dlnd_language_translation.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>dlnd_language_translation</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>

<style type="text/css">
    /*!
*
* Twitter Bootstrap
*
*/
/*!
 * Bootstrap v3.3.7 (http://getbootstrap.com)
 * Copyright 2011-2016 Twitter, Inc.
 * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
 */
/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
  font-family: sans-serif;
  -ms-text-size-adjust: 100%;
  -webkit-text-size-adjust: 100%;
}
body {
  margin: 0;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
hgroup,
main,
menu,
nav,
section,
summary {
  display: block;
}
audio,
canvas,
progress,
video {
  display: inline-block;
  vertical-align: baseline;
}
audio:not([controls]) {
  display: none;
  height: 0;
}
[hidden],
template {
  display: none;
}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
  font-style: italic;
}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
  background: #ff0;
  color: #000;
}
small {
  font-size: 80%;
}
sub,
sup {
  font-size: 75%;
  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
  top: -0.5em;
}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
  overflow: hidden;
}
figure {
  margin: 1em 40px;
}
hr {
  box-sizing: content-box;
  height: 0;
}
pre {
  overflow: auto;
}
code,
kbd,
pre,
samp {
  font-family: monospace, monospace;
  font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
  color: inherit;
  font: inherit;
  margin: 0;
}
button {
  overflow: visible;
}
button,
select {
  text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
  -webkit-appearance: button;
  cursor: pointer;
}
button[disabled],
html input[disabled] {
  cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
  border: 0;
  padding: 0;
}
input {
  line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
  box-sizing: border-box;
  padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: textfield;
  box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
  -webkit-appearance: none;
}
fieldset {
  border: 1px solid #c0c0c0;
  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
}
legend {
  border: 0;
  padding: 0;
}
textarea {
  overflow: auto;
}
optgroup {
  font-weight: bold;
}
table {
  border-collapse: collapse;
  border-spacing: 0;
}
td,
th {
  padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
  *,
  *:before,
  *:after {
    background: transparent !important;
    color: #000 !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 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

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

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
@media (max-width: 991px) {
  #ipython_notebook {
    margin-left: 10px;
  }
}
[dir="rtl"] #ipython_notebook {
  float: right !important;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#login_widget {
  float: right;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  text-align: center;
  vertical-align: middle;
  display: inline;
  opacity: 0;
  z-index: 2;
  width: 12ex;
  margin-right: -12ex;
}
.alternate_upload .btn-upload {
  height: 22px;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
[dir="rtl"] #tabs li {
  float: right;
}
ul#tabs {
  margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
  margin-right: 0px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons {
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
  padding-top: 1px;
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
  float: right !important;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: baseline;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
#tree-selector {
  padding-right: 0px;
}
[dir="rtl"] #tree-selector a {
  float: right;
}
#button-select-all {
  min-width: 50px;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
[dir="rtl"] #new-menu {
  text-align: right;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
[dir="rtl"] #running .col-sm-8 {
  float: right !important;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
  font-weight: bold;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  border-left-width: 1px;
  padding-left: 5px;
  background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
  border-left-color: #90CAF9;
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected {
  border-color: #ababab;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
  div.cell.selected {
    border-color: transparent;
  }
}
div.cell.selected.jupyter-soft-selected {
  border-left-width: 0;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  padding: 0.4em;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
  /* .CodeMirror-lines */
  padding: 0;
  border: 0;
  border-radius: 0;
}
/*

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

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
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<h1 id="Language-Translation">Language Translation<a class="anchor-link" href="#Language-Translation">&#182;</a></h1><p>In this project, you’re going to take a peek into the realm of neural network machine translation.  You’ll be training a sequence to sequence model on a dataset of English and French sentences that can translate new sentences from English to French.</p>
<h2 id="Get-the-Data">Get the Data<a class="anchor-link" href="#Get-the-Data">&#182;</a></h2><p>Since translating the whole language of English to French will take lots of time to train, we have provided you with a small portion of the English corpus.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">helper</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>

<span class="n">source_path</span> <span class="o">=</span> <span class="s1">&#39;data/small_vocab_en&#39;</span>
<span class="n">target_path</span> <span class="o">=</span> <span class="s1">&#39;data/small_vocab_fr&#39;</span>
<span class="n">source_text</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="n">source_path</span><span class="p">)</span>
<span class="n">target_text</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="n">target_path</span><span class="p">)</span>
</pre></div>

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<h2 id="Explore-the-Data">Explore the Data<a class="anchor-link" href="#Explore-the-Data">&#182;</a></h2><p>Play around with view_sentence_range to view different parts of the data.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">view_sentence_range</span> <span class="o">=</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>

<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Dataset Stats&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Roughly the number of unique words: </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="nb">len</span><span class="p">({</span><span class="n">word</span><span class="p">:</span> <span class="kc">None</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">()})))</span>

<span class="n">sentences</span> <span class="o">=</span> <span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)</span>
<span class="n">word_counts</span> <span class="o">=</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">sentence</span><span class="o">.</span><span class="n">split</span><span class="p">())</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">sentences</span><span class="p">]</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Number of sentences: </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="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;Average number of words in a sentence: </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">average</span><span class="p">(</span><span class="n">word_counts</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;English sentences </span><span class="si">{}</span><span class="s1"> to </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="o">*</span><span class="n">view_sentence_range</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)[</span><span class="n">view_sentence_range</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span><span class="n">view_sentence_range</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="nb">print</span><span class="p">(</span><span class="s1">&#39;French sentences </span><span class="si">{}</span><span class="s1"> to </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="o">*</span><span class="n">view_sentence_range</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">target_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)[</span><span class="n">view_sentence_range</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span><span class="n">view_sentence_range</span><span class="p">[</span><span class="mi">1</span><span class="p">]]))</span>
</pre></div>

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<pre>Dataset Stats
Roughly the number of unique words: 227
Number of sentences: 137861
Average number of words in a sentence: 13.225277634719028

English sentences 0 to 10:
new jersey is sometimes quiet during autumn , and it is snowy in april .
the united states is usually chilly during july , and it is usually freezing in november .
california is usually quiet during march , and it is usually hot in june .
the united states is sometimes mild during june , and it is cold in september .
your least liked fruit is the grape , but my least liked is the apple .
his favorite fruit is the orange , but my favorite is the grape .
paris is relaxing during december , but it is usually chilly in july .
new jersey is busy during spring , and it is never hot in march .
our least liked fruit is the lemon , but my least liked is the grape .
the united states is sometimes busy during january , and it is sometimes warm in november .

French sentences 0 to 10:
new jersey est parfois calme pendant l&#39; automne , et il est neigeux en avril .
les états-unis est généralement froid en juillet , et il gèle habituellement en novembre .
california est généralement calme en mars , et il est généralement chaud en juin .
les états-unis est parfois légère en juin , et il fait froid en septembre .
votre moins aimé fruit est le raisin , mais mon moins aimé est la pomme .
son fruit préféré est l&#39;orange , mais mon préféré est le raisin .
paris est relaxant en décembre , mais il est généralement froid en juillet .
new jersey est occupé au printemps , et il est jamais chaude en mars .
notre fruit est moins aimé le citron , mais mon moins aimé est le raisin .
les états-unis est parfois occupé en janvier , et il est parfois chaud en novembre .
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<h2 id="Implement-Preprocessing-Function">Implement Preprocessing Function<a class="anchor-link" href="#Implement-Preprocessing-Function">&#182;</a></h2><h3 id="Text-to-Word-Ids">Text to Word Ids<a class="anchor-link" href="#Text-to-Word-Ids">&#182;</a></h3><p>As you did with other RNNs, you must turn the text into a number so the computer can understand it. In the function <code>text_to_ids()</code>, you'll turn <code>source_text</code> and <code>target_text</code> from words to ids.  However, you need to add the <code>&lt;EOS&gt;</code> word id at the end of <code>target_text</code>.  This will help the neural network predict when the sentence should end.</p>
<p>You can get the <code>&lt;EOS&gt;</code> word id by doing:</p>
<div class="highlight"><pre><span></span><span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;EOS&gt;&#39;</span><span class="p">]</span>
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<p>You can get other word ids using <code>source_vocab_to_int</code> and <code>target_vocab_to_int</code>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">text_to_ids</span><span class="p">(</span><span class="n">source_text</span><span class="p">,</span> <span class="n">target_text</span><span class="p">,</span> <span class="n">source_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Convert source and target text to proper word ids</span>
<span class="sd">    :param source_text: String that contains all the source text.</span>
<span class="sd">    :param target_text: String that contains all the target text.</span>
<span class="sd">    :param source_vocab_to_int: Dictionary to go from the source words to an id</span>
<span class="sd">    :param target_vocab_to_int: Dictionary to go from the target words to an id</span>
<span class="sd">    :return: A tuple of lists (source_id_text, target_id_text)</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">source_id</span> <span class="o">=</span> <span class="p">[[</span><span class="n">source_vocab_to_int</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="s1">&#39; &#39;</span><span class="p">)</span> <span class="k">if</span> <span class="n">word</span> <span class="o">!=</span> <span class="s1">&#39;&#39;</span><span class="p">]</span>\
                 <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)]</span>

    <span class="n">target_id</span> <span class="o">=</span> <span class="p">[[</span><span class="n">target_vocab_to_int</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="s1">&#39; &#39;</span><span class="p">)</span> <span class="o">+</span> <span class="p">[</span><span class="s1">&#39;&lt;EOS&gt;&#39;</span><span class="p">]</span> <span class="k">if</span> <span class="n">word</span> <span class="o">!=</span> <span class="s1">&#39;&#39;</span><span class="p">]</span>\
                 <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">target_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)]</span>
    
    <span class="k">return</span> <span class="n">source_id</span><span class="p">,</span> <span class="n">target_id</span>

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<span class="n">tests</span><span class="o">.</span><span class="n">test_text_to_ids</span><span class="p">(</span><span class="n">text_to_ids</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Preprocess-all-the-data-and-save-it">Preprocess all the data and save it<a class="anchor-link" href="#Preprocess-all-the-data-and-save-it">&#182;</a></h3><p>Running the code cell below will preprocess all the data and save it to file.</p>

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<span class="n">helper</span><span class="o">.</span><span class="n">preprocess_and_save_data</span><span class="p">(</span><span class="n">source_path</span><span class="p">,</span> <span class="n">target_path</span><span class="p">,</span> <span class="n">text_to_ids</span><span class="p">)</span>
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<h1 id="Check-Point">Check Point<a class="anchor-link" href="#Check-Point">&#182;</a></h1><p>This is your first checkpoint. If you ever decide to come back to this notebook or have to restart the notebook, you can start from here. The preprocessed data has been saved to disk.</p>

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<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">helper</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>

<span class="p">(</span><span class="n">source_int_text</span><span class="p">,</span> <span class="n">target_int_text</span><span class="p">),</span> <span class="p">(</span><span class="n">source_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">),</span> <span class="n">_</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_preprocess</span><span class="p">()</span>
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<h3 id="Check-the-Version-of-TensorFlow-and-Access-to-GPU">Check the Version of TensorFlow and Access to GPU<a class="anchor-link" href="#Check-the-Version-of-TensorFlow-and-Access-to-GPU">&#182;</a></h3><p>This will check to make sure you have the correct version of TensorFlow and access to a GPU</p>

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<span class="kn">from</span> <span class="nn">distutils.version</span> <span class="k">import</span> <span class="n">LooseVersion</span>
<span class="kn">import</span> <span class="nn">warnings</span>
<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span>
<span class="kn">from</span> <span class="nn">tensorflow.python.layers.core</span> <span class="k">import</span> <span class="n">Dense</span>

<span class="c1"># Check TensorFlow Version</span>
<span class="k">assert</span> <span class="n">LooseVersion</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">__version__</span><span class="p">)</span> <span class="o">&gt;=</span> <span class="n">LooseVersion</span><span class="p">(</span><span class="s1">&#39;1.1&#39;</span><span class="p">),</span> <span class="s1">&#39;Please use TensorFlow version 1.1 or newer&#39;</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;TensorFlow Version: </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">tf</span><span class="o">.</span><span class="n">__version__</span><span class="p">))</span>

<span class="c1"># Check for a GPU</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">tf</span><span class="o">.</span><span class="n">test</span><span class="o">.</span><span class="n">gpu_device_name</span><span class="p">():</span>
    <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">&#39;No GPU found. Please use a GPU to train your neural network.&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Default GPU Device: </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">tf</span><span class="o">.</span><span class="n">test</span><span class="o">.</span><span class="n">gpu_device_name</span><span class="p">()))</span>
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<pre>TensorFlow Version: 1.1.0
Default GPU Device: /gpu:0
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<h2 id="Build-the-Neural-Network">Build the Neural Network<a class="anchor-link" href="#Build-the-Neural-Network">&#182;</a></h2><p>You'll build the components necessary to build a Sequence-to-Sequence model by implementing the following functions below:</p>
<ul>
<li><code>model_inputs</code></li>
<li><code>process_decoder_input</code></li>
<li><code>encoding_layer</code></li>
<li><code>decoding_layer_train</code></li>
<li><code>decoding_layer_infer</code></li>
<li><code>decoding_layer</code></li>
<li><code>seq2seq_model</code></li>
</ul>
<h3 id="Input">Input<a class="anchor-link" href="#Input">&#182;</a></h3><p>Implement the <code>model_inputs()</code> function to create TF Placeholders for the Neural Network. It should create the following placeholders:</p>
<ul>
<li>Input text placeholder named "input" using the TF Placeholder name parameter with rank 2.</li>
<li>Targets placeholder with rank 2.</li>
<li>Learning rate placeholder with rank 0.</li>
<li>Keep probability placeholder named "keep_prob" using the TF Placeholder name parameter with rank 0.</li>
<li>Target sequence length placeholder named "target_sequence_length" with rank 1</li>
<li>Max target sequence length tensor named "max_target_len" getting its value from applying tf.reduce_max on the target_sequence_length placeholder. Rank 0.</li>
<li>Source sequence length placeholder named "source_sequence_length" with rank 1</li>
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<p>Return the placeholders in the following the tuple (input, targets, learning rate, keep probability, target sequence length, max target sequence length, source sequence length)</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">model_inputs</span><span class="p">():</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Create TF Placeholders for input, targets, learning rate, and lengths of source and target sequences.</span>
<span class="sd">    :return: Tuple (input, targets, learning rate, keep probability, target sequence length,</span>
<span class="sd">    max target sequence length, source sequence length)</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">inputs</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;input&#39;</span><span class="p">)</span>
    <span class="n">targets</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">])</span>
    <span class="n">learning_rate</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
    <span class="n">keep_prob</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;keep_prob&#39;</span><span class="p">)</span>
    <span class="n">target_sequence_length</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="kc">None</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;target_sequence_length&#39;</span><span class="p">)</span>
    <span class="n">max_target_len</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">reduce_max</span><span class="p">(</span><span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;max_target_len&#39;</span><span class="p">)</span>
    <span class="n">source_sequence_length</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="kc">None</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;source_sequence_length&#39;</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">inputs</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">learning_rate</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> <span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_target_len</span><span class="p">,</span> <span class="n">source_sequence_length</span>


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<span class="n">tests</span><span class="o">.</span><span class="n">test_model_inputs</span><span class="p">(</span><span class="n">model_inputs</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Process-Decoder-Input">Process Decoder Input<a class="anchor-link" href="#Process-Decoder-Input">&#182;</a></h3><p>Implement <code>process_decoder_input</code> by removing the last word id from each batch in <code>target_data</code> and concat the GO ID to the begining of each batch.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">process_decoder_input</span><span class="p">(</span><span class="n">target_data</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Preprocess target data for encoding</span>
<span class="sd">    :param target_data: Target Placehoder</span>
<span class="sd">    :param target_vocab_to_int: Dictionary to go from the target words to an id</span>
<span class="sd">    :param batch_size: Batch Size</span>
<span class="sd">    :return: Preprocessed target data</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">first_elements</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">fill</span><span class="p">([</span><span class="n">batch_size</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;GO&gt;&#39;</span><span class="p">])</span>
    <span class="n">target_data</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">first_elements</span><span class="p">,</span> <span class="n">target_data</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
    <span class="n">target_data</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">strided_slice</span><span class="p">(</span><span class="n">target_data</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span>
    <span class="k">return</span> <span class="n">target_data</span>


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<span class="n">tests</span><span class="o">.</span><span class="n">test_process_encoding_input</span><span class="p">(</span><span class="n">process_decoder_input</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Encoding">Encoding<a class="anchor-link" href="#Encoding">&#182;</a></h3><p>Implement <code>encoding_layer()</code> to create a Encoder RNN layer:</p>
<ul>
<li>Embed the encoder input using <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/layers/embed_sequence"><code>tf.contrib.layers.embed_sequence</code></a></li>
<li>Construct a <a href="https://github.com/tensorflow/tensorflow/blob/6947f65a374ebf29e74bb71e36fd82760056d82c/tensorflow/docs_src/tutorials/recurrent.md#stacking-multiple-lstms">stacked</a> <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/rnn/LSTMCell"><code>tf.contrib.rnn.LSTMCell</code></a> wrapped in a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/rnn/DropoutWrapper"><code>tf.contrib.rnn.DropoutWrapper</code></a></li>
<li>Pass cell and embedded input to <a href="https://www.tensorflow.org/api_docs/python/tf/nn/dynamic_rnn"><code>tf.nn.dynamic_rnn()</code></a></li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">imp</span> <span class="k">import</span> <span class="n">reload</span>
<span class="n">reload</span><span class="p">(</span><span class="n">tests</span><span class="p">)</span>

<span class="k">def</span> <span class="nf">encoding_layer</span><span class="p">(</span><span class="n">rnn_inputs</span><span class="p">,</span> <span class="n">rnn_size</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> 
                   <span class="n">source_sequence_length</span><span class="p">,</span> <span class="n">source_vocab_size</span><span class="p">,</span> 
                   <span class="n">encoding_embedding_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Create encoding layer</span>
<span class="sd">    :param rnn_inputs: Inputs for the RNN</span>
<span class="sd">    :param rnn_size: RNN Size</span>
<span class="sd">    :param num_layers: Number of layers</span>
<span class="sd">    :param keep_prob: Dropout keep probability</span>
<span class="sd">    :param source_sequence_length: a list of the lengths of each sequence in the batch</span>
<span class="sd">    :param source_vocab_size: vocabulary size of source data</span>
<span class="sd">    :param encoding_embedding_size: embedding size of source data</span>
<span class="sd">    :return: tuple (RNN output, RNN state)</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">embedding</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">embed_sequence</span><span class="p">(</span><span class="n">rnn_inputs</span><span class="p">,</span>
                                                 <span class="n">vocab_size</span><span class="o">=</span><span class="n">source_vocab_size</span><span class="p">,</span>
                                                 <span class="n">embed_dim</span><span class="o">=</span><span class="n">encoding_embedding_size</span><span class="p">)</span>
    
