machine_translation.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />

<title>machine_translation</title>

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<style type="text/css">
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 * Bootstrap v3.3.7 (http://getbootstrap.com)
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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]) {
  display: none;
  height: 0;
}
[hidden],
template {
  display: none;
}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
  font-style: italic;
}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
  background: #ff0;
  color: #000;
}
small {
  font-size: 80%;
}
sub,
sup {
  font-size: 75%;
  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
  top: -0.5em;
}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
  overflow: hidden;
}
figure {
  margin: 1em 40px;
}
hr {
  box-sizing: content-box;
  height: 0;
}
pre {
  overflow: auto;
}
code,
kbd,
pre,
samp {
  font-family: monospace, monospace;
  font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
  color: inherit;
  font: inherit;
  margin: 0;
}
button {
  overflow: visible;
}
button,
select {
  text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
  -webkit-appearance: button;
  cursor: pointer;
}
button[disabled],
html input[disabled] {
  cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
  border: 0;
  padding: 0;
}
input {
  line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
  box-sizing: border-box;
  padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: textfield;
  box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
  -webkit-appearance: none;
}
fieldset {
  border: 1px solid #c0c0c0;
  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
}
legend {
  border: 0;
  padding: 0;
}
textarea {
  overflow: auto;
}
optgroup {
  font-weight: bold;
}
table {
  border-collapse: collapse;
  border-spacing: 0;
}
td,
th {
  padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
  *,
  *:before,
  *:after {
    background: transparent !important;
    box-shadow: none !important;
    text-shadow: none !important;
  }
  a,
  a:visited {
    text-decoration: underline;
  }
  a[href]:after {
    content: " (" attr(href) ")";
  }
  abbr[title]:after {
    content: " (" attr(title) ")";
  }
  a[href^="#"]:after,
  a[href^="javascript:"]:after {
    content: "";
  }
  pre,
  blockquote {
    border: 1px solid #999;
    page-break-inside: avoid;
  }
  thead {
    display: table-header-group;
  }
  tr,
  img {
    page-break-inside: avoid;
  }
  img {
    max-width: 100% !important;
  }
  p,
  h2,
  h3 {
    orphans: 3;
    widows: 3;
  }
  h2,
  h3 {
    page-break-after: avoid;
  }
  .navbar {
    display: none;
  }
  .btn > .caret,
  .dropup > .btn > .caret {
    border-top-color: #000 !important;
  }
  .label {
    border: 1px solid #000;
  }
  .table {
    border-collapse: collapse !important;
  }
  .table td,
  .table th {
    background-color: #fff !important;
  }
  .table-bordered th,
  .table-bordered td {
    border: 1px solid #ddd !important;
  }
}
@font-face {
  font-family: 'Glyphicons Halflings';
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
}
.glyphicon {
  position: relative;
  top: 1px;
  display: inline-block;
  font-family: 'Glyphicons Halflings';
  font-style: normal;
  font-weight: normal;
  line-height: 1;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
.glyphicon-asterisk:before {
  content: "\002a";
}
.glyphicon-plus:before {
  content: "\002b";
}
.glyphicon-euro:before,
.glyphicon-eur:before {
  content: "\20ac";
}
.glyphicon-minus:before {
  content: "\2212";
}
.glyphicon-cloud:before {
  content: "\2601";
}
.glyphicon-envelope:before {
  content: "\2709";
}
.glyphicon-pencil:before {
  content: "\270f";
}
.glyphicon-glass:before {
  content: "\e001";
}
.glyphicon-music:before {
  content: "\e002";
}
.glyphicon-search:before {
  content: "\e003";
}
.glyphicon-heart:before {
  content: "\e005";
}
.glyphicon-star:before {
  content: "\e006";
}
.glyphicon-star-empty:before {
  content: "\e007";
}
.glyphicon-user:before {
  content: "\e008";
}
.glyphicon-film:before {
  content: "\e009";
}
.glyphicon-th-large:before {
  content: "\e010";
}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
.glyphicon-remove:before {
  content: "\e014";
}
.glyphicon-zoom-in:before {
  content: "\e015";
}
.glyphicon-zoom-out:before {
  content: "\e016";
}
.glyphicon-off:before {
  content: "\e017";
}
.glyphicon-signal:before {
  content: "\e018";
}
.glyphicon-cog:before {
  content: "\e019";
}
.glyphicon-trash:before {
  content: "\e020";
}
.glyphicon-home:before {
  content: "\e021";
}
.glyphicon-file:before {
  content: "\e022";
}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
  content: "\e025";
}
.glyphicon-download:before {
  content: "\e026";
}
.glyphicon-upload:before {
  content: "\e027";
}
.glyphicon-inbox:before {
  content: "\e028";
}
.glyphicon-play-circle:before {
  content: "\e029";
}
.glyphicon-repeat:before {
  content: "\e030";
}
.glyphicon-refresh:before {
  content: "\e031";
}
.glyphicon-list-alt:before {
  content: "\e032";
}
.glyphicon-lock:before {
  content: "\e033";
}
.glyphicon-flag:before {
  content: "\e034";
}
.glyphicon-headphones:before {
  content: "\e035";
}
.glyphicon-volume-off:before {
  content: "\e036";
}
.glyphicon-volume-down:before {
  content: "\e037";
}
.glyphicon-volume-up:before {
  content: "\e038";
}
.glyphicon-qrcode:before {
  content: "\e039";
}
.glyphicon-barcode:before {
  content: "\e040";
}
.glyphicon-tag:before {
  content: "\e041";
}
.glyphicon-tags:before {
  content: "\e042";
}
.glyphicon-book:before {
  content: "\e043";
}
.glyphicon-bookmark:before {
  content: "\e044";
}
.glyphicon-print:before {
  content: "\e045";
}
.glyphicon-camera:before {
  content: "\e046";
}
.glyphicon-font:before {
  content: "\e047";
}
.glyphicon-bold:before {
  content: "\e048";
}
.glyphicon-italic:before {
  content: "\e049";
}
.glyphicon-text-height:before {
  content: "\e050";
}
.glyphicon-text-width:before {
  content: "\e051";
}
.glyphicon-align-left:before {
  content: "\e052";
}
.glyphicon-align-center:before {
  content: "\e053";
}
.glyphicon-align-right:before {
  content: "\e054";
}
.glyphicon-align-justify:before {
  content: "\e055";
}
.glyphicon-list:before {
  content: "\e056";
}
.glyphicon-indent-left:before {
  content: "\e057";
}
.glyphicon-indent-right:before {
  content: "\e058";
}
.glyphicon-facetime-video:before {
  content: "\e059";
}
.glyphicon-picture:before {
  content: "\e060";
}
.glyphicon-map-marker:before {
  content: "\e062";
}
.glyphicon-adjust:before {
  content: "\e063";
}
.glyphicon-tint:before {
  content: "\e064";
}
.glyphicon-edit:before {
  content: "\e065";
}
.glyphicon-share:before {
  content: "\e066";
}
.glyphicon-check:before {
  content: "\e067";
}
.glyphicon-move:before {
  content: "\e068";
}
.glyphicon-step-backward:before {
  content: "\e069";
}
.glyphicon-fast-backward:before {
  content: "\e070";
}
.glyphicon-backward:before {
  content: "\e071";
}
.glyphicon-play:before {
  content: "\e072";
}
.glyphicon-pause:before {
  content: "\e073";
}
.glyphicon-stop:before {
  content: "\e074";
}
.glyphicon-forward:before {
  content: "\e075";
}
.glyphicon-fast-forward:before {
  content: "\e076";
}
.glyphicon-step-forward:before {
  content: "\e077";
}
.glyphicon-eject:before {
  content: "\e078";
}
.glyphicon-chevron-left:before {
  content: "\e079";
}
.glyphicon-chevron-right:before {
  content: "\e080";
}
.glyphicon-plus-sign:before {
  content: "\e081";
}
.glyphicon-minus-sign:before {
  content: "\e082";
}
.glyphicon-remove-sign:before {
  content: "\e083";
}
.glyphicon-ok-sign:before {
  content: "\e084";
}
.glyphicon-question-sign:before {
  content: "\e085";
}
.glyphicon-info-sign:before {
  content: "\e086";
}
.glyphicon-screenshot:before {
  content: "\e087";
}
.glyphicon-remove-circle:before {
  content: "\e088";
}
.glyphicon-ok-circle:before {
  content: "\e089";
}
.glyphicon-ban-circle:before {
  content: "\e090";
}
.glyphicon-arrow-left:before {
  content: "\e091";
}
.glyphicon-arrow-right:before {
  content: "\e092";
}
.glyphicon-arrow-up:before {
  content: "\e093";
}
.glyphicon-arrow-down:before {
  content: "\e094";
}
.glyphicon-share-alt:before {
  content: "\e095";
}
.glyphicon-resize-full:before {
  content: "\e096";
}
.glyphicon-resize-small:before {
  content: "\e097";
}
.glyphicon-exclamation-sign:before {
  content: "\e101";
}
.glyphicon-gift:before {
  content: "\e102";
}
.glyphicon-leaf:before {
  content: "\e103";
}
.glyphicon-fire:before {
  content: "\e104";
}
.glyphicon-eye-open:before {
  content: "\e105";
}
.glyphicon-eye-close:before {
  content: "\e106";
}
.glyphicon-warning-sign:before {
  content: "\e107";
}
.glyphicon-plane:before {
  content: "\e108";
}
.glyphicon-calendar:before {
  content: "\e109";
}
.glyphicon-random:before {
  content: "\e110";
}
.glyphicon-comment:before {
  content: "\e111";
}
.glyphicon-magnet:before {
  content: "\e112";
}
.glyphicon-chevron-up:before {
  content: "\e113";
}
.glyphicon-chevron-down:before {
  content: "\e114";
}
.glyphicon-retweet:before {
  content: "\e115";
}
.glyphicon-shopping-cart:before {
  content: "\e116";
}
.glyphicon-folder-close:before {
  content: "\e117";
}
.glyphicon-folder-open:before {
  content: "\e118";
}
.glyphicon-resize-vertical:before {
  content: "\e119";
}
.glyphicon-resize-horizontal:before {
  content: "\e120";
}
.glyphicon-hdd:before {
  content: "\e121";
}
.glyphicon-bullhorn:before {
  content: "\e122";
}
.glyphicon-bell:before {
  content: "\e123";
}
.glyphicon-certificate:before {
  content: "\e124";
}
.glyphicon-thumbs-up:before {
  content: "\e125";
}
.glyphicon-thumbs-down:before {
  content: "\e126";
}
.glyphicon-hand-right:before {
  content: "\e127";
}
.glyphicon-hand-left:before {
  content: "\e128";
}
.glyphicon-hand-up:before {
  content: "\e129";
}
.glyphicon-hand-down:before {
  content: "\e130";
}
.glyphicon-circle-arrow-right:before {
  content: "\e131";
}
.glyphicon-circle-arrow-left:before {
  content: "\e132";
}
.glyphicon-circle-arrow-up:before {
  content: "\e133";
}
.glyphicon-circle-arrow-down:before {
  content: "\e134";
}
.glyphicon-globe:before {
  content: "\e135";
}
.glyphicon-wrench:before {
  content: "\e136";
}
.glyphicon-tasks:before {
  content: "\e137";
}
.glyphicon-filter:before {
  content: "\e138";
}
.glyphicon-briefcase:before {
  content: "\e139";
}
.glyphicon-fullscreen:before {
  content: "\e140";
}
.glyphicon-dashboard:before {
  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
  content: "\e143";
}
.glyphicon-link:before {
  content: "\e144";
}
.glyphicon-phone:before {
  content: "\e145";
}
.glyphicon-pushpin:before {
  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
  content: "\e149";
}
.glyphicon-sort:before {
  content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
  content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
  content: "\e154";
}
.glyphicon-sort-by-attributes:before {
  content: "\e155";
}
.glyphicon-sort-by-attributes-alt:before {
  content: "\e156";
}
.glyphicon-unchecked:before {
  content: "\e157";
}
.glyphicon-expand:before {
  content: "\e158";
}
.glyphicon-collapse-down:before {
  content: "\e159";
}
.glyphicon-collapse-up:before {
  content: "\e160";
}
.glyphicon-log-in:before {
  content: "\e161";
}
.glyphicon-flash:before {
  content: "\e162";
}
.glyphicon-log-out:before {
  content: "\e163";
}
.glyphicon-new-window:before {
  content: "\e164";
}
.glyphicon-record:before {
  content: "\e165";
}
.glyphicon-save:before {
  content: "\e166";
}
.glyphicon-open:before {
  content: "\e167";
}
.glyphicon-saved:before {
  content: "\e168";
}
.glyphicon-import:before {
  content: "\e169";
}
.glyphicon-export:before {
  content: "\e170";
}
.glyphicon-send:before {
  content: "\e171";
}
.glyphicon-floppy-disk:before {
  content: "\e172";
}
.glyphicon-floppy-saved:before {
  content: "\e173";
}
.glyphicon-floppy-remove:before {
  content: "\e174";
}
.glyphicon-floppy-save:before {
  content: "\e175";
}
.glyphicon-floppy-open:before {
  content: "\e176";
}
.glyphicon-credit-card:before {
  content: "\e177";
}
.glyphicon-transfer:before {
  content: "\e178";
}
.glyphicon-cutlery:before {
  content: "\e179";
}
.glyphicon-header:before {
  content: "\e180";
}
.glyphicon-compressed:before {
  content: "\e181";
}
.glyphicon-earphone:before {
  content: "\e182";
}
.glyphicon-phone-alt:before {
  content: "\e183";
}
.glyphicon-tower:before {
  content: "\e184";
}
.glyphicon-stats:before {
  content: "\e185";
}
.glyphicon-sd-video:before {
  content: "\e186";
}
.glyphicon-hd-video:before {
  content: "\e187";
}
.glyphicon-subtitles:before {
  content: "\e188";
}
.glyphicon-sound-stereo:before {
  content: "\e189";
}
.glyphicon-sound-dolby:before {
  content: "\e190";
}
.glyphicon-sound-5-1:before {
  content: "\e191";
}
.glyphicon-sound-6-1:before {
  content: "\e192";
}
.glyphicon-sound-7-1:before {
  content: "\e193";
}
.glyphicon-copyright-mark:before {
  content: "\e194";
}
.glyphicon-registration-mark:before {
  content: "\e195";
}
.glyphicon-cloud-download:before {
  content: "\e197";
}
.glyphicon-cloud-upload:before {
  content: "\e198";
}
.glyphicon-tree-conifer:before {
  content: "\e199";
}
.glyphicon-tree-deciduous:before {
  content: "\e200";
}
.glyphicon-cd:before {
  content: "\e201";
}
.glyphicon-save-file:before {
  content: "\e202";
}
.glyphicon-open-file:before {
  content: "\e203";
}
.glyphicon-level-up:before {
  content: "\e204";
}
.glyphicon-copy:before {
  content: "\e205";
}
.glyphicon-paste:before {
  content: "\e206";
}
.glyphicon-alert:before {
  content: "\e209";
}
.glyphicon-equalizer:before {
  content: "\e210";
}
.glyphicon-king:before {
  content: "\e211";
}
.glyphicon-queen:before {
  content: "\e212";
}
.glyphicon-pawn:before {
  content: "\e213";
}
.glyphicon-bishop:before {
  content: "\e214";
}
.glyphicon-knight:before {
  content: "\e215";
}
.glyphicon-baby-formula:before {
  content: "\e216";
}
.glyphicon-tent:before {
  content: "\26fa";
}
.glyphicon-blackboard:before {
  content: "\e218";
}
.glyphicon-bed:before {
  content: "\e219";
}
.glyphicon-apple:before {
  content: "\f8ff";
}
.glyphicon-erase:before {
  content: "\e221";
}
.glyphicon-hourglass:before {
  content: "\231b";
}
.glyphicon-lamp:before {
  content: "\e223";
}
.glyphicon-duplicate:before {
  content: "\e224";
}
.glyphicon-piggy-bank:before {
  content: "\e225";
}
.glyphicon-scissors:before {
  content: "\e226";
}
.glyphicon-bitcoin:before {
  content: "\e227";
}
.glyphicon-btc:before {
  content: "\e227";
}
.glyphicon-xbt:before {
  content: "\e227";
}
.glyphicon-yen:before {
  content: "\00a5";
}
.glyphicon-jpy:before {
  content: "\00a5";
}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
  content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
  content: "\e232";
}
.glyphicon-education:before {
  content: "\e233";
}
.glyphicon-option-horizontal:before {
  content: "\e234";
}
.glyphicon-option-vertical:before {
  content: "\e235";
}
.glyphicon-menu-hamburger:before {
  content: "\e236";
}
.glyphicon-modal-window:before {
  content: "\e237";
}
.glyphicon-oil:before {
  content: "\e238";
}
.glyphicon-grain:before {
  content: "\e239";
}
.glyphicon-sunglasses:before {
  content: "\e240";
}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
  content: "\e243";
}
.glyphicon-object-align-top:before {
  content: "\e244";
}
.glyphicon-object-align-bottom:before {
  content: "\e245";
}
.glyphicon-object-align-horizontal:before {
  content: "\e246";
}
.glyphicon-object-align-left:before {
  content: "\e247";
}
.glyphicon-object-align-vertical:before {
  content: "\e248";
}
.glyphicon-object-align-right:before {
  content: "\e249";
}
.glyphicon-triangle-right:before {
  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
  height: 100%;
  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
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<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
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.highlight .mi { color: #666666 } /* Literal.Number.Integer */
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.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
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.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
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.highlight .vi { color: #19177C } /* Name.Variable.Instance */
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.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
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<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
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.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

