notebooks/mlp-learning-curve.ipynb

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    "tags": []
   },
   "source": [
    "# MLP Learning Curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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     "end_time": "2020-05-22T12:33:59.833885",
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   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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     "start_time": "2020-05-22T12:33:59.843978",
     "status": "completed"
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    "tags": []
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('..')\n",
    "\n",
    "import matplotlib.pylab as plt\n",
    "from tqdm import tqdm\n",
    "from IPython import display\n",
    "\n",
    "from src.visualization import plot_learning_curve\n",
    "from src.experiment_tagging import get_model_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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    "tags": []
   },
   "outputs": [],
   "source": [
    "LEARNING_CURVES_PARAMS = [('MNIST', {}),\n",
    "                          ('FASHION', {}),\n",
    "                          ('CIFAR10', {}),\n",
    "                          # ('LINE', {}),\n",
    "                          # ('RANDOM', {'secondary_y': ('train_loss', 'test_loss')}),\n",
    "                          # ('MNIST-x10-EPOCHS', {}),\n",
    "                          ('CIFAR10', {'start': 1, 'step': 1}),\n",
    "                          # ('RANDOM-x50-EPOCHS', {'start': 20, 'step': 20, 'secondary_y': ('train_loss', 'test_loss')}),\n",
    "                          # ('RANDOM-OVERFITTING', {}),\n",
    "                          ('FASHION', {'start': 1, 'step': 1}),\n",
    "                          ('MNIST', {'start': 1, 'step': 1}),\n",
    "                          ('MNIST+DROPOUT', {'start': 1, 'step': 1}),\n",
    "                          ('FASHION+DROPOUT', {'start': 1, 'step': 1}),\n",
    "                          ('CNN-MNIST', {}),\n",
    "                          ('CNN-CIFAR10', {}),\n",
    "                          ('CNN-FASHION', {}),\n",
    "                          ('CNN-MNIST+DROPOUT', {}),\n",
    "                          ('CNN-CIFAR10+DROPOUT', {}),\n",
    "                          ('CNN-FASHION+DROPOUT', {})]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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     "exception": false,
     "start_time": "2020-05-22T12:34:03.105883",
     "status": "completed"
    },
    "scrolled": false,
    "tags": []
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     "name": "stderr",
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      "\r",
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     "text": [
      "#### MNIST\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ave_in_out</th>\n",
       "      <th>is_pruned</th>\n",
       "      <th>ncut</th>\n",
       "      <th>test_acc</th>\n",
       "      <th>test_loss</th>\n",
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       "      <td>0.298732</td>\n",
       "      <td>False</td>\n",
       "      <td>2.503970</td>\n",
       "      <td>0.9792</td>\n",
       "      <td>0.086104</td>\n",
       "      <td>0.999233</td>\n",
       "      <td>0.003393</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.302624</td>\n",
       "      <td>False</td>\n",
       "      <td>2.491828</td>\n",
       "      <td>0.9794</td>\n",
       "      <td>0.073905</td>\n",
       "      <td>0.999133</td>\n",
       "      <td>0.003947</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.313147</td>\n",
       "      <td>False</td>\n",
       "      <td>2.459579</td>\n",
       "      <td>0.9812</td>\n",
       "      <td>0.075895</td>\n",
       "      <td>0.999567</td>\n",
       "      <td>0.002444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.320388</td>\n",
       "      <td>False</td>\n",
       "      <td>2.437871</td>\n",
       "      <td>0.9826</td>\n",
       "      <td>0.079448</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000203</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.398070</td>\n",
       "      <td>True</td>\n",
       "      <td>2.226999</td>\n",
       "      <td>0.9743</td>\n",
       "      <td>0.084641</td>\n",
       "      <td>0.983667</td>\n",
       "      <td>0.050424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.475014</td>\n",
       "      <td>True</td>\n",
       "      <td>2.051252</td>\n",
       "      <td>0.9725</td>\n",
       "      <td>0.108376</td>\n",
       "      <td>0.992367</td>\n",
       "      <td>0.021521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.513626</td>\n",
       "      <td>True</td>\n",
       "      <td>1.973115</td>\n",
       "      <td>0.9781</td>\n",
       "      <td>0.090984</td>\n",
       "      <td>0.995850</td>\n",
       "      <td>0.011347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.500091</td>\n",
       "      <td>True</td>\n",
       "      <td>1.999817</td>\n",
       "      <td>0.9788</td>\n",
       "      <td>0.096470</td>\n",
       "      <td>0.997083</td>\n",
       "      <td>0.009462</td>\n",
       "    </tr>\n",
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       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.298732      False  2.503970    0.9792   0.086104   0.999233   \n",
       "10       0.302624      False  2.491828    0.9794   0.073905   0.999133   \n",
       "15       0.313147      False  2.459579    0.9812   0.075895   0.999567   \n",
       "20       0.320388      False  2.437871    0.9826   0.079448   1.000000   \n",
       "25       0.398070       True  2.226999    0.9743   0.084641   0.983667   \n",
       "30       0.475014       True  2.051252    0.9725   0.108376   0.992367   \n",
       "35       0.513626       True  1.973115    0.9781   0.090984   0.995850   \n",
       "40       0.500091       True  1.999817    0.9788   0.096470   0.997083   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        0.003393  \n",
       "10       0.003947  \n",
       "15       0.002444  \n",
       "20       0.000203  \n",
       "25       0.050424  \n",
       "30       0.021521  \n",
       "35       0.011347  \n",
       "40       0.009462  "
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      "\r",
      "  8%|▊         | 1/13 [00:29<05:57, 29.80s/it]"
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     "text": [
      "#### FASHION\n"
     ]
    },
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       "      <th></th>\n",
       "      <th>ave_in_out</th>\n",
       "      <th>is_pruned</th>\n",
       "      <th>ncut</th>\n",
       "      <th>test_acc</th>\n",
       "      <th>test_loss</th>\n",
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       "    <tr>\n",
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       "      <td>0.312102</td>\n",
       "      <td>False</td>\n",
       "      <td>2.462744</td>\n",
       "      <td>0.8958</td>\n",
       "      <td>0.334922</td>\n",
       "      <td>0.965533</td>\n",
       "      <td>0.095046</td>\n",
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       "      <th>10</th>\n",
       "      <td>0.315924</td>\n",
       "      <td>False</td>\n",
       "      <td>2.451208</td>\n",
       "      <td>0.8896</td>\n",
       "      <td>0.351025</td>\n",
       "      <td>0.966217</td>\n",
       "      <td>0.094195</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.317949</td>\n",
       "      <td>False</td>\n",
       "      <td>2.445141</td>\n",
       "      <td>0.8908</td>\n",
       "      <td>0.369626</td>\n",
       "      <td>0.970083</td>\n",
       "      <td>0.087015</td>\n",
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.322847</td>\n",
       "      <td>False</td>\n",
       "      <td>2.430586</td>\n",
       "      <td>0.8921</td>\n",
       "      <td>0.429442</td>\n",
       "      <td>0.983483</td>\n",
       "      <td>0.052817</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.440250</td>\n",
       "      <td>True</td>\n",
       "      <td>2.127094</td>\n",
       "      <td>0.8655</td>\n",
       "      <td>0.364537</td>\n",
       "      <td>0.889800</td>\n",
       "      <td>0.292877</td>\n",
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       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.476574</td>\n",
       "      <td>True</td>\n",
       "      <td>2.047975</td>\n",
       "      <td>0.8791</td>\n",
       "      <td>0.342904</td>\n",
       "      <td>0.912917</td>\n",
       "      <td>0.228573</td>\n",
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       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.500045</td>\n",
       "      <td>True</td>\n",
       "      <td>1.999911</td>\n",
       "      <td>0.8882</td>\n",
       "      <td>0.323757</td>\n",
       "      <td>0.930433</td>\n",
       "      <td>0.181828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.522749</td>\n",
       "      <td>True</td>\n",
       "      <td>1.955514</td>\n",
       "      <td>0.8844</td>\n",
       "      <td>0.364730</td>\n",
       "      <td>0.943067</td>\n",
       "      <td>0.147317</td>\n",
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       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.312102      False  2.462744    0.8958   0.334922   0.965533   \n",
       "10       0.315924      False  2.451208    0.8896   0.351025   0.966217   \n",
       "15       0.317949      False  2.445141    0.8908   0.369626   0.970083   \n",
       "20       0.322847      False  2.430586    0.8921   0.429442   0.983483   \n",
       "25       0.440250       True  2.127094    0.8655   0.364537   0.889800   \n",
       "30       0.476574       True  2.047975    0.8791   0.342904   0.912917   \n",
       "35       0.500045       True  1.999911    0.8882   0.323757   0.930433   \n",
       "40       0.522749       True  1.955514    0.8844   0.364730   0.943067   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        0.095046  \n",
       "10       0.094195  \n",
       "15       0.087015  \n",
       "20       0.052817  \n",
       "25       0.292877  \n",
       "30       0.228573  \n",
       "35       0.181828  \n",
       "40       0.147317  "
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      "\r",
      " 15%|█▌        | 2/13 [01:12<06:09, 33.62s/it]"
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     "text": [
      "#### CIFAR10\n"
     ]
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       "      <td>0.344352</td>\n",
       "      <td>False</td>\n",
       "      <td>2.368680</td>\n",
       "      <td>0.4384</td>\n",
       "      <td>1.709334</td>\n",
       "      <td>0.62868</td>\n",
       "      <td>1.068558</td>\n",
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       "      <th>10</th>\n",
       "      <td>0.349221</td>\n",
       "      <td>False</td>\n",
       "      <td>2.355100</td>\n",
       "      <td>0.4272</td>\n",
       "      <td>1.797239</td>\n",
       "      <td>0.66846</td>\n",
       "      <td>0.958869</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.311117</td>\n",
       "      <td>False</td>\n",
       "      <td>2.465734</td>\n",
       "      <td>0.4153</td>\n",
       "      <td>1.833363</td>\n",
       "      <td>0.67322</td>\n",
       "      <td>0.939058</td>\n",
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       "      <th>20</th>\n",
       "      <td>0.321359</td>\n",
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       "      <td>2.434990</td>\n",
       "      <td>0.4234</td>\n",
       "      <td>1.857192</td>\n",
       "      <td>0.66016</td>\n",
       "      <td>0.968364</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.414280</td>\n",
       "      <td>True</td>\n",
       "      <td>2.187514</td>\n",
       "      <td>0.4212</td>\n",
       "      <td>1.824176</td>\n",
       "      <td>0.64754</td>\n",
       "      <td>1.002244</td>\n",
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       "      <th>30</th>\n",
       "      <td>0.447669</td>\n",
       "      <td>True</td>\n",
       "      <td>2.110442</td>\n",
       "      <td>0.4265</td>\n",
       "      <td>1.843362</td>\n",
       "      <td>0.65106</td>\n",
       "      <td>0.992971</td>\n",
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       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.483530</td>\n",
       "      <td>True</td>\n",
       "      <td>2.033492</td>\n",
       "      <td>0.4286</td>\n",
       "      <td>1.871332</td>\n",
       "      <td>0.66716</td>\n",
       "      <td>0.950089</td>\n",
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       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.514982</td>\n",
       "      <td>True</td>\n",
       "      <td>1.970479</td>\n",
       "      <td>0.4222</td>\n",
       "      <td>1.951416</td>\n",
       "      <td>0.68554</td>\n",
       "      <td>0.898098</td>\n",
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       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.543950</td>\n",
       "      <td>True</td>\n",
       "      <td>1.915801</td>\n",
       "      <td>0.3840</td>\n",
       "      <td>1.727342</td>\n",
       "      <td>0.38692</td>\n",
       "      <td>1.719610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.556664</td>\n",
       "      <td>True</td>\n",
       "      <td>1.892750</td>\n",
       "      <td>0.3920</td>\n",
       "      <td>1.716206</td>\n",
       "      <td>0.43998</td>\n",
       "      <td>1.580413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.559710</td>\n",
       "      <td>True</td>\n",
       "      <td>1.887309</td>\n",
       "      <td>0.4185</td>\n",
       "      <td>1.676686</td>\n",
       "      <td>0.48746</td>\n",
       "      <td>1.443539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.566347</td>\n",
       "      <td>True</td>\n",
       "      <td>1.875563</td>\n",
       "      <td>0.4173</td>\n",
       "      <td>1.715791</td>\n",
       "      <td>0.54426</td>\n",
       "      <td>1.287576</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.344352      False  2.368680    0.4384   1.709334    0.62868   \n",
       "10       0.349221      False  2.355100    0.4272   1.797239    0.66846   \n",
       "15       0.311117      False  2.465734    0.4153   1.833363    0.67322   \n",
       "20       0.321359      False  2.434990    0.4234   1.857192    0.66016   \n",
       "25       0.414280       True  2.187514    0.4212   1.824176    0.64754   \n",
       "30       0.447669       True  2.110442    0.4265   1.843362    0.65106   \n",
       "35       0.483530       True  2.033492    0.4286   1.871332    0.66716   \n",
       "40       0.514982       True  1.970479    0.4222   1.951416    0.68554   \n",
       "45       0.543950       True  1.915801    0.3840   1.727342    0.38692   \n",
       "50       0.556664       True  1.892750    0.3920   1.716206    0.43998   \n",
       "55       0.559710       True  1.887309    0.4185   1.676686    0.48746   \n",
       "60       0.566347       True  1.875563    0.4173   1.715791    0.54426   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        1.068558  \n",
       "10       0.958869  \n",
       "15       0.939058  \n",
       "20       0.968364  \n",
       "25       1.002244  \n",
       "30       0.992971  \n",
       "35       0.950089  \n",
       "40       0.898098  \n",
       "45       1.719610  \n",
       "50       1.580413  \n",
       "55       1.443539  \n",
       "60       1.287576  "
      ]
     },
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    {
     "name": "stderr",
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      "\r",
      " 23%|██▎       | 3/13 [02:51<08:51, 53.18s/it]"
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      "#### LINE\n"
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       "      <th>ave_in_out</th>\n",
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       "      <td>1.000</td>\n",
       "      <td>0.000019</td>\n",
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       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1.177125</td>\n",
       "      <td>True</td>\n",
       "      <td>1.192517</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000005</td>\n",
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       "</table>\n",
       "</div>"
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       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.368501      False  2.302817       1.0   0.009356      0.982   \n",
       "10       0.371556      False  2.294746       1.0   0.002578      1.000   \n",
       "15       0.379551      False  2.273887       1.0   0.000673      1.000   \n",
       "20       0.381351      False  2.269244       1.0   0.000166      1.000   \n",
       "25       0.518983       True  1.962741       1.0   0.000341      1.000   \n",
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       "40       1.177125       True  1.192517       1.0   0.000005      1.000   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        0.089788  \n",
       "10       0.003133  \n",
       "15       0.000784  \n",
       "20       0.000187  \n",
       "25       0.000428  \n",
       "30       0.000073  \n",
       "35       0.000019  \n",
       "40       0.000005  "
      ]
     },
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 31%|███       | 4/13 [04:21<09:38, 64.33s/it]"
     ]
    },
    {
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     "text": [
      "#### RANDOM\n"
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       "      <td>2.305616</td>\n",
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       "      <th>15</th>\n",
       "      <td>0.360948</td>\n",
       "      <td>False</td>\n",
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       "      <td>0.0987</td>\n",
       "      <td>2.306007</td>\n",
       "      <td>0.112467</td>\n",
       "      <td>2.300280</td>\n",
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.296249</td>\n",
       "      <td>False</td>\n",
       "      <td>2.511777</td>\n",
       "      <td>0.0948</td>\n",
       "      <td>2.311919</td>\n",
       "      <td>0.120950</td>\n",
       "      <td>2.296012</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.410462</td>\n",
       "      <td>True</td>\n",
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       "      <td>0.1021</td>\n",
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       "      <td>0.166588</td>\n",
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       "      <th>35</th>\n",
       "      <td>0.239126</td>\n",
       "      <td>True</td>\n",
       "      <td>2.705900</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.315830</td>\n",
       "      <td>0.099233</td>\n",
       "      <td>2.314996</td>\n",
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       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.821347</td>\n",
       "      <td>True</td>\n",
       "      <td>1.513607</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>2.316033</td>\n",
       "      <td>0.099267</td>\n",
       "      <td>2.317961</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.359509      False  2.326911    0.1021   2.307334   0.099533   \n",
       "10       0.354817      False  2.339681    0.0947   2.306377   0.098650   \n",
       "15       0.360948      False  2.323021    0.0987   2.306007   0.112467   \n",
       "20       0.296249      False  2.511777    0.0948   2.311919   0.120950   \n",
       "25       0.410462       True  2.196688    0.1021   2.315045   0.099650   \n",
       "30       0.166588       True  3.000354    0.1039   2.307347   0.100233   \n",
       "35       0.239126       True  2.705900    0.1021   2.315830   0.099233   \n",
       "40       0.821347       True  1.513607    0.1030   2.316033   0.099267   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        2.307488  \n",
       "10       2.305616  \n",
       "15       2.300280  \n",
       "20       2.296012  \n",
       "25       2.317250  \n",
       "30       2.317089  \n",
       "35       2.314996  \n",
       "40       2.317961  "
      ]
     },
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 38%|███▊      | 5/13 [06:13<10:29, 78.63s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#### MNIST-x10-EPOCHS\n"
     ]
    },
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       "      <td>0.306358</td>\n",
       "      <td>False</td>\n",
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       "      <td>0.9796</td>\n",
       "      <td>0.086730</td>\n",
       "      <td>0.998717</td>\n",
       "      <td>4.821035e-03</td>\n",
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       "      <th>15</th>\n",
       "      <td>0.310690</td>\n",
       "      <td>False</td>\n",
       "      <td>2.467035</td>\n",
       "      <td>0.9783</td>\n",
       "      <td>0.089501</td>\n",
       "      <td>0.999683</td>\n",
       "      <td>2.380544e-03</td>\n",
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.312849</td>\n",
       "      <td>False</td>\n",
