models/failure_prediction/jnotebooks/Bi_LSTMstacked_LSTM_Correlation.ipynb

   1 {
   2   "nbformat": 4,
   3   "nbformat_minor": 0,
   4   "metadata": {
   5     "colab": {
   6       "name": "Bi-LSTMstacked-LSTM_Correlation.ipynb",
   7       "provenance": [],
   8       "collapsed_sections": []
   9     },
  10     "kernelspec": {
  11       "display_name": "Python 3",
  12       "name": "python3"
  13     },
  14     "language_info": {
  15       "name": "python"
  16     }
  17   },
  18   "cells": [
  19     {
  20       "cell_type": "markdown",
  21       "metadata": {
  22         "id": "l43uL109ZssB"
  23       },
  24       "source": [
  25         "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
  26         "\n",
  27         "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
  28         "\n",
  29         "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
  30         "you may not use this file except in compliance with the License.\n",
  31         "You may obtain a copy of the License at\n",
  32         "\n",
  33         "    http://www.apache.org/licenses/LICENSE-2.0\n",
  34         "\n",
  35         "Unless required by applicable law or agreed to in writing, software\n",
  36         "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
  37         "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
  38         "See the License for the specific language governing permissions and\n",
  39         "limitations under the License."
  40       ]
  41     },
  42     {
  43       "cell_type": "code",
  44       "metadata": {
  45         "colab": {
  46           "base_uri": "https://localhost:8080/"
  47         },
  48         "id": "YQ6lT1e2hrx4",
  49         "outputId": "14ee2b60-05d7-4163-d420-58970bc4e4b0"
  50       },
  51       "source": [
  52         "from google.colab import drive\n",
  53         "drive.mount('/content/drive')"
  54       ],
  55       "execution_count": null,
  56       "outputs": [
  57         {
  58           "output_type": "stream",
  59           "name": "stdout",
  60           "text": [
  61             "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
  62           ]
  63         }
  64       ]
  65     },
  66     {
  67       "cell_type": "code",
  68       "metadata": {
  69         "id": "tLhroy5BnMnC"
  70       },
  71       "source": [
  72         "# Importing libraries\n",
  73         "import tensorflow as tf\n",
  74         "import matplotlib.pyplot as plt\n",
  75         "import matplotlib as mpl\n",
  76         "import pandas as pd\n",
  77         "import numpy as np\n",
  78         "import os"
  79       ],
  80       "execution_count": null,
  81       "outputs": []
  82     },
  83     {
  84       "cell_type": "code",
  85       "metadata": {
  86         "colab": {
  87           "base_uri": "https://localhost:8080/",
  88           "height": 521
  89         },
  90         "id": "2-UpMVsSnfCI",
  91         "outputId": "87e645f2-f2f9-4e8e-e0b9-fd807224892a"
  92       },
  93       "source": [
  94         "df_Ellis  = pd.read_csv(\"/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
  95         "df_Ellis"
  96       ],
  97       "execution_count": null,
  98       "outputs": [
  99         {
 100           "output_type": "execute_result",
 101           "data": {
 102             "text/html": [
 103               "<div>\n",
 104               "<style scoped>\n",
 105               "    .dataframe tbody tr th:only-of-type {\n",
 106               "        vertical-align: middle;\n",
 107               "    }\n",
 108               "\n",
 109               "    .dataframe tbody tr th {\n",
 110               "        vertical-align: top;\n",
 111               "    }\n",
 112               "\n",
 113               "    .dataframe thead th {\n",
 114               "        text-align: right;\n",
 115               "    }\n",
 116               "</style>\n",
 117               "<table border=\"1\" class=\"dataframe\">\n",
 118               "  <thead>\n",
 119               "    <tr style=\"text-align: right;\">\n",
 120               "      <th></th>\n",
 121               "      <th>Timestamp</th>\n",
 122               "      <th>ellis-cpu.system_perc</th>\n",
 123               "      <th>ellis-cpu.wait_perc</th>\n",
 124               "      <th>ellis-load.avg_1_min</th>\n",
 125               "      <th>ellis-mem.free_mb</th>\n",
 126               "      <th>ellis-net.in_bytes_sec</th>\n",
 127               "      <th>ellis-net.out_packets_sec</th>\n",
 128               "      <th>Label</th>\n",
 129               "    </tr>\n",
 130               "  </thead>\n",
 131               "  <tbody>\n",
 132               "    <tr>\n",
 133               "      <th>0</th>\n",
 134               "      <td>14-09-2016 0:00</td>\n",
 135               "      <td>0.5</td>\n",
 136               "      <td>12.9</td>\n",
 137               "      <td>1.730</td>\n",
 138               "      <td>3949</td>\n",
 139               "      <td>5413.200</td>\n",
 140               "      <td>62.067</td>\n",
 141               "      <td>1</td>\n",
 142               "    </tr>\n",
 143               "    <tr>\n",
 144               "      <th>1</th>\n",
 145               "      <td>14-09-2016 0:00</td>\n",
 146               "      <td>0.4</td>\n",
 147               "      <td>10.3</td>\n",
 148               "      <td>1.790</td>\n",
 149               "      <td>3950</td>\n",
 150               "      <td>5201.667</td>\n",
 151               "      <td>59.567</td>\n",
 152               "      <td>1</td>\n",
 153               "    </tr>\n",
 154               "    <tr>\n",
 155               "      <th>2</th>\n",
 156               "      <td>14-09-2016 0:01</td>\n",
 157               "      <td>0.4</td>\n",
 158               "      <td>11.8</td>\n",
 159               "      <td>1.520</td>\n",
 160               "      <td>3950</td>\n",
 161               "      <td>5370.733</td>\n",
 162               "      <td>61.200</td>\n",
 163               "      <td>1</td>\n",
 164               "    </tr>\n",
 165               "    <tr>\n",
 166               "      <th>3</th>\n",
 167               "      <td>14-09-2016 0:01</td>\n",
 168               "      <td>0.4</td>\n",
 169               "      <td>12.9</td>\n",
 170               "      <td>1.430</td>\n",
 171               "      <td>3949</td>\n",
 172               "      <td>5292.467</td>\n",
 173               "      <td>60.400</td>\n",
 174               "      <td>1</td>\n",
 175               "    </tr>\n",
 176               "    <tr>\n",
 177               "      <th>4</th>\n",
 178               "      <td>14-09-2016 0:02</td>\n",
 179               "      <td>0.5</td>\n",
 180               "      <td>12.1</td>\n",
 181               "      <td>1.440</td>\n",
 182               "      <td>3950</td>\n",
 183               "      <td>5318.167</td>\n",
 184               "      <td>61.700</td>\n",
 185               "      <td>1</td>\n",
 186               "    </tr>\n",
 187               "    <tr>\n",
 188               "      <th>...</th>\n",
 189               "      <td>...</td>\n",
 190               "      <td>...</td>\n",
 191               "      <td>...</td>\n",
 192               "      <td>...</td>\n",
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 195               "      <td>...</td>\n",
 196               "      <td>...</td>\n",
 197               "    </tr>\n",
 198               "    <tr>\n",
 199               "      <th>176995</th>\n",
 200               "      <td>13-12-2016 21:20</td>\n",
 201               "      <td>0.4</td>\n",
 202               "      <td>0.3</td>\n",
 203               "      <td>0.030</td>\n",
 204               "      <td>3484</td>\n",
 205               "      <td>230.967</td>\n",
 206               "      <td>2.167</td>\n",
 207               "      <td>0</td>\n",
 208               "    </tr>\n",
 209               "    <tr>\n",
 210               "      <th>176996</th>\n",
 211               "      <td>13-12-2016 21:20</td>\n",
 212               "      <td>0.2</td>\n",
 213               "      <td>0.3</td>\n",
 214               "      <td>0.018</td>\n",
 215               "      <td>3484</td>\n",
 216               "      <td>218.433</td>\n",
 217               "      <td>0.767</td>\n",
 218               "      <td>0</td>\n",
 219               "    </tr>\n",
 220               "    <tr>\n",
 221               "      <th>176997</th>\n",
 222               "      <td>13-12-2016 21:21</td>\n",
 223               "      <td>0.6</td>\n",
 224               "      <td>0.3</td>\n",
 225               "      <td>0.010</td>\n",
 226               "      <td>3483</td>\n",
 227               "      <td>160.967</td>\n",
 228               "      <td>1.867</td>\n",
 229               "      <td>0</td>\n",
 230               "    </tr>\n",
 231               "    <tr>\n",
 232               "      <th>176998</th>\n",
 233               "      <td>13-12-2016 21:21</td>\n",
 234               "      <td>0.6</td>\n",
 235               "      <td>0.3</td>\n",
 236               "      <td>0.007</td>\n",
 237               "      <td>3484</td>\n",
 238               "      <td>188.367</td>\n",
 239               "      <td>2.100</td>\n",
 240               "      <td>0</td>\n",
 241               "    </tr>\n",
 242               "    <tr>\n",
 243               "      <th>176999</th>\n",
 244               "      <td>13-12-2016 21:22</td>\n",
 245               "      <td>0.4</td>\n",
 246               "      <td>0.1</td>\n",
 247               "      <td>0.040</td>\n",
 248               "      <td>3484</td>\n",
 249               "      <td>229.833</td>\n",
 250               "      <td>2.400</td>\n",
 251               "      <td>0</td>\n",
 252               "    </tr>\n",
 253               "  </tbody>\n",
 254               "</table>\n",
 255               "<p>177000 rows × 8 columns</p>\n",
 256               "</div>"
 257             ],
 258             "text/plain": [
 259               "               Timestamp  ...  Label\n",
 260               "0        14-09-2016 0:00  ...      1\n",
 261               "1        14-09-2016 0:00  ...      1\n",
 262               "2        14-09-2016 0:01  ...      1\n",
 263               "3        14-09-2016 0:01  ...      1\n",
 264               "4        14-09-2016 0:02  ...      1\n",
 265               "...                  ...  ...    ...\n",
 266               "176995  13-12-2016 21:20  ...      0\n",
 267               "176996  13-12-2016 21:20  ...      0\n",
 268               "176997  13-12-2016 21:21  ...      0\n",
 269               "176998  13-12-2016 21:21  ...      0\n",
 270               "176999  13-12-2016 21:22  ...      0\n",
 271               "\n",
 272               "[177000 rows x 8 columns]"
 273             ]
 274           },
 275           "metadata": {},
 276           "execution_count": 41
 277         }
 278       ]
 279     },
 280     {
 281       "cell_type": "code",
 282       "metadata": {
 283         "colab": {
 284           "base_uri": "https://localhost:8080/",
 285           "height": 293
 286         },
 287         "id": "92xBt43BnjAo",
 288         "outputId": "747e6ee9-2da1-43af-c751-1261f54d6c2c"
 289       },
 290       "source": [
 291         "df_Ellis.plot()"
 292       ],
 293       "execution_count": null,
 294       "outputs": [
 295         {
 296           "output_type": "execute_result",
 297           "data": {
 298             "text/plain": [
 299               "<matplotlib.axes._subplots.AxesSubplot at 0x7ff3f424b5d0>"
 300             ]
 301           },
 302           "metadata": {},
 303           "execution_count": 42
 304         },
 305         {
 306           "output_type": "display_data",
 307           "data": {
 308 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\n",
 309             "text/plain": [
 310               "<Figure size 432x288 with 1 Axes>"
 311             ]
 312           },
 313           "metadata": {}
 314         }
 315       ]
 316     },
 317     {
 318       "cell_type": "markdown",
 319       "metadata": {
 320         "id": "46U0FXYB6AbD"
 321       },
 322       "source": [
 323         "We showed here the histograms of Ellis data"
 324       ]
 325     },
 326     {
 327       "cell_type": "code",
 328       "metadata": {
 329         "colab": {
 330           "base_uri": "https://localhost:8080/",
 331           "height": 879
 332         },
 333         "id": "RSo-aa-SIoBR",
 334         "outputId": "eeead93b-89b4-4798-976c-1b065bbbc4a3"
 335       },
 336       "source": [
 337         "# we show here the hist\n",
 338         "df_Ellis.hist(bins=100,figsize=(20,15))\n",
 339         "#save_fig(\"attribute_histogram_plots\")\n",
 340         "plt.show()"
 341       ],
 342       "execution_count": null,
 343       "outputs": [
 344         {
 345           "output_type": "display_data",
 346           "data": {
 347 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\n",
 348             "text/plain": [
 349               "<Figure size 1440x1080 with 9 Axes>"
 350             ]
 351           },
 352           "metadata": {}
 353         }
 354       ]
 355     },
 356     {
 357       "cell_type": "code",
 358       "metadata": {
 359         "colab": {
 360           "base_uri": "https://localhost:8080/",
 361           "height": 634
 362         },
 363         "id": "gggaMJ_2LtFs",
 364         "outputId": "c3ac6c2e-c7f3-48ae-c562-23bb7b60c5b4"
 365       },
 366       "source": [
 367         "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
 368         "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
 369         "plt.xlabel('Timestamp', fontsize=30);"
 370       ],
 371       "execution_count": null,
 372       "outputs": [
 373         {
 374           "output_type": "display_data",
 375           "data": {
 376 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\n",
 377             "text/plain": [
 378               "<Figure size 1440x720 with 1 Axes>"
 379             ]
 380           },
 381           "metadata": {}
 382         }
 383       ]
 384     },
 385     {
 386       "cell_type": "code",
 387       "metadata": {
 388         "colab": {
 389           "base_uri": "https://localhost:8080/",
 390           "height": 634
 391         },
 392         "id": "R_ctvXcQL1Xf",
 393         "outputId": "d553c7b1-3a00-40dd-ad5f-cc695d3ecbae"
 394       },
 395       "source": [
 396         "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
 397         "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
 398         "plt.xlabel('Timestamp', fontsize=30);"
 399       ],
 400       "execution_count": null,
 401       "outputs": [
 402         {
 403           "output_type": "display_data",
 404           "data": {
 405 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\n",
 406             "text/plain": [
 407               "<Figure size 1440x720 with 1 Axes>"
 408             ]
 409           },
 410           "metadata": {}
 411         }
 412       ]
 413     },
 414     {
 415       "cell_type": "markdown",
 416       "metadata": {
 417         "id": "9jTOMzOqEQEZ"
 418       },
 419       "source": [
 420         "## Identifying trends in Time Series data\n",
 421         "There are several ways to think about identifying trends in time series. One popular way is by taking a rolling average, which means that, for each time point, we take the average of the points on either side of it. Note that the number of points is specified by a window size, which we need to choose.\n",
 422         "\n",
 423         "What happens then because we take the average is it tends to smooth out noise and seasonality. We will see that below right now. Check out this rolling average of `'ellis-cpu.wait_perc'` using the built-in `pandas` methods.\n",
 424         "\n",
 425         "When it comes to determining the window size, here, it makes sense to first try out one of twelve months, as we're talking about yearly seasonality.\n",
 426         "\n",
 427         "Note that in the code chunk above we used two sets of squared brackets to extract the `'ellis-cpu.wait_perc'` column as a DataFrame; If we would have used one set, like `df_Ellis['ellis-cpu.wait_perc']`, we would have created a pandas Series.\n",
 428         "\n",
 429         "In the code chunk above, you also chained methods: you called methods on an object one after another. Method chaining is pretty popular and pandas is one of the packages that really allows you to use that style of programming to the max!"
 430       ]
 431     },
 432     {
 433       "cell_type": "code",
 434       "metadata": {
 435         "colab": {
 436           "base_uri": "https://localhost:8080/",
 437           "height": 634
 438         },
 439         "id": "Gkd5ecCmL6Bw",
 440         "outputId": "c8f8cd9a-8477-46b9-e350-9b501f8bf55b"
 441       },
 442       "source": [
 443         "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
 444         "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
 445         "plt.xlabel('Year', fontsize=30);"
 446       ],
 447       "execution_count": null,
 448       "outputs": [
 449         {
 450           "output_type": "display_data",
 451           "data": {
 452             "image/png": "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\n",
 453             "text/plain": [
 454               "<Figure size 1440x720 with 1 Axes>"
 455             ]
 456           },
 457           "metadata": {}
 458         }
 459       ]
 460     },
 461     {
 462       "cell_type": "markdown",
 463       "metadata": {
 464         "id": "JKNmf5TeFvQt"
 465       },
 466       "source": [
 467         "We have successfully removed the seasonality and we saw an upward trend for `ellis-cpu.wait_perc`! But how do these two search terms compare?\n",
 468         "\n",
 469         "We can figure this out by plotting the trends of `'ellis-cpu.wait_perc'`, `cpu_system_perc` and `'load_avg_1_min'` on a single figure:"
 470       ]
 471     },
 472     {
 473       "cell_type": "code",
 474       "metadata": {
 475         "colab": {
 476           "base_uri": "https://localhost:8080/",
 477           "height": 624
 478         },
 479         "id": "EycZrQU0MBSX",
 480         "outputId": "02683682-38ad-4745-c7bb-99a9058bb755"
 481       },
 482       "source": [
 483         "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
 484         "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
 485         "plt.xlabel('Year', fontsize=20); "
 486       ],
 487       "execution_count": null,
 488       "outputs": [
 489         {
 490           "output_type": "display_data",
 491           "data": {
 492 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\n",
 493             "text/plain": [
 494               "<Figure size 1440x720 with 1 Axes>"
 495             ]
 496           },
 497           "metadata": {}
 498         }
 499       ]
 500     },
 501     {
 502       "cell_type": "markdown",
 503       "metadata": {
 504         "id": "PTkbQPa_6MNb"
 505       },
 506       "source": [
 507         "We established the correlation matrix for Ellis data.\n",
 508         "Seaborn has five built-in themes to style its plots: `darkgrid`, `whitegrid`, `dark`, `white`, and `ticks`. Seaborn defaults to using the darkgrid theme for its plots, but we can change this styling to better suit our presentation needs.\n",
 509         "\n",
 510         "To use any of the preset themes pass the name of it to `sns.set_style()`."