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<h1 id="Artificial-Intelligence-Nanodegree">Artificial Intelligence Nanodegree<a class="anchor-link" href="#Artificial-Intelligence-Nanodegree">&#182;</a></h1><h2 id="Machine-Translation-Project">Machine Translation Project<a class="anchor-link" href="#Machine-Translation-Project">&#182;</a></h2><p>In this notebook, sections that end with <strong>'(IMPLEMENTATION)'</strong> in the header indicate that the following blocks of code will require additional functionality which you must provide. Please be sure to read the instructions carefully!</p>
<h2 id="Introduction">Introduction<a class="anchor-link" href="#Introduction">&#182;</a></h2><p>In this notebook, you will build a deep neural network that functions as part of an end-to-end machine translation pipeline. Your completed pipeline will accept English text as input and return the French translation.</p>
<ul>
<li><strong>Preprocess</strong> - You'll convert text to sequence of integers.</li>
<li><strong>Models</strong> Create models which accepts a sequence of integers as input and returns a probability distribution over possible translations. After learning about the basic types of neural networks that are often used for machine translation, you will engage in your own investigations, to design your own model!</li>
<li><strong>Prediction</strong> Run the model on English text.</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%</span><span class="k">load_ext</span> autoreload
<span class="o">%</span><span class="k">aimport</span> helper, tests
<span class="o">%</span><span class="k">autoreload</span> 1
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">collections</span>

<span class="kn">import</span> <span class="nn">helper</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">matplotlib</span> <span class="k">import</span> <span class="n">pyplot</span>
<span class="kn">from</span> <span class="nn">pandas</span> <span class="k">import</span> <span class="n">DataFrame</span>
<span class="kn">import</span> <span class="nn">project_tests</span> <span class="k">as</span> <span class="nn">tests</span>

<span class="kn">from</span> <span class="nn">keras.preprocessing.text</span> <span class="k">import</span> <span class="n">Tokenizer</span>
<span class="kn">from</span> <span class="nn">keras.preprocessing.sequence</span> <span class="k">import</span> <span class="n">pad_sequences</span>
<span class="kn">from</span> <span class="nn">keras.models</span> <span class="k">import</span> <span class="n">Model</span><span class="p">,</span> <span class="n">Sequential</span>
<span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">GRU</span><span class="p">,</span> <span class="n">Input</span><span class="p">,</span> <span class="n">Dense</span><span class="p">,</span> <span class="n">TimeDistributed</span><span class="p">,</span> <span class="n">Activation</span><span class="p">,</span> <span class="n">RepeatVector</span><span class="p">,</span> <span class="n">Bidirectional</span><span class="p">,</span> <span class="n">LSTM</span><span class="p">,</span> <span class="n">Dropout</span>
<span class="kn">from</span> <span class="nn">keras.layers.embeddings</span> <span class="k">import</span> <span class="n">Embedding</span>
<span class="kn">from</span> <span class="nn">keras.optimizers</span> <span class="k">import</span> <span class="n">Adam</span><span class="p">,</span> <span class="n">rmsprop</span>
<span class="kn">from</span> <span class="nn">keras.losses</span> <span class="k">import</span> <span class="n">sparse_categorical_crossentropy</span><span class="p">,</span> <span class="n">categorical_crossentropy</span>
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<pre>Using TensorFlow backend.
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<h3 id="Verify-access-to-the-GPU">Verify access to the GPU<a class="anchor-link" href="#Verify-access-to-the-GPU">&#182;</a></h3><p>The following test applies only if you expect to be using a GPU, e.g., while running in a Udacity Workspace or using an AWS instance with GPU support. Run the next cell, and verify that the device_type is "GPU".</p>
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<li>If the device is not GPU &amp; you are running from a Udacity Workspace, then save your workspace with the icon at the top, then click "enable" at the bottom of the workspace.</li>
<li>If the device is not GPU &amp; you are running from an AWS instance, then refer to the cloud computing instructions in the classroom to verify your setup steps.</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">tensorflow.python.client</span> <span class="k">import</span> <span class="n">device_lib</span>
<span class="nb">print</span><span class="p">(</span><span class="n">device_lib</span><span class="o">.</span><span class="n">list_local_devices</span><span class="p">())</span>
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<pre>[name: &#34;/cpu:0&#34;
device_type: &#34;CPU&#34;
memory_limit: 268435456
locality {
}
incarnation: 15495246828385944096
, name: &#34;/gpu:0&#34;
device_type: &#34;GPU&#34;
memory_limit: 357433344
locality {
  bus_id: 1
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incarnation: 11437601037674840354
physical_device_desc: &#34;device: 0, name: Tesla K80, pci bus id: 0000:00:04.0&#34;
]
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<h2 id="Dataset">Dataset<a class="anchor-link" href="#Dataset">&#182;</a></h2><p>We begin by investigating the dataset that will be used to train and evaluate your pipeline.  The most common datasets used for machine translation are from <a href="http://www.statmt.org/">WMT</a>.  However, that will take a long time to train a neural network on.  We'll be using a dataset we created for this project that contains a small vocabulary.  You'll be able to train your model in a reasonable time with this dataset.</p>
<h3 id="Load-Data">Load Data<a class="anchor-link" href="#Load-Data">&#182;</a></h3><p>The data is located in <code>data/small_vocab_en</code> and <code>data/small_vocab_fr</code>. The <code>small_vocab_en</code> file contains English sentences with their French translations in the <code>small_vocab_fr</code> file. Load the English and French data from these files from running the cell below.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Load English data</span>
<span class="n">english_sentences</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_data</span><span class="p">(</span><span class="s1">&#39;data/small_vocab_en&#39;</span><span class="p">)</span>
<span class="c1"># Load French data</span>
<span class="n">french_sentences</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_data</span><span class="p">(</span><span class="s1">&#39;data/small_vocab_fr&#39;</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Dataset Loaded&#39;</span><span class="p">)</span>
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<pre>Dataset Loaded
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<h3 id="Files">Files<a class="anchor-link" href="#Files">&#182;</a></h3><p>Each line in <code>small_vocab_en</code> contains an English sentence with the respective translation in each line of <code>small_vocab_fr</code>.  View the first two lines from each file.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">for</span> <span class="n">sample_i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">2</span><span class="p">):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;small_vocab_en Line </span><span class="si">{}</span><span class="s1">:  </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">sample_i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">english_sentences</span><span class="p">[</span><span class="n">sample_i</span><span class="p">]))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;small_vocab_fr Line </span><span class="si">{}</span><span class="s1">:  </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">sample_i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">french_sentences</span><span class="p">[</span><span class="n">sample_i</span><span class="p">]))</span>
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<pre>small_vocab_en Line 1:  new jersey is sometimes quiet during autumn , and it is snowy in april .
small_vocab_fr Line 1:  new jersey est parfois calme pendant l&#39; automne , et il est neigeux en avril .
small_vocab_en Line 2:  the united states is usually chilly during july , and it is usually freezing in november .
small_vocab_fr Line 2:  les états-unis est généralement froid en juillet , et il gèle habituellement en novembre .
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s1">&#39;there are </span><span class="si">{}</span><span class="s1"> of sentences in English&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">english_sentences</span><span class="p">)))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;there are </span><span class="si">{}</span><span class="s1"> of sentences in French&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">french_sentences</span><span class="p">)))</span>
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<pre>there are 137861 of sentences in English
there are 137861 of sentences in French
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<p>From looking at the sentences, you can see they have been preprocessed already.  The puncuations have been delimited using spaces. All the text have been converted to lowercase.  This should save you some time, but the text requires more preprocessing.</p>
<h3 id="Vocabulary">Vocabulary<a class="anchor-link" href="#Vocabulary">&#182;</a></h3><p>The complexity of the problem is determined by the complexity of the vocabulary.  A more complex vocabulary is a more complex problem.  Let's look at the complexity of the dataset we'll be working with.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">english_words_counter</span> <span class="o">=</span> <span class="n">collections</span><span class="o">.</span><span class="n">Counter</span><span class="p">([</span><span class="n">word</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">english_sentences</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">sentence</span><span class="o">.</span><span class="n">split</span><span class="p">()])</span>
<span class="n">french_words_counter</span> <span class="o">=</span> <span class="n">collections</span><span class="o">.</span><span class="n">Counter</span><span class="p">([</span><span class="n">word</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">french_sentences</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">sentence</span><span class="o">.</span><span class="n">split</span><span class="p">()])</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">{}</span><span class="s1"> English words.&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">([</span><span class="n">word</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">english_sentences</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">sentence</span><span class="o">.</span><span class="n">split</span><span class="p">()])))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">{}</span><span class="s1"> unique English words.&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">english_words_counter</span><span class="p">)))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;10 Most common words in the English dataset:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;&quot;&#39;</span> <span class="o">+</span> <span class="s1">&#39;&quot; &quot;&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="o">*</span><span class="n">english_words_counter</span><span class="o">.</span><span class="n">most_common</span><span class="p">(</span><span class="mi">10</span><span class="p">)))[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="s1">&#39;&quot;&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">{}</span><span class="s1"> French words.&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">([</span><span class="n">word</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">french_sentences</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">sentence</span><span class="o">.</span><span class="n">split</span><span class="p">()])))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">{}</span><span class="s1"> unique French words.&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">french_words_counter</span><span class="p">)))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;10 Most common words in the French dataset:&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;&quot;&#39;</span> <span class="o">+</span> <span class="s1">&#39;&quot; &quot;&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="o">*</span><span class="n">french_words_counter</span><span class="o">.</span><span class="n">most_common</span><span class="p">(</span><span class="mi">10</span><span class="p">)))[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="s1">&#39;&quot;&#39;</span><span class="p">)</span>
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<pre>1823250 English words.
227 unique English words.
10 Most common words in the English dataset:
&#34;is&#34; &#34;,&#34; &#34;.&#34; &#34;in&#34; &#34;it&#34; &#34;during&#34; &#34;the&#34; &#34;but&#34; &#34;and&#34; &#34;sometimes&#34;

