Image Classifier Project.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>Image Classifier Project</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
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 * Bootstrap v3.3.7 (http://getbootstrap.com)
 * Copyright 2011-2016 Twitter, Inc.
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/*! 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]) {
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}
[hidden],
template {
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}
a {
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}
a:active,
a:hover {
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}
abbr[title] {
  border-bottom: 1px dotted;
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b,
strong {
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}
dfn {
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}
h1 {
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  margin: 0.67em 0;
}
mark {
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  color: #000;
}
small {
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}
sub,
sup {
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  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
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}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
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}
figure {
  margin: 1em 40px;
}
hr {
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pre {
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code,
kbd,
pre,
samp {
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button,
input,
optgroup,
select,
textarea {
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button {
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button,
select {
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}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
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}
button[disabled],
html input[disabled] {
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}
button::-moz-focus-inner,
input::-moz-focus-inner {
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input {
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input[type="checkbox"],
input[type="radio"] {
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}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
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input[type="search"] {
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input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
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fieldset {
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legend {
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textarea {
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optgroup {
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}
table {
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}
td,
th {
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}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
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    color: #000 !important;
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@font-face {
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  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
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}
.glyphicon {
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  top: 1px;
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.glyphicon-eur:before {
  content: "\20ac";
}
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}
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}
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}
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}
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}
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}
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}
.glyphicon-heart:before {
  content: "\e005";
}
.glyphicon-star:before {
  content: "\e006";
}
.glyphicon-star-empty:before {
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}
.glyphicon-user:before {
  content: "\e008";
}
.glyphicon-film:before {
  content: "\e009";
}
.glyphicon-th-large:before {
  content: "\e010";
}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
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}
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}
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}
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}
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}
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}
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}
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}
.glyphicon-file:before {
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}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
  content: "\e025";
}
.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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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
.glyphicon-align-justify:before {
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}
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}
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}
.glyphicon-indent-right:before {
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}
.glyphicon-facetime-video:before {
  content: "\e059";
}
.glyphicon-picture:before {
  content: "\e060";
}
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}
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}
.glyphicon-tint:before {
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
.glyphicon-chevron-left:before {
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}
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}
.glyphicon-plus-sign:before {
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}
.glyphicon-minus-sign:before {
  content: "\e082";
}
.glyphicon-remove-sign:before {
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}
.glyphicon-ok-sign:before {
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}
.glyphicon-question-sign:before {
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}
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}
.glyphicon-screenshot:before {
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}
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}
.glyphicon-ok-circle:before {
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}
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}
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}
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}
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}
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  content: "\e094";
}
.glyphicon-share-alt:before {
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}
.glyphicon-resize-full:before {
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}
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}
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}
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}
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}
.glyphicon-fire:before {
  content: "\e104";
}
.glyphicon-eye-open:before {
  content: "\e105";
}
.glyphicon-eye-close:before {
  content: "\e106";
}
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}
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  content: "\e108";
}
.glyphicon-calendar:before {
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}
.glyphicon-random:before {
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}
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  content: "\e111";
}
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  content: "\e112";
}
.glyphicon-chevron-up:before {
  content: "\e113";
}
.glyphicon-chevron-down:before {
  content: "\e114";
}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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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 {
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}
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}
.glyphicon-briefcase:before {
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}
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}
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  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
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}
.glyphicon-link:before {
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}
.glyphicon-phone:before {
  content: "\e145";
}
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  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
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}
.glyphicon-sort:before {
  content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
  content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
  content: "\e154";
}
.glyphicon-sort-by-attributes:before {
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}
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}
.glyphicon-unchecked:before {
  content: "\e157";
}
.glyphicon-expand:before {
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}
.glyphicon-collapse-down:before {
  content: "\e159";
}
.glyphicon-collapse-up:before {
  content: "\e160";
}
.glyphicon-log-in:before {
  content: "\e161";
}
.glyphicon-flash:before {
  content: "\e162";
}
.glyphicon-log-out:before {
  content: "\e163";
}
.glyphicon-new-window:before {
  content: "\e164";
}
.glyphicon-record:before {
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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-floppy-disk:before {
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}
.glyphicon-floppy-saved:before {
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}
.glyphicon-floppy-remove:before {
  content: "\e174";
}
.glyphicon-floppy-save:before {
  content: "\e175";
}
.glyphicon-floppy-open:before {
  content: "\e176";
}
.glyphicon-credit-card:before {
  content: "\e177";
}
.glyphicon-transfer:before {
  content: "\e178";
}
.glyphicon-cutlery:before {
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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 {
  content: "\e183";
}
.glyphicon-tower:before {
  content: "\e184";
}
.glyphicon-stats:before {
  content: "\e185";
}
.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-stereo:before {
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}
.glyphicon-sound-dolby:before {
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}
.glyphicon-sound-5-1:before {
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.glyphicon-sound-6-1:before {
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.glyphicon-sound-7-1:before {
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}
.glyphicon-copyright-mark:before {
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}
.glyphicon-registration-mark:before {
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}
.glyphicon-cloud-download:before {
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}
.glyphicon-cloud-upload:before {
  content: "\e198";
}
.glyphicon-tree-conifer:before {
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}
.glyphicon-tree-deciduous:before {
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}
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.glyphicon-paste:before {
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}
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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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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
.glyphicon-lamp:before {
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}
.glyphicon-duplicate:before {
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}
.glyphicon-piggy-bank:before {
  content: "\e225";
}
.glyphicon-scissors:before {
  content: "\e226";
}
.glyphicon-bitcoin:before {
  content: "\e227";
}
.glyphicon-btc:before {
  content: "\e227";
}
.glyphicon-xbt:before {
  content: "\e227";
}
.glyphicon-yen:before {
  content: "\00a5";
}
.glyphicon-jpy:before {
  content: "\00a5";
}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
  content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
  content: "\e232";
}
.glyphicon-education:before {
  content: "\e233";
}
.glyphicon-option-horizontal:before {
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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 {
  content: "\e238";
}
.glyphicon-grain:before {
  content: "\e239";
}
.glyphicon-sunglasses:before {
  content: "\e240";
}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
  content: "\e243";
}
.glyphicon-object-align-top:before {
  content: "\e244";
}
.glyphicon-object-align-bottom:before {
  content: "\e245";
}
.glyphicon-object-align-horizontal:before {
  content: "\e246";
}
.glyphicon-object-align-left:before {
  content: "\e247";
}
.glyphicon-object-align-vertical:before {
  content: "\e248";
}
.glyphicon-object-align-right:before {
  content: "\e249";
}
.glyphicon-triangle-right:before {
  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.2.0 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=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#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;
}
.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;
}
@-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 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  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 {
  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:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.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 {
  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: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-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.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";
}
/*!
*
* 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;
}
/**
 * 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 {
  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;
}
@media (max-width: 991px) {
  #ipython_notebook {
    margin-left: 10px;
  }
}
[dir="rtl"] #ipython_notebook {
  float: right !important;
}
#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#login_widget {
  float: right;
}
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;
}
@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;
}
/*!
*
* 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 {
  text-align: center;
  vertical-align: middle;
  display: inline;
  opacity: 0;
  z-index: 2;
  width: 12ex;
  margin-right: -12ex;
}
.alternate_upload .btn-upload {
  height: 22px;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
[dir="rtl"] #tabs li {
  float: right;
}
ul#tabs {
  margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
  margin-right: 0px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
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 {
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
  padding-top: 1px;
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
  float: right !important;
}
.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: baseline;
  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;
}
.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_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;
}
.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;
}
#tree-selector {
  padding-right: 0px;
}
[dir="rtl"] #tree-selector a {
  float: right;
}
#button-select-all {
  min-width: 50px;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
}
.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.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.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.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.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;
}
[dir="rtl"] #new-menu {
  text-align: right;
}
.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;
}
[dir="rtl"] #running .col-sm-8 {
  float: right !important;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-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.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.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.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.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);
  }
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
  font-weight: bold;
}
/* 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;
  border-left-width: 1px;
  padding-left: 5px;
  background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
  border-left-color: #90CAF9;
  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 {
  border-color: #ababab;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
  div.cell.selected {
    border-color: transparent;
  }
}
div.cell.selected.jupyter-soft-selected {
  border-left-width: 0;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@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. */
  padding: 0.4em;
}
.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. We need the 0 value because of how we size */
  /* .CodeMirror-lines */
  padding: 0;
  border: 0;
  border-radius: 0;
}
/*

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;
}
/* 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: 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 {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.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;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.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;
}
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.unrendered .text_cell_render {
  display: none;
}
.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;
}
/* 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;
}
.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 {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#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;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -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.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.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;
}
.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;
}
#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;
}
#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;
}
#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.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.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.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.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.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.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
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<h1 id="Developing-an-AI-application">Developing an AI application<a class="anchor-link" href="#Developing-an-AI-application">&#182;</a></h1><p>Going forward, AI algorithms will be incorporated into more and more everyday applications. For example, you might want to include an image classifier in a smart phone app. To do this, you'd use a deep learning model trained on hundreds of thousands of images as part of the overall application architecture. A large part of software development in the future will be using these types of models as common parts of applications.</p>
<p>In this project, you'll train an image classifier to recognize different species of flowers. You can imagine using something like this in a phone app that tells you the name of the flower your camera is looking at. In practice you'd train this classifier, then export it for use in your application. We'll be using <a href="http://www.robots.ox.ac.uk/~vgg/data/flowers/102/index.html">this dataset</a> of 102 flower categories, you can see a few examples below.</p>
<p><img src='assets/Flowers.png' width=500px></p>
<p>The project is broken down into multiple steps:</p>
<ul>
<li>Load and preprocess the image dataset</li>
<li>Train the image classifier on your dataset</li>
<li>Use the trained classifier to predict image content</li>
</ul>
<p>We'll lead you through each part which you'll implement in Python.</p>
<p>When you've completed this project, you'll have an application that can be trained on any set of labeled images. Here your network will be learning about flowers and end up as a command line application. But, what you do with your new skills depends on your imagination and effort in building a dataset. For example, imagine an app where you take a picture of a car, it tells you what the make and model is, then looks up information about it. Go build your own dataset and make something new.</p>
<p>First up is importing the packages you'll need. It's good practice to keep all the imports at the beginning of your code. As you work through this notebook and find you need to import a package, make sure to add the import up here.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Imports here</span>
<span class="o">%</span><span class="k">matplotlib</span> inline


