main.html

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

<title>main</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>


<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 {
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}
.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 {
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}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
.glyphicon-remove:before {
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}
.glyphicon-zoom-in:before {
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}
.glyphicon-zoom-out:before {
  content: "\e016";
}
.glyphicon-off:before {
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}
.glyphicon-signal:before {
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}
.glyphicon-cog:before {
  content: "\e019";
}
.glyphicon-trash:before {
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}
.glyphicon-home:before {
  content: "\e021";
}
.glyphicon-file:before {
  content: "\e022";
}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
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}
.glyphicon-download:before {
  content: "\e026";
}
.glyphicon-upload:before {
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}
.glyphicon-inbox:before {
  content: "\e028";
}
.glyphicon-play-circle:before {
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}
.glyphicon-repeat:before {
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}
.glyphicon-refresh:before {
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}
.glyphicon-list-alt:before {
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}
.glyphicon-lock:before {
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}
.glyphicon-flag:before {
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}
.glyphicon-headphones:before {
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}
.glyphicon-volume-off:before {
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}
.glyphicon-volume-down:before {
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}
.glyphicon-volume-up:before {
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}
.glyphicon-qrcode:before {
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}
.glyphicon-barcode:before {
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}
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}
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}
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}
.glyphicon-bookmark:before {
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}
.glyphicon-print:before {
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}
.glyphicon-camera:before {
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}
.glyphicon-font:before {
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}
.glyphicon-bold:before {
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}
.glyphicon-italic:before {
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}
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}
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}
.glyphicon-align-right:before {
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}
.glyphicon-align-justify:before {
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}
.glyphicon-list:before {
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}
.glyphicon-indent-left:before {
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}
.glyphicon-indent-right:before {
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}
.glyphicon-facetime-video:before {
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}
.glyphicon-picture:before {
  content: "\e060";
}
.glyphicon-map-marker:before {
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}
.glyphicon-adjust:before {
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}
.glyphicon-tint:before {
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}
.glyphicon-edit:before {
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}
.glyphicon-share:before {
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}
.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 {
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}
.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 {
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}
.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 {
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}
.glyphicon-briefcase:before {
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}
.glyphicon-fullscreen:before {
  content: "\e140";
}
.glyphicon-dashboard:before {
  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
  content: "\e143";
}
.glyphicon-link:before {
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}
.glyphicon-phone:before {
  content: "\e145";
}
.glyphicon-pushpin:before {
  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
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}
.glyphicon-sort:before {
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}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
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}
.glyphicon-sort-by-order-alt:before {
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}
.glyphicon-sort-by-attributes:before {
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.glyphicon-sort-by-attributes-alt:before {
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.glyphicon-unchecked:before {
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.glyphicon-expand:before {
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}
.glyphicon-collapse-down:before {
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}
.glyphicon-collapse-up:before {
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.glyphicon-log-in:before {
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.glyphicon-flash:before {
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}
.glyphicon-log-out:before {
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.glyphicon-new-window:before {
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.glyphicon-record:before {
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.glyphicon-save:before {
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.glyphicon-open:before {
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.glyphicon-saved:before {
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.glyphicon-import:before {
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.glyphicon-export:before {
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.glyphicon-send:before {
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.glyphicon-floppy-disk:before {
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.glyphicon-floppy-saved:before {
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}
.glyphicon-floppy-remove:before {
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}
.glyphicon-floppy-save:before {
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}
.glyphicon-floppy-open:before {
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}
.glyphicon-credit-card:before {
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.glyphicon-transfer:before {
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.glyphicon-cutlery:before {
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.glyphicon-header:before {
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.glyphicon-compressed:before {
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.glyphicon-earphone:before {
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.glyphicon-phone-alt:before {
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.glyphicon-tower:before {
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.glyphicon-stats:before {
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.glyphicon-sd-video:before {
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.glyphicon-hd-video:before {
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.glyphicon-subtitles:before {
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.glyphicon-sound-5-1:before {
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.glyphicon-paste:before {
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.glyphicon-alert:before {
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.glyphicon-equalizer:before {
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.glyphicon-king:before {
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.glyphicon-queen:before {
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}
.glyphicon-pawn:before {
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}
.glyphicon-bishop:before {
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.glyphicon-knight:before {
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}
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}
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}
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}
.glyphicon-bed:before {
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}
.glyphicon-apple:before {
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}
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}
.glyphicon-hourglass:before {
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}
.glyphicon-lamp:before {
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}
.glyphicon-duplicate:before {
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}
.glyphicon-piggy-bank:before {
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}
.glyphicon-scissors:before {
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}
.glyphicon-bitcoin:before {
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}
.glyphicon-btc:before {
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}
.glyphicon-xbt:before {
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}
.glyphicon-yen:before {
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}
.glyphicon-jpy:before {
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}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
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}
.glyphicon-ice-lolly-tasted:before {
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}
.glyphicon-education:before {
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}
.glyphicon-option-horizontal:before {
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}
.glyphicon-option-vertical:before {
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}
.glyphicon-menu-hamburger:before {
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}
.glyphicon-modal-window:before {
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}
.glyphicon-oil:before {
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}
.glyphicon-grain:before {
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}
.glyphicon-sunglasses:before {
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}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
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}
.glyphicon-object-align-top:before {
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}
.glyphicon-object-align-bottom:before {
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}
.glyphicon-object-align-horizontal:before {
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}
.glyphicon-object-align-left:before {
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}
.glyphicon-object-align-vertical:before {
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}
.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;
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}
.notification_widget.success:active,
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fieldset[disabled] .notification_widget.success:hover,
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fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
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fieldset[disabled] .notification_widget.success.focus {
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}
.notification_widget.success .badge {
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  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,
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.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 {
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.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
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fieldset[disabled] .notification_widget.info:focus,
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.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
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}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
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  color: #fff;
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}
.notification_widget.danger:active:hover,
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}
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fieldset[disabled] .notification_widget.danger:hover,
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fieldset[disabled] .notification_widget.danger:focus,
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fieldset[disabled] .notification_widget.danger.focus {
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.notification_widget.danger .badge {
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div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
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  bottom: 0px;
  width: 100%;
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  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);
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div#pager pre {
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  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
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  right: 20px;
}
div#pager #pager-contents {
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  height: 100%;
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div#pager #pager-contents #pager-container {
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  padding: 15px 0px;
  box-sizing: border-box;
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  -webkit-box-sizing: border-box;
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div#pager .ui-resizable-handle {
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  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
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div#pager .ui-resizable-handle::after {
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  left: 50%;
  height: 3px;
  width: 30px;
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  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;
}
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  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 {
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  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 {
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}
[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;
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  span.checkpoint_status,
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}
@media (min-width: 768px) and (max-width: 991px) {
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}
.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 {
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  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 {
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}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
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  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 {
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    opacity: 1;
  }
  to {
    opacity: 0;
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}
@-webkit-keyframes fadeOut {
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  to {
    opacity: 0;
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}
@-moz-keyframes fadeIn {
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}
@-webkit-keyframes fadeIn {
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  to {
    opacity: 1;
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}
/*properties of tooltip after "expand"*/
.bigtooltip {
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  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 {
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  -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*/
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}
.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 {
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}
.ipython_tooltip .tooltiptext pre {
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  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
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  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 {
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  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
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ul.typeahead-list > li > a {
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[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;
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[dir="rtl"] .edit-shortcut.pull-right {
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#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
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  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
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}
[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 {
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  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
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  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,
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  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
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  background: white;
}
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}
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<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="Deploy-and-monitor-a-machine-learning-workflow-for-Image-Classification">Deploy and monitor a machine learning workflow for Image Classification<a class="anchor-link" href="#Deploy-and-monitor-a-machine-learning-workflow-for-Image-Classification">&#182;</a></h1>
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<div class="prompt input_prompt">In&nbsp;[8]:</div>
<div class="inner_cell">
    <div class="input_area">
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<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</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">json</span>
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<h2 id="Setting-up-this-notebook">Setting up this notebook<a class="anchor-link" href="#Setting-up-this-notebook">&#182;</a></h2><p>Notes about the instance size and kernel setup: this notebook has been tested on</p>
<ol>
<li>The <code>Python 3 (Data Science)</code> kernel</li>
<li>The <code>ml.t3.medium</code> Sagemaker notebook instance</li>
</ol>
<h2 id="Data-Staging">Data Staging<a class="anchor-link" href="#Data-Staging">&#182;</a></h2><p>We'll use a sample dataset called CIFAR to simulate the challenges Scones Unlimited are facing in Image Classification. In order to start working with CIFAR we'll need to:</p>
<ol>
<li>Extract the data from a hosting service</li>
<li>Transform it into a usable shape and format</li>
<li>Load it into a production system</li>
</ol>
<p>In other words, we're going to do some simple ETL!</p>
<h3 id="1.-Extract-the-data-from-the-hosting-service">1. Extract the data from the hosting service<a class="anchor-link" href="#1.-Extract-the-data-from-the-hosting-service">&#182;</a></h3><p>In the cell below, define a function <code>extract_cifar_data</code> that extracts python version of the CIFAR-100 dataset. The CIFAR dataaset is open source and generously hosted by the University of Toronto at: <a href="https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz">https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz</a></p>

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<span class="k">def</span> <span class="nf">extract_cifar_data</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;cifar.tar.gz&quot;</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;A function for extracting the CIFAR-100 dataset and storing it as a gzipped file</span>
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<span class="sd">    Arguments:</span>
<span class="sd">    url      -- the URL where the dataset is hosted</span>
<span class="sd">    filename -- the full path where the dataset will be written</span>
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<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># Todo: request the data from the data url</span>
    <span class="c1"># Hint: use `requests.get` method</span>
    <span class="n">r</span> <span class="o">=</span> <span class="n">requests</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">url</span><span class="p">)</span>
    <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="s2">&quot;wb&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">file_context</span><span class="p">:</span>
        <span class="n">file_context</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">r</span><span class="o">.</span><span class="n">content</span><span class="p">)</span>
    <span class="k">return</span>
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<p>Let's test it out! Run the following cell and check whether a new file <code>cifar.tar.gz</code> is created in the file explorer.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">extract_cifar_data</span><span class="p">(</span><span class="s2">&quot;https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz&quot;</span><span class="p">)</span>     
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<h3 id="2.-Transform-the-data-into-a-usable-shape-and-format">2. Transform the data into a usable shape and format<a class="anchor-link" href="#2.-Transform-the-data-into-a-usable-shape-and-format">&#182;</a></h3><p>Clearly, distributing the data as a gzipped archive makes sense for the hosting service! It saves on bandwidth, storage, and it's a widely-used archive format. In fact, it's so widely used that the Python community ships a utility for working with them, <code>tarfile</code>, as part of its Standard Library. Execute the following cell to decompress your extracted dataset:</p>

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<span class="k">with</span> <span class="n">tarfile</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s2">&quot;cifar.tar.gz&quot;</span><span class="p">,</span> <span class="s2">&quot;r:gz&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">tar</span><span class="p">:</span>
    <span class="n">tar</span><span class="o">.</span><span class="n">extractall</span><span class="p">()</span>
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<p>A new folder <code>cifar-100-python</code> should be created, containing <code>meta</code>, <code>test</code>, and <code>train</code> files. These files are <code>pickles</code> and the <a href="https://www.cs.toronto.edu/~kriz/cifar.html">CIFAR homepage</a> provides a simple script that can be used to load them. We've adapted the script below for you to run:</p>

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<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;./cifar-100-python/meta&quot;</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">dataset_meta</span> <span class="o">=</span> <span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s1">&#39;bytes&#39;</span><span class="p">)</span>

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;./cifar-100-python/test&quot;</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">dataset_test</span> <span class="o">=</span> <span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s1">&#39;bytes&#39;</span><span class="p">)</span>

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;./cifar-100-python/train&quot;</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">dataset_train</span> <span class="o">=</span> <span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s1">&#39;bytes&#39;</span><span class="p">)</span>
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<span class="n">dataset_train</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span>
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<pre>dict_keys([b&#39;filenames&#39;, b&#39;batch_label&#39;, b&#39;fine_labels&#39;, b&#39;coarse_labels&#39;, b&#39;data&#39;])</pre>
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<p>As documented on the homepage, <code>b'data'</code> contains rows of 3073 unsigned integers, representing three channels (red, green, and blue) for one 32x32 pixel image per row.</p>

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<pre>3072</pre>
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<p>For a simple gut-check, let's transform one of our images. Each 1024 items in a row is a channel (red, green, then blue). Each 32 items in the channel are a row in the 32x32 image. Using python, we can stack these channels into a 32x32x3 array, and save it as a PNG file:</p>

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<span class="c1"># Each 1024 in a row is a channel (red, green, then blue)</span>
<span class="n">row</span> <span class="o">=</span> <span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;data&#39;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="n">red</span><span class="p">,</span> <span class="n">green</span><span class="p">,</span> <span class="n">blue</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">1024</span><span class="p">],</span> <span class="n">row</span><span class="p">[</span><span class="mi">1024</span><span class="p">:</span><span class="mi">2048</span><span class="p">],</span> <span class="n">row</span><span class="p">[</span><span class="mi">2048</span><span class="p">:]</span>

<span class="c1"># Each 32 items in the channel are a row in the 32x32 image</span>
<span class="n">red</span> <span class="o">=</span> <span class="n">red</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="n">green</span> <span class="o">=</span> <span class="n">green</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="n">blue</span> <span class="o">=</span> <span class="n">blue</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="c1"># Combine the channels into a 32x32x3 image!</span>
<span class="n">combined</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">dstack</span><span class="p">((</span><span class="n">red</span><span class="p">,</span><span class="n">green</span><span class="p">,</span><span class="n">blue</span><span class="p">))</span>
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<p>For a more concise version, consider the following:</p>

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<span class="n">test_image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">dstack</span><span class="p">((</span>
    <span class="n">row</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">1024</span><span class="p">]</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="n">row</span><span class="p">[</span><span class="mi">1024</span><span class="p">:</span><span class="mi">2048</span><span class="p">]</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="n">row</span><span class="p">[</span><span class="mi">2048</span><span class="p">:]</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="p">))</span>
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<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">test_image</span><span class="p">);</span>
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<p>Looks like a cow! Let's check the label. <code>dataset_meta</code> contains label names in order, and <code>dataset_train</code> has a list of labels for each row.</p>

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<div class="prompt input_prompt">In&nbsp;[10]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;fine_labels&#39;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
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<pre>19</pre>
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<p>Our image has a label of <code>19</code>, so let's see what the 19th item is in the list of label names.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">dataset_meta</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;fine_label_names&#39;</span><span class="p">][</span><span class="mi">19</span><span class="p">])</span>
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<pre>b&#39;cattle&#39;
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<p>Ok! 'cattle' sounds about right. By the way, using the previous two lines we can do:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">n</span> <span class="o">=</span> <span class="mi">0</span>
<span class="nb">print</span><span class="p">(</span><span class="n">dataset_meta</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;fine_label_names&#39;</span><span class="p">][</span><span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;fine_labels&#39;</span><span class="p">][</span><span class="n">n</span><span class="p">]])</span>
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<pre>b&#39;cattle&#39;
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<p>Now we know how to check labels, is there a way that we can also check file names? <code>dataset_train</code> also contains a <code>b'filenames'</code> key. Let's see what we have here:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;filenames&#39;</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span>
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<pre>b&#39;bos_taurus_s_000507.png&#39;
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<p>"Taurus" is the name of a subspecies of cattle, so this looks like a pretty reasonable filename. To save an image we can also do:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">imsave</span><span class="p">(</span><span class="s2">&quot;file.png&quot;</span><span class="p">,</span> <span class="n">test_image</span><span class="p">)</span>
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<p>Your new PNG file should now appear in the file explorer -- go ahead and pop it open to see!</p>
<p>Now that you know how to reshape the images, save them as files, and capture their filenames and labels, let's just capture all the bicycles and motorcycles and save them. Scones Unlimited can use a model that tells these apart to route delivery drivers automatically.</p>
<p>In the following cell, identify the label numbers for Bicycles and Motorcycles:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>

<span class="c1"># Todo: Filter the dataset_train and dataset_meta objects to find the label numbers for Bicycle and Motorcycles</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">dataset_meta</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;fine_label_names&#39;</span><span class="p">],</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;fine_label_names&#39;</span><span class="p">])</span>

<span class="n">df</span><span class="p">[</span><span class="s1">&#39;fine_label_names&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;fine_label_names&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s1">&#39;ascii&#39;</span><span class="p">)</span>

<span class="n">df</span><span class="p">[(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;fine_label_names&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;motorcycle&#39;</span><span class="p">)</span> <span class="o">|</span> <span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;fine_label_names&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="s1">&#39;bicycle&#39;</span><span class="p">)]</span>
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      <th>8</th>
      <td>bicycle</td>
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      <th>48</th>
      <td>motorcycle</td>
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<p>Good job! We only need objects with label 8 and 48 -- this drastically simplifies our handling of the data! Below we construct a dataframe for you, and you can safely drop the rows that don't contain observations about bicycles and motorcycles. Fill in the missing lines below to drop all other rows:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Construct the dataframe</span>
<span class="n">df_train</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span>
    <span class="s2">&quot;filenames&quot;</span><span class="p">:</span> <span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;filenames&#39;</span><span class="p">],</span>
    <span class="s2">&quot;labels&quot;</span><span class="p">:</span> <span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;fine_labels&#39;</span><span class="p">],</span>
    <span class="s2">&quot;row&quot;</span><span class="p">:</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;filenames&#39;</span><span class="p">]))</span>
<span class="p">})</span>

<span class="c1"># Drop all rows from df_train where label is not 8 or 48</span>
<span class="n">df_train</span> <span class="o">=</span> <span class="n">df_train</span><span class="p">[(</span><span class="n">df_train</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">8</span><span class="p">)</span> <span class="o">|</span> <span class="p">(</span><span class="n">df_train</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">48</span><span class="p">)]</span>

<span class="c1"># Decode df_train.filenames so they are regular strings</span>
<span class="n">df_train</span><span class="p">[</span><span class="s2">&quot;filenames&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df_train</span><span class="p">[</span><span class="s2">&quot;filenames&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span>
    <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s2">&quot;utf-8&quot;</span><span class="p">)</span>
<span class="p">)</span>


<span class="n">df_test</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span>
    <span class="s2">&quot;filenames&quot;</span><span class="p">:</span> <span class="n">dataset_test</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;filenames&#39;</span><span class="p">],</span>
    <span class="s2">&quot;labels&quot;</span><span class="p">:</span> <span class="n">dataset_test</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;fine_labels&#39;</span><span class="p">],</span>
    <span class="s2">&quot;row&quot;</span><span class="p">:</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">dataset_test</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;filenames&#39;</span><span class="p">]))</span>
<span class="p">})</span>

<span class="c1"># Drop all rows from df_test where label is not 8 or 48</span>
<span class="n">df_test</span> <span class="o">=</span> <span class="n">df_test</span><span class="p">[(</span><span class="n">df_test</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">8</span><span class="p">)</span> <span class="o">|</span> <span class="p">(</span><span class="n">df_test</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">48</span><span class="p">)]</span>

<span class="c1"># Decode df_test.filenames so they are regular strings</span>
<span class="n">df_test</span><span class="p">[</span><span class="s2">&quot;filenames&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df_test</span><span class="p">[</span><span class="s2">&quot;filenames&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span>
    <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s2">&quot;utf-8&quot;</span><span class="p">)</span>
<span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">display</span><span class="p">(</span><span class="n">df_train</span><span class="o">.</span><span class="n">head</span><span class="p">())</span>
<span class="n">display</span><span class="p">(</span><span class="n">df_train</span><span class="o">.</span><span class="n">info</span><span class="p">())</span>
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      <th>labels</th>
      <th>row</th>
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      <th>16</th>
      <td>bike_s_000682.png</td>
      <td>8</td>
      <td>16</td>
    </tr>
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      <th>30</th>
      <td>bike_s_000127.png</td>
      <td>8</td>
      <td>30</td>
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      <th>130</th>
      <td>cycle_s_002598.png</td>
      <td>8</td>
      <td>130</td>
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      <th>152</th>
      <td>minibike_s_000824.png</td>
      <td>48</td>
      <td>152</td>
    </tr>
    <tr>
      <th>195</th>
      <td>motorcycle_s_001856.png</td>
      <td>48</td>
      <td>195</td>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
Int64Index: 1000 entries, 16 to 49985
Data columns (total 3 columns):
 #   Column     Non-Null Count  Dtype 
---  ------     --------------  ----- 
 0   filenames  1000 non-null   object
 1   labels     1000 non-null   int64 
 2   row        1000 non-null   int64 
dtypes: int64(2), object(1)
memory usage: 31.2+ KB
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<pre>None</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">display</span><span class="p">(</span><span class="n">df_test</span><span class="o">.</span><span class="n">head</span><span class="p">())</span>
<span class="n">display</span><span class="p">(</span><span class="n">df_test</span><span class="o">.</span><span class="n">info</span><span class="p">())</span>
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<table border="1" class="dataframe">
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      <th></th>
      <th>filenames</th>
      <th>labels</th>
      <th>row</th>
    </tr>
  </thead>
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    <tr>
      <th>27</th>
      <td>safety_bike_s_000390.png</td>
      <td>8</td>
      <td>27</td>
    </tr>
    <tr>
      <th>28</th>
      <td>bike_s_000658.png</td>
      <td>8</td>
      <td>28</td>
    </tr>
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      <th>116</th>
      <td>velocipede_s_001744.png</td>
      <td>8</td>
      <td>116</td>
    </tr>
    <tr>
      <th>161</th>
      <td>bike_s_000643.png</td>
      <td>8</td>
      <td>161</td>
    </tr>
    <tr>
      <th>319</th>
      <td>ordinary_bicycle_s_000437.png</td>
      <td>8</td>
      <td>319</td>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
Int64Index: 200 entries, 27 to 9939
Data columns (total 3 columns):
 #   Column     Non-Null Count  Dtype 
---  ------     --------------  ----- 
 0   filenames  200 non-null    object
 1   labels     200 non-null    int64 
 2   row        200 non-null    int64 
dtypes: int64(2), object(1)
memory usage: 6.2+ KB
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<pre>None</pre>
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<p>Now that the data is filtered for just our classes, we can save all our images.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">!</span>mkdir ./train
<span class="o">!</span>mkdir ./test
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<pre>mkdir: cannot create directory ‘./train’: File exists
mkdir: cannot create directory ‘./test’: File exists
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<p>In the previous sections we introduced you to several key snippets of code:</p>
<ol>
<li>Grabbing the image data:</li>
</ol>
<div class="highlight"><pre><span></span><span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;data&#39;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
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<ol>
<li>A simple idiom for stacking the image data into the right shape</li>
</ol>
<div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="n">np</span><span class="o">.</span><span class="n">dstack</span><span class="p">((</span>
    <span class="n">row</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">1024</span><span class="p">]</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="n">row</span><span class="p">[</span><span class="mi">1024</span><span class="p">:</span><span class="mi">2048</span><span class="p">]</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="n">row</span><span class="p">[</span><span class="mi">2048</span><span class="p">:]</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="p">))</span>
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<ol>
<li>A simple <code>matplotlib</code> utility for saving images</li>
</ol>
<div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">imsave</span><span class="p">(</span><span class="n">path</span><span class="o">+</span><span class="n">row</span><span class="p">[</span><span class="s1">&#39;filenames&#39;</span><span class="p">],</span> <span class="n">target</span><span class="p">)</span>
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<p>Compose these together into a function that saves all the images into the <code>./test</code> and <code>./train</code> directories. Use the comments in the body of the <code>save_images</code> function below to guide your construction of the function:</p>

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<div class=" highlight hl-ipython3"><pre><span></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">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>

<span class="k">def</span> <span class="nf">save_images</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">df</span><span class="p">,</span> <span class="n">row</span><span class="p">):</span>
    <span class="c1">#Grab the image data in row-major form</span>
    <span class="k">if</span> <span class="n">path</span> <span class="o">==</span> <span class="s1">&#39;train/&#39;</span><span class="p">:</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">dataset_train</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;data&#39;</span><span class="p">][</span><span class="n">row</span><span class="p">]</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">dataset_test</span><span class="p">[</span><span class="sa">b</span><span class="s1">&#39;data&#39;</span><span class="p">][</span><span class="n">row</span><span class="p">]</span>
    