1961295 French words.
355 unique French words.
10 Most common words in the French dataset:
&#34;est&#34; &#34;.&#34; &#34;,&#34; &#34;en&#34; &#34;il&#34; &#34;les&#34; &#34;mais&#34; &#34;et&#34; &#34;la&#34; &#34;parfois&#34;
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<p>For comparison, <em>Alice's Adventures in Wonderland</em> contains 2,766 unique words of a total of 15,500 words.</p>
<h2 id="Preprocess">Preprocess<a class="anchor-link" href="#Preprocess">&#182;</a></h2><p>For this project, you won't use text data as input to your model. Instead, you'll convert the text into sequences of integers using the following preprocess methods:</p>
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<li>Tokenize the words into ids</li>
<li>Add padding to make all the sequences the same length.</li>
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<p>Time to start preprocessing the data...</p>
<h3 id="Tokenize-(IMPLEMENTATION)">Tokenize (IMPLEMENTATION)<a class="anchor-link" href="#Tokenize-(IMPLEMENTATION)">&#182;</a></h3><p>For a neural network to predict on text data, it first has to be turned into data it can understand. Text data like "dog" is a sequence of ASCII character encodings.  Since a neural network is a series of multiplication and addition operations, the input data needs to be number(s).</p>
<p>We can turn each character into a number or each word into a number.  These are called character and word ids, respectively.  Character ids are used for character level models that generate text predictions for each character.  A word level model uses word ids that generate text predictions for each word.  Word level models tend to learn better, since they are lower in complexity, so we'll use those.</p>
<p>Turn each sentence into a sequence of words ids using Keras's <a href="https://keras.io/preprocessing/text/#tokenizer"><code>Tokenizer</code></a> function. Use this function to tokenize <code>english_sentences</code> and <code>french_sentences</code> in the cell below.</p>
<p>Running the cell will run <code>tokenize</code> on sample data and show output for debugging.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">tokenize</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
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<span class="sd">    Tokenize x</span>
<span class="sd">    :param x: List of sentences/strings to be tokenized</span>
<span class="sd">    :return: Tuple of (tokenized x data, tokenizer used to tokenize x)</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">x_tk</span> <span class="o">=</span> <span class="n">Tokenizer</span><span class="p">()</span>
    <span class="n">x_tk</span><span class="o">.</span><span class="n">fit_on_texts</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">x_tk</span><span class="o">.</span><span class="n">texts_to_sequences</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="n">x_tk</span>

<span class="n">tests</span><span class="o">.</span><span class="n">test_tokenize</span><span class="p">(</span><span class="n">tokenize</span><span class="p">)</span>

<span class="c1"># Tokenize Example output</span>
<span class="n">text_sentences</span> <span class="o">=</span> <span class="p">[</span>
    <span class="s1">&#39;The quick brown fox jumps over the lazy dog .&#39;</span><span class="p">,</span>
    <span class="s1">&#39;By Jove , my quick study of lexicography won a prize .&#39;</span><span class="p">,</span>
    <span class="s1">&#39;This is a short sentence .&#39;</span><span class="p">]</span>
<span class="n">text_tokenized</span><span class="p">,</span> <span class="n">text_tokenizer</span> <span class="o">=</span> <span class="n">tokenize</span><span class="p">(</span><span class="n">text_sentences</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">text_tokenizer</span><span class="o">.</span><span class="n">word_index</span><span class="p">)</span>
<span class="nb">print</span><span class="p">()</span>
<span class="k">for</span> <span class="n">sample_i</span><span class="p">,</span> <span class="p">(</span><span class="n">sent</span><span class="p">,</span> <span class="n">token_sent</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">text_sentences</span><span class="p">,</span> <span class="n">text_tokenized</span><span class="p">)):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Sequence </span><span class="si">{}</span><span class="s1"> in x&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">sample_i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  Input:  </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">sent</span><span class="p">))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  Output: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">token_sent</span><span class="p">))</span>
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<pre>{&#39;the&#39;: 1, &#39;quick&#39;: 2, &#39;a&#39;: 3, &#39;brown&#39;: 4, &#39;fox&#39;: 5, &#39;jumps&#39;: 6, &#39;over&#39;: 7, &#39;lazy&#39;: 8, &#39;dog&#39;: 9, &#39;by&#39;: 10, &#39;jove&#39;: 11, &#39;my&#39;: 12, &#39;study&#39;: 13, &#39;of&#39;: 14, &#39;lexicography&#39;: 15, &#39;won&#39;: 16, &#39;prize&#39;: 17, &#39;this&#39;: 18, &#39;is&#39;: 19, &#39;short&#39;: 20, &#39;sentence&#39;: 21}

Sequence 1 in x
  Input:  The quick brown fox jumps over the lazy dog .
  Output: [1, 2, 4, 5, 6, 7, 1, 8, 9]
Sequence 2 in x
  Input:  By Jove , my quick study of lexicography won a prize .
  Output: [10, 11, 12, 2, 13, 14, 15, 16, 3, 17]
Sequence 3 in x
  Input:  This is a short sentence .
  Output: [18, 19, 3, 20, 21]
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<h3 id="Padding-(IMPLEMENTATION)">Padding (IMPLEMENTATION)<a class="anchor-link" href="#Padding-(IMPLEMENTATION)">&#182;</a></h3><p>When batching the sequence of word ids together, each sequence needs to be the same length.  Since sentences are dynamic in length, we can add padding to the end of the sequences to make them the same length.</p>
<p>Make sure all the English sequences have the same length and all the French sequences have the same length by adding padding to the <strong>end</strong> of each sequence using Keras's <a href="https://keras.io/preprocessing/sequence/#pad_sequences"><code>pad_sequences</code></a> function.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">pad</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">length</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Pad x</span>
<span class="sd">    :param x: List of sequences.</span>
<span class="sd">    :param length: Length to pad the sequence to.  If None, use length of longest sequence in x.</span>
<span class="sd">    :return: Padded numpy array of sequences</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">if</span> <span class="n">length</span> <span class="o">==</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">length</span> <span class="o">=</span> <span class="nb">max</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">text</span><span class="p">)</span> <span class="k">for</span> <span class="n">text</span> <span class="ow">in</span> <span class="n">x</span><span class="p">])</span>
        
    <span class="k">return</span> <span class="n">pad_sequences</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">maxlen</span><span class="o">=</span><span class="n">length</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="s2">&quot;post&quot;</span><span class="p">)</span>

<span class="n">tests</span><span class="o">.</span><span class="n">test_pad</span><span class="p">(</span><span class="n">pad</span><span class="p">)</span>

<span class="c1"># Pad Tokenized output</span>
<span class="n">test_pad</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">text_tokenized</span><span class="p">)</span>
<span class="k">for</span> <span class="n">sample_i</span><span class="p">,</span> <span class="p">(</span><span class="n">token_sent</span><span class="p">,</span> <span class="n">pad_sent</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">text_tokenized</span><span class="p">,</span> <span class="n">test_pad</span><span class="p">)):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Sequence </span><span class="si">{}</span><span class="s1"> in x&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">sample_i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  Input:  </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">token_sent</span><span class="p">)))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  Output: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">pad_sent</span><span class="p">))</span>
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<pre>Sequence 1 in x
  Input:  [1 2 4 5 6 7 1 8 9]
  Output: [1 2 4 5 6 7 1 8 9 0]
Sequence 2 in x
  Input:  [10 11 12  2 13 14 15 16  3 17]
  Output: [10 11 12  2 13 14 15 16  3 17]
Sequence 3 in x
  Input:  [18 19  3 20 21]
  Output: [18 19  3 20 21  0  0  0  0  0]
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<h3 id="Preprocess-Pipeline">Preprocess Pipeline<a class="anchor-link" href="#Preprocess-Pipeline">&#182;</a></h3><p>Your focus for this project is to build neural network architecture, so we won't ask you to create a preprocess pipeline.  Instead, we've provided you with the implementation of the <code>preprocess</code> function.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">preprocess</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Preprocess x and y</span>
<span class="sd">    :param x: Feature List of sentences</span>
<span class="sd">    :param y: Label List of sentences</span>
<span class="sd">    :return: Tuple of (Preprocessed x, Preprocessed y, x tokenizer, y tokenizer)</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">preprocess_x</span><span class="p">,</span> <span class="n">x_tk</span> <span class="o">=</span> <span class="n">tokenize</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
    <span class="n">preprocess_y</span><span class="p">,</span> <span class="n">y_tk</span> <span class="o">=</span> <span class="n">tokenize</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>

    <span class="n">preprocess_x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preprocess_x</span><span class="p">)</span>
    <span class="n">preprocess_y</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preprocess_y</span><span class="p">)</span>

    <span class="c1"># Keras&#39;s sparse_categorical_crossentropy function requires the labels to be in 3 dimensions</span>
    <span class="n">preprocess_y</span> <span class="o">=</span> <span class="n">preprocess_y</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">*</span><span class="n">preprocess_y</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>

    <span class="k">return</span> <span class="n">preprocess_x</span><span class="p">,</span> <span class="n">preprocess_y</span><span class="p">,</span> <span class="n">x_tk</span><span class="p">,</span> <span class="n">y_tk</span>