    <span class="n">lstm_cell</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">size</span><span class="p">:</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">LSTMCell</span><span class="p">(</span><span class="n">size</span><span class="p">)</span>

    <span class="n">stack</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">MultiRNNCell</span><span class="p">([</span><span class="n">lstm_cell</span><span class="p">(</span><span class="n">rnn_size</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_layers</span><span class="p">)])</span>
    <span class="n">drop</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">DropoutWrapper</span><span class="p">(</span><span class="n">stack</span><span class="p">,</span> <span class="n">input_keep_prob</span><span class="o">=</span><span class="n">keep_prob</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">dynamic_rnn</span><span class="p">(</span><span class="n">drop</span><span class="p">,</span> <span class="n">embedding</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">embedding</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>

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<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_encoding_layer</span><span class="p">(</span><span class="n">encoding_layer</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Decoding---Training">Decoding - Training<a class="anchor-link" href="#Decoding---Training">&#182;</a></h3><p>Create a training decoding layer:</p>
<ul>
<li>Create a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/TrainingHelper"><code>tf.contrib.seq2seq.TrainingHelper</code></a> </li>
<li>Create a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/BasicDecoder"><code>tf.contrib.seq2seq.BasicDecoder</code></a></li>
<li>Obtain the decoder outputs from <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/dynamic_decode"><code>tf.contrib.seq2seq.dynamic_decode</code></a></li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">decoding_layer_train</span><span class="p">(</span><span class="n">encoder_state</span><span class="p">,</span> <span class="n">dec_cell</span><span class="p">,</span> <span class="n">dec_embed_input</span><span class="p">,</span> 
                         <span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_summary_length</span><span class="p">,</span> 
                         <span class="n">output_layer</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Create a decoding layer for training</span>
<span class="sd">    :param encoder_state: Encoder State</span>
<span class="sd">    :param dec_cell: Decoder RNN Cell</span>
<span class="sd">    :param dec_embed_input: Decoder embedded input</span>
<span class="sd">    :param target_sequence_length: The lengths of each sequence in the target batch</span>
<span class="sd">    :param max_summary_length: The length of the longest sequence in the batch</span>
<span class="sd">    :param output_layer: Function to apply the output layer</span>
<span class="sd">    :param keep_prob: Dropout keep probability</span>
<span class="sd">    :return: BasicDecoderOutput containing training logits and sample_id</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">training_helper</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">TrainingHelper</span><span class="p">(</span><span class="n">dec_embed_input</span><span class="p">,</span> <span class="n">target_sequence_length</span><span class="p">)</span>
    <span class="n">decoder</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">BasicDecoder</span><span class="p">(</span><span class="n">dec_cell</span><span class="p">,</span> <span class="n">training_helper</span><span class="p">,</span> <span class="n">encoder_state</span><span class="p">,</span> <span class="n">output_layer</span><span class="p">)</span>
    <span class="n">outputs</span><span class="p">,</span> <span class="o">*</span><span class="n">_</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">dynamic_decode</span><span class="p">(</span><span class="n">decoder</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">outputs</span>


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<span class="n">tests</span><span class="o">.</span><span class="n">test_decoding_layer_train</span><span class="p">(</span><span class="n">decoding_layer_train</span><span class="p">)</span>
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<h3 id="Decoding---Inference">Decoding - Inference<a class="anchor-link" href="#Decoding---Inference">&#182;</a></h3><p>Create inference decoder:</p>
<ul>
<li>Create a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/GreedyEmbeddingHelper"><code>tf.contrib.seq2seq.GreedyEmbeddingHelper</code></a></li>
<li>Create a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/BasicDecoder"><code>tf.contrib.seq2seq.BasicDecoder</code></a></li>
<li>Obtain the decoder outputs from <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/dynamic_decode"><code>tf.contrib.seq2seq.dynamic_decode</code></a></li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">decoding_layer_infer</span><span class="p">(</span><span class="n">encoder_state</span><span class="p">,</span> <span class="n">dec_cell</span><span class="p">,</span> <span class="n">dec_embeddings</span><span class="p">,</span> <span class="n">start_of_sequence_id</span><span class="p">,</span>
                         <span class="n">end_of_sequence_id</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span>
                         <span class="n">vocab_size</span><span class="p">,</span> <span class="n">output_layer</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Create a decoding layer for inference</span>
<span class="sd">    :param encoder_state: Encoder state</span>
<span class="sd">    :param dec_cell: Decoder RNN Cell</span>
<span class="sd">    :param dec_embeddings: Decoder embeddings</span>
<span class="sd">    :param start_of_sequence_id: GO ID</span>
<span class="sd">    :param end_of_sequence_id: EOS Id</span>
<span class="sd">    :param max_target_sequence_length: Maximum length of target sequences</span>
<span class="sd">    :param vocab_size: Size of decoder/target vocabulary</span>
<span class="sd">    :param decoding_scope: TenorFlow Variable Scope for decoding</span>
<span class="sd">    :param output_layer: Function to apply the output layer</span>
<span class="sd">    :param batch_size: Batch size</span>
<span class="sd">    :param keep_prob: Dropout keep probability</span>
<span class="sd">    :return: BasicDecoderOutput containing inference logits and sample_id</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">embed_helper</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">GreedyEmbeddingHelper</span><span class="p">(</span><span class="n">dec_embeddings</span><span class="p">,</span>
                                                            <span class="n">batch_size</span> <span class="o">*</span> <span class="p">[</span><span class="n">start_of_sequence_id</span><span class="p">],</span>
                                                            <span class="n">end_of_sequence_id</span><span class="p">)</span>
    <span class="n">decoder</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">BasicDecoder</span><span class="p">(</span><span class="n">dec_cell</span><span class="p">,</span> <span class="n">embed_helper</span><span class="p">,</span> <span class="n">encoder_state</span><span class="p">,</span> <span class="n">output_layer</span><span class="p">)</span>
    <span class="n">outputs</span><span class="p">,</span> <span class="o">*</span><span class="n">_</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">dynamic_decode</span><span class="p">(</span><span class="n">decoder</span><span class="p">,</span>
                                                    <span class="n">impute_finished</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> 
                                                    <span class="n">maximum_iterations</span><span class="o">=</span><span class="n">max_target_sequence_length</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">outputs</span>


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<span class="n">tests</span><span class="o">.</span><span class="n">test_decoding_layer_infer</span><span class="p">(</span><span class="n">decoding_layer_infer</span><span class="p">)</span>
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<h3 id="Build-the-Decoding-Layer">Build the Decoding Layer<a class="anchor-link" href="#Build-the-Decoding-Layer">&#182;</a></h3><p>Implement <code>decoding_layer()</code> to create a Decoder RNN layer.</p>
<ul>
<li>Embed the target sequences</li>
<li>Construct the decoder LSTM cell (just like you constructed the encoder cell above)</li>
<li>Create an output layer to map the outputs of the decoder to the elements of our vocabulary</li>
<li>Use the your <code>decoding_layer_train(encoder_state, dec_cell, dec_embed_input, target_sequence_length, max_target_sequence_length, output_layer, keep_prob)</code> function to get the training logits.</li>
<li>Use your <code>decoding_layer_infer(encoder_state, dec_cell, dec_embeddings, start_of_sequence_id, end_of_sequence_id, max_target_sequence_length, vocab_size, output_layer, batch_size, keep_prob)</code> function to get the inference logits.</li>
</ul>
<p>Note: You'll need to use <a href="https://www.tensorflow.org/api_docs/python/tf/variable_scope">tf.variable_scope</a> to share variables between training and inference.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">decoding_layer</span><span class="p">(</span><span class="n">dec_input</span><span class="p">,</span> <span class="n">encoder_state</span><span class="p">,</span>
                   <span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span>
                   <span class="n">rnn_size</span><span class="p">,</span>
                   <span class="n">num_layers</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_size</span><span class="p">,</span>
                   <span class="n">batch_size</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> <span class="n">decoding_embedding_size</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Create decoding layer</span>
<span class="sd">    :param dec_input: Decoder input</span>
<span class="sd">    :param encoder_state: Encoder state</span>
<span class="sd">    :param target_sequence_length: The lengths of each sequence in the target batch</span>
<span class="sd">    :param max_target_sequence_length: Maximum length of target sequences</span>
<span class="sd">    :param rnn_size: RNN Size</span>
<span class="sd">    :param num_layers: Number of layers</span>
<span class="sd">    :param target_vocab_to_int: Dictionary to go from the target words to an id</span>
<span class="sd">    :param target_vocab_size: Size of target vocabulary</span>
<span class="sd">    :param batch_size: The size of the batch</span>
<span class="sd">    :param keep_prob: Dropout keep probability</span>
<span class="sd">    :param decoding_embedding_size: Decoding embedding size</span>
<span class="sd">    :return: Tuple of (Training BasicDecoderOutput, Inference BasicDecoderOutput)</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">dec_embeddings</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">random_uniform</span><span class="p">([</span><span class="n">target_vocab_size</span><span class="p">,</span> <span class="n">decoding_embedding_size</span><span class="p">]))</span>
    <span class="n">dec_embed_input</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">embedding_lookup</span><span class="p">(</span><span class="n">dec_embeddings</span><span class="p">,</span> <span class="n">dec_input</span><span class="p">)</span>
    
    <span class="n">lstm_cell</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">size</span><span class="p">:</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">LSTMCell</span><span class="p">(</span><span class="n">size</span><span class="p">)</span>
    <span class="n">stack</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">MultiRNNCell</span><span class="p">([</span><span class="n">lstm_cell</span><span class="p">(</span><span class="n">rnn_size</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_layers</span><span class="p">)])</span>
    <span class="n">dec_cell</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">DropoutWrapper</span><span class="p">(</span><span class="n">stack</span><span class="p">,</span> <span class="n">input_keep_prob</span><span class="o">=</span><span class="n">keep_prob</span><span class="p">)</span>
       
    <span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">variable_scope</span><span class="p">(</span><span class="s1">&#39;decoding&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">scope</span><span class="p">:</span>
        <span class="n">output_layer</span> <span class="o">=</span> <span class="n">Dense</span><span class="p">(</span><span class="n">target_vocab_size</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;output_layer&#39;</span><span class="p">)</span>
        <span class="n">dec_train</span> <span class="o">=</span> <span class="n">decoding_layer_train</span><span class="p">(</span><span class="n">encoder_state</span><span class="p">,</span> <span class="n">dec_cell</span><span class="p">,</span> <span class="n">dec_embed_input</span><span class="p">,</span> 
                                         <span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span> 
                                         <span class="n">output_layer</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">)</span>
        <span class="n">scope</span><span class="o">.</span><span class="n">reuse_variables</span><span class="p">()</span>
        <span class="n">dec_infer</span> <span class="o">=</span> <span class="n">decoding_layer_infer</span><span class="p">(</span><span class="n">encoder_state</span><span class="p">,</span> <span class="n">dec_cell</span><span class="p">,</span> <span class="n">dec_embeddings</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;GO&gt;&#39;</span><span class="p">],</span>
                                         <span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;EOS&gt;&#39;</span><span class="p">],</span> <span class="n">max_target_sequence_length</span><span class="p">,</span>
                                         <span class="n">target_vocab_size</span><span class="p">,</span> <span class="n">output_layer</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">)</span>
        
    <span class="k">return</span> <span class="n">dec_train</span><span class="p">,</span> <span class="n">dec_infer</span>


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<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_decoding_layer</span><span class="p">(</span><span class="n">decoding_layer</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Build-the-Neural-Network">Build the Neural Network<a class="anchor-link" href="#Build-the-Neural-Network">&#182;</a></h3><p>Apply the functions you implemented above to:</p>
<ul>
<li>Encode the input using your <code>encoding_layer(rnn_inputs, rnn_size, num_layers, keep_prob,  source_sequence_length, source_vocab_size, encoding_embedding_size)</code>.</li>
<li>Process target data using your <code>process_decoder_input(target_data, target_vocab_to_int, batch_size)</code> function.</li>
<li>Decode the encoded input using your <code>decoding_layer(dec_input, enc_state, target_sequence_length, max_target_sentence_length, rnn_size, num_layers, target_vocab_to_int, target_vocab_size, batch_size, keep_prob, dec_embedding_size)</code> function.</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">seq2seq_model</span><span class="p">(</span><span class="n">input_data</span><span class="p">,</span> <span class="n">target_data</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span>
                  <span class="n">source_sequence_length</span><span class="p">,</span> <span class="n">target_sequence_length</span><span class="p">,</span>
                  <span class="n">max_target_sentence_length</span><span class="p">,</span>
                  <span class="n">source_vocab_size</span><span class="p">,</span> <span class="n">target_vocab_size</span><span class="p">,</span>
                  <span class="n">enc_embedding_size</span><span class="p">,</span> <span class="n">dec_embedding_size</span><span class="p">,</span>
                  <span class="n">rnn_size</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Build the Sequence-to-Sequence part of the neural network</span>
<span class="sd">    :param input_data: Input placeholder</span>
<span class="sd">    :param target_data: Target placeholder</span>
<span class="sd">    :param keep_prob: Dropout keep probability placeholder</span>
<span class="sd">    :param batch_size: Batch Size</span>
<span class="sd">    :param source_sequence_length: Sequence Lengths of source sequences in the batch</span>
<span class="sd">    :param target_sequence_length: Sequence Lengths of target sequences in the batch</span>
<span class="sd">    :param source_vocab_size: Source vocabulary size</span>
<span class="sd">    :param target_vocab_size: Target vocabulary size</span>
<span class="sd">    :param enc_embedding_size: Decoder embedding size</span>
<span class="sd">    :param dec_embedding_size: Encoder embedding size</span>
<span class="sd">    :param rnn_size: RNN Size</span>
<span class="sd">    :param num_layers: Number of layers</span>
<span class="sd">    :param target_vocab_to_int: Dictionary to go from the target words to an id</span>
<span class="sd">    :return: Tuple of (Training BasicDecoderOutput, Inference BasicDecoderOutput)</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">encoder_output</span><span class="p">,</span> <span class="n">encoder_state</span> <span class="o">=</span> <span class="n">encoding_layer</span><span class="p">(</span><span class="n">input_data</span><span class="p">,</span> <span class="n">rnn_size</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> 
                                                   <span class="n">source_sequence_length</span><span class="p">,</span> <span class="n">source_vocab_size</span><span class="p">,</span> 
                                                   <span class="n">enc_embedding_size</span><span class="p">)</span>
    <span class="n">decoder_input</span> <span class="o">=</span> <span class="n">process_decoder_input</span><span class="p">(</span><span class="n">target_data</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">)</span>
    <span class="n">decoder_output</span> <span class="o">=</span> <span class="n">decoding_layer</span><span class="p">(</span><span class="n">decoder_input</span><span class="p">,</span> <span class="n">encoder_state</span><span class="p">,</span> <span class="n">target_sequence_length</span><span class="p">,</span> 
                                    <span class="n">max_target_sentence_length</span><span class="p">,</span> <span class="n">rnn_size</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> 
                                    <span class="n">target_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_size</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> 
                                    <span class="n">dec_embedding_size</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">decoder_output</span>


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<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_seq2seq_model</span><span class="p">(</span><span class="n">seq2seq_model</span><span class="p">)</span>
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<pre>Tests Passed
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<h2 id="Neural-Network-Training">Neural Network Training<a class="anchor-link" href="#Neural-Network-Training">&#182;</a></h2><h3 id="Hyperparameters">Hyperparameters<a class="anchor-link" href="#Hyperparameters">&#182;</a></h3><p>Tune the following parameters:</p>
<ul>
<li>Set <code>epochs</code> to the number of epochs.</li>
<li>Set <code>batch_size</code> to the batch size.</li>
<li>Set <code>rnn_size</code> to the size of the RNNs.</li>
<li>Set <code>num_layers</code> to the number of layers.</li>
<li>Set <code>encoding_embedding_size</code> to the size of the embedding for the encoder.</li>
<li>Set <code>decoding_embedding_size</code> to the size of the embedding for the decoder.</li>
<li>Set <code>learning_rate</code> to the learning rate.</li>
<li>Set <code>keep_probability</code> to the Dropout keep probability</li>
<li>Set <code>display_step</code> to state how many steps between each debug output statement</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of Epochs</span>
<span class="n">epochs</span> <span class="o">=</span> <span class="mi">10</span>
<span class="c1"># Batch Size</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="mi">128</span>
<span class="c1"># RNN Size</span>
<span class="n">rnn_size</span> <span class="o">=</span> <span class="mi">64</span>
<span class="c1"># Number of Layers</span>
<span class="n">num_layers</span> <span class="o">=</span> <span class="mi">3</span>
<span class="c1"># Embedding Size</span>
<span class="n">encoding_embedding_size</span> <span class="o">=</span> <span class="mi">128</span>
<span class="n">decoding_embedding_size</span> <span class="o">=</span> <span class="mi">128</span>
<span class="c1"># Learning Rate</span>
<span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">0.01</span>
<span class="c1"># Dropout Keep Probability</span>
<span class="n">keep_probability</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="n">display_step</span> <span class="o">=</span> <span class="mi">16</span>
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<h3 id="Build-the-Graph">Build the Graph<a class="anchor-link" href="#Build-the-Graph">&#182;</a></h3><p>Build the graph using the neural network you implemented.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">save_path</span> <span class="o">=</span> <span class="s1">&#39;checkpoints/dev&#39;</span>
<span class="p">(</span><span class="n">source_int_text</span><span class="p">,</span> <span class="n">target_int_text</span><span class="p">),</span> <span class="p">(</span><span class="n">source_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">),</span> <span class="n">_</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_preprocess</span><span class="p">()</span>
<span class="n">max_target_sentence_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">sentence</span><span class="p">)</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">source_int_text</span><span class="p">])</span>

<span class="n">train_graph</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Graph</span><span class="p">()</span>
<span class="k">with</span> <span class="n">train_graph</span><span class="o">.</span><span class="n">as_default</span><span class="p">():</span>
    <span class="n">input_data</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">lr</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> <span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span> <span class="n">source_sequence_length</span> <span class="o">=</span> <span class="n">model_inputs</span><span class="p">()</span>

    <span class="c1">#sequence_length = tf.placeholder_with_default(max_target_sentence_length, None, name=&#39;sequence_length&#39;)</span>
    <span class="n">input_shape</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">input_data</span><span class="p">)</span>

