05_SimpleXml.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "SimpleXml5.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "metadata": {
        "id": "VrIDlK2mvNsS",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        " # -*- coding: utf-8 -*-\n",
        "\"\"\"SimpleXml.ipynb\n",
        "\n",
        "Automatically generated by Colaboratory.\n",
        "\n",
        "Original file is located at\n",
        "    https://colab.research.google.com/drive/1ZLBNKY4Cile4EZslasgQ0z9hMf4rZJBv\n",
        "\"\"\"\n",
        "\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "\n",
        "import numpy as np # for multidimensional arrays"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "8tEeyPXoDTBA",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Constants\n",
        "INPUT_WIDTH = 24\n",
        "\n",
        "# Word index\n",
        "word_index = {}\n",
        "word_index[\"<PAD>\"] = 0\n",
        "word_index[\"<VALUE UP>\"] = 1\n",
        "word_index[\"<VALUE DOWN>\"] = 2\n",
        "word_index[\"<STRING CHANGE>\"] = 3\n",
        "word_index[\"<CHILD CHANGE>\"] = 4\n",
        "word_index[\"<NUMBER CHANGE>\"] = 5\n",
        "word_index[\"<UNKNOWN>\"] = 6\n",
        "word_index[\".\"] = 7\n",
        "word_index[\"entry\"] = 8\n",
        "word_index[\"document\"] = 9\n",
        "word_index[\"validationxml\"] = 10\n",
        "word_index[\"browserxml\"] = 11\n",
        "word_index[\"arrangement\"] = 12\n",
        "word_index[\"base\"] = 13\n",
        "word_index[\"text()\"] = 14\n",
        "word_index[\"dlitem\"] = 15\n",
        "word_index[\"@label\"] = 16\n",
        "word_index[\"node\"] = 17\n",
        "word_index[\"member\"] = 18\n",
        "word_index[\"@type\"] = 19\n",
        "word_index[\"displayxml\"] = 20\n",
        "word_index[\"sheets\"] = 21\n",
        "word_index[\"sheet\"] = 22\n",
        "word_index[\"root\"] = 23\n",
        "word_index[\"@Y\"] = 24\n",
        "word_index[\"attr\"] = 25\n",
        "word_index[\"@rtti\"] = 26\n",
        "word_index[\"textstylemanager\"] = 27\n",
        "word_index[\"textstyle\"] = 28\n",
        "word_index[\"Entry\"] = 29\n",
        "word_index[\"@chronoid\"] = 30\n",
        "word_index[\"@X\"] = 31\n",
        "word_index[\"renderstylexml\"] = 32\n",
        "word_index[\"bodychecksum\"] = 33\n",
        "word_index[\"bodychecksumxml\"] = 34\n",
        "word_index[\"executablexml\"] = 35\n",
        "word_index[\"BrowInfo\"] = 36\n",
        "word_index[\"transform\"] = 37\n",
        "word_index[\"primattrstack\"] = 38\n",
        "word_index[\"primattr\"] = 39\n",
        "word_index[\"renderstyletable\"] = 40\n",
        "word_index[\"style\"] = 41\n",
        "word_index[\"attributesxml\"] = 42\n",
        "word_index[\"attributesets\"] = 43\n",
        "word_index[\"attributeset\"] = 44\n",
        "word_index[\"attribute\"] = 45\n",
        "word_index[\"occurrence\"] = 46\n",
        "word_index[\"@style\"] = 47\n",
        "word_index[\"feaxml\"] = 48\n",
        "word_index[\"fearesults\"] = 49\n",
        "word_index[\"simulationresults\"] = 50\n",
        "word_index[\"resultsummary\"] = 51\n",
        "word_index[\"RelativeReactionForces\"] = 52\n",
        "word_index[\"constraintReactionForce\"] = 53\n",
        "word_index[\"@maxComponent\"] = 54\n",
        "word_index[\"propertiesxml\"] = 55\n",
        "word_index[\"propertysets\"] = 56\n",
        "word_index[\"propertyset\"] = 57\n",
        "word_index[\"property\"] = 58\n",
        "word_index[\"@value\"] = 59\n",
        "word_index[\"EndTreatments\"] = 60\n",
        "word_index[\"EndTreatment\"] = 61\n",
        "word_index[\"Lengthen\"] = 62\n",
        "word_index[\"workgeometryxml\"] = 63\n",
        "word_index[\"workplanes\"] = 64\n",
        "word_index[\"@blue\"] = 65\n",
        "word_index[\"@green\"] = 66\n",
        "word_index[\"@red\"] = 67\n",
        "word_index[\"@ambient\"] = 68\n",
        "word_index[\"@diffuse\"] = 69\n",
        "word_index[\"@internalname\"] = 70\n",
        "word_index[\"testingaddin\"] = 71\n",
        "word_index[\"apixml\"] = 72\n",
        "word_index[\"assemblychecksumxml\"] = 73\n",
        "word_index[\"component\"] = 74\n",
        "word_index[\"bodyoverrides\"] = 75\n",
        "word_index[\"bodyoverride\"] = 76\n",
        "word_index[\"@count\"] = 77\n",
        "word_index[\"FDesign\"] = 78\n",
        "word_index[\"Object\"] = 79\n",
        "word_index[\"Calc\"] = 80\n",
        "word_index[\"thl\"] = 81\n",
        "word_index[\"@Val\"] = 82\n",
        "word_index[\"dcxml\"] = 83\n",
        "word_index[\"features\"] = 84\n",
        "word_index[\"feature\"] = 85\n",
        "word_index[\"@health\"] = 86\n",
        "word_index[\"@Z\"] = 87\n",
        "\n",
        "# Train data\n",
        "train_data_raw = []; train_labels = []; train_ids = []\n",
        "train_data_raw.append([4, 1, 7, 10, 71, 72]);                                                                       train_labels.append(0); train_ids.append(\"colorschemescoll_001#0\")\n",
        "train_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8]);                                                        train_labels.append(1); train_ids.append(\"copy_paste_part#1\")\n",
        "train_data_raw.append([5, 2, 7, 10, 9, 42, 43, 44, 45, 78, 79, 80, 81, 82]);                                        train_labels.append(0); train_ids.append(\"dac_chains_calc_10201020#0\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 73, 74, 75, 76, 33, 14]);                                                    train_labels.append(0); train_ids.append(\"feat_807811#0\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 83, 84, 85, 86]);                                                            train_labels.append(0); train_ids.append(\"smmsb_createpunch#0\")\n",
        "train_data_raw.append([5, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 15, 18, 24]);                 train_labels.append(0); train_ids.append(\"tc5356#5\")\n",
        "train_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 13, 25, 25, 27, 28, 18, 18, 14]);             train_labels.append(0); train_ids.append(\"idw_etsy_d1207#0\")\n",
        "train_data_raw.append([5, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 15, 13, 37, 38, 39, 18, 65]);                     train_labels.append(0); train_ids.append(\"dm_at_appendfilenameinviewblockname_0004#0\")\n",
        "train_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 13, 15, 15, 15, 15, 15, 15, 18, 87]); train_labels.append(0); train_ids.append(\"dm_migr_r11_coolingtower#0\")\n",
        "train_data_raw.append([5, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 18, 31]);                     train_labels.append(0); train_ids.append(\"592453#0\")\n",