<span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">english_tokenizer</span><span class="p">,</span> <span class="n">french_tokenizer</span> <span class="o">=</span>\
    <span class="n">preprocess</span><span class="p">(</span><span class="n">english_sentences</span><span class="p">,</span> <span class="n">french_sentences</span><span class="p">)</span>
    
<span class="n">max_english_sequence_length</span> <span class="o">=</span> <span class="n">preproc_english_sentences</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="n">max_french_sequence_length</span> <span class="o">=</span> <span class="n">preproc_french_sentences</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="n">english_vocab_size</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">english_tokenizer</span><span class="o">.</span><span class="n">word_index</span><span class="p">)</span>
<span class="n">french_vocab_size</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">french_tokenizer</span><span class="o">.</span><span class="n">word_index</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Data Preprocessed&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Max English sentence length:&quot;</span><span class="p">,</span> <span class="n">max_english_sequence_length</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Max French sentence length:&quot;</span><span class="p">,</span> <span class="n">max_french_sequence_length</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;English vocabulary size:&quot;</span><span class="p">,</span> <span class="n">english_vocab_size</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;French vocabulary size:&quot;</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">)</span>
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<pre>Data Preprocessed
Max English sentence length: 15
Max French sentence length: 21
English vocabulary size: 199
French vocabulary size: 344
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<h4 id="Example-of-output-and-input-format">Example of output and input format<a class="anchor-link" href="#Example-of-output-and-input-format">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">preproc_french_sentences</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
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<pre>array([[ 4],
       [32],
       [31],
       [ 1],
       [12],
       [19],
       [ 2],
       [49],
       [ 6],
       [ 3],
       [95],
       [69],
       [ 2],
       [51],
       [ 0],
       [ 0],
       [ 0],
       [ 0],
       [ 0],
       [ 0],
       [ 0]], dtype=int32)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">preproc_english_sentences</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
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<pre>array([ 5, 20, 21,  1,  9, 62,  4, 43,  7,  3,  1,  9, 51,  2, 45], dtype=int32)</pre>
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<h2 id="Models">Models<a class="anchor-link" href="#Models">&#182;</a></h2><p>In this section, you will experiment with various neural network architectures.
You will begin by training four relatively simple architectures.</p>
<ul>
<li>Model 1 is a simple RNN</li>
<li>Model 2 is a RNN with Embedding</li>
<li>Model 3 is a Bidirectional RNN</li>
<li>Model 4 is an optional Encoder-Decoder RNN</li>
</ul>
<p>After experimenting with the four simple architectures, you will construct a deeper architecture that is designed to outperform all four models.</p>
<h3 id="Ids-Back-to-Text">Ids Back to Text<a class="anchor-link" href="#Ids-Back-to-Text">&#182;</a></h3><p>The neural network will be translating the input to words ids, which isn't the final form we want.  We want the French translation.  The function <code>logits_to_text</code> will bridge the gab between the logits from the neural network to the French translation.  You'll be using this function to better understand the output of the neural network.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">logits_to_text</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="n">tokenizer</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Turn logits from a neural network into text using the tokenizer</span>
<span class="sd">    :param logits: Logits from a neural network</span>
<span class="sd">    :param tokenizer: Keras Tokenizer fit on the labels</span>
<span class="sd">    :return: String that represents the text of the logits</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">index_to_words</span> <span class="o">=</span> <span class="p">{</span><span class="nb">id</span><span class="p">:</span> <span class="n">word</span> <span class="k">for</span> <span class="n">word</span><span class="p">,</span> <span class="nb">id</span> <span class="ow">in</span> <span class="n">tokenizer</span><span class="o">.</span><span class="n">word_index</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
    <span class="n">index_to_words</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;&lt;PAD&gt;&#39;</span>

    <span class="k">return</span> <span class="s1">&#39; &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">index_to_words</span><span class="p">[</span><span class="n">prediction</span><span class="p">]</span> <span class="k">for</span> <span class="n">prediction</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="mi">1</span><span class="p">)])</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;`logits_to_text` function loaded.&#39;</span><span class="p">)</span>
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<pre>`logits_to_text` function loaded.
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">source_to_text</span><span class="p">(</span><span class="n">text</span><span class="p">,</span> <span class="n">tokenizer</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Reverse translate the source text from integer back into English using the tokenizer.</span>
<span class="sd">    :param sentences: Text from the source</span>
<span class="sd">    :param tokenizer: Keras Tokenizer fit on the labels</span>
<span class="sd">    :return: String that represents the text of the preprocess text</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">index_to_words</span> <span class="o">=</span> <span class="p">{</span><span class="nb">id</span><span class="p">:</span> <span class="n">word</span> <span class="k">for</span> <span class="n">word</span><span class="p">,</span> <span class="nb">id</span> <span class="ow">in</span> <span class="n">tokenizer</span><span class="o">.</span><span class="n">word_index</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
    <span class="n">index_to_words</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;&lt;PAD&gt;&#39;</span>
    
    <span class="k">return</span> <span class="s1">&#39; &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">index_to_words</span><span class="p">[</span><span class="n">reverse_translate</span><span class="p">]</span> <span class="k">for</span> <span class="n">reverse_translate</span> <span class="ow">in</span> <span class="n">text</span><span class="p">])</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;`source_to_text` function loaded.&#39;</span><span class="p">)</span>
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<pre>`source_to_text` function loaded.
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<h4 id="Create-a-DataFrame-for-storing-models'-loss-information">Create a DataFrame for storing models' loss information<a class="anchor-link" href="#Create-a-DataFrame-for-storing-models'-loss-information">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">()</span>
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<h3 id="Model-1:-RNN-(IMPLEMENTATION)">Model 1: RNN (IMPLEMENTATION)<a class="anchor-link" href="#Model-1:-RNN-(IMPLEMENTATION)">&#182;</a></h3><p><img src="images/rnn.png" alt="RNN">
A basic RNN model is a good baseline for sequence data.  In this model, you'll build a RNN that translates English to French.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">simple_model</span><span class="p">(</span><span class="n">input_shape</span><span class="p">,</span> <span class="n">output_sequence_length</span><span class="p">,</span> <span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Build and train a basic RNN on x and y</span>
<span class="sd">    :param input_shape: Tuple of input shape</span>
<span class="sd">    :param output_sequence_length: Length of output sequence</span>
<span class="sd">    :param english_vocab_size: Number of unique English words in the dataset</span>
<span class="sd">    :param french_vocab_size: Number of unique French words in the dataset</span>
<span class="sd">    :return: Keras model built, but not trained</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># simple params</span>
    <span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">1e-3</span>
    
    <span class="c1"># loss: 1.0069 - acc: 0.6808 - val_loss: nan - val_acc: 0.6841</span>
    <span class="n">X</span> <span class="o">=</span> <span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Inputs&quot;</span><span class="p">)</span>  
    <span class="n">RNN</span> <span class="o">=</span> <span class="n">GRU</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;RNN&quot;</span><span class="p">)(</span><span class="n">X</span><span class="p">)</span>
    <span class="n">y</span> <span class="o">=</span> <span class="n">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="n">french_vocab_size</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Outputs&quot;</span><span class="p">)(</span><span class="n">RNN</span><span class="p">)</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">Model</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Activation</span><span class="p">(</span><span class="s2">&quot;softmax&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;softmax_activation&quot;</span><span class="p">)(</span><span class="n">y</span><span class="p">))</span>
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">sparse_categorical_crossentropy</span><span class="p">,</span>
                  <span class="n">optimizer</span><span class="o">=</span><span class="n">Adam</span><span class="p">(</span><span class="n">learning_rate</span><span class="p">),</span>
                  <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>
    <span class="k">return</span> <span class="n">model</span>

<span class="n">tests</span><span class="o">.</span><span class="n">test_simple_model</span><span class="p">(</span><span class="n">simple_model</span><span class="p">)</span>

<span class="c1"># Reshaping the input to work with a basic RNN</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">max_french_sequence_length</span><span class="p">)</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">tmp_x</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">2</span><span class="p">],</span> <span class="mi">1</span><span class="p">))</span>

<span class="c1"># # Train the neural network</span>
<span class="n">simple_rnn_model</span> <span class="o">=</span> <span class="n">simple_model</span><span class="p">(</span>
    <span class="n">tmp_x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span>
    <span class="n">max_french_sequence_length</span><span class="p">,</span>
    <span class="n">english_vocab_size</span><span class="p">,</span>
    <span class="n">french_vocab_size</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">simple_rnn_model</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>
<span class="nb">print</span><span class="p">()</span>
<span class="n">hist1</span> <span class="o">=</span> <span class="n">simple_rnn_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">validation_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>

<span class="c1"># # Print prediction(s)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">logits_to_text</span><span class="p">(</span><span class="n">simple_rnn_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">[:</span><span class="mi">1</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> <span class="n">french_tokenizer</span><span class="p">))</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
Inputs (InputLayer)          (None, 21, 1)             0         
_________________________________________________________________
RNN (GRU)                    (None, 21, 512)           789504    
_________________________________________________________________
Outputs (TimeDistributed)    (None, 21, 344)           176472    
_________________________________________________________________
softmax_activation (Activati (None, 21, 344)           0         
=================================================================
Total params: 965,976
Trainable params: 965,976
Non-trainable params: 0
_________________________________________________________________
None

Train on 110288 samples, validate on 27573 samples
Epoch 1/10
110288/110288 [==============================] - 19s 176us/step - loss: 2.2333 - acc: 0.5160 - val_loss: nan - val_acc: 0.5914
Epoch 2/10
110288/110288 [==============================] - 19s 169us/step - loss: 1.4322 - acc: 0.6112 - val_loss: nan - val_acc: 0.6269
Epoch 3/10
110288/110288 [==============================] - 19s 169us/step - loss: 1.2587 - acc: 0.6366 - val_loss: nan - val_acc: 0.6332
Epoch 4/10
110288/110288 [==============================] - 19s 169us/step - loss: 1.1518 - acc: 0.6559 - val_loss: nan - val_acc: 0.6637
Epoch 5/10
110288/110288 [==============================] - 19s 169us/step - loss: 1.0758 - acc: 0.6699 - val_loss: nan - val_acc: 0.6754
Epoch 6/10
110288/110288 [==============================] - 19s 169us/step - loss: 1.0181 - acc: 0.6774 - val_loss: nan - val_acc: 0.6791
Epoch 7/10
110288/110288 [==============================] - 19s 169us/step - loss: 0.9721 - acc: 0.6848 - val_loss: nan - val_acc: 0.6847
Epoch 8/10
110288/110288 [==============================] - 19s 169us/step - loss: 0.9316 - acc: 0.6928 - val_loss: nan - val_acc: 0.6996
Epoch 9/10
110288/110288 [==============================] - 19s 169us/step - loss: 0.8941 - acc: 0.7024 - val_loss: nan - val_acc: 0.7107
Epoch 10/10
110288/110288 [==============================] - 19s 169us/step - loss: 0.8585 - acc: 0.7140 - val_loss: nan - val_acc: 0.7261
new jersey est parfois chaud en l&#39; et il et il est en en &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span><span class="p">[</span><span class="s2">&quot;simpleRNN&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">hist1</span><span class="o">.</span><span class="n">history</span><span class="p">[</span><span class="s1">&#39;loss&#39;</span><span class="p">]</span>
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<h3 id="Model-2:-Embedding-(IMPLEMENTATION)">Model 2: Embedding (IMPLEMENTATION)<a class="anchor-link" href="#Model-2:-Embedding-(IMPLEMENTATION)">&#182;</a></h3><p><img src="images/embedding.png" alt="RNN">
You've turned the words into ids, but there's a better representation of a word.  This is called word embeddings.  An embedding is a vector representation of the word that is close to similar words in n-dimensional space, where the n represents the size of the embedding vectors.</p>
<p>In this model, you'll create a RNN model using embedding.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.utils</span> <span class="k">import</span> <span class="n">plot_model</span>

<span class="k">def</span> <span class="nf">embed_model</span><span class="p">(</span><span class="n">input_shape</span><span class="p">,</span> <span class="n">output_sequence_length</span><span class="p">,</span> <span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Build and train a RNN model using word embedding on x and y</span>
<span class="sd">    :param input_shape: Tuple of input shape</span>
<span class="sd">    :param output_sequence_length: Length of output sequence</span>
<span class="sd">    :param english_vocab_size: Number of unique English words in the dataset</span>
<span class="sd">    :param french_vocab_size: Number of unique French words in the dataset</span>
<span class="sd">    :return: Keras model built, but not trained</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">1e-3</span>
        
