAPDwCN0AAORQ+/btU4MGDUzv+/fvL0kKDg7W7NmzdfToUS1cuFAXL15UwYIFVa1aNW3fvl1ly5aVJBUqVEjr1q3T+++/rxdffFGJiYkqW7asfvjhB9MTziVp7dq1GjNmjBISElShQgX98MMPatKkiWl5YmKijh07Zho5l6QpU6bI2tpaQUFBSkhIUEBAgGbOnGlanitXLq1Zs0Y9evSQn5+f8ubNq+DgYNND2nLlyqVLly6pU6dOio6OVqFChdS6dWuNGjXKMicTAAALYZ7uDGKebgBZiXm6AQAAcjbm6QYAAAAAIJsRugEAAAAAsBBCNwAAAAAAFkLoBgAAAADAQgjdAAAAAABYSLZOGRYWFqaJEydq//79On/+vFauXKlWrVql2fftt9/WnDlzNGXKFPXt29fUfvnyZfXu3VurV682TU0ybdo05cuXz9Tn999/V0hIiPbu3StXV1f17t1bgwYNsvDRAQAA4HFUfmH57C4BQAYcDD6Y3SVkiWwd6b527ZoqVKigGTNm3LPfypUrtWvXLnl6eqZa1qFDBx0+fFihoaFas2aNwsLC1L17d9Py+Ph4NWrUSMWLF9f+/fs1ceJEjRw5UnPnzs3y4wEAAAAA4G7ZOtLdpEkTNWnS5J59zp07p969e2v9+vUKDDSf1/bIkSNat26d9u7dq6pVq0qSPv30UzVt2lSTJk2Sp6enlixZolu3bmnevHmytbVV2bJlFRERocmTJ5uFcwAAAAAAstpjfU93cnKyOnbsqIEDB6ps2bKploeHh8vZ2dkUuCXJ399f1tbW2r17t6lP3bp1ZWtra+oTEBCgY8eO6cqVK+nuOyEhQfHx8WYvAAAAAAAy47EO3ePHj5eNjY369OmT5vKoqCi5ubmZtdnY2MjFxUVRUVGmPu7u7mZ9Ut6n9EnLuHHj5OTkZHoVLVr0YQ4FAAAAAPAUemxD9/79+zVt2jQtWLBAVlZWj3z/Q4cOVVxcnOl15syZR14DAAAAACBne2xD9/bt2xUTE6NixYrJxsZGNjY2OnXqlAYMGCAvLy9JkoeHh2JiYszWu337ti5fviwPDw9Tn+joaLM+Ke9T+qTFzs5Ojo6OZi8AAAAAADLjsQ3dHTt21O+//66IiAjTy9PTUwMHDtT69eslSX5+foqNjdX+/ftN623evFnJycmqXr26qU9YWJgSExNNfUJDQ1WqVCkVKFDg0R4UAAAAAOCpkq1PL7969ar++usv0/vIyEhFRETIxcVFxYoVU8GCBc36586dWx4eHipVqpQkqXTp0mrcuLG6deum2bNnKzExUb169VK7du1M04u1b99eo0aNUteuXTV48GAdOnRI06ZN05QpUx7dgQLA02ykU3ZXACAjRsZldwUA8ETK1tC9b98+NWjQwPS+f//+kqTg4GAtWLAgQ9tYsmSJevXqpYYNG8ra2lpBQUGaPn26abmTk5M2bNigkJAQValSRYUKFdKIESOYLgwAAAAAYHHZGrrr168vwzAy3P/kyZOp2lxcXLR06dJ7rvf8889r+/btmS0PAAAAAICH8tje0w0AAAAAQE5H6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEKyNXSHhYWpefPm8vT0lJWVlVatWmValpiYqMGDB6t8+fLKmzevPD091alTJ/3zzz9m27h8+bI6dOggR0dHOTs7q2vXrrp69apZn99//1116tSRvb29ihYtqgkTJjyKwwMAAAAAPOWyNXRfu3ZNFSpU0IwZM1Itu379ug4cOKDhw4frwIED+v7773Xs2DG1aNHCrF+HDh10+PBhhYaGas2aNQoLC1P37t1Ny+Pj49WoUSMVL15c+/fv18SJEzVy5EjNnTvX4scHAAAAAHi62WTnzps0aaImTZqkuczJyUmhoaFmbZ999pleeOEFnT59WsWKFdORI0e0bt067d27V1WrVpUkffrpp2ratKkmTZokT09PLVmyRLdu3dK8efNka2ursmXLKiIiQpMnTzYL5wAAAAAAZLUcdU93XFycrKys5OzsLEkKDw+Xs7OzKXBLkr+/v6ytrbV7925Tn7p168rW1tbUJyAgQMeOHdOVK1fS3VdCQoLi4+PNXgAAAAAAZEaOCd03b97U4MGD9dprr8nR0VGSFBUVJTc3N7N+NjY2cnFxUVRUlKmPu7u7WZ+U9yl90jJu3Dg5OTmZXkWLFs3KwwEAAAAAPAVyROhOTExU27ZtZRiGZs2a9Uj2OXToUMXFxZleZ86ceST7BQAAAAA8ObL1nu6MSAncp06d0ubNm02j3JLk4eGhmJgYs/63b9/W5cuX5eHhYeoTHR1t1iflfUqftNjZ2cnOzi6rDgMAAAAA8BR6rEe6UwL38ePHtXHjRhUsWNBsuZ+fn2JjY7V//35T2+bNm5WcnKzq1aub+oSFhSkxMdHUJzQ0VKVKlVKBAgUezYEAAAAAAJ5K2Rq6r169qoiICEVEREiSIiMjFRERodOnTysxMVFt2rTRvn37tGTJEiUlJSkqKkpRUVG6deuWJKl06dJq3LixunXrpj179mjnzp3q1auX2rVrJ09PT0lS+/btZWtrq65du+rw4cNavny5pk2bpv79+2fXYQMAAAAAnhLZenn5vn371KBBA9P7lCAcHByskSNH6scff5QkVaxY0Wy9LVu2qH79+pKkJUuWqFevXmrYsKGsra0VFBSk6dOnm/o6OTlpw4YNCgkJUZUqVVSoUCGNGDGC6cIAAAAAABaXraG7fv36Mgwj3eX3WpbCxcVFS5cuvWef559/Xtu3b890fQAAAAAAPIzH+p5uAAAAAAByMkI3AAAAAAAWQugGAAAAAMBCCN0AAAAAAFgIoRsAAAAAAAshdAMAAAAAYCGEbgAAAAAALITQDQAAAACAhRC6AQAAAACwEEI3AAAAAAAWQugGAAAAAMBCCN0AAAAAAFgIoRsAAAAAAAshdAMAAAAAYCGEbgAAAAAALITQDQAAAACAhRC6AQAAAACwEEI3AAAAAAAWQugGAAAAAMBCCN0AAAAAAFgIoRsAAAAAAAshdAMAAAAAYCGEbgAAAAAALITQDQAAAACAhRC6AQAAAACwEEI3AAAAAAAWQugGAAAAAMBCCN0AAAAAAFgIoRsAAAAAAAshdAMAAAAAYCGEbgAAAAAALITQDQAAAACAhRC6AQAAAACwEEI3AAAAAAAWQugGAAAAAMBCCN0AAAAAAFgIoRsAAAAAAAshdAMAAAAAYCGEbgAAAAAALITQDQAAAACAhTxU6E5ISMiqOgAAAAAAeOJkKnSvXbtWwcHBevbZZ5U7d27lyZNHjo6OqlevnsaMGaN//vnHUnUCAAAAAJDjZCh0r1y5UiVLltQbb7whGxsbDR48WN9//73Wr1+vL774QvXq1dPGjRv17LPP6u2339aFCxcsXTcAAAAAAI89m4x0mjBhgqZMmaImTZrI2jp1Tm/btq0k6dy5c/r000/11VdfqV+/fllbKQAAAAAAOUyGQnd4eHiGNvbMM8/o448/fqiCAAAAAAB4Ujz008uTkpIUERGhK1euZEU9AAAAAAA8MTIduvv27asvv/xS0p3AXa9ePVWuXFlFixbV1q1bs7o+AAAAAAByrEyH7m+//VYVKlSQJK1evVqRkZE6evSo+vXrp/fffz/LCwQAAAAAIKfKdOi+ePGiPDw8JEk///yzXnnlFdOTzQ8ePJjlBQIAAAAAkFNlOnS7u7vrjz/+UFJSktatW6eXXnpJknT9+nXlypUrU9sKCwtT8+bN5enpKSsrK61atcpsuWEYGjFihAoXLiwHBwf5+/vr+PHjZn0uX76sDh06yNHRUc7OzuratauuXr1q1uf3339XnTp1ZG9vr6JFi2rChAmZPWwAAAAAADIt06G7S5cuatu2rcqVKycrKyv5+/tLknbv3i1fX99MbevatWuqUKGCZsyYkebyCRMmaPr06Zo9e7Z2796tvHnzKiAgQDdv3jT16dChgw4fPqzQ0FCtWbNGYWFh6t69u2l5fHy8GjVqpOLFi2v//v2aOHGiRo4cqblz52b20AEAAAAAyJQMTRl2t5EjR6pcuXI6c+aMXnnlFdnZ2UmScuXKpSFDhmRqW02aNFGTJk3SXGYYhqZOnaphw4apZcuWkqRFixbJ3d1dq1atUrt27XTkyBGtW7dOe/fuVdWqVSVJn376qZo2bapJkybJ09NTS5Ys0a1btzRv3jzZ2tqqbNmyioiI0OTJk83COQAAAAAAWe2Bpgxr06aN+vXrpyJFipjagoODTeE4K0RGRioqKso0ki5JTk5Oql69umne8PDwcDk7O5sCtyT5+/vL2tpau3fvNvWpW7eubG1tTX0CAgJ07NgxpjkDAAAAAFhUhka6p0+fnuEN9unT54GLuVtUVJSkO/eQ383d3d20LCoqSm5ubmbLbWxs5OLiYtbH29s71TZSlhUoUCDN/SckJCghIcH0Pj4+/iGOBgAAAADwNMpQ6J4yZYrZ+wsXLuj69etydnaWJMXGxipPnjxyc3PLstCd3caNG6dRo0ZldxkAAAAAgBwsQ5eXR0ZGml5jxoxRxYoVdeTIEV2+fFmXL1/WkSNHVLlyZX344YdZVljKtGTR0dFm7dHR0aZlHh4eiomJMVt++/ZtXb582axPWtu4ex9pGTp0qOLi4kyvM2fOPNwBAQAAAACeOpm+p3v48OH69NNPVapUKVNbqVKlNGXKFA0bNizLCvP29paHh4c2bdpkaouPj9fu3bvl5+cnSfLz81NsbKz2799v6rN582YlJyerevXqpj5hYWFKTEw09QkNDVWpUqXSvbRckuzs7OTo6Gj2AgAAAAAgMzIdus+fP6/bt2+nak9KSko1onw/V69eVUREhCIiIiTdGVGPiIjQ6dOnZWVlpb59++qjjz7Sjz/+qIMHD6pTp07y9PRUq1atJEmlS5dW48aN1a1bN+3Zs0c7d+5Ur1691K5dO3l6ekqS2rdvL1tbW3Xt2lWHDx/W8uXLNW3aNPXv3z+zhw4AAAAAQKZkOnQ3bNhQb731lg4cOGBq279/v3r06GH2pPGM2LdvnypVqqRKlSpJkvr3769KlSppxIgRkqRBgwapd+/e6t69u6pVq6arV69q3bp1sre3N21jyZIl8vX1VcOGDdW0aVPVrl3bbA5uJycnbdiwQZGRkapSpYoGDBigESNGMF0YAAAAAMDirAzDMDKzwoULFxQcHKx169Ypd+7cku7cRx0QEKAFCxakepr4kyI+Pl5OTk6Ki4t7rC819xryU3aXACADTn4cmN0lPDojnbK7AgAZMTIuuyt4ZMovLJ/dJQDIgIPBB7O7hHvKaEbM0NPL7+bq6qqff/5Zf/75p44ePSpJ8vX1VcmSJR+8WgAAAAAAnkCZDt0pSpYsSdAGAAAAAOAeMh26k