        "train_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 15, 13, 37, 38, 39, 18, 66]);                     train_labels.append(0); train_ids.append(\"dm_at_appendfilenameinviewblockname_0004#1\")\n",
        "train_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 15, 13, 37, 38, 39, 18, 67]);                     train_labels.append(0); train_ids.append(\"dm_at_appendfilenameinviewblockname_0004#2\")\n",
        "train_data_raw.append([5, 1, 7, 10, 9, 42, 43, 44, 45, 60, 61, 62, 14]);                                            train_labels.append(0); train_ids.append(\"curvedframe_trimtoframe_spline#0\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 34, 33, 14]);                                                                train_labels.append(0); train_ids.append(\"bug116303#0\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 48, 49, 50, 51, 52, 53, 54]);                                                train_labels.append(0); train_ids.append(\"cylinder-30x1000x1500n#0\")\n",
        "train_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 18, 24]);                     train_labels.append(0); train_ids.append(\"907031#1\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 55, 56, 57, 58, 59]);                                                        train_labels.append(0); train_ids.append(\"curvedframe_trimtoframe_arc#0\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 32, 46, 47]);                                                                train_labels.append(0); train_ids.append(\"windshield wiper#6\")\n",
        "train_data_raw.append([4, 1, 7, 10, 9, 63, 64]);                                                                    train_labels.append(0); train_ids.append(\"parker union tee 164ca-264ca 164ca-2#1\")\n",
        "train_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 16]);                                                          train_labels.append(1); train_ids.append(\"break link_nx_part2#3\")\n",
        "train_data_raw.append([4, 1, 7, 10, 35, 36, 29, 29, 29, 29, 29]);                                                   train_labels.append(0); train_ids.append(\"md_mbs_c1213#3\")\n",
        "train_data_raw.append([4, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 13, 15, 15, 15, 15, 15]);             train_labels.append(0); train_ids.append(\"idw_replacemodelreference_c1102#0\")\n",
        "train_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8]);                                                     train_labels.append(1); train_ids.append(\"copy_paste_part#3\")\n",
        "train_data_raw.append([4, 2, 7, 10, 9, 11, 12, 8, 8]);                                                              train_labels.append(1); train_ids.append(\"break link_nx_part2#5\")\n",
        "train_data_raw.append([3, 2, 7, 10, 9, 32, 40, 41, 68]);                                                            train_labels.append(0); train_ids.append(\"windshield wiper#0\")\n",
        "train_data_raw.append([3, 2, 7, 10, 9, 32, 40, 41, 69]);                                                            train_labels.append(0); train_ids.append(\"windshield wiper#1\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 16]);                                                    train_labels.append(1); train_ids.append(\"copy_paste_part#0\")\n",
        "train_data_raw.append([5, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 18, 24]);                     train_labels.append(0); train_ids.append(\"tc5356#0\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 16]);                                                       train_labels.append(1); train_ids.append(\"break link_nx_part2#0\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 32, 40, 41, 70]);                                                            train_labels.append(0); train_ids.append(\"windshield wiper#2\")\n",
        "train_data_raw.append([5, 1, 7, 10, 9, 63, 64, 77]);                                                                train_labels.append(0); train_ids.append(\"parker union tee 164ca-264ca 164ca-2#0\")\n",
        "train_data_raw.append([5, 2, 7, 10, 9, 11, 12, 8, 8, 30]);                                                          train_labels.append(1); train_ids.append(\"break link_nx_part2#2\")\n",
        "train_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 18, 31]);                     train_labels.append(0); train_ids.append(\"907031#10\")\n",
        "train_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 16]);                                                 train_labels.append(1); train_ids.append(\"copy_paste_part#2\")\n",
        "train_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 26]);                                                          train_labels.append(1); train_ids.append(\"break link_nx_part2#4\")\n",
        "train_data_raw.append([4, 1, 7, 10, 35, 36, 29, 29, 29, 29, 29, 29, 29]);                                           train_labels.append(0); train_ids.append(\"md_mbs_c1213#0\")\n",
        "train_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8]);                                                              train_labels.append(1); train_ids.append(\"5456_moveeop#0\")\n",
        "\n",
        "# Validation data\n",
        "validation_data_raw = []; validation_labels = []; validation_ids = []\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8]);                                                              validation_labels.append(1); validation_ids.append(\"5456_moveeop#0\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 16]);                                                       validation_labels.append(1); validation_ids.append(\"break link_nx_part2#0\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 11, 12, 8, 8, 30]);                                                          validation_labels.append(1); validation_ids.append(\"break link_nx_part2#2\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 16]);                                                          validation_labels.append(1); validation_ids.append(\"break link_nx_part2#3\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 26]);                                                          validation_labels.append(1); validation_ids.append(\"break link_nx_part2#4\")\n",