    <span class="n">train_logits</span><span class="p">,</span> <span class="n">inference_logits</span> <span class="o">=</span> <span class="n">seq2seq_model</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">reverse</span><span class="p">(</span><span class="n">input_data</span><span class="p">,</span> <span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span>
                                                   <span class="n">targets</span><span class="p">,</span>
                                                   <span class="n">keep_prob</span><span class="p">,</span>
                                                   <span class="n">batch_size</span><span class="p">,</span>
                                                   <span class="n">source_sequence_length</span><span class="p">,</span>
                                                   <span class="n">target_sequence_length</span><span class="p">,</span>
                                                   <span class="n">max_target_sequence_length</span><span class="p">,</span>
                                                   <span class="nb">len</span><span class="p">(</span><span class="n">source_vocab_to_int</span><span class="p">),</span>
                                                   <span class="nb">len</span><span class="p">(</span><span class="n">target_vocab_to_int</span><span class="p">),</span>
                                                   <span class="n">encoding_embedding_size</span><span class="p">,</span>
                                                   <span class="n">decoding_embedding_size</span><span class="p">,</span>
                                                   <span class="n">rnn_size</span><span class="p">,</span>
                                                   <span class="n">num_layers</span><span class="p">,</span>
                                                   <span class="n">target_vocab_to_int</span><span class="p">)</span>


    <span class="n">training_logits</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">identity</span><span class="p">(</span><span class="n">train_logits</span><span class="o">.</span><span class="n">rnn_output</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;logits&#39;</span><span class="p">)</span>
    <span class="n">inference_logits</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">identity</span><span class="p">(</span><span class="n">inference_logits</span><span class="o">.</span><span class="n">sample_id</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;predictions&#39;</span><span class="p">)</span>

    <span class="n">masks</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">sequence_mask</span><span class="p">(</span><span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;masks&#39;</span><span class="p">)</span>

    <span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">name_scope</span><span class="p">(</span><span class="s2">&quot;optimization&quot;</span><span class="p">):</span>
        <span class="c1"># Loss function</span>
        <span class="n">cost</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">sequence_loss</span><span class="p">(</span>
            <span class="n">training_logits</span><span class="p">,</span>
            <span class="n">targets</span><span class="p">,</span>
            <span class="n">masks</span><span class="p">)</span>

        <span class="c1"># Optimizer</span>
        <span class="n">optimizer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">AdamOptimizer</span><span class="p">(</span><span class="n">lr</span><span class="p">)</span>

        <span class="c1"># Gradient Clipping</span>
        <span class="n">gradients</span> <span class="o">=</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">compute_gradients</span><span class="p">(</span><span class="n">cost</span><span class="p">)</span>
        <span class="n">capped_gradients</span> <span class="o">=</span> <span class="p">[(</span><span class="n">tf</span><span class="o">.</span><span class="n">clip_by_value</span><span class="p">(</span><span class="n">grad</span><span class="p">,</span> <span class="o">-</span><span class="mf">1.</span><span class="p">,</span> <span class="mf">1.</span><span class="p">),</span> <span class="n">var</span><span class="p">)</span> <span class="k">for</span> <span class="n">grad</span><span class="p">,</span> <span class="n">var</span> <span class="ow">in</span> <span class="n">gradients</span> <span class="k">if</span> <span class="n">grad</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">]</span>
        <span class="n">train_op</span> <span class="o">=</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">apply_gradients</span><span class="p">(</span><span class="n">capped_gradients</span><span class="p">)</span>
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<p>Batch and pad the source and target sequences</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
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<span class="k">def</span> <span class="nf">pad_sentence_batch</span><span class="p">(</span><span class="n">sentence_batch</span><span class="p">,</span> <span class="n">pad_int</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Pad sentences with &lt;PAD&gt; so that each sentence of a batch has the same length&quot;&quot;&quot;</span>
    <span class="n">max_sentence</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">sentence</span><span class="p">)</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">sentence_batch</span><span class="p">])</span>
    <span class="k">return</span> <span class="p">[</span><span class="n">sentence</span> <span class="o">+</span> <span class="p">[</span><span class="n">pad_int</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="n">max_sentence</span> <span class="o">-</span> <span class="nb">len</span><span class="p">(</span><span class="n">sentence</span><span class="p">))</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">sentence_batch</span><span class="p">]</span>


<span class="k">def</span> <span class="nf">get_batches</span><span class="p">(</span><span class="n">sources</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">source_pad_int</span><span class="p">,</span> <span class="n">target_pad_int</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Batch targets, sources, and the lengths of their sentences together&quot;&quot;&quot;</span>
    <span class="k">for</span> <span class="n">batch_i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sources</span><span class="p">)</span><span class="o">//</span><span class="n">batch_size</span><span class="p">):</span>
        <span class="n">start_i</span> <span class="o">=</span> <span class="n">batch_i</span> <span class="o">*</span> <span class="n">batch_size</span>

        <span class="c1"># Slice the right amount for the batch</span>
        <span class="n">sources_batch</span> <span class="o">=</span> <span class="n">sources</span><span class="p">[</span><span class="n">start_i</span><span class="p">:</span><span class="n">start_i</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
        <span class="n">targets_batch</span> <span class="o">=</span> <span class="n">targets</span><span class="p">[</span><span class="n">start_i</span><span class="p">:</span><span class="n">start_i</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>

        <span class="c1"># Pad</span>
        <span class="n">pad_sources_batch</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">pad_sentence_batch</span><span class="p">(</span><span class="n">sources_batch</span><span class="p">,</span> <span class="n">source_pad_int</span><span class="p">))</span>
        <span class="n">pad_targets_batch</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">pad_sentence_batch</span><span class="p">(</span><span class="n">targets_batch</span><span class="p">,</span> <span class="n">target_pad_int</span><span class="p">))</span>

        <span class="c1"># Need the lengths for the _lengths parameters</span>
        <span class="n">pad_targets_lengths</span> <span class="o">=</span> <span class="p">[]</span>
        <span class="k">for</span> <span class="n">target</span> <span class="ow">in</span> <span class="n">pad_targets_batch</span><span class="p">:</span>
            <span class="n">pad_targets_lengths</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">target</span><span class="p">))</span>

        <span class="n">pad_source_lengths</span> <span class="o">=</span> <span class="p">[]</span>
        <span class="k">for</span> <span class="n">source</span> <span class="ow">in</span> <span class="n">pad_sources_batch</span><span class="p">:</span>
            <span class="n">pad_source_lengths</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">source</span><span class="p">))</span>

        <span class="k">yield</span> <span class="n">pad_sources_batch</span><span class="p">,</span> <span class="n">pad_targets_batch</span><span class="p">,</span> <span class="n">pad_source_lengths</span><span class="p">,</span> <span class="n">pad_targets_lengths</span>
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<h3 id="Train">Train<a class="anchor-link" href="#Train">&#182;</a></h3><p>Train the neural network on the preprocessed data. If you have a hard time getting a good loss, check the forms to see if anyone is having the same problem.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">get_accuracy</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="n">logits</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Calculate accuracy</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">max_seq</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">target</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">logits</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">if</span> <span class="n">max_seq</span> <span class="o">-</span> <span class="n">target</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">target</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span>
            <span class="n">target</span><span class="p">,</span>
            <span class="p">[(</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">),(</span><span class="mi">0</span><span class="p">,</span><span class="n">max_seq</span> <span class="o">-</span> <span class="n">target</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="s1">&#39;constant&#39;</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">max_seq</span> <span class="o">-</span> <span class="n">logits</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">logits</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span>
            <span class="n">logits</span><span class="p">,</span>
            <span class="p">[(</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">),(</span><span class="mi">0</span><span class="p">,</span><span class="n">max_seq</span> <span class="o">-</span> <span class="n">logits</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="s1">&#39;constant&#39;</span><span class="p">)</span>

    <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">equal</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="n">logits</span><span class="p">))</span>

<span class="c1"># Split data to training and validation sets</span>
<span class="n">train_source</span> <span class="o">=</span> <span class="n">source_int_text</span><span class="p">[</span><span class="n">batch_size</span><span class="p">:]</span>
<span class="n">train_target</span> <span class="o">=</span> <span class="n">target_int_text</span><span class="p">[</span><span class="n">batch_size</span><span class="p">:]</span>
<span class="n">valid_source</span> <span class="o">=</span> <span class="n">source_int_text</span><span class="p">[:</span><span class="n">batch_size</span><span class="p">]</span>
<span class="n">valid_target</span> <span class="o">=</span> <span class="n">target_int_text</span><span class="p">[:</span><span class="n">batch_size</span><span class="p">]</span>
<span class="p">(</span><span class="n">valid_sources_batch</span><span class="p">,</span> <span class="n">valid_targets_batch</span><span class="p">,</span> <span class="n">valid_sources_lengths</span><span class="p">,</span> <span class="n">valid_targets_lengths</span> <span class="p">)</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="n">get_batches</span><span class="p">(</span><span class="n">valid_source</span><span class="p">,</span>
                                                                                                             <span class="n">valid_target</span><span class="p">,</span>
                                                                                                             <span class="n">batch_size</span><span class="p">,</span>
                                                                                                             <span class="n">source_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;PAD&gt;&#39;</span><span class="p">],</span>
                                                                                                             <span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;PAD&gt;&#39;</span><span class="p">]))</span>                                                                                                  
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">(</span><span class="n">graph</span><span class="o">=</span><span class="n">train_graph</span><span class="p">)</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">global_variables_initializer</span><span class="p">())</span>

    <span class="k">for</span> <span class="n">epoch_i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">epochs</span><span class="p">):</span>
        <span class="k">for</span> <span class="n">batch_i</span><span class="p">,</span> <span class="p">(</span><span class="n">source_batch</span><span class="p">,</span> <span class="n">target_batch</span><span class="p">,</span> <span class="n">sources_lengths</span><span class="p">,</span> <span class="n">targets_lengths</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span>
                <span class="n">get_batches</span><span class="p">(</span><span class="n">train_source</span><span class="p">,</span> <span class="n">train_target</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span>
                            <span class="n">source_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;PAD&gt;&#39;</span><span class="p">],</span>
                            <span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;PAD&gt;&#39;</span><span class="p">])):</span>

            <span class="n">_</span><span class="p">,</span> <span class="n">loss</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span>
                <span class="p">[</span><span class="n">train_op</span><span class="p">,</span> <span class="n">cost</span><span class="p">],</span>
                <span class="p">{</span><span class="n">input_data</span><span class="p">:</span> <span class="n">source_batch</span><span class="p">,</span>
                 <span class="n">targets</span><span class="p">:</span> <span class="n">target_batch</span><span class="p">,</span>
                 <span class="n">lr</span><span class="p">:</span> <span class="n">learning_rate</span><span class="p">,</span>
                 <span class="n">target_sequence_length</span><span class="p">:</span> <span class="n">targets_lengths</span><span class="p">,</span>
                 <span class="n">source_sequence_length</span><span class="p">:</span> <span class="n">sources_lengths</span><span class="p">,</span>
                 <span class="n">keep_prob</span><span class="p">:</span> <span class="n">keep_probability</span><span class="p">})</span>


            <span class="k">if</span> <span class="n">batch_i</span> <span class="o">%</span> <span class="n">display_step</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">and</span> <span class="n">batch_i</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>


                <span class="n">batch_train_logits</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span>
                    <span class="n">inference_logits</span><span class="p">,</span>
                    <span class="p">{</span><span class="n">input_data</span><span class="p">:</span> <span class="n">source_batch</span><span class="p">,</span>
                     <span class="n">source_sequence_length</span><span class="p">:</span> <span class="n">sources_lengths</span><span class="p">,</span>
                     <span class="n">target_sequence_length</span><span class="p">:</span> <span class="n">targets_lengths</span><span class="p">,</span>
                     <span class="n">keep_prob</span><span class="p">:</span> <span class="mf">1.0</span><span class="p">})</span>


                <span class="n">batch_valid_logits</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span>
                    <span class="n">inference_logits</span><span class="p">,</span>
                    <span class="p">{</span><span class="n">input_data</span><span class="p">:</span> <span class="n">valid_sources_batch</span><span class="p">,</span>
                     <span class="n">source_sequence_length</span><span class="p">:</span> <span class="n">valid_sources_lengths</span><span class="p">,</span>
                     <span class="n">target_sequence_length</span><span class="p">:</span> <span class="n">valid_targets_lengths</span><span class="p">,</span>
                     <span class="n">keep_prob</span><span class="p">:</span> <span class="mf">1.0</span><span class="p">})</span>

                <span class="n">train_acc</span> <span class="o">=</span> <span class="n">get_accuracy</span><span class="p">(</span><span class="n">target_batch</span><span class="p">,</span> <span class="n">batch_train_logits</span><span class="p">)</span>

                <span class="n">valid_acc</span> <span class="o">=</span> <span class="n">get_accuracy</span><span class="p">(</span><span class="n">valid_targets_batch</span><span class="p">,</span> <span class="n">batch_valid_logits</span><span class="p">)</span>

                <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Epoch </span><span class="si">{:&gt;3}</span><span class="s1"> Batch </span><span class="si">{:&gt;4}</span><span class="s1">/</span><span class="si">{}</span><span class="s1"> - Train Accuracy: </span><span class="si">{:&gt;6.4f}</span><span class="s1">, Validation Accuracy: </span><span class="si">{:&gt;6.4f}</span><span class="s1">, Loss: </span><span class="si">{:&gt;6.4f}</span><span class="s1">&#39;</span>
                      <span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">epoch_i</span><span class="p">,</span> <span class="n">batch_i</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">source_int_text</span><span class="p">)</span> <span class="o">//</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">train_acc</span><span class="p">,</span> <span class="n">valid_acc</span><span class="p">,</span> <span class="n">loss</span><span class="p">))</span>