    <span class="n">X</span> <span class="o">=</span> <span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Inputs&quot;</span><span class="p">)</span>
    <span class="n">embedding</span> <span class="o">=</span> <span class="n">Embedding</span><span class="p">(</span><span class="n">english_vocab_size</span><span class="p">,</span> <span class="mi">256</span><span class="p">,</span> <span class="n">input_length</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Embeddings&quot;</span><span class="p">)(</span><span class="n">X</span><span class="p">)</span>
    <span class="n">RNN</span> <span class="o">=</span> <span class="n">GRU</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;RNN&quot;</span><span class="p">)(</span><span class="n">embedding</span><span class="p">)</span>
    <span class="n">y</span> <span class="o">=</span> <span class="n">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="n">french_vocab_size</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Outputs&quot;</span><span class="p">)(</span><span class="n">RNN</span><span class="p">)</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">Model</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Activation</span><span class="p">(</span><span class="s2">&quot;softmax&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Activation&quot;</span><span class="p">)(</span><span class="n">y</span><span class="p">))</span>
    
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">sparse_categorical_crossentropy</span><span class="p">,</span>
                  <span class="n">optimizer</span><span class="o">=</span><span class="n">Adam</span><span class="p">(</span><span class="n">learning_rate</span><span class="p">),</span>
                  <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>
    
    <span class="k">return</span> <span class="n">model</span>

<span class="n">tests</span><span class="o">.</span><span class="n">test_embed_model</span><span class="p">(</span><span class="n">embed_model</span><span class="p">)</span>

<span class="c1"># Inputs preparation using max french length</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">max_french_sequence_length</span><span class="p">)</span>

<span class="c1"># Train the neural network</span>
<span class="n">embed_rnn_model</span> <span class="o">=</span> <span class="n">embed_model</span><span class="p">(</span>
    <span class="n">tmp_x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span>
    <span class="n">max_french_sequence_length</span><span class="p">,</span>
    <span class="n">english_vocab_size</span><span class="p">,</span>
    <span class="n">french_vocab_size</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">embed_rnn_model</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>

<span class="n">hist2</span> <span class="o">=</span> <span class="n">embed_rnn_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">validation_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>

<span class="c1"># Print prediction(s)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">logits_to_text</span><span class="p">(</span><span class="n">embed_rnn_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">[:</span><span class="mi">1</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> <span class="n">french_tokenizer</span><span class="p">))</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
Inputs (InputLayer)          (None, 21)                0         
_________________________________________________________________
Embeddings (Embedding)       (None, 21, 256)           50944     
_________________________________________________________________
RNN (GRU)                    (None, 21, 512)           1181184   
_________________________________________________________________
Outputs (TimeDistributed)    (None, 21, 344)           176472    
_________________________________________________________________
Activation (Activation)      (None, 21, 344)           0         
=================================================================
Total params: 1,408,600
Trainable params: 1,408,600
Non-trainable params: 0
_________________________________________________________________
None
Train on 110288 samples, validate on 27573 samples
Epoch 1/10
110288/110288 [==============================] - 24s 214us/step - loss: 2.8042 - acc: 0.4815 - val_loss: nan - val_acc: 0.5898
Epoch 2/10
110288/110288 [==============================] - 23s 210us/step - loss: 1.2854 - acc: 0.6941 - val_loss: nan - val_acc: 0.7723
Epoch 3/10
110288/110288 [==============================] - 23s 210us/step - loss: 0.7110 - acc: 0.8092 - val_loss: nan - val_acc: 0.8378
Epoch 4/10
110288/110288 [==============================] - 23s 210us/step - loss: 0.4758 - acc: 0.8580 - val_loss: nan - val_acc: 0.8753
Epoch 5/10
110288/110288 [==============================] - 23s 210us/step - loss: 0.3659 - acc: 0.8858 - val_loss: nan - val_acc: 0.8939
Epoch 6/10
110288/110288 [==============================] - 23s 210us/step - loss: 0.3091 - acc: 0.9010 - val_loss: nan - val_acc: 0.9049
Epoch 7/10
110288/110288 [==============================] - 23s 210us/step - loss: 0.2729 - acc: 0.9110 - val_loss: nan - val_acc: 0.9132
Epoch 8/10
110288/110288 [==============================] - 23s 210us/step - loss: 0.2485 - acc: 0.9178 - val_loss: nan - val_acc: 0.9195
Epoch 9/10
110288/110288 [==============================] - 23s 210us/step - loss: 0.2299 - acc: 0.9231 - val_loss: nan - val_acc: 0.9225
Epoch 10/10
110288/110288 [==============================] - 23s 210us/step - loss: 0.2163 - acc: 0.9270 - val_loss: nan - val_acc: 0.9260
new jersey est parfois calme au l&#39; automne et il est neigeux en avril &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span><span class="p">[</span><span class="s2">&quot;embedRNN&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">hist2</span><span class="o">.</span><span class="n">history</span><span class="p">[</span><span class="s1">&#39;loss&#39;</span><span class="p">]</span>
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<h3 id="Model-3:-Bidirectional-RNNs-(IMPLEMENTATION)">Model 3: Bidirectional RNNs (IMPLEMENTATION)<a class="anchor-link" href="#Model-3:-Bidirectional-RNNs-(IMPLEMENTATION)">&#182;</a></h3><p><img src="images/bidirectional.png" alt="RNN">
One restriction of a RNN is that it can't see the future input, only the past.  This is where bidirectional recurrent neural networks come in.  They are able to see the future data.</p>

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<h4 id="Bidirectional-RNN-using-&quot;Sum&quot;-Merge-mode">Bidirectional RNN using "Sum" Merge mode<a class="anchor-link" href="#Bidirectional-RNN-using-&quot;Sum&quot;-Merge-mode">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">bd_sum_model</span><span class="p">(</span><span class="n">input_shape</span><span class="p">,</span> <span class="n">output_sequence_length</span><span class="p">,</span> <span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Build and train a bidirectional RNN model on x and y</span>
<span class="sd">    :param input_shape: Tuple of input shape</span>
<span class="sd">    :param output_sequence_length: Length of output sequence</span>
<span class="sd">    :param english_vocab_size: Number of unique English words in the dataset</span>
<span class="sd">    :param french_vocab_size: Number of unique French words in the dataset</span>
<span class="sd">    :return: Keras model built, but not trained</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">1e-3</span>
    
    <span class="n">X</span> <span class="o">=</span> <span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Inputs&quot;</span><span class="p">)</span>
    <span class="n">Bi_RNN</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">GRU</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;RNN&quot;</span><span class="p">),</span> <span class="n">merge_mode</span><span class="o">=</span><span class="s2">&quot;sum&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Bi-Dir_Sum&quot;</span><span class="p">)(</span><span class="n">X</span><span class="p">)</span>
    <span class="n">y</span> <span class="o">=</span> <span class="n">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="n">french_vocab_size</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;TimeDistributed_Outputs&quot;</span><span class="p">)(</span><span class="n">Bi_RNN</span><span class="p">)</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">Model</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Activation</span><span class="p">(</span><span class="s2">&quot;softmax&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Activation&quot;</span><span class="p">)(</span><span class="n">y</span><span class="p">))</span>
    
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">sparse_categorical_crossentropy</span><span class="p">,</span>
                  <span class="n">optimizer</span><span class="o">=</span><span class="n">Adam</span><span class="p">(</span><span class="n">learning_rate</span><span class="p">),</span>
                  <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>

    <span class="k">return</span> <span class="n">model</span>

<span class="n">tests</span><span class="o">.</span><span class="n">test_bd_model</span><span class="p">(</span><span class="n">bd_sum_model</span><span class="p">)</span>

<span class="c1"># Reshaping the input to work with a basic RNN</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">max_french_sequence_length</span><span class="p">)</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">tmp_x</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">2</span><span class="p">],</span> <span class="mi">1</span><span class="p">))</span>

<span class="c1"># Train the neural network</span>
<span class="n">bd_sum_rnn_model</span> <span class="o">=</span> <span class="n">bd_sum_model</span><span class="p">(</span>
    <span class="n">tmp_x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span>
    <span class="n">max_french_sequence_length</span><span class="p">,</span>
    <span class="n">english_vocab_size</span><span class="p">,</span>
    <span class="n">french_vocab_size</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">bd_sum_rnn_model</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>
<span class="nb">print</span><span class="p">()</span>

<span class="n">hist3</span> <span class="o">=</span> <span class="n">bd_sum_rnn_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">validation_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>

<span class="c1"># Print prediction(s)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">logits_to_text</span><span class="p">(</span><span class="n">bd_sum_rnn_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">[:</span><span class="mi">1</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> <span class="n">french_tokenizer</span><span class="p">))</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
Inputs (InputLayer)          (None, 21, 1)             0         
_________________________________________________________________
Bi-Dir_Sum (Bidirectional)   (None, 21, 512)           1579008   
_________________________________________________________________
TimeDistributed_Outputs (Tim (None, 21, 344)           176472    
_________________________________________________________________
Activation (Activation)      (None, 21, 344)           0         
=================================================================
Total params: 1,755,480
Trainable params: 1,755,480
Non-trainable params: 0
_________________________________________________________________
None

Train on 110288 samples, validate on 27573 samples
Epoch 1/10
110288/110288 [==============================] - 33s 302us/step - loss: 1.8873 - acc: 0.5714 - val_loss: nan - val_acc: 0.6263
Epoch 2/10
110288/110288 [==============================] - 32s 294us/step - loss: 1.2549 - acc: 0.6432 - val_loss: nan - val_acc: 0.6566
Epoch 3/10
110288/110288 [==============================] - 32s 294us/step - loss: 1.1132 - acc: 0.6715 - val_loss: nan - val_acc: 0.6769
Epoch 4/10
110288/110288 [==============================] - 32s 295us/step - loss: 1.0160 - acc: 0.6892 - val_loss: nan - val_acc: 0.6942
Epoch 5/10
110288/110288 [==============================] - 32s 294us/step - loss: 0.9431 - acc: 0.7017 - val_loss: nan - val_acc: 0.7010
Epoch 6/10
110288/110288 [==============================] - 32s 294us/step - loss: 0.8908 - acc: 0.7099 - val_loss: nan - val_acc: 0.7038
Epoch 7/10
110288/110288 [==============================] - 32s 294us/step - loss: 0.8477 - acc: 0.7182 - val_loss: nan - val_acc: 0.7223
Epoch 8/10
110288/110288 [==============================] - 32s 294us/step - loss: 0.8151 - acc: 0.7240 - val_loss: nan - val_acc: 0.7270
Epoch 9/10
110288/110288 [==============================] - 32s 294us/step - loss: 0.7791 - acc: 0.7333 - val_loss: nan - val_acc: 0.7389
Epoch 10/10
110288/110288 [==============================] - 32s 294us/step - loss: 0.7419 - acc: 0.7428 - val_loss: nan - val_acc: 0.7502
new jersey est parfois calme au mois de mai et il est en en &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span><span class="p">[</span><span class="s2">&quot;bd_sum&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">hist3</span><span class="o">.</span><span class="n">history</span><span class="p">[</span><span class="s1">&#39;loss&#39;</span><span class="p">]</span>
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<h4 id="Bidirectional-RNN-using-&quot;Concatenation&quot;-Merge-mode">Bidirectional RNN using "Concatenation" Merge mode<a class="anchor-link" href="#Bidirectional-RNN-using-&quot;Concatenation&quot;-Merge-mode">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">bd_concat_model</span><span class="p">(</span><span class="n">input_shape</span><span class="p">,</span> <span class="n">output_sequence_length</span><span class="p">,</span> <span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Build and train a bidirectional RNN model on x and y</span>
<span class="sd">    :param input_shape: Tuple of input shape</span>
<span class="sd">    :param output_sequence_length: Length of output sequence</span>
<span class="sd">    :param english_vocab_size: Number of unique English words in the dataset</span>
<span class="sd">    :param french_vocab_size: Number of unique French words in the dataset</span>
<span class="sd">    :return: Keras model built, but not trained</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">1e-3</span>
    
