{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Welcome to Deep Learning with conx!\n",
    "\n",
    "This is a live Jupyter notebook running in the cloud via mybinder.\n",
    "\n",
    "Quick links:\n",
    "\n",
    "* [Conx Notebooks](../notebooks/)\n",
    "* [SIGCSE 2018 Workshop Materials](../notebooks/collections/sigcse-2018/)\n",
    "\n",
    "Or you can start working right here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n",
      "/usr/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n",
      "  return f(*args, **kwds)\n",
      "conx, version 3.5.11\n"
     ]
    }
   ],
   "source": [
    "import conx as cx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "net = cx.Network(\"XOR\", 2, 5, 1, activation=\"sigmoid\")\n",
    "net.compile(error=\"mse\", optimizer=cx.SGD(lr=0.1, momentum=0.9))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "net.dataset.load([\n",
    "    [(0, 0), (1,)],\n",
    "    [(0, 1), (0,)],\n",
    "    [(1, 0), (0,)],\n",
    "    [(1, 1), (1,)],\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "model_id": "9b5de2cdaeba4cc2be73572dc68dd1e9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Dashboard</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Dashboard(children=(Accordion(children=(HBox(children=(VBox(children=(Select(description='Dataset:', index=1, options=('Test', 'Train'), rows=1, value='Train'), FloatSlider(value=1.0, continuous_update=False, description='Zoom', max=3.0, min=0.5), IntText(value=150, description='Horizontal space between banks:', style=DescriptionStyle(description_width='initial')), IntText(value=30, description='Vertical space between layers:', style=DescriptionStyle(description_width='initial')), HBox(children=(Checkbox(value=False, description='Show Targets', style=DescriptionStyle(description_width='initial')), Checkbox(value=False, description='Errors', style=DescriptionStyle(description_width='initial')))), Select(description='Features:', options=('',), rows=1, value=''), IntText(value=3, description='Feature columns:', style=DescriptionStyle(description_width='initial')), FloatText(value=2.0, description='Feature scale:', style=DescriptionStyle(description_width='initial'))), 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style=ButtonStyle()), Button(description='Play', icon='play', layout=Layout(width='100%'), style=ButtonStyle()), Button(icon='refresh', layout=Layout(width='25%'), style=ButtonStyle())), layout=Layout(height='50px', width='100%'))), layout=Layout(width='100%')), HTML(value='<p style=\"text-align:center\"></p>', layout=Layout(justify_content='center', overflow_x='auto', overflow_y='auto', width='95%')), Output()))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "require(['base/js/namespace'], function(Jupyter) {\n",
       "    Jupyter.notebook.kernel.comm_manager.register_target('conx_svg_control', function(comm, msg) {\n",
       "        comm.on_msg(function(msg) {\n",
       "            var data = msg[\"content\"][\"data\"];\n",
       "            var images = document.getElementsByClassName(data[\"class\"]);\n",
       "            for (var i = 0; i < images.length; i++) {\n",
       "                if (data[\"href\"]) {\n",
       "                    images[i].setAttributeNS(null, \"href\", data[\"href\"]);\n",
       "                }\n",
       "                if (data[\"src\"]) {\n",
       "                    images[i].setAttributeNS(null, \"src\", data[\"src\"]);\n",
       "                }\n",
       "            }\n",
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      ],
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "require(['base/js/namespace'], function(Jupyter) {\n",
       "    Jupyter.notebook.kernel.comm_manager.register_target('conx_svg_control', function(comm, msg) {\n",
       "        comm.on_msg(function(msg) {\n",
       "            var data = msg[\"content\"][\"data\"];\n",
       "            var images = document.getElementsByClassName(data[\"class\"]);\n",
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       "                if (data[\"href\"]) {\n",
       "                    images[i].setAttributeNS(null, \"href\", data[\"href\"]);\n",
       "                }\n",
       "                if (data[\"src\"]) {\n",
       "                    images[i].setAttributeNS(null, \"src\", data[\"src\"]);\n",
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       "            }\n",
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       "<IPython.core.display.Javascript object>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "net.dashboard()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg height=\"288pt\" version=\"1.1\" viewBox=\"0 0 720 288\" width=\"720pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       " <defs>\n",
       "  <style type=\"text/css\">\n",
       "*{stroke-linecap:butt;stroke-linejoin:round;}\n",
       "  </style>\n",
       " </defs>\n",
       " <g id=\"figure_1\">\n",
       "  <g id=\"patch_1\">\n",
       "   <path d=\"M 0 288  L 720 288  L 720 0  L 0 0  z \" style=\"fill:#ffffff;\"/>\n",
       "  </g>\n",
       "  <g id=\"axes_1\">\n",
       "   <g id=\"patch_2\">\n",
       "    <path d=\"M 90 252  L 343.636364 252  L 343.636364 34.56  L 90 34.56  z \" style=\"fill:#ffffff;\"/>\n",
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      "========================================================================\n",
      "       |  Training |  Training \n",
      "Epochs |     Error |  Accuracy \n",
      "------ | --------- | --------- \n",
      "# 1231 |   0.00875 |   1.00000 \n"
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\"><title>Layer: hidden (hidden)\n shape = (5,)\n Keras class = Dense\n activation = sigmoid</title></image><text x=\"280.0\" y=\"132.0\" font-family=\"monospace\" font-size=\"12\" text-anchor=\"start\" alignment-baseline=\"central\">hidden</text><line x1=\"175.0\" y1=\"184\" x2=\"175.0\" y2=\"157\" stroke=\"black\" stroke-width=\"2\" marker-end=\"url(#arrow)\"><title>Weights from input to hidden\n hidden/kernel:0 has shape (2, 5)\n hidden/bias:0 has shape (5,)</title></line><rect x=\"124.0\" y=\"184\" width=\"102\" height=\"52\" style=\"fill:none;stroke:black;stroke-width:2\"/><image id=\"XOR_input_6\" class=\"XOR_input\" x=\"125.0\" y=\"185\" height=\"50\" width=\"100\" preserveAspectRatio=\"none\" 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      "model_module_version": "1.1.0",
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       "icon": "backward",
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