    <span class="c1"># Save Model</span>
    <span class="n">saver</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">Saver</span><span class="p">()</span>
    <span class="n">saver</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">save_path</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Model Trained and Saved&#39;</span><span class="p">)</span>
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<pre>Epoch   0 Batch   16/1077 - Train Accuracy: 0.2883, Validation Accuracy: 0.3363, Loss: 3.2891
Epoch   0 Batch   32/1077 - Train Accuracy: 0.4022, Validation Accuracy: 0.4148, Loss: 2.7788
Epoch   0 Batch   48/1077 - Train Accuracy: 0.4105, Validation Accuracy: 0.4549, Loss: 2.6523
Epoch   0 Batch   64/1077 - Train Accuracy: 0.4066, Validation Accuracy: 0.4702, Loss: 2.5039
Epoch   0 Batch   80/1077 - Train Accuracy: 0.4402, Validation Accuracy: 0.4940, Loss: 2.3081
Epoch   0 Batch   96/1077 - Train Accuracy: 0.4512, Validation Accuracy: 0.4961, Loss: 2.1869
Epoch   0 Batch  112/1077 - Train Accuracy: 0.4410, Validation Accuracy: 0.4925, Loss: 2.1360
Epoch   0 Batch  128/1077 - Train Accuracy: 0.5052, Validation Accuracy: 0.5075, Loss: 1.8937
Epoch   0 Batch  144/1077 - Train Accuracy: 0.4622, Validation Accuracy: 0.5288, Loss: 1.9959
Epoch   0 Batch  160/1077 - Train Accuracy: 0.5020, Validation Accuracy: 0.5291, Loss: 1.7860
Epoch   0 Batch  176/1077 - Train Accuracy: 0.4727, Validation Accuracy: 0.5259, Loss: 1.6053
Epoch   0 Batch  192/1077 - Train Accuracy: 0.5059, Validation Accuracy: 0.5263, Loss: 1.4594
Epoch   0 Batch  208/1077 - Train Accuracy: 0.4498, Validation Accuracy: 0.4989, Loss: 1.2631
Epoch   0 Batch  224/1077 - Train Accuracy: 0.4703, Validation Accuracy: 0.4996, Loss: 1.1904
Epoch   0 Batch  240/1077 - Train Accuracy: 0.5055, Validation Accuracy: 0.5316, Loss: 1.0460
Epoch   0 Batch  256/1077 - Train Accuracy: 0.4770, Validation Accuracy: 0.5210, Loss: 1.0518
Epoch   0 Batch  272/1077 - Train Accuracy: 0.4877, Validation Accuracy: 0.5234, Loss: 0.9706
Epoch   0 Batch  288/1077 - Train Accuracy: 0.5141, Validation Accuracy: 0.5547, Loss: 0.9462
Epoch   0 Batch  304/1077 - Train Accuracy: 0.5316, Validation Accuracy: 0.5661, Loss: 0.8284
Epoch   0 Batch  320/1077 - Train Accuracy: 0.5496, Validation Accuracy: 0.5455, Loss: 0.8488
Epoch   0 Batch  336/1077 - Train Accuracy: 0.5293, Validation Accuracy: 0.5423, Loss: 0.8362
Epoch   0 Batch  352/1077 - Train Accuracy: 0.5109, Validation Accuracy: 0.5859, Loss: 0.8096
Epoch   0 Batch  368/1077 - Train Accuracy: 0.5656, Validation Accuracy: 0.5831, Loss: 0.7817
Epoch   0 Batch  384/1077 - Train Accuracy: 0.5570, Validation Accuracy: 0.6090, Loss: 0.7443
Epoch   0 Batch  400/1077 - Train Accuracy: 0.5719, Validation Accuracy: 0.5692, Loss: 0.7379
Epoch   0 Batch  416/1077 - Train Accuracy: 0.5840, Validation Accuracy: 0.5952, Loss: 0.7081
Epoch   0 Batch  432/1077 - Train Accuracy: 0.5945, Validation Accuracy: 0.5895, Loss: 0.7050
Epoch   0 Batch  448/1077 - Train Accuracy: 0.5730, Validation Accuracy: 0.5955, Loss: 0.6902
Epoch   0 Batch  464/1077 - Train Accuracy: 0.6289, Validation Accuracy: 0.6225, Loss: 0.6561
Epoch   0 Batch  480/1077 - Train Accuracy: 0.6118, Validation Accuracy: 0.6090, Loss: 0.6544
Epoch   0 Batch  496/1077 - Train Accuracy: 0.5938, Validation Accuracy: 0.6232, Loss: 0.6591
Epoch   0 Batch  512/1077 - Train Accuracy: 0.6184, Validation Accuracy: 0.5973, Loss: 0.6217
Epoch   0 Batch  528/1077 - Train Accuracy: 0.6137, Validation Accuracy: 0.6072, Loss: 0.6081
Epoch   0 Batch  544/1077 - Train Accuracy: 0.6199, Validation Accuracy: 0.6257, Loss: 0.5985
Epoch   0 Batch  560/1077 - Train Accuracy: 0.5758, Validation Accuracy: 0.6456, Loss: 0.5852
Epoch   0 Batch  576/1077 - Train Accuracy: 0.6542, Validation Accuracy: 0.6548, Loss: 0.6032
Epoch   0 Batch  592/1077 - Train Accuracy: 0.6227, Validation Accuracy: 0.6417, Loss: 0.5784
Epoch   0 Batch  608/1077 - Train Accuracy: 0.6098, Validation Accuracy: 0.6662, Loss: 0.5812
Epoch   0 Batch  624/1077 - Train Accuracy: 0.6670, Validation Accuracy: 0.6641, Loss: 0.5287
Epoch   0 Batch  640/1077 - Train Accuracy: 0.6291, Validation Accuracy: 0.6598, Loss: 0.5292
Epoch   0 Batch  656/1077 - Train Accuracy: 0.6227, Validation Accuracy: 0.6562, Loss: 0.5340
Epoch   0 Batch  672/1077 - Train Accuracy: 0.6466, Validation Accuracy: 0.6690, Loss: 0.5046
Epoch   0 Batch  688/1077 - Train Accuracy: 0.6527, Validation Accuracy: 0.6687, Loss: 0.5170
Epoch   0 Batch  704/1077 - Train Accuracy: 0.6270, Validation Accuracy: 0.6431, Loss: 0.5253
Epoch   0 Batch  720/1077 - Train Accuracy: 0.6476, Validation Accuracy: 0.6406, Loss: 0.5348
Epoch   0 Batch  736/1077 - Train Accuracy: 0.6669, Validation Accuracy: 0.6527, Loss: 0.4850
Epoch   0 Batch  752/1077 - Train Accuracy: 0.6503, Validation Accuracy: 0.6420, Loss: 0.4538
Epoch   0 Batch  768/1077 - Train Accuracy: 0.6773, Validation Accuracy: 0.6747, Loss: 0.4697
Epoch   0 Batch  784/1077 - Train Accuracy: 0.6883, Validation Accuracy: 0.6644, Loss: 0.4527
Epoch   0 Batch  800/1077 - Train Accuracy: 0.6301, Validation Accuracy: 0.6577, Loss: 0.4704
Epoch   0 Batch  816/1077 - Train Accuracy: 0.6887, Validation Accuracy: 0.6609, Loss: 0.4856
Epoch   0 Batch  832/1077 - Train Accuracy: 0.6562, Validation Accuracy: 0.6619, Loss: 0.4536
Epoch   0 Batch  848/1077 - Train Accuracy: 0.6898, Validation Accuracy: 0.6619, Loss: 0.4493
Epoch   0 Batch  864/1077 - Train Accuracy: 0.6820, Validation Accuracy: 0.6626, Loss: 0.4345
Epoch   0 Batch  880/1077 - Train Accuracy: 0.7160, Validation Accuracy: 0.6580, Loss: 0.4342
Epoch   0 Batch  896/1077 - Train Accuracy: 0.6398, Validation Accuracy: 0.6658, Loss: 0.4434
Epoch   0 Batch  912/1077 - Train Accuracy: 0.6605, Validation Accuracy: 0.6602, Loss: 0.4300
Epoch   0 Batch  928/1077 - Train Accuracy: 0.7078, Validation Accuracy: 0.6538, Loss: 0.4175
Epoch   0 Batch  944/1077 - Train Accuracy: 0.6886, Validation Accuracy: 0.6598, Loss: 0.4112
Epoch   0 Batch  960/1077 - Train Accuracy: 0.6778, Validation Accuracy: 0.6609, Loss: 0.3862
Epoch   0 Batch  976/1077 - Train Accuracy: 0.6723, Validation Accuracy: 0.6634, Loss: 0.3854
Epoch   0 Batch  992/1077 - Train Accuracy: 0.6984, Validation Accuracy: 0.6896, Loss: 0.4013
Epoch   0 Batch 1008/1077 - Train Accuracy: 0.7246, Validation Accuracy: 0.6694, Loss: 0.4076
Epoch   0 Batch 1024/1077 - Train Accuracy: 0.7000, Validation Accuracy: 0.6893, Loss: 0.3939
Epoch   0 Batch 1040/1077 - Train Accuracy: 0.7340, Validation Accuracy: 0.6996, Loss: 0.4005
Epoch   0 Batch 1056/1077 - Train Accuracy: 0.7332, Validation Accuracy: 0.6953, Loss: 0.3675
Epoch   0 Batch 1072/1077 - Train Accuracy: 0.7396, Validation Accuracy: 0.7099, Loss: 0.3646
Epoch   1 Batch   16/1077 - Train Accuracy: 0.7195, Validation Accuracy: 0.7095, Loss: 0.3668
Epoch   1 Batch   32/1077 - Train Accuracy: 0.7385, Validation Accuracy: 0.7053, Loss: 0.3393
Epoch   1 Batch   48/1077 - Train Accuracy: 0.6953, Validation Accuracy: 0.7035, Loss: 0.3756
Epoch   1 Batch   64/1077 - Train Accuracy: 0.6676, Validation Accuracy: 0.6882, Loss: 0.3429
Epoch   1 Batch   80/1077 - Train Accuracy: 0.7227, Validation Accuracy: 0.7170, Loss: 0.3504
Epoch   1 Batch   96/1077 - Train Accuracy: 0.7055, Validation Accuracy: 0.7177, Loss: 0.3392
Epoch   1 Batch  112/1077 - Train Accuracy: 0.7121, Validation Accuracy: 0.7145, Loss: 0.3343
Epoch   1 Batch  128/1077 - Train Accuracy: 0.7623, Validation Accuracy: 0.7234, Loss: 0.3160
Epoch   1 Batch  144/1077 - Train Accuracy: 0.7064, Validation Accuracy: 0.7273, Loss: 0.3763
Epoch   1 Batch  160/1077 - Train Accuracy: 0.7430, Validation Accuracy: 0.7148, Loss: 0.3353
Epoch   1 Batch  176/1077 - Train Accuracy: 0.7316, Validation Accuracy: 0.7088, Loss: 0.3216
Epoch   1 Batch  192/1077 - Train Accuracy: 0.7523, Validation Accuracy: 0.7273, Loss: 0.3351
Epoch   1 Batch  208/1077 - Train Accuracy: 0.7533, Validation Accuracy: 0.7337, Loss: 0.3029
Epoch   1 Batch  224/1077 - Train Accuracy: 0.7609, Validation Accuracy: 0.7486, Loss: 0.3286
Epoch   1 Batch  240/1077 - Train Accuracy: 0.7844, Validation Accuracy: 0.7429, Loss: 0.3077
Epoch   1 Batch  256/1077 - Train Accuracy: 0.7121, Validation Accuracy: 0.7347, Loss: 0.3280
Epoch   1 Batch  272/1077 - Train Accuracy: 0.7039, Validation Accuracy: 0.7418, Loss: 0.3370
Epoch   1 Batch  288/1077 - Train Accuracy: 0.7348, Validation Accuracy: 0.7276, Loss: 0.3325
Epoch   1 Batch  304/1077 - Train Accuracy: 0.7161, Validation Accuracy: 0.7230, Loss: 0.2813
Epoch   1 Batch  320/1077 - Train Accuracy: 0.7785, Validation Accuracy: 0.7408, Loss: 0.3061
Epoch   1 Batch  336/1077 - Train Accuracy: 0.7316, Validation Accuracy: 0.7319, Loss: 0.3253
Epoch   1 Batch  352/1077 - Train Accuracy: 0.7344, Validation Accuracy: 0.7511, Loss: 0.2859
Epoch   1 Batch  368/1077 - Train Accuracy: 0.7871, Validation Accuracy: 0.7322, Loss: 0.2782
Epoch   1 Batch  384/1077 - Train Accuracy: 0.7543, Validation Accuracy: 0.7614, Loss: 0.2695
Epoch   1 Batch  400/1077 - Train Accuracy: 0.8145, Validation Accuracy: 0.7560, Loss: 0.2849
Epoch   1 Batch  416/1077 - Train Accuracy: 0.7695, Validation Accuracy: 0.7543, Loss: 0.2710
Epoch   1 Batch  432/1077 - Train Accuracy: 0.7887, Validation Accuracy: 0.7539, Loss: 0.2581
Epoch   1 Batch  448/1077 - Train Accuracy: 0.7590, Validation Accuracy: 0.7500, Loss: 0.2687
Epoch   1 Batch  464/1077 - Train Accuracy: 0.7789, Validation Accuracy: 0.7592, Loss: 0.2652
Epoch   1 Batch  480/1077 - Train Accuracy: 0.7866, Validation Accuracy: 0.7525, Loss: 0.2565
Epoch   1 Batch  496/1077 - Train Accuracy: 0.7410, Validation Accuracy: 0.7766, Loss: 0.2435
Epoch   1 Batch  512/1077 - Train Accuracy: 0.7742, Validation Accuracy: 0.7585, Loss: 0.2384
Epoch   1 Batch  528/1077 - Train Accuracy: 0.7867, Validation Accuracy: 0.7635, Loss: 0.2458
Epoch   1 Batch  544/1077 - Train Accuracy: 0.8102, Validation Accuracy: 0.7681, Loss: 0.2286
Epoch   1 Batch  560/1077 - Train Accuracy: 0.7988, Validation Accuracy: 0.7678, Loss: 0.2290
Epoch   1 Batch  576/1077 - Train Accuracy: 0.8088, Validation Accuracy: 0.7599, Loss: 0.2347
Epoch   1 Batch  592/1077 - Train Accuracy: 0.7852, Validation Accuracy: 0.7802, Loss: 0.2320
Epoch   1 Batch  608/1077 - Train Accuracy: 0.7816, Validation Accuracy: 0.7766, Loss: 0.2484
Epoch   1 Batch  624/1077 - Train Accuracy: 0.7939, Validation Accuracy: 0.7649, Loss: 0.2192
Epoch   1 Batch  640/1077 - Train Accuracy: 0.7846, Validation Accuracy: 0.7784, Loss: 0.2189
Epoch   1 Batch  656/1077 - Train Accuracy: 0.7582, Validation Accuracy: 0.7820, Loss: 0.2279
Epoch   1 Batch  672/1077 - Train Accuracy: 0.7820, Validation Accuracy: 0.7805, Loss: 0.2090
Epoch   1 Batch  688/1077 - Train Accuracy: 0.8074, Validation Accuracy: 0.7816, Loss: 0.2131
Epoch   1 Batch  704/1077 - Train Accuracy: 0.7820, Validation Accuracy: 0.7852, Loss: 0.2363
Epoch   1 Batch  720/1077 - Train Accuracy: 0.8244, Validation Accuracy: 0.8072, Loss: 0.2246
Epoch   1 Batch  736/1077 - Train Accuracy: 0.8133, Validation Accuracy: 0.7692, Loss: 0.1915
Epoch   1 Batch  752/1077 - Train Accuracy: 0.8025, Validation Accuracy: 0.7876, Loss: 0.1938
Epoch   1 Batch  768/1077 - Train Accuracy: 0.7883, Validation Accuracy: 0.8061, Loss: 0.2026
Epoch   1 Batch  784/1077 - Train Accuracy: 0.8164, Validation Accuracy: 0.7653, Loss: 0.1927
Epoch   1 Batch  800/1077 - Train Accuracy: 0.8086, Validation Accuracy: 0.7827, Loss: 0.2012
Epoch   1 Batch  816/1077 - Train Accuracy: 0.8183, Validation Accuracy: 0.7823, Loss: 0.2155
Epoch   1 Batch  832/1077 - Train Accuracy: 0.8035, Validation Accuracy: 0.7741, Loss: 0.1883
Epoch   1 Batch  848/1077 - Train Accuracy: 0.7883, Validation Accuracy: 0.8146, Loss: 0.1964
Epoch   1 Batch  864/1077 - Train Accuracy: 0.8117, Validation Accuracy: 0.7912, Loss: 0.1868
Epoch   1 Batch  880/1077 - Train Accuracy: 0.7695, Validation Accuracy: 0.7955, Loss: 0.2034
Epoch   1 Batch  896/1077 - Train Accuracy: 0.7812, Validation Accuracy: 0.7805, Loss: 0.1975
Epoch   1 Batch  912/1077 - Train Accuracy: 0.7750, Validation Accuracy: 0.7827, Loss: 0.1940
Epoch   1 Batch  928/1077 - Train Accuracy: 0.8301, Validation Accuracy: 0.8203, Loss: 0.2007
Epoch   1 Batch  944/1077 - Train Accuracy: 0.7965, Validation Accuracy: 0.7802, Loss: 0.1791
Epoch   1 Batch  960/1077 - Train Accuracy: 0.7943, Validation Accuracy: 0.7749, Loss: 0.1757
Epoch   1 Batch  976/1077 - Train Accuracy: 0.7801, Validation Accuracy: 0.7894, Loss: 0.1728
Epoch   1 Batch  992/1077 - Train Accuracy: 0.8395, Validation Accuracy: 0.8061, Loss: 0.1631
Epoch   1 Batch 1008/1077 - Train Accuracy: 0.8145, Validation Accuracy: 0.8200, Loss: 0.1954
Epoch   1 Batch 1024/1077 - Train Accuracy: 0.8172, Validation Accuracy: 0.7965, Loss: 0.1740
Epoch   1 Batch 1040/1077 - Train Accuracy: 0.8146, Validation Accuracy: 0.8100, Loss: 0.1694
Epoch   1 Batch 1056/1077 - Train Accuracy: 0.8453, Validation Accuracy: 0.8111, Loss: 0.1566
Epoch   1 Batch 1072/1077 - Train Accuracy: 0.8214, Validation Accuracy: 0.8036, Loss: 0.1574
Epoch   2 Batch   16/1077 - Train Accuracy: 0.7965, Validation Accuracy: 0.8036, Loss: 0.1686
Epoch   2 Batch   32/1077 - Train Accuracy: 0.8214, Validation Accuracy: 0.8210, Loss: 0.1651
Epoch   2 Batch   48/1077 - Train Accuracy: 0.7949, Validation Accuracy: 0.8146, Loss: 0.1867
Epoch   2 Batch   64/1077 - Train Accuracy: 0.8141, Validation Accuracy: 0.8217, Loss: 0.1379
Epoch   2 Batch   80/1077 - Train Accuracy: 0.8180, Validation Accuracy: 0.8072, Loss: 0.1518
Epoch   2 Batch   96/1077 - Train Accuracy: 0.8156, Validation Accuracy: 0.8288, Loss: 0.1562
Epoch   2 Batch  112/1077 - Train Accuracy: 0.8129, Validation Accuracy: 0.8111, Loss: 0.1416
Epoch   2 Batch  128/1077 - Train Accuracy: 0.8571, Validation Accuracy: 0.7816, Loss: 0.1395
Epoch   2 Batch  144/1077 - Train Accuracy: 0.8203, Validation Accuracy: 0.7997, Loss: 0.1758
Epoch   2 Batch  160/1077 - Train Accuracy: 0.8273, Validation Accuracy: 0.8175, Loss: 0.1379
Epoch   2 Batch  176/1077 - Train Accuracy: 0.8055, Validation Accuracy: 0.8136, Loss: 0.1433
Epoch   2 Batch  192/1077 - Train Accuracy: 0.8293, Validation Accuracy: 0.8317, Loss: 0.1410
Epoch   2 Batch  208/1077 - Train Accuracy: 0.8441, Validation Accuracy: 0.8260, Loss: 0.1370
Epoch   2 Batch  224/1077 - Train Accuracy: 0.8418, Validation Accuracy: 0.8026, Loss: 0.1507
Epoch   2 Batch  240/1077 - Train Accuracy: 0.8809, Validation Accuracy: 0.8406, Loss: 0.1445
Epoch   2 Batch  256/1077 - Train Accuracy: 0.8180, Validation Accuracy: 0.8356, Loss: 0.1519
Epoch   2 Batch  272/1077 - Train Accuracy: 0.8333, Validation Accuracy: 0.8324, Loss: 0.1732
Epoch   2 Batch  288/1077 - Train Accuracy: 0.8734, Validation Accuracy: 0.8594, Loss: 0.1513
Epoch   2 Batch  304/1077 - Train Accuracy: 0.8538, Validation Accuracy: 0.8345, Loss: 0.1275
Epoch   2 Batch  320/1077 - Train Accuracy: 0.8844, Validation Accuracy: 0.8516, Loss: 0.1283
Epoch   2 Batch  336/1077 - Train Accuracy: 0.8270, Validation Accuracy: 0.8537, Loss: 0.1524
Epoch   2 Batch  352/1077 - Train Accuracy: 0.8984, Validation Accuracy: 0.8413, Loss: 0.1162
Epoch   2 Batch  368/1077 - Train Accuracy: 0.8750, Validation Accuracy: 0.8683, Loss: 0.1209
Epoch   2 Batch  384/1077 - Train Accuracy: 0.8559, Validation Accuracy: 0.8665, Loss: 0.1148
Epoch   2 Batch  400/1077 - Train Accuracy: 0.8781, Validation Accuracy: 0.8800, Loss: 0.1382
Epoch   2 Batch  416/1077 - Train Accuracy: 0.8887, Validation Accuracy: 0.8821, Loss: 0.1280
Epoch   2 Batch  432/1077 - Train Accuracy: 0.9035, Validation Accuracy: 0.8697, Loss: 0.1125
Epoch   2 Batch  448/1077 - Train Accuracy: 0.8930, Validation Accuracy: 0.8619, Loss: 0.1204
Epoch   2 Batch  464/1077 - Train Accuracy: 0.8543, Validation Accuracy: 0.8892, Loss: 0.1178
Epoch   2 Batch  480/1077 - Train Accuracy: 0.8828, Validation Accuracy: 0.8722, Loss: 0.1076
Epoch   2 Batch  496/1077 - Train Accuracy: 0.8887, Validation Accuracy: 0.8857, Loss: 0.1090
Epoch   2 Batch  512/1077 - Train Accuracy: 0.8961, Validation Accuracy: 0.9002, Loss: 0.1066
Epoch   2 Batch  528/1077 - Train Accuracy: 0.8879, Validation Accuracy: 0.8828, Loss: 0.1124
Epoch   2 Batch  544/1077 - Train Accuracy: 0.8977, Validation Accuracy: 0.8771, Loss: 0.0869
Epoch   2 Batch  560/1077 - Train Accuracy: 0.8684, Validation Accuracy: 0.8793, Loss: 0.0976
Epoch   2 Batch  576/1077 - Train Accuracy: 0.8931, Validation Accuracy: 0.8633, Loss: 0.0976
Epoch   2 Batch  592/1077 - Train Accuracy: 0.9027, Validation Accuracy: 0.8853, Loss: 0.0950
Epoch   2 Batch  608/1077 - Train Accuracy: 0.8953, Validation Accuracy: 0.8853, Loss: 0.0997
Epoch   2 Batch  624/1077 - Train Accuracy: 0.8813, Validation Accuracy: 0.8707, Loss: 0.1087
Epoch   2 Batch  640/1077 - Train Accuracy: 0.8798, Validation Accuracy: 0.9023, Loss: 0.0903
Epoch   2 Batch  656/1077 - Train Accuracy: 0.9094, Validation Accuracy: 0.8977, Loss: 0.0958
Epoch   2 Batch  672/1077 - Train Accuracy: 0.8936, Validation Accuracy: 0.8864, Loss: 0.0917
Epoch   2 Batch  688/1077 - Train Accuracy: 0.8930, Validation Accuracy: 0.8888, Loss: 0.0967
Epoch   2 Batch  704/1077 - Train Accuracy: 0.8848, Validation Accuracy: 0.8714, Loss: 0.0973
Epoch   2 Batch  720/1077 - Train Accuracy: 0.8927, Validation Accuracy: 0.9031, Loss: 0.0978
Epoch   2 Batch  736/1077 - Train Accuracy: 0.9194, Validation Accuracy: 0.8800, Loss: 0.0783
Epoch   2 Batch  752/1077 - Train Accuracy: 0.8810, Validation Accuracy: 0.9027, Loss: 0.0945
Epoch   2 Batch  768/1077 - Train Accuracy: 0.8859, Validation Accuracy: 0.8924, Loss: 0.0861
Epoch   2 Batch  784/1077 - Train Accuracy: 0.9176, Validation Accuracy: 0.8654, Loss: 0.0825
Epoch   2 Batch  800/1077 - Train Accuracy: 0.8855, Validation Accuracy: 0.8913, Loss: 0.0907
Epoch   2 Batch  816/1077 - Train Accuracy: 0.9235, Validation Accuracy: 0.9055, Loss: 0.1028
Epoch   2 Batch  832/1077 - Train Accuracy: 0.9234, Validation Accuracy: 0.8967, Loss: 0.0754
Epoch   2 Batch  848/1077 - Train Accuracy: 0.9227, Validation Accuracy: 0.8981, Loss: 0.0777
Epoch   2 Batch  864/1077 - Train Accuracy: 0.8812, Validation Accuracy: 0.8771, Loss: 0.0863
Epoch   2 Batch  880/1077 - Train Accuracy: 0.9102, Validation Accuracy: 0.8896, Loss: 0.0938
Epoch   2 Batch  896/1077 - Train Accuracy: 0.9067, Validation Accuracy: 0.8878, Loss: 0.0917
Epoch   2 Batch  912/1077 - Train Accuracy: 0.9086, Validation Accuracy: 0.8803, Loss: 0.0753
Epoch   2 Batch  928/1077 - Train Accuracy: 0.8969, Validation Accuracy: 0.8952, Loss: 0.0910
Epoch   2 Batch  944/1077 - Train Accuracy: 0.9029, Validation Accuracy: 0.8828, Loss: 0.0695
Epoch   2 Batch  960/1077 - Train Accuracy: 0.8876, Validation Accuracy: 0.8924, Loss: 0.0682
Epoch   2 Batch  976/1077 - Train Accuracy: 0.9199, Validation Accuracy: 0.9091, Loss: 0.0723
Epoch   2 Batch  992/1077 - Train Accuracy: 0.9379, Validation Accuracy: 0.9091, Loss: 0.0766
Epoch   2 Batch 1008/1077 - Train Accuracy: 0.9246, Validation Accuracy: 0.8743, Loss: 0.0966
Epoch   2 Batch 1024/1077 - Train Accuracy: 0.8684, Validation Accuracy: 0.9137, Loss: 0.0786
Epoch   2 Batch 1040/1077 - Train Accuracy: 0.8997, Validation Accuracy: 0.9006, Loss: 0.0812
Epoch   2 Batch 1056/1077 - Train Accuracy: 0.8941, Validation Accuracy: 0.9052, Loss: 0.0742
Epoch   2 Batch 1072/1077 - Train Accuracy: 0.9234, Validation Accuracy: 0.9087, Loss: 0.0719
Epoch   3 Batch   16/1077 - Train Accuracy: 0.8762, Validation Accuracy: 0.8963, Loss: 0.0841
Epoch   3 Batch   32/1077 - Train Accuracy: 0.9107, Validation Accuracy: 0.9038, Loss: 0.0804
Epoch   3 Batch   48/1077 - Train Accuracy: 0.8988, Validation Accuracy: 0.9098, Loss: 0.0944
Epoch   3 Batch   64/1077 - Train Accuracy: 0.9086, Validation Accuracy: 0.9045, Loss: 0.0612
Epoch   3 Batch   80/1077 - Train Accuracy: 0.9281, Validation Accuracy: 0.9123, Loss: 0.0777
Epoch   3 Batch   96/1077 - Train Accuracy: 0.8895, Validation Accuracy: 0.9006, Loss: 0.0891
Epoch   3 Batch  112/1077 - Train Accuracy: 0.9125, Validation Accuracy: 0.9130, Loss: 0.0592
Epoch   3 Batch  128/1077 - Train Accuracy: 0.9431, Validation Accuracy: 0.9073, Loss: 0.0580
Epoch   3 Batch  144/1077 - Train Accuracy: 0.9157, Validation Accuracy: 0.8807, Loss: 0.0921
Epoch   3 Batch  160/1077 - Train Accuracy: 0.8984, Validation Accuracy: 0.8885, Loss: 0.0615
Epoch   3 Batch  176/1077 - Train Accuracy: 0.9102, Validation Accuracy: 0.9169, Loss: 0.0630
Epoch   3 Batch  192/1077 - Train Accuracy: 0.9309, Validation Accuracy: 0.8974, Loss: 0.0659
Epoch   3 Batch  208/1077 - Train Accuracy: 0.9044, Validation Accuracy: 0.8981, Loss: 0.0685
Epoch   3 Batch  224/1077 - Train Accuracy: 0.9254, Validation Accuracy: 0.9080, Loss: 0.0761
Epoch   3 Batch  240/1077 - Train Accuracy: 0.9320, Validation Accuracy: 0.9265, Loss: 0.0705
Epoch   3 Batch  256/1077 - Train Accuracy: 0.9020, Validation Accuracy: 0.8903, Loss: 0.0898
Epoch   3 Batch  272/1077 - Train Accuracy: 0.9137, Validation Accuracy: 0.9130, Loss: 0.0942
Epoch   3 Batch  288/1077 - Train Accuracy: 0.9094, Validation Accuracy: 0.9066, Loss: 0.0770
Epoch   3 Batch  304/1077 - Train Accuracy: 0.9081, Validation Accuracy: 0.8871, Loss: 0.0779
Epoch   3 Batch  320/1077 - Train Accuracy: 0.9023, Validation Accuracy: 0.8984, Loss: 0.0656
Epoch   3 Batch  336/1077 - Train Accuracy: 0.8891, Validation Accuracy: 0.8832, Loss: 0.0980
Epoch   3 Batch  352/1077 - Train Accuracy: 0.9355, Validation Accuracy: 0.9013, Loss: 0.0603
Epoch   3 Batch  368/1077 - Train Accuracy: 0.9363, Validation Accuracy: 0.8885, Loss: 0.0715