    <span class="n">X</span> <span class="o">=</span> <span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Inputs&quot;</span><span class="p">)</span>
    <span class="n">Bi_RNN</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">GRU</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">),</span> <span class="n">merge_mode</span><span class="o">=</span><span class="s2">&quot;concat&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Bi-Dir_Concat&quot;</span><span class="p">)(</span><span class="n">X</span><span class="p">)</span>
    <span class="n">y</span> <span class="o">=</span> <span class="n">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="n">french_vocab_size</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;TimeDistributed_Outputs&quot;</span><span class="p">)(</span><span class="n">Bi_RNN</span><span class="p">)</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">Model</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Activation</span><span class="p">(</span><span class="s2">&quot;softmax&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Activation&quot;</span><span class="p">)(</span><span class="n">y</span><span class="p">))</span>
    
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">sparse_categorical_crossentropy</span><span class="p">,</span>
                  <span class="n">optimizer</span><span class="o">=</span><span class="n">Adam</span><span class="p">(</span><span class="n">learning_rate</span><span class="p">),</span>
                  <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>

    <span class="k">return</span> <span class="n">model</span>

<span class="n">tests</span><span class="o">.</span><span class="n">test_bd_model</span><span class="p">(</span><span class="n">bd_concat_model</span><span class="p">)</span>

<span class="c1"># Reshaping the input to work with a basic RNN</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">max_french_sequence_length</span><span class="p">)</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">tmp_x</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">2</span><span class="p">],</span> <span class="mi">1</span><span class="p">))</span>

<span class="c1"># Train the neural network</span>
<span class="n">bd_concat_rnn_model</span> <span class="o">=</span> <span class="n">bd_concat_model</span><span class="p">(</span>
    <span class="n">tmp_x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span>
    <span class="n">max_french_sequence_length</span><span class="p">,</span>
    <span class="n">english_vocab_size</span><span class="p">,</span>
    <span class="n">french_vocab_size</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">bd_concat_rnn_model</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>
<span class="nb">print</span><span class="p">()</span>

<span class="n">hist4</span> <span class="o">=</span> <span class="n">bd_concat_rnn_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">validation_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>

<span class="c1"># Print prediction(s)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">logits_to_text</span><span class="p">(</span><span class="n">bd_concat_rnn_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">[:</span><span class="mi">1</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> <span class="n">french_tokenizer</span><span class="p">))</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
Inputs (InputLayer)          (None, 21, 1)             0         
_________________________________________________________________
Bi-Dir_Concat (Bidirectional (None, 21, 1024)          1579008   
_________________________________________________________________
TimeDistributed_Outputs (Tim (None, 21, 344)           352600    
_________________________________________________________________
Activation (Activation)      (None, 21, 344)           0         
=================================================================
Total params: 1,931,608
Trainable params: 1,931,608
Non-trainable params: 0
_________________________________________________________________
None

Train on 110288 samples, validate on 27573 samples
Epoch 1/10
110288/110288 [==============================] - 35s 316us/step - loss: 1.8661 - acc: 0.5713 - val_loss: nan - val_acc: 0.6277
Epoch 2/10
110288/110288 [==============================] - 34s 308us/step - loss: 1.2394 - acc: 0.6447 - val_loss: nan - val_acc: 0.6613
Epoch 3/10
110288/110288 [==============================] - 34s 308us/step - loss: 1.1002 - acc: 0.6717 - val_loss: nan - val_acc: 0.6851
Epoch 4/10
110288/110288 [==============================] - 34s 308us/step - loss: 1.0024 - acc: 0.6898 - val_loss: nan - val_acc: 0.6952
Epoch 5/10
110288/110288 [==============================] - 34s 308us/step - loss: 0.9343 - acc: 0.7016 - val_loss: nan - val_acc: 0.7116
Epoch 6/10
110288/110288 [==============================] - 34s 308us/step - loss: 0.8787 - acc: 0.7133 - val_loss: nan - val_acc: 0.7212
Epoch 7/10
110288/110288 [==============================] - 34s 308us/step - loss: 0.8299 - acc: 0.7231 - val_loss: nan - val_acc: 0.7315
Epoch 8/10
110288/110288 [==============================] - 34s 308us/step - loss: 0.7852 - acc: 0.7358 - val_loss: nan - val_acc: 0.7435
Epoch 9/10
110288/110288 [==============================] - 34s 308us/step - loss: 0.7369 - acc: 0.7529 - val_loss: nan - val_acc: 0.7526
Epoch 10/10
110288/110288 [==============================] - 34s 308us/step - loss: 0.6916 - acc: 0.7707 - val_loss: nan - val_acc: 0.7739
new jersey est parfois calme au mois de il et il en en &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span><span class="p">[</span><span class="s2">&quot;bd_concat&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">hist4</span><span class="o">.</span><span class="n">history</span><span class="p">[</span><span class="s1">&#39;loss&#39;</span><span class="p">]</span>
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<h3 id="Model-4:-Encoder-Decoder-(OPTIONAL)">Model 4: Encoder-Decoder (OPTIONAL)<a class="anchor-link" href="#Model-4:-Encoder-Decoder-(OPTIONAL)">&#182;</a></h3><p>Time to look at encoder-decoder models.  This model is made up of an encoder and decoder. The encoder creates a matrix representation of the sentence.  The decoder takes this matrix as input and predicts the translation as output.</p>
<p>Create an encoder-decoder model in the cell below.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">encdec_model</span><span class="p">(</span><span class="n">input_shape</span><span class="p">,</span> <span class="n">output_sequence_length</span><span class="p">,</span> <span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Build and train an encoder-decoder model on x and y</span>
<span class="sd">    :param input_shape: Tuple of input shape</span>
<span class="sd">    :param output_sequence_length: Length of output sequence</span>
<span class="sd">    :param english_vocab_size: Number of unique English words in the dataset</span>
<span class="sd">    :param french_vocab_size: Number of unique French words in the dataset</span>
<span class="sd">    :return: Keras model built, but not trained</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">learning_rate</span><span class="o">=</span><span class="mf">1e-3</span>
    
    <span class="c1"># Encoder</span>
    <span class="n">X</span> <span class="o">=</span> <span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Inputs&quot;</span><span class="p">)</span>
    <span class="n">embedding</span> <span class="o">=</span> <span class="n">Embedding</span><span class="p">(</span><span class="n">english_vocab_size</span><span class="p">,</span> <span class="mi">256</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Source_Embedding&quot;</span><span class="p">)(</span><span class="n">X</span><span class="p">)</span>
    <span class="n">encoder</span><span class="p">,</span> <span class="n">state_h</span><span class="p">,</span> <span class="n">state_c</span> <span class="o">=</span> <span class="n">LSTM</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="n">return_state</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Encoder&quot;</span><span class="p">)(</span><span class="n">embedding</span><span class="p">)</span>
    
    <span class="c1"># Decoder</span>
    <span class="n">decoder_inputs</span> <span class="o">=</span> <span class="n">RepeatVector</span><span class="p">(</span><span class="n">output_sequence_length</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Decoder_Inputs&quot;</span><span class="p">)(</span><span class="n">encoder</span><span class="p">)</span>    
    <span class="n">decoder</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">LSTM</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">return_state</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Decoder&quot;</span><span class="p">)(</span><span class="n">decoder_inputs</span><span class="p">,</span> <span class="n">initial_state</span><span class="o">=</span><span class="p">[</span><span class="n">state_h</span><span class="p">,</span> <span class="n">state_c</span><span class="p">])</span>
    <span class="n">decoder_y</span> <span class="o">=</span> <span class="n">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="n">french_vocab_size</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Outputs&quot;</span><span class="p">)(</span><span class="n">decoder</span><span class="p">)</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">Model</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Activation</span><span class="p">(</span><span class="s2">&quot;softmax&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Activation&quot;</span><span class="p">)(</span><span class="n">decoder_y</span><span class="p">))</span>
    
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">sparse_categorical_crossentropy</span><span class="p">,</span>
                  <span class="n">optimizer</span><span class="o">=</span><span class="n">Adam</span><span class="p">(</span><span class="n">learning_rate</span><span class="p">),</span>
                  <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>
    
    <span class="k">return</span> <span class="n">model</span>

<span class="c1"># tests.test_encdec_model(encdec_model)</span>

<span class="c1"># Reshaping the input to work with a basic RNN</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">max_english_sequence_length</span><span class="p">)</span>

<span class="c1"># Train the neural network</span>
<span class="n">encdec_rnn_model</span> <span class="o">=</span> <span class="n">encdec_model</span><span class="p">(</span>
    <span class="n">tmp_x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span>
    <span class="n">max_french_sequence_length</span><span class="p">,</span>
    <span class="n">english_vocab_size</span><span class="p">,</span>
    <span class="n">french_vocab_size</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">encdec_rnn_model</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>
<span class="nb">print</span><span class="p">()</span>

<span class="n">hist5</span> <span class="o">=</span> <span class="n">encdec_rnn_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">validation_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>

<span class="c1"># Print prediction(s)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">logits_to_text</span><span class="p">(</span><span class="n">encdec_rnn_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">[:</span><span class="mi">1</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> <span class="n">french_tokenizer</span><span class="p">))</span>
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<pre>__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
Inputs (InputLayer)             (None, 15)           0                                            
__________________________________________________________________________________________________
Source_Embedding (Embedding)    (None, 15, 256)      50944       Inputs[0][0]                     
__________________________________________________________________________________________________
Encoder (LSTM)                  [(None, 512), (None, 1574912     Source_Embedding[0][0]           
__________________________________________________________________________________________________
Decoder_Inputs (RepeatVector)   (None, 21, 512)      0           Encoder[0][0]                    
__________________________________________________________________________________________________
Decoder (LSTM)                  [(None, 21, 512), (N 2099200     Decoder_Inputs[0][0]             
                                                                 Encoder[0][1]                    
                                                                 Encoder[0][2]                    
__________________________________________________________________________________________________
Outputs (TimeDistributed)       (None, 21, 344)      176472      Decoder[0][0]                    
__________________________________________________________________________________________________
Activation (Activation)         (None, 21, 344)      0           Outputs[0][0]                    
==================================================================================================
Total params: 3,901,528
Trainable params: 3,901,528
Non-trainable params: 0
__________________________________________________________________________________________________
None

Train on 110288 samples, validate on 27573 samples
Epoch 1/10
110288/110288 [==============================] - 51s 460us/step - loss: 2.7021 - acc: 0.4674 - val_loss: nan - val_acc: 0.5313
Epoch 2/10
110288/110288 [==============================] - 50s 451us/step - loss: 1.5696 - acc: 0.5909 - val_loss: nan - val_acc: 0.6304
Epoch 3/10
110288/110288 [==============================] - 50s 451us/step - loss: 1.2494 - acc: 0.6519 - val_loss: nan - val_acc: 0.6761
Epoch 4/10
110288/110288 [==============================] - 50s 451us/step - loss: 1.0808 - acc: 0.6893 - val_loss: nan - val_acc: 0.7075
Epoch 5/10
110288/110288 [==============================] - 50s 451us/step - loss: 0.9509 - acc: 0.7227 - val_loss: nan - val_acc: 0.7410
Epoch 6/10
110288/110288 [==============================] - 50s 451us/step - loss: 0.8423 - acc: 0.7502 - val_loss: nan - val_acc: 0.7657
Epoch 7/10
110288/110288 [==============================] - 50s 451us/step - loss: 0.7373 - acc: 0.7777 - val_loss: nan - val_acc: 0.7895
Epoch 8/10
110288/110288 [==============================] - 50s 451us/step - loss: 0.6383 - acc: 0.8060 - val_loss: nan - val_acc: 0.8180
Epoch 9/10
110288/110288 [==============================] - 50s 451us/step - loss: 0.5935 - acc: 0.8171 - val_loss: nan - val_acc: 0.8387
Epoch 10/10
110288/110288 [==============================] - 50s 451us/step - loss: 0.4571 - acc: 0.8592 - val_loss: nan - val_acc: 0.8718
new jersey est parfois chaud au cours et l&#39; automne et en est &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span><span class="p">[</span><span class="s2">&quot;encdec&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">hist5</span><span class="o">.</span><span class="n">history</span><span class="p">[</span><span class="s1">&#39;loss&#39;</span><span class="p">]</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">source_to_text</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">english_tokenizer</span><span class="p">))</span>
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<pre>new jersey is sometimes quiet during autumn and it is snowy in april &lt;PAD&gt; &lt;PAD&gt;
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<h3 id="Model-5:-Custom-(IMPLEMENTATION)">Model 5: Custom (IMPLEMENTATION)<a class="anchor-link" href="#Model-5:-Custom-(IMPLEMENTATION)">&#182;</a></h3><p>Use everything you learned from the previous models to create a model that incorporates embedding and a bidirectional rnn into one model.</p>