        "validation_data_raw.append([4, 2, 7, 10, 9, 11, 12, 8, 8]);                                                              validation_labels.append(1); validation_ids.append(\"break link_nx_part2#5\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 16]);                                                    validation_labels.append(1); validation_ids.append(\"copy_paste_part#0\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8]);                                                        validation_labels.append(1); validation_ids.append(\"copy_paste_part#1\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 16]);                                                 validation_labels.append(1); validation_ids.append(\"copy_paste_part#2\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8]);                                                     validation_labels.append(1); validation_ids.append(\"copy_paste_part#3\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8, 16]);                                              validation_labels.append(1); validation_ids.append(\"copy_paste_part#4\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8]);                                                  validation_labels.append(1); validation_ids.append(\"copy_paste_part#5\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8, 8, 16]);                                           validation_labels.append(1); validation_ids.append(\"copy_paste_part#6\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8, 8]);                                               validation_labels.append(1); validation_ids.append(\"copy_paste_part#7\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8]);                                                                 validation_labels.append(1); validation_ids.append(\"bug108192#0\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 16]);                                                       validation_labels.append(1); validation_ids.append(\"bug116272#1\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 16]);                                                          validation_labels.append(1); validation_ids.append(\"bug37980#0\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 11, 12, 8, 8, 8, 30]);                                                       validation_labels.append(1); validation_ids.append(\"futureanycad_update_catia_assembly4#6\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 16]);                                                 validation_labels.append(1); validation_ids.append(\"non-associative_import_catia_assm2#2\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 8, 8]);                                                           validation_labels.append(1); validation_ids.append(\"non-associative_import_catia_assm2#3\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 16]);                                                    validation_labels.append(1); validation_ids.append(\"non-associative_import_catia_assm2#26\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8, 16]);                                              validation_labels.append(1); validation_ids.append(\"localsave_swx_1#2\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8, 8, 16]);                                           validation_labels.append(1); validation_ids.append(\"localsave_swx_1#3\")\n",
        "validation_data_raw.append([4, 2, 7, 10, 9, 11, 12, 8]);                                                                 validation_labels.append(1); validation_ids.append(\"selective_catia_part12#0\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 19]);                                                             validation_labels.append(1); validation_ids.append(\"createtextboxconstraintproxy_001#0\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 14]);                                                             validation_labels.append(1); validation_ids.append(\"createtextboxconstraintproxy_001#1\")\n",
        "validation_data_raw.append([4, 2, 7, 10, 9, 11, 12, 8, 14]);                                                             validation_labels.append(1); validation_ids.append(\"createtextboxconstraintproxy_001#2\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 26]);                                                       validation_labels.append(1); validation_ids.append(\"additionaldisplaysettings_ipn#1\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 26]);                                                       validation_labels.append(1); validation_ids.append(\"additionaldisplaysettings_ipn#4\")\n",
        "validation_data_raw.append([4, 2, 7, 10, 9, 11, 12, 8, 8, 8]);                                                           validation_labels.append(1); validation_ids.append(\"additionaldisplaysettings_ipn#5\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 14]);                                                             validation_labels.append(1); validation_ids.append(\"moveoccurrence_01#1\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 11, 12, 8, 14]);                                                             validation_labels.append(1); validation_ids.append(\"part_ang_set paramter sensor then create#2\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 26]);                                                             validation_labels.append(1); validation_ids.append(\"sheet_dia_set parameter then create#0\")\n",
        "validation_data_raw.append([4, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8]);                                                        validation_labels.append(1); validation_ids.append(\"constraints_1215425#4\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 16]);                                                             validation_labels.append(1); validation_ids.append(\"iam_fllt_l9105#0\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 16]);                                                             validation_labels.append(1); validation_ids.append(\"translator_aliasimportoption_003#0\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 30]);                                                    validation_labels.append(1); validation_ids.append(\"translator_stepplacecomponentimportoption_004#1\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 30]);                                                 validation_labels.append(1); validation_ids.append(\"translator_stepplacecomponentimportoption_004#3\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 30]);                                                    validation_labels.append(1); validation_ids.append(\"derv_1509172#1\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 11, 12, 8, 8, 30]);                                                          validation_labels.append(1); validation_ids.append(\"derv_1509172#4\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 11, 12, 8, 8, 8, 30]);                                                       validation_labels.append(1); validation_ids.append(\"dprt_rmm_11#0\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8, 8, 8, 16]);                                        validation_labels.append(1); validation_ids.append(\"am_migr_r10_arm system#13\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 26]);                                                    validation_labels.append(1); validation_ids.append(\"am_migr_r10_arm