<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">OrderedDict</span>
<span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">OrderedDict</span>
<span class="kn">from</span> <span class="nn">torch</span> <span class="k">import</span> <span class="n">nn</span>
<span class="kn">from</span> <span class="nn">torch</span> <span class="k">import</span> <span class="n">optim</span>
<span class="kn">import</span> <span class="nn">torch.nn.functional</span> <span class="k">as</span> <span class="nn">F</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">datasets</span><span class="p">,</span> <span class="n">transforms</span><span class="p">,</span> <span class="n">models</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
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<h2 id="Load-the-data">Load the data<a class="anchor-link" href="#Load-the-data">&#182;</a></h2><p>Here you'll use <code>torchvision</code> to load the data (<a href="http://pytorch.org/docs/0.3.0/torchvision/index.html">documentation</a>). The data should be included alongside this notebook, otherwise you can <a href="https://s3.amazonaws.com/content.udacity-data.com/nd089/flower_data.tar.gz">download it here</a>. The dataset is split into three parts, training, validation, and testing. For the training, you'll want to apply transformations such as random scaling, cropping, and flipping. This will help the network generalize leading to better performance. You'll also need to make sure the input data is resized to 224x224 pixels as required by the pre-trained networks.</p>
<p>The validation and testing sets are used to measure the model's performance on data it hasn't seen yet. For this you don't want any scaling or rotation transformations, but you'll need to resize then crop the images to the appropriate size.</p>
<p>The pre-trained networks you'll use were trained on the ImageNet dataset where each color channel was normalized separately. For all three sets you'll need to normalize the means and standard deviations of the images to what the network expects. For the means, it's <code>[0.485, 0.456, 0.406]</code> and for the standard deviations <code>[0.229, 0.224, 0.225]</code>, calculated from the ImageNet images.  These values will shift each color channel to be centered at 0 and range from -1 to 1.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_dir</span> <span class="o">=</span> <span class="s1">&#39;flowers&#39;</span>
<span class="n">train_dir</span> <span class="o">=</span> <span class="n">data_dir</span> <span class="o">+</span> <span class="s1">&#39;/train&#39;</span>
<span class="n">valid_dir</span> <span class="o">=</span> <span class="n">data_dir</span> <span class="o">+</span> <span class="s1">&#39;/valid&#39;</span>
<span class="n">test_dir</span> <span class="o">=</span> <span class="n">data_dir</span> <span class="o">+</span> <span class="s1">&#39;/test&#39;</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">means</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.485</span><span class="p">,</span> <span class="mf">0.456</span><span class="p">,</span> <span class="mf">0.406</span><span class="p">]</span>
<span class="n">std</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.229</span><span class="p">,</span> <span class="mf">0.224</span><span class="p">,</span> <span class="mf">0.225</span><span class="p">]</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Define your transforms for the training, validation, and testing sets</span>
<span class="n">train_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">RandomRotation</span><span class="p">(</span><span class="mi">30</span><span class="p">),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">RandomResizedCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">RandomHorizontalFlip</span><span class="p">(),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">(</span><span class="n">means</span><span class="p">,</span> <span class="n">std</span><span class="p">)])</span>
                                                        

<span class="n">test_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="mi">256</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">(</span><span class="n">means</span><span class="p">,</span> <span class="n">std</span><span class="p">)])</span>

<span class="n">validation_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="mi">256</span><span class="p">),</span>
                                            <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                            <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                            <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">(</span><span class="n">means</span><span class="p">,</span> <span class="n">std</span><span class="p">)])</span>


<span class="c1"># TODO: Load the datasets with ImageFolder</span>
<span class="n">train_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">train_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">train_transforms</span><span class="p">)</span>
<span class="n">test_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">test_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">test_transforms</span><span class="p">)</span>
<span class="n">validation_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">valid_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">validation_transforms</span><span class="p">)</span>

<span class="c1"># TODO: Using the image datasets and the trainforms, define the dataloaders</span>
<span class="n">trainloader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">32</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">testloader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">test_data</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">32</span><span class="p">)</span>
<span class="n">validationloader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">validation_data</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">32</span><span class="p">)</span>
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<h3 id="Label-mapping">Label mapping<a class="anchor-link" href="#Label-mapping">&#182;</a></h3><p>You'll also need to load in a mapping from category label to category name. You can find this in the file <code>cat_to_name.json</code>. It's a JSON object which you can read in with the <a href="https://docs.python.org/2/library/json.html"><code>json</code> module</a>. This will give you a dictionary mapping the integer encoded categories to the actual names of the flowers.</p>

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

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;cat_to_name.json&#39;</span><span class="p">,</span> <span class="s1">&#39;r&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">cat_to_name</span> <span class="o">=</span> <span class="n">json</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
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<h1 id="Building-and-training-the-classifier">Building and training the classifier<a class="anchor-link" href="#Building-and-training-the-classifier">&#182;</a></h1><p>Now that the data is ready, it's time to build and train the classifier. As usual, you should use one of the pretrained models from <code>torchvision.models</code> to get the image features. Build and train a new feed-forward classifier using those features.</p>
<p>We're going to leave this part up to you. If you want to talk through it with someone, chat with your fellow students! You can also ask questions on the forums or join the instructors in office hours.</p>
<p>Refer to <a href="https://review.udacity.com/#!/rubrics/1663/view">the rubric</a> for guidance on successfully completing this section. Things you'll need to do:</p>
<ul>
<li>Load a <a href="http://pytorch.org/docs/master/torchvision/models.html">pre-trained network</a> (If you need a starting point, the VGG networks work great and are straightforward to use)</li>
<li>Define a new, untrained feed-forward network as a classifier, using ReLU activations and dropout</li>
<li>Train the classifier layers using backpropagation using the pre-trained network to get the features</li>
<li>Track the loss and accuracy on the validation set to determine the best hyperparameters</li>
</ul>
<p>We've left a cell open for you below, but use as many as you need. Our advice is to break the problem up into smaller parts you can run separately. Check that each part is doing what you expect, then move on to the next. You'll likely find that as you work through each part, you'll need to go back and modify your previous code. This is totally normal!</p>
<p>When training make sure you're updating only the weights of the feed-forward network. You should be able to get the validation accuracy above 70% if you build everything right. Make sure to try different hyperparameters (learning rate, units in the classifier, epochs, etc) to find the best model. Save those hyperparameters to use as default values in the next part of the project.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">model_setup</span><span class="p">(</span><span class="n">structure</span><span class="o">=</span><span class="s1">&#39;vgg19&#39;</span><span class="p">,</span><span class="n">dropout</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">hidden_layer1</span> <span class="o">=</span> <span class="mi">512</span><span class="p">,</span><span class="n">lr</span> <span class="o">=</span> <span class="mf">0.001</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Input parameters:</span>
<span class="sd">    ------------------------------------------------------------</span>
<span class="sd">    Structure:     &#39;vgg19&#39; (default), &#39;densenet121&#39; or &#39;alexnet&#39;</span>
<span class="sd">    Dropout:       default is 0.5</span>
<span class="sd">    learning_rate: default is 0.001</span>
<span class="sd">    ------------------------------------------------------------</span>
<span class="sd">    Returns model, optimizer and criterion</span>
<span class="sd">    ------------------------------------------------------------</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="n">structures</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;vgg19&quot;</span><span class="p">:</span><span class="mi">25088</span><span class="p">,</span>
                  <span class="s2">&quot;densenet121&quot;</span> <span class="p">:</span> <span class="mi">1024</span><span class="p">,</span>
                  <span class="s2">&quot;alexnet&quot;</span> <span class="p">:</span> <span class="mi">9216</span> <span class="p">}</span>
    
    <span class="c1"># Download correct architecture</span>
    <span class="k">if</span> <span class="n">structure</span> <span class="o">==</span> <span class="s1">&#39;vgg19&#39;</span><span class="p">:</span>
        <span class="n">model</span> <span class="o">=</span> <span class="n">models</span><span class="o">.</span><span class="n">vgg19</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>        
    <span class="k">elif</span> <span class="n">structure</span> <span class="o">==</span> <span class="s1">&#39;densenet121&#39;</span><span class="p">:</span>
        <span class="n">model</span> <span class="o">=</span> <span class="n">models</span><span class="o">.</span><span class="n">densenet121</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="k">elif</span> <span class="n">structure</span> <span class="o">==</span> <span class="s1">&#39;alexnet&#39;</span><span class="p">:</span>
        <span class="n">model</span> <span class="o">=</span> <span class="n">models</span><span class="o">.</span><span class="n">alexnet</span><span class="p">(</span><span class="n">pretrained</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Invalid model, try &#39;densenet121&#39;, &#39;alexnet&#39; or leave blank for vgg19&quot;</span><span class="p">)</span>
        
    
    <span class="c1"># Freeze parameters in the pretrained model </span>
    <span class="k">for</span> <span class="n">param</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">():</span>
        <span class="n">param</span><span class="o">.</span><span class="n">requires_grad</span> <span class="o">=</span> <span class="kc">False</span>
        
        <span class="c1"># Setup custom classifier</span>
        <span class="n">classifier</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="n">OrderedDict</span><span class="p">([</span>
            <span class="p">(</span><span class="s1">&#39;dropout&#39;</span><span class="p">,</span><span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">dropout</span><span class="p">)),</span>
            <span class="p">(</span><span class="s1">&#39;inputs&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">structures</span><span class="p">[</span><span class="n">structure</span><span class="p">],</span> <span class="n">hidden_layer1</span><span class="p">)),</span>
            <span class="p">(</span><span class="s1">&#39;relu1&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">()),</span>
            <span class="p">(</span><span class="s1">&#39;hidden_layer1&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">hidden_layer1</span><span class="p">,</span> <span class="mi">200</span><span class="p">)),</span>
            <span class="p">(</span><span class="s1">&#39;relu2&#39;</span><span class="p">,</span><span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">()),</span>
            <span class="p">(</span><span class="s1">&#39;hidden_layer2&#39;</span><span class="p">,</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="mi">200</span><span class="p">,</span><span class="mi">150</span><span class="p">)),</span>
            <span class="p">(</span><span class="s1">&#39;relu3&#39;</span><span class="p">,</span><span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">()),</span>
            <span class="p">(</span><span class="s1">&#39;hidden_layer3&#39;</span><span class="p">,</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="mi">150</span><span class="p">,</span><span class="mi">102</span><span class="p">)),</span>
            <span class="p">(</span><span class="s1">&#39;output&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">LogSoftmax</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
                          <span class="p">]))</span>
        
        
        <span class="n">model</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">classifier</span>
        <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">NLLLoss</span><span class="p">()</span>
        <span class="n">optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span> <span class="p">)</span>
        <span class="n">model</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
        
        <span class="k">return</span> <span class="n">model</span> <span class="p">,</span> <span class="n">optimizer</span> <span class="p">,</span><span class="n">criterion</span> 

    
<span class="n">model</span><span class="p">,</span><span class="n">optimizer</span><span class="p">,</span><span class="n">criterion</span> <span class="o">=</span> <span class="n">model_setup</span><span class="p">()</span>
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<pre>Downloading: &#34;https://download.pytorch.org/models/vgg19-dcbb9e9d.pth&#34; to /root/.torch/models/vgg19-dcbb9e9d.pth
100%|██████████| 574673361/574673361 [00:18&lt;00:00, 31048049.07it/s]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">check_perfomance</span><span class="p">(</span><span class="n">loader</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">criterion</span><span class="p">,</span> <span class="n">device</span><span class="p">,</span> <span class="n">optimizer</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Validation function, takes dataloader, model, criterion, device and optimizer as </span>
<span class="sd">    arguments and returns test_loss and accuracy</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">test_loss</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">accuracy</span> <span class="o">=</span> <span class="mi">0</span>
    
    <span class="c1"># Loop over images and labels in dataloader</span>
    <span class="k">for</span> <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="ow">in</span> <span class="n">loader</span><span class="p">:</span>
        <span class="n">images</span> <span class="o">=</span> <span class="n">images</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
        <span class="n">optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
       
        <span class="c1"># Calculate loss</span>
        <span class="n">output</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">images</span><span class="p">)</span>
        <span class="n">test_loss</span> <span class="o">+=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
        
        <span class="c1"># Accuracy</span>
        <span class="n">ps</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">output</span><span class="p">)</span>
        <span class="n">equality</span> <span class="o">=</span> <span class="p">(</span><span class="n">labels</span><span class="o">.</span><span class="n">data</span> <span class="o">==</span> <span class="n">ps</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)[</span><span class="mi">1</span><span class="p">])</span>
        <span class="n">accuracy</span> <span class="o">+=</span> <span class="n">equality</span><span class="o">.</span><span class="n">type</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">FloatTensor</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>

    <span class="k">return</span> <span class="n">test_loss</span><span class="p">,</span> <span class="n">accuracy</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Training </span>
<span class="k">def</span> <span class="nf">train_model</span><span class="p">(</span><span class="n">optimizer</span><span class="p">,</span> <span class="n">criterion</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">5</span><span class="p">):</span>
    
    <span class="c1"># Set Device to cuda if availble else cpu</span>
    <span class="c1"># And initiate some internal variabels </span>
    <span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s2">&quot;cuda:0&quot;</span> <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span> <span class="k">else</span> <span class="s1">&#39;cpu&#39;</span><span class="p">)</span>
    <span class="n">model</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
    <span class="n">print_every</span> <span class="o">=</span> <span class="mi">5</span>
    <span class="n">steps</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">best_accuracy</span> <span class="o">=</span> <span class="mf">0.0</span>
    <span class="n">best_model</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;model_state&#39;</span><span class="p">:</span> <span class="n">model</span><span class="p">}</span>
    <span class="n">running_loss</span> <span class="o">=</span> <span class="mi">0</span>

    <span class="k">for</span> <span class="n">e</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">epochs</span><span class="p">):</span>
        
        <span class="n">model</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>    

        <span class="k">for</span> <span class="n">inputs</span><span class="p">,</span> <span class="n">labels</span> <span class="ow">in</span> <span class="n">trainloader</span><span class="p">:</span>
        
            <span class="n">steps</span> <span class="o">+=</span> <span class="mi">1</span>
            <span class="c1"># Move input and label to current device. CUDA if available, else CPU</span>
            <span class="n">inputs</span> <span class="o">=</span> <span class="n">inputs</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
            <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>

            <span class="n">optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            <span class="c1"># Feed-forward</span>
            <span class="n">output</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">inputs</span><span class="p">)</span>
            <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span>
            <span class="c1"># Backpropagation</span>
            <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
            
            
            <span class="n">running_loss</span> <span class="o">+=</span> <span class="n">loss</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
            
            <span class="k">if</span> <span class="n">steps</span> <span class="o">%</span> <span class="n">print_every</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">model</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
                <span class="n">test_loss</span> <span class="o">=</span> <span class="mi">0</span>
                <span class="n">accuracy</span> <span class="o">=</span> <span class="mi">0</span>
                <span class="n">optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>          
                <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
                                                          
                    <span class="n">test_loss</span><span class="p">,</span> <span class="n">accuracy</span> <span class="o">=</span> <span class="n">check_perfomance</span><span class="p">(</span><span class="n">validationloader</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">criterion</span><span class="p">,</span> <span class="n">device</span><span class="p">,</span> <span class="n">optimizer</span><span class="p">)</span>
                                
                <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Epoch: </span><span class="si">{}</span><span class="s2">/</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">e</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">epochs</span><span class="p">),</span>
                      <span class="s2">&quot;Loss: </span><span class="si">{:.4f}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">running_loss</span><span class="o">/</span><span class="n">print_every</span><span class="p">),</span>
                      <span class="s2">&quot;Device : </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">device</span><span class="p">),</span>
                      <span class="s2">&quot;Test_loss : </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">test_loss</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">validationloader</span><span class="p">)),</span>
                      <span class="s2">&quot;Test_Accuracy : </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">accuracy</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">validationloader</span><span class="p">)))</span>
                             
                <span class="n">running_loss</span> <span class="o">=</span> <span class="mi">0</span>
              
    <span class="k">return</span> <span class="n">model</span>
            
           
<span class="kn">from</span> <span class="nn">workspace_utils</span> <span class="k">import</span> <span class="n">active_session</span>
<span class="k">with</span> <span class="n">active_session</span><span class="p">():</span>
    <span class="c1"># do long-running work here</span>
    <span class="n">final_model</span> <span class="o">=</span> <span class="n">train_model</span><span class="p">(</span><span class="n">optimizer</span><span class="p">,</span> <span class="n">criterion</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
</pre></div>

