dlnd_face_generation.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />

<title>dlnd_face_generation</title>

<script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>

<script>
(function() {
  function addWidgetsRenderer() {
    var mimeElement = document.querySelector('script[type="application/vnd.jupyter.widget-view+json"]');
    var scriptElement = document.createElement('script');
    var widgetRendererSrc = '@jupyter-widgets/html-manager@*/dist/embed-amd.js';
    var widgetState;

    // Fallback for older version:
    try {
      widgetState = mimeElement && JSON.parse(mimeElement.innerHTML);

      if (widgetState && (widgetState.version_major < 2 || !widgetState.version_major)) {
        widgetRendererSrc = 'jupyter-js-widgets@*/dist/embed.js';
      }
    } catch(e) {}

    scriptElement.src = widgetRendererSrc;
    document.body.appendChild(scriptElement);
  }

  document.addEventListener('DOMContentLoaded', addWidgetsRenderer);
}());
</script>

<style type="text/css">
    /*!
*
* Twitter Bootstrap
*
*/
/*!
 * Bootstrap v3.3.7 (http://getbootstrap.com)
 * Copyright 2011-2016 Twitter, Inc.
 * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
 */
/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
  font-family: sans-serif;
  -ms-text-size-adjust: 100%;
  -webkit-text-size-adjust: 100%;
}
body {
  margin: 0;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
hgroup,
main,
menu,
nav,
section,
summary {
  display: block;
}
audio,
canvas,
progress,
video {
  display: inline-block;
  vertical-align: baseline;
}
audio:not([controls]) {
  display: none;
  height: 0;
}
[hidden],
template {
  display: none;
}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
  font-style: italic;
}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
  background: #ff0;
  color: #000;
}
small {
  font-size: 80%;
}
sub,
sup {
  font-size: 75%;
  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
  top: -0.5em;
}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
  overflow: hidden;
}
figure {
  margin: 1em 40px;
}
hr {
  box-sizing: content-box;
  height: 0;
}
pre {
  overflow: auto;
}
code,
kbd,
pre,
samp {
  font-family: monospace, monospace;
  font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
  color: inherit;
  font: inherit;
  margin: 0;
}
button {
  overflow: visible;
}
button,
select {
  text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
  -webkit-appearance: button;
  cursor: pointer;
}
button[disabled],
html input[disabled] {
  cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
  border: 0;
  padding: 0;
}
input {
  line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
  box-sizing: border-box;
  padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: textfield;
  box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
  -webkit-appearance: none;
}
fieldset {
  border: 1px solid #c0c0c0;
  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
}
legend {
  border: 0;
  padding: 0;
}
textarea {
  overflow: auto;
}
optgroup {
  font-weight: bold;
}
table {
  border-collapse: collapse;
  border-spacing: 0;
}
td,
th {
  padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
  *,
  *:before,
  *:after {
    background: transparent !important;
    box-shadow: none !important;
    text-shadow: none !important;
  }
  a,
  a:visited {
    text-decoration: underline;
  }
  a[href]:after {
    content: " (" attr(href) ")";
  }
  abbr[title]:after {
    content: " (" attr(title) ")";
  }
  a[href^="#"]:after,
  a[href^="javascript:"]:after {
    content: "";
  }
  pre,
  blockquote {
    border: 1px solid #999;
    page-break-inside: avoid;
  }
  thead {
    display: table-header-group;
  }
  tr,
  img {
    page-break-inside: avoid;
  }
  img {
    max-width: 100% !important;
  }
  p,
  h2,
  h3 {
    orphans: 3;
    widows: 3;
  }
  h2,
  h3 {
    page-break-after: avoid;
  }
  .navbar {
    display: none;
  }
  .btn > .caret,
  .dropup > .btn > .caret {
    border-top-color: #000 !important;
  }
  .label {
    border: 1px solid #000;
  }
  .table {
    border-collapse: collapse !important;
  }
  .table td,
  .table th {
    background-color: #fff !important;
  }
  .table-bordered th,
  .table-bordered td {
    border: 1px solid #ddd !important;
  }
}
@font-face {
  font-family: 'Glyphicons Halflings';
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
}
.glyphicon {
  position: relative;
  top: 1px;
  display: inline-block;
  font-family: 'Glyphicons Halflings';
  font-style: normal;
  font-weight: normal;
  line-height: 1;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
.glyphicon-asterisk:before {
  content: "\002a";
}
.glyphicon-plus:before {
  content: "\002b";
}
.glyphicon-euro:before,
.glyphicon-eur:before {
  content: "\20ac";
}
.glyphicon-minus:before {
  content: "\2212";
}
.glyphicon-cloud:before {
  content: "\2601";
}
.glyphicon-envelope:before {
  content: "\2709";
}
.glyphicon-pencil:before {
  content: "\270f";
}
.glyphicon-glass:before {
  content: "\e001";
}
.glyphicon-music:before {
  content: "\e002";
}
.glyphicon-search:before {
  content: "\e003";
}
.glyphicon-heart:before {
  content: "\e005";
}
.glyphicon-star:before {
  content: "\e006";
}
.glyphicon-star-empty:before {
  content: "\e007";
}
.glyphicon-user:before {
  content: "\e008";
}
.glyphicon-film:before {
  content: "\e009";
}
.glyphicon-th-large:before {
  content: "\e010";
}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
.glyphicon-remove:before {
  content: "\e014";
}
.glyphicon-zoom-in:before {
  content: "\e015";
}
.glyphicon-zoom-out:before {
  content: "\e016";
}
.glyphicon-off:before {
  content: "\e017";
}
.glyphicon-signal:before {
  content: "\e018";
}
.glyphicon-cog:before {
  content: "\e019";
}
.glyphicon-trash:before {
  content: "\e020";
}
.glyphicon-home:before {
  content: "\e021";
}
.glyphicon-file:before {
  content: "\e022";
}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
  content: "\e025";
}
.glyphicon-download:before {
  content: "\e026";
}
.glyphicon-upload:before {
  content: "\e027";
}
.glyphicon-inbox:before {
  content: "\e028";
}
.glyphicon-play-circle:before {
  content: "\e029";
}
.glyphicon-repeat:before {
  content: "\e030";
}
.glyphicon-refresh:before {
  content: "\e031";
}
.glyphicon-list-alt:before {
  content: "\e032";
}
.glyphicon-lock:before {
  content: "\e033";
}
.glyphicon-flag:before {
  content: "\e034";
}
.glyphicon-headphones:before {
  content: "\e035";
}
.glyphicon-volume-off:before {
  content: "\e036";
}
.glyphicon-volume-down:before {
  content: "\e037";
}
.glyphicon-volume-up:before {
  content: "\e038";
}
.glyphicon-qrcode:before {
  content: "\e039";
}
.glyphicon-barcode:before {
  content: "\e040";
}
.glyphicon-tag:before {
  content: "\e041";
}
.glyphicon-tags:before {
  content: "\e042";
}
.glyphicon-book:before {
  content: "\e043";
}
.glyphicon-bookmark:before {
  content: "\e044";
}
.glyphicon-print:before {
  content: "\e045";
}
.glyphicon-camera:before {
  content: "\e046";
}
.glyphicon-font:before {
  content: "\e047";
}
.glyphicon-bold:before {
  content: "\e048";
}
.glyphicon-italic:before {
  content: "\e049";
}
.glyphicon-text-height:before {
  content: "\e050";
}
.glyphicon-text-width:before {
  content: "\e051";
}
.glyphicon-align-left:before {
  content: "\e052";
}
.glyphicon-align-center:before {
  content: "\e053";
}
.glyphicon-align-right:before {
  content: "\e054";
}
.glyphicon-align-justify:before {
  content: "\e055";
}
.glyphicon-list:before {
  content: "\e056";
}
.glyphicon-indent-left:before {
  content: "\e057";
}
.glyphicon-indent-right:before {
  content: "\e058";
}
.glyphicon-facetime-video:before {
  content: "\e059";
}
.glyphicon-picture:before {
  content: "\e060";
}
.glyphicon-map-marker:before {
  content: "\e062";
}
.glyphicon-adjust:before {
  content: "\e063";
}
.glyphicon-tint:before {
  content: "\e064";
}
.glyphicon-edit:before {
  content: "\e065";
}
.glyphicon-share:before {
  content: "\e066";
}
.glyphicon-check:before {
  content: "\e067";
}
.glyphicon-move:before {
  content: "\e068";
}
.glyphicon-step-backward:before {
  content: "\e069";
}
.glyphicon-fast-backward:before {
  content: "\e070";
}
.glyphicon-backward:before {
  content: "\e071";
}
.glyphicon-play:before {
  content: "\e072";
}
.glyphicon-pause:before {
  content: "\e073";
}
.glyphicon-stop:before {
  content: "\e074";
}
.glyphicon-forward:before {
  content: "\e075";
}
.glyphicon-fast-forward:before {
  content: "\e076";
}
.glyphicon-step-forward:before {
  content: "\e077";
}
.glyphicon-eject:before {
  content: "\e078";
}
.glyphicon-chevron-left:before {
  content: "\e079";
}
.glyphicon-chevron-right:before {
  content: "\e080";
