Hugging Face's logo

Spaces:
sagawa
/
ReactionT5
Running

App Files Community
ReactionT5
File size: 80,276 Bytes 
08ccc8e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
 
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92432099",
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1112/1112 [3:05:38<00:00, 10.02s/it]\n",
    "Top-1: 0.5% || Invalid 16.69%\n",
    "Top-2: 1.0% || Invalid 23.80%\n",
    "Top-3: 1.6% || Invalid 28.18%\n",
    "Top-4: 2.1% || Invalid 31.25%\n",
    "Top-5: 2.5% || Invalid 33.73%\n",
    "prediction: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1112/1112 [3:05:18<00:00, 10.00s/it]\n",
    "Top-1: 0.2% || Invalid 22.41%\n",
    "Top-2: 0.7% || Invalid 28.65%\n",
    "Top-3: 1.0% || Invalid 32.95%\n",
    "Top-4: 1.3% || Invalid 36.12%\n",
    "Top-5: 1.6% || Invalid 38.94%\n",
    "prediction: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1112/1112 [3:07:23<00:00, 10.11s/it]\n",
    "Top-1: 0.2% || Invalid 31.81%\n",
    "Top-2: 0.6% || Invalid 36.80%\n",
    "Top-3: 0.8% || Invalid 40.56%\n",
    "Top-4: 1.0% || Invalid 43.56%\n",
    "Top-5: 1.1% || Invalid 46.23%\n",
    "prediction: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1112/1112 [3:04:23<00:00,  9.95s/it]\n",
    "Top-1: 0.1% || Invalid 57.28%\n",
    "Top-2: 0.3% || Invalid 61.50%\n",
    "Top-3: 0.3% || Invalid 64.65%\n",
    "Top-4: 0.4% || Invalid 67.02%\n",
    "Top-5: 0.4% || Invalid 69.05%\n",
    "prediction: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1112/1112 [3:07:16<00:00, 10.10s/it]\n",
    "Top-1: 0.4% || Invalid 64.24%\n",
    "Top-2: 0.6% || Invalid 67.45%\n",
    "Top-3: 0.7% || Invalid 69.89%\n",
    "Top-4: 0.7% || Invalid 71.78%\n",
    "Top-5: 0.8% || Invalid 73.41%\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6a089a12",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_2056154/465102246.py:21: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  ax.set_yticklabels([int(i) for i in ax.get_yticks()], fontsize=12)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f69ce998510>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAqkAAAG3CAYAAACXEsyxAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8g+/7EAAAACXBIWXMAAA9hAAAPYQGoP6dpAABX/klEQVR4nO3deZyNdf/H8feZ7cxmDmOGGcvYQoSQVG5LpYWKViq5SYlSSdLdrU1UKEvqp/WOFOlOypIlEW6EEApZx9LMGGafM/t2rt8fx5xxzFgGM3MNr+fjcR6c7/W5rvO9zlzL+1zLORbDMAwBAAAAJuJR0R0AAAAATkVIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOmUOqSmp6dr1KhR6tatm4KDg2WxWDRjxowSa3fv3q1u3bopMDBQwcHB+uc//6n4+PhidQ6HQ++++64aNGggX19ftWrVSt98802pZwYAAACXhlKH1ISEBI0ZM0a7d+/W1Vdffdq66Ohode7cWQcOHNDYsWM1YsQILV68WLfeeqtyc3Pdal955RW99NJLuvXWW/V///d/ioiIUJ8+ffTf//639HMEAACASs9iGIZRmhFycnKUnJyssLAwbdmyRddee62++OILPfroo251Q4YM0YwZM7Rnzx5FRERIklasWKFbb71Vn376qQYNGiRJiomJUYMGDTRo0CBNnTpVkmQYhrp06aJDhw7p8OHD8vT0vAizCgAAgMqi1EdSrVarwsLCzlr3/fff66677nIFVEm65ZZb1KRJE82ZM8fVtmDBAuXl5WnIkCGuNovFoqeeekrR0dHasGFDabsIAACASs6rLCYaExOjuLg4tWvXrtiw9u3ba8mSJa7n27ZtU0BAgJo1a1asrnB4x44di00nJydHOTk5rucOh0NJSUmqXr26LBbLxZoVAAAAXCSGYSgtLU21atWSh8eZj5WWSUiNjY2VJIWHhxcbFh4erqSkJOXk5MhqtSo2NlY1a9YsFiwLxz169GiJrzFu3DiNHj36IvccAAAAZS0qKkp16tQ5Y02ZhNSsrCxJzksDTuXr6+uqsVqtrn/PVFeSkSNHavjw4a7nqampioiIUFRUlIKCgi54HgAAAHBx2e121a1bV1WqVDlrbZmEVD8/P0lyOx1fKDs7263Gz8/vnOpOZbVaSwy3QUFBhFQAAAATO5dLM8vky/wLT9UXnvY/WWxsrIKDg10BMzw8XMeOHdOpXzJQOG6tWrXKoosAAAAwsTIJqbVr11ZoaKi2bNlSbNimTZvUunVr1/PWrVsrMzNTu3fvdqv77bffXMMBAABweSmzn0W9//77tWjRIkVFRbnafvnlF+3bt0+9evVytd19993y9vbWRx995GozDEOffPKJateurQ4dOpRVFwEAAGBS53VN6tSpU5WSkuK68/7HH39UdHS0JOnZZ5+VzWbTyy+/rO+++0433XSTnnvuOaWnp2vChAlq2bKlBgwY4JpWnTp1NGzYME2YMEF5eXm69tprNX/+fK1du1Zff/01X+QPAABwGSr1L05JUv369XXkyJEShx06dEj169eXJO3atUvDhw/XunXr5OPjozvvvFOTJk1SzZo13cZxOBx655139Omnnyo2NlaNGzfWyJEj9cgjj5xzn+x2u2w2m1JTU7lxCgAAwIRKk9fOK6SaESEVAADA3EqT18rsmlQAAADgfBFSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJiOV0V3AAAAABXA4ZB27ZKSk6Vq1aSrrpI8zHP8kpAKnMzkKywqIZYpAGa0fr00daq0e7eUkyNZrVKzZtIzz0gdOlR07yQRUs/f5bTjuVzmtRKssKhkWKYAmNH69dKIEVJSkhQeLvn5SVlZ0rZtzvaJE02xjbIYhmFUdCcuBrvdLpvNptTUVAUFBZXti11OO57LZV5Pt8IeO+YM5iZZYVGJsEwBMCOHQ+rbV9q6VbriCsliKRpmGFJkpNS2rTRzZpkckCpNXiOkltbltOO5XOa1gldYXCQnb8oMo+j5qe1nqi2p5ky1pxvf4ZAGDZL++ENq2LBomSqsPXxYatVK+vBD5zJ1utc/l76fqa2sakua9/IY/0zv/fn8nc71tUrz3p1t/NL260zjl/UyUVIfL/bfqTxfy6zLxNnGv9jvXUKCtGKF86CT10kn1K+4wrmfT0+XUlKkr76SWrbUxVaavMbp/tJwOJxHFZOSpFq1nIEtO9s5zGaTYmKk11+XRo6s/GHG4ZDGjpWio53zmp1dNK9BQc72V191hliLpWjlcDiK/l/Sw+Eomn7hv6eru9BpnGk6J497/Li0cqVz5dy3z9l+8gqem+tcoQcNkkJDi9orasdhtp1MaTbGZbHhNiO7Xdq+3bkDsNuLD8/Pl5Yvl3r3dq5PAFBeEhOd+3OLRcrLK2ov3C/6+Tn3i8nJFdO/kxBSS2PXLudp7/Bw5x/v6FH34fn50ubN0pgxlX/Hc/JO9tCh4sPz86Xff5feeafyz2tiopSR4VxBTz6KWsgwnB9I/vpLql69/PuHyic/37k8eXmVvEx5eTk//BiG5OPjPsxicR+n8P+ntp+t9mzjn632Yo5fVrUX67XOZfzSvvdnGr807/OFjn8pLRMXY/zS/J3O9lqVdZk4cMB5kKlKFcnfv6jd19f5b1aW8yhrtWqqaITU0khOdl6X6efn/BRis7kPdzik1FSpQQOpXr2K6ePFcuSIM5TZbEVHhU9eyAvntXFjqVEjZ5uHR9HKUNKjcDol1Z087EzTOtvwc6k5dfjhw86wHRjo/NueujHIynKe/hg8uGheC98PM+xkSnqN8tzwl+dO4tTxzPg+S9KOHVK/flLVqs7l6lSFp9M+/LBMTqcBwGm1aiX98IPzJqmaNd23XYbhvKSvbVvnTdIVjJBaGtWqOT9dZGVJISHOx8nS052fTF54ofLveHbscF5Pd6adbGCg9NxzlX9eHQ5p1SrnClunTvEVNjJSat9e+uc/K/9lHCgfV13lvMFw2zbnBxsT7wQAXGY8PJw3P48Y4dy/hYUVv+fk6adNsb+r+B5UJoU7nmPHSr627tgxqXnzS2PHcznNa+EKW62ac4VNT5cKCpz/RkaaaoVFJcEyBcDMOnRw3vzcpo3zrM7hw85/27Y11U3R3N1fWoV3vCcnl/zpw0R/3At2Oc2rVPLXbTVv7gwTl9J8ovywTAEwswr4HnS+gqoivif1Ut3xXE7zKl0+P1yA8sMyBQAuhNTyuNv8ctrxXE7zCgAAygzfk1oePDwq/w1D5+pymlcAAGAKHA4DAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDqEVAAAAJgOIRUAAACmQ0gFAACA6RBSAQAAYDplGlL379+vhx56SHXq1JG/v7+uvPJKjRkzRpmZmW5169evV8eOHeXv76+wsDANHTpU6enpZdk1AAAAmJhXWU04KipK7du3l81m0zPPPKPg4GBt2LBBo0aN0u+//64FCxZIkrZv366uXbuqWbNmmjx5sqKjozVx4kTt379fS5cuLavuAQAAwMTKLKTOnDlTKSkpWrduna666ipJ0qBBg+RwOPTVV18pOTlZ1apV08svv6xq1app9erVCgoKkiTVr19fTzzxhH7++WfddtttZdVFAAAAmFSZne632+2SpJo1a7q1h4eHy8PDQz4+PrLb7Vq+fLn69u3rCqiS1K9fPwUGBmrOnDll1T0AAACYWJmF1BtvvFGS9Pjjj2v79u2KiorSt99+q48//lhDhw5VQECAduzYofz8fLVr185tXB8fH7Vu3Vrbtm0rq+4BAADAxMrsdH+3bt305ptvauzYsVq4cKGr/ZVXXtFbb70lSYqNjZXkPLp6qvDwcK1du/a008/JyVFOTo7reeGRWwAAAFR+ZRZSJee1pZ07d9b999+v6tWra/HixRo7dqzCwsL0zDPPKCsrS5JktVqLjevr6+saXpJx48Zp9OjRZdZ3AAAAVJwyC6n//e9/NWjQIO3bt0916tSRJN13331yOBx66aWX9PDDD8vPz0+S3I6IFsrOznYNL8nIkSM1fPhw13O73a66dete5LkAAABARSiza1I/+ugjtWnTxhVQC/Xs2VOZmZnatm2b6zR/4Wn/k8XGxqpWrVqnnb7ValVQUJDbAwAAAJeGMgupx48fV0FBQbH2vLw8SVJ+fr5atGghLy8vbdmyxa0mNzdX27dvV+vWrcuqewAAADCxMgupTZo00bZt27Rv3z639m+++UYeHh5q1aqVbDabbrnlFs2aNUtpaWmumpkzZyo9PV29evUqq+4BAADAxCyGYRhlMeE1a9bo5ptvVvXq1fXMM8+oevXqWrRokZYuXaqBAwfqP//5jyRp69at6tChg5o3b65BgwYpOjpakyZNUufOnbVs2bJzfj273S6bzabU1FRO/QMAAJhQafJamYVUSdq0aZPeeOMNbdu2TYmJiWrQoIH69++vf/3rX/LyKrpna926dXrppZe0detWValSRb1799a4ceNUpUqVc34tQioAAIC5mSaklidCKgAAgLmVJq+V2TWpAAAAwPkipAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATKfMQ+rWrVvVs2dPBQcHy9/fXy1atNAHH3zgVrN+/Xp17NhR/v7+CgsL09ChQ5Wenl7WXQMAAIBJeZXlxH/++Wf16NFDbdq00WuvvabAwEBFRkYqOjraVbN9+3Z17dpVzZo10+TJkxUdHa2JEydq//79Wrp0aVl2DwAAACZVZiHVbrerX79+uvPOOzV37lx5eJR80Pbll19WtWrVtHr1agUFBUmS6tevryeeeEI///yzbrvttrLqIgAAAEyqzE73z549W8ePH9fbb78tDw8PZWRkyOFwuNXY7XYtX75cffv2dQVUSerXr58CAwM1Z86csuoeAAAATKzMQuqKFSsUFBSkmJgYNW3aVIGBgQoKCtJTTz2l7OxsSdKOHTuUn5+vdu3auY3r4+Oj1q1ba9u2baedfk5Ojux2u9sDAAAAl4YyC6n79+9Xfn6+7r77bt1+++36/vvv9dhjj+mTTz7RgAEDJEmxsbGSpPDw8GLjh4eH6+jRo6ed/rhx42Sz2VyPunXrls2MAAAAoNyV2TWp6enpyszM1JNPPum6m/++++5Tbm6uPv30U40ZM0ZZWVmSJKvVWmx8X19f1/CSjBw5UsOHD3c9t9vtBFUAAIBLRJkdSfXz85MkPfzww27tffr0kSRt2LDBVZOTk1Ns/OzsbNfwklitVgUFBbk9AAAAcGkosyOptWrV0q5du1SzZk239ho1akiSkpOT1ahRI0lFp/1PFhsbq1q1apVV9wAAqJQMw1BBQYHy8/MruiuAG29vb3l6el606ZVZSL3mmmu0fPly141ThQqvMw0NDVWLFi3k5eWlLVu2qHfv3q6a3Nxcbd++3a0NAIDLmWEYSklJUXx8vAoKCiq6O0CJqlatqrCwMFkslgueVpmF1N69e2v8+PGaNm2abr75Zlf7559/Li8vL914442y2Wy65ZZbNGvWLL322muqUqWKJGnmzJlKT09Xr169yqp7AABUKseOHVNKSorrEjcvL6+LEgSAi8EwDGVmZiouLk5SyTfFl1aZhdQ2bdroscce0/Tp05Wfn68uXbpo9erV+u677zRy5EjXqfy3335bHTp0UJcuXTRo0CBFR0dr0qRJuu2229StW7ey6h4AAJVGQUGBUlNTFRoaqpCQkIruDlCiwnuJ4uLiVKNGjQs+9V+mP4v6ySefKCIiQl988YXmzZunevXq6b333tOwYcNcNW3bttWKFSv00ksv6fnnn1eVKlX0+OOPa9y4cWXZNQAAKo28vDwZhqGAgICK7gpwRv7+/pKcy+yFhlSLYRjGxehURbPb7bLZbEpNTeVOfwDAJSU7O1uHDh1SgwYN5OvrW9HdAU7rbMtqafJamX0FFQAAAHC+CKkAAAAwHUIqAADAeXjjjTf4hoUyREgFAAAVasaMGbJYLK6Hl5eXateurUcffVQxMTEV2rfMzEy98cYbWr16dbm/dv369d3el9M9ZsyYccb6J598stz7fjGU6d39AAAA52rMmDFq0KCBsrOztXHjRs2YMUPr1q3Tzp07K+yGsczMTI0ePVqSdOONN7oNe/XVV/Xvf/+