       "      <td>2.460480</td>\n",
       "      <td>0.9787</td>\n",
       "      <td>0.098227</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.650834e-04</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.320103</td>\n",
       "      <td>False</td>\n",
       "      <td>2.438717</td>\n",
       "      <td>0.9756</td>\n",
       "      <td>0.084000</td>\n",
       "      <td>0.984750</td>\n",
       "      <td>4.798618e-02</td>\n",
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       "      <th>30</th>\n",
       "      <td>0.323960</td>\n",
       "      <td>False</td>\n",
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       "      <td>0.9768</td>\n",
       "      <td>0.081235</td>\n",
       "      <td>0.993383</td>\n",
       "      <td>1.994302e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.326631</td>\n",
       "      <td>False</td>\n",
       "      <td>2.419458</td>\n",
       "      <td>0.9781</td>\n",
       "      <td>0.088773</td>\n",
       "      <td>0.996717</td>\n",
       "      <td>1.038723e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.325641</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422359</td>\n",
       "      <td>0.9782</td>\n",
       "      <td>0.101042</td>\n",
       "      <td>0.996350</td>\n",
       "      <td>1.026103e-02</td>\n",
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       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.315957</td>\n",
       "      <td>False</td>\n",
       "      <td>2.451110</td>\n",
       "      <td>0.9797</td>\n",
       "      <td>0.087551</td>\n",
       "      <td>0.996867</td>\n",
       "      <td>9.268631e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.329995</td>\n",
       "      <td>False</td>\n",
       "      <td>2.409654</td>\n",
       "      <td>0.9768</td>\n",
       "      <td>0.115202</td>\n",
       "      <td>0.997667</td>\n",
       "      <td>8.122570e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.330678</td>\n",
       "      <td>False</td>\n",
       "      <td>2.407672</td>\n",
       "      <td>0.9780</td>\n",
       "      <td>0.104215</td>\n",
       "      <td>0.998017</td>\n",
       "      <td>5.933828e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.340652</td>\n",
       "      <td>False</td>\n",
       "      <td>2.379105</td>\n",
       "      <td>0.9769</td>\n",
       "      <td>0.114527</td>\n",
       "      <td>0.997250</td>\n",
       "      <td>8.793578e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>0.348671</td>\n",
       "      <td>False</td>\n",
       "      <td>2.356626</td>\n",
       "      <td>0.9779</td>\n",
       "      <td>0.112699</td>\n",
       "      <td>0.997433</td>\n",
       "      <td>7.769395e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.353838</td>\n",
       "      <td>False</td>\n",
       "      <td>2.342364</td>\n",
       "      <td>0.9776</td>\n",
       "      <td>0.122548</td>\n",
       "      <td>0.996600</td>\n",
       "      <td>1.067367e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0.348922</td>\n",
       "      <td>False</td>\n",
       "      <td>2.355929</td>\n",
       "      <td>0.9814</td>\n",
       "      <td>0.108013</td>\n",
       "      <td>0.999183</td>\n",
       "      <td>2.659809e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.351451</td>\n",
       "      <td>False</td>\n",
       "      <td>2.348932</td>\n",
       "      <td>0.9802</td>\n",
       "      <td>0.112428</td>\n",
       "      <td>0.998600</td>\n",
       "      <td>4.298960e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0.350253</td>\n",
       "      <td>False</td>\n",
       "      <td>2.352242</td>\n",
       "      <td>0.9756</td>\n",
       "      <td>0.147622</td>\n",
       "      <td>0.999267</td>\n",
       "      <td>2.432656e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.350094</td>\n",
       "      <td>False</td>\n",
       "      <td>2.352681</td>\n",
       "      <td>0.9809</td>\n",
       "      <td>0.114414</td>\n",
       "      <td>0.999533</td>\n",
       "      <td>1.778099e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.353903</td>\n",
       "      <td>False</td>\n",
       "      <td>2.342186</td>\n",
       "      <td>0.9803</td>\n",
       "      <td>0.112896</td>\n",
       "      <td>0.998983</td>\n",
       "      <td>2.631724e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>0.352646</td>\n",
       "      <td>False</td>\n",
       "      <td>2.345640</td>\n",
       "      <td>0.9817</td>\n",
       "      <td>0.103061</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.097612e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>0.353218</td>\n",
       "      <td>False</td>\n",
       "      <td>2.344066</td>\n",
       "      <td>0.9824</td>\n",
       "      <td>0.105392</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.429004e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>0.352345</td>\n",
       "      <td>False</td>\n",
       "      <td>2.346468</td>\n",
       "      <td>0.9827</td>\n",
       "      <td>0.109078</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.595406e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>0.350898</td>\n",
       "      <td>False</td>\n",
       "      <td>2.350458</td>\n",
       "      <td>0.9831</td>\n",
       "      <td>0.113568</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.055753e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>0.348003</td>\n",
       "      <td>False</td>\n",
       "      <td>2.358481</td>\n",
       "      <td>0.9832</td>\n",
       "      <td>0.119010</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.162006e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>0.345808</td>\n",
       "      <td>False</td>\n",
       "      <td>2.364603</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.124478</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.426112e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>0.345352</td>\n",
       "      <td>False</td>\n",
       "      <td>2.365879</td>\n",
       "      <td>0.9830</td>\n",
       "      <td>0.129594</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.402248e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>0.345323</td>\n",
       "      <td>False</td>\n",
       "      <td>2.365958</td>\n",
       "      <td>0.9830</td>\n",
       "      <td>0.134395</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.216859e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>0.345304</td>\n",
       "      <td>False</td>\n",
       "      <td>2.366014</td>\n",
       "      <td>0.9831</td>\n",
       "      <td>0.138493</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.447597e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>0.344560</td>\n",
       "      <td>False</td>\n",
       "      <td>2.368098</td>\n",
       "      <td>0.9830</td>\n",
       "      <td>0.141423</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.804233e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>0.344550</td>\n",
       "      <td>False</td>\n",
       "      <td>2.368124</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.143164</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.957119e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>0.344544</td>\n",
       "      <td>False</td>\n",
       "      <td>2.368143</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.144265</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.443161e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>0.344254</td>\n",
       "      <td>False</td>\n",
       "      <td>2.368955</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.144852</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.652406e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>0.343518</td>\n",
       "      <td>False</td>\n",
       "      <td>2.371023</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.145211</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.145767e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>0.343516</td>\n",
       "      <td>False</td>\n",
       "      <td>2.371028</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.145339</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.770258e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>0.343515</td>\n",
       "      <td>False</td>\n",
       "      <td>2.371031</td>\n",
       "      <td>0.9834</td>\n",
       "      <td>0.145437</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.539786e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0.343514</td>\n",
       "      <td>False</td>\n",
       "      <td>2.371034</td>\n",
       "      <td>0.9832</td>\n",
       "      <td>0.145373</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.349052e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>0.343513</td>\n",
       "      <td>False</td>\n",
       "      <td>2.371036</td>\n",
       "      <td>0.9832</td>\n",
       "      <td>0.145308</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.229842e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0.343513</td>\n",
       "      <td>False</td>\n",
       "      <td>2.371038</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.145170</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.104673e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>0.343512</td>\n",
       "      <td>False</td>\n",
       "      <td>2.371039</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.144994</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.045068e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>0.343188</td>\n",
       "      <td>False</td>\n",
       "      <td>2.371950</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.144755</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.953975e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>0.434798</td>\n",
       "      <td>True</td>\n",
       "      <td>2.139499</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.144522</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.616215e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>0.479725</td>\n",
       "      <td>True</td>\n",
       "      <td>2.041389</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>0.144312</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.119510e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>0.516837</td>\n",
       "      <td>True</td>\n",
       "      <td>1.966884</td>\n",
       "      <td>0.9834</td>\n",
       "      <td>0.144086</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.900960e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>0.522979</td>\n",
       "      <td>True</td>\n",
       "      <td>1.955074</td>\n",
       "      <td>0.9835</td>\n",
       "      <td>0.143912</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.702277e-10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.300284      False  2.499113    0.9796   0.105727   0.999050   \n",
       "10       0.306358      False  2.480288    0.9796   0.086730   0.998717   \n",
       "15       0.310690      False  2.467035    0.9783   0.089501   0.999683   \n",
       "20       0.312849      False  2.460480    0.9787   0.098227   1.000000   \n",
       "25       0.320103      False  2.438717    0.9756   0.084000   0.984750   \n",
       "30       0.323960      False  2.427302    0.9768   0.081235   0.993383   \n",
       "35       0.326631      False  2.419458    0.9781   0.088773   0.996717   \n",
       "40       0.325641      False  2.422359    0.9782   0.101042   0.996350   \n",
       "45       0.315957      False  2.451110    0.9797   0.087551   0.996867   \n",
       "50       0.329995      False  2.409654    0.9768   0.115202   0.997667   \n",
       "55       0.330678      False  2.407672    0.9780   0.104215   0.998017   \n",
       "60       0.340652      False  2.379105    0.9769   0.114527   0.997250   \n",
       "65       0.348671      False  2.356626    0.9779   0.112699   0.997433   \n",
       "70       0.353838      False  2.342364    0.9776   0.122548   0.996600   \n",
       "75       0.348922      False  2.355929    0.9814   0.108013   0.999183   \n",
       "80       0.351451      False  2.348932    0.9802   0.112428   0.998600   \n",
       "85       0.350253      False  2.352242    0.9756   0.147622   0.999267   \n",
       "90       0.350094      False  2.352681    0.9809   0.114414   0.999533   \n",
       "95       0.353903      False  2.342186    0.9803   0.112896   0.998983   \n",
       "100      0.352646      False  2.345640    0.9817   0.103061   1.000000   \n",
       "105      0.353218      False  2.344066    0.9824   0.105392   1.000000   \n",
       "110      0.352345      False  2.346468    0.9827   0.109078   1.000000   \n",
       "115      0.350898      False  2.350458    0.9831   0.113568   1.000000   \n",
       "120      0.348003      False  2.358481    0.9832   0.119010   1.000000   \n",
       "125      0.345808      False  2.364603    0.9833   0.124478   1.000000   \n",
       "130      0.345352      False  2.365879    0.9830   0.129594   1.000000   \n",
       "135      0.345323      False  2.365958    0.9830   0.134395   1.000000   \n",
       "140      0.345304      False  2.366014    0.9831   0.138493   1.000000   \n",
       "145      0.344560      False  2.368098    0.9830   0.141423   1.000000   \n",
       "150      0.344550      False  2.368124    0.9833   0.143164   1.000000   \n",
       "155      0.344544      False  2.368143    0.9833   0.144265   1.000000   \n",
       "160      0.344254      False  2.368955    0.9833   0.144852   1.000000   \n",
       "165      0.343518      False  2.371023    0.9833   0.145211   1.000000   \n",
       "170      0.343516      False  2.371028    0.9833   0.145339   1.000000   \n",
       "175      0.343515      False  2.371031    0.9834   0.145437   1.000000   \n",
       "180      0.343514      False  2.371034    0.9832   0.145373   1.000000   \n",
       "185      0.343513      False  2.371036    0.9832   0.145308   1.000000   \n",
       "190      0.343513      False  2.371038    0.9833   0.145170   1.000000   \n",
       "195      0.343512      False  2.371039    0.9833   0.144994   1.000000   \n",
       "200      0.343188      False  2.371950    0.9833   0.144755   1.000000   \n",
       "205      0.434798       True  2.139499    0.9833   0.144522   1.000000   \n",
       "210      0.479725       True  2.041389    0.9833   0.144312   1.000000   \n",
       "215      0.516837       True  1.966884    0.9834   0.144086   1.000000   \n",
       "220      0.522979       True  1.955074    0.9835   0.143912   1.000000   \n",
       "\n",
       "         train_loss  \n",
       "epoch                \n",
       "5      3.316488e-03  \n",
       "10     4.821035e-03  \n",
       "15     2.380544e-03  \n",
       "20     2.650834e-04  \n",
       "25     4.798618e-02  \n",
       "30     1.994302e-02  \n",
       "35     1.038723e-02  \n",
       "40     1.026103e-02  \n",
       "45     9.268631e-03  \n",
       "50     8.122570e-03  \n",
       "55     5.933828e-03  \n",
       "60     8.793578e-03  \n",
       "65     7.769395e-03  \n",
       "70     1.067367e-02  \n",
       "75     2.659809e-03  \n",
       "80     4.298960e-03  \n",
       "85     2.432656e-03  \n",
       "90     1.778099e-03  \n",
       "95     2.631724e-03  \n",
       "100    4.097612e-05  \n",
       "105    1.429004e-05  \n",
       "110    5.595406e-06  \n",
       "115    2.055753e-06  \n",
       "120    7.162006e-07  \n",
       "125    2.426112e-07  \n",
       "130    8.402248e-08  \n",
       "135    3.216859e-08  \n",
       "140    1.447597e-08  \n",
       "145    7.804233e-09  \n",
       "150    4.957119e-09  \n",
       "155    3.443161e-09  \n",
       "160    2.652406e-09  \n",
       "165    2.145767e-09  \n",
       "170    1.770258e-09  \n",
       "175    1.539786e-09  \n",
       "180    1.349052e-09  \n",
       "185    1.229842e-09  \n",
       "190    1.104673e-09  \n",
       "195    1.045068e-09  \n",
       "200    9.953975e-10  \n",
       "205    9.616215e-10  \n",
       "210    9.119510e-10  \n",
       "215    8.900960e-10  \n",
       "220    8.702277e-10  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 46%|████▌     | 6/13 [21:32<38:35, 330.74s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#### CIFAR10\n"
     ]
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>ave_in_out</th>\n",
       "      <th>is_pruned</th>\n",
       "      <th>ncut</th>\n",
       "      <th>test_acc</th>\n",
       "      <th>test_loss</th>\n",
       "      <th>train_acc</th>\n",
       "      <th>train_loss</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>epoch</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.344352</td>\n",
       "      <td>False</td>\n",
       "      <td>2.368680</td>\n",
       "      <td>0.4384</td>\n",
       "      <td>1.709334</td>\n",
       "      <td>0.62868</td>\n",
       "      <td>1.068558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.349221</td>\n",
       "      <td>False</td>\n",
       "      <td>2.355100</td>\n",
       "      <td>0.4272</td>\n",
       "      <td>1.797239</td>\n",
       "      <td>0.66846</td>\n",
       "      <td>0.958869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.311117</td>\n",
       "      <td>False</td>\n",
       "      <td>2.465734</td>\n",
       "      <td>0.4153</td>\n",
       "      <td>1.833363</td>\n",
       "      <td>0.67322</td>\n",
       "      <td>0.939058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.321359</td>\n",
       "      <td>False</td>\n",
       "      <td>2.434990</td>\n",
       "      <td>0.4234</td>\n",
       "      <td>1.857192</td>\n",
       "      <td>0.66016</td>\n",
       "      <td>0.968364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.414280</td>\n",
       "      <td>True</td>\n",
       "      <td>2.187514</td>\n",
       "      <td>0.4212</td>\n",
       "      <td>1.824176</td>\n",
       "      <td>0.64754</td>\n",
       "      <td>1.002244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.447669</td>\n",
       "      <td>True</td>\n",
       "      <td>2.110442</td>\n",
       "      <td>0.4265</td>\n",
       "      <td>1.843362</td>\n",
       "      <td>0.65106</td>\n",
       "      <td>0.992971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.483530</td>\n",
       "      <td>True</td>\n",
       "      <td>2.033492</td>\n",
       "      <td>0.4286</td>\n",
       "      <td>1.871332</td>\n",
       "      <td>0.66716</td>\n",
       "      <td>0.950089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.514982</td>\n",
       "      <td>True</td>\n",
       "      <td>1.970479</td>\n",
       "      <td>0.4222</td>\n",
       "      <td>1.951416</td>\n",
       "      <td>0.68554</td>\n",
       "      <td>0.898098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.543950</td>\n",
       "      <td>True</td>\n",
       "      <td>1.915801</td>\n",
       "      <td>0.3840</td>\n",
       "      <td>1.727342</td>\n",
       "      <td>0.38692</td>\n",
       "      <td>1.719610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.556664</td>\n",
       "      <td>True</td>\n",
       "      <td>1.892750</td>\n",
       "      <td>0.3920</td>\n",
       "      <td>1.716206</td>\n",
       "      <td>0.43998</td>\n",
       "      <td>1.580413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.559710</td>\n",
       "      <td>True</td>\n",
       "      <td>1.887309</td>\n",
       "      <td>0.4185</td>\n",
       "      <td>1.676686</td>\n",
       "      <td>0.48746</td>\n",
       "      <td>1.443539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.566347</td>\n",
       "      <td>True</td>\n",
       "      <td>1.875563</td>\n",
       "      <td>0.4173</td>\n",
       "      <td>1.715791</td>\n",
       "      <td>0.54426</td>\n",
       "      <td>1.287576</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.344352      False  2.368680    0.4384   1.709334    0.62868   \n",
       "10       0.349221      False  2.355100    0.4272   1.797239    0.66846   \n",
       "15       0.311117      False  2.465734    0.4153   1.833363    0.67322   \n",
       "20       0.321359      False  2.434990    0.4234   1.857192    0.66016   \n",
       "25       0.414280       True  2.187514    0.4212   1.824176    0.64754   \n",
       "30       0.447669       True  2.110442    0.4265   1.843362    0.65106   \n",
       "35       0.483530       True  2.033492    0.4286   1.871332    0.66716   \n",
       "40       0.514982       True  1.970479    0.4222   1.951416    0.68554   \n",
       "45       0.543950       True  1.915801    0.3840   1.727342    0.38692   \n",
       "50       0.556664       True  1.892750    0.3920   1.716206    0.43998   \n",
       "55       0.559710       True  1.887309    0.4185   1.676686    0.48746   \n",
       "60       0.566347       True  1.875563    0.4173   1.715791    0.54426   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        1.068558  \n",
       "10       0.958869  \n",
       "15       0.939058  \n",
       "20       0.968364  \n",
       "25       1.002244  \n",
       "30       0.992971  \n",
       "35       0.950089  \n",
       "40       0.898098  \n",