    <span class="c1"># Consolidated stacking/reshaping from earlier</span>
    <span class="n">target</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">dstack</span><span class="p">((</span>
        <span class="n">img</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">1024</span><span class="p">]</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="n">img</span><span class="p">[</span><span class="mi">1024</span><span class="p">:</span><span class="mi">2048</span><span class="p">]</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="n">img</span><span class="p">[</span><span class="mi">2048</span><span class="p">:]</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="p">))</span>
    
    <span class="c1"># Save the image</span>
    <span class="n">filename</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;row&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">row</span><span class="p">][</span><span class="s1">&#39;filenames&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">imsave</span><span class="p">(</span><span class="n">path</span><span class="o">+</span><span class="n">filename</span><span class="p">,</span> <span class="n">target</span><span class="p">)</span>
    
    <span class="c1"># Return any signal data you want for debugging</span>
    <span class="k">return</span>

<span class="c1">## TODO: save ALL images using the save_images function</span>
<span class="c1"># saving train images</span>
<span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">df_train</span><span class="p">[</span><span class="s1">&#39;row&#39;</span><span class="p">]:</span>
    <span class="n">save_images</span><span class="p">(</span><span class="s1">&#39;train/&#39;</span><span class="p">,</span> <span class="n">df_train</span><span class="p">,</span> <span class="n">row</span><span class="p">)</span>
<span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">df_test</span><span class="p">[</span><span class="s1">&#39;row&#39;</span><span class="p">]:</span>
    <span class="n">save_images</span><span class="p">(</span><span class="s1">&#39;test/&#39;</span><span class="p">,</span> <span class="n">df_test</span><span class="p">,</span> <span class="n">row</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_train</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df_train</span><span class="p">[</span><span class="s1">&#39;row&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1023</span><span class="p">,</span> <span class="s1">&#39;filenames&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
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<pre>&#39;ordinary_bicycle_s_000100.png&#39;</pre>
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<h3 id="3.-Load-the-data">3. Load the data<a class="anchor-link" href="#3.-Load-the-data">&#182;</a></h3><p>Now we can load the data into S3.</p>
<p>Using the sagemaker SDK grab the current region, execution role, and bucket.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">sagemaker</span>
<span class="kn">from</span> <span class="nn">sagemaker.session</span> <span class="kn">import</span> <span class="n">Session</span>
<span class="kn">from</span> <span class="nn">sagemaker</span> <span class="kn">import</span> <span class="n">get_execution_role</span>

<span class="n">session</span> <span class="o">=</span> <span class="n">sagemaker</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span>

<span class="n">bucket</span><span class="o">=</span> <span class="n">session</span><span class="o">.</span><span class="n">default_bucket</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Default Bucket: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">bucket</span><span class="p">))</span>

<span class="n">region</span> <span class="o">=</span> <span class="n">session</span><span class="o">.</span><span class="n">boto_region_name</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;AWS Region: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">region</span><span class="p">))</span>

<span class="n">role</span> <span class="o">=</span> <span class="n">get_execution_role</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;RoleArn: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">role</span><span class="p">))</span>
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<pre>Default Bucket: sagemaker-us-east-1-631734214354
AWS Region: us-east-1
RoleArn: arn:aws:iam::631734214354:role/service-role/AmazonSageMaker-ExecutionRole-20220730T200723
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<p>With this data we can easily sync your data up into S3!</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>

<span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s2">&quot;DEFAULT_S3_BUCKET&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">bucket</span>
<span class="o">!</span>aws s3 sync ./train s3://<span class="si">${</span><span class="nv">DEFAULT_S3_BUCKET</span><span class="si">}</span>/train/
<span class="o">!</span>aws s3 sync ./test s3://<span class="si">${</span><span class="nv">DEFAULT_S3_BUCKET</span><span class="si">}</span>/test/
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<pre>upload: train/.ipynb_checkpoints/bicycle_s_000038-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/bicycle_s_000038-checkpoint.png
upload: train/.ipynb_checkpoints/bicycle_s_000156-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/bicycle_s_000156-checkpoint.png
upload: train/.ipynb_checkpoints/bicycle_s_000039-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/bicycle_s_000039-checkpoint.png
upload: train/.ipynb_checkpoints/bicycle_s_000124-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/bicycle_s_000124-checkpoint.png
upload: train/.ipynb_checkpoints/velocipede_s_001200-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/velocipede_s_001200-checkpoint.png
upload: train/.ipynb_checkpoints/bicycle_s_000043-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/bicycle_s_000043-checkpoint.png
upload: train/.ipynb_checkpoints/ordinary_bicycle_s_000205-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/ordinary_bicycle_s_000205-checkpoint.png
upload: train/.ipynb_checkpoints/motorcycle_s_001622-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/motorcycle_s_001622-checkpoint.png
upload: train/bicycle_s_000051.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000051.png
upload: train/.ipynb_checkpoints/ordinary_bicycle_s_000029-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/ordinary_bicycle_s_000029-checkpoint.png
upload: train/.ipynb_checkpoints/motorcycle_s_001287-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/motorcycle_s_001287-checkpoint.png
upload: train/.ipynb_checkpoints/bike_s_000129-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/bike_s_000129-checkpoint.png
upload: train/bicycle_s_000066.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000066.png
upload: train/.ipynb_checkpoints/motorcycle_s_002140-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/motorcycle_s_002140-checkpoint.png
upload: train/.ipynb_checkpoints/bicycle_s_001002-checkpoint.png to s3://sagemaker-us-east-1-631734214354/train/.ipynb_checkpoints/bicycle_s_001002-checkpoint.png
upload: train/bicycle_s_000017.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000017.png
upload: train/bicycle_s_000038.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000038.png
upload: train/bicycle_s_000137.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000137.png
upload: train/bicycle_s_000021.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000021.png
upload: train/bicycle_s_000147.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000147.png
upload: train/bicycle_s_000156.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000156.png
upload: train/bicycle_s_000149.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000149.png
upload: train/bicycle_s_000124.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000124.png
upload: train/bicycle_s_000159.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000159.png
upload: train/bicycle_s_000099.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000099.png
upload: train/bicycle_s_000235.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000235.png
upload: train/bicycle_s_000279.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000279.png
upload: train/bicycle_s_000282.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000282.png
upload: train/bicycle_s_000180.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000180.png
upload: train/bicycle_s_000231.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000231.png
upload: train/bicycle_s_000314.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000314.png
upload: train/bicycle_s_000243.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000243.png
upload: train/bicycle_s_000043.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000043.png
upload: train/bicycle_s_000408.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000408.png
upload: train/bicycle_s_000392.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000392.png
upload: train/bicycle_s_000396.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000396.png
upload: train/bicycle_s_000435.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000435.png
upload: train/bicycle_s_000039.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000039.png
upload: train/bicycle_s_000399.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000399.png
upload: train/bicycle_s_000437.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000437.png
upload: train/bicycle_s_000071.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000071.png
upload: train/bicycle_s_000371.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000371.png
upload: train/bicycle_s_000369.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000369.png
upload: train/bicycle_s_000463.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000463.png
upload: train/bicycle_s_000467.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000467.png
upload: train/bicycle_s_000537.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000537.png
upload: train/bicycle_s_000546.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000546.png
upload: train/bicycle_s_000491.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000491.png
upload: train/bicycle_s_000035.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000035.png
upload: train/bicycle_s_000561.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000561.png
upload: train/bicycle_s_000536.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000536.png
upload: train/bicycle_s_000569.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000569.png
upload: train/bicycle_s_000668.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000668.png
upload: train/bicycle_s_000759.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000759.png
upload: train/bicycle_s_000522.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000522.png
upload: train/bicycle_s_000667.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000667.png
upload: train/bicycle_s_000723.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000723.png
upload: train/bicycle_s_000774.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000774.png
upload: train/bicycle_s_000775.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000775.png
upload: train/bicycle_s_000753.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000753.png
upload: train/bicycle_s_000778.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000778.png
upload: train/bicycle_s_000781.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000781.png
upload: train/bicycle_s_000829.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000829.png
upload: train/bicycle_s_000785.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000785.png
upload: train/bicycle_s_000986.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000986.png
upload: train/bicycle_s_000782.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000782.png
upload: train/bicycle_s_000978.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000978.png
upload: train/bicycle_s_000951.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000951.png
upload: train/bicycle_s_000822.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000822.png
upload: train/bicycle_s_000861.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000861.png
upload: train/bicycle_s_001002.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001002.png
upload: train/bicycle_s_000996.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_000996.png
upload: train/bicycle_s_001168.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001168.png
upload: train/bicycle_s_001111.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001111.png
upload: train/bicycle_s_001203.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001203.png
upload: train/bicycle_s_001247.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001247.png
upload: train/bicycle_s_001245.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001245.png
upload: train/bicycle_s_001205.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001205.png
upload: train/bicycle_s_001338.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001338.png
upload: train/bicycle_s_001348.png to s3://sagemaker-us-east-1-631734214354/train/bicycle_s_001348.png
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upload: test/velocipede_s_000369.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_000369.png
upload: test/velocipede_s_001232.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001232.png
upload: test/velocipede_s_001201.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001201.png
upload: test/velocipede_s_000001.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_000001.png
upload: test/velocipede_s_001277.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001277.png
upload: test/velocipede_s_000863.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_000863.png
upload: test/velocipede_s_000041.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_000041.png
upload: test/velocipede_s_001335.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001335.png
upload: test/velocipede_s_001466.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001466.png
upload: test/velocipede_s_001355.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001355.png
upload: test/velocipede_s_001379.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001379.png
upload: test/velocipede_s_001699.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001699.png
upload: test/velocipede_s_001633.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001633.png
upload: test/velocipede_s_001744.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001744.png
upload: test/velocipede_s_001790.png to s3://sagemaker-us-east-1-631734214354/test/velocipede_s_001790.png
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<p>And that's it! You can check the bucket and verify that the items were uploaded.</p>
<h2 id="Model-Training">Model Training<a class="anchor-link" href="#Model-Training">&#182;</a></h2><p>For Image Classification, Sagemaker <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/image-classification.html">also expects metadata</a> e.g. in the form of TSV files with labels and filepaths. We can generate these using our Pandas DataFrames from earlier:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">to_metadata_file</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">prefix</span><span class="p">):</span>
    <span class="n">df</span><span class="p">[</span><span class="s2">&quot;s3_path&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;filenames&quot;</span><span class="p">]</span>
    <span class="n">df</span><span class="p">[</span><span class="s2">&quot;labels&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;labels&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="mi">0</span> <span class="k">if</span> <span class="n">x</span><span class="o">==</span><span class="mi">8</span> <span class="k">else</span> <span class="mi">1</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">df</span><span class="p">[[</span><span class="s2">&quot;row&quot;</span><span class="p">,</span> <span class="s2">&quot;labels&quot;</span><span class="p">,</span> <span class="s2">&quot;s3_path&quot;</span><span class="p">]]</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span>
        <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">prefix</span><span class="si">}</span><span class="s2">.lst&quot;</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s2">&quot;</span><span class="se">\t</span><span class="s2">&quot;</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">False</span>
    <span class="p">)</span>
    
<span class="n">to_metadata_file</span><span class="p">(</span><span class="n">df_train</span><span class="o">.</span><span class="n">copy</span><span class="p">(),</span> <span class="s2">&quot;train&quot;</span><span class="p">)</span>
<span class="n">to_metadata_file</span><span class="p">(</span><span class="n">df_test</span><span class="o">.</span><span class="n">copy</span><span class="p">(),</span> <span class="s2">&quot;test&quot;</span><span class="p">)</span>
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<p>We can also upload our manifest files:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">boto3</span>

<span class="c1"># Upload files</span>
<span class="n">boto3</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span><span class="o">.</span><span class="n">resource</span><span class="p">(</span><span class="s1">&#39;s3&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">Bucket</span><span class="p">(</span>
    <span class="n">bucket</span><span class="p">)</span><span class="o">.</span><span class="n">Object</span><span class="p">(</span><span class="s1">&#39;train.lst&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">upload_file</span><span class="p">(</span><span class="s1">&#39;./train.lst&#39;</span><span class="p">)</span>
<span class="n">boto3</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span><span class="o">.</span><span class="n">resource</span><span class="p">(</span><span class="s1">&#39;s3&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">Bucket</span><span class="p">(</span>
    <span class="n">bucket</span><span class="p">)</span><span class="o">.</span><span class="n">Object</span><span class="p">(</span><span class="s1">&#39;test.lst&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">upload_file</span><span class="p">(</span><span class="s1">&#39;./test.lst&#39;</span><span class="p">)</span>
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<p>Using the <code>bucket</code> and <code>region</code> info we can get the latest prebuilt container to run our training job, and define an output location on our s3 bucket for the model. Use the <code>image_uris</code> function from the SageMaker SDK to retrieve the latest <code>image-classification</code> image below:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Use the image_uris function to retrieve the latest &#39;image-classification&#39; image</span>
<span class="kn">from</span> <span class="nn">sagemaker</span> <span class="kn">import</span> <span class="n">image_uris</span>

<span class="n">algo_image</span> <span class="o">=</span> <span class="n">image_uris</span><span class="o">.</span><span class="n">retrieve</span><span class="p">(</span><span class="n">framework</span><span class="o">=</span><span class="s1">&#39;image-classification&#39;</span><span class="p">,</span> <span class="n">region</span><span class="o">=</span><span class="n">region</span><span class="p">,</span> <span class="n">version</span><span class="o">=</span><span class="s1">&#39;latest&#39;</span><span class="p">)</span>
<span class="n">s3_output_location</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;s3://</span><span class="si">{</span><span class="n">bucket</span><span class="si">}</span><span class="s2">/models/image_model&quot;</span>
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<pre>Defaulting to the only supported framework/algorithm version: 1. Ignoring framework/algorithm version: latest.
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<p>We're ready to create an estimator! Create an estimator <code>img_classifier_model</code> that uses one instance of <code>ml.p3.2xlarge</code>. Ensure that y ou use the output location we defined above - we'll be referring to that later!</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">img_classifier_model</span><span class="o">=</span><span class="n">sagemaker</span><span class="o">.</span><span class="n">estimator</span><span class="o">.</span><span class="n">Estimator</span><span class="p">(</span>
    <span class="n">image_uri</span><span class="o">=</span><span class="n">algo_image</span><span class="p">,</span>
    <span class="n">role</span><span class="o">=</span><span class="n">role</span><span class="p">,</span>
    <span class="n">instance_count</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
    <span class="n">instance_type</span><span class="o">=</span><span class="s1">&#39;ml.p3.2xlarge&#39;</span><span class="p">,</span>
    <span class="n">output_path</span><span class="o">=</span><span class="n">s3_output_location</span><span class="p">,</span>
    <span class="n">sagemaker_session</span><span class="o">=</span><span class="n">session</span>
    
<span class="p">)</span>
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<p>We can also set a few key hyperparameters and define the inputs for our model:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">img_classifier_model</span><span class="o">.</span><span class="n">set_hyperparameters</span><span class="p">(</span>
    <span class="n">image_shape</span><span class="o">=</span> <span class="s1">&#39;3,32,32&#39;</span><span class="p">,</span> <span class="c1"># TODO: Fill in</span>
    <span class="n">num_classes</span><span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">df_train</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">])),</span> <span class="c1"># TODO: Fill in</span>
    <span class="n">num_training_samples</span><span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">df_train</span><span class="p">)</span><span class="c1"># TODO: fill in</span>
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<p>The <code>image-classification</code> image uses four input channels with very specific input parameters. For convenience, we've provided them below:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sagemaker.debugger</span> <span class="kn">import</span> <span class="n">Rule</span><span class="p">,</span> <span class="n">rule_configs</span>
<span class="kn">from</span> <span class="nn">sagemaker.session</span> <span class="kn">import</span> <span class="n">TrainingInput</span>
<span class="n">model_inputs</span> <span class="o">=</span> <span class="p">{</span>
        <span class="s2">&quot;train&quot;</span><span class="p">:</span> <span class="n">sagemaker</span><span class="o">.</span><span class="n">inputs</span><span class="o">.</span><span class="n">TrainingInput</span><span class="p">(</span>
            <span class="n">s3_data</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;s3://</span><span class="si">{</span><span class="n">bucket</span><span class="si">}</span><span class="s2">/train/&quot;</span><span class="p">,</span>
            <span class="n">content_type</span><span class="o">=</span><span class="s2">&quot;application/x-image&quot;</span>
        <span class="p">),</span>
        <span class="s2">&quot;validation&quot;</span><span class="p">:</span> <span class="n">sagemaker</span><span class="o">.</span><span class="n">inputs</span><span class="o">.</span><span class="n">TrainingInput</span><span class="p">(</span>
            <span class="n">s3_data</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;s3://</span><span class="si">{</span><span class="n">bucket</span><span class="si">}</span><span class="s2">/test/&quot;</span><span class="p">,</span>
            <span class="n">content_type</span><span class="o">=</span><span class="s2">&quot;application/x-image&quot;</span>
        <span class="p">),</span>
        <span class="s2">&quot;train_lst&quot;</span><span class="p">:</span> <span class="n">sagemaker</span><span class="o">.</span><span class="n">inputs</span><span class="o">.</span><span class="n">TrainingInput</span><span class="p">(</span>
            <span class="n">s3_data</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;s3://</span><span class="si">{</span><span class="n">bucket</span><span class="si">}</span><span class="s2">/train.lst&quot;</span><span class="p">,</span>
            <span class="n">content_type</span><span class="o">=</span><span class="s2">&quot;application/x-image&quot;</span>
        <span class="p">),</span>
        <span class="s2">&quot;validation_lst&quot;</span><span class="p">:</span> <span class="n">sagemaker</span><span class="o">.</span><span class="n">inputs</span><span class="o">.</span><span class="n">TrainingInput</span><span class="p">(</span>
            <span class="n">s3_data</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;s3://</span><span class="si">{</span><span class="n">bucket</span><span class="si">}</span><span class="s2">/test.lst&quot;</span><span class="p">,</span>
            <span class="n">content_type</span><span class="o">=</span><span class="s2">&quot;application/x-image&quot;</span>
        <span class="p">)</span>
<span class="p">}</span>
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<p>Great, now we can train the model using the model_inputs. In the cell below, call the <code>fit</code> method on our model,:</p>