 511       ]
 512     },
 513     {
 514       "cell_type": "code",
 515       "metadata": {
 516         "colab": {
 517           "base_uri": "https://localhost:8080/",
 518           "height": 710
 519         },
 520         "id": "Pi8UMMitMa3Q",
 521         "outputId": "6e2c3c3c-5a69-42ef-87a8-7dfdd65e7ceb"
 522       },
 523       "source": [
 524         "# we establish the corrmartrice\n",
 525         "import seaborn as sns\n",
 526         "color = sns.color_palette()\n",
 527         "sns.set_style('darkgrid')\n",
 528         "\n",
 529         "correaltionMatrice = df_Ellis.corr()\n",
 530         "f, ax = plt.subplots(figsize=(20, 10))\n",
 531         "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
 532         "plt.show()"
 533       ],
 534       "execution_count": null,
 535       "outputs": [
 536         {
 537           "output_type": "display_data",
 538           "data": {
 539 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\n",
 540             "text/plain": [
 541               "<Figure size 1440x720 with 2 Axes>"
 542             ]
 543           },
 544           "metadata": {}
 545         }
 546       ]
 547     },
 548     {
 549       "cell_type": "markdown",
 550       "metadata": {
 551         "id": "tdg8lD0OHEtH"
 552       },
 553       "source": [
 554         "Correlation between rows or columns of two DataFrame objectsCompute pairwise"
 555       ]
 556     },
 557     {
 558       "cell_type": "code",
 559       "metadata": {
 560         "colab": {
 561           "base_uri": "https://localhost:8080/"
 562         },
 563         "id": "rkYwyKtXMvpy",
 564         "outputId": "ab6efc64-5329-4ad2-e5a8-acecf7c79eff"
 565       },
 566       "source": [
 567         "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
 568       ],
 569       "execution_count": null,
 570       "outputs": [
 571         {
 572           "output_type": "execute_result",
 573           "data": {
 574             "text/plain": [
 575               "ellis-cpu.system_perc       -0.316956\n",
 576               "ellis-cpu.wait_perc          0.886739\n",
 577               "ellis-load.avg_1_min         1.000000\n",
 578               "ellis-mem.free_mb           -0.335300\n",
 579               "ellis-net.in_bytes_sec      -0.681849\n",
 580               "ellis-net.out_packets_sec   -0.116851\n",
 581               "Label                        0.279330\n",
 582               "dtype: float64"
 583             ]
 584           },
 585           "metadata": {},
 586           "execution_count": 49
 587         }
 588       ]
 589     },
 590     {
 591       "cell_type": "code",
 592       "metadata": {
 593         "colab": {
 594           "base_uri": "https://localhost:8080/",
 595           "height": 235
 596         },
 597         "id": "5oQK-ddinvCM",
 598         "outputId": "3e1fc354-aefb-496b-9e08-d05a458f9c23"
 599       },
 600       "source": [
 601         "## ## using multivariate feature \n",
 602         "\n",
 603         "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
 604         "\n",
 605         "features = df_Ellis[features_3]\n",
 606         "features.index = df_Ellis['Timestamp']\n",
 607         "features.head()"
 608       ],
 609       "execution_count": null,
 610       "outputs": [
 611         {
 612           "output_type": "execute_result",
 613           "data": {
 614             "text/html": [
 615               "<div>\n",
 616               "<style scoped>\n",
 617               "    .dataframe tbody tr th:only-of-type {\n",
 618               "        vertical-align: middle;\n",
 619               "    }\n",
 620               "\n",
 621               "    .dataframe tbody tr th {\n",
 622               "        vertical-align: top;\n",
 623               "    }\n",
 624               "\n",
 625               "    .dataframe thead th {\n",
 626               "        text-align: right;\n",
 627               "    }\n",
 628               "</style>\n",
 629               "<table border=\"1\" class=\"dataframe\">\n",
 630               "  <thead>\n",
 631               "    <tr style=\"text-align: right;\">\n",
 632               "      <th></th>\n",
 633               "      <th>ellis-cpu.wait_perc</th>\n",
 634               "      <th>ellis-load.avg_1_min</th>\n",
 635               "      <th>ellis-net.in_bytes_sec</th>\n",
 636               "      <th>Label</th>\n",
 637               "    </tr>\n",
 638               "    <tr>\n",
 639               "      <th>Timestamp</th>\n",
 640               "      <th></th>\n",
 641               "      <th></th>\n",
 642               "      <th></th>\n",
 643               "      <th></th>\n",
 644               "    </tr>\n",
 645               "  </thead>\n",
 646               "  <tbody>\n",
 647               "    <tr>\n",
 648               "      <th>14-09-2016 0:00</th>\n",
 649               "      <td>12.9</td>\n",
 650               "      <td>1.73</td>\n",
 651               "      <td>5413.200</td>\n",
 652               "      <td>1</td>\n",
 653               "    </tr>\n",
 654               "    <tr>\n",
 655               "      <th>14-09-2016 0:00</th>\n",
 656               "      <td>10.3</td>\n",
 657               "      <td>1.79</td>\n",
 658               "      <td>5201.667</td>\n",
 659               "      <td>1</td>\n",
 660               "    </tr>\n",
 661               "    <tr>\n",
 662               "      <th>14-09-2016 0:01</th>\n",
 663               "      <td>11.8</td>\n",
 664               "      <td>1.52</td>\n",
 665               "      <td>5370.733</td>\n",
 666               "      <td>1</td>\n",
 667               "    </tr>\n",
 668               "    <tr>\n",
 669               "      <th>14-09-2016 0:01</th>\n",
 670               "      <td>12.9</td>\n",
 671               "      <td>1.43</td>\n",
 672               "      <td>5292.467</td>\n",
 673               "      <td>1</td>\n",
 674               "    </tr>\n",
 675               "    <tr>\n",
 676               "      <th>14-09-2016 0:02</th>\n",
 677               "      <td>12.1</td>\n",
 678               "      <td>1.44</td>\n",
 679               "      <td>5318.167</td>\n",
 680               "      <td>1</td>\n",
 681               "    </tr>\n",
 682               "  </tbody>\n",
 683               "</table>\n",
 684               "</div>"
 685             ],
 686             "text/plain": [
 687               "                 ellis-cpu.wait_perc  ...  Label\n",
 688               "Timestamp                             ...       \n",
 689               "14-09-2016 0:00                 12.9  ...      1\n",
 690               "14-09-2016 0:00                 10.3  ...      1\n",
 691               "14-09-2016 0:01                 11.8  ...      1\n",
 692               "14-09-2016 0:01                 12.9  ...      1\n",
 693               "14-09-2016 0:02                 12.1  ...      1\n",
 694               "\n",
 695               "[5 rows x 4 columns]"
 696             ]
 697           },
 698           "metadata": {},
 699           "execution_count": 50
 700         }
 701       ]
 702     },
 703     {
 704       "cell_type": "code",
 705       "metadata": {
 706         "colab": {
 707           "base_uri": "https://localhost:8080/",
 708           "height": 386
 709         },
 710         "id": "qbqn755fo81g",
 711         "outputId": "a8c2999d-5fd1-4de3-f8fd-05cd6ff14622"
 712       },
 713       "source": [
 714         "features.plot(subplots=True)"
 715       ],
 716       "execution_count": null,
 717       "outputs": [
 718         {
 719           "output_type": "execute_result",
 720           "data": {
 721             "text/plain": [
 722               "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f21c0790>,\n",
 723               "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f217f790>,\n",
 724               "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f2132b90>,\n",
 725               "       <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3f20e9f50>],\n",
 726               "      dtype=object)"
 727             ]
 728           },
 729           "metadata": {},
 730           "execution_count": 51
 731         },
 732         {
 733           "output_type": "display_data",
 734           "data": {
 735             "image/png": "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\n",
 736             "text/plain": [
 737               "<Figure size 432x288 with 4 Axes>"
 738             ]
 739           },
 740           "metadata": {}
 741         }
 742       ]
 743     },
 744     {
 745       "cell_type": "code",
 746       "metadata": {
 747         "id": "jJQD1x9psWCH"
 748       },
 749       "source": [
 750         "features = features.values"
 751       ],
 752       "execution_count": null,
 753       "outputs": []
 754     },
 755     {
 756       "cell_type": "markdown",
 757       "metadata": {
 758         "id": "Q23ry_WpH6tt"
 759       },
 760       "source": [
 761         "train test split for simple time series moving window average"
 762       ]
 763     },
 764     {
 765       "cell_type": "code",
 766       "metadata": {
 767         "colab": {
 768           "base_uri": "https://localhost:8080/"
 769         },
 770         "id": "xf8WCiykpUzN",
 771         "outputId": "6375471f-a7ec-4416-95e0-4f9a82872168"
 772       },
 773       "source": [
 774         "### standardize data\n",
 775         "train_split = 141600\n",
 776         "tf.random.set_seed(13)\n",
 777         "\n",
 778         "### standardize data\n",
 779         "features_mean = features[:train_split].mean()\n",
 780         "features_std = features[:train_split].std()\n",
 781         "features  = (features - features_mean)/ features_std\n",
 782         "\n",
 783         "print(type(features))\n",
 784         "print(features.shape)\n"
 785       ],
 786       "execution_count": null,
 787       "outputs": [
 788         {
 789           "output_type": "stream",
 790           "name": "stdout",
 791           "text": [
 792             "<class 'numpy.ndarray'>\n",
 793             "(177000, 4)\n"
 794           ]
 795         }
 796       ]
 797     },
 798     {
 799       "cell_type": "markdown",
 800       "metadata": {
 801         "id": "22Y4ztlZIpFG"
 802       },
 803       "source": [
 804         "Created multivariate data"
 805       ]
 806     },
 807     {
 808       "cell_type": "code",
 809       "metadata": {
 810         "id": "1a0hNDmppnLB"
 811       },
 812       "source": [
 813         "### create mutlivariate data\n",
 814         "\n",
 815         "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
 816         "                      step ,  single_step = False):\n",
 817         "  data = []\n",
 818         "  labels = []\n",
 819         "  start_idx = start_idx + history_size\n",
 820         "  if end_idx is None:\n",
 821         "    end_idx = len(features)- target_size\n",
 822         "  for i in range(start_idx , end_idx ):\n",
 823         "    idxs = range(i-history_size, i, step) ### using step\n",
 824         "    data.append(features[idxs])\n",
 825         "    if single_step:\n",
 826         "      labels.append(target[i+target_size])\n",
 827         "    else:\n",
 828         "      labels.append(target[i:i+target_size])\n",
 829         "\n",
 830         "  return np.array(data) , np.array(labels)"
 831       ],
 832       "execution_count": null,
 833       "outputs": []
 834     },
 835     {