}
.glyphicon-plus-sign:before {
  content: "\e081";
}
.glyphicon-minus-sign:before {
  content: "\e082";
}
.glyphicon-remove-sign:before {
  content: "\e083";
}
.glyphicon-ok-sign:before {
  content: "\e084";
}
.glyphicon-question-sign:before {
  content: "\e085";
}
.glyphicon-info-sign:before {
  content: "\e086";
}
.glyphicon-screenshot:before {
  content: "\e087";
}
.glyphicon-remove-circle:before {
  content: "\e088";
}
.glyphicon-ok-circle:before {
  content: "\e089";
}
.glyphicon-ban-circle:before {
  content: "\e090";
}
.glyphicon-arrow-left:before {
  content: "\e091";
}
.glyphicon-arrow-right:before {
  content: "\e092";
}
.glyphicon-arrow-up:before {
  content: "\e093";
}
.glyphicon-arrow-down:before {
  content: "\e094";
}
.glyphicon-share-alt:before {
  content: "\e095";
}
.glyphicon-resize-full:before {
  content: "\e096";
}
.glyphicon-resize-small:before {
  content: "\e097";
}
.glyphicon-exclamation-sign:before {
  content: "\e101";
}
.glyphicon-gift:before {
  content: "\e102";
}
.glyphicon-leaf:before {
  content: "\e103";
}
.glyphicon-fire:before {
  content: "\e104";
}
.glyphicon-eye-open:before {
  content: "\e105";
}
.glyphicon-eye-close:before {
  content: "\e106";
}
.glyphicon-warning-sign:before {
  content: "\e107";
}
.glyphicon-plane:before {
  content: "\e108";
}
.glyphicon-calendar:before {
  content: "\e109";
}
.glyphicon-random:before {
  content: "\e110";
}
.glyphicon-comment:before {
  content: "\e111";
}
.glyphicon-magnet:before {
  content: "\e112";
}
.glyphicon-chevron-up:before {
  content: "\e113";
}
.glyphicon-chevron-down:before {
  content: "\e114";
}
.glyphicon-retweet:before {
  content: "\e115";
}
.glyphicon-shopping-cart:before {
  content: "\e116";
}
.glyphicon-folder-close:before {
  content: "\e117";
}
.glyphicon-folder-open:before {
  content: "\e118";
}
.glyphicon-resize-vertical:before {
  content: "\e119";
}
.glyphicon-resize-horizontal:before {
  content: "\e120";
}
.glyphicon-hdd:before {
  content: "\e121";
}
.glyphicon-bullhorn:before {
  content: "\e122";
}
.glyphicon-bell:before {
  content: "\e123";
}
.glyphicon-certificate:before {
  content: "\e124";
}
.glyphicon-thumbs-up:before {
  content: "\e125";
}
.glyphicon-thumbs-down:before {
  content: "\e126";
}
.glyphicon-hand-right:before {
  content: "\e127";
}
.glyphicon-hand-left:before {
  content: "\e128";
}
.glyphicon-hand-up:before {
  content: "\e129";
}
.glyphicon-hand-down:before {
  content: "\e130";
}
.glyphicon-circle-arrow-right:before {
  content: "\e131";
}
.glyphicon-circle-arrow-left:before {
  content: "\e132";
}
.glyphicon-circle-arrow-up:before {
  content: "\e133";
}
.glyphicon-circle-arrow-down:before {
  content: "\e134";
}
.glyphicon-globe:before {
  content: "\e135";
}
.glyphicon-wrench:before {
  content: "\e136";
}
.glyphicon-tasks:before {
  content: "\e137";
}
.glyphicon-filter:before {
  content: "\e138";
}
.glyphicon-briefcase:before {
  content: "\e139";
}
.glyphicon-fullscreen:before {
  content: "\e140";
}
.glyphicon-dashboard:before {
  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
  content: "\e143";
}
.glyphicon-link:before {
  content: "\e144";
}
.glyphicon-phone:before {
  content: "\e145";
}
.glyphicon-pushpin:before {
  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
  content: "\e149";
}
.glyphicon-sort:before {
  content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
  content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
  content: "\e154";
}
.glyphicon-sort-by-attributes:before {
  content: "\e155";
}
.glyphicon-sort-by-attributes-alt:before {
  content: "\e156";
}
.glyphicon-unchecked:before {
  content: "\e157";
}
.glyphicon-expand:before {
  content: "\e158";
}
.glyphicon-collapse-down:before {
  content: "\e159";
}
.glyphicon-collapse-up:before {
  content: "\e160";
}
.glyphicon-log-in:before {
  content: "\e161";
}
.glyphicon-flash:before {
  content: "\e162";
}
.glyphicon-log-out:before {
  content: "\e163";
}
.glyphicon-new-window:before {
  content: "\e164";
}
.glyphicon-record:before {
  content: "\e165";
}
.glyphicon-save:before {
  content: "\e166";
}
.glyphicon-open:before {
  content: "\e167";
}
.glyphicon-saved:before {
  content: "\e168";
}
.glyphicon-import:before {
  content: "\e169";
}
.glyphicon-export:before {
  content: "\e170";
}
.glyphicon-send:before {
  content: "\e171";
}
.glyphicon-floppy-disk:before {
  content: "\e172";
}
.glyphicon-floppy-saved:before {
  content: "\e173";
}
.glyphicon-floppy-remove:before {
  content: "\e174";
}
.glyphicon-floppy-save:before {
  content: "\e175";
}
.glyphicon-floppy-open:before {
  content: "\e176";
}
.glyphicon-credit-card:before {
  content: "\e177";
}
.glyphicon-transfer:before {
  content: "\e178";
}
.glyphicon-cutlery:before {
  content: "\e179";
}
.glyphicon-header:before {
  content: "\e180";
}
.glyphicon-compressed:before {
  content: "\e181";
}
.glyphicon-earphone:before {
  content: "\e182";
}
.glyphicon-phone-alt:before {
  content: "\e183";
}
.glyphicon-tower:before {
  content: "\e184";
}
.glyphicon-stats:before {
  content: "\e185";
}
.glyphicon-sd-video:before {
  content: "\e186";
}
.glyphicon-hd-video:before {
  content: "\e187";
}
.glyphicon-subtitles:before {
  content: "\e188";
}
.glyphicon-sound-stereo:before {
  content: "\e189";
}
.glyphicon-sound-dolby:before {
  content: "\e190";
}
.glyphicon-sound-5-1:before {
  content: "\e191";
}
.glyphicon-sound-6-1:before {
  content: "\e192";
}
.glyphicon-sound-7-1:before {
  content: "\e193";
}
.glyphicon-copyright-mark:before {
  content: "\e194";
}
.glyphicon-registration-mark:before {
  content: "\e195";
}
.glyphicon-cloud-download:before {
  content: "\e197";
}
.glyphicon-cloud-upload:before {
  content: "\e198";
}
.glyphicon-tree-conifer:before {
  content: "\e199";
}
.glyphicon-tree-deciduous:before {
  content: "\e200";
}
.glyphicon-cd:before {
  content: "\e201";
}
.glyphicon-save-file:before {
  content: "\e202";
}
.glyphicon-open-file:before {
  content: "\e203";
}
.glyphicon-level-up:before {
  content: "\e204";
}
.glyphicon-copy:before {
  content: "\e205";
}
.glyphicon-paste:before {
  content: "\e206";
}
.glyphicon-alert:before {
  content: "\e209";
}
.glyphicon-equalizer:before {
  content: "\e210";
}
.glyphicon-king:before {
  content: "\e211";
}
.glyphicon-queen:before {
  content: "\e212";
}
.glyphicon-pawn:before {
  content: "\e213";
}
.glyphicon-bishop:before {
  content: "\e214";
}
.glyphicon-knight:before {
  content: "\e215";
}
.glyphicon-baby-formula:before {
  content: "\e216";
}
.glyphicon-tent:before {
  content: "\26fa";
}
.glyphicon-blackboard:before {
  content: "\e218";
}
.glyphicon-bed:before {
  content: "\e219";
}
.glyphicon-apple:before {
  content: "\f8ff";
}
.glyphicon-erase:before {
  content: "\e221";
}
.glyphicon-hourglass:before {
  content: "\231b";
}
.glyphicon-lamp:before {
  content: "\e223";
}
.glyphicon-duplicate:before {
  content: "\e224";
}
.glyphicon-piggy-bank:before {
  content: "\e225";
}
.glyphicon-scissors:before {
  content: "\e226";
}
.glyphicon-bitcoin:before {
  content: "\e227";
}
.glyphicon-btc:before {
  content: "\e227";
}
.glyphicon-xbt:before {
  content: "\e227";
}
.glyphicon-yen:before {
  content: "\00a5";
}
.glyphicon-jpy:before {
  content: "\00a5";
}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
  content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
  content: "\e232";
}
.glyphicon-education:before {
  content: "\e233";
}
.glyphicon-option-horizontal:before {
  content: "\e234";
}
.glyphicon-option-vertical:before {
  content: "\e235";
}
.glyphicon-menu-hamburger:before {
  content: "\e236";
}
.glyphicon-modal-window:before {
  content: "\e237";
}
.glyphicon-oil:before {
  content: "\e238";
}
.glyphicon-grain:before {
  content: "\e239";
}
.glyphicon-sunglasses:before {
  content: "\e240";
}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
  content: "\e243";
}
.glyphicon-object-align-top:before {
  content: "\e244";
}
.glyphicon-object-align-bottom:before {
  content: "\e245";
}
.glyphicon-object-align-horizontal:before {
  content: "\e246";
}
.glyphicon-object-align-left:before {
  content: "\e247";
}
.glyphicon-object-align-vertical:before {
  content: "\e248";
}
.glyphicon-object-align-right:before {
  content: "\e249";
}
.glyphicon-triangle-right:before {
  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
  height: 100%;
  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
    </style>
<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
.highlight .vm { color: #19177C } /* Name.Variable.Magic */
.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
    </style>
<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