Epoch   3 Batch  384/1077 - Train Accuracy: 0.8996, Validation Accuracy: 0.9187, Loss: 0.0583
Epoch   3 Batch  400/1077 - Train Accuracy: 0.9254, Validation Accuracy: 0.9190, Loss: 0.0702
Epoch   3 Batch  416/1077 - Train Accuracy: 0.9348, Validation Accuracy: 0.9162, Loss: 0.0608
Epoch   3 Batch  432/1077 - Train Accuracy: 0.9062, Validation Accuracy: 0.8981, Loss: 0.0598
Epoch   3 Batch  448/1077 - Train Accuracy: 0.9262, Validation Accuracy: 0.8984, Loss: 0.0706
Epoch   3 Batch  464/1077 - Train Accuracy: 0.9113, Validation Accuracy: 0.9087, Loss: 0.0645
Epoch   3 Batch  480/1077 - Train Accuracy: 0.9178, Validation Accuracy: 0.8984, Loss: 0.0710
Epoch   3 Batch  496/1077 - Train Accuracy: 0.9105, Validation Accuracy: 0.9158, Loss: 0.0579
Epoch   3 Batch  512/1077 - Train Accuracy: 0.9375, Validation Accuracy: 0.8981, Loss: 0.0595
Epoch   3 Batch  528/1077 - Train Accuracy: 0.9102, Validation Accuracy: 0.8963, Loss: 0.0764
Epoch   3 Batch  544/1077 - Train Accuracy: 0.9336, Validation Accuracy: 0.8793, Loss: 0.0409
Epoch   3 Batch  560/1077 - Train Accuracy: 0.9195, Validation Accuracy: 0.9105, Loss: 0.0583
Epoch   3 Batch  576/1077 - Train Accuracy: 0.9330, Validation Accuracy: 0.8938, Loss: 0.0596
Epoch   3 Batch  592/1077 - Train Accuracy: 0.9152, Validation Accuracy: 0.8991, Loss: 0.0626
Epoch   3 Batch  608/1077 - Train Accuracy: 0.9301, Validation Accuracy: 0.9041, Loss: 0.0758
Epoch   3 Batch  624/1077 - Train Accuracy: 0.8899, Validation Accuracy: 0.9134, Loss: 0.0729
Epoch   3 Batch  640/1077 - Train Accuracy: 0.9263, Validation Accuracy: 0.9258, Loss: 0.0552
Epoch   3 Batch  656/1077 - Train Accuracy: 0.9137, Validation Accuracy: 0.8991, Loss: 0.0608
Epoch   3 Batch  672/1077 - Train Accuracy: 0.9301, Validation Accuracy: 0.9141, Loss: 0.0568
Epoch   3 Batch  688/1077 - Train Accuracy: 0.9453, Validation Accuracy: 0.8970, Loss: 0.0619
Epoch   3 Batch  704/1077 - Train Accuracy: 0.9039, Validation Accuracy: 0.9180, Loss: 0.0767
Epoch   3 Batch  720/1077 - Train Accuracy: 0.9264, Validation Accuracy: 0.9158, Loss: 0.0634
Epoch   3 Batch  736/1077 - Train Accuracy: 0.9494, Validation Accuracy: 0.9055, Loss: 0.0573
Epoch   3 Batch  752/1077 - Train Accuracy: 0.9241, Validation Accuracy: 0.9197, Loss: 0.0676
Epoch   3 Batch  768/1077 - Train Accuracy: 0.8938, Validation Accuracy: 0.8821, Loss: 0.0684
Epoch   3 Batch  784/1077 - Train Accuracy: 0.9227, Validation Accuracy: 0.9073, Loss: 0.0534
Epoch   3 Batch  800/1077 - Train Accuracy: 0.9195, Validation Accuracy: 0.9023, Loss: 0.0633
Epoch   3 Batch  816/1077 - Train Accuracy: 0.9301, Validation Accuracy: 0.9155, Loss: 0.0776
Epoch   3 Batch  832/1077 - Train Accuracy: 0.9230, Validation Accuracy: 0.9009, Loss: 0.0514
Epoch   3 Batch  848/1077 - Train Accuracy: 0.9418, Validation Accuracy: 0.9016, Loss: 0.0515
Epoch   3 Batch  864/1077 - Train Accuracy: 0.9090, Validation Accuracy: 0.9034, Loss: 0.0622
Epoch   3 Batch  880/1077 - Train Accuracy: 0.9285, Validation Accuracy: 0.9162, Loss: 0.0701
Epoch   3 Batch  896/1077 - Train Accuracy: 0.9235, Validation Accuracy: 0.9023, Loss: 0.0616
Epoch   3 Batch  912/1077 - Train Accuracy: 0.9176, Validation Accuracy: 0.8949, Loss: 0.0603
Epoch   3 Batch  928/1077 - Train Accuracy: 0.8848, Validation Accuracy: 0.9105, Loss: 0.0797
Epoch   3 Batch  944/1077 - Train Accuracy: 0.9219, Validation Accuracy: 0.9055, Loss: 0.0610
Epoch   3 Batch  960/1077 - Train Accuracy: 0.9219, Validation Accuracy: 0.9158, Loss: 0.0563
Epoch   3 Batch  976/1077 - Train Accuracy: 0.9082, Validation Accuracy: 0.9073, Loss: 0.0519
Epoch   3 Batch  992/1077 - Train Accuracy: 0.9160, Validation Accuracy: 0.9112, Loss: 0.0595
Epoch   3 Batch 1008/1077 - Train Accuracy: 0.9305, Validation Accuracy: 0.9052, Loss: 0.0735
Epoch   3 Batch 1024/1077 - Train Accuracy: 0.9004, Validation Accuracy: 0.9116, Loss: 0.0620
Epoch   3 Batch 1040/1077 - Train Accuracy: 0.9186, Validation Accuracy: 0.9283, Loss: 0.0713
Epoch   3 Batch 1056/1077 - Train Accuracy: 0.9223, Validation Accuracy: 0.9258, Loss: 0.0559
Epoch   3 Batch 1072/1077 - Train Accuracy: 0.9647, Validation Accuracy: 0.9279, Loss: 0.0522
Epoch   4 Batch   16/1077 - Train Accuracy: 0.8996, Validation Accuracy: 0.9073, Loss: 0.0718
Epoch   4 Batch   32/1077 - Train Accuracy: 0.9103, Validation Accuracy: 0.9073, Loss: 0.0642
Epoch   4 Batch   48/1077 - Train Accuracy: 0.9184, Validation Accuracy: 0.9073, Loss: 0.0861
Epoch   4 Batch   64/1077 - Train Accuracy: 0.9531, Validation Accuracy: 0.8991, Loss: 0.0472
Epoch   4 Batch   80/1077 - Train Accuracy: 0.9211, Validation Accuracy: 0.9261, Loss: 0.0502
Epoch   4 Batch   96/1077 - Train Accuracy: 0.9027, Validation Accuracy: 0.9212, Loss: 0.0596
Epoch   4 Batch  112/1077 - Train Accuracy: 0.9160, Validation Accuracy: 0.9311, Loss: 0.0476
Epoch   4 Batch  128/1077 - Train Accuracy: 0.9498, Validation Accuracy: 0.9208, Loss: 0.0492
Epoch   4 Batch  144/1077 - Train Accuracy: 0.9186, Validation Accuracy: 0.9201, Loss: 0.0759
Epoch   4 Batch  160/1077 - Train Accuracy: 0.9121, Validation Accuracy: 0.9251, Loss: 0.0488
Epoch   4 Batch  176/1077 - Train Accuracy: 0.9051, Validation Accuracy: 0.9190, Loss: 0.0549
Epoch   4 Batch  192/1077 - Train Accuracy: 0.9285, Validation Accuracy: 0.9190, Loss: 0.0608
Epoch   4 Batch  208/1077 - Train Accuracy: 0.9182, Validation Accuracy: 0.8974, Loss: 0.0513
Epoch   4 Batch  224/1077 - Train Accuracy: 0.9477, Validation Accuracy: 0.9066, Loss: 0.0696
Epoch   4 Batch  240/1077 - Train Accuracy: 0.9313, Validation Accuracy: 0.9165, Loss: 0.0551
Epoch   4 Batch  256/1077 - Train Accuracy: 0.9383, Validation Accuracy: 0.9023, Loss: 0.0718
Epoch   4 Batch  272/1077 - Train Accuracy: 0.9211, Validation Accuracy: 0.9169, Loss: 0.0845
Epoch   4 Batch  288/1077 - Train Accuracy: 0.9328, Validation Accuracy: 0.9311, Loss: 0.0595
Epoch   4 Batch  304/1077 - Train Accuracy: 0.9360, Validation Accuracy: 0.8878, Loss: 0.0612
Epoch   4 Batch  320/1077 - Train Accuracy: 0.9207, Validation Accuracy: 0.9187, Loss: 0.0525
Epoch   4 Batch  336/1077 - Train Accuracy: 0.9172, Validation Accuracy: 0.9041, Loss: 0.0795
Epoch   4 Batch  352/1077 - Train Accuracy: 0.9395, Validation Accuracy: 0.9141, Loss: 0.0470
Epoch   4 Batch  368/1077 - Train Accuracy: 0.9301, Validation Accuracy: 0.9148, Loss: 0.0531
Epoch   4 Batch  384/1077 - Train Accuracy: 0.9223, Validation Accuracy: 0.9158, Loss: 0.0511
Epoch   4 Batch  400/1077 - Train Accuracy: 0.9215, Validation Accuracy: 0.9183, Loss: 0.0645
Epoch   4 Batch  416/1077 - Train Accuracy: 0.9500, Validation Accuracy: 0.9048, Loss: 0.0610
Epoch   4 Batch  432/1077 - Train Accuracy: 0.9402, Validation Accuracy: 0.9286, Loss: 0.0590
Epoch   4 Batch  448/1077 - Train Accuracy: 0.9316, Validation Accuracy: 0.9031, Loss: 0.0656
Epoch   4 Batch  464/1077 - Train Accuracy: 0.9297, Validation Accuracy: 0.8864, Loss: 0.0562
Epoch   4 Batch  480/1077 - Train Accuracy: 0.9174, Validation Accuracy: 0.9070, Loss: 0.0537
Epoch   4 Batch  496/1077 - Train Accuracy: 0.9215, Validation Accuracy: 0.8686, Loss: 0.0657
Epoch   4 Batch  512/1077 - Train Accuracy: 0.9457, Validation Accuracy: 0.9013, Loss: 0.0554
Epoch   4 Batch  528/1077 - Train Accuracy: 0.9074, Validation Accuracy: 0.8988, Loss: 0.0621
Epoch   4 Batch  544/1077 - Train Accuracy: 0.9391, Validation Accuracy: 0.8793, Loss: 0.0360
Epoch   4 Batch  560/1077 - Train Accuracy: 0.9051, Validation Accuracy: 0.9041, Loss: 0.0657
Epoch   4 Batch  576/1077 - Train Accuracy: 0.9408, Validation Accuracy: 0.9009, Loss: 0.0437
Epoch   4 Batch  592/1077 - Train Accuracy: 0.9379, Validation Accuracy: 0.8956, Loss: 0.0532
Epoch   4 Batch  608/1077 - Train Accuracy: 0.9195, Validation Accuracy: 0.8949, Loss: 0.0713
Epoch   4 Batch  624/1077 - Train Accuracy: 0.9208, Validation Accuracy: 0.9119, Loss: 0.0635
Epoch   4 Batch  640/1077 - Train Accuracy: 0.8981, Validation Accuracy: 0.9002, Loss: 0.0497
Epoch   4 Batch  656/1077 - Train Accuracy: 0.9336, Validation Accuracy: 0.9041, Loss: 0.0591
Epoch   4 Batch  672/1077 - Train Accuracy: 0.9237, Validation Accuracy: 0.8906, Loss: 0.0493
Epoch   4 Batch  688/1077 - Train Accuracy: 0.9582, Validation Accuracy: 0.9062, Loss: 0.0510
Epoch   4 Batch  704/1077 - Train Accuracy: 0.9184, Validation Accuracy: 0.9066, Loss: 0.0656
Epoch   4 Batch  720/1077 - Train Accuracy: 0.8993, Validation Accuracy: 0.9094, Loss: 0.0562
Epoch   4 Batch  736/1077 - Train Accuracy: 0.9391, Validation Accuracy: 0.8949, Loss: 0.0426
Epoch   4 Batch  752/1077 - Train Accuracy: 0.9122, Validation Accuracy: 0.9102, Loss: 0.0574
Epoch   4 Batch  768/1077 - Train Accuracy: 0.9449, Validation Accuracy: 0.9265, Loss: 0.0467
Epoch   4 Batch  784/1077 - Train Accuracy: 0.9566, Validation Accuracy: 0.9141, Loss: 0.0390
Epoch   4 Batch  800/1077 - Train Accuracy: 0.9301, Validation Accuracy: 0.9251, Loss: 0.0492
Epoch   4 Batch  816/1077 - Train Accuracy: 0.9268, Validation Accuracy: 0.9112, Loss: 0.0670
Epoch   4 Batch  832/1077 - Train Accuracy: 0.9363, Validation Accuracy: 0.8991, Loss: 0.0462
Epoch   4 Batch  848/1077 - Train Accuracy: 0.9363, Validation Accuracy: 0.9190, Loss: 0.0413
Epoch   4 Batch  864/1077 - Train Accuracy: 0.9133, Validation Accuracy: 0.9329, Loss: 0.0601
Epoch   4 Batch  880/1077 - Train Accuracy: 0.9355, Validation Accuracy: 0.9073, Loss: 0.0533
Epoch   4 Batch  896/1077 - Train Accuracy: 0.9128, Validation Accuracy: 0.9052, Loss: 0.0486
Epoch   4 Batch  912/1077 - Train Accuracy: 0.9352, Validation Accuracy: 0.9048, Loss: 0.0499
Epoch   4 Batch  928/1077 - Train Accuracy: 0.8844, Validation Accuracy: 0.8935, Loss: 0.0678
Epoch   4 Batch  944/1077 - Train Accuracy: 0.9126, Validation Accuracy: 0.9055, Loss: 0.0401
Epoch   4 Batch  960/1077 - Train Accuracy: 0.9204, Validation Accuracy: 0.9233, Loss: 0.0506
Epoch   4 Batch  976/1077 - Train Accuracy: 0.9203, Validation Accuracy: 0.9066, Loss: 0.0427
Epoch   4 Batch  992/1077 - Train Accuracy: 0.9277, Validation Accuracy: 0.9066, Loss: 0.0588
Epoch   4 Batch 1008/1077 - Train Accuracy: 0.9445, Validation Accuracy: 0.9059, Loss: 0.0589
Epoch   4 Batch 1024/1077 - Train Accuracy: 0.9230, Validation Accuracy: 0.9180, Loss: 0.0621
Epoch   4 Batch 1040/1077 - Train Accuracy: 0.9280, Validation Accuracy: 0.9148, Loss: 0.0575
Epoch   4 Batch 1056/1077 - Train Accuracy: 0.9395, Validation Accuracy: 0.9045, Loss: 0.0531
Epoch   4 Batch 1072/1077 - Train Accuracy: 0.9513, Validation Accuracy: 0.9237, Loss: 0.0492
Epoch   5 Batch   16/1077 - Train Accuracy: 0.9172, Validation Accuracy: 0.9265, Loss: 0.0541
Epoch   5 Batch   32/1077 - Train Accuracy: 0.9226, Validation Accuracy: 0.9325, Loss: 0.0542
Epoch   5 Batch   48/1077 - Train Accuracy: 0.9125, Validation Accuracy: 0.9222, Loss: 0.0658
Epoch   5 Batch   64/1077 - Train Accuracy: 0.9176, Validation Accuracy: 0.9183, Loss: 0.0483
Epoch   5 Batch   80/1077 - Train Accuracy: 0.9238, Validation Accuracy: 0.9322, Loss: 0.0548
Epoch   5 Batch   96/1077 - Train Accuracy: 0.9270, Validation Accuracy: 0.9357, Loss: 0.0543
Epoch   5 Batch  112/1077 - Train Accuracy: 0.9281, Validation Accuracy: 0.9233, Loss: 0.0505
Epoch   5 Batch  128/1077 - Train Accuracy: 0.9535, Validation Accuracy: 0.8991, Loss: 0.0571
Epoch   5 Batch  144/1077 - Train Accuracy: 0.9227, Validation Accuracy: 0.9158, Loss: 0.0757
Epoch   5 Batch  160/1077 - Train Accuracy: 0.9352, Validation Accuracy: 0.9343, Loss: 0.0462
Epoch   5 Batch  176/1077 - Train Accuracy: 0.9055, Validation Accuracy: 0.9137, Loss: 0.0484
Epoch   5 Batch  192/1077 - Train Accuracy: 0.9359, Validation Accuracy: 0.9290, Loss: 0.0506
Epoch   5 Batch  208/1077 - Train Accuracy: 0.9156, Validation Accuracy: 0.9247, Loss: 0.0461
Epoch   5 Batch  224/1077 - Train Accuracy: 0.9508, Validation Accuracy: 0.9158, Loss: 0.0542
Epoch   5 Batch  240/1077 - Train Accuracy: 0.9590, Validation Accuracy: 0.8999, Loss: 0.0533
Epoch   5 Batch  256/1077 - Train Accuracy: 0.9141, Validation Accuracy: 0.9151, Loss: 0.0731
Epoch   5 Batch  272/1077 - Train Accuracy: 0.9364, Validation Accuracy: 0.9158, Loss: 0.0756
Epoch   5 Batch  288/1077 - Train Accuracy: 0.9418, Validation Accuracy: 0.9418, Loss: 0.0677
Epoch   5 Batch  304/1077 - Train Accuracy: 0.9516, Validation Accuracy: 0.9045, Loss: 0.0583
Epoch   5 Batch  320/1077 - Train Accuracy: 0.9434, Validation Accuracy: 0.9116, Loss: 0.0484
Epoch   5 Batch  336/1077 - Train Accuracy: 0.9074, Validation Accuracy: 0.8746, Loss: 0.0704
Epoch   5 Batch  352/1077 - Train Accuracy: 0.9547, Validation Accuracy: 0.9002, Loss: 0.0418
Epoch   5 Batch  368/1077 - Train Accuracy: 0.9355, Validation Accuracy: 0.9148, Loss: 0.0518
Epoch   5 Batch  384/1077 - Train Accuracy: 0.9328, Validation Accuracy: 0.9325, Loss: 0.0400
Epoch   5 Batch  400/1077 - Train Accuracy: 0.9316, Validation Accuracy: 0.9144, Loss: 0.0571
Epoch   5 Batch  416/1077 - Train Accuracy: 0.9570, Validation Accuracy: 0.9283, Loss: 0.0458
Epoch   5 Batch  432/1077 - Train Accuracy: 0.9270, Validation Accuracy: 0.9261, Loss: 0.0507
Epoch   5 Batch  448/1077 - Train Accuracy: 0.9250, Validation Accuracy: 0.9098, Loss: 0.0604
Epoch   5 Batch  464/1077 - Train Accuracy: 0.9113, Validation Accuracy: 0.9123, Loss: 0.0578
Epoch   5 Batch  480/1077 - Train Accuracy: 0.9412, Validation Accuracy: 0.9158, Loss: 0.0579
Epoch   5 Batch  496/1077 - Train Accuracy: 0.9352, Validation Accuracy: 0.9130, Loss: 0.0491
Epoch   5 Batch  512/1077 - Train Accuracy: 0.9465, Validation Accuracy: 0.9034, Loss: 0.0442
Epoch   5 Batch  528/1077 - Train Accuracy: 0.9062, Validation Accuracy: 0.9137, Loss: 0.0672
Epoch   5 Batch  544/1077 - Train Accuracy: 0.9336, Validation Accuracy: 0.8860, Loss: 0.0495
Epoch   5 Batch  560/1077 - Train Accuracy: 0.9203, Validation Accuracy: 0.9158, Loss: 0.0509
Epoch   5 Batch  576/1077 - Train Accuracy: 0.9609, Validation Accuracy: 0.8967, Loss: 0.0381
Epoch   5 Batch  592/1077 - Train Accuracy: 0.9422, Validation Accuracy: 0.9041, Loss: 0.0417
Epoch   5 Batch  608/1077 - Train Accuracy: 0.9426, Validation Accuracy: 0.9130, Loss: 0.0566
Epoch   5 Batch  624/1077 - Train Accuracy: 0.9278, Validation Accuracy: 0.9094, Loss: 0.0531
Epoch   5 Batch  640/1077 - Train Accuracy: 0.9297, Validation Accuracy: 0.9197, Loss: 0.0486
Epoch   5 Batch  656/1077 - Train Accuracy: 0.9406, Validation Accuracy: 0.9229, Loss: 0.0607
Epoch   5 Batch  672/1077 - Train Accuracy: 0.9345, Validation Accuracy: 0.9240, Loss: 0.0468
Epoch   5 Batch  688/1077 - Train Accuracy: 0.9480, Validation Accuracy: 0.9062, Loss: 0.0535
Epoch   5 Batch  704/1077 - Train Accuracy: 0.9270, Validation Accuracy: 0.9173, Loss: 0.0526
Epoch   5 Batch  720/1077 - Train Accuracy: 0.9383, Validation Accuracy: 0.9261, Loss: 0.0542
Epoch   5 Batch  736/1077 - Train Accuracy: 0.9408, Validation Accuracy: 0.9261, Loss: 0.0484
Epoch   5 Batch  752/1077 - Train Accuracy: 0.9282, Validation Accuracy: 0.8931, Loss: 0.0573
Epoch   5 Batch  768/1077 - Train Accuracy: 0.9328, Validation Accuracy: 0.9251, Loss: 0.0595
Epoch   5 Batch  784/1077 - Train Accuracy: 0.9633, Validation Accuracy: 0.9219, Loss: 0.0410
Epoch   5 Batch  800/1077 - Train Accuracy: 0.9258, Validation Accuracy: 0.9233, Loss: 0.0472
Epoch   5 Batch  816/1077 - Train Accuracy: 0.9461, Validation Accuracy: 0.9339, Loss: 0.0614
Epoch   5 Batch  832/1077 - Train Accuracy: 0.9543, Validation Accuracy: 0.9144, Loss: 0.0387
Epoch   5 Batch  848/1077 - Train Accuracy: 0.9379, Validation Accuracy: 0.9165, Loss: 0.0481
Epoch   5 Batch  864/1077 - Train Accuracy: 0.9242, Validation Accuracy: 0.9102, Loss: 0.0413
Epoch   5 Batch  880/1077 - Train Accuracy: 0.9320, Validation Accuracy: 0.9094, Loss: 0.0632
Epoch   5 Batch  896/1077 - Train Accuracy: 0.9190, Validation Accuracy: 0.9062, Loss: 0.0508
Epoch   5 Batch  912/1077 - Train Accuracy: 0.9293, Validation Accuracy: 0.9158, Loss: 0.0579
Epoch   5 Batch  928/1077 - Train Accuracy: 0.9168, Validation Accuracy: 0.9215, Loss: 0.0500
Epoch   5 Batch  944/1077 - Train Accuracy: 0.9446, Validation Accuracy: 0.9197, Loss: 0.0422
Epoch   5 Batch  960/1077 - Train Accuracy: 0.9297, Validation Accuracy: 0.9364, Loss: 0.0399
Epoch   5 Batch  976/1077 - Train Accuracy: 0.9383, Validation Accuracy: 0.9183, Loss: 0.0423
Epoch   5 Batch  992/1077 - Train Accuracy: 0.9195, Validation Accuracy: 0.9144, Loss: 0.0553
Epoch   5 Batch 1008/1077 - Train Accuracy: 0.9395, Validation Accuracy: 0.9165, Loss: 0.0520
Epoch   5 Batch 1024/1077 - Train Accuracy: 0.9227, Validation Accuracy: 0.9261, Loss: 0.0556
Epoch   5 Batch 1040/1077 - Train Accuracy: 0.9330, Validation Accuracy: 0.9283, Loss: 0.0516
Epoch   5 Batch 1056/1077 - Train Accuracy: 0.9434, Validation Accuracy: 0.9268, Loss: 0.0436
Epoch   5 Batch 1072/1077 - Train Accuracy: 0.9557, Validation Accuracy: 0.9364, Loss: 0.0456
Epoch   6 Batch   16/1077 - Train Accuracy: 0.9238, Validation Accuracy: 0.9240, Loss: 0.0492
Epoch   6 Batch   32/1077 - Train Accuracy: 0.9390, Validation Accuracy: 0.9318, Loss: 0.0460
Epoch   6 Batch   48/1077 - Train Accuracy: 0.9203, Validation Accuracy: 0.9474, Loss: 0.0719
Epoch   6 Batch   64/1077 - Train Accuracy: 0.9395, Validation Accuracy: 0.9286, Loss: 0.0422
Epoch   6 Batch   80/1077 - Train Accuracy: 0.9293, Validation Accuracy: 0.9428, Loss: 0.0512
Epoch   6 Batch   96/1077 - Train Accuracy: 0.9195, Validation Accuracy: 0.9180, Loss: 0.0508
Epoch   6 Batch  112/1077 - Train Accuracy: 0.9301, Validation Accuracy: 0.9126, Loss: 0.0415
Epoch   6 Batch  128/1077 - Train Accuracy: 0.9576, Validation Accuracy: 0.9336, Loss: 0.0443
Epoch   6 Batch  144/1077 - Train Accuracy: 0.9219, Validation Accuracy: 0.9130, Loss: 0.0796
Epoch   6 Batch  160/1077 - Train Accuracy: 0.9375, Validation Accuracy: 0.9016, Loss: 0.0430
Epoch   6 Batch  176/1077 - Train Accuracy: 0.9336, Validation Accuracy: 0.9151, Loss: 0.0440
Epoch   6 Batch  192/1077 - Train Accuracy: 0.9398, Validation Accuracy: 0.9240, Loss: 0.0473
Epoch   6 Batch  208/1077 - Train Accuracy: 0.9293, Validation Accuracy: 0.9165, Loss: 0.0473
Epoch   6 Batch  224/1077 - Train Accuracy: 0.9344, Validation Accuracy: 0.9013, Loss: 0.0444
Epoch   6 Batch  240/1077 - Train Accuracy: 0.9688, Validation Accuracy: 0.9045, Loss: 0.0427
Epoch   6 Batch  256/1077 - Train Accuracy: 0.9254, Validation Accuracy: 0.9229, Loss: 0.0641
Epoch   6 Batch  272/1077 - Train Accuracy: 0.9327, Validation Accuracy: 0.9187, Loss: 0.0795
Epoch   6 Batch  288/1077 - Train Accuracy: 0.9449, Validation Accuracy: 0.9190, Loss: 0.0525
Epoch   6 Batch  304/1077 - Train Accuracy: 0.9342, Validation Accuracy: 0.9091, Loss: 0.0557
Epoch   6 Batch  320/1077 - Train Accuracy: 0.9062, Validation Accuracy: 0.8999, Loss: 0.0513
Epoch   6 Batch  336/1077 - Train Accuracy: 0.9152, Validation Accuracy: 0.9059, Loss: 0.0720
Epoch   6 Batch  352/1077 - Train Accuracy: 0.9367, Validation Accuracy: 0.8974, Loss: 0.0475
Epoch   6 Batch  368/1077 - Train Accuracy: 0.9461, Validation Accuracy: 0.9173, Loss: 0.0480
Epoch   6 Batch  384/1077 - Train Accuracy: 0.9672, Validation Accuracy: 0.9233, Loss: 0.0370
Epoch   6 Batch  400/1077 - Train Accuracy: 0.9320, Validation Accuracy: 0.9322, Loss: 0.0489
Epoch   6 Batch  416/1077 - Train Accuracy: 0.9414, Validation Accuracy: 0.9279, Loss: 0.0498
Epoch   6 Batch  432/1077 - Train Accuracy: 0.9469, Validation Accuracy: 0.9339, Loss: 0.0537
Epoch   6 Batch  448/1077 - Train Accuracy: 0.9414, Validation Accuracy: 0.9112, Loss: 0.0558
Epoch   6 Batch  464/1077 - Train Accuracy: 0.9289, Validation Accuracy: 0.9173, Loss: 0.0483
Epoch   6 Batch  480/1077 - Train Accuracy: 0.9552, Validation Accuracy: 0.9237, Loss: 0.0343
Epoch   6 Batch  496/1077 - Train Accuracy: 0.9410, Validation Accuracy: 0.9180, Loss: 0.0520
Epoch   6 Batch  512/1077 - Train Accuracy: 0.9617, Validation Accuracy: 0.9336, Loss: 0.0455
Epoch   6 Batch  528/1077 - Train Accuracy: 0.9117, Validation Accuracy: 0.9332, Loss: 0.0511
Epoch   6 Batch  544/1077 - Train Accuracy: 0.9531, Validation Accuracy: 0.9055, Loss: 0.0267
Epoch   6 Batch  560/1077 - Train Accuracy: 0.9207, Validation Accuracy: 0.9215, Loss: 0.0517
Epoch   6 Batch  576/1077 - Train Accuracy: 0.9478, Validation Accuracy: 0.9045, Loss: 0.0418
Epoch   6 Batch  592/1077 - Train Accuracy: 0.9488, Validation Accuracy: 0.9162, Loss: 0.0494
Epoch   6 Batch  608/1077 - Train Accuracy: 0.9379, Validation Accuracy: 0.9432, Loss: 0.0538
Epoch   6 Batch  624/1077 - Train Accuracy: 0.9315, Validation Accuracy: 0.9396, Loss: 0.0510
Epoch   6 Batch  640/1077 - Train Accuracy: 0.9457, Validation Accuracy: 0.9379, Loss: 0.0408
Epoch   6 Batch  656/1077 - Train Accuracy: 0.9145, Validation Accuracy: 0.8935, Loss: 0.0519
Epoch   6 Batch  672/1077 - Train Accuracy: 0.9479, Validation Accuracy: 0.9247, Loss: 0.0362
Epoch   6 Batch  688/1077 - Train Accuracy: 0.9453, Validation Accuracy: 0.9403, Loss: 0.0474
Epoch   6 Batch  704/1077 - Train Accuracy: 0.9230, Validation Accuracy: 0.9325, Loss: 0.0488
Epoch   6 Batch  720/1077 - Train Accuracy: 0.9202, Validation Accuracy: 0.9268, Loss: 0.0454
Epoch   6 Batch  736/1077 - Train Accuracy: 0.9317, Validation Accuracy: 0.9300, Loss: 0.0347
Epoch   6 Batch  752/1077 - Train Accuracy: 0.9219, Validation Accuracy: 0.9155, Loss: 0.0451
Epoch   6 Batch  768/1077 - Train Accuracy: 0.9543, Validation Accuracy: 0.9311, Loss: 0.0365
Epoch   6 Batch  784/1077 - Train Accuracy: 0.9520, Validation Accuracy: 0.9173, Loss: 0.0472
Epoch   6 Batch  800/1077 - Train Accuracy: 0.9383, Validation Accuracy: 0.9293, Loss: 0.0444