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<span class="n">img_classifier_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">model_inputs</span><span class="p">)</span>
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<pre>2022-08-26 12:13:11 Starting - Starting the training job...
2022-08-26 12:13:37 Starting - Preparing the instances for trainingProfilerReport-1661515991: InProgress
.........
2022-08-26 12:14:55 Downloading - Downloading input data...
2022-08-26 12:15:36 Training - Downloading the training image............
2022-08-26 12:17:41 Training - Training image download completed. Training in progress..<span class="ansi-blue-fg">Docker entrypoint called with argument(s): train</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Reading default configuration from /opt/amazon/lib/python3.7/site-packages/image_classification/default-input.json: {&#39;use_pretrained_model&#39;: 0, &#39;num_layers&#39;: 152, &#39;epochs&#39;: 30, &#39;learning_rate&#39;: 0.1, &#39;lr_scheduler_factor&#39;: 0.1, &#39;optimizer&#39;: &#39;sgd&#39;, &#39;momentum&#39;: 0, &#39;weight_decay&#39;: 0.0001, &#39;beta_1&#39;: 0.9, &#39;beta_2&#39;: 0.999, &#39;eps&#39;: 1e-08, &#39;gamma&#39;: 0.9, &#39;mini_batch_size&#39;: 32, &#39;image_shape&#39;: &#39;3,224,224&#39;, &#39;precision_dtype&#39;: &#39;float32&#39;}</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Merging with provided configuration from /opt/ml/input/config/hyperparameters.json: {&#39;image_shape&#39;: &#39;3,32,32&#39;, &#39;num_classes&#39;: &#39;2&#39;, &#39;num_training_samples&#39;: &#39;1000&#39;}</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Final configuration: {&#39;use_pretrained_model&#39;: 0, &#39;num_layers&#39;: 152, &#39;epochs&#39;: 30, &#39;learning_rate&#39;: 0.1, &#39;lr_scheduler_factor&#39;: 0.1, &#39;optimizer&#39;: &#39;sgd&#39;, &#39;momentum&#39;: 0, &#39;weight_decay&#39;: 0.0001, &#39;beta_1&#39;: 0.9, &#39;beta_2&#39;: 0.999, &#39;eps&#39;: 1e-08, &#39;gamma&#39;: 0.9, &#39;mini_batch_size&#39;: 32, &#39;image_shape&#39;: &#39;3,32,32&#39;, &#39;precision_dtype&#39;: &#39;float32&#39;, &#39;num_classes&#39;: &#39;2&#39;, &#39;num_training_samples&#39;: &#39;1000&#39;}</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Searching for .lst files in /opt/ml/input/data/train_lst.</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Creating record files for train.lst</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Done creating record files...</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Searching for .lst files in /opt/ml/input/data/validation_lst.</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Creating record files for test.lst</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Done creating record files...</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] use_pretrained_model: 0</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] multi_label: 0</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Performing random weight initialization</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] ---- Parameters ----</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] num_layers: 152</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] data type: &lt;class &#39;numpy.float32&#39;&gt;</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] epochs: 30</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] optimizer: sgd</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] momentum: 0.9</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] weight_decay: 0.0001</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] learning_rate: 0.1</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] num_training_samples: 1000</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] mini_batch_size: 32</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] image_shape: 3,32,32</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] num_classes: 2</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] augmentation_type: None</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] kv_store: device</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] checkpoint_frequency not set, will store the best model</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] --------------------</span>
<span class="ansi-blue-fg">[08/26/2022 12:17:47 INFO 140175355221824] Setting number of threads: 7</span>
<span class="ansi-blue-fg">[12:17:58] /opt/brazil-pkg-cache/packages/AIAlgorithmsMXNet/AIAlgorithmsMXNet-1.4.x_ecl_Cuda_11.1.x.19.0/AL2_x86_64/generic-flavor/src/src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (setting env variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:04 INFO 140175355221824] Epoch[0] Batch [20]#011Speed: 110.821 samples/sec#011accuracy=0.556548</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:06 INFO 140175355221824] Epoch[0] Train-accuracy=0.586694</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:06 INFO 140175355221824] Epoch[0] Time cost=7.529</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:06 INFO 140175355221824] Epoch[0] Validation-accuracy=0.505208</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:06 INFO 140175355221824] Storing the best model with validation accuracy: 0.505208</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:07 INFO 140175355221824] Saved checkpoint to &#34;/opt/ml/model/image-classification-0001.params&#34;</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:10 INFO 140175355221824] Epoch[1] Batch [20]#011Speed: 172.385 samples/sec#011accuracy=0.657738</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:12 INFO 140175355221824] Epoch[1] Train-accuracy=0.671371</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:12 INFO 140175355221824] Epoch[1] Time cost=5.431</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:13 INFO 140175355221824] Epoch[1] Validation-accuracy=0.625000</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:13 INFO 140175355221824] Storing the best model with validation accuracy: 0.625000</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:13 INFO 140175355221824] Saved checkpoint to &#34;/opt/ml/model/image-classification-0002.params&#34;</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:17 INFO 140175355221824] Epoch[2] Batch [20]#011Speed: 181.412 samples/sec#011accuracy=0.703869</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:19 INFO 140175355221824] Epoch[2] Train-accuracy=0.695565</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:19 INFO 140175355221824] Epoch[2] Time cost=5.251</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:19 INFO 140175355221824] Epoch[2] Validation-accuracy=0.572917</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:23 INFO 140175355221824] Epoch[3] Batch [20]#011Speed: 182.586 samples/sec#011accuracy=0.715774</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:25 INFO 140175355221824] Epoch[3] Train-accuracy=0.729839</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:25 INFO 140175355221824] Epoch[3] Time cost=5.227</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:25 INFO 140175355221824] Epoch[3] Validation-accuracy=0.812500</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:26 INFO 140175355221824] Storing the best model with validation accuracy: 0.812500</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:26 INFO 140175355221824] Saved checkpoint to &#34;/opt/ml/model/image-classification-0004.params&#34;</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:30 INFO 140175355221824] Epoch[4] Batch [20]#011Speed: 180.911 samples/sec#011accuracy=0.769345</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:31 INFO 140175355221824] Epoch[4] Train-accuracy=0.759073</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:31 INFO 140175355221824] Epoch[4] Time cost=5.263</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:32 INFO 140175355221824] Epoch[4] Validation-accuracy=0.838542</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:32 INFO 140175355221824] Storing the best model with validation accuracy: 0.838542</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:33 INFO 140175355221824] Saved checkpoint to &#34;/opt/ml/model/image-classification-0005.params&#34;</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:36 INFO 140175355221824] Epoch[5] Batch [20]#011Speed: 180.664 samples/sec#011accuracy=0.781250</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:38 INFO 140175355221824] Epoch[5] Train-accuracy=0.773185</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:38 INFO 140175355221824] Epoch[5] Time cost=5.281</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:39 INFO 140175355221824] Epoch[5] Validation-accuracy=0.833333</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:43 INFO 140175355221824] Epoch[6] Batch [20]#011Speed: 181.701 samples/sec#011accuracy=0.806548</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:44 INFO 140175355221824] Epoch[6] Train-accuracy=0.801411</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:44 INFO 140175355221824] Epoch[6] Time cost=5.245</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:45 INFO 140175355221824] Epoch[6] Validation-accuracy=0.828125</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:49 INFO 140175355221824] Epoch[7] Batch [20]#011Speed: 181.774 samples/sec#011accuracy=0.818452</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:51 INFO 140175355221824] Epoch[7] Train-accuracy=0.822581</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:51 INFO 140175355221824] Epoch[7] Time cost=5.228</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:51 INFO 140175355221824] Epoch[7] Validation-accuracy=0.803571</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:55 INFO 140175355221824] Epoch[8] Batch [20]#011Speed: 183.099 samples/sec#011accuracy=0.806548</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:57 INFO 140175355221824] Epoch[8] Train-accuracy=0.802419</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:57 INFO 140175355221824] Epoch[8] Time cost=5.204</span>
<span class="ansi-blue-fg">[08/26/2022 12:18:57 INFO 140175355221824] Epoch[8] Validation-accuracy=0.807292</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:01 INFO 140175355221824] Epoch[9] Batch [20]#011Speed: 180.868 samples/sec#011accuracy=0.809524</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:03 INFO 140175355221824] Epoch[9] Train-accuracy=0.820565</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:03 INFO 140175355221824] Epoch[9] Time cost=5.313</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:04 INFO 140175355221824] Epoch[9] Validation-accuracy=0.843750</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:04 INFO 140175355221824] Storing the best model with validation accuracy: 0.843750</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:05 INFO 140175355221824] Saved checkpoint to &#34;/opt/ml/model/image-classification-0010.params&#34;</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:08 INFO 140175355221824] Epoch[10] Batch [20]#011Speed: 181.405 samples/sec#011accuracy=0.843750</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:10 INFO 140175355221824] Epoch[10] Train-accuracy=0.836694</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:10 INFO 140175355221824] Epoch[10] Time cost=5.278</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:10 INFO 140175355221824] Epoch[10] Validation-accuracy=0.750000</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:14 INFO 140175355221824] Epoch[11] Batch [20]#011Speed: 183.122 samples/sec#011accuracy=0.831845</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:16 INFO 140175355221824] Epoch[11] Train-accuracy=0.826613</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:16 INFO 140175355221824] Epoch[11] Time cost=5.226</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:17 INFO 140175355221824] Epoch[11] Validation-accuracy=0.781250</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:21 INFO 140175355221824] Epoch[12] Batch [20]#011Speed: 180.269 samples/sec#011accuracy=0.864583</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:22 INFO 140175355221824] Epoch[12] Train-accuracy=0.868952</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:22 INFO 140175355221824] Epoch[12] Time cost=5.262</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:23 INFO 140175355221824] Epoch[12] Validation-accuracy=0.796875</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:27 INFO 140175355221824] Epoch[13] Batch [20]#011Speed: 182.525 samples/sec#011accuracy=0.855655</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:29 INFO 140175355221824] Epoch[13] Train-accuracy=0.860887</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:29 INFO 140175355221824] Epoch[13] Time cost=5.233</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:29 INFO 140175355221824] Epoch[13] Validation-accuracy=0.848958</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:29 INFO 140175355221824] Storing the best model with validation accuracy: 0.848958</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:30 INFO 140175355221824] Saved checkpoint to &#34;/opt/ml/model/image-classification-0014.params&#34;</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:33 INFO 140175355221824] Epoch[14] Batch [20]#011Speed: 182.793 samples/sec#011accuracy=0.903274</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:35 INFO 140175355221824] Epoch[14] Train-accuracy=0.893145</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:35 INFO 140175355221824] Epoch[14] Time cost=5.207</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:36 INFO 140175355221824] Epoch[14] Validation-accuracy=0.802083</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:40 INFO 140175355221824] Epoch[15] Batch [20]#011Speed: 183.580 samples/sec#011accuracy=0.879464</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:41 INFO 140175355221824] Epoch[15] Train-accuracy=0.871976</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:41 INFO 140175355221824] Epoch[15] Time cost=5.200</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:42 INFO 140175355221824] Epoch[15] Validation-accuracy=0.830357</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:46 INFO 140175355221824] Epoch[16] Batch [20]#011Speed: 180.891 samples/sec#011accuracy=0.909226</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:48 INFO 140175355221824] Epoch[16] Train-accuracy=0.894153</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:48 INFO 140175355221824] Epoch[16] Time cost=5.254</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:48 INFO 140175355221824] Epoch[16] Validation-accuracy=0.838542</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:52 INFO 140175355221824] Epoch[17] Batch [20]#011Speed: 182.791 samples/sec#011accuracy=0.937500</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:54 INFO 140175355221824] Epoch[17] Train-accuracy=0.933468</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:54 INFO 140175355221824] Epoch[17] Time cost=5.224</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:54 INFO 140175355221824] Epoch[17] Validation-accuracy=0.869792</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:55 INFO 140175355221824] Storing the best model with validation accuracy: 0.869792</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:55 INFO 140175355221824] Saved checkpoint to &#34;/opt/ml/model/image-classification-0018.params&#34;</span>
<span class="ansi-blue-fg">[08/26/2022 12:19:59 INFO 140175355221824] Epoch[18] Batch [20]#011Speed: 182.888 samples/sec#011accuracy=0.897321</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:00 INFO 140175355221824] Epoch[18] Train-accuracy=0.912298</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:00 INFO 140175355221824] Epoch[18] Time cost=5.217</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:01 INFO 140175355221824] Epoch[18] Validation-accuracy=0.828125</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:05 INFO 140175355221824] Epoch[19] Batch [20]#011Speed: 177.204 samples/sec#011accuracy=0.938988</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:07 INFO 140175355221824] Epoch[19] Train-accuracy=0.936492</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:07 INFO 140175355221824] Epoch[19] Time cost=5.364</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:07 INFO 140175355221824] Epoch[19] Validation-accuracy=0.830357</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:11 INFO 140175355221824] Epoch[20] Batch [20]#011Speed: 181.377 samples/sec#011accuracy=0.946429</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:13 INFO 140175355221824] Epoch[20] Train-accuracy=0.945565</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:13 INFO 140175355221824] Epoch[20] Time cost=5.254</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:14 INFO 140175355221824] Epoch[20] Validation-accuracy=0.822917</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:18 INFO 140175355221824] Epoch[21] Batch [20]#011Speed: 183.173 samples/sec#011accuracy=0.936012</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:19 INFO 140175355221824] Epoch[21] Train-accuracy=0.929435</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:19 INFO 140175355221824] Epoch[21] Time cost=5.216</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:20 INFO 140175355221824] Epoch[21] Validation-accuracy=0.760417</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:24 INFO 140175355221824] Epoch[22] Batch [20]#011Speed: 182.764 samples/sec#011accuracy=0.952381</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:26 INFO 140175355221824] Epoch[22] Train-accuracy=0.941532</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:26 INFO 140175355221824] Epoch[22] Time cost=5.231</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:26 INFO 140175355221824] Epoch[22] Validation-accuracy=0.843750</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:30 INFO 140175355221824] Epoch[23] Batch [20]#011Speed: 181.994 samples/sec#011accuracy=0.956845</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:32 INFO 140175355221824] Epoch[23] Train-accuracy=0.949597</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:32 INFO 140175355221824] Epoch[23] Time cost=5.232</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:32 INFO 140175355221824] Epoch[23] Validation-accuracy=0.830357</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:36 INFO 140175355221824] Epoch[24] Batch [20]#011Speed: 182.436 samples/sec#011accuracy=0.949405</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:38 INFO 140175355221824] Epoch[24] Train-accuracy=0.949597</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:38 INFO 140175355221824] Epoch[24] Time cost=5.223</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:39 INFO 140175355221824] Epoch[24] Validation-accuracy=0.838542</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:43 INFO 140175355221824] Epoch[25] Batch [20]#011Speed: 182.122 samples/sec#011accuracy=0.958333</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:44 INFO 140175355221824] Epoch[25] Train-accuracy=0.959677</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:44 INFO 140175355221824] Epoch[25] Time cost=5.231</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:45 INFO 140175355221824] Epoch[25] Validation-accuracy=0.828125</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:49 INFO 140175355221824] Epoch[26] Batch [20]#011Speed: 179.580 samples/sec#011accuracy=0.964286</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:51 INFO 140175355221824] Epoch[26] Train-accuracy=0.967742</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:51 INFO 140175355221824] Epoch[26] Time cost=5.270</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:51 INFO 140175355221824] Epoch[26] Validation-accuracy=0.822917</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:55 INFO 140175355221824] Epoch[27] Batch [20]#011Speed: 183.191 samples/sec#011accuracy=0.979167</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:57 INFO 140175355221824] Epoch[27] Train-accuracy=0.973790</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:57 INFO 140175355221824] Epoch[27] Time cost=5.222</span>
<span class="ansi-blue-fg">[08/26/2022 12:20:57 INFO 140175355221824] Epoch[27] Validation-accuracy=0.825893</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:02 INFO 140175355221824] Epoch[28] Batch [20]#011Speed: 179.620 samples/sec#011accuracy=0.962798</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:03 INFO 140175355221824] Epoch[28] Train-accuracy=0.959677</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:03 INFO 140175355221824] Epoch[28] Time cost=5.357</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:04 INFO 140175355221824] Epoch[28] Validation-accuracy=0.875000</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:04 INFO 140175355221824] Storing the best model with validation accuracy: 0.875000</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:05 INFO 140175355221824] Saved checkpoint to &#34;/opt/ml/model/image-classification-0029.params&#34;</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:08 INFO 140175355221824] Epoch[29] Batch [20]#011Speed: 183.270 samples/sec#011accuracy=0.989583</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:10 INFO 140175355221824] Epoch[29] Train-accuracy=0.988911</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:10 INFO 140175355221824] Epoch[29] Time cost=5.225</span>
<span class="ansi-blue-fg">[08/26/2022 12:21:10 INFO 140175355221824] Epoch[29] Validation-accuracy=0.828125</span>

2022-08-26 12:21:37 Uploading - Uploading generated training model
2022-08-26 12:22:17 Completed - Training job completed
ProfilerReport-1661515991: NoIssuesFound
Training seconds: 438
Billable seconds: 438
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<p>If all goes well, you'll end up with a model topping out above <code>.8</code> validation accuracy. With only 1000 training samples in the CIFAR dataset, that's pretty good. We could definitely pursue data augmentation &amp; gathering more samples to help us improve further, but for now let's proceed to deploy our model.</p>
<h3 id="Getting-ready-to-deploy">Getting ready to deploy<a class="anchor-link" href="#Getting-ready-to-deploy">&#182;</a></h3><p>To begin with, let's configure Model Monitor to track our deployment. We'll define a <code>DataCaptureConfig</code> below:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sagemaker.model_monitor</span> <span class="kn">import</span> <span class="n">DataCaptureConfig</span>

<span class="n">data_capture_config</span> <span class="o">=</span> <span class="n">DataCaptureConfig</span><span class="p">(</span>
    <span class="c1">## TODO: Set config options</span>
    <span class="n">enable_capture</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
    <span class="n">sampling_percentage</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span>
    <span class="n">destination_s3_uri</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;s3://</span><span class="si">{</span><span class="n">bucket</span><span class="si">}</span><span class="s2">/data_capture&quot;</span>
<span class="p">)</span>
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<p>Note the <code>destination_s3_uri</code> parameter: At the end of the project, we can explore the <code>data_capture</code> directory in S3 to find crucial data about the inputs and outputs Model Monitor has observed on our model endpoint over time.</p>
<p>With that done, deploy your model on a single <code>ml.m5.xlarge</code> instance with the data capture config attached:</p>

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<h4 id="Load-the-trained-model">Load the trained model<a class="anchor-link" href="#Load-the-trained-model">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">sagemaker</span>

<span class="n">img_classifier_model</span> <span class="o">=</span> <span class="n">sagemaker</span><span class="o">.</span><span class="n">estimator</span><span class="o">.</span><span class="n">Estimator</span><span class="o">.</span><span class="n">attach</span><span class="p">(</span><span class="s1">&#39;image-classification-2022-08-26-12-13-11-840&#39;</span><span class="p">)</span>
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<pre>
2022-08-26 12:22:17 Starting - Preparing the instances for training
2022-08-26 12:22:17 Downloading - Downloading input data
2022-08-26 12:22:17 Training - Training image download completed. Training in progress.
2022-08-26 12:22:17 Uploading - Uploading generated training model
2022-08-26 12:22:17 Completed - Training job completed
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">img_classifier_model</span><span class="p">)</span>
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<pre>&lt;sagemaker.estimator.Estimator object at 0x7fa2bdb5a1c0&gt;
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<h4 id="Deploying-the-model">Deploying the model<a class="anchor-link" href="#Deploying-the-model">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">deployment</span> <span class="o">=</span> <span class="n">img_classifier_model</span><span class="o">.</span><span class="n">deploy</span><span class="p">(</span>
    <span class="c1">## TODO: fill in deployment options</span>
    <span class="n">initial_instance_count</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">instance_type</span><span class="o">=</span><span class="s2">&quot;ml.m5.xlarge&quot;</span><span class="p">,</span>
    <span class="n">data_capture_config</span><span class="o">=</span><span class="n">data_capture_config</span><span class="p">,</span>
    <span class="n">endpoint_name</span><span class="o">=</span><span class="s1">&#39;image-classification-model-endpoint&#39;</span>
    <span class="p">)</span>

<span class="n">endpoint</span> <span class="o">=</span> <span class="n">deployment</span><span class="o">.</span><span class="n">endpoint_name</span>
<span class="nb">print</span><span class="p">(</span><span class="n">endpoint</span><span class="p">)</span>
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<pre>---------------!image-classification-model-endpoint
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<pre>&lt;sagemaker.model.Model object at 0x7fe6469cd070&gt;
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<p>Note the endpoint name for later as well.</p>
<p>Next, instantiate a Predictor:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sagemaker.predictor</span> <span class="kn">import</span> <span class="n">Predictor</span>

<span class="n">predictor</span> <span class="o">=</span> <span class="n">Predictor</span><span class="p">(</span><span class="n">endpoint</span><span class="p">)</span>
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<p>In the code snippet below we are going to prepare one of your saved images for prediction. Use the predictor to process the <code>payload</code>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sagemaker.serializers</span> <span class="kn">import</span> <span class="n">IdentitySerializer</span>
<span class="kn">import</span> <span class="nn">base64</span>

<span class="n">predictor</span><span class="o">.</span><span class="n">serializer</span> <span class="o">=</span> <span class="n">IdentitySerializer</span><span class="p">(</span><span class="s2">&quot;image/png&quot;</span><span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;./test/bicycle_s_001789.png&quot;</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">payload</span> <span class="o">=</span> <span class="n">f</span><span class="o">.</span><span class="n">read</span><span class="p">()</span>

    
<span class="n">inference</span> <span class="o">=</span> <span class="n">predictor</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">payload</span><span class="p">)</span>
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<p>Your <code>inference</code> object is an array of two values, the predicted probability value for each of your classes (bicycle and motorcycle respectively.) So, for example, a value of <code>b'[0.91, 0.09]'</code> indicates the probability of being a bike is 91% and being a motorcycle is 9%.</p>

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<pre>b&#39;[0.9999560117721558, 4.4019066990586e-05]&#39;
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<h3 id="Draft-Lambdas-and-Step-Function-Workflow">Draft Lambdas and Step Function Workflow<a class="anchor-link" href="#Draft-Lambdas-and-Step-Function-Workflow">&#182;</a></h3><p>Your operations team uses Step Functions to orchestrate serverless workflows. One of the nice things about Step Functions is that <a href="https://docs.aws.amazon.com/step-functions/latest/dg/connect-stepfunctions.html">workflows can call other workflows</a>, so the team can easily plug your workflow into the broader production architecture for Scones Unlimited.</p>
<p>In this next stage you're going to write and deploy three Lambda functions, and then use the Step Functions visual editor to chain them together! Our functions are going to work with a simple data object:</p>
<div class="highlight"><pre><span></span><span class="p">{</span>
    <span class="s2">&quot;inferences&quot;</span><span class="p">:</span> <span class="p">[],</span> <span class="c1"># Output of predictor.predict</span>
    <span class="s2">&quot;s3_key&quot;</span><span class="p">:</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="c1"># Source data S3 key</span>
    <span class="s2">&quot;s3_bucket&quot;</span><span class="p">:</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="c1"># Source data S3 bucket</span>
    <span class="s2">&quot;image_data&quot;</span><span class="p">:</span> <span class="s2">&quot;&quot;</span>  <span class="c1"># base64 encoded string containing the image data</span>
<span class="p">}</span>
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<p>A good test object that you can use for Lambda tests and Step Function executions, throughout the next section, might look like this:</p>
<div class="highlight"><pre><span></span><span class="p">{</span>
  <span class="s2">&quot;image_data&quot;</span><span class="p">:</span> <span class="s2">&quot;&quot;</span><span class="p">,</span>
  <span class="s2">&quot;s3_bucket&quot;</span><span class="p">:</span> <span class="n">MY_BUCKET_NAME</span><span class="p">,</span> <span class="c1"># Fill in with your bucket</span>
  <span class="s2">&quot;s3_key&quot;</span><span class="p">:</span> <span class="s2">&quot;test/bicycle_s_000513.png&quot;</span>
<span class="p">}</span>
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<p>Using these fields, your functions can read and write the necessary data to execute your workflow. Let's start with the first function. Your first Lambda function will copy an object from S3, base64 encode it, and then return it to the step function as <code>image_data</code> in an event.</p>
<p>Go to the Lambda dashboard and create a new Lambda function with a descriptive name like "serializeImageData" and select thr 'Python 3.8' runtime. Add the same permissions as the SageMaker role you created earlier. (Reminder: you do this in the Configuration tab under "Permissions"). Once you're ready, use the starter code below to craft your Lambda handler:</p>
<div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">json</span>
<span class="kn">import</span> <span class="nn">boto3</span>
<span class="kn">import</span> <span class="nn">base64</span>

<span class="n">s3</span> <span class="o">=</span> <span class="n">boto3</span><span class="o">.</span><span class="n">client</span><span class="p">(</span><span class="s1">&#39;s3&#39;</span><span class="p">)</span>

<span class="k">def</span> <span class="nf">lambda_handler</span><span class="p">(</span><span class="n">event</span><span class="p">,</span> <span class="n">context</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;A function to serialize target data from S3&quot;&quot;&quot;</span>

    <span class="c1"># Get the s3 address from the Step Function event input</span>
    <span class="n">key</span> <span class="o">=</span> <span class="c1">## TODO: fill in</span>
    <span class="n">bucket</span> <span class="o">=</span> <span class="c1">## TODO: fill in</span>

    <span class="c1"># Download the data from s3 to /tmp/image.png</span>
    <span class="c1">## TODO: fill in</span>

    <span class="c1"># We read the data from a file</span>
    <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;/tmp/image.png&quot;</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
        <span class="n">image_data</span> <span class="o">=</span> <span class="n">base64</span><span class="o">.</span><span class="n">b64encode</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">read</span><span class="p">())</span>

    <span class="c1"># Pass the data back to the Step Function</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Event:&quot;</span><span class="p">,</span> <span class="n">event</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
    <span class="k">return</span> <span class="p">{</span>
        <span class="s1">&#39;statusCode&#39;</span><span class="p">:</span> <span class="mi">200</span><span class="p">,</span>
        <span class="s1">&#39;body&#39;</span><span class="p">:</span> <span class="p">{</span>
            <span class="s2">&quot;image_data&quot;</span><span class="p">:</span> <span class="n">image_data</span><span class="p">,</span>
            <span class="s2">&quot;s3_bucket&quot;</span><span class="p">:</span> <span class="n">bucket</span><span class="p">,</span>
            <span class="s2">&quot;s3_key&quot;</span><span class="p">:</span> <span class="n">key</span><span class="p">,</span>
            <span class="s2">&quot;inferences&quot;</span><span class="p">:</span> <span class="p">[]</span>
        <span class="p">}</span>
    <span class="p">}</span>
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<p>The next function is responsible for the classification part - we're going to take the image output from the previous function, decode it, and then pass inferences back to the the Step Function.</p>
<p>Because this Lambda will have runtime dependencies (i.e. the SageMaker SDK) you'll need to package them in your function. <em>Key reading:</em> <a href="https://docs.aws.amazon.com/lambda/latest/dg/python-package-create.html#python-package-create-with-dependency">https://docs.aws.amazon.com/lambda/latest/dg/python-package-create.html#python-package-create-with-dependency</a></p>
<p>Create a new Lambda function with the same rights and a descriptive name, then fill in the starter code below for your classifier Lambda.</p>
<div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">json</span>
<span class="kn">import</span> <span class="nn">sagemaker</span>
<span class="kn">import</span> <span class="nn">base64</span>
<span class="kn">from</span> <span class="nn">sagemaker.serializers</span> <span class="kn">import</span> <span class="n">IdentitySerializer</span>

<span class="c1"># Fill this in with the name of your deployed model</span>
<span class="n">ENDPOINT</span> <span class="o">=</span> <span class="c1">## TODO: fill in</span>

<span class="k">def</span> <span class="nf">lambda_handler</span><span class="p">(</span><span class="n">event</span><span class="p">,</span> <span class="n">context</span><span class="p">):</span>

    <span class="c1"># Decode the image data</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">base64</span><span class="o">.</span><span class="n">b64decode</span><span class="p">(</span><span class="c1">## TODO: fill in)</span>

    <span class="c1"># Instantiate a Predictor</span>
    <span class="n">predictor</span> <span class="o">=</span> <span class="c1">## TODO: fill in</span>

    <span class="c1"># For this model the IdentitySerializer needs to be &quot;image/png&quot;</span>
    <span class="n">predictor</span><span class="o">.</span><span class="n">serializer</span> <span class="o">=</span> <span class="n">IdentitySerializer</span><span class="p">(</span><span class="s2">&quot;image/png&quot;</span><span class="p">)</span>

    <span class="c1"># Make a prediction:</span>
    <span class="n">inferences</span> <span class="o">=</span> <span class="c1">## TODO: fill in</span>

    <span class="c1"># We return the data back to the Step Function    </span>
    <span class="n">event</span><span class="p">[</span><span class="s2">&quot;inferences&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">inferences</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s1">&#39;utf-8&#39;</span><span class="p">)</span>
    <span class="k">return</span> <span class="p">{</span>
        <span class="s1">&#39;statusCode&#39;</span><span class="p">:</span> <span class="mi">200</span><span class="p">,</span>
        <span class="s1">&#39;body&#39;</span><span class="p">:</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">event</span><span class="p">)</span>
    <span class="p">}</span>
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<p>Finally, we need to filter low-confidence inferences. Define a threshold between 1.00 and 0.000 for your model: what is reasonble for you? If the model predicts at <code>.70</code> for it's highest confidence label, do we want to pass that inference along to downstream systems? Make one last Lambda function and tee up the same permissions:</p>
<div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">json</span>