    </style>
<style type="text/css">
    body[data-notebook-name] > #header #header-container:not(.show-panel), /* body has data-notebook-name attribute when 
a notebook is open. this rule won't be applied when the notebook is not open (in 404 view for example) */
body[data-notebook-name] #menubar-container #maintoolbar:not(.show-panel),
body[data-notebook-name] #menubar-container ul.navbar-nav:not(.show-panel) {
  display: none;
}

#menubar.only-panel #menus.navbar-default {
    background: #fff;
    border-color: #fff;
}

.toolbar.with-statusbar{
    margin-top: 3px;
    margin-bottom: 0;
}

    </style>


<style type="text/css">
/* Overrides of notebook CSS for static HTML export */
body {
  overflow: visible;
  padding: 8px;
}

div#notebook {
  overflow: visible;
  border-top: none;
}@media print {
  div.cell {
    display: block;
    page-break-inside: avoid;
  } 
  div.output_wrapper { 
    display: block;
    page-break-inside: avoid; 
  }
  div.output { 
    display: block;
    page-break-inside: avoid; 
  }
}
</style>

<!-- Custom stylesheet, it must be in the same directory as the html file -->
<link rel="stylesheet" href="custom.css">

<!-- Loading mathjax macro -->
<!-- Load mathjax -->
    <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_HTML"></script>
    <!-- MathJax configuration -->
    <script type="text/x-mathjax-config">
    MathJax.Hub.Config({
        tex2jax: {
            inlineMath: [ ['$','$'], ["\\(","\\)"] ],
            displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
            processEscapes: true,
            processEnvironments: true
        },
        // Center justify equations in code and markdown cells. Elsewhere
        // we use CSS to left justify single line equations in code cells.
        displayAlign: 'center',
        "HTML-CSS": {
            styles: {'.MathJax_Display': {"margin": 0}},
            linebreaks: { automatic: true }
        }
    });
    </script>
    <!-- End of mathjax configuration --></head>
<body>
  <div tabindex="-1" id="notebook" class="border-box-sizing">
    <div class="container" id="notebook-container">

<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="Face-Generation">Face Generation<a class="anchor-link" href="#Face-Generation">&#182;</a></h1><p>In this project, you'll define and train a DCGAN on a dataset of faces. Your goal is to get a generator network to generate <em>new</em> images of faces that look as realistic as possible!</p>
<p>The project will be broken down into a series of tasks from <strong>loading in data to defining and training adversarial networks</strong>. At the end of the notebook, you'll be able to visualize the results of your trained Generator to see how it performs; your generated samples should look like fairly realistic faces with small amounts of noise.</p>
<h3 id="Get-the-Data">Get the Data<a class="anchor-link" href="#Get-the-Data">&#182;</a></h3><p>You'll be using the <a href="http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html">CelebFaces Attributes Dataset (CelebA)</a> to train your adversarial networks.</p>
<p>This dataset is more complex than the number datasets (like MNIST or SVHN) you've been working with, and so, you should prepare to define deeper networks and train them for a longer time to get good results. It is suggested that you utilize a GPU for training.</p>
<h3 id="Pre-processed-Data">Pre-processed Data<a class="anchor-link" href="#Pre-processed-Data">&#182;</a></h3><p>Since the project's main focus is on building the GANs, we've done <em>some</em> of the pre-processing for you. Each of the CelebA images has been cropped to remove parts of the image that don't include a face, then resized down to 64x64x3 NumPy images. Some sample data is show below.</p>
<p><img src='assets/processed_face_data.png' width=60% /></p>
<blockquote><p>If you are working locally, you can download this data <a href="https://s3.amazonaws.com/video.udacity-data.com/topher/2018/November/5be7eb6f_processed-celeba-small/processed-celeba-small.zip">by clicking here</a></p>
</blockquote>
<p>This is a zip file that you'll need to extract in the home directory of this notebook for further loading and processing. After extracting the data, you should be left with a directory of data <code>processed_celeba_small/</code></p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[1]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># can comment out after executing</span>
<span class="c1">#!unzip processed_celeba_small.zip</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[2]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ls</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre><span class="ansi-blue-intense-fg ansi-bold">assets</span>/                     problem_unittests.py        <span class="ansi-blue-intense-fg ansi-bold">__pycache__</span>/
dlnd_face_generation.ipynb  <span class="ansi-blue-intense-fg ansi-bold">processed_celeba_small</span>/
<span class="ansi-blue-intense-fg ansi-bold">__MACOSX</span>/                   processed_celeba_small.zip
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[3]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_dir</span> <span class="o">=</span> <span class="s1">&#39;processed_celeba_small/&#39;</span>

<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">pickle</span> <span class="k">as</span> <span class="nn">pkl</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>
<span class="c1">#import helper</span>

<span class="o">%</span><span class="k">matplotlib</span> inline
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Visualize-the-CelebA-Data">Visualize the CelebA Data<a class="anchor-link" href="#Visualize-the-CelebA-Data">&#182;</a></h2><p>The <a href="http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html">CelebA</a> dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations, you'll only need the images. Note that these are color images with <a href="https://en.wikipedia.org/wiki/Channel_(digital_image">3 color channels (RGB)</a>#RGB_Images) each.</p>
<h3 id="Pre-process-and-Load-the-Data">Pre-process and Load the Data<a class="anchor-link" href="#Pre-process-and-Load-the-Data">&#182;</a></h3><p>Since the project's main focus is on building the GANs, we've done <em>some</em> of the pre-processing for you. Each of the CelebA images has been cropped to remove parts of the image that don't include a face, then resized down to 64x64x3 NumPy images. This <em>pre-processed</em> dataset is a smaller subset of the very large CelebA data.</p>
<blockquote><p>There are a few other steps that you'll need to <strong>transform</strong> this data and create a <strong>DataLoader</strong>.</p>
</blockquote>
<h4 id="Exercise:-Complete-the-following-get_dataloader-function,-such-that-it-satisfies-these-requirements:">Exercise: Complete the following <code>get_dataloader</code> function, such that it satisfies these requirements:<a class="anchor-link" href="#Exercise:-Complete-the-following-get_dataloader-function,-such-that-it-satisfies-these-requirements:">&#182;</a></h4><ul>
<li>Your images should be square, Tensor images of size <code>image_size x image_size</code> in the x and y dimension.</li>
<li>Your function should return a DataLoader that shuffles and batches these Tensor images.</li>
</ul>
<h4 id="ImageFolder">ImageFolder<a class="anchor-link" href="#ImageFolder">&#182;</a></h4><p>To create a dataset given a directory of images, it's recommended that you use PyTorch's <a href="https://pytorch.org/docs/stable/torchvision/datasets.html#imagefolder">ImageFolder</a> wrapper, with a root directory <code>processed_celeba_small/</code> and data transformation passed in.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[4]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># necessary imports</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">datasets</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">transforms</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[5]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">image_size</span><span class="p">,</span> <span class="n">data_dir</span><span class="o">=</span><span class="s1">&#39;processed_celeba_small/&#39;</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Batch the neural network data using DataLoader</span>
<span class="sd">    :param batch_size: The size of each batch; the number of images in a batch</span>
<span class="sd">    :param img_size: The square size of the image data (x, y)</span>
<span class="sd">    :param data_dir: Directory where image data is located</span>
<span class="sd">    :return: DataLoader with batched data</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># TODO: Implement function and return a dataloader</span>
    <span class="n">transform</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span>
        <span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span>
        <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">()</span>
    <span class="p">])</span>
    
    <span class="n">data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">data_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">transform</span><span class="p">)</span>  
    <span class="n">data_loader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">data_loader</span>
    
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Create-a-DataLoader">Create a DataLoader<a class="anchor-link" href="#Create-a-DataLoader">&#182;</a></h2><h4 id="Exercise:-Create-a-DataLoader-celeba_train_loader-with-appropriate-hyperparameters.">Exercise: Create a DataLoader <code>celeba_train_loader</code> with appropriate hyperparameters.<a class="anchor-link" href="#Exercise:-Create-a-DataLoader-celeba_train_loader-with-appropriate-hyperparameters.">&#182;</a></h4><p>Call the above function and create a dataloader to view images.</p>
<ul>
<li>You can decide on any reasonable <code>batch_size</code> parameter</li>
<li>Your <code>image_size</code> <strong>must be</strong> <code>32</code>. Resizing the data to a smaller size will make for faster training, while still creating convincing images of faces!</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[6]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define function hyperparameters</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="mi">128</span>
<span class="n">img_size</span> <span class="o">=</span> <span class="mi">32</span>
<span class="n">image_channels</span> <span class="o">=</span> <span class="mi">3</span>

<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># Call your function and get a dataloader</span>
<span class="n">celeba_train_loader</span> <span class="o">=</span> <span class="n">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">img_size</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Next, you can view some images! You should seen square images of somewhat-centered faces.</p>
<p>Note: You'll need to convert the Tensor images into a NumPy type and transpose the dimensions to correctly display an image, suggested <code>imshow</code> code is below, but it may not be perfect.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[7]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper display function</span>
<span class="k">def</span> <span class="nf">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">):</span>
    <span class="n">npimg</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">npimg</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">)))</span>

<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># obtain one batch of training images</span>
<span class="n">dataiter</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">celeba_train_loader</span><span class="p">)</span>
<span class="n">images</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">dataiter</span><span class="o">.</span><span class="n">next</span><span class="p">()</span> <span class="c1"># _ for no labels</span>

<span class="c1"># plot the images in the batch, along with the corresponding labels</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="n">plot_size</span><span class="o">=</span><span class="mi">20</span>
<span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">plot_size</span><span class="p">):</span>
    <span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="n">plot_size</span><span class="o">/</span><span class="mi">2</span><span class="p">,</span> <span class="n">idx</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">xticks</span><span class="o">=</span><span class="p">[],</span> <span class="n">yticks</span><span class="o">=</span><span class="p">[])</span>
    <span class="n">imshow</span><span class="p">(</span><span class="n">images</span><span class="p">[</span><span class="n">idx</span><span class="p">])</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h4 id="Exercise:-Pre-process-your-image-data-and-scale-it-to-a-pixel-range-of--1-to-1">Exercise: Pre-process your image data and scale it to a pixel range of -1 to 1<a class="anchor-link" href="#Exercise:-Pre-process-your-image-data-and-scale-it-to-a-pixel-range-of--1-to-1">&#182;</a></h4><p>You need to do a bit of pre-processing; you know that the output of a <code>tanh</code> activated generator will contain pixel values in a range from -1 to 1, and so, we need to rescale our training images to a range of -1 to 1. (Right now, they are in a range from 0-1.)</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[8]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Complete the scale function</span>
<span class="k">def</span> <span class="nf">scale</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">feature_range</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)):</span>
    <span class="sd">&#39;&#39;&#39; Scale takes in an image x and returns that image, scaled</span>
<span class="sd">       with a feature_range of pixel values from -1 to 1. </span>
<span class="sd">       This function assumes that the input x is already scaled from 0-1.&#39;&#39;&#39;</span>
    <span class="c1"># assume x is scaled to (0, 1)</span>
    <span class="c1"># scale to feature_range and return scaled x</span>
    