7zF57ypQpSk9Pdz1fsmSJvvnmG7333ntuX0XWoUMH1/9bt26tF154wW06TZo0KbM+liVCKgAAlzOHQ9q1S0pOlqpVk666SvKomBOt3bt3V7t27SRJAwcOVEhIiN555x0tXLjQlL9C6eXlJS+vsotS99xzj9vzY8eO6ZtvvtE999yj+vXrlzhO7dq11bdv3zLrU3nidD8AAJer9eulvn2lfv2kJ590/tu3r7PdBDp16iRJioyMdLXt2bNHDzzwgIKDg+Xr66t27dpp4cKFbuMlJSVpxIgRatmypQIDAxUUFKTu3bvrjz/+KPYa2dnZeuONN9SkSRP5+voqPDxc9913nyIjI3X48GGFhoZKkkaPHu06ff7GG29IKvma1Pz8fL355ptq1KiRrFar6tevr5dfflk5OTludfXr19ddd92ldevWqX379vL19VXDhg311VdfXfD7lpubq4yMjAueTkUjpAIAcDlav14aMULaulWqWlWqX9/577ZtznYTBNXDhw9LkqpVqyZJ2rVrl66//nrt3r1b//73vzVp0iQFBATonnvu0bx581zjHTx4UPPnz9ddd92lyZMn68UXX9SOHTvUpUsXHT161FVXUFCgu+66S6NHj9Y111yjSZMm6bnnnlNqaqp27typ0NBQffzxx5Kke++9VzNnztTMmTN13333nbbPAwcO1Ouvv662bdvqvffeU5cuXTRu3Dg99NBDxWoPHDigBx54QLfeeqsmTZqkatWq6dFHH9WuXbvO+z1buXKl/P39FRgYqPr16+v9998/72lVOOMSkZqaakgyUlNTK7orAABcVFlZWcZff/1lZGVluQ9wOAwjK6v0j4wMw+jd2zCaNDGM7t0N4447ih7duzvbH3zQWVea6Toc5zV/X3zxhSHJWLFihREfH29ERUUZc+fONUJDQw2r1WpERUUZhmEYXbt2NVq2bGlkZ2ef9BY4jA4dOhiNGzd2tWVnZxsFBQVur3Ho0CHDarUaY8aMcbVNnz7dkGRMnjy5WJ8cJ+YlPj7ekGSMGjWqWM2oUaOMk6PU9u3bDUnGwIED3epGjBhhSDJWrlzpaqtXr54hyVizZo2rLS4uzrBarcYLL7xQ4vs0YcIEQ5Jx6NChEof36NHDeOedd4z58+cb06ZNMzp16mRIMv71r3+VWF8WTrusnlCavMY1qQAAVFY5OVKvXqUfz26Xtm+XvLyklJTiw/PzpaVLpe7dpdL8iuN330kXcIPTLbfc4va8fv36mjVrlurUqaOkpCStXLlSY8aMUVpamtLS0lx1t99+u0aNGqWYmBjVrl1bVqvVNaygoEApKSkKDAxU06ZNtXXrVtew77//XiEhIXr22WeL9eV8vlpqyZIlkqThw4e7tb/wwguaOHGiFi9erJtuusnV3rx5c9clDZIUGhqqpk2b6uDBg6V+bUnFLnsYMGCAunfvrsmTJ+vZZ59VnTp1zmu6FYXT/QAAXG7y8pw3TJ3ut9U9PZ3D8/LKtVsffvihli9frrlz5+qOO+5QQkKCK3AeOHBAhmHotddeU2hoqNtj1KhRkqS4uDhJksPh0HvvvafGjRvLarUqJCREoaGh+vPPP5Wamup6vcjISDVt2vSi3fx05MgReXh46IorrnBrDwsLU9WqVXXkyBG39oiIiGLTqFatmpKTky9KfywWi55//nnl5+dXyFdoXSiOpAIAUFlZrc6jl6W1c6c0cKBks0mBgcWHp6dLqanSBx9ILVqUrj8XoH379q67+++55x517NhRffr00d69e+VwOCRJI0aM0O23317i+IXhcOzYsXrttdf02GOP6c0331RwcLA8PDw0bNgw13TK0rkehfU8zYcEwzAuWl/q1q0ryXkzWWVDSAUAoLKyWM7v9HrbtlLz5s6bpKpUcU6nkGFIcXHOmrZtK+zrqDw9PTVu3DjddNNNmjp1qh577DFJkre3d7HLAk41d+5c3XTTTZo2bZpbe0pKitv3izZq1Ei//fab8vLy5O3tXeK0SnPav169enI4HNq/f7+aNWvmaj9+/LhSUlJUr169c57WxVJ46UDhtxRUJpzuBwDgcuPhIT3zjPN7USMjnUdOCwqc/0ZGOtuffrrCAmqhG2+8Ue3bt9eUKVMUFBSkG2+8UZ9++qliY2OL1cbHx7v+7+npWexo5HfffVfs16vuv/9+JSQkaOrUqcWmVzi+v7+/JGfAPZs77rhDkvNL+E82efJkSdKdd9551mmcr6SkJBUUFLi15eXlafz48fLx8XG7Fray4EgqAACXow4dpIkTpalTpd27pePHnafr27Z1BtSTfsWoIr344ovq1auXZsyYoQ8//FAdO3ZUy5Yt9cQTT6hhw4Y6fvy4NmzYoOjoaNf3oN51110aM2aMBgwYoA4dOmjHjh36+uuv1bBhQ7dp9+vXT1999ZWGDx+uTZs2qVOnTsrIyNCKFSs0ZMgQ3X333fLz81Pz5s317bffqkmTJgoODlaLFi3UooTLIK6++mr1799fn332mVJSUtSlSxdt2rRJX375pe65554yDYoLFy7UW2+9pQceeEANGjRQUlKSZs+erZ07d2rs2LEKCwsrs9cuK4RUAAAuVx06SNdfb5pfnCrJfffdp0aNGmnixIl64okntGXLFo0ePVozZsxQYmKiatSooTZt2uj11193jfPyyy8rIyNDs2fP1rfffqu2bdtq8eLFxX7C1NPTU0uWLNHbb7+t2bNn6/vvv1f16tVdQbjQ559/rmeffVbPP/+8cnNzNWrUqBJDamFtw4YNNWPGDM2bN09hYWEaOXKk6+austKyZUs1b95cs2bNUnx8vHx8fNS6dWvNmTNHvc7nGyBMwGJczKtzK5DdbpfNZlNqaqqCSvN1GQAAmFx2drYOHTqkBg0aVNhv2APn4mzLamnymnk+KgEAAAAnEFIBAABgOoRUAAAAmA4hFQAAAKZDSAUAAIDpEFIBAABgOoRUAAAAmA4hFQAAAKZDSAUAAIDpEFIBAABgOoRUAAAAmA4hFQAA4BJjsVj0xhtvVHQ3LgghFQAAmEJkZKQGDx6shg0bytfXV0FBQfrHP/6h999/X1lZWRXdvUrLYrGc02P16tVnrB8/fny59turXF8NAACgBIsXL1avXr1ktVrVr18/tWjRQrm5uVq3bp1efPFF7dq1S5999llFd7NSmjlzptvzr776SsuXLy/W3qxZM9f/b731VvXr189teJs2bcqukyUgpAIAcBmKj5fs9tMPDwqSQkPLpy+HDh3SQw89pHr16mnlypUKDw93DXv66ad14MABLV68uHw6cwnq27ev2/ONGzdq+fLlxdpP1qRJkzMOLw+c7gcA4DITHy/16SP16nX6R58+zrry8O677yo9PV3Tpk1zC6iFrrjiCj333HOSpPz8fL355ptq1KiRrFar6tevr5dfflk5OTlu49SvX1933XWXVq9erXbt2snPz08tW7Z0ndL+4Ycf1LJlS/n6+uqaa67Rtm3b3MZ/9NFHFRgYqIMHD+r2229XQECAatWqpTFjxsgwDLfajIwMvfDCC6pbt66sVquaNm2qiRMnutUdPnxYFotFM2bMKDZ/p14/+sYbb8hisejAgQN69NFHVbVqVdlsNg0YMECZmZlu4+bk5Oj5559XaGioqlSpop49eyo6Ovqs7/m5yMrKUnZ29kWZ1vkgpAIAcJmx26XERMlqlapWLf6wWp3Dz3Sk9WL68ccf1bBhQ3Xo0OGstQMHDtTrr7+utm3b6r333lOXLl00btw4PfTQQ8VqDxw4oD59+qhHjx4aN26ckpOT1aNHD3399dd6/vnn1bdvX40ePVqRkZHq3bu3HA6H2/gFBQXq1q2batasqXfffVfXXHONRo0apVGjRrlqDMNQz5499d5776lbt26aPHmymjZtqhdffFHDhw+/oPeld+/eSktL07hx49S7d2/NmDFDo0ePLvZ+TJkyRbfddpvGjx8vb29v3XnnnRf0upI0Y8YMBQQEyM/PT82bN9fs2bMveJqlxel+AAAquTMd7PLwkHx83GtzciSHwxlG/fyK10vOmpyc00/71OmeL7vdrpiYGN19991nrf3jjz/05ZdfauDAgfrPf/4jSRoyZIhq1KihiRMnatWqVbrppptc9Xv37tX69et1ww03SJKaN2+u22