system#20\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 26]);                                                 validation_labels.append(1); validation_ids.append(\"am_migr_r10_arm system#79\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8, 26]);                                              validation_labels.append(1); validation_ids.append(\"am_migr_r10_arm system#98\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 11, 12, 8, 8, 8, 8, 8, 8, 8, 8, 16]);                                        validation_labels.append(1); validation_ids.append(\"sm brace- small#8\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 48, 49, 50, 51, 52, 53, 54]);                                                validation_labels.append(0); validation_ids.append(\"cylinder-30x1000x1500n#0\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 35, 36, 29, 29, 29, 29, 29, 29, 29]);                                           validation_labels.append(0); validation_ids.append(\"md_mbs_c1213#0\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 35, 36, 29, 29, 29, 29, 29]);                                                   validation_labels.append(0); validation_ids.append(\"md_mbs_c1213#3\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 34, 33, 14]);                                                                validation_labels.append(0); validation_ids.append(\"bug116303#0\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 71, 72]);                                                                       validation_labels.append(0); validation_ids.append(\"colorschemescoll_001#0\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 55, 56, 57, 58, 59]);                                                        validation_labels.append(0); validation_ids.append(\"curvedframe_trimtoframe_arc#0\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 42, 43, 44, 45, 60, 61, 62, 14]);                                            validation_labels.append(0); validation_ids.append(\"curvedframe_trimtoframe_spline#0\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 73, 74, 75, 76, 33, 14]);                                                    validation_labels.append(0); validation_ids.append(\"feat_807811#0\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 63, 64, 77]);                                                                validation_labels.append(0); validation_ids.append(\"parker union tee 164ca-264ca 164ca-2#0\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 63, 64]);                                                                    validation_labels.append(0); validation_ids.append(\"parker union tee 164ca-264ca 164ca-2#1\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 18, 24]);                     validation_labels.append(0); validation_ids.append(\"tc5356#0\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 15, 18, 24]);                 validation_labels.append(0); validation_ids.append(\"tc5356#5\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 42, 43, 44, 45, 78, 79, 80, 81, 82]);                                        validation_labels.append(0); validation_ids.append(\"dac_chains_calc_10201020#0\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 15, 13, 37, 38, 39, 18, 65]);                     validation_labels.append(0); validation_ids.append(\"dm_at_appendfilenameinviewblockname_0004#0\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 15, 13, 37, 38, 39, 18, 66]);                     validation_labels.append(0); validation_ids.append(\"dm_at_appendfilenameinviewblockname_0004#1\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 15, 13, 37, 38, 39, 18, 67]);                     validation_labels.append(0); validation_ids.append(\"dm_at_appendfilenameinviewblockname_0004#2\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 13, 25, 25, 27, 28, 18, 18, 14]);             validation_labels.append(0); validation_ids.append(\"idw_etsy_d1207#0\")\n",
        "validation_data_raw.append([5, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 18, 31]);                     validation_labels.append(0); validation_ids.append(\"592453#0\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 18, 24]);                     validation_labels.append(0); validation_ids.append(\"907031#1\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 15, 15, 18, 31]);                     validation_labels.append(0); validation_ids.append(\"907031#10\")\n",
        "validation_data_raw.append([4, 1, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 13, 15, 15, 15, 15, 15]);             validation_labels.append(0); validation_ids.append(\"idw_replacemodelreference_c1102#0\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 32, 40, 41, 68]);                                                            validation_labels.append(0); validation_ids.append(\"windshield wiper#0\")\n",
        "validation_data_raw.append([3, 2, 7, 10, 9, 32, 40, 41, 69]);                                                            validation_labels.append(0); validation_ids.append(\"windshield wiper#1\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 32, 40, 41, 70]);                                                            validation_labels.append(0); validation_ids.append(\"windshield wiper#2\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 32, 46, 47]);                                                                validation_labels.append(0); validation_ids.append(\"windshield wiper#6\")\n",
        "validation_data_raw.append([3, 1, 7, 10, 9, 83, 84, 85, 86]);                                                            validation_labels.append(0); validation_ids.append(\"smmsb_createpunch#0\")\n",
        "validation_data_raw.append([5, 2, 7, 10, 9, 20, 21, 22, 9, 23, 17, 13, 13, 17, 13, 13, 15, 15, 15, 15, 15, 15, 18, 87]); validation_labels.append(0); validation_ids.append(\"dm_migr_r11_coolingtower#0\")\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "fI6IrfgnDYws",
        "colab_type": "code",
        "outputId": "0c0c13ee-b931-48f8-c47a-a81ca316d94e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "#print(word_index)\n",
        "print(\"word_index length: \", len(word_index))\n"
      ],
      "execution_count": 121,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "word_index length:  88\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "pL4FYiOSp_Yx",
        "colab_type": "code",
        "outputId": "125566a8-d149-4a17-f97a-f6a99cc94020",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "cell_type": "code",
      "source": [
        "# Pad train data\n",
        "train_data = keras.preprocessing.sequence.pad_sequences(train_data_raw, value=word_index[\"<PAD>\"], padding='post', maxlen=INPUT_WIDTH)\n",
        "print(train_data.shape)\n",
        "\n",
        "# Pad validation data\n",