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

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<div class="output_area">

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


<div class="output_subarea output_stream output_stdout output_text">
<pre>Epoch: 1/5...  Loss: 4.5686 Device : cuda:0.. Test_loss : 4.762556837155269.. Test_Accuracy : 0.04927884787321091..
Epoch: 1/5...  Loss: 4.5560 Device : cuda:0.. Test_loss : 4.483763658083403.. Test_Accuracy : 0.04326923191547394..
Epoch: 1/5...  Loss: 4.4997 Device : cuda:0.. Test_loss : 4.403651659305279.. Test_Accuracy : 0.05889423191547394..
Epoch: 1/5...  Loss: 4.4362 Device : cuda:0.. Test_loss : 4.338086898510273.. Test_Accuracy : 0.09855769574642181..
Epoch: 1/5...  Loss: 4.4407 Device : cuda:0.. Test_loss : 4.215989204553457.. Test_Accuracy : 0.10456730425357819..
Epoch: 1/5...  Loss: 4.3290 Device : cuda:0.. Test_loss : 4.17513108253479.. Test_Accuracy : 0.07091346383094788..
Epoch: 1/5...  Loss: 4.1934 Device : cuda:0.. Test_loss : 3.975369691848755.. Test_Accuracy : 0.12259615212678909..
Epoch: 1/5...  Loss: 4.0937 Device : cuda:0.. Test_loss : 3.785089529477633.. Test_Accuracy : 0.15024039149284363..
Epoch: 1/5...  Loss: 3.9512 Device : cuda:0.. Test_loss : 3.662318390149337.. Test_Accuracy : 0.17668269574642181..
Epoch: 1/5...  Loss: 3.9187 Device : cuda:0.. Test_loss : 3.5351819075070896.. Test_Accuracy : 0.2055288404226303..
Epoch: 1/5...  Loss: 3.6583 Device : cuda:0.. Test_loss : 3.3722260273419895.. Test_Accuracy : 0.25360578298568726..
Epoch: 1/5...  Loss: 3.4274 Device : cuda:0.. Test_loss : 3.17190722318796.. Test_Accuracy : 0.2584134638309479..
Epoch: 1/5...  Loss: 3.3972 Device : cuda:0.. Test_loss : 3.0862242120962877.. Test_Accuracy : 0.25120192766189575..
Epoch: 1/5...  Loss: 3.2929 Device : cuda:0.. Test_loss : 3.009326954300587.. Test_Accuracy : 0.2836538553237915..
Epoch: 1/5...  Loss: 2.8272 Device : cuda:0.. Test_loss : 2.851747446335279.. Test_Accuracy : 0.30649039149284363..
Epoch: 1/5...  Loss: 2.8568 Device : cuda:0.. Test_loss : 2.745913001207205.. Test_Accuracy : 0.3263888657093048..
Epoch: 1/5...  Loss: 3.1494 Device : cuda:0.. Test_loss : 2.5666062510930576.. Test_Accuracy : 0.37032586336135864..
Epoch: 1/5...  Loss: 2.8109 Device : cuda:0.. Test_loss : 2.53383541565675.. Test_Accuracy : 0.3521634638309479..
Epoch: 1/5...  Loss: 2.9244 Device : cuda:0.. Test_loss : 2.4496747988920946.. Test_Accuracy : 0.37139421701431274..
Epoch: 1/5...  Loss: 2.8770 Device : cuda:0.. Test_loss : 2.400138169527054.. Test_Accuracy : 0.37379807233810425..
Epoch: 1/5...  Loss: 2.5359 Device : cuda:0.. Test_loss : 2.4872470257373958.. Test_Accuracy : 0.34014421701431274..
Epoch: 1/5...  Loss: 2.4734 Device : cuda:0.. Test_loss : 2.246267944574356.. Test_Accuracy : 0.3798076808452606..
Epoch: 1/5...  Loss: 2.3700 Device : cuda:0.. Test_loss : 2.241307189831367.. Test_Accuracy : 0.41693374514579773..
Epoch: 1/5...  Loss: 2.5352 Device : cuda:0.. Test_loss : 1.9758983139808362.. Test_Accuracy : 0.4409722089767456..
Epoch: 1/5...  Loss: 2.4083 Device : cuda:0.. Test_loss : 1.8837317153811455.. Test_Accuracy : 0.4815705120563507..
Epoch: 1/5...  Loss: 2.0364 Device : cuda:0.. Test_loss : 1.8299460273522596.. Test_Accuracy : 0.4811698794364929..
Epoch: 1/5...  Loss: 2.2255 Device : cuda:0.. Test_loss : 1.7932741596148565.. Test_Accuracy : 0.5078792572021484..
Epoch: 1/5...  Loss: 2.3775 Device : cuda:0.. Test_loss : 1.7433050443919806.. Test_Accuracy : 0.5061431527137756..
Epoch: 1/5...  Loss: 2.0908 Device : cuda:0.. Test_loss : 1.741408187036331.. Test_Accuracy : 0.4983974099159241..
Epoch: 1/5...  Loss: 1.8632 Device : cuda:0.. Test_loss : 1.64933826143925.. Test_Accuracy : 0.544738233089447..
Epoch: 1/5...  Loss: 2.0295 Device : cuda:0.. Test_loss : 1.9778035649886498.. Test_Accuracy : 0.4815705120563507..
Epoch: 1/5...  Loss: 1.9339 Device : cuda:0.. Test_loss : 1.7153029453295927.. Test_Accuracy : 0.5219017267227173..
Epoch: 1/5...  Loss: 2.1166 Device : cuda:0.. Test_loss : 1.7679452437620897.. Test_Accuracy : 0.529113233089447..
Epoch: 1/5...  Loss: 2.1113 Device : cuda:0.. Test_loss : 1.5878780300800617.. Test_Accuracy : 0.5512820482254028..
Epoch: 1/5...  Loss: 2.0221 Device : cuda:0.. Test_loss : 1.578277234847729.. Test_Accuracy : 0.5536859035491943..
Epoch: 1/5...  Loss: 2.1042 Device : cuda:0.. Test_loss : 1.54491319335424.. Test_Accuracy : 0.5735844373703003..
Epoch: 1/5...  Loss: 1.8583 Device : cuda:0.. Test_loss : 1.5652329382988124.. Test_Accuracy : 0.5618323087692261..
Epoch: 1/5...  Loss: 1.9315 Device : cuda:0.. Test_loss : 1.4759523559075136.. Test_Accuracy : 0.5741185545921326..
Epoch: 1/5...  Loss: 1.7170 Device : cuda:0.. Test_loss : 1.522979165499027.. Test_Accuracy : 0.573317289352417..
Epoch: 1/5...  Loss: 1.6235 Device : cuda:0.. Test_loss : 1.549775026165522.. Test_Accuracy : 0.5705128312110901..
Epoch: 1/5...  Loss: 2.0861 Device : cuda:0.. Test_loss : 1.4308938831090927.. Test_Accuracy : 0.5841346383094788..
Epoch: 2/5...  Loss: 1.8735 Device : cuda:0.. Test_loss : 1.4221908106253698.. Test_Accuracy : 0.5924144983291626..
Epoch: 2/5...  Loss: 1.8893 Device : cuda:0.. Test_loss : 1.38415515766694.. Test_Accuracy : 0.6225961446762085..
Epoch: 2/5...  Loss: 1.7915 Device : cuda:0.. Test_loss : 1.4569979527821908.. Test_Accuracy : 0.5956196188926697..
Epoch: 2/5...  Loss: 1.9526 Device : cuda:0.. Test_loss : 1.4959699199176753.. Test_Accuracy : 0.5880075097084045..
Epoch: 2/5...  Loss: 1.6703 Device : cuda:0.. Test_loss : 1.3731433405325963.. Test_Accuracy : 0.6295405626296997..
Epoch: 2/5...  Loss: 1.7134 Device : cuda:0.. Test_loss : 1.2903825955895276.. Test_Accuracy : 0.6356837749481201..
Epoch: 2/5...  Loss: 1.5136 Device : cuda:0.. Test_loss : 1.1870428297955256.. Test_Accuracy : 0.6511752009391785..
Epoch: 2/5...  Loss: 1.5294 Device : cuda:0.. Test_loss : 1.2761352818745832.. Test_Accuracy : 0.638488233089447..
Epoch: 2/5...  Loss: 1.6899 Device : cuda:0.. Test_loss : 1.21915963693307.. Test_Accuracy : 0.6581196188926697..
Epoch: 2/5...  Loss: 1.3329 Device : cuda:0.. Test_loss : 1.233621351994001.. Test_Accuracy : 0.6634615659713745..
Epoch: 2/5...  Loss: 1.5575 Device : cuda:0.. Test_loss : 1.1659213642661388.. Test_Accuracy : 0.6531784534454346..
Epoch: 2/5...  Loss: 1.6752 Device : cuda:0.. Test_loss : 1.352560273729838.. Test_Accuracy : 0.6245993971824646..
Epoch: 2/5...  Loss: 1.6116 Device : cuda:0.. Test_loss : 1.244676248385356.. Test_Accuracy : 0.6495726704597473..
Epoch: 2/5...  Loss: 1.3750 Device : cuda:0.. Test_loss : 1.2688233777880669.. Test_Accuracy : 0.6399573087692261..
Epoch: 2/5...  Loss: 1.6347 Device : cuda:0.. Test_loss : 1.2066749706864357.. Test_Accuracy : 0.648103654384613..
Epoch: 2/5...  Loss: 1.8047 Device : cuda:0.. Test_loss : 1.2118539366011436.. Test_Accuracy : 0.6448984742164612..
Epoch: 2/5...  Loss: 1.7421 Device : cuda:0.. Test_loss : 1.2511602502602797.. Test_Accuracy : 0.6216613054275513..
Epoch: 2/5...  Loss: 1.4995 Device : cuda:0.. Test_loss : 1.289868792089132.. Test_Accuracy : 0.6221955418586731..
Epoch: 2/5...  Loss: 1.5212 Device : cuda:0.. Test_loss : 1.0737460496333928.. Test_Accuracy : 0.682692289352417..
Epoch: 2/5...  Loss: 1.5898 Device : cuda:0.. Test_loss : 1.2519600013127694.. Test_Accuracy : 0.6507745981216431..
Epoch: 2/5...  Loss: 1.8245 Device : cuda:0.. Test_loss : 1.2165870981720777.. Test_Accuracy : 0.648103654384613..
Epoch: 2/5...  Loss: 1.4737 Device : cuda:0.. Test_loss : 1.1788362551193972.. Test_Accuracy : 0.6503738760948181..
Epoch: 2/5...  Loss: 1.2750 Device : cuda:0.. Test_loss : 1.1134786766309004.. Test_Accuracy : 0.6705395579338074..
Epoch: 2/5...  Loss: 1.6009 Device : cuda:0.. Test_loss : 1.1421873047947884.. Test_Accuracy : 0.6738782525062561..
Epoch: 2/5...  Loss: 1.4795 Device : cuda:0.. Test_loss : 1.1869092411719835.. Test_Accuracy : 0.6461004018783569..
Epoch: 2/5...  Loss: 1.5283 Device : cuda:0.. Test_loss : 1.2032893139582415.. Test_Accuracy : 0.6466346383094788..
Epoch: 2/5...  Loss: 1.5144 Device : cuda:0.. Test_loss : 1.1083405441962755.. Test_Accuracy : 0.6758813858032227..
Epoch: 2/5...  Loss: 1.5168 Device : cuda:0.. Test_loss : 1.0626828412596996.. Test_Accuracy : 0.6789530515670776..