+/XU888YT27NmjiIgISVK1atU0ePBgrVmzRjfeeKNr/OzsbHXr1k0ffPCB67V69Oihd955R0OHDlVISIgWLlyolStX6q233tIrr7wiyXmJQq9evfT+++/rmWeeUaNGjc7rvWnTpo2mTZvmep6YmKhp06bpnXfecb0fs2bN0pAhQ/Thhx+6XvuRRx7Rn3/+eV6vKUkdOnRQ79691aBBAx09elQffvihHnnkEaWmpuqpp5467+mWFiEVAIBKrlev0w9r10466cCf+vaVkpKkQ4ckLy/no1CVKtJJ987o3/+WTjmz7dK4sTR58oX1W3KGVOdrVzlr7ZIlSySp2BHKF154QRMnTtTixYvdQmrz5s1dAVWSrrvuOknSzTff7AqoJ7cfPHjQLaRK0jPPPOP6v8Vi0TPPPKPFixdrxYoVeuihh7RkyRJ5enpq6NChxfo0d+5cLV261G0apfHkk0+6Pe/UqZPmzZsnu92uoKAg1/tx6msPGzbsgo58/vrrr27PH3vsMV1zzTV6+eWX9eijj8rv1E82ZYTT/QAAoMIEBQVJktLS0s5ae+TIEXl4eOiKK65waw8LC1PVqlV15MgRt/aTg6gk2Ww2SVLdunVLbE9OTnZr9/DwUMOGDd3amjRpIsl5jWlhn2rVqlUsZBfeKX9qn0rj1P5Xq1bNrZ+F78epR2qbNm163q9ZEh8fHz3zzDNKSUnR77//flGnfSYcSQUAoJL77rvTD/M45XDUrFnSwYPOG6OqVpUCAk4/7vjx0ikZ7bTTPV9BQUGqVauWdu7cec7jWCyWc6rz9PQsVfupN0RdTKfrc0FBwWnHqYh+nk5hsE9KSiq31+RIKgAAlZyv7+kfp1436uvrvBbVw6Pkx8ms1nOf7oW46667FBkZqQ0bNpyxrl69enI4HNq/f79b+/Hjx5WSkqJ69epdvE5JcjgcOnjwoFvbvn37JDm/PaCwT0ePHi12JHjPnj2u4VLRUdCUlBS3ugs50lr4fkRGRrq1792797yneTqF70NoeX0vmQipAABctrKypIyM4o/y/nGnf/3rXwoICNDAgQN1/PjxYsMjIyP1/vvv64477pAkTZkyxW345BMXx16Mu9pPNXXqVNf/DcPQ1KlT5e3tra5du0qS7rjjDhUUFLjVSdJ7770ni8Wi7t27S3IeMQ4JCdGaNWvc6j766KPz7lvhtAtv7Cp06vtTGvElfO9YWlqapkyZopCQEF1zzTXnPe3S4nQ/AACXmaAgqXp159dMnfL1oi7VqzvrykOjRo00e/ZsPfjgg2rWrJnbL06tX79e3333nR599FE999xz6t+/vz777DOlpKSoS5cu2rRpk7788kvdc889bjdNXQy+vr766aef1L9/f1133XVaunSpFi9erJdfftl1RLFHjx666aab9Morr+jw4cO6+uqr9fPPP2vBggUaNmyY2/WiAwcO1Pjx4zVw4EC1a9dOa9ascR2ZPR+tW7fWww8/rI8++kipqanq0KGDfvnlFx04cOC8p/nhhx9q/vz56tGjhyIiIhQbG6vp06fr77//1syZM+VzMQ+hnwUhFQCAy0xoqDR7tnl+cUqSevbsqT///FMTJkzQggUL9PHHH8tqtapVq1aaNGmSnnjiCUnS559/roYNG2rGjBmaN2+ewsLCNHLkSLfvLr1YPD099dNPP+mpp57Siy++qCpVqmjUqFF6/fXXXTUeHh5auHChXn/9dX377bf64osvVL9+fU2YMEEvvPCC2/Ref/11xcfHa+7cuZozZ466d++upUuXqkaNGufdx+nTpys0NFRff/215s+fr5tvvlmLFy8udnPYufrHP/6h9evX6/PPP1diYqICAgLUvn17TZ8+XTfffPN59/N8WIyKuPq2DNjtdtlsNqWmprruFAQA4FKQnZ2tQ4cOqUGDBvL19a3o7lwWHn30Uc2dO1fp6ekV3ZVK5WzLamnyGtekAgAAwHQIqQAAADAdQioAAABMh5AKAABwihkzZnA9agUjpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQCgAAANMhpAIAgMva6tWrZbFYNHfu3IruCk5CSAUAABXGYrGc02P16tVnrB8/fnyJ01+9erXuu+8+hYWFycfHRzVq1FCPHj30ww8/lONc4nx4VXQHAABA+UvITFBqdupph9t8bQrxDynzfsycOdPt+VdffaXly5cXa2/WrJnr/7feeqv69evnNrxNmzbFpj1q1CiNGTNGjRs31uDBg1WvXj0lJiZqyZIluv/++/X111+rT58+F3FucDERUgEAuMzkFeTpyUVP6mDywdPWNKzWUN/c/428Pb3LtC99+/Z1e75x40YtX768WPvJmjRpcsbhkjR37lyNGTNGDzzwgGbPni1v76L5ePHFF7Vs2TLl5eVdWOdRpsrtdP/bb78ti8WiFi1aFBu2fv16dezYUf7+/goLC9PQoUOVnp5eXl0DAOCy4uXhpdpVais1J1VVfasWe6TmpKp2ldry8jDvsaysrCxlZ2efdvhrr72m4OBgTZ8+3S2gFrr99tt11113ubU5HA69/fbbqlOnjnx9fdW1a1cdOHCg2Li//fabunXrJpvNJn9/f3Xp0kW//vqrW80bb7whi8Wiffv2qW/fvrLZbAoNDdVrr70mwzAUFRWlu+++W0FBQQoLC9OkSZPO8524dJVLSI2OjtbYsWMVEBBQbNj27dvVtWtXZWZmavLkyRo4cKA+++wz9erVqzy6BgBApZedn63s/GwZhuFqy3fkKzs/W3kFecVqcwpy1O/qfrJZbcp35Mvf219+Xn7y8/ZTviNfNqtN/Vv3V05Bzmmnm1uQW27zd6oZM2YoICBAfn5+at68uWbPnu02fP/+/dqzZ4/uueceValS5ZynO378eM2bN08jRozQyJEjtXHjRj3yyCNuNStXrlTnzp1lt9s1atQojR07VikpKbr55pu1adOmYtN88MEH5XA4NH78eF133XV66623NGXKFN16662qXbu23nnnHV1xxRUaMWKE1qxZc35vyCWqXD4ijRgxQtdff70KCgqUkJDgNuzll19WtWrVtHr1agUFBUmS6tevryeeeEI///yzbrvttvLoIgAAlVav75wHdmbdO0s2X5sk6YfdP2jmnzN1W8Pb9Ox1z7pq+/7QVzkFOfq8x+fqFNFJyyKXKTMvU1H2KAX7BsuQodsb3a42YW3Ud15f2XPs+vCODxVhi5Ak/XLwF03dPFXX1b5Or3Z+tdzntUOHDurdu7caNGigo0eP6sMPP9Qjjzyi1NRUPfXUU5Kk3bt3S5JatmxZqmlnZ2dr+/bt8vHxkSRVq1ZNzz33nHbu3KkWLVrIMAw9+eSTuummm7R06VJZLBZJ0uDBg3XVVVfp1Vdf1c8//+w2zfbt2+vTTz+VJA0aNEj169fXCy+8oHHjxumll16SJD388MOqVauWpk+frs6dO5//m3OJKfMjqWvWrNHcuXM1ZcqUYsPsdrvrupPCgCpJ/fr1U2BgoObMmVPW3QMA4LJksVjUv3V/+Xv7KzMvU5KUXZAtf29/9W/d3xXAzObXX3/Vc889p549e+rJJ5/U77//rhYtWujll19WVlaWJGe+kFSqo6iSNGDAAFdAlaROnTpJkg4edF67u337du3fv199+vRRYmKiEhISlJCQoIyMDHXt2lVr1qyRw+Fwm+bAgQNd//f09FS7du1kGIYef/xxV3vVqlXVtGlT1+vAqUyPpBYUFOjZZ5/VwIEDS/w0s2PHDuXn56tdu3Zu7T4+PmrdurW2bdt22mnn5OQoJyfH9bxwgQQA4HLzXa/vJElWT6ur7b5m96ln057ytHi61c66b5arNtQ/VJ0iOumnAz/pmrBrFJkcqU4RndQmzHmn/LSe04pNt2vDrupSv4s8LOb4FksfHx8988wzrsDasWNH14GvtLS0Uk0rIiLC7Xm1atUkScnJyZKclxFIUv/+/U87jdTUVNd4JU3TZrPJ19dXISEhxdoTExNL1d9LXZmG1E8++URHjhzRihUrShweGxsrSQoPDy82LDw8XGvXrj3ttMeNG6fRo0dfnI4CAFCJ+Xr5Fmvz8vAq8canU2v7t+6vtX+vVUx6jAJ8AtyOopZmuhWpbt26kqSkpCRJ0