        "validation_data = keras.preprocessing.sequence.pad_sequences(validation_data_raw, value=word_index[\"<PAD>\"], padding='post', maxlen=INPUT_WIDTH)\n",
        "print(validation_data.shape)"
      ],
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(37, 24)\n",
            "(73, 24)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "5ts5dy3kqgVX",
        "colab_type": "code",
        "outputId": "20c6ae5e-1fff-4581-ba29-3f3fc7da3934",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 3723
        }
      },
      "cell_type": "code",
      "source": [
        "model = tf.keras.models.Sequential([\n",
        "    tf.keras.layers.Embedding(len(word_index), 16, input_length=INPUT_WIDTH),\n",
        "    tf.keras.layers.GlobalMaxPooling1D(),\n",
        "    tf.keras.layers.Dense(16, activation=tf.nn.relu),\n",
        "    tf.keras.layers.Dense(1, activation=tf.nn.sigmoid)\n",
        "])\n",
        "\n",
        "model.summary()\n",
        "\n",
        "model.compile(optimizer='adam',\n",
        "              loss='binary_crossentropy',\n",
        "              metrics=['accuracy'])\n",
        "\n",
        "# Train\n",
        "history = model.fit(train_data, train_labels, epochs=100, batch_size=4, validation_data=(validation_data, validation_labels), verbose=1)\n",
        "\n",
        "# See final loss and accuracy\n",
        "results = model.evaluate(validation_data, validation_labels)\n",
        "print(results)\n"
      ],
      "execution_count": 123,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "embedding_16 (Embedding)     (None, 24, 16)            1408      \n",
            "_________________________________________________________________\n",
            "global_max_pooling1d_6 (Glob (None, 16)                0         \n",
            "_________________________________________________________________\n",
            "dense_32 (Dense)             (None, 16)                272       \n",
            "_________________________________________________________________\n",
            "dense_33 (Dense)             (None, 1)                 17        \n",
            "=================================================================\n",
            "Total params: 1,697\n",
            "Trainable params: 1,697\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n",
            "Train on 37 samples, validate on 73 samples\n",
            "Epoch 1/100\n",
            "37/37 [==============================] - 1s 17ms/sample - loss: 0.6909 - acc: 0.7297 - val_loss: 0.6894 - val_acc: 0.3699\n",
            "Epoch 2/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.6793 - acc: 0.7297 - val_loss: 0.6888 - val_acc: 0.3699\n",
            "Epoch 3/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.6675 - acc: 0.7297 - val_loss: 0.6868 - val_acc: 0.3699\n",
            "Epoch 4/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.6555 - acc: 0.7297 - val_loss: 0.6843 - val_acc: 0.3699\n",
            "Epoch 5/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.6437 - acc: 0.7297 - val_loss: 0.6805 - val_acc: 0.3699\n",
            "Epoch 6/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.6314 - acc: 0.7297 - val_loss: 0.6744 - val_acc: 0.3699\n",
            "Epoch 7/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.6193 - acc: 0.7297 - val_loss: 0.6707 - val_acc: 0.3699\n",
            "Epoch 8/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.6034 - acc: 0.7297 - val_loss: 0.6633 - val_acc: 0.3699\n",
            "Epoch 9/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.5866 - acc: 0.7297 - val_loss: 0.6536 - val_acc: 0.3699\n",
            "Epoch 10/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.5684 - acc: 0.7297 - val_loss: 0.6425 - val_acc: 0.3699\n",
            "Epoch 11/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.5484 - acc: 0.7297 - val_loss: 0.6253 - val_acc: 0.3699\n",
            "Epoch 12/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.5267 - acc: 0.7297 - val_loss: 0.6090 - val_acc: 0.3699\n",
            "Epoch 13/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.5033 - acc: 0.7838 - val_loss: 0.5895 - val_acc: 0.6849\n",
            "Epoch 14/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.4781 - acc: 0.9189 - val_loss: 0.5684 - val_acc: 0.9315\n",
            "Epoch 15/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.4513 - acc: 1.0000 - val_loss: 0.5449 - val_acc: 1.0000\n",
            "Epoch 16/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.4246 - acc: 1.0000 - val_loss: 0.5161 - val_acc: 1.0000\n",
            "Epoch 17/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.3968 - acc: 1.0000 - val_loss: 0.4927 - val_acc: 1.0000\n",
            "Epoch 18/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.3685 - acc: 1.0000 - val_loss: 0.4674 - val_acc: 1.0000\n",
            "Epoch 19/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.3405 - acc: 1.0000 - val_loss: 0.4410 - val_acc: 1.0000\n",
            "Epoch 20/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.3132 - acc: 1.0000 - val_loss: 0.4153 - val_acc: 1.0000\n",
            "Epoch 21/100\n",
            "37/37 [==============================] - 0s 980us/sample - loss: 0.2866 - acc: 1.0000 - val_loss: 0.3845 - val_acc: 1.0000\n",
            "Epoch 22/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.2623 - acc: 1.0000 - val_loss: 0.3541 - val_acc: 1.0000\n",
            "Epoch 23/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.2379 - acc: 1.0000 - val_loss: 0.3276 - val_acc: 1.0000\n",
            "Epoch 24/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.2159 - acc: 1.0000 - val_loss: 0.3021 - val_acc: 1.0000\n",
            "Epoch 25/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.1947 - acc: 1.0000 - val_loss: 0.2807 - val_acc: 1.0000\n",
            "Epoch 26/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.1757 - acc: 1.0000 - val_loss: 0.2542 - val_acc: 1.0000\n",
            "Epoch 27/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.1579 - acc: 1.0000 - val_loss: 0.2328 - val_acc: 1.0000\n",
            "Epoch 28/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.1424 - acc: 1.0000 - val_loss: 0.2104 - val_acc: 1.0000\n",
            "Epoch 29/100\n",
            "37/37 [==============================] - 0s 997us/sample - loss: 0.1287 - acc: 1.0000 - val_loss: 0.1918 - val_acc: 1.0000\n",
            "Epoch 30/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.1160 - acc: 1.0000 - val_loss: 0.1761 - val_acc: 1.0000\n",
            "Epoch 31/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.1048 - acc: 1.0000 - val_loss: 0.1610 - val_acc: 1.0000\n",
            "Epoch 32/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0944 - acc: 1.0000 - val_loss: 0.1475 - val_acc: 1.0000\n",
            "Epoch 33/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0853 - acc: 1.0000 - val_loss: 0.1355 - val_acc: 1.0000\n",