Epoch: 2/5...  Loss: 1.3969 Device : cuda:0.. Test_loss : 1.0400496056446662.. Test_Accuracy : 0.6857638955116272..
Epoch: 2/5...  Loss: 1.6033 Device : cuda:0.. Test_loss : 1.1630010943000133.. Test_Accuracy : 0.6812232732772827..
Epoch: 2/5...  Loss: 1.2785 Device : cuda:0.. Test_loss : 0.9871371640608861.. Test_Accuracy : 0.7341079115867615..
Epoch: 2/5...  Loss: 1.4771 Device : cuda:0.. Test_loss : 0.9458495814066666.. Test_Accuracy : 0.7450587749481201..
Epoch: 2/5...  Loss: 1.2522 Device : cuda:0.. Test_loss : 1.0787751554296567.. Test_Accuracy : 0.6927083134651184..
Epoch: 2/5...  Loss: 1.3356 Device : cuda:0.. Test_loss : 0.9759386846652398.. Test_Accuracy : 0.7272969484329224..
Epoch: 2/5...  Loss: 1.1625 Device : cuda:0.. Test_loss : 1.0718726962804794.. Test_Accuracy : 0.6804219484329224..
Epoch: 2/5...  Loss: 1.6751 Device : cuda:0.. Test_loss : 1.0973667668608518.. Test_Accuracy : 0.6818910241127014..
Epoch: 2/5...  Loss: 1.5138 Device : cuda:0.. Test_loss : 1.0168253836723475.. Test_Accuracy : 0.6987179517745972..
Epoch: 2/5...  Loss: 1.3841 Device : cuda:0.. Test_loss : 1.0478964917934859.. Test_Accuracy : 0.6948450803756714..
Epoch: 2/5...  Loss: 1.3575 Device : cuda:0.. Test_loss : 0.9772750425797242.. Test_Accuracy : 0.7147436141967773..
Epoch: 2/5...  Loss: 1.3483 Device : cuda:0.. Test_loss : 1.073108386534911.. Test_Accuracy : 0.6920405626296997..
Epoch: 2/5...  Loss: 1.3126 Device : cuda:0.. Test_loss : 1.0865052061585279.. Test_Accuracy : 0.6965811848640442..
Epoch: 3/5...  Loss: 1.3748 Device : cuda:0.. Test_loss : 0.9706341389280099.. Test_Accuracy : 0.7357104420661926..
Epoch: 3/5...  Loss: 1.2743 Device : cuda:0.. Test_loss : 0.9598650141404226.. Test_Accuracy : 0.7354434132575989..
Epoch: 3/5...  Loss: 1.4388 Device : cuda:0.. Test_loss : 1.00762440264225.. Test_Accuracy : 0.7271634340286255..
Epoch: 3/5...  Loss: 1.2264 Device : cuda:0.. Test_loss : 0.8703155987537824.. Test_Accuracy : 0.7434561848640442..
Epoch: 3/5...  Loss: 1.0820 Device : cuda:0.. Test_loss : 0.912733966914507.. Test_Accuracy : 0.7561431527137756..
Epoch: 3/5...  Loss: 1.1551 Device : cuda:0.. Test_loss : 0.9478650709184316.. Test_Accuracy : 0.7381142973899841..
Epoch: 3/5...  Loss: 1.3035 Device : cuda:0.. Test_loss : 0.9482550552258124.. Test_Accuracy : 0.7354434132575989..
Epoch: 3/5...  Loss: 1.2827 Device : cuda:0.. Test_loss : 0.9103461601413213.. Test_Accuracy : 0.7419871687889099..
Epoch: 3/5...  Loss: 1.2220 Device : cuda:0.. Test_loss : 0.9247393378844628.. Test_Accuracy : 0.729567289352417..
Epoch: 3/5...  Loss: 1.2552 Device : cuda:0.. Test_loss : 0.8601510352813281.. Test_Accuracy : 0.7570780515670776..
Epoch: 3/5...  Loss: 1.0078 Device : cuda:0.. Test_loss : 0.8628571142370884.. Test_Accuracy : 0.7549412250518799..
Epoch: 3/5...  Loss: 1.0310 Device : cuda:0.. Test_loss : 0.9265355505049229.. Test_Accuracy : 0.7393162250518799..
Epoch: 3/5...  Loss: 1.1363 Device : cuda:0.. Test_loss : 0.9074050887272909.. Test_Accuracy : 0.7470619678497314..
Epoch: 3/5...  Loss: 1.2865 Device : cuda:0.. Test_loss : 0.8785885689923396.. Test_Accuracy : 0.7530715465545654..
Epoch: 3/5...  Loss: 0.9151 Device : cuda:0.. Test_loss : 0.9533427896407934.. Test_Accuracy : 0.7239583134651184..
Epoch: 3/5...  Loss: 1.1612 Device : cuda:0.. Test_loss : 0.9062486766622617.. Test_Accuracy : 0.7411859035491943..
Epoch: 3/5...  Loss: 1.1846 Device : cuda:0.. Test_loss : 0.8546646137077075.. Test_Accuracy : 0.7517361044883728..
Epoch: 3/5...  Loss: 1.2270 Device : cuda:0.. Test_loss : 0.8263763149197285.. Test_Accuracy : 0.7510684132575989..
Epoch: 3/5...  Loss: 1.1783 Device : cuda:0.. Test_loss : 0.8721701422562966.. Test_Accuracy : 0.7453258037567139..
Epoch: 3/5...  Loss: 1.4271 Device : cuda:0.. Test_loss : 0.9161724763420912.. Test_Accuracy : 0.7323717474937439..
Epoch: 3/5...  Loss: 1.1635 Device : cuda:0.. Test_loss : 0.960397638953649.. Test_Accuracy : 0.7158119678497314..
Epoch: 3/5...  Loss: 1.0549 Device : cuda:0.. Test_loss : 0.9516140414545169.. Test_Accuracy : 0.7401174902915955..
Epoch: 3/5...  Loss: 0.8368 Device : cuda:0.. Test_loss : 0.9800651468909704.. Test_Accuracy : 0.7314369678497314..
Epoch: 3/5...  Loss: 1.3930 Device : cuda:0.. Test_loss : 0.8749328209803655.. Test_Accuracy : 0.7525373697280884..
Epoch: 3/5...  Loss: 1.4428 Device : cuda:0.. Test_loss : 0.8358146101236343.. Test_Accuracy : 0.7645565867424011..
Epoch: 3/5...  Loss: 1.1030 Device : cuda:0.. Test_loss : 0.8622262959296887.. Test_Accuracy : 0.7377136945724487..
Epoch: 3/5...  Loss: 1.2815 Device : cuda:0.. Test_loss : 0.9145075547007414.. Test_Accuracy : 0.7186164855957031..
Epoch: 3/5...  Loss: 1.2670 Device : cuda:0.. Test_loss : 0.7911947936965869.. Test_Accuracy : 0.7645565867424011..
Epoch: 3/5...  Loss: 1.3282 Device : cuda:0.. Test_loss : 0.8222722583092176.. Test_Accuracy : 0.7705662250518799..
Epoch: 3/5...  Loss: 0.9491 Device : cuda:0.. Test_loss : 0.8489499034789892.. Test_Accuracy : 0.7654914855957031..
Epoch: 3/5...  Loss: 1.2249 Device : cuda:0.. Test_loss : 0.8041078256299863.. Test_Accuracy : 0.7820513248443604..
Epoch: 3/5...  Loss: 1.2134 Device : cuda:0.. Test_loss : 0.8089211583137512.. Test_Accuracy : 0.7633546590805054..
Epoch: 3/5...  Loss: 1.1720 Device : cuda:0.. Test_loss : 0.8537714143212025.. Test_Accuracy : 0.7542734742164612..
Epoch: 3/5...  Loss: 0.9235 Device : cuda:0.. Test_loss : 0.8695512866744628.. Test_Accuracy : 0.7487980723381042..
Epoch: 3/5...  Loss: 1.1184 Device : cuda:0.. Test_loss : 0.8098004506184504.. Test_Accuracy : 0.7461271286010742..
Epoch: 3/5...  Loss: 1.3383 Device : cuda:0.. Test_loss : 0.7310157512816099.. Test_Accuracy : 0.7922008037567139..
Epoch: 3/5...  Loss: 0.8543 Device : cuda:0.. Test_loss : 0.7356578621726769.. Test_Accuracy : 0.8006142973899841..
Epoch: 3/5...  Loss: 1.0938 Device : cuda:0.. Test_loss : 0.7815669795068411.. Test_Accuracy : 0.8000801801681519..
Epoch: 3/5...  Loss: 1.1612 Device : cuda:0.. Test_loss : 0.7835544940943902.. Test_Accuracy : 0.7849892973899841..
Epoch: 3/5...  Loss: 1.0081 Device : cuda:0.. Test_loss : 0.7925218916856326.. Test_Accuracy : 0.7820513248443604..
Epoch: 3/5...  Loss: 1.2119 Device : cuda:0.. Test_loss : 0.8449636193422171.. Test_Accuracy : 0.7558761239051819..
Epoch: 4/5...  Loss: 1.0458 Device : cuda:0.. Test_loss : 0.759057702926489.. Test_Accuracy : 0.7808493971824646..
Epoch: 4/5...  Loss: 1.0891 Device : cuda:0.. Test_loss : 0.8328015506267548.. Test_Accuracy : 0.7628205418586731..
Epoch: 4/5...  Loss: 1.1070 Device : cuda:0.. Test_loss : 0.811637584406596.. Test_Accuracy : 0.7715011239051819..
Epoch: 4/5...  Loss: 1.1031 Device : cuda:0.. Test_loss : 0.8695080068248969.. Test_Accuracy : 0.7588140964508057..
Epoch: 4/5...  Loss: 1.0395 Device : cuda:0.. Test_loss : 0.8144854152431855.. Test_Accuracy : 0.7796474695205688..
Epoch: 4/5...  Loss: 1.1286 Device : cuda:0.. Test_loss : 0.8073848783969879.. Test_Accuracy : 0.7765758037567139..
Epoch: 4/5...  Loss: 1.0445 Device : cuda:0.. Test_loss : 0.8037307967360203.. Test_Accuracy : 0.7861912250518799..
Epoch: 4/5...  Loss: 1.0702 Device : cuda:0.. Test_loss : 0.8913756918448669.. Test_Accuracy : 0.7489315867424011..
Epoch: 4/5...  Loss: 1.1069 Device : cuda:0.. Test_loss : 0.7857886094313401.. Test_Accuracy : 0.781784176826477..
Epoch: 4/5...  Loss: 0.8883 Device : cuda:0.. Test_loss : 0.7266395759697144.. Test_Accuracy : 0.7889957427978516..
Epoch: 4/5...  Loss: 1.1836 Device : cuda:0.. Test_loss : 0.6672092381005104.. Test_Accuracy : 0.8070245981216431..
Epoch: 4/5...  Loss: 0.8300 Device : cuda:0.. Test_loss : 0.7482990940602926.. Test_Accuracy : 0.7877938151359558..
Epoch: 4/5...  Loss: 1.1314 Device : cuda:0.. Test_loss : 0.7116500741014113.. Test_Accuracy : 0.8070245981216431..
Epoch: 4/5...  Loss: 0.8737 Device : cuda:0.. Test_loss : 0.6877702425878781.. Test_Accuracy : 0.8123664855957031..
Epoch: 4/5...  Loss: 0.8949 Device : cuda:0.. Test_loss : 0.7812780081652678.. Test_Accuracy : 0.7690972685813904..
Epoch: 4/5...  Loss: 1.1418 Device : cuda:0.. Test_loss : 0.7789745078637049.. Test_Accuracy : 0.7799145579338074..
Epoch: 4/5...  Loss: 0.9780 Device : cuda:0.. Test_loss : 0.8118256617050904.. Test_Accuracy : 0.7606837749481201..