 836       "cell_type": "code",
 837       "metadata": {
 838         "colab": {
 839           "base_uri": "https://localhost:8080/"
 840         },
 841         "id": "Z0CivgkitfgE",
 842         "outputId": "3f2a841e-eec2-4cf9-e370-4ab5a8bcc725"
 843       },
 844       "source": [
 845         "### generate multivariate data\n",
 846         "\n",
 847         "history = 720\n",
 848         "future_target = 72\n",
 849         "STEP = 6\n",
 850         "\n",
 851         "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
 852         "                                            future_target, STEP , single_step = True)\n",
 853         "\n",
 854         "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
 855         "                                        future_target, STEP, single_step = True)\n",
 856         "\n",
 857         "print(x_train_ss.shape , y_train_ss.shape)\n",
 858         "print(x_val_ss.shape , y_val_ss.shape)"
 859       ],
 860       "execution_count": null,
 861       "outputs": [
 862         {
 863           "output_type": "stream",
 864           "name": "stdout",
 865           "text": [
 866             "(140880, 120, 4) (140880,)\n",
 867             "(34608, 120, 4) (34608,)\n"
 868           ]
 869         }
 870       ]
 871     },
 872     {
 873       "cell_type": "markdown",
 874       "metadata": {
 875         "id": "MMSskyxNaMj3"
 876       },
 877       "source": [
 878         "The `tf.data.Dataset` API supports writing descriptive and efficient input pipelines. Dataset usage following a common pattern:\n",
 879         "- Creating a source dataset from our input data.\n",
 880         "- Applied dataset transformations to preprocess the data.\n",
 881         "- Iterate over the dataset and process the elements.\n",
 882         "Note: Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.\n",
 883         "Once we have a dataset, we can apply transformations to prepare the data for our model:"
 884       ]
 885     },
 886     {
 887       "cell_type": "code",
 888       "metadata": {
 889         "colab": {
 890           "base_uri": "https://localhost:8080/"
 891         },
 892         "id": "VBdr2epGu3aq",
 893         "outputId": "719a1cea-6548-4597-fc05-b183cc485387"
 894       },
 895       "source": [
 896         "## tensorflow dataset\n",
 897         "batch_size = 256\n",
 898         "buffer_size = 10000\n",
 899         "\n",
 900         "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
 901         "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
 902         "\n",
 903         "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
 904         "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
 905         "\n",
 906         "print(train_ss)\n",
 907         "print(val_ss)"
 908       ],
 909       "execution_count": null,
 910       "outputs": [
 911         {
 912           "output_type": "stream",
 913           "name": "stdout",
 914           "text": [
 915             "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n",
 916             "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n"
 917           ]
 918         }
 919       ]
 920     },
 921     {
 922       "cell_type": "code",
 923       "metadata": {
 924         "colab": {
 925           "base_uri": "https://localhost:8080/"
 926         },
 927         "id": "IN6IQykaEzcF",
 928         "outputId": "f7877fba-a745-4f3e-f654-c8cdeed5181e"
 929       },
 930       "source": [
 931         "x_train_ss.shape[-2:]"
 932       ],
 933       "execution_count": null,
 934       "outputs": [
 935         {
 936           "output_type": "execute_result",
 937           "data": {
 938             "text/plain": [
 939               "(120, 4)"
 940             ]
 941           },
 942           "metadata": {},
 943           "execution_count": 57
 944         }
 945       ]
 946     },
 947     {
 948       "cell_type": "code",
 949       "metadata": {
 950         "id": "9eQpwUyGglu_"
 951       },
 952       "source": [
 953         "def root_mean_squared_error(y_true, y_pred):\n",
 954         "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
 955       ],
 956       "execution_count": null,
 957       "outputs": []
 958     },
 959     {
 960       "cell_type": "code",
 961       "metadata": {
 962         "colab": {
 963           "base_uri": "https://localhost:8080/"
 964         },
 965         "id": "1cKtTAzqyiyL",
 966         "outputId": "004c1521-5b4c-4304-fa58-76bd01a9dcca"
 967       },
 968       "source": [
 969         "from keras.layers import Activation, Dense, Dropout\n",
 970         "from keras.utils.vis_utils import plot_model\n",
 971         "### Modelling using LSTM\n",
 972         "steps = 50\n",
 973         "\n",
 974         "EPOCHS =20\n",
 975         "\n",
 976         "single_step_model = tf.keras.models.Sequential()\n",
 977         "\n",
 978         "single_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:])))\n",
 979         "#single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
 980         "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
 981         "#single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
 982         "#model.add(Dense(units=1, activation='relu'))\n",
 983         "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
 984         "single_step_model.add(tf.keras.layers.Dense(1))\n",
 985         "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
 986         "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
 987         "\n",
 988         "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
 989         "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
 990         "                                                  validation_steps = 50)\n",
 991         "\n",
 992         "plot_model(single_step_model, to_file='/content/drive/MyDrive/LFN Anuket/Analysis/data/Final/Bi-LSTM.png', show_shapes=True, show_layer_names=True)\n",
 993         "single_step_model.summary()\n",
 994         "\n"
 995       ],
 996       "execution_count": null,
 997       "outputs": [
 998         {
 999           "output_type": "stream",
1000           "name": "stdout",
1001           "text": [
1002             "Epoch 1/20\n",
1003             "50/50 [==============================] - 52s 924ms/step - loss: 0.0746 - rmse: 0.1454 - val_loss: 0.0103 - val_rmse: 0.0111\n",
1004             "Epoch 2/20\n",
1005             "50/50 [==============================] - 45s 900ms/step - loss: 0.0075 - rmse: 0.0093 - val_loss: 0.0136 - val_rmse: 0.0137\n",
1006             "Epoch 3/20\n",
1007             "50/50 [==============================] - 45s 898ms/step - loss: 0.0068 - rmse: 0.0077 - val_loss: 0.0027 - val_rmse: 0.0033\n",
1008             "Epoch 4/20\n",
1009             "50/50 [==============================] - ETA: 0s - loss: 0.0050 - rmse: 0.0061Epoch 5/20\n",
1010             "50/50 [==============================] - 44s 893ms/step - loss: 0.0089 - rmse: 0.0104 - val_loss: 0.0058 - val_rmse: 0.0062\n",
1011             "Epoch 6/20\n",
1012             "50/50 [==============================] - 45s 896ms/step - loss: 0.0081 - rmse: 0.0088 - val_loss: 0.0100 - val_rmse: 0.0102\n",
1013             "Epoch 7/20\n",
1014             "50/50 [==============================] - 45s 908ms/step - loss: 0.0063 - rmse: 0.0072 - val_loss: 0.0054 - val_rmse: 0.0057\n",
1015             "Epoch 8/20\n",
1016             "50/50 [==============================] - 45s 911ms/step - loss: 0.0030 - rmse: 0.0038 - val_loss: 0.0044 - val_rmse: 0.0046\n",
1017             "Epoch 9/20\n",
1018             "50/50 [==============================] - 45s 913ms/step - loss: 0.0056 - rmse: 0.0066 - val_loss: 0.0055 - val_rmse: 0.0055\n",
1019             "Epoch 10/20\n",
1020             "50/50 [==============================] - 46s 917ms/step - loss: 0.0045 - rmse: 0.0055 - val_loss: 0.0070 - val_rmse: 0.0070\n",
1021             "Epoch 11/20\n",
1022             "50/50 [==============================] - 45s 910ms/step - loss: 0.0035 - rmse: 0.0040 - val_loss: 0.0014 - val_rmse: 0.0015\n",
1023             "Epoch 12/20\n",
1024             "50/50 [==============================] - 44s 898ms/step - loss: 0.0198 - rmse: 0.0304 - val_loss: 0.0077 - val_rmse: 0.0077\n",
1025             "Epoch 13/20\n",
1026             "50/50 [==============================] - 45s 900ms/step - loss: 0.0051 - rmse: 0.0065 - val_loss: 0.0012 - val_rmse: 0.0013\n",
1027             "Epoch 14/20\n",
1028             "50/50 [==============================] - 48s 965ms/step - loss: 0.0060 - rmse: 0.0074 - val_loss: 0.0026 - val_rmse: 0.0026\n",
1029             "Epoch 15/20\n",
1030             "50/50 [==============================] - 46s 917ms/step - loss: 0.0041 - rmse: 0.0053 - val_loss: 0.0017 - val_rmse: 0.0018\n",
1031             "Epoch 16/20\n",
1032             "50/50 [==============================] - 45s 914ms/step - loss: 0.0040 - rmse: 0.0053 - val_loss: 0.0035 - val_rmse: 0.0035\n",
1033             "Epoch 17/20\n",
1034             "50/50 [==============================] - 45s 910ms/step - loss: 0.0025 - rmse: 0.0027 - val_loss: 0.0025 - val_rmse: 0.0026\n",
1035             "Epoch 18/20\n",
1036             "50/50 [==============================] - ETA: 0s - loss: 0.0025 - rmse: 0.0027Epoch 19/20\n",
1037             "50/50 [==============================] - 45s 909ms/step - loss: 0.0024 - rmse: 0.0027 - val_loss: 0.0023 - val_rmse: 0.0024\n",
1038             "Epoch 20/20\n",
1039             "50/50 [==============================] - 46s 917ms/step - loss: 0.0020 - rmse: 0.0024 - val_loss: 7.3451e-04 - val_rmse: 8.8589e-04\n",
1040             "Model: \"sequential_3\"\n",
1041             "_________________________________________________________________\n",
1042             "Layer (type)                 Output Shape              Param #   \n",
1043             "=================================================================\n",
1044             "bidirectional_3 (Bidirection (None, 120, 64)           9472      \n",
1045             "_________________________________________________________________\n",
1046             "lstm_7 (LSTM)                (None, 100)               66000     \n",
1047             "_________________________________________________________________\n",
1048             "activation_3 (Activation)    (None, 100)               0         \n",
1049             "_________________________________________________________________\n",
1050             "dense_3 (Dense)              (None, 1)                 101       \n",
1051             "=================================================================\n",
1052             "Total params: 75,573\n",
1053             "Trainable params: 75,573\n",
1054             "Non-trainable params: 0\n",
1055             "_________________________________________________________________\n"
1056           ]
1057         }
1058       ]
1059     },
1060     {
1061       "cell_type": "code",
1062       "metadata": {
1063         "id": "rePzISUuFmlM"
1064       },
1065       "source": [
1066         ""
1067       ],
1068       "execution_count": null,
1069       "outputs": []
1070     },
1071     {
1072       "cell_type": "code",
1073       "metadata": {
1074         "colab": {
1075           "base_uri": "https://localhost:8080/",
1076           "height": 281
1077         },
1078         "id": "Pgev0dgzzBVx",
1079         "outputId": "90d76f79-4228-4f67-ef58-eb0c6f9e9390"
1080       },
1081       "source": [
