100_cairo_2000_1024_32.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# file name meaning\n",
    "\n",
    "eg. 100_cairo_2000_1024_32.ipynb\n",
    "\n",
    "`[tag]_[dataset_name]_[epochs/maxIters]_[data_length/seq_len]_[batch_size]`"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "from train_network_synthetic import train_ttn\n",
    "\n",
    "from configuration import general\n",
    "import os\n",
    "from configuration.configure import JUPYTER_TOKEN\n",
    "\n",
    "\n",
    "nb_name_file = general.ipy_nb_name(JUPYTER_TOKEN[\"token_lists\"])"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "theNotebook = nb_name_file.split('_')\n",
    "assert len(theNotebook) == 5, 'The number of parameters should be 5'\n",
    "\n",
    "global title_param\n",
    "title_param = {\n",
    "    'num': theNotebook[0],\n",
    "    'dataset_name': theNotebook[1],\n",
    "    'maxIters': int(theNotebook[2]),\n",
    "    'seq_len': int(theNotebook[3]),\n",
    "    'batch_size': int(theNotebook[4]),\n",
    "}\n",
    "\n",
    "# assert title_param['dataset'] in ['cairo', 'milan', 'kyoto7', 'kyoto8', 'kyoto11'], 'Please correct the dataset name！'\n",
    "# assert title_param['model_name'] in ['WCNN','LSTM'], 'The method is wrong. Please correct it！'\n",
    "# assert title_param['optimizer'] in ['rms', 'adagrad'], 'The optimizer is wrong. Please correct it！'\n",
    "# assert title_param['calculation_unit'] in ['0', '1', '2'], 'Error in calculation unit selection, please correct！'\n",
    "\n",
    "display(title_param)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "dict_cus = {\n",
    "    \"dataset_name\": \"\",\n",
    "    \"maxIters\": \"\",  # 100000\n",
    "    \"seq_len\": \"\",\n",
    "    \"batch_size\": \"\",\n",
    "}\n",
    "\n",
    "dict_cus = general.Merge(dict_cus, title_param)\n",
    "dict_cus"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "calculation_unit = general.getAvailableId()\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = calculation_unit\n",
    "\n",
    "if calculation_unit != \"-1\":\n",
    "    config = tf.ConfigProto()\n",
    "    config.gpu_options.allow_growth = True\n",
    "    session = tf.Session(config=config)\n",
    "\n",
    "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "[origin](#origin)\n",
    "\n",
    "[C](#constrain)\n",
    "\n",
    "[CS_1](#constrain_1)\n",
    "\n",
    "[CS_2](#constrain_2)\n",
    "\n",
    "[CS_3](#constrain_3)\n",
    "\n",
    "[CS_4](#constrain_4)\n",
    "\n",
    "[CS_5](#constrain_5)\n",
    "\n",
    "[statics](#statics)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# <a id='origin'>origin</a>"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "%%time\n",
    "dict_cus[\"distance_int\"] = 9999\n",
    "train_ttn(dict_cus)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "```bash\n",
    "\n",
    "```"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# <a id='C'>C</a>"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "%%time\n",
    "dict_cus[\"distance_int\"] = 999\n",
    "train_ttn(dict_cus)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "```bash\n",
    "\n",
    "```"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# <a id='constrain_1'>CS_1</a>"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "%%time\n",
    "dict_cus[\"distance_int\"] = 1\n",
    "train_ttn(dict_cus)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "```bash\n",
    "\n",
    "```"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# <a id='constrain_2'>CS_2</a>"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "%%time\n",
    "dict_cus[\"distance_int\"] = 2\n",
    "train_ttn(dict_cus)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "```bash\n",
    "\n",
    "```"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# <a id='constrain_3'>CS_3</a>"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "%%time\n",
    "dict_cus[\"distance_int\"] = 3\n",
    "train_ttn(dict_cus)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "```bash\n",
    "\n",
    "```"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# <a id='constrain_4'>CS_4</a>"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "%%time\n",
    "dict_cus[\"distance_int\"] = 4\n",
    "train_ttn(dict_cus)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "```bash\n",
    "\n",
    "```"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# <a id='constrain_5'>CS_5</a>"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "%%time\n",
    "dict_cus[\"distance_int\"] = 5\n",
    "train_ttn(dict_cus)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "```bash\n",
    "\n",
    "```"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# <a id='statics'>statics</a>"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "dict_cus[\"num_classes\"] = 0\n",
    "dict_cus[\"num_train\"] = 0\n",
    "\n",
    "from configuration import configure\n",
    "configure.parameters_dict = general.Merge(configure.parameters_dict, dict_cus)\n",
    "weights_dir = general.getWeightsDir(configure.parameters_dict, 2)\n",
    "general.showResult(weights_dir)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
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