<span class="n">THRESHOLD</span> <span class="o">=</span> <span class="o">.</span><span class="mi">93</span>


<span class="k">def</span> <span class="nf">lambda_handler</span><span class="p">(</span><span class="n">event</span><span class="p">,</span> <span class="n">context</span><span class="p">):</span>

    <span class="c1"># Grab the inferences from the event</span>
    <span class="n">inferences</span> <span class="o">=</span> <span class="c1">## TODO: fill in</span>

    <span class="c1"># Check if any values in our inferences are above THRESHOLD</span>
    <span class="n">meets_threshold</span> <span class="o">=</span> <span class="c1">## TODO: fill in</span>

    <span class="c1"># If our threshold is met, pass our data back out of the</span>
    <span class="c1"># Step Function, else, end the Step Function with an error</span>
    <span class="k">if</span> <span class="n">meets_threshold</span><span class="p">:</span>
        <span class="k">pass</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span><span class="p">(</span><span class="s2">&quot;THRESHOLD_CONFIDENCE_NOT_MET&quot;</span><span class="p">)</span>

    <span class="k">return</span> <span class="p">{</span>
        <span class="s1">&#39;statusCode&#39;</span><span class="p">:</span> <span class="mi">200</span><span class="p">,</span>
        <span class="s1">&#39;body&#39;</span><span class="p">:</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">event</span><span class="p">)</span>
    <span class="p">}</span>
</pre></div>
<p>Once you have tested the lambda functions, save the code for each lambda function in a python script called 'lambda.py'.</p>
<p>With your lambdas in place, you can use the Step Functions visual editor to construct a workflow that chains them together. In the Step Functions console you'll have the option to author a Standard step function <em>Visually</em>.</p>
<p>When the visual editor opens, you'll have many options to add transitions in your workflow. We're going to keep it simple and have just one: to invoke Lambda functions. Add three of them chained together. For each one, you'll be able to select the Lambda functions you just created in the proper order, filter inputs and outputs, and give them descriptive names.</p>
<p>Make sure that you:</p>
<ol>
<li>Are properly filtering the inputs and outputs of your invokations (e.g. <code>$.body</code>)</li>
<li>Take care to remove the error handling from the last function - it's supposed to "fail loudly" for your operations colleagues!</li>
</ol>
<p>Take a screenshot of your working step function in action and export the step function as JSON for your submission package.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%%writefile</span> lambda_function.py

<span class="kn">import</span> <span class="nn">json</span>
<span class="kn">import</span> <span class="nn">sagemaker</span>
<span class="kn">import</span> <span class="nn">base64</span>
<span class="kn">from</span> <span class="nn">sagemaker.serializers</span> <span class="kn">import</span> <span class="n">IdentitySerializer</span>
<span class="kn">from</span> <span class="nn">sagemaker.predictor</span> <span class="kn">import</span> <span class="n">Predictor</span>

<span class="c1"># Fill this in with the name of your deployed model</span>
<span class="n">ENDPOINT</span> <span class="o">=</span> <span class="s1">&#39;image-classification-2022-08-26-12-31-30-912&#39;</span>

<span class="k">def</span> <span class="nf">lambda_handler</span><span class="p">(</span><span class="n">event</span><span class="p">,</span> <span class="n">context</span><span class="p">):</span>

    <span class="c1"># Decode the image data</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">base64</span><span class="o">.</span><span class="n">b64decode</span><span class="p">(</span><span class="n">event</span><span class="p">[</span><span class="s2">&quot;image_data&quot;</span><span class="p">])</span>

    <span class="c1"># Instantiate a Predictor</span>
    <span class="n">predictor</span> <span class="o">=</span> <span class="n">Predictor</span><span class="p">(</span><span class="n">ENDPOINT</span><span class="p">)</span>

    <span class="c1"># For this model the IdentitySerializer needs to be &quot;image/png&quot;</span>
    <span class="n">predictor</span><span class="o">.</span><span class="n">serializer</span> <span class="o">=</span> <span class="n">IdentitySerializer</span><span class="p">(</span><span class="s2">&quot;image/png&quot;</span><span class="p">)</span>

    <span class="c1"># Make a prediction:</span>
    <span class="n">inferences</span> <span class="o">=</span> <span class="n">predictor</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>

    <span class="c1"># We return the data back to the Step Function    </span>
    <span class="n">event</span><span class="p">[</span><span class="s2">&quot;inferences&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">inferences</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s1">&#39;utf-8&#39;</span><span class="p">)</span>
    <span class="k">return</span> <span class="p">{</span>
        <span class="s1">&#39;statusCode&#39;</span><span class="p">:</span> <span class="mi">200</span><span class="p">,</span>
        <span class="s1">&#39;body&#39;</span><span class="p">:</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">event</span><span class="p">)</span>
    <span class="p">}</span>
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<pre>Overwriting lambda_function.py
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<p>Great! Now you can use the files in <code>./test</code> as test files for our workflow. Depending on our threshold, our workflow should reliably pass predictions about images from <code>./test</code> on to downstream systems, while erroring out for inferences below our confidence threshold!</p>
<h3 id="Testing-and-Evaluation">Testing and Evaluation<a class="anchor-link" href="#Testing-and-Evaluation">&#182;</a></h3><p>Do several step function invokations using data from the <code>./test</code> folder. This process should give you confidence that the workflow both <em>succeeds</em> AND <em>fails</em> as expected. In addition, SageMaker Model Monitor will generate recordings of your data and inferences which we can visualize.</p>
<p>Here's a function that can help you generate test inputs for your invokations:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">random</span>
<span class="kn">import</span> <span class="nn">boto3</span>
<span class="kn">import</span> <span class="nn">json</span>


<span class="k">def</span> <span class="nf">generate_test_case</span><span class="p">():</span>
    <span class="c1"># Setup s3 in boto3</span>
    <span class="n">s3</span> <span class="o">=</span> <span class="n">boto3</span><span class="o">.</span><span class="n">resource</span><span class="p">(</span><span class="s1">&#39;s3&#39;</span><span class="p">)</span>
    
    <span class="c1"># Randomly pick from sfn or test folders in our bucket</span>
    <span class="n">objects</span> <span class="o">=</span> <span class="n">s3</span><span class="o">.</span><span class="n">Bucket</span><span class="p">(</span><span class="n">bucket</span><span class="p">)</span><span class="o">.</span><span class="n">objects</span><span class="o">.</span><span class="n">filter</span><span class="p">(</span><span class="n">Prefix</span><span class="o">=</span><span class="s2">&quot;test&quot;</span><span class="p">)</span>
    
    <span class="c1"># Grab any random object key from that folder!</span>
    <span class="n">obj</span> <span class="o">=</span> <span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">([</span><span class="n">x</span><span class="o">.</span><span class="n">key</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">objects</span><span class="p">])</span>
    
    <span class="k">return</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">({</span>
        <span class="s2">&quot;image_data&quot;</span><span class="p">:</span> <span class="s2">&quot;&quot;</span><span class="p">,</span>
        <span class="s2">&quot;s3_bucket&quot;</span><span class="p">:</span> <span class="n">bucket</span><span class="p">,</span>
        <span class="s2">&quot;s3_key&quot;</span><span class="p">:</span> <span class="n">obj</span>
    <span class="p">})</span>
<span class="n">generate_test_case</span><span class="p">()</span>
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<pre>&#39;{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/motorcycle_s_001508.png&#34;}&#39;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">10</span><span class="p">):</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">generate_test_case</span><span class="p">())</span>
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<pre>{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/motorcycle_s_001508.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/safety_bicycle_s_000280.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/dirt_bike_s_000001.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/minibike_s_001651.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/motorbike_s_000333.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/safety_bike_s_000438.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/safety_bike_s_000438.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/bike_s_001073.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/bike_s_000941.png&#34;}
{&#34;image_data&#34;: &#34;&#34;, &#34;s3_bucket&#34;: &#34;sagemaker-us-east-1-631734214354&#34;, &#34;s3_key&#34;: &#34;test/minibike_s_000497.png&#34;}
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">json</span>

<span class="n">execution_name</span>
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<pre>&#39;test-motorcycle_s_000602-png&#39;</pre>
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<h4 id="invoking-the-step-function-from-code-using-generate-testcase-function">invoking the step function from code using generate testcase function<a class="anchor-link" href="#invoking-the-step-function-from-code-using-generate-testcase-function">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">boto3</span>
<span class="kn">import</span> <span class="nn">json</span>
<span class="kn">from</span> <span class="nn">time</span> <span class="kn">import</span> <span class="n">sleep</span>
<span class="kn">from</span> <span class="nn">random</span> <span class="kn">import</span> <span class="n">randint</span>

<span class="n">sf_client</span> <span class="o">=</span> <span class="n">boto3</span><span class="o">.</span><span class="n">client</span><span class="p">(</span><span class="s1">&#39;stepfunctions&#39;</span><span class="p">)</span>

<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span>
    <span class="k">try</span><span class="p">:</span>
        <span class="n">sm_arn</span> <span class="o">=</span> <span class="s1">&#39;arn:aws:states:us-east-1:631734214354:stateMachine:Scones-Unlimited-State-Machine&#39;</span>
        <span class="n">payload_str</span><span class="o">=</span><span class="n">generate_test_case</span><span class="p">()</span>
        <span class="n">payload</span><span class="o">=</span><span class="n">json</span><span class="o">.</span><span class="n">loads</span><span class="p">(</span><span class="n">payload_str</span><span class="p">)</span>
        <span class="n">execution_name</span><span class="o">=</span> <span class="n">payload</span><span class="p">[</span><span class="s1">&#39;s3_key&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;/&#39;</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">)</span>


        <span class="n">response</span> <span class="o">=</span> <span class="n">sf_client</span><span class="o">.</span><span class="n">start_execution</span><span class="p">(</span>
            <span class="n">stateMachineArn</span><span class="o">=</span><span class="n">sm_arn</span><span class="p">,</span>
            <span class="n">name</span><span class="o">=</span><span class="n">execution_name</span><span class="p">,</span>
            <span class="nb">input</span><span class="o">=</span><span class="n">payload_str</span><span class="p">,</span>
        <span class="p">)</span>

        <span class="nb">print</span><span class="p">(</span><span class="n">response</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="o">*</span><span class="mi">15</span><span class="p">)</span>
        <span class="n">sleep</span><span class="p">(</span><span class="n">randint</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">20</span><span class="p">))</span>
    <span class="k">except</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Probably a repeated execution&#39;</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="o">*</span><span class="mi">15</span><span class="p">)</span>
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<pre>{&#39;executionArn&#39;: &#39;arn:aws:states:us-east-1:631734214354:execution:Scones-Unlimited-State-Machine:test-motorcycle_s_001261-png&#39;, &#39;startDate&#39;: datetime.datetime(2022, 8, 27, 17, 49, 8, 532000, tzinfo=tzlocal()), &#39;ResponseMetadata&#39;: {&#39;RequestId&#39;: &#39;1c9d5d4a-553e-451e-a93d-bed0f10e097b&#39;, &#39;HTTPStatusCode&#39;: 200, &#39;HTTPHeaders&#39;: {&#39;x-amzn-requestid&#39;: &#39;1c9d5d4a-553e-451e-a93d-bed0f10e097b&#39;, &#39;date&#39;: &#39;Sat, 27 Aug 2022 17:49:08 GMT&#39;, &#39;content-type&#39;: &#39;application/x-amz-json-1.0&#39;, &#39;content-length&#39;: &#39;155&#39;}, &#39;RetryAttempts&#39;: 0}}
---------------
{&#39;executionArn&#39;: &#39;arn:aws:states:us-east-1:631734214354:execution:Scones-Unlimited-State-Machine:test-safety_bicycle_s_001153-png&#39;, &#39;startDate&#39;: datetime.datetime(2022, 8, 27, 17, 49, 17, 738000, tzinfo=tzlocal()), &#39;ResponseMetadata&#39;: {&#39;RequestId&#39;: &#39;f9bde179-17b8-4e02-a103-051412fb763b&#39;, &#39;HTTPStatusCode&#39;: 200, &#39;HTTPHeaders&#39;: {&#39;x-amzn-requestid&#39;: &#39;f9bde179-17b8-4e02-a103-051412fb763b&#39;, &#39;date&#39;: &#39;Sat, 27 Aug 2022 17:49:17 GMT&#39;, &#39;content-type&#39;: &#39;application/x-amz-json-1.0&#39;, &#39;content-length&#39;: &#39;159&#39;}, &#39;RetryAttempts&#39;: 0}}
---------------
{&#39;executionArn&#39;: &#39;arn:aws:states:us-east-1:631734214354:execution:Scones-Unlimited-State-Machine:test-cycle_s_001044-png&#39;, &#39;startDate&#39;: datetime.datetime(2022, 8, 27, 17, 49, 27, 930000, tzinfo=tzlocal()), &#39;ResponseMetadata&#39;: {&#39;RequestId&#39;: &#39;acfe2362-a578-47f0-b83c-74688ed058b2&#39;, &#39;HTTPStatusCode&#39;: 200, &#39;HTTPHeaders&#39;: {&#39;x-amzn-requestid&#39;: &#39;acfe2362-a578-47f0-b83c-74688ed058b2&#39;, &#39;date&#39;: &#39;Sat, 27 Aug 2022 17:49:27 GMT&#39;, &#39;content-type&#39;: &#39;application/x-amz-json-1.0&#39;, &#39;content-length&#39;: &#39;149&#39;}, &#39;RetryAttempts&#39;: 0}}
---------------
{&#39;executionArn&#39;: &#39;arn:aws:states:us-east-1:631734214354:execution:Scones-Unlimited-State-Machine:test-cycle_s_002661-png&#39;, &#39;startDate&#39;: datetime.datetime(2022, 8, 27, 17, 49, 30, 142000, tzinfo=tzlocal()), &#39;ResponseMetadata&#39;: {&#39;RequestId&#39;: &#39;08c86236-6d4c-46d3-b530-22b4c79aea7c&#39;, &#39;HTTPStatusCode&#39;: 200, &#39;HTTPHeaders&#39;: {&#39;x-amzn-requestid&#39;: &#39;08c86236-6d4c-46d3-b530-22b4c79aea7c&#39;, &#39;date&#39;: &#39;Sat, 27 Aug 2022 17:49:30 GMT&#39;, &#39;content-type&#39;: &#39;application/x-amz-json-1.0&#39;, &#39;content-length&#39;: &#39;150&#39;}, &#39;RetryAttempts&#39;: 0}}
---------------
Probably a repeated execution
---------------
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<p>In the Step Function dashboard for your new function, you can create new executions and copy in the generated test cases. Do several executions so that you can generate data you can evaluate and visualize.</p>
<p>Once you've done several executions, let's visualize the record of our inferences. Pull in the JSONLines data from your inferences like so:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sagemaker.s3</span> <span class="kn">import</span> <span class="n">S3Downloader</span>

<span class="c1"># In S3 your data will be saved to a datetime-aware path</span>
<span class="c1"># Find a path related to a datetime you&#39;re interested in</span>
<span class="n">data_path</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;s3://</span><span class="si">{</span><span class="n">bucket</span><span class="si">}</span><span class="s2">/data_capture/image-classification-model-endpoint/AllTraffic/2022/08/27/17/&quot;</span>

<span class="n">S3Downloader</span><span class="o">.</span><span class="n">download</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span> <span class="s2">&quot;captured_data&quot;</span><span class="p">)</span>

<span class="c1"># Feel free to repeat this multiple times and pull in more data</span>
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<p>The data are in JSONLines format, where multiple valid JSON objects are stacked on top of eachother in a single <code>jsonl</code> file. We'll import an open-source library, <code>jsonlines</code> that was purpose built for parsing this format.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">!</span>pip install jsonlines
<span class="kn">import</span> <span class="nn">jsonlines</span>
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<pre>Looking in indexes: https://pypi.org/simple, https://pip.repos.neuron.amazonaws.com
Collecting jsonlines
  Downloading jsonlines-3.1.0-py3-none-any.whl (8.6 kB)
Requirement already satisfied: attrs&gt;=19.2.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.8/site-packages (from jsonlines) (21.2.0)
Installing collected packages: jsonlines
Successfully installed jsonlines-3.1.0
<span class="ansi-yellow-fg">WARNING: You are using pip version 22.0.4; however, version 22.2.2 is available.
You should consider upgrading via the &#39;/home/ec2-user/anaconda3/envs/python3/bin/python -m pip install --upgrade pip&#39; command.</span><span class="ansi-yellow-fg">
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<p>Now we can extract the data from each of the source files:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>

<span class="c1"># List the file names we downloaded</span>
<span class="n">file_handles</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">listdir</span><span class="p">(</span><span class="s2">&quot;./captured_data&quot;</span><span class="p">)</span>

<span class="c1"># Dump all the data into an array</span>
<span class="n">json_data</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">jsonl</span> <span class="ow">in</span> <span class="n">file_handles</span><span class="p">:</span>
    <span class="k">with</span> <span class="n">jsonlines</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;./captured_data/</span><span class="si">{</span><span class="n">jsonl</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
        <span class="n">json_data</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">read</span><span class="p">())</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pprint</span>

<span class="n">pprint</span><span class="o">.</span><span class="n">pprint</span><span class="p">(</span><span class="n">json_data</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<pre>{&#39;captureData&#39;: {&#39;endpointInput&#39;: {&#39;data&#39;: &#39;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&#39;,
                                   &#39;encoding&#39;: &#39;BASE64&#39;,
                                   &#39;mode&#39;: &#39;INPUT&#39;,
                                   &#39;observedContentType&#39;: &#39;image/png&#39;},
                 &#39;endpointOutput&#39;: {&#39;data&#39;: &#39;[0.0029940030071884394, &#39;
                                            &#39;0.9970059990882874]&#39;,
                                    &#39;encoding&#39;: &#39;JSON&#39;,
                                    &#39;mode&#39;: &#39;OUTPUT&#39;,
                                    &#39;observedContentType&#39;: &#39;application/json&#39;}},
 &#39;eventMetadata&#39;: {&#39;eventId&#39;: &#39;5a624674-cee8-455a-9dff-1dff93f017e8&#39;,
                   &#39;inferenceTime&#39;: &#39;2022-08-27T17:21:04Z&#39;},
 &#39;eventVersion&#39;: &#39;0&#39;}
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<p>The data should now be a list of dictionaries, with significant nesting. We'll give you an example of some code that grabs data out of the objects and visualizes it:</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define how we&#39;ll get our data</span>
<span class="k">def</span> <span class="nf">simple_getter</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
    <span class="n">inferences</span> <span class="o">=</span> <span class="n">obj</span><span class="p">[</span><span class="s2">&quot;captureData&quot;</span><span class="p">][</span><span class="s2">&quot;endpointOutput&quot;</span><span class="p">][</span><span class="s2">&quot;data&quot;</span><span class="p">]</span>
    <span class="n">timestamp</span> <span class="o">=</span> <span class="n">obj</span><span class="p">[</span><span class="s2">&quot;eventMetadata&quot;</span><span class="p">][</span><span class="s2">&quot;inferenceTime&quot;</span><span class="p">]</span>
    <span class="k">return</span> <span class="n">json</span><span class="o">.</span><span class="n">loads</span><span class="p">(</span><span class="n">inferences</span><span class="p">),</span> <span class="n">timestamp</span>

<span class="n">simple_getter</span><span class="p">(</span><span class="n">json_data</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
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<pre>([0.0029940030071884394, 0.9970059990882874], &#39;2022-08-27T17:21:04Z&#39;)</pre>
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<p>Finally, here's an example of a visualization you can build with this data. In this last part, you will take some time and build your own - the captured data has the input images, the resulting inferences, and the timestamps.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Populate the data for the x and y axis</span>
<span class="n">x</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">y</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">obj</span> <span class="ow">in</span> <span class="n">json_data</span><span class="p">:</span>
    <span class="n">inference</span><span class="p">,</span> <span class="n">timestamp</span> <span class="o">=</span> <span class="n">simple_getter</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span>
    
    <span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">inference</span><span class="p">))</span>
    <span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">timestamp</span><span class="p">)</span>

<span class="c1"># Todo: here is an visualization example, take some time to build another visual that helps monitor the result</span>
<span class="c1"># Plot the data</span>
<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;r&#39;</span> <span class="k">if</span> <span class="n">k</span><span class="o">&lt;.</span><span class="mi">8</span> <span class="k">else</span> <span class="s1">&#39;b&#39;</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">y</span> <span class="p">])</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axhline</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;g&#39;</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">(</span><span class="n">bottom</span><span class="o">=.</span><span class="mi">6</span><span class="p">)</span>

<span class="c1"># Add labels</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Confidence&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s2">&quot;Observed Recent Inferences&quot;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">14</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;Pictured with confidence threshold for production use&quot;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>

<span class="c1"># Give it some pizzaz!</span>
<span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s2">&quot;Solarize_Light2&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">gcf</span><span class="p">()</span><span class="o">.</span><span class="n">autofmt_xdate</span><span class="p">()</span>
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<h3 id="Todo:-build-your-own-visualization">Todo: build your own visualization<a class="anchor-link" href="#Todo:-build-your-own-visualization">&#182;</a></h3>
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<h5 id="PIE-Chart-of-confidence">PIE Chart of confidence<a class="anchor-link" href="#PIE-Chart-of-confidence">&#182;</a></h5>
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<div class="prompt input_prompt">In&nbsp;[46]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Populate the data for the x and y axis</span>
<span class="n">x</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">y</span> <span class="o">=</span> <span class="p">[]</span>


<span class="n">THRESHOLD</span> <span class="o">=</span> <span class="mf">0.8</span>
<span class="n">cnt_greater_than_confidence</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">number_of_inferences</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">json_data</span><span class="p">)</span>

<span class="k">for</span> <span class="n">obj</span> <span class="ow">in</span> <span class="n">json_data</span><span class="p">:</span>
    <span class="n">inference</span><span class="p">,</span> <span class="n">timestamp</span> <span class="o">=</span> <span class="n">simple_getter</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span>
    
    <span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">inference</span><span class="p">))</span>
    <span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">timestamp</span><span class="p">)</span>
    
    <span class="n">cnt_greater_than_confidence</span> <span class="o">+=</span> <span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">inference</span><span class="p">)</span><span class="o">&gt;</span> <span class="n">THRESHOLD</span><span class="p">)</span>

<span class="c1"># Plot the data</span>
<span class="n">pie_wedge_cnts</span> <span class="o">=</span> <span class="p">[</span><span class="n">cnt_greater_than_confidence</span><span class="p">,</span> <span class="n">number_of_inferences</span> <span class="o">-</span> <span class="n">cnt_greater_than_confidence</span><span class="p">]</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">wedges</span><span class="p">,</span> <span class="n">text</span><span class="p">,</span> <span class="n">autotexts</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">pie</span><span class="p">(</span><span class="n">pie_wedge_cnts</span><span class="p">,</span> <span class="n">colors</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;b&#39;</span><span class="p">,</span> <span class="s1">&#39;r&#39;</span><span class="p">],</span> <span class="n">autopct</span><span class="o">=</span><span class="s2">&quot;</span><span class="si">%.2f</span><span class="s2">&quot;</span><span class="p">,</span> <span class="n">textprops</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span><span class="n">color</span><span class="o">=</span><span class="s2">&quot;w&quot;</span><span class="p">))</span>

<span class="c1"># Add labels &amp; legend</span>
<span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;&gt; Confidence&#39;</span><span class="p">,</span> <span class="s1">&#39;&lt;= Confidence&#39;</span><span class="p">]</span>
<span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">wedges</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="s1">&#39;upper right&#39;</span><span class="p">)</span>


<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s2">&quot;Observed Recent Inferences&quot;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">14</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">&quot;Showing the Percentage of inferences passing the confidence threshold&quot;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">setp</span><span class="p">(</span><span class="n">autotexts</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="s1">&#39;bold&#39;</span><span class="p">)</span>

<span class="c1"># Give it some pizzaz!</span>
<span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s2">&quot;Solarize_Light2&quot;</span><span class="p">)</span>
</pre></div>

