{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from ipywidgets import widgets\n",
    "from IPython.display import display\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from ipywidgets import interact\n",
    "import codecs\n",
    "import os\n",
    "import predictor\n",
    "import featureEngine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "htmlExtractor = predictor.HtmlExtractor(\"../model_data/ep069-loss0.072-val_loss0.112-f10.9943.h5\")\n",
    "os.environ[\"CUDA_DEVICE_ORDER\"] = \"PCI_BUS_ID\" \n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f4562469d58c430898b50b3b7d95376f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value='', layout=Layout(height='250px', width='1000px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "71a046126db94da983b3e1fdaad5a2ed",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Text(value='', description='网址')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cb72dcfb83934ed99bdb9711eaf196af",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Button(description='确定', style=ButtonStyle())"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "get 0.5814552307128906\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_1 (InputLayer)         (None, None, 24)          0         \n",
      "_________________________________________________________________\n",
      "masking_1 (Masking)          (None, None, 24)          0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, None, 48)          1200      \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, None, 24)          1176      \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, None, 2)           50        \n",
      "=================================================================\n",
      "Total params: 2,426\n",
      "Trainable params: 2,426\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "[[[  1.00000000e+00   9.40029388e-09]\n",
      "  [  9.99995351e-01   4.60667252e-06]\n",
      "  [  9.99384522e-01   6.15498284e-04]\n",
      "  [  9.85354185e-01   1.46457935e-02]\n",
      "  [  9.94794548e-01   5.20543288e-03]\n",
      "  [  2.24231422e-01   7.75768638e-01]\n",
      "  [  1.00000000e+00   3.39124240e-09]\n",
      "  [  1.00000000e+00   5.50823742e-09]]]\n",
      "- [ 0.22423142  0.77576864]\n",
      "get 1.6057071685791016\n",
      "[[[  1.00000000e+00   1.03884693e-10]\n",
      "  [  9.99999881e-01   1.68546819e-07]\n",
      "  [  1.00000000e+00   5.91857496e-14]\n",
      "  [  9.98932660e-01   1.06734445e-03]\n",
      "  [  9.97052431e-01   2.94757914e-03]\n",
      "  [  9.99667764e-01   3.32222058e-04]\n",
      "  [  9.98742521e-01   1.25746324e-03]\n",
      "  [  9.98303771e-01   1.69626670e-03]\n",
      "  [  9.99998927e-01   1.03774880e-06]\n",
      "  [  1.00000000e+00   6.50773315e-12]]]\n",
      "- [ 0.99705243  0.00294758]\n",
      "get 3.614809036254883\n",
      "[[[  9.99854922e-01   1.45085098e-04]\n",
      "  [  9.99969959e-01   3.00647098e-05]\n",
      "  [  1.00000000e+00   1.19228585e-12]\n",
      "  [  9.99999881e-01   8.68961010e-08]\n",
      "  [  1.00000000e+00   4.31398972e-10]\n",
      "  [  9.99977469e-01   2.24798350e-05]\n",
      "  [  1.00000000e+00   5.53568136e-10]\n",
      "  [  1.00000000e+00   1.44458706e-17]\n",
      "  [  9.99977469e-01   2.24798350e-05]\n",
      "  [  9.99996901e-01   3.14698491e-06]\n",
      "  [  9.99997258e-01   2.69731800e-06]\n",
      "  [  1.00000000e+00   2.15537102e-16]\n",
      "  [  1.00000000e+00   5.46710233e-09]\n",
      "  [  1.00000000e+00   8.95392961e-12]\n",
      "  [  1.00000000e+00   9.46214153e-16]\n",
      "  [  1.00000000e+00   1.08718163e-13]\n",
      "  [  9.99993920e-01   6.03018179e-06]\n",
      "  [  9.89776492e-01   1.02235582e-02]\n",
      "  [  7.15422988e-01   2.84577042e-01]]]\n",
      "- [ 0.71542299  0.28457704]\n"
     ]
    }
   ],
   "source": [
    "textarea = widgets.HTML(value=\"\", layout=widgets.Layout(width='1000px', height='250px'))\n",
    "display(textarea)\n",
    "\n",
    "\n",
    "url_text = widgets.Text(value='',disabled=False,description=\"网址\")\n",
    "display(url_text)\n",
    "\n",
    "def click_submit(b):\n",
    "    url = url_text.value\n",
    "    x,list_inner = featureEngine.getInput_byJS(url)\n",
    "    max_ = htmlExtractor.predict(x)\n",
    "    textarea.value = \"<div>\"+list_inner[max_]+\"</div>\"\n",
    "    \n",
    "submit = widgets.Button(description=\"确定\")\n",
    "submit.on_click(click_submit)\n",
    "display(submit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}