Epoch: 4/5...  Loss: 1.2447 Device : cuda:0.. Test_loss : 0.7876517517635455.. Test_Accuracy : 0.7664263248443604..
Epoch: 4/5...  Loss: 0.8882 Device : cuda:0.. Test_loss : 0.7845812428456086.. Test_Accuracy : 0.7871261239051819..
Epoch: 4/5...  Loss: 1.1071 Device : cuda:0.. Test_loss : 0.7479727540451747.. Test_Accuracy : 0.7952724695205688..
Epoch: 4/5...  Loss: 0.8603 Device : cuda:0.. Test_loss : 0.7184878312624418.. Test_Accuracy : 0.7994123697280884..
Epoch: 4/5...  Loss: 0.9242 Device : cuda:0.. Test_loss : 0.7201504695873994.. Test_Accuracy : 0.8006142973899841..
Epoch: 4/5...  Loss: 0.8247 Device : cuda:0.. Test_loss : 0.7593993544578552.. Test_Accuracy : 0.7891292572021484..
Epoch: 4/5...  Loss: 1.1620 Device : cuda:0.. Test_loss : 0.8144613773776934.. Test_Accuracy : 0.7660256028175354..
Epoch: 4/5...  Loss: 1.1084 Device : cuda:0.. Test_loss : 0.7746024343829888.. Test_Accuracy : 0.780715823173523..
Epoch: 4/5...  Loss: 0.8004 Device : cuda:0.. Test_loss : 0.8469797238134421.. Test_Accuracy : 0.7545405626296997..
Epoch: 4/5...  Loss: 0.9767 Device : cuda:0.. Test_loss : 0.8497868853692825.. Test_Accuracy : 0.7636217474937439..
Epoch: 4/5...  Loss: 0.7932 Device : cuda:0.. Test_loss : 0.8508035789888638.. Test_Accuracy : 0.7674946188926697..
Epoch: 4/5...  Loss: 1.2498 Device : cuda:0.. Test_loss : 0.7676853715227201.. Test_Accuracy : 0.7732371687889099..
Epoch: 4/5...  Loss: 1.0884 Device : cuda:0.. Test_loss : 0.744837107280126.. Test_Accuracy : 0.7952724695205688..
Epoch: 4/5...  Loss: 1.1191 Device : cuda:0.. Test_loss : 0.8197122571560053.. Test_Accuracy : 0.7657585144042969..
Epoch: 4/5...  Loss: 0.9181 Device : cuda:0.. Test_loss : 0.8048521692936237.. Test_Accuracy : 0.7799145579338074..
Epoch: 4/5...  Loss: 1.0485 Device : cuda:0.. Test_loss : 0.740715194780093.. Test_Accuracy : 0.7859241962432861..
Epoch: 4/5...  Loss: 1.0167 Device : cuda:0.. Test_loss : 0.723017234641772.. Test_Accuracy : 0.7848557829856873..
Epoch: 4/5...  Loss: 0.8428 Device : cuda:0.. Test_loss : 0.7332267311330025.. Test_Accuracy : 0.7927350401878357..
Epoch: 4/5...  Loss: 0.9838 Device : cuda:0.. Test_loss : 0.6681343311300645.. Test_Accuracy : 0.8150373697280884..
Epoch: 4/5...  Loss: 1.0943 Device : cuda:0.. Test_loss : 0.6484071159592042.. Test_Accuracy : 0.8250534534454346..
Epoch: 4/5...  Loss: 0.9232 Device : cuda:0.. Test_loss : 0.6649243840231345.. Test_Accuracy : 0.8169070482254028..
Epoch: 4/5...  Loss: 1.0378 Device : cuda:0.. Test_loss : 0.7176233604550362.. Test_Accuracy : 0.7982104420661926..
Epoch: 4/5...  Loss: 1.0725 Device : cuda:0.. Test_loss : 0.7343127269011277.. Test_Accuracy : 0.7946046590805054..
Epoch: 4/5...  Loss: 1.0136 Device : cuda:0.. Test_loss : 0.6672742332403476.. Test_Accuracy : 0.8063568472862244..
Epoch: 5/5...  Loss: 1.1557 Device : cuda:0.. Test_loss : 0.6598494895375692.. Test_Accuracy : 0.8054219484329224..
Epoch: 5/5...  Loss: 0.9202 Device : cuda:0.. Test_loss : 0.7352759537215416.. Test_Accuracy : 0.7873931527137756..
Epoch: 5/5...  Loss: 0.9627 Device : cuda:0.. Test_loss : 0.737551885155531.. Test_Accuracy : 0.7835203409194946..
Epoch: 5/5...  Loss: 0.8672 Device : cuda:0.. Test_loss : 0.6729287992303188.. Test_Accuracy : 0.7936698198318481..
Epoch: 5/5...  Loss: 0.9184 Device : cuda:0.. Test_loss : 0.6728199866528695.. Test_Accuracy : 0.7946046590805054..
Epoch: 5/5...  Loss: 1.0523 Device : cuda:0.. Test_loss : 0.7318796435227761.. Test_Accuracy : 0.8006142973899841..
Epoch: 5/5...  Loss: 0.8919 Device : cuda:0.. Test_loss : 0.7319818090360898.. Test_Accuracy : 0.7919337749481201..
Epoch: 5/5...  Loss: 0.9608 Device : cuda:0.. Test_loss : 0.7103085979246176.. Test_Accuracy : 0.8063568472862244..
Epoch: 5/5...  Loss: 0.9071 Device : cuda:0.. Test_loss : 0.7018805793844737.. Test_Accuracy : 0.8008813858032227..
Epoch: 5/5...  Loss: 0.9587 Device : cuda:0.. Test_loss : 0.7202522892218369.. Test_Accuracy : 0.7951388955116272..
Epoch: 5/5...  Loss: 0.7595 Device : cuda:0.. Test_loss : 0.7089212519618181.. Test_Accuracy : 0.8027511239051819..
Epoch: 5/5...  Loss: 0.6663 Device : cuda:0.. Test_loss : 0.7298324469190377.. Test_Accuracy : 0.7979434132575989..
Epoch: 5/5...  Loss: 0.9607 Device : cuda:0.. Test_loss : 0.7645496657261481.. Test_Accuracy : 0.7895299196243286..
Epoch: 5/5...  Loss: 0.8192 Device : cuda:0.. Test_loss : 0.7930828799995092.. Test_Accuracy : 0.7765758037567139..
Epoch: 5/5...  Loss: 0.8615 Device : cuda:0.. Test_loss : 0.7290209084749222.. Test_Accuracy : 0.8059561848640442..
Epoch: 5/5...  Loss: 0.8043 Device : cuda:0.. Test_loss : 0.6724872589111328.. Test_Accuracy : 0.8155715465545654..
Epoch: 5/5...  Loss: 0.9377 Device : cuda:0.. Test_loss : 0.645936862207376.. Test_Accuracy : 0.8194444179534912..
Epoch: 5/5...  Loss: 0.8773 Device : cuda:0.. Test_loss : 0.6621698894752905.. Test_Accuracy : 0.8255876302719116..
Epoch: 5/5...  Loss: 0.8114 Device : cuda:0.. Test_loss : 0.714272531752403.. Test_Accuracy : 0.8012820482254028..
Epoch: 5/5...  Loss: 0.9648 Device : cuda:0.. Test_loss : 0.7036195683937806.. Test_Accuracy : 0.8178418874740601..
Epoch: 5/5...  Loss: 0.7578 Device : cuda:0.. Test_loss : 0.7147353027875607.. Test_Accuracy : 0.8015491962432861..
Epoch: 5/5...  Loss: 0.8682 Device : cuda:0.. Test_loss : 0.6618485811811227.. Test_Accuracy : 0.8114315867424011..
Epoch: 5/5...  Loss: 0.9425 Device : cuda:0.. Test_loss : 0.6164678232027934.. Test_Accuracy : 0.8277243971824646..
Epoch: 5/5...  Loss: 0.7986 Device : cuda:0.. Test_loss : 0.6611089878357373.. Test_Accuracy : 0.8246527314186096..
Epoch: 5/5...  Loss: 1.0229 Device : cuda:0.. Test_loss : 0.6619697453883978.. Test_Accuracy : 0.8229166865348816..
Epoch: 5/5...  Loss: 0.7286 Device : cuda:0.. Test_loss : 0.694170263237678.. Test_Accuracy : 0.8133013248443604..
Epoch: 5/5...  Loss: 0.9872 Device : cuda:0.. Test_loss : 0.7572457927923936.. Test_Accuracy : 0.7895299196243286..
Epoch: 5/5...  Loss: 1.0888 Device : cuda:0.. Test_loss : 0.7574543356895447.. Test_Accuracy : 0.7967414855957031..
Epoch: 5/5...  Loss: 1.0088 Device : cuda:0.. Test_loss : 0.7255236176917186.. Test_Accuracy : 0.7984775304794312..
Epoch: 5/5...  Loss: 0.8508 Device : cuda:0.. Test_loss : 0.6990498401797735.. Test_Accuracy : 0.8042200803756714..
Epoch: 5/5...  Loss: 0.8326 Device : cuda:0.. Test_loss : 0.6946865239968667.. Test_Accuracy : 0.8102296590805054..
Epoch: 5/5...  Loss: 0.9528 Device : cuda:0.. Test_loss : 0.653331231039304.. Test_Accuracy : 0.8270565867424011..
Epoch: 5/5...  Loss: 0.9152 Device : cuda:0.. Test_loss : 0.7423968601685303.. Test_Accuracy : 0.8018162250518799..
Epoch: 5/5...  Loss: 0.8815 Device : cuda:0.. Test_loss : 0.6901708566225492.. Test_Accuracy : 0.8042200803756714..
Epoch: 5/5...  Loss: 1.0429 Device : cuda:0.. Test_loss : 0.6710408501900159.. Test_Accuracy : 0.8282585144042969..
Epoch: 5/5...  Loss: 0.9440 Device : cuda:0.. Test_loss : 0.7031958005749263.. Test_Accuracy : 0.8035523295402527..
Epoch: 5/5...  Loss: 0.7697 Device : cuda:0.. Test_loss : 0.6638749344990804.. Test_Accuracy : 0.8116986751556396..
Epoch: 5/5...  Loss: 0.9447 Device : cuda:0.. Test_loss : 0.6717513859845125.. Test_Accuracy : 0.8153044581413269..
Epoch: 5/5...  Loss: 0.7891 Device : cuda:0.. Test_loss : 0.7127989656650103.. Test_Accuracy : 0.7996794581413269..
Epoch: 5/5...  Loss: 0.9623 Device : cuda:0.. Test_loss : 0.6781166230256741.. Test_Accuracy : 0.8189102411270142..
Epoch: 5/5...  Loss: 0.9307 Device : cuda:0.. Test_loss : 0.7816430318814057.. Test_Accuracy : 0.7828525304794312..
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<h2 id="Testing-your-network">Testing your network<a class="anchor-link" href="#Testing-your-network">&#182;</a></h2><p>It's good practice to test your trained network on test data, images the network has never seen either in training or validation. This will give you a good estimate for the model's performance on completely new images. Run the test images through the network and measure the accuracy, the same way you did validation. You should be able to reach around 70% accuracy on the test set if the model has been trained well.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Do validation on the test set</span>