pVXXinJeTCsNDw9PUtsL7wmt/Ao6YQJE9S6desSawMDA886zbO9DpzKbClLTEzU66+/rtdee02hoaEl1hQelrdarcWG+fr6uoaXZOTIkRo+fLjrud1udy2kAADg3LQJa6NOEZ00b8883Xvlva6jqJVJ4WnywrzRpEkTNW3aVAsWLND7779fLDier0aNGkmSgoKCdMstt1yUaeL0yuxY/auvvqrg4GA9++yzp63x8/OTJLfT9oWys7Ndw0titVoVFBTk9gAAAKVjsVg0oM0A3dboNg1oM8C016JKUnx8fLG2tLQ0TZkyRSEhIbrmmmtc7aNHj1ZiYqIGDhyo/Pz8YuP9/PPPWrRoUale/5prrlGjRo00ceLEEr8qs6T+4fyVyZHU/fv367PPPtOUKVN09OhRV3t2drby8vJ0+PBhBQUFuU7zF572P1lsbKxq1apVFt0DAAAnaR3WWp/3/Lyiu3FWH374oebPn68ePXooIiJCsbGxmj59uv7++2/NnDnT7aanBx98UDt27NDbb7+tbdu26eGHH3b94tRPP/2kX375pdhXV52Nh4eHPv/8c3Xv3l1XXXWVBgwYoNq1aysmJkarVq1SUFCQfvzxx4s925etMgmpMTExcjgcGjp0qIYOHVpseIMGDfTcc89p9OjR8vLy0pYtW9S7d2/X8NzcXG3fvt2tDQAAXN7+8Y9/aP369fr888+VmJiogIAAtW/fXtOnT9fNN99crP6tt97SzTffrA8++EAff/yxkpKSVK1aNV1//fVasGCBevbsWeo+3HjjjdqwYYPefPNNTZ06Venp6QoLC9N1112nwYMHX4zZxAkWowyu0k1ISNC6deuKtb/66qtKS0vT+++/r0aNGqlly5bq3r27/vjjD+3du9f1VRHTpk3TwIEDtXTpUnXr1u2cXtNut8tmsyk1NZVT/wCAS0p2drYOHTqkBg0ayNe3+M1MgFmcbVktTV4rkyOpISEhuueee4q1F35X6snD3n77bXXo0EFdunTRoEGDFB0drUmTJum2224754AKAACAS0uFf8lZ27ZttWLFCvn5+en555/XZ599pscff1xz586t6K4BAACggpTrF52tXr26xPaOHTvq119/Lc+uAAAAwMQq/EgqAAAAcCpCKgAAAEyHkAoAQCXBz2bC7C7mMkpIBQDA5Ap/6z0vL6+CewKcWeGve3l5XfhtT4RUAABMztvbW1arVampqRxNhanZ7XZ5enq6PlhdiHK9ux8AAJyfkJAQxcTEKDo6WjabTd7e3rJYLBXdLUCS8zR/RkaG7Ha7wsPDL8qySUgFAKASKPx1noSEBMXExFRwb4DiLBaLqlatKpvNdlGmR0gFAKCSCAoKUlBQkPLy8lRQUFDR3QHceHt7X5TT/IUIqQAAVDLe3t7y9vau6G4AZYobpwAAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYTpmF1M2bN+uZZ57RVVddpYCAAEVERKh3797at29fsdrdu3erW7duCgwMVHBwsP75z38qPj6+rLoGAAAAk/Mqqwm/8847+vXXX9WrVy+1atVKx44d09SpU9W2bVtt3LhRLVq0kCRFR0erc+fOstlsGjt2rNLT0zVx4kTt2LFDmzZtko+PT1l1EQAAACZVZiF1+PDhmj17tlvIfPDBB9WyZUuNHz9es2bNkiSNHTtWGRkZ+v333xURESFJat++vW699VbNmDFDgwYNKqsuAgAAwKQshmEY5fmC11xzjSTp999/lyTVrFlTXbp00Zw5c9zqmjZtqrp162rFihXnNF273S6bzabU1FQFBQVd3E4DAADggpUmr5XrjVOGYej48eMKCQmRJMXExCguLk7t2rUrVtu+fXtt27atPLsHAAAAkyjXkPr1118rJiZGDz74oCQpNjZWkhQeHl6sNjw8XElJScrJySlxWjk5ObLb7W4PAAAAXBrKLaTu2bNHTz/9tG644Qb1799fkpSVlSVJslqtxep9fX3dak41btw42Ww216Nu3bpl1HMAAACUt3IJqceOHdOdd94pm82muXPnytPTU5Lk5+cnSSUeLc3OznarOdXIkSOVmprqekRFRZVR7wEAAFDeyuzu/kKpqanq3r27UlJStHbtWtWqVcs1rPA0f+Fp/5PFxsYqODi4xKOskvPo6+mGAQAAoHIr05CanZ2tHj16aN++fVqxYoWaN2/uNrx27doKDQ3Vli1bio27adMmtW7duiy7BwAAAJMqs9P9BQUFevDBB7VhwwZ99913uuGGG0qsu//++7Vo0SK30/W//PKL9u3bp169epVV9wAAAGBiZfY9qcOGDdP777+vHj16qHfv3sWG9+3bV5IUFRWlNm3aqGrVqnruueeUnp6uCRMmqE6dOtq8efM5n9Lne1IBAADMrTR5rcxC6o033qj//e9/px1+8svu2rVLw4cP17p16+Tj46M777xTkyZNUs2aNc/59QipAAAA5maKkFreCKkAAADmZtpfnAIAAADOBSEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApuNV0R2obBIyE5SanXra4TZfm0L8Q8qxRwAAAOeusmQZQmop5BXk6clFT+pg8sHT1jSs1lDf3P+NvD29y7FnuFCVZYVF5cEyBcCMKlOWMUVIzcnJ0euvv66ZM2cqOTlZrVq10ltvvaVbb721orvmxsvDS9W8aishfZtqBdST5aRhhqSjGUd0TWhteXmY4m29YHv+TtDRpNPvZGsF23RlROXfyeYV5GnA92dfYX/oU/ErLCoHlikAZlWZskzF90DSo48+qrlz52rYsGFq3LixZsyYoTvuuEOrVq1Sx44dK7p7LgkJFv35VX8lNFirpPx8eebbXMMKvFLl8LLpz7X9ldDJotDQCuzoRXD0WJ46v/uk0r1Pv5MNzGuo7a9+o1phlXsnm5zopT/W1tZx2zb5ZNUrNjzX74jSdtZW8u1eqlGjAjqISodlCoBZVaYsU+E3Tm3atEn//e9/NW7cOE2YMEGDBg3SypUrVa9ePf3rX/+q6O65sdul3L/bKCilkxz+cZJvqgoCo2T4JcrhH6eglE7K/buN5v31oxbsWaCM3AzXuDH2GK05skZ7Eva4TXN3/G79Ff+XsvOzXW0ZuRk6mnZUKdkpbrU5+TnKK8iTYRhlOp+SlJnuJcNeWw6fVFmNqsUeDp9UGfbaykw3xeecC5KWZpH//v7yKrDJ0ztfVo8A18PTO19eBTb57++vtDTL2ScG6NJbphyGQwWOArdtj8NwKLcgV7kFuW61Ofk5yszLVL4j39WW78iXPceu9Nx0t9r03HQlZSUpJz/HrTY+I16JmYlutSnZKYpNi3XbruYV5CkqNUox9hi32oTMBB1OOex2uUW+I18Hkg4oMinSrfZ4+nHtTdirhMwEt9qdcTu1M26n2zwfTTuqP479odi0WFebYRjaGrtVvx/9XQWOAld7jD1Gm2I26XDKYbfX2xC1Qeuj1ru9b1GpUVpzZI32Jux1q117ZK1WHVqlrLwst9rlkcv15/E/3WpXHVqlnw78pLScNLfaH/f+qE0xm9xql0cu1/w985WUleRqi7ZHa+5fc7XmyBq32mUHlunbnd/qePpxt3n7+s+v9dOBn9xql+5fqi+3f6mo1ChXW2xarKZvm655u+e51S7Zv0Sf/f6ZDiQdcLUdTz+ujzZ/pFl/znKrXbRvkT747QPtitvlakvITNB7G97TZ79/Vqx2wq8T9PvR311tKdkpGrd2nCatn1Ss9q01b2l91HpXW3puut5Y/YZGrx5drL+vrXxNvxz8xdWWk5+jkStGauSKkcoryHOrffHnF/Xj3h9dbYZhaPiy4Rq+bLjbMrzswDINXTpU3+781u31nlv6nIYsHuL2N1pxcIUG/ThI07dNL1b7+ILH3ZbLVYdWqf/8/vrgtw+K1Q5c0ldpCVVdWcbwS5SnT7a8vA23LGO3q8JVeEidO3euPD09NWjQIFebr6+vHn/8cW3YsEFRUVFnGLv8WWRR3cT+8jb8VWCNV55PrPJ9jsvb8Fft+P4yHBZ9f+ArfbblcyWmF20stsZu1TtrJ+j7XQuVnS3XY8zqt/Xispf0d9IxV+36qPV6YsFgTf71A