    <span class="n">minimum</span><span class="p">,</span> <span class="n">maximum</span> <span class="o">=</span> <span class="n">feature_range</span>
    <span class="k">return</span> <span class="n">x</span><span class="o">*</span><span class="p">(</span><span class="n">maximum</span> <span class="o">-</span> <span class="n">minimum</span><span class="p">)</span> <span class="o">+</span> <span class="n">minimum</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[9]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># check scaled range</span>
<span class="c1"># should be close to -1 to 1</span>
<span class="n">img</span> <span class="o">=</span> <span class="n">images</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="n">scaled_img</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Min: &#39;</span><span class="p">,</span> <span class="n">scaled_img</span><span class="o">.</span><span class="n">min</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Max: &#39;</span><span class="p">,</span> <span class="n">scaled_img</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Min:  tensor(-0.9451)
Max:  tensor(0.9059)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<hr>
<h1 id="Define-the-Model">Define the Model<a class="anchor-link" href="#Define-the-Model">&#182;</a></h1><p>A GAN is comprised of two adversarial networks, a discriminator and a generator.</p>
<h2 id="Discriminator">Discriminator<a class="anchor-link" href="#Discriminator">&#182;</a></h2><p>Your first task will be to define the discriminator. This is a convolutional classifier like you've built before, only without any maxpooling layers. To deal with this complex data, it's suggested you use a deep network with <strong>normalization</strong>. You are also allowed to create any helper functions that may be useful.</p>
<h4 id="Exercise:-Complete-the-Discriminator-class">Exercise: Complete the Discriminator class<a class="anchor-link" href="#Exercise:-Complete-the-Discriminator-class">&#182;</a></h4><ul>
<li>The inputs to the discriminator are 32x32x3 tensor images</li>
<li>The output should be a single value that will indicate whether a given image is real or fake</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[10]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="kn">import</span> <span class="nn">torch.nn.functional</span> <span class="k">as</span> <span class="nn">F</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[11]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper function for convolution layers</span>
<span class="k">def</span> <span class="nf">conv</span><span class="p">(</span><span class="n">in_dims</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">,</span> <span class="n">kernel</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="c1"># Creates a convolutional layer, with optional normalization.</span>
    
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">conv_layer</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">(</span><span class="n">in_dims</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">,</span> 
                           <span class="n">kernel</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="p">(</span><span class="ow">not</span> <span class="n">norm</span><span class="p">))</span>
    
    <span class="c1"># append conv layer</span>
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">conv_layer</span><span class="p">)</span>

    <span class="k">if</span> <span class="n">norm</span><span class="p">:</span>
        <span class="c1"># append normalization layer</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_dims</span><span class="p">))</span>
     
    <span class="c1"># using Sequential container</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[12]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Discriminator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Discriminator Module</span>
<span class="sd">        :param conv_dim: The depth of the first convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Discriminator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>

        <span class="c1"># complete init function</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>  
        
        <span class="c1"># 32x32 input</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv1</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">image_channels</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> 
        
        <span class="c1"># 16x16 out</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv2</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        
        <span class="c1"># 8x8 out</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv3</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        
        <span class="c1"># 4x4 out, fully-connected layer         </span>
        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: Discriminator logits; the output of the neural network</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># define feedforward behavior</span>
        
        <span class="c1"># all hidden layers + leaky relu activation</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv1</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv2</span><span class="p">(</span><span class="n">out</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv3</span><span class="p">(</span><span class="n">out</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        
        <span class="c1"># flatten</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>
        
        <span class="c1"># final output layer</span>
        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>        
        <span class="k">return</span> <span class="n">out</span>


<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_discriminator</span><span class="p">(</span><span class="n">Discriminator</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Tests Passed
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Generator">Generator<a class="anchor-link" href="#Generator">&#182;</a></h2><p>The generator should upsample an input and generate a <em>new</em> image of the same size as our training data <code>32x32x3</code>. This should be mostly transpose convolutional layers with normalization applied to the outputs.</p>
<h4 id="Exercise:-Complete-the-Generator-class">Exercise: Complete the Generator class<a class="anchor-link" href="#Exercise:-Complete-the-Generator-class">&#182;</a></h4><ul>
<li>The inputs to the generator are vectors of some length <code>z_size</code></li>
<li>The output should be a image of shape <code>32x32x3</code></li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[13]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper function for deconvolution layers</span>
<span class="k">def</span> <span class="nf">deconv</span><span class="p">(</span><span class="n">in_dims</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">,</span> <span class="n">kernel</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="c1"># create a deconvolutional layer, with optional normalization.</span>
    
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">deconv_layer</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">ConvTranspose2d</span><span class="p">(</span><span class="n">in_dims</span><span class="p">,</span> <span class="n">out_dims</span><span class="p">,</span> 
                                              <span class="n">kernel</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="p">(</span><span class="ow">not</span> <span class="n">norm</span><span class="p">))</span>
    <span class="c1"># append deconvolutional layer</span>
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">deconv_layer</span><span class="p">)</span>
    
    <span class="k">if</span> <span class="n">norm</span><span class="p">:</span>
        <span class="c1"># append normalization layer</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_dims</span><span class="p">))</span>
        
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[14]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Generator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
    
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Generator Module</span>
<span class="sd">        :param z_size: The length of the input latent vector, z</span>
<span class="sd">        :param conv_dim: The depth of the inputs to the *last* transpose convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Generator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>

        <span class="c1"># complete init function</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>
        
        <span class="c1"># fully-connected layer</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>

        <span class="c1"># deconv layers</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv2</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv3</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: A 32x32x3 Tensor image as output</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># define feedforward behavior</span>
        
        <span class="c1"># fully-connected + reshape </span>
        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span> 
        
        <span class="c1"># hidden deconv layers + relu</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv2</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        
        <span class="c1"># last layer + tanh activation</span>
        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">t_conv3</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
        
        <span class="k">return</span> <span class="n">out</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_generator</span><span class="p">(</span><span class="n">Generator</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Tests Passed
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Initialize-the-weights-of-your-networks">Initialize the weights of your networks<a class="anchor-link" href="#Initialize-the-weights-of-your-networks">&#182;</a></h2><p>To help your models converge, you should initialize the weights of the convolutional and linear layers in your model. From reading the <a href="https://arxiv.org/pdf/1511.06434.pdf">original DCGAN paper</a>, they say:</p>
<blockquote><p>All weights were initialized from a zero-centered Normal distribution with standard deviation 0.02.</p>
</blockquote>
<p>So, your next task will be to define a weight initialization function that does just this!</p>
<p>You can refer back to the lesson on weight initialization or even consult existing model code, such as that from <a href="https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/models/networks.py">the <code>networks.py</code> file in CycleGAN Github repository</a> to help you complete this function.</p>
<h4 id="Exercise:-Complete-the-weight-initialization-function">Exercise: Complete the weight initialization function<a class="anchor-link" href="#Exercise:-Complete-the-weight-initialization-function">&#182;</a></h4><ul>
<li>This should initialize only <strong>convolutional</strong> and <strong>linear</strong> layers</li>
<li>Initialize the weights to a normal distribution, centered around 0, with a standard deviation of 0.02.</li>
<li>The bias terms, if they exist, may be left alone or set to 0.</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[18]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">weights_init_normal</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Applies initial weights to certain layers in a model .</span>
<span class="sd">    The weights are taken from a normal distribution </span>
<span class="sd">    with mean = 0, std dev = 0.02.</span>
<span class="sd">    :param m: A module or layer in a network    </span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># classname will be something like:</span>
    <span class="c1"># `Conv`, `BatchNorm2d`, `Linear`, etc.</span>
    <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
    
    <span class="c1"># TODO: Apply initial weights to convolutional and linear layers</span>
    <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="s1">&#39;weight&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="p">(</span><span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Conv&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span> <span class="ow">or</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Linear&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">):</span>
        <span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
        
        <span class="c1"># The bias terms, if they exist, set to 0</span>
        <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="s1">&#39;bias&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="n">m</span><span class="o">.</span><span class="n">bias</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">zero_</span><span class="p">()</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Build-complete-network">Build complete network<a class="anchor-link" href="#Build-complete-network">&#182;</a></h2><p>Define your models' hyperparameters and instantiate the discriminator and generator from the classes defined above. Make sure you've passed in the correct input arguments.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[19]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">build_network</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">,</span> <span class="n">g_conv_dim</span><span class="p">,</span> <span class="n">z_size</span><span class="p">):</span>
    <span class="c1"># define discriminator and generator</span>
    <span class="n">D</span> <span class="o">=</span> <span class="n">Discriminator</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">)</span>
    <span class="n">G</span> <span class="o">=</span> <span class="n">Generator</span><span class="p">(</span><span class="n">z_size</span><span class="o">=</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">=</span><span class="n">g_conv_dim</span><span class="p">)</span>

    <span class="c1"># initialize model weights</span>
    <span class="n">D</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init_normal</span><span class="p">)</span>
    <span class="n">G</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init_normal</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">D</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">()</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">D</span><span class="p">,</span> <span class="n">G</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h4 id="Exercise:-Define-model-hyperparameters">Exercise: Define model hyperparameters<a class="anchor-link" href="#Exercise:-Define-model-hyperparameters">&#182;</a></h4>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[20]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define model hyperparams</span>
<span class="n">d_conv_dim</span> <span class="o">=</span> <span class="mi">64</span>
<span class="n">g_conv_dim</span> <span class="o">=</span> <span class="mi">64</span>
<span class="n">z_size</span> <span class="o">=</span> <span class="mi">100</span>

<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">D</span><span class="p">,</span> <span class="n">G</span> <span class="o">=</span> <span class="n">build_network</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">,</span> <span class="n">g_conv_dim</span><span class="p">,</span> <span class="n">z_size</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Discriminator(
  (conv1): Sequential(
    (0): Conv2d(3, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
  )
  (conv2): Sequential(
    (0): Conv2d(64, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (conv3): Sequential(
    (0): Conv2d(128, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (fc): Linear(in_features=4096, out_features=1, bias=True)
)