<span class="k">def</span> <span class="nf">accuracy_test</span><span class="p">(</span><span class="n">model</span><span class="p">):</span>    
    <span class="n">correct</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">total</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">model</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="s1">&#39;cuda:0&#39;</span><span class="p">)</span>
    <span class="n">model</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
    <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
        <span class="k">for</span> <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="ow">in</span> <span class="n">testloader</span><span class="p">:</span>
            <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">images</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="s1">&#39;cuda:0&#39;</span><span class="p">),</span> <span class="n">labels</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="s1">&#39;cuda:0&#39;</span><span class="p">)</span>
            <span class="n">outputs</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">images</span><span class="p">)</span>
            <span class="n">_</span><span class="p">,</span> <span class="n">predicted</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">outputs</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
            <span class="n">total</span> <span class="o">+=</span> <span class="n">labels</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
            <span class="n">correct</span> <span class="o">+=</span> <span class="p">(</span><span class="n">predicted</span> <span class="o">==</span> <span class="n">labels</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>

    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy of the network on the test images: </span><span class="si">%d</span><span class="s1"> </span><span class="si">%%</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="mi">100</span> <span class="o">*</span> <span class="n">correct</span> <span class="o">/</span> <span class="n">total</span><span class="p">))</span>
    
<span class="n">accuracy_test</span><span class="p">(</span><span class="n">loaded_model</span><span class="p">)</span>
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<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
<span class="ansi-red-fg">NameError</span>                                 Traceback (most recent call last)
<span class="ansi-green-fg">&lt;ipython-input-8-d62ba7e0e495&gt;</span> in <span class="ansi-cyan-fg">&lt;module&gt;</span><span class="ansi-blue-fg">()</span>
<span class="ansi-green-intense-fg ansi-bold">     16</span>     print<span class="ansi-blue-fg">(</span><span class="ansi-blue-fg">&#39;Accuracy of the network on the test images: %d %%&#39;</span> <span class="ansi-blue-fg">%</span> <span class="ansi-blue-fg">(</span><span class="ansi-cyan-fg">100</span> <span class="ansi-blue-fg">*</span> correct <span class="ansi-blue-fg">/</span> total<span class="ansi-blue-fg">)</span><span class="ansi-blue-fg">)</span>
<span class="ansi-green-intense-fg ansi-bold">     17</span> 
<span class="ansi-green-fg">---&gt; 18</span><span class="ansi-red-fg"> </span>accuracy_test<span class="ansi-blue-fg">(</span>loaded_model<span class="ansi-blue-fg">)</span>

<span class="ansi-red-fg">NameError</span>: name &#39;loaded_model&#39; is not defined</pre>
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<h2 id="Save-the-checkpoint">Save the checkpoint<a class="anchor-link" href="#Save-the-checkpoint">&#182;</a></h2><p>Now that your network is trained, save the model so you can load it later for making predictions. You probably want to save other things such as the mapping of classes to indices which you get from one of the image datasets: <code>image_datasets['train'].class_to_idx</code>. You can attach this to the model as an attribute which makes inference easier later on.</p>
<p><code>model.class_to_idx = image_datasets['train'].class_to_idx</code></p>
<p>Remember that you'll want to completely rebuild the model later so you can use it for inference. Make sure to include any information you need in the checkpoint. If you want to load the model and keep training, you'll want to save the number of epochs as well as the optimizer state, <code>optimizer.state_dict</code>. You'll likely want to use this trained model in the next part of the project, so best to save it now.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Save the checkpoint </span>

<span class="k">def</span> <span class="nf">save_checkpoint</span><span class="p">(</span><span class="n">model</span><span class="p">):</span>
    <span class="n">model</span><span class="o">.</span><span class="n">class_to_idx</span> <span class="o">=</span> <span class="n">train_data</span><span class="o">.</span><span class="n">class_to_idx</span>
    
    <span class="n">checkpoint</span> <span class="o">=</span> <span class="p">{</span>
                  <span class="s1">&#39;hidden_units&#39;</span> <span class="p">:</span> <span class="mi">512</span><span class="p">,</span>
                  <span class="s1">&#39;arch&#39;</span> <span class="p">:</span> <span class="s1">&#39;vgg19&#39;</span><span class="p">,</span>
                  <span class="s1">&#39;optimizer&#39;</span> <span class="p">:</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">state_dict</span><span class="p">,</span>
                  <span class="s1">&#39;class_to_idx&#39;</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">class_to_idx</span><span class="p">,</span>
                  <span class="s1">&#39;state_dict&#39;</span> <span class="p">:</span>  <span class="n">model</span><span class="o">.</span><span class="n">state_dict</span><span class="p">()</span>              
    
                 <span class="p">}</span>
    
    <span class="n">torch</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">,</span> <span class="s1">&#39;checkpoint.pth&#39;</span><span class="p">)</span>
    
<span class="n">save_checkpoint</span><span class="p">(</span><span class="n">final_model</span><span class="p">)</span>
    
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<h2 id="Loading-the-checkpoint">Loading the checkpoint<a class="anchor-link" href="#Loading-the-checkpoint">&#182;</a></h2><p>At this point it's good to write a function that can load a checkpoint and rebuild the model. That way you can come back to this project and keep working on it without having to retrain the network.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Write a function that loads a checkpoint and rebuilds the model</span>

<span class="k">def</span> <span class="nf">load_checkpoint</span><span class="p">(</span><span class="n">filepath</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Loads checkpoint of model. Takes filepath as input and returns loaded model.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">checkpoint</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">filepath</span><span class="p">)</span>
    <span class="n">arch</span> <span class="o">=</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;arch&#39;</span><span class="p">]</span>
    <span class="n">hidden_units</span> <span class="o">=</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;hidden_units&#39;</span><span class="p">]</span>

    
    <span class="n">model</span><span class="p">,</span><span class="n">_</span><span class="p">,</span><span class="n">_</span> <span class="o">=</span> <span class="n">model_setup</span><span class="p">(</span><span class="n">arch</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">hidden_units</span><span class="p">)</span>
    <span class="n">model</span><span class="o">.</span><span class="n">class_to_idx</span> <span class="o">=</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;class_to_idx&#39;</span><span class="p">]</span>
    <span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;state_dict&#39;</span><span class="p">])</span>
    
    <span class="k">return</span> <span class="n">model</span>

<span class="n">loaded_model</span> <span class="o">=</span> <span class="n">load_checkpoint</span><span class="p">(</span><span class="s1">&#39;checkpoint.pth&#39;</span><span class="p">)</span>
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<h1 id="Inference-for-classification">Inference for classification<a class="anchor-link" href="#Inference-for-classification">&#182;</a></h1><p>Now you'll write a function to use a trained network for inference. That is, you'll pass an image into the network and predict the class of the flower in the image. Write a function called <code>predict</code> that takes an image and a model, then returns the top $K$ most likely classes along with the probabilities. It should look like</p>
<div class="highlight"><pre><span></span><span class="n">probs</span><span class="p">,</span> <span class="n">classes</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">probs</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">classes</span><span class="p">)</span>
<span class="o">&gt;</span> <span class="p">[</span> <span class="mf">0.01558163</span>  <span class="mf">0.01541934</span>  <span class="mf">0.01452626</span>  <span class="mf">0.01443549</span>  <span class="mf">0.01407339</span><span class="p">]</span>
<span class="o">&gt;</span> <span class="p">[</span><span class="s1">&#39;70&#39;</span><span class="p">,</span> <span class="s1">&#39;3&#39;</span><span class="p">,</span> <span class="s1">&#39;45&#39;</span><span class="p">,</span> <span class="s1">&#39;62&#39;</span><span class="p">,</span> <span class="s1">&#39;55&#39;</span><span class="p">]</span>
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<p>First you'll need to handle processing the input image such that it can be used in your network.</p>
<h2 id="Image-Preprocessing">Image Preprocessing<a class="anchor-link" href="#Image-Preprocessing">&#182;</a></h2><p>You'll want to use <code>PIL</code> to load the image (<a href="https://pillow.readthedocs.io/en/latest/reference/Image.html">documentation</a>). It's best to write a function that preprocesses the image so it can be used as input for the model. This function should process the images in the same manner used for training.</p>
<p>First, resize the images where the shortest side is 256 pixels, keeping the aspect ratio. This can be done with the <a href="http://pillow.readthedocs.io/en/3.1.x/reference/Image.html#PIL.Image.Image.thumbnail"><code>thumbnail</code></a> or <a href="http://pillow.readthedocs.io/en/3.1.x/reference/Image.html#PIL.Image.Image.thumbnail"><code>resize</code></a> methods. Then you'll need to crop out the center 224x224 portion of the image.</p>
<p>Color channels of images are typically encoded as integers 0-255, but the model expected floats 0-1. You'll need to convert the values. It's easiest with a Numpy array, which you can get from a PIL image like so <code>np_image = np.array(pil_image)</code>.</p>
<p>As before, the network expects the images to be normalized in a specific way. For the means, it's <code>[0.485, 0.456, 0.406]</code> and for the standard deviations <code>[0.229, 0.224, 0.225]</code>. You'll want to subtract the means from each color channel, then divide by the standard deviation.</p>
<p>And finally, PyTorch expects the color channel to be the first dimension but it's the third dimension in the PIL image and Numpy array. You can reorder dimensions using <a href="https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.ndarray.transpose.html"><code>ndarray.transpose</code></a>. The color channel needs to be first and retain the order of the other two dimensions.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">process_image</span><span class="p">(</span><span class="n">image_path</span><span class="p">):</span>
    