7faJ398Wvd8c592HtvnVtt7zkMas2qsW+2oX97Ukwuf1o6jRRu93fG79e/lr+rj3z53q52xdbYmrJ2i3ceLjprGZx2TV06wLBbJ4pkvHwXIRwGSV5byfGPl6fBT9aj+slgsisuI0xe/z9R3Oxa4TXfR7p/1yW/TtPPoftd0EzIT9H8bP9b0LTPdaufvWqKJ697X5r+LNrxJWUkat2aCJq1zfx/m7lioN1a+pf9FblTh/iM1O1Wv/jJKr/8yxq12zp/z9eKykVq65xdXbWZepoYtHa6hi4crM8uhnBzJmtxGvnm1lBG4Q3nWWHl6Sh6ehvKtxyXPfMVH/EepmVmu6f6wc5EGLxyimdu+1cmfGZ5e/KwGLxyi46mprtrFu5dr8MIhmr5lphyOotrnf3pBgxcO0d+Jca7a5fv+p8ELh+jj3z53q31p+UgNXjhEB+KiXbWrIzdo8MIhen/9Ryoo2jfq9ZVvaPDCIdp97KCrdv3h3zV44RBNWDvFrfat/43V4IVDtD16t6v296idGrxwiN5a/Y7yi3KG3l03UYMXDtHmv/901f4Zs1eDFw7RqF/edKt9f+MHGrxwiNYd2uyq3Xv8sAYvHKKRP7/mVvvR5k80eOEQ/XJgnav2UEKsBi8cohd+esmtdtrW6Rq8cIiW7V3lqo1OStDghUP07OLn3Wpn/fm1Bi8cooV//eSqjU9N0+CFQzR44RDlFe1TNGfXdxq8cIjm7ihaP1PTc1y1GdlFgWL+ngUavHCIZm+f66rNyjJctYlpzvXeL7WN/HIjlBG4Q7m+0fL0kDw8DOVb4ySPAsXV+0RxaUU7oOWRy/XoD48XWz+f+vFZ/fP7R3U48airduWhlXr4u76asHZKsdpe3z6kPSety2uOrNH9/+2lN1a+5VY7ZNFQ9Zx9r7ZFF+3410et152zeuiFn15yqx26eLh6zr5HG//e6qrdfmy77v3v/Xp+6Ytuta+sGKVe3z6oNQd/c9XuTdirh+c+omFLXnCrHb9mov75fX+tPLDOVXsk5Ygenf+Yhi11r/2/DR9r4IJBWr7/f67auIw4PbloSLHaaVu+0tOLntVP+1a61s+U7BQ9t/R5Pf/TCLfa//75vYb/NEKL9yx31WblZeml5SP10s8jlZnlcNUu/GupXl7xqn7c/ZOrNt+Rr9dXjtLrK99QSnq2q/bn/as1etWbbrWSNHbtOL39v3FKsKe7atce+k3vrJ2ghbuXuq33H/z2f5r462QdS01x1W6K2q4pGz4oVjtt2xf6v40fKiY5oWj9PLpHn2z+TIv2/OS23v935xz9Z8s0/Z143FW75/ghfbH1y2K1P+5dpK+2z9LhxFhX7cGEGM3+879asvdnt3Vu+cFfNGfnXB1KPFq0fibH6/td87Rs/wq32nVHftWC3T/qUEKMq/Z4aooW712qFQdWudVuPbpNy/Yv16HEotrEtHStiFypVQfXuNXuivtLqw+tcatNSc/WuiPr9evfG91qI5MOasPfv7nVpmXmaXP079oUvcVtGxGVGq2tR7frSFLRvGVmOfTnsZ3689hO5eYV/ZHjMuL1V9weRaccd1vW9sbv1974/crKKXqDk7OTFZl4SLH2BLfawylROpIcpczsog6n56YrJjVWcWnJbrXH0uJ1LC1OmTlFtdn52UpIT1JyRppbbXKmXak5qZIKXFnG8E6Xp6chw8cub8NfdRP7yyJzfICu8MNg27ZtU5MmTRQUFOTW3r59e0nS9u3bVbdu3WLj5eTkKCen6NO3vRwjf2B6GwWnd9LxqguVbw9Tvk+ydKiTDm1oo4J8KXN1J3lZc/RxpJ/GjXKOU92/uiI3tNKxn+tp48Siaf1VJ1z5ngH6v11W/d84Z5uHxUM7t/vp4P98tW1KUe32+gXK9ZImb/fQFyemkZOfo41bM7Q9OVubJxfV7og4qiyfaCUvz9O3/+dsS85O1n9X/SHP5FwtiS6q3VV3szKsB7Quu6MWfNxQkhSXFatEv80qSK+iPK84eaQGySKL8qrFyfA6Lp+Y7vJLbSPJGTzfXjBHeYm19dXfd7umu7fWeqX6/66mSfW15svGkiR7jl1Tly1RZkJ1zTv8T1ftgbA/lBS4XnPiG2vTrFaSnDuKr/63RvaEAK1+Z6ir9mDNSCVU+U2LEq7Suv9Ivr5SniNP8zZuVWK8l9t7djg0VnG2nfolqaU6fCDZbM4jQL9s36+4OCnyE4eyMjx0+JBFubWuUX7rtUrPs8vHCFeBt12eDn/lZlaR3YjW8887FOTnnG50cKqOBkdpfWqSurwhRUQ423/bHaWomAIdnl4gnxPbodiqdkWFRGmdvYk6/Vtq7HwrtGlPtA4cydTBGfnyPbExPG5L15HQKK1Jr6eO/lLLls72LXuPamdkkg58mSf/E3kpvkqGDtWM0uqMmurgLV17rbP9931HtWVvrPbOzFGVEwfokwKzdCAsSkFZVXWDRSq8imbbgVit2xml3bNyZDtxsCbFP0v7akUpINtXNxRIXbueWKYOHtfP26K0a3aWqp04EGD3y9Ge2lHyy5XaZ0t33uls/+twvOb/FqUd32Sq+omDZ+nWXP1VN0rWvBxdmy7dd5+zfX90guavidL2bzNU48RqnOWTpx0RUfIusOmaJKlPH2d7ZGyi5q+K0tY5aQo7cZAsx6tAf9SPkofDqjbHpccec7b/HZ+k+auitGWuXf9JdrbleTq0rYHzg2/rGOmpp078jZKTNX9VlDZ9n6ovT+TGAouh3xs5axtHGhrxvLM9MT1V81dFaWNKir45cfDNkLT5Cmdt+C6H/tnb+YHWlna9EoNWKSMvTTmpksPHLuX7S9lVleuI1fQZ+brhxPKakZehZb/GaVNqipYUHbTS1gaJyvdMU9CWAn14YhuRW5CrNZtStS01Q2veLardXj9duV4ZemdzgWsbUeAo0Obt2dqRnKPf3yuq3RGRpyyffI3fYLi2EZK06y9pT7KhfR+e1FZXyrBK4381tODjovbdu6W/kqS/Pz2prbZFaX7S+FXSzdOcbRaLRXv3SjuTpF7Timr3hXsoNcCiccul7l8W1R484K0d8d7qNaOoNrKmj1ICfDVuqafu+drZ5mHxUPTBQCUfD1Cvkw6+HQkJUFIVmyb9ZNXdnzu3ER4WDyUcCVHsUU/1+qaoNjrYpsQqNRX3U4Du+dC5jfCweMgeXVt//y09+K1cu+vYqsFKCIrQ8WVVdc8kqUYNZ3+zjzVUZKT0zzke8jyRVeKCqishqImOL6uhu2sXbSMsCc21Z7dDj831lPeJbURiYA3F21rq2M91dE9Y0TbCO+lq7d+Woyfn+ri2Jyn+YYqzXatj2Y10d/WibYR/yjXasjFdQ7/3l/VEVrH71VScraOO5TRSj6CibUTV9Ou0YXWqRvwQJL8T2550a03F2brqWF4dbQgo2kaEZP1Dq1c21Ss/VHfVZvrUUJztDh3Pq6H/+RZtI2rnddYvv1yp0fNqurZT2d6hig+6T3EF1bTMs2gbUV83aunyKzV+XoQ+OFGb6xmieNvDiisI1EIVbSMae9+kBT831eR5V+jTE7V5HsFKCBqgeMNXc/KKthFX+d+sucua6qN5LfTlidoCjyAlVHlSFsNTX2UWbSNa227W7KVNNW1eY/33RK3DEqCkwGGSpM/TirYR14bcpBlLmujrefU070StIR+lBL4kSfo03lPDT2wjOtS6SZ+Pb6K5eeFa4qqV7P6vO2uj/PXKSGd7l3pd9NGYplqUH6JfTgrFdr/Rkgx9GllVb57IEZ0iOumjN5toRZZNv55Um2EdI0MOfbqrpt49sY34R8Q/9MnbTfVraoB6nbTeZ3m/qdysAsUfCFfN5t4KTu+kuKClshg+yvWKVqj9dgWmt9Hp70YpXxUeUmNjYxUeHl6svbDt6NGjxYZJ0rhx4zR69OgSh5W1wqOpSYFrlasCWXJC5Lu36JNHnZihCgiQfE/K1h3qdlCL4x10Uq6WJDWPniBJCmxR1Na1YVd1jO1a7FB7qyOfymHJk62Rr6vt+jrXq0PSJ0qK93GrbXB8uBweWQoKre9qa1K9iVpnjFBSUhW32popPZXrlSh/ax1XW7BvqKyH7lGBd7LyrvxGho9dllybPAqsMrKryXffI675DfYLVmNHD8Wl2dymG5z+D/nn1JdfXoSrrapvVbXQQzqS4u9WWz3tRvnnNFZgdlNXm83Xpms9ntDeBPd5C7F3VWBWM7faKj5VdKP1eW2Ncz85EGq/TUFZreSXU9QHXy9f3RHwutYflSzydLVbdz4ho9p+5dXcJKPAUK5XnELtt8nY+rgS4i3yqOd70nRvUVBWS3nnV3d7vQeqv6mlmwx5OYre4+D0zgrIaSzv/Gputb1qvKZ56x1u06iWcZ38cuvKq8D9vewV9m/lr8mTNa9oXbFlttWVMW/Lq8D9A16v2i8ofWWO/HKL5rlKVktdGfO2PAsC3Wrvr/usEpZlyz+ngastILuprox5Wx4OP7faeyMG6+9FmfLLLbrG0j+n4Ylaq1vtPfUHaM8P6W598Mur46w13P+ePev31dZveso3t2j588mroStj3pbFcN9E9WjwoH6NuV2+ebVcbd4F1XRlzNuS4SFdXVR7R4N7tSymi6x5Ya42z4IAZ60kNSmqvb3BXfoh5nr55BVdIOph+LhqPSKKrru+uf6tujKmtXzy3W8aLKz1rhHgags7NkAx+X8qr+ZvMmTI8IuTz9+3y/vPwSookKw9q7pqO9frrFaxzeTIDio2XcPiUEDjmq62f9T9h9rFXaksu/8ptWNlyKGg+kUXkl1f53r9I/E/xbYRTWPeliwOVQ0vWtba1Wqnrqlf6ehRr+K1cig4pGiZuLrm1borc44ORLuvc02PjpFkyFalaBrNQprpgbwF2nnE/ehMk1jnTtt60uLTsFpDPaQftOWIW6kaHX9BpwqvEq6Hvb/Rr6fU1ksYrHoJg93agv2C9bD/F/rllNo6SY+oTtIjbm0BPgHqE/SJlvx9yuul3KvwlHvd2rw8vNSn2vuad8pJvxr2bqph71aszw+FjNc30e5t1dM7q3p652K1D9R4RWmn7AKrZl6rqpnXFqu9u+Zzio11bwvKaqWgrFbFau8IG6h9x93bAnOaKDCuSbHaW8Ie0u/x7m3+ufVVP/6pYrWda/bU6gT3Nt+8cNVNHFCs9oaat+rHJPc2n4Lqqp3Up1htuxodVSvZvc3bEaTwlPuK1bYKaaewlHZubZ4Of9VMvbNYbbPqLVTD3sKtzcPwUUha12K1jao1VkhaY7c2izwVnO5M8x4nLdoRQRGqlhFxSq3F9XfzPKk2vEq4bFnFM1BQlvPTx8lrYnX/6grKqa6cPPfagJwrnNM9eXxrkALzgnTSVTeSnNthR45kcTg/fBVmmWyfGHk6zHUUVZIsRnlc4HgGjRo1UtOmTbVkyRK39oMHD6pRo0Z67733NGzYsGLjlXQktW7dukpNTS12VPZiiYyUevWSqlaV/AMM7ao7TMeqzlPN5HvV/O8pysywKCVFmj1bathQ8vCQfE7aL2Rnn37aF1KbkyOd7q9osbjvAM61NjJSeuABKchm6EizYUqwLZN/9hXK9D2gkNTbVW/3FKXZLfruO6lRIyk3V26nnk7lW5TvLmqt1erstyTl5cntNNW51h486PwUXrWqlB+6VTsaDJRhKZDF8NTVRz6XZ1xbJScX/V3PNN38fLmdTjqVj4/z73exa729JU/P0tcWFMjtlNapvLycj9LWOhzOv93FrjUMFfugd761np7O9+Ji13p4SFFRRduK3OonlikVyCJPtTz0ubzi2yolRfrmG6lZs6JxK9M2Qqq49b68txFnqz3bOsc2onjt5b6NKI9scLragwelRx6RqlVzzzJhKffqqqiiLFO4f7/Y7Ha7bDbbOeW1Cj+S6ufn5xY2C2WfeHf9/PyKDZMkq9Uqq9Va4rDyYJFFdRMGqMAjQxGJA+TpYZGHh3MhsVrdN6KFSmo7ndLUluZtKE2txSJ5elgUkdRfyVXWKtsaJU+HvyKS+svTw/2Tlo/PaSZSgrKq9fYu2kiUptZqletvVzXbeSlH4QoblNlGmZYz/11PdvIG8GzMUOvpWbQzupi1Hh7nvgyXptZiqVy1UvFlqmp2G2V6FN+hSJVvG2GG9b48thFnY4Z1mW2EkxnW+9JuI8q79uQPTSdnmboJA0x1FFUyQUgNDw9XTExMsfbYE+ctatWqVWxYRcs6ce2eV0ZrXZHwuSQp46T2S0lWluQb30ZBQZ0UHzJPoQn3yjO+zSU7r5JFIVEDlOPIUEjMAGVmWC7JeUX5YJkCYFaVIctUeEht3bq1Vq1aJbvd7nbY97fffnMNN4ugIKl6dSkx8fSH8qtXd9ZVdu7zalHA/gHKzM9QwKEBSrU7P2ldmvMqKaW1wmI+V4GklBM1l8q8onywTAEwq8qUZSr8mtTffvtN119/vSZMmKARI0ZIcl5v2qJFC1WvXl0bN248p+mU5hqHCxEfrzN+d1hQkCr8y28vFua1yKU0rygfLFMAzKoit0+V6prU6667Tr169dLIkSMVFxenK664Ql9++aUOHz6sadOmnX0C5Sw09PLZsTCvwPljmQJgVpVl+1ThIVWSvvrqK7322muaOXOmkpOT1apVKy1atEidOxf/Sg4AAABc+ir8dP/FUl6n+wEAAHB+SpPXKvxnUQEAAIBTEVIBAABgOoRUAAAAmA4hFQAAAKZDSAUAAIDpEFIBAABgOoRUAAAAmA4hFQAAAKZjil+cuhgKf5PAfqYfowUAAECFKcxp5/JbUpdMSE1LS5Mk1a1bt4J7AgAAgDNJS0uTzWY7Y80l87OoDodDR48eVZUqVWSxWMrlNe12u+rWrauoqKhL/qdYmVfg/LFMATCr8t4+GYahtLQ01apVSx4eZ77q9JI5kurh4aE6depUyGsHBQVdNjse5hU4fyxTAMyqPLdPZzuCWogbpwAAAGA6hFQAAACYDiH1AlitVo0aNUpWq7Wiu1LmmFfg/LFMATArM2+fLpkbpwAAAHDp4EgqAAAATIeQCgAAANMhpAIAAMB0CKkAAAAwHUIqAAAATIeQegbp6ekaNWqUunXrpuDgYFksFs2YMaPE2t27d6tbt24KDAxUcHCw/vnPfyo+Pr58O3wBdu3apV69eqlhw4by9/dXSEiIOnfurB9//LFYbWWf19WrV8tisZT42Lhxo1vt+vXr1bFjR/n7+yssLExDhw5Venp6BfUcZlAW2wWHw6F3331XDRo0kK+vr1q1aqVvvvmmjOcEwKVm8+bNeuaZZ3TVVVcpICBAERER6t27t/bt21estjJsny6Zn0UtCwkJCRozZowiIiJ09dVXa/Xq1SXWRUdHq3PnzrLZbBo7dqzS09M1ceJE7dixQ5s2bZKPj0/5dvw8HDlyRGlpaerfv79q1aqlzMxMff/99+rZs6c+/fRTDRo0SNKlMa+Fhg4dqmuvvdat7YorrnD9f/v27eratauaNWumyZMnKzo6WhMnTtT+/fu1dOnS8u4uTKIstguvvPKKxo8fryeeeELXXnutFixYoD59+shiseihhx4qpzkDUNm98847+vXXX9WrVy+1atVKx44d09SpU9W2bVtt3LhRLVq0kFSJtk8GTis7O9uIjY01DMMwNm/ebEgyvvjii2J1Tz31lOHn52ccOXLE1bZ8+XJDkvHpp5+WV3cvuvz8fOPqq682mjZt6mq7FOZ11apVhiTju+++O2Nd9+7djfDwcCM1NdXV9p///MeQZCxbtqysuwmTutjbhejoaMPb29t4+umnXW0Oh8Po1KmTUadOHSM/P7/sZgbAJeXXX381cnJy3Nr27dtnWK1W45FHHnG1VZbtE6f7z8BqtSosLOysdd9//73uuusuRUREuNpuueUWNWnSRHPmzCnLLpYpT09P1a1bVykpKa62S21e09LSlJ+fX6zdbrdr+fLl6tu3r4KCglzt/fr1U2BgYKWcV1wcF3u7sGDBAuXl5WnIkCGuNovFoqeeekrR0dHasGHDxZ0BAJesDh06FDuj2bhxY1111VXavXu3q62ybJ8IqRcoJiZGcXFxateuXbFh7du317Zt2yqgV+cvIyNDCQkJioyM1HvvvaelS5eqa9euki69eR0wYICCgoLk6+urm266SVu2bHEN27Fjh/Lz84vNq4+Pj1q3bl3p5hXlqzTryrZt2xQQEKBmzZoVqyscDgDnyzAMHT9+XCEhIZIq1/aJa1IvUGxsrCQpPDy82LDw8HAlJSUpJyfHlL+JW5IXXnhBn376qSTJw8ND9913n6ZOnSrp0plXHx