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<h5 id="Lineplot-with-confidence-line">Lineplot with confidence line<a class="anchor-link" href="#Lineplot-with-confidence-line">&#182;</a></h5>
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<div class="prompt input_prompt">In&nbsp;[47]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axhline</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;g&#39;</span><span class="p">,</span> <span class="n">linestyle</span><span class="o">=</span><span class="s1">&#39;--&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">(</span><span class="n">bottom</span><span class="o">=.</span><span class="mi">6</span><span class="p">)</span>

<span class="c1"># Add labels</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Confidence&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s2">&quot;Observed Recent Inferences&quot;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">14</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;Pictured with confidence threshold for production use&quot;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>

<span class="c1"># Give it some pizzaz!</span>
<span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s2">&quot;Solarize_Light2&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">gcf</span><span class="p">()</span><span class="o">.</span><span class="n">autofmt_xdate</span><span class="p">()</span>
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83yG+4DoKGhke989ydMSl9E6rTFfPrFGn7x9PM0N7eQlrGUu+7/UbeW1l9ffI3f/v5vgLI22S9//UfmL7mJl//5X7IOHmX+kptIz7ySZdfcaUp4m3XwKJMzljBz3rX869/v9GjfI48+xVer1gNww60P8sDDTwDw37c/5OnfvABcfGt+6unn2bFrH2kZS3nxH28Ayny5K665i7jk2b3O59p/4DCz5l/H5IwlTJ99NfX1DbS0tJjOwZTpy0xzxd5+dyU33vZQt30++9yL7Ny9nx/8+Bf831O/NzufVVU1LF1+B1OmL+N7P3zSLOvFeys+Y/rsq0nLWMr3fvik6SGs9Y3jV8/8ickZS8ice41pxYMLFyq44dYHmZyxhMkZS9i150Cf+zHyj3+9SUnpBRZecQsLl91i+r6nMu7/7uM88fPfsnDZLTz5q+fIPZfPFdfcRXrmlcxddAOnTp8FlJZqytSFTM5YwrzFFxNX93bOV6z8gknpi0iZupAnf9VzMunn/vQyCZPmsuSq2zl9Jrfb74ePZPPkL5/jm3WbSMtYSnNzc6/71frG8czv/sKMOctNyZmNLFh6M4//7DfMmn8dKVMXsm//IUBpLT78yM9ZuvwO7n3wMc4XFLH4yttInbaYxVfeRkFhMaAs4TRz3rVkzLqKX//2z6b9dr3uAD96/Fe8/e5KoHs9q6vT8Ztn/8rKT78mLWMpH33ylVnLt7ey7//u4zz6xK+ZNf86oifO7HFtvb7uz3/8602S0haQOm0xt9/zA0DJk/nAw0+QMesqpkxfxpdfr+vx+lgbwrkJeqSjo4O16zebJR0G+P0fX8LdXcuR/d9yeN8GFszN5Plnf2Fq8b33Vv/dk7V1Ojav/4Qf/eA7PPrEr1n5/r/Zv2sN999zK7/qdEoPfO8JXvzLb9m5pffW1uxZGezYtQ9QlnM5eeoMADt37WPWzGlm2z737C+YlTmNg3vXmebEHTl6gg/f/RdH9m9g5SdfU1hUYqZpa2vj9nse4e9//g2H9q5n/eoVODs7mZztkf3f8v47r3D/Q4/T0tLS6z6ffuoxpqal8O6bL/PCc+bdcr977u/MmjGNrD1rWX7VYtND6uSpM6z85Gu2b/qcg3vXoVareP9DpVu1sbGJjGlpHNq7ntmzMvjPWx8A8OhPf83c2dM5tHc9B3Z9Q2JCbJ/7MfKjH3yHoEB/Nn6zko1rV/ZZBkDOmTzWr17BX/74a773wyd5+W/Psn/XGl547ml++NgvAfj98y/yzZfvcWjver74+E2TtqfzU1JSxi9+9TzfrvmIg3vWcSDrCF98tdbMxqyDR/nok6/I2r2WT1a8brasjZHUSYn85uknuOXG5Rzcu46amrpe99vY2ERiYhy7t31tSqHWlcbGJnZs/oJXXvwDD37/p6bvDx46xhcr/8v7b7/Cjx5/mrvuuJHD+zZw+63XmbqaH/vpMzz80N3s3bGaAH/fbvu+lJ7qmauri9mx3HrTNebXrJeyAUrLytm28TO++vQtnnr6+X7L78qf/vJPsnZ/w+F9G3j1ZUX73J9eZv68mezdsZqNaz/i57/8A42NTQPa71ggnJvADGMLbNrMqwgLDeaB+24z+33jph384OF7TZ89PT0GXMYtNy0H4HROLsdPnGbp1XeQlrGU5/70MkUlpdTV6ait1TF3trIe2F1dlqzpyuzMaezYuY8TJ3NISIjBz8+H0tIL7Nl3kMzpU/u1Y8G8mbi7a3FyciIhPobzBUVmv5/OySUwwI/0qakAaLUa7Ozs2LFrP3fdodgUHxdNeFgwOWfyLNrnpWzfsZc7b78egKuuWIinpzsAmzbv5OCho2TMUlpcm7bsJC+vAFAmcF995SIA0iYnk39eKWPz1l1876G7ASXHpru7ts/99EVvZQDcdMNVqNVqGhoa2bXnALfe+T3SMpby/R89SWlZOQCZ09O5/+EneOPND9DrL+aH7On87M86wtw5M/D19cbOzo7bb72+23jZjl37uG75MlxcnNFqNSy/anG/x9DXftVqtSnxdE/cdsu1gLI6hE7XQG1tHQDLr1psWoFgz74s7rj1OgDuvuNGdu7eD8CuPQe4vVNvrCd90Vs964veyga4dvlSVCoVExNiuVBe2W/5XUlOSuCu+3/Meys+M9mwYeM2XvjrP0nLWMqCpbfQ0tJqegmzZkRuSYEZxhZYbyh5Efveh53azpQ4FpQs7V1xdXEx7SsxIbZb66y2tq7XVQK6EhwcSE1tHes2bGH2zAxqamr5+LNVuLm6oNG49at3dHQw/a1Wq+noMO+uk+WeVyvoK2Fuf/vsiR7LQOaeu27mud892e03e3s7k0atVtOh7338p6/99EVfZRiT+hoMBjzc3XusL6/+43n27jvEmrUbSZu+lIN7lG16Oj+WJpS2pE50pa/9Ojk5miVT7q8s4+eeEmr3pOnJVjs7tVkiaON90Vs9Gwhd9V3PcU/noK/7c9Xn77Btx16+Xr2eP/zxJY5lbUSW4eMPXicuNmpINo42ouUmGBCLF83hn69dHAMz5g+0t7envb0dAH9/H8orKqmqqqG1tdW0OOOlxMVGUVFZZRrzaG9vJ/vEaTw83HF315i6HLtGOV7K9Iw0Xnrlv8yZlcGszAz++uK/u3VJAmjcXGloaBjQscbHRVFSeoH9Bw4DUF/fQEdHB3NmZfBBZ9dezplzFBSWEBcbOaB9G5ndZV/frNtMTY3SQlgwbyaffr6a8s437+rqmn5bgQvmzeS1N94FlCAJna7e4v1oNK7UD/D8aLUaIiaE8vFnyqKksiybFvvMPZdPxrTJ/PbXP8XH26tbl29XMtIns237Hiorq9Hr9Xz08ZfMmTXdbJvZMzP44uu1NDc3U1/fwKo13/ZrnyX77Y2Vn3wNKC1Gd3cN7u7abtvMyJjChx9/BcD7H37OzBnpAGROn2r2vZHwsBBOnjpDa2srdXU6Nm3ZCfRezzQaN+obGnu0r7eyLaG3+9NgMFBYVML8uZn86Q+/pLZOR0NDI0sWzeGVV98yOcpDh49bXNZYIpybYED88uc/pqa2zhQssHnrbgAe+s4dpE5bwl33/wh7e3ue/sVjzJi7nOU33k9cXM9vfA4ODqx8/9/84lfPMTljCWnTl7Frj+Lo/vvaX/nR479i5rxruy1D0pVZmRl0dHQQHRVB2uQkqmtqmZXZPUouJTkBOzs7JmcsMQWU9IeDgwMr/vdPHn3i10zOWMLSq++gpaWV73/3HvQGPZPSF3H73T/gzdf/Nug1uH791ONs27mXqTOuYMPGrabFMycmxPK7Z37GsuV3kjptMUuvvtPU5dcbL/75t2zeuotJ6YtIz7yS7JM5Fu/noe/cyVXX3WMWUGIJ7771Mm++/SGTM5aQPGWhKcDn/576gymQY/asDCalTOx1H4GB/vzhdz9n4RW3KMEwqUlce8k6aWmTk7nlxuWkTV/GTXd8t8dxssHstzc8Pd2ZNf86fvDjX/DGv/7c4zYv/fV3vPPuSlKnLeb9FZ/x4l9+C8CLf/ktr/77HTJmXYVOV2/aPjQkiJtvvLrzPvmxaY253urZ/DkzOHkyxxRQYknZltDb/anX67nnO48qgVIzlvHYDx/Ew8OdX/3iUdrbO0idtpiUqQstWlzXGhC5JQUCgaALC5bezAvP/Uqsij3OES03gUAgENgcouUmEAgEAptDtNwEAoFAYHMI5yYQCAQCm0PMc7MC6nS6IeklSbJ4rpDQC73QC72t6CVAq+0+TQNEy80m0Go0Qi/0Qi/0l51eperdhQnnJhAIBAKbQzg3gUAgENgcYsytB/739Q6OnS1C4+rEr797XbffZVlm5fp9HM8twsHejnuvnkVYoDcA2blFrFy/D4MsMzM1hmWZKaNsvUAgEAhEy60HZkyK5ke39Z51/HhuMeXVOn73/Ru488oZfLBWSUFlMBhYsXYvP7xtMc88fB37s/MoqagdJasFAoFAYES03HogJiyAytr6Xn8/mlPA9JQoJEkiMtiP5pY26uqbqKprwM9Lg6+nMkCaPjGCozkFBPl6jJLlF+kwyNS0QE0LVLdAdbNs+lv5X6a6GWpbAakW2SAroUeY/rv4/yUJyy/9Xq2qM8t2PhDs1fDU7HZSPAclH1NKGmR+v8vAPaltTPcba2sE4wFZlilthCPlMocvQHaVzIzQJr6fIqMa4soAAnOEcxsEtfVNeGpdTZ89tK7U1jdRU9+Ep8b8+7ziih73sf3gabYfygHgvqtnEOTvMyhbdhe2s+lwE5XNKqqbZaqaDFQ2ydS1DiS0dqhJagbn2Ix8drKV2ct6Due1FPdewoFHUv/rXQ0cvGCg6UALS28bf/YL/cjrDbLM2WoDB0raySrt4GBpB2UN5vfb2ZpWJMmRJ2c6D3rpG2s9/pHW97XSh3Bug6DHKRm91Mne6urstDhmp8UByjy3wc51O1Rk4L1j3Q1SSeDuCF5O4OkEXk4SXs7KZ+U75bOHI3hqNejqlZaqcU+m/2Xzz1zyWQY0bm4DXi4F4HQ1/HKbgZJ6w5Dm+rlrtaOuP14hsz5XceqnqvScKa3Dz3XwD6bxdvxC37O+TS9zqgoOl8scKZc5WgH1bebbax0gxQ9S/SS0DvDnfTL/O9KKi9TGfckDHymypuMfbb26j6kAwrkNAk+tCzW6i+ss1eoa8XBzQa83UFPf/fuRZGqgxJOznHCmBS8nqdORKY5NrbLsYevupsLJMPguEXetmrpBvHE6qBQXWVxvYDwN/8qyzCsHFcdmp4IOA+wqkbkuRnQrXW40tMkcK2hnZ56BI+UyJ6qg9ZL1af1dYJKfRKq/4tAmuGPWBenr7sRP1jXy2mEZd0cD18eOn3thKFQ1y6w6K3NVgh6fEfBEwrkNgpSYULYcOMXUiRHklVTg5OiAu8YFN1cnyqt1VNbW46FxYf+JPB64bs6I2hLnJTFtghN1urb+N7YyvJ1BLSmVvKVDxslufDiHncVwuFx5gbg7UeKVgzK7imSuixlrywQjgSzLlDdBfh2c18mc7/J/RTOAea9FhLvixCb5Qaq/REA/Lfpl0Q6U1Tbxp70yL+yV0TrKLAwfH/fCUNheKPPqYZkTNc38aQQek8K59cB/Pt9KzvkyGppbePLllSyfk4per7ypz5kST1J0CMdzi3n6X5/hYK/m3qtnAUoT+dal03l5xQYMBpnMSdEE+Y7DSIlRQq2SCHCF4gYoa4QJ7mNtUf/oDTL/6my13Z8ssSBMcW77y5QuKQe17T+UbJWWDpnCejhfJ1Ogu+jMCnTQ3NGzxkEF8b5qkr0NTPKTSPEFD6eB14HrY1XUtRp47bDMMzsMuNmryAiy7bq0rUjpuVkQYQ+0Dvv+hXPrgQevn9vn75IkcfuynperT44OITk6ZCTMskkC3RTnVtowPpzbN+dkztVBoCvcECvhoJaI81ZzukrPoQuQETTWFgosRZZl/ndc5nh1PbnVekobeg+t8nSEcHcI10qEu8MEd4lwLQS4gpfH0MacjNybJFHbCh+elHlyq4F/LFKR5GubDq6pXeZAqRKqMH+CPeiFcxPYGEqXjUxZo0yvUTlWQkuHzOtHlMffw6mSqZU2N9ye01V6dhXLNv+2bUucqIJXD8uA0ixTSxCsgXAthLtLTOj8P0wL7o4jf10lSeLHU0DXCmvOyfxkk4F/L1UR4WF7dWpPCbQZIMkHfF1V1A393aAbwrkJxpRAN+X/0oEHW446H59Wxl5iPWFJxMUHztwJ9rx+sIVdxTKPp4+hgYIBUaBTXlSmB9vx6BQDIW5gP8bdyipJ4qkZoGuT2VEEP95o4PWlKgLdbMvBbe/skpwTOnLHdXmE5QislsDOaYGljX1vN9bUtSpdWACPpKnMot1S/NVoHaCw/uIDU2D9lHS+UCX72xHhLo25YzNip5L4/WwVqX5Q0QSPbjRQ3Ww79arDILOz07nNFs5NYKsY30iVbknr5X/HZerbYGoATAs0/81OJTG9sztyd7F1H4fgIsWdSYhC3a3vMehkJ/GX+SpiPKFAB49vMtDYZht160g56NogVAMThjb3u0+s76oKLisCjC03K+6WLGuU+fiU8mD5YZqqxywSM4KV/3cK5zZuKKpXrlWo1jofg24OEi8uVBGiURIe/GyLgVb9+K9f2wsvdkkONiOLJVjnVRVcNvi6KAP5lc1Y7Y37+mGZNgMsniAR793zzTgjSEICDl1QIsEE1o+xW9JanRuAt7PEywtV+DjDwQvw9DYDHYbxW79kWTZNARjJLkkQzk0wxtipJALclGp4wQrH3c7WyHxzTsZOBd9L7f1m9HCSSPKFdgMcKBtFAwWDoqVDprJZyTBjrH/WSpBG4qWFKjQOsK0Int8jI/eYA9D6ya1VXio8HSF5cOl0Lca6r6rgsiBIo1RDa+ya/NchAzJwfYxEsKbvN80ZneNuxsFygfVibLUFulqepm4sifKU+NsCFU5qWJ0r84+D49PBbevskpwZIo34eRfOTTDmBHd2C5VaWVBJVpnMrmJwsYfvpPR/I84MUbbZVTI+HzyXE0WdwSTBmrG1YyAk+0o8P1eFWoIPTsi8mz3+6thoTAEwIpybYMwJtsKWmyzL/LMzzdZdEyU8LUipFOsJPs5K+PbZmpG2UDAUSjqXnQkeZ/PHZgRLPDNTGd/91yGZL84Mbbmp0aS8SeZkFTiqu0ccjwTCuQnGHKNzK7OiMbfNBUoGCy8nuD3BsgegJEnMCO7smhRRk1aNseUWNI5abkaWRKh4YppSz17YK7Ph3PhImm6MkpwWyKgkSRfOTTDmXBxzsw6H0GGQefWQ8kb84CQJZ3vLb8SZnc5tl3BuVo2x5RYyzlpuRm6KU/HQJAmDDM9vbxoX3eCj2SUJwrkJrICLY25jbEgnX55RssOHaeGa6IHdiOmBSgTe8UoGuBq6YDQpHodjbpdyf7KEh6PyUmhsiVorjW0yB8qURZRnhQjnJrhM8HdVoZKgsgnax3iuW1O7zH+PKjZ8f7IKuwFGdLnaS6T6gUGGPSXCuVkjBlk2RUsGuY2tLUNBJUlM9lf+PnjBuuva7hKZDgMk+2LR+PVwIBIn90J2bhEr1+/DIMvMTI1hWWaK2e+Nza38b9VOKmvrsVOruefqmQT7KWu3PfXKxzg52KOSJFQqFU89sHwsDmHcYK+W8HWGC03Kv5AxfJv+4IRMdYuSrXxe6OD2MTNY4kBnpOXSiOG1TzB0KpqU+YheTuAygC5nayTNX2JzgczBC3CtFS+Wu61Q+X/OKLXaQDi3HjEYDKxYu5dH71iCp9aF599cRUpMGEG+HqZt1u46Sqi/F9+/eQFllbWsWLeXx+9cavr9J3ctw83FaQysH58EuimOrbRh7JxbVbPMBycuJkcebGqgzGCJl7Jk9pTI6A3yuJhHdTkxHqcB9Eaav7Jk1MELyvSTkUxnNVg6DDK7S0YnK0lXRLdkD+SXVOLnpcHXU4OdWk36xAiO5hSYbVNaUUd8hBLPGuDjQVVtA7qG5rEw1yawhgTKbx2TaeqAmcEw2X/wN2GYVnHQda2QXTmMBgqGhfE6DaAnIjyUbr6KJqx23O3QBahvUxYjDtMK5zam1NQ34alxNX320LpSU99ktk2IvyeHTp0HIK+4guq6BmrqlYgICYmXPljPc//9mu0HT4+e4eOYsU6gXKiT+TxHRiXBDyYP7baQJMmUrURETVofttRyU0kS6cFKB5y1jrsZs5KMZpckiG5Ji7m0tb80M5mV6/fx+ze+JNjPk9AAL9Qq5aH4s3uvxEPjgq6xmZc+WE+AjzsxYQFm+u0HT7P9UA4A9109gyD/oSVac9cObe2IsdZH+jgDTVS22eOude13++Eu/7/ZavSygRviHUgLH3r5S2Lb+fh0A3vLVPzcAtvG+vxfTvqK1gagnWhfZ9y1jqNe/nDrpwW1sD63nePV9twziHtnqOX3pZdlmR3FOkDming33LU9u5zBlt/Q0PvbsHBuPeCpcTG1wgBqdY14uLmYbePs6MC9y2cBygX85T8/wdtDCb3y0Cjbal2dSY0LI6+ksptzm50Wx+y0OADqdDrqdINfZ91dqx33eg91CwAFNW3U6fSjWn5Bswtrz7bjqIZ7J3YMeF89lR+rkXFSw8lKPWfK6vBz6f2t1RrO/+Wkz69W6penXQt1utZxZ/+lpAe7As3sKWqjtq5jwONuI2l/TrVMaYMBb2cId26kTtfdtqGUb2xQ9IToluyB8CAfyqt1VNbW06HXs/9EHimx5qFzTS2tdOiVm2TH4TPEhAXg7OhAa1s7La3tALS2tXPyXAnBXQJRBD0T2BmSPdpZSmRZ5q+7lbHSm+Ml/F2Hp+vEUS0xtTPFkFjA1Loo7nzZDxnH0wC6Eu2lwsMRqxx3M3ZJzgqWzFavHw1Ey60H1CoVty6dzssrNmAwyGROiibI15NtWacAmDMlnrLKOt76ajsqlUSgjwd3XzUTAF1jC699sgkAg0EmPTGCxKiQMTuW8YK/C0hAeZMSXTXQ+WWDZU8J7C3uQOsA9yQOb5kzgyV2FMnsKpatOkz7cqKhTaauVclv6O081tYMD8b5bpsLlHG30FEM2uiPbaOclaQrwrn1QnJ0CMnR5k5pzpR409+RIX48+4Mbu+l8PTU8/dC1I26frWGvlvBxUd4+yxtHJ+ef3iDzz840W/cmSWgdh/cGzAxWwrT3l0KbXsZBbT0PncsVY6st2A2rDJsfLNY4362sUSanGpztMPVijCaiW1JgNQQaIyZHqWtyT4mSvT/QTeKm+OF/0Pm7SkR5QFMHHC4f9t0LBoEtpN3qibTOqSvG+W7WgDFRckaQ0k0/2gjnJrAaAjrHu0ZrXbdT1Uo5V8Q4jNjNJxIpWxfFNjTHrSsRHljduNtYTQEwIpybwGowBpWM1ly3/Drl/2hP9YiVkSmcm1Vhqy03a8szWd+mdJGqpYuL+I42wrkJrIbRjpjMr1MeApEj6NySfEHrAAU6ZaK4YGwpqu9suWlsq+UGXbsmx9gQlAhhvQwpfuA+zGPZliKcm8BqCDR2S47Cum56g0xB59SakXRudiqJDJGtxGoo6RJQYmtY07jbWCRKvhTh3ARWw2h2S5Y1QqsefJ1BM8JvlpnByv/CuY0tHQaZC43KlJNAG3Ru1jLu1q6/mCh5LKYAGBHOTWA1+HdGSxrnuo0kxvG2cPcRLQaA6UESEkp3UVO7cHBjRVkj6GXwc8Emp2VYy7jbwQvQ2A5RHmPb/Sucm8BqcFRL+DgrD6DKEV5gwTjeFuE+8jefp5PERB9lDbEDZSNenKAXbDWYpCvWMO5mjJKcPYZdkiCcm8DKGK3VAfI6W24TRqHlBmJKgDVgq9MAujLW426yLLN9DLOSdEU4N4FVYVzXbaSDSowttwmj0HID8ykBYz3Yf7lyObTcxnrc7XS1Mqzg6wzx3qNffleEcxNYFcYsJSM5HUCWZdOY22i13GK9lFyG5U1wtnZ0yhSYc7HlNsaGjCBjPe5mSpQcOvqJki9FODeBVTEaEZNVzdDQrsw/83IauXK6opIkMo1TAopEy20suNhys91uSYApAWM37mZKlDzG420gnJvAyhiNFFxdIyVHM3luZucNv6tEOLfRRpbly6JbEsZu3