5KStGDBAm3atEkxMTFKTk42W7558+YsKw4AAAAAgJws06H7nXfe0YIFCxQYGKhy5crJysrKEnUBAAAAAJDjZTp0L1u2TN98842aNm1qiXoAAAAAAHhiZHrKMFtbW5UoUcIStQAAAAAA8ETJdOgeMGCApk2bpkzONAYAAAAAwFMn05eX79ixQ1u2bNHatWtVtmxZ01zdKb7//vssKw4AAAAAgJws06Hb2dlZL7/8siVqAQAAAADgiZLp0D1//nxL1AEAAAAAwBMn06E7xYULF3Ts2DFJUqlSpeTq6pplRQEAAAAA8CTI9IPUrl27pjfeeEOFCxdW3bp1VbduXXl6eqpr1666fv26JWoEAAAAACBHynTo7t+/v7Zt26bVq1crNjZWsbGx+uGHH7Rt2zYNGDDAEjUCAAAAAJAjZfry8u+++07ffvut6tevb2pr2rSpHBwc1LZtW82aNSsr6wMAAAAAIMfK9Ej39evX5e7unqrdzc2Ny8sBAAAAALhLpkO3n5+fPvjgA928edPUduPGDY0aNUp+fn5ZWhwAAAAAADlZpi8vnzZtmgICAlSkSBFVqFBBkvTbb7/J3t5e69evz/ICAQAAAADIqTIdusuVK6fjx49ryZIlOnr0qCTptddeU4cOHeTg4JDlBQIAAAAAkFM90DzdefLkUbdu3bK6FgAAAAAAniiZvqd73LhxmjdvXqr2efPmafz48VlSFAAAAAAAT4JMh+45c+bI19c3VXvZsmU1e/bsLCkKAAAAAIAnQaZDd1RUlAoXLpyq3dXVVefPn8+SogAAAAAAeBJkOnQXLVpUO3fuTNW+c+dOeXp6ZklRAAAAAAA8CTL9ILVu3bqpb9++SkxM1IsvvihJ2rRpkwYNGqQBAwZkeYEAAAAAAORUmQ7dAwcO1KVLl9SzZ0/dunVLkmRvb6/Bgwdr6NChWV4gAAAAAAA5VaZDt5WVlcaPH6/hw4fryJEjcnBw0HPPPSc7OztL1AcAAAAAQI6V6Xu6U0RFReny5cvy8fGRnZ2dDMPIyroAAAAAAMjxMh26L126pIYNG6pkyZJq2rSp6YnlXbt25Z5uAAAAAADukunQ3a9fP+XOnVunT59Wnjx5TO2vvvqq1q1bl6XFAQAAAACQk2X6nu4NGzZo/fr1KlKkiFn7c889p1OnTmVZYQAAAAAA5HSZHum+du2a2Qh3isuXL/MwNQAAAAAA7pLp0F2nTh0tWrTI9N7KykrJycmaMGGCGjRokKXFAQAAAACQk2X68vIJEyaoYcOG2rdvn27duqVBgwbp8OHDunz5snbu3GmJGgEAAAAAyJEyPdJdrlw5/fnnn6pdu7Zatmypa9euqXXr1vr111/l4+NjiRoBAAAAAMiRMj3SLUlOTk56//33s7oWAAAAAACeKJke6V63bp127Nhhej9jxgxVrFhR7du315UrV7K0OAAAAAAAcrJMh+6BAwcqPj5eknTw4EH1799fTZs2VWRkpPr375/lBQIAAAAAkFNl+vLyyMhIlSlTRpL03XffqXnz5ho7dqwOHDigpk2bZnmBAAAAAADkVJke6ba1tdX169clSRs3blSjRo0kSS4uLqYRcAAAAAAA8AAj3bVr11b//v1Vq1Yt7dmzR8uXL5ck/fnnnypSpEiWFwgAAAAAQE6V6ZHuzz77TDY2Nvr22281a9YsPfPMM5KktWvXqnHjxlleIAAAAAAAOVWmR7qLFSumNWvWpGqfMmVKlhQEAAAAAMCTIkMj3deuXcvURjPbHwAAAACAJ1GGQneJEiX08ccf6/z58+n2MQxDoaGhatKkiaZPn55lBQIAAAAAkFNl6PLyrVu36r333tPIkSNVoUIFVa1aVZ6enrK3t9eVK1f0xx9/KDw8XDY2Nho6dKjeeustS9cNAAAAAMBjL0Ohu1SpUvruu+90+vRprVixQtu3b9cvv/yiGzduqFChQqpUqZI+//xzNWnSRLly5bJ0zQAAAAAA5AiZepBasWLFNGDAAA0YMMBS9QAAAAAA8MTI9JRhAAAAAAAgYwjdAAAAAABYCKEbAAAAAAALeaxDd1JSkoYPHy5vb285ODjIx8dHH374oQzDMPUxDEMjRoxQ4cKF5eDgIH9/fx0/ftxsO5cvX1aHDh3k6OgoZ2dnde3aVVevXn3UhwMAAAAAeMo81qF7/PjxmjVrlj777DMdOXJE48eP14QJE/Tpp5+a+kyYMEHTp0/X7NmztXv3buXNm1cBAQG6efOmqU+HDh10+PBhhYaGas2aNQoLC1P37t2z45AAAAAAAE+RTD29PEVsbKz27NmjmJgYJScnmy3r1KlTlhQmSb/88otatmypwMBASZKXl5e+/vpr7dmzR9KdUe6pU6dq2LBhatmypSRp0aJFcnd316pVq9SuXTsdOXJE69at0969e1W1alVJ0qeffqqmTZtq0qRJ8vT0zLJ6AQAAAAC4W6ZD9+rVq9WhQwddvXpVjo6OsrKyMi2zsrLK0tBds2ZNzZ07V3/++adKliyp3377TTt27NDkyZMlSZGRkYqKipK/v79pHScnJ1WvXl3h4eFq166dwsPD5ezsbArckuTv7y9ra2vt3r1bL7/8cpr7TkhIUEJCgul9fHx8lh0XAAAAAODpkOnQPWDAAL3xxhsaO3as8uTJY4maTIYMGaL4+Hj5+voqV65cSkpK0pgxY9ShQwdJUlRUlCTJ3d3dbD13d3fTsqioKLm5uZktt7GxkYuLi6lPWsaNG6dRo0Zl5eEAAAAAAJ4ymb6n+9y5c+rTp4/FA7ckffPNN1qyZImWLl2qAwcOaOHChZo0aZIWLlxo8X0PHTpUcXFxpteZM2csvk8AAAAAwJMl0yPdAQEB2rdvn5599llL1GNm4MCBGjJkiNq1aydJKl++vE6dOqVx48YpODhYHh4ekqTo6GgVLlzYtF50dLQqVqwoSfLw8FBMTIzZdm/fvq3Lly+b1k+LnZ2d7OzssviIAAAAAABPk0yH7sDAQA0cOFB//PGHypcvr9y5c5stb9GiRZYVd/36dVlbmw/G58qVy/TwNm9vb3l4eGjTpk2mkB0fH6/du3erR48ekiQ/Pz/FxsZq//79qlKliiRp8+bNSk5OVvXq1bOsVgAAAAAA/ivTobtbt26SpNGjR6daZmVlpaSkpIev6v81b95cY8aMUbFixVS2bFn9+uuvmjx5st544w3T/vr27auPPvpIzz33nLy9vTV8+HB5enqqVatWkqTSpUurcePG6tatm2bPnq3ExET16tVL7dq148nlAAAAAACLynTo/u8UYZb06aefavjw4erZs6diYmLk6empt956SyNGjDD1GTRokK5du6bu3bsrNjZWtWvX1rp162Rvb2/qs2TJEvXq1UsNGzaUtbW1goKCNH369Ed2HAAAAACAp5OVYRhGdheRE8THx8vJyUlxcXFydHTM7nLS5TXkp+wuAUAGnPw4MLtLeHRGOmV3BQAyYmRcdlfwyJRfWD67SwCQAQeDD2Z3CfeU0YyY6aeXS9K2bdvUvHlzlShRQiVKlFCLFi20ffv2By4WAAAAAIAnUaZD91dffSV/f3/lyZNHffr0UZ8+feTg4KCGDRtq6dKllqgRAAAAAIAcKdP3dI8ZM0YTJkxQv379TG19+vTR5MmT9eGHH6p9+/ZZWiAAAAAAADlVpke6//77bzVv3jxVe4sWLRQZGZklRQEAAAAA8CTIdOguWrSoNm3alKp948aNKlq0aJYUBQAAAADAkyDTl5cPGDBAffr0UUREhGrWrClJ2rlzpxYsWKBp06ZleYEAAAAAAORUmQ7dPXr0kIeHhz755BN98803kqTSpUtr+fLlatmyZZYXCAAAAABATpXp0C1JL7/8sl5++eWsrgUAAAAAgCfKA83TDQAAAAAA7i9DI90uLi76888/VahQIRUoUEBWVlbp9r18+XKWFQcAAAAAQE6WodA9ZcoU5c+f3/Tve4VuAAAAAABwR4ZCd3BwsOnfnTt3tlQtAAAAAAA8UTJ9T3euXLkUExOTqv3SpUvKlStXlhQFAAAAAMCTINOh2zCMNNsTEhJka2v70AUBAAAAAPCkyPCUYdOnT5ckWVlZ6YsvvlC+fPlMy5KSkhQWFiZfX9+srxAAAAAAgBwqw6F7ypQpku6MdM+ePdvsUnJbW1t5eXlp9uzZWV8hAAAAAAA5VIZDd2RkpCSpQYMG+v7771WgQAGLFQUAAAAAwJMgw6E7xZYtWyxRBwAAAAAAT5xMh25JOnv2rH788UedPn1at27dMls2efLkLCkMAAAAAICcLtOhe9OmTWrRooWeffZZHT16VOXKldPJkydlGIYqV65siRoBAAAAAMiRMj1l2NChQ/Xuu+/q4MGDsre313fffaczZ86oXr16euWVVyxRIwAAAAAAOVKmQ/eRI0fUqVMnSZKNjY1u3LihfPnyafTo0Ro/fnyWFwgAAAAAQE6V6dCdN29e033chQsX1okTJ0zLLl68mHWVAQAAAACQw2X6nu4aNWpox44dKl26tJo2baoBAwbo4MGD+v7771WjRg1L1AgAAAAAQI6U6dA9efJkXb16VZI0atQoXb16VcuXL9dzzz3Hk8sBAAAAALhLpkJ3UlKSzp49q+eff17SnUvNZ8+ebZHCAAAAAADI6TJ1T3euXLnUqFEjXblyxVL1AAAAAADwxMj0g9TKlSunv//+2xK1AAAAAADwRMl06P7oo4/07rvvas2aNTp//rzi4+PNXgAAAAAA4I5MP0itadOmkqQWLVrIysrK1G4YhqysrJSUlJR11QEAAAAAkINlOnRv2bLFEnUAAAAAAPDEyXTorlevniXqAAAAAADgiZPp0B0WFnbP5XXr1n3gYgAAAAAAeJJkOnTXr18/Vdvd93ZzTzcAAAAAAHdk+unlV65cMXvFxMRo3bp1qlatmjZs2GCJGgEAAAAAyJEyPdLt5OSUqu2ll16Sra2t+vfvr/3792dJYQAAAAAA5HSZHulOj7u7u44dO5ZVmwMAAAAAIMfL9Ej377//bvbeMAydP39eH3/8sSpWrJhVdQEAAAAAkONlOnRXrFhRVlZWMgzDrL1GjRqaN29elhUGAAAAAEBOl+nQHRkZafbe2tparq6usre3z7KiAAAAAAB4EmQ6dBcvXtwSdQAAAAAA8MTJVOhOTk7WggUL9P333+vkyZOysrKSt7e32rRpo44dO5rN1w0AAAAAwNMuw08vNwxDLVq00Jtvvqlz586pfPnyKlu2rE6dOqXOnTvr5ZdftmSdAAAAAADkOBke6V6wYIHCwsK0adMmNWjQwGzZ5s2b1apVKy1atEidOnXK8iIBAAAAAMiJMjzS/fXXX+u9995LFbgl6cUXX9SQIUO0ZMmSLC0OAAAAAICcLMOh+/fff1fjxo3TXd6kSRP99ttvWVIUAAAAAABPggyH7suXL8vd3T3d5e7u7rpy5UqWFAUAAAAAwJMgw6E7KSlJNjbp3wKeK1cu3b59O0uKAgAAAADgSZDhB6kZhqHOnTvLzs4uzeUJCQlZVhQAAAAAAE+CDI90BwcHy83NTU5OTmm+3NzcLPLk8nPnzun1119XwYIF5eDgoPLly2vfvn2m5YZhaMSIESpcuLAcHBzk7++v48ePm23j8uXL6tChgxwdHeXs7KyuXbvq6tWrWV4rAAAAAAB3y/BI9/z58y1ZR5quXLmiWrVqqUGDBlq7dq1cXV11/PhxFShQwNRnwoQJmj59uhYuXChvb28NHz5cAQEB+uOPP2Rvby9J6tChg86fP6/Q0FAlJiaqS5cu6t69u5YuXfrIjwkAAAAA8PTIcOjODuPHj1fRokXNAr+3t7fp34ZhaOrUqRo2bJhatmwpSVq0aJHc3d21atUqtWvXTkeOHNG6deu0d+9eVa1aVZL06aefqmnTppo0aZI8PT0f7UEBAAAAAJ4aGb68PDv8+OOPqlq1ql555RW5ubmpUqVK+vzzz03LIyMjFRUVJX9/f1Obk5OTqlevrvDwcElSeHi4nJ2dTYFbkvz9/WVtba3du3c/uoMBAAAAADx1HuvQ/ffff2vWrFl67rnntH79evXo0UN9+vTRwoULJUlRUVGSlGoqM3d3d9OyqKgoubm5mS23sbGRi4uLqU9aEhISFB8fb/YCAAAAACAzHuvLy5OTk1W1alWNHTtWklSpUiUdOnRIs2fPVnBwsEX3PW7cOI0aNcqi+wAAAAAAPNke65HuwoULq0yZMmZtpUuX1unTpyVJHh4ekqTo6GizPtHR0aZlHh4eiomJMVt++/ZtXb582dQnLUOHDlVcXJzpdebMmYc+HgAAAADA0+WxDt21atXSsWPHzNr+/PNPFS9eXNKdh6p5eHho06ZNpuXx8fHavXu3/Pz8JEl+fn6KjY3V/v37TX02b96s5ORkVa9ePd1929nZydHR0ewFAAAAAEBmPNaXl/fr1081a9bU2LFj1bZtW+3Zs0dz587V3LlzJUlWVlbq27evPvroIz333HOmKcM8PT3VqlUrSXdGxhs3bqxu3bpp9uzZSkxMVK9evdSuXTueXA4AAAAAsKjHOnRXq1ZNK1eu1NChQzV69Gh5e3tr6tSp6tChg6nPoEGDdO3aNXXv3l2xsbGqXbu21q1bZ5qjW5KWLFmiXr16qWHDhrK2tlZQUJCmT5+eHYcEAAAAAHiKWBmGYWR3ETlBfHy8nJycFBcX91hfau415KfsLgFABpz8ODC7S3h0RjpldwUAMmJkXHZX8MiUX1g+u0sAkAEHgw9mdwn3lNGM+Fjf0w0AAAAAQE5G6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEJyVOj++OOPZWVlpb59+5rabt68qZCQEBUsWFD58uVTUFCQoqOjzdY7ffq0AgMDlSdPHrm5uWngwIG6ffv2I64eAAAAAPC0yTGhe+/evZozZ46ef/55s/Z+/fpp9erVWrFihbZt26Z//vlHrVu3Ni1PSkpSYGCgbt26pV9++UULFy7UggULNGLEiEd9CAAAAACAp0yOCN1Xr15Vhw4d9Pnnn6tAgQKm9ri4OH355ZeaPHmyXnzxRVWpUkXz58/XL7/8ol27dkmSNmzYoD/++ENfffWVKlasqCZNmujDDz/UjBkzdOvWrew6JAAAAADAUyBHhO6QkBAFBgbK39/frH3//v1KTEw0a/f19VWxYsUUHh4uSQoPD1f58uXl7u5u6hMQEKD4+HgdPnw43X0mJCQoPj7e7AUAAAAAQGbYZHcB97Ns2TIdOHBAe/fuTbUsKipKtra2cnZ2Nmt3d3dXVFSUqc/dgTtlecqy9IwbN06jRo16yOoBAAAAAE+zx3qk+8yZM3rnnXe0ZMkS2dvbP9J9Dx06VHFxcabXmTNnHun+AQAAAAA532Mduvfv36+YmBhVrlxZNjY2srGx0bZt2zR9+nTZ2NjI3d1dt27dUmxsrNl60dHR8vDwkCR5eHikepp5yvuUPmmxs7OTo6Oj2QsAAAAAgMx4rEN3w4YNdfDgQUVERJheVatWVYcOHUz/zp07tzZt2mRa59ixYzp9+rT8/PwkSX5+fjp48KBiYmJMfUJDQ+Xo6KgyZco88mMCAAAAADw9Hut7uvPnz69y5cqZteXNm1cFCxY0tXft2lX9+/eXi4uLHB0d1bt3b/n5+alGjRqSpEaNGqlMmTLq2LGjJkyYoKioKA0bNkwhISGys7N75McEAAAAAHh6PNahOyOmTJkia2trBQUFKSEhQQEBAZo5c6Zpea5cubRmzRr16NFDfn5+yps3r4KDgzV69OhsrBoAAAAA8DTIcaF769atZu/t7e01Y8YMzZgxI911ihcvrp9//tnClQEAAAAAYO6xvqcbAAAAAICcjNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgIYRuAAAAAAAshNANAAAAAICFELoBAAAAALAQQjcAAAAAABZC6AYAAAAAwEII3QAAAAAAWAihGwAAAAAACyF0AwAAAABgITbZXQAAAADwoJKSkpSYmJipdQrbFrZQNQCy0s2bN7N1/7lz51auXLkeejuEbgAAAOQ4hmEoKipKsbGxmV53cInBWV8QgCwXGRmZ3SXI2dlZHh4esrKyeuBtELoBAACQ46QEbjc3N+XJkydTvxDfvnLbgpUByCreBbyzbd+GYej69euKiYmRJBUu/OBXyBC6AQAAkKMkJSWZAnfBggUzvb51bh5rBOQE9vb22bp/BwcHSVJMTIzc3Nwe+FJzPnEAAACQo6Tcw50nT55srgTAky7lcyazz464G6EbAAAAOdLD3GMJABmRFZ8zhG4AAADgETEMQyP7j1TN52qqnGs5HT149L7rnDt9LsN9c4JyruW06edNmV4v9nKs6pauq3Onz1mgqgfTqHIjLZ69OLvLyBY5+dhv3bolLy8v7du375Hsj9ANAAAAPCI7Nu3QqmWrNGPJDG09tFUlSpfI7pIeyIHdB1TBo4KC6gelWvb1l1+rUeVGqlyksl4LeE0HDxzMkn3OnTJXDRo30DPFnsmS7eUkj+MfXpZtWKY2ndpkdxkPxNbWVu+++64GD340MxnwIDUAAAA8MbyG/PRI9/fTu16Z6n/m5Bm5uruq0guVLFPQIxAfF6/3er2n6nWq69KFS2bL1q5cqwkjJmjExBF6vsrzWjxnsd5q+5ZWh69WQdfMP/QuxY3rN/T9ku8155s5D1v+YyXxVqJy2+bO7jIeiEshl+wu4aF06NBBAwYM0OHDh1W2bFmL7ouRbgAAAOAReL/X+xo7dKzOnz2vcq7l1KhyI0l3Rr87BnaUn4+fapWspZ7te+p05Ol7buuvo3+pZ/uequ5dXS94vaBOzTqZ1klOTtasSbPU8PmGqvRMJQXVD9KOTTtM66aMmoauCVWXVl1UtVhVta7fWhF7IzJ0HKPfHa3A1oGqUK1CqmWLZi9Sm9fb6OX2L8unlI9GTBohewd7rVy60qzfhegLevvVt1WlaBU1rtpYG37ccM99bt+4XbZ2tqpQ9X/7TEpK0vB3hiugSoCqFK2iZjWaafGc1Jc7f7/ke7Ws3VKVnqmk+mXra8zgMaZl8XHxGjVglOqWqavKRSqrVZ1W2rphq2n5gV0H1KlZJ1UpWkUNKzTU2KFjdf3a9XTrjI+L14i+I1THt46qe1fXGy+/oaOH/jc6PWPCDAXVD9K3i79VQJUAVS5SWdL9vwcCqgRIktq82EblXMupc8vOpmXfLv5WzWs2V+UildXcr7mWzVt2z3O5Z+celXMtp11hu9TWv62qFquqDk07KPKv/82JfTrytHp37K26ZeqqWvFqevWlVxW+LdxsO3dfXj7orUEa8OYAs+WJiYmqXaq2flj+g6Q735efT/3c9PVqXb/1fb/uCxYskLOzs9asWaNSpUopT548atOmja5fv66FCxfKy8tLBQoUUJ8+fZSUlGRaz8vLSx9++KFee+015c2bV88884xmzJhhtu0CBQqoVq1aWrbs3ucrKzz2oXvcuHGqVq2a8ufPLzc3N7Vq1UrHjh0z63Pz5k2FhISoYMGCypcvn4KCghQdHW3W5/Tp0woMDFSePHnk5uamgQMH6vZt5mgEAADAozFk7BD1GtJL7p7u2npoq5ZtuPPL/o3rN9SpRyctD12uL7/7UtbW1nqn8ztKTk5OczvR56MV3CJYtra2+nLll/pm0zd6uf3LptDx1dyvtHDmQg0YNUDfb/tetV6spV4de+nUiVNm25k+dro69+ysb7d8K69nvTTorUH3/f145dKVOnvqrHoM7JFqWeKtRP3x2x+qUa+Gqc3a2lo16tbQb/t+M+v72cefyb+Zv77b+p0CgwI1sPtAnfjzRLr73b9rv8o8X8asLTk5We6e7vrky0/0w44f9Pa7b2v62Olat2qdqc+y+cs0ZsgYtenYRivDVurTrz5VMe9ipvV7tOuhX/f8qo9nfqwfdvygvsP7Kpf1nWmhTkee1luvvqWXmr2k77d+r0mfT9Kvu3/V2CFj062zf9f+unzxsmYtm6VvNn6j0s+X1ptBbyruSpypz+nI09q4ZqOmzp+qb7d8K+n+3wNfb/hakvTFd19o66GtmrZgmiRpzbdrNGP8DPV5r49+3Pmj+rzfR59+/Kl+WPZDujWmmD52ugaOGqjloctlk8tGw/sMNy27fu266vjX0ZfffalvN3+r2i/WVq/Xe+n82fNpbiswKFDbNmzT9av/+4PEzi07dfPGTfkH+kuSPp/6uX785keNmDhCq7avUqe3OmlIzyHau3PvPeu8fv26pk+frmXLlmndunXaunWrXn75Zf3888/6+eeftXjxYs2ZM0fffvut2XoTJ05UhQoV9Ouvv2rIkCF65513FBoaatbnhRde0Pbt2+97rh7WY395+bZt2xQSEqJq1arp9u3beu+999SoUSP98ccfyps3rySpX79++umnn7RixQo5OTmpV69eat26tXbu3Cnpzl/BAgMD5eHhoV9++UXnz59Xp06dlDt3bo0dm/4PDQAAAJBV8jvmV968eZUrVy4Vci9kan+p+Utm/T6c9qHq+NbRiWMn9Fzp51Jt5+svv1Z+x/ya+PlE5c5959JkLx8v0/IFMxbojd5vqOnLTSVJ/Uf0154de7R4zmINmzDM1K9zz86q16ieJClkcIha1m6p05Gn9exzz6ZZ/6kTpzTloylatHqRbGxSx4grl68oKSkp1WXkBd0Kmo2iSlKjFo3UpuOd+4F7D+2t8G3hWvrFUg2fMFxpOX/2vFw9XM3acufOrV6De5neFyleRL/t/U3rf1ivxq0aS5LmTp6r4B7B6vhWR1O/8pXKS5LCt4Xr4IGD+vGXH03nr6hXUVO/L6Z9oWZtmqnj23fWLe5TXEPHDlXnlp01fOJw2dnbmdVzYNcBHTpwSGFHwmRrZytJGjhqoDb/vFkbVm/QK51ekXRnBHjsjLFml2ff73vApeCdvs4FnM2+d2aMn6GBowfqpWYvmc7B38f+1jeLvlHLdi3TPJcp+rzXR9VqVZMkde3TVT3b91TCzQTZ2dvJt5yvfMv5mvr2Htpbm37epC3rtqj9m+1TbavWi7XkkMdBG3/eqBZtW0iSfv7uZ9UPqK+8+fLqVsItfTHtC33+7eeqWK2i6Vwf2H1AKxatMNWRlsTERM2aNUs+Pj6SpDZt2mjx4sWKjo5Wvnz5VKZMGTVo0EBbtmzRq6+++r+aatXSkCFDJEklS5bUzp07NWXKFL300v/Otaenp06dMv9jlCU89qF73bp1Zu8XLFggNzc37d+/X3Xr1lVcXJy+/PJLLV26VC+++KIkaf78+SpdurR27dqlGjVqaMOGDfrjjz+0ceNGubu7q2LFivrwww81ePBgjRw5Ura2ttlxaAAAAIBOnTilz8Z/poMHDurKpSum0c3zZ8+nGbqPHTqmytUrmwL33a7+e1UxUTGp7hmv9EIlHTtsfrVoybIlTf9OCXKXL1zWs889q2rF/xeCmr3STMPGD9OgtwcpZFCIWcB/UHdfJp7y/u7LsP/r5o2bcvNwS9X+9Zdfa+XSlTp/7rxu3ripxMREU1i8dOGSYqJiVKNujVTrSXfOo7une7rHc+zwMf35x59a8+0as/bk5GSdPX1WPiV9UvW/fu26apWsZdaecDNBZ06eMb33LOKZ6n7ozH4PSHdGo8+cPKMRfUfog34fmNqTkpKUzzGfJOntV9/W/l377+y3qKd+2PG/EfCSZf739Xd1v/MHjcsXL6twkcK6fvW6ZkycobDQMF2Mvqjbt28r4WaCzp9Le6TbxsZGAS0C9NO3P6lF2xa6fu26tqzboolzJ0q6M7p/4/oNdWvTzWy9xMRElS5fWpLUsnZL/XPmH0lSlRpVNHv5bEl35slOCdyS5O7uLi8vL+XLl8+sLSYmxmzbfn5+qd5PnTrVrM3BwUHXr6d/u0BWeexD93/Fxd25NMPF5c436v79+5WYmCh/f39TH19fXxUrVkzh4eGqUaOGwsPDVb58ebm7u5v6BAQEqEePHjp8+LAqVUr9IIuEhAQlJCSY3sfHx1vqkAAAAPAU6/V6LxUuUlgjJ4+Uq4erjGRDreq0UmJiYpr9/zvC+qBy2/wvtKfMRZxs3Al73235zrQsb/68unb1mg5HHNbRg0dNl1cnJyfLMAxV8KiguSvmqnL1ysqVK1eqh6tdirmkQm6F9DAKFCyg+Djz38d/XvmzJo2cpIGjBqpC1QrKmy+v5s+Yr9/3/y5Jsnewv+c273cer1+7rlc6vaLXu72ealnhIoXT7O/q7qr5q+anWpbfKb/p3w55HFItz+z3QMr+JGnk5JF6vvLzZsusc925i3jU1FFKuHEn09jkNo9+d783ff3/P+xPHDlR4dvC9e7Id1XMu5js7e3V741+SryVfj2BbQLVpWUXXbpwSeHbwmVnb6daL9Yyq3Xm0plyL+xutl5uuzvfh7O+nqXbiXdub7Bz+N/X5r9/XLKyskqzLb3bMe7l8uXLcnV1vX/Hh5SjQndycrL69u2rWrVqqVy5cpKkqKgo2draytnZ2ayvu7u7oqKiTH3uDtwpy1OWpWXcuHEaNWpUFh8BAAAA8D+xl2MV+VekRk4eqSp+VSTduUz5XkqWLakfl/+oxMTEVOEjX/58cvNw0697fjW7ZPfXPb+aLqvOiGLPFjN7n5ycrJVh5g9DWzZ/mfZs36PJ8ybrmWLPKLdtbpWpUEa7w3arYdOGpvV2b9+t17q+Zrbu7/t/V8tXW5q99y3vq/T4lvfVmhXmI84RuyNUsVpFtXujnant7hHlvPny6pliz2hX2C69UPuFVNssWaakov+J1skTJ9Mc7S7zfBn9/effqc5Feko/X1oXYy4ql02uTE1rlpHvgZQnnCcl/+9hYYXcCsnNw01nT51VszbN0tz2fwNuRkXsiVCrdq1M92Nfv3rdNAqdnkovVJLHMx5at2qddmzaoUYtGpm+P31K+cjWzlbnz51P91Jyz6KeD1Rrenbt2pXqfenSpc3aDh06lOYAbFbLUaE7JCREhw4d0o4dO+7f+SENHTpU/fv3N72Pj49X0aJF77EGAAAAkDmOzo5ydnHWisUr5OruqvPnzmvKh1PuuU77ru219IulGthtoN7s+6by58+v3/b/pvKVy8u7hLe6hHTRjAkzVNSrqHzL+2rV0lU6euioxs8a/8B1Wltbp7rM2aWQi2ztbM3aO73dSe/3fl9lK5ZVucrl9NWcr3Tj+g21eq2V2bobftygshXKqnKNylrz7RodPHBQo6eOTnf/tRrU0rSPpikuNk5Ozk6S7vxh4MdvftTOzTv1TPFntPqb1Tr06yGzwNtzYE+NHjhaLoVcVKdhHV27ek2/7vlVHbp1ULVa1VTFr4r6demngaMHqph3MUUej5SVlZVqN6ytN3q/oQ5NOmjM4DEKej1IDnkcdOLPEwrfGq73x7+fqka/en6qULWC+nTqo/4f9JeXj5diomIUFhqmhoENVa5iuTSPLSPfAy6FXGTvYK8dm3bIvbC77OztlN8xv3oO6qmP3/9Y+fLnU+2GtXUr4ZYORxxWfFy8gnsEp3s+76fYs8W0cc1G1W9UX7K68+C7jIwkN23dVN8s/EanTpzSvJXzTO158+VV556dNWH4BBnJhipVr6Sr8Vf1655flS9/vvvef/4gdu7cqQkTJqhVq1YKDQ3VihUr9NNP5lMKbt++XR9++GGW7/u/ckzo7tWrl9asWaOwsDAVKVLE1O7h4aFbt24pNjbWbLQ7OjpaHh4epj579uwx217K081T+vyXnZ2d7Oyy5tIdAAAAIC3W1taaOHeixr03Tq3qtpJXCS8NHTNUXVp1SXcdZxdnffn9l/pk5Cfq0rKLrK2t5VvO13Qfd4fuHfTvv/9q0geTdOniJfmU9NFniz9TcZ/iFj+eJi830ZVLV/TZ+M90MeaifMv5avby2akuLw8ZFKK1q9bqo8EfydXdVRPmTJBPKZ90tnpnVLr086W1/of1ahvcVpLUNritjh48qne7vSsrKys1ad1Er3Z51Wx6tJbtWiohIUGLZy/WpJGTVMClgNlDy6bOn6qJH0zUoLcG6cb1GyrmXUx9h/WVJJUqW0rzf5iv6WOnq1PzTjIMQ0W9i6pxy8Zp1mhlZaVZy2Zp2phpGt5nuC5fuqxCboVUxa/KPecoz8j3gI2NjYaMGaLZn8zWjPEzVLlGZS34YYHadGwjhzwOmv/ZfH0y6hM55HFQydIl9fpbqS+Jz4xBowdp+DvD9Xrg63J2cVbX3l119d+r910vsE2g5k6ZK8+inqpU3XwEuffQ3ipQsIC+mPaFzpw6I0cnR5UuX1rd+nZLZ2sPZ8CAAdq3b59GjRolR0dHTZ48WQEBAabl4eHhiouLU5s2bSyy/7tZGYZhWHwvD8EwDPXu3VsrV67U1q1b9dxz5n9hi4uLk6urq77++msFBQVJko4dOyZfX1/TPd1r165Vs2bNdP78ebm53XkAw9y5czVw4EDFxMRkKFzHx8fLyclJcXFxcnR0zPoDzSJeQ366fycA2e7kx4HZXcKjM9IpuysAkBEj4+7f5zFx8+ZNRUZGytvbW/b2975vNy2HLx62QFWwtG0btumTUZ9o1fZVsrZ+7Gc+RhYoW6jsA63n5eWlvn37qm/fvun2efXVV1WhQgW9995799zWvT5vMpoRH/uR7pCQEC1dulQ//PCD8ufPb7oH28nJSQ4ODnJyclLXrl3Vv39/ubi4yNHRUb1795afn59q1LjzpMJGjRqpTJky6tixoyZMmKCoqCgNGzZMISEhjGYDAAAAOUC9RvV0+u/Tij4frcLPpH6QGZBRt27dUvny5dWvX79Hsr/HPnTPmjVLklS/fn2z9vnz56tz586SpClTpsja2lpBQUFKSEhQQECAZs6caeqbK1curVmzRj169JCfn5/y5s2r4OBgjR6d/n0jAAAAAB4vKXNmAw/D1tZWw4YNu3/HLPLYh+6MXP1ub2+vGTNmaMaMGen2KV68uH7++eesLA0AAAAA8Jg5efJkdpdghpshAAAAAACwEEI3AAAAAAAWQugGAAAAAMBCCN0AAAAAAFgIoRsAAAAAAAshdAMAAAAAYCGEbgAAAOARMQxDI/uPVM3naqqcazkdPXj0vuucO30uw31zgnKu5bTp502ZXi/2cqzqlq6rc6fPpdtnz849KudaTvFx8Q9T4hNjxoQZCqofZHo/ZfQUjR0yNhsrejoRugEAAIBHZMemHVq1bJVmLJmhrYe2qkTpEtld0gM5sPuAKnhUMAt0Kb7+8ms1qtxIlYtU1msBr+nggYNZss+5U+aqQeMGeqbYM1myvadR55DO+mH5Dzpz8kx2l/JUscnuAgAAAIAsM9Lpvl3KZuHuDvf6JVP9z5w8I1d3V1V6oVIWVvFoxcfF671e76l6neq6dOGS2bK1K9dqwogJGjFxhJ6v8rwWz1mst9q+pdXhq1XQteAD7/PG9Rv6fsn3mvPNnIct/6lWoGAB1WpQS8sXLNe7I9/N7nKeGox0AwAAAI/A+73e19ihY3X+7HmVcy2nRpUbSboz+t0xsKP8fPxUq2Qt9WzfU6cjT99zW38d/Us92/dUde/qesHrBXVq1sm0TnJysmZNmqWGzzdUpWcqKah+kHZs2mFaN+Vy9dA1oerSqouqFquq1vVbK2JvRIaOY/S7oxXYOlAVqlVItWzR7EVq83obvdz+ZfmU8tGISSNk72CvlUtXmvW7EH1Bb7/6tqoUraLGVRtrw48b7rnP7Ru3y9bOVhWqmu8zLDRMgdUDVaVoFXVp1UX/nP4n1boHdh1Qp2adVKVoFTWs0FBjh47V9WvXTctvJdzSxA8m6sXyL6pa8Wp6LeA17dm5x7R81der5Ofjp00/b1LTF5qqcpHK6v5Kd50/d97U5+iho+rSqote8HpB1b2rq23DtjoUcSjD60vS5rWb9cqLr6hykcpqXLWxZk6cqdu3b5uWx8fFa0TfEarjW0fVvavrjZff0NFD5rccfDHtC9UtU1cveL2g4e8M162bt1Kdj3oB9bR25dp7nm9kLUI3AAAA8AgMGTtEvYb0krunu7Ye2qplG5ZJujOK26lHJy0PXa4vv/tS1tbWeqfzO0pOTk5zO9HnoxXcIli2trb6cuWX+mbTN3q5/ctKSkqSJH019ystnLlQA0YN0PfbvletF2upV8deOnXilNl2po+drs49O+vbLd/K61kvDXprkFnIS8vKpSt19tRZ9RjYI9WyxFuJ+uO3P1SjXg1Tm7W1tWrUraHf9v1m1vezjz+TfzN/fbf1OwUGBWpg94E68eeJdPe7f9d+lXm+jFnb+XPn1bdLX9UPqK9vt3yroNeDNOXDKWZ9Tkee1luvvqWXmr2k77d+r0mfT9Kvu381u695zJAx+m3vb5o4d6K+2/qdGrVopLdffdvsfN24cUNzp8zV2Bljtfinxfo3/l8N7DbQtHxIjyFy93TXstBl+mbjN+rap6tsbGwyvP7+8P16L+Q9vd79df2w4weNmDRCPyz7QXOnzDX16d+1vy5fvKxZy2bpm43fqPTzpfVm0JuKuxInSVq3ap1mTpypd957R8s3Lperu6uWzV+W6lyWr1xe0f9E3/PeeGQtQjcAAADwCOR3zK+8efMqV65cKuReSC6FXCRJLzV/SS81e0nFni0m3/K++nDahzr+x3GdOJZ2CP36y6+V3zG/Jn4+UeUqlpOXj5debv+yvEt4S5IWzFigN3q/oaYvN5V3CW/1H9FfvuV8tXjOYrPtdO7ZWfUa1ZOXj5dCBofonzP/3HOE/dSJU5ry0RR9POtjs0CZ4srlK0pKSkp1GXlBt4K6GHPRrK1Ri0Zq07GNvHy81Htob5WtWFZLv1ia7r7Pnz0vVw9Xs7bl85erqFdRDRw9UN4lvNWsTTO1atfKrM8X075QszbN1PHtjiruU1yVXqikoWOH6sdvflTCzQSdP3teq75epcnzJquKXxUV8y6mLiFdVLl6Za38+n+j87cTb+v9j99XxWoVVbZCWY35bIwi9kaY7lc/f/a8/Or66dnnnlVxn+IKaBkg33K+GV5/1qRZ6tqnq1q2a6miXkVVs35N9RrSSysWrpB0Z7T+0IFDmvzlZJWrWE7FfYpr4KiByu+YXxtW37lKYPHcxWrdvrWCXg+Sdwlv9Xmvj3xK+aQ6l24e/9fefUZVcX1tAH8ul14uSBWRHqoFKRY0igW7iMYWG4LEWLDFqDFWLNjFaGwxUYz+FRuCxq7YjWIDRaUIIqBiAztS5O73gy+jI9VCsOzfWqzFnDJnzyDH2czMuYYAgNvpRZ8KYBWD3+lmjDHGGGOsEqUmp2LJnCWIvRCLh5kPhTvcGTczYONgU6R9wuUEuNR3gZKSUpG6Z0+f4d6de0XeGXeu54yEKwmiMtsatsL3+kb6AICs+1mwsrFCXfO6Ql2Hbh0wcc5EjB00FgFjA2BhbfHex1ro7cfEndycijwq/aacFzlCsljo+rXrqOVSS7yftx55T7iSgMSridi5daeoXC6X42baTdy8cRMFBQVoX7+9qD4/Lx/aVV6vD6CoqIiazjWFbSsbK8i0Zbie+CoGn8E+mPLTFPyz5R80aNIArTq2gpmlWbn7J1xJQPSZaNGdbblcjtycXLzIfoGEKwnIfp6NRraNRHHm5uQKi6KlJKage7/u4vPh5oQzJ86IylRUVQC8Oqfsv8FJN2OMMcYYY5VoaJ+hMK5ujMDgQBhUNQDJCZ0ad0J+fn6x7QuTpg+lpPg6aZdIJAAAOb1K+MMOhwl1GloaeP7sOa7EXEF8bLzwaLZcLgcRwamqE1ZuWQmX+i6QSqVFFlfLvJcJfUP9D4q1il6V9/oYsOzn2ejm0w19BvQpUmdc3RiJVxIhlUqxOXIzpApSUb26hnq5xwkYG4D2Xdrj2IFjOB55HEvnLsW8lfPg2d6z3HEGjA0otr2Kqgqyn2fDwMgAIREhReq1tLXKHScA4XH0KvpV3qkfe3+cdDPGGGOMMVZJHmU9QkpSCgKDA+Hq7grg1aPEpbGtYYsdm3YgPz+/yN1uTS1NGFY1RPSZaNRt9PpudfSZaNRyrvX2rkpkZmUm2pbL5Qg/Jl4MbWPIRpw5fgbBq4NhYmYCJWUlODo5IupYFFq0ayH0izoehZ7+PUV9L52/BO8e3qJt+1r2KIl9LXvs3CK+W21lY4Uj+46Iyt5+d9yxtiOuJ14vcjyFHGo7oKCgAFn3s4TzX5yXL1/iSswV4c56SlIKnjx+AitbK6GNhbUFLKwt4DPIB2N+HIOI0AghiS6rv0MtB6QkpZQa54N7DyBVlJb4kWmWtpaIPR9b5Ly+LSk+CYpKivjG7vP8uLrPEb/TzRhjjDHGWCWR6cigo6uDLeu2IO16GqKOR2Hu5Lml9unl3wvPnj7DmAFjcDnmMlKTU7Fj8w6kJKUAAPwC/LD699XYE74HKUkpWDhtIeIvx6PPj0Xv9paXgoICbBxsRF+6+rpQVlGGjYONcFfYZ5APtv5vK7Zv3I7kxGRMHzMdL7JfoFPPTqL97d+xH9vWb8ON5BvCo/W9/HuVOH6jZo2QnJCMx48eC2U9fHsg9Xoq5gfOR0pSCnaF7cL2jdtF/foP64+YszEI+iUI8bHxSE1OxaE9hxD0SxCAV4ly+67tMX7oeBzYeQA3U28i9kIs/vztTxzdf1TYj6KSImb+OhOXzl/ClYtXMHHYRDi5OaGWSy3kvMhB0C9BOHPyDG6n38aFqAu4HH1ZlJCX1h8ABo8ejH82/4Nl85YhKT4JyYnJ2B2+G4tnLgYAuHu4w8nNCcN9huPk4ZO4lXYL0WeisShokbBKep8BfRAeGo7wDeHCeU2KTypyLs+fPg/XBq5QVVMt8+fOPg6+080YY4wxxlglUVBQwLyV8zBr/Cx0atIJFt9Y4NegX+HXya/EPjq6Oli1bRUWBC6An7cfFBQUYF/TXniPu/ePvfH06VPMnzIfmQ8yYW1rjSXrlsDc2rzCj6dt57Z4mPkQS+YswYN7D2Bf0x4rNq0o8nh5wNgA7InYgxm/zICBkQHm/jG32EW/Ctk62sKhtgP2bd8nvLdsXN0YC0MWYu7Eudjw1wbUcq6FERNGYNKISUI/uxp2CNkegsUzF8PHywdEBFNLU7TxbiO0mbF4Bv4I/gPzp8zH3Yy7qKJbBbXdasOjlYfQRk1NDf2H9cfYQWNxL+MeXBq4YPpv0wEAUqkUjx4+wviA8ci8n4kqulXg2d4TAWMDytUfABo1b4Sl65di+fzlWP37aigqKsLSxhJd+nQB8Orx/+Ubl2NR0CJMGj4JWZlZ0DfUh6u7q7BwXdvObZF+Ix3B04KRm5OLlh1aoodfD5w8dFJ0LveG78XgsUVXn2cVR0JEVNlBfA6ePHkCbW1tPH78GDKZrLLDKZHFuF2VHQJjrBxuzG5fdqMvRaB22W0YY5Uv8HHZbT4ROTk5SElJgaWlJVRV3/1u3ZUHVyogKlbRju4/igVTFyDieAQUFP67B3YjQiMwZ+IcnEo+VSn9P6bjB49j3pR52HZ0W7Er0H9qaujXqOwQSp1vypsjfvpnmjHGGGOMMfbV82jlgbTrabibcRfGJsaVHc5n6UX2C8xYPOOzSLi/JHy2GWOMMcYYY5+FvoP6VnYIn7VWHVtVdghfJV5IjTHGGGOMMcZK0Klnpw96NPxD+7PPHyfdjDHGGGOMMcZYBeGkmzHGGGOMMcYYqyCcdDPGGGOMMcYYYxWEk27GGGOMMcYYY6yCcNLNGGOMMcYYY4xVEE66GWOMMcYYY4yxCsJJN2OMMcYYY/8RIkLgqEA0tGmImgY1ER8bX2afW2m3yt32c1DToCYid0e+c79HWY/QxKEJbqXdKrHNmZNnUNOgJp48fvIhIX4xls5dii5Nu3zUfb7vz+9TtGLFCnh5eVX4OIoVPgJjjDHGGGP/kVp/1/pPx9vYfuM7tT8ReQIRGyMQEhECU3NT6OjpVExgFexC1AX4efvhG/tvEHYkTFQXuioUIUtD8ODeA9jVsMP4WeNRy+XDfy4rF65EszbNYGJm8sH7YgwA+vfvj+nTp+P48eNo3LhxhY3Dd7oZY4wxxhj7j6TfSIeBkQGc6zlD30gfioqf3z2wJ4+fYPzQ8ajfuH6Ruj3hezB38lwMHj0YWyK3wK6GHQZ2H4jM+5kfNOaL7BfYtn4bvuv93Qfth4lNGDoBS+curewwKo2ysjJ69eqFxYsXV+g4nHQzxhhjjDH2H5gwdAJm/joTGTczUNOgJlq5tALw6u533/Z94W7tjka2jTCk1xCkpaSVuq+k+CQM6TUE9S3ro55FPfh08BH6yOVyLJ+/HC1qt4CziTO6NO2CE5EnhL6Fj6sf2HkAfp384Gbmhu+afoeYszHlOo5po6eh/Xft4VTXqUjd2hVr0bVPV3Tu1RnWdtaYPH8yVNVUEb4hXNTu/t37GNRjEFxNXdHGrQ3279hf6pjHDx6HsooynNzEYx47cAzt67eHq6kr/Dr54Xba7SJ9L5y+AJ8OPnA1dUULpxaY+etMZD/PFurzcvMwb8o8NK/VHHXN66Jn6544c/KMUB8RGgF3a3dE7o5Eu3rt4FLdBT92+xEZtzKENvGX4+HXyQ/1LOqhvmV9dG/RHZdjLpe7PwAc2nMI3Zp3g0t1F7Rxa4Nl85bh5cuXQv2Tx08weeRkNLZvjPqW9dG/c3/EXxa/cvDXor/QxLEJ6lnUw6QRk5CXk1fqeS1LanIq+nn1g0t1F3Rs1BH/HvlXVN+/c38E/RIkKst6kIU61erg9LHTAIBWLq2wcuFKTBw+EfUs6sGzjie2rN0i6hM8LRjt67eHm5kb2ri1we+zfkd+fr5QHxgYiDp16mD16tUwMzODpqYmhgwZgoKCAsydOxdVq1aFoaEhgoLEsaSlpcHb2xuampqQyWTo3r077t69K2rj5eWFHTt24MWLFx90rkrDSTdjjDHGGGP/gXEzx2HouKEwqmaEI5ePYOP+V4+mv8h+AZ/BPth0YBNWha2CgoICRviOgFwuL3Y/dzPuol/HflBWVsaq8FXYHLkZnXt1RkFBAQDgfyv/h7+X/Y2fp/6MbUe3oVHzRhjadyhSk1NF+1k8czF8h/hi6+GtsLCywNiBY0VJXnHCN4TjZupNDB4zuEhdfl4+rl68igYeDYQyBQUFNGjSABfPXRS1XTJ7CTw7eCLsSBjad2mPMT+OQXJiconjnj99Ho61HUVlGbcyMNJvJJq2boqth7eiS58uWDh9oahNWkoaBvYYiJYdWmLbkW2Y/+d8REdFY+a4mUKboHFBuHj2IuatnIewI2Fo1bEVBvUYJDpfL168wMqFKzFz6Uys27UOT588xZgBY4T6cYPHwaiaETYe2IjNBzfDf7i/6CmGsvqfP3Ue4wPGo8+PfbD9xHZMnj8Z2zdux8qFK4U2o/xHIetBFpZvXI7NBzfDobYDfujyAx4/fAwA2BuxF8vmLcOI8SOw6eAmGBgZYGPIu73+8Ca5XI6RfiOhpKyEDXs3YPK8yVg4TXx+u/Tpgl3bdiEv93Vyv3PrThgZG4mehPh7+d+oWacmth7aiu/9vsf0MdORkpQi1GtoaGDG7zOw/cR2jAsah63rtmLdinWisZKTk7Fnzx7s3bsXoaGhWLVqFdq3b4+bN2/i6NGjmDNnDiZOnIioqCghfm9vb2RlZeHo0aM4cOAArl+/jh49eoj26+bmhpcvXwr9KgIn3YwxxhhjjP0HtGRa0NDQgFQqhb6RPnT1dQEALb1aomWHljCzMoN9LXtMXzQd165eQ3JC8Ulo6KpQaMm0MO/PeahZpyYsrC3QuVdnWH5jCQBYs3QN+g/rj3ad28HyG0uMmjwK9jXtse4PcRLjO8QXHq08YGFtgYBfAnA7/Xapd9hTk1OxcMZCzF4+u9jH4h9mPURBQQH0DPRE5XqGenhw74GorFXHVujatyssrC0w7NdhqFGnBjb8taHEsTNuZsCgqoGobFPIJphamGLMtDGw/MYSHbp2QKfvO4na/LXoL3To2gF9B/WFubU5nOs549eZv2LH5h3IzclFxs0MRIRGIHh1MFzdXWFmaQa/AD+41HdBeOjru/Mv819iwuwJqFO3Dmo41UDQkiDEnI1B7IVYIT73Ju6wsrGCubU5Wnu3hn1N+3L3Xz5/OfyH+8P7e2+YWpiiYdOGGDpuKLb8/eqO8IXTF3D5wmUErwpGzTo1YW5tjjFTx0BLpoX9/7x6SmDdynX4rtd36NKnCyy/scTw8cNhbWdd4jkty6mjp5ByLQUzl86EfU17uDV0w4gJI0RtPNt7Anh1l75QxMYIeH/vDYlEIpQ19myM7/t/DzMrM/gP94eOng7OnHj9NMHAnwfCuZ4zTMxM0LR1U/gG+GLv9r2iseRyOVavXg1HR0d4eXmhWbNmSEhIwG+//QY7Ozv4+fnBzs4Ohw8fBgBERkYiNjYWGzZsgKurK+rXr4+1a9fi6NGjOHv2rLBfdXV1aGtrIzVV/Eepj+nze4mEMcYYY4yxL0hqciqWzFmC2AuxeJj5ULjDnXEzAzYONkXaJ1xOgEt9FygpKRWpe/b0Ge7duQfnes6icud6zki4kiAqs61hK3yvb6QPAMi6nwUrGyvUNa8r1HXo1gET50zE2EFjETA2ABbWFu99rIXefkzcyc2pyKPSb8p5kQPDqoaisuvXrhdZoO3tR94TriQg8Woidm7dKSqXy+W4mXYTN2/cREFBAdrXby+qz8/Lh3YVbWFbUVERNZ1rCttWNlaQactwPfFVDD6DfTDlpyn4Z8s/aNCkAVp1bAUzS7Ny90+4koDoM9GiO9tyuRy5Obl4kf0CCVcSkP08G41sG4nizM3JRfqNdABASmIKuvfrLj4fbk6i5Hbn1p2Y+vNU0XFC8uoPNYVWbFwBV3dXXE+8jqomVUXn/e3zq6KqAq9uXgjfEI42ndrg6sWrSIpLwpJ1S0TtbB1f/1uTSCTQN9RH1oMsoWxP+B6s/3M90m+kI/t5NgoKCqCppSnah4WFBbS0tIRtIyMjSKVSKCgoiMru3bsHAIiLi4OpqSlMTU2FekdHR+jo6CAuLg51677+N66mpobs7NevHHxsnHQzxhhjjDFWiYb2GQrj6sYIDA6EQVUDkJzQqXEn0Tutb1JRVfko4yopvk7aC+9KyulVwh92+PWK5BpaGnj+7DmuxFxBfGy88Gi2XC4HEcGpqhNWblkJl/oukEqlRRZNy7yXCX1D/Q+KtYpelff6GLDs59no5tMNfQb0KVJnXN0YiVcSIZVKsTlyM6QKUlG9uoZ6uccJGBuA9l3a49iBYzgeeRxL5y7FvJXzhDvB5YkzYGxAse1VVFWQ/TwbBkYGCIkIKVKvpa1VpKwkzdo0Q22X2sJ28LRgGBobis6PobFhcV1L1KVPF3Rt1hV3bt9BRGgE6jWuh2qm1URt3vy3BgASSIQ/LsWcjcG4weMwZOwQNGreCFpaWtgTsQd/L/tbvI+3/sgkkUiKLSvptYzSZGVlwcDAoOyG74mTbsYYY4wxxirJo6xHSElKQWBwIFzdXQG8epS4NLY1bLFj0w7k5+cXSTo0tTRhWNUQ0WeiUbfR6zt50WeiUcu5/B/bZWZlJtqWy+UIPyZeDG1jyEacOX4GwauDYWJmAiVlJTg6OSLqWBRatGsh9Is6HoWe/j1FfS+dvwTvHt6ibfta9iiJfS177NwivlttZWOFI/uOiMrefnfcsbYjrideL3I8hRxqO6CgoABZ97OE81+cly9f4krMFeHOekpSCp48fgIrWyuhjYW1BSysLeAzyAdjfhyDiNAIIYkuq79DLQekJKWUGueDew8gVZSW+JFplraWiD0fW+S8vklDUwMamhqibe0q2sWOa2VrhTu37uD+nfvCo/2Xzl0q0s7W0RY16tTA1nVbsWvbLkyYPaHY+EoSczYGxqbGGDhqoFB2O73ognjvysHBAenp6UhPTxfudl+9ehWPHj2Co+Pr9QGSk5ORk5MDZ2fnknb1wfidbsYYY4wxxiqJTEcGHV0dbFm3BWnX0xB1PApzJ88ttU8v/1549vQZxgwYg8sxl5GanIodm3cIC1P5Bfhh9e+rsSd8D1KSUrBw2kLEX45Hnx+L3u0tLwUFBdg42Ii+dPV1oayiDBsHG+GusM8gH2z931Zs37gdyYnJmD5mOl5kv0Cnnp1E+9u/Yz+2rd+GG8k3hEfre/n3KnH8Rs0aITkhGY8fPRbKevj2QOr1VMwPnI+UpBTsCtuF7Ru3i/r1H9YfMWdjEPRLEOJj45GanIpDew4JK25bWFugfdf2GD90PA7sPICbqTcReyEWf/72J47uPyrsR1FJETN/nYlL5y/hysUrmDhsIpzcnFDLpRZyXuQg6JcgnDl5BrfTb+NC1AVcjr4sSshL6w8Ag0cPxj+b/8GyecuQFJ+E5MRk7A7fjcUzX32UlbuHO5zcnDDcZzhOHj6JW2m3EH0mGouCFgmrpPcZ0AfhoeEI3xAunNek+KR3/VEL3D3cYW5tjvHDxiP+cjzOnzqPRTMXFdu2S58uWLV4FYhI+INLeZlbmePOzTvYHb4baSlp+N/K/yFyd+R7x13I09MTtWrVQu/evXHhwgWcOXMGPj4+8PDwgJubm9Du+PHjsLKygrX1+7//XhZOuhljjDHGGKskCgoKmLdyHq5evIpOTTphzqQ5+HnKz6X20dHVwaptq5D9PBt+3n7o7tkdYevChMXNev/YGz6DfTB/ynx0btIZJw6dwJJ1S2BubV7hx9O2c1uMDhyNJXOWoGuzroi/HI8Vm1YUebw8YGwA9kTswXce3+Gfzf9g7h9zS130y9bRFg61HbBv+z6hzLi6MRaGLMSh3YfQpWkXbF6zuchCX3Y17BCyPQQ3rt+Aj5cPujbviiVzlogWZZuxeAa8unth/pT56ODeAcN9huNyzGUYVzcW2qipqaH/sP4YO2gs+rbvCzUNNcz/cz4AQCqV4tHDRxgfMB7tG7TH6B9Go3GLxggYG1Cu/gDQqHkjLF2/FP8e/hfft/oevdv0xroV64THtCUSCZZvXA5Xd1dMGj4J7Ru8WvH99s3bwsJ1bTu3xcBRAxE8LRjdW3RHRnoGeviJV+p+FwoKClj09yLkvshFz9Y9MeWnKRgxfkSxbdt1bgdFRUW069zunV9/aNamGfoO6ouZ42aia7OuiDkbg0GjBr133IUkEgm2b9+OKlWqoEmTJvD09ISVlRU2bdokahcaGooBAwZ88HilxkJEVKEjfCGePHkCbW1tPH78GDKZrLLDKZHFuF2VHQJjrBxuzG5fdqMvRaB22W0YY5Uv8HHZbT4ROTk5SElJgaWlJVRVVd+5/5UHVyogKlbRju4/igVTFyDieIRo8ayKFhEagTkT5+BU8qlK6f85uJV2C23rtsXG/Rvh6ORYdodyqqFf46PtqzhXrlxB8+bNkZiYCG3t4q9XSptvypsj8jvdjDHGGGOMsU+eRysPpF1Pw92MuzA2MS67A6tw+fn5eJz1GItnLUZt19ofNeH+L2RkZGDt2rUlJtwfCyfdjDHGGGOMsc9C30F9KzsE9oboM9Ho36k/LKwtELw6uLLDeWeenuVbXf5DcdLNGGOMMcYYYyXo1LNTkYXg/sv+n7J6jerh8v3LlR3GJ48XUmOMMcYYY4wxxioIJ92MMcYYY4wxxlgF4aSbMcYYY4x9lvhDeBhjFe1jzDOcdDPGGGOMsc+KkpISACA7O7uSI2GMfekK55nCeed98EJqjDHGGGPssyKVSqGjo4N79+4BANTV1SGRSMrdX54vr6jQGGMfUU5OTqWNTUTIzs7GvXv3oKOjA6lU+t774qSbMcYYY4x9dqpWrQoAQuL9Lu49e/c+jLH/nuKjyk9XdXR0hPnmfVX+UTDGGGOMMfaOJBIJjI2NYWhoiPz8/HfqOyJ8RAVFxRj7mHZ03lGp4yspKX3QHe5CX1XSvXTpUsybNw937tyBk5MTfv/9d9SrV6+yw2KMMcYYY+9JKpW+80VxRl5GBUXDGPuYVFVVKzuEj+KrWUht06ZNGDVqFKZMmYILFy7AyckJrVu3fq9HkhhjjDHGGGOMsfL4apLu4OBgDBgwAH5+fnB0dMSKFSugrq6O1atXV3ZojDHGGGOMMca+UF9F0p2Xl4fz58/D09NTKFNQUICnpydOnTpViZExxhhjjDHGGPuSfRXvdD948AAFBQUwMjISlRsZGSE+Pr7YPrm5ucjNzRW2Hz9+DAB48uRJxQX6Echz+fMqGfscfOpzyUeVS5UdAWOsPL6ieangRUFlh8AYK4dP/XqpMD6i0q91voqk+33MmjULU6dOLVJuampaCdEwxr402r9VdgSMMfaW2dqVHQFjjIloD/485qWnT59CW7vkWL+KpFtfXx9SqRR3794Vld+9e7fEz1z79ddfMWrUKGFbLpcjKysLenp6kEgkFRovY4WePHkCU1NTpKenQyaTVXY4jDHG8xJj7JPD8xKrLESEp0+folq1aqW2+yqSbmVlZbi6uiIyMhKdOnUC8CqJjoyMxNChQ4vto6KiAhUVFVGZjo5OBUfKWPFkMhn/J8IY+6TwvMQY+9TwvMQqQ2l3uAt9FUk3AIwaNQr9+vWDm5sb6tWrh99++w3Pnz+Hn59fZYfGGGOMMcYYY+wL9dUk3T169MD9+/cxefJk3LlzB3Xq1MHevXuLLK7GGGOMMcYYY4x9LF9N0g0AQ4cOLfFxcsY+RSoqKpgyZUqRVx0YY6yy8LzEGPvU8LzEPnUSKmt9c8YYY4wxxhhjjL0XhcoOgDHGGGOMMcYY+1Jx0s0YY4wxxhhjjFUQTroZ+39r1qz5aj8W7ms+dsY+V02bNsXIkSMrO4xPgkQiQURERGWHwVil4fngtY89HwQGBqJOnTofbX/s68RJN2OVwNfXV/jM+E9Bjx49kJiYWNlhMMYYY4wx9sXhpJuxjyg/P7+yQ3gvampqMDQ0rOwwGGOMMcYqzI0bNyCRSCo7DPYV4qSbfVL27t2Lb7/9Fjo6OtDT00OHDh2QnJws1N+8eRM9e/aErq4uNDQ04ObmhqioKKH+n3/+Qd26daGqqgp9fX107txZqMvNzcXo0aNhYmICDQ0N1K9fH0eOHCk1nu3bt8PFxQWqqqqwsrLC1KlT8fLlS6FeIpFg+fLl6NixIzQ0NBAUFISCggL4+/vD0tISampqsLOzw6JFi4Q+gYGB+Pvvv7F9+3ZIJBJIJBIhjvT0dHTv3h06OjrQ1dWFt7c3bty4UWqMTZs2xfDhwzF27Fjo6uqiatWqCAwMFLUJDg5GrVq1oKGhAVNTUwwZMgTPnj0T6t98vDwxMRESiQTx8fGifSxcuBDW1tbC9uXLl9G2bVtoamrCyMgIffv2xYMHD0qN1cLCAjNmzICPjw80NTVhbm6OHTt24P79+/D29oampiZq166Nc+fOFYktIiICNjY2UFVVRevWrZGenl7qWIx9SZ4/fy783hgbG2PBggWi+vLMbydOnEDjxo2hpqYGU1NTDB8+HM+fPxfqLSwsMH36dPTs2RMaGhowMTHB0qVLhXoiQmBgIMzMzKCiooJq1aph+PDh5e4PAI8ePcIPP/wAAwMDyGQyNG/eHBcvXhS1KWvevXbtGpo0aQJVVVU4OjriwIED731eGfsc8XxQsfPB7NmzYWRkBC0tLfj7+yMnJ0eoO3bsGJSUlHDnzh1Rn5EjR6Jx48YAXl+37Nu3Dw4ODtDU1ESbNm2QkZEhtD979ixatmwJfX19aGtrw8PDAxcuXBDtUyKR4I8//kCHDh2grq4OBwcHnDp1CklJSWjatCk0NDTQsGFD0XUyACxfvhzW1tZQVlaGnZ0d1q1b98HnhH0ExNgnZOvWrRQWFkbXrl2j6Oho8vLyolq1alFBQQE9ffqUrKysqHHjxnT8+HG6du0abdq0if79918iItq5cydJpVKaPHkyXb16lWJiYmjmzJnCvn/44Qdq2LAhHTt2jJKSkmjevHmkoqJCiYmJREQUEhJC2traQvtjx46RTCajNWvWUHJyMu3fv58sLCwoMDBQaAOADA0NafXq1ZScnEypqamUl5dHkydPprNnz9L169fpf//7H6mrq9OmTZuIiOjp06fUvXt3atOmDWVkZFBGRgbl5uZSXl4eOTg4UP/+/enSpUt09epV6tWrF9nZ2VFubm6J58zDw4NkMhkFBgZSYmIi/f333ySRSGj//v1Cm4ULF9KhQ4coJSWFIiMjyc7OjgYPHizUv33sbm5uNHHiRNE4rq6uQtnDhw/JwMCAfv31V4qLi6MLFy5Qy5YtqVmzZqX+fM3NzUlXV5dWrFhBiYmJNHjwYJLJZNSmTRvavHkzJSQkUKdOncjBwYHkcrkQm5KSErm5udG///5L586do3r16lHDhg1LHYuxL8ngwYPJzMyMDh48SJcuXaIOHTqQlpYWjRgxgojKnt+SkpJIQ0ODFi5cSImJiXTy5ElydnYmX19fYQxzc3PS0tKiWbNmUUJCAi1evJikUqkwl2zZsoVkMhnt3r2bUlNTKSoqilauXFnu/kREnp6e5OXlRWfPnqXExET6+eefSU9PjzIzM4mo7Hm3oKCAatasSS1atKCYmBg6evQoOTs7EwAKDw+vyB8BY58Mng/efz5ISUmh0tKfTZs2kYqKCv31118UHx9PEyZMIC0tLXJychLa2Nra0ty5c4XtvLw80tfXp9WrVxPR6+sWT09POnv2LJ0/f54cHByoV69eQp/IyEhat24dxcXF0dWrV8nf35+MjIzoyZMnQhsAZGJiQps2bRKujywsLKh58+a0d+9eunr1KjVo0IDatGkj9Nm2bRspKSnR0qVLKSEhgRYsWEBSqZQOHTpU4jGz/wYn3eyTdv/+fQJAsbGx9Mcff5CWlpYwGb/N3d2devfuXWxdamoqSaVSunXrlqi8RYsW9OuvvxJR0cSzRYsWoqSdiGjdunVkbGwsbAOgkSNHlnkcAQEB1KVLF2G7X79+5O3tXWTfdnZ2QrJJRJSbm0tqamq0b9++Evft4eFB3377raisbt269Msvv5TYZ8uWLaSnpydsv33sCxcuJGtra2E7ISGBAFBcXBwREU2fPp1atWol2md6ejoBoISEhBLHNTc3pz59+gjbGRkZBIAmTZoklJ06dYoAUEZGhhAbADp9+rTQJi4ujgBQVFRUiWMx9qV4+vQpKSsr0+bNm4WyzMxMUlNToxEjRpRrfvP396cff/xRVH/8+HFSUFCgFy9eENGr3883L96IiHr06EFt27YlIqIFCxaQra0t5eXlFRtnWf2PHz9OMpmMcnJyRG2sra3pjz/+EGIubd7dt28fKSoqio51z549nHSzrwbPBx82H5SVdLu7u9OQIUNEZfXr1xcl3XPmzCEHBwdhOywsjDQ1NenZs2dE9Pq6JSkpSWizdOlSMjIyKnHcgoIC0tLSon/++UcoAyC6AVJ4fbRq1SqhLDQ0lFRVVYXthg0b0oABA0T77tatG7Vr167Esdl/gx8vZ5+Ua9euoWfPnrCysoJMJoOFhQUAIC0tDTExMXB2doaurm6xfWNiYtCiRYti62JjY1FQUABbW1toamoKX0ePHi3yWE6hixcvYtq0aaL2AwYMQEZGBrKzs4V2bm5uRfouXboUrq6uMDAwgKamJlauXIm0tLRSj/3ixYtISkqClpaWMJ6uri5ycnKQnJyM48ePi2JZv3690Ld27dqifRkbG+PevXvC9sGDB9GiRQuYmJhAS0sLffv2RWZmpug43vT999/jxo0bOH36NABg/fr1cHFxgb29vRDr4cOHRfEU1iUnJ2P9+vWiuuPHjxcbq5GREQCgVq1aRcrejF9RURF169YVtu3t7aGjo4O4uLhSzyljX4Lk5GTk5eWhfv36Qpmuri7s7OwAlG9+u3jxItasWSOqb926NeRyOVJSUoT9uru7i8Z2d3cXfs+6deuGFy9ewMrKCgMGDEB4eLjoMc+y+l+8eBHPnj2Dnp6eKI6UlBRRnKXNu3FxcTA1NUW1atVKHJOxLxnPB+8+H9SoUUPoX6NGDQAQ7bNt27ZC27i4ONG5LW6fvr6+SEpKEq6R1qxZg+7du0NDQ0Noo66uLnol7+3rsrt372LAgAGwsbGBtrY2ZDIZnj17VuRasTzXTDk5OXjy5IkQf6NGjUT7aNSoEV8vfQIUKzsAxt7k5eUFc3Nz/Pnnn6hWrRrkcjlq1qyJvLw8qKmpldq3tPpnz55BKpXi/PnzkEqlojpNTc0S+0ydOhXfffddkTpVVVXh+zcnWQDYuHEjRo8ejQULFsDd3R1aWlqYN2+e6N3zksZzdXUVJdOFDAwMoKysjJiYGKGscPIFACUlJVF7iUQCuVwO4NWiIR06dMDgwYMRFBQEXV1dnDhxAv7+/sjLy4O6unqR8apWrYrmzZtjw4YNaNCgATZs2IDBgweLYvXy8sKcOXOK9DU2NoZcLhf9p2ViYlJsrIWLmRRXVhg/Y6x05Znfnj17hoEDB4reuSxkZmZWrnFMTU2RkJCAgwcP4sCBAxgyZAjmzZuHo0ePFpmDSorT2Ni42LU0CteUKO+8yxgrHs8HRe3evVtY6PbWrVto2rSp6HqqrOvLtxkaGsLLywshISGwtLTEnj17ihxHcddlRCRs9+vXD5mZmVi0aBHMzc2hoqICd3d35OXllbgfvmb6vHHSzT4ZmZmZSEhIwJ9//iksRnHixAmhvnbt2vjrr7+QlZVV7N3u2rVrIzIyEn5+fkXqnJ2dUVBQgHv37gn7LouLiwsSEhLwzTffvNNxnDx5Eg0bNsSQIUOEsrfvpisrK6OgoKDIeJs2bYKhoSFkMlmx+37XWADg/PnzkMvlWLBgARQUXj3csnnz5jL79e7dG2PHjkXPnj1x/fp1fP/996JYw8LCYGFhAUXF4qcRLS2td461JC9fvsS5c+dQr149AEBCQgIePXoEBweHjzYGY58qa2trKCkpISoqSrggfvjwIRITE+Hh4VGu+c3FxQVXr14tcw4pvHPz5vabv2dqamrw8vKCl5cXAgICYG9vj9jYWLi4uJTZ38XFBXfu3IGioqLwFFNxcZY27zo4OCA9PR0ZGRkwNjYudkzGvmQ8H7xW3vnA3Nxc+L7wmqW0fUZFRcHHx6fE8wAAP/zwA3r27Inq1avD2tq6yN3lspw8eRLLli1Du3btALxaSLesxWjLw8HBASdPnkS/fv1EYzk6On7wvtkHquzn2xkrVFBQQHp6etSnTx+6du0aRUZGUt26dYV3c3Jzc8nW1pYaN25MJ06coOTkZNq6dauwkNrhw4dJQUFBWEjt0qVLNHv2bGH/vXv3JgsLCwoLC6Pr169TVFQUzZw5k3bu3ElERd9r3rt3LykqKlJgYCBdvnyZrl69SqGhoTRhwgShDYp5b2jRokUkk8lo7969lJCQQBMnTiSZTCZ6HygoKIjMzMwoPj6e7t+/T3l5efT8+XOysbGhpk2b0rFjx+j69et0+PBhGjZsGKWnp5d43jw8PITFUwp5e3tTv379iIgoJiaGANBvv/1GycnJtHbtWjIxMSEA9PDhw2KPnYjoyZMnpKamRk5OTtSiRQtR3a1bt8jAwIC6du1KZ86coaSkJNq7dy/5+vrSy5cvS4zV3NycFi5cKCp7+xwWvm8VHR0txKakpET16tWj06dP07lz56hBgwbUoEGDEsdh7EszaNAgMjc3p8jISIqNjaWOHTuSpqam8Ltf1vx28eJFUlNTo4CAAIqOjqbExESKiIiggIAAYQxzc3OSyWQ0Z84cSkhIoCVLlpBUKqW9e/cS0avfxb/++otiY2MpOTmZJk6cSGpqavTgwYNy9ZfL5fTtt9+Sk5MT7du3j1JSUujkyZM0fvx4Onv2LBGVPe8WFBSQo6MjtWzZkmJiYujYsWPk6urK73SzrwrPB+8/H5T1TvfGjRtJVVWVVq9eTQkJCTR58uQiC6kVjm1qakrKysqia83Cc/P2NVV4eLhoXGdnZ2rZsiVdvXqVTp8+TY0bNyY1NTXRNVJZ10dEr65937yeCw8PJyUlJVq2bBklJiYKC6kdPny4xGNm/w1Outkn5cCBA+Tg4EAqKipUu3ZtOnLkiGjSuXHjBnXp0oVkMhmpq6uTm5ubaDGtsLAwqlOnDikrK5O+vj599913Ql3hquIWFhakpKRExsbG1LlzZ7p06RIRFT9J7t27lxo2bEhqamokk8moXr16otU5i5vYc3JyyNfXl7S1tUlHR4cGDx5M48aNE03Y9+7do5YtW5KmpiYBECbDjIwM8vHxIX19fVJRUSErKysaMGAAPX78uMRzVlbSTUQUHBxMxsbGpKamRq1bt6a1a9eWmXQTEXXv3p0ACCtyvikxMZE6d+5MOjo6pKamRvb29jRy5EjRQnBve9+kW1tbm8LCwsjKyopUVFTI09OTUlNTSxyHsS/N06dPqU+fPqSurk5GRkY0d+5c0e9+WfMbEdGZM2eEeUdDQ4Nq165NQUFBQr25uTlNnTqVunXrRurq6lS1alVatGiRUB8eHk7169cnmUxGGhoa1KBBAzp48GC5+xO9+mPesGHDqFq1aqSkpESmpqbUu3dvSktLE9qUNe8mJCTQt99+S8rKymRra0t79+7lpJt9VXg+eP/5oKykm+jVjRF9fX3S1NSkfv360dixY4sk3UREkyZNIqlUSrdv3xaVlyfpvnDhArm5uZGqqirZ2NjQli1bilwjvU/STUS0bNkysrKyIiUlJbK1taW1a9eWerzsvyEheuMFA8YY+8SsWbMGI0eOxKNHjyo7FMa+aBYWFhg5ciRGjhxZKf0ZY58Ong/K5u/vj/v372PHjh2VHQr7DPA73YwxxhhjjDFWDo8fP0ZsbCw2bNjACTcrN066GWOMMcYYY6wcvL29cebMGQwaNAgtW7as7HDYZ4IfL2eMMcYYY4wxxiqIQmUHwBhjjDHGGGOMfak46WaMMcYYY4wxxioIJ92MMcYYY4wxxlgF4aSbMcYYY4wxxhirIJx0M8YYY4wxxhhjFYSTbsYYY+wTFxgYiDp16nzQPm7cuAGJRIKYmJiPElNJmjZtipEjR1boGIwxxtjnhJNuxhhj7AOlp6ejf//+qFatGpSVlWFubo4RI0YgMzPznfclkUgQEREhKhs9ejQiIyM/KEZTU1NkZGSgZs2aH7SfQkeOHIFEIsGjR49E5du2bcP06dM/yhjFCQwMhEQiKfWLMcYY+5Rw0s0YY4x9gOvXr8PNzQ3Xrl1DaGgokpKSsGLFCkRGRsLd3R1ZWVkfPIampib09PQ+aB9SqRRVq1aFoqLiB8dTGl1dXWhpaVXY/kePHo2MjAzhq3r16pg2bZqojDHGGPuUcNLNGGOMfYCAgAAoKytj//798PDwgJmZGdq2bYuDBw/i1q1bmDBhgtDWwsIC06dPR8+ePaGhoQETExMsXbpUVA8AnTt3hkQiEbbffrzc19cXnTp1wsyZM2FkZAQdHR1MmzYNL1++xJgxY6Crq4vq1asjJCRE6PP24+W+vr7F3iU+cuQIAGDdunVwc3ODlpYWqlatil69euHevXvCvpo1awYAqFKlCiQSCXx9fQEUfbz84cOH8PHxQZUqVaCuro62bdvi2rVrQv2aNWugo6ODffv2wcHBAZqammjTpk2JybOmpiaqVq0qfEmlUiHGlStXwtPTs0ifOnXqYNKkSaJzN3XqVBgYGEAmk2HQoEHIy8sT2svlcsyaNQuWlpZQU1ODk5MTtm7dWmw8jDHGWFk46WaMMcbeU1ZWFvbt24chQ4ZATU1NVFe1alX07t0bmzZtAhEJ5fPmzYOTkxOio6Mxbtw4jBgxAgcOHAAAnD17FgAQEhKCjIwMYbs4hw4dwu3bt3Hs2DEEBwdjypQp6NChA6pUqYKoqCgMGjQIAwcOxM2bN4vtv2jRItHd4REjRsDQ0BD29vYAgPz8fEyfPh0XL15EREQEbty4ISTWpqamCAsLAwAkJCQgIyMDixYtKnYcX19fnDt3Djt27MCpU6dARGjXrh3y8/OFNtnZ2Zg/fz7WrVuHY8eOIS0tDaNHjy7t1Berf//+iIuLE5236OhoXLp0CX5+fkJZZGQk4uLicOTIEYSGhmLbtm2YOnWqUD9r1iysXbsWK1aswJUrV/DTTz+hT58+OHr06DvHxBhjjIEYY4wx9l5Onz5NACg8PLzY+uDgYAJAd+/eJSIic3NzatOmjahNjx49qG3btsJ2cfubMmUKOTk5Cdv9+vUjc3NzKigoEMrs7OyocePGwvbLly9JQ0ODQkNDiYgoJSWFAFB0dHSROMPCwkhVVZVOnDhR4rGePXuWANDTp0+JiOjw4cMEgB4+fChq5+HhQSNGjCAiosTERAJAJ0+eFOofPHhAampqtHnzZiIiCgkJIQCUlJQktFm6dCkZGRmVGMubzM3NaeHChcJ227ZtafDgwcL2sGHDqGnTpsJ2v379SFdXl54/fy6ULV++nDQ1NamgoIBycnJIXV2d/v33X9E4/v7+1LNnz3LFxBhjjL2J73QzxhhjH4jeuJNdFnd39yLbcXFx7zxmjRo1oKDw+r9xIyMj1KpVS9iWSqXQ09MTHgkvSXR0NPr27YslS5agUaNGQvn58+fh5eUFMzMzaGlpwcPDAwCQlpZW7hjj4uKgqKiI+vXrC2V6enqws7MTHbO6ujqsra2FbWNj4zLjLsmAAQMQGhqKnJwc5OXlYcOGDejfv7+ojZOTE9TV1YVtd3d3PHv2DOnp6UhKSkJ2djZatmwJTU1N4Wvt2rVITk5+r5gYY4x93Sp2NRXGGGPsC/bNN99AIpEgLi4OnTt3LlIfFxeHKlWqwMDA4KOPraSkJNqWSCTFlsnl8hL3cefOHXTs2BE//PAD/P39hfLnz5+jdevWaN26NdavXw8DAwOkpaWhdevWonefP5bi4n6XP2S8ycvLCyoqKggPD4eysjLy8/PRtWvXcvd/9uwZAGDXrl0wMTER1amoqLxXTIwxxr5unHQzxhhj70lPTw8tW7bEsmXL8NNPP4ne675z5w7Wr18PHx8f0cdYnT59WrSP06dPw8HBQdhWUlJCQUFBhceek5MDb29v2NvbIzg4WFQXHx+PzMxMzJ49G6ampgCAc+fOidooKysDQKmxOjg44OXLl4iKikLDhg0BAJmZmUhISICjo+PHPByBoqIi+vXrh5CQECgrK+P7778v8r79xYsX8eLFC6H89OnT0NTUhKmpKXR1daGiooK0tDTh7j5jjDH2ITjpZowxxj7AkiVL0LBhQ7Ru3RozZsyApaUlrly5gjFjxsDExARBQUGi9idPnsTcuXPRqVMnHDhwAFu2bMGuXbuEegsLC0RGRqJRo0ZQUVFBlSpVKiTugQMHIj09HZGRkbh//75QrqurCzMzMygrK+P333/HoEGDcPny5SKfvW1ubg6JRIKdO3eiXbt2UFNTg6ampqiNjY0NvL29MWDAAPzxxx/Q0tLCuHHjYGJiAm9v7wo5LgD44YcfhD9knDx5skh9Xl4e/P39MXHiRNy4cQNTpkzB0KFDoaCgAC0tLYwePRo//fQT5HI5vv32Wzx+/BgnT56ETCZDv379KixuxhhjXyZ+p5sxxhj7ADY2Njh37hysrKzQvXt3WFtb48cff0SzZs1w6tQp6Orqitr//PPPOHfuHJydnTFjxgwEBwejdevWQv2CBQtw4MABmJqawtnZucLiPnr0KDIyMuDo6AhjY2Ph699//4WBgQHWrFmDLVu2wNHREbNnz8b8+fNF/U1MTDB16lSMGzcORkZGGDp0aLHjhISEwNXVFR06dIC7uzuICLt37y7ySPnHZGNjg4YNG8Le3l70PnmhFi1awMbGBk2aNEGPHj3QsWNHBAYGCvXTp0/HpEmTMGvWLDg4OKBNmzbYtWsXLC0tKyxmxhhjXy4Jve9LU4wxxhh7JxYWFhg5cqToc6zZx0dEsLGxwZAhQzBq1ChRna+vLx49eoSIiIjKCY4xxthXhx8vZ4wxxtgX4/79+9i4cSPu3Lkj+mxuxhhjrLJw0s0YY4yxL4ahoSH09fWxcuXKCnsfnjHGGHsX/Hg5Y4wxxhhjjDFWQXghNcYYY4wxxhhjrIJw0s0YY4wxxhhjjFUQTroZY4wxxhhjjLEKwkk3Y4wxxhhjjDFWQTjpZowxxhhjjDHGKggn3YwxxhhjjDHGWAXhpJsxxhhjjDHGGKsgnHQzxhhjjDHGGGMVhJNuxhhjjDHGGGOsgvwfUU5wN4lBIwIAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Assuming the CSV is already read into combined_df\n",
+    "# Convert the timestamp column to datetime type\n",
+    "combined_df['timestamp'] = pd.to_datetime(combined_df['timestamp'])\n",
+    "\n",
+    "# Filter for falcon-40b, 1 process, 1 node, and 4 GPUs\n",
+    "df_filtered = combined_df[(combined_df['model'] == 'falcon-40b') & \n",
+    "                          (combined_df['num_processes'] == 1) & \n",
+    "                          (combined_df['num_nodes'] == 1) & \n",
+    "                          (combined_df['num_gpus'] == 4)]\n",
+    "\n",
+    "# Calculate experiment duration for each parallelism type\n",
+    "df_grouped_duration = df_filtered.groupby('model_parallelism').apply(lambda x: (x['timestamp'].max() - x['timestamp'].min()).seconds).reset_index()\n",
+    "df_grouped_duration.columns = ['model_parallelism', 'experiment_duration']\n",
+    "\n",
+    "# Plotting experiment duration\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "\n",
+    "for parallelism, duration in zip(df_grouped_duration['model_parallelism'], df_grouped_duration['experiment_duration']):\n",
+    "    plt.bar(parallelism, duration, label=f\"falcon-40b ({parallelism})\")\n",
+    "    plt.annotate(f\"{duration:.2f}s\", \n",
+    "                 (parallelism, duration),\n",
+    "                 textcoords=\"offset points\",\n",
+    "                 xytext=(0, 10),\n",
+    "                 ha='center')\n",
+    "\n",
+    "plt.title('Experiment Duration for falcon-40b (1 Process, 1 Node, 4 GPU)')\n",
+    "plt.xlabel('Optimization Type')\n",
+    "plt.ylabel('Duration (seconds)')\n",
+    "plt.legend(loc='lower right')\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}