       "45       1.719610  \n",
       "50       1.580413  \n",
       "55       1.443539  \n",
       "60       1.287576  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 54%|█████▍    | 7/13 [27:24<33:42, 337.14s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#### RANDOM-x50-EPOCHS\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ave_in_out</th>\n",
       "      <th>is_pruned</th>\n",
       "      <th>ncut</th>\n",
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       "      <th>5</th>\n",
       "      <td>0.355942</td>\n",
       "      <td>False</td>\n",
       "      <td>2.336606</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.310955</td>\n",
       "      <td>0.097967</td>\n",
       "      <td>2.307100</td>\n",
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       "      <th>10</th>\n",
       "      <td>0.356321</td>\n",
       "      <td>False</td>\n",
       "      <td>2.335573</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.308504</td>\n",
       "      <td>0.100067</td>\n",
       "      <td>2.305387</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.350606</td>\n",
       "      <td>False</td>\n",
       "      <td>2.351266</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.305254</td>\n",
       "      <td>0.099583</td>\n",
       "      <td>2.304654</td>\n",
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.294397</td>\n",
       "      <td>False</td>\n",
       "      <td>2.517634</td>\n",
       "      <td>0.0965</td>\n",
       "      <td>2.304393</td>\n",
       "      <td>0.098450</td>\n",
       "      <td>2.304219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.294644</td>\n",
       "      <td>False</td>\n",
       "      <td>2.516849</td>\n",
       "      <td>0.0988</td>\n",
       "      <td>2.311399</td>\n",
       "      <td>0.098683</td>\n",
       "      <td>2.316921</td>\n",
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       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.296858</td>\n",
       "      <td>False</td>\n",
       "      <td>2.509858</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.318370</td>\n",
       "      <td>0.100267</td>\n",
       "      <td>2.318280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.302130</td>\n",
       "      <td>False</td>\n",
       "      <td>2.493361</td>\n",
       "      <td>0.1039</td>\n",
       "      <td>2.308077</td>\n",
       "      <td>0.100583</td>\n",
       "      <td>2.317127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.306480</td>\n",
       "      <td>False</td>\n",
       "      <td>2.479913</td>\n",
       "      <td>0.0965</td>\n",
       "      <td>2.309423</td>\n",
       "      <td>0.099233</td>\n",
       "      <td>2.318400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.322708</td>\n",
       "      <td>False</td>\n",
       "      <td>2.430996</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>2.324148</td>\n",
       "      <td>0.100783</td>\n",
       "      <td>2.317787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.320082</td>\n",
       "      <td>False</td>\n",
       "      <td>2.438781</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.322442</td>\n",
       "      <td>0.100783</td>\n",
       "      <td>2.317174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.320181</td>\n",
       "      <td>False</td>\n",
       "      <td>2.438486</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>2.334742</td>\n",
       "      <td>0.101117</td>\n",
       "      <td>2.315692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.320644</td>\n",
       "      <td>False</td>\n",
       "      <td>2.437110</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.315603</td>\n",
       "      <td>0.099700</td>\n",
       "      <td>2.317409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>0.323089</td>\n",
       "      <td>False</td>\n",
       "      <td>2.429870</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.324509</td>\n",
       "      <td>0.100483</td>\n",
       "      <td>2.317212</td>\n",
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       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.322433</td>\n",
       "      <td>False</td>\n",
       "      <td>2.431809</td>\n",
       "      <td>0.0988</td>\n",
       "      <td>2.325819</td>\n",
       "      <td>0.100117</td>\n",
       "      <td>2.317218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0.347559</td>\n",
       "      <td>False</td>\n",
       "      <td>2.359716</td>\n",
       "      <td>0.0941</td>\n",
       "      <td>2.341359</td>\n",
       "      <td>0.100800</td>\n",
       "      <td>2.317006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.323519</td>\n",
       "      <td>False</td>\n",
       "      <td>2.428601</td>\n",
       "      <td>0.1003</td>\n",
       "      <td>2.313021</td>\n",
       "      <td>0.102667</td>\n",
       "      <td>2.316950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0.324085</td>\n",
       "      <td>False</td>\n",
       "      <td>2.426933</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.317903</td>\n",
       "      <td>0.101350</td>\n",
       "      <td>2.316999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.325065</td>\n",
       "      <td>False</td>\n",
       "      <td>2.424051</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>2.319771</td>\n",
       "      <td>0.102200</td>\n",
       "      <td>2.318608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.323900</td>\n",
       "      <td>False</td>\n",
       "      <td>2.427478</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.309376</td>\n",
       "      <td>0.098417</td>\n",
       "      <td>2.316847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>0.328097</td>\n",
       "      <td>False</td>\n",
       "      <td>2.415177</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>2.313287</td>\n",
       "      <td>0.101100</td>\n",
       "      <td>2.317602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>0.328349</td>\n",
       "      <td>False</td>\n",
       "      <td>2.414442</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.315201</td>\n",
       "      <td>0.099317</td>\n",
       "      <td>2.318657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>0.329196</td>\n",
       "      <td>False</td>\n",
       "      <td>2.411974</td>\n",
       "      <td>0.1042</td>\n",
       "      <td>2.313695</td>\n",
       "      <td>0.100150</td>\n",
       "      <td>2.317820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>0.328625</td>\n",
       "      <td>False</td>\n",
       "      <td>2.413637</td>\n",
       "      <td>0.0965</td>\n",
       "      <td>2.309560</td>\n",
       "      <td>0.101417</td>\n",
       "      <td>2.317001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>0.329909</td>\n",
       "      <td>False</td>\n",
       "      <td>2.409901</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.321404</td>\n",
       "      <td>0.101833</td>\n",
       "      <td>2.318134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>0.329895</td>\n",
       "      <td>False</td>\n",
       "      <td>2.409943</td>\n",
       "      <td>0.1042</td>\n",
       "      <td>2.325037</td>\n",
       "      <td>0.100683</td>\n",
       "      <td>2.316771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>0.330357</td>\n",
       "      <td>False</td>\n",
       "      <td>2.408602</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.317416</td>\n",
       "      <td>0.100017</td>\n",
       "      <td>2.317817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>0.329867</td>\n",
       "      <td>False</td>\n",
       "      <td>2.410025</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>2.305767</td>\n",
       "      <td>0.098683</td>\n",
       "      <td>2.317835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>0.328964</td>\n",
       "      <td>False</td>\n",
       "      <td>2.412650</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.333505</td>\n",
       "      <td>0.101300</td>\n",
       "      <td>2.316775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>0.328868</td>\n",
       "      <td>False</td>\n",
       "      <td>2.412930</td>\n",
       "      <td>0.1042</td>\n",
       "      <td>2.315379</td>\n",
       "      <td>0.101617</td>\n",
       "      <td>2.316213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>0.328860</td>\n",
       "      <td>False</td>\n",
       "      <td>2.412954</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.315767</td>\n",
       "      <td>0.100700</td>\n",
       "      <td>2.317925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875</th>\n",
       "      <td>0.325625</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422407</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.324281</td>\n",
       "      <td>0.100233</td>\n",
       "      <td>2.316854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>0.325636</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422376</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.323624</td>\n",
       "      <td>0.099700</td>\n",
       "      <td>2.317254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>0.324753</td>\n",
       "      <td>False</td>\n",
       "      <td>2.424969</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.310489</td>\n",
       "      <td>0.098817</td>\n",
       "      <td>2.317833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>0.326131</td>\n",
       "      <td>False</td>\n",
       "      <td>2.420925</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.313672</td>\n",
       "      <td>0.099533</td>\n",
       "      <td>2.315808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>0.324741</td>\n",
       "      <td>False</td>\n",
       "      <td>2.425003</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.313402</td>\n",
       "      <td>0.099767</td>\n",
       "      <td>2.317491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>0.325637</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422372</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.327268</td>\n",
       "      <td>0.100250</td>\n",
       "      <td>2.317143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>905</th>\n",
       "      <td>0.325164</td>\n",
       "      <td>False</td>\n",
       "      <td>2.423761</td>\n",
       "      <td>0.1003</td>\n",
       "      <td>2.320317</td>\n",
       "      <td>0.099017</td>\n",
       "      <td>2.317965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>910</th>\n",
       "      <td>0.325636</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422374</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.319006</td>\n",
       "      <td>0.100583</td>\n",
       "      <td>2.317111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>915</th>\n",
       "      <td>0.326115</td>\n",
       "      <td>False</td>\n",
       "      <td>2.420971</td>\n",
       "      <td>0.1003</td>\n",
       "      <td>2.333408</td>\n",
       "      <td>0.100217</td>\n",
       "      <td>2.316686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>920</th>\n",
       "      <td>0.325636</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422375</td>\n",
       "      <td>0.1042</td>\n",
       "      <td>2.316808</td>\n",
       "      <td>0.099867</td>\n",
       "      <td>2.316765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>925</th>\n",
       "      <td>0.325701</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422184</td>\n",
       "      <td>0.1039</td>\n",
       "      <td>2.312121</td>\n",
       "      <td>0.099600</td>\n",
       "      <td>2.317557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>0.324959</td>\n",
       "      <td>False</td>\n",
       "      <td>2.424364</td>\n",
       "      <td>0.0965</td>\n",
       "      <td>2.314447</td>\n",
       "      <td>0.102767</td>\n",
       "      <td>2.316571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>935</th>\n",
       "      <td>0.325439</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422954</td>\n",
       "      <td>0.0965</td>\n",
       "      <td>2.310216</td>\n",
       "      <td>0.100300</td>\n",
       "      <td>2.317065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>940</th>\n",
       "      <td>0.325439</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422953</td>\n",
       "      <td>0.1039</td>\n",
       "      <td>2.316181</td>\n",
       "      <td>0.099117</td>\n",
       "      <td>2.316900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>945</th>\n",
       "      <td>0.324962</td>\n",
       "      <td>False</td>\n",
       "      <td>2.424355</td>\n",
       "      <td>0.0965</td>\n",
       "      <td>2.313311</td>\n",
       "      <td>0.102817</td>\n",
       "      <td>2.315467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>950</th>\n",
       "      <td>0.325440</td>\n",
       "      <td>False</td>\n",
       "      <td>2.422950</td>\n",
       "      <td>0.0965</td>\n",
       "      <td>2.316452</td>\n",
       "      <td>0.099217</td>\n",
       "      <td>2.318253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>955</th>\n",
       "      <td>0.323426</td>\n",
       "      <td>False</td>\n",
       "      <td>2.428877</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>2.325961</td>\n",
       "      <td>0.097717</td>\n",
       "      <td>2.318317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>960</th>\n",
       "      <td>0.324576</td>\n",
       "      <td>False</td>\n",
       "      <td>2.425490</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.307571</td>\n",
       "      <td>0.098733</td>\n",
       "      <td>2.317703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>965</th>\n",
       "      <td>0.325069</td>\n",
       "      <td>False</td>\n",
       "      <td>2.424040</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.315706</td>\n",
       "      <td>0.099650</td>\n",
       "      <td>2.317360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>0.325067</td>\n",
       "      <td>False</td>\n",
       "      <td>2.424047</td>\n",
       "      <td>0.0988</td>\n",
       "      <td>2.316583</td>\n",
       "      <td>0.099450</td>\n",
       "      <td>2.316597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>0.324580</td>\n",
       "      <td>False</td>\n",
       "      <td>2.425478</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.331406</td>\n",
       "      <td>0.101583</td>\n",
       "      <td>2.317923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>0.324323</td>\n",
       "      <td>False</td>\n",
       "      <td>2.426232</td>\n",
       "      <td>0.0988</td>\n",
       "      <td>2.310636</td>\n",
       "      <td>0.099433</td>\n",
       "      <td>2.319168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>0.324820</td>\n",
       "      <td>False</td>\n",
       "      <td>2.424771</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.336629</td>\n",
       "      <td>0.100300</td>\n",
       "      <td>2.317784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>0.325027</td>\n",
       "      <td>False</td>\n",
       "      <td>2.424164</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.322149</td>\n",
       "      <td>0.100850</td>\n",
       "      <td>2.317971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>0.324335</td>\n",
       "      <td>False</td>\n",
       "      <td>2.426197</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>2.317241</td>\n",
       "      <td>0.100267</td>\n",
       "      <td>2.318802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>0.324339</td>\n",
       "      <td>False</td>\n",
       "      <td>2.426187</td>\n",
       "      <td>0.0941</td>\n",
       "      <td>2.315547</td>\n",
       "      <td>0.100333</td>\n",
       "      <td>2.317142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>0.428518</td>\n",
       "      <td>True</td>\n",
       "      <td>2.153970</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.319396</td>\n",
       "      <td>0.098450</td>\n",
       "      <td>2.319460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1010</th>\n",
       "      <td>0.503119</td>\n",
       "      <td>True</td>\n",
       "      <td>1.993782</td>\n",
       "      <td>0.0965</td>\n",
       "      <td>2.338564</td>\n",
       "      <td>0.100083</td>\n",
       "      <td>2.319345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1015</th>\n",
       "      <td>0.166650</td>\n",
       "      <td>True</td>\n",
       "      <td>3.000076</td>\n",
       "      <td>0.0947</td>\n",
       "      <td>2.307906</td>\n",
       "      <td>0.100033</td>\n",
       "      <td>2.316284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1020</th>\n",
       "      <td>0.466702</td>\n",
       "      <td>True</td>\n",
       "      <td>2.068890</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>2.310847</td>\n",
       "      <td>0.101300</td>\n",
       "      <td>2.318163</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>204 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.355942      False  2.336606    0.1024   2.310955   0.097967   \n",
       "10       0.356321      False  2.335573    0.0947   2.308504   0.100067   \n",
       "15       0.350606      False  2.351266    0.0947   2.305254   0.099583   \n",
       "20       0.294397      False  2.517634    0.0965   2.304393   0.098450   \n",
       "25       0.294644      False  2.516849    0.0988   2.311399   0.098683   \n",
       "30       0.296858      False  2.509858    0.1021   2.318370   0.100267   \n",
       "35       0.302130      False  2.493361    0.1039   2.308077   0.100583   \n",
       "40       0.306480      False  2.479913    0.0965   2.309423   0.099233   \n",
       "45       0.322708      False  2.430996    0.1030   2.324148   0.100783   \n",
       "50       0.320082      False  2.438781    0.1021   2.322442   0.100783   \n",
       "55       0.320181      False  2.438486    0.1030   2.334742   0.101117   \n",
       "60       0.320644      False  2.437110    0.1021   2.315603   0.099700   \n",
       "65       0.323089      False  2.429870    0.1021   2.324509   0.100483   \n",
       "70       0.322433      False  2.431809    0.0988   2.325819   0.100117   \n",
       "75       0.347559      False  2.359716    0.0941   2.341359   0.100800   \n",
       "80       0.323519      False  2.428601    0.1003   2.313021   0.102667   \n",
       "85       0.324085      False  2.426933    0.1024   2.317903   0.101350   \n",
       "90       0.325065      False  2.424051    0.1030   2.319771   0.102200   \n",
       "95       0.323900      False  2.427478    0.1024   2.309376   0.098417   \n",
       "100      0.328097      False  2.415177    0.1030   2.313287   0.101100   \n",
       "105      0.328349      False  2.414442    0.1024   2.315201   0.099317   \n",
       "110      0.329196      False  2.411974    0.1042   2.313695   0.100150   \n",
       "115      0.328625      False  2.413637    0.0965   2.309560   0.101417   \n",
       "120      0.329909      False  2.409901    0.1024   2.321404   0.101833   \n",
       "125      0.329895      False  2.409943    0.1042   2.325037   0.100683   \n",
       "130      0.330357      False  2.408602    0.0947   2.317416   0.100017   \n",
       "135      0.329867      False  2.410025    0.1030   2.305767   0.098683   \n",
       "140      0.328964      False  2.412650    0.1024   2.333505   0.101300   \n",
       "145      0.328868      False  2.412930    0.1042   2.315379   0.101617   \n",
       "150      0.328860      False  2.412954    0.1021   2.315767   0.100700   \n",
       "...           ...        ...       ...       ...        ...        ...   \n",
       "875      0.325625      False  2.422407    0.1021   2.324281   0.100233   \n",
       "880      0.325636      False  2.422376    0.1024   2.323624   0.099700   \n",
       "885      0.324753      False  2.424969    0.1021   2.310489   0.098817   \n",
       "890      0.326131      False  2.420925    0.0947   2.313672   0.099533   \n",
       "895      0.324741      False  2.425003    0.1024   2.313402   0.099767   \n",
       "900      0.325637      False  2.422372    0.1024   2.327268   0.100250   \n",
       "905      0.325164      False  2.423761    0.1003   2.320317   0.099017   \n",
       "910      0.325636      False  2.422374    0.1021   2.319006   0.100583   \n",
       "915      0.326115      False  2.420971    0.1003   2.333408   0.100217   \n",
       "920      0.325636      False  2.422375    0.1042   2.316808   0.099867   \n",
       "925      0.325701      False  2.422184    0.1039   2.312121   0.099600   \n",
       "930      0.324959      False  2.424364    0.0965   2.314447   0.102767   \n",
       "935      0.325439      False  2.422954    0.0965   2.310216   0.100300   \n",
       "940      0.325439      False  2.422953    0.1039   2.316181   0.099117   \n",
       "945      0.324962      False  2.424355    0.0965   2.313311   0.102817   \n",
       "950      0.325440      False  2.422950    0.0965   2.316452   0.099217   \n",
       "955      0.323426      False  2.428877    0.1021   2.325961   0.097717   \n",