Generator(
  (fc): Linear(in_features=100, out_features=4096, bias=True)
  (t_conv1): Sequential(
    (0): ConvTranspose2d(256, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv2): Sequential(
    (0): ConvTranspose2d(128, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv3): Sequential(
    (0): ConvTranspose2d(64, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
  )
)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Training-on-GPU">Training on GPU<a class="anchor-link" href="#Training-on-GPU">&#182;</a></h3><p>Check if you can train on GPU. Here, we'll set this as a boolean variable <code>train_on_gpu</code>. Later, you'll be responsible for making sure that</p>
<blockquote><ul>
<li>Models,</li>
<li>Model inputs, and</li>
<li>Loss function arguments</li>
</ul>
</blockquote>
<p>Are moved to GPU, where appropriate.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[21]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">torch</span>

<span class="c1"># Check for a GPU</span>
<span class="n">train_on_gpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span><span class="p">()</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">train_on_gpu</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;No GPU found. Please use a GPU to train your neural network.&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Training on GPU!&#39;</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Training on GPU!
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<hr>
<h2 id="Discriminator-and-Generator-Losses">Discriminator and Generator Losses<a class="anchor-link" href="#Discriminator-and-Generator-Losses">&#182;</a></h2><p>Now we need to calculate the losses for both types of adversarial networks.</p>
<h3 id="Discriminator-Losses">Discriminator Losses<a class="anchor-link" href="#Discriminator-Losses">&#182;</a></h3><blockquote><ul>
<li>For the discriminator, the total loss is the sum of the losses for real and fake images, <code>d_loss = d_real_loss + d_fake_loss</code>. </li>
<li>Remember that we want the discriminator to output 1 for real images and 0 for fake images, so we need to set up the losses to reflect that.</li>
</ul>
</blockquote>
<h3 id="Generator-Loss">Generator Loss<a class="anchor-link" href="#Generator-Loss">&#182;</a></h3><p>The generator loss will look similar only with flipped labels. The generator's goal is to get the discriminator to <em>think</em> its generated images are <em>real</em>.</p>
<h4 id="Exercise:-Complete-real-and-fake-loss-functions">Exercise: Complete real and fake loss functions<a class="anchor-link" href="#Exercise:-Complete-real-and-fake-loss-functions">&#182;</a></h4><p><strong>You may choose to use either cross entropy or a least squares error loss to complete the following <code>real_loss</code> and <code>fake_loss</code> functions.</strong></p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[22]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">real_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">,</span> <span class="n">smooth</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being real.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: real loss&#39;&#39;&#39;</span>
    
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>    
    <span class="c1"># label smoothing</span>
    <span class="k">if</span> <span class="n">smooth</span><span class="p">:</span>  <span class="c1"># smooth, real labels = 0.9 or as given by smooth parameter</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span><span class="o">*</span><span class="mf">0.9</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span> <span class="c1"># real labels = 1</span>
   
    <span class="c1"># move labels to GPU if available     </span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    
    <span class="c1"># binary cross entropy with logits loss</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="c1"># calculate loss</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>

<span class="k">def</span> <span class="nf">fake_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being fake.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: fake loss&#39;&#39;&#39;</span>
    
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span> <span class="c1"># fake labels = 0</span>
    
    <span class="c1"># move labels to GPU if available     </span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    
    <span class="c1"># binary cross entropy with logits loss</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="c1"># calculate loss</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Optimizers">Optimizers<a class="anchor-link" href="#Optimizers">&#182;</a></h2><h4 id="Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">Exercise: Define optimizers for your Discriminator (D) and Generator (G)<a class="anchor-link" href="#Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">&#182;</a></h4><p>Define optimizers for your models with appropriate hyperparameters.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[24]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.optim</span> <span class="k">as</span> <span class="nn">optim</span>

<span class="c1"># params</span>
<span class="n">lr</span> <span class="o">=</span> <span class="mf">0.0002</span>
<span class="n">b1</span><span class="o">=</span><span class="mf">0.5</span>
<span class="n">b2</span><span class="o">=</span><span class="mf">0.999</span> 

<span class="c1"># Create optimizers for the discriminator D and generator G</span>
<span class="n">d_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">D</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="p">,</span> <span class="p">[</span><span class="n">b1</span><span class="p">,</span> <span class="n">b2</span><span class="p">])</span>
<span class="n">g_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="p">,</span> <span class="p">[</span><span class="n">b1</span><span class="p">,</span> <span class="n">b2</span><span class="p">])</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<hr>
<h2 id="Training">Training<a class="anchor-link" href="#Training">&#182;</a></h2><p>Training will involve alternating between training the discriminator and the generator. You'll use your functions <code>real_loss</code> and <code>fake_loss</code> to help you calculate the discriminator losses.</p>
<ul>
<li>You should train the discriminator by alternating on real and fake images</li>
<li>Then the generator, which tries to trick the discriminator and should have an opposing loss function</li>
</ul>
<h4 id="Saving-Samples">Saving Samples<a class="anchor-link" href="#Saving-Samples">&#182;</a></h4><p>You've been given some code to print out some loss statistics and save some generated "fake" samples.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h4 id="Exercise:-Complete-the-training-function">Exercise: Complete the training function<a class="anchor-link" href="#Exercise:-Complete-the-training-function">&#182;</a></h4><p>Keep in mind that, if you've moved your models to GPU, you'll also have to move any model inputs to GPU.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[26]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">n_epochs</span><span class="p">,</span> <span class="n">print_every</span><span class="o">=</span><span class="mi">50</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Trains adversarial networks for some number of epochs</span>
<span class="sd">       param, D: the discriminator network</span>
<span class="sd">       param, G: the generator network</span>
<span class="sd">       param, n_epochs: number of epochs to train for</span>
<span class="sd">       param, print_every: when to print and record the models&#39; losses</span>
<span class="sd">       return: D and G losses&#39;&#39;&#39;</span>
    
    <span class="c1"># move models to GPU</span>
    <span class="n">D</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    <span class="n">G</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>  
    
    <span class="c1"># keep track of loss and generated, &quot;fake&quot; samples</span>
    <span class="n">samples</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">losses</span> <span class="o">=</span> <span class="p">[]</span>


    <span class="c1"># Get some fixed data for sampling. These are images that are held</span>
    <span class="c1"># constant throughout training, and allow us to inspect the model&#39;s performance</span>
    <span class="n">sample_size</span><span class="o">=</span><span class="mi">16</span>
    <span class="n">fixed_z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">sample_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
    <span class="n">fixed_z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">fixed_z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>    

    <span class="c1"># epoch training loop</span>
    <span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_epochs</span><span class="p">):</span>

        <span class="c1"># batch training loop</span>
        <span class="k">for</span> <span class="n">batch_i</span><span class="p">,</span> <span class="p">(</span><span class="n">real_images</span><span class="p">,</span> <span class="n">_</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">celeba_train_loader</span><span class="p">):</span>
          
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">real_images</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>

            <span class="n">batch_size</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
            <span class="n">real_images</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>

            <span class="c1"># ===============================================</span>
            <span class="c1">#         YOUR CODE HERE: TRAIN THE NETWORKS</span>
            <span class="c1"># ===============================================</span>
            
            <span class="c1"># 1. Train the discriminator on real and fake images</span>
            
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            
            <span class="n">d_real</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>        
            <span class="n">d_real_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">d_real</span><span class="p">)</span> 
            
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
            
            <span class="n">d_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">d_fake_loss</span> <span class="o">=</span> <span class="n">fake_loss</span><span class="p">(</span><span class="n">d_fake</span><span class="p">)</span>
            
            <span class="c1"># add up loss and perform backprop</span>
            <span class="n">d_loss</span> <span class="o">=</span> <span class="n">d_real_loss</span> <span class="o">+</span> <span class="n">d_fake_loss</span>
            <span class="n">d_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
        
            <span class="c1"># 2. Train the generator with an adversarial loss</span>
          
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
            
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">g_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span>
            
            <span class="n">g_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
            
            <span class="c1"># ===============================================</span>
            <span class="c1">#              END OF YOUR CODE</span>
            <span class="c1"># ===============================================</span>

            <span class="c1"># Print some loss stats</span>
            <span class="k">if</span> <span class="n">batch_i</span> <span class="o">%</span> <span class="n">print_every</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="c1"># append discriminator loss and generator loss</span>
                <span class="n">losses</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">d_loss</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">g_loss</span><span class="o">.</span><span class="n">item</span><span class="p">()))</span>
                <span class="c1"># print discriminator and generator loss</span>
                <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Epoch [</span><span class="si">{:5d}</span><span class="s1">/</span><span class="si">{:5d}</span><span class="s1">] | d_loss: </span><span class="si">{:6.4f}</span><span class="s1"> | g_loss: </span><span class="si">{:6.4f}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
                        <span class="n">epoch</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">n_epochs</span><span class="p">,</span> <span class="n">d_loss</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">g_loss</span><span class="o">.</span><span class="n">item</span><span class="p">()))</span>


        <span class="c1">## AFTER EACH EPOCH##    </span>
        <span class="c1"># this code assumes your generator is named G, feel free to change the name</span>
        <span class="c1"># generate and save sample, fake images</span>
        <span class="n">G</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span> <span class="c1"># for generating samples</span>
        <span class="n">samples_z</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">fixed_z</span><span class="p">)</span>
        <span class="n">samples</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">samples_z</span><span class="p">)</span>
        <span class="n">G</span><span class="o">.</span><span class="n">train</span><span class="p">()</span> <span class="c1"># back to training mode</span>

    <span class="c1"># Save training generator samples</span>
    <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;train_samples.pkl&#39;</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
        <span class="n">pkl</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">samples</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
    
    <span class="c1"># finally return losses</span>
    <span class="k">return</span> <span class="n">losses</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Set your number of training epochs and train your GAN!</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[27]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># set number of epochs </span>
<span class="n">n_epochs</span> <span class="o">=</span> <span class="mi">20</span>