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<h3 id="Bidirectional-and-embedding-RNN">Bidirectional and embedding RNN<a class="anchor-link" href="#Bidirectional-and-embedding-RNN">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">model_final</span><span class="p">(</span><span class="n">input_shape</span><span class="p">,</span> <span class="n">output_sequence_length</span><span class="p">,</span> <span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Build and train a model that incorporates embedding, encoder-decoder, and bidirectional RNN on x and y</span>
<span class="sd">    :param input_shape: Tuple of input shape</span>
<span class="sd">    :param output_sequence_length: Length of output sequence</span>
<span class="sd">    :param english_vocab_size: Number of unique English words in the dataset</span>
<span class="sd">    :param french_vocab_size: Number of unique French words in the dataset</span>
<span class="sd">    :return: Keras model built, but not trained</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">1e-3</span>
    
    <span class="c1"># Building Bidrectional RNN with Embedding Model</span>
    <span class="n">X</span> <span class="o">=</span> <span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Inputs&quot;</span><span class="p">)</span>
    <span class="n">embedding</span> <span class="o">=</span> <span class="n">Embedding</span><span class="p">(</span><span class="n">english_vocab_size</span><span class="p">,</span> <span class="mi">256</span><span class="p">,</span> <span class="n">input_length</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Embeddings&quot;</span><span class="p">)(</span><span class="n">X</span><span class="p">)</span>
    <span class="n">BiDirect_RNN</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">GRU</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;BD_RNN&quot;</span><span class="p">)(</span><span class="n">embedding</span><span class="p">)</span>
    <span class="n">y</span> <span class="o">=</span> <span class="n">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="n">french_vocab_size</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Outputs&quot;</span><span class="p">)(</span><span class="n">BiDirect_RNN</span><span class="p">)</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">Model</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Activation</span><span class="p">(</span><span class="s2">&quot;softmax&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Activation&quot;</span><span class="p">)(</span><span class="n">y</span><span class="p">))</span>
    
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">sparse_categorical_crossentropy</span><span class="p">,</span>
                  <span class="n">optimizer</span><span class="o">=</span><span class="n">Adam</span><span class="p">(</span><span class="n">learning_rate</span><span class="p">),</span>
                  <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>  
    
    <span class="k">return</span> <span class="n">model</span>

<span class="n">tests</span><span class="o">.</span><span class="n">test_model_final</span><span class="p">(</span><span class="n">model_final</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Final Model Loaded&#39;</span><span class="p">)</span>

<span class="c1"># Reshaping the input to work with a basic RNN</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">max_french_sequence_length</span><span class="p">)</span>

<span class="c1"># Train the neural network</span>
<span class="n">final_rnn_model</span> <span class="o">=</span> <span class="n">model_final</span><span class="p">(</span>
    <span class="n">tmp_x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span>
    <span class="n">max_french_sequence_length</span><span class="p">,</span>
    <span class="n">english_vocab_size</span><span class="p">,</span>
    <span class="n">french_vocab_size</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">final_rnn_model</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>
<span class="nb">print</span><span class="p">()</span>

<span class="n">hist6</span> <span class="o">=</span> <span class="n">final_rnn_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">validation_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>

<span class="c1"># Print prediction(s)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">logits_to_text</span><span class="p">(</span><span class="n">final_rnn_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">[:</span><span class="mi">1</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> <span class="n">french_tokenizer</span><span class="p">))</span>
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<pre>Final Model Loaded
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
Inputs (InputLayer)          (None, 21)                0         
_________________________________________________________________
Embeddings (Embedding)       (None, 21, 256)           50944     
_________________________________________________________________
BD_RNN (Bidirectional)       (None, 21, 1024)          2362368   
_________________________________________________________________
Outputs (TimeDistributed)    (None, 21, 344)           352600    
_________________________________________________________________
Activation (Activation)      (None, 21, 344)           0         
=================================================================
Total params: 2,765,912
Trainable params: 2,765,912
Non-trainable params: 0
_________________________________________________________________
None

Train on 110288 samples, validate on 27573 samples
Epoch 1/10
110288/110288 [==============================] - 44s 400us/step - loss: 2.5675 - acc: 0.5000 - val_loss: nan - val_acc: 0.6405
Epoch 2/10
110288/110288 [==============================] - 43s 390us/step - loss: 1.0877 - acc: 0.7338 - val_loss: nan - val_acc: 0.7958
Epoch 3/10
110288/110288 [==============================] - 43s 390us/step - loss: 0.6145 - acc: 0.8290 - val_loss: nan - val_acc: 0.8621
Epoch 4/10
110288/110288 [==============================] - 43s 390us/step - loss: 0.3989 - acc: 0.8841 - val_loss: nan - val_acc: 0.9035
Epoch 5/10
110288/110288 [==============================] - 43s 390us/step - loss: 0.2888 - acc: 0.9141 - val_loss: nan - val_acc: 0.9225
Epoch 6/10
110288/110288 [==============================] - 43s 390us/step - loss: 0.2209 - acc: 0.9334 - val_loss: nan - val_acc: 0.9377
Epoch 7/10
110288/110288 [==============================] - 43s 390us/step - loss: 0.1825 - acc: 0.9447 - val_loss: nan - val_acc: 0.9483
Epoch 8/10
110288/110288 [==============================] - 43s 390us/step - loss: 0.1512 - acc: 0.9542 - val_loss: nan - val_acc: 0.9577
Epoch 9/10
110288/110288 [==============================] - 43s 390us/step - loss: 0.1292 - acc: 0.9611 - val_loss: nan - val_acc: 0.9619
Epoch 10/10
110288/110288 [==============================] - 43s 390us/step - loss: 0.1140 - acc: 0.9656 - val_loss: nan - val_acc: 0.9654
new jersey est parfois calme pendant cours automne et il est neigeux en avril &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span><span class="p">[</span><span class="s2">&quot;final_model&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">hist6</span><span class="o">.</span><span class="n">history</span><span class="p">[</span><span class="s1">&#39;loss&#39;</span><span class="p">]</span>
</pre></div>

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<div class="prompt input_prompt">In&nbsp;[29]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span>
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    <div class="prompt output_prompt">Out[29]:</div>




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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x7f9e80101550&gt;</pre>
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<img 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<h3 id="Bidirectional-Encoder-Decoder-RNN-using-&quot;Sum&quot;-Merge-mode">Bidirectional Encoder-Decoder RNN using "Sum" Merge mode<a class="anchor-link" href="#Bidirectional-Encoder-Decoder-RNN-using-&quot;Sum&quot;-Merge-mode">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">bd_encdec_model_final</span><span class="p">(</span><span class="n">input_shape</span><span class="p">,</span> <span class="n">output_sequence_length</span><span class="p">,</span> <span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Build and train a model that incorporates embedding, encoder-decoder, and bidirectional RNN on x and y</span>
<span class="sd">    :param input_shape: Tuple of input shape</span>
<span class="sd">    :param output_sequence_length: Length of output sequence</span>
<span class="sd">    :param english_vocab_size: Number of unique English words in the dataset</span>
<span class="sd">    :param french_vocab_size: Number of unique French words in the dataset</span>
<span class="sd">    :return: Keras model built, but not trained</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">1e-3</span>
    
    <span class="c1"># Model</span>
    <span class="n">X</span> <span class="o">=</span> <span class="n">Input</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">:],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Inputs&quot;</span><span class="p">)</span>
    <span class="n">embedding</span> <span class="o">=</span> <span class="n">Embedding</span><span class="p">(</span><span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">,</span> <span class="n">input_length</span><span class="o">=</span><span class="n">input_shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Embeddings&quot;</span><span class="p">)(</span><span class="n">X</span><span class="p">)</span>
    <span class="n">BiDirect_RNN</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">GRU</span><span class="p">(</span><span class="mi">256</span><span class="p">,</span> <span class="n">dropout</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">recurrent_dropout</span><span class="o">=</span><span class="mf">0.4</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;BD_RNN&quot;</span><span class="p">)(</span><span class="n">embedding</span><span class="p">)</span>
    <span class="n">decoder_input</span> <span class="o">=</span> <span class="n">RepeatVector</span><span class="p">(</span><span class="n">output_sequence_length</span><span class="p">)(</span><span class="n">BiDirect_RNN</span><span class="p">)</span>
    <span class="n">BiDirect_Decode_RNN</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">GRU</span><span class="p">(</span><span class="mi">256</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">dropout</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">recurrent_dropout</span><span class="o">=</span><span class="mf">0.4</span><span class="p">),</span> <span class="n">merge_mode</span><span class="o">=</span><span class="s2">&quot;concat&quot;</span><span class="p">)(</span><span class="n">decoder_input</span><span class="p">)</span>
    <span class="n">y</span> <span class="o">=</span> <span class="n">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="n">french_vocab_size</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Outputs&quot;</span><span class="p">)(</span><span class="n">BiDirect_Decode_RNN</span><span class="p">)</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">Model</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Activation</span><span class="p">(</span><span class="s2">&quot;softmax&quot;</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Activation&quot;</span><span class="p">)(</span><span class="n">y</span><span class="p">))</span>
    
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">sparse_categorical_crossentropy</span><span class="p">,</span>
                  <span class="n">optimizer</span><span class="o">=</span><span class="n">Adam</span><span class="p">(</span><span class="n">learning_rate</span><span class="p">),</span>
                  <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>  
    
    <span class="k">return</span> <span class="n">model</span>

<span class="c1"># tests.test_model_final(bd_encdec_model_final)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Final Model Loaded&#39;</span><span class="p">)</span>
<span class="c1"># TODO: Train the final model</span>

<span class="c1"># Reshaping the input to work with a basic RNN</span>
<span class="n">tmp_x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">max_english_sequence_length</span><span class="p">)</span>
<span class="c1"># tmp_x = tmp_x.reshape((-1, preproc_french_sentences.shape[-2], 1))</span>

<span class="c1"># Train the neural network</span>
<span class="n">final_bd_encdec_model</span> <span class="o">=</span> <span class="n">bd_encdec_model_final</span><span class="p">(</span>
    <span class="n">tmp_x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span>
    <span class="n">max_french_sequence_length</span><span class="p">,</span>
    <span class="n">english_vocab_size</span><span class="p">,</span>
    <span class="n">french_vocab_size</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">final_bd_encdec_model</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>
<span class="nb">print</span><span class="p">()</span>

<span class="n">hist7</span> <span class="o">=</span> <span class="n">final_bd_encdec_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span> <span class="n">validation_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>

<span class="c1"># Print prediction(s)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">logits_to_text</span><span class="p">(</span><span class="n">final_bd_encdec_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">tmp_x</span><span class="p">[:</span><span class="mi">1</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> <span class="n">french_tokenizer</span><span class="p">))</span>
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<pre>Final Model Loaded
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
Inputs (InputLayer)          (None, 15)                0         
_________________________________________________________________
Embeddings (Embedding)       (None, 15, 344)           68456     
_________________________________________________________________
BD_RNN (Bidirectional)       (None, 512)               923136    
_________________________________________________________________
repeat_vector_1 (RepeatVecto (None, 21, 512)           0         
_________________________________________________________________
bidirectional_1 (Bidirection (None, 21, 512)           1181184   
_________________________________________________________________
Outputs (TimeDistributed)    (None, 21, 344)           176472    
_________________________________________________________________
Activation (Activation)      (None, 21, 344)           0         
=================================================================
Total params: 2,349,248
Trainable params: 2,349,248
Non-trainable params: 0
_________________________________________________________________
None

