auto encoder.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Model\n",
    "from keras.layers import *\n",
    "\n",
    "def get_model():\n",
    "    image_input = Input(shape=(784,))\n",
    "    encoding_input = Input(shape=(64, ))\n",
    "    encoder = Dense(int(encoding_input.shape[1]), activation=\"relu\")(image_input)\n",
    "    decoder = Dense(784, activation=\"sigmoid\")(encoder)\n",
    "    \n",
    "    autoencoder = Model(image_input, decoder)\n",
    "        \n",
    "    encoder = Model(image_input, encoder)\n",
    "    decoder = Model(encoding_input, autoencoder.layers[-1](encoding_input))\n",
    "    return  autoencoder, encoder, decoder\n",
    "\n",
    "autoencoder, encoder, decoder = get_model()\n",
    "\n",
    "autoencoder.compile(optimizer='adam', \n",
    "                    loss='binary_crossentropy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.datasets import mnist\n",
    "import numpy as np\n",
    "(x_train, _), (x_test, _) = mnist.load_data()\n",
    "x_train = x_train.astype('float32') / 255.\n",
    "x_test = x_test.astype('float32') / 255.\n",
    "x_train = x_train.reshape((len(x_train), np.prod(x_train.shape[1:])))\n",
    "x_test = x_test.reshape((len(x_test), np.prod(x_test.shape[1:])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.cast instead.\n",
      "Train on 60000 samples, validate on 10000 samples\n",
      "Epoch 1/50\n",
      "60000/60000 [==============================] - 6s 93us/step - loss: 0.2447 - val_loss: 0.1608\n",
      "Epoch 2/50\n",
      "60000/60000 [==============================] - 5s 83us/step - loss: 0.1411 - val_loss: 0.1244\n",
      "Epoch 3/50\n",
      "60000/60000 [==============================] - 5s 83us/step - loss: 0.1165 - val_loss: 0.1072\n",
      "Epoch 4/50\n",
      "60000/60000 [==============================] - 5s 84us/step - loss: 0.1030 - val_loss: 0.0969\n",
      "Epoch 5/50\n",
      "60000/60000 [==============================] - 5s 82us/step - loss: 0.0943 - val_loss: 0.0899\n",
      "Epoch 6/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0883 - val_loss: 0.0850\n",
      "Epoch 7/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0840 - val_loss: 0.0814\n",
      "Epoch 8/50\n",
      "60000/60000 [==============================] - 5s 82us/step - loss: 0.0810 - val_loss: 0.0790\n",
      "Epoch 9/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0789 - val_loss: 0.0774\n",
      "Epoch 10/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0775 - val_loss: 0.0761\n",
      "Epoch 11/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0765 - val_loss: 0.0754\n",
      "Epoch 12/50\n",
      "60000/60000 [==============================] - 5s 82us/step - loss: 0.0757 - val_loss: 0.0747\n",
      "Epoch 13/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0752 - val_loss: 0.0744\n",
      "Epoch 14/50\n",
      "60000/60000 [==============================] - 5s 82us/step - loss: 0.0748 - val_loss: 0.0740\n",
      "Epoch 15/50\n",
      "60000/60000 [==============================] - 5s 82us/step - loss: 0.0745 - val_loss: 0.0737\n",
      "Epoch 16/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0743 - val_loss: 0.0735\n",
      "Epoch 17/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0741 - val_loss: 0.0733\n",
      "Epoch 18/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0739 - val_loss: 0.0733\n",
      "Epoch 19/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0738 - val_loss: 0.0732\n",
      "Epoch 20/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0737 - val_loss: 0.0730\n",
      "Epoch 21/50\n",
      "60000/60000 [==============================] - 5s 82us/step - loss: 0.0736 - val_loss: 0.0730\n",
      "Epoch 22/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0735 - val_loss: 0.0729\n",
      "Epoch 23/50\n",
      "60000/60000 [==============================] - 5s 79us/step - loss: 0.0735 - val_loss: 0.0729\n",
      "Epoch 24/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0734 - val_loss: 0.0727\n",
      "Epoch 25/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0733 - val_loss: 0.0727\n",
      "Epoch 26/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0733 - val_loss: 0.0728\n",
      "Epoch 27/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0732 - val_loss: 0.0727\n",
      "Epoch 28/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0732 - val_loss: 0.0726\n",
      "Epoch 29/50\n",
      "60000/60000 [==============================] - 5s 91us/step - loss: 0.0731 - val_loss: 0.0726\n",
      "Epoch 30/50\n",
      "60000/60000 [==============================] - 5s 83us/step - loss: 0.0731 - val_loss: 0.0726\n",
      "Epoch 31/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0731 - val_loss: 0.0725\n",
      "Epoch 32/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0731 - val_loss: 0.0725\n",
      "Epoch 33/50\n",
      "60000/60000 [==============================] - 5s 82us/step - loss: 0.0730 - val_loss: 0.0725\n",
      "Epoch 34/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0730 - val_loss: 0.0725\n",
      "Epoch 35/50\n",
      "60000/60000 [==============================] - 5s 82us/step - loss: 0.0730 - val_loss: 0.0725\n",
      "Epoch 36/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0730 - val_loss: 0.0725\n",
      "Epoch 37/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0729 - val_loss: 0.0725\n",
      "Epoch 38/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0729 - val_loss: 0.0724\n",
      "Epoch 39/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0729 - val_loss: 0.0724\n",
      "Epoch 40/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0729 - val_loss: 0.0724\n",
      "Epoch 41/50\n",
      "60000/60000 [==============================] - 5s 87us/step - loss: 0.0729 - val_loss: 0.0723\n",
      "Epoch 42/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0728 - val_loss: 0.0723\n",
      "Epoch 43/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0728 - val_loss: 0.0723\n",
      "Epoch 44/50\n",
      "60000/60000 [==============================] - 5s 80us/step - loss: 0.0728 - val_loss: 0.0723\n",
      "Epoch 45/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0728 - val_loss: 0.0723\n",
      "Epoch 46/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0728 - val_loss: 0.0723\n",
      "Epoch 47/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0728 - val_loss: 0.0723\n",
      "Epoch 48/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0728 - val_loss: 0.0723\n",
      "Epoch 49/50\n",
      "60000/60000 [==============================] - 5s 79us/step - loss: 0.0728 - val_loss: 0.0722\n",
      "Epoch 50/50\n",
      "60000/60000 [==============================] - 5s 81us/step - loss: 0.0727 - val_loss: 0.0723\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7ff10c462c18>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "autoencoder.fit(x_train, x_train,\n",
    "                epochs=50,\n",
    "                batch_size=256,\n",
    "                shuffle=True,\n",
    "                validation_data=(x_test, x_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "encoded_imgs = encoder.predict(x_test)\n",
    "decoded_imgs = decoder.predict(encoded_imgs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure, axes = plt.subplots(2, 10)\n",
    "for i in range(10):\n",
    "    plt.gray()\n",
    "    axes[0, i].imshow(x_test[i].reshape(28, 28))\n",
    "    axes[1, i].imshow(decoded_imgs[i].reshape(28, 28))"
   ]
  },
  {
   "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}