1082         "## plot train test loss \n",
1083         "\n",
1084         "def plot_loss(history , title):\n",
1085         "  loss = history.history['loss']\n",
1086         "  val_loss = history.history['val_loss']\n",
1087         "\n",
1088         "  epochs = range(len(loss))\n",
1089         "  plt.figure()\n",
1090         "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
1091         "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
1092         "  plt.title(title)\n",
1093         "  plt.legend()\n",
1094         "  plt.grid()\n",
1095         "  plt.show()\n",
1096         "\n",
1097         "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
1098       ],
1099       "execution_count": null,
1100       "outputs": [
1101         {
1102           "output_type": "display_data",
1103           "data": {
1104 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\n",
1105             "text/plain": [
1106               "<Figure size 432x288 with 1 Axes>"
1107             ]
1108           },
1109           "metadata": {}
1110         }
1111       ]
1112     },
1113     {
1114       "cell_type": "code",
1115       "metadata": {
1116         "colab": {
1117           "base_uri": "https://localhost:8080/",
1118           "height": 281
1119         },
1120         "id": "EnYf6j4okEoC",
1121         "outputId": "16fab4ff-15d9-424a-a599-6f03e1ad0e8b"
1122       },
1123       "source": [
1124         "## plot train test loss \n",
1125         "\n",
1126         "def plot_loss(history , title):\n",
1127         "  loss = history.history['rmse']\n",
1128         "  val_loss = history.history['val_rmse']\n",
1129         "\n",
1130         "  epochs = range(len(loss))\n",
1131         "  plt.figure()\n",
1132         "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
1133         "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
1134         "  plt.title(title)\n",
1135         "  plt.legend()\n",
1136         "  plt.grid()\n",
1137         "  plt.show()\n",
1138         "\n",
1139         "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
1140       ],
1141       "execution_count": null,
1142       "outputs": [
1143         {
1144           "output_type": "display_data",
1145           "data": {
1146 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\n",
1147             "text/plain": [
1148               "<Figure size 432x288 with 1 Axes>"
1149             ]
1150           },
1151           "metadata": {}
1152         }
1153       ]
1154     },
1155     {
1156       "cell_type": "code",
1157       "metadata": {
1158         "id": "WMegV8mNAwe_"
1159       },
1160       "source": [
1161         "### fucntion to create time steps\n",
1162         "def create_time_steps(length):\n",
1163         "  return list(range(-length,0))\n",
1164         "\n",
1165         "### function to plot time series data\n",
1166         "\n",
1167         "def plot_time_series(plot_data, delta , title):\n",
1168         "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
1169         "  marker = ['.-' , 'rx' , 'go']\n",
1170         "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
1171         "\n",
1172         "  if delta:\n",
1173         "    future = delta\n",
1174         "  else:\n",
1175         "    future = 0\n",
1176         "  plt.title(title)\n",
1177         "  for i , x in enumerate(plot_data):\n",
1178         "    if i :\n",
1179         "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
1180         "    else:\n",
1181         "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
1182         "  plt.legend()\n",
1183         "  plt.xlim([time_steps[0], (future+5) *2])\n",
1184         "\n",
1185         "  plt.xlabel('Time_Step')\n",
1186         "  return plt"
1187       ],
1188       "execution_count": null,
1189       "outputs": []
1190     },
1191     {
1192       "cell_type": "code",
1193       "metadata": {
1194         "id": "q99i2c-9XKF3"
1195       },
1196       "source": [
1197         "### Moving window average\n",
1198         "\n",
1199         "def MWA(history):\n",
1200         "  return np.mean(history)"
1201       ],
1202       "execution_count": null,
1203       "outputs": []
1204     },
1205     {
1206       "cell_type": "code",
1207       "metadata": {
1208         "id": "xFJT1rZDAUVL",
1209         "colab": {
1210           "base_uri": "https://localhost:8080/",
1211           "height": 1000
1212         },
1213         "outputId": "d0dc9e7a-bc96-4f19-815f-da9ed8a82408"
1214       },
1215       "source": [
1216         "# plot time series and predicted values\n",
1217         "\n",
1218         "for x, y in val_ss.take(5):\n",
1219         "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
1220         "                    single_step_model.predict(x)[0]], 12,\n",
1221         "                   'Single Step Prediction')\n",
1222         "  plot.show()"
1223       ],
1224       "execution_count": null,
1225       "outputs": [
1226         {
1227           "output_type": "display_data",
1228           "data": {
1229             "image/png": "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\n",
1230             "text/plain": [
1231               "<Figure size 432x288 with 1 Axes>"
1232             ]
1233           },
1234           "metadata": {}
1235         },
1236         {
1237           "output_type": "display_data",
1238           "data": {
1239 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\n",
1240             "text/plain": [
1241               "<Figure size 432x288 with 1 Axes>"
1242             ]
1243           },
1244           "metadata": {}
1245         },
1246         {
1247           "output_type": "display_data",
1248           "data": {
1249 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\n",
1250             "text/plain": [
1251               "<Figure size 432x288 with 1 Axes>"
1252             ]
1253           },
1254           "metadata": {}
1255         },
1256         {
1257           "output_type": "display_data",
1258           "data": {
1259 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\n",
1260             "text/plain": [
1261               "<Figure size 432x288 with 1 Axes>"
1262             ]
1263           },
1264           "metadata": {}
1265         },
1266         {
1267           "output_type": "display_data",
1268           "data": {
1269 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\n",
1270             "text/plain": [
1271               "<Figure size 432x288 with 1 Axes>"
1272             ]
1273           },
1274           "metadata": {}
1275         }
1276       ]
1277     },
1278     {
1279       "cell_type": "markdown",
1280       "metadata": {
1281         "id": "_KXWQVmyCSix"
1282       },
1283       "source": [
1284         "# **MultiStep Forcasting**"
1285       ]
1286     },
1287     {
1288       "cell_type": "code",
1289       "metadata": {
1290         "id": "Lu7m2Rr4AbMK",
1291         "colab": {
1292           "base_uri": "https://localhost:8080/"
1293         },
1294         "outputId": "e0d07c10-c644-4a91-8723-5fc94e35c3a5"
1295       },
1296       "source": [
1297         "future_target = 72 # 72 future values\n",
1298         "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
1299         "                                                 train_split, history,\n",
1300         "                                                 future_target, STEP)\n",
1301         "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
1302         "                                             train_split, None, history,\n",
1303         "                                             future_target, STEP)\n",
1304         "\n",
1305         "print(x_train_multi.shape)\n",
1306         "print(y_train_multi.shape)"
1307       ],
1308       "execution_count": null,
1309       "outputs": [
1310         {
1311           "output_type": "stream",
1312           "name": "stdout",
1313           "text": [
1314             "(140880, 120, 4)\n",
1315             "(140880, 72)\n"
1316           ]
1317         }
1318       ]
1319     },
1320     {
1321       "cell_type": "code",
1322       "metadata": {
1323         "id": "GLRv5D16CrHj"
1324       },
1325       "source": [
1326         "#  TF DATASET\n",
1327         "\n",
1328         "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
1329         "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
1330         "\n",
1331         "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
1332         "val_data_multi = val_data_multi.batch(batch_size).repeat()"
1333       ],
1334       "execution_count": null,
1335       "outputs": []
1336     },
1337     {
1338       "cell_type": "code",
1339       "metadata": {
1340         "id": "fjXexah9C8yg",
1341         "colab": {
1342           "base_uri": "https://localhost:8080/"
1343         },
1344         "outputId": "8e521731-9e70-48b3-b630-44adc32f93fb"
1345       },
1346       "source": [
1347         "print(train_data_multi)\n",
1348         "print(val_data_multi)"
1349       ],
1350       "execution_count": null,
1351       "outputs": [
1352         {
1353           "output_type": "stream",
1354           "name": "stdout",
1355           "text": [
1356             "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n",
1357             "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n"
1358           ]
1359         }
1360       ]
1361     },
1362     {
1363       "cell_type": "code",
1364       "metadata": {
1365         "id": "7mtLZ6S-DPU-",
1366         "colab": {
1367           "base_uri": "https://localhost:8080/",
1368           "height": 385
1369         },
1370         "outputId": "c6ae5f81-b61d-47e6-cd05-f96a5658ae2d"
1371       },
1372       "source": [
1373         "#plotting function\n",
1374         "def multi_step_plot(history, true_future, prediction):\n",
1375         "  plt.figure(figsize=(12, 6))\n",
1376         "  num_in = create_time_steps(len(history))\n",
1377         "  num_out = len(true_future)\n",
1378         "  plt.grid()\n",
1379         "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
1380         "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
1381         "           label='True Future')\n",
1382         "  if prediction.any():\n",
1383         "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
1384         "             label='Predicted Future')\n",
1385         "  plt.legend(loc='upper left')\n",
1386         "  plt.show()\n",
1387         "  \n",
1388         "\n",
1389         "\n",
1390         "for x, y in train_data_multi.take(1):\n",
1391         "  multi_step_plot(x[0], y[0], np.array([0]))"
1392       ],
1393       "execution_count": null,
1394       "outputs": [
1395         {
1396           "output_type": "display_data",
1397           "data": {
1398 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\n",
1399             "text/plain": [
1400               "<Figure size 864x432 with 1 Axes>"
1401             ]
1402           },
1403           "metadata": {}
1404         }
1405       ]
1406     },
1407     {
1408       "cell_type": "markdown",
1409       "metadata": {
1410         "id": "eaIjVnzCJwCS"
1411       },
1412       "source": [
1413         "Bi-directional LSTM:\n",
1414         "On some sequence prediction problems, it can be beneficial to allow the LSTM model to learn the input sequence both forward and backwards and concatenate both interpretations. This is known as bidirectional.\n",
1415         "\n",