K2kXuZsDbjYw5SA/rcfaYRzE1gVo5GlJF83uuNtRqYFgJ0KjlVAXatwcKNJbauSwNrNXmmx2zIR7mMz7mYMJJkRJFnFVAvh3ARWRUCXMTf9CM11G+3xNiOuDhKpfmCQYa9ovY0qxlZbkMa2lrrpCUmSSOscd8saxXG3i1MARq3IPhHrufVCdm4RK9fvwyDLzEyNYVlmitnvjc2t/G/VTipr67FTq7nn6pkE+3lapBX0jpOdhKcT1LQoY2N+rsNfxmjOcbuUGcESB8pkdhXDkohRL/6yxRhMYiurb/dHWoDEpgKZg2Vw3Sis71bXKnO4XEmUbIwMHmtEy60HDAYDK9bu5Ye3LeaZh69jf3YeJRW1Ztus3XWUUH8vnn7oWu6/ZhYrN+yzWCvoG2PEZMkIdU2OVcsNLs53210ij1jLVNCdiy0363jwjjTGcbdDozTutqszUfJkf4Z90d/BIpxbD+SXVOLnpcHXU4OdWk36xAiO5hSYbVNaUUd8hLK8bICPB1W1Degami3SCvrGONetbATmutW3yVQ2g5P6YhfoaBKuVULR61rhZNXol3+5YlyB+3JpuZnG3ZqhcBTG3bZbSVaSrohuyR6oqW/CU3PxyeehdSWvuMJsmxB/Tw6dOk90qD95xRVU1zVQU99okRZg+8HTbD+UA8B9V88gyN9nSDa7a7U2o5/g1QTnW6npcMRd6zys5Z8r6wDqifBU4+l+UTOaxz8voon3j7VyoNKBmVHOo17+5agva6oHOoj1d8Vdaz/q5Y+FPiOkgXW57ZyscyI5xHHEym/Ty+wpVf6+KkGDu3bgq2wMtvyGht7nDAnnZiGXjkEvzUxm5fp9/P6NLwn28yQ0wAu1queGcE/j17PT4pidFgdAnU5HnU43aNvctVqb0nvaGwDIq2qlTtc+rOVnlyj7DnUzmDSjffxTfWXeBzada+G+hHarO/+2qC+o0wPgoWqiTmd+Q44H+wejT/Y2sC4XduY3szS0dcTKP1LjTFM7xHiCG43UDXBXQym/t2cuCOfWI54aF2rqLw741Ooa8XBzMdvG2dGBe5fPApQ5NL/85yd4e7jR1t7Rr1bQN0FuEiBTNgJz3cZyvM3IZH9wVENONVQ0ybgP7aVd0A8tHTIVTUqww0gEKFkryribbBp3G6ko0U15bcDY55K8FDHm1gPhQT6UV+uorK2nQ69n/4k8UmJDzbZpammlQ6+8De44fIaYsACcHR0s0gr6JnAEkyePdk7JnnCyk5jaOcl1t0ikPOKUdr5rBropi8deLozGuJtBltmUp/SuWNN4G4iWW4+oVSpuXTqdl1dswGCQyZwUTZCvJ9uyTgEwZ0o8ZZV1vPXVdlQqiUAfD+6+amafWoHldJ3rZpDlYc1RZ2y5RYxhyw1gZojEzmKZXSUyd08ZW1tsHVNmksskmMSIcb7bpgIlW0mYdvidz8kqpffB3wXivIZ990NCOLdeSI4OITnafDbinCnxpr8jQ/x49gc3WqwVWI6zvYSHo5JVoroZfIapV7elQ6akQemeChnjFEzKXCCZfaXKgLxg5CiuV87v5TINoCsjPd/NNHE7VLK6yfGiW1JglZgSKA/jXLdCHcgojs1+jNMDBbhKRHlAUztklXSMqS22zuU2DaArIz3fzRqnABgRzk1glVwcdxu+GzLPNN42bLscEjM6J3RvPd9/RKg1cqFR5rtr9Xx4vPdIPGvgcm65jeS426ELMufqQONwMd2XNSGcm8AqCTBO5B7GltvFSEnreMgZ0xTtLBx/zk2WZf6018DRCvjfkZaxNqdPLueWW9c8k8O5vluHQeYv+5RpNfdOchzznpCeEM5NYJWMRMRkvpW13JJ9wNkOzlYbqGgaX+Nu3+Yr+TEB8msNNLZbp/0GWaakS9Lky5E04/puZcO3z89zZHJrlfv0gbRRWhRxgAjnJrBKjCm4hnNdt4uRktbxlmmvvrhq8v5S63QOPVHXKvO3/Yq9DiplHDOnemxt6o3KZmgzgKcjuNpbx3UfbYZ73K26Web1I8p+Hk9X4WRnnedVODeBVRIwzC23DoNMQecbfLgVTZqeFqg8GPaVjrEhA+DlLJmaVmUy+hWRiv0nq6zTOV8uC5T2xXCPu716WKa+DaYHWc/yNj0hnJvAKgnsMtdtON42Sxqgw6A4TWcreoM3Orf9ZaO7avJg2VcqszpXxkEFv5iuIsFb+f6UlSaBNi51E+RmPdd8tBnOcbfsSpmvz8rYqeAn6SqrC//vinBuAqvE1UFC6wCteqgehngFa0i71RMR7uDnKlHVDLm1Y21N37R0yPxpjxJE8J0UiTCtRLy38nA7XW2djtnYchvreY1jzXCMuxnki0EkdyRIIzIpfDixaed24lwJ/1u1k39+9C0A50sqOZU/jvp/LnMCjHPdhqFr0hRMYmU3pCRJzAhRstTvs/JxtzeOyBQ3QJQH3JWonMcoD7BXwXkdNLZZn/3Fl3kwiZHhGHf7+qzMySrwdYH7kq3rPuoJm3Vum/efZMXa3fh5aThTeAEAe3s1X205OMaWCSzlYtfk0B+a1tpyA8gMVRIFWbNzO10t8+FJGQmlO9KYo9FeLRHrrSxxcrpmDA3shYsrcFv/w3gkGeq4W12rzL8OKefyx1MkXKyoa783bNa5bdx3gkfvWMKyzBRTbsIAb3cuVA9+aQfB6HIxYnLo+zJN4PawvpvS2HI7dME6U3F1GGSe221AL8Mt8RJJvubnMMlPcW6nrDCoRLTcFIY67vbGEZm6Vkjzh0Xh1ncP9YTNOrfWtna8tObrW+gNhj7X/xFYF8M1102WZc5bScLknvB1VRHloYwvHuu+ru2Y89FJmdPVSjDOw6ndH2wTfZWWp7UFlTS2ydS2KssL+Vi25q1NM9hxt5xqmc9yZNQSPGHlQSRdsdknfXSYP2t3HTP7btP+k8RNCBgjiwQDJdCUpWRoLYLyJmjqUOY6uTta5415cUqAdbV+iusvzmn6vwxVj91RicaWm5UFlRgzkwS5MawrS4xXBjPuJncGkRhkuDlOIspz/JxHm3Vuty3J4PDpAp565WNa2tp55tXPOHgyn5sWpY+1aQILGa6WmzWPtxmxRucmyzJ/3GOgVQ9LJkimdGGXEuOlxl4FBTposKKgkq7OTTC4cbe1eTJHK8DTCR6cNH4cG9jwkjfuGhd+8Z2ryS+ppFrXiKfWhQlBvuINbhzRNVpyKCsJW8MCpf2R6qdEHZ6qUgbvraGF+c05mf1loHWAx6b2bo+DWiLaU1nb63Q1TLGSzhFjwuSQyzBhck8MdH23xjaZVw4q5/CHaRJuDuPrPNqscyssq8LVxYmIYF8ign0BqNY10tTcSoh//6vqZecWsXL9PgyyzMzUGJZlppj93tzSxptfbqNa14jBILN4eiKZk5QFk5565WOcHOxRSRIqlYqnHlg+/Ad4GaBxkHCzh4Z2ZW03z0GmsBsPLTdne4lkXzh4AQ6UwcLwsbWnulnmxQPKg+3RqRJezn0/2OK9JE5WyZyqlpkSYB0PQdFy685A1nf77zGZqmZI9r2YiWY8YbPdkm99tR293mD2nV6v562vtverNRgMrFi7lx/etphnHr6O/dl5lFTUmm2zJesUgb4ePP3QtfzkrmV88u1+OvR60+8/uWsZv3roWuHYhohxXbehrA4wHlpu0KVrsmTsu/ZePCCja4P0ALjSggdbvBVmKhEtt+5YOu6WVyvzUefUjyfSVeOyx8tmnVt1XSO+nubxv76eWqpq+x/AyS+pxM9Lg6+nBju1mvSJERzNKTDbRgJaWtuRZZnW9nZcnR1RiUjMYWc4xt3GQ8sNzMfdxjIV165imfX5Mo5qeHK6ZdFxxkwl1jQdoMTYcrvMpwF0xZJxN1mW+et+ZerHdbEXs9CMN2y2W9JD60JBaRVhgd6m7wpKq3DX9B8TXFPfhKfm4jQCD60recXmMdrzpibwr4838vOXVtLa1s6D1881vd1ISLz0wXokSWL25Fhmp8V1K2P7wdNsP5QDwH1XzyDI32dQx2nEXTu0bMDWqg/3aoKiVmo6HHHX9t4v2Zu+ptlATWsdLvYQE6Dt9UFtDcc/zU3G3bGO0kYZHW6EadWjWj4o4yx/3qfMBf1xhjMTgy3rC04N1WKvqqWwHlSOGjQDHDMc7vPfYZApa6wFICFQi2M/meut4fqPlj4jpIF1ue2crHMiOcSxm37d2TYOlDXi7ijxs9la3J36f2kfq+NvaOj9rddmndvCaYm8+vFGlsxIxsdTQ2VNPRv2HOeKmSn9i3vg0mdi9rliQvy9ePzOpVTU1PPSB+uJDvPH2dGBn917JR4aF3SNzbz0wXoCfNyJCTMfZZ+dFmdyenU6HXW6wU8ud9dqbVbvZa90LedVtVCnaxuw/ugFY9ot0NX3/KpqTcc/xV9mUwFsPFPPDbGW9QQMZ/l/32+gtEEmzguujWjt9Zxfqm9urCfGE05Uwf7zugGNu43E+S+pl+kwKKmiWprq6Ss9qTVd/9HQJ3sbWJcLO/ObWRraaqZvbpd5frtyz30vFVRtDdT1UwXG8vj7mrdss/1osyfHctPiaRw7W8hnGw9w7GwhNy5K77EVdSmeGhdq6i8O8tTqGvFwczHbZveRs0yOC0eSJPy8tPh4uFFWqfR/eWiUbbWuzqTGhZFXUjmMR3Z5YcpS0jC47q7xMt5mZCynBByvkFl5Spms2zXFlqXEWVHXZNFlvPp2f/Q17vbOcZkLTRDnBddEj497pjdstuUGMCVhAlMSJgxYFx7kQ3m1jsraejw0Luw/kccD180x28bL3ZVT+SXEhPmja2imrEqHr6eG1rZ2ZBmcHO1pbWvn5LkSrpo9aZiO6PJjqAEl42W8zYji3GSyykBvkFEP0MEMlg6DzPN7DMjAbQmDG2eJ7wxCPmUFC5cag0mCRDBJNy4dd/PovDcKdTLvn1DO20+nqUat7o0UNu3cTpwrpvBCNa1tHWbfXzN3cp86tUrFrUun8/KKDRgMMpmTogny9WRb1ikA5kyJ58pZk3jn6x387vUvALhhwRTcXJyoqKnntU82AWAwyKQnRpAYZcUr+lk5pkVLGwc31y1fN75abkEaiRANFNUr88aSfEen3PeyZXJrIdgNHhrkZN0Eb8UxW8PCpcZpAMGi5daNS+e7JXc+nl48YKDdAFdFSST7jo/7pS9s1rmtWLuHgyfziQ0PwMH+4mFaesmSo0NIjjZ3SnOmxJv+9tC48OgdS7rpfD01PP3QtYOyWdAdrQO42ENTO+jawN1xYPrx1nIDSA+UKKqX2Vcqd0tSPBLk1ep586jikH4+XYVTP8EXvRHpAQ4qxTE3tMljOun34jSAMTPBquk63+1eYEeRzM5icLWHH0we/44NbNi5HTiRxy8fvKZb8mTB+EKSJAJdlYU8SxsG5tya2mXKGpXMH+NpIu+0QInPc2T2l8p8Z3DxTxZjkGWe2dxEm0GZz2Yc8xsMdiolU8kJK8hUcnECt208qIcbZdxN5tAFmdYOmb/vV4JIvjtJwrufCfvjBZsNKHF1dsTF0WGszRAMA8Zxt4EufVPQGYAVqmHAwRFjydQAUElwrFJx0CPJV2dl9pd04OmoZCIZKsaxurHsmpRlWazA3Q9dx92e2dJkWoT2xrjxc5/0h806t0UZibz55TbOFZVTUVNv9k8wvghw7VwdYIARk6Y13MZRlyQoaccSvKHDoKzxNlJUNcu8kqWco8fTpWHJZ2kKKhnDTCW6NmhsV7qzB9qNfbnQdX23L08rsf4/SR94hKw1Y7Pdkiu+2Q3AsTOF5j9IEq8+de8YWCQYLINtuV0cbxt/N+y0QInsSmXcbWbIyNj/4UmZhnaYFWbH4gmG/gUWEN8ZVDKWy98UGVttboybtcfGAuO4G8DiCZLV5AQdLmzWub36y/vG2gTBMBHoqjwwBzrXzTjHzRoXKO2PaYESbx2TR2y+W0ObsgAlwA/TnZGkpmHZb9egkvo2Gc0YBJWUmKYBjHrR4wrFmcm42MGP0mzLsYENd0saqdY1cq64fKzNEAyBwc51G88ttyQfcLaDvDoobxp+B/f5GZnGdkjzh0kBw/eOawwqATg9Rl2TRaZpAOPvuo8mEe4Sz86WeH25Bj9X2ztXNuvcqusaeOGdNfzmtc956f31AGSdzOfdVTvH2DLBQBlM8uR2vUxRvTL1I3Roae/GBHu1xOTOMZH9w9x6a9XLfHhS2efdicP/CEgwZioZo65JYzBJsGi59cviCSqmBNlmB57NOrf31+wmOTqEF392J2q1cpgTI4I4mVcyxpYJBoq7o9KKaWhXurosoage9LIyBWCw87bGmoupuIZ3v9+cU9bpivGE6UHDu2+4uPzNyTFquRV3dl+Lltvljc06t/zSSpZmJputQ+Ts5EBza/+JYAXWhXGuG0CZha23vHE4eftSjM5t/zAugaM3yLyfrezrrkRpRAIu4r2UfZ4e45abmAZweWOzzk3j6kRF9SWZwitq8XIfR7N5BSYCBhgxOd4SJvdEhDv4OkN1C5ytHZ59bi1U8gkGusLC8JE5NxEe4KhWWs+61tF1cK16mYomUEvgL/I3XNbYrHNbnJHEP1duZNeRMxgMMvuzz/Gfz7ewZEbSWJsmGASBrgNbHWA8pt26FEmSSB/GVQJkWea9bCXk/85EacTmNJkFlYxyEuXSBpBRcpLa0pwtwcCxWec2MzWGGxZMIetkPp5aV3YfPcs1cyeTkRQ11qYJBoFprpuF3ZK20HIDSA9U/h+OoJKsMiU1locjXB01sufF2DU52kElptW3RQfNZY9thsl0khoXTmpc+FibIRgGLq4O0P/D0iDLnO/skR7PLTe4uATOoQtKl5ujevBO6d3OVtst8dKIB9kkdAaVjHamkiJTwuTx/VIjGDo25dx2Hj5j0XYzU2NG2BLBcKMsWipbNOZW1gCtevBxZkwmEQ8n3s4SUR5K4ujjFYNPRny6WmZvqRJ1Ohr5A+OMmUpGOcdkSWcwiZjALbAp57b3eK7pb1mWyS0qx93VGU+tKzW6Ruoam4kO9bfIuWXnFrFy/T4MsszM1BiWZZqnZ29uaePNL7dRrWvEYJBZPD2RzEkxFmkFA2cg0ZL5NtJqMzItUCK3VslWMtgUSe91RkheGzM8OST7I8JdCSopblCCSrSjUCZAkZgGIOjEppzbT+5aZvr7w3V7SI0LY+G0RNN3G/edoNKCxMkGg4EVa/fy6B1L8NS68Pybq0iJCSPI18O0zZasUwT6evDIrYuob2zhmdc+Y1pSJCpJ6lcrGDieTsrDUtcGjW0yrn20yPJsZLzNyLRAiRUnFef2/b7X2e2RonqZjedl1BLcnjA658ROJRHjCccrlaAS49jhSFMiJnALOrHZgJJ9x88xf2qC2Xfzp8abte56I7+kEj8vDb6eGuzUatInRnA0p8BsGwloaW1HlmVa29txdXZEpVJZpBUMHEmSzFbl7gtbiJTsymR/ZU26U1VQN4jQ+g9OyBhkWBoh4T+KaZZGe/kbWZbFCtwCEzbVcuuK1tWZIzmFTI6/GFBy9EwhGhenfrU19U14ai5OkvHQupJXXGG2zbypCfzr4438/KWVtLa18+D1c1FJkkXaSzlUfpyFn93a429/m/MM9028BYC3T6zkJ9t+2+t+qr+Xbfp7/ic3c6TyRI/b3ZNwEy/OVfZzuCKbBa/d0us+N924klRfpfX72NZn+N/JT3rcbpLPRDbf9LHps9driT1uB4M/pqzqW6luPcm0j/o+pkPl2eQ03sZ3N8N3N1v3MVlynZzsJEK0J1hXfBsRb/W8T0uOKecYbC4d/WN6bIfyr+sxQWfd+3TodS/NP5lvr/+QymZlrDWnMYWwN0f2mLryYModvJD5y2E9poHUvVeX/JFbI5cDI/iM6OOY9t2zmmiXCcDo3091PzjZ6z5s1rndsiSD1z/bzIY9x/HUulKta6S0spbv3jBvUPu7NJFD9rliQvy9ePzOpVTU1PPSB+uJDvO3SAuw/eBpth/KASBzrnev5To7OeOu1Zr+7gvjdgBqtbrX7RzsHUzbujX1PdPVzdXVtK2Dfe+Lv6rVarPy+2Kwx+TQR6Sg8ZhkWe43wbI1HZOl12lykAPrinvf53g8puGqe8byzzZ0AH0PO4zEMXXddizup67lj8V16rrfsah7vSHpmwrHbuGlEaahqYXjucXU1Tfh7uZMUnQIbha03M4VlbNq+2F+fPsSANbuPArAspkXA0Ne+fBblmYmE9Pp0P7+3lqumz8FWZb71V5KnU7X62+W4K7VDmkf40X/v+MG/nVI5o6JEj+ecrFHvau+qlnmqk8MuNnDhltVFqWXGg/Hf7JK5v41BgJd4bPrzY+rN31ju8x1nxmob4PXl6pI8ev5XIyU/R0GmYUfGmjVw7pbVL0GsgxX+atzDTy7S2bJBInfzbZ8xGU8XH+h7xm1SoWbW8990DY75gbg5uLE9OQolmYmMz0l2iLHBhAe5EN5tY7K2no69Hr2n8gjJTbUbBsvd1dO5StJmHUNzZRV6fD11FikFQyOi6sD9P4+1nW8zZYWqoz1BK2DMt5YZOFi8l+ckalvg0l+9OrYRhJjUAmMTqYSMYFb0BWb6pZ8ecV6U4vpL/9bgxL20Z2f3nNFn/tRq1TcunQ6L6/YgMEgkzkpmiBfT7ZlnQJgzpR4rpw1iXe+3sHvXv8CgBsWTDE5z560gqFjnOvWV7ejrUVKGlGrlFRcG88rUZOh2r6Pr73Lsjb3jMCyNpYS7y1xvFKZ72ZMBD1SFImEyYIu2JRzm54cbfp7ZmrskPaVHB1CcnSI2XdzpsSb/vbQuPDoHUss1gqGjilaso+5bsaW23hcfbs/0gNh43klz+SNcX1vuy5PSSAc5QGZwaNiXo/EmzKVjPzoR0mDcQVu23qxEQwOm3JuR3IKmJYUCShhwcZJ1QLbwMsZHFRQ2wpN7TIu9t0fYraSU7InpgUoLdesMmU8q7fEwAZZ5t0RXtbGUpQckzKnRqFb0tRyE92SAmxszO1kXolp3auV6/eNsTWC4UYlSaalb3rrmjxvY3PcuhKkkQjRKIu29pWzcXshnNcpLd3FE8bWyU/ozFRS0jC4OXqW0tQuU9OivPz4uIxYMYJxhE213KJC/Hjh7dX4ebvT3qHnra+297jd/dfMHmXLBMNFoCsU6BTnFulh/ltDm0xFs/IwDeg/enlckh4oUVSvjLsl+XZ3XLIsmxIk354wcsvaWIqdSiLWC45VKA45YwRW/gZMk7cD3TBboFhw+WJTLbfv3jiPeVMT8PfSIkng66Hp8Z9g/BLQmWGjpIeISeN4W5hWCcCwRab1s77b4XIl5ZW7I1wTbR3nIG4UVuYWabcEl2JTLTd7OzsykpX12vQGA1fPSR1bgwTDTl/ruuXrbHe8zcjUAFBJSkuosV3G9ZJxR2Or7aY4CecexiTHAuPyNyOZhkskTBZcik05t64snzOZ5pY2yqrqaG3vMPstfsIoZXEVDDuBfYy55dUq/9vieJsRjYNEgjdkV8KhCzCrS1DumRqZXcVKt+zNo7CsjaWYgkpGcG23YjENQHAJNuvcdh89y4q1e3B0sMPB7uJhShL8/pGbxtAywVBQuiXlHidy23KkZFemBUpkVyrjbrNCLh5r12VtPJys5xyEdwaVlDYqQSUjseSOaRqAaLkJOrFZ5/bF5oN894Z5JIn5ZjaFqVuyh5abafVty1PyjUumBUq8dUw2G3craZD5Nn90l7WxlNEIKhETuAWXYlMBJV0xyAYmRo5QaJZgzPBxBjsV1LRAS8fFh3urXqakAdQShNq4c0vyUVbUzq+D8kblHKw4IaOXldD/QCtsvcR3BpWMxGRuvUE2jcEGijlugk5s1rktnZHMmh1HMcg2mxf6skTVZV23ruNuBTowyEq0XF+rB9gC9mqJtM4FKPaXydQ0G/jq7MVJ29aIKVPJCERMljUY0Mvg6wxOdtZ5/ILRx2a7JTfuzaausZn1e47j6uxo9tvzP7p5jKwSDAcBrko3VGnDxeAR03ibjbfajEwLlNhZLLOvFKraWmnVw8xgiPa0zod7grcyVnpyBIJKCnVKhGiQ6JIUdMFmndv9184ZaxMEI4QxgXJpo4wxOfbF1QCs8+E+3Cjz3WT2lcjsKWkF4O4xTJDcH+FacFIrre3hDiopqFOcm5gGIOiKzTq32PCAsTZBMEIYl74p6zLXretSN5cDE9yVbriKZgCZZF9laRtrRa2SiBmhoJKizpabmMAt6IrNOje93sCaHUfYezyX2vomPDQuZCRFccWsFOz6WVVXYN30FDF5uUwDMCJJyhI4a84px313omULs44lCd4SxypkTlbJZAQNn62FdXoAgkUwiaALNuvcPt10gPySSu64YgZe7m5U1zWwZscRmtvauWXxtLE2TzAEAi+Z69ZhkCnonAYQfpm03ACmB8GacxDlqTKbzG2txHsp/w93UIlxzC1ELHUj6ILNOreDJ/P51YPXmBYQDfB2JyzAm2ff+Moi55adW8TK9fswyDIzU2NYlpli9vv63cfZdzwXUJYYKa2s4y+P34arsyNPvfIxTg72qCQJlUrFUw8sH/4DvIy5NEtJkc5AuwH8XOiWjsqWWRguUdEEi2PdUEl9rOBqJRiDSoY7U4kpoES03ARdsFnn1vsMgP7fGg0GAyvW7uXRO5bgqXXh+TdXkRITRpCvh2mbJTOSWDIjCYCjOYVs3JdtFpX5k7uWmRyrYHjxcVbms1U2K/PbztUq3VKXy3ibEbVK4s5ECXetmjrdWFvTP2FaZX5eWSPUtsjDkkWlrlVG1yrjYgee4nYTdMF6w6uGyJSEcP61ciPZucWUVtaSnVvEqx9vIi1hQr/a/JJK/Lw0+HpqsFOrSZ8YwdGcgl6333/iHFMTI4fRekFfqFUS/p1BJRcaIbdGeXOPuEzG28YrapVEjKfy93AtXlrSGVQUpMHqxxwFo4vNttxuWDiVNTuO8uG6PaaAkvTESK6cldKvtqa+CU/NxQXBPLSu5BVX9LhtW3sH2bnF3LZ0uuk7CYmXPliPJEnMnhzL7LS4brrtB0+z/VAOAPddPYMgf5+BHqIZ7tqhTfAab/pQ93