       "960      0.324576      False  2.425490    0.0947   2.307571   0.098733   \n",
       "965      0.325069      False  2.424040    0.1024   2.315706   0.099650   \n",
       "970      0.325067      False  2.424047    0.0988   2.316583   0.099450   \n",
       "975      0.324580      False  2.425478    0.1024   2.331406   0.101583   \n",
       "980      0.324323      False  2.426232    0.0988   2.310636   0.099433   \n",
       "985      0.324820      False  2.424771    0.0947   2.336629   0.100300   \n",
       "990      0.325027      False  2.424164    0.0947   2.322149   0.100850   \n",
       "995      0.324335      False  2.426197    0.1024   2.317241   0.100267   \n",
       "1000     0.324339      False  2.426187    0.0941   2.315547   0.100333   \n",
       "1005     0.428518       True  2.153970    0.0947   2.319396   0.098450   \n",
       "1010     0.503119       True  1.993782    0.0965   2.338564   0.100083   \n",
       "1015     0.166650       True  3.000076    0.0947   2.307906   0.100033   \n",
       "1020     0.466702       True  2.068890    0.1030   2.310847   0.101300   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        2.307100  \n",
       "10       2.305387  \n",
       "15       2.304654  \n",
       "20       2.304219  \n",
       "25       2.316921  \n",
       "30       2.318280  \n",
       "35       2.317127  \n",
       "40       2.318400  \n",
       "45       2.317787  \n",
       "50       2.317174  \n",
       "55       2.315692  \n",
       "60       2.317409  \n",
       "65       2.317212  \n",
       "70       2.317218  \n",
       "75       2.317006  \n",
       "80       2.316950  \n",
       "85       2.316999  \n",
       "90       2.318608  \n",
       "95       2.316847  \n",
       "100      2.317602  \n",
       "105      2.318657  \n",
       "110      2.317820  \n",
       "115      2.317001  \n",
       "120      2.318134  \n",
       "125      2.316771  \n",
       "130      2.317817  \n",
       "135      2.317835  \n",
       "140      2.316775  \n",
       "145      2.316213  \n",
       "150      2.317925  \n",
       "...           ...  \n",
       "875      2.316854  \n",
       "880      2.317254  \n",
       "885      2.317833  \n",
       "890      2.315808  \n",
       "895      2.317491  \n",
       "900      2.317143  \n",
       "905      2.317965  \n",
       "910      2.317111  \n",
       "915      2.316686  \n",
       "920      2.316765  \n",
       "925      2.317557  \n",
       "930      2.316571  \n",
       "935      2.317065  \n",
       "940      2.316900  \n",
       "945      2.315467  \n",
       "950      2.318253  \n",
       "955      2.318317  \n",
       "960      2.317703  \n",
       "965      2.317360  \n",
       "970      2.316597  \n",
       "975      2.317923  \n",
       "980      2.319168  \n",
       "985      2.317784  \n",
       "990      2.317971  \n",
       "995      2.318802  \n",
       "1000     2.317142  \n",
       "1005     2.319460  \n",
       "1010     2.319345  \n",
       "1015     2.316284  \n",
       "1020     2.318163  \n",
       "\n",
       "[204 rows x 7 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      " 62%|██████▏   | 8/13 [3:52:07<5:26:43, 3920.76s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#### RANDOM-OVERFITTING\n"
     ]
    },
    {
     "data": {
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       "<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>ave_in_out</th>\n",
       "      <th>is_pruned</th>\n",
       "      <th>ncut</th>\n",
       "      <th>test_acc</th>\n",
       "      <th>test_loss</th>\n",
       "      <th>train_acc</th>\n",
       "      <th>train_loss</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>epoch</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.360476</td>\n",
       "      <td>False</td>\n",
       "      <td>2.324294</td>\n",
       "      <td>0.0984</td>\n",
       "      <td>6.829137</td>\n",
       "      <td>0.995333</td>\n",
       "      <td>0.055619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.356205</td>\n",
       "      <td>False</td>\n",
       "      <td>2.335888</td>\n",
       "      <td>0.0983</td>\n",
       "      <td>6.820205</td>\n",
       "      <td>0.986333</td>\n",
       "      <td>0.088294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.360313</td>\n",
       "      <td>False</td>\n",
       "      <td>2.324735</td>\n",
       "      <td>0.0967</td>\n",
       "      <td>7.050941</td>\n",
       "      <td>0.970333</td>\n",
       "      <td>0.120270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.359272</td>\n",
       "      <td>False</td>\n",
       "      <td>2.327551</td>\n",
       "      <td>0.0979</td>\n",
       "      <td>7.090057</td>\n",
       "      <td>0.987667</td>\n",
       "      <td>0.083086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.356949</td>\n",
       "      <td>False</td>\n",
       "      <td>2.333860</td>\n",
       "      <td>0.0988</td>\n",
       "      <td>6.880790</td>\n",
       "      <td>0.986667</td>\n",
       "      <td>0.080836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.359086</td>\n",
       "      <td>False</td>\n",
       "      <td>2.328056</td>\n",
       "      <td>0.1007</td>\n",
       "      <td>6.283785</td>\n",
       "      <td>0.987000</td>\n",
       "      <td>0.107416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.358792</td>\n",
       "      <td>False</td>\n",
       "      <td>2.328853</td>\n",
       "      <td>0.0982</td>\n",
       "      <td>6.491294</td>\n",
       "      <td>0.987667</td>\n",
       "      <td>0.093603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.358723</td>\n",
       "      <td>False</td>\n",
       "      <td>2.329039</td>\n",
       "      <td>0.0985</td>\n",
       "      <td>6.229526</td>\n",
       "      <td>0.989667</td>\n",
       "      <td>0.105271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.359726</td>\n",
       "      <td>False</td>\n",
       "      <td>2.326322</td>\n",
       "      <td>0.0974</td>\n",
       "      <td>5.861799</td>\n",
       "      <td>0.858667</td>\n",
       "      <td>0.583323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.360020</td>\n",
       "      <td>False</td>\n",
       "      <td>2.325526</td>\n",
       "      <td>0.1008</td>\n",
       "      <td>6.165287</td>\n",
       "      <td>0.990333</td>\n",
       "      <td>0.108353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.362461</td>\n",
       "      <td>False</td>\n",
       "      <td>2.318945</td>\n",
       "      <td>0.1014</td>\n",
       "      <td>6.286006</td>\n",
       "      <td>0.996333</td>\n",
       "      <td>0.090301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.356387</td>\n",
       "      <td>False</td>\n",
       "      <td>2.335394</td>\n",
       "      <td>0.1054</td>\n",
       "      <td>5.762041</td>\n",
       "      <td>0.996333</td>\n",
       "      <td>0.122274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>0.362958</td>\n",
       "      <td>False</td>\n",
       "      <td>2.317609</td>\n",
       "      <td>0.1023</td>\n",
       "      <td>5.991163</td>\n",
       "      <td>0.999000</td>\n",
       "      <td>0.092692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.362448</td>\n",
       "      <td>False</td>\n",
       "      <td>2.318981</td>\n",
       "      <td>0.1003</td>\n",
       "      <td>6.286534</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.069168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0.364818</td>\n",
       "      <td>False</td>\n",
       "      <td>2.312625</td>\n",
       "      <td>0.1006</td>\n",
       "      <td>6.568859</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.053703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.361899</td>\n",
       "      <td>False</td>\n",
       "      <td>2.320458</td>\n",
       "      <td>0.1015</td>\n",
       "      <td>6.868506</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.040589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0.358323</td>\n",
       "      <td>False</td>\n",
       "      <td>2.330124</td>\n",
       "      <td>0.1014</td>\n",
       "      <td>7.178130</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.030125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.356738</td>\n",
       "      <td>False</td>\n",
       "      <td>2.334437</td>\n",
       "      <td>0.1018</td>\n",
       "      <td>7.459829</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.022111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.359800</td>\n",
       "      <td>False</td>\n",
       "      <td>2.326123</td>\n",
       "      <td>0.1008</td>\n",
       "      <td>7.720803</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.016505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>0.362069</td>\n",
       "      <td>False</td>\n",
       "      <td>2.319999</td>\n",
       "      <td>0.1009</td>\n",
       "      <td>7.961647</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>0.384238</td>\n",
       "      <td>True</td>\n",
       "      <td>2.261835</td>\n",
       "      <td>0.0998</td>\n",
       "      <td>2.465458</td>\n",
       "      <td>0.203333</td>\n",
       "      <td>2.204097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>0.399884</td>\n",
       "      <td>True</td>\n",
       "      <td>2.222509</td>\n",
       "      <td>0.1003</td>\n",
       "      <td>3.207212</td>\n",
       "      <td>0.427333</td>\n",
       "      <td>1.680979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>0.407291</td>\n",
       "      <td>True</td>\n",
       "      <td>2.204364</td>\n",
       "      <td>0.1015</td>\n",
       "      <td>3.311140</td>\n",
       "      <td>0.477667</td>\n",
       "      <td>1.522121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>0.412234</td>\n",
       "      <td>True</td>\n",
       "      <td>2.192420</td>\n",
       "      <td>0.0941</td>\n",
       "      <td>4.344411</td>\n",
       "      <td>0.614333</td>\n",
       "      <td>1.115975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>0.423932</td>\n",
       "      <td>True</td>\n",
       "      <td>2.164661</td>\n",
       "      <td>0.0971</td>\n",
       "      <td>4.679480</td>\n",
       "      <td>0.621333</td>\n",
       "      <td>1.110651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>0.438540</td>\n",
       "      <td>True</td>\n",
       "      <td>2.130969</td>\n",
       "      <td>0.1083</td>\n",
       "      <td>4.562681</td>\n",
       "      <td>0.629667</td>\n",
       "      <td>1.042877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>0.442707</td>\n",
       "      <td>True</td>\n",
       "      <td>2.121549</td>\n",
       "      <td>0.1038</td>\n",
       "      <td>4.580468</td>\n",
       "      <td>0.693667</td>\n",
       "      <td>0.883180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>0.455677</td>\n",
       "      <td>True</td>\n",
       "      <td>2.092757</td>\n",
       "      <td>0.1039</td>\n",
       "      <td>4.626603</td>\n",
       "      <td>0.715000</td>\n",
       "      <td>0.842821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>0.471120</td>\n",
       "      <td>True</td>\n",
       "      <td>2.059478</td>\n",
       "      <td>0.0984</td>\n",
       "      <td>5.045933</td>\n",
       "      <td>0.755667</td>\n",
       "      <td>0.687666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>0.477242</td>\n",
       "      <td>True</td>\n",
       "      <td>2.046576</td>\n",
       "      <td>0.0971</td>\n",
       "      <td>5.728310</td>\n",
       "      <td>0.799000</td>\n",
       "      <td>0.575846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>0.494346</td>\n",
       "      <td>True</td>\n",
       "      <td>2.011372</td>\n",
       "      <td>0.1023</td>\n",
       "      <td>6.119018</td>\n",
       "      <td>0.811333</td>\n",
       "      <td>0.522807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>0.483836</td>\n",
       "      <td>True</td>\n",
       "      <td>2.032859</td>\n",
       "      <td>0.1006</td>\n",
       "      <td>5.429702</td>\n",
       "      <td>0.807000</td>\n",
       "      <td>0.526325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>0.503347</td>\n",
       "      <td>True</td>\n",
       "      <td>1.993329</td>\n",
       "      <td>0.1043</td>\n",
       "      <td>6.261506</td>\n",
       "      <td>0.905333</td>\n",
       "      <td>0.286336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>0.517359</td>\n",
       "      <td>True</td>\n",
       "      <td>1.965874</td>\n",
       "      <td>0.0995</td>\n",
       "      <td>6.480720</td>\n",
       "      <td>0.935000</td>\n",
       "      <td>0.214145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>0.526463</td>\n",
       "      <td>True</td>\n",
       "      <td>1.948438</td>\n",
       "      <td>0.0963</td>\n",
       "      <td>7.030436</td>\n",
       "      <td>0.939333</td>\n",
       "      <td>0.192770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0.544938</td>\n",
       "      <td>True</td>\n",
       "      <td>1.913988</td>\n",
       "      <td>0.0988</td>\n",
       "      <td>6.534091</td>\n",
       "      <td>0.940667</td>\n",
       "      <td>0.180051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>0.543444</td>\n",
       "      <td>True</td>\n",
       "      <td>1.916729</td>\n",
       "      <td>0.1021</td>\n",
       "      <td>7.358488</td>\n",
       "      <td>0.999333</td>\n",
       "      <td>0.023148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0.543113</td>\n",
       "      <td>True</td>\n",
       "      <td>1.917338</td>\n",
       "      <td>0.1014</td>\n",
       "      <td>7.746240</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.013059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>0.543729</td>\n",
       "      <td>True</td>\n",
       "      <td>1.916207</td>\n",
       "      <td>0.1024</td>\n",
       "      <td>7.822792</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.009487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>0.546003</td>\n",
       "      <td>True</td>\n",
       "      <td>1.912040</td>\n",
       "      <td>0.1025</td>\n",
       "      <td>7.861462</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.002760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.360476      False  2.324294    0.0984   6.829137   0.995333   \n",
       "10       0.356205      False  2.335888    0.0983   6.820205   0.986333   \n",
       "15       0.360313      False  2.324735    0.0967   7.050941   0.970333   \n",
       "20       0.359272      False  2.327551    0.0979   7.090057   0.987667   \n",
       "25       0.356949      False  2.333860    0.0988   6.880790   0.986667   \n",
       "30       0.359086      False  2.328056    0.1007   6.283785   0.987000   \n",
       "35       0.358792      False  2.328853    0.0982   6.491294   0.987667   \n",
       "40       0.358723      False  2.329039    0.0985   6.229526   0.989667   \n",
       "45       0.359726      False  2.326322    0.0974   5.861799   0.858667   \n",
       "50       0.360020      False  2.325526    0.1008   6.165287   0.990333   \n",
       "55       0.362461      False  2.318945    0.1014   6.286006   0.996333   \n",
       "60       0.356387      False  2.335394    0.1054   5.762041   0.996333   \n",
       "65       0.362958      False  2.317609    0.1023   5.991163   0.999000   \n",
       "70       0.362448      False  2.318981    0.1003   6.286534   1.000000   \n",
       "75       0.364818      False  2.312625    0.1006   6.568859   1.000000   \n",
       "80       0.361899      False  2.320458    0.1015   6.868506   1.000000   \n",
       "85       0.358323      False  2.330124    0.1014   7.178130   1.000000   \n",
       "90       0.356738      False  2.334437    0.1018   7.459829   1.000000   \n",
       "95       0.359800      False  2.326123    0.1008   7.720803   1.000000   \n",
       "100      0.362069      False  2.319999    0.1009   7.961647   1.000000   \n",
       "105      0.384238       True  2.261835    0.0998   2.465458   0.203333   \n",
       "110      0.399884       True  2.222509    0.1003   3.207212   0.427333   \n",
       "115      0.407291       True  2.204364    0.1015   3.311140   0.477667   \n",
       "120      0.412234       True  2.192420    0.0941   4.344411   0.614333   \n",
       "125      0.423932       True  2.164661    0.0971   4.679480   0.621333   \n",
       "130      0.438540       True  2.130969    0.1083   4.562681   0.629667   \n",
       "135      0.442707       True  2.121549    0.1038   4.580468   0.693667   \n",
       "140      0.455677       True  2.092757    0.1039   4.626603   0.715000   \n",
       "145      0.471120       True  2.059478    0.0984   5.045933   0.755667   \n",
       "150      0.477242       True  2.046576    0.0971   5.728310   0.799000   \n",
       "155      0.494346       True  2.011372    0.1023   6.119018   0.811333   \n",
       "160      0.483836       True  2.032859    0.1006   5.429702   0.807000   \n",
       "165      0.503347       True  1.993329    0.1043   6.261506   0.905333   \n",
       "170      0.517359       True  1.965874    0.0995   6.480720   0.935000   \n",
       "175      0.526463       True  1.948438    0.0963   7.030436   0.939333   \n",
       "180      0.544938       True  1.913988    0.0988   6.534091   0.940667   \n",
       "185      0.543444       True  1.916729    0.1021   7.358488   0.999333   \n",
       "190      0.543113       True  1.917338    0.1014   7.746240   1.000000   \n",
       "195      0.543729       True  1.916207    0.1024   7.822792   1.000000   \n",
       "200      0.546003       True  1.912040    0.1025   7.861462   1.000000   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        0.055619  \n",
       "10       0.088294  \n",
       "15       0.120270  \n",
       "20       0.083086  \n",
       "25       0.080836  \n",
       "30       0.107416  \n",
       "35       0.093603  \n",
       "40       0.105271  \n",
       "45       0.583323  \n",
       "50       0.108353  \n",
       "55       0.090301  \n",
       "60       0.122274  \n",
       "65       0.092692  \n",
       "70       0.069168  \n",
       "75       0.053703  \n",
       "80       0.040589  \n",
       "85       0.030125  \n",
       "90       0.022111  \n",
       "95       0.016505  \n",
       "100      0.012760  \n",
       "105      2.204097  \n",
       "110      1.680979  \n",
       "115      1.522121  \n",
       "120      1.115975  \n",
       "125      1.110651  \n",
       "130      1.042877  \n",
       "135      0.883180  \n",
       "140      0.842821  \n",
       "145      0.687666  \n",
       "150      0.575846  \n",
       "155      0.522807  \n",
       "160      0.526325  \n",
       "165      0.286336  \n",
       "170      0.214145  \n",
       "175      0.192770  \n",
       "180      0.180051  \n",
       "185      0.023148  \n",
       "190      0.013059  \n",
       "195      0.009487  \n",
       "200      0.002760  "
      ]
     },
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    },
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     "output_type": "stream",
     "text": [
      "\r",
      " 69%|██████▉   | 9/13 [4:56:51<4:20:39, 3909.97s/it]"
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    },
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     "text": [
      "#### FASHION\n"
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       "      <th>ave_in_out</th>\n",
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       "      <td>0.970083</td>\n",
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       "      <th>20</th>\n",
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       "      <td>False</td>\n",
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       "      <td>0.8921</td>\n",
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       "      <td>0.052817</td>\n",
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       "      <th>25</th>\n",
       "      <td>0.440250</td>\n",
       "      <td>True</td>\n",
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       "      <th>35</th>\n",
       "      <td>0.500045</td>\n",
       "      <td>True</td>\n",
       "      <td>1.999911</td>\n",
       "      <td>0.8882</td>\n",
       "      <td>0.323757</td>\n",
       "      <td>0.930433</td>\n",
       "      <td>0.181828</td>\n",
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       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.522749</td>\n",
       "      <td>True</td>\n",
       "      <td>1.955514</td>\n",
       "      <td>0.8844</td>\n",
       "      <td>0.364730</td>\n",
       "      <td>0.943067</td>\n",
       "      <td>0.147317</td>\n",
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       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.312102      False  2.462744    0.8958   0.334922   0.965533   \n",
       "10       0.315924      False  2.451208    0.8896   0.351025   0.966217   \n",