8f3X///brjjjsUEhKiv/76SxMnTlSnTp20fv16tWnT5qzzunbt2vLuNiqR0qwrsbGxqlmzpiwWS7E6STp69GjZdxjAJevrr79WTEyMxowZI6lybZ8IqRcoKytLkkoMZr6+vq4aswe3QsOGDdMDDzygo0ePas6cOSooKFBubq6kS2deO3TooA4dOrie9+zZUw888IBatWqlkSNH6qeffjrrvBYOB0pSmnXldOvMyXUAcD727Nmjp59+WjfccIP69+8vqXJtnzjdf4H8/PwkSTk5OcWGZWdnu9VUBldeeaVuueUW9evXT4sWLVJ6erp69OghwzAuuXk92RVXXKG7775bq1atUkFBwVnntbLOJ8pHadYVPz+/S3KdAlCxjh07pjvvvFM2m01z586Vp6enpMq1fSKkXqDCQ96Fh89PFhsbq+DgYNMfWTyTBx54QJs3b9a+ffsu+XmtW7eucnNzlZGRcdZ5rVWrVnl3D5VIadaV8PBwHTt2TIZhFKuTxLIGoNRSU1PVvXt3paSk6KeffnLbjlSm7RMh9QLVrl1boaGhbjfdFNq0aZNat25d/p26iAoP5aempl7y83rw4EH5+voqMDBQLVq0kJeXV7F5zc3N1fbt2yv9vKJslWZdad26tTIzM93uvJWk3377zTUcAM5Vdna2evTooX379mnRokVq3ry52/DKtH0ipF4E999/vxYtWqSoqChX2y+//KJ9+/apV69eFdizcxcXF1esLS8vT1999ZX8/PxcC/mlMK8l/aLGH3/8oYULF+q2226Th4eHbDabbrnlFs2aNUtpaWmuupkzZyo9Pb3SzCsqzrmuK3fffbe8vb310UcfudoMw9Ann3yi2rVru10/DQBnUlBQoAcffFAbNmzQd999pxtuuKHEusqyfbIYpx7DhZupU6cqJSVFR48e1ccff6z77rtPbdq0kSQ9++yzstlsioqKUps2bVS1alU999xzSk9P14QJE1SnTh1t3ry5UpwCv/fee2W329W5c2fVrl1bx44d09dff609e/Zo0qRJGj58uCRdEvN68803y8/PTx06dFCNGjX0119/6bPPPpO3t7c2bNjg+qqNrVu3qkOHDmrevLkGDRqk6OhoTZo0SZ07d9ayZcsqeC5QkS72duFf//qXJkyYoEGDBunaa6/V/PnztXjxYn399dfq06dPRc0mgEpm2LBhev/999WjRw/17t272PC+fftKKt2+vEK3T2X6UwGXgHr16hmSSnwcOnTIVbdz507jtttuM/z9/Y2qVasajzzyiHHs2LGK63gpffPNN8Ytt9xi1KxZ0/Dy8jKqVatm3HLLLcaCBQuK1Vb2eX3//feN9u3bG8HBwYaXl5cRHh5u9O3b19i/f3+x2rVr1xodOnQwfH19jdDQUOPpp5827HZ7BfQaZnKxtwsFBQXG2LFjjXr16hk+Pj7GVVddZcyaNasc5wjApaBLly6n3TadGvkqw/aJI6kAAAAwHa5JBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApkNIBQAAgOkQUgEAAGA6hFQAAACYDiEVAAAApvP/VBMLpeFdQ3wAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# top1 accuracy\n",
    "CompoundT5 = [0, 0, 0, 0, 0]\n",
    "ReactionT5 = [92.8, 92.8, 92.9, 93.0, 93.2]\n",
    "T5Chem = [0.5, 0.2, 0.2, 0.1, 0.4][::-1]\n",
    "\n",
    "\n",
    "# plot\n",
    "import matplotlib.pyplot as plt\n",
    "fig, ax = plt.subplots(1, figsize=(8, 5))\n",
    "\n",
    "\n",
    "ax.plot([10,30,50,100,200], ReactionT5, \"o-\", label='ReactionT5', color='red', alpha=0.7)\n",
    "ax.plot([10,30,50,100,200], CompoundT5, \"s--\", label='CompoundT5', color='blue', alpha=0.7)\n",
    "ax.plot([10,30,50,100,200], T5Chem, \"v:\", label='T5Chem', color='green', alpha=0.7)\n",
    "\n",
    "\n",
    "plt.ylim(-5, 100)\n",
    "ax.set_xticks([10,30,50,100,200])\n",
    "ax.set_xticklabels([10,30,50,100,200], fontsize=12)\n",
    "# ax.set_yticks([10,20,30,40,50,60])\n",
    "ax.set_yticklabels([int(i) for i in ax.get_yticks()], fontsize=12)\n",
    "# plt.tight_layout()\n",
    "ax.legend(loc=\"best\", fontsize=12)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "818bcb61",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_2056154/1623126519.py:21: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  ax.set_yticklabels([int(i) for i in ax.get_yticks()], fontsize=12)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f69c90f7810>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Top5 invalidity\n",
    "CompoundT5 = [32.75, 18.76, 11.07, 20.99, 10.62]\n",
    "ReactionT5 = [12.5, 12.4, 12.5, 12.6, 12.9]\n",
    "T5Chem = [33.73, 38.94, 46.23, 69.05, 73.41][::-1]\n",
    "\n",
    "\n",
    "# plot\n",
    "import matplotlib.pyplot as plt\n",
    "fig, ax = plt.subplots(1, figsize=(8, 5))\n",
    "\n",
    "\n",
    "ax.plot([10,30,50,100,200], ReactionT5, \"o-\", label='ReactionT5', color='red', alpha=0.7)\n",
    "ax.plot([10,30,50,100,200], CompoundT5, \"s--\", label='CompoundT5', color='blue', alpha=0.7)\n",
    "ax.plot([10,30,50,100,200], T5Chem, \"v:\", label='T5Chem', color='green', alpha=0.7)\n",
    "\n",
    "\n",
    "# plt.ylim(0, 35)\n",
    "ax.set_xticks([10,30,50,100,200])\n",
    "ax.set_xticklabels([10,30,50,100,200], fontsize=12)\n",
    "# ax.set_yticks([10,20,30,40,50,60])\n",
    "ax.set_yticklabels([int(i) for i in ax.get_yticks()], fontsize=12)\n",
    "# plt.tight_layout()\n",
    "ax.legend(loc=\"best\", fontsize=12)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "reactiont5",
   "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": "3.8.18"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}