pKGjrQyS6cq2kDIMHfGXetYz/K4Slf6AennxTYxNGKVvIbHFiqdR5y+dUX2oBGJnja464dfL/keDl/Qm9OQ0MPy4N0YnPO7WzhBY6eKeSGBVO5Zu5krpk72fTbZ5sOUFBWRWTwwGOme3spPHqmkKgQP7MuyZ/deyUeGhd0jc289MF6AnzciQkzn5owOy3O5PTqdDrqdIPvV3LXai87va+T0lo7W97IuWqlA8LfsYU6XeuolC/0g9NHapTrdqikhTpd+5DLP1uu7M/PqWPQ+xhP50/ozVGreu98tLluybU7jxET6t/jb3HhAXyz42i/+/DUuFBTf3GAvlbXiIdbz2vX78/OI/2SLkkPjbKt1tWZ1Lgw8koqLTVfYCHGFFylDZBbc3mOuY1H4k0Llw7P/oo6X9zFNADBpdiccyu8UE1iVHCPv8VHBFFQ1n+oVniQD+XVOipr6+nQ69l/Io+U2NBu2zW3tHGmoIxJXX5rbWunpbXd9PfJcyUEdwlEEQwPxojJoxUyje3KytOeVrTMi6BnugaV1LQMfUpASX3nIqViGoDgEmyuW7KlrY0OvQGHHpqrer2Blrb2fvehVqm4del0Xl6xAYNBJnNSNEG+nmzLOgXAnCnxABw6fZ6JkUE4OtibtLrGFl77ZBMABoNMemIEiVHjYBLSOMOYgutoufJZtNrGB+rO5W+OlCuZSmb0/B5qMcWi5SboBZtzbgHe7pw4V0JqXFi3306cKyHA27KnYHJ0CMmXrAVndGpGMifFkDkpxuw7X08NTz907QCtFgwUYwoufefL/wSteHMfL8R7SRwplzlVLTMjePDXrV0vc6ERVNLFbmqBwIjNdUsunJbIB9/s4tCp86blbgyyzKFT5/ngm90sykgcYwsFw4GvizLXzYhouY0fTMvfDHFtt53FyqzVQDcV9ja+zJFg4Nhcy21aUiS6xmbe/no7HZ8bcHNxpKGpFXs7NVfPSe0W/CEYn9ipJHxdLmYpifAQD7fxQvwQM5VUNsm8lCWzIV9xjjND7QD9sNknsA1szrkBLMpIZGZqDOeKKmhsbsXV2ZHIEF+cHR3G2jTBMBLodtG5iZbb+CFMowSVXGiC6mYZdwunOOkNMp/lyLx2WAkiclTDAykSD2e40NxYP7JGC8YdNuncAJwdHXqNmhTYBoGuEodQUi/59zxTQ2CFqFUScV5wuFzJVBLR88wdM05Wyfxpj8GU2WRmMDwxTUWQm4SDWqJ5ZE0WjENs1rkJbB/jdIAIT3Wvk+wF1km8l8ThcplTVTJX9LFdQ5vSUvv0tIyMkhz7iXQVc0JFui1B3wjnJhi3hHV2Z8X5qBFjLuOLuM6gktO9LH8jy8qY2ktZMlXNSvDQbQkSD6RIuFxGKz8IBo9wboJxy/wwiebpcEW8M+h7zzEnsD6My9+c7CGopEAn88JeAwfKlM8pvvB/GSqiPYVTE1iOcG6CcYuDWuK6GAl3V9W4WPJFcJEwLbjYQXkTVDUZsENZvuh/x5V/7QbQOsAP0ySujpZQiS5IwQARzk0gEIw6KknJVHK4HLIr9DQ3y/xln4GizqDH5VESj6RJw7Lmm+DyRDg3gUAwJsR7K0Elv9nSSGmDMvYW6Q7/N11Fqp9waoKhIZybQCAYE+K9lP9LG2Sc1PDgJInbEiTsVMKxCYaOcG4CgWBMyAiSCNPKxPnY80iqngBX4dQEw4dwbgKBYEzwdJJYea0ad63bkBa7FAh6wuYSJwsEAoFAIJybQCAQCGwO0S3ZC9m5Raxcvw+DLDMzNYZlmSlmv6/ffZx9x3MBZUmd0so6/vL4bbg6O/arFQgEAsHIIpxbDxgMBlas3cujdyzBU+vC82+uIiUmjCBfD9M2S2YksWRGEgBHcwrZuC8bV2dHi7QCgUAgGFlEt2QP5JdU4uelwddTg51aTfrECI7mFPS6/f4T55jauU7cQLUCgUAgGH5Ey60Hauqb8NRcXLfeQ+tKXnFFj9u2tXeQnVvMbUunD0i7/eBpth/KAeC+q2cQ5O8zJJvdtRYuiiX0Qi/0Qm8j+oaG3nPKCudmIb2ltjt6ppCoED9cnR0HpJ2dFsfstDgA6nS6IYVCu2u1Qi/0Qi/0l51ereq981F0S/aAp8aFmvpG0+daXSMebj2vhrk/O4/0zi7JgWoFAoFAMDII59YD4UE+lFfrqKytp0OvZ/+JPFJiQ7tt19zSxpmCMiZ1+c1SrUAgEAhGDtEt2QNqlYpbl07n5RUbMBhkMidFE+TrybasUwDMmRIPwKHT55kYGYSjg32/WoFAIBCMHsK59UJydAjJ0SFm3xmdmpHMSTFkToqxSCsQCASC0UN0SwoEAoHA5hDOTSAQCAQ2h3BuAoFAILA5hHMTCAQCgc0hnJtAIBAIbA7h3AQCgUBgcwjnJhAIBAKbQzg3gUAgENgcwrkJBAKBwOYQzk0gEAgENodwbgKBQCCwOYRzEwgEAoHNIZybQCAQCGwO4dwEAoFAYHOIJW96ITu3iJXr92GQZWamxrAsM6XbNqfPl/Lx+n3oDTJuLo48cfcVADz1ysc4OdijkiRUKhVPPbB8tM0XCASCyxrh3HrAYDCwYu1eHr1jCZ5aF55/cxUpMWEE+XqYtmlqaWXF2j38+LbFeLm7oWtsNtvHT+5ahpuL0yhbLhAIBAIQ3ZI9kl9SiZ+XBl9PDXZqNekTIziaU2C2zb7jeUyOC8fL3Q0AravzWJgqEAgEgh4QLbceqKlvwlPjavrsoXUlr7jCbJvy6jr0Bpm/vvsNrW0dLEhPYHpKNAASEi99sB5Jkpg9OZbZaXGjar9AIBBc7gjnZiGSZP5Zb5ApKK3ksTuX0t6h509vryYi2Bd/b3d+du+VeGhc0DU289IH6wnwcScmLMBMv/3gabYfygHgvqtnEOTvMyT73LVaoRd6oRf6y0rf0NDQ62/CufWAp8aFmvpG0+daXSMebi7m22hdcHMJxtHBHkcHe2LCAigqr8Hf2x0PjbKt1tWZ1Lgw8koquzm32WlxphZdnU5HnU43aHvdtVqhF3qhF/rLTq9W9T6yJsbceiA8yIfyah2VtfV06PXsP5FHSmyo2TaTYsM4W1iO3mCgrb2D/JIKArzdaW1rp6W1HYDWtnZOnishuEsgikAgEAhGHtFy6wG1SsWtS6fz8ooNGAwymZOiCfL1ZFvWKQDmTIkn0MeDxMhgnn3jS1SSxMzUGIL9PKmoqee1TzYBYDDIpCdGkBgVMpaHIxAIBJcdwrn1QnJ0CMnR5k5pzpR4s89LZiSxZEaS2Xe+nhqefujaEbdPIBAIBL0juiUFAoFAYHMI5yYQCAQCm0M4N4FAIBDYHMK5CQQCgcDmEM5NIBAIBDaHcG4CgUAgsDmEcxMIBAKBzSGcm0AgEAhsDuHcBAKBQGBzCOcmEAgEAptDODeBQCAQ2BzCuQkEAoHA5hDOTSAQCAQ2h3BuAoFAILA5hHMTCAQCgc0h1nPrhezcIlau34dBlpmZGsOyzJRu25w+X8rH6/ehN8i4uTjyxN1XWKwVCAQCwcghnFsPGAwGVqzdy6N3LMFT68Lzb64iJSaMIF8P0zZNLa2sWLuHH9+2GC93N3SNzRZrBQKBQDCyiG7JHsgvqcTPS4OvpwY7tZr0iREczSkw22bf8Twmx4Xj5e4GgNbV2WKtQCAQCEYW0XLrgZr6Jjw1rqbPHlpX8oorzLYpr65Db5D567vf0NrWwYL0BKanRFukBdh+8DTbD+UA8PD1s3B0sB+0vaXllWhcnIRe6IVe6C8rvcFg6PU34dwsRJLMP+sNMgWllTx251LaO/T86e3VRAT7WqQFmJ0Wx+y0uGGx7eWPNvPUA8uFXuiFXugvO31vCOfWA54aF2rqG02fa3WNeLi5mG+jdcHNJRhHB3scHeyJCQugqLzGIq1AIBAIRhYx5tYD4UE+lFfrqKytp0OvZ/+JPFJiQ822mRQbxtnCcvQGA23tHeSXVBDg7W6RViAQCAQji2i59YBapeLWpdN5ecUGDAaZzEnRBPl6si3rFABzpsQT6ONBYmQwz77xJSpJYmZqDMF+ngA9akeS2ZNjhV7ohV7oL0t9b0j6pkJ5RPYsEAgEAsEYIbolBQKBQGBzCOcmEAgEAptDODeBQCAQ2BzCuY0DdhzKYeX6vegNBmR54EOkQi/0Qi/041U/WES0pBWTW1TOul3HKK2sRZZlblmSIfRCL/RCf1noh4pwblZIS2s7H67bw4VqHYsyEnF1cuBwZ35Kg8GAStV3g1vox7e+ubWNj9btHbf2C73QD0U/XAjnZoWU1+iIDPblnuWzUEkSWSfz0TW2AFhUMSpqdEQMQV9WVUdUiN+g9Req68bU/qHqh2p/efXgr59eb6BG1zRm50+WZSpr64kc5PUfqh6GVv+Ho/yhXP/G5lbqGprGtP4N5f61BvuHC+HcrIQT50rYfug0Ny6cSliAN2EB3qbfzhSUEeTjASgPP7W6ewXZeyyX82VVRAT5kJ4YSegA9blF5WhdnfD11BIW6M2EIJ8B6fccy6WppZXoEH/CA30IDxyYfqj2D1W/P/scTS1tRIcOzv4DJ/Ko1jUSEeRLTJg/YYEDL3/trmMsnp7E9OQosyWSRuP4D5zI4+Cp81yRmUxogDch/l6jqh9q/R9q+UO9/odPF/Du6p3EhgXw8E3zzRI3jEb5Q71/h2r/UO//kUAElFgJBaWVlFXWca6ogpa2dgDaO/QAuDo54uSorBpgrBh6vZINu7Wtnbe+2s6uo2eJCvHjf6t2cjq/1GK9rrGZv777Df/86FsOnSqgvUOPSpKQZdm0TW964zafbTrA1gMnMRhk3vxyGyfOFSvbGPrXD8X+oeoB2to7eOfrHew4fAZ7OzXvrt7JqbwSs2360lfW1vPiB+vYfigHF0cHXv9sM2cLL1hcPiiL227af5KbF6UzPTnK9P1oXP8aXSMvvLOG3UfPMndKnJlTtOT4h6o3Mtj6P9Tyh3r9L1TV8Y8VG9h+6DRLZySjUknUd7ZSOvQjX/+Gcv8O1f6h3v8jjXBuVkJLWzsB3u7kl1RQUl4DgL2dGoC8kgo0rsqSEI3NrXy+OYvsXKUCGWQZCbh3+SymJExgUUYirW0d/eqPny0ClJtrcnw4Ny1Kp7GlldyicgAkSTJVxN7KN25TUV3P7VfMYFFGIktmJPHt3mzKq3WoVf3rB2v/cOhBeYB26A08cN0cMifFMHNSDO+t2U1VXUO/xy/LMuXV9WQkRfH4nUuZNTmW9MRI2totP/8A2bnFzJsST3xEEM0tbaaHi6XXnyFc/9r6Jlpa27huXhpx4YEmxwL0e/wANfWNQ9IbGWz9H2r5Q7n+BoOBU/mlTE2M4Ee3LSY5JsRktyzL2Kktq396w+DKB+X+TY0b3P07VPuHev+PNKJbcgw4cCKPIF9PAry1qFQq9AYDGlcnJseFs+dYLiUVtQT6eCCpJJwc7PHUuBLq783GfdnsPXYOdzdn0hMjAGhoaqFDr2f3kTMYZJkNe44zIyWahuYWMifFAOCpNdc72Nvh76VFlmU8NC7Mm5pAa2s7G/Yc51xROSF+nri5OJnWSrpUPyHIh8ToYGRZpqW1HU+tC7qGZmRZJnNSDGcLyzl8uoBF0xORZblXPUB1XSN6gzwg+4eq17o6Mzk+nPaODuoamuno0NPU0obW1Zmk6BC+2XWUozmFzE9PQK83dNM7OdgTGx6AJElEh/rhYK/cRt/sPMqOQzm4OTsCEhMjg3rUG8+/sYvG11NLXWMz2w+eZtvB03i5uxId6k/mpBhcnR27Xf+u9jc2t6IfxPX389QCEOjrwZy0eDbvP0mQnyfHc4sI9PEgNiyAyfHhPdrvoXEhIykSWZaZEOjD7MlxA9Ib668xuGCg9X+o5St6pYVcW9804OvvoXFhWlIkKpWKuVPiTfe1j4eGs4UXKK2sJSLYF73BgNTD+XdysCcuPABQxscGU35GUhQGgwEfDw3zpsTT1t5h8f2rdXUmNS4MgywPyv6h3v+x4QGm+3ckEc5tFLlQVcfrn23B3c0ZFycH/L3cWTYzGXs7O/JLKkmKCmHulDjeW7ObzQdOcsuSacSFB3LsbCFHzxYSEeRDa3sHeoOBb3YcJdDHgytnpbBkRjL7s/PILSrnD4/cRGlVHau2HSbU34vQAG+OnSnk6JlCgn09kWUZNxdHYsKUh7Px7czZyYHY8ACOnClU3uYmRpgGf4+dKeLomUJC/DypqNEpb2ydvzk7OSDTOYgd6oezo4NyDKt3MTstFmdHB1P5PemD/TyZOyWOY2eLOFNwoU/7h6oP8vFAlmVkZLZlncZT68LyOZPRuDqxftcxfL205JdUkhY/ga0HTzE7LRY7tdqknxgRxLXzJvPG51v5eMM+Eh++3uTYyqrqAHj8zqXoGptZuWEv/3fvlbg4OXK0l/NvfLNWq1VU1NZT3NzKT+5eRnmVjg17s/H11JIaF8axs0UcPdu7/QvSJ3LkTGG/x9+1/NhwfwCcHOyJnxDA3uO51De1cOOCqRSUVfPZpgPETQjAxcnR7Py1d3Sg1xv4YvNBokL9WJyRSFJ0MPss0Hetv2t3Hh1w/R9q+eb6LKLD/FkyPQmtmzPrdh3Dr5/r31X/1ZaDRAb7sSgjEbVahV5vwN5OTXpiJGcKLxAR7Guqo8fPFnWrPyvX7+M337ueqBA/dh05Y1H961r+l1uyiAzxY9E0pXxndf/3b9f6s/1gDh4aF66aPQm1yjL7h3r/T4wI4qEb5uLb+WI10gjnNopU6xqJnxDIzYunUVJRw6Z9J/lq6yFuXJiOj4eGipp6tmadorK2nqgQP0L8vGjv6GBaUhRJUcHIKBXNqN+49wRfbjnI9QumUt/YgpuzI+4aF9w1Luw4lMOh0wUE+LgzLSmKqBBfth/KIW5CIDctSgeUPnU7tdIFIUkSseEBnC+torSytvMmklGpJKYlRRIX7k9xRS3piZFszTrN/uxzpCdGAjAtMZI1O44QGeJLqL8X4YE+eGhcOHTqPFMSJpCRHEVsWO/66FB/2jv0uDg69Gp/X+Vboo8M9uH42WIWTZ9AcnQIB07kmbpwrpiZwoVqHdm5xcycFENKbChVdQ3kFpYTGuBFRnI0iZFBxEcE0djcypLpSWSdzGf19iNcNXsSBlnG30vLFTNTTNd6474T7D56ltmT45ieHEVkcPfz39begYO9HXHhAZzKK6GlrR0HezvCg5Tzl1tUTkJEINOSInu0/1xxBbIsExniR0tbR5/H39P1b+/owN7ODl9PLfcun0WAtzsAoQHe7Ms+x55jucxKjSUjOYqIIB/2HDvH9RmJpMSEcuxMIcdzi6nWNeLt7sZ918zGvw99YmT3+juQ+h8ZPLTye7L/2Nki6htbuGrWJEoraznex/WPCPLups8+V0xVXQN+XlqzFxW7zr8NBgNNLW1MS4rqsf58vfUQy+dO5qpZk6ioqR9S+UCf929P9Se/pNI0Ptef/bFhfkO6/xMjg4mPCBq2Z6klCOc2ihReqKappQ2AAG93Fk1P5PVPN7M4I4mGphb+88VWrpuXxq1LM/h04wFyzpeZxsMA1u85bqZfPCOJ1z/dzOy0OJpaWqlrbKZa14iX1hU7OxUh/p7Y29lx48KpSJIyUFzX0ExecQXHzhTSrtcTGxZAZIgfrs6OqFQqZqbG8PW2w7zw9hoam1t5+qFrTeUH+nri46HB2dGBVdsPMyk2DAd7OyKCfQkP9CHrRD66hhZS48Kwt7cjPNAHRwd7blzYsz41Lgx7O6UKllfrqG9q6dH+3sq3VG88/kmx4aab+PDp87S2dVB0oRpvDzfiJwQSPyEQUIIU1CoVE4KM9k+9eA3Lqmhubed7Ny3gD//9iqtmT0LVudS6QZZRSRJt7R14al2JDvHHwd6OGxb0fP7bOvTEhgcwMTKI6SnRZOcWs/vIWWZNjqW1rZ3QAG9T+b3ZX1xeQ4CPO7rGZrPrr1ZLA7r+Ad7uppectvYOtK7O3ez39dSalnWKCPblyy0HWZaZjEqlMj1ggW564/W/tP5aWv+N9g+2/L7sb9fr8dK6onVzJq7L9bdTq03X/4YFU3rUf7X1EEtnJJtde38vLZv3n2RB+kRUKhVuLk591p/lcyfj5e6Gl7vb0Mvv5f7tr/74eGhMAR992T/U+3+0EQElo4Bx0H96chTZuUVU1NSjUqkI8HZnclw4m/af4PZl0/njj29h3tQEfDw0zJ0ST1J0CAaDoW99fDjbDp4mKTqEpuZWPlq3l2ff+BK1SkVyp96Y8GZachTlNTre/no7re0deGndyDqZzzc7j5psPXy6gB2HcogM8eNXD12Do4OdKWWOj4cGgMnx4Xi4ubBhz3GTbuG0iUSG+LHt4CmefeNLQMbfW2uWcudS/frdF/XJMaE0NLeY7AcU+2V5UPquxy91Oh/jjf3V1kO4OjuRHB3CziNnWLPjCKAENWzcd4K/vbcWD40L9nZq9J0RY0a8PdwA8PXUkBwdyu9e/4L31+wCoK6+ia1Zp/jzO2twcXQg2N+zz/Pv7e5G1ok8Vm8/QkpMKJmTojmVX8ILb6+mXa9nenJUv/bvOJzDul3HSY0LM7v+yAz4+je1tJnsd3N2JMjPwzRuA0qLSKVSmeqkl7sbMpicYlNLK9t60A+1/g+1/L70gKmOtXa5/j4ebqbAit70nlrXi+V3bhMR7IvW1ZnK2npl3wbzqMC+6k9LWzub9puX37X+9VW+8QXLeP+GB/ko96+jfb/1f3Vn/e/N/sHc/w72avy9R6f7sTeEcxtmCkqrKKmoMftOJUnU1jehdXUmc1IMX2zOApRQ2cgQP1rbO2ht68DJwZ7s3GJWbz+MwaD0gatUqr71wX60tSvaO66YQfyEQGLCApiSMAF7OzuTvq6+CScHexZOS+S+5bO5efE05qcnMDM1ltr6JnQNzQBU1tUzJy2WzJRoXJyU1pwkSegam01lAly/YAq7j56lqaVVOUaVxJSECcxMjaG9Q09ZZR12ajVqC/UeGhfuWz6buAkBeGhcmJoQodgvSQPSR4f6ETchkMxJMabjB0zHB7AsM5nbl01nzpR40uInUFnboOxfhqraBhzt7XBysEelUqHuHJM06sur6zEYDJRV1VFWWUtFTT3RYcr4VVVdA6fPl+Lv7U6grwd2anW/53/W5DgqanTUNTQRHuhD+sRIEiKDmJMWh4N9F/sbe7Z/SkIEhReqQIY7rphBXHgAqs63fMuvfyONza3U1jdxpqCMqFA/piZGmOzvev6NLYTyah0tbe14aV2VqFWDgYamVs4UlhM3IZD0pAiz47e0/h87U8iH6/ZQXq0z1f+BlJ9TcIGYMH+mJ0dZbL9KktAbDNjZqalvaOa6eVO4dl6aSWtJ+cZpC8XlNQT5eVJereu8L8zrX1/1p6NDT2VNA0lRIaTGhpnqnyXlGyN0q+rqiQ3zJzU2TLl/Ox1bb/UnLX4CVbX11NU3AUrvkrvGmRPnSkz2D+T+v/PKTB65ZSH3LZ9tGs8fK4RzGyba2jt488ttvPDOavYdP0dDU4vpt9yicr7YkoUsyyzLTOF8aSUHTuShVqloaWtHr1fexN74bAurtx/G1dmRlev3sevIGQDOFl7oU28wyDS1tPHO1zvYn32OAG9tN/3nW7IwyDITgnyICPY12VbX0ISzoz1uLo58vukAp/PLCPDx4IstB036c0XlfLbpAHqDQRl8NhgI8fdi6sQI3vpyO//9Yhtrdhzhv19sZdO+k8yaHIu/l7spyCK3qJzPN2X1od/Kqm2HefXjjWSdyGdmagxJ0SFm568//bpdx9i0/wR7juXi7ubMyvX72H4oR7G/uJzPNh8w3ZjGIBBQbnqNixNaV2eq6ho4W3iBZTNTuHpOqmmbs4UX+GzzAWRZJtDHnX3Z5/jnR99y/YKpXD0nlVXblJeRIzkF1OiaSI4JYe3Oo2w5cMqi8+/i5IidWs1/Pt/K2t3HQIYV3+xhz7FcQJkEazz+nuzXujrj5GhPRU09e47lsjQzuZv9/ZXv6uzI6fOllFbW4al17X7+Oq+/8WFZWllHSkwo7R0dvLtqJ9sP5vDV1kNU1tbjaG/Xzf7+6r+jgx2fbtzPmp1HiQj27X7+Oo+/t/L3HMtl5+Ecquoa8Pd277X+9qhfvZNdR87wztc7+HZfNoUXqrrdv32Wv3onOw+f4Y3PtrBp3wm83V273X991Z/V249gMBjYsOc4eSUVBPgM3P7dR8/w6scbyTl/gdlT4nq9f3qqP24uTmhcnfh043427z9J3ITAXs9/b/f/xn0nAPDu7GK1BsSY2zDR2tZBRJAvEyOCKKuqI6egjLT4CQBEhfgRFeIHgJOjPbcszmD30bMcOJFHcXkNV86aRHm1jtjwAFNobof+YndAdKg/0aH+w6I3UlvfxPZDpzl06jxLM5NBkmhoauX2ZdMJC/AmwMed1z/dQoi/F5EhfkR22g+YIqWaWto4mVfC0sxk/L3c8dC48sB1CTQ2t5JXVGEamO56/L3ppyVG8tZXxSzKSCQtfoLpRrJUf8XMFD74ZjdXzExh6sQIIoJ8+WJzFuEB3kQG+xEZfFEPyhjd3uO5yvF3jlucyi8lMSqYqRMj0BsMNDS24K5xMTt/jg72PHj9XOLClfGRiZFBONorrbzmlnZuXDiV6FB/9HqD6W3akvNfUFZFoI8HD14/F4AQfy82HzjJ9OQoYsICiAkL6Nf+0+f7t7/X6w+UVdb1e/6MXYCVtfXsOZrLvuPnmBwfjp+3lobm1n7t763+SpJES2v/56+38jOSo/hgze5+629v+tS4cAwGud/7tzd9eJA3apXEnH7uv97qD0C9Bfdfb+XHhQey52guCy24f3qqPyqVyqLzDz3ff1fOmoS1IZzbEMjOLcbN2ZGQAC80rk7MTI3Bzk7Nht3HKSitItTfC19PbbdkoSmxoUSF+rFp3wlmT45lYmQwkiSZ3qj3HD3Ll1sOsnBaollU0qX6DXuOk5EURWJUsGlg1xI9wOYDJ6ms1vH4ncvQuDpRWVtPU0sbskG5IePCA9G6OpN1Mp8QP89uOeFO5ZVQ19DEd66dQ3JMqGnCLYCrsyPlNTrOFpbj46HpMVmqUf/AdXNN9i+cNpHDpwuob2zhyJkCgnw98fXQMD89oZv9XfXGQBA3Z0c69AbaOwM1YsMD2Jd9jkBfDzP7ALZmnaKovJrr508lIVLRe2ld0TU0kXUyn7U7j+LjocHbw42lM5JNk1BdnR1ND6aDJ/Nxc3FiRkoUTS2t6A0GjuQUcr60ks83ZZGRFMU3O4+aRVF2Pf/nCsuVaL6kKOoamkzRiqA8BI0puLo+qLraf760ktmT48jozGripXWjrr5v+y8tf/bkODKSomhta0fj6tTv+TOO35wvqcTL3ZVpiZHMT08YkP3G+rtmxxFiwwOYkRJNVV0DeoPc7/m7tPyMpEjmTU2gvFpnUf3tZn9SJPOnJtDW3sHM1FjUalWf929vx9/W3mF6Aejp/jM6JbP6cyofDzcX5k2NR9fQTGNz66Dtb21rZ2FGosX3z9asUxReqOaauWkkRATS1NJKh97y+nsqrwRHBzue++HNaN2cu/1uDYhuyUFwvrSSv777Det3H2PV9sOs2X6EhqYWZYxEUibvtnXoOZVfZroxDAYDFTX1bNhznPOllbz2ySbOFl5gy4FTrNp22NQNUq1rpK6xme/fvIBJsaF8tfUQxZ0ZG8qrdSb9fz7faop6+2rrIRqblb7vmn7063cfp7SylsOnz5NTeAEnR+X9xsdDg7+3lk37T7BmxxHe+GwLSdHBHDp1nmpdI6Ak5DWWv3b3MVpa2zl+togvtxw02W9MqzMjJZqiC9WA0m9vTGh7qd5of3NLG3HhgbS1d7D3eC5XzUplYkQQ63cf6/H4u+pX7zhCe4ceJ0cHSitrae3MUrEgfSKn8kqoqNGZHX99YwvnS6vQ62V2HTnDqm2H0TU24+xoT0tbB4dPF/DA9XO5bWkGtfWNHD1TiN5goLK2nm/3ZnO+tJKXPljP1qxT7Dl6lq+2HsLezo756QloXJ3YfeQs/3fvVSzJTObomUJTNpCKGp0pCGZuWhwNza18ufUgbe0duLu54Kl1NdWxxuYW0ziNWqXCIMtU1NSb9AvSJ9LY3MYXW7JMb9gdej3tHfo+7b+0fKPe0cEelSRR1s/5W7f7GAB3XZlJS2u7SW+p/cYghA69nhPnSvhyi3L83u5uzEyN6ff8XVr+55uV8v28tPh6afqtv93s79Q72NuhVkn93r+9Hb+xq6+3+0+SJMqrdXy7N5v6xhb++u43bNp3kg17svl8cxaODnZEhviyYW/2oOx3dLAnIti33/tn/W7l/ikur0ECjuYUDKj+Gq9f7IRAblyYbrWODYRzGzDtHXo27jvB1IkRPH7XMpbNTKGppY2KmnrTNqEB3gR4aamo0VHf2IJer9wgLk4OeGndetSXdz5AvLSuLJ2RzMTIYCKCfYkLD2TLgZMAuLk44qV1Y+fhM6QnKvpZabE0t7ShUilvdJ796H08NZzOL2NB+kTC/L3ZuPeEye6lmcnMmRJPe4eeiZHB3LgwnYSIIM4WKLkS3ZydTOVPS4w0K984X84YkSVJoO60yRjx5+rk2KO+qdN+NxdHblqUzpP3X01MmD9J0SEkRYewNetUt+M30ze3Ym+nZurECRSVVZNfUklLaztaN2eiQv3Zn51n0vt5aalvasHPS8tP77mCGxcpYc5fbj5IfEQQHXo95dV1uDgpc8ZiwwPJPleMuvP6eWpcezz/eoOBsABvkqKCmRgVTFigN/5eWiZGBrHn2FlAafUZQ9Y9NC5MT4kiIsiX9zqj5bpG1p04V0JKTCiAcn0lCRcnB5PeU3tR/+7qnQDEhgXQ1q6nvFrXq/09lf+/VYo+IzmKwn7On7+X0jrzcncdlP3GCbwaF6du9keF+PV7/noq/3+rdij1d0b/9bcv+41xkX3dv33qOyMY+7z/PDTUN7Xg62le/z75dj9LZyQzb2o8be0Ds//d1Ur5Hm4u3Ly47/vH273z/kmKHFT9NV4/49ifNSOc2wAwyDL2dmqumJliSt8TFeJHfkkFcuetYbzBZ6XFIUkS//5sC0/8fQWllbU4OzkwZeKEHvW9YW+nNg0OOzkq+psXTzOlVso6kU9pVR0lFbWmnITG0OtL9c6ODqTFhzMpNpS5U+K5fsEUdhzOobquQdm/gz1RIX5cOy+NmakxpkmcxmguR0f7XssvrqihoanVVO6EIF/2HT8HKC03gyz3qi+rqjPNAfTz0prZr1Kp+j3+smodZwou4OXuxvSUKA6fLuDgqXxAaSEYxwtcnBxJjQujtLKW2nrlbdhT68qijEQKL1RztvAC86cmEB7ow+6jyg1d19BEoLc7eoOhz/KLLlTT0tpOQ1MrusZmyiprlfI79ESG+GGQZVP5ABU19RRdqOEHtyzk+Nki6hqaTF1PxnoWEeLHul3H+OPbq6iua8DVuWd9dm6xEo3o5sz0lCjCA717tL+38k+cK6ZG14iPh4b0pEgOnT7f5/kbCfvrGpo67W1G1zCw83fiXAl19U24OjsSFeLH1XNSe6y/zk4Ofdrfteu0p/u3N/uNemOXYVcn3/X+663+Lc5IpKCsimNnCokO9eeauQOzPzu3iLr6JlMqt67lW3r/DLT+jgfEmFs/VNbWm8aN6Ky8gV2Wb0ACrZsLdiplTMJ4g+fkl7JxbzYTI4P41YPX4NWly6YvPShhw6fPl7Jx3wn8vLREh/qbEgTDxYSyW7NOUd/UwsxJMRw6dZ7mljbuvnomTc2tnMwrYeO+E8pk4lB/k/3GXHGgDPonRATx9bbD3Lt8FjIgoUR+Hj1TyNdbDxHq743GxQm9Xm86tv7KB2UyaJCvJ0dOFzApLgw6xxx60x8+XWDSd3ToOXa2iPW7j+Hl7kZUiJ/ZfK+e9ec5cCKP25dNx8XJgW0Hc9hy4BSODnZMCPIxHb9KUkKWP9t4gJN5JSREBOHm4sS8qUp+xYdumMfCjES+2XmEv7+/DmSZB66fi9R5bvqyf3+2Uv6BE3l8te0wFdU6NC5OLMpIAll5/TEeg7ubCy5ODjjY27FkehJ/ens1of7efP/mBSDL7D2WS3ZuMRMCffjx7Uvw0LiYxm1600cE+/LdG+bh5uLEul3Hutnfl/6Fd9YQFeLLg9fPw9XJgZ1HzrDlwCmcHe1N588YFj8i9r+1msgQXx64bi5ZJ/L5etthygdy/t65WL5eb+DQqfM91l+L7Adyzpd1u3/7O/9GvTIloYxv92bj7uZsdv/1Xv8S2HnkDMkxoegNBg4O1P4ux9/Wrif7XMEA75+e66+Ph4ZFGUnjoqV2KaLl1gslFTW8+P46fv+fr0xzS1TSxeUgjF1wyptmk2n9LuP4R0VtAwE+HuR0tigs1RsMBvQGAyfOFePrqWFaYqSSPaTzwWLUA2ROiuY7185hZmoMM1NjaGhu5UK1jubWNmWeigzODvam7CNdyze+3V2/YApnCi5wvlRJxWNMAVVZU4+DvR3HzxVhb29nmm/TX/ld+/db2tp56+vtpvNnib6sqo7G5lZO5ZUgIZnZ35d+1uRYanSNlFXWkhgVwpLpSajVKgovVOPs5GA23wpg2cwU0+RtUBy9o4M9tfVN+HtpmTslno4OPefLqnBzcbLI/hpdI1V1Ddy8eBrTEpXcfudKKnB16T5fsLK2nvb2Dipr68kpKKOxudXUZVhUXkNMWACuzo5k5xXjqXXtV9/U0oq3u/LSEuDtzpwpcT3a35feQ6Pok2NCmZ+egIO9Hd7ubmbnf6Tsb2xpxd3NBUmSuH7BFNKHcP70egPVdQ091l9L9ABVNfXd7l9L9fVNLZzMK0GvN3D6fJlF9S/YzxNXZ0fTOOVQ7K9raBrw/XNp/b169iTuvDKTh2+a3y0YabwgnNsltLV38NG6vbz91Q7iIwKZGBlMbuf6XJW19by3Zictre2mt6Di8hqiOrttVq7fy8a9J/hw3R62HzzN1IkTBqT/aP1e1u85ztpdxyguryXEz4sNe7P5dOP+bnrAlHoKoK2tA3s7Nb6eGhzs7SirqmPGpGju6mxJXao3ZmN3cXLkqtmT+Gj9Pt5bvYvPNh7gw7V7OHjqPFP6sL+38r3dXflo3V4+XLeX5JiQAev9vLSoVBJF5TV92t+T3sHeDg+NCx+t28tH6/cyKTa0W/kr1u6mpbWd2ZNj6dArCXwBkKGltQ0XJwc+WreXFd/sGbD9DvZ2uDo58NnGA6zZcZTJ8WHd9O+v2UVLazu+nhrySip54e01pCdG8sB1c9m8/wRt7R3sPnIWXWMzaQnhA9SfNNXf3uzvS28cG6praOKLzQdJT4zodv5H0v6tWadoa+9g1bbDQzp/X209xIET+T3WX0v0H63by9Ze7l9L9DsO5VBYVt1j+X3Vv6aWNpwc7flsY9ag7QdlusVg7x/Pzsw8Qb6eZguejkckfVOh3P9mlw/ZuUUUldco2b5VKv77xVYWpE80hdlfGta8/VAOX2zOwsfDjahQf+InBFBaWTdofWZKNGcKLjBrciz2dmqO5BRQUFbFVbNTUXVmQuga1l6jayTrZD67j54lIzmKxRmJHMkpIOvkeR64bo5pG62rs5K9vIew8m/3ZvPpt/uZMyWeiZHKPB9L7b+0/GBfD4ou1LBo+uD0A7V/wOV3WQm4uLyGLzZn4eToQF5xObMmxxLq7zUk+y0tv7WtnfOlVUQE+5geMpv3n8Tbw42SiloWD1Lv06kfbPlzp8Rx9Exh7+ffyu23Bn2xBcffW/0L8fOiuHzw9aff69dP/V0yPcms+3U8I8bcUNImeXfOqk+IDCYx6uLs/pbWdo7kFBIR7IuhB8dQdKEaL3c3HrphnjI2J8ukxIQNSR/i7wXAybwS3vl6B+mJkew4eJo5U+K7zdc6eCqf42eLeOiGefh5apAkCW93N5wc7MjOLWLV9iN4uLng6GDHtfPSzMK1AQrKlCziT3/3OoJ8PTDIMpNiLbe/a/kB3u4YZHlA52+o9g+4/C5L3Af7eXL/tbM5klPIVbMnDdn+gZTv2LkmHChLIfl7uzM/PaGz/oQOSZ88SP3cKXGoVCqLzr812j+e9NB7/euaXWSkrp+Rg6fyyTlfZqq/gE04NrjMuyXrGpr4+3tr+dUrn5jmkhgvq2m+1qRoahsaae/oMM3XamxuZdW2w9Q1NFFaWUtRWdXFSZZD1BsHbhubWymrrOPOKzNZMG0iW7JOcSSnAID6xhZWbz9CXUMTR3IKOZ1fapaHsLm1HTu1mn3Hz3HdvDQeunEeMrD/RB5t7coCl0b9p9/uZ9fhM6as4Jba31P5Q9UPzP7DQyp/zY4j1Oga+fcnm/nf1zuGxf7BlP/399bym9c+H3D9Gwn9QM6/Ndo/HvWDrX9DvX6rtx8GYP7UBH5wy0KzCfi2wmXp3Dr0ei5U6ziVX0pyTCgZKVF80zm4e2kGbYNBRq1SYW9np0QsShKODnY4OthzKr+UlJiQYdUbU/a4OjsyPz2BKQkT8PfSMjM1hk2d+ducnexxsLfr1JvbDxAV6oe9vZrCC9VKMIEkMSM5iqM5hTjY2+HoYGfSD/b4eyt/qHrL7bcfUvn2dnbkFJSN2fEPtfyR0lt6/q3V/stdb8n1M5uvprJdF2C7R9YLu46c4dnXvyS/uIKECUHMn5rArYszOJlXalq8Ei46mehQf47kFKBraEYlSew8nMOzr3+J1tWpUz9xWPWSJJkts2Gkta2DyfETTPZf1He3X61SMSVhAnETAsk6mQ9AVV0jgT7ubM061a9+YPYPv3682z/e9eL8j299X9evpTP7zLSk7in5bI3LJqDkTEEZX245SFlVHT+750rTqr1G1u8+zolzxTx251LTwoPGuSlvfLqF8EBvjucWjaq+oUlJE7Vu9zE6OvToDQaq6hr61XdNrrpx7wkqauqp1jVgp1ZTretfP9bHP97tH+96cf7Ht76n69fc2sZdV2Wa5theDth8y621rZ2V6/fy+aYskqJCiJ8QZMrDqO+SuXvJjCQam1vZn31Ome/VGS7f2NSKo4MdR88Ujqq+vUMJjT99vhSHziCSyXHhFumNGdZ9PDRcNXsSGlcnnBzsSYu3TD/Wxz/e7R/venH+x7e+6/W7YeFUbluWwc/uvfKycmxgwy03WZZZte0wHhoXfL20pszxW7NOcfp8Gd+9YZ5pO4Os9GufKy7nvdW7iJ8QiK6xBS93V3w9NKOuj5sQSH1js5LV3d1t3Nkv9EIv9GOrr29q5Y4rpuPs6MDlik223PYey+Vv761l99GzbM06ZaoYsiyTEBGEvZ2aHZ0LMcpcXJ+oobGV0opa8oorqK5r4EB23pjo84srqK5rZN/xc+PSfqEXeqEfO72usZmbFk29rB0b2Jhz0xsM7Dycw47DOdywYCrP/ehm3DUulFQoKaGMc6hSY8OUQdrGZlPofWVtPTmFZSyanoSdnZqbF08TeqEXeqEfN/qzRRd4/K5lPHj9PNzdXLjcsYlJ3C1t7Tg52KNWqUiLn8DM1FgASitrcXKwp2vwoVqtIirEj9yicjbtO8l189NoaVP6p29amE5zSxvOTg5CL/RCL/TjQg/Keow3LJiK4CLj3rmt232MrBP5xE0IINjPi+nJUaYM+oE+HlTVNVB0oZpgP0/TwoMaVyeSooLZsCebL7ccJDu3WOiFXuiFftzpa+ub8NCIVlpPjNtuyYamFt7+ejsFpVXcfVUmE4J82XLgJDW6RiWMtvN1Z1pSJGc7E492Xard39sdF2cHyqt1Qi/0Qi/040ofGeLHgzfMFY6tD8Zty83RwY6JEcGmyYhe7m6c6Fy00VPrahpktVOrcXFyQJaV9aCMfdRuLo4kR4cKvdALvdCPO70xXZegd8Zty83ezs4sQatapazd5e7mDFyc4R/g7c6uI2eRJMlswT2hF3qhF/rxqhf0z7hwbpW19bR3KIuAdl1C3ZjsF6ChuQWNqxNendn9jTnaokL9mJ0WS0tbuzInROiFXuiFfhzpl81MRm+4OGFbYBlW3bY9mVfCl1sOonV1Rq838KPbF6NSqUz90cYUNSqVitr6JlycHAHIzi1GrZKQwaR/49Mt/Oj2xUhd+rOFXuiFXuitVR8fEYRapWLhtEQEA8dqW27Vuka+3nqIpTOS+cEtC2lpa+fQqfOAUilUkkRFTb0pEeiZggvo9Xo++GY3a3YcobGlTeiFXuiFflzq1WrzdRsFA8eqnFvXZndlTT0h/l7ERyiz893dnPHz0tKh1wPwzc6j/Pmd1eQWKpmwSypqOVdcgb+3Oz+790o0Lk5CL/RCL/TjRp9XUmnSx4T5IxgaVtMtuXn/SU7llxIT5k/mpGgCfNxpamnlw7V7OFtYjq+XhjU7jiBJErcvm46zoz3PPHw9rs5KU97JwY4Qfy9kWaappVXohV7ohX7c6NMTI7h9WYapa1IwdKwicfKhU+dZu+soNyyYyp5judjbqVmUkYifl5bN+0/S3NrGlbMm0aHX88yrn3P/tbOJDlXebPR6A0fPFAq90Au90I9LvXFhUsHwYhVnNb+kgjlp8cRNCOTqOan4eGr4ZudRQEmtZVyqwU6tJiUmlPJqHaB0Y6rVKqEXeqEX+nGrF4wMo3pmLw1lNX728dCwP/scAN7ubqREh9Da1k5uUTk+Hm5s2HOc7NwiVm8/zKn8UiJD/Mz2I/RCL/RCb+36NTuOmOmN4f6CkWFMnZvx4qYlTMDB3o7DpwsAcHdzITY8gNyictITI5mWFMX+7Dwqa+r58e2LCehchVbohV7ohX686gUjy6g4t7ziCt78chufbz5IcXmNaZ6HcUKji5MDqXFhbDt4ClmWcXZyoK1dT0tLGwDhgd506A24uTrT1NIm9EIv9EI/bvTzpsZz55WZ3LN8Fp5aVwSjw4g6N4OsrIb93ppdJEYFYzAY2HLgJEUXqpXCO/OntXfomRgZjLubC++t2UVtfROFF6pQq1UmfXJMiNALvdAL/bjR29ldnKtmbyfmrY02I+rcVJKEp9aFe6+eRUZSFFfMTKG6rhHZcLF78utth3jtk02dq8emo3V15r9fbMXZ0YErZqYIvdALvdCPS/2yzGQEY8ewz3M7fPo8pZV1hPh5khwTSnpiJHZqFe0detxcnHB0tKeuoRkAXWMz5dU6bl82HV9PLaB0AahVKsIDvVGpVEIv9EIv9ONGf+28NNraO0TWfitg2Fpu9Y0tvPrxRr7dewJXJwf+t2onh06dx8HeDpVKhb2dGr3eQK2uEX9vpSJoXZ154Lq5+HpqqWtoNum1rk5CL/RCL/TjRm8chwOxHI21MGxXoaJWR1SIP0tmJAHg4GDPhj3HmRwfbtqmrKoOjasz/t7utLS2U1pZS0SwL7IsU1VXL/RCL/RCPy71Yjka62NIzm3P0bN4ursSEeRLeIAPPu4aQIkiCvRxJ9jPEwC9wYBapaKhuQUHezt2HTnDt3uzmRDkQ1t7BxHBQi/0Qi/040u/cNpEJgT5iPlqVsqAnZssy+gamvnvl9uQJAlfDw07Dp3h1iXT0Lo5m5ZwKKuso7EzFNa4quyJcyXszz6HbDBgb6emqq6R/dl57Dgs9EIv9EJv/foD2eewV6v4zrVzCPH3QmC9DGjMzWAwIEkSLW3teGhcePzOpdx+xXRcnR14b80us21P5JWQ1tmk13UOwCZGBvPg9XNZPncy/t7uQi/0Qi/040afHB3CA9fP5Z7ls4RjGwdY5Nz0BgNfbM7iiy0HyTlfxoUqnamPWa1SceuSDM4VVZBzvsw098PR3g4fDw1fbT3E399fy4q1ezieW4TW1VnohV7ohX7c6F/8YB3VukaiQ/2ZOjECwfigX+eWc76M5/77NU0tbfh6avlq6yHUaonT58vIK64AlDQ0V82exKrthwGlhbfryBle/3QzpRU1gIQsy0Iv9EIv9ONK39LaxuN3LsNLZBYZd/Q75iZJEounJzE9OQqAwrIqKmsbWD4nlRVr9/DUA8sxyDKpcWGcPl9GVV0DBoOBOWlxTE+OprW9g6q6BqEXeqEX+nGnDwv0tvRZKrAy+m25hQd6MyVhgimPWlSoH9W6RjInxWAwGNi8/yQqSaJW14RKUrJi+3pquWVJBmGB3kIv9EIv9ONWLxi/9Ntyu3RC4sm8EkL8lMHUe5bPYsehHP750beUVdUxe3IcoERUGsNjhV7ohV7ox6teMH6xeCqAwWAASaK+oYWUmaEAODnYc938NEoqavF2dzNlvO6pYgi90Au90I9XvWD8YbFzkyRJWfbBxZHi8ho+3rAPV2dHbl2aYVoyXeiFXuiF3hb1gvHHgJxb4YUq9h0/R2VtA5mTopmZGmtxQUIv9EIv9ONVLxh/SPqmQrn/zRRqdI3sPZbLwozEQa1PJPRCL/RCP171gvHFgJybQCAQCATjgRFdrFQgEAgEgrFAODeBQCAQ2BzCuQkEAoHA5hDOTSAQCAQ2h3BuAoFAILA5hHMTCAQCgc0hnJtAIBAIbI7/B1NF3oWqE7ReAAAAAElFTkSuQmCC
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<h3 id="Congratulations!">Congratulations!<a class="anchor-link" href="#Congratulations!">&#182;</a></h3><p>You've reached the end of the project. In this project you created an event-drivent ML workflow that can be incorporated into the Scones Unlimited production architecture. You used the SageMaker Estimator API to deploy your SageMaker Model and Endpoint, and you used AWS Lambda and Step Functions to orchestrate your ML workflow. Using SageMaker Model Monitor, you instrumented and observed your Endpoint, and at the end of the project you built a visualization to help stakeholders understand the performance of the Endpoint over time. If you're up for it, you can even go further with these stretch goals:</p>
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<li>Extend your workflow to incorporate more classes: the CIFAR dataset includes other vehicles that Scones Unlimited can identify with this model.</li>
<li>Modify your event driven workflow: can you rewrite your Lambda functions so that the workflow can process multiple image inputs in parallel? Can the Step Function "fan out" to accomodate this new workflow?</li>
<li>Consider the test data generator we provided for you. Can we use it to create a "dummy data" generator, to simulate a continuous stream of input data? Or a big paralell load of data?</li>
<li>What if we want to get notified every time our step function errors out? Can we use the Step Functions visual editor in conjunction with a service like SNS to accomplish this? Try it out!</li>
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