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       "40       0.522749       True  1.955514    0.8844   0.364730   0.943067   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        0.095046  \n",
       "10       0.094195  \n",
       "15       0.087015  \n",
       "20       0.052817  \n",
       "25       0.292877  \n",
       "30       0.228573  \n",
       "35       0.181828  \n",
       "40       0.147317  "
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      "\r",
      " 77%|███████▋  | 10/13 [5:11:03<2:29:37, 2992.59s/it]"
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     "text": [
      "#### MNIST\n"
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       "      <td>True</td>\n",
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       "      <td>0.992367</td>\n",
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       "      <th>35</th>\n",
       "      <td>0.513626</td>\n",
       "      <td>True</td>\n",
       "      <td>1.973115</td>\n",
       "      <td>0.9781</td>\n",
       "      <td>0.090984</td>\n",
       "      <td>0.995850</td>\n",
       "      <td>0.011347</td>\n",
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       "    <tr>\n",
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       "      <td>0.500091</td>\n",
       "      <td>True</td>\n",
       "      <td>1.999817</td>\n",
       "      <td>0.9788</td>\n",
       "      <td>0.096470</td>\n",
       "      <td>0.997083</td>\n",
       "      <td>0.009462</td>\n",
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       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.298732      False  2.503970    0.9792   0.086104   0.999233   \n",
       "10       0.302624      False  2.491828    0.9794   0.073905   0.999133   \n",
       "15       0.313147      False  2.459579    0.9812   0.075895   0.999567   \n",
       "20       0.320388      False  2.437871    0.9826   0.079448   1.000000   \n",
       "25       0.398070       True  2.226999    0.9743   0.084641   0.983667   \n",
       "30       0.475014       True  2.051252    0.9725   0.108376   0.992367   \n",
       "35       0.513626       True  1.973115    0.9781   0.090984   0.995850   \n",
       "40       0.500091       True  1.999817    0.9788   0.096470   0.997083   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        0.003393  \n",
       "10       0.003947  \n",
       "15       0.002444  \n",
       "20       0.000203  \n",
       "25       0.050424  \n",
       "30       0.021521  \n",
       "35       0.011347  \n",
       "40       0.009462  "
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      "\r",
      " 85%|████████▍ | 11/13 [5:25:27<1:18:27, 2353.97s/it]"
     ]
    },
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     "text": [
      "#### MNIST+DROPOUT\n"
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       "      <td>0.9689</td>\n",
       "      <td>0.116021</td>\n",
       "      <td>0.953600</td>\n",
       "      <td>0.159097</td>\n",
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       "      <th>40</th>\n",
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       "      <td>0.9719</td>\n",
       "      <td>0.111121</td>\n",
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       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.359384      False  2.327248    0.9740   0.105312   0.959300   \n",
       "10       0.393271      False  2.238962    0.9732   0.111157   0.954300   \n",
       "15       0.404808      False  2.210413    0.9710   0.114635   0.948833   \n",
       "20       0.417564      False  2.179684    0.9719   0.114706   0.949817   \n",
       "25       0.494651       True  2.010755    0.9522   0.175967   0.926250   \n",
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       "35       0.649870       True  1.739328    0.9689   0.116021   0.953600   \n",
       "40       0.661881       True  1.721346    0.9719   0.111121   0.957600   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        0.140763  \n",
       "10       0.161029  \n",
       "15       0.179749  \n",
       "20       0.174829  \n",
       "25       0.252180  \n",
       "30       0.189139  \n",
       "35       0.159097  \n",
       "40       0.142936  "
      ]
     },
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      "\r",
      " 92%|█████████▏| 12/13 [5:40:19<31:55, 1915.33s/it]  "
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      "#### FASHION+DROPOUT\n"
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       "        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>ave_in_out</th>\n",
       "      <th>is_pruned</th>\n",
       "      <th>ncut</th>\n",
       "      <th>test_acc</th>\n",
       "      <th>test_loss</th>\n",
       "      <th>train_acc</th>\n",
       "      <th>train_loss</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>epoch</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.361910</td>\n",
       "      <td>False</td>\n",
       "      <td>2.320427</td>\n",
       "      <td>0.8727</td>\n",
       "      <td>0.372651</td>\n",
       "      <td>0.870250</td>\n",
       "      <td>0.372586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.382457</td>\n",
       "      <td>False</td>\n",
       "      <td>2.266398</td>\n",
       "      <td>0.8723</td>\n",
       "      <td>0.372789</td>\n",
       "      <td>0.865733</td>\n",
       "      <td>0.392952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.397036</td>\n",
       "      <td>False</td>\n",
       "      <td>2.229565</td>\n",
       "      <td>0.8715</td>\n",
       "      <td>0.378603</td>\n",
       "      <td>0.863700</td>\n",
       "      <td>0.403447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.411116</td>\n",
       "      <td>False</td>\n",
       "      <td>2.195110</td>\n",
       "      <td>0.8726</td>\n",
       "      <td>0.378019</td>\n",
       "      <td>0.865667</td>\n",
       "      <td>0.398399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.486524</td>\n",
       "      <td>True</td>\n",
       "      <td>2.027320</td>\n",
       "      <td>0.8483</td>\n",
       "      <td>0.428743</td>\n",
       "      <td>0.837167</td>\n",
       "      <td>0.466343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.571120</td>\n",
       "      <td>True</td>\n",
       "      <td>1.867204</td>\n",
       "      <td>0.8603</td>\n",
       "      <td>0.404465</td>\n",
       "      <td>0.851950</td>\n",
       "      <td>0.422231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.668011</td>\n",
       "      <td>True</td>\n",
       "      <td>1.712313</td>\n",
       "      <td>0.8604</td>\n",
       "      <td>0.412654</td>\n",
       "      <td>0.857517</td>\n",
       "      <td>0.405409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.696490</td>\n",
       "      <td>True</td>\n",
       "      <td>1.671556</td>\n",
       "      <td>0.8676</td>\n",
       "      <td>0.394206</td>\n",
       "      <td>0.865050</td>\n",
       "      <td>0.384994</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ave_in_out  is_pruned      ncut  test_acc  test_loss  train_acc  \\\n",
       "epoch                                                                    \n",
       "5        0.361910      False  2.320427    0.8727   0.372651   0.870250   \n",
       "10       0.382457      False  2.266398    0.8723   0.372789   0.865733   \n",
       "15       0.397036      False  2.229565    0.8715   0.378603   0.863700   \n",
       "20       0.411116      False  2.195110    0.8726   0.378019   0.865667   \n",
       "25       0.486524       True  2.027320    0.8483   0.428743   0.837167   \n",
       "30       0.571120       True  1.867204    0.8603   0.404465   0.851950   \n",
       "35       0.668011       True  1.712313    0.8604   0.412654   0.857517   \n",
       "40       0.696490       True  1.671556    0.8676   0.394206   0.865050   \n",
       "\n",
       "       train_loss  \n",
       "epoch              \n",
       "5        0.372586  \n",
       "10       0.392952  \n",
       "15       0.403447  \n",
       "20       0.398399  \n",
       "25       0.466343  \n",
       "30       0.422231  \n",
       "35       0.405409  \n",
       "40       0.384994  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100%|██████████| 13/13 [5:55:54<00:00, 1621.18s/it]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "100%|██████████| 13/13 [5:55:54<00:00, 1642.65s/it]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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wsbXIHz0aE2Obxo60amSv9oUFvv32W1OHoJTAzu7G/s+7du1ix44d7N+/H1tbW4KCgoqsQXhrPcOsrKwK929ubs7BgwcJDg5m3bp1LFiwgD///JNFixZx4MABtm7dygN+fqyZPh3DgYNkhoWBXo+lgwOHLS15+NNPsQvwZ/m6dZwODcWyWbNy9W9hcWMzEY1Gg05X/PqE7OzsMk0B3wkhxEDgS0AD/FdK+ektxycCXwDX/wAtkFL+t6Q21V8h5Y5ZmpvRtrEjbRvfvJw6JTM3PzFe4/SVNE5eSuPn0Ggyc/UACAEtXG1p4+6YP7XqQGt3R5q72qIxqz+jx9atW5d+klItSqshmJqaiouLC7a2tpw6dYq///670vpu3bo158+f58yZM/j4+LB8+XL69OlDeno6mZmZDB48GH9/f7y9vZE6HWe2bMHzdAQTDv7Do1bWpH+1ACtfH9yeeAL7vn0x+LRkcKdOPD7wP6X27e/vz88//0zfvn05ceIER4+Wfm22qJ9VREQEI0aMqPDPoDRCCA2wELgPiAH+EUJsllKeuOXUNVLKF8rarkqESpVxtrWkt7cbvb1vTBsZDJLo5MyCkeOpy9c4fTmN7ScuF+zkY2OhoVUj+4IE2aaxcSTpamdpoldStX755RcAHnjgARNHori5ueHv70+HDh0YNGgQ999//03HBw4cyKJFi2jbti2tW7emd+/elda3tbU133//PSNGjChYLDN58mSSkpIYNmwYIiuLrgYDm/oEEXG3P4Zr17gKHBOQ3qYN47+aj9Uto72WLVsWJNaSPPfcc0yYMIF27drRpk0b2rdvj5PT7VtWFjZ69Giefvpp5s+fz7p162jevDlnzpzBr4gVppWoJ3BGSnkWQAjxEzAMuDURlovJ6hHa2dnJjIwMk/St1DxZuXoir15PjmkF06xJhSqLNHSwKliUc32Bjk9D+1pfwFnVI7xB1SO8Wd6lS6T9+SfpwX+ScfCg8cZ2V1fs+/TBPigIO39/NPbFl+7bsGEDYWFhBStHi6PX68nLy8Pa2pqoqCjuvfdeTp8+jaVl2d98btiwgUOHDjFz5swyP6eof28hRC5QeEi6WEq5OP/YI8BAKeVT+d+PA3oVHv3lT41+AsQDEcDLUsrokuJQI0KlRrCx1NDJw5lOHjduRpZSEp+eU7Ao52T+6HHZ3vPk6g0AaMwE3lq7gkU51xNkU2cbtThHqXWklORERJAWHEx68J9kHz8OgKWnJ64TxuPQvz82nTsjNGV78zd8+HASExNLPS8zM5O+ffuSl5eHlJKvv/66XEkQjPcmTps2rVzPKa4pKeWdDCt/AVZLKXOEEM8APwAl3tyoRoRKraPTGzifmMHJS2nGJJk/eoxJvrEgwcHKvGBatbW7I23dHWjl7lAj731UI8Ib6vKI8Pnnn2fv3r03PTZlyhQmjhtHZtgh0v8MJi34T/JijKXjbDp3xr5/fxzu7Y+Vt7cpQq5yxYwIi61QL4S4C/hASvmf/O/fBJBSflLM+RogSUpZ4jyvGhEqtY65xgyfhg74NHTggc43Hk/LziMif1HO9WuPmw7HkZZzseCcps42+Ytybqxg9dLaqV11lCq3cOHCgq8NmZmkh4SQHvwnkf4B6FNTEZaW2N7VG7dJT+PQty/mDRqYMNoa6x/AVwjhhXFV6GhgTOEThBCNpZSX8r8dCpwsrVGVCJU6w8Hagu4tXOne4sZNklJK4lKzOXUp/9aOy2mcvnyNnafj0V+/99HcDJ8G9vmLchxo38SJ3t5u9WrlqlL1dAkJpO3cabzet28fMjcXMycnHIL6YN+vP/YB/pjZFX+9TwEppU4I8QKwHePtE0ullMeFEB8CoVLKzcBLQoihgA5IAiaW1q6aGlXqpRydnqirGQUjx5P5t3lcTcsBYO6ozgzv6lEtsURHG6/jNyvn/V11UV2bGs05e4604B2kB/9J1pEjICUWTZti378fDv36Y9u9G8Ki5k3XV5fyTo1WFTUiVOolK3NNkQWbkzJyGTD3L3adjq+2RKgSYN0hDQZj4dpg4/W+3HPnALBu1w7tC8/j0L8/Vq1bq4VcNYxKhIpSiKudJf4+WvaeScBgkJhVw/TomjVrABg1alSV96VUPkNODhn79xuT385d6BMSwNwcu549cBk7Fod+fbFo0sTUYSolUCsEFOUWAT5aEtKNu+JUh2+++YZvvvmmWvpSSna9DFNpdMnJpGzcSMyLLxFx193ETH6Wa9t+JcbJEe3Hs2i1by/Nly7F9bGxtyVBT09PEhISqiT+jRs38uGHHxZ5bPPmzXz6acn7t+7atatgX9FbzZs3j8zMzILv7733XpKTkysebA2iEqGi3CLQ17haL+RMvIkjUapbSYkwNyaGpB9+4ML4CUQGBHLpjTfJOnIEp6EP0GzJEnz37+OJ48cR99xjsurtn3/+ebG1FIcOHcobb7xR4bZvTYTjxo0r05uG2kBNjSrKLdydrPFpaM+eyAQm3dPS1OHUW58d/IxTSacqtc02rm14vefrxR6/qR7hvffy4cTH+f2jj7D+91+aG4ybOFj5+uA4cQIzf/uNv+Pj0a1bx7tt23Jl0SLi4uLo27cvWq2WnTt3lhrPnDlzWLp0KQBPPfUUU6dOJSMjg5EjRxITE4Ner+fdd99l1KhRRdYkLCwiIgIrKyu0Wi0AEydOxNramsOHD+Pv70+nTp0IDQ1lwYIFREVFMXbsWDIyMhg2bBjz5s0jPT0dgPT0dB555BGOHTtG9+7dWbFiBV999dVtr23o0KEEBgby9ttvV+jfoiZRiVBRihDgo2X1wYtk5+mxtqjdW7gpZffJzJmY/XuUOQ89TNrOnZzfshUfwM7PD/t+fZm2Zg1Pvvoq8fHx6L29CQ8OBoybcTs5OTFnzhx27txZkIxKEhYWxvfff8+BAweQUtKrVy/69OnD2bNnadKkCVu3bi1oOzExsciahIXt3buXbt263fRYTEwM+/btQ6PRsGzZsoLHp0yZwpQpU3j00UdZtGjRTc85fPgwx48fp0mTJvj7+7N3715eeuml216bi4sLOTk5JCYm3laGqrZRiVBRihDoq2XZvvOEXUjG36f0P2pK5Stp5FaZ9OnpZOzeTVrwn2Tv2sW7BgMp//sfdgH+bGvYgIUHDmB27CgcO0p6ejr3REYSGBjItGnTeP311xkyZAiBgYHl7jckJIThw4cXlHl66KGH2LNnDwMHDrytbZ1OV2RNwsIuXbpEg1tuwh8xYgSaIrZj279/Pxs3bgRgzJgxTJ8+veBYz5498fAwrpju0qUL58+fJyAgoMjXcL3+oEqEilIH9fJ2w9xMsCcyocoT4bp166q0feV2eVeukP7nn6TtCDZuZp2Xh8bVFY2/Px/v2MHS/fsws7EhYto0nu/Xj2eeeea2Ng4dOsS2bdt455136N+/P++9916lxNaqVasi2y6qJmFhNjY2pKam3vSYXQVu0L+1lqKp6w9WB7VYRlGKYG9lTrfmLtWyYEar1ZZpKk2pOCkl2RERJCxaxLlHRnCmTxCXZ3xIXkwMruPG0WLVSnz37Mbt/ffYmZGOWf4f9//85z8sXbq04PpZbGwsV69eJS4uDltbWx577DFeffVVDh06BJRez7CwwMBANm7cSGZmJhkZGWzYsIHAwMAi205PTyc1NZXBgwczd+5cjhw5clt7bdu25cyZM2Xqu3fv3qxfvx6An376qUzPufW1SSm5fPkynp6eZXp+TaZGhIpSjABfLXN3RJCUkVultRCvX7uZOHFilfVRH0mdjqzDh0nbEUzan3+Sl7+Dj3XnTjR45RUc+vfD0tv7ppvbb61H+MUXX3Dy5EnuuusuAOzt7VmxYgVnzpzh1VdfxczMDAsLi4LbXyZNmsTAgQNp0qRJqYtlunXrxsSJE+nZsydgXCzTtWtXtm/fflvbaWlpDBs2jOzsbKSUzJkz57b27rnnHqZNm4aUstQb9ufNm8djjz3GrFmzGDhwYKm1B4t6bWFhYfTu3Rtz89qfRtQWa4pSjEMXk3no63189WhXHuhcdTdEq+oTN9zpFmuGnBwy9uwhbUcw6bt2oU9JQVhYYHv3XTj064993yAsGjasxIhrlilTpvDAAw9w7733lnheZmYmNjbGUmU//fQTq1evZtOmTeXua+jQofTv37/C8aot1hSlhuvU1AkHa3NCIhOqNBEqd06fnkHKmjUkLvsefXwCZk5O2Pe5B4d+/bELCCixeG1d8tZbb3HgwIFSzwsLC+OFF15ASomzs3PBLRzl0aFDhztKgjWJSoSKUgxzjRl3t3Qj5ExCmaablOqnT0khacVKkpYvx5Cait3dd+H68SfY9e5l8s2se/XqRU5Ozk2PLV++nI4dO1ZZn40aNWLo0KGlnhcYGFjkdcbyePrpp+/o+TWJSoSKUoIA3wZsP36FcwkZeDewN3U4Sj5dfDyJy5aRsvonDJmZ2Pfvj/aZSdh06mTq0AqUZWSm1AwqESpKCQLzb50IOZOgEmENkBcbS+J335Gybj1Sp8Nx0CDcJk3CunUrU4em1GIqESpKCVq42eLhYsOeyATG3+VZJX1s27atStqtS3LOniNxyRJSf/kFhMD5wWG4PfUUli1amDo0pQ5QiVBRSiCEINBXy5Yjl9DpDZhrKv/WW1tb20pvs67IPnmShG8Xk7Z9O8LKCpcxj+L2+ONYNG5s6tCUOqTU32ohRDMhxE4hxAkhxHEhxJQSzu0hhNAJIR6p3DAVxXQCfBqQlqPjSMzt+ztWhq+//rrO7OJfWTIPHSb6mcmcG/4QGSEhuD39ND7BO3B/6y2VBJVKV5a3tzpgmpSyHdAbeF4I0e7Wk4QQGuAz4PfKDVFRTOvulm4IAXsiq6aG3M8//8zPP/9cJW3XJlJKOHKEC+MncGHMGLKOHKHB1Cn4/BlMw1dexryW72cJMHjw4CI3zK5s4eHhJU65Hz58mCeffLLIY6Ghobz00ksltn/+/Hk6dOhQ5LFly5YRFxdX8P3o0aOJjIwsQ9SmU2oilFJeklIeyv86DTgJNC3i1BeB9cDVSo1QUUzMxc6Sjk2dCKmiRFjfSYOBtOBgzo8aDR/MIPf8eRq+8To+fwajnTzZZLX9qsK2bdtwdnau8n5KS4Qff/xxkclOp9Ph5+fH/PnzK9z3rYnw2Wef5fPPP69we9WhXNcIhRCeQFfgwC2PNwWGA32BHiU8fxIwCcDSsuq2rFKUyhbgo+Xb3WdJy87Dwdq096fVFVKn49qvv5G4eDE5kZFYNGsGz06m5bPPYmZpyeWPPybnZOXWI7Rq2wb3t94q8ZwHH3yQ6OhosrOzmTJlCpMmTWLRokVERUXxxRdfAMY/9tdr+61YsYL58+eTm5tLr169+Prrr4us+ADG6vShoaGkp6czaNAgAgIC2LdvH02bNmXTpk3FbmAdHh7O5MmTyczMpGXLlixduhQXFxeCgoKYPXs2fn5+JCQk4OfnR0REBO+99x5ZWVmEhITw5ptvMmrUqIK20tLS+Pfff+ncuTMAH3zwAVFRUZw9e5bmzZvzzDPPMHv2bLZs2UJ8fDxjxowhLi6Ou+66iz/++IOwsDAA9Ho9Tz/99E3xb926ldDQUMaOHYuNjQ379+8nMDCQiRMnotPpaux2bGW+8i+EsMc44psqpbx2y+F5wOtSSkNJbUgpF0sp/aSUfjX1B6IoRQn0bYDeIPn7bJKpQ6n1DLm5JK9dS9Tg+4l79VWkNNDki89p+es2GDAAMxO/SV66dClhYWGEhoYyf/58EhMTefjhh9mwYUPBOWvWrGH06NGcPHmSNWvWsHfvXsLDw9FoNKxcubJM/URGRvL8889z/PhxnJ2dCzbBLsr48eP57LPP+Pfff+nYsSMzZswo9lxLS0s+/PBDRo0aRXh4+E1JEIxTn7dOa544cYIdO3awevXqmx6fMWMG/fr14/jx4zzyyCNcvHixxPgfeeQR/Pz8WLlyJeHh4djY2GBmZoaPj88d38BflcqUjYQQFhiT4Eop5f+KOMUP+Cl/5w0tMFgIoZNSbqy0SBXFhLq1cMbGQkNIZDz3tWtk6nBqJUNWFilr15L43VJ0V65g3aEDjRZ8hX2/fgiz29+TlzZyqyrz588vSHrR0VvSlE4AACAASURBVNFERkbSu3dvvL29+fvvv/H19eXUqVP4+/uzcOFCwsLC6NHDOBGWlZVFwzLuZerl5UWXLl0A6N69O+fPny/yvNTUVFJSUujTpw8AEyZMYMSIERV+fUXVLRw6dGiRo9GQkJCCn8XAgQNxcXEpd/xwo25h9+7dKxx3VSo1EQpjdvsOOCmlvH3Lc0BK6VXo/GXAFpUElbrEylxDL29X9pyp/OuEdX2zbX1aGskrV5H0ww/ok5Ox9fOj8axZ2PnfXeO2rdu1axc7duxg//792NraEhQURHZ2NmBc9PHzzz/Tpk0bhg8fjhACKSUTJkzgk08+KXdft9b9y8rKKncb5ubmGAzGibjrcZbGxsbmtnMro25hSfHX9LqFZZka9QfGAf2EEOH5H4OFEJOFEJOrOD5FqTECfLScjc8gLqX8f7DqI11yMlfnzeNMv/7Ez5uHdccOtFi5ghYrlmMf4F/jkiAYR18uLi7Y2tpy6tQp/v7774Jjw4cPZ9OmTaxevZrRo0cD0L9/f9atW8fVq8Y1gklJSVy4cKFSY3JycsLFxYU9e/YAxv1Kr48OPT09C67ZFS7wXFJdxPLULfT39y9Y0fz777+TnJxc6nOK6jsiIqLYVaY1QVlWjYZIKYWUspOUskv+xzYp5SIp5aIizp8opVQlt5U6J9DXOJ1U2atHZ8+ezezZsyu1TVPKu3KFK598wpl+/Un8djF2d9+N5/p1NF+8GNsaOjV23cCBA9HpdLRt25Y33niD3r17FxxzcXGhbdu2XLhwoaCGYLt27fjoo48YMGAAnTp14r777uPSpUuVHtcPP/zAq6++SqdOnQgPD+e9994DYPr06XzzzTd07dqVhIQb/y/79u3LiRMn6NKlC2vWrLmprTZt2pCamlqmAsLvv/8+v//+Ox06dGDt2rW4u7vj4OBQ4nMmTpzI5MmT6dKlC1lZWVy5cgUbGxvc3d0r8Mqrh6pHqChlJKWk18fB9PJ246tHu1Zau3WlHmHuxYskLvkvKRs3gsGA05AhuE16GquWLcvcxp3WI1TKZu7cuTg4OPDUU0+VeF5OTg4ajQZzc3P279/Ps88+S3h4eLn7cnR0LPK+RVWPUFFqGSEEAT5adkXEYzBIzMxq3tSeKeRERpKweAnXtm5FmJvj/MjDuD35FJYeRd1urNQEzz77LGvXri31vIsXLzJy5EgMBgOWlpYsWbKk3H05Ozszbty4ioRZbVQiVJRyCPDV8r/DsZy4dI0OTZ1MHY5JZR09RsK3i0jfEYywtcV14kRcJ06o0xXgy6qitQiff/559u7de9NjU6ZM4fHHH6/U+KytrcuUnHx9fTl8+PAd9VXZsVcFlQgVpRwCCpVlqo+JUEpJ5j//kPjtYjL27sXM0RHtc8/hMu4xzAstrb/TPmriQpryqGgtwoULF1ZyJDWXqS7LFUUlQkUph4aO1rRu5EBIZAKT+5T92ldJavKy8uuklGTs3k3Ct4vJOnQIjZsbDadPw3n0aDT2lVen0dramsTERNzc3Gp9MlSKJ6UkMTERa2trU4cCqESoKOUW4Ktl+d8XyM7TY21R9FZa5fHrr79WQlRVQ+r1pP2xg4TF35Jz4iTmTRrT6N13cH74Ycyq4I+Yh4cHMTExxMfHV3rbSs1ibW2Nh4eHqcMAVCJUlHIL8NXyXcg5/jmfVHBLRV0j8/JI3bKVxCVLyD17FktPTxrPmoXTA0MQVbgFmoWFBV5eXqWfqCiVSCVCRSmnXl6uWGrMCIlMqJREOHPmTADefffdO27rThlyckhZv56k/35HXlwcVm3a0HTuHBwGDEAUs5G0otR2KhEqSjnZWprTrYUzuyMTeLMS2gsODgZMmwj16RmkrFlD4rLv0ccnYNO5M43efQf7oCB1rU6p81QiVJQKCPRtwBfbTxOflkMDB6vSn1BD6VNSSFqxkqTlyzGkpmJ7V2+0X8zGtldPlQCVekMlQkWpgAAfLV9sP82+qASGdal9N47r4uNJXLaMlNU/YcjMxL5fP7TPTMImv0adotQnKhEqSgV0aOqEk40FeyJrVyLUp2cQP2cOKevWIXU6HAcNwm3SJKxbtzJ1aIpiMioRKkoFaMwE/j5uhEQm3PEN4G5ubpUYWcmuzJpF6qZNOD00HO1TT2Hp6VltfStKTaUSoaJUUIBPA7YdvUxUfDo+DUvekb8kJVUmr0zpIXtJ3bABt2eeoeHLU6ulT0WpDcpSj1BRlCIE+hq3W9tTyWWZqoIhI4PL77+PpZcX2ueeNXU4ilKjqESoKBXUzNWWFm62d1yf8M033+TNNyvjRozixc+fT15sLI1nfoiZVe1d5aooVUFNjSrKHQjw0bLxcCx5egMWmoq9r9y/f38lR3WzrPBwkn5cjsuYR7H186vSvhSlNlIjQkW5A4G+WjJy9Ry+mGLqUIokc3O59O67mDdqRINXXjF1OIpSI6lEqCh34K6WWswEhETWzE2iExYvISfyDO4fvF+pVSIUpS5RiVBRCsnWZbMuYh2JWYllOt/JxoJOHs7sOVPzFszkREaS8O23OA4ZgkNQkKnDUZQaSyVCRckXlx7HhN8mMGP/DMZuG0tUSlSZnhfoq+VIdAqpWXkV6tfDw6PSy9FIvZ64d95BY2dHo7eqdiGOotR2KhEqCrA/bj+jtozi4rWLTPebTrYum3HbxrE/rvSFLAE+WgwS9keVbRR5qxUrVrBixYoKPbc4yStXkn3kXxq9/Rbmrq6V2rai1DUqESr1mpSSpceWMnnHZNys3Vh9/2omtJ/AqvtX0ciuEc/teI71ESXf8N61uQu2lhpCztSM64S5MbFcnTsPu3sCcRwyxNThKEqNpxKhUm9l5GUw7a9pzA2by73N72XV/avwdPIEoIl9E34c9CM9G/fkg/0fMDdsLgZpKLIdS3Mzenu7Vfh+wqlTpzJ1auXs9CKl5PL77yOEoPEHH6gKEopSBioRKvXSudRzjNk6huCLwUzrPo3ZfWZja2F70zkOlg4s7L+QEa1GsPTYUqb/ZZwyLUqAj5bziZlEJ2WWO5bw8HDCw8Mr9DpulbpxExl799Jg2itYNGlSKW0qSl2nEqFS7wRfDObRrY+SnJ3M4vsWM7HDxGJHTuZm5rzb+12m+01nx4UdPLH9CRKybh/5Xd9uLcSEq0d1CQlc+fRTbLp1w+XRR00Wh6LUNioRKvWG3qBn/qH5TN05FU9HT9YMWUOvxr1KfZ4QggntJzC371wikyMZu3UsZ5LP3HSOT0N7Gjla3fF2a3fi8qxZyMxMGn80E2GmfrUVpazUb4tSL6TmpPJ88PMsObqE4T7D+WHQDzS2b1yuNvo378+ygcvINeQy7tdx7IvbV3BMCEGATwP2RiWgN8jKDr9UacHBpP36G9rnn8PK27va+1eU2kwlQqXOO5V0ilFbRnHg8gHeu+s9Ztw9AytNxTaebq9tz6rBq2hs35jndjzHuoh1BccCfbWkZOZxPC61XG22atWKVq0qXhhXn5bG5RkfYtW6NW5PPlnhdhSlvlKbbit12i9RvzBj/wycrJxYNnAZnRt0vuM2G9s35seBPzJ993Rm7J/BxWsXmdp9Kv4+N8oydfJwLnN7ixcvvqN4rn4xG11CAh4LFyIsLO6oLUWpj9SIUKmT8gx5fHLgE94KeYuO2o6sGbKmUpLgdfaW9izot4BRrUfx/fHvmbZrGvY2Btq4O1TrdcKMAwdJ+flnXCdOxKZjh2rrV1HqEiFl9V/PALCzs5MZGRkm6Vup2+Iz45n+13QOXT3EuHbjeLn7y1iYVc1ISUrJ8hPLmR06m/Zu7WkpX+Tnv1M58v4AbCw1ZWpj0qRJQPlHhobsbM4OGwYSvDdtxMzGptzxK0pNI4TIlFLaVWefampUqVPCr4bzyq5XSM9L57PAzxjsPbhK+xNCML79eDwcPHhjzxvEmr2LznwMB84lEtS6YZnaiIiIqFDfCQsWkHfhIs2Xfa+SoKLcATU1qtQJUkp+OvUTj29/HGtza5YPWl7lSbCwfs378f3A79FoJLYtFrHueHCV9pd17DiJ3y/DecQj2PXuXaV9KUpdpxKhUutl67J5Z+87zDowi7sa38Xq+1fT2rV1tcfR3q09q+9fhY3Q8te1T1kbsbZK+pF5eVx65x3MXV1p+OqrVdKHotQnKhEqtVpseizjfx3P5qjNPNv5WRb0X4CTlZPJ4nG3c2dsi8/RZfjy4f4P+b/Q/yt2j9KKSlz6PTmnTtHovXfRODpWatuKUh+pa4RKrbUvbh+v7X4Ng8HAgn4L6NOsj6lDAqB/q+bM+308/QP+ZtnxZUSnRfNJ4CfYmBd9Ha9Lly5lbjvn7DkSFi7EYcAAHO+7r7JCVpR6Ta0aVWodKSXfHfuOrw5/hbeTN/P6zqOFYwtTh1XAYJB0/+gPglo3oHvH43z+z+e0d2vPV/2/QmujrXC70mDgwvjx5ERE0nLrFswbNKjEqBWlZjDFqlE1NarUKum56byy6xW+PPQlA1oMYOXglTUqCQKYmQnu9tGy90wiY9uO5cu+XxKVGsWYrWOITI6scLspa9aQFRpGo9dfV0lQUSqRSoRKrXE29Sxjto1hZ/ROpvtN5/N7Pr+tdFJNEeij5WpaDpFX0+nbvC/LBi5Db9Az7tdx7I3de9O5jz32GI899liJ7eVdvszV2f+H3d134fTQ8KoMXVFqNCHEQCHEaSHEGSHEGyWc97AQQgoh/EprUyVCpVYIvhDMmK1jSM1JZfF9i5nQfkKNLjob4HtjuzWAdm7tWHn/SjzsPXg++Hl+Pv1zwbkxMTHExMQU25ax2O4HSIMB9xkzavTrVpSqJITQAAuBQUA74FEhRLsiznMApgAHytKuSoRKjaY36Pny0JdM3TUVbydv1gxZQ8/GPU0dVqk8XGzx0toREhlf8Ji7nTs/DPoB/6b+zPx7JrP/mY3eoC+1rWtbt5H+1180mPISls2aVWXYilLT9QTOSCnPSilzgZ+AYUWcNxP4DCi6kvYt1KpRpcZKyU7htd2vsf/Sfh72fZi3er2FpcbS1GGVWYCPlvWHYsjVGbA0N77ntLOw48u+X/LFP1/ww4kfiE6LRppLhK7oUZ4uOZkrs2Zh3akTruPGVWf4imIq5kKI0ELfL5ZSXt9/sCkQXehYDHBTUVEhRDegmZRyqxCiTDfaqkSo1EgnEk/wyq5XuJp5lffvep9HWj1i6pDKLcBXy/K/L3DoYjK9vd0KHjc3M+fNXm/S3LE5n//zOWKQwHFH0fcDXvnkE/RpaTSfOROhKdvepYpSy+mklKVe1yuKEMIMmANMLM/z1NSoUuNsjtrM+F/HozPo+GHgD7UyCQLc1dINjZkothrF2LZjmd93PrhC1sNZnE46fdPx9N27ubb5F7STJmHduuL1ChWlDokFCl8f8Mh/7DoHoAOwSwhxHugNbC5twYxKhEqNkafPY9bfs3g75G06NejEmiFr6Nigo6nDqjBHaws6ezix50zxZZn6NOvD6qGrcXR0ZMJvEwiJDQFAn57Bpfc/wLJlS9wmP1NdIStKTfcP4CuE8BJCWAKjgc3XD0opU6WUWimlp5TSE/gbGCqlDC26OSOVCJUa4WrmVZ7Y/gQ/nf6JCe0msPi+xbjZuJX+xBouwLcBR2NSSM3MK/actm5tWXX/Kpo5NOP54OdZc2oN8XPnort8mcYfzcTMsvZcF1WUqiSl1AEvANuBk8DPUsrjQogPhRBDK9quukaomNyhK4eY9tc0MvIy+OKeLxjoNdDUIVWaQF8t84Mj2ReVwKCOjYs85+GHHwZg+U/LeW33a6xdP5OOq/S4jBmDbdeu1RmuotR4UsptwLZbHnuvmHODytKmGhEqJiOlZNXJVTy5/UlszW1ZOXhlnUqCAF2aOWNvZV7i9GhiYiKJiYnYWtgy9+7PeW2HPQkO8Hn3ODLzMqsxWkWpn1QiVEwiS5fF2yFv88nBT/Bv6s/qIavxdfE1dViVzkJjRm9v12IXzNwqefESHC6lkjp1DH8m7GPibxO5mnm1iqNUlPpNJUKl2sWkxTD+1/FsObuF57o8x/x+83G0rLvlhAJ8tFxMyuRiYsmju+zTp0lc8l+chg3lgTHv8lW/r7hw7QJjto65bUWpoiiVRyVCpVrti93H6K2jiU2PZUH/BTzb+VnMRN3+bxjga9wge8+Z+GLPMZOSS2+/g8bRkYZvGLdPvMfjHn4c9CMSyfhfx7M7Zne1xKso9U3d/guk1BhSSpb8u4TJOybT0LYhP93/E/d43GPqsKpFywZ2NHayLnZ6tH///kxq2pTsY8dwf+dtzF1cCo61dm3NqsGraOHYghf/fJHVp1ZXV9iKUm+oRKhUufTcdF7e9TLzD89noNdAVgxaQXPH5qYOq9oIIQjw0bIvKhG94fb6n69PmECXEyex79sXh0GDbjveyK4RywYu456m9/DxgY/57OBnZdqjVFGUslGJUKlSZ1PO8ujWR9kVvYvXerzGZ4Gf1djSSVUpwFdLalYeR2NTb3pcSsml995HaDS4v/9esZUlbC1smdd3Ho+1fYwVJ1cwdedUtaJUUSqJSoRKldlxYQePbn2Ua7nXWDJgCePajau3JYT8fYxlmQpXowBIXb+ezL//Zo21NRbu7iW2oTHT8HrP13m719vsjt3NxN8mciXjSpXFrCj1hUqESqXTG/TMC5vHy7texsfZhzVD1tDDvYepwzIprb0V7Ro7FtQnBMi7epUrn31OhIUFO83