Train on 110288 samples, validate on 27573 samples
Epoch 1/20
110288/110288 [==============================] - 48s 435us/step - loss: 2.5659 - acc: 0.4700 - val_loss: nan - val_acc: 0.5444
Epoch 2/20
110288/110288 [==============================] - 45s 411us/step - loss: 1.5785 - acc: 0.5963 - val_loss: nan - val_acc: 0.6512
Epoch 3/20
110288/110288 [==============================] - 45s 412us/step - loss: 1.2168 - acc: 0.6697 - val_loss: nan - val_acc: 0.7090
Epoch 4/20
110288/110288 [==============================] - 45s 412us/step - loss: 0.9961 - acc: 0.7184 - val_loss: nan - val_acc: 0.7501
Epoch 5/20
110288/110288 [==============================] - 46s 413us/step - loss: 0.8484 - acc: 0.7524 - val_loss: nan - val_acc: 0.7842
Epoch 6/20
110288/110288 [==============================] - 45s 409us/step - loss: 0.7225 - acc: 0.7862 - val_loss: nan - val_acc: 0.8223
Epoch 7/20
110288/110288 [==============================] - 45s 410us/step - loss: 0.6107 - acc: 0.8197 - val_loss: nan - val_acc: 0.8546
Epoch 8/20
110288/110288 [==============================] - 45s 409us/step - loss: 0.5179 - acc: 0.8481 - val_loss: nan - val_acc: 0.8820
Epoch 9/20
110288/110288 [==============================] - 45s 409us/step - loss: 0.4370 - acc: 0.8727 - val_loss: nan - val_acc: 0.9054
Epoch 10/20
110288/110288 [==============================] - 45s 411us/step - loss: 0.3635 - acc: 0.8942 - val_loss: nan - val_acc: 0.9249
Epoch 11/20
110288/110288 [==============================] - 45s 411us/step - loss: 0.3048 - acc: 0.9124 - val_loss: nan - val_acc: 0.9404
Epoch 12/20
110288/110288 [==============================] - 45s 411us/step - loss: 0.2596 - acc: 0.9259 - val_loss: nan - val_acc: 0.9488
Epoch 13/20
110288/110288 [==============================] - 45s 411us/step - loss: 0.2255 - acc: 0.9356 - val_loss: nan - val_acc: 0.9550
Epoch 14/20
110288/110288 [==============================] - 45s 411us/step - loss: 0.1975 - acc: 0.9435 - val_loss: nan - val_acc: 0.9607
Epoch 15/20
110288/110288 [==============================] - 46s 414us/step - loss: 0.1807 - acc: 0.9483 - val_loss: nan - val_acc: 0.9587
Epoch 16/20
110288/110288 [==============================] - 46s 413us/step - loss: 0.1678 - acc: 0.9516 - val_loss: nan - val_acc: 0.9659
Epoch 17/20
110288/110288 [==============================] - 46s 413us/step - loss: 0.1515 - acc: 0.9561 - val_loss: nan - val_acc: 0.9663
Epoch 18/20
110288/110288 [==============================] - 46s 413us/step - loss: 0.1402 - acc: 0.9590 - val_loss: nan - val_acc: 0.9689
Epoch 19/20
110288/110288 [==============================] - 46s 413us/step - loss: 0.1307 - acc: 0.9615 - val_loss: nan - val_acc: 0.9711
Epoch 20/20
110288/110288 [==============================] - 46s 413us/step - loss: 0.1221 - acc: 0.9641 - val_loss: nan - val_acc: 0.9720
new jersey est parfois calme pendant l&#39; automne et il et il en avril &lt;PAD&gt; avril &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
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<h2 id="Prediction-(IMPLEMENTATION)">Prediction (IMPLEMENTATION)<a class="anchor-link" href="#Prediction-(IMPLEMENTATION)">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">final_predictions</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">x_tk</span><span class="p">,</span> <span class="n">y_tk</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Gets predictions using the final model</span>
<span class="sd">    :param x: Preprocessed English data</span>
<span class="sd">    :param y: Preprocessed French data</span>
<span class="sd">    :param x_tk: English tokenizer</span>
<span class="sd">    :param y_tk: French tokenizer</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">x</span> <span class="o">=</span> <span class="n">pad</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">bd_encdec_model_final</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">y</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">english_vocab_size</span><span class="p">,</span> <span class="n">french_vocab_size</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>
    <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">epochs</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span> <span class="n">validation_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>
    
    <span class="n">score</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Test score:&#39;</span><span class="p">,</span> <span class="n">score</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Test accuracy:&#39;</span><span class="p">,</span> <span class="n">score</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
    
    <span class="c1">## DON&#39;T EDIT ANYTHING BELOW THIS LINE</span>
    <span class="n">y_id_to_word</span> <span class="o">=</span> <span class="p">{</span><span class="n">value</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">value</span> <span class="ow">in</span> <span class="n">y_tk</span><span class="o">.</span><span class="n">word_index</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
    <span class="n">y_id_to_word</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;&lt;PAD&gt;&#39;</span>

    <span class="n">sentence</span> <span class="o">=</span> <span class="s1">&#39;he saw a old yellow truck&#39;</span>
    <span class="n">sentence</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_tk</span><span class="o">.</span><span class="n">word_index</span><span class="p">[</span><span class="n">word</span><span class="p">]</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">sentence</span><span class="o">.</span><span class="n">split</span><span class="p">()]</span>
    <span class="c1"># Not using encoder-decoder model, so change the max length to longest target output length.</span>
    <span class="n">sentence</span> <span class="o">=</span> <span class="n">pad_sequences</span><span class="p">([</span><span class="n">sentence</span><span class="p">],</span> <span class="n">maxlen</span><span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">padding</span><span class="o">=</span><span class="s1">&#39;post&#39;</span><span class="p">)</span>
    <span class="n">sentences</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">sentence</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]])</span>
    <span class="n">predictions</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">sentences</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">sentences</span><span class="p">))</span>
    

    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Sample 1:&#39;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">y_id_to_word</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">x</span><span class="p">)]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">predictions</span><span class="p">[</span><span class="mi">0</span><span class="p">]]))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Il a vu un vieux camion jaune&#39;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Sample 2:&#39;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">y_id_to_word</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">x</span><span class="p">)]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">predictions</span><span class="p">[</span><span class="mi">1</span><span class="p">]]))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">y_id_to_word</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">x</span><span class="p">)]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">y</span><span class="p">[</span><span class="mi">0</span><span class="p">]]))</span>


<span class="n">final_predictions</span><span class="p">(</span><span class="n">preproc_english_sentences</span><span class="p">,</span> <span class="n">preproc_french_sentences</span><span class="p">,</span> <span class="n">english_tokenizer</span><span class="p">,</span> <span class="n">french_tokenizer</span><span class="p">)</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
Inputs (InputLayer)          (None, 15)                0         
_________________________________________________________________
Embeddings (Embedding)       (None, 15, 344)           68456     
_________________________________________________________________
BD_RNN (Bidirectional)       (None, 512)               923136    
_________________________________________________________________
repeat_vector_2 (RepeatVecto (None, 21, 512)           0         
_________________________________________________________________
bidirectional_2 (Bidirection (None, 21, 512)           3148800   
_________________________________________________________________
Outputs (TimeDistributed)    (None, 21, 344)           176472    
_________________________________________________________________
Activation (Activation)      (None, 21, 344)           0         
=================================================================
Total params: 4,316,864
Trainable params: 4,316,864
Non-trainable params: 0
_________________________________________________________________
None
Train on 110288 samples, validate on 27573 samples
Epoch 1/20
110288/110288 [==============================] - 69s 628us/step - loss: 2.4463 - acc: 0.4827 - val_loss: nan - val_acc: 0.5813
Epoch 2/20
110288/110288 [==============================] - 67s 605us/step - loss: 1.4346 - acc: 0.6256 - val_loss: nan - val_acc: 0.6745
Epoch 3/20
110288/110288 [==============================] - 67s 605us/step - loss: 1.0861 - acc: 0.6978 - val_loss: nan - val_acc: 0.7436
Epoch 4/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.8518 - acc: 0.7502 - val_loss: nan - val_acc: 0.7851
Epoch 5/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.6891 - acc: 0.7919 - val_loss: nan - val_acc: 0.8326
Epoch 6/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.5509 - acc: 0.8330 - val_loss: nan - val_acc: 0.8749
Epoch 7/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.4321 - acc: 0.8693 - val_loss: nan - val_acc: 0.9081
Epoch 8/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.3358 - acc: 0.8987 - val_loss: nan - val_acc: 0.9300
Epoch 9/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.2656 - acc: 0.9204 - val_loss: nan - val_acc: 0.9439
Epoch 10/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.2181 - acc: 0.9344 - val_loss: nan - val_acc: 0.9525
Epoch 11/20
110288/110288 [==============================] - 67s 605us/step - loss: 0.1857 - acc: 0.9439 - val_loss: nan - val_acc: 0.9584
Epoch 12/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.1639 - acc: 0.9501 - val_loss: nan - val_acc: 0.9638
Epoch 13/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.1470 - acc: 0.9549 - val_loss: nan - val_acc: 0.9667
Epoch 14/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.1323 - acc: 0.9595 - val_loss: nan - val_acc: 0.9692
Epoch 15/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.1216 - acc: 0.9626 - val_loss: nan - val_acc: 0.9708
Epoch 16/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.1129 - acc: 0.9650 - val_loss: nan - val_acc: 0.9724
Epoch 17/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.1039 - acc: 0.9676 - val_loss: nan - val_acc: 0.9740
Epoch 18/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.0968 - acc: 0.9699 - val_loss: nan - val_acc: 0.9755
Epoch 19/20
110288/110288 [==============================] - 67s 605us/step - loss: 0.0902 - acc: 0.9719 - val_loss: nan - val_acc: 0.9770
Epoch 20/20
110288/110288 [==============================] - 67s 604us/step - loss: 0.0859 - acc: 0.9732 - val_loss: nan - val_acc: 0.9779
Test score: nan
Test accuracy: 0.98302327353
Sample 1:
il a vu un vieux camion jaune &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
Il a vu un vieux camion jaune
Sample 2:
new jersey est parfois calme pendant l&#39; automne et il est neigeux en avril &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
new jersey est parfois calme pendant l&#39; automne et il est neigeux en avril &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt; &lt;PAD&gt;
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<h2 id="Submission">Submission<a class="anchor-link" href="#Submission">&#182;</a></h2><p>When you're ready to submit, complete the following steps:</p>
<ol>
<li>Review the <a href="https://review.udacity.com/#!/rubrics/1004/view">rubric</a> to ensure your submission meets all requirements to pass</li>
<li><p>Generate an HTML version of this notebook</p>
<ul>
<li>Run the next cell to attempt automatic generation (this is the recommended method in Workspaces)</li>
<li>Navigate to <strong>FILE -&gt; Download as -&gt; HTML (.html)</strong></li>
<li>Manually generate a copy using <code>nbconvert</code> from your shell terminal
<pre><code>$ pip install nbconvert
$ python -m nbconvert machine_translation.ipynb</code></pre>
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<li><p>Submit the project</p>
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<li><p>If you are in a Workspace, simply click the "Submit Project" button (bottom towards the right)</p>
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<li><p>Otherwise, add the following files into a zip archive and submit them</p>
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<li><code>helper.py</code></li>
<li><code>machine_translation.ipynb</code></li>
<li><code>machine_translation.html</code><ul>
<li>You can export the notebook by navigating to <strong>File -&gt; Download as -&gt; HTML (.html)</strong>.</li>
</ul>
</li>
</ul>
</li>
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<h3 id="Generate-the-html">Generate the html<a class="anchor-link" href="#Generate-the-html">&#182;</a></h3><p><strong>Save your notebook before running the next cell to generate the HTML output.</strong> Then submit your project.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Save before you run this cell!</span>
<span class="o">!!</span>jupyter nbconvert *.ipynb
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<pre>[&#39;[NbConvertApp] Converting notebook machine_translation.ipynb to html&#39;,
 &#39;[NbConvertApp] Writing 450017 bytes to machine_translation.html&#39;,
 &#39;[NbConvertApp] Converting notebook machine_translation-zh.ipynb to html&#39;,
 &#39;[NbConvertApp] Writing 328614 bytes to machine_translation-zh.html&#39;]</pre>
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<h2 id="Optional-Enhancements">Optional Enhancements<a class="anchor-link" href="#Optional-Enhancements">&#182;</a></h2><p>This project focuses on learning various network architectures for machine translation, but we don't evaluate the models according to best practices by splitting the data into separate test &amp; training sets -- so the model accuracy is overstated. Use the <a href="http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html"><code>sklearn.model_selection.train_test_split()</code></a> function to create separate training &amp; test datasets, then retrain each of the models using only the training set and evaluate the prediction accuracy using the hold out test set. Does the "best" model change?</p>

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