Epoch   6 Batch  816/1077 - Train Accuracy: 0.9416, Validation Accuracy: 0.9322, Loss: 0.0593
Epoch   6 Batch  832/1077 - Train Accuracy: 0.9613, Validation Accuracy: 0.9233, Loss: 0.0416
Epoch   6 Batch  848/1077 - Train Accuracy: 0.9543, Validation Accuracy: 0.9212, Loss: 0.0390
Epoch   6 Batch  864/1077 - Train Accuracy: 0.9086, Validation Accuracy: 0.9329, Loss: 0.0410
Epoch   6 Batch  880/1077 - Train Accuracy: 0.9238, Validation Accuracy: 0.9457, Loss: 0.0580
Epoch   6 Batch  896/1077 - Train Accuracy: 0.9202, Validation Accuracy: 0.9240, Loss: 0.0478
Epoch   6 Batch  912/1077 - Train Accuracy: 0.9523, Validation Accuracy: 0.9336, Loss: 0.0411
Epoch   6 Batch  928/1077 - Train Accuracy: 0.9551, Validation Accuracy: 0.9435, Loss: 0.0467
Epoch   6 Batch  944/1077 - Train Accuracy: 0.9583, Validation Accuracy: 0.9311, Loss: 0.0299
Epoch   6 Batch  960/1077 - Train Accuracy: 0.9010, Validation Accuracy: 0.9219, Loss: 0.0427
Epoch   6 Batch  976/1077 - Train Accuracy: 0.9223, Validation Accuracy: 0.9350, Loss: 0.0342
Epoch   6 Batch  992/1077 - Train Accuracy: 0.9402, Validation Accuracy: 0.9357, Loss: 0.0469
Epoch   6 Batch 1008/1077 - Train Accuracy: 0.9520, Validation Accuracy: 0.9304, Loss: 0.0643
Epoch   6 Batch 1024/1077 - Train Accuracy: 0.8992, Validation Accuracy: 0.9165, Loss: 0.0487
Epoch   6 Batch 1040/1077 - Train Accuracy: 0.9531, Validation Accuracy: 0.9038, Loss: 0.0476
Epoch   6 Batch 1056/1077 - Train Accuracy: 0.9250, Validation Accuracy: 0.9226, Loss: 0.0449
Epoch   6 Batch 1072/1077 - Train Accuracy: 0.9602, Validation Accuracy: 0.9219, Loss: 0.0456
Epoch   7 Batch   16/1077 - Train Accuracy: 0.9320, Validation Accuracy: 0.9233, Loss: 0.0477
Epoch   7 Batch   32/1077 - Train Accuracy: 0.9520, Validation Accuracy: 0.9233, Loss: 0.0484
Epoch   7 Batch   48/1077 - Train Accuracy: 0.9320, Validation Accuracy: 0.9201, Loss: 0.0727
Epoch   7 Batch   64/1077 - Train Accuracy: 0.9570, Validation Accuracy: 0.9268, Loss: 0.0388
Epoch   7 Batch   80/1077 - Train Accuracy: 0.9266, Validation Accuracy: 0.9322, Loss: 0.0366
Epoch   7 Batch   96/1077 - Train Accuracy: 0.9313, Validation Accuracy: 0.9364, Loss: 0.0363
Epoch   7 Batch  112/1077 - Train Accuracy: 0.9328, Validation Accuracy: 0.9350, Loss: 0.0416
Epoch   7 Batch  128/1077 - Train Accuracy: 0.9658, Validation Accuracy: 0.9187, Loss: 0.0435
Epoch   7 Batch  144/1077 - Train Accuracy: 0.9182, Validation Accuracy: 0.9045, Loss: 0.0563
Epoch   7 Batch  160/1077 - Train Accuracy: 0.9449, Validation Accuracy: 0.9169, Loss: 0.0342
Epoch   7 Batch  176/1077 - Train Accuracy: 0.9359, Validation Accuracy: 0.9212, Loss: 0.0380
Epoch   7 Batch  192/1077 - Train Accuracy: 0.9344, Validation Accuracy: 0.9293, Loss: 0.0432
Epoch   7 Batch  208/1077 - Train Accuracy: 0.9520, Validation Accuracy: 0.9343, Loss: 0.0471
Epoch   7 Batch  224/1077 - Train Accuracy: 0.9613, Validation Accuracy: 0.9151, Loss: 0.0449
Epoch   7 Batch  240/1077 - Train Accuracy: 0.9680, Validation Accuracy: 0.9403, Loss: 0.0461
Epoch   7 Batch  256/1077 - Train Accuracy: 0.9121, Validation Accuracy: 0.9254, Loss: 0.0546
Epoch   7 Batch  272/1077 - Train Accuracy: 0.9461, Validation Accuracy: 0.9368, Loss: 0.0632
Epoch   7 Batch  288/1077 - Train Accuracy: 0.9473, Validation Accuracy: 0.9272, Loss: 0.0566
Epoch   7 Batch  304/1077 - Train Accuracy: 0.9583, Validation Accuracy: 0.9144, Loss: 0.0488
Epoch   7 Batch  320/1077 - Train Accuracy: 0.9375, Validation Accuracy: 0.9265, Loss: 0.0616
Epoch   7 Batch  336/1077 - Train Accuracy: 0.9125, Validation Accuracy: 0.9126, Loss: 0.0680
Epoch   7 Batch  352/1077 - Train Accuracy: 0.9355, Validation Accuracy: 0.9034, Loss: 0.0458
Epoch   7 Batch  368/1077 - Train Accuracy: 0.9484, Validation Accuracy: 0.9208, Loss: 0.0442
Epoch   7 Batch  384/1077 - Train Accuracy: 0.9520, Validation Accuracy: 0.9173, Loss: 0.0439
Epoch   7 Batch  400/1077 - Train Accuracy: 0.9504, Validation Accuracy: 0.9165, Loss: 0.0579
Epoch   7 Batch  416/1077 - Train Accuracy: 0.9566, Validation Accuracy: 0.9261, Loss: 0.0373
Epoch   7 Batch  432/1077 - Train Accuracy: 0.9527, Validation Accuracy: 0.9109, Loss: 0.0530
Epoch   7 Batch  448/1077 - Train Accuracy: 0.9227, Validation Accuracy: 0.9038, Loss: 0.0499
Epoch   7 Batch  464/1077 - Train Accuracy: 0.9391, Validation Accuracy: 0.9229, Loss: 0.0512
Epoch   7 Batch  480/1077 - Train Accuracy: 0.9404, Validation Accuracy: 0.9403, Loss: 0.0455
Epoch   7 Batch  496/1077 - Train Accuracy: 0.9398, Validation Accuracy: 0.9183, Loss: 0.0485
Epoch   7 Batch  512/1077 - Train Accuracy: 0.9625, Validation Accuracy: 0.9116, Loss: 0.0484
Epoch   7 Batch  528/1077 - Train Accuracy: 0.9074, Validation Accuracy: 0.9201, Loss: 0.0526
Epoch   7 Batch  544/1077 - Train Accuracy: 0.9633, Validation Accuracy: 0.8842, Loss: 0.0260
Epoch   7 Batch  560/1077 - Train Accuracy: 0.9480, Validation Accuracy: 0.9190, Loss: 0.0445
Epoch   7 Batch  576/1077 - Train Accuracy: 0.9494, Validation Accuracy: 0.9222, Loss: 0.0384
Epoch   7 Batch  592/1077 - Train Accuracy: 0.9453, Validation Accuracy: 0.9247, Loss: 0.0420
Epoch   7 Batch  608/1077 - Train Accuracy: 0.9262, Validation Accuracy: 0.9400, Loss: 0.0550
Epoch   7 Batch  624/1077 - Train Accuracy: 0.9353, Validation Accuracy: 0.9446, Loss: 0.0460
Epoch   7 Batch  640/1077 - Train Accuracy: 0.9353, Validation Accuracy: 0.9492, Loss: 0.0384
Epoch   7 Batch  656/1077 - Train Accuracy: 0.9395, Validation Accuracy: 0.9283, Loss: 0.0531
Epoch   7 Batch  672/1077 - Train Accuracy: 0.9490, Validation Accuracy: 0.9368, Loss: 0.0355
Epoch   7 Batch  688/1077 - Train Accuracy: 0.9527, Validation Accuracy: 0.9158, Loss: 0.0405
Epoch   7 Batch  704/1077 - Train Accuracy: 0.9227, Validation Accuracy: 0.9141, Loss: 0.0460
Epoch   7 Batch  720/1077 - Train Accuracy: 0.9095, Validation Accuracy: 0.9247, Loss: 0.0468
Epoch   7 Batch  736/1077 - Train Accuracy: 0.9498, Validation Accuracy: 0.9311, Loss: 0.0343
Epoch   7 Batch  752/1077 - Train Accuracy: 0.9483, Validation Accuracy: 0.9290, Loss: 0.0410
Epoch   7 Batch  768/1077 - Train Accuracy: 0.9633, Validation Accuracy: 0.9176, Loss: 0.0389
Epoch   7 Batch  784/1077 - Train Accuracy: 0.9645, Validation Accuracy: 0.9251, Loss: 0.0299
Epoch   7 Batch  800/1077 - Train Accuracy: 0.9598, Validation Accuracy: 0.9251, Loss: 0.0384
Epoch   7 Batch  816/1077 - Train Accuracy: 0.9589, Validation Accuracy: 0.9293, Loss: 0.0403
Epoch   7 Batch  832/1077 - Train Accuracy: 0.9473, Validation Accuracy: 0.9229, Loss: 0.0281
Epoch   7 Batch  848/1077 - Train Accuracy: 0.9461, Validation Accuracy: 0.9286, Loss: 0.0423
Epoch   7 Batch  864/1077 - Train Accuracy: 0.9184, Validation Accuracy: 0.9329, Loss: 0.0391
Epoch   7 Batch  880/1077 - Train Accuracy: 0.9336, Validation Accuracy: 0.9272, Loss: 0.0552
Epoch   7 Batch  896/1077 - Train Accuracy: 0.9268, Validation Accuracy: 0.9268, Loss: 0.0486
Epoch   7 Batch  912/1077 - Train Accuracy: 0.9383, Validation Accuracy: 0.9169, Loss: 0.0445
Epoch   7 Batch  928/1077 - Train Accuracy: 0.9328, Validation Accuracy: 0.9453, Loss: 0.0495
Epoch   7 Batch  944/1077 - Train Accuracy: 0.9438, Validation Accuracy: 0.9226, Loss: 0.0281
Epoch   7 Batch  960/1077 - Train Accuracy: 0.9375, Validation Accuracy: 0.9332, Loss: 0.0459
Epoch   7 Batch  976/1077 - Train Accuracy: 0.9363, Validation Accuracy: 0.9300, Loss: 0.0487
Epoch   7 Batch  992/1077 - Train Accuracy: 0.9379, Validation Accuracy: 0.9496, Loss: 0.0473
Epoch   7 Batch 1008/1077 - Train Accuracy: 0.9383, Validation Accuracy: 0.9222, Loss: 0.0552
Epoch   7 Batch 1024/1077 - Train Accuracy: 0.9168, Validation Accuracy: 0.9517, Loss: 0.0507
Epoch   7 Batch 1040/1077 - Train Accuracy: 0.9400, Validation Accuracy: 0.9151, Loss: 0.0498
Epoch   7 Batch 1056/1077 - Train Accuracy: 0.9477, Validation Accuracy: 0.9347, Loss: 0.0383
Epoch   7 Batch 1072/1077 - Train Accuracy: 0.9594, Validation Accuracy: 0.9375, Loss: 0.0398
Epoch   8 Batch   16/1077 - Train Accuracy: 0.9398, Validation Accuracy: 0.9332, Loss: 0.0609
Epoch   8 Batch   32/1077 - Train Accuracy: 0.9583, Validation Accuracy: 0.9414, Loss: 0.0379
Epoch   8 Batch   48/1077 - Train Accuracy: 0.9340, Validation Accuracy: 0.9368, Loss: 0.0622
Epoch   8 Batch   64/1077 - Train Accuracy: 0.9563, Validation Accuracy: 0.9091, Loss: 0.0440
Epoch   8 Batch   80/1077 - Train Accuracy: 0.9414, Validation Accuracy: 0.9538, Loss: 0.0409
Epoch   8 Batch   96/1077 - Train Accuracy: 0.9309, Validation Accuracy: 0.9450, Loss: 0.0380
Epoch   8 Batch  112/1077 - Train Accuracy: 0.9281, Validation Accuracy: 0.9151, Loss: 0.0347
Epoch   8 Batch  128/1077 - Train Accuracy: 0.9576, Validation Accuracy: 0.9233, Loss: 0.0324
Epoch   8 Batch  144/1077 - Train Accuracy: 0.9132, Validation Accuracy: 0.9279, Loss: 0.0597
Epoch   8 Batch  160/1077 - Train Accuracy: 0.9430, Validation Accuracy: 0.9336, Loss: 0.0404
Epoch   8 Batch  176/1077 - Train Accuracy: 0.9215, Validation Accuracy: 0.9123, Loss: 0.0492
Epoch   8 Batch  192/1077 - Train Accuracy: 0.9176, Validation Accuracy: 0.9339, Loss: 0.0534
Epoch   8 Batch  208/1077 - Train Accuracy: 0.9271, Validation Accuracy: 0.9261, Loss: 0.0474
Epoch   8 Batch  224/1077 - Train Accuracy: 0.9516, Validation Accuracy: 0.9400, Loss: 0.0488
Epoch   8 Batch  240/1077 - Train Accuracy: 0.9570, Validation Accuracy: 0.9297, Loss: 0.0382
Epoch   8 Batch  256/1077 - Train Accuracy: 0.9281, Validation Accuracy: 0.9286, Loss: 0.0625
Epoch   8 Batch  272/1077 - Train Accuracy: 0.9557, Validation Accuracy: 0.9389, Loss: 0.0647
Epoch   8 Batch  288/1077 - Train Accuracy: 0.9574, Validation Accuracy: 0.9332, Loss: 0.0482
Epoch   8 Batch  304/1077 - Train Accuracy: 0.9576, Validation Accuracy: 0.9141, Loss: 0.0439
Epoch   8 Batch  320/1077 - Train Accuracy: 0.9387, Validation Accuracy: 0.9393, Loss: 0.0451
Epoch   8 Batch  336/1077 - Train Accuracy: 0.9246, Validation Accuracy: 0.9293, Loss: 0.0650
Epoch   8 Batch  352/1077 - Train Accuracy: 0.9262, Validation Accuracy: 0.9208, Loss: 0.0425
Epoch   8 Batch  368/1077 - Train Accuracy: 0.9453, Validation Accuracy: 0.9247, Loss: 0.0427
Epoch   8 Batch  384/1077 - Train Accuracy: 0.9625, Validation Accuracy: 0.9460, Loss: 0.0380
Epoch   8 Batch  400/1077 - Train Accuracy: 0.9543, Validation Accuracy: 0.9169, Loss: 0.0451
Epoch   8 Batch  416/1077 - Train Accuracy: 0.9504, Validation Accuracy: 0.9201, Loss: 0.0351
Epoch   8 Batch  432/1077 - Train Accuracy: 0.9578, Validation Accuracy: 0.9318, Loss: 0.0424
Epoch   8 Batch  448/1077 - Train Accuracy: 0.9309, Validation Accuracy: 0.9173, Loss: 0.0467
Epoch   8 Batch  464/1077 - Train Accuracy: 0.9297, Validation Accuracy: 0.9031, Loss: 0.0365
Epoch   8 Batch  480/1077 - Train Accuracy: 0.9387, Validation Accuracy: 0.9276, Loss: 0.0323
Epoch   8 Batch  496/1077 - Train Accuracy: 0.9348, Validation Accuracy: 0.9339, Loss: 0.0495
Epoch   8 Batch  512/1077 - Train Accuracy: 0.9602, Validation Accuracy: 0.9251, Loss: 0.0557
Epoch   8 Batch  528/1077 - Train Accuracy: 0.9301, Validation Accuracy: 0.9212, Loss: 0.0574
Epoch   8 Batch  544/1077 - Train Accuracy: 0.9441, Validation Accuracy: 0.9183, Loss: 0.0376
Epoch   8 Batch  560/1077 - Train Accuracy: 0.9563, Validation Accuracy: 0.9165, Loss: 0.0369
Epoch   8 Batch  576/1077 - Train Accuracy: 0.9601, Validation Accuracy: 0.9244, Loss: 0.0438
Epoch   8 Batch  592/1077 - Train Accuracy: 0.9559, Validation Accuracy: 0.9325, Loss: 0.0346
Epoch   8 Batch  608/1077 - Train Accuracy: 0.9449, Validation Accuracy: 0.9400, Loss: 0.0558
Epoch   8 Batch  624/1077 - Train Accuracy: 0.9382, Validation Accuracy: 0.9119, Loss: 0.0483
Epoch   8 Batch  640/1077 - Train Accuracy: 0.9528, Validation Accuracy: 0.9098, Loss: 0.0324
Epoch   8 Batch  656/1077 - Train Accuracy: 0.9301, Validation Accuracy: 0.9219, Loss: 0.0392
Epoch   8 Batch  672/1077 - Train Accuracy: 0.9632, Validation Accuracy: 0.9272, Loss: 0.0342
Epoch   8 Batch  688/1077 - Train Accuracy: 0.9543, Validation Accuracy: 0.9279, Loss: 0.0407
Epoch   8 Batch  704/1077 - Train Accuracy: 0.9258, Validation Accuracy: 0.9155, Loss: 0.0422
Epoch   8 Batch  720/1077 - Train Accuracy: 0.9437, Validation Accuracy: 0.9403, Loss: 0.0400
Epoch   8 Batch  736/1077 - Train Accuracy: 0.9408, Validation Accuracy: 0.9290, Loss: 0.0276
Epoch   8 Batch  752/1077 - Train Accuracy: 0.9219, Validation Accuracy: 0.9258, Loss: 0.0360
Epoch   8 Batch  768/1077 - Train Accuracy: 0.9555, Validation Accuracy: 0.9325, Loss: 0.0367
Epoch   8 Batch  784/1077 - Train Accuracy: 0.9574, Validation Accuracy: 0.9165, Loss: 0.0306
Epoch   8 Batch  800/1077 - Train Accuracy: 0.9563, Validation Accuracy: 0.9283, Loss: 0.0358
Epoch   8 Batch  816/1077 - Train Accuracy: 0.9482, Validation Accuracy: 0.9336, Loss: 0.0461
Epoch   8 Batch  832/1077 - Train Accuracy: 0.9449, Validation Accuracy: 0.9169, Loss: 0.0336
Epoch   8 Batch  848/1077 - Train Accuracy: 0.9516, Validation Accuracy: 0.9343, Loss: 0.0318
Epoch   8 Batch  864/1077 - Train Accuracy: 0.9215, Validation Accuracy: 0.9510, Loss: 0.0419
Epoch   8 Batch  880/1077 - Train Accuracy: 0.9445, Validation Accuracy: 0.9588, Loss: 0.0505
Epoch   8 Batch  896/1077 - Train Accuracy: 0.9317, Validation Accuracy: 0.9379, Loss: 0.0343
Epoch   8 Batch  912/1077 - Train Accuracy: 0.9574, Validation Accuracy: 0.9467, Loss: 0.0352
Epoch   8 Batch  928/1077 - Train Accuracy: 0.9492, Validation Accuracy: 0.9439, Loss: 0.0473
Epoch   8 Batch  944/1077 - Train Accuracy: 0.9528, Validation Accuracy: 0.9411, Loss: 0.0307
Epoch   8 Batch  960/1077 - Train Accuracy: 0.9252, Validation Accuracy: 0.9258, Loss: 0.0447
Epoch   8 Batch  976/1077 - Train Accuracy: 0.9480, Validation Accuracy: 0.9368, Loss: 0.0392
Epoch   8 Batch  992/1077 - Train Accuracy: 0.9367, Validation Accuracy: 0.9208, Loss: 0.0460
Epoch   8 Batch 1008/1077 - Train Accuracy: 0.9570, Validation Accuracy: 0.9197, Loss: 0.0600
Epoch   8 Batch 1024/1077 - Train Accuracy: 0.9195, Validation Accuracy: 0.9105, Loss: 0.0510
Epoch   8 Batch 1040/1077 - Train Accuracy: 0.9449, Validation Accuracy: 0.9173, Loss: 0.0414
Epoch   8 Batch 1056/1077 - Train Accuracy: 0.9277, Validation Accuracy: 0.9268, Loss: 0.0323
Epoch   8 Batch 1072/1077 - Train Accuracy: 0.9587, Validation Accuracy: 0.9297, Loss: 0.0328
Epoch   9 Batch   16/1077 - Train Accuracy: 0.9520, Validation Accuracy: 0.9176, Loss: 0.0406
Epoch   9 Batch   32/1077 - Train Accuracy: 0.9658, Validation Accuracy: 0.9371, Loss: 0.0307
Epoch   9 Batch   48/1077 - Train Accuracy: 0.9324, Validation Accuracy: 0.9354, Loss: 0.0558
Epoch   9 Batch   64/1077 - Train Accuracy: 0.9516, Validation Accuracy: 0.9354, Loss: 0.0392
Epoch   9 Batch   80/1077 - Train Accuracy: 0.9586, Validation Accuracy: 0.9478, Loss: 0.0508
Epoch   9 Batch   96/1077 - Train Accuracy: 0.9480, Validation Accuracy: 0.9400, Loss: 0.0379
Epoch   9 Batch  112/1077 - Train Accuracy: 0.9516, Validation Accuracy: 0.9325, Loss: 0.0326
Epoch   9 Batch  128/1077 - Train Accuracy: 0.9669, Validation Accuracy: 0.9389, Loss: 0.0442
Epoch   9 Batch  144/1077 - Train Accuracy: 0.9272, Validation Accuracy: 0.9226, Loss: 0.0661
Epoch   9 Batch  160/1077 - Train Accuracy: 0.9398, Validation Accuracy: 0.9435, Loss: 0.0338
Epoch   9 Batch  176/1077 - Train Accuracy: 0.9258, Validation Accuracy: 0.9286, Loss: 0.0510
Epoch   9 Batch  192/1077 - Train Accuracy: 0.9527, Validation Accuracy: 0.9279, Loss: 0.0378
Epoch   9 Batch  208/1077 - Train Accuracy: 0.9386, Validation Accuracy: 0.9368, Loss: 0.0355
Epoch   9 Batch  224/1077 - Train Accuracy: 0.9453, Validation Accuracy: 0.9286, Loss: 0.0516
Epoch   9 Batch  240/1077 - Train Accuracy: 0.9746, Validation Accuracy: 0.9229, Loss: 0.0402
Epoch   9 Batch  256/1077 - Train Accuracy: 0.9250, Validation Accuracy: 0.9212, Loss: 0.0666
Epoch   9 Batch  272/1077 - Train Accuracy: 0.9397, Validation Accuracy: 0.9254, Loss: 0.0596
Epoch   9 Batch  288/1077 - Train Accuracy: 0.9574, Validation Accuracy: 0.9393, Loss: 0.0575
Epoch   9 Batch  304/1077 - Train Accuracy: 0.9572, Validation Accuracy: 0.9300, Loss: 0.0475
Epoch   9 Batch  320/1077 - Train Accuracy: 0.9555, Validation Accuracy: 0.9173, Loss: 0.0416
Epoch   9 Batch  336/1077 - Train Accuracy: 0.9266, Validation Accuracy: 0.9304, Loss: 0.0660
Epoch   9 Batch  352/1077 - Train Accuracy: 0.9539, Validation Accuracy: 0.9339, Loss: 0.0410
Epoch   9 Batch  368/1077 - Train Accuracy: 0.9492, Validation Accuracy: 0.9144, Loss: 0.0397
Epoch   9 Batch  384/1077 - Train Accuracy: 0.9668, Validation Accuracy: 0.9453, Loss: 0.0299
Epoch   9 Batch  400/1077 - Train Accuracy: 0.9344, Validation Accuracy: 0.9364, Loss: 0.0564
Epoch   9 Batch  416/1077 - Train Accuracy: 0.9551, Validation Accuracy: 0.9379, Loss: 0.0346
Epoch   9 Batch  432/1077 - Train Accuracy: 0.9555, Validation Accuracy: 0.9343, Loss: 0.0351
Epoch   9 Batch  448/1077 - Train Accuracy: 0.9359, Validation Accuracy: 0.9137, Loss: 0.0436
Epoch   9 Batch  464/1077 - Train Accuracy: 0.9531, Validation Accuracy: 0.9180, Loss: 0.0399
Epoch   9 Batch  480/1077 - Train Accuracy: 0.9642, Validation Accuracy: 0.9315, Loss: 0.0312
Epoch   9 Batch  496/1077 - Train Accuracy: 0.9402, Validation Accuracy: 0.9254, Loss: 0.0421
Epoch   9 Batch  512/1077 - Train Accuracy: 0.9672, Validation Accuracy: 0.9208, Loss: 0.0416
Epoch   9 Batch  528/1077 - Train Accuracy: 0.9281, Validation Accuracy: 0.9130, Loss: 0.0498
Epoch   9 Batch  544/1077 - Train Accuracy: 0.9508, Validation Accuracy: 0.9165, Loss: 0.0267
Epoch   9 Batch  560/1077 - Train Accuracy: 0.9422, Validation Accuracy: 0.9141, Loss: 0.0410
Epoch   9 Batch  576/1077 - Train Accuracy: 0.9720, Validation Accuracy: 0.9339, Loss: 0.0302
Epoch   9 Batch  592/1077 - Train Accuracy: 0.9492, Validation Accuracy: 0.9339, Loss: 0.0379
Epoch   9 Batch  608/1077 - Train Accuracy: 0.9426, Validation Accuracy: 0.9453, Loss: 0.0536
Epoch   9 Batch  624/1077 - Train Accuracy: 0.9475, Validation Accuracy: 0.9446, Loss: 0.0508
Epoch   9 Batch  640/1077 - Train Accuracy: 0.9423, Validation Accuracy: 0.9361, Loss: 0.0345
Epoch   9 Batch  656/1077 - Train Accuracy: 0.9406, Validation Accuracy: 0.9311, Loss: 0.0354
Epoch   9 Batch  672/1077 - Train Accuracy: 0.9550, Validation Accuracy: 0.9453, Loss: 0.0435
Epoch   9 Batch  688/1077 - Train Accuracy: 0.9617, Validation Accuracy: 0.9524, Loss: 0.0357
Epoch   9 Batch  704/1077 - Train Accuracy: 0.9125, Validation Accuracy: 0.9371, Loss: 0.0424
Epoch   9 Batch  720/1077 - Train Accuracy: 0.9227, Validation Accuracy: 0.9325, Loss: 0.0402
Epoch   9 Batch  736/1077 - Train Accuracy: 0.9482, Validation Accuracy: 0.9503, Loss: 0.0356
Epoch   9 Batch  752/1077 - Train Accuracy: 0.9472, Validation Accuracy: 0.9382, Loss: 0.0345
Epoch   9 Batch  768/1077 - Train Accuracy: 0.9590, Validation Accuracy: 0.9375, Loss: 0.0371
Epoch   9 Batch  784/1077 - Train Accuracy: 0.9703, Validation Accuracy: 0.9315, Loss: 0.0313
Epoch   9 Batch  800/1077 - Train Accuracy: 0.9555, Validation Accuracy: 0.9453, Loss: 0.0348
Epoch   9 Batch  816/1077 - Train Accuracy: 0.9428, Validation Accuracy: 0.9485, Loss: 0.0473
Epoch   9 Batch  832/1077 - Train Accuracy: 0.9617, Validation Accuracy: 0.9265, Loss: 0.0292
Epoch   9 Batch  848/1077 - Train Accuracy: 0.9516, Validation Accuracy: 0.9300, Loss: 0.0438
Epoch   9 Batch  864/1077 - Train Accuracy: 0.9480, Validation Accuracy: 0.9347, Loss: 0.0416
Epoch   9 Batch  880/1077 - Train Accuracy: 0.9477, Validation Accuracy: 0.9570, Loss: 0.0421
Epoch   9 Batch  896/1077 - Train Accuracy: 0.9248, Validation Accuracy: 0.9247, Loss: 0.0360
Epoch   9 Batch  912/1077 - Train Accuracy: 0.9488, Validation Accuracy: 0.9382, Loss: 0.0386
Epoch   9 Batch  928/1077 - Train Accuracy: 0.9375, Validation Accuracy: 0.9467, Loss: 0.0431
Epoch   9 Batch  944/1077 - Train Accuracy: 0.9260, Validation Accuracy: 0.9510, Loss: 0.0445
Epoch   9 Batch  960/1077 - Train Accuracy: 0.9390, Validation Accuracy: 0.9308, Loss: 0.0438
Epoch   9 Batch  976/1077 - Train Accuracy: 0.9500, Validation Accuracy: 0.9336, Loss: 0.0373
Epoch   9 Batch  992/1077 - Train Accuracy: 0.9391, Validation Accuracy: 0.9450, Loss: 0.0647
Epoch   9 Batch 1008/1077 - Train Accuracy: 0.9453, Validation Accuracy: 0.9453, Loss: 0.0522
Epoch   9 Batch 1024/1077 - Train Accuracy: 0.9242, Validation Accuracy: 0.9414, Loss: 0.0543
Epoch   9 Batch 1040/1077 - Train Accuracy: 0.9465, Validation Accuracy: 0.9471, Loss: 0.0464
Epoch   9 Batch 1056/1077 - Train Accuracy: 0.9426, Validation Accuracy: 0.9553, Loss: 0.0354
Epoch   9 Batch 1072/1077 - Train Accuracy: 0.9546, Validation Accuracy: 0.9237, Loss: 0.0350
Model Trained and Saved
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<h3 id="Save-Parameters">Save Parameters<a class="anchor-link" href="#Save-Parameters">&#182;</a></h3><p>Save the <code>batch_size</code> and <code>save_path</code> parameters for inference.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
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<span class="c1"># Save parameters for checkpoint</span>
<span class="n">helper</span><span class="o">.</span><span class="n">save_params</span><span class="p">(</span><span class="n">save_path</span><span class="p">)</span>
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<h1 id="Checkpoint">Checkpoint<a class="anchor-link" href="#Checkpoint">&#182;</a></h1>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
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<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">helper</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>