1416         "Here, `tf.keras.layers.Bidirectional` is a bidirectional wrapper for RNNs which inherits from `Wrapper`, `Layer`, and `module`"
1417       ]
1418     },
1419     {
1420       "cell_type": "code",
1421       "metadata": {
1422         "id": "snN_Flr5DWQN",
1423         "colab": {
1424           "base_uri": "https://localhost:8080/"
1425         },
1426         "outputId": "be27d60a-53b9-4e83-f1e3-45bf9b751196"
1427       },
1428       "source": [
1429         "multi_step_model = tf.keras.models.Sequential()\n",
1430         "multi_step_model.add(tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32,\n",
1431         "                                          return_sequences=True,\n",
1432         "                                          input_shape=x_train_multi.shape[-2:])))\n",
1433         "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
1434         "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
1435         "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
1436         "#model.add(Dense(units=1, activation='relu'))\n",
1437         "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
1438         "#aDD dropout layer (0.3)\n",
1439         "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
1440         "\n",
1441         "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
1442         "\n",
1443         "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
1444         "                                          steps_per_epoch=steps,\n",
1445         "                                          validation_data=val_data_multi,\n",
1446         "                                          validation_steps=50)"
1447       ],
1448       "execution_count": null,
1449       "outputs": [
1450         {
1451           "output_type": "stream",
1452           "name": "stdout",
1453           "text": [
1454             "Epoch 1/20\n",
1455             "50/50 [==============================] - 54s 946ms/step - loss: 0.1534 - rmse: 0.2114 - val_loss: 0.0481 - val_rmse: 0.0489\n",
1456             "Epoch 2/20\n",
1457             "50/50 [==============================] - 46s 917ms/step - loss: 0.0785 - rmse: 0.0995 - val_loss: 0.0406 - val_rmse: 0.0412\n",
1458             "Epoch 3/20\n",
1459             "50/50 [==============================] - 46s 916ms/step - loss: 0.0619 - rmse: 0.0781 - val_loss: 0.0095 - val_rmse: 0.0100\n",
1460             "Epoch 4/20\n",
1461             "50/50 [==============================] - 46s 919ms/step - loss: 0.0526 - rmse: 0.0661 - val_loss: 0.0170 - val_rmse: 0.0172\n",
1462             "Epoch 5/20\n",
1463             "50/50 [==============================] - 46s 915ms/step - loss: 0.0466 - rmse: 0.0584 - val_loss: 0.0077 - val_rmse: 0.0080\n",
1464             "Epoch 6/20\n",
1465             "50/50 [==============================] - 46s 920ms/step - loss: 0.0421 - rmse: 0.0529 - val_loss: 0.0325 - val_rmse: 0.0326\n",
1466             "Epoch 7/20\n",
1467             "50/50 [==============================] - 47s 937ms/step - loss: 0.0390 - rmse: 0.0489 - val_loss: 0.0140 - val_rmse: 0.0141\n",
1468             "Epoch 8/20\n",
1469             "50/50 [==============================] - 47s 936ms/step - loss: 0.0365 - rmse: 0.0458 - val_loss: 0.0085 - val_rmse: 0.0086\n",
1470             "Epoch 9/20\n",
1471             "50/50 [==============================] - 47s 935ms/step - loss: 0.0342 - rmse: 0.0429 - val_loss: 0.0196 - val_rmse: 0.0196\n",
1472             "Epoch 10/20\n",
1473             "50/50 [==============================] - 46s 927ms/step - loss: 0.0325 - rmse: 0.0406 - val_loss: 0.0135 - val_rmse: 0.0136\n",
1474             "Epoch 11/20\n",
1475             "50/50 [==============================] - 46s 920ms/step - loss: 0.0308 - rmse: 0.0385 - val_loss: 0.0187 - val_rmse: 0.0187\n",
1476             "Epoch 12/20\n",
1477             "50/50 [==============================] - 45s 918ms/step - loss: 0.0297 - rmse: 0.0371 - val_loss: 0.0072 - val_rmse: 0.0074\n",
1478             "Epoch 13/20\n",
1479             "50/50 [==============================] - 46s 924ms/step - loss: 0.0281 - rmse: 0.0352 - val_loss: 0.0015 - val_rmse: 0.0018\n",
1480             "Epoch 14/20\n",
1481             "50/50 [==============================] - 46s 922ms/step - loss: 0.0269 - rmse: 0.0336 - val_loss: 0.0153 - val_rmse: 0.0154\n",
1482             "Epoch 15/20\n",
1483             "50/50 [==============================] - 46s 920ms/step - loss: 0.0257 - rmse: 0.0323 - val_loss: 0.0049 - val_rmse: 0.0050\n",
1484             "Epoch 16/20\n",
1485             "50/50 [==============================] - 45s 905ms/step - loss: 0.0252 - rmse: 0.0315 - val_loss: 0.0031 - val_rmse: 0.0033\n",
1486             "Epoch 17/20\n",
1487             "50/50 [==============================] - 45s 907ms/step - loss: 0.0239 - rmse: 0.0299 - val_loss: 0.0178 - val_rmse: 0.0178\n",
1488             "Epoch 18/20\n",
1489             "50/50 [==============================] - 45s 906ms/step - loss: 0.0230 - rmse: 0.0289 - val_loss: 0.0084 - val_rmse: 0.0085\n",
1490             "Epoch 19/20\n",
1491             "50/50 [==============================] - 45s 906ms/step - loss: 0.0224 - rmse: 0.0280 - val_loss: 0.0072 - val_rmse: 0.0072\n",
1492             "Epoch 20/20\n",
1493             "50/50 [==============================] - 45s 913ms/step - loss: 0.0216 - rmse: 0.0271 - val_loss: 0.0101 - val_rmse: 0.0101\n"
1494           ]
1495         }
1496       ]
1497     },
1498     {
1499       "cell_type": "code",
1500       "metadata": {
1501         "id": "Ay5m27doDsTt",
1502         "colab": {
1503           "base_uri": "https://localhost:8080/",
1504           "height": 281
1505         },
1506         "outputId": "74bc7df8-2315-401b-8cd8-d7632c14abb7"
1507       },
1508       "source": [
1509         "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
1510       ],
1511       "execution_count": null,
1512       "outputs": [
1513         {
1514           "output_type": "display_data",
1515           "data": {
1516             "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEICAYAAABRSj9aAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzdeZxN9R/H8ddd5s6+MeYSQ5mRPRQho8kMhsa+lgglW4rqp30lREqMsmQtbYhkhhJZS5aoKVvIWGcGs+937r3n98c1l4nZV/d+no/HPObee7bPucb7nPs93/s9KkVRFIQQQtgsdWUXIIQQonxJ0AshhI2ToBdCCBsnQS+EEDZOgl4IIWycBL0QQtg4CfrbTMOGDTl79my+08PCwti3b18FVlTxirOPt8v7Udi/a0lcuHCBhg0bYjQaARg1ahTr168v0rzFtXDhQl577bUS15qfdevW8eijj5b5eu2NtrILsBfBwcFcvnyZXbt2Ua1aNevrffr04dixY2zbto06deoUa50vv/wyer2e5557zvpaZGRkgcusWbOGpUuXEhcXh7OzM02bNmXOnDm4ubndcn1l4dKlS4SFhVmfZ2Rk4OzsjEqlAuDTTz+ldevWRV5fYftY0nlt3ZIlS8pkPfv27WPy5Mns2rXL+trYsWPLZN2ifEjQV6DatWsTGRnJsGHDADhx4gSZmZkVtv39+/czZ84clixZQpMmTUhKSmL79u3lvt077riDw4cPW583bNiQDRs2UK9evZvmNRqNaLXyZylEWZKmmwrUu3dvvvvuO+vz7777jj59+uSZZ9iwYaxZs8b6PL+Prt988w0bN25k6dKltGrVynpGFRwczK+//nrL7f/111+0bNmSJk2aAODl5UXfvn1xc3PLd31xcXE888wztGvXjuDgYD777DPr+sLDw3n22WeZNGkSrVq1om/fvhw/frxY78m6det45JFHmD59Om3btiU8PJxz587x+OOP07ZtW9q2bcsLL7xASkqKdZkb9zE8PJyJEyfy4osv0qpVK8LCwvjrr79KNO+RI0fo06cPrVq1su7XnDlzbll3UWpcunQpPXv25L777mPSpElkZ2dbpy9ZsoTAwEACAwNZu3Ztvu/Ppk2b6NevX57XVqxYYf332bFjB3369OHee+8lKCiI8PDwfNd149+WyWRi5syZtG3blpCQEHbu3Jln3m+//Zbu3bvTqlUrQkJC+PrrrwHLp7GnnnqKy5cv06pVK1q1akVcXBzh4eH873//sy6/bds2wsLCaN26NcOGDeP06dNFfm8KcujQIfr37899991H//79OXTokHXaunXrCAkJoVWrVgQHB/P9998DcPbsWYYOHcp9991H27ZtmTRpUpG2ZUsk6CtQy5YtSUtL4/Tp05hMJiIjI+nVq1eJ1jV48GB69uzJk08+yeHDh1m4cGGhy7Ro0YI9e/Ywb948fv/9dwwGQ4HrM5vNjBs3joYNG7Jr1y5WrlzJypUr2b17t3W5bdu20a1bN/bv30+PHj0YP348OTk5xdqXqKgo/Pz8+OWXXxg3bhyKojBmzBh2797N5s2biY2NLTDAfv75Z8LCwjh48CDBwcFMnTq12PMaDAYmTJhA3759rfuydevWfNdTlBo3b97MkiVL2LZtGydOnGDdunUA7Nq1i2XLlrFs2TK2bNnC3r17891Op06dOHPmDNHR0dbXNm7cSM+ePQFwdnZm5syZHDx4kEWLFvHVV18VWHeu1atXs337dr777ju+/fZbfvjhhzzTq1evzqJFizh06BAzZsxgxowZHDlyBBcXFz799FN8fX05fPgwhw8fRq/X51n2zJkzvPDCC7z66qvs3buXBx98kLFjx+b5e8vvvSlIUlISY8aMYdiwYezbt4+RI0cyZswYEhMTycjI4N133+XTTz/l8OHDfP311zRu3BiAuXPn0qFDBw4cOMCuXbsYOnRooduyNRL0FSz3rP6XX37B39//pv8k5al169aEh4dz9OhRxowZQ9u2bZkxYwYmk+mW8//1118kJCQwYcIEdDodfn5+DBo0iE2bNlnnadq0Kd26dcPBwYGRI0diMBj4888/i1WXr68vw4YNQ6vV4uTkRL169ejQoQM6nY5q1aoxcuRIDhw4kO/y9913H0FBQWg0Gnr37l3gp4r85v3zzz8xGo08/vjjODg40LVrV5o3b57veopS47Bhw9Dr9Xh5edGpUyeOHTsGWEKuX79+3H333bi4uDBhwoR8t+Ps7ExISAgREREAREdH8++//xIcHAxA27ZtadiwIWq1mkaNGhEWFsb+/fvzXV+uzZs3M3z4cGrVqoWXlxdjxozJM/2hhx6ibt26qFQq7r//fjp06MDBgwcLXS9YPoUEBQXRoUMHHBwcePLJJ8nKysrTfJffe1OQHTt2UK9ePfr06YNWq6VHjx7Ur1/f2vyoVqs5efIkWVlZ+Pr60qBBAwC0Wi2XLl3i8uXLODo6Fut6kK2QxtAK1rt3b4YOHcqFCxfo3bt3uW6rVatW1seRkZHccccdBAUFERQUhNlsZt++fUycOJG77rqLRx555KblL168yOXLl/P8xzCZTHme16xZ0/pYrVaj1+u5fPlyseq8cR0AV69eZdq0aRw8eJD09HQURcHDwyPf5X18fKyPnZycyM7OzretP795L1++jF6vt14gBqhVq1a+2yxKjTVq1LA+dnZ2tr4vly9fplmzZtZptWvXznc7AD179uS9995jwoQJRERE0LlzZ5ydnQHLAWr27NmcPHmSnJwcDAYD3bp1K3B9uTXcuH933HFHnuk7d+7k448/Jjo6GrPZTFZWFnfffXeh681d943rU6vV1KpVi7i4OOtr+b03xVlvbt1xcXG4uLgwZ84cli1bxmuvvca9997LSy+9hL+/P5MnT2bu3LkMGDAAT09PRo4cyYABA4q0L7ZCgr6C1a5dmzp16rBz506mTZt203RnZ+c8F2ivXr2a77puDKVbufEM6r/UajXt27enXbt2nDx58pbrq1WrFnXq1GHLli35ric2Ntb62Gw2ExcXh6+vb4F1/dd/t/vhhx+iUqnYuHEjXl5ebN26lSlTphRrncVVo0YN4uLiUBTFWk9MTAx+fn63nL80Nfr6+hITE2N9funSpQLnf+CBB0hISODYsWNERETwyiuvWKe98MILDB06lCVLluDo6Mi0adNITEwstIYaNWrkqeHGxwaDgWeffZaZM2cSEhKCg4MD48ePJ3eg28L+7nx9ffnnn3+szxVFISYmptSfXn19fW96r2JiYujYsSMAHTt2pGPHjmRlZfHRRx/xxhtv8OWXX1KjRg3effddAA4ePMjIkSNp06bNLTsD2CppuqkE06ZNY+XKlbi4uNw0rXHjxvz0009kZmZy9uzZAi/UVa9enQsXLhR5u1u3biUyMpLk5GQURSEqKor9+/fTokWLW67vnnvuwdXVlcWLF5OVlYXJZOKff/4hKirKOs+RI0fYsmULRqORlStXotPprOsrqfT0dFxcXHB3dycuLq7MugUWpGXLlmg0GlatWoXRaGTr1q15LtSWZY3dunVj/fr1nDp1iszMTObPn1/g/A4ODnTr1o1Zs2aRnJxMhw4d8tTh6emJo6MjUVFR1iaewnTv3p3PP/+c2NhYkpOTWbx4sXWawWDAYDBQrVo1tFotO3fu5JdffrFOr169OklJSaSmpua77p07d7J3715ycnJYtmwZOp0uzyfMkggKCiI6OpqNGzdiNBrZtGkTp06d4qGHHuLq1ats3bqVjIwMdDodLi4uqNWWeMu9hgLg6emJSqWyTrMX9rW3VUTdunXzbf8dPnw4Dg4OPPDAA7z00kvWi263MmDAAE6dOkXr1q0ZP358odv19PRk9erVdO3alXvvvZfJkyfz5JNPWi8I/3d9Go2GhQsXcvz4cUJCQmjXrh2vv/46aWlp1nWGhISwadMm2rRpw4YNGwgPD8fBwaGY70heEyZM4OjRo7Ru3ZrRo0fTtWvXUq2vKHQ6HeHh4axdu5Y2bdrw/fff89BDD6HT6cq8xqCgIIYPH87w4cPp0qUL7dq1K3SZnj178uuvv9KtW7c8TVJvvfUW8+bNo1WrVnz88cd07969SDUMGjSIwMBAevfuTd++ffPU7+bmxuuvv86kSZNo06YNERER1msCAP7+/oSFhdG5c2dat26dp0kGoH79+rz//vtMnTqVdu3asX37dhYuXJjve1lU3t7eLFy4kOXLl9O2bVuWLFnCwoULqVatGmazmRUrVtCxY0fuv/9+Dhw4wNtvvw1YrjUNHDiQVq1aMW7cOF577bV8P6nZKpXceESUVHh4OGfPnmX27NmVXUq5GDhwII888gj9+/ev7FKEKBU5oxfimv3793PlyhWMRiPr16/nxIkT1vZfIW5ncjFWiGvOnDnDpEmTyMzMpE6dOsybN6/YF5aFqIqk6UYIIWycNN0IIYSNq3JNN2azGZNJPmQIIURxODho8p1W5YLeZFJISsqo7DKEEOK2UqOGe77TpOlGCCFsnAS9EELYOAl6IYSwcVWujV4IUfZMJiOJiVcwGg2FzyyqNK1Wh7d3DTSaose3BL0QdiAx8QpOTi64utYsdPRJUXUpikJ6egqJiVfw8cl/GO3/kqYbIeyA0WjA1dVDQv42p1KpcHX1KPYnMwl6IeyEhLxtKMm/o00F/fr1Wm64P7MQQghsqI0+OxvGjHHmjTeyeeYZueAkRFWRnJzExImW+yUkJMSjVqvx8vIG4NNPVxZ4/4Ljx4/yww+RTJo0ucjbGzCgJy4uLqhUKtzdPXj99XeoWdPSnh0Y2JquXbvz5puWm8IbjUb69OlGkybNmDXrIxIS4nnvvanExcVhMhmpWbMWs2fPIybmEo89NpC6da/flWrw4CF0796j2O9HZbCZoHd0BF9fM6dO2dSHFCFue56eXqxY8SUAS5cuwtnZhSFDhlmn53d/X4BGjZrQqFGTYm9z3rxFeHl5sXTpIlauXMpLL70OWG7V+e+/p8nOzsLR0YkDB/bh43N9hNIlSxbSunVbBg16FIBTp05ap9WuXdu6H7cbmwl6AH9/CXohbgfTpr2NTqfjn39OcM89LQgJ6crcuR9gMGTj6OjEq6++Sd26d3Lo0EG+/noVs2Z9xNKli4iLi+XSpYvExcUxaNCjDBx4803tb9S0aXPWrv06z2vt23fg11/30KlTZ7Zu/ZHOnbsSFfUHAPHxV7n//ut3/AoIaFD2O18JbCroAwLMREba1C4JUea++UbLV1+V7naP//XoozkMHmws1jJXrlxm4cJlaDQa0tPT+PjjT9FqtRw4sI9Fiz5m2rT3b1rm3LmzzJu3kIyMDIYM6U/fvgPy/TQAsG/fXjp2fCjPayEhXVmx4lMeeKAjp0+fIiyslzXo+/UbxFtvvcK3366mdev7CQvrhY9PDQAuXrzIiBFDrOt57rnJtGhRuvvgVhSbSkV/fzMJCWoSEqBatcquRghRkE6dOqPRWEZcTEtL49133+bChXOoVCqMxlsfNNq374BOp0On0+Ht7U1CQjy+vvqb5nv22TGkpKTg7OzMU0+NzTMtIKABMTExbN36I+3bd8gzrW3b9qxevYHfftvLvn2/MHLkY3z22TeANN1UGQEBZgBOnVJz//3mSq5GiKpp8GBjsc++y4OTk5P18ZIlC7n33tbMmDGbmJhLPPPMmFsu4+Bw/QbjarUak8l0y/nmzVuEm5sbU6a8wdKli3jmmefzTA8MfJCPP55LePgikpOT8kzz8PCka9dudO3ajRdfnMSffx6iYcPGJd3NKsGmGrRzg/70aZvaLSFsXlpaGjVqWJpINm3aWCbr1Gq1PPvsC/zwQyQpKcl5poWF9WLkyKfw9w/I8/rvvx8gKysLgIyMdC5evIBeX7NM6qlMNnVGX7eugoODIkEvxG3mscce591332blyqW0bx9YZuv18fGhc+dQ1q1bw4gRo6yv+/rqb3kh98SJY8yZMwuNRoPZbKZHjz40btyUmJhLN7XRh4X1KvRicFVRpHvG7tq1i2nTpmE2mxk4cCCjR4/OM3358uWsWbMGjUZDtWrVmD59OrVr1wZg/fr1LFiwAIBx48bRt2/fAreVk2Mq1Y1HOnRwoUEDMytWZJV4HULYmtjYs9SsWa/wGcVt4Vb/nqW68YjJZGLKlCksWbKEyMhIIiIiOHXqVJ55GjduzLfffsvGjRsJDQ3l/fctV8uTkpKYP38+q1evZs2aNcyfP5/k5ORbbabM+Pub5YxeCCFuUGgiRkVFUa9ePfz8/NDpdISFhbFt27Y887Rr1w5nZ2cAWrZsSWxsLAB79uyhQ4cOeHl54enpSYcOHdi9e3c57MZ1AQFmzpxRk881GiGEsDuFBn1cXBw1a16/GKHX64mLi8t3/rVr1/Lggw+WaNmy4O+vYDCoOHdOBnASQggo4143GzZs4O+//2bUqFGFz1xO/P2l540QQtyo0DTU6/XWphiwnKXr9Td/QeHXX39l4cKFLFiwAJ1OV6xly9KNfemFEEIUIeibN29OdHQ058+fx2AwEBkZSXBwcJ55jh49yptvvsmCBQuoXr269fXAwED27NlDcnIyycnJ7Nmzh8DAsus6dSvVqyt4eSkS9EIIcU2haajVannzzTcZNWoUDz/8MN27d6dBgwbMnTvXelF21qxZZGRkMHHiRHr37s3YsZavHHt5eTF+/HgGDBjAgAEDePrpp/Hy8irXHVKpLM03//4rQS9EVfHMM2PYt29vntdWr/6S2bNn5LvMhAmjOX78KAD/+9+zpKam3jTP0qWL+PLLzwvc9q5dOzhz5l/r8yVLFnLgwL7ilH9Lhw4dJDQ0iBEjhjBkSH/mz//IOm3Tpo0EBrbOs51du3YQGNia7du3AvDLL7sZOXIIw4c/ytChA/nuu2+t+9SnT3dGjBhi/bnVvhdHkb4wFRQURFBQUJ7XJk6caH28YsWKfJfNDfmKFBBgZudOTYVuUwiRv86dQ9m2bQtt27a3vrZ16xbGj3+2SMvPnj2vxNvevXsHDzwQyF131Qdg1KixhSxRdC1atGLWrI/Izs5i5MjHePDBh7jnnpYA+PsHsG3bFtq0aQvA1q0/EhBwN2AZmnnWrGl8+ulKfH31GAwGYmMvWdc7aNCQPEM5l5ZNfTM2V0CAmW++cSAtDdzcKrsaIUSnTiF8+ukCcnJycHBwICbmElevXqFFi1bMnj2DY8eOkp2dTadOITz55M3j3AwY0JMlSz7Hy8uLlSuXsnlzJN7e3vj66q3j0Hz//Xq+/349OTk51KlThzfemMrJkyfYs2cXf/xxiJUrlzFt2ixWrFjCAw8E0qlTZw4e3M/HH3+EyWSiUaMm/O9/r6DT6RgwoCfdu/fgl192YTQamTp1JvXq3Znv/jk6OtGgwd1cuXLF+to997QiKuowRqMRg8HAhQvnadDAEvQZGemYTCY8PT0B0Ol01K2b//pLyyaD/saeNy1ayOBmQtzI8ZsvcfpqVZmuM+vRoWQPHpLvdA8PT5o0acpvv/1Cx44PsXXrFoKDu6BSqRg9ejweHp6YTCYmThzHqVMn8x0H/vjxY2zbtoUVK77EZDLyxBNDrUEfFNSJXr0s37xfvPgTIiK+Y8CARwgMfNAa7DfKzs5m+vR3+OijT6hbtx5Tp77Jd9+tZdAgy354enqybNkXrFu3hq+++pyXX34j3/1LSUnh/PnztGx5fdhilQpat76fffv2kp6eRmDgg8TEXLK+H4GBD9K/f0/uu68NHTp0pHPnUNRqS5Pz6tVfsmXLZgDc3d0JD19U4PtfGJsO+lOnJOiFqCo6dw5l69YtdOz4ENu2bbEG588//8T336/HZDIRH3+V6Oh/8w36qKjDPPhgJ+vIl4GBD1qn/fvvaT79dAFpaalkZmbmuYHIrZw7d5Zate6w3h6we/cerFu3xhr0QUGWTicNGzZm587tt1zHn38eZvjwR7lw4RyDBg2henWfPNNDQrqydu03pKWlMWHCJD7/fLl12ssvv8Hp06c4eHAfX331OQcO7OO1194GpOmmSO66y4xKJT1vhLiV7MFDCjz7Li+BgUHMm/chJ04cJysri0aNGnPp0kW++moVn376GR4eHkyb9jYGQ8nu+Tx9+jtMnz6bBg3uZtOmjRw+/Hup6s0dElmjUWMy3XpY59w2+kuXLjJmzEiCgzvToEFD6/QmTZpx+vQ0nJyc8txvNpe/fwD+/gGEhoYxcGAva9CXNZtMQicn8POTUSyFqEpcXFyujTk/hS5dQgFIT0/HyckZNzc3EhLi+e23XwtcR4sW97J79w6ys7PIyEjnl1+uD6mSkZGOj48PRqPR2uyRu92MjJsHSqxbtx4xMZe4cOE8AD/+uImWLe8t0b7dcUdthg4dzqpVK2+aNnbsBMaMeTrPaxkZGRw6dND6/OTJE3lGEShrNnlGD5YLsnJGL0TV0rlzKK+++j/eeWc6AA0a3M3ddzdkyJAB6PV6mjdvUeDyDRs2Iji4C8OHD8Hb2zvPjcNHjRrH6NEj8PLyokmTZtZwDwnpyqxZ01i79mvefXeWdX5HR0deffUt3njjJevF2D59+pd43/r06c9XX62ytsPn+u9drCwUvvzyM95/fzqOjk44OzvlOZu/sY0eYMaM2dSqdUeJayvSMMUVqbTDFOd6/XVHVq1y4MyZNFQy7I2wczJMsW0p82GKb1f+/mYyMlTExEjKCyHsm80GvYx5I4QQFjabghL0QuRVxVppRQmV5N/RZlOwZk0FFxfpeSMEgFarIz09RcL+NqcoCunpKWi1umItZ7O9bnIHN5MzeiHA27sGiYlXSEtLquxSRClptTq8vWsUb5lyqqVKCAgw8/vvMriZEBqNFh+fWpVdhqgkNn266+9v5vx5FZmZlV2JEEJUHpsO+oAAM4qi4swZm95NIYQokE0nYG7PG7kgK4SwZzadgPXrS9ALIYRNJ6CbG9SqJT1vhBD2zeYTMCDALGf0Qgi7ZvMJWL++5YxevicihLBXNh/0AQFmkpNVXL0qg5sJIeyTXQQ9yAVZIYT9svn0u/H+sUIIYY9sPv38/BQcHWVwMyGE/bL59NNoLDcLP31a2uiFEPbJ5oMeZBRLIYR9s4v0CwgwEx2tJiensisRQoiKZxdB7+9vxmhUce6cNN8IIeyP3QQ9SM8bIYR9sovkk/vHCiHsmV0kn7c3VK8uY94IIeyT3SSf9LwRQtgru0k+GcVSCGGv7Cb5/P0VrlxRk5JS2ZUIIUTFspuglwuyQgh7ZTepJ0EvhLBXdpN69eqZ0WhkcDMhhP2xm9TT6aBuXUXO6IUQdqdIqbdr1y5CQ0Pp0qULixcvvmn6gQMH6Nu3L02aNOGHH37IM61x48b07t2b3r17M3bs2LKpuoQCAqSLpRDC/mgLm8FkMjFlyhSWL1+OXq9nwIABBAcHExAQYJ2nVq1azJgxg2XLlt20vJOTExs2bCjbqkvI39/M7t0OmM2glrwXQtiJQuMuKiqKevXq4efnh06nIywsjG3btuWZp06dOjRq1Ah1FU/PgAAzWVkqLl6Uwc2EEPaj0GSOi4ujZs2a1ud6vZ64uLgibyA7O5t+/foxaNAgtm7dWrIqy4j0vBFC2KNCm25Ka/v27ej1es6fP8/w4cO5++67qVu3bnlv9pZyR7E8fVpNp06mSqlBCCEqWqGntnq9ntjYWOvzuLg49Hp9kTeQO6+fnx/3338/R48eLUGZZcPXV8HdXXreCCHsS6GJ17x5c6Kjozl//jwGg4HIyEiCg4OLtPLk5GQMBgMACQkJHDp0KM9F3IqmUknPGyGE/Sm06Uar1fLmm28yatQoTCYT/fv3p0GDBsydO5dmzZoREhJCVFQUEyZMICUlhe3btxMeHk5kZCSnT5/mrbfeQqVSoSgKTz31VKUGPUD9+mZ++01TqTUIIURFUimKolR2ETfKyTGRlJRRbuv/4AMdM2c6cuZMKq6u5bYZIYSoUDVquOc7ze7aMHJ73vz7r93tuhDCTtld2uX2vJGgF0LYC7tLu/r1pS+9EMK+2F3aubhAnTrS80YIYT/sMu38/eW2gkII+2GXaZfbl75q9TcSQojyYbdBn5am4vJlGdxMCGH77DLo5YKsEMKe2GXSySiWQgh7YpdJV7u2grOzDG4mhLAPdpl0ajXcdZdZvjQlhLALdpt0MoqlEMJe2G3SBQSYOXdOxbVRlIUQwmbZbdD7+5sxmVRER9vtWyCEsBN2m3LS80YIYS/sNuVyR7GUoBdC2Dq7TTkPD6hRQ8a8EULYPrtOOel5I4SwB3adcgEBZv79V8a7EULYNrsOen9/M/HxahITK7sSIYQoP3Yd9NLzRghhD+w64XKDXi7ICiFsmV0nXN26Cg4OMriZEMK22XXCabVw553S80YIYdvsPuHk/rFCCFtn9wnn769w5owak6myKxFCiPJh90EfEGDGYFBx7pz0pxdC2Ca7D/rcMW/kJiRCCFtl9+kmfemFELbO7tOtenUFLy/pYimEsF12n24qlfS8EULYNkk3ZBRLIYRtk3TDckYfG6smLa2yKxFCiLInQc/1njfSfCOEsEWSbEjPGyGEbZNkA+66y4xKpcgZvRDCJkmyAU5O4OcnQS+EsE2SbNdIzxshhK0qUrLt2rWL0NBQunTpwuLFi2+afuDAAfr27UuTJk344Ycf8kxbv349Xbt2pWvXrqxfv75sqi4HAQGWvvSKUtmVCCFE2So06E0mE1OmTGHJkiVERkYSERHBqVOn8sxTq1YtZsyYQY8ePfK8npSUxPz581m9ejVr1qxh/vz5JCcnl+0elBF/fzMZGSpiYmRwMyGEbSk06KOioqhXrx5+fn7odDrCwsLYtm1bnnnq1KlDo0aNUKvzrm7Pnj106NABLy8vPD096dChA7t37y7bPSgj0vNGCGGrCk21uLg4atasaX2u1+uJi4sr0spLs2xFyw36Xbs0lVyJEEKULTl9vaZWLYV+/XIID9fx888S9kII21Fo0Ov1emJjY63P4+Li0Ov1RVp5aZatDB98kEXjxmbGjnUmOlra6oUQtqHQoG/evDnR0dGcP38eg8FAZGQkwcHBRVp5YGAge/bsITk5mUNkLFAAACAASURBVOTkZPbs2UNgYGCpiy4vrq6wfHkmigIjRjiTnl7ZFQkhROmpFKXwDoU7d+5k+vTpmEwm+vfvz7hx45g7dy7NmjUjJCSEqKgoJkyYQEpKCo6Ojvj4+BAZGQnA2rVrWbRoEQBjx46lf//+BW4rJ8dEUlJGGexayf38s4ZHH3Wmb18jCxZkoZKTeyFEFVejhnu+04oU9BWpKgQ9wJw5OmbMcGTq1CzGjMmp7HKEEKJAEvQlYDbDyJFObNmiZe3aTDp0MFV2SUIIkS8J+hJKTYXQUBeSklT89FMGtWtXqbdKCCGsCgp66V5ZAHd3WLEii8xMFU884UxWVmVXJIQQxSdBX4i77zYzf34Whw9reOUVRxkLRwhx25GgL4KwMCOTJmXzxRc6PvvMobLLEUKIYpE2+iIymWDIEGf27NHw3XcZtGljruyShBDCSi7GlpHEROja1ZXsbPjppwz0+ir11gkh7JhcjC0j3t6Wb84mJ6sYNcoJg6GyKxJCiMJJ0BdTs2Zm5szJYt8+LW+95VjZ5QghRKG0lV3A7ahfPyOHDxtYtEhHy5YmBg82VnZJQgiRL2mjLyGjEQYOdOb33zVERGRwzz1ycVYIUXmkjb4caLWweHEW1aopjBzpTHy8jHwmhKiaJOhLoUYNheXLM4mLUzFmjBNGacERQlRBEvSl1KqVmZkzs9m1S8v06brKLkcIIW4iF2PLwGOP5XD4sJr58x2pXl1h3Lgc1HIIFUJUEXIxtoxkZ8Po0U5s3uxAUJCR8PAsatasUm+tEMKGycXYCuDoaBnp8v33s9i/X0NQkCsREfKBSQhR+SToy5BKBcOH57BtWzr16pl54glnJk1yJC2tsisTQtgzCfpyEBCgEBmZwXPPZfP11w4EB7ty8KC81UKIyiHpU04cHOCVVwx8910mJhP07OnCrFk66YIphKhwEvTlrF07E9u3p9Ovn5HZsx3p2dOFf/+VL1cJISqOBH0F8PCAjz/OYvHiTE6dUhMc7MqXX2rlblVCiAohQV+B+vQxsmNHOq1amZg0yZknnnAiIaGyqxJC2DoJ+gpWu7bCt99m8uabWWzZoiUoyJXt2zWVXZYQwoZJ0FcCtRomTMjhhx8y8PRUGDzYhddfdyQrq7IrE0LYIgn6StS8uZmffspg1CgDixfr6NrVhT17NNJ2L4QoUxL0lczZGaZPz+arrzJITFTRr58LXbu6sH69VrpiCiHKhIx1U4VkZsKaNQ4sWKDj9Gk1fn5mxowxMGRIDm5ulV2dEKIqK2isGwn6Kshshh9/1PLJJw7s26fF01NhxAgDo0bloNdXqX8uIUQVIUF/Gzt4UM0nn+iIjNTi4AD9+xsZP95Aw4Zy60IhxHUS9DbgzBkVixbp+OorBzIzVXTubAn8Dh1MqOSLtkLYPQl6GxIfr2LFCgeWLnXg6lU1LVqYGD/eQM+eRrQyKrIQdkuC3gZlZsLatQ4sWODAqVMa64XbQYNy8PKq7OqEEBVNgt6Gmc2wZYuGTz7R8dtvWrRahY4dTfToYaR7dyM+PlXqn1cIUU4k6O3En3+q2bBBS0SEA9HRatRqhfbtLaEfFmaUWxsKYcMk6O2MosDff6uJjNQSEaHln38sY+m0aWOiR48cevQw4udXpf7ZhRClJEFv5/75R01EhJaNG7UcOWIJ/ZYtLWf6PXrkUL9+lfoTEEKUgAS9sDpzRkVEhAORkVoOHbKEfuPGuaFvpFEjs3TXFOI2VOqg37VrF9OmTcNsNjNw4EBGjx6dZ7rBYODFF1/kyJEjeHl5MWfOHOrUqcOFCxd4+OGHueuuuwBo0aIFU6ZMKXBbEvQV5+JFFZGRljP9/fs1KIqKWrXMtG1rsv40bmxGI6MoC1HllSroTSYToaGhLF++HL1ez4ABA/jwww8JCAiwzvPFF19w4sQJpkyZQmRkJD/99BMfffQRFy5cYOzYsURERBS5WAn6yhEXp+KHH7Ts3avht980XLpkGe/Ow0OhTZvrwd+qlQknp0ouVghxk4KCvtCv2ERFRVGvXj38/PwACAsLY9u2bXmC/ueff2bChAkAhIaGMmXKFKpYi5AohF6vMHx4DsOH56AocOGCin37LKG/f7+G6dMdAdDpFFq0MNO2rZF27Uy0aWPC27uSixdCFKjQoI+Li6NmzZrW53q9nqioqJvmqVWrlmWFWi3u7u4kJiYCcOHCBfr06YObmxuTJk2idevWZVl/HupzZzH71AAXl3Lbhj1QqcDPT8HPz8iAAZaxkhMS4MABzbXw17JokY758y2N+Y0aXT/jb9nSxF13KdLcI0QVUq5fmvf19WX79u14e3vz999/8/TTTxMZGYlbeYy5azLh3bkjqNVkjhhF5hOjUXx9y347dqpaNQgNNREaagIMZGbCH39Yzvj37dOwbp0DK1fqAHB2VmjUyEzTpiaaNjXTpImZJk1MeHpW7j4IYa8KDXq9Xk9sbKz1eVxcHHq9/qZ5YmJiqFmzJkajkdTUVLy9vVGpVOh0lv/8zZo1o27dupw5c4bmzZuX8W4AGg3JX67FZd6HuMx5H5eP55I18BEyx07AdHfDst+enXN2hvbtTbRvbwLAZIKjR9UcOaLmyBENR4+q2bRJy6pV1+9tU6eO+Vrwm6y/5exfiPJXaNA3b96c6Ohozp8/j16vJzIykg8++CDPPMHBwaxfv55WrVrx448/0q5dO1QqFQkJCXh6eqLRaDh//jzR0dHWtv7yYGx9PymffY3m1EmcF36M0+ovcV61kuwuoWSOe4acDh2RvoPlQ6Ox3BqxeXMzYGnuURTLRd4bw//oUTVbt+owmSz/Djee/TdpYqZxYzONGpmpXl2u8QhRVorUvXLnzp1Mnz4dk8lE//79GTduHHPnzqVZs2aEhISQnZ3N5MmTOXbsGJ6ensyZMwc/Pz9+/PFH5s2bh1arRa1W88wzzxAcHFzgtsqy143q6lWcVyzBedli1FevknNPSzLHTSC7V19wcCiTbYjiy8qCkyfznv0fOaImIeH62X+NGpbAv/5jolEjM+75dywQwq7JF6YyM3Fa+w3OC8LRnjqJqXYdMp8aR9aw4SjuHmW7LVEiuWf/x46pOX5czYkTao4f13D8uJqMjOufwurUsQR/w4aW8G/c2EyDBmacnSuxeCGqAAn6XGYzuq0/4vxJOLpf92B29yBr6HAyR4/DXLtO+WxTlIrZDOfPq66Fv8Z6IDh5Uo3BYDkAqNUKd96p0LChiYAAM/XqKdSrZ6ZePTO1ayvy4U3YBQn6W9D+cQjnBeE4fv8dANm9+5E5/hmM97Qs922L0jMaITpaxbFjlrP+3J+zZ68fAAA0GoXatS3Bf+edloOA5bflR8buF7ZCgr4A6vPncF68AKdVK1Gnp5H6wTyyho2osO2LsmUyQWysirNn1Zw9a/kdHa22Pr96VZ1nfk/P62f/d95pvvb9AcvvOnXM8pUMcduQoC8CVUoyHkMHoz15goT9f0rbvY1KS+Na6KuJjlZZH589q+bcORU5OXl7Zfn4XA/96wcBM3XqWB7LxWFRVUjQF5H28O94h3Yi/fnJZLz8RqXUICqPyQSXL6s4d07NhQsqzp9Xc/685Xfu8+zsvAcCLy/lWvBbDgR6vYKPj6V7qI+PQvXqlh9XV+nZK8qXBH0xuI8egeOWH0j47TDmmrUqrQ5R9SgKXLmi4vx5FRcuqPMcEC5csBwgbuwhdCMnp+uhf+MB4PpjMz4+lgNFzZpyAVkUnwR9MajP/Eu1wDZkPfIYaR/Mq7Q6xO1HUSA9HeLjVcTHq7h6Nfe32vraja/Hx6tueWBQqy2Bf8cdCrVrm62/a9e+/rxGDQW1+hZFCLslQV9Mrq+9iPPSxSTu2ifDJ4hylZGR98AQG6vm4kUVFy9afl+6pObSJRWZmXkPCDqd5cy/Th1zngNCrVpmatRQ8PW1HAxkSGn7IUFfTKqrV6l2fwtyAh8k5bOvKrUWIRQFEhJUXLqkuukgkPs7JkaF0XjzpwNPT4UaNcz4+l4Pf8tj8w2PLc1H0lx0e5OgLwGXOe/jOmMqid//iLFd+8ouR4gC5V5IjotTceWKisuX1Vy+rOLy5dznlteuXFGRmnrr6wi51wmqVbv+k3stIffxjdPkAnPVIkFfEunpVGvXCnMdP5I2bbX5v2hVagqeQwaSHfowmRMmVnY5ohxlZGAN/ytXrh8QLl+2NCElJFh+4uNVJCaqrAPQ/ZejY94DQPXqCu7uCi4u4Op642/LQSH3Ncvz649dXGToqbJQqjtM2S1XVzJeeg33559BF7kRQ49elV1RuXJ9/WUc9u3FYd9eFFdXskaOquySRDlxceHaMBEKYC5wXrMZUlKwBv+NB4Hrjy0Xm8+fV5OaChkZt77IXBCdzhL4Xl4Ker2lqUmvV679vt705Otr6akkQ1sXj5zRF8RoxPuh9mAykbhrn82edug2R+I5/FEynnkOzYlj6H76kdTFy8nu3a+ySxO3KbMZMjMtoZ+enhv+kJ6u+s/jvL+TkizNT5ZmKDUpKbfuleTjo9zyYFC9uoKnp+WThaen5RqFh4florSNfyiXppvS0P2wCc/HHyF11hyyRjxZ2eWUOdWVK1QLaoupVm2SNm8DkwmvQX3QHjpI8qrV5HQKqewShR3LzMTarBQXl7eZKfd57nWJ/JqYABwclGuhb7nhvYeH5bnloID1sZubgpubpZnJzc3S5GT5bXns6FiBO19MEvSloSh49eqG5t/TxO/7A8rjNoiVRVHwGP4ouu3bSNy6G1PDRgCokpPw6v0wmugzJH37Pcb72lRyoUIUzGzGek0hORlSU1UkJ1t+UlIsr6Wk5D62/KSmYp3+3+6r+XFwyBv+bm6W6wy5BwV3d8unCQ8PyzweHtefX59mObhoy7jhXIK+lLQH9+P9cGfSJ79CxuRXKrucMuP05ee4T3qatCnTyRw7Ic80dVwsXj26okpJJmnjFvk+gbBpBgPW8E9PV137sTxOS7v+Wu7jtDTLdMvv64/T0iwHlFt1df2v3ANEbvC7uysMHpzDwIHGEu2DBH0Z8HhiGLqftxK//0+buOm4+mw03g89gLFlK5K/3citvmapPvMv3j26ojg4kBSxBXOd8rsNpBC2QlEsd1FLTbUcOFJSLF1aU1KuHwhyX0tNxTotJUVF//45jBqVU6LtStCXAc3pk3gH3k/W4yNJm/lhZZdTOiYTnn3D0B75m8Qdv2L2q5vvrJq//8Krz8OYfX1J2rgFpXr1CixUCFFUBQW9jJZRRCb/BmQ9PhKnz5ajOX2yssspFecF89H99itp02YWGPIApmbNSVn1DZoL5/Ec0h9VWmoFVSmEKCsS9MWQ/sLLKE7OuE6bUtmllJjmyN+4vjeV7Id7kj14SJGWyWn3ACmfrkQb9Scewx+D7OxyrlIIUZYk6ItB8fUlc/wzOEZsQHtwf2WXU3zZ2Xg8PRrFw5PU2XOL1bHYENqd1Dnz0e3egcf4pyzfuRdC3BYk6IspY9wzmGv44vbOG5arLrcR1/dnoD36N6lz5qP4+BR7+exHHiPtnek4bvwOt5deuO32Xwh7pXn77bffruwibmQ2K2Rlleyqc4XQ6VBcXXFesQTjPS0xBTSo7IqKRLvvN9yfn0DWkGFkPl3ysWyMbe5HlZ2Ny+JPwGwiJzCoDKssOVV8PK7vvYvDvr2Ya9ZCqSYXjYV9cXXN/9tc0uumJHJy8H6wLWg0JO7YW/bffChjqrRUvDt1AAUSd/yC4lbKG50qCm4vPIvzqpWkvfsemaPHl02hJazFccM63F6djCopCcxmVGYzOS1bkT1gMFl9BpR7d1j12Wgct2zGYed2jM2akzFpMjIQfCVQFNsf56AA0uumrDk4kP7a22j/OYHT11+UzTqzs9Ft/RH1pYtls74buL71GupzZ0mdv7D0IQ+gUpE2aw7ZD/fE7fWXcVzzdenXWQLq2Bg8hj+Kx+iRmPzqkrh1Nwl/HCPtnelgMuP2+stUb9EQz0f6WWpMSyubDZvNaA/ux2X6FLyD