            "Epoch 34/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0773 - acc: 1.0000 - val_loss: 0.1243 - val_acc: 1.0000\n",
            "Epoch 35/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0702 - acc: 1.0000 - val_loss: 0.1134 - val_acc: 1.0000\n",
            "Epoch 36/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0636 - acc: 1.0000 - val_loss: 0.1045 - val_acc: 1.0000\n",
            "Epoch 37/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0579 - acc: 1.0000 - val_loss: 0.0957 - val_acc: 1.0000\n",
            "Epoch 38/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0528 - acc: 1.0000 - val_loss: 0.0881 - val_acc: 1.0000\n",
            "Epoch 39/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0482 - acc: 1.0000 - val_loss: 0.0815 - val_acc: 1.0000\n",
            "Epoch 40/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0442 - acc: 1.0000 - val_loss: 0.0746 - val_acc: 1.0000\n",
            "Epoch 41/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0400 - acc: 1.0000 - val_loss: 0.0682 - val_acc: 1.0000\n",
            "Epoch 42/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0364 - acc: 1.0000 - val_loss: 0.0627 - val_acc: 1.0000\n",
            "Epoch 43/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0331 - acc: 1.0000 - val_loss: 0.0572 - val_acc: 1.0000\n",
            "Epoch 44/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0301 - acc: 1.0000 - val_loss: 0.0529 - val_acc: 1.0000\n",
            "Epoch 45/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0275 - acc: 1.0000 - val_loss: 0.0493 - val_acc: 1.0000\n",
            "Epoch 46/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0251 - acc: 1.0000 - val_loss: 0.0457 - val_acc: 1.0000\n",
            "Epoch 47/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0232 - acc: 1.0000 - val_loss: 0.0423 - val_acc: 1.0000\n",
            "Epoch 48/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0213 - acc: 1.0000 - val_loss: 0.0398 - val_acc: 1.0000\n",
            "Epoch 49/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0198 - acc: 1.0000 - val_loss: 0.0371 - val_acc: 1.0000\n",
            "Epoch 50/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0182 - acc: 1.0000 - val_loss: 0.0350 - val_acc: 1.0000\n",
            "Epoch 51/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0170 - acc: 1.0000 - val_loss: 0.0332 - val_acc: 1.0000\n",
            "Epoch 52/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0159 - acc: 1.0000 - val_loss: 0.0312 - val_acc: 1.0000\n",
            "Epoch 53/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0148 - acc: 1.0000 - val_loss: 0.0293 - val_acc: 1.0000\n",
            "Epoch 54/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0137 - acc: 1.0000 - val_loss: 0.0274 - val_acc: 1.0000\n",
            "Epoch 55/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0128 - acc: 1.0000 - val_loss: 0.0256 - val_acc: 1.0000\n",
            "Epoch 56/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0120 - acc: 1.0000 - val_loss: 0.0243 - val_acc: 1.0000\n",
            "Epoch 57/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0112 - acc: 1.0000 - val_loss: 0.0229 - val_acc: 1.0000\n",
            "Epoch 58/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0106 - acc: 1.0000 - val_loss: 0.0217 - val_acc: 1.0000\n",
            "Epoch 59/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0100 - acc: 1.0000 - val_loss: 0.0206 - val_acc: 1.0000\n",
            "Epoch 60/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0094 - acc: 1.0000 - val_loss: 0.0196 - val_acc: 1.0000\n",
            "Epoch 61/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0089 - acc: 1.0000 - val_loss: 0.0189 - val_acc: 1.0000\n",
            "Epoch 62/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0085 - acc: 1.0000 - val_loss: 0.0181 - val_acc: 1.0000\n",
            "Epoch 63/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0080 - acc: 1.0000 - val_loss: 0.0172 - val_acc: 1.0000\n",
            "Epoch 64/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0076 - acc: 1.0000 - val_loss: 0.0164 - val_acc: 1.0000\n",
            "Epoch 65/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0072 - acc: 1.0000 - val_loss: 0.0158 - val_acc: 1.0000\n",
            "Epoch 66/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0069 - acc: 1.0000 - val_loss: 0.0152 - val_acc: 1.0000\n",
            "Epoch 67/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0066 - acc: 1.0000 - val_loss: 0.0146 - val_acc: 1.0000\n",
            "Epoch 68/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0063 - acc: 1.0000 - val_loss: 0.0139 - val_acc: 1.0000\n",
            "Epoch 69/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0060 - acc: 1.0000 - val_loss: 0.0133 - val_acc: 1.0000\n",
            "Epoch 70/100\n",
            "37/37 [==============================] - 0s 986us/sample - loss: 0.0057 - acc: 1.0000 - val_loss: 0.0129 - val_acc: 1.0000\n",
            "Epoch 71/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0055 - acc: 1.0000 - val_loss: 0.0125 - val_acc: 1.0000\n",
            "Epoch 72/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0053 - acc: 1.0000 - val_loss: 0.0120 - val_acc: 1.0000\n",
            "Epoch 73/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0051 - acc: 1.0000 - val_loss: 0.0116 - val_acc: 1.0000\n",
            "Epoch 74/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0048 - acc: 1.0000 - val_loss: 0.0112 - val_acc: 1.0000\n",
            "Epoch 75/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0046 - acc: 1.0000 - val_loss: 0.0107 - val_acc: 1.0000\n",
            "Epoch 76/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0044 - acc: 1.0000 - val_loss: 0.0103 - val_acc: 1.0000\n",
            "Epoch 77/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0043 - acc: 1.0000 - val_loss: 0.0100 - val_acc: 1.0000\n",
            "Epoch 78/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0041 - acc: 1.0000 - val_loss: 0.0096 - val_acc: 1.0000\n",
            "Epoch 79/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0039 - acc: 1.0000 - val_loss: 0.0093 - val_acc: 1.0000\n",
            "Epoch 80/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0038 - acc: 1.0000 - val_loss: 0.0090 - val_acc: 1.0000\n",
            "Epoch 81/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0037 - acc: 1.0000 - val_loss: 0.0087 - val_acc: 1.0000\n",
            "Epoch 82/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0035 - acc: 1.0000 - val_loss: 0.0085 - val_acc: 1.0000\n",
            "Epoch 83/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0034 - acc: 1.0000 - val_loss: 0.0082 - val_acc: 1.0000\n",