    <span class="c1"># Open image with PIL</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">image_path</span><span class="p">)</span>
    
    <span class="c1"># Resize the image</span>
    <span class="k">if</span> <span class="n">image</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">image</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">1</span><span class="p">]:</span>
        <span class="n">image</span><span class="o">.</span><span class="n">thumbnail</span><span class="p">((</span><span class="mi">10000</span><span class="p">,</span> <span class="mi">256</span><span class="p">))</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">image</span><span class="o">.</span><span class="n">thumbnail</span><span class="p">((</span><span class="mi">256</span><span class="p">,</span> <span class="mi">10000</span><span class="p">))</span>
        
    <span class="c1"># Crop the image</span>
    <span class="n">left_margin</span> <span class="o">=</span> <span class="p">(</span><span class="n">image</span><span class="o">.</span><span class="n">width</span><span class="o">-</span><span class="mi">224</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>
    <span class="n">bottom_margin</span> <span class="o">=</span> <span class="p">(</span><span class="n">image</span><span class="o">.</span><span class="n">height</span><span class="o">-</span><span class="mi">224</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>
    <span class="n">right_margin</span> <span class="o">=</span> <span class="n">left_margin</span> <span class="o">+</span> <span class="mi">224</span>
    <span class="n">top_margin</span> <span class="o">=</span> <span class="n">bottom_margin</span> <span class="o">+</span> <span class="mi">224</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">crop</span><span class="p">((</span><span class="n">left_margin</span><span class="p">,</span> <span class="n">bottom_margin</span><span class="p">,</span> <span class="n">right_margin</span><span class="p">,</span>   
                      <span class="n">top_margin</span><span class="p">))</span>
    <span class="c1"># Normalize the image</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">image</span><span class="p">)</span><span class="o">/</span><span class="mi">255</span>
    <span class="n">image</span> <span class="o">=</span> <span class="p">(</span><span class="n">image</span> <span class="o">-</span> <span class="n">means</span><span class="p">)</span><span class="o">/</span><span class="n">std</span>
    
    <span class="c1"># Move color channels to first dimension as expected by PyTorch</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">transpose</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
    
    <span class="k">return</span> <span class="n">image</span>
    
            
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<p>To check your work, the function below converts a PyTorch tensor and displays it in the notebook. If your <code>process_image</code> function works, running the output through this function should return the original image (except for the cropped out portions).</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">imshow</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="k">if</span> <span class="n">ax</span> <span class="ow">is</span> <span class="kc">None</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="c1"># PyTorch tensors assume the color channel is the first dimension</span>
    <span class="c1"># but matplotlib assumes is the third dimension</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">transpose</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
    
    <span class="c1"># Add title if function is called with title argument</span>
    <span class="k">if</span> <span class="n">title</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="n">title</span><span class="p">)</span>
        
    <span class="c1"># Undo preprocessing</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">std</span> <span class="o">*</span> <span class="n">image</span> <span class="o">+</span> <span class="n">means</span>
    
    <span class="c1"># Image needs to be clipped between 0 and 1 or it looks like noise when displayed</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">clip</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
    
    <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">ax</span>
<span class="n">imshow</span><span class="p">(</span><span class="n">process_image</span><span class="p">(</span><span class="s2">&quot;flowers/test/10/image_07090.jpg&quot;</span><span class="p">))</span>
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<h2 id="Class-Prediction">Class Prediction<a class="anchor-link" href="#Class-Prediction">&#182;</a></h2><p>Once you can get images in the correct format, it's time to write a function for making predictions with your model. A common practice is to predict the top 5 or so (usually called top-$K$) most probable classes. You'll want to calculate the class probabilities then find the $K$ largest values.</p>
<p>To get the top $K$ largest values in a tensor use <a href="http://pytorch.org/docs/master/torch.html#torch.topk"><code>x.topk(k)</code></a>. This method returns both the highest <code>k</code> probabilities and the indices of those probabilities corresponding to the classes. You need to convert from these indices to the actual class labels using <code>class_to_idx</code> which hopefully you added to the model or from an <code>ImageFolder</code> you used to load the data (<a href="#Save-the-checkpoint">see here</a>). Make sure to invert the dictionary so you get a mapping from index to class as well.</p>
<p>Again, this method should take a path to an image and a model checkpoint, then return the probabilities and classes.</p>
<div class="highlight"><pre><span></span><span class="n">probs</span><span class="p">,</span> <span class="n">classes</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">probs</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">classes</span><span class="p">)</span>
<span class="o">&gt;</span> <span class="p">[</span> <span class="mf">0.01558163</span>  <span class="mf">0.01541934</span>  <span class="mf">0.01452626</span>  <span class="mf">0.01443549</span>  <span class="mf">0.01407339</span><span class="p">]</span>
<span class="o">&gt;</span> <span class="p">[</span><span class="s1">&#39;70&#39;</span><span class="p">,</span> <span class="s1">&#39;3&#39;</span><span class="p">,</span> <span class="s1">&#39;45&#39;</span><span class="p">,</span> <span class="s1">&#39;62&#39;</span><span class="p">,</span> <span class="s1">&#39;55&#39;</span><span class="p">]</span>
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<div class="prompt input_prompt">In&nbsp;[19]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">5</span> <span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Prediction function. Takes, images_path, model, category_label, gpu(True/False), k=number</span>
<span class="sd">    of probable flowers as input. Returns a list of flowername, flowerlabels, and probabilities</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s2">&quot;cuda:0&quot;</span> <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span> <span class="k">else</span> <span class="s1">&#39;cpu&#39;</span><span class="p">)</span>
    <span class="n">model</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>

    <span class="n">img</span> <span class="o">=</span> <span class="n">process_image</span><span class="p">(</span><span class="n">image_path</span><span class="p">)</span>

    <span class="c1"># transform numpy to tensor object</span>
    <span class="n">image_tensor</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">img</span><span class="p">)</span><span class="o">.</span><span class="n">type</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">FloatTensor</span><span class="p">)</span>
    <span class="c1"># Add batch of size 1 to image</span>
    <span class="n">model_input</span> <span class="o">=</span> <span class="n">image_tensor</span><span class="o">.</span><span class="n">unsqueeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>

    <span class="c1"># Probabilities</span>
    <span class="n">probs</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">model_input</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)))</span>


    <span class="c1"># Highest probabilities, 5 by default</span>
    <span class="n">top_probs</span><span class="p">,</span> <span class="n">top_labs</span> <span class="o">=</span> <span class="n">probs</span><span class="o">.</span><span class="n">topk</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="n">top_probs</span> <span class="o">=</span> <span class="n">top_probs</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
    <span class="n">top_labs</span> <span class="o">=</span> <span class="n">top_labs</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>

    <span class="c1"># Convert indices to classes</span>
    <span class="n">idx_to_class</span> <span class="o">=</span> <span class="p">{</span><span class="n">val</span><span class="p">:</span> <span class="n">key</span> <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">val</span> <span class="ow">in</span>
                                      <span class="n">model</span><span class="o">.</span><span class="n">class_to_idx</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>

    <span class="c1"># Get top labels and top frloer names</span>
    <span class="n">top_labels</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">top_flowers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">top_labs</span><span class="p">:</span>
        <span class="n">top_labels</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">idx_to_class</span><span class="p">[</span><span class="n">label</span><span class="p">])</span>
        <span class="n">top_flowers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">cat_to_name</span><span class="p">[</span><span class="n">idx_to_class</span><span class="p">[</span><span class="n">label</span><span class="p">]])</span>

    <span class="k">return</span> <span class="n">top_probs</span><span class="p">,</span> <span class="n">top_labels</span><span class="p">,</span> <span class="n">top_flowers</span>
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<h2 id="Sanity-Checking">Sanity Checking<a class="anchor-link" href="#Sanity-Checking">&#182;</a></h2><p>Now that you can use a trained model for predictions, check to make sure it makes sense. Even if the testing accuracy is high, it's always good to check that there aren't obvious bugs. Use <code>matplotlib</code> to plot the probabilities for the top 5 classes as a bar graph, along with the input image. It should look like this:</p>
<p><img src='assets/inference_example.png' width=300px></p>
<p>You can convert from the class integer encoding to actual flower names with the <code>cat_to_name.json</code> file (should have been loaded earlier in the notebook). To show a PyTorch tensor as an image, use the <code>imshow</code> function defined above.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">sanity_check</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
    <span class="c1"># Set up plot</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">6</span><span class="p">,</span><span class="mi">10</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">subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
    
    <span class="c1"># Takes flower number</span>
    <span class="n">flower_num</span> <span class="o">=</span> <span class="n">image_path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;/&#39;</span><span class="p">)[</span><span class="mi">2</span><span class="p">]</span>
    
    <span class="n">title_</span> <span class="o">=</span> <span class="n">cat_to_name</span><span class="p">[</span><span class="n">flower_num</span><span class="p">]</span>
    <span class="c1"># Plot flower</span>
    <span class="n">img</span> <span class="o">=</span> <span class="n">process_image</span><span class="p">(</span><span class="n">image_path</span><span class="p">)</span>
    <span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">ax</span><span class="p">,</span> <span class="n">title</span> <span class="o">=</span> <span class="n">title_</span><span class="p">);</span>
    <span class="c1"># Make prediction</span>
    <span class="n">probs</span><span class="p">,</span> <span class="n">labs</span><span class="p">,</span> <span class="n">flowers</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="s1">&#39;cpu&#39;</span><span class="p">))</span> 
    <span class="c1"># Plot bar chart</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">)</span>
    <span class="n">sns</span><span class="o">.</span><span class="n">barplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">probs</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">flowers</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">sns</span><span class="o">.</span><span class="n">color_palette</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">show</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sanity_check</span><span class="p">(</span><span class="s2">&quot;flowers/test/100/image_07902.jpg&quot;</span><span class="p">,</span> <span class="n">loaded_model</span><span class="p">)</span>
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