2lG9zT24vfYS2uPHcP3wfby7PIj20MGy2ZYoEnVsDF4Ph+AVHIjD9m2VXU6VI2f0JaUoeIV1QX3+HAm/HQZX1xKtRn3pIk4rl+L8+QrUV6+iODmROWosGc8+h+LlXeoydVs24zl0MBkTJpH+Zhn3FsrKwnPIABx++5WUz77C0Dm0bNefH0XB6cvPcX3rNVSGbNJffoPM0eNu+mSlOXEcx29X4/TtajTnz6G4uJDdvQdZAweT82Cn4n0SS09Ht3M7ui2bcdzyA+qrV1A0GnLad8DQtRvZXbtjru+Pw88/4f78s6hjY8icMIn0/70sZ/flTHPkbzwfG4g6KQmzjw+ac2cxPBRM2lvvYmrarLLLqzDyhalyov1tL969Qkl/5Q0ynptc9AUVBYfffsV5ySJ0mzaC2YwhtDtZgx/DcXMEjmu+RvHwJGPiC2SOGlPioFBdvUq1oHaYfWqQuGVHuYzIpEpNwbNvD7QnT5C0egPGtu3KfBs3Ukefwf2Fieh278DwQCCpH4Zjru9f8EJmMw77f8NxzTc4blx/LRBqkNW3P9kDBmNsee8tP/KrL11Et+UHdFs2o9u9E1V2NmYPTwwhnTGEPowhuPMtD8aqlGRc33oN5y8+w9iwEalzP8F4b+uyegvKh9GIy7wPUdzdyRwx6rYZqVW3bQvuo0ageHiQvGo1prsb4rzsU1zmzEKVnEz24CGkv/w65jtqV3ap5U6Cvhx5PP4oDnt2kbD/z8J7smRk4PTtapyXLkZ79G/MXl5kPTaczBFPYq53p3U2zZG/cZ32No5bt2CqXYf0l14je+AjFGsQbkWxDNuwZTOJP+7A1Kx5yXawCFRXruDVsyvq+HhSP/oYQ0iXsj+LNZlwXrIQ1xlTUdQa0t+aStawEbccuqFA2dnotv2E09pv0G3ZjMpgwOgfYGnP7zcQdWoKuh82odvyAw5Rf1g2Xe9Osrs9jCH0YXLati9yCN4uZ/eq+Hg8Ro9At3snAMbGTUmdNafcD9ql5bR8CW6v/A9jk2akfLEac607rNNUSYm4zJmN89JFoNGQMfZpMidMQnH3qMSKy5cEfTnS/HMC7wfbkvnkaNKnzbrlPOqz0TgvX4LTl5+hTkrC2KQZmaPGkNVvoOUuEPlw+GU3rlPfxOHQ7xgbNSb99bcxdOlWpAtOjqu/wmPCGNJef4fMZ58r8f4VlfrcWbz6hqE5fw6zmzuGrqFkh/W2hH4B+1gUmn9O4D7paRwO7ie7c1fS3v8Ic+06pa5ZlZyE48YNOH67Gt0vu62vKyoVxtb3kx36MIbQ7pYB3Up4ka+qn91r/orCc8QQ1JfjSH3/IxQPT9xeexHNxQtkPjqU9DenVr1hL0wmXN9+HZdFH5PdtRspC5flO6qs+mw0rjOm4LRuLWYfH9L/94rlBOE2+cRSHBL05czthYk4fb2KhD0HMN9V3/KiouCwczvOSxeh2/IDqNVkh/Uia9QYy1lhUYNDUdBFbMB12jto/z2NoX0H0t94B2Pr+/NdRH3hPN5B7TE1aUrSd5uK90mgNAwGHPbsxDHiexw3bUSdkIDi7IwhpCvZPXph6BJavDOqnBxc5n+EywczUdzcSHt3Jtn9B5VLzwr1hfM4Rn6P2dMLQ+fQEn3PoCBV8ezecd0a3J+bgNnLm5QVX2BsdZ9lQno6rh/OwnlBOIq7O+mvv0PWY48X/9NTeUhPx2PcKBx/iCTjqbGkT5lRpL9v7eHfcX3nDXS/7sEY0ID0N6Zg6PawTfXSkaAvZ+q4WKq1bUl2126kfRiO4zdfWppnTp3E7OND5uMjyXr8idK1E+bk4LRqJa6z30N95TLZYb1If+2tm/vxm814DuiF9vAhErf/gvnOu0q3cyVlNOKw9xccIzagi9yI5nIcik6HoVMI2WG9MHR7uMCLzdqoP3Cf+DTaI3+R1acfadPeR6lRowJ3oOxVmbN7oxHXqW/hsiAcQ7sHSFny2S27oGpOHMftpefR/bqHnPtakzZrDsbmLSq+3mvUsTF4DHsE7V9/kvbue2SNGlu8FSgKuh834zr1TbQn/8HQ7gHS3363Sn3CKg0J+grg8t5UXD98H7ObO+q0VHJa3Uvmk2Mst+Mry4ugaWm4LPoY5/lzUWVlkvXYcDImv4xZXxMA50Uf4/bGK6R+GE7W0OFlt93SMJnQHtiPY+QGHCO+R3PxAopWS07HILJ79Ca7e4/rZ9CZmbjOfg/nT+Zh9qlB2qw5GLqHVW79Zawyz+5VCfF4jH4C3a7tZD7xFGlTZoBOl/8CioLjmq9xe/t1VAnxZI4aQ8ZLr1V4W7fmyN94Dh2EOjGRlMXLMHTtXvKVGY2Wk6ZZ01FfvUJW3/6kv/pWnutkFUJRUMfGoDl+DO3xY2j+OU5OUCey+/Qv0eok6CuAKjUFz8H9MNW7k8xRY8r9rkyqK1dwmTML55XLwMGBjDHjMXTphlffMAxBnUj5/Juq+bFUUdAe/t3SvLPxOzRno1HUanIeCMTQqTNOX36G9vQpMh97nPS330Xx9KrsistFZZzda/7+y9IeHxtD6vsfkf3o0CIvq0pKxHXGVJxWLMXsqyd9ynRLIFXA35jDzz/hMWoEipsbKV+sLrNPFaq0VJznz8VlQTiYTGQ+MZqs4SMx+9RA8fAs031TXbmC9vhRNCeOoT12DO2JY2hOHEednGSdx+xTg4xnniNz3IQC1pQ/CXobpj7zL67vTcVp/bcAmKtVI2HnPhS9vpIrKwJFQfP3X5Yz/Y0b0J78B1PdeqR+MI+coE6VXV2FyHN2//RE0ie/Ui5n947r1+I+6WlLe/zyVSU+qGj/OITb5Odw+PMwhgc7kTZzNib/8hsGxGn5EtxenYyxcVNSVn1TLt0k1bExuMychtNXq1CZzQAoGg2Ktzdm72oo3tUwV6uOudq1x97VUKpd+129Oubc17y9UaWloj1x/NpZ+lE0J46jPX4UdXy8dXtmLy+MjZpgatgYY6NGmBo1wdiwcamvC0nQ2wHtn4dx/mQeWY8OI+eh4Moup0TU585iruELzs6VXUqFuvHs3uzhiSG0O9m9+mII6lT60DeZcH33bVw+nktO2/YkL/ms9CcBJhNOK5fhOn0KqqxMMiZMJGPi/8r2381kwvWdN3BZOJ/sLqGkLlpWNt/qLoDm5D9oDx1EnZiAKjEBdUIi6oT4a49zX4tHVcRhus1u7pgaNsLYqDGmRo0xNmyMqXETzL76cvkkJEEvxG3AYe8vOH79BY6bIyxf6nJzvx76nUKKHfqqxAQ8Ro9Et3M7mSOeJO3dmQW3xxeT6vJl3N55Hac1X2OqeydpM2ZZuv+W1o09a0aNsfSsqSrjSSkKZGSgTkywHBASroV/guW54uSMqbEl1M2161Ro86kEvRC3E4MBhz27cNz4naWbamIiZlc3DKHdyO7Rx/LdhELOnjVH/ra0x8dcIm3mh5bukeXE4ZfduL30PNp/TmCs74/5jtqY9TUx16yFuablt0l/7bG+ZoG1q+Ni8Rg6GO1ff5I+dQaZT40rt7ptjQS9ELernBwcftl9PfTj41FcXMnuGkp2zz4YQrre9IU0xw3rcJ84HrOHJynLPi/wOxdlxmDAecUStAf2o4mNQX3t51bNHGYvL8tBwHowqIWpZk0Udw9cZ0y19KxZtAxDaCl61tihUgf9rl27mDZtGmazmYEDBzJ69Og80w0GAy+++CJHjhzBy8uLOXPmUKeO5ZuLixYtYu3atajVal5//XU6duxY4LYk6IXIh9GIw697cPz+Oxw3fW8ZBM/FxfKFtF59MAR3xuWjD3AJn0NOm7YkL1tVuRflFQVVchLq2Fhr8F8/CMSijsv9HYvKaATAVLNWmfassSelCnqTyURoaCjLly9Hr9czYMAAPvzwQwICAqzzfPHFF5w4cYIpU6YQGRnJTz/9xEcffcSpU6d4/vnnWbt2LXFxcYwcOZIff/wRTQHfZJOgF6IITCZLm/7G73CM+B71lcsoajUqs5nM4U+SNq1s2+PLldmMKj4edWwM5jvvtOnxaMpTqcajj4qKol69evj5+aHT6QgLC2PbtrzjPf/888/07dsXgNDQUPbu3YuiKGzbto2wsDB0Oh1+fn7Uq1ePqKioUu6OEAKNhpzAB0mb+SHxUSdI2rCZzDFPk7JgCWnvz7l9Qh5ArUapUQNT83sk5MtJoZey4+LiqFmzpvW5Xq+/Kazj4uKoVauWZYVaLe7u7iQmJhIXF0eLFi3yLBsXF1dWtQshwBL67TuQ075DZVciqqgqMEqREEKI8lRo0Ov1emJjY63P4+Li0P/nAo9erycmJgYAo9FIamoq3t7eRVpWCCFE+So06Js3b050dDTnz5/HYDAQGRlJcHDeb14GBwezfv16AH788UfatWuHSqUiODiYyMhIDAYD58+fJzo6mnvuuad89kQIIcQtFdpGr9VqefPNNxk1ahQmk4n+/fvToEED5s6dS7NmzQgJCWHAgAFMnjyZLl264OnpyZw5cwBo0KAB3bt35+GHH0aj0fDmm28W2ONGCCFE2ZMvTAkhhA0oVfdKIYQQtzcJeiGEsHES9EIIYeOqXBu9EEKIsiVn9EIIYeMk6IUQwsZJ0AshhI2ToBdCCBsnQS+EEDZOgl4IIWycBL0QQti4Qgc1q4pKcw/b8hYTE8OLL75IfHw8KpWKQYMGMXz48Dzz7Nu3j/Hjx1tr6tKlCxMmTKiQ+nIFBwfj6uqKWq1Go9Gwbt26PNMVRWHatGns3LkTJycn3nvvPZo2bVohtf37778899xz1ufnz5/n2WefZcSIEdbXKvo9fOWVV9ixYwfVq1cnIiICgKSkJJ577jkuXrxI7dq1+eijj/D09Lxp2fXr17NgwQIAxo0bZ70bW3nXN3PmTLZv346DgwN169ZlxowZeHjcfAenwv4Wyqu+8PBwVq9eqs/EoAAABYtJREFUTbVq1QB4/vnnCQoKumnZwv6/l1d9kyZN4syZMwCkpqbi7u7Ohg0bblq2It6/UlNuM0ajUQkJCVHOnTunZGdnKz179lROnjyZZ55Vq1Ypb7zxhqIoihIREaFMnDixwuqLi4tT/v77b0VRFCU1NVXp2rXrTfX99ttvyujRoyusplvp1KmTEh8fn+/0HTt2KE8++aRiNpuVw4cPKwMGDKjA6q4zGo3KAw88oFy4cCHP6xX9Hu7fv1/5+++/lbCwMOtrM2fOVBYtWqQoiqIsWrRImTVr1k3LJSYmKsHBwUpiYqKSlJSkBAcHK0lJSRVS3+7du5WcnBxFURRl1qxZt6xPUQr/Wyiv+ubNm6csWbKkwOWK8v+9vOq70YwZM5Tw8PBbTquI96+0brumm9Lcw7Yi+Pr6Ws983dzcqF+//m15+8Rt27bRp08fVCoVLVu2JCUlhcuXL1d4HXv37sXPz4/atWtX+LZv1KZNm5vO1nPfI4A+ffqwdevWm5bbs2cPHTp0wMvLC09PTzp06MDu3bsrpL7AwEC0WsuH9pYtW+a5CVBFu1V9RVGU/+/lXZ+iKGzevJkePXqU+XYrym0X9Le6h+1/gzS/e9hWtAsXLnDs2LE8983N9ccff9CrVy9GjRrFyZMnK7w2gCeffJJ+/frxzTff3DTtv+9zzZo1K+WAFRkZme9/sMp+D+Pj4/H19QWgRo0axMfH3zRPUf5eK8K3337Lgw8+mO/0gv4WytMXX3xBz549eeWVV0hOTr5pelV4/w4ePEj16tW58847852nst6/orot2+hvB+np6Tz77LO8+uqruLm55ZnWtGlTfv75Z1xdXdm5cydPP/00W7ZsqdD6vvrqK/R6PfHx8YwcOZL69evTpk2bCq2hMAaDgZ9//pkXXnjhpmlV4T28kUqlQqVSVdr2C7JgwQI0Gg29evW65fTK+lt49NFHGT9+PCqVirlz5/Lee+8xY8aMct9ucUVERBR4Nn87/F+67c7oS3MP24qSk5PDs88+S8+ePenatetN093c3HB1dQUgKCgIo9FIQkJChdUHWN+z6tWr06VLF6Kiom6afuP7HBsbW+H3+921axdNmzbFx8fnpmlV4T2sXr26tTnr8uXL1ouKN6rs+yavW7eOHTt2MHv27HwPRIX9LZQXHx8fNBoNarWagQMH8tdff92ytsp8/4xGIz/99BMPP/xwvvNU1vtXHLdd0JfmHrYVQVEU/t/eHbyYE4YBHP+Wy85BOXOb4uofEEVOlAt/gIsDKblyUhzlpnDn4MCBUi6Eg1Li4i9QkqTkoPA7qPnZ1tZu2452ej6naeateXpm3mdm3neayWQyqKpKNBp92ma73WpzBovFguv1quuF6HQ6cTweteXxeIzdbn/Xxuv10mq1uN1uzOdzzGazNkyhl06nQyAQeLrt1TmE/zkCaLVa+Hy+D21cLhej0YjD4cDhcGA0GuFyuXSJbzgcUqvVKJfLKIrytM1XzoXf8jjn0+/3n+73K/39N00mE1RVfTd89OiV+fuOPzd085N/2OphNpvRbrdxOByEQiHg/trYer0G7o+rvV6Per2OyWTi7e2NYrGo62P/brcjkUgAcLlcCAaDuN1u6vW6FqPH42EwGOD3+1EUhUKhoFt8cO80k8mEXC6nrXuMT+8cptNpptMp+/0et9tNMpkkFouRSqVoNptYrVZKpRIAy+WSRqNBPp/HYrEQj8cJh8MAJBIJLBaLLvFVKhXO57N2w+F0Osnlcmw2G7LZLNVq9dNzQY/4ptMpq9UKAJvNph3rx/g+6+96xBeJROh2ux9uNl6Rv5+S79ELIYTB/bmhGyGEEN8jhV4IIQxOCr0QQhicFHohhDA4KfRCCGFwUuiFEMLgpNALIYTB/QPWbEfvzkntfwAAAABJRU5ErkJggg==\n",
1517             "text/plain": [
1518               "<Figure size 432x288 with 1 Axes>"
1519             ]
1520           },
1521           "metadata": {}
1522         }
1523       ]
1524     },
1525     {
1526       "cell_type": "code",
1527       "metadata": {
1528         "id": "6ZFP49W4D2wp",
1529         "colab": {
1530           "base_uri": "https://localhost:8080/",
1531           "height": 1000
1532         },
1533         "outputId": "cdd29cbc-c26e-46d0-aaaf-0d2a8a4cb047"
1534       },
1535       "source": [
1536         "for x, y in val_data_multi.take(5):\n",
1537         "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
1538       ],
1539       "execution_count": null,
1540       "outputs": [
1541         {
1542           "output_type": "display_data",
1543           "data": {
1544 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\n",
1545             "text/plain": [
1546               "<Figure size 864x432 with 1 Axes>"
1547             ]
1548           },
1549           "metadata": {}
1550         },
1551         {
1552           "output_type": "display_data",
1553           "data": {
1554 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\n",
1555             "text/plain": [
1556               "<Figure size 864x432 with 1 Axes>"
1557             ]
1558           },
1559           "metadata": {}
1560         },
1561         {
1562           "output_type": "display_data",
1563           "data": {
1564 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\n",
1565             "text/plain": [
1566               "<Figure size 864x432 with 1 Axes>"
1567             ]
1568           },
1569           "metadata": {}
1570         },
1571         {
1572           "output_type": "display_data",
1573           "data": {
1574 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sak/v7+ysz82WtXfuqfH19lZW1sc7jNbsnNtfDDz/qNlhL0u7d/1Ru7p6Lurc7f/zjs8rMfFmZmS83Gto///yQPvzw/Wbd2zRNORwOzycCAACPXHb5CAiQDLns5qF63T/cMUxThuRssedpkaQnNYsRPc2At7eWe+50aesBtCf1vzHVfGgkWfYtaejQYfriiy+Uk/OJVq9OV1BQkI4cOaKXXtqg9PQ/affuf+r8+UrdcccUxcXFyzRN/d//m6Z//OPviojoJV/f739lc+Yka86cFF111dX66KMPlJHx/2S3OxQcHKyHH35Umze/Jh8fH23b9pbmzp2vfv2u0FNPLdfJkyclSQ88ME9DhgxTaWmJfvvbxfruu+907bXXqTn/mFF7DCUlJbrvvul65ZXXtHp1uiorK7Rnz2eaPj1Jhw9/rYCAbpo6dbokafr0BKWlrZQkzZs3R1dffa0OHjygp576g7Kztys7e4fOn6/UqFG36N57/8OS9x4AgM6kJrvUr08O+uUs1xfY7TIDAurOaMv9boxSdeA1uwa4vE4erpWqw37Z4iWSmtZOrz213HOHcF1LY30ZrQjXVVVV+uijD/TjH/9EknTo0AH9+c9/UZ8+Udq8+TUFBgZq9eo/q7KyUvfff69GjLhBn39+UN98c0Tr1m1QcXGRpk2botjY2+vct7i4WGlpqfrTnzLUp0+UTp0qVY8ePTVp0uQ6gfa3v12shIS7NXToMJ04cUIPPjhHL720UWvWPKchQ4Zp5sxZ+uCD/9Ubb2x2+xoeeOA/5ONjk6+vr5577kWX5/j6+uq++2brwIH9mjdvgSTp+eefdXvPo0fztHjxUl177XX6+OOPlJeXp+eee1Gmaerhh+fp009zNGzY9c16rwEAQHXArp9hAlOXui4XuVDmUTuMG2fLZBQ1vqW5UVKs088857zODA6RUXbGZUcSSdX9sR2OBosRHVF9XY6rzhjbUcs9dwjXtbj7NuTtt6SKigolJU2VVD1z/bOfTVJu7mcaPPga9ekTJUn6xz8+0hdffKF33smWJJWVndHRo3n69NPdGjdugmw2my67LFzXX//vDe6/b1+uhg4d7rxXjx49XY7jk08+1uHDXzt/Lisr09mzZ/Xpp7uVmpomSfrJT25SUFAPt6/lj398tkEttrd69eqta6+9TpL08ccf6R//+EgzZ94tSSovP6ujR78hXAMAYJGyxUtctrOrCbq1w3hTOoE4ovrWuS70+mvkU+w6kDdWN+1qXHWu9fWVcbZMl0X2bNMuIZ4Qrmtx943J229JNTXX9QXUqoMyTVNz587Xj388ss45za1bboxpOvTss2vk7+9v2T1tti7OOunKyopGzrPJNL+vp66s9W229uJO0zQ1bVqS4uLiLRsjAACo28LODA6pLuUoLm40qNYpLXHV+9pF4HU3KWmqOlwH/XKWAlOXNnjO+mUsZnBIdX14cbFzNtznwix6S5TuWoUFjbW4K/yvqQVqSSNGjFRW1kbn4sZvvjmi8vJyDRs2XNnZ22W321VQUKCcnE8aXHvNNdfps89269tvj0mSTp0qlSR16xao8vLvu6f8+7/foE2b/uL8+fPPD0qShg0bru3b35ZUHeZPnz7V5HH37t1bBw8ekCS9885O5/Fu3brp7Nmztc7ro0OHqs87ePCAjh//1uX9fvzjkXrzzb86r/3uu3wVu/n2CwAAmqZmBtp2NE+GacqnuEhGeblOP/Ocx3Z2Na3vTq9aXR3KVR2UHYGBkmHIp6hIhml6XuDo4tz6jSNqt9krPHhYhQcOq+BkqczAwAZlJu11gSPhupY622vWbOXZSi1fJk6M0xVX9Nc999yt6dMT9PvfL5fdbteoUbeob99oTZs2RcuWPeYsn6gtJCRE8+cv0uLF85WY+As99thCSdKNN/5U7767S0lJU/XZZ7uVkjJfBw78S4mJd2natCnKytokSZo5c5Y++2y3pk1L0Lvv7lJkZK8mj/sXv5iurKyNmjlzqkpKSpzHr7/+33T48NdKSpqqnTu3afToMTp16pSmTUvQpk1/UXR0P5f3GzHiBsXE3KrZs2dqxoyf65FHFtQJ6QAAoPkaW1fWFDXh3OfCDoyGJOPsWZeBV6YaTlbWm/GuObf7ooc89rWWWq50tyXQ5xqXJH6vAAA03WWRPV32oq7pMe2Ju57ZrpiGUWeBoyOqr3yO5rnsHNJYN5La9dnunt/VjpGthT7XAAAAnZS79WNNXVfWnBnimgWOtXdRdPSNdnmupzZ/NTPrbVm621yEawAAgA7O23DqLoSbhtHg54qYCU17/iY8b02ob8vS3eYiXAMAAHRQNTtPB/1ylsyuAXKEhroNp43tUu0unFf+9OY6AdswTQWsf8nlQsX64bgpzOAQ55hqOozUzIa3x2AtdZJw3YHKyiF+nwAANEVzOoTUP7d+Nw93M8ddvvrS5ULFoDn/4by2dsCX5Hx+MzS00fGbvr4yys64HVN71eEXNBYUHFfXrt0UGNhDhuFpE060d6ZpqqzslM6dO6vLLuvd1sMBAKDdas4iwItdMOhuoaRUPbNdftfdClj/UoMNa04//d+SpKBf/7JOxxHnnWw2yW53WZPdlosYa3O3oLHDh2u7vUrFxd+pqsr1Fpy49HTp4qeQkHDZbOyBBACAO83pEHKx3UQ8dRExbTYZdrvL43I46mwU44jqq4qYCQ3CuKsx1e9G0ha7NboL1x0+ndhsXZjhBAAAnU5zdp42Q0JkFDXctM3dQkbnbo9H81z2sHZyEawlOQO3UVxUPZP9zHPOlnuNBWupug679jbp7W23xk5Rcw0AANDZNLVDiP+mV2WcPt3getPPT2WLlzRY6Bi4YN739dmqXsTotgzCZvM4ztot9zy1