<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># call training function</span>
<span class="n">losses</span> <span class="o">=</span> <span class="n">train</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">n_epochs</span><span class="o">=</span><span class="n">n_epochs</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Epoch [    1/   20] | d_loss: 1.5455 | g_loss: 0.8278
Epoch [    1/   20] | d_loss: 0.0810 | g_loss: 4.1815
Epoch [    1/   20] | d_loss: 0.1893 | g_loss: 3.8313
Epoch [    1/   20] | d_loss: 0.3941 | g_loss: 2.7477
Epoch [    1/   20] | d_loss: 0.5673 | g_loss: 1.8567
Epoch [    1/   20] | d_loss: 1.3411 | g_loss: 0.7837
Epoch [    1/   20] | d_loss: 1.0242 | g_loss: 2.3756
Epoch [    1/   20] | d_loss: 0.7950 | g_loss: 1.3947
Epoch [    1/   20] | d_loss: 0.9988 | g_loss: 1.6699
Epoch [    1/   20] | d_loss: 0.9218 | g_loss: 1.1678
Epoch [    1/   20] | d_loss: 1.0543 | g_loss: 1.6103
Epoch [    1/   20] | d_loss: 0.9924 | g_loss: 1.1141
Epoch [    1/   20] | d_loss: 1.0288 | g_loss: 1.0404
Epoch [    1/   20] | d_loss: 0.9332 | g_loss: 1.5726
Epoch [    1/   20] | d_loss: 1.2062 | g_loss: 1.2675
Epoch [    2/   20] | d_loss: 1.0951 | g_loss: 1.6633
Epoch [    2/   20] | d_loss: 1.2231 | g_loss: 0.6751
Epoch [    2/   20] | d_loss: 1.0197 | g_loss: 1.3834
Epoch [    2/   20] | d_loss: 1.3080 | g_loss: 0.4925
Epoch [    2/   20] | d_loss: 1.0391 | g_loss: 0.9565
Epoch [    2/   20] | d_loss: 1.3351 | g_loss: 1.0077
Epoch [    2/   20] | d_loss: 1.0543 | g_loss: 0.9683
Epoch [    2/   20] | d_loss: 1.0462 | g_loss: 1.1836
Epoch [    2/   20] | d_loss: 1.2806 | g_loss: 0.7404
Epoch [    2/   20] | d_loss: 1.7416 | g_loss: 0.3990
Epoch [    2/   20] | d_loss: 0.8956 | g_loss: 1.1370
Epoch [    2/   20] | d_loss: 1.1647 | g_loss: 1.1090
Epoch [    2/   20] | d_loss: 1.0272 | g_loss: 1.3712
Epoch [    2/   20] | d_loss: 1.0797 | g_loss: 0.9743
Epoch [    2/   20] | d_loss: 1.2275 | g_loss: 1.7546
Epoch [    3/   20] | d_loss: 1.1922 | g_loss: 0.9429
Epoch [    3/   20] | d_loss: 1.0784 | g_loss: 1.3857
Epoch [    3/   20] | d_loss: 0.9997 | g_loss: 1.3101
Epoch [    3/   20] | d_loss: 1.0917 | g_loss: 1.0173
Epoch [    3/   20] | d_loss: 0.9966 | g_loss: 1.5914
Epoch [    3/   20] | d_loss: 1.1413 | g_loss: 0.9790
Epoch [    3/   20] | d_loss: 0.8973 | g_loss: 1.1746
Epoch [    3/   20] | d_loss: 1.1719 | g_loss: 1.4707
Epoch [    3/   20] | d_loss: 0.8242 | g_loss: 1.4985
Epoch [    3/   20] | d_loss: 1.1743 | g_loss: 1.4460
Epoch [    3/   20] | d_loss: 0.9052 | g_loss: 1.1629
Epoch [    3/   20] | d_loss: 1.0454 | g_loss: 1.6719
Epoch [    3/   20] | d_loss: 1.1396 | g_loss: 1.6554
Epoch [    3/   20] | d_loss: 1.1435 | g_loss: 0.7246
Epoch [    3/   20] | d_loss: 1.2047 | g_loss: 0.8740
Epoch [    4/   20] | d_loss: 1.5592 | g_loss: 2.3890
Epoch [    4/   20] | d_loss: 1.0472 | g_loss: 1.2090
Epoch [    4/   20] | d_loss: 0.9649 | g_loss: 0.8305
Epoch [    4/   20] | d_loss: 1.1131 | g_loss: 1.0021
Epoch [    4/   20] | d_loss: 0.9242 | g_loss: 1.4756
Epoch [    4/   20] | d_loss: 0.8929 | g_loss: 1.4259
Epoch [    4/   20] | d_loss: 1.0430 | g_loss: 1.4503
Epoch [    4/   20] | d_loss: 1.0005 | g_loss: 1.1976
Epoch [    4/   20] | d_loss: 1.2947 | g_loss: 0.7059
Epoch [    4/   20] | d_loss: 1.1889 | g_loss: 2.1182
Epoch [    4/   20] | d_loss: 1.0999 | g_loss: 1.4466
Epoch [    4/   20] | d_loss: 1.2397 | g_loss: 1.5690
Epoch [    4/   20] | d_loss: 1.1053 | g_loss: 1.6581
Epoch [    4/   20] | d_loss: 1.4958 | g_loss: 2.7628
Epoch [    4/   20] | d_loss: 0.8549 | g_loss: 1.6294
Epoch [    5/   20] | d_loss: 1.1426 | g_loss: 1.6998
Epoch [    5/   20] | d_loss: 0.9971 | g_loss: 1.5366
Epoch [    5/   20] | d_loss: 0.9163 | g_loss: 1.4210
Epoch [    5/   20] | d_loss: 1.0221 | g_loss: 1.5891
Epoch [    5/   20] | d_loss: 0.9474 | g_loss: 1.2769
Epoch [    5/   20] | d_loss: 0.9882 | g_loss: 1.2223
Epoch [    5/   20] | d_loss: 1.1817 | g_loss: 0.6600
Epoch [    5/   20] | d_loss: 0.8719 | g_loss: 1.2730
Epoch [    5/   20] | d_loss: 0.9428 | g_loss: 1.2398
Epoch [    5/   20] | d_loss: 1.2804 | g_loss: 1.2526
Epoch [    5/   20] | d_loss: 0.9647 | g_loss: 1.4683
Epoch [    5/   20] | d_loss: 1.0891 | g_loss: 0.9766
Epoch [    5/   20] | d_loss: 0.7769 | g_loss: 1.3434
Epoch [    5/   20] | d_loss: 1.2075 | g_loss: 1.4556
Epoch [    5/   20] | d_loss: 0.9583 | g_loss: 1.8239
Epoch [    6/   20] | d_loss: 0.9219 | g_loss: 1.2145
Epoch [    6/   20] | d_loss: 0.7259 | g_loss: 1.4041
Epoch [    6/   20] | d_loss: 0.9200 | g_loss: 0.9529
Epoch [    6/   20] | d_loss: 1.0445 | g_loss: 1.1074
Epoch [    6/   20] | d_loss: 0.8309 | g_loss: 1.7432
Epoch [    6/   20] | d_loss: 0.8527 | g_loss: 1.3109
Epoch [    6/   20] | d_loss: 1.0083 | g_loss: 1.0347
Epoch [    6/   20] | d_loss: 1.1517 | g_loss: 0.8824
Epoch [    6/   20] | d_loss: 1.0454 | g_loss: 0.7123
Epoch [    6/   20] | d_loss: 1.1744 | g_loss: 1.7555
Epoch [    6/   20] | d_loss: 1.1573 | g_loss: 0.6908
Epoch [    6/   20] | d_loss: 0.9168 | g_loss: 1.2131
Epoch [    6/   20] | d_loss: 1.0890 | g_loss: 1.0902
Epoch [    6/   20] | d_loss: 1.0610 | g_loss: 1.2726
Epoch [    6/   20] | d_loss: 0.8782 | g_loss: 1.4455
Epoch [    7/   20] | d_loss: 0.8986 | g_loss: 1.6095
Epoch [    7/   20] | d_loss: 1.3131 | g_loss: 0.7290
Epoch [    7/   20] | d_loss: 0.9127 | g_loss: 1.4569
Epoch [    7/   20] | d_loss: 0.9405 | g_loss: 0.5923
Epoch [    7/   20] | d_loss: 1.1393 | g_loss: 1.2006
Epoch [    7/   20] | d_loss: 1.0185 | g_loss: 1.7679
Epoch [    7/   20] | d_loss: 0.9994 | g_loss: 1.9506
Epoch [    7/   20] | d_loss: 1.1142 | g_loss: 0.6440
Epoch [    7/   20] | d_loss: 1.3695 | g_loss: 0.6641
Epoch [    7/   20] | d_loss: 0.9390 | g_loss: 1.3459
Epoch [    7/   20] | d_loss: 0.7766 | g_loss: 1.7380
Epoch [    7/   20] | d_loss: 0.9192 | g_loss: 1.8862
Epoch [    7/   20] | d_loss: 1.0284 | g_loss: 2.5882
Epoch [    7/   20] | d_loss: 0.9528 | g_loss: 1.3735
Epoch [    7/   20] | d_loss: 0.7971 | g_loss: 1.0919
Epoch [    8/   20] | d_loss: 0.9915 | g_loss: 1.5332
Epoch [    8/   20] | d_loss: 0.8875 | g_loss: 1.0852
Epoch [    8/   20] | d_loss: 1.0955 | g_loss: 1.6834
Epoch [    8/   20] | d_loss: 0.9196 | g_loss: 1.2249
Epoch [    8/   20] | d_loss: 1.0674 | g_loss: 0.8393
Epoch [    8/   20] | d_loss: 1.1789 | g_loss: 0.8714
Epoch [    8/   20] | d_loss: 0.8437 | g_loss: 1.0756
Epoch [    8/   20] | d_loss: 1.5401 | g_loss: 0.4451
Epoch [    8/   20] | d_loss: 0.9384 | g_loss: 0.9299
Epoch [    8/   20] | d_loss: 0.9193 | g_loss: 1.2826
Epoch [    8/   20] | d_loss: 0.9950 | g_loss: 0.7786
Epoch [    8/   20] | d_loss: 0.8869 | g_loss: 1.7110
Epoch [    8/   20] | d_loss: 0.7856 | g_loss: 1.3884
Epoch [    8/   20] | d_loss: 0.9458 | g_loss: 1.6109
Epoch [    8/   20] | d_loss: 1.0967 | g_loss: 2.5311
Epoch [    9/   20] | d_loss: 0.9366 | g_loss: 0.9784
Epoch [    9/   20] | d_loss: 0.7772 | g_loss: 0.9901
Epoch [    9/   20] | d_loss: 1.0249 | g_loss: 1.9759
Epoch [    9/   20] | d_loss: 0.9600 | g_loss: 0.8135
Epoch [    9/   20] | d_loss: 1.1902 | g_loss: 0.8257
Epoch [    9/   20] | d_loss: 0.9772 | g_loss: 1.3238
Epoch [    9/   20] | d_loss: 1.1751 | g_loss: 1.5568
Epoch [    9/   20] | d_loss: 0.9524 | g_loss: 1.2160
Epoch [    9/   20] | d_loss: 0.9485 | g_loss: 1.9287
Epoch [    9/   20] | d_loss: 0.8937 | g_loss: 2.0934
Epoch [    9/   20] | d_loss: 0.9934 | g_loss: 0.9074
Epoch [    9/   20] | d_loss: 1.0466 | g_loss: 2.2041
Epoch [    9/   20] | d_loss: 1.0448 | g_loss: 0.7640
Epoch [    9/   20] | d_loss: 0.9729 | g_loss: 0.9780
Epoch [    9/   20] | d_loss: 0.7932 | g_loss: 1.5118
Epoch [   10/   20] | d_loss: 0.8013 | g_loss: 1.3548
Epoch [   10/   20] | d_loss: 0.8790 | g_loss: 1.2901
Epoch [   10/   20] | d_loss: 1.0583 | g_loss: 1.4119
Epoch [   10/   20] | d_loss: 1.5811 | g_loss: 2.7034
Epoch [   10/   20] | d_loss: 0.9085 | g_loss: 2.0873
Epoch [   10/   20] | d_loss: 0.9610 | g_loss: 0.8426
Epoch [   10/   20] | d_loss: 0.9140 | g_loss: 1.2437
Epoch [   10/   20] | d_loss: 0.7957 | g_loss: 1.5906
Epoch [   10/   20] | d_loss: 0.8079 | g_loss: 1.0719
Epoch [   10/   20] | d_loss: 0.8048 | g_loss: 1.6170
Epoch [   10/   20] | d_loss: 0.8195 | g_loss: 1.0007
Epoch [   10/   20] | d_loss: 0.8312 | g_loss: 1.3213
Epoch [   10/   20] | d_loss: 1.0086 | g_loss: 1.0627
Epoch [   10/   20] | d_loss: 0.8108 | g_loss: 2.2274
Epoch [   10/   20] | d_loss: 0.8547 | g_loss: 1.5404
Epoch [   11/   20] | d_loss: 0.7098 | g_loss: 1.4646
Epoch [   11/   20] | d_loss: 1.0158 | g_loss: 1.9326
Epoch [   11/   20] | d_loss: 0.8033 | g_loss: 2.3577
Epoch [   11/   20] | d_loss: 0.7225 | g_loss: 1.7837
Epoch [   11/   20] | d_loss: 1.0684 | g_loss: 2.0886
Epoch [   11/   20] | d_loss: 0.9478 | g_loss: 0.8107
Epoch [   11/   20] | d_loss: 0.7243 | g_loss: 1.3088
Epoch [   11/   20] | d_loss: 0.7737 | g_loss: 1.2411
Epoch [   11/   20] | d_loss: 0.7934 | g_loss: 1.2243
Epoch [   11/   20] | d_loss: 0.7189 | g_loss: 1.1606
Epoch [   11/   20] | d_loss: 0.8716 | g_loss: 1.6096
Epoch [   11/   20] | d_loss: 0.8928 | g_loss: 1.1193
Epoch [   11/   20] | d_loss: 0.7844 | g_loss: 1.5980
Epoch [   11/   20] | d_loss: 0.7657 | g_loss: 1.6848
Epoch [   11/   20] | d_loss: 1.0548 | g_loss: 0.6849
Epoch [   12/   20] | d_loss: 0.9703 | g_loss: 0.9689
Epoch [   12/   20] | d_loss: 0.7499 | g_loss: 2.2625
Epoch [   12/   20] | d_loss: 0.7404 | g_loss: 1.8637
Epoch [   12/   20] | d_loss: 0.6931 | g_loss: 1.6235
Epoch [   12/   20] | d_loss: 0.8690 | g_loss: 2.3672
Epoch [   12/   20] | d_loss: 0.6249 | g_loss: 1.8004
Epoch [   12/   20] | d_loss: 0.8186 | g_loss: 1.0025
Epoch [   12/   20] | d_loss: 0.6476 | g_loss: 1.4172
Epoch [   12/   20] | d_loss: 1.0308 | g_loss: 0.7680
Epoch [   12/   20] | d_loss: 0.7263 | g_loss: 1.5996
Epoch [   12/   20] | d_loss: 0.9139 | g_loss: 1.9952
Epoch [   12/   20] | d_loss: 1.0289 | g_loss: 1.6718
Epoch [   12/   20] | d_loss: 0.7430 | g_loss: 1.5828
Epoch [   12/   20] | d_loss: 0.6164 | g_loss: 2.2279
Epoch [   12/   20] | d_loss: 3.3517 | g_loss: 6.1052
Epoch [   13/   20] | d_loss: 2.0314 | g_loss: 0.2963
Epoch [   13/   20] | d_loss: 1.0801 | g_loss: 2.7119
Epoch [   13/   20] | d_loss: 0.6554 | g_loss: 1.2979
Epoch [   13/   20] | d_loss: 0.5152 | g_loss: 1.9198
Epoch [   13/   20] | d_loss: 0.6909 | g_loss: 1.4722
Epoch [   13/   20] | d_loss: 0.8433 | g_loss: 1.0020
Epoch [   13/   20] | d_loss: 0.9961 | g_loss: 2.7113
Epoch [   13/   20] | d_loss: 0.7792 | g_loss: 0.9345
Epoch [   13/   20] | d_loss: 0.6086 | g_loss: 1.6746
Epoch [   13/   20] | d_loss: 0.5727 | g_loss: 1.5371
Epoch [   13/   20] | d_loss: 1.0191 | g_loss: 0.7673
Epoch [   13/   20] | d_loss: 0.6480 | g_loss: 1.8112
Epoch [   13/   20] | d_loss: 0.6064 | g_loss: 1.7057
Epoch [   13/   20] | d_loss: 0.7097 | g_loss: 1.6280
Epoch [   13/   20] | d_loss: 0.5407 | g_loss: 1.7427
Epoch [   14/   20] | d_loss: 0.6558 | g_loss: 1.3422
Epoch [   14/   20] | d_loss: 0.7082 | g_loss: 0.9145
Epoch [   14/   20] | d_loss: 0.6328 | g_loss: 2.6378
Epoch [   14/   20] | d_loss: 0.6207 | g_loss: 1.1718
Epoch [   14/   20] | d_loss: 0.5668 | g_loss: 1.5450
Epoch [   14/   20] | d_loss: 0.5589 | g_loss: 2.1929
Epoch [   14/   20] | d_loss: 0.5390 | g_loss: 1.8277
Epoch [   14/   20] | d_loss: 0.6000 | g_loss: 1.0425
Epoch [   14/   20] | d_loss: 0.5206 | g_loss: 2.1515
Epoch [   14/   20] | d_loss: 0.5284 | g_loss: 2.0335
Epoch [   14/   20] | d_loss: 2.1806 | g_loss: 0.0802
Epoch [   14/   20] | d_loss: 0.5184 | g_loss: 1.7660
Epoch [   14/   20] | d_loss: 0.4460 | g_loss: 1.8190
Epoch [   14/   20] | d_loss: 0.5203 | g_loss: 1.6949
Epoch [   14/   20] | d_loss: 0.6122 | g_loss: 2.0506
Epoch [   15/   20] | d_loss: 0.5774 | g_loss: 1.6458
Epoch [   15/   20] | d_loss: 0.5312 | g_loss: 1.5987
Epoch [   15/   20] | d_loss: 0.7871 | g_loss: 2.0828
Epoch [   15/   20] | d_loss: 0.4817 | g_loss: 2.2020
Epoch [   15/   20] | d_loss: 0.4812 | g_loss: 1.7040
Epoch [   15/   20] | d_loss: 0.6416 | g_loss: 2.1745
Epoch [   15/   20] | d_loss: 0.5511 | g_loss: 1.6770
Epoch [   15/   20] | d_loss: 0.9730 | g_loss: 0.9888
Epoch [   15/   20] | d_loss: 1.0241 | g_loss: 0.9793
Epoch [   15/   20] | d_loss: 0.3917 | g_loss: 2.1109
Epoch [   15/   20] | d_loss: 0.5859 | g_loss: 1.7203
Epoch [   15/   20] | d_loss: 0.5646 | g_loss: 2.1453
Epoch [   15/   20] | d_loss: 0.6546 | g_loss: 2.3754
Epoch [   15/   20] | d_loss: 0.6647 | g_loss: 1.4258
Epoch [   15/   20] | d_loss: 0.6134 | g_loss: 1.3023
Epoch [   16/   20] | d_loss: 0.5447 | g_loss: 2.3951
Epoch [   16/   20] | d_loss: 0.2927 | g_loss: 2.5444
Epoch [   16/   20] | d_loss: 0.4685 | g_loss: 2.6362
Epoch [   16/   20] | d_loss: 0.4428 | g_loss: 1.7535
Epoch [   16/   20] | d_loss: 0.3752 | g_loss: 2.0930
Epoch [   16/   20] | d_loss: 1.3896 | g_loss: 3.8024
Epoch [   16/   20] | d_loss: 0.4486 | g_loss: 2.4533
Epoch [   16/   20] | d_loss: 0.5020 | g_loss: 2.8989
Epoch [   16/   20] | d_loss: 1.1171 | g_loss: 3.4389
Epoch [   16/   20] | d_loss: 0.4826 | g_loss: 1.5488
Epoch [   16/   20] | d_loss: 0.5509 | g_loss: 1.8809
Epoch [   16/   20] | d_loss: 0.6053 | g_loss: 2.5187
Epoch [   16/   20] | d_loss: 0.4855 | g_loss: 2.1216
Epoch [   16/   20] | d_loss: 0.5431 | g_loss: 2.2160
Epoch [   16/   20] | d_loss: 2.0962 | g_loss: 1.0431
Epoch [   17/   20] | d_loss: 0.8609 | g_loss: 0.8253
Epoch [   17/   20] | d_loss: 0.4033 | g_loss: 2.2995
Epoch [   17/   20] | d_loss: 0.4646 | g_loss: 1.9165
Epoch [   17/   20] | d_loss: 0.5560 | g_loss: 1.5726
Epoch [   17/   20] | d_loss: 0.4841 | g_loss: 2.0898
Epoch [   17/   20] | d_loss: 0.5110 | g_loss: 2.1671
Epoch [   17/   20] | d_loss: 0.4361 | g_loss: 1.9988
Epoch [   17/   20] | d_loss: 0.5944 | g_loss: 1.5224
Epoch [   17/   20] | d_loss: 0.3242 | g_loss: 2.6435
Epoch [   17/   20] | d_loss: 0.7220 | g_loss: 1.5668
Epoch [   17/   20] | d_loss: 0.4250 | g_loss: 1.8058
Epoch [   17/   20] | d_loss: 0.4053 | g_loss: 2.2005
Epoch [   17/   20] | d_loss: 0.5816 | g_loss: 2.9196
Epoch [   17/   20] | d_loss: 0.5023 | g_loss: 1.7169
Epoch [   17/   20] | d_loss: 0.6409 | g_loss: 1.2521
Epoch [   18/   20] | d_loss: 0.4760 | g_loss: 1.1117
Epoch [   18/   20] | d_loss: 0.6143 | g_loss: 5.5299
Epoch [   18/   20] | d_loss: 0.3605 | g_loss: 2.6896
Epoch [   18/   20] | d_loss: 1.5757 | g_loss: 3.2707
Epoch [   18/   20] | d_loss: 0.5046 | g_loss: 2.1701
Epoch [   18/   20] | d_loss: 0.5642 | g_loss: 1.2187
Epoch [   18/   20] | d_loss: 0.5590 | g_loss: 3.9221
Epoch [   18/   20] | d_loss: 0.4661 | g_loss: 2.3628
Epoch [   18/   20] | d_loss: 0.5289 | g_loss: 2.9121
Epoch [   18/   20] | d_loss: 0.3320 | g_loss: 2.9242
Epoch [   18/   20] | d_loss: 0.6078 | g_loss: 2.6467
Epoch [   18/   20] | d_loss: 0.4435 | g_loss: 1.8137
Epoch [   18/   20] | d_loss: 3.0576 | g_loss: 0.2389
Epoch [   18/   20] | d_loss: 0.3660 | g_loss: 2.3391
Epoch [   18/   20] | d_loss: 0.3923 | g_loss: 2.0344
Epoch [   19/   20] | d_loss: 0.3554 | g_loss: 2.1991
Epoch [   19/   20] | d_loss: 0.3759 | g_loss: 2.5596
Epoch [   19/   20] | d_loss: 2.8341 | g_loss: 3.5649
Epoch [   19/   20] | d_loss: 0.4194 | g_loss: 2.1891
Epoch [   19/   20] | d_loss: 0.3764 | g_loss: 2.8090
Epoch [   19/   20] | d_loss: 0.9474 | g_loss: 0.6982
Epoch [   19/   20] | d_loss: 0.4943 | g_loss: 2.5052
Epoch [   19/   20] | d_loss: 0.3152 | g_loss: 2.0197
Epoch [   19/   20] | d_loss: 0.3578 | g_loss: 2.3674
Epoch [   19/   20] | d_loss: 0.5266 | g_loss: 1.7613
Epoch [   19/   20] | d_loss: 0.5180 | g_loss: 3.2370
Epoch [   19/   20] | d_loss: 0.3554 | g_loss: 1.8040
Epoch [   19/   20] | d_loss: 0.5233 | g_loss: 1.8054
Epoch [   19/   20] | d_loss: 0.3243 | g_loss: 2.5412
Epoch [   19/   20] | d_loss: 0.4459 | g_loss: 1.1745
Epoch [   20/   20] | d_loss: 0.5353 | g_loss: 2.6624
Epoch [   20/   20] | d_loss: 0.4646 | g_loss: 2.3147
Epoch [   20/   20] | d_loss: 0.3562 | g_loss: 2.0953
Epoch [   20/   20] | d_loss: 0.3913 | g_loss: 2.4116
Epoch [   20/   20] | d_loss: 0.3044 | g_loss: 3.4514
Epoch [   20/   20] | d_loss: 0.3620 | g_loss: 2.2138
Epoch [   20/   20] | d_loss: 0.4944 | g_loss: 1.5808
Epoch [   20/   20] | d_loss: 0.5525 | g_loss: 1.7348
Epoch [   20/   20] | d_loss: 0.3924 | g_loss: 3.0053
Epoch [   20/   20] | d_loss: 0.3116 | g_loss: 2.1453
Epoch [   20/   20] | d_loss: 0.4064 | g_loss: 2.2985
Epoch [   20/   20] | d_loss: 0.3655 | g_loss: 2.3402
Epoch [   20/   20] | d_loss: 2.0672 | g_loss: 0.2036
Epoch [   20/   20] | d_loss: 0.3370 | g_loss: 1.8299
Epoch [   20/   20] | d_loss: 0.3388 | g_loss: 2.1212
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Training-loss">Training loss<a class="anchor-link" href="#Training-loss">&#182;</a></h2><p>Plot the training losses for the generator and discriminator, recorded after each epoch.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[28]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">losses</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">losses</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Discriminator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Generator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Training Losses&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt output_prompt">Out[28]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>&lt;matplotlib.legend.Legend at 0x7f9c3b4939b0&gt;</pre>
</div>