            "Epoch 84/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0033 - acc: 1.0000 - val_loss: 0.0079 - val_acc: 1.0000\n",
            "Epoch 85/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0032 - acc: 1.0000 - val_loss: 0.0077 - val_acc: 1.0000\n",
            "Epoch 86/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0031 - acc: 1.0000 - val_loss: 0.0075 - val_acc: 1.0000\n",
            "Epoch 87/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0030 - acc: 1.0000 - val_loss: 0.0073 - val_acc: 1.0000\n",
            "Epoch 88/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0029 - acc: 1.0000 - val_loss: 0.0071 - val_acc: 1.0000\n",
            "Epoch 89/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0028 - acc: 1.0000 - val_loss: 0.0069 - val_acc: 1.0000\n",
            "Epoch 90/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0027 - acc: 1.0000 - val_loss: 0.0067 - val_acc: 1.0000\n",
            "Epoch 91/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0026 - acc: 1.0000 - val_loss: 0.0066 - val_acc: 1.0000\n",
            "Epoch 92/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0025 - acc: 1.0000 - val_loss: 0.0064 - val_acc: 1.0000\n",
            "Epoch 93/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0025 - acc: 1.0000 - val_loss: 0.0062 - val_acc: 1.0000\n",
            "Epoch 94/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0024 - acc: 1.0000 - val_loss: 0.0061 - val_acc: 1.0000\n",
            "Epoch 95/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0023 - acc: 1.0000 - val_loss: 0.0059 - val_acc: 1.0000\n",
            "Epoch 96/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0022 - acc: 1.0000 - val_loss: 0.0058 - val_acc: 1.0000\n",
            "Epoch 97/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0022 - acc: 1.0000 - val_loss: 0.0056 - val_acc: 1.0000\n",
            "Epoch 98/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0021 - acc: 1.0000 - val_loss: 0.0055 - val_acc: 1.0000\n",
            "Epoch 99/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0021 - acc: 1.0000 - val_loss: 0.0053 - val_acc: 1.0000\n",
            "Epoch 100/100\n",
            "37/37 [==============================] - 0s 1ms/sample - loss: 0.0020 - acc: 1.0000 - val_loss: 0.0052 - val_acc: 1.0000\n",
            "73/73 [==============================] - 0s 121us/sample - loss: 0.0052 - acc: 1.0000\n",
            "[0.005226926200334238, 1.0]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "cPIfRF8INgc_",
        "colab_type": "code",
        "outputId": "61affd6f-3540-4657-9296-52b3cc385e6c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        }
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "history_dict = history.history\n",
        "history_dict.keys()\n",
        "acc = history_dict['acc']\n",
        "val_acc = history_dict['val_acc']\n",
        "loss = history_dict['loss']\n",
        "val_loss = history_dict['val_loss']\n",
        "\n",
        "epochs = range(1, len(acc) + 1)\n",
        "\n",
        "# \"bo\" is for \"blue dot\"\n",
        "plt.plot(epochs, loss, 'bo', label='Training loss')\n",
        "# b is for \"solid blue line\"\n",
        "plt.plot(epochs, val_loss, 'b', label='Validation loss')\n",
        "plt.title('Training and validation loss')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Loss')\n",
        "plt.legend()\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 124,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9XEREfJ+St48xc913377uY5Yt09C5iEhVoi6ZD0pMdHi01rtQ8+YuWrd2sn69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\nIibzL3mOmEPqV6IgAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 576x396 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "6MqKDINMN5px",
        "colab_type": "code",
        "outputId": "5205a005-de0f-4854-d677-bdb565871507",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        }
      },
      "cell_type": "code",
      "source": [
        "plt.clf()   # clear figure\n",
        "\n",
        "plt.plot(epochs, acc, 'bo', label='Training acc')\n",
        "plt.plot(epochs, val_acc, 'b', label='Validation acc')\n",
        "plt.title('Training and validation accuracy')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.legend()\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 125,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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EJH8Mb5nhd7yJiOSP4S0zmZkucHOz4PbbOWxORCRXDG+Z+e03F9x1lxku/C9LRCRb/Cde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\niCSG4U1ERCQx/x9TtyttUrgmUgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 576x396 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "zygKqfqlgmX1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1278
        },
        "outputId": "1407014e-45f4-4945-9c07-d4330723a228"
      },
      "cell_type": "code",
      "source": [
        "# Review data\n",
        "  \n",
        "reverse_word_index = dict([(value, key) for (key, value) in word_index.items()])\n",
        "\n",
        "def decode_review(text):\n",
        "    return ' '.join([reverse_word_index.get(i, '?') for i in text])\n",
        "  \n",
        "  \n",
        "x =  decode_review(train_data_raw[0])\n",
        "\n",
        "predictions = model.predict(validation_data)\n",
        "for index, data_item in enumerate(validation_data):\n",
        "    print(\"Prediction: \" + str(predictions[index]).ljust(12) , \"Data: \" + decode_review(data_item))\n",
        "\n",
        "  "
      ],
      "execution_count": 132,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9934429]  Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry @chronoid <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947566]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry @rtti <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry entry entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9934429]  Data: <NUMBER CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry @chronoid <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9811332]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry @type <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.97007924] Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry text() <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9709426]  Data: <CHILD CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry text() <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947566]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry @rtti <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947566]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry @rtti <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.97007924] Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry text() <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9709426]  Data: <CHILD CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry text() <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947566]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry @rtti <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947019]  Data: <CHILD CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9934429]  Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry @chronoid <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9934429]  Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry entry @chronoid <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9934429]  Data: <NUMBER CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry @chronoid <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9934429]  Data: <NUMBER CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry @chronoid <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9934429]  Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry @chronoid <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947566]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry @rtti <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947566]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry entry @rtti <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9947566]  Data: <STRING CHANGE> <VALUE DOWN> . validationxml document browserxml arrangement entry entry entry entry entry entry @rtti <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.9948746]  Data: <STRING CHANGE> <VALUE UP> . validationxml document browserxml arrangement entry entry entry entry entry entry entry entry @label <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00182033] Data: <STRING CHANGE> <VALUE UP> . validationxml document feaxml fearesults simulationresults resultsummary RelativeReactionForces constraintReactionForce @maxComponent <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00082487] Data: <CHILD CHANGE> <VALUE UP> . validationxml executablexml BrowInfo Entry Entry Entry Entry Entry Entry Entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00082487] Data: <CHILD CHANGE> <VALUE UP> . validationxml executablexml BrowInfo Entry Entry Entry Entry Entry <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00110781] Data: <STRING CHANGE> <VALUE UP> . validationxml document bodychecksumxml bodychecksum text() <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00131553] Data: <CHILD CHANGE> <VALUE UP> . validationxml testingaddin apixml <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00149718] Data: <STRING CHANGE> <VALUE UP> . validationxml document propertiesxml propertysets propertyset property @value <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00100988] Data: <NUMBER CHANGE> <VALUE UP> . validationxml document attributesxml attributesets attributeset attribute EndTreatments EndTreatment Lengthen text() <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00131452] Data: <STRING CHANGE> <VALUE UP> . validationxml document assemblychecksumxml component bodyoverrides bodyoverride bodychecksum text() <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00091767] Data: <NUMBER CHANGE> <VALUE UP> . validationxml document workgeometryxml workplanes @count <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00080994] Data: <CHILD CHANGE> <VALUE UP> . validationxml document workgeometryxml workplanes <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.0001699]  Data: <NUMBER CHANGE> <VALUE UP> . validationxml document displayxml sheets sheet document root node base base node base dlitem dlitem member @Y <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.0001699]  Data: <NUMBER CHANGE> <VALUE UP> . validationxml document displayxml sheets sheet document root node base base node base dlitem dlitem dlitem member @Y <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00113806] Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document attributesxml attributesets attributeset attribute FDesign Object Calc thl @Val <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00017914] Data: <NUMBER CHANGE> <VALUE UP> . validationxml document displayxml sheets sheet document root node base dlitem base transform primattrstack primattr member @blue <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00017655] Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document displayxml sheets sheet document root node base dlitem base transform primattrstack primattr member @green <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00017801] Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document displayxml sheets sheet document root node base dlitem base transform primattrstack primattr member @red <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00027418] Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document displayxml sheets sheet document root node base base base attr attr textstylemanager textstyle member member text() <PAD> <PAD> <PAD>\n",
            "Prediction: [0.0001699]  Data: <NUMBER CHANGE> <VALUE UP> . validationxml document displayxml sheets sheet document root node base base node base dlitem dlitem member @X <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.0001699]  Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document displayxml sheets sheet document root node base base node base dlitem dlitem member @Y <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.0001699]  Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document displayxml sheets sheet document root node base base node base dlitem dlitem member @X <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00016984] Data: <CHILD CHANGE> <VALUE UP> . validationxml document displayxml sheets sheet document root node base base node base base dlitem dlitem dlitem dlitem dlitem <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00058311] Data: <STRING CHANGE> <VALUE DOWN> . validationxml document renderstylexml renderstyletable style @ambient <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00054058] Data: <STRING CHANGE> <VALUE DOWN> . validationxml document renderstylexml renderstyletable style @diffuse <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00053054] Data: <STRING CHANGE> <VALUE UP> . validationxml document renderstylexml renderstyletable style @internalname <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00137669] Data: <STRING CHANGE> <VALUE UP> . validationxml document renderstylexml occurrence @style <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00156528] Data: <STRING CHANGE> <VALUE UP> . validationxml document dcxml features feature @health <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD> <PAD>\n",
            "Prediction: [0.00027052] Data: <NUMBER CHANGE> <VALUE DOWN> . validationxml document displayxml sheets sheet document root node base base node base base dlitem dlitem dlitem dlitem dlitem dlitem member @Z\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}