/DMNo3qm24sNcVoa4RoAAKADamr7usDUpTLOn29wvRnYXZIaLHQMyHy+YbiVi7Z8AQEqnzGzQcB3xefY0eqFij4eoqlpyigudnuP9qDD11wDAACgodqlHS53TzQMmSEh8nFRLuKKKcnRN7pBHbTzeY4dlXx8XNZgO0JCZZwr91gSUtPCrz3s1thpFzQCAACgrprWe42FWUdIqIziokZ3UaytKeHW1fOaAQEyAwI8hvg6XUZc3KO1N5Vh+3MAAIBOqn7ddPfFDzXekcPXt7q22d3jLkpA3O32WPu5A1OXqvyuuxuUqrgr9TAvPFftkpb2vlsjM9cAAAAdmMvZYrkPztKFVnlu+kzX70Xt6BvtthWeu5nq+mG4OX22a5eZtFUbPomZawAAgE4pMHWpywWIjTHcBOuaa40L58gwVBEzwW24dfncLjp7NKezSWM7SbYHzFwDAAB0YG43iJHnkN0UNZu6uArYzdmcpikz0he7k2RLYEEjAABAJxR21RUuFwvWdAMxipq2aLGxMO4u3LoLwzU7NDa3rONid5JsCZSFAAAAdDLuNoiRqjd/McrLVT7zvib1om5sQxh3PaZdlnvoQtlJTVnH/fcp7KormlTa4W7HSHfH2wLhGgAAoINyt0FMDaO8XF2zXpPZNaC6M4ckR2CgTD+/Ouc5N4QxXM9duwu39Tt7mDZbg9lvQ5JPUZHb2una3UaMoqIGu0E21qmkLRCuAQAAOqim7FpoFBfJ50I/a0OS4XCo/O4ZDVrdlT35tMqT7m1WGz6pOmAX5eyrLttwONyPw8VCx/oLGH3OltUJ56ZhqPyuu9tNGz6JmmsAAIAOy13NsyeNLRD0phWep/HUr51uyvjbYjGjxIJGAACATsfTTozuFim21AJBT+OpH5TdLWCsrS0WM0osaAQAAOh06tc8O0JC5QgNdZZ7mKGhLq9rqQWCFfEJKr/r7gZ109KFoH+2rE7ddVPG0Z4WM0pehuuSkhLNnDlT48eP18yZM1Va6vpbw+DBgzVp0iRNmjRJs2fPdh5ftGiRbr/9dk2cOFEPPPCAysrK6ly3detWDRo0SLm5ud4MEwAAoNOqXfNcePCwCg8cVsHJUhXl7NOZ1LQmbd5iJf/tW13Olrta2Oiq20ht7W0xo+RluM7IyNDIkSO1bds2jRw5UhkZGS7P69q1qzZv3qzNmzcrPT3deXzRokX661//qtdff129e/fWSy+95HzszJkz+vOf/6yhQ4d6M0QAAACobteN0Ouvkf+mVxvMbNcsXmzJBYKeFlnWXtjoaea9pcd6Mbp4c/HOnTu1du1aSVJcXJymT5+u+fPnN/n67t27S5JM09S5c+fqPPaHP/xBs2bN0vPPP+/NEAEAADq9+rXONduGS9UBtjUDqiOqr8dFirUDeGuPz1tezVwXFhYqIiJCkhQeHq7CwkKX51VUVGjy5MlKSEjQjh076jy2cOFC3Xjjjfrqq680ffp0SdK+fft04sQJjR492pvhAQAAQBf6XddbROiq9V1r8FTqIbW/Ourm8DhznZSUpIKCggbHU1JS6vxsGIYMN43Fd+3apcjISOXl5SkxMVEDBw5Uv379JEkrVqyQ3W7XE088oS1btuiOO+7Q7373O61YseJiXg8AAADqcVeK0ZQ+2E3V1BZ9NccCU5fK52ieZBh1OoK0xzrq5vAYrjMzM90+FhYWpvz8fEVERCg/P1+hblacRkZGSpKio6M1YsQI7d+/3xmuJclmsyk2NlarV6/W+PHjdejQIc2YMUOS9N133+n+++/XqlWrdN111zXntQEAAEDuSzGsmiH2VHZSX+1SD2/6ZrdHXpWFjBkzRllZWZKkrKwsjR07tsE5paWlqqyslCQVFRUpJydHAwYMkGmaOnLkiKTqmuvs7Gz1799fQUFB+vvf/67s7GxlZ2dr2LBhBGsAAAAvuCrFcDdD7GrhoyfelJ3U7mZSlLPvkg7WkpcLGpOTk5WSkqKNGzeqT58+WrlypSQpNzdX69evV2pqqr788kstWbJEhmHINE3NmjVLAwYMkMPh0IIFC1RWVibTNDVo0CAtXdr6dT8AAAAdXZ1SjEZmiJs7A12jNcpOLhXs0AgAANBJ1S/JMM6WyaeoqMF5nrYYd7dNeVttTd4a2KERAAAATjWz1LajeTJMs/r/XQRryfMMdHPKTjo6wjUAAEAn5LJO2s25nhY+tsVmNO0VZSEAAACd0GWRPeu0wKthqm7INgMCOm1QbgxlIQAAAHByNxttdguUabPJlGTabCq/626CdTMQrgEAADohl3XSvr4yqs7LsNtlSDLsdgWsf6lJ7fhQjXANAADQCbmqkzaDgmRc2J+kRlttk36pouYaAAAAkhqpwzYMFZwsbYMRtV/UXAMAAKBR7uqwrdomvTMgXAMAAEAS/aqtQLgGAACAJPpVW4GaawAAAKCZqLkGAAAAWhjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALBIF28uLikp0dy5c3Xs2DFFRUVp5cqV6tmzZ4PzBg8erIEDB0qSevfurfT0dEnSokWLtHfvXpmmqSuvvFIrVqxQYGCgJGnLli3605/+JMMwdNVVV+m//uu/vBkqAAAA0OIM0zTNi704LS1NwcHBSk5OVkZGhkpLSzV//vwG5w0fPly7d+9ucPzMmTPq3r27JGnFihUKCwtTcnKyDh8+rJSUFL344ovq2bOnCgsLFRYW5nE858/bVVJy9mJfDgAAANAk4eFBLo97VRayc+dOxcXFSZLi4uK0Y8eOZl1fE6xN09S5c+ecx1999VXdfffdzlnwpgRrAAAAoK15Fa4LCwsVEREhSQoPD1dhYaHL8yoqKjR58mQlJCQ0COALFy7UjTfeqK+++krTp0+XJB0+fFhff/217rrrLiUkJOjdd9/1ZpgAAABAq/BYc52UlKSCgoIGx1NSUur8bBiGDMNweY9du3YpMjJSeXl5SkxM1MCBA9WvXz9J1eUgdrtdTzzxhLZs2aL4+HjZ7XYdObDsoOYAABTgSURBVHJEa9eu1YkTJzRt2jS9/vrr6tGjx8W8RgAAAKBVeAzXmZmZbh8LCwtTfn6+IiIilJ+fr9DQUJfnRUZGSpKio6M1YsQI7d+/3xmuJclmsyk2NlarV69WfHy8IiMjNXToUPn6+io6OlpXXHGFDh8+rCFDhjTz5QEAAACtx6uykDFjxigrK0uSlJWVpbFjxzY4p7S0VJWVlZKkoqIi5eTkaMCAATJNU0eOHJFUXXOdnZ2t/v37S5LGjRunjz/+2HnN4cOHFR0d7c1QAQAAgBbnVbeQ4uJipaSk6Pjx4+rTp49Wrlyp4OBg5ebmav369UpNTVVOTo6WLFkiwzBkmqZmzJihKVOmyOFwaOrUqSorK5Npmho0aJCWLl2q7t27yzRN/e53v9N7770nm82m2bNnKzY21uN46BYCAACA1uCuW4hX4bq9IVwDAACgNbRIKz4AAAAA3yNcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABbp4s3FJSUlmjt3ro4dO6aoqCitXLlSPXv2bHDe4MGDNXDgQElS7969lZ6eLklatGiR9u7dK9M0deWVV2rFihUKDAzUt99+qwULFuj06dOy2+36zW9+o5tvvtmboQIAAAAtzjBN07zYi9PS0hQcHKzk5GRlZGSotLRU8+fPb3De8OHDtXv37gbHz5w5o+7du0uSVqxYobCwMCUnJ+vRRx/V4MGDNXXqVH3xxRdKTk5Wdna2x/GcP29XScnZi305AAAAQJOEhwe5PO5VWcjOnTsVFxcnSYqLi9OOHTuadX1NsDZNU+fOnXMeNwxDZ86ckSSdPn1aERER3gwTAAAAaBVelYUUFhY6g294eLgKCwtdnldRUaHJkyerS5cuSk5O1rhx45yPLVy4UH/729/0gx/8QA8//LAkac6cObr33nu1bt06lZeXa82aNd4MEwAAAGgVHsN1UlKSCgoKGhxPSUmp87NhGDIMw+U9du3apcjISOXl5SkxMVEDBw5Uv379JFWXg9jtdj3xxBPasmWL4uPj9eabb+qOO+7QPffco927d+uhhx7SG2+8IR8f1l8CAACg/fIYrjMzM90+FhYWpvz8fEVERCg/P1+hoaEuz4uMjJQkRUdHa8SIEdq/f78zXEuSzWZTbGysVq9erfj4eG3cuFGrV6+WVF2vXVFRoeLiYoWFhTXntQEAAACtyqup4DFjxigrK0uSlJWVpbFjxzY4p7S0VJWVlZKkoqIi5eTkaMCAATJNU0eOHJFUXXOdnZ2t/v37S6ruKPLhhx9Kkr788ktVVFS4De4AAABAe+FVt5Di4mKlpKTo+PHj6tOnj1auXKng4GDl5uZq/fr1Sk1NVU5OjpYsWSLDMGSapmbMmKEpU6bI4XBo6tSpKisrk2maGjRokJYuXaru3bvriy++0COPPKKzZ8/KMAzNnz9fN910k8fx0C0EAAAArcFdtxCvwnV7Q7gGAABAa2iRVnwAAAAAvke4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALEK4BgAAACxCuAYAAAAsQrgGAAAALOJVuC4pKdHMmTM1fvx4zZw5U6WlpS7PGzx4sCZNmqRJkyZp9uzZDR5ftmyZhg8f7vy5srJSKSkpiomJ0ZQpU3T06FFvhgkAAAC0Cq/CdUZGhkaOHKlt27Zp5MiRysjIcHle165dtXnzZm3evFnp6el1HsvNzW0Qyjds2KAePXpo+/btSkpK0lNPPeXNMAEAAIBW4VW43rlzp+Li4iRJcXFx2rFjR7Out9vtSktL0/z58+scz87O1h133CFJmjBhgj788EOZpunNUAEAAIAW51W4LiwsVEREhCQpPDxchYWFLs+rqKjQ5MmTlZCQUCeAr1u3TmPHjnXeo8bJkyfVu3dvSVKXLl0UFBSk4uJib4YKAAAAtLgunk5ISkpSQUFBg+MpKSl1fjYMQ4ZhuLzHrl27FBkZqby8PCUmJmrgwIHy9/fX22+/rbVr117k0AEAAID2xWO4zszMdPtYWFiY8vPzFRERofz8fIWGhro8LzIyUpIUHR2tESNGaP/+/eratau++eYbjR8/XpJUXl6umJgYbd++XZGRkTp+/Lh69eqlqqoqnT59WiEhIRfx8gAAAIDW41VZyJgxY5SVlSVJysrK0tixYxucU1paqsrKSklSUVGRcnJyNGDAAI0ePVrvv/++srOzlZ2drYCAAG3fvt153//5n/+RJG3dulU33HCD21lxAAAAoL3wKlwnJyfr/fff1/jx4/XBBx8oOTlZUnUHkMWLF0uSvvzyS8XHx+v2229XYmKiZs2apQEDBjR63zvvvFMlJSWKiYnRmjVr9Jvf/MabYQIAAACtwjA7UBuO8+ftKik529bDAAAAQAcXHh7k8jg7NAIAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFunizcUlJSWaO3eujh07pqioKK1cuVI9e/ZscN7gwYM1cOBASVLv3r2Vnp5e5/Fly5Zp06ZN2r17tyRpzZo12rBhg2w2m0JDQ7V8+XJFRUV5M1QAAACgxXk1c52RkaGRI0dq27ZtGjlypDIyMlye17VrV23evFmbN29uEKxzc3NVWlpa59jgwYO1adMmvf7665owYYJ+//vfezNMAAAAoFV4Fa537typuLg4SVJcXJx27NjRrOvtdrvS0tI0f/78OsdvuOEGBQQESJKGDRumEydOeDNMAAAAoFV4Fa4LCwsVEREhSQoPD1dhYaHL8yoqKjR58mQlJCTUCeDr1q3T2LFjnfdwZePGjRo1apQ3wwQAAABahcea66SkJBUUFDQ4npKSUudnwzBkGIbLe+zatUuRkZHKy8tTYmKiBg4cKH9/f7399ttau3at2+fevHmz9u7dq3Xr1nkaJgAAANDmPIbrzMxMt4+FhYUpPz9fERERys/PV2hoqMvzIiMjJUnR0dEaMWKE9u/fr65du+qbb77R+PHjJUnl5eWKiYnR9u3bJUkffPCB0tPTtW7dOvn5+TX3dQEAAACtzquykDFjxigrK0uSlJWVpbFjxzY4p7S0VJWVlZKkoqIi5eTkaMCAARo9erTef/99ZWdnKzs7WwEBAc5gvX//fj322GNatWqVwsLCvBkiAAAA0GoM0zTNi724uLhYKSkpOn78uPr06aOVK1cqODhYubm5Wr9+vVJTU5WTk6MlS5bIMAyZpqkZM2ZoypQpDe41fPhwZyu+pKQkHTp0SOHh4ZJct+9z5fx5u0pKzl7sywEAAACaJDw8yOVxr8J1e0O4BgAAQGtwF67ZoREAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwSJe2HgAAAABaxoIF/srM9JVptvVIWk5goPTUU+cUH1/V1kORRLgGAADokBYs8NeaNb6SjLYeSosqK5PmzOkqqX0EbMM0O853mfPn7SopOduqz3n6XJUee+uASsvPt+rzAgAAuDJ5aG/97Jpe6t27u+z2jh2sa+vb16GcnLJWe77w8CCXx5m59pJhSIF+NlXZO8x3FAAAcAnz72KTJNntbTyQVnbsWPv4IkG49lJ3/y5aFju4rYcBAABQh83WuQJ2VFT7mOikWwgAAEAHNGPGeUntI3C2NJvN1OLFFW09DEnMXAMAAHRITz5ZHTbpFtK6WNAIAAAANJO7BY2UhQAAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAW6VDbnwMAAABtiZlrAAAAwCKEawAAAMAihGsAAADAIoRrAAAAwCKEawAAAMAihGsAAADAIoTrZnrrrbcUGxurq666Srm5uc7j77//viZPnqyJEydq8uTJ+vDDD52P7d27VxMnTlRMTIyWLVsmuh82nbv3W5KeffZZxcTEaMKECXrvvfecx999911NmDBBMTExysjIaO0hdyj/+te/lJCQoEmTJmny5Mnas2ePJMk0TS1btkwxMTGaOHGi9u3b18Yj7TjWrl2rW2+9VbGxsUpLS3Med/d5hzVeeOEFDRo0SEVFRZL4jLeUJ598UrfeeqsmTpyo//zP/9SpU6ecj/EZbxn8ndgGTDTLF198YX755ZfmtGnTzD179jiP79u3zzxx4oRpmqZ58OBB86abbnI+Fh8fb+7evdt0OBzmvffea77zzjutPu5Llbv3+/PPPzcnTpxoVlRUmN988405duxYs6qqyqyqqjLHjh1rfvPNN2ZFRYU5ceJE8/PPP2/DV3BpmzlzpvPz+s4775jTpk1z/vnee+81HQ6HuXv3bvPOO+9sy2F2GB9++KGZmJhoVlRUmKZpmgUFBaZpuv+8wxrffvutec8995ijR482CwsLTdPkM95S3nvvPfP8+fOmaZpmWlqamZaWZpomn/GWwt+JbYOZ62b6wQ9+oP79+zc4fvXVVysyMlKS9MMf/lAVFRWqrKxUfn6+zpw5o2HDhskwDMXFxWnnzp2tPexLlrv3e+fOnYqNjZWfn5+io6N1+eWXa8+ePdqzZ48uv/xyRUdHy8/PT7GxsbzfXjAMQ2VlZZKk06dPKyIiQlL1+x8XFyfDMDRs2DCdOnVK+fn5bTnUDuGVV15RcnKy/Pz8JElhYWGS3H/eYY0VK1Zo/vz5MgzDeYzPeMu46aab1KVLF0nSsGHDdOLECUl8xlsKfye2DcJ1C9i6dauuvvpq+fn56eTJk+rVq5fzsV69eunkyZNtOLqOof77GhkZqZMnT7o9jouzaNEipaWl6eabb9aTTz6pefPmSWr4/vO5tsbhw4f1ySefaMqUKZo2bZozXPC5bjk7duxQRESErrrqqjrH+Yy3vE2bNmnUqFGS+Iy3FN7XttGlrQfQHiUlJamgoKDB8ZSUFI0bN67Raz///HM99dRTeuGFF1pqeB2ON+83vNfY+//RRx9p4cKFmjBhgrZs2aLFixcrMzOz9QfZgTT2ftvtdpWWlurVV19Vbm6uUlJSmGWyQGPv+bPPPst/ry3WlP+mr1q1SjabTbfffntrDw9ocYRrFy42PJw4cUJz5szRk08+qX79+kmq/pZY889eNefUlI+g2sW83/Xf15MnTzrfV3fH4Vpj7/+CBQu0ePFiSdJtt92mRx55RBKfa2809n6/8soriomJkWEYGjJkiHx8fFRcXNzo5x2euXvPDx48qKNHj2rSpEmSqj/HkydP1oYNG/iMe8HTf9Nfe+01vfPOO8rMzHSW4vAZbxm8r22DshCLnDp1SsnJyXrwwQf1ox/9yHk8IiJC3bt316effirTNJWVlaWxY8e24Ug7hjFjxujNN99UZWWl8vLydPjwYQ0ZMkTXXXedDh8+rLy8PFVWVurNN9/UmDFj2nq4l6yIiAh9/PHHkqSPPvpIV1xxhaTq9z8rK0umaerTTz9VUFCQsx4bF2/cuHH6+9//Lkn6+uuvdf78eYWEhLj9vMM7gwYN0ocffqjs7GxlZ2erV69eeu211xQeHs5nvIW8++67Wr16tVatWqWAgADncT7jLYO/E9uGYZr0hWuO7du364knnlBRUZF69OihwYMH6/nnn9czzzyjjIwMXX755c5zX3jhBYWFhSk3N1cLFy7UuXPnNGrUKD366KN1Fs7APXfvt1T9z4qbNm2SzWbTokWLdPPNN0uS/va3v2n58uWy2+2Kj4/X/fff35Yv4ZL2ySefaPny5aqqqpK/v7+WLFmia6+9VqZp6vHHH9d7772ngIAALV++XNddd11bD/eSV1lZqUWLFunAgQPy9fXVQw89pJEjR0py/3mHdcaMGaONGzcqNDSUz3gLiYmJUWVlpYKDgyVJQ4cO1eOPPy6Jz3hL4e/E1ke4BgAAACxCWQgAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYJH/D5ldfcFNPSdnAAAAAElFTkSuQmCC\n",
1575             "text/plain": [
1576               "<Figure size 864x432 with 1 Axes>"
1577             ]
1578           },
1579           "metadata": {}
1580         },
1581         {
1582           "output_type": "display_data",
1583           "data": {
1584 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\n",
1585             "text/plain": [
1586               "<Figure size 864x432 with 1 Axes>"
1587             ]
1588           },
1589           "metadata": {}
1590         }
1591       ]
1592     },
1593     {
1594       "cell_type": "code",
1595       "metadata": {
1596         "id": "DNKMjVoAVqZP",
1597         "colab": {
1598           "base_uri": "https://localhost:8080/"
1599         },
1600         "outputId": "befefa8a-e8e1-4147-d23f-db668c092471"
1601       },
1602       "source": [
1603         "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
1604         "print('MAE: {}'.format(scores[1]))"
1605       ],
1606       "execution_count": null,
1607       "outputs": [
1608         {
1609           "output_type": "stream",
1610           "name": "stdout",
1611           "text": [
1612             "705/705 [==============================] - 132s 186ms/step - loss: 0.0101 - rmse: 0.0102\n",
1613             "MAE: 0.010171186178922653\n"
1614           ]
1615         }
1616       ]
1617     },
1618     {
1619       "cell_type": "code",
1620       "metadata": {
1621         "id": "YXcsNZ8yu9Ay"
1622       },
1623       "source": [
1624         "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
1625         "print('MAE: {}'.format(scores[1]))\n"
1626       ],
1627       "execution_count": null,
1628       "outputs": []
1629     },
1630     {
1631       "cell_type": "code",
1632       "metadata": {
1633         "id": "uCFgbZEOvZ9A"
1634       },
1635       "source": [
1636         "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
1637         "\n",
1638         "plt.figure(figsize=(10,5))\n",
1639         "plt.plot(y_pred_test)\n",
1640         "plt.plot(y_val_multi)\n",
1641         "plt.ylabel(\"Value\")\n",
1642         "plt.xlabel(\"Timestap\")\n",
1643         "plt.legend(loc='upper left')\n",
1644         "plt.show()"
1645       ],
1646       "execution_count": null,
1647       "outputs": []
1648     },
1649     {
1650       "cell_type": "code",
1651       "metadata": {
1652         "id": "dHPRJUt4aXoq"
1653       },
1654       "source": [
1655         ""
1656       ],
1657       "execution_count": null,
1658       "outputs": []
1659     }
1660   ]
1661 }