<span class="n">_</span><span class="p">,</span> <span class="p">(</span><span class="n">source_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">),</span> <span class="p">(</span><span class="n">source_int_to_vocab</span><span class="p">,</span> <span class="n">target_int_to_vocab</span><span class="p">)</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_preprocess</span><span class="p">()</span>
<span class="n">load_path</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_params</span><span class="p">()</span>
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<h2 id="Sentence-to-Sequence">Sentence to Sequence<a class="anchor-link" href="#Sentence-to-Sequence">&#182;</a></h2><p>To feed a sentence into the model for translation, you first need to preprocess it.  Implement the function <code>sentence_to_seq()</code> to preprocess new sentences.</p>
<ul>
<li>Convert the sentence to lowercase</li>
<li>Convert words into ids using <code>vocab_to_int</code><ul>
<li>Convert words not in the vocabulary, to the <code>&lt;UNK&gt;</code> word id.</li>
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</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">sentence_to_seq</span><span class="p">(</span><span class="n">sentence</span><span class="p">,</span> <span class="n">vocab_to_int</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Convert a sentence to a sequence of ids</span>
<span class="sd">    :param sentence: String</span>
<span class="sd">    :param vocab_to_int: Dictionary to go from the words to an id</span>
<span class="sd">    :return: List of word ids</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">ids</span> <span class="o">=</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">lower</span><span class="p">()</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="p">):</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="n">ids</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vocab_to_int</span><span class="p">[</span><span class="n">word</span><span class="p">])</span>
        <span class="k">except</span> <span class="ne">KeyError</span><span class="p">:</span>
            <span class="n">ids</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;UNK&gt;&#39;</span><span class="p">])</span>
    <span class="k">return</span> <span class="n">ids</span>