LvqH26DajWdBvgXFF6bYxnEo6VRUhK0q9oRKhUqmSs5OZvGMy3x37jhGtRvD9wO9xtyt5pFNfBPpqOXQxmYwcHQBXZn6EzMlhpZMjspwj5UCPQH4c9CMCoVaUKsodUolQqTQnEk8westoDl05xIy7Z/DeXe/VqvqBVS3AV0ueXnLwXBLXtv9O2h9/oH3xBa6aV2ynw9aurVl1/yo8HT158c8XWXlyZSVHrCj1Q6mJUAjRTAixUwhxQghxXAgxpYhzhgkh/hVChAshQoUQAVUTrlJTbTqzifG/jseAgR8G/cBDvg+ZOqQap4enK5bmZvx95DyXP5qJVbu2uD3++B212dC2IcsGLqOPRx8+Pfgpnxz4RK0oVZRyKstbUR0wTUp5SAjhAIQJIf6QUp4odE4wsFlKKYUQnYCfgTZVEK9Sw+Tp8/jsn89Yc3oNvdx78Xmfz3G1djV1WDWStYWGXl6uuK/6Fn1SMs2//RZhbs6QIUPuqF1bC1vmBs1lTtgcfjzxI7HpsXx+z+f1cnWuolREqYlQSnkJuJT/dZoQ4iTQFDhR6Jz0Qk+xA26/WUqpc65mXuWVXa9wJP4Ij7d/nJe6vYS5mSpoUpIheTF0Or0P6/ETsW7XDoDp06ffcbsaMw2v9niV5g7N+eTgJ0z4bQJf9ftKXZ9VlDIo1zVCIYQn0BU4UMSx4UKIU8BW4InKCE6pucKuhDHyl5FEJEcwu89sXvF7RSXBUhgyM+m45mti7LQc7vtIlfQxqs0oFvRfQHRaNGO3juVk4skq6UdR6pIyJ0IhhD2wHpgqpbx263Ep5QYpZRvgQWBmMW1Myr+GGKrT6Soas2IiUkrOppzl2yPf8tT2p7C3tGfV4FX8x/M/pg6tVoif/xXiUhzf3zWGPRfTCh4PCgoiKCio0voJaBrAj4N+xMzMjAm/TWBX9K5Ka1tR6qIyvYUXQlhgTIIrpZT/K+lcKeVuIYS3EEIrpUy45dhiYDGAnZ2dmj6t4QzSQGRyJKFXQgm7EkbYlTCSspMA6NusL7MCZuFg6WDiKGuHrKNHSfrxR5xHjULbpjchZxKQUlbZBgOtXFqxavAqXvzzRabsnMJrPV5jbNuxVdKXotR2pSZCYfxN/Q44KaWcU8w5PkBU/mKZboAVkFipkSpVTm/Qcyr5FKGXQwm9EsqhK4e4lmsc/De2a4x/E3/83P3wa+RHM4dm9XaXmPKSublcevsdzBs0oOH0aQScTmHzkThOX0mjjXvVlZ9qYNuApf9Zylshb/HpwU+5cO0Cr/V4TU1hK8otyvIb4Q+MA44KIcLzH3sLaA4gpVwEPAyMF0LkAVnAKCmlGvHVcHmGPE4kniD0snHEd/jqYdLzjOuemjk0o3/z/gWJr4l9ExNHW3sl/Pe/5ERE4PH112gcHAj0Nf7ahUQmVGkiBOOK0jlBc5gbNpdlx5cRkxbDF32+wM7Crkr7VZSKMFXaKMuq0RCgxLf+UsrPgM8qKyilauTqczmacJSwK2GEXg4lPD6cLF0WAF5OXgzyGoRfIz+6N+pOI7tGJo62bsiJiiLxm0U4Dh6EQ7++ADR2sqFlAzv2RCbwVKB3lcdgJsyY5jeNZg7N+PjAx4zdOpYRrUcQ0DSAFo4tqrx/RSmLg5cOMiesyEnHKqfmSOqwbF02/8b/S+gV41Tnv/H/kqPPAcDXxZcHfR6ke6PudG/UHa2N1sTR1j1Sr+fS2+9gZmtLo7ffvulYoG8DfvrnIjk6PSNHjqyWeEa2HomHvQefHPyETw9+ChhH/gFNAwhsGkgP9x5Ym1tXSyyKct3ppNPMPTSXvbF7TXa7jzDVUNTOzk5mZGSYpO+6KjMvk/Cr4QWJ72jCUXQGHQJBG9c2dG/UHT93P7o37I6ztbOpw63zkpav4MqsWTT57FOchg276diOE1d46sdQVj3di7tbVv+bkOhr0eyJ3UNIbAj/XP6HbH02Vhor/Nz9CGwaqEaLSpWLTY9l4eGFbDm7BQdLByZ1msToNqOxNrfOlFJW69y9SoS1WFpuGoevHi64xnc88Th6qUcjNLRza4dfIz/83P3o0rALjpZVey1KuVlebCxRDwzFtls3mi1ZfNvCovQcHV1m/M7T93jz4j3GIsW2tqbZCSZHn0Po5VBCYkMIiQ3h/LXzwI3RYkDTAHq498DG3MYk8Sl1S0p2CkuOLmH1qdWYCTPGth3Lkx2fLPgbJYRQiVApXkp2CmFXwwoS3+nk0xikAXMzczpqOxoTXyM/OjfsrBZDmJCUkuhJz5AZFkbLXzZj0bRpkeeNWLSP7DwDaevfAWDXrl3VGGXxotOiC5LiwUsHb4wWG/kVJMYWji3UqmGlXLJ0Waw8uZLvjn5Hpi6TYS2H8VyX526bDlWJULlJQlZCwf17oVdCiUyOBMDSzJLODTsbpzob+dGpQSf1br0GSd28mbjXXqfR22/jOu6xYs/7ckck84IjaBryOeYaUWMSYWE5+hzCLocVTKNeHy162HsYry16BKrRolIinUHHpjOb+Dr8a65mXSWoWRBTuk7Bx8WnyPNVIqznrmZeLbiHL/RKKOdSzwFgY25DlwZdCq7xddR2VOWNaihdYiJnB9+PpZcXLVauQGiKL7gbdiGZh7/Zh0PwLNzsLGtkIrxVTFrMjdHi5YNk6bKwNLOkh3sPNVpUbiKlZGf0Tr489CVnU8/SuUFnXu7+Mt0bdS/xeSoR1jNx6XHGpJef/KLTogGws7Cja8OuBdf42rm1w8LMwsTRKmUR+8o00v74A68N/8PKp+h3vNfp9Aa6zvyD1LXv4N3ArlYkwsJy9DmEXQkrSIzX37ip0aJy+Oph5obN5fDVw3g6ejK1+1T6NetXpjdIKhHWYVJKotOib0p8lzIuAeBo6Ui3Rt0KEl9rl9Zq949aKO3PncQ89xzaF1+gwfPPl+k5k34MZc0HT9G1uXOtS4S3Km606Od+49qip6OnGi3WYWdTzjLv0Dx2Ru+kgU0DnuvyHA/6PFiuv2cqEdYhUkrOpZ4rmOYMuxzG1ayrALhYuRhvY8i/xufr4ouZKFchEKWG0aelcXbIA2gcHfFavw5hWbap6+X7z/PyR1/y+sA2vPriM1UbZDUqbrTY1L7pTfctqpqJdcOVjCt8c+QbNpzZgK25LU90eIKxbcdW6N9XJcJaLCMvg+MJxzmacJSjCUc5fPVwwQbVWhttwYpOP3c/vJ281bviOubSBx+Q8vNaPH9ajU2nTmV+3rmEDPrO3sXMYe0Zd5dn1QVoYrHpsYTEGJPigcsHCkaL3Rt1L5hGVaPF2uda7jW+P/Y9K06sQCd1jG49mkmdJuFi7VLhNlUirCXyDHmcST5TkPSOJRwjKiUKmV+PuJlDMzo36FyQ+Jo7NFe/4HVY5j//cGHceFwnTKDRm2+U67lSSnq9t5E27g78+Py9VRRhzZKrz71ptHg29SygRou1Sa4+l9WnVrPk6BKu5Vzjfu/7eb7L83g4eNxx2yoR1kBSSmLTYzmWcIx/E/7lWMIxTiaeJFufDYCzlTMdtR3pqO1IB20HOmo7ql1b6hFDdjbnhj2I1Ovx3rwJswrcFN+8fQ8SM3JIjQrHXFP/pshj02PZG7uXPbF7OHDJOFq0MLO4cd+iRwBejl7qzWQNoDfo2XZuGwsOLyAuIw7/Jv5M7T6VNq5tKq0PlQhrgNSc1JuS3rGEYwVTnFYaK9q6tqWDtgOdGnSig7YDHvYe6he0Hrv6f3NIXLKE5ku/w+7uuyvURscedxN5JY29e3bTvUXFp5TqgtJGiwFNA+jp3lONFquZlJK9cXuZGzaXiOQI2rm14+XuL9O7ce9K70slwmqWo8/hVNIpjiUcM05zxh/lYtpFAAQCbyfvm5Ker4uvuo1BKZB94gTnRozEadgwmnw8q8LtBAT2IfRCEp8t/R9T7vWtxAhrv7j0OEJiQ9Ro0YSOJRxjbthcDl4+iIe9B1O6TWGA54AqW+CnEmEVMkgDF65dKEh4RxOOcjr5NDqDDoAGNg2MU5wNjNOc7dzaqerrSrGkTse5kSPRXY2n5dYtaJycKtxWUFAQR2NT6TdtIWsnV2xUWR/k6nM5dPVQwaKbqNQoQI0Wq8rFaxeZf3g+289vx9XalWc6PcOIViOw0FTtYEAlwkqUkJVQkPCOJhzleMJx0vLSALA1t6WDtkPBNb2O2o6q/p5SLglLlhD/f3No+uWXOP5nwB21FRQUxMWk0lUVmwAAIABJREFUTMyGfED4+wOwt1L3kJbF9dFiSGwIBy4dIFOXiYWZBd0adaOne096uPegg1uHKv/DXdckZCXw7ZFvWRexDguNBRPaT2Bi+4nVtn+xSoQVlJmXyYnEEzdd27t+s7pGaGjl0uqmpOfl5IXGrPitrxSlJLnnz3N22IPY3xOIx1df3XF7a9as4fTlayy91IT/jvfj3nbqTVl55enzjKPF2BD2x+3ndPJpwLg9YdeGXenh3oMe7j3ULk0lyMjL4IfjP7Ds+DJy9bk80uoRJneeXO21SlUiLAOdQUdUStSN63oJRzmTcgaDNADGaZLrCa9jg460cW2jtnhSKo00GLg4YSLZp07hvWULFo0aVkq7OTo9nWf8zugezflgaPtKabM+S8lOIexKGAcvH+Tg5YOcSTkDGGeDujbqSk/3nvR070kb1zb1fhenPEMe6yLWsejIIpKykxjQYgAvdn0RTydPk8RjikRYo/8HSCm5nHG5IOEdTTjKicQTZOmyAOPWZB21HenXvB8dtR1p79YeNxs3E0et1GUpa9eR+c8/NP5oZqUlweho4x6zPb3c2BMZXylt1nfO1s70b9Gf/i36A5CUnUTo5VAOXj5I6OVQ5obNBcDewr5gKtXP3Y82Lm3qzWyRlJLtF7bz1aGvuJh2Eb9Gfizot4D/b+++46Oq0sePf85MeqMkgSCEloTeOxg0IiqCgBVpYscCImtZV9fd36qru19FxRVRUAQVVFBUJIIKSJXeBIGE0GsCoaQSUub8/rgDhJCQNpObmXner9e8MnPnzr3PdYhPzrnnPKdteFuzQ6ty1apFmJ6bfll1lu0nt3Mq5xQA3hZvWtZuSdtwY75eu7B2RAZHymgxUWXyUlLYN+A2/Nq0oeH0Tx32by8uLg6AEa9+yusLdrHmxT7UqyG9GM6Uei6Vjckb2ZC8gfXJ6y8uLxXsE0znup3pWrcr3ep1o1mtZm5Z/nD98fW8s+kddpzaQUytGMZ3Gk/v+r2rxf9PPa5FuCN1x8V7ettObrv4jxGgSY0mXFv/2otJr1mtZnLTW5hGa03yK6+i8/Op9+orTvkfRmyMcS9mZVIqQ7pEOvz44pIw/zD6NelHvyb9gEtLoK1PXs+G5A0sO7wMMHqdutTtQrd63dyiLnDi6UTe3fwuvx/9nXqB9Xg99nUGNBngMa3gkpiWCG3hNob+NBSAUL9Q2oa3ZVDUINqEtaF1WGtCfELMCk2IK2T8/DOZv/1Gneefx6dhQ6eco0VEMGFBvqySRFjl6gTUoX/T/vRv2h+A5KxkNiRvuPj47fBvwKWC+V0jutK1bleiakZVi1ZUaY5lHmPSlknE74sn2CeY57o8x9AWQ/G1+podWrVgWiJU5xRvX/82bcPaEhEY4RL/mIRnyj9zhuTX/o1fmzbUvn+U086jlCI2OpSVSanYbBqLRX4nzBIRGMHAqIEMjBoIwPHM4xdbixuSN7Do4CIAavvVvpgUu9brWu0m95/NOcvH2z/mq4SvsCgLD7Z5kIfbPiwNjSLMS4SZipsbV27+lRBV4cR//4+C9HTjvqCXc39lYmPC+WHrMXYlp9P6mopP0heOVS+oHoOjBzM4ejBgrL14ISmuT17PLwd+AYwu1wtJsVtEN9MK7p/LP8esXbOYtn0a2fnZDI4azJMdniQiMKLKY3EF1XrUqBBmy1y5irR58wh9/DH8mjd3yjmeffbZi89jo437hKuSUiURVmMNghvQILgBd8TcgdaaIxlHLk7V2JC8gYUHFgJGl+uFFmO3iG40CHZubeJ8Wz7z9sxj8tbJnDh3grjIOJ7u+DTRtaKddk53UK1GjQpRndiystg3cBDK15cmP3yPxbdq7qfc9M5yImr48cXD3avkfMKxtNYcTD94carG+uT1F0e/RwRGGC3GCGNUav2g+g4759LDS3lv83vsS9tH+/D2/KXzX+hct7NDjl+VPG7UqBDV2YmJ75F3/DiNZs10ahJMTDSqoDS3tzhjY8L4ct0hcvIK8PP27NF8rkgpReMajWlcozFDmg9Ba83+tP0Xu1F/P/Y78/fNB4wCIBdGpXat25V6QfXKfb4tJ7bw7qZ32XJiC41DGjPxhon0iexTre5VVnfSIhSiGNlbtnBw+AhqDRtGxD//4dRzXZhHuGzZMgB+S0jhoRkbmflw94tTKoT70Fqz9+zei92oG1M2cvb8WQAaBDW4OFWjW0S3q9ZA3nd2HxM3T2Tp4aWE+4fzZIcnuT36dpevlCMtQiGqAVtuLsf/8Q+8IiIIf+aZKj9/9yaheFsVK/eclETohpRSRNeKJrpWNMNbDsembSSdSbo4+GbxwcV8l/QdAI1CGl1Mil0juhIeEE5KVgof/vEh3+/5ngCvAMZ1HMeIliNk1Y1KkEQoRBGnPppC7p69RE75CGtQlf5hCkCgrxcdG9ZiVVIq3FrlpxdVzKIsNK/dnOa1mzOy1UgKbAXsPrP7YmL89cCvzE2aC0DjkMYkZyWTr/MZ3mI4o9uNppafZy/m7AiSCIXb0Vpjy8rGlpFOQXo6BWlp2DIyKEhLN7alpVOQkYEtPY2C9AwK0tOxpdv3TU9HnztHyMCBBF1/vWnX0Ds6jLcX7eZU5nlCg2TSsyexWqy0DG1Jy9CWjGo9igJbAQlnEthw3OhG7VinI6PbjaZBcAOzQ3UbkghFtaTz8uzJ6kKCKpq4ikliGenY7EmOgoKrHt8SHIw1JARLSAjWkBB8GjcyngeH4BUeTs17h1TRlRYvNsZIhL/vPcWg9teYGoswl9VipXVoa1qHtuaBNg+YHY5bkkQonEJrjc7OpuBCSyw97dLzi62yS4mrID0Nmz2xFaSno7Ozr3p85e2NpUYNrCEhWIODsdauhU+jRlhrhGAJDrEnuWCsITWwhgRfTHjWkBAsQUEoa/UZjfnyyy9fsa1dg5qE+HmxKumkJEIhnEwSoYfSBQXo3Fx0Xp7x0/6wXbbN/jMv94p9CzIzCyWuS0nsUussA/LzrxqDJSjo8lZZo4alJ7HgEKw1QlC+vm4zPLxv375XbLNaFL2iwliVlIrW2m2uVYjqSBKhk2mtIS8PW26ePaHkXUoshR/2JGO7uC2v2ERVOCldsW9x++fmYsu7sP3Se6V1HZaJt/elBBUSjLVmTXwiI7HUCLk8idmT14UkZg0OxhIcXK1aZWbaunUrAB06dLhse2xMGD/vSGZfahZR4UFmhCaER5BEWMjF7rysLGxZWcaAi4vPizyyr3yvIPvS5/S5cxeTkiMpb2+Uj4/xKPz84sMbi78fhARj8fFBeRd5/+JnjJ+Wko7lfel4xnPvS/v6+GAJDET5+UlLxQHGjx8PXJpHeEHvmEvl1iQRCuE8Lp0ItdbonJwrE1JWVpGEVkpSu5DYsrOhjAUGVEAAlsAArAGBWAKNh3d4HSyNjefK3++yxHExsVyWcAolo2KTWpHPeHtL4vEgjUIDiaztz8qkVO7v1djscIRwW6YlQi+tyUlMvGpyuqxlll1MMsvOLnMXn/Lzu5iwLIGBWAICsIbWxrthJJbAQKyF37tsv0AsgQGXb/P3l249USVio8OZ/8cx8gpseFtdd0FYIaoz0xJhpE2zf/DtJb5/ofvtQtKyBAZiDQnBu169QknpUoKyFtm3aNJz9vI5QjhD75gwvlp/iD8On6VL49pmhyOEWzItO5y0KOq/995lCa1wq0x5e5sVmhDVRq+oUJSClUmpkgiFcBIpui2EyVavXg1Ar169in1/8KRVeFktzH2i+PeFcCdSdFsID1RSArwgNiaMj5bvIz0njxA/6SkRwtHk7rsQJlu9evXFVmFxYqPDKbBp1u49VYVRCeE5pEUohMleeukl4Mp5hBd0alQTf28rq/akcnPriCqMTAjPIC1CIao5Xy8r3ZvWNpZlEsLDKaX6KaUSlVJ7lFJ/K+b9x5VS25VSW5VSq5RSrUo7piRCIVxAbHQY+1KzOHr2nNmhCGEapZQV+ABjpc5WwLBiEt2XWuu2WusOwJvAO6UdVxKhEC6gd0w4AKuSTpociRCm6gbs0Vrv01rnAl8DgwvvoLVOL/QyECh1aoQkQiFcQLO6QdQJ9mWldI8Kz1YfOFzo9RH7tssopcYopfZitAjHlXZQGSwjhMkmTpxY6j5KKWKjw1i2+yQ2m8ZikZqzwm15KaU2Fno9VWs9tTwH0Fp/AHyglBoOvAzcf9UTlj9GIYQjFV1+qSSxMWF8t+UoO4+n06Z+DSdHJYRp8rXWXUp47ygQWeh1A/u2knwNfFjaCaVrVAiTLV68mMWLF5e6X2y0sSyTdI8KD7YBiFFKNVFK+QBDgR8L76CUiin0cgCQVNpBpUUohMn+/e9/A8WvVF9YnRA/mtcNZtWekzwRF1UVoQlRrWit85VSY4FfACvwqdZ6h1LqVWCj1vpHYKxSqi+QB5yhlG5RkEQohEuJjQnji7UHyckrwM+7AkuBHd4A856Efv+B6KsnXiGqI631AmBBkW3/LPT86fIeU7pGhXAhsTFh5ObbWL//dMUOsHkGpO6GWUNg/ccOjU0IVyWJUAgX0r1JbXysFlbtqcB9woJ8SFwIzftDzE2w4DlY+ALYyra4tRDuShKhEC4kwMeLTo1qVmzAzOG1kH0K2g2BoV9CjzGw7iP4aiicz3B8sEK4CEmEQphsypQpTJkypcz7944JZ9fxdE5mnC/fiXbFg9XXuDdosUK/N2DAO7BnCUy7Bc4eLv0YQrghSYRCmKx58+Y0b968zPtfmEaxem85WoVaQ0I8NI0D3+BL27s+DCO/hbTD8HEfOLKp7McUwk1IIhTCZPPnz2f+/Pll3r9N/RrUDPAuX/fo8T+MZNfytivfi+oDDy8Cb3+Y0R92/FD24wrhBiQRCmGyt99+m7fffrvM+1stimujwliVlIrWpdYTNiT8BMpiDJQpTp0W8OhvUK89fHM/rJhgtCKF8AClJkKlVKRSaqlSaqdSaodS6oo5GkqpEUqpbfY1oFYrpdo7J1whBBjTKJLTc9h7MrNsH0iIh4Y9ITCs5H0Cw2DUj9D2HvjtNfjhScgv531IIVxQWVqE+cCzWutWQA9gTDHrP+0HrtdatwVeA8pVIFUIUT7lKrd2ai+c2AktiukWLcrbD+78GOJegj++hC/ugOwKzlkUwkWUmgi11se11pvtzzOAXRRZ9kJrvVprfcb+ci1GIVQhhJNE1g6gcWhA2VatT4g3frYYULaDKwVxL8Bd0+DIRvjkRkgttVyjEC6rXPcIlVKNgY7Auqvs9jCwsITPj1ZKbVRKbczPzy/PqYUQRcTGhLFm3yly821X33FXPES0hVqNyneCtnfD/fMhJ91IhvtXVDxYIaqxMidCpVQQMBcYX2QF4ML73ICRCF8o7n2t9VStdRetdRcvLylzKgTAF198wRdffFHuz8VGh5OdW8CWQ2dK3ikjGY6shxYDKxZcw+7w6BIIrmd0k27+vGLHEaIaK1MiVEp5YyTBWVrr70rYpx3wCTBYa33KcSEK4d4iIyOJjIwsfcciekaFYlFcvdxaor02cXHTJsqqVmN4+Fdoch38+BT8+g+wldIKFcKFlGXUqAKmAbu01u+UsE9D4DvgPq31bseGKIR7mz17NrNnzy7352r4e9M+spRya7vioVYTqFN0fFs5+dWA4d9Al4dh9f9gzn2Qm1W5YwpRTZSlRXgtcB/QRym11f7or5R6XCn1uH2ffwKhwGT7+xudFbAQ7ubDDz/kww9LXUS7WL2jw9h25Cxp2XlXvpmTZtzXa3mbMQCmsqxeMOBt6Pdfo6U5/VZIP1754wphsrKMGl2ltVZa63Za6w72xwKt9Uda64/s+zyita5V6P0uzg9dCBEbE45Nw5p9xbQKd/8KtryK3x8sjlLQ4wkY9rUxLePjPkbVGiFcmFSWEcKFdWxYk0Afa/HdownzIbAONOjq+BM3uwUe+tlIjJ/2g4QFpX9GiGpKEqEQLszbaqFH09ArB8zknYOkxdCiP1ic9Gse0dYoyxbeHL4eDqvfl7JswiVJIhTCxcXGhHHwVDaHT2df2rhvOeRlObZbtDjBEfDAAmg5EH59GeLHQ0Ex9yuFqMYkEQphsm+//ZZvv/22wp/vHVNMubWE+eAbYkx5cDafALjnM4h9BjbNgJl3wbmrzG0UopqRRCiEycLCwggLu0ox7FJEhQcREeLHqj0njQ0F+ZC4EGJuBi8fB0VZCosF+v4/GDwZDq6GaTfD6X1Vc24hKkkSoRAmmzFjBjNmzKjw55VSxMaE8fueUxTYNBxeC9mnKjeJvqI6joBRP0DWSfj4Rji4pupjEKKcJBEKYbLKJkIwukfTzuXx59E0YxK91Rei+zomwPJqHAuPLAH/WvD5IPij/MUChKhKkgiFcAPX2pdlWpV00lhtomkc+AabF1BoFDyyGCK7w/ej4bd/S1k2UW1JIhTCDYQF+dKyXgiHd62FtMPmdIsWFVAbRn4HHUfCirdg7kPGtA4hqhlJhEK4id4xYTRI/g2tLNC8v9nhGLx8YNAk6PsK7PgeZtwGmSfMjkqIy0giFMJNxEaH0VdtIC2sMwRWfBSqwykFseNhyBeQssMYRJOy0+yohLhIEqEQJluwYAELFlS+RFn3GmdpYTnMOr9eDojKCVoNggcXQEGuMb0iabHZEQkBSCIUwnQBAQEEBARU+ji+e4xkOuts20ofy2nqdzLKstVuDF/eA+ummh2REJIIhTDb5MmTmTx5cuUPtCuek0HNWXEygBPpOZU/nrPUqA8P/gwxt8DC52HB80YRACFMIolQCJPNmTOHOXPmVO4gGclwZAO25gOAUlatrw58g2DoLOgxBtZPha+GQk662VEJDyWJUAh3kLgA0IR3uYvagT6sutqq9dWFxQr93oDb3oW9v8Gnt8DZQ2ZHJTyQJEIh3MGueKjVBEtEa3pFGcsyaVdZEqnLQzDyW0g7aowoPbLR7IiEh5FEKISry0mD/SuMSfRK0TsmjBMZ59mdkml2ZGUX1QceWQTe/jBjAPz5ndkRCQ8iiVAIV7f7V7DlXVx7MDYmHICVSSfNjKr8wpsbI0rrdYBvHzSq0bhKq1a4NEmEQphs2bJlLFu2rOIHSJgPgXWgQVcA6tf0p2lYYPUfMFOcwDAYNQ/aDjHqk/7wBOSfNzsq4eYkEQrhyvJyjInpLfobawLaxcaEsW7fac7nF5gYXAV5+8GdU+GGv8MfX8Hnt0PWKbOjEm5MEqEQJpswYQITJkyo2If3LYO8rIvdohfERodxLq+AzQfPVj5AMygF1/8V7poGRzfBJzfCyd1mRyXclCRCIUwWHx9PfHx8xT6cMB98Q6DJdZdt7hEVitWiLq1a76ra3g0PxMP5DJjW10j8QjiYJEIhXFVBPiQuhJibjVUeCgnx86ZDZE3XmE9YmshuxiCa4Gtg5l2w6TOzIxJuRhKhEK7q8FrIPlXi2oOx0WFsO5rG2ezcKg7MCWo1god/gSbXw/xx8OvLYHPB+5+iWpJEKISr2hUPVl+I7lvs271jwtAaVu91k4EmfjVg+Bzo+iisfh9m3we5WWZHJdyAJEIhTObv74+/v3/5PqQ1JPwETePAN7jYXdpH1iTI14uV7tA9eoHVCwZMgFvfhN0L4dN+kH7M7KiEi5NEKITJFi5cyMKFC8v3oeRtkHaoxG5RAG+rhR5NQ11/wExxuj8Gw76G0/vg4z5wbKvZEQkXJolQCFe0Kx6UBZr3v+puvWPCOHz6HAdPuWEXYrNb4KFfQFlh+q1GC1mICpBEKITJXnvtNV577bXyfSghHhr2NCqxXEVsjPG+W3WPFhbRxhhRWqclfD0Cfv+flGUT5SaJUAiTLVmyhCVLlpT9A6f2womd0KLkbtELmoYFck0NP/eYRlGS4LrwwE/QajAs+gfMG2MUIheijCQRCuFqEuyT71sMKHVXpRSxMWGs3ptKgc2NW0re/nD3dLjuedj6JUzqCn/OldahKBNJhEK4moSfIKKtMbeuDGJjwknPyWfbERctt1ZWFgv0eRkeXQLBEfDtQzDzTqMFLcRVSCIUwpVkpMDh9VfUFr2aa6NCAdy7e7Sw+p3h0aXGFIvDG2ByT1j+pqxiIUokiVAIk4WGhhIaGlq2nRN/AvRVp01ccfwgX1pfE8JKV1yWqaIsVmOKxdgNxsocS1+HD3vBvuVmRyaqIUmEQphs7ty5zJ07t2w774qHWk2gTqtynSM2Jowth86QdT6/AhG6sJB6cM8MGDEXbPnw+SD4bjRknjA7MlGNSCIUwlXkpMH+FUZrUKlyfbR3dDh5BZp1+92k3Fp5xfSFJ9cag2n+/A4mdYEN08BmMzsyUQ1IIhTCZC+++CIvvvhi6Tvu/hVseWWaNlFUl8a18PWyuO98wrLw9jcG0zyxGiLawU/PwLSb4Pg2syMTJpNEKITJ1qxZw5o1a0rfMSEeAutAg27lPoeft5VuTWp7zoCZqwlvBvfPhzumwpkDMPV6+PklY81D4ZEkEQrhCvJyYM9iY+CHpWK/trHRYSSdyCQ5LcfBwbkgpaD9vfDURuh0P6z9ACZ1g53zZO6hB5JEKIQr2LcMcjPLNW2iqAvl1lZ50ujR0vjXgoET4eFFEFAb5oyCL4cYLUXhMSQRCuEKEuaDbwg0ua7Ch2gZEUJooA+rktxwNYrKiuwGo5fDza/Dgd/hgx6w8m3Id4NFjUWpJBEKYbIGDRrQoEGDkncoyIfEhRBzM3j5VPg8Fovi2ugwVu05hZbuvytZvaDXWBi73hhluuRV+CgWDqwyOzLhZJIIhTDZzJkzmTlzZsk7HF4L2afKVFu0NDe0CCc18zzvLUmSZFiSGg3g3pkwbDbknYMZA+D7JyBLupTdlSRCIaq7hJ/A6gsxN1X6UIPa1+euTg2YuDiJN39JlGR4Nc37wZi1EPsX2D4H3u8Mmz6TuYduSBKhECYbP34848ePL/5NrY1qMk3jwDe40ueyWhRv3d2O4d0b8uGyvbwav1OS4dX4BELff8Hjq4xqPvPHwfR+kLLD7MiEA0kiFMJkW7duZevWrcW/mbwN0g6Vq7ZoaSwWxeu3t+HBaxsz/fcD/P2HP7G58xJNjlCnJTy4AAZPhtQk+Kg3/PoPyM0yOzLhAJIIhajOdsWDskDz/g49rFKKf97Wisevj+LLdYf469xt7r1eoSMoBR1HwFOboMNwWP0/+KA7JCwwOzJRSZIIhajOEuKhYU8IDHP4oZVSvNCvOeP7xvDtpiP8ZfZW8grk/lepAmrD4Enw4M/gEwRfD4OvhsPZw2ZHJipIEqEQ1dWpvXBiZ4Vqi5aVUorxfZvxQr8W/PjHMcZ+uZncfEmGZdKoJzy+Evq+Ant/gw+6we/vQUGe2ZG5NaVUP6VUolJqj1Lqb8W8/4xSaqdSaptSaolSqtQVrCURCmGyZs2a0axZsyvfSPjJ+OmAaROleSIuin/e1opfdqTw+MxN5OQVOP2cbsHqDbHjYcw6o9jBon/ClOvg0FqzI3NLSikr8AFwK9AKGKaUKrom2Ragi9a6HfAt8GapxzVrxFhgYKDOypIbzUKUaNrNkJdtjFisIjPXHuTlH/4kNjqMj0d1wd/HWmXndnlaG3+8LHwB0o9Ap1FGazGgttmRuRSlVLbWOrCE93oC/9Ja32J//SKA1vo/JezfEZiktb72aueUFqEQ1VFGChxeX6naohUxskcj3rq7Hav3pnL/9PVketpCvpWhlDG6d8w66PUUbJllrHu4ZZYU8i4fL6XUxkKP0YXeqw8Uvhl7xL6tJA8DC0s7oSRCIUw2evRoRo8effnGxJ8A7dBpE2V1T5dIJg7tyKaDZ7hv2jrSzsk9r3LxDYKb/w2PrYDaUTDvSaM6zYkEsyNzFfla6y6FHlMrchCl1EigC/BWaftKIhTCZLt372b37t2Xb9wVD7WaGJO4TTCo/TV8MLwTfx5NY8QnazmTJcWnyy2iDTz0Cwx8z5iA/9G1sPgVyM02OzJXdhSILPS6gX3bZZRSfYG/A4O01udLO6gkQiGqm5w02L/CaA0qZVoY/dpEMOW+zuxOyWTYx2tJzSz1/yeiKIsFOj8AYzdC23tg1TswuTvs/sXsyFzVBiBGKdVEKeUDDAV+LLyD/b7gFIwkeKIsB5VEKER1k7QIbHlOnTZRVn1a1OXT+7ty4FQW905ZQ0q6LOpbIUHhcMdHcH88ePkZax7OHglpVzRmxFVorfOBscAvwC5gjtZ6h1LqVaXUIPtubwFBwDdKqa1KqR9LONxFMmpUCJPFxcUBsGzZMmPDnPvh4Gp4NrHCq9E72rp9p3hoxgbCgn358tEe1K/pb3ZIris/16hKs+ItsHjBDS9Bt8eMZaDEVUeNOkv1+C0TwoN16NCBDh06GC/ycmDPYmjRv9okQYDuTUP54pHunM7KZchHazh0Su5zVZiXD1z3HDy51qga9MtLMDUOjmw0OzKPVWqLUCkVCXwO1AU0MFVr/V6RfVoA04FOwN+11hNKO7G0CIUoRuLP8NW9MGKusThsNbP9SBr3fboOPy8rsx7tTlR4kNkhuTatYdePxtzDjGTo8iDc+E/wr2V2ZKapri3CfOBZrXUroAcwppiZ/KeBcUCpCVAIcRUJ88E3xKhSUg21bVCDrx7tQV6BjXunrCUxOcPskFybUtBqMIxZDz2egE0zYFJX2DZH5h5WoVITodb6uNZ6s/15BsYNyvpF9jmhtd4AyIQjIcpp5MiRjBw5EgryIXEhxNxsdJ9VUy3rhTD7sR5YFAyduoY/j6aZHZLr8wuBfv+B0cugRiR89yh8PshY8kk4XbluQiilGgMdgXUVOZlSavSFagH5+VKxQgiAI0eOcOTIETi8DrJPVUlt0cqKrhPMnMd64u9tZfjHa9l6+KzZIbmHeu3hkcUw4G049gd82At+ex3yzpkdmVsrcyJUSgUBc4HxWuv0ipxMaz31QrUALy8ZISXEZRLiweoLMTcmFMBHAAAgAElEQVSZHUmZNA4LZPZjPakZ4MPIT9ax4cBps0NyDxYrdH0Exm4wuk1XvAmTexqDqIRTlCkRKqW8MZLgLK31d84NSQhPpI1qMk3jwDfY7GDKLLJ2AHMe60mdYF9GTVvP6j2pZofkPoLrwl2fwH0/GIszz7wLvnkA0o+ZHZnbKTURKqUUMA3YpbV+x/khCeF5ooPOQdohU2qLVlZEDT++fqwHkbX9eXDGBpYllqmYhyirqBvgidUQ9yIkLID32sO8sXAy0ezI3EZZpk/EAiuB7cCFFTtfAhoCaK0/UkpFABuBEPs+mUCrq3WhyvQJIQwvvvgifa3rudF7MzyX5JTV6KvC6axcRn6yjj0nMpk0vCM3t44wOyT3c3q/MRl/65eQnwPN+kGvcdCol6nl+BzJjOkTUllGiOpgck9j7tiDC8yOpFLSsvMYNX09O46m8d7QjgxoV8/skNxTViqs/xjWT4Vzp+GaTnDtOGPZLhevUFNd5xEKIZzp1F44sdMlRouWpkaANzMf7kbHhjV56qvNfLf5iNkhuafAMLjhRfjLDmOE6bkzxv3D9zvBuqmQK42M8pAWoRAm++yxLtxfLwme3ga1GpkdjkNk5+bzyGcbWbPvFP+5oy1DuzU0OyT3ZiuAhJ+MbtMjG4zeha6PQLfREFTH7OjKRbpGhfBA2/9yDX4WGzFvJ5sdikPl5BXw2BebWL77JK8Obs2ono3NDskzHFoLv/8PEheA1QfaD4VeT0FYjNmRlYl0jQrhaTJSaB2SxcrUGmZH4nB+3lamjurMTa3q8s95O5i6Yq/ZIXmGhj1g2JfGPMQOw+CPr2FSF/hqGBxcI6XbiiGJUAgzJf6ERcHK1JpmR+IUvl5WJo/oxIB29XhjQQLvL5GSYVUmLAYGvmfcR7zur3BoDUzvB5/0hZ3zjO5UAUgiFMJcu+I5es6H/Vl+ZkfiNN5WC+/d24E7O9bn7UW7mfBLImbdkvFIQeHQ5+9GQuw/AbJTYc4oeL+zMfI0V5bUkkQohFly0mD/Cg4FtOPGG6vfkkuO5GW1MOGe9gztGsmkpXt4/addkgyrmk8gdHsUntoM93wGAbVhwXPwbmtY+oYxJcNDyWAZIcyy/VuY+zA89ItxX8cD2GyaV+bv4LM1B7mvRyNeGdQai8U9JoK7HK2N7tLV7xsDa7z8oP0w6DkWwqJNC8uMwTKuPfNSCFe2az4E1oEG3cyOpMpYLIp/DWqNn7eVKSv2kZtv440722KVZFj1lDIq0jTqBSd3w5r3YessY03EFgOMijUNu5sdZZWQFqEQZsjLgbeioO3d3Dp5NwALFy40Oaiqo7Xm3cVJ/G9JErd3uIYJ97THyyp3akyXkWJUq9nwCeScNf5Iu3YcNO9vrIpRBWT6hBCeYt8yyM2EFgM5d+4c58551npzSimeuakZz9/SnB+2HmPc11vIzbeV/kHhXMF14cZ/wDM74dY3ITMZZo+ESV1hwzS3XRdREqEQZkiYD74h0OQ6syMx1Zgbonl5QEsWbE/myVmbyMmTIf3Vgk8gdH8MntoCd08HvxD46RljYM2y/0LWKbMjdChJhEJUNVsBJC40FuD18jE7GtM90rspr93ehsW7TvDo5xs5lyvJsNqwekGbO+HRpfDAT1C/Cyz7j5EQ458x6uS6AUmEQlS1Q2sh+xS0cL21B53lvh6NePOudqzak8qDM9aTdT7f7JBEYUpB41gYMQeeXAdt74ItXxhzEWePhMMbzI6wUiQRClHVEuLB6mu0CIHbbruN226TpDikayQT7+3AhgNnGPXpetJz8swOSRSnTgsY/AGM3w6xf4H9K2BaX/i0n1H42+Z693pl1KgQVUlrmNgO6rQ0/roWV1i4/ThPfbWFVteE8PlD3agZIN3H1dr5TKN1uGYypB2C0GhjLmL7YeBd/opJMmpUCHeXvM34n0VLaQGW5Na29fhoZGcSjmcw7ON1nMo8b3ZI4mp8g6DHEzBuC9w1zRhoEz8eJraB5W9C9mmzIyyVJEIhqlLCT6Asxrwsu7i4OOLi4syLqRrq26oun9zfhf2pmQydupYT6TlmhyRKY/WCtnfD6OVw/3yo1wGWvm4MrFnwPJzeb3aEJZJEKERV2hUPkT2MFcbFVV3XLJzpD3Tj6Nlz3Dt1LcfOuuccNrejlDEtaOS38MQaaH0HbJwO73eCOffDkU1mR3gFSYRCVJXT++DEDukWLYeeUaF88XA3UjPOM2TKGg6flpUSXErdVnD7ZGNgTa9xsHcpfNIHpvc3phBVk4E1kgiFqCq74o2fMm2iXDo3qs2sR7uTkZPPkClr2J8qg+xcTkg9uOkVeGYH3PIGnDkIXw2Fyd1h02dGyUETSSIUoqokxENEW6jVyOxIXE67BjX56tEe5ObbGDJlDUkpGWaHJCrCNxh6joGnt8Kdn4CXL8wfBxPbwooJpg2skUQoRFXISIHD66HFwCveGjJkCEOGDDEhKNfS6poQvh5tLFd179S17DyWbnJEosKs3tDuHnhsJYyaZ/yB+Ntr8G4bU8KReYRCVIWN040h5U+shrqtzY7Gpe1PzWL4x2vJzi3gi4e70a5BTbNDEo6Q/CesmYS6c4rMIxTCLSXEQ60mUKfVFW9lZ2eTnS2DQMqqSVggcx7rSYi/FyM+Xsemg9V/npoog4g2cMdHppxaEqEQzpaTBvuWG4udqisXoO3fvz/9+/cv5oOiJJG1A5jzWE/Cgn25b9p61ux1r9UQRNWSRCiEsyUtAlsetLzy/qCouHo1/Jk9ugf1a/rzwPT1rNh90uyQhIuSRCiEs+2aD4F1jNW+hUPVCfHj69E9aBoexCOfbWTJrhSzQxIuSBKhEM6UlwN7FkOL/mCRXzdnCA3y5atHu9OyXjCPfbGJn7YdNzsk4WLkN1MIZ9q/HHIzi502IRynZoAPXzzSnfaRNRnz5WbGzNrMUSnJJsrIy+wAhHBru+aDb4hRe7EEDzzwQNXF48ZC/LyZ9Uh3pizfx+Rle1iSkMKTcdGMvq4pft5Ws8MT1ZjMIxTCWWwFMKEZNL0e7v7U7Gg8ypEz2byxYBcLticTWduflwe04uZWdVHFjNoV1YusRyiEOzm0FrJTS60tmpqaSmpqahUF5Rka1Apg8ojOfPlId/y9rTz2xSZGfbqePSekNJu4krQIhXCWn1+EDdPgr3uNGosluLAW4bJly6omLg+TV2Bj5tqDvLNoN+dyC3igV2PG9Y0hxM/b7NBEMaRFKIS70NpYbaJp3FWToHA+b6uFB69twrLn4ri7cwOm/b6fPhOW883Gw9hs5jQERPUiiVAIZ0jeDmmHZO3BaiQ0yJf/3tWOeWOuJbK2P89/u407P1zNH4fPmh2aMJkkQiGcISEelAWaS+m06qZdg5rMfbwXb9/TniNnzjH4g9/567d/cDLjvNmhCZNIIhTCGXbFQ2QPCAwzOxJRDItFcVfnBix97npGX9eU7zYfpc+EZUxbtZ+8guqxarqoOjJYRghHO70P/tfRWIm755hSd589ezYA9957r7MjEyXYcyKTV+N3smL3SaLrBPGvga2JjZE/YsxgxmAZSYRCONrv/4NF/4Cnt8lq9C5Ea83iXSd4LX4nh05n0691BH8f0JLI2gFmh+ZRJBEK4Q6m3Qx52fD4qjLtfvjwYQAiIyOdGZUoo5y8Aqat2s+k3/Zg05rHr4/i8euj8PeR6jRVQRKhEK4uIwXebg5xL0LcC2X6iMwjrJ6OnT3HGwt2Eb/tOPVr+vPygJb0axMh1WmcTOYRCuHqEhcAWqZNuIFravozaXgnvh7dg2A/L56YtZkRn6xjd4pUp3E3kgiFcKSEeKjVGOq0MjsS4SA9moYS/1Qsrw5uzY5j6dz63kpemb+DtHN5ZocmHEQSoRCOkpMG+5YbtUWl+8yteFktjOrZmKXPxTG0ayQzVh+gz4RlzN5wSKrTuAFJhEI4StIisOVBS1l70F3VDvTh9TvaMn9sLE3DA3lh7nZun/w7mw+dMTs0UQkyWEYIR5lzPxxcDc8mlms1+vnz5wMwcKAkUFeitebHP47xxoJdpKSf565ODXjh1ubUCfYzOzSXJqNGhXBVeTnwVhS0vRsGvmd2NKIKZZ7P54Ole/hk5T58vayMuzGaB3o1wcdLOtwqQkaNCuGq9i+H3ExoUf5WXWJiIomJiU4ISlSFIF8vXujXgl//cj3dmtTmjQUJ9HtvBct3nzQ7NFFG0iIUwhHmjYUdPxhrD3r5luujMo/QvfyWkMKr83dy4FQ2N7Wqyz8GtKJhqFSnKStpEQrhimwFkLgQmt1c7iQo3E+fFnX55S/X8UK/Fvy+J5W+7y5nwi+JZOfmmx2aKIEkQiEq69BayE41pk0IAfh6WXkiLoqlz8XRv00Ek5bu4ca3lzP/j2OY1QsnSiaJUIjKSogHqy/E3GR2JKKaqRvix8ShHfnm8Z7UCvDhqa+2MHTqWnYdTzc7NFGIJEIhKkNrIxE2jQPfYLOjEdVU18a1mf9ULK/f0YbdKRkM+N9K/jnvT85m55odmkAGywhROce3wZTeMOh96DSqQodYvHgxAH379nVkZKKaOpudyzuLdjNz7UFq+Hvz3C3NGdq1IVaLVCMCGSwjhOtJiAdlgWa3VvgQffv2lSToQWoG+PDq4Db8NK43zeoG8/fv/2TQpFVsPHDa7NBcglKqn1IqUSm1Ryn1t2Lev04ptVkpla+Uurssx5REKERl7IqHyB4QFF7hQ2zdupWtW7c6MCjhClrWC+Hr0T14f1hHTmflcvdHaxj/9RaS03LMDq3aUkpZgQ+AW4FWwDClVNEK94eAB4Avy3pcL0cFKITHOb0PTuyAW96o1GHGjx8PyDxCT6SUYmD7a7ixZR0mL93L1BX7+HVnCk/1ieGh2Mb4esliwEV0A/ZorfcBKKW+BgYDOy/soLU+YH/PVtaDSotQiIraFW/8lGkTopICfLx47pbmLHrmOq6NDuP/fk6g38SVLE04YXZoZvBSSm0s9Bhd6L36wOFCr4/Yt1VKqYlQKRWplFqqlNqplNqhlHq6mH2UUup/9j7bbUqpTpUNTIhqL+EniGgLtRqZHYlwE41CA/l4VBdmPNgVpeDBGRt4aMYGDqR61MDCfK11l0KPqc4+YVm6RvOBZ7XWm5VSwcAmpdQirfXOQvvcCsTYH92BD+0/SxTsXQA7fwSLFZTV/tNy6efFbVajkn/hfa7YvzzvSSNYOEDmCTi8DuJeNDsS4YbimtehV1QYn60+wHtLkrj53RU83LsJY2+IJtDXo+9oHQUiC71uYN9WKaX+F9VaHweO259nKKV2YTRFCyfCwcDn2piLsVYpVVMpVc/+2WI1CMiDOfdVLvqKuizJXkiSRRPnhQRcNCmXMWH7BEFQXQiqY/wMjrj0PCAMrB79j9n1JfwEaGgxwOxIhJvy8bLw6HVNGdzhGv7v50Q+XLaX7zYf4YV+Lbi9Q30snjndYgMQo5RqgpEAhwLDK3vQcs0jVEo1BlYAbbTW6YW2xwP/1Vqvsr9eArygtd5Y5POjgdEAwf7endP3bTLqNOoCsNnsPwtAF3l+cZ/C7xXep/B7Rfe/8FMXs+3CcUo41hWxlCPO8xlGq+F8WjH/IS1GMrwsUda9/HWQPXH6Bstq59XRzLvg1B4Yt7XS38/q1asB6NWrlyMiE25q08EzvDJ/B9uOpNGqXgh/u7UF1zWr+Gjl6qq0eYRKqf7ARMAKfKq1fl0p9SqwUWv9o1KqK/A9UAvIAZK11q2ves6yJkKlVBCwHHhda/1dkffKlAgL85gJ9XnnIDPFSIqZKcYjI+XKbZkpYCumKK+Xv5EQC7coL3vUufTT6l311+eJctLgzSjo/hjc8rrZ0QgPYrNp5m87xlu/JHLkzDlio8P4260taFO/htmhOYwZE+rL1D+nlPIG5gKziiZBO6f027oFb3+o1dh4XI3NBjln7Yky+cokmZkCqUmwf6WxX3ECQgslxyKJs3CL06+mtDIrI2kR2PKgpWNWlJcWoSgri0UxuEN9+rWJYObaQ0z6LYnb3l/FoPbX8PwtzYmsLcs9VUSpLUKllAI+A05rrceXsM8AYCzQH2OQzP+01t2udlyPaRE6Q/55e6I8AZnJl7cui7Y2C85f+Xmr75WtyWJbnHVkWaHifPMAHPgdnk10yOArWY9QVFR6Th5Tlu9l2qr9FNg0I3s04qk+MdQO9DE7tAozo0VYlkQYC6wEtgMXJii+BDQE0Fp/ZE+Wk4B+QDbw4NW6RUESYZXQ2t7KPHEpOWYkF98tm32q+GP41SzSorQnyKg+xtQBT5OXA29FQdu7YeB7DjmkJEJRWclpOUxcvJs5Gw8T6OPF43FRPHRtE/x9XG9CfrVMhM4iibCaKciDrJMld8sWTqL59hJQTeOg51MQfaPndLXu/gW+HAIj5kKMY+qDSiIUjpKUksH//ZzI4l0p1A3x5S99m3F35wZ4WV1n2pgkQlH9aQ1ZqbDlC1g3xeiardMKeo41Wknu3pU6byzs+AH+utdh1yqJUDjahgOneWPBLrYcOkt0nSBe6NeCvi3roFzgD1ZZfUJUf0oZBaZ7PwPjt8HtHxrb5z0JE9vCyrch202r6NsKIHEhNLvZ/RO+cGldG9fmuyd68dHITthsmkc/38iQKWvYdPCM2aFVS9IiFJWnNez9DVa/D/uWgncAdLwPejwBtZuYHZ3jHPgdZvSHu6dDmzsddtgLK0906NDBYccU4oK8AhuzNxxm4uIkUjPP0691BM/3a05UeJDZoRVLukaF60veDms+gO3fGsUFWg407iNGdjU7ssr7+SXY8InRLSqr0QsXk3U+n2mr9jNl+V5y8m3c2zWS8TfGUCfEz+zQLiOJULiP9GPGPcSN043qOpE9oNdYaN7fKEHnarSG99pBeEsYMcehh5YV6kVVSs08z/tLkpi17hDeVguP9m7C6OujCKomNUwlEQr3cz4DtsyEtZPh7CGo3RR6PAkdRoCPC03+Pb4NpvSGQe9Dp1EOPbQMlhFmOJCaxVu/JvLTtuOEBvow7sYYhnVriI+XuUNHZLCMcD++wca9wqe2wD0zjHmJC56Dd1vDb/82pmW4goR4o0Zss1vNjkQIh2gcFsgHwzsxb8y1xNQN4v/9uIOb3l1O/LZjmNVAMou0CEXV0hoOrYHVkyBxgVEftd29xvSLOi3Mjq5kk3uBXw14aKHDDy0tQmE2rTXLEk/y34UJJKZk0L5BDf52a0t6RoVWeSzSIhTuTylo1AuGfQljN0LHkbD9G5jcHWbdA/tXGMmyOjm9D07sgJayEr1wT0opbmhRhwVP92bCPe05mXGeYR+v5YHp60lITi/9AC5OWoTCfFmpsGEarJ8K2akQ0Q56jYPWt1ePFTVWvw+/vgxPb3PKavTSIhTVTU5eAZ+tPsAHS/eQcT6fOzs24Jmbm1G/pr/Tzy2DZYRnyzsH22Yb0y9Sd0NIfeP+YqdRRrekWabdAnlZ8Pgqpxw+MTERgObNmzvl+EJU1NnsXCYv28uM1QcAeLBXY56Mi6ZGgPP+QJVEKAQYS1Il/QprJsGBleATDJ3vh+6PQ83I0j/vSJknYEIziHsR4l6o2nMLUU0cOZPNO4t28/2Wo4T4eTPmhihG9WyMn7fjp0JJIhSiqGNbjIE1O743Xre+A3o9BddUURWWjdMhfjw8/jtEtHHKKebPnw/AwIGOWd9QCGfZeSyd//s5geW7T1K/pj/P3NSM2zvWx2pxXA1TSYRClOTsIWOC/qbPIDcDGvc2EmL0TQ5ZE7BEM++CU3tg3FanrbAh9wiFq1m9J5X/LExg+9E0WkQE88KtLYhrFu6Qot4yalSIktRsCLe8Ds/sgJteg1N7jeWQJnc3kmNejuPPmZMG+5ZDi9s8Z5kpIcqgV3QY88Zcy/vDOpKdW8CD0zcw/ON1bDty1uzQKkQSoXAtfjXg2nHGyhd3fmysAjF/HExsA8vfhKwSFhiuiKRFYMsz6qUKIS5jsSgGtr+Gxc9cz78GtiIxJYNBk35n7JebOXjKtXr7pGtUuDatjbmHq9+HPYvAyx86DIeeYyA0qnLH/uYBY8WJZxOd2v0qXaPCHWTk5DF1xT4+WbmffJuNEd0b8VSfaEKDyrdkmdwjFKIyTuwyRppumwMFedBigHEfMbJ7+bs283LgrShjseGB7zknXjtJhMKdnEjP4d3FSczZeBh/byuPXdeUh3s3IcCnbEW9JREK4QgZKcbk/I3T4NwZqN/FWPmixUCwlrHC/u5fjHuQI76FmJucGu7hw4cBiIys4qkhQjjRnhOZvPlzAr/uTKFOsC/j+zZjSJcGeFmv3rsiiVAIR8rNgq1fGhP0z+yHmo2MlS86jgTfUhYlnTcWdvxgrD0oq9ELUWEbD5zmPwsT2HTwDE3DA/nrLS24pXXdEkeYSiIUwhlsBUaB79Xvw+F1xoCbLg9D98cgOKL4/Sc0g6bXw92fOj282bNnA3Dvvfc6/VxCmEFrza87U3jz5wT2nsyic6NavHhrC7o0rn3FvpIIhXC2w+uNhJgQD8oK7YYYA2vqtr60z8HVMP1WuHs6tLnT6SHJPULhKfILbHyz6QjvLtrNiYzz3NSqLi/0a050neCL+0giFKKqnN4Haz80Fg3Oy4aoG437iE1vgF/+Dhs+MbpFfYNLP1YlSSIUniY7N59PV+3no+X7yM7N596ukYzv24y6IX6SCIWoctmnYeOnxuCazBSo28aoL3pNRxgxp0pCkEQoPNWpzPO8/9seZq07iNWieCS2Kc/3ayGVZYSoUgG14brnYPx2GPyBcX8w64SxBJQQwqlCg3z516DWLH7mem5qFcGkpXtMiUNahEIUpjWcTITw5lVWVk1ahEIYth05S/vIWtI1KoSnSU1NBSAsLMzkSIQwnxn3CMs4u1gI4SySAIUwl9wjFMJkM2bMYMaMGWaHIYTHkq5RIUwm9wiFuETWIxRCCCGqmCRCIYQQHk0SoRBCCI8miVAIIYRHk8EyQpgsOzsbgICAAJMjEcJ8Mo9QCA8kCVAIc0nXqBAmmzx5MpMnTzY7DCE8lnSNCmEymUcoxCUyj1AIIYSoYpIIhRBCeDRJhEIIITyaJEIhhBAezbTBMkopG3DOlJNXDS8g3+wgnEiuz3W587WBXJ+r89daV2kjzcx5hJu11l1MPL9TKaU2yvW5Lne+Pne+NpDrc3VKqY1VfU7pGhVCCOHRJBEKIYTwaGYmwqkmnrsqyPW5Nne+Pne+NpDrc3VVfn2mDZYRQgghqgPpGhVCCOHRJBEKIYTwaKYkQqXUAaXUdqXUVjOGyjqaUupTpdQJpdSfhbbVVkotUkol2X/WMjPGyijh+v6llDpq/w63KqX6mxljRSmlIpVSS5VSO5VSO5RST9u3u8X3d5Xrc5fvz08ptV4p9Yf9+l6xb2+ilFqnlNqjlJqtlPIxO9byusq1zVBK7S/03XUwO9bKUEpZlVJblFLx9tdV/t2Z2SK8QWvdwU3mw8wA+hXZ9jdgidY6Blhif+2qZnDl9QG8a/8OO2itF1RxTI6SDzyrtW4F9ADGKKVa4T7fX0nXB+7x/Z0H+mit2wMdgH5KqR7A/2FcXzRwBnjYxBgrqqRrA3i+0He31bwQHeJpYFeh11X+3UnXqANorVcAp4tsHgx8Zn/+GXB7lQblQCVcn1vQWh/XWm+2P8/A+IWsj5t8f1e5PregDZn2l972hwb6AN/at7vk93eVa3MbSqkGwADgE/trhQnfnVmJUAO/KqU2KaVGmxSDs9XVWh+3P08G6poZjJOMVUpts3edumTXYWFKqcZAR2Adbvj9Fbk+cJPvz961thU4ASwC9gJntdYXypAdwUWTf9Fr01pf+O5et3937yqlfE0MsbImAn8FbPbXoZjw3ZmVCGO11p2AWzG6aq4zKY4qoY05Km71lxzwIRCF0WVzHHjb3HAqRykVBMwFxmut0wu/5w7fXzHX5zbfn9a6QGvdAWgAdANamBySwxS9NqVUG+BFjGvsCtQGXjAxxApTSt0GnNBabzI7FlMSodb6qP3nCeB7jH+87iZFKVUPwP7zhMnxOJTWOsX+S2oDPsaFv0OllDdGkpiltf7Ovtltvr/irs+dvr8LtNZngaVAT6CmUupCLeUGwFHTAnOAQtfWz97drbXW54HpuO53dy0wSCl1APgao0v0PUz47qo8ESqlApVSwReeAzcDf179Uy7pR+B++/P7gXkmxuJwF5KE3R246HdovycxDdiltX6n0Ftu8f2VdH1u9P2FK6Vq2p/7Azdh3AddCtxt380lv78Sri2h0B9oCuP+mUt+d1rrF7XWDbTWjYGhwG9a6xGY8N1VeWUZpVRTjFYgGKtffKm1fr1Kg3AwpdRXQBwQBqQA/w/4AZgDNAQOAkO01i454KSE64vD6FbTwAHgsUL31FyGUioWWAls59J9ipcw7qO5/Pd3lesbhnt8f+0wBlRYMf6wn6O1ftX+/5mvMboOtwAj7S0ol3GVa/sNCAcUsBV4vNCgGpeklIoDntNa32bGdycl1oQQQng0mT4hhBDCo0kiFEII4dEkEQohhPBokgiFEEJ4NEmEQgghPJokQiFcgFIq7kJ1fiGEY0kiFEII4dEkEQrhQEqpkfY15LYqpabYiyZn2osj71BKLVFKhdv37aCUWmsvnvz9hcLXSqlopdRi+zp0m5VSUfbDBymlvlVKJSilZtkriwghKkkSoRAOopRqCdwLXGsvlFwAjAACgY1a69bAcozKPACfAy9ordthVH65sH0W8IF9HbpeGEWxwVg5YjzQCmiKUatRCFFJXqXvIoQooxuBzsAGe2PNH6NYtw2Ybd9nJvCdUqoGUFNrvdy+/TPgG3sd3vpa6+8BtNY5APbjrddaH7G/3go0BlY5/7KEcG+SCIVwHAV8prV+8bKNSv2jyH4VrWtYuN5iAfL7K4RDSNeoEI6zBLhbKVUHQClVW3HRwDUAAACvSURBVCnVCOP37EI1/eHAKq11GnBGKdXbvv0+YLl9FfkjSqnb7cfwVUoFVOlVCOFh5C9KIRxEa71TKfUy8KtSygLkAWOALIxFVV/G6Cq91/6R+4GP7IluH/Cgfft9wBSl1Kv2Y9xThZchhMeR1SeEcDKlVKbWOsjsOIQQxZOuUSGEEB5NWoRCCCE8mrQIhRBCeDRJhEIIITyaJEIhhBAeTRKhEEIIjyaJUAghhEf7/2/7QYskWY8uAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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HBwcee+wxBgwYkPfMr3PnzoSFhTF06FDuvffef9V3+vRpfHx8rjnWu3dvatSo8a+y27ZtY8KECQA0bdqU5s2b552zs7PLu2ebNm346aefrvseatasSVxc5XuMVZJMkg1M0lqHAh2AJ5RSoQXK/Ay00Fq3BEYCn5ZtmGBrsOHNQc14+vb6rNgTw9ile0nLzCn+QiGs3EcffcRHH31k6TDEdTg7Xx3AuGXLFjZt2sTOnTv566+/aNWqVaF7EBbcz7C454s26enYzn6PoSmXcenejTqrV5EVFAiY9zz8/fffGTJkCOvXr6dv374ALFy4kBkzZhAdHU2bNm1ITEy8pk5HR8d/xZb/vZSU0WjM64Er7r2kp6eXqAvY2hSbCLXWp7XW+3K/vwQcBPwLlEnRV+dhOGNuOZY5pRTP9GnI6/c05edD8Tz46S6SUjPL41ZCVJiGDRvSsGFDS4chKH4PweTkZDw9PXFycuLQoUPs2rXrpu9Z8/Jl6s5fgM2+fXyUmUH6hAkY3NxYsmQJ3bp1IyUlheTkZPr37897773HX3/9BcDx48dp374906dPx8fHh+jo6GvqbdCgQYlaomBuXa5YsQKAiIgI/vmn+Gezhf2sjhw5QtOmTUt0T2tyQ32LSqkQoBWwu5Bzg5RSh4AfMLcKC7t+tFJqj1JqT3GfkIryUIdg5j/Qmv2xFxmycCdxSWmlrksIS/v+++/5/vvvLR2GALy8vOjcuTNNmzZl8uTJ/zrft29fsrOzady4MVOmTKFDhw6lvpfWmgvLV/DQ/gPYZGcT/OUX3JX7TLFZs2bY2NgwduxYLl26xIABA2jevDldunRh9uzZAEyePJlmzZrRtGlTOnXqRIsWLa6p39nZmXr16nHs2LFiYxk/fjwJCQmEhoby8ssv06RJE9zdi56/PXz4cGbOnEmrVq04fvw4WVlZHDt2LG+ATWVS4gn1SikX4FfgDa316iLK3QZM1VoXOTu4qAn1JbXrRCKPf7EHZ3tbvnysHQ18q/cyQaJykv0Ir6ouE+pNqamcmTaN5O/W4dy5M7VnvoNtIc/ubtaaNWvYu3dvsfNUc3JyyMrKwsHBgePHj9OrVy8OHz6MnZ3dDd1r3759vP766yW+plJNqFdKGYFVwFdFJUEArfVvQF2llHcZxFekDnW9WD6mIzlaM2TBDvacOl/etxRCiJuScewYJ4cOJXnd93g//RSBH39ULkkQYNCgQYSEhBRbLjU1lS5dutCiRQsGDRrE/PnzbygJgnlu4qRJk0oZqWWVZNSoAj4DDmqtZ1+nTH3guNZaK6VaA/ZAYmFly1pobTdWj+vEI4t+58FPd/PhA63pHepbEbcWQogSe+KJJ+C33xiVlU0G8IHRSC9HRx4t550dRo0aVWwZV1dX9uzZc1P3ue+++27qeksqyTzCzsBDwD9KqfDcYy8CQQBa64XAYOBhpVQWkAYM0xW4iGlgDSe+HduRkV/sYcySPbw5qBnD2wVV1O2FEKJIpowMXvb2ISkrG8e2bfB/dzZf+da0dFgiV7GJMHc+YJGz17XWbwNvl1VQpeHlYs/Xo9oz/qt9TFn9DwmXMnjy9voy8V4IYVGZUVHETJxIRsRBvB4fhc+ECbIThJWpUr8NZ3tbPn2kLc+v/Jt3fzpC/KUMXhvYBIONJENhvZYsWWLpEEQ5ufjTT5x+8SWwsSFg/nxcb+9h6ZBEIapUIgQwGmyYdV8LfFzt+ei3EyRezmD20JY4GKv2Dsui8goMDLR0CKKM6aws4t+dzfnFi3Fo2hT/OXOwC/Av/kJhEVUuEQLY2Che6N8YH1d7ZvxwkMSU3/nkkba4ORgtHZoQ/7J8+XIAhg0bZuFIRFnIOn2a2P88Q1p4OJ4PPkjN55/D5gZHYIqKVaUX6xzVtS5zhrVkb+QFhn20i/iL/14KSQhLW7BgAQsWLLB0GIKb248QYMmkSZwYNIiMI0fwn/0ufq+8/K8kGBISwrlz5bPH6tq1a5k+fXqh59atW1fsNklbtmy57v6Fc+bMITU1Ne91r169uHDhQumDtSJVOhEC3NPKn0VhtxKZeJl7F+zgREKKpUMSQlip0iZCnZNDwty5tF7/A8rLi5CVK3Hr378cIizaO++8w/jx4/91PDs7m4EDBzJlypRS110wET700EM39aHBmlTJrtGCbmvgw7LHOzBy8R8MWbiTRWG30jKw7DbQFEKUvbd/f5tD5w+VaZ2NajTi+XbPX/d8wf0IZ86cycyZM1mxYgUZGRkMGjSIadOmcfnyZYYOHUpMTAwu2dm8FxSM68mTrEu5xMrISNweG8nmzZuLjWf27NksWrQIMM/3mzhx4jV15+Tk8MorrzBs2DCmTJnCunXrrtmTML8jR45gb2+Pt7d5LZOwsDAcHBz4888/6dy5M82bN2fPnj18+OGHHD9+nAcffJDLly9z9913M2fOHFJSzI2ElJQUhgwZwv79+2nTpg1Lly7lgw8+IC4ujh49euDt7c3mzZsZOHAgXbt25aWXXirtr8NqVItECNAi0IOV4zrx8KLd3P/xLhaMaE33hjKPRwhxVcH9CDdu3MjRo0f5/fff0VozcOBAfvvtNxISEqhduzbfvvYasc9MIjsujlpvvMFHk55hz5YtecmoKHv37uXzzz9n9+7daK1p37493bp148SJE9SuXZsffvgBMC/0nZiYyJo1a/61J2F+27dvp3Xr1tcci4mJYceOHRgMBhYvXpx3fMKECUyYMIH777+fhQsXXnPNn3/+yYEDB6hduzadO3dm+/btPP3008yePZvNmzfnvTdPT08yMjJITEz81zZUlU21SYQAdbydWTWuE2GL/mDUF3t4Z0hz7m0dYOmwhBCFKKrlVlE2btzIxo0badWqFWBuLR09epQunTuz67nnObltO6aaNbllxXIcGjaESc+UuO5t27YxaNCgvK2R7r33XrZu3Urfvn2ZNGkSzz//PAMGDKBr165kZ2cXuidhfoXtP3jfffdhKGTlmp07d7J27VoAHnjgAZ599tm8c+3atSMgwPx3sWXLlpw6dYouXboU+h6u7D9Y2RNhlX9GWFBNVweWj+nArSE1eGbFX3z823FLhySquZUrV7Jy5UpLhyEKobXmhRdeIDw8nPDwcI4dO0bY4ME4zXmfkUYjSY0b8awph3dyR/6WhQYNGrBv3z6aNWvGyy+/zPTp06+7J2F+ZbX/4I3spVhZ9x8sqNolQgBXByOLR97Knc1q8eaPh5ixPgKTqcJWhBPiGt7e3iXqShPlr+Aee3fccQeLFi3Ke34W9fPPHLtnECnbtuE15Xk6rVrFU88/z759+wq9vihdu3Zl7dq1pKamcvnyZdasWUPXrl2Ji4vDycmJESNGMHnyZPbt23fdPQnza9y4cYm2XALo0KEDq1atAuCbb74p0TUF35vWmjNnzpRoUW9rV626RvOztzUw9/5WeLvY8em2k5xLyeCdIS2ws62Wnw2EBV15dhMWFmbROMS1+xH269ePmTNncvDgQTp26EBfk+ZhkwnbmjU58/RTDJs9G5s5czAajXnTX0aPHk3fvn2pXbt2sYNlWrduTVhYGO3atQPMg2VatWrFhg0bmDx5MjY2Nnl1X7p0ibvvvpv09HS01nl7EuZ32223MWnSJLTWxS4tOWfOHEaMGMEbb7xB3759i917sLD3tnfvXjp06IBtFVgursT7EZa1stiPsCxorZm/5TgzNxym6y3eLBzRBmf7yv+LFZWH7Ed4lTXuR5iTksLpl1/h0v/+h0v37tR+678YPKxz1PmECRO466676NWryO1gSU1NxdHREaUU33zzDcuWLeO777674XsNHDiQnj17ljpea9mPsNr/xVdK8USP+vi42PPCmn+4/5NdLAq7FW8X++IvFkJUaemHDxP79AQyY2LwmfQMXo89hrKx3l6jF198kd27dxdbbu/evTz55JNorfHw8MibwnEjmjZtelNJ0JpU+xZhfpsizvLE1/uo5e7AksfaE1jDydIhiWpAWoRXWVOLMGnVKs5Mfx2Dmxv+s9/F6dZbb+j69u3bk5GRcc2xJUuW0KxZs7IMs1KTFqEV6hXqy9ePt2fk4j3cu2AHix+9lSa1i+87F0JUHaa0NM5Mf53kNWtw6tAB/1kzsS3FYKaStMzEjVNK9QXeBwzAp1rrf60bp5QaCrwGaOAvrfUDRdVpvW18C2kTXIOVYztia6MY9tEudhwvnzUBhRDWJ+PESU4NHUby2rV4jx9H0GeflioJivKhlDIA84B+QChwv1IqtECZW4AXgM5a6ybAxOLqlURYiFt8XVk9vhO13B0IW/QHP/x92tIhiSrsxx9/5Mcff7R0GNXexR9/5NSQIWQnJBD48cf4PP00qpDJ6MKi2gHHtNYntNaZwDfA3QXKPA7M01pfANBaxxdXqSTC66jl7si3YzvSPMCdJ5ft44sdpywdkqiinJyccHKS59GWYsrM5Mz014l9ZhL2DRtSZ81qXLoWvpKKqBC2Sqk9+b5G5zvnD0Tnex2Teyy/BkADpdR2pdSu3K7Uom948zFXXR5Odiwd1Z4nv/6TV9cdIOFSBpP6NCh2jo4QN+LKCv6F7RogyldmTCyxEyeSvn8/NR59lJrP/AdllH1LLSxba932Jq63BW4BugMBwG9KqWZa638v0JpLWoTFcDAaWDiiNcNvDeTDzceYsuofsnNMlg5LVCErVqxgxYoVlg6j2rn0y2ZO3nsvmZGRBHz4Ab7PP1fuSbB///6FLphd1sLDw4vsbv/zzz957LHHCj23Z88enn766SLrP3XqFE2bNi303OLFi4mLi8t7PXz4cI4ePVqCqEskFgjM9zog91h+McA6rXWW1vokcARzYrwuSYQlYGuw4b/3NuOp2+uzfE80Y5fuJS0zx9JhCSFKQWdlET9rFjHjx2MM8KfOqpW4FjMBvaz8+OOPeFTAZPziEuGbb75ZaLLLzs6mbdu2zJ07t9T3LpgIx40bxzvvvFPq+gr4A7hFKVVHKWUHDAfWFSizFnNrEKWUN+au0hNFVSpdoyWklGJSn4bUdLVn6roDjPhsN5890hYPJ7viLxZC3LAzb75JxsGy3Y/QGBxE5slTpO3di8ewYfi++AI29tcunnHPPfcQHR1Neno6EyZMYPTo0SxcuJDjx48zc+ZMwPzH/srefkuXLmXu3LlkZmbSvn175s+fX+iOD2DenX7Pnj2kpKTQr18/unTpwo4dO/D39+e777677gLW4eHhjB07ltTUVOrVq8eiRYvw9PSke/fuzJo1i7Zt23Lu3Dnatm3LkSNHmDp1KmlpaWzbto0XXniBYcOG5dV16dIl/v77b1q0aAHAa6+9xvHjxzlx4gRBQUGMGTOGWbNmsX79ehISEnjggQeIi4ujY8eO/PTTT+zduxeAnJwcHn/88Wvi/+GHH9izZw8PPvggjo6O7Ny5k65duxIWFkZ2dvZNL8emtc5WSj0JbMA8fWKR1vqAUmo6sEdrvS73XB+lVASQA0zWWicWVa+0CG/QQx1DmPdAa/6JSWbIwp3EJaVZOiQhRAnkJCdzcf160g8epPbMd6g17bV/JUGARYsWsXfvXvbs2cPcuXNJTExk8ODBrFmzJq/M8uXLGT58OAcPHmT58uVs376d8PBwDAYDX331VYniOXr0KE888QQHDhzAw8MjbxHswjz88MO8/fbb/P333zRr1oxp06Zdt6ydnR3Tp09n2LBhhIeHX5MEwdz1WbBbMyIigk2bNrFs2bJrjk+bNo3bb7+dAwcOMGTIEKKiooqMf8iQIbRt25avvvqK8PBwHB0dsbGxoX79+oUuFF4aWusftdYNtNb1tNZv5B6bmpsE0WbPaK1DtdbNtNbFriouLcJS6N+sFh5ORsZ8uZfBC3bwxch2NPB1tXRYQlQpfi++WCb16Jwczi1YyLl587CrV5eA99/Hvl6965afO3duXtKLjo7m6NGjdOjQgbp167Jr1y5uueUWDh06ROfOnZk3bx579+7l1txVZ9LS0qhZs2QbftepU4eWLVsC0KZNG06dOlVoueTkZJKSkujWrRsAjzzyCPfdd19J3/6/FLZv4cCBAwttjW7bti3vZ9G3b188PT1vOH64um9hmzZtSh13eZJEWI3iExQAACAASURBVEqd6nmzfExHHvn8d+5buJPPHmlL25Aalg5LVEKytFr5yT5/nrjJz3F5+3bcBt5Frddew6aIqSpbtmxh06ZN7Ny5EycnJ7p37563x9/w4cNZsWIFjRo1YtCgQSil0FrzyCOP8N///veGYyu4719a2o33Ltna2mIymQfvFdyL8HrKa9/CouK39n0LpWv0JoTWdmP1uE7UcLbjwU9381PEWUuHJITIlbpvHycH3UvqH3/gN30atd9+u8gkCObWl6enJ05OThw6dIhdu3blnRs0aBDfffcdy5YtY/jw4QD07NmTlStXEh9vnrN9/vx5IiMjy/R9uLu74+npydatWwHzeqVXWochISF5z+zyb+5c1L6IN7JvYefOnfNGNG/cuJELFy4Ue01h9z5y5Mh1R5laA0mENymwhhMrx3akkZ8rY5bs4Zvfo4q/SIh8Zs2axaxZsywdRpWhtSZx0edEPvQwyt6ekG+W4Tl0aInm//bt25fs7GwaN27MlClT6NChQ945T09PGjduTGRkZN4egqGhocyYMYM+ffrQvHlzevfuzenTZb8S1RdffMHkyZNp3rw54eHhTJ06FYBnn32WBQsW0KpVK86du7ocZI8ePYiIiKBly5YsX778mroaNWpEcnJyiTYQfvXVV9m4cSNNmzbl22+/xc/PD1fXoh8DhYWFMXbsWFq2bElaWhpnz57F0dERPz+/UrzziiG7T5SRyxnZjPtqH78dSWBS7wY8eXt9mXgvSkR2n7jqZnefyLl4kbgXXiTl559x7d2bWm++gaGYP9zV0XvvvYerqyujRo0qslxGRgYGgwFbW1t27tzJuHHjCA8Pv+F7ubm5FTpvUXafqGKc7W359OG2PL/qb9796Qjh0Un0b1aL7g198JK9DYUod9nnzxP16Egyjh/H94UpeD78sHwYvY5x48bx7bffFlsuKiqKoUOHYjKZsLOz45NPPrnhe3l4ePDQQw+VJswKIy3CMmYyaeb+cpSlu6I4l5KBUtAiwIPbG9Xk9kY1Ca3lho2N/OMUV0mL8KrStgiz4uOJenQkWbGxBHz4IS5dOpdDdCVX2r0In3jiCbZv337NsQkTJvDoo4+WeYzWwFpahJIIy4nJpNkfl8wvh+LZfCiev2KSAfBxtadHQx9ub1STLrf44GIvjfLqThLhVQcPHqRRo0Y31JLLOn2ayLAwshPOEbhwAc65z++EddNac+jQIatIhPJXuJzY2CiaB3jQPMCDib0akHApg1+PJLD5UDz/988ZVuyJwWhQ3BpSg9sb1aRHo5rU9XaWrpxqyJqHlVc0BwcHEhMT8fLyKtG/hcyYGKIeCSMnOZmgTz/FqXWrCohS3CytNYmJiTg4OFg6FEBahBaRlWNib+QFNh+K55dD8RyNTwEg2MuJHg3NSbF9nRo4GGUvNFG9ZGVlERMTU7I5cXFxMPVVyMiAV6dC/frlH6AoMw4ODgQEBGAssNC5dI1WU9HnU9l82NyFuuN4IhnZJhyNBjrX985tLfpQy11aDUJckXHsGJGPPgrZOQR9vgiHRo0sHZIoI5IIBWmZOew8cS732WICsblrmTbyc80bcNMy0ANbg0wBrSpef/11AF555RULR1I5pB86RNTIx8BgQ/Dnn2MvLcEqRRKhuIbWmqPxKfyS24W6N/ICOSaNh5OR224xD7jp1sAHT2fZAaMyk8EyJZf2z36iRo3CxtGRoM8XYV+njqVDEmVMBsuIayilaODrSgNfV8Z2q0dyahZbjyXwy6F4fj2cwLq/4rBR0CrIkx4NfeiROz1DBtyIqij1zz+Jfnw0Bnd3gr5YjF1AgKVDElWEtAgrKZNJ81dMEpsPm0ei/hNrnp7h5+ZAj0Y+dG9Yky71vXGW6RlWT1qExUv94w+ix4zF4ONN8OLFGGvVsnRIopxI16gotfiL6Ww5nMDmw/FsPXqOlIxs7Aw2tK9bgx4Nzc8WQ7wr9P8tUUKSCIt2eccOosc/gdHfn6DPF2Es4TZHonKSRCjKRGa2iT2nzpufLR6O50SC+edc19uZ7rlJsV2dGtjZyoAbazB48GCAIjdmra4ubdlC7NMTsAsJIejzRdh6eVk6JFHOJBGKchGZeNk8Z/FwArtOJJKZbcLZzkCXW7zz5i36ulnHxFYhrrj400/EPjMJhwYNCPz0E2zzbQorqi5JhKLcpWZms/1YYt68xdPJ5onLTWq7cXujmnRvaJ6eYZD1UIUFXfzxR2InP4dj06YEfvIxBjc3S4ckKogkQlGhtNYcOnOJXw7Fs+WweXqGSUMNZzu6NTCPQu12iw/uTsbiKxOl9sILLwCUapfzqihpzVpOv/QSjq1bEbjwIwwu8my7OpFEKCwqKTUzbz3UX48kcCE1CxsFbYI96ZE7mb+hr6tMzyhjMljmqgvLV3Dmtddw7tiBgA8/LHZHeVH1SCIUViPHpAmPTspbDzXi9EUAars70L1RTXo39qVTfS/sbWU91JslidDs/JKlnH3jDZy73UbA3LnY2Ms+ntWRJEJhtc4kp7PlsDkpbjt2jtTMHJztDHRvVJM7mvjRvaEPbg7ShVoakggh8bPPiJ85C5dePfGfPRsbO1ktqbqSRCgqhYzsHHYcS2RjxBl+ijjLuZRMjAZFp3re9GniS+9QX2q6yijUkqruiTBh/nzOzf0At/79qP322yijfKCqziQRikonx6T5M+oCGw6cYcOBs0SdT0UpaBXowR1N/OjTxI86MpG/SCNGjABg6dKlFo6kYmmtSZjzPokffYT73XdT6803UAbpaq/urDIRKqUCgS8BX0ADH2ut3y9Q5kHgeUABl4BxWuu/iqpXEmHVo7Xm8NlLbDxwlg0HznAgzvxcsYGvC31C/bijiR9N/WUtVGH+fyX+7Xc4v3gxHvfdh9+011A2ssCDsN5EWAuopbXep5RyBfYC92itI/KV6QQc1FpfUEr1A17TWrcvql5JhFVfzIVUNh44y8aIM/x+8jwmbR5s06eJH31Cfbm1Tg2Msp1UtaNNJs7OmMGFr5fhOWIEvi+9KB+ORB6rTIT/ukCp74APtdY/Xee8J7Bfa+1fVD2SCKuX85cz+fngWTYcOMvWowlkZJtwdzTSs3FN+oT60a2BD4521bNbbOLEiQDMmTPHwpGUP52Tw+lXXyV55SpqPDaSms8+K0lQXMPqE6FSKgT4DWiqtb54nTLPAo201qMKOTcaGA1gZ2fXJiMjoxQhi8ouNTOb344ksPHAWTYdPMvF9GwcjDZ0vcWHO5r40bNRzWq1x2J1GSyjs7OJe/FFLq77Hu/x4/B+6ilJguJfrDoRKqVcgF+BN7TWq69TpgcwH+iitU4sqj5pEQqArBwTv588z8YDZ9gYcZbTyekYbBTtQmrQp4kvfZr44e/haOkwy1V1SIQ6K4vYyc9x6X//w2fiBLzHjrV0SMJKWW0iVEoZgfXABq317OuUaQ6sAfpprY8UV6ckQlGQ1pp/YpPZcOAMGw+c5Wh8CgBN/d24I9Q8ArWBr0uVa0VU9URoyswkduJ/SPnlF2o+/zxej4ZZOiRhxawyESrzX50vgPNa64nXKRME/AI8rLXeUZIbSyIUxTmRkMLGCPMI1D+jkgAI8XKiTxM/7mjiS6tAT2yqwOLgVTkRmtLTiXnqaS5v3YrvKy9T48EHLR2SsHLWmgi7AFuBfwBT7uEXgSAArfVCpdSnwGAgMvd8tta6bVH1SiIUNyL+YjobI86yMeIsO4+fIytH4+1iT+9QX+5o4kvHepV3ubfRo0cD8PHHH1s4krJlSk0levwTpO7ejd/0aXjed5+lQxKVgFUmwvIiiVCUVnJaFlsOx7PxwFm2HI7ncmYOLva29GhUkz6hvnRv6IOrLPdmUTkpKUSPGUvan39S+63/4j5woKVDEpWEJEIhblB6Vg47jp9j44Gz/BRxlsTLmdgZbOhU34s+oX70DvXFx1UWb65IOcnJRD0+mvSICPxnzcStb19LhyQqEUmEQtyEHJNmX9QFNuw/w4aIM0SfT0MpaB3kyR1NfOkT6keIFS73VpW6RrMvXCDqscfIPHoM/znv4dqzp6VDEpWMJEIhysiVTYevrGxzZbm3hr6u9Gniyx1N/GhS2zqWe6sqg2Wyz50j6tGRZEZFEfDhB7h07WrpkEQlJIlQiHISfT6Vn3JHoP5xyrzcm7+HI71DfenTxJd2ITWwtdByb1UhEWadPUtU2KNknTlD4Px5OHfsaOmQRCUliVCICnD+ciabDp5lY77l3jycjPRsZB6B2vWWil3urbInwqzYWCLDHiXn/HkCP1qIU9siB4wLUSRJhEJUsMsZ2Ww9msCGA2f5OXe5Nyc7A58+0pZO9bwrJIbKnAgzo6KIDAvDdCmFoE8/wbFFC0uHJCo5SyRC24q8mRDWxtnelr5Na9G3aS2yckzsPnGeF9f8wytr9/O/ibdVyO4YLVu2LPd7lIeMEyeJCgtDZ2YStPhzHJs0sXRIQpSKtAiFKGBTxFlGfbmHqQNCGdmljqXDsUrpR44QNfIx0JqgRYtwaNjA0iGJKsISLULZDE6IAno2rsltDXx4b9MRElNkh5SC0iMiiHr4EZRSBC/5UpKgqPQkEQpRgFKKqQMak5qZw7s/Fbt+/E0bMWIEI0aMKPf7lIW0v/8mMuxRlJMjwUuXYF+3rqVDEuKmSSIUohD1a7rycMdglv0exYG45HK9V0xMDDExMeV6j7KQum8fUY+OxODuTsiSJdgFB1s6JCHKhCRCIa5jYs8GeDgamf59BJZ6lm4tLu/aTdSox7H18SF4yZcY/f0tHZIQZUYSoRDX4e5kZFKfhuw+eZ7/23/G0uFYTMrWbUSPGYOdf21zEvTzs3RIQpQpSYRCFOH+dkE08nPljR8Okp6VY+lwKtylX34hZvx47OrWJejLL7H18bF0SEKUOUmEQhTBYKOYelcosUlpfPLbiXK5R8eOHelohUuSXfzfBmKenoB9o0YEL/4cW09PS4ckRLmQeYRClMC4pXvZcjiBX57tRi13R0uHU+6Sv/+euOen4NiyJYEff4TBxcXSIYlqQuYRCmGlXuzfmBytefv/Dlk6lHKXtGoVcc89j1PbtgR98rEkQVHlSSIUogQCazgx5ra6rA2PY2/k+TKte/DgwQwePLhM6yytC8uWcfqll3Hu1InAjxZi42x9+zcKUdYkEQpRQuO618PPzYFp30dgMpXdI4XExEQSExPLrL5Sx7F4MWemTcelRw8C5s/DxrHqdwELAZIIhSgxJztbpvRrxN8xyazcZ/0T4G/EuY8+Jv6tt3Ht04eA9+dgY29v6ZCEKJRSqq9S6rBS6phSakoh58OUUglKqfDcr1HF1SmJUIgbcHfL2rQO8uCd/x3mUnqWpcO5aVprEuZ+QMJ77+E2YAD+s99F2dlZOiwhCqWUMgDzgH5AKHC/Uiq0kKLLtdYtc78+La5eSYRC3AClFK/e1YRzKRl8uPmYpcO5KVprEt59l3Pz5+N+773UfvstlK3szCasWjvgmNb6hNY6E/gGuPtmK5VEKMQNahHowZA2ASzadpKT525+ClDPnj3p2bNnGURWclprzr75XxI//QyP+4dTa8brKIOhQmMQ4jpslVJ78n2NznfOH4jO9zom91hBg5VSfyulViqlAou7ocwjFKIU4i+m02PWFjrW8+bTR9paOpwbok0mzkybTtLy5dR45GFqTpmCUsrSYQkBFD2PUCk1BOirtR6V+/ohoL3W+sl8ZbyAFK11hlJqDDBMa317UfeUFqEQpVDTzYEnb7+FTQfP8tuRBEuHU2I6J4fTL71M0vLleI0eLUlQVDaxQP4WXkDusTxa60St9ZWNRD8F2hRXqSRCIUppZJcQgr2ceH19BFk5plLX069fP/r161eGkRXOdPkyMU8+RfKaNXg/9SQ+/5koSVBUNn8Atyil6iil7IDhwLr8BZRStfK9HAgcLK5SSYRClJK9rYGX7wzlaHwKX+2KLHU9aWlppKWllWFk/5Z1Np7Ihx4m5ddf8X3lZXyeeEKSoKh0tNbZwJPABswJboXW+oBSarpSamBusaeVUgeUUn8BTwNhxdUrzwiFuAlaax5e9Dt/RSexZXIPajjf+NSD7t27A7Bly5ayDS5X+qFDRI8dh+niRfzfm41Lt27lch8hyoKsNSpEJaOU4pUBoVzOzGH2T4ctHc6/pPz2G5EPPAhaE/zVUkmCQhRCEqEQN6mBrysPdQjm691RHDx90dLh5LmwbBnRY8dhDA4mZMVyHBo3tnRIQlglSYRClIGJvW7BzdHI9O8juNHHDQMGDGDAgAFlFovOyeHsW2+b1w3t2pWQpUsw+vqWWf1CVDXyjFCIMrJk5yle+e4AC0e0pm/TWsWWLw+m1FRiJz9Hys8/4zliBL4vTJGJ8qJSkWeEQlRi97cLoqGvKzN+OEh6Vk6F3z8rPndk6ObN+L74In4vvyRJUIgSkEQoRBmxNdgw9a5QYi6k8dm2kyW+rnv37nkjR0sr/fARTg0bTsbJkwTM+5AaDz90U/UJUZ1IIhSiDHWu780dTXyZt/kYZ5LTK+SeKVu3EfnAA5CTQ8jSJbj26FEh9xWiqpBEKEQZe6l/KNkmzTv/O1Tu97rwzXKix47FGBhoHhkaWtiONEKIokgiFKKMBXk58XjXOqz+M5Z9URfK5R7aZOLsOzM589prOHfpTPDSpRj9/MrlXkJUdZIIhSgH47vXp6arPdPWHcBkKtuR2aa0NGInTOT8okV4PnA/gfPmYXCp0EF2QlQpsgunEOXA2d6WKf0a8cyKv1j9ZyxD2gRct+zQoUNLXG92QgLR458gff9+fF+YgufDD8uaoULcJJlHKEQ5MZk09y7YQWxSGpuf7Y6L/c197sw4epToMWPJvnAB/1kzca3gzXyFqAgyj1CIKsTGRvHqXaEkXMpg3uZj1y2XmppKampqkXWlbN/OqfsfwJSVSfCSJZIEhShDkgiFKEetgjy5t7U/n209SWRi4T0g/fv3p3///tet48KKFUSPHoOxdm3qLF+OY9Mm5RWuENWSJEIhytnzfRtha1C88UOx+4NeQ5tMxL/7Lmemvopzx44Ef/0Vxtq1yylKIaovSYRClDNfNwee6FGfjRFn2Xb0XImuMaWnE/ufZ0j85FM8hg0jcOECDC4u5RypENWTJEIhKsBjXeoQVMOJ6esPkJ1jKrJsdmIikY88wqWNG6n53HP4vfYqylYGeAtRXiQRClEBHIwGXrqzMUfOpvDV7qjrlss4doxTQ4eRcfgI/nPfx2vkozI9QohyJh8zhaggfUJ96Vzfi9k/HWFgi9p4OtsBEBYWBsDlnTuJeXoCyt6e4CVf4tismQWjFaL6kBahEBVEKcXUAU24lJ7Fe5uO5B0PCwvjHldXoh4fjdHPlzrLv5EkKEQFKjYRKqUClVKblVIRSqkDSqkJhZRppJTaqZTKUEo9Wz6hClH5NfRzZUSHYJbuiuTQmYtok4lTb7zB6ZdexrldO4K//hqjv7+lwxSiWil2ZRmlVC2gltZ6n1LKFdgL3KO1jshXpiYQDNwDXNBazyruxrKyjKiuLlzOpPusLbTwceDNI2u49L//sdXRkcd/340yGi0dnhAWZYmVZYp9Rqi1Pg2czv3+klLqIOAPROQrEw/EK6XuLK9AhagqPJ3teK59TRymT+HS+UhWu7rwk5MToyUJCmERN/SMUCkVArQCdpfmZkqp0UqpPUqpPdnZ2aWpQohKL+PECdq/+xz1k+P4qMcoNjg5gYwMFcJiSpwIlVIuwCpgotb6YmluprX+WGvdVmvd1lbmRYlq6PLu3zk1/H5Mqamkvf0Ba90bVdhO9kKIwpUoESqljJiT4Fda69XlG5IQVVPSmrVEjRqFbU0fQpYvp8OAbvQJ9SU2KY3MYibZCyHKT7HNMmWezfsZcFBrPbv8QxKiatFakzB3LokLFuLUsQMB77+Pwc0NgJfubMz3a/pTI7iGhaMUovoqyajRLsBW4B/gysfWF4EgAK31QqWUH7AHcMstkwKEFtWFKqNGRXVgysjg9IsvcfGHH3AfMphar776r5Ghb//vEAu2HGfN+E60CvK0UKRCWAdLjBqVjXmFKCfZFy4Q88STpO3bh88zz+D1+KhCl0s7dOwkwz7aSZ2QYFaP64SNjQycEdWXbMwrRBWRcfIkp4YNJ33/fvzfm4336Mevu2bo2FGPkv3LB4RHJ7E2PLaCIxVCSCIUooyl/vGHeWTopUsEfbEYt379ir3Gx9WeFgHuvPV/h7icIVOLhKhIkgiFKEPJ331H5MjHsPXyImTFcpxatSrxtVPvakL8pQzmbzlWjhEKIQqSRChEGTCPDP2AuOen4NS6NSHLvsYuMPCG6mgT7MmgVv58svUkUYmp5RSpEKIgSYRC3CRTZiZxzz3PufnzcR80iKBPPsbg7l6qup7v2whbG8WbPx4s4yiFENcjy7sIcROyL1wg5qmnSNuzF5+JE/EaM/qGN9KdNGlS3vd+7g480aM+MzccZsexc3Sq713WIQshCpDpE0KUUuapU0SPGUvW6dPU+u+buN9ZNmvOp2fl0Gv2r7jY27L+qS7YGqTjRlQfMn1CiEoidc8eTg0bTk5yMkGLP7+pJHj48GEOHz6c99rBaODlOxtz6Mwllv0eVRbhCiGKIIlQiBuU/P16oh4dicHTk5Dl3+DUuvVN1TdmzBjGjBlzzbE7mvjRsa4X7/50hKTUzJuqXwhRNEmEQpSQ1pqEefOImzwZx5YtCflmGXbBweVyL6UUU+8K5WJaFnM2HS2XewghzCQRClECpsxMTk+ZwrkPPsT97rsJ+uxTDB4e5XrPxrXceKB9EEt2RXLk7KVyvZcQ1ZkkQiGKkZOURPRjo0j+bh3eTz9Frbf+i7Kzq5B7P9O7Ic52Bl5fH4GlBrYJUdVJIhSiCJlRUZwafj9p4eHUnvkOPuPH3/D0iJtRw9mO//RuwNaj59h0ML7C7itEdSLTJ4S4jtR9+4h54kkwmQiY9yFObduWy302bdoEQK9evQo9n5Vjot/7W8nKMbHxP7dhb2solziEsAYyfUIIK5H8ww9EhT2KjZureWRoOSVBMCfA6yVBAKPBhqkDQolMTOXz7afKLQ4hqitJhELkMqWlkX74CAlz5xI36Vkcmjcj5JtvsAsJKdf7hoeHEx4eXmSZ2xr40KuxLx/8fJT4S+nlGo8Q1Y10jYpqxZSaSmZUFJmRUWRGRpIZFUlW7vfZ8VefwbnddRe13piBTQUMiunevTsAW7ZsKbLcqXOX6f3er9zd0p9Z97Uo97iEsARLdI3KWqOiyslJuUxWdG6ii4wiMyqSzEhzwstOSLimrMHLC7ugIJw7dcIuOAhjUBD2deti36hRhQ6KKYkQb2dGdqnDR7+e4KEOwbQILN/pG0JUF5IIRaWUk5JCVlS+ZBcZaW7pRUWSk3DumrIGH2/sgoJx7tIFu+DgvIRnFxyMwcXFQu+gdJ7sUZ9Ve2N57fsDrB7XyeqStRCVkSRCYbVyLl0iMzKKrNwWnbl1Z056OYmJ15S19fHBGByEy223YRcUfDXhBQZhcKnQXpZy5epg5Lm+DXlu5d98Fx7HPa38LR2SEJWeJEJhUTkXLxb6vC4zKoqc8+evKWvr64tdUBAuPbqbE12QOdnZBQZi41x1kl1xhrQOYMnOSP77fwfpHeqLs738MxbiZshgGVHucpKTzS25U5HXPK/LjIoi58KFa8ra+vlhl9ttebULMwS7wABsnJws9A7K144dOwDo1KlTia/ZG3mewQt28tTt9ZnUp2F5hSZEhbPEYBlJhKJM5CQlXX1Od+rq87qsU5HkJCdfLagUtrX8zK25ggkvKAgbBwfLvYlKZsI3f/J/+8/w8zPdCKxRNT8kiOpHEqGwWtpkIjs+nqyYGLJiY695XpcZFYWpQLIz1qqFMTjo2i7M4GCMAQGS7AooTYsQ4HRyGrfP+pUejXyY/2Cb8ghNiAoniVBYjNaanAsXyIqNJSsmhsyYGLJizN9nxcSQFReHzsq6eoGNDcZatczJrUDCMwYGVsj8u6qipPMIC/PBz0d596cjLHu8Ax3reZVtYEJYQHGJUCnVF3gfMACfaq3fuk65wcBK4Fat9Z6i7ilP2auRnJTLZMXG5CW3zPyJLjYWU2rqNeUNHh4YAwKwb9wY1969MAYEYPQPwBjgj9HfX5KdFXj8trp880c0074/wPqnumBrkMWiRNWllDIA84DeQAzwh1JqndY6okA5V2ACsLsk9UoirEJMGRlkxcblJbuCrbprntUBNk5O5uQWGIhTxw7YBQRcTXb+/lVq2kFV5WA08NKdjRn/1T6++SOaER3KZ6NgIaxEO+CY1voEgFLqG+BuIKJAudeBt4HJJalUEmElorOzyTpzNrcFVyDRxcZes0QYgDIaMfr7YwwIwKFZ03yJznzM4OEhE7KrgH5N/WhfpwbvbjzMXc1r4+5ktHRIQtwMW6VU/q7Mj7XWH+d+7w9E5zsXA7TPf7FSqjUQqLX+QSklibCy0VqTnZBgTm75W3WxceZkd/o05ORcvcDGBqOfH8aAAJy7dMHoX/tqsgsIwNbHB2UjXWVVnVKKqXeFctcH25jz8xFevauJpUMS4mZka61Ltd2LUsoGmA2E3ch1kggrkNYaU3Ly1WdzsbkjMK+07GJj0RkZ11xj8PHGzj8AxxYtcLvzTowB/leTnZ8fyiif/iu7OXPm3HQdTWq7M7xdEF/ujOSBdkHc4utaBpEJYXVigcB8rwNyj13hCjQFtuT2dvkB65RSA4saMCOjRstBVnw86QcO5HVbZsZe7cI0paRcU9bG3d3ckvO/0pLzv6YLU6YaiJJKTMmg+6wttAz04MuR7aTbW1RKRY0aVUrZAkeAnpgT4B/AA1rrA9cpvwV4VkaNVhBTRgYpv/xC0uo1XN6+HUwmAJSDgzm5+Qfg1KbNtcnO3x+Dm5uFvLgQFwAAIABJREFUIxeWVtwO9SXl5WLPxF4NeH19BL8ciqdnY9+yCE8Iq6G1zlZKPQlswDx9YpHW+oBSajqwR2u9rjT1SovwJmitSd9/gOQ1q0n+4UdMycnY+vnhfs/duHTrhl1gIAYvL/lkLop0M/MIC8rKMdF3zm/kmDQb/9MNO1t5RiwqF9mPsJLIPneO5HXfk7xmDRlHj6Ls7XHt1Qv3ewfh3KEDymCwdIiimjIabJh6VxMeWfQ7i3ecZPRt9SwdkhBWTxJhCenMTC79+ivJq9eQ8ttvkJODQ4vm+L32Gm79+0kXp7Aa3Rr40LNRTeb+fIx7WvlT01WeMwtRFEmExUg/dIik1au5+P16ci5cwNbHB69Hw3AfNAj7evJpW1inl+5szB1zfmPWhsO8M6SFpcMRwqpJIixE9oULXPx+PUlr1pBx8CDKaMSlZ088Bt2Dc+fOKFv5sQnrVtfHhUc71+GTrScY0SGY5gEelg5JCKslg2Vy6exsUrZuJXn1/7d33+FRlWkfx79PJr3TEkqCdEhAmoBSFBRWASmCIlJUbIjddYsVG7rqvuyu7q7YWVRQQKULSlFQEelIC6FDCIEQCOl15nn/OJMwoSQhmcmZmdyf68qVzMzJOfdhEn45z3nKfLJWr4aiIgLbtydixAjCbx6Mb506ZpcovFRiYiIAbds6d13BzPwibpi6mivqhfD1pJ7SaUt4BFl9wgQF+/dzdt58MhYtwpqWhqVuXSKGDiVi5AgCnfwfkxA1bc7Gozz9zQ7euaMzwzs3MbscISokQVhDrBkZZC5dytn5C8jfvh18fQnt25fIkSMIve46ma1F1KjFixcDMHToUKfv22rTDH/3F05nF7LqT30J9pdmfeHeJAhdSFut5Py6joz588lauRJdWEhAmzZEjBxBxNCh+NaTtdyEOZw5jvBiNh4+w6j31/F4/9Y89Yc2LjmGEM4i4whdoODQITIWLCRj4UKKT5zAEhFB5KhRRtNnfLzcNxFer3uzugzt1JgP1hzg9m4xxNQJNrskIdyKVwahNTubzGXLyJi/gLwtW8DHh5Br+xD9zDOE3nC9LCgrap1nB7Vjxe4TvLFsD++O7Wp2OUK4Fa8JQm2zkbthAxnz55P5/XJ0fj7+LVoQ9ec/ET5sGH5RUWaXKIRpGkcG8VDfVvxr5V7uvOY017SQWwFClPD4ICw8doyM+QvIWLCAouRkfMLCiBg+nMiRIwjs2FGaPoWwm3hdC+ZuSuKVxbtZ8lgfLD7yuyEEeGhnGVtuLpnLl5Mxbz65GzaAUoT07EnEyJGEDegvSxcJj5KUZCy4HRsbW8GW1bdk+3Ee/WIrU4a3586ezVx+PCEul/QaLYfWmrwtWzg7bx5Zy77DlpuL3xVNiRwxgojhw/Fr1MiF1QrhHbTWjPt4PTuTM/jhz/2oHxpgdklClCFBeBFFKSlkLFzI2fnzKTpyFJ/gYMIGDSRy5EiCunaVpk/h8ebMmQPA6NGja+R4+1OzGfTOTwzr1IR/3C7zkAr34pZBqJSKBT4DogENfKi1fue8bRTwDjAYyAUmaK23lLff8oLQlp9P1oqVZMyfT866daA1wT16EDFyBOE33ohPsHT/Ft7D1eMIL+at7/bw3uoDfDWpJ92b1a2x4wpREXcdR1gM/ElrvUUpFQZsVkqt0FrvdthmENDa/nE18J79c6Vprcn//XfOzl9A5tKl2LKy8GvcmPoPP0zEiFvwj4m5nN0JIcrx2A2tWLTtOJMX7GTJY33wtcgCvqL2qjAItdYpQIr96yylVALQBHAMwuHAZ9q4vPxNKRWplGpk/95yFZ1MJXPxIs7OX0DhgQOowEDCb7qRiBEjCe7RHeUjv6BCOFuwvy+Th8QzaeZmPl13hPv6NDe7JCFMc1nDJ5RSzYAuwPrzXmoCJDk8PmZ/rkwQKqUmAhMB6vr7c/TBB8n5+Rew2Qjq2pVGr00hbOBALKGhl3cWQojLdlP7aPq2acC/VuxlSMdGRIdLb2tRO1X6ckspFQp8Azyptc6sysG01h9qrbtprbs1Uj4U7Emk3gMP0PK7ZTT7YhaRt90mIShEDVFK8cqw9hRabbz+bYLZ5QhhmkpdESql/DBCcJbWet5FNkkGHAdBxdifu6QTPopWP6xCWSyVrVUIr/T111+bduxm9UOY1Lcl/161jzu6x9KrVX3TahHCLBVeEdp7hH4CJGit/3mJzRYBdynDNUBGRfcH85SSEBQCqF+/PvXrmxdAD/drSWzdICYv3Elhsc20OoQwS2WaRnsDdwI3KKW22T8GK6UmKaUm2bdZChwE9gMfAQ+7plwhvM+MGTOYMWOGaccP9LPwyrD2HDiVw/S1h0yrQwizuP2AeiG8nRnjCC/m/k83sXZ/Gqv+1JfGkUGm1iJqLzPGEcrYBCEEAC8NjUejmbJkd8UbC+FFJAiFEADE1g3m0etbsWznCdbsPWV2OULUGAlCIUSpB65rQYv6Iby0cCf5RVazyxGiRkgQCiFKBfhaeGV4ew6fzuWjnw6aXY4QNUI6ywhhstzcXACC3Wgy+UdmbWFlwklWPtWX2LruU5fwftJZRohaKDg42K1CEOCFIXFYfBSvLN5ldilCuJwEoRAmmzZtGtOmTTO7jDIaRQTxRP/WrExIZeXuk2aXI4RLSdOoECZzl3GE5yuy2hj8zs/kFVlZ8ce+BPnLTFDC9aRpVAjhNvwsPrw6vAPH0vN4b/V+s8sRwmUkCIUQl9SzZT1u6dyY99cc5FCatOAI7yRBKIQo13OD4wjw9eGlRbsw61aKEK4kQSiEKFdUeCB//EMbftp7iu92njC7HCGcTjrLCCEqVGy1MfS/azmbW8jKp/oSElCppUyFuGzSWUYI4ZZ8LT68dkt7UjLy+fcP+8wuRwinkiAUwmRTp05l6tSpZpdRoauuqMuoq2L45OdD7E/NMrscIZxGglAIky1ZsoQlS5aYXUalPDOoHcH+FiYvkI4zwntIEAohKq1eaAB/GdiOdQdPs+j342aXI4RTSBAKIS7L2B5N6RgTwevfJpCVX2R2OUJUmwShEOKyWHwUU4Z34FR2Af9aIR1nhOeTIBTCZEFBQQQFBZldxmXpFBvJmB5N+XTdYRJSMs0uR4hqkXGEQogqOZtbyPVTV9MqKpS5D/ZEKWV2ScILyDhCIYTHiAz255lB7dh4OJ1vtiSbXY4QVSZBKITJpkyZwpQpU8wuo0pGXRVL16aRvLE0gYxc6TgjPJMEoRAmW7VqFatWrTK7jCrx8VFMuaUD6bmFTF2eaHY5QlSJBKEQolraN47grp7NmLn+CDuOZZhdjhCXTYJQCFFtT93YhnohAUxeuBObTWacEZ5FglAIUW3hgX48f3M7tiWdZc6mJLPLEeKySBAKYbJ69epRr149s8uotls6N6FH87q89d0ezuQUml2OEJUm4wiFEE6TeCKLwf/+mVFXxfDmrR3NLkd4IBlHKITwaG0bhnFv72bM3pjElqPpZpcjvJBSaqBSKlEptV8p9cxFXp+klNqhlNqmlPpFKRVf4T7lilAIcz377LMAvPHGGyZX4hzZBcX0/8dqGoQFsPCRPlh8ZMYZUXnlXREqpSzAXuAPwDFgIzBGa73bYZtwrXWm/ethwMNa64HlHVOuCIUw2bp161i3bp3ZZThNaIAvk4fEszM5k1nrj5hdjvAuPYD9WuuDWutCYDYw3HGDkhC0CwEqvNqTIBRCON3NVzaiT6v6/N/3iZzKKjC7HOFZfJVSmxw+Jjq81gRw7JZ8zP5cGUqpR5RSB4C/A49XdEAJQiGE0ymleGV4e/KLrLyxLMHscoRnKdZad3P4+PByd6C1fldr3RJ4Gnihou0lCIUQLtGyQSgPXNuCeVuS2XDojNnlCO+QDMQ6PI6xP3cps4FbKtqpBKEQJouJiSEmJsbsMlzi0Rta0SQyiMkLdlJktZldjvB8G4HWSqnmSil/4A5gkeMGSqnWDg9vBipcPVp6jQohXOr7XSd48PPNvHBzHPdf28LscoSbq2gcoVJqMPA2YAGma61fV0q9CmzSWi9SSr0DDACKgHTgUa31rnKPKUEohHAlrTX3zNjIpsPprPpTX6LDA80uSbgxGVAvRC305JNP8uSTT5pdhssopXhlWHsKrTZe+1Y6zgj3I0EohMm2bdvGtm3bzC7Dpa6oF8JDfVuy+PfjrN2fZnY5QpQhQSiEqBEP9WtJ07rBvLhwJ4XF0nFGuA8JQiFEjQj0s/DKsPYcOJXDJ78cMrscIUpJEAohasz17aK4MT6af6/aR/LZPLPLEQKQIBTCdG3atKFNmzZml1FjXhwaj0YzZfHuijcWogbI8AkhRI1798f9/N/3icy4pzv92kaZXY5wIzJ8QghRK9x/bXNa1A/hpUW7yC+yml2OqOUkCIUw2cSJE5k4cWLFG3qRAF8Lrw7vwJHTuXz400GzyxG1nAShECbbu3cve/fuNbuMGtendX1u7tiId3/cT9KZXLPLEbVYhUGolJqulEpVSu28xOt1lFLzlVLblVIblFIdnF+mEMIbvXBzHBYfxcuLyp0KUgiXqswV4QygvGXunwO2aa07AncB7zihLiFELdAoIognB7Rm1Z5UVuw+aXY5opaqMAi11j8B5S0mFg/8YN92D9BMKRXtnPKEEN7unt7NaRMdysuLdpFXKB1nRM1zxj3C34GRAEqpHsAVGIslCiEqoXPnznTu3NnsMkzjZ/Hh1eEdSD6bx7TV+80uR9RClRpHqJRqBizRWl9w/08pFY7RHNoF2AG0Ax7QWl8wi7BSaiIwEcDf3/+qgoKC6tQuhPAif5yzjW+3p/D9H6+jef0aHUYm3IgZ4wirHYTnbaeAQ0BHrXVmedvKgHohhKPUrHz6T11D56aRfHZvD4z/TkRt45ED6pVSkUopf/vD+4GfKgpBIcQ548ePZ/z48WaXYbqosECeurENP+9LY9nOE2aXI2qRygyf+BJYB7RVSh1TSt2nlJqklJpk3yQO2KmUSgQGAU+4rlwhvM+xY8c4duyY2WW4hTuvuYL4RuG8ung3OQXFZpcjagnfijbQWo+p4PV1QO2ZMVgI4TK+Fh+m3NKBW9/7lX//sI9nB8WZXZKoBWRmGSGEW7nqijrc3i2GT34+xL6TWWaXI2oBCUIhhNt5emA7QgJ8mbxwJ2atkCNqDwlCIUzWs2dPevbsaXYZbqVeaAB/uaktvx08w6Lfj5tdjvBysh6hEMItWW2aEdPWkpKRz6o/9SU80M/skkQN8MjhE0IID5J5HNa9C/nuP8LJ4qN47ZYOpGUX8PaKfWaXI7yYBKEQJrv11lu59dZbXX+glO3w0Q3w/XPwfm848qvrj1lNHWMiGdujKZ+uO0xCivuHt/BMEoRCmOz06dOcPn3atQfZuxymDwRlgREfgPKBGTfDqlehuNC1x66mv9zUloggPyYv2InNJh1nhPNJEArh7TZ8BF+Ohvqt4P6V0OkOmPQLdB4HP/8DPhkAp9x3YeDIYH+eGdSOTUfS+WaLTDwgnE+CUAhvZbPC98/D0j9D65vgnmUQ3sh4LSAMhv8XRs+Es0nwwXVGYLrpUIXbusbQtWkkby7bQ0ZukdnlCC8jQSiENyrMhbl3wbr/wtWT4I5Z4H+RjnhxQ+HhddCstxGYs0ZBlvstkOvjo5hySwfScwuZujzR7HKEl5EgFMJk/fv3p3///s7bYdZJ4/5f4lIY+BYMegt8LJfePqwhjPsaBk+Fwz/Dez0hYYnz6nGS9o0juKtnM2auP8KOYxlmlyO8iIwjFMKbpCYYV3W5p+G26dB20OV9/6lE+OZ+OLEdut4FN70BAaGuqbUKMvOL6P+PNTSODGL+Q73w8ZGlmryNjCMUQlTdgR/hkxvBWgj3LL38EARo0BbuXwV9/ghbPof3+0DSRufXWkXhgX48PziO35POMntjktnlCC8hQSiEyQYNGsSgQVUILUdbPodZt0FErBFkjbtUfV++/jDgZZjwrdHhZvpN8OMbYHWPZZGGd27M1c3r8vfv93Amx72HfgjPIEEohMny8vLIy8ur2jfbbLDyFVj0KDTvC/d+B5GxzimsWW946Be4chSsedMIxNMHnLPvalDK6DiTnV/MW8v2mF2O8AIShEJ4qqJ8+OY++OWfcNUEGDsHAsOde4zACBj5gXG/8fQ+eP9a2Pyp6cMs2kSHcW+f5szZlMSWo+mm1iI8nwShEJ4o5zR8Ngx2zYM/vApD3gaLCyel7nArPLQOYrrB4sdh9ljISXPd8Srhif6taRgeyOQFO7HKjDOiGiQIhfA0afvh4/6Q8juM+hR6PwGqBnpPRjSBOxfATX+D/SthWk9j6jaThAT4MnlIPLuOZzLztyOm1SE8nwShECYbMmQIQ4YMqdzGh9caU6IVZMHdS6D9La4t7nw+PtDzEZi4GkIawBejYMlTxgB+Ewy+siF9WtVn6vJETmUVmFKD8HwyjlAIT7F9Lix8BOo0g7FzoW5zc+spyocfphiz19RrDSM/hCZda7yMA6eyGfj2Twzt2Jh/ju5c48cXziXjCIUQF9IaVr8F8x6A2KvhvuXmhyCAXyDc9DrctRAKc+CTP8BPU40hFzWoZYNQJl7Xgnlbk1l/0MWreAivJFeEQpisX79+AKxevfrCF4sLYfET8PsX0GkMDP23Mc7P3eSlG02ku+ZB7DVGT9M6zWru8IVWBvxzDaEBvix5vA9+Fvkb31PJFaEQ4py8dJg50gjB65+HW95zzxAECKpjDLEY+RGk7ob3+sC2L2psmEWQv4WXhsaTeDKLT389XCPHFN5DglAId3TmkDFdWtJ6I1z6/rVmeoZWh1LQ8XZ4aC006ggLHoKv7obcMzVy+D/ER3NDuyimLk9kW9LZGjmm8A4ShEK4m6SN8PEAyDllDFfoeLvZFV2eyKZw92IY8ArsWWoMs9i/yuWHVUrx1q0diQoL5N4ZGzmcJrdeROVIEArhTnYtgE+HGAvn3rfSmObME/lYoM+T8MAqY3aamSNh2TNQVMWp5CqpQVgAn97bA4C7pm+QIRWiUqSzjBAmmzZtGmjNw52LYcWLRs/QO76EkHpml+YcRXmw4iXY8AE0iINbP4KGV7r0kFuPpjPmo99oEx3Glw9cQ0iAr0uPJ5zHjM4yEoRCmM1aZKwOv3kGtB9pdIrxCzS7KufbvxIWPGzcM+w/GXo+ZgzQd5FVCSd54LNNXNemAR/d1U16knoI6TUqRG2Tn4n181uNELz2T3DrJ94ZggCtBhjzlbYdaFz5fjYMzrpuTcH+cdG8PuJKViee4vn5OzDrj37h/iQIhTBLxjGYPhB9cA1/39MU+r/o0isktxBSD27/HIa/C8e3wnu9YcfXLjvcmB5NeaJ/a+ZuOsa/Vu5z2XGEZ/Py3zoh3NTxrfBRf8hI4ukdLVl6wkvuB1aGUtBlPEz6BaLaGUtJfX0f5LlmyMOTA1ozulss/161jy/WH3XJMYRnkyAUoqYlLoP/DQaLP9y3nM3pTl5D0FPUbQ4TlsL1L8Cu+cbV4aGfnX4YpRSvj+jA9W0b8MKCHazcfdLpxxCeTYJQiJq0/gNjLb8G7eD+lRAVZ3ZF5rL4Qt+/wH0rwDcAPh0KyydDsXOHPfhafHh3XFeubBLBo19ukcV8RRkShELUBJsVlj0Ny/4KbQfDhG8hLNrsqtxHzFUw6Wfodg/8+m+j2fjkbqceItjfl08mdCc6PJD7Zmzk4Klsp+5feC4JQiFcrSAbZo+D9e9Dz0fh9s/AP7j05QkTJjBhwgTz6nMX/iEw5F8wZjZkpcCH/eC398Bmc9oh6ocG8Ok9PfBRirv/JwPuhUHGEQrhSpkp8OVoOLEDBv0dejxgdkWeITsVFj0Ge7+DFtfDLdMgvLHTdv970lnu+PA3WkaFMHtiT0JlwL3bqGgcoVJqIPAOYAE+1lq/ed7rTwH3A8XAKeBerfWR8o4pV4RCuMrJXcacoWn7jaucS4RgWloaaWlpNVycmwuNMv7NhrxtTDw+racx/ZyTdIqNZNq4riSkZPHwrC0UWZ131SlcRyllAd4FBgHxwBilVPx5m20FummtOwJfA3+vaL8ShEK4wv6V8MlNoK1w73fQ5qZLbnrbbbdx22231WBxHkIp457hgz9D3RbGShbzH4L8TKfs/vp2Ubwx4kp+2nuKZ76RAfceogewX2t9UGtdCMwGhjtuoLX+UWuda3/4GxBT0U4lCIVwtk3/g1m3GwvT3r/KWJJIVF39VnDfcrjur7B9NrzfG46sc8qub+8eyx8HtOGbLcf4x/K9TtmnqDZfpdQmh4+JDq81ARynIzpmf+5S7gOWVXjAqtUphLiAzQarXoa170DrG42FagPCzK7KO1j84IbnjWna5k+EGYOhzx+h7zPVXqz48f6tOJGZx39/3E90RCB3XnOFk4oWVVSste5W3Z0opcYD3YC+FW0rV4RCOENRHnw9wQjB7vcbq0dICDpf06uNGWk6j4Wf/wGf/AFOVe9KTinFlOEd6N8uipcW7mT5rhNOKla4QDIQ6/A4xv5cGUqpAcDzwDCtdYVdgyUIhaiu7FPGQPDdi+DG12HwVGOguHCNgDBjrtLbP4ezR+GD62Djx1CNe3y+Fh/+M7YLHWMieezLrWw+IgPu3dRGoLVSqrlSyh+4A1jkuIFSqgvwAUYIplZmpzJ8QojqOJUIs0YZ3f1v/Qjihl72LubMmQPA6NGjnV2d98s6YSztdGCV0Rw97L/VmqjgdHYBt72/jvTcQr55qBctG4Q6sVhRGZUYPjEYeBtj+MR0rfXrSqlXgU1a60VKqZXAlUCK/VuOaq2HlXtMCUIhqujQTzBnvDFn6Jg5xuwoouZpDRs+ghWTjUH5g/4OccOqfO/w6OlcRr63lkA/C/Me6kVUuJcui+WmZGFeITzFti9g0eNQryWMnQt1qt7BIinJ6AQXGxtbwZaiXKl7YN79xuQFgRHQbgi0HwHN+152KO44lsHoD9fRrF4Icx68hrBAPxcVLc4nQSiEu9MaVr8Ba94y/oO9/TMIiqzWLvv16wfA6tWrq19fbWctggM/GKtZ7FkKBRn2UBxqhGKLvkYP1EpYnZjKfZ9uomeLekyf0B1/X+lSURMkCIVwZ8UFsPBR2DEXOo835sWsZtd9kCB0meICOPCjEYqJS6EgEwIjIc7hSrGCUPxqUxJ/+Xo7I7o04Z+3d0IpVUPF115mBKF0bROiMnLPGPcDj6yFGybDtX8yZj4R7ss3ANoOND6KC85dKe5aCFtnQlAdh+bT6y4aiqO6xXIyM5+py/fSMCKQpwe2M+FEhKtJEApRkdMH4Ivb4WwS3PoJXCnToXkc3wBoO8j4KMp3CMUFsPVzIxTj7M2nza4rM/zlketbkZKRz3urD9AoIpC7ejYz7zyES1QYhEqp6cAQIFVr3eEir0cAM4Gm9v1N1Vr/z9mFCjeQnwHHt0LK78a9mIBwY0xXmQ+H5/yCPP+q6eh6mD3GuDd49yJoeo3ZFYnq8guEdoONj6J8Y+jFrvmwcx5s+QyC6jqE4rUoiy+vDu9AalYBLy3aRVRYIAM7NDT7LIQTVXiPUCl1HZANfHaJIHwOiNBaP62UagAkAg3tE6JektwjdHNF+Ubvu+NbIHkLJG+G0/subx/KcmE4lhecgeEX394vBHxM6Kiw8xtjkueIGBj3ldFD1AUWL14MwNChlz8GUThRUR7st4fi3u+gMBuC65WGYl7jnoydvoldxzOZdf/VdG9W1+yKvZLbdpZRSjUDllwiCJ/FmPLmEaAZsAJoo7Uud10TCUI3YrPCqT3nAu/4FmMJIVux8XpoNDS5Cpp0hcZdoXEXY7xWQZbRAaEg67yPiz13ieeLcsuvDQBVTpBeKmgv8px/WOVmfNHamL7rhynQtBfcMQuCveM/Pa012UXZhPnL9G/lKsozVhDZNR8Sv4OiHAiuT37rm3k+sRU/5rdm7sN9aBUl/47O5qlBGIYxxU07IAwYrbX+9hL7mQhMBPD397+qoEBWh65xWkP6YYcrvS1GU2eR/Y+SgAho3Lls8IU3dl0Tp7UYCs8Lx/zMywvTgixjH5XhF3yJsHT4+swB4z/AK0cZU3n5Brjm3O0SExMBaNu2rUuPk5qbysu/vszPyT/TLbob4+PH0y+mHxYfi0uP6/GK8mDfCvuV4vdQlMMZwllj6UnfEROpG389yL+h03hqEN4G9AaeAlpiXBF20lqXu2iYXBHWkOzUsld6yVsg74zxmiXAWCKoyVVG4DW5ylj3zYxmyOqy2YymrApD8/znMi/8GmX0Cr3+uRq5x+nq4RNaa747/B2v/fYahdZChrcazs/HfuZ4znGahDZhXNw4RrQaQai/TCdWocJc2L+CjE1z8TuwgmBVgC24AT7xw4x7ilf0klCsJk8Nwm+BN7XWP9sf/wA8o7XeUN4+JQhdID8TUrYZoVdytZd5zHhN+UCDOOMqr4k99KLiKz24uNbQ2ugI5ITxgZXlyiBMz0/ntd9eY/mR5XSs35HX+7xOs4hmFNuK+THpR2bunsmW1C2E+IUwotUIxrYbS2y4zHBTGb/sPsrsWZ8wPnwzVxdvRhXlQkgUlIRi054SilXgqUH4HnBSa/2yUioa2IJxRZhW3j4lCKupKB9O7jTC7rj9ii9tH2B/P+s0P9e02eQq48rPv0Z/tkQluSoIVyet5uVfXyajMINHOj/ChPYT8PW58B7prrRdzEyYyXeHv8Nqs9I3ti93xt1J94bdZQB5BeZtOcZTc3/n9o51eLPjSXx2z4e9y6E4z7i3HlcSitdIKFaSWwahUupLoB9QHzgJvAT4AWit31dKNQZmAI0AhXF1OLOiA0sQXgab1VjlwLEH58ldYCsyXg+JOndPryT8vKRzR23g7CDMLszmrY1vsWD/AtrUacPf+vyNtnUrvv94KvcUcxLnMDdxLukF6bSp04bxceMZ3GIwARbX3if1ZNNW7+fv3yXu7EPEAAAZ9UlEQVTyYN8WPDsoDgpzjHuJu+Yb9xZLQjF+uBGKsdd45u2HGuKWQegqEoSXoDWcPeJwX28rHN/m0Jkl3OjMUnKl16QrhDfx/PF6tZgzg3B9ynomr53MydyT3NfhPiZ1moS/5fKaeQusBSw9uJTPEz5nX/o+6gbW5fa2tzO67WjqB9Wvdo3eRmvNiwt38flvR3hpaDz39G5+7sWCbNjnGIr5ENrQIRSvllA8jwRhbZR96lzTZkkzZ+5p4zVLADS8smwPznqt5BfHy6xcuRKAAQMGVHkfecV5vL35bb7Y8wXNwpvxWp/X6NSgU7Xq0lqz4cQGZu6eyZpja7D4WBjcfDDj4sYRXy++Wvv2Nlab5qGZm1mRcJJ3x3Zl8JWNLtyoINsYn7h7wblQDGt0LhRjesjvNhKE3q8gy7i6c+zBmWEswWN0ZmlX9r5eVHyNdtoQnun3U7/zwi8vcDjzMOPixvFE1ycI8g1y6jGOZh7liz1fMH/ffHKLc+ka1ZU74+/k+tjrZfiFXX6RlXEfr2dHcgaf39uDq1vUu/TGBVllm0+tBRDW2CEUu9faUJQg9CbFBXBiZ9n7eml7Ke3MEnmFw329q6BhRwiQ7uu10bZt2wDo3LnzZX1fobWQ935/j+k7pxMdHM2U3lO4utHVriixVFZhFvP3zeeLPV+QnJ1Mk9AmjGk3hpGtR8ogfSA9p5Db3v+VU1kFfP1QL9pEV+LfpCDLGLRfcqVYEortbzFCsUm3WhWKEoSeLCMZjm2ApA2QtB5Stjt0ZmlQdqxe4y4QUs5fi6JWqco9wsQziTz3y3PsTd/LLa1u4a/d/1qjQWS1WVmdtJrPEz5n88nNBPsGc0urWxgbN5Yrwqu+SLE3OJaey8hpv+Lro5j3cG8aRlzGCvf5mUbz6a4FsH8FWAuNPgDx9lCM6eb1/QEkCD2FtQhObIekjUboJW04N17PN8i4yovpdi78ImK8/odXVN3lBGGxrZj/7fwf036fRoR/BC/3epl+sf1cWl9Fdp/ezayEWSw9tNQYfhHTl3Hx47i64dW1dvjFruMZjP7gN2LqBDF3Uk/Cq7LCfX7GuSvF/SvtoRgDrfobfQei2xu3T6q5MLS7kSB0Vzmn7Vd79tBL3mJ0iQbjBzO2h9H7K7aH8QMqg9TFZahsEB7OOMzza59n+6nt3HjFjbxwzQvUCazj+gIrKS0vjbmJc5mTOIcz+WdoFdmKO+PvZHDzwQT6XsZVkZdYuz+NCf/bQLcr6jLj3u4E+FbjXmp+BiQuM64Uk36DvPRzr0XEGqEY3R6iOxgfdVtUbl5dNyRB6A5sNmMC6pLQS1pvzD0J4OMLjTqdC72YHhDRxNx6hcerKAht2saXe77k7c1v42/x54VrXmBQ80E1V+BlKrAWsOzQMj7f/Tl70/dSJ6AOo9qOYnTb0UQFR5ldXo1asDWZJ+dsY2inxrwzujM+Pk64QtYaslKMscQnd9o/7zL6IJRMlO8baHS+i+5QNiQ94JaMBKEZ8jMhedO50Du2yZhzEiC4/rnQi73aGL/n59zeeEKUF4THs4/z4toXWX9iPX2a9OGVXq94TJhordl0chOf7/6c1UmrsfhYGNhsIOPjx9O+Xnuzy6sx7685wJvL9vDAtc15/mYXDjspLjDC8MTOsgGZk3pum9CG5109tof6bdyqd7oEoatpDWcOngu9pA2QuhujJ6cyfihKrvRiexjNC7X0HoeoOb/++isAvXr1Kn1Oa82C/Qt4a+NbaK35a/e/MrL1SI+955aUmWQMv9g/n5yiHLpGdWVc3DhuaHrDRad98yZaa15ZvJsZvx7mhZvjuP/aFjVbQHbquVAsuYo8tce45wjg4wcN2joEpD0kQ6NN+f9PgtDZivKMmVlKmzk3QK59CtSAcGOsTuzVENvd6KIcGO7aeoSohLS8NF7+9WXWHFtDt+huTOk9hZiwGLPLcorswmzm75/PrIRZJGcn0yikEWPbjWVkm5GE+3vv75/Vpnn0iy0s23mC/47twpCOjU0uqAhOH7BfOTpcPWYmn9smuF7ZK8fo9kZzq4tbxSQIqysjuey9vRPbz7WZ12tlhF5J+DVoV6vG5gj35XhFWLJcUl5RHk90fYLx8ePxUd73c2q1WVl9bDWzEmax8cRGgnyDGN5yOOPixtEsopnZ5blEfpGVuz7ZwLaks3x2Xw+uKW/AvVlyzxitZGXuP+4+1zlQ+UC91hc2rzqxZ7wE4eUoHcJQ0sy58bwhDFcZV3ol4RcicyQK99SvXz9s/jauef4alh1eRod6HXi9z+u0iKzhJjST7Dmzh5m7Z7L00FKKbEVc2+RaxsePp2ejnh7bFHwpGblF3Pb+r5zIzOfrSb1o29ADJiGwWY3FvE/utN9/tIfk2SPntgmIuLBpNSquSpOESBCWJyfNoUPLxrJDGCJiHZo5ZQiD8Cy9xvciu3c2lhALkzpN4r4r7/P6+2YXk5aXxleJXzE7cXbp8ItxceMY0mKIVw2/SD6bx8hpa1Eo5j3ci8aRHtoBLz8TUhPKNq2e3AWFWfYNFNRtfmHzamSzclvjJAhL2KwOQxg2njeEwc9YW0+GMAgPl1OUw/9t/D++2fcNlnQLX975JXH14swuy3SF1kKWHVrGzISZ7Dmzh8iASEa1MYZfRIdEm12eUySkZHL7++toFBnIV5N6ERHkJX+4aw1njzoE4w7j8+kDlE4v6RcC0fFlA9JhYoDaG4T5GcawhWMbZQiDqBU2ntjI5LWTSclJwf93f4K3BrPmhzVml+VWtNZsPrmZmQkz+eHoD1iUhRub3cj4uPFc2eBKs8urtl/3p3H3/zbQtWkdPr23B4F+Xjx5eWEunEooe+V4Ygfknz23jX1iADVubu0JwsaRgfr455MuPYShJPzqNJchDMJr5Bfn886Wd5iZMJPYsFj+1udvPHn7k4DzV6j3JklZSXy550vm7ZtHTlEOnRp0Ynz8eAY0HeDRzcgLtyXzxOxt3HxlI/4zpotzBtx7iotNDHBiJ+rR9bUnCLs1tuhNjzUue2+vyVUyhEF4rZ1pO3nul+c4lHGI0W1H89RVTxHsF1zl1Sdqo+zCbBYeWMishFkkZSXRMKQhY9qN4dbWtxIREGF2eVXy0U8HeX1pAvf2bs6LQ2Wdx1rVNFo3LEifyciRIQzC6xVZi3h/+/t8suMT6gfV59Xer9Krca+Kv1FcktVm5adjPzEzYSYbTmwgyDeIYS2HMTZuLC0iPKu3rdaaKUsSmL72kDkD7t1MrQpCt5liTQgX2pu+lxd+eYGEMwkMazmMp3s8fcHAcWesUF+bJZ5JZFbCLL49+C2FtkK6N+xO9+judI7qTMcGHQnxq9H/U6vEZtM8Nnsr325P4d9jujCsk8kD7k0kQSiEl7DarMzYNYN3t71LmH8YL/Z8kf5N+19026qsRygudDrvNHP3zmXFkRXsT9+PRuOjfGhbpy2dozrTJaoLXaK60DCkodmlXlR+kZW7pm9g69F0Pr2nB71a1c6xzxKEQniBo5lHef6X59l2ahsDmg5gcs/J1A2se8ntJQidL7Mwk+2ntrM1dSvbUrexI20HefZxxw1DGtKlQZfScGxTpw0WH/fosZmRW8SoD34l5Ww+cyf1JK5R7eszIUEohAezaRtzEufwr83/wtfHl+eufo6bm99c4ewoEoSuV2QrYu+ZvWxN3Voajql5xqoMwb7BdGzQkS5RRjh2atDJ1ObU42fzGDntVzSaeQ/3pomnDrivIglCITzUiZwTTF47md9SfqN349683OvlSjfBSRDWPK01x3OOl4bi1tSt7Evf5zbNqXtOZDLq/XVEhwfyzaReRAR7yYD7SpAgFMLDaK1ZfHAxb65/k2JdzJ+7/ZlRbUZd1hyZEoTuIaswq0xz6va07aY2p647cJq7p2+gc2wkn93n5QPuHUgQCuFB0vLSmLJuCj8k/UDXqK681vs1YsNjL3s/iYmJALRt29bZJYpqKLYVk5ieWHrFuPXk1hpvTl2y/TiPfrGVwVc25D9jumKpBQPuJQiF8BArjqxgyropZBdl83iXx7kz/k636XAhXKOi5tQ2ddrQucG55tRGoY2cctyPfz7Ia98mMKFXM14aGu91K3KcT4JQCDeXUZDBGxve4NuD3xJXN46/9fkbreq0qtY+Fy9eDMDQoUOdUaKoQeU1p0YHR9M1qmtpc2rrOq2rPB3ca0t28/Evh3h2UDse7NvSmafgdiQIhXBja5PX8uLaFzmdf5qJHSfyQMcH8POpficGuUfoPS5oTk3dSmpu9ZtTbTbN47O3smR7Co/f0IprWtYjvlE4kcH+rjwdU0gQCuGGcotymbppKl/t/YqWES15/drXaV+vvdP2L0HovbTWpOSklBm2sTd9b5WaUwuKrTz4+WZWJ54qfa5xRCBxjcIdPsK4ol6IR99LlCAUws1sPrmZF355geTsZO6Kv4vHuj5GgCXAqceQIKxdsguzjebUU0Y4bj9Vtjm15IqxpHfq+c2pqVn5JKRkkZCSWfpx4FQOVpvxf3mQn4W2DcOIaxROfCPjc7tG4YQGeMYqHRKEQriJAmsB/9nyHz7b/RmNQxvzWu/X6Nawm0uOJUFYuxXbitmbvrdMJ5yTuScBozn1ygZXGleMDbrQsUFHQv1DL9hHfpGVfSezSUjJZLdDQGbmF5duc0W9YOIanrtyjGsUTkydILfrfCNBKNye1ppCWyFWm7XibSn7s3Wxn7ULtuEi21TiZ7Qy+65sTUlZSbz868scyDjAqDaj+HO3PxPsF1xhDVUlQSjOl5Lt0Jx6ymhOtWkbPsqHqOAoQv1CCfULJcQ/5NzXfiHnPvuHEuIbQn6RH6fOKpLP2DiaZmXfiWKSTlvR2lj1JyzQ1x6O9ivIxuG0iQ4zdcyiBKGoMq01xbZi8qx55Bfnk1+cT15xHvnW/NLH53+dV5xX5vmSxwXWgot+b8nrFwsYbxMVFMUrvV+hT5M+Lj9WUlISALGxlz8GUdQO2YXZbE/bzrbUbSRnJ5NTlEN2UTY5hfbP9sclTawVCbQE4auCwBZIUZEf+QV+FBcHgC0AbIFEBoYRHRZJTEQkzerWo039+jSOiCTMP6w0cEP9QvGzOH/GGwlCL1VkKyobMBWEUYG14KJB5hhyZYLN/tmqK75KO5+vjy9BliACfQNLP8o8ttif8w0iwBJQ+tzFuoErLmxiqUyzS2W+ryb37efjx4ArBnjsQq+i9iq2FZNbnHtBQF4sNHOKcsguND7nFOWQnp9FRkEWuUU5FOpcqMQfvP4+/sbVp+PVqMOV6gVXqX7nXcHanwu0BJb+XpoRhJ5x99REVpuV7KJsMgsyySzKND4XZpJVmEVmofG49GuH53OKckoDq1gXV3yg81iUhSBfI5ACLAHG1/ZQqhNYp8zjknByDKuS73UMMsftS7at6rgm4Txz5swBYPTo0SZXIjydr48v4f7hF6x5ebm01uQV55GSeZYdKSdJOHmKfWmnOHwmneOZ6VjJQ/kUUOxbgF+IDf/gYvIDiikuLuBsQQr5xUa4ZhVlUWyr+P8/i7KUhqQZasUVYaG1sDS0SgKrNLTOD7bzns8uyi53377Kl/CAcML8w0p/AEuaDy4aRhcJtguuwnwDnTI+TXgGuUcoPEmx1cahtBx2l3bMMXqwnsoqKN0mOjygdEhHm+hAmta3UC9ck1d83lXpRa5S/3bt36Rp9GK01uQW514QZJe6Gjv/+QJrQbn7D/INKhNkJWEWHuDw9UWeD/cPJ8jX/XpdCc8iQSi8QVp2gcOQDiMc96dmU2wf1hHo50Pb6LAy4x7bNQojPLDsH/21qmlU+2u+O/zdxcPsvKu0rMKscu9/KRSh/qFlgqxBZIMLA8w//KJXb/4W75udQQghalL90ACubd2Aa1s3KH2uoNjK/tRsElKy2H3cCMnvdp1g9sak0m1i6gSVBmO8SQsRmxeEkZq/rPnLuUIc2rbD/cOJDIykaXjTiq/SAsIJ9QvFR/mYdSpCCCEuIsDXQvvGEbRvHAFXGc9prTmRmV965Vgy7nFlwklMaqA0LwhVumLesHmlYebYa0gIIYR3UkrRKCKIRhFB3NAuuvT5vEIriSez6PJWhd8/EHgHsAAfa63fPO/164C3gY7AHVrrryusyRPuEQrhzdLS0gCoX7++yZUIYb7y7hEqpSzAXuAPwDFgIzBGa73bYZtmQDjwZ2BRZYJQ+s4LYTIJQCEqrQewX2t9EEApNRsYDpQGodb6sP01W2V3KjfWhDDZjBkzmDFjhtllCOEufJVSmxw+Jjq81gRIcnh8zP5c9Q5Y3R0IIaqnJAQnTJhgah1CuIlirbVrZri/BLkiFEII4SmSAcdJeWPsz1WLBKEQQghPsRForZRqrpTyB+4AFlV3pxKEQgghPILWuhh4FPgeSADmaq13KaVeVUoNA1BKdVdKHQNGAR8opXZVtF+5RyiEEMJjaK2XAkvPe+5Fh683YjSZVlqF4wiVUtOBIUCq1rrDRV7/CzDO/tAXiAMaaK3PlLdfGUcohCE3NxeA4GDXLf4rhKdwy/UI7aP0s4HPLhaE5207FPij1vqGig4sQSiEEOJ8ZgRhhfcItdY/AeVe3TkYA3xZrYqEqGWmTZvGtGnTzC5DiFrLaZ1llFLBwEDgm3K2mVgySLK4+PIXqxXCG82dO5e5c+eaXYYQtZYze40OBdaWd29Qa/2h1rqb1rqbr6/00xFCCGE+ZwbhHUizqBBCCA/jlCBUSkUAfYGFztifEEIIUVMqbJ9USn0J9APq2wcpvgT4AWit37dvNgJYrrWWbqBCCCE8imnrEdqXyMgz5eA1wxfw5h5Bcn6ey5vPDeT8PF2Q1rpGZz0zs8fKlpqeYbwmKaU2yfl5Lm8+P28+N5Dz83RKqU01fUyZa1QIIUStJkEohBCiVjMzCD808dg1Qc7Ps3nz+XnzuYGcn6er8fMzrbOMEEII4Q6kaVQIIUStJkEohBCiVjMlCJVSh5VSO5RS28zoKutsSqnpSqlUpdROh+fqKqVWKKX22T/XMbPG6rjE+b2slEq2v4fblFKDzayxqpRSsUqpH5VSu5VSu5RST9if94r3r5zz85b3L1AptUEp9bv9/F6xP99cKbVeKbVfKTVHKeVvdq2Xq5xzm6GUOuTw3nU2u9bqUEpZlFJblVJL7I9r/L0z84rweq11Zy8ZDzMDY+UNR88Aq7TWrYFV9seeagYXnh/Av+zvYWf7qtGeqBj4k9Y6HrgGeEQpFY/3vH+XOj/wjvevALhBa90J6AwMVEpdA7yFcX6tgHTgPhNrrKpLnRvAXxzeu23mlegUTwAJDo9r/L2TplEnuMSajcOBT+1ffwrcUqNFOdFlrknpUbTWKVrrLfavszB+IZvgJe9fOefnFbQh2/7Qz/6hgRuAr+3Pe+T7V865eQ2lVAxwM/Cx/bHChPfOrCDUwHKl1Gal1ESTanC1aK11iv3rE0C0mcW4yKNKqe32plOPbDp0pJRqBnQB1uOF79955wde8v7Zm9a2AanACuAAcFZrXTIN2TE8NPzPPzetdcl797r9vfuXUirAxBKr623gr4DN/rgeJrx3ZgVhH611V2AQRlPNdSbVUSO0MUbFq/6SA94DWmI02aQA/zC3nOpRSoViLCr9pNY60/E1b3j/LnJ+XvP+aa2tWuvOQAzQA2hncklOc/65KaU6AM9inGN3oC7wtIklVplSagiQqrXebHYtpgSh1jrZ/jkVmI/xw+ttTiqlGgHYP6eaXI9Taa1P2n9JbcBHePB7qJTywwiJWVrrefanveb9u9j5edP7V0JrfRb4EegJRCqlSuZSjgGSTSvMCRzObaC9uVtrrQuA/+G5711vYJhS6jAwG6NJ9B1MeO9qPAiVUiFKqbCSr4EbgZ3lf5dHWgTcbf/6brxsrcaSkLAbgYe+h/Z7Ep8ACVrrfzq85BXv36XOz4vevwZKqUj710HAHzDug/4I3GbfzCPfv0uc2x6HP9AUxv0zj3zvtNbPaq1jtNbNMBZ2/0FrPQ4T3rsan1lGKdUC4yoQjNUvvtBav16jRTiZclizETiJsWbjAmAu0BQ4AtyutfbIDieXOL9+GM1qGjgMPOhwT81jKKX6AD8DOzh3n+I5jPtoHv/+lXN+Y/CO968jRocKC8Yf9nO11q/a/5+ZjdF0uBUYb7+C8hjlnNsPQANAAduASQ6dajySUqof8Get9RAz3juZYk0IIUStJsMnhBBC1GoShEIIIWo1CUIhhBC1mgShEEKIWk2CUAghRK0mQSiEB1BK9SuZnV8I4VwShEIIIWo1CUIhnEgpNd6+htw2pdQH9kmTs+2TI+9SSq1SSjWwb9tZKfWbffLk+SUTXyulWimlVtrXoduilGpp332oUuprpdQepdQs+8wiQohqkiAUwkmUUnHAaKC3faJkKzAOCAE2aa3bA2swZuYB+Ax4WmvdEWPml5LnZwHv2teh64UxKTYYK0c8CcQDLTDmahRCVJNvxZsIISqpP3AVsNF+sRaEMVm3DZhj32YmME8pFQFEaq3X2J//FPjKPg9vE631fACtdT6AfX8btNbH7I+3Ac2AX1x/WkJ4NwlCIZxHAZ9qrZ8t86RSk8/brqrzGjrOt2hFfn+FcAppGhXCeVYBtymlogCUUnWVUldg/J6VzKY/FvhFa50BpCulrrU/fyewxr6K/DGl1C32fQQopYJr9CyEqGXkL0ohnERrvVsp9QKwXCnlAxQBjwA5GIuqvoDRVDra/i13A+/bg+4gcI/9+TuBD5RSr9r3MaoGT0OIWkdWnxDCxZRS2VrrULPrEEJcnDSNCiGEqNXkilAIIUStJleEQgghajUJQiGEELWaBKEQQohaTYJQCCFErSZBKIQQolb7f2lhia3n408WAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for model_name, params in tqdm(LEARNING_CURVES_PARAMS):\n",
    "    print(f'#### {model_name}')\n",
    "    \n",
    "    _, ax = plt.subplots(1, figsize=(7, 7))\n",
    "    ax.set_title(model_name)\n",
    "    _, df = plot_learning_curve(get_model_path(model_name), ax=ax)\n",
    "\n",
    "    display.display(df)"
   ]
  }
 ],
 "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": "3.7.3"
  },
  "papermill": {
   "duration": 21367.480454,
   "end_time": "2020-05-22T18:30:06.436959",
   "environment_variables": {},
   "exception": null,
   "input_path": "./notebooks/mlp-learning-curve.ipynb",
   "output_path": "./notebooks/mlp-learning-curve.ipynb",
   "parameters": {},
   "start_time": "2020-05-22T12:33:58.956505",
   "version": "1.1.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}