</div>

<div class="output_area">

    <div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Generator-samples-from-training">Generator samples from training<a class="anchor-link" href="#Generator-samples-from-training">&#182;</a></h2><p>View samples of images from the generator, and answer a question about the strengths and weaknesses of your trained models.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[35]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper function for viewing a list of passed in sample images</span>
<span class="k">def</span> <span class="nf">view_samples</span><span class="p">(</span><span class="n">epoch</span><span class="p">,</span> <span class="n">samples</span><span class="p">):</span>
    <span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span><span class="mi">4</span><span class="p">),</span> <span class="n">nrows</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">sharex</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">ax</span><span class="p">,</span> <span class="n">img</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">axes</span><span class="o">.</span><span class="n">flatten</span><span class="p">(),</span> <span class="n">samples</span><span class="p">[</span><span class="n">epoch</span><span class="p">]):</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
        <span class="n">img</span> <span class="o">=</span> <span class="p">((</span><span class="n">img</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="mi">255</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_visible</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">yaxis</span><span class="o">.</span><span class="n">set_visible</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
        <span class="n">im</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">32</span><span class="p">,</span><span class="mi">32</span><span class="p">,</span><span class="mi">3</span><span class="p">)))</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[36]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Load samples from generator, taken while training</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;train_samples.pkl&#39;</span><span class="p">,</span> <span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">samples</span> <span class="o">=</span> <span class="n">pkl</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span> 
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[38]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">_</span> <span class="o">=</span> <span class="n">view_samples</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="n">samples</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[41]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">_</span> <span class="o">=</span> <span class="n">view_samples</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span> <span class="n">samples</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span> 
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[46]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">_</span> <span class="o">=</span> <span class="n">view_samples</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">samples</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Question:-What-do-you-notice-about-your-generated-samples-and-how-might-you-improve-this-model?">Question: What do you notice about your generated samples and how might you improve this model?<a class="anchor-link" href="#Question:-What-do-you-notice-about-your-generated-samples-and-how-might-you-improve-this-model?">&#182;</a></h3><p>When you answer this question, consider the following factors:</p>
<ul>
<li>The dataset is biased; it is made of "celebrity" faces that are mostly white</li>
<li>Model size; larger models have the opportunity to learn more features in a data feature space</li>
<li>Optimization strategy; optimizers and number of epochs affect your final result</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong></p>
<ol>
<li>The training data does not have the complete face. Features like hairstyle &amp; chins are not visible. As a results, the generated images miss chins and complete hairstyle. Data should preferably have the complete face.</li>
</ol>
<ol>
<li>Obtaining higher resolution images as a dataset( Maybe 128x128 ) and then training the model on those images.</li>
</ol>
<ol>
<li>DCGAN is not a typical network where reduction in loss will point towards a better model. I don't know why it isn't so I'm not sure if higher epochs makes the generaotor generate more accurate and realistic faces.</li>
</ol>
<ol>
<li>The dataset is biased. It is made of celebrity faces that are mostly white.Faces of people of All races and different countries should be included in the dataset. Also, we need to add more images in the dataset till it has almost equal number of white and non-white celebrity faces.</li>
</ol>
<ol>
<li>Model size matters. we have to ensure that our models reconginze and generate faces correctly. Deep models allow to catch some more characteristrics of the faces. For face generation task, we need to learn more complex features so we need a bigger network.</li>
</ol>
<ol>
<li>We can use different optimizers: SGD for the discriminator and keep Adam for the generator. Training for more epochs may also affect quality of final generated faces</li>
</ol>
<ol>
<li>The photo angles are different. If all photos were taken from a similar angle it would have been easier for the network to train and to learn that faces are usually more or less symmetrical. (better feature extraction)</li>
</ol>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Submitting-This-Project">Submitting This Project<a class="anchor-link" href="#Submitting-This-Project">&#182;</a></h3><p>When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -&gt; "Download as". Include the "problem_unittests.py" files in your submission.</p>

</div>
</div>
</div>
    </div>
  </div>
</body>

 
<script type="application/vnd.jupyter.widget-state+json">
{"state": {}, "version_major": 2, "version_minor": 0}
</script>


</html>