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<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
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<span class="n">tests</span><span class="o">.</span><span class="n">test_sentence_to_seq</span><span class="p">(</span><span class="n">sentence_to_seq</span><span class="p">)</span>
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<pre>Tests Passed
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<h2 id="Translate">Translate<a class="anchor-link" href="#Translate">&#182;</a></h2><p>This will translate <code>translate_sentence</code> from English to French.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">translate_sentence</span> <span class="o">=</span> <span class="s1">&#39;he saw a old yellow truck .&#39;</span>


<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">translate_sentence</span> <span class="o">=</span> <span class="n">sentence_to_seq</span><span class="p">(</span><span class="n">translate_sentence</span><span class="p">,</span> <span class="n">source_vocab_to_int</span><span class="p">)</span>

<span class="n">loaded_graph</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Graph</span><span class="p">()</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">(</span><span class="n">graph</span><span class="o">=</span><span class="n">loaded_graph</span><span class="p">)</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="c1"># Load saved model</span>
    <span class="n">loader</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">import_meta_graph</span><span class="p">(</span><span class="n">load_path</span> <span class="o">+</span> <span class="s1">&#39;.meta&#39;</span><span class="p">)</span>
    <span class="n">loader</span><span class="o">.</span><span class="n">restore</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">load_path</span><span class="p">)</span>

    <span class="n">input_data</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;input:0&#39;</span><span class="p">)</span>
    <span class="n">logits</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;predictions:0&#39;</span><span class="p">)</span>
    <span class="n">target_sequence_length</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;target_sequence_length:0&#39;</span><span class="p">)</span>
    <span class="n">source_sequence_length</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;source_sequence_length:0&#39;</span><span class="p">)</span>
    <span class="n">keep_prob</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;keep_prob:0&#39;</span><span class="p">)</span>

    <span class="n">translate_logits</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="p">{</span><span class="n">input_data</span><span class="p">:</span> <span class="p">[</span><span class="n">translate_sentence</span><span class="p">]</span><span class="o">*</span><span class="n">batch_size</span><span class="p">,</span>
                                         <span class="n">target_sequence_length</span><span class="p">:</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">translate_sentence</span><span class="p">)</span><span class="o">*</span><span class="mi">2</span><span class="p">]</span><span class="o">*</span><span class="n">batch_size</span><span class="p">,</span>
                                         <span class="n">source_sequence_length</span><span class="p">:</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">translate_sentence</span><span class="p">)]</span><span class="o">*</span><span class="n">batch_size</span><span class="p">,</span>
                                         <span class="n">keep_prob</span><span class="p">:</span> <span class="mf">1.0</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;Input&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  Word Ids:      </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">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">translate_sentence</span><span class="p">]))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  English Words: </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">source_int_to_vocab</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">translate_sentence</span><span class="p">]))</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">Prediction&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  Word Ids:      </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">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">translate_logits</span><span class="p">]))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;  French Words: </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="s2">&quot; &quot;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">target_int_to_vocab</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">translate_logits</span><span class="p">])))</span>
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<pre>INFO:tensorflow:Restoring parameters from checkpoints/dev
Input
  Word Ids:      [126, 25, 187, 135, 20, 89, 149]
  English Words: [&#39;he&#39;, &#39;saw&#39;, &#39;a&#39;, &#39;old&#39;, &#39;yellow&#39;, &#39;truck&#39;, &#39;.&#39;]

Prediction
  Word Ids:      [56, 170, 332, 256, 189, 81, 209, 235, 1]
  French Words: il a vu un camion rouge brillant . &lt;EOS&gt;
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<h2 id="Imperfect-Translation">Imperfect Translation<a class="anchor-link" href="#Imperfect-Translation">&#182;</a></h2><p>You might notice that some sentences translate better than others.  Since the dataset you're using only has a vocabulary of 227 English words of the thousands that you use, you're only going to see good results using these words.  For this project, you don't need a perfect translation. However, if you want to create a better translation model, you'll need better data.</p>
<p>You can train on the <a href="http://www.statmt.org/wmt10/training-giga-fren.tar">WMT10 French-English corpus</a>.  This dataset has more vocabulary and richer in topics discussed.  However, this will take you days to train, so make sure you've a GPU and the neural network is performing well on dataset we provided.  Just make sure you play with the WMT10 corpus after you've submitted this project.</p>
<h2 id="Submitting-This-Project">Submitting This Project<a class="anchor-link" href="#Submitting-This-Project">&#182;</a></h2><p>When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_language_translation.ipynb" and